Miracle-dz/UniFAR-FTUs huggingface dataset:
Novel techniques for characterising graphene nanoplatelets using Raman spectroscopy and machine learning

A significant challenge for graphene nanoplatelet (GNP) suppliers is the characterisation of platelet morphology in industrial environments. This challenge is further exacerbated to platelet surface chemistry when scalable functionalisation processes, such as plasma treatment, are used to modify the GNPs to improve the filler-matrix interphase in nanocomposites. The costly and complex suite of analytical equipment necessary for a complete material description makes quality control and process optimisation difficult. Raman spectroscopy is a facile and accessible characterisation technique, with recent advancements unlocking fast mapping for rapid data collection. In this study, we develop novel techniques to better characterise GNP morphology and changes in surface chemistry using Raman maps of bulk powders. Providing a bespoke algorithmic framework for the analysis of these advanced materials. An unsupervised peak fitting and processing algorithm was used to extract crystallinity data and correlate it with laser-diffraction-derived lateral size values for a commercial set of GNPs rapidly and accurately. Classical machine learning was used to identify the most informative Raman features for classifying the plasma-functionalised GNPs. The initial material properties were found to affect the peak features that were the most useful for classification. In low defect density and low specific surface area GNPs, the D peak full width at half maximum is found to be the most useful, whereas the I2D/IG ratio is the most useful in the opposite case. Finally, a convolutional neural network was trained to discern between different GNP grades with 86% accuracy. This work demonstrates how computer vision could be deployed for rapid and accurate quality control on the factory floor.
Heavy Youngsters—Habitat and Climate Factors Lead to a Significant Increase in Body Weight of Wild Boar Females

Simple Summary Long-term monitoring of wild boar reproduction in Lower Saxony, Germany, facilitated the description of body weight development in two different habitat types over an 18-year period. Here, not only the sampling year but also habitat and climate factors proved to be of considerable importance for the development of Sus scrofa body weight. Additionally, of particular interest were differences in the timing of puberty achievement among habitats. Abstract As one of the most abundant game species in Europe, European wild boar (Sus scrofa) populations prove highly adaptable to cultivated landscapes. The ongoing process of climate change and the high agricultural yields seem to further optimize the living conditions for this species. In long-term reproduction monitoring, we collected data on the body weight of wild boar females. Over an 18-year period, the body weight of wild boar females increased continuously, then stopped and decreased. It was possible to detect differences between the body weights of animals from forest and agricultural areas. For these areas, differences in body weight development also led to a significant distinction in the onset of puberty. We conclude that, even in a highly cultivated landscape, forested areas provide habitat characteristics that may strongly influence reproduction. Second, with dominant agricultural areas in Germany, wild boar reproduction has been favored in recent decades.
Cuff-less Estimation of Blood Pressure from Vibrational Cardiography Using a Convolutional Neural Network

Wearable monitoring is important for the diagnosis, prevention, and treatment of cardiovascular diseases and overall cardiac health. A key indicator, Blood pressure (BP), currently relies on cuff-based devices for measurement that are cumbersome for ambulatory monitoring scenarios. Vibrational cardiography (VCG) is an unobtrusive, non-invasive tool which records cardiac vibrations on the surface of the chest. This work proposes using VCG in a novel method to estimate BP from a single point of contact. VCG was recorded by an inertial measurement unit on the xiphoid process of 62 subjects. A convolutional neural network was trained on the VCG waveforms to estimate systolic and diastolic BP. This resulted in an r-squared correlation coefficient of 0.86 and 0.89 and a mean-absolute-error of 3.4 mmHg and 2.2 mmHg for systolic and diastolic BP, respectively. Therefore, this work shows the applicability of using exclusively VCG for BP estimation. It affirms the value of VCG as an all-purpose health monitor, while also improving on the current techniques for continuous BP monitoring. This indicates the potential of VCG in many forms of wearable monitoring including remote healthcare, fitness, and wellness monitoring.
Whole-brain MR spectroscopic imaging reveals regional metabolite abnormalities in perinatally HIV infected young adults

Perinatally acquired HIV (PHIV) has been associated with brain structural and functional deficiencies, and with poorer cognitive performance despite the advent of antiretroviral therapy (ART). However, investigation of brain metabolite levels in PHIV measured by proton magnetic resonance spectroscopy (MRS) methods, is still limited with often inconclusive or contradictory findings. In general, these MRS-based methods have used a single voxel approach that can only evaluate metabolite concentrations in a few select brain anatomical regions. Additionally, most of the published data have been on children perinatally infected with HIV with only a few studies examining adult populations, though not exclusively. Therefore, this prospective and cross-sectional study aims to evaluate metabolite differences at the whole-brain level, using a unique whole-brain proton magnetic resonance spectroscopy imaging (MRSI) method, in a group of PHIV infected young adults (N = 28) compared to age and gender matched control sample (N = 28), and to find associations with HIV clinical factors and neurocognitive scores. MRSI data were acquired on a 3T scanner with a TE of 70 ms. Brain metabolites levels of total N-acetylaspartate (tNAA), total choline (tCho) and total creatine (tCre), as well as ratios of tNAA/tCre, tCho/tCre, and tNAA/tCho, were obtained from the whole brain level and evaluated at the level of gray matter (GM) and white matter (WM) tissue types and anatomical regions of interest (ROI). Our results indicate extensive metabolic abnormalities throughout the brains of PHIV infected subjects with significantly elevated levels of tCre and tCho, notably in GM regions. Decreases in tNAA and ratios of tNAA/tCre and tNAA/tCho were also found mostly in WM regions. These metabolic alterations indicate increased glial activation, inflammation, neuronal dysfunction, and energy metabolism in PHIV infected individuals, which correlated with a reduction in CD4 cell count, and lower cognitive scores. Our findings suggest that significant brain metabolite alterations and associated neurological complications persist in the brains of those with PHIV on long-term ART, and advocates the need for continued monitoring of their brain health.
Some Priors for Sparse Regression Modelling

A wide range of methods, Bayesian and others, tackle regression when there are many variables. In the Bayesian context, the prior is constructed to reflect ideas of variable selection and to encourage appropriate shrinkage. The prior needs to be reasonably robust to different signal to noise structures. Two simple evergreen prior constructions stem from ridge regression on the one hand and g-priors on the other. We seek to embed recent ideas about sparsity of the regression coefficients and robustness into these priors. We also explore the gains that can be expected from these differing approaches
PRESSURE AND HEAT TRANSFER IN CROSS FLOW OVER CYLINDERS BETWEEN TWO PARALLEL PLATES

Heat transfer and fluid flow over a row of in-line cylinders placed between two parallel plates are studied numerically. Flow is incompressible, two-dimensional, and laminar. The spacing between cylinders causes three different separation patterns. When the spacing is small, the separated flow between cylinders is stable. As the spacing increases, flow in the separated zone becomes temporal and periodic. At higher spacing, the separated flow is local and does not extend to the next cylinder. In general, the pressure drop in the flow and heat transfer to the flow are spatially periodic, indicating fully developed characteristics
Dynamics of the judgment of tactile stimulus intensity

In the future, artificial agents will need to make assessments of tactile stimuli in order to interact intelligently with the environment and with humans. Such assessments will depend on exquisite and robust mechanosensors, but sensors alone do not make judgments and choices. Rather, the central processing of mechanosensor inputs must be implemented with algorithms that produce ‘behavioral states’ in the artificial agent that resemble or mimic perceptual judgments in biology. In this study, we consider the problem of perceptual judgment as applied to vibration intensity. By a combination of computational modeling and simulation followed by psychophysical testing of vibration intensity perception in rats, we show that a simple yet highly salient judgment—is the current stimulus strong or weak? —can be explained as the comparison of ongoing sensory input against a criterion constructed as the time-weighted average of the history of recent stimuli. Simulations and experiments explore how judgments are shaped by the distribution of stimuli along the intensity dimension and, most importantly, by the time constant of integration which dictates the dynamics of criterion updating. The findings of this study imply that judgments made by the real nervous system are not absolute readouts of physical parameters but are context-dependent; algorithms of this form can be built into artificial systems.
Statistical Foundation for Decision Making in Nuclear Safety–Related Problems Using Best Estimate Plus Uncertainty Analyses

Abstract The response of a complex physical system is often evaluated by a tolerance interval for a percentile of the distribution of a variable of interest that is estimated by best-estimate codes. This tolerance interval is used as a test statistic to make decisions about the behavior of the system in the context of the specific safety issue. The most common methods to determine such tolerance intervals are order statistics methods leading to the so-called “95/95” level of safety standard. The application of these methods is predicated on the assumption that the simulated responses are identical to those of an actual reactor under the postulated conditions. We present here a novel statistical framework [referred to as EVS (extreme value statistics) methodology], not relying on the above assumption, for deriving tolerance limits involving data selected from a population that is different from the population of interest. Such a situation arises when the unobservable population is being estimated by an imperfect code and imperfect input. This leads us to distinguishing between “true” system stochastic (aleatory) variables and those resulting from the safety codes (subject to epistemic uncertainty). Methods using Monte Carlo sampling or sensitivity analysis, order statistics, and EVS methods produce different solutions as a consequence of a difference in how the true values and data are distinguished. This difference ultimately leads to different test statistics that are used to solve a decision-making problem. Closed-form expressions for the EVS-based tolerance limits are derived for a large class of models representing complex systems. Problems, both analytical and using actual reactor operating data, are presented and solved. EVS results demonstrate substantial improvements in operational and safety margins when compared to results obtained from existing methods used in the nuclear industry.
The Dispersion of Standard Air

By combining Barrell and Sears’ measurements in the visible and Koch’s and Traub’s in the ultraviolet, a dispersion formula for standard air has been derived, viz., (n−1)108=6432.8+2 949 810(146−σ2)−1+25 540(41−σ2)−1,σ being vacuum wave number in μ−1, which should satisfy all needs of precision spectroscopy, in particular for converting wavelengths in air into vacuum values.
Watershed Segmentation Based on Histogram Threshold and Lowest Mean Edge Value

A novel algorithm based on gradient image histogram threshold and lowest mean edge value is proposed. Image objects are initialized using the gradient image histogram threshold and grow up using the watershed segmentation algorithm. To reduce the number of image objects, a merge method based on lowest mean edge value is proposed. The segmentation result revealed the advantage of this method in preventing over-segmentation.
Negatively chirped laser enables nonlinear excitation and nanoprocessing with sub-20-fs pulses

It has long been considered that the advantages emerging from employing chirp pre-compensation in nonlinear microscopy were overweighed by the complexity of prism- or grating-based compressors. These concerns were refuted with the advent of dispersive-mirrors-based compressors that are compact, user-friendly and sufficiently accurate to support sub-20-fs pulse delivery. Recent advances in the design of dispersive multilayer mirrors resulted in improved bandwidth (covering now as much as half of the gain bandwidth of Ti:Sapphire) and increased dispersion per bounce (one reflection off a state-of-the-art dispersive mirror pre-compensates the dispersion corresponding to >10mm of glass). The compressor built with these mirrors is sufficiently compact to be integrated in the housing of a sub-12-fs Ti:Sapphire oscillator. A complete scanning nonlinear microscope (FemtOgene, JenLab GmbH) equipped with highly-dispersive, large-NA objectives (Zeiss EC Plan-Neofluoar 40x/1.3, Plan-Neofluar 63x/1,25 Oil) was directly seeded with this negatively chirped laser. The pulse duration was measured at the focus of the objectives by inserting a scanning autocorrelator in the beam path between the laser and the microscope and recording the second order interferometric autocorrelation traces with the detector integrated in the microscope. Pulse durations <20fs were measured with both objectives. The system has been applied for two-photon imaging, transfection and optical manipulation of stem cells. Here we report on the successful transfection of human stem cells by transient optoporation of the cell membrane with a low mean power of < 7 mW and a short μs beam dwell time. Optically transfected cells were able to reproduce. The daughter cell expressed also green fluorescent proteins (GFP) indicating the successful modification of the cellular DNA.
Task Demands and Sentence Reading Comprehension among Healthy Older Adults: The Complementary Roles of Cognitive Reserve and Working Memory

Ageing entails different functional brain changes. Education, reading experience, and leisure activities, among others, might contribute to the maintenance of cognitive performance among older adults and are conceptualised as proxies for cognitive reserve. However, ageing also conveys a depletion of working memory capacity, which adversely impacts language comprehension. This study investigated how cognitive reserve proxies and working memory jointly predict the performance of healthy older adults in a sentence reading comprehension task, and how their predictive value changes depending on sentence structure and task demands. Cognitively healthy older adults (n = 120) completed a sentence–picture verification task under two conditions: concurrent viewing of the sentence and picture or their sequential presentation, thereby imposing greater demands on working memory. They also completed a questionnaire on cognitive reserve proxies as well as a verbal working memory test. The sentence structure was manipulated by altering the canonical word order and modifying the amount of propositional information. While the cognitive reserve was the main predictor in the concurrent condition, the predictive role of working memory increased under the sequential presentation, particularly for complex sentences. These findings highlight the complementary roles played by cognitive reserve and working memory in the reading comprehension of older adults.
Solving Eigenvalue and Singular Value Problems on an Undersized Systolic Array

Systolic architectures due to Brent, Luk and Van Loan are today the most promising method for computing the symmetric eigenvalue and singular value decompositions in real time. These systolic arrays, however, are only able to decompose matrices of a given fixed size. Here we present two modified algorithms and a modified array that do not have this disadvantage. The results of a numerical experiment show that a combination of one of our new algorithms and the modified array can decompose matrices of arbitrary size with little or no loss of efficiency.
Blue Photons from Broad-Spectrum LEDs Control Growth, Morphology, and Coloration of Indoor Hydroponic Red-Leaf Lettuce

For indoor crop production, blue + red light-emitting diodes (LEDs) have high photosynthetic efficacy but create pink or purple hues unsuitable for workers to inspect crops. Adding green light to blue + red light forms a broad spectrum (white light), which is created by: phosphor-converted blue LEDs that cast photons with longer wavelengths, or a combination of blue, green, and red LEDs. A broad spectrum typically has a lower energy efficiency than dichromatic blue + red light but increases color rendering and creates a visually pleasing work environment. Lettuce growth depends on the interactions of blue and green light, but it is not clear how phosphor-converted broad spectra, with or without supplemental blue and red light, influence crop growth and quality. We grew red-leaf lettuce ‘Rouxai’ in an indoor deep-flow hydroponic system at 22 °C air temperature and ambient CO2. Upon germination, plants received six LED treatments delivering different blue fractions (from 7% to 35%) but the same total photon flux density (400 to 799 nm) of 180 μmol·m−2·s−1 under a 20 h photoperiod. The six LED treatments were: (1) warm white (WW180); (2) mint white (MW180); (3) MW100 + blue10 + red70; (4) blue20 + green60 + red100; (5) MW100 + blue50 + red30; and (6) blue60 + green60 + red60. Subscripts denote photon flux densities in μmol·m−2·s−1. Treatments 3 and 4 had similar blue, green, and red photon flux densities, as did treatments 5 and 6. At the harvest of mature plants, lettuce biomass, morphology, and color were similar under WW180 and MW180, which had different green and red fractions but similar blue fractions. As the blue fraction in broad spectra increased, shoot fresh mass, shoot dry mass, leaf number, leaf size, and plant diameter generally decreased and red leaf coloration intensified. Compared to blue + green + red LEDs, white LEDs supplemented with blue + red LEDs had similar effects on lettuce when they delivered similar blue, green, and red photon flux densities. We conclude that the blue photon flux density in broad spectra predominantly controls lettuce biomass, morphology, and coloration.
Minimum time-energy trajectory planning for automatic ship berthing

A ship optimal trajectory planning method based on the dynamic model of the ship is presented. First a mathematical modular model is introduced for describing the non-linear dynamics of the ship. Then the problem of optimal trajectory planning is discussed. The trajectory is obtained through the optimization of a time-energy criterion, taking into account constraints on the steering system, environment, non-linearities, and non-convexity of the state space equations. The discrete augmented Lagrangian approach is used to compute the optimal constrained controller. The method was programmed on a HP700 workstation. This approach was applied to automatic ship berthing maneuver. >
Artificial molecule realization of a magnetic wall

The design of magnetic materials can be achieved with artificial magnetic molecules formed by electrically small loop antennas loaded with passive electrical circuit elements. A time derivative Lorentz material response is achieved with a series resistor and capacitor load. It is shown that the parameters of this magnetic molecule can be selected to yield a time derivative Lorentz material that acts as a highly conducting magnetic wall.
Research progress of glutathione peroxidase family (GPX) in redoxidation

Maintaining the balance of a cell’s redox function is key to determining cell fate. In the critical redox system of mammalian cells, glutathione peroxidase (GPX) is the most prominent family of proteins with a multifaceted function that affects almost all cellular processes. A total of eight members of the GPX family are currently found, namely GPX1-GPX8. They have long been used as antioxidant enzymes to play an important role in combating oxidative stress and maintaining redox balance. However, each member of the GPX family has a different mechanism of action and site of action in maintaining redox balance. GPX1-4 and GPX6 use selenocysteine as the active center to catalyze the reduction of H2O2 or organic hydroperoxides to water or corresponding alcohols, thereby reducing their toxicity and maintaining redox balance. In addition to reducing H2O2 and small molecule hydroperoxides, GPX4 is also capable of reducing complex lipid compounds. It is the only enzyme in the GPX family that directly reduces and destroys lipid hydroperoxides. The active sites of GPX5 and GPX7-GPX8 do not contain selenium cysteine (Secys), but instead, have cysteine residues (Cys) as their active sites. GPX5 is mainly expressed in epididymal tissue and plays a role in protecting sperm from oxidative stress. Both enzymes, GPX7 and GPX8, are located in the endoplasmic reticulum and are necessary enzymes involved in the oxidative folding of endoplasmic reticulum proteins, and GPX8 also plays an important role in the regulation of Ca2+ in the endoplasmic reticulum. With an in-depth understanding of the role of the GPX family members in health and disease development, redox balance has become the functional core of GPX family, in order to further clarify the expression and regulatory mechanism of each member in the redox process, we reviewed GPX family members separately.
Incorporation of chondroitin sulfate into macroporous bacterial cellulose scaffold for improved bioactivity

Lack of bioactivity limits the applications of bacterial cellulose (BC) in biomedical fields. In this study, we report the facile preparation of a macroporous BC (PBC)/chondroitin sulfate (CS) scaffold using the ex situ method by adding CS solution into the suspension of BC fragments followed by crosslinking with 1-ethyl-3(3-dimethyl aminopropyl) carbodiimide (EDC) and N-hydroxysuccinimide (NHS) and freeze drying. The PBC/CS scaffold was characterized for morphology, physicochemical properties, cell behavior, and capability of inducing mineral deposition. Results show that the PBC/CS scaffold presents improved mechanical properties, cell adhesion, and proliferation over the PBC scaffold. Moreover, the presence of CS greatly enhances the deposition of minerals on the PBC/CS scaffold, an indicator of bioactivity. The present study provides a simple methodology for improving the bioactivity of BC and the results of the present work suggest that the PBC/CS scaffold has potential for use in bone tissue engineering. Graphical Abstract