Miracle-dz/UniFAR-FTUs huggingface dataset:
Wavelength-Dependent Effects of Photobiomodulation for Wound Care in Diabetic Wounds

Photobiomodulation, showing positive effects on wound healing processes, has been performed mainly with lasers in the red/infrared spectrum. Light of shorter wavelengths can significantly influence biological systems. This study aimed to evaluate and compare the therapeutic effects of pulsed LED light of different wavelengths on wound healing in a diabetic (db/db) mouse excision wound model. LED therapy by Repuls was applied at either 470 nm (blue), 540 nm (green) or 635 nm (red), at 40 mW/cm2 each. Wound size and wound perfusion were assessed and correlated to wound temperature and light absorption in the tissue. Red and trend-wise green light positively stimulated wound healing, while blue light was ineffective. Light absorption was wavelength-dependent and was associated with significantly increased wound perfusion as measured by laser Doppler imaging. Shorter wavelengths ranging from green to blue significantly increased wound surface temperature, while red light, which penetrates deeper into tissue, led to a significant increase in core body temperature. In summary, wound treatment with pulsed red or green light resulted in improved wound healing in diabetic mice. Since impeded wound healing in diabetic patients poses an ever-increasing socio-economic problem, LED therapy may be an effective, easily applied and cost-efficient supportive treatment for diabetic wound therapy.
High‐frequency harmonics and source level of humpback whale songs

The songs of 8 male humpback whales were recorded at ranges varying from 20 to 40 m with a calibrated system that had a flat frequency response to 22 kHz. The songs consisted of bursts of sounds called units. Units were organized into phrases and phrases into themes. Most of the units had mean duration between 1 and 2 s and mean silent periods between units between 1 and 2 s. Many of the recorded songs contained units that had high‐frequency harmonics that extended beyond 15 kHz. The amplitudes of the higher‐frequency harmonics of some units were within 18–24 dB of the fundamental or the highest level harmonic at frequencies out to 13.5 kHz. These harmonic results suggest that humpback whale songs have a broadband quality not previously reported and may provide some insights on the high‐frequency limit of hearing in these whales. The source levels of the different songs were also estimated by considering the root mean square sound pressure level referenced to 1 m for the unit with the largest level for ea.
Biasing characteristics of unshielded, boundary exchange-coupled SAL/MR sensors

A magnetoresistive (MR) sensor with patterned exchange-biasing layer at its end regions exhibits quite and stable responses. A mathematical model simulating an unshielded, boundary exchange-biased SAL/MR structure is developed. The modeled results are in good agreement with the experimental data. However, biasing characteristics are quite different from modeled results assuming infinitely long stripes. For the boundary exchange-coupled SAL/MR design, the strip height has a significant impact on the biasing characteristics and the effect becomes even more pronounced as the track width is further reduced. >
On Transient Semi‐Arid Ecosystem Dynamics Using Landlab: Vegetation Shifts, Topographic Refugia, and Response to Climate

Projecting how arid and semi‐arid ecosystems respond to global change requires the integration of a wide array of analytical and numerical models to address different aspects of complex ecosystems. We used the Landlab earth surface modeling toolkit (Hobley et al., 2017, https://doi.org/10.5194/esurf-5-21-2017) to couple several ecohydrologic and vegetation dynamics processes to investigate the controls of exogenous drivers (climate, topography, fires, and grazing) and endogenous grass‐fire feedback mechanisms. Aspect‐controlled ecosystems and historical woody plant encroachment (WPE) narratives in central New Mexico, USA are used to construct simulations. Modeled ecosystem response to climatic wetness (i.e., higher precipitation, lower potential evapotranspiration) on topography follows the Boyko's “geo‐ecological law of distribution. ” Shrubs occupy cooler pole‐facing slopes in the dry end of their ecoclimatic range (Mean Annual Precipitation, MAP ≤ 200 mm), and shift toward warmer equator‐facing slopes as regional moisture increases (MAP > 250 mm). Trees begin to occupy pole‐facing slopes when MAP > 200 mm, and gradually move to valleys. Pole‐facing slopes increase species diversity at the landscape scale by hosting relict populations during dry periods. WPE observed in the region since the middle 1800s is predicted as a three‐phase phenomenon. Phase II, rapid expansion, requires the removal of the positive grass‐fire feedback by livestock grazing or fire suppression. Regime shifts from grassland to shrubland are marked by critical thresholds that involve grass cover remaining below 40%, shrub cover increasing to 10%–20% range, and the grass connectivity, Cg, remaining below 0.15. A critical transition to shrubland is predicted when grazing pressure is not removed before shrub cover attains 60%.
Face expression recognition based on NGO-BILSTM model

Introduction Facial expression recognition has always been a hot topic in computer vision and artificial intelligence. In recent years, deep learning models have achieved good results in accurately recognizing facial expressions. BILSTM network is such a model. However, the BILSTM network's performance depends largely on its hyperparameters, which is a challenge for optimization. Methods In this paper, a Northern Goshawk optimization (NGO) algorithm is proposed to optimize the hyperparameters of BILSTM network for facial expression recognition. The proposed methods were evaluated and compared with other methods on the FER2013, FERplus and RAF-DB datasets, taking into account factors such as cultural background, race and gender. Results The results show that the recognition accuracy of the model on FER2013 and FERPlus data sets is much higher than that of the traditional VGG16 network. The recognition accuracy is 89.72% on the RAF-DB dataset, which is 5.45, 9.63, 7.36, and 3.18% higher than that of the proposed facial expression recognition algorithms DLP-CNN, gACNN, pACNN, and LDL-ALSG in recent 2 years, respectively. Discussion In conclusion, NGO algorithm effectively optimized the hyperparameters of BILSTM network, improved the performance of facial expression recognition, and provided a new method for the hyperparameter optimization of BILSTM network for facial expression recognition.
Robust control of uncertain systems via norm- and sector-bounded LQG-type controllers

Addresses the design of linear-quadratic-Gaussian (LQG) controllers for uncertain linear time-invariant systems that are either norm-bounded or belong to a given sector. The system matrices are assumed to be affine functions of parameters confined to a convex polytopic region in the parameter space. The resulting controllers themselves satisfy certain norm or sector conditions and provide robust stability as well as optimal performance.
Singulary cylindric and polyadic equality algebras

This paper is a contribution to the structure and representation theory of finitedimensional cylindric and polyadic equality algebras. The main result is that every singulary algebra is representable, where an algebra is singular y if it is generated by elements supported by singletons. In particular, all prime algebras are representable (a prime algebra has no proper subalgebra, and every cylindric or polyadic equality algebra has a prime subalgebra). Since every polyadic algebra can be embedded in a polyadic equality algebra the results also apply to them. Every infinite-dimensional singulary algebra is locally finite and hence is known to be representable, so we shall be concerned just with the finite-dimensional case, where previously very little was known about representation. It may be mentioned that for any dimension greater than one there are nonrepresentable cylindric and polyadic equality algebras(2). For some special kinds of singulary algebras we obtain a direct construction of the representation, which brings out the structure of the algebra clearly. The methods used essentially constitute an algebraic version of Behmann's solution of the decision problem for the singulary predicate calculus with equality(3). Since only finitely many variables are available, the algebraization has some novel features. The essential ideas can be seen in the case of prime algebras, for which no advanced results about cylindric or polyadic algebras are needed. In the general case, however, use is made of the fact that a cylindric algebra is representable if every finitely generated subalgebra of it is. In the last section of the paper we discuss the logical counterpart of the methods and results of the algebraic part of the paper.
Citrous Lime—A Functional Reductive Booster for Oil-Mediated Green Synthesis of Bioactive Silver Nanospheres for Healthcare Clothing Applications and Their Eco-Mapping with SDGs

Silver nanoparticles (Ag-NPs) are most effective against pathogens and have widely been studied as antibacterial agents in commodity clothing, medical textile, and other hygiene products. However, prolonged utilization of silver and rapid mutation in bacterium stains has made them resistant to conventional silver agents. On the other hand, strict compliance against excessive utilization of toxic reagents and the current sustainability drive is forcing material synthesis toward green routes with extended functionality. In this study, we proposed an unprecedented chemical-free green synthesis of bioactive Ag-NPs without the incorporation of any chemicals. Cinnamon essential oil (ECO) was used as a bio-reducing agent with and without the mediation of lime extract. A rapid reaction completion with better shape and size control was observed in the vicinity of lime extract when incorporated into the reaction medium. The interaction of natural metabolites and citrus compounds with nanoparticles was established using Fourier transform infrared spectroscopy (FTIR) and Raman spectroscopy. The application of as-prepared nanoparticles on textiles encompasses extended bioactivity to treated fabric with infused easy-care performance. To the best of our knowledge, this is the first reported instance of utilizing bioactive silver nanoparticles as a functional finish, both as an antimicrobial and as for easy care in the absolute absence of toxic chemicals. The easy-care performance of fabric treated with lime-mediated nanoparticles was found to be 141O, which is around 26% better than bare cotton without any significant loss in fabric strength. Furthermore, to enlighten the sustainability of the process, the development traits were mapped with the United Nations Sustainable Development Goals (SDGs), which show significant influence on SDGs 3, 8, 9, and 14. With the effective suspension of microorganisms, added functionality, and eco-mapping with SDGs with the chemical-free synthesis of nanoparticles, widespread utilization can be found in various healthcare and hygiene products along with the fulfillment of sustainability needs.
The Probability of Chance Correlation Using Partial Least Squares (PLS)

The frequency of chance correlation using partial least squares (PLS) has been measured experimentally for variously dimensioned data, comprising either completely random numbers, random numbers containing a perfect correlation within, and CoMFA field descriptors. This frequency, much lower than that for stepwise multiple regression, is maximal for datasets in which the number of descriptors equals the number of compounds, and surprisingly decreases indefinitely as the number of descriptors becomes much greater than the number of compounds. However, perfect correlations involving descriptor subsets are not detected by PLS if the number of irrelevant descriptors is excessive. In CoMFA applications, the probability of chance correlation is usually negligible. For example with 21 compounds a crossvalidated r2 value greater than 0.25 will occur by chance in less than 5% of trials.
The impact of users' trust on intention to use the mobile medical platform: Evidence from China

Introduction The mobile medical platform effectively complements offline medical services as it can provide patients with broader and more convenient medical services, effectively solving the shortage of medical resources in the public health system. Although the public interest in healthcare service platforms continues to rise, the market data shows that the adoption and acceptance have not reached a high level. How to increase the utilization rate of the mobile medical platform to relieve medical pressure has become an urgent issue to be discussed. Based on the framework of “trust-intention” this research introduces innovation acceptance and technical risk concerns as the two moderating variables to attempt to build a research model of users' intention to use the mobile medical platform. The analysis illustrated that users' trust in the mobile medical platform would positively affect their use intention. The researchers further explored the moderating role of innovation acceptance and technical risk concerns. Methods Use questionnaire to collect data in China, then use the OLS least square method for the regression test. Results The results showed that users with high personal innovation acceptance would positively promote the relationship between trust and use intention. In contrast, users who are more concerned about the risks of innovative technologies will weaken the relationship between trust and use intention. Discussion The findings theoretically extend the academic research of use intention to the specific context of the mobile medical platform and enrich the research framework of “trust-intention”.
Bed Stability of Step‐Pool Channels With Macrorough Sidewalls

A step‐pool bed morphology often develops in steep mountain streams. The main controlling parameters of step formation and stability are hydraulic forcing, sediment transport, and granular effects (i.e., grain‐grain interlocking, jamming). Previous studies found macrorough sidewalls to further increase bed stability due to grain‐sidewall interlocking but the effect of the reduced bed shear stress caused by sidewall friction was not explicitly considered. The present study aims at untangling hydraulic effects induced by the macrorough sidewalls and granular effects, that is, grain‐sidewall interaction. Flume experiments with five types of macrorough sidewalls were conducted under clear‐water conditions for bed slopes ranging between 4% and 10% and jamming ratios 5.3 < Wm/d84 < 11.2, where Wm is the mean channel width and d84 is a characteristic grain size of the sediment mixture. A modified sidewall correction procedure accounting for sidewall friction was applied to estimate bed shear stress. Bed stability considerably increased with increasing sidewall roughness. The dimensionless bed shear stress θRb controlled step occurrence as the system evolved toward a state of a maximum number of steps for critical Shields ratios θRb/θc ≈ 1. Contrary to the expectations, fewer steps formed in the roughest sidewall experiments as few very stable steps inhibited sediment relocation and therewith step formation. Steps were more frequently located in the constrictions caused by the macrorough elements and sustained higher bed shear stress increments. Overall, hydraulic effects fully explained the increase in bed stability in moderately rough sidewall experiments whereas granular effects became important in channels with strong local constrictions.
Simple treatment of multi-term dispersion in FDTD

Three new simple and efficient algorithms are proposed for the numerical treatment of the multi-term Debye or Lorentz dispersion in the FDTD method. The formulation is based on the auxiliary differential equation, but requires much fewer operations than the published schemes. The approach is equivalent to the best higher order recursive schemes in terms of memory and computational expense, but without the linearity assumptions.
Turbulent length scales and anisotropy downstream of a wall mounted sphere

ABSTRACT Characteristics of turbulent mixing-length, length scales and anisotropy in the wall-wake flow downstream of a sphere placed on a rough wall are studied. The Prandtl's mixing-length in wall-wake flow increases compared to that in upstream flow, while the Taylor microscale and the Kolmogorov length scale decrease. As the downstream distance increases, the defects (difference between upstream and downstream distributions) in vertical distributions of mixing-length and length scales gradually disappear to recover their distributions in undisturbed upstream flow. These distributions of the defects exhibit some degree of similarity, as they are scaled by their individual peak values and the vertical distance is scaled by the height of occurrence of their individual half-peak defects. In anisotropy analysis, the streamwise, spanwise and vertical components of anisotropy in wall-wake flow are less, more and invariant, compared to their individual upstream trends. However, the former two components recover with an increase in downstream distance.
Validation of a new signal processing scheme for the MST Radar at Aberystwyth

This paper describes a new signal processing scheme for the 46.5 MHz Doppler Beam Swinging wind- profiling radar at Aberystwyth, in the UK. Although the techniques used are similar to those already described in literature - i.e. the identification of multiple signal com- ponents within each spectrum and the use of radial- and time-continuity algorithms for quality-control purposes - it is shown that they must be adapted for the specific meteorolog- ical environment above Aberystwyth. In particular they need to take into account the three primary causes of unwanted signals: ground clutter, interference, and Rayleigh scatter from hydrometeors under stratiform precipitation conditions. Attention is also paid to the fact that short-period gravity- wave activity can lead to an invalidation of the fundamental assumption of the wind field remaining stationary over the temporal and spatial scales encompassed by a cycle of obser- vation. Methods of identifying and accounting for such con- ditions are described. The random measurement error associ- ated with horizontal wind components is estimated to be 3.0- 4.0 m s 1 for single cycle data. This reduces to 2.0-3.0 m s 1 for data averaged over 30 min. The random measurement er- ror associated with vertical wind components is estimated to be 0.2-0.3 m s 1 . This cannot be reduced by time-averaging
Diet Control and Swimming Exercise Ameliorate HFD-Induced Cognitive Impairment Related to the SIRT1-NF-κB/PGC-1α Pathways in ApoE-/- Mice

High-fat diet- (HFD-) induced neuroinflammation may ultimately lead to an increased risk of cognitive impairment. Here, we evaluate the effects of diet control and swimming or both on the prevention of cognitive impairment by enhancing SIRT1 activity. Twenty-week-old ApoE-/- mice were fed a HFD for 8 weeks and then were treated with diet control and/or swimming for 8 weeks. Cognitive function was assessed using the novel object recognition test (NORT) and Y-maze test. The expression of sirtuin-1 (SIRT1), peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC-1α), brain-derived neurotrophic factor (BDNF), nuclear factor kappa B p65 (NF-κB p65), interleukin-1β (IL-1β), and tumour necrosis factor-α (TNF-α) in the hippocampus was measured by western blotting. The levels of fractional anisotropy (FA), N-acetylaspartate (NAA)/creatine (Cr) ratio, choline (Cho)/Cr ratio, and myo-inositol (MI)/Cr ratio in the hippocampus were evaluated by diffusion tensor imaging (DTI) and magnetic resonance spectroscopy (MRS) using 7.0-T magnetic resonance imaging (MRI). Our results showed that cognitive dysfunction and hippocampal neuroinflammation appeared to be remarkably observed in apolipoprotein E (ApoE)-/- mice fed with HFD. Diet control plus swimming significantly reversed HFD-induced cognitive decline, reduced the time spent exploring the novel object, and ameliorated spontaneous alternation in the Y-maze test. Compared with the HFD group, ApoE-/- mice fed diet control and/or subjected to swimming had an increase in FA, NAA/Cr, and Cho/Cr; a drop in MI/Cr; elevated expression levels of SIRT1, PGC-1α, and BDNF; and inhibited production of proinflammatory cytokines, including NF-κB p65, IL-1β, and TNF-α. SIRT1, an NAD+-dependent class III histone enzyme, deacetylases and regulates the activity of PGC-1α and NF-κB. These data indicated that diet control and/or swimming ameliorate cognitive deficits through the inhibitory effect of neuroinflammation via SIRT1-mediated pathways, strongly suggesting that swimming and/or diet control could be potentially effective nonpharmacological treatments for cognitive impairment.
Year in Review: Gout Clinical Research

Gout is a prevalent and burdensome condition despite the advances in our knowledge of its underlying mechanisms, prevention, and treatment. There is still work to be done to elucidate relevant questions that could lead to better patient care. This conference report summarizes eight impactful publications which inform and improve clinical care in gout from October 2021 to October 2022. The articles we present here address innovative management approaches, the use of serum urate as a surrogate marker, the occurrence of complications such as cardiovascular events and lower extremity amputation, the evaluation of mortality in patients with chronic kidney disease and gout, the effect of intensive serum urate control on radiographic outcomes, and the impact of COVID-19 infection in patients with gout. The conclusions reached by these publications are noteworthy. Some of them are potentially practice-changing, and all provide exciting follow-up questions.
Application of wavelets in blind source separation

It was previously shown that sparse representations can improve and simplify the estimation of an unknown mixing matrix of a set of images and thereby improve the quality of separation of source images. Here we propose a multiscale approach to the problem of blind separation of images from a set of their mixtures. We take advantage of the properties of multiscale transforms such as wavelet packets and decompose signals and images according to sets of local features. The resulting partial representations on a tree of data structure depict various degrees of sparsity. We show how the separation error is affected by the sparsity of the decomposition coefficients, and by the misfit between the prior, formulated in accordance with the probabilistic model of the coefficients' distribution, and the actual distribution of the coefficients. Our error estimator, based on the Taylor expansion of the quasi Log-Likelihood function, is used in selection of the best subsets of coefficients, utilized in turn for further separation. The performance of the proposed method is assessed by separation of noise-free and noisy data. Experiments with simulated and real signals and images demonstrate significant improvement of separation quality over previously reported results.
The Sponge-like Topology of Large-Scale Structure in the Universe

We describe and apply a quantitative measure of the topology of large scale structure: the genus of density contours in a smoothed density distribution. For random phase (gaussian) density fields, the mean genus per unit volume exhibits a universal dependence on threshold density, with a normalizing factor that can be calculated from the power spectrum. The topology of the observational sample is consistent with the random phase, cold dark matter model.