Miracle-dz/UniFAR-FTUs huggingface dataset:
Non-invasive blood oxygenation monitoring from different sites of human body using diffuse reflectance spectroscopy: a feasibility study of diabetic foot monitoring

Diabetic foot ulcer is one of the most common causes of lower-extremity amputation of diabetic patients worldwide. Researchers have identified several optical diagnostic techniques to diagnose diabetic foot ulcer by monitoring average blood oxygenation state in the foot tissue. However, they need sophisticated equipment and specialized expertise. In addition, they may not be able to resolve the relative local blood volume fraction of reduced/- oxyhemoglobin within the bulk of highly scattering tissue media. Therefore, aim of the study is to extract localized blood volume fraction of reduced/-oxyhemoglobin by using diffuse reflectance spectroscopy (DRS). To prove the feasibility of DRS for diabetic foot ulcer detection, we measured the localized blood volume concentrations of reduced hemoglobin (RHb), oxyhemoglobin (HbO2), and oxygen saturation (SO2) from different sites such as lips, earlobe, finger and foot of human subjects by using DRS. The measured average level of HbO2 and SO2 found highest in lips followed by a finger, earlobe, and foot, while the average level of RHb followed the reverse trend. Thus, the preliminary results suggest that the proposed approach could be used for real-time, accurate, and noninvasive monitoring of blood oxygenation parameters from the site of ulcerated foot that may help in early diagnosis, treatment planning, and monitoring of diabetic foot. This may reduce the health-care cost and improve the quality of life of diabetic foot patients.
Improvement of texture reconstruction based on underlying pattern modification

In this paper, we propose a method for reconstructing rough patterns from a texture image while retaining fine texture information using deep learning. The proposed method is based on a deep neural network called pix2pix, which can learn the conversion process between input and output images. In the previous method, which is an improvement on pix2pix, two images were input: an original texture image to be edited and an editing pattern image to be reflected in it. However, these two images alone do not accurately reproduce the color of the original texture image. Therefore, we improve the previous method and improve the reproducibility of the pattern by inputting a pattern image that links the input original texture image to the editing pattern image. The effectiveness of the improved method was verified through several experiments. Future work is to improve the quality of the generated images to improve blur and reproduce accurate input texture information.
An angle measurement algorithm based on ER-FT feature for high-voltage switch

Angle measurement of high-voltage switch based on image is one of crucial technologies to accomplish the evaluating of switch state automatically. To realize the automation detection of the switch status, we analyze limited data and propose an angle measurement algorithm based on ER-FT feature fusion strategy that combines the extra-red feature with frequency-tuned saliency feature to detect the red positioning marks on image. In order to promote angle detecting accuracy and robust under the conditions of the complex background and various weather and illumination, we propose a two-stage segmentation scheme, and an improved Gamma correction (Gamma-M) as image pre-processing is designed in this paper to balance the brightness contrast. The experiments on RasPi are therefore carried out to demonstrate the effectiveness of our method based on the evaluation index such as IoU, the success rate of angle estimation and average angle error. The experimental results demonstrate that the ER-FT algorithm with Gamma-M pre-processing significantly improves the success rate of angle estimation and achieves a higher segmentation accuracy for red mark, while keeps a low average angle error. The outdoor test on RasPi also illustrates the algorithm proposed in this paper is effective and applicable.
The research on the effect of spectral distributions on specular gloss measurement

Specular gloss is the perception by an observer of the shiny appearance of a surface. This perception changes whenever there is a change in the relative position or spectral distribution of the source, the sample, or the observer. However, the spectral distribution of the source in ISO 2813 is CIE standard illuminant C, which is different from CIE standard illuminant D65 and CIE standard illuminant A in JJG696-2015. During the measurement, the reflected flux of the sample is influenced by the luminous reflectance of the sample and the spectral distribution of the source. This paper mainly analyses the influence of different spectral distributions on specular gloss measurement. Combined with the luminous reflectance of the sample in the wavelength range from400nm to 760nm, we theoretically and experimentally analyzed the difference of the specular gloss values under the spectral distributions of CIE standard illuminant D65 and CIE standard illuminant A.
Comparative study on three reconstruction algorithms for a single pixel hyperspectrometer

In this paper, we introduce a single-pixel hyperspectral system based on liquid crystal variable phase retarder (LCVR). Compressed sensing reconstruction algorithms L1-magic, Two-Step Iterative Shrink-age/Thresholding (TwIST), Gradient Projection for Sparse Reconstruction (GPSR) for single-pixel hyperspectral reconstruction are compared. The root mean square error (RMSE), peak signal-to-noise ratio (PSNR), correlation coefficients (CC) and convergence time (CT) are used as the evaluation criterions to estimate the performance of algorithms under various compression ratio. It helps us to choose the optimal algorithm to different application cases.
BER performance of the polar-coded underwater wireless optical communication

Aiming at the phenomenon of signal fading and system performance degradation due to the light intensity fluctuation and beam off-axis drift in the line-of-sight (LOS) transmission of laser-based cross-medium communication systems, which are affected by absorption, scattering, and turbulence, a joint coding scheme based on polar codes and pulse position modulation (PPM) is proposed to study the encoding and decoding as well as the method to improve system performance for laser-based signal transmission from atmosphere to underwater. The laser wireless transmission characteristics and the principle of channel merging and splitting of polar codes are analyzed. Furthermore, in terms of bit error ratio (BER) comparisons are made by simulations between the PPM systems with and without polar codes over weak turbulent channels, and meanwhile the effects of code length and rate on BER are discussed. The simulation results show that, compared to the traditional PPM systems without polar codes at the same BER, a system using the joint coding of the Polar Codes and PPM can obtain a code gain from 1 to 2, namely its BER performance and anti-interference ability could be improved. And thus this research can provide a new technical means for practical applications.
One-pot synthesized millimeter-sized perovskite single crystals for photodetectors

In this work, we fabricated millimeter-sized perovskite single crystal and applied it into photodetectors. The yellowphase perovskite crystals can be obtained through solvent circulation and evaporation, which shows smooth surface and square-shape, and emits green color under 365 nm UV excitation. The photodetector based on it displayed larger response speed and high spectral responsivity.
Diode-pumped Tm:YAG mode-locking laser based on a MoS2 saturable absorber

In this paper, we firstly demonstrate a diode-pumped passive mode-locking laser based on a Tm:YAG crystal and a MoS2 saturable absorber. The Tm:YAG laser produced a 2.68 W continuous-wave (CW) output power at 2013.8 nm. A maximum average output power of 0.2 W was achieved at a pulse repetition rate of 232.2 MHz and a pulse width of about 297.5 ps were achieved under the passive mode-locking operation. In addition, the M2 factors were 1.07 and 1.05 in horizontal and vertical directions, respectively, indicating the near-diffraction limited beam propagation.
Harnessing generative adversarial networks to generate synthetic mitosis images for classification of cell images

The task of detecting and tracking of mitosis is important in many biomedical areas such as cancer and stem cell research. This task becomes complex when done in a high-density cell array, largely due to an extremely imbalanced data, with a very small number of proliferating cells in each image. Using the fact that before proliferating, cells seems to get rounder and brighter, our group extracted bright blobs in each image and considered the patch around each blob as a candidate for mitosis. These candidates were labeled and divided into training, validation and test sets, and used for training of a Convolutional Neural Network (CNN). In the current work, in order to overcome the small number of mitosis samples in the training set, we generated synthetic patches of mitosis using Generative Adversarial Networks (GANs). Trying to predict the labels of the test set candidates using a CNN trained by both real and the synthetically generated images showed an increase in both sensitivity and specificity, in comparison to a CNN trained only on real examples.
A Process-Model for Minimizing Adverse Effects when Using Head Mounted Display-Based Virtual Reality for Individuals with Autism

Interest in the use of virtual reality technologies for individuals with autism spectrum disorders has been increasing for over two decades. Recently, research interest has been growing in the area of head mounted display-based virtual reality technologies, thanks to increased availability and affordability. Affordances and theorized benefits of headset-based virtual reality for individuals with autism spectrum disorders are quite promising. However, very little attention has been given in the literature to implementation safety and ethics. This is a particular concern in light of documented adverse effects associated with headset-based virtual reality. To approach this gap, this article details how the authors approached the issue of minimizing adverse effects with related and overlapping methods, but from two separate, independent research sites—one in the United States and one in the United Kingdom. A structured within- and across-case analysis of the two independent studies was conducted to identify central implementation processes and procedures. Analysis resulted in development of a model for minimizing potential adverse effects of headset-based virtual reality for this population. We assert that our model could provide clarity in terms of design and implementation of headset-based virtual reality for individuals with autism spectrum disorders, guide implementations of future researchers and practitioners, and contribute to minimizing and controlling for potential adverse effects.
Impact of UV-B radiation on photosynthesis ? an overview -

Ultraviolet-B (UV-B) radiation constitutes a minor part of the solar spectrum, being most of this solar radiation absorbed by the UV-screening stratospheric ozone layer. Yet, a global depletion of the ozone layer, largely due to the release of chlorofluorocarbons caused by human activities, has resulted in an increase of solar UV-B radiation at the earth’s surface. Accordingly, in the temperate latitudes, such ozone decrease reached ca. 3% and 6% in the North and South hemispheres, respectively, between 2002 and 2005 (as compared to the 1970s). Despite the uncertainty of long-term predictions, it is also estimated an UV-B increase of 5-10% over temperate latitudes within the next 15 years In this context, this work aim at to present an overview of plants sensitivity/tolerance to UV-B irradiation mostly considering the key photosynthetic metabolism. doi: http://dx.doi. org/10.9755/ejfa.v24i6. 14673
From the Editor

We must continue disseminating robust, high-quality research and evidence-based innovations that challenge and expand our teaching practices to ensure that the next generation of nurses and nurse educators are well prepared and ready to educate students to improve global health. I welcome diversity of thought and perspective, as well as scholarly dialogue and debate as NEP transitions into the next decade. Weexperience many transitions in the course of our lives: from nursing student to expert clinician, from expert clinician to novice educator, from novice educator to master teacher, and from novice researcher to funded investigator. Transitions take time (Schlossberg, 2011) and can be stressful as we face new demands and challenges.Meleis (2010) defined transition as “a passage from one fairly stable state to another fairly stable state.characterized by different dynamic stages, milestones, and turning points” (p. 11). Meleis described these stages as a process related to change and development that can be empowering and growth producing but also accompanied by uncertainty— a time to reflect on where we have been and to consider future possibilities. She noted that the process of transition is essentially positive. Nursing Education Perspectives (NEP) is in a time of transition. Reflecting the National League for Nursing’s (NLN) dedication to excellence in nursing education, NEP, led by Dr. Joyce J. Fitzpatrick as editor, has long been at the forefront of disseminating topics of relevance to nurse faculty and leaders in nursing education. But with the start of 2020, after 22 years in the role, Joyce stepped down asNEP editor. As we bid her adieu, let us reflect on the role Joyce has had in the journal’s growth and maturation. Joyce was named editor of the NLN journal, then titled Nursing and Health Care Perspectives, in January 1998. At that time, we published three to four main articles per issue, with a general emphasis on community health, service-learning, and nurse-managed academic clinics, and the size of the journal never exceeded 48 pages, including advertisements. To reflect the renewed focus in the NLN mission on nursing education, the NLN Board of Governors in 2001 renamed the journal Nursing Education Perspectives. The new title first appeared in the January-February 2002 issue. At that time, there was only an occasional article on research in nursing education— for example, that first issue with the new title included “A Comparison of Student-Centered Versus Traditional Methods of Teaching Basic Nursing Skills in a Learning Laboratory” by Dr. Pamela Jeffries and colleagues (Jeffries, Rew, & Cramer, 2002). As the NLN clarified its mission and goals to advance the science of nursing education, the landscape of research in nursing education exploded, Joyce became more and more selective in soliciting manuscripts that reported on rigorous multisite research studies. She steered the transformation of the NLN official journal into what it is now, the research journal of the NLN and the premier nursing education journal for scholarship in nursing education.
Neural changes following equine‐assisted therapy for posttraumatic stress disorder: A longitudinal multimodal imaging study

While effective treatments for posttraumatic stress disorder (PTSD) exist, many individuals, including military personnel and veterans fail to respond to them. Equine‐assisted therapy (EAT), a novel PTSD treatment, may complement existing PTSD interventions. This study employs longitudinal neuro‐imaging, including structural magnetic resonance imaging (sMRI), resting state‐fMRI (rs‐fMRI), and diffusion tensor imaging (DTI), to determine mechanisms and predictors of EAT outcomes for PTSD.
Natural Occurring Non-Synonymous Single Nucleotide Polymorphisms in Integrase and RNase H Regulate Assembly and Autoprocessing of HIV-1

Recently, a genome-wide association study using plasma HIV RNA reported that 14 naturally occurring non-synonymous single nucleotide polymorphisms (SNPs) in HIV derived from anti-retrovirus naïve patients were associated with virus load (VL). However, the impact of each mutation on viral fitness was not investigated. Here, we constructed a series of HIV variants encoding each SNP using site-directed mutagenesis and examined their replicative abilities and biological properties. An HIV variant containing Met-to-Ile change at codon 50 in integrase (HIV(IN:M50I)) was found an impaired virus. Despite the mutation being in integrase, a quantification assay demonstrated that the virus release was significantly suppressed (P<0.001). Transmission electron microscopy analyses revealed that the accumulation of abnormal shapes of buds on the plasma membrane and the released virus particles retained immature forms. Western blot analysis demonstrated a defect in autoprocessing of GagPol and Gag polyproteins in the HIV(IN:M50I) particles. Förster Resonance Energy Transfer (FRET) assay displayed that GagPol containing IN:M50I (GagPol(IN:M50I)) significantly increased the efficiency of homodimerization (P<0.05) and heterodimerization with Gag (P<0.001), compared to GagPol(WT). HIV replication assay using a series of variants of HIV(IN:M50I) elucidated that the C-terminus residues, Asn at codon 288, plays a key role in the defect and the impaired maturation and replication capability was rescued by two other VL-associated SNPs, Ser-to-Asn change at codon 17 in integrase or Asn-to-Ser change at codon 79 in RNase H. These data demonstrate that Gag and GagPol assembly, virus release and autoprocessing are not only regulated by integrase but also RNase H. Importance A nascent HIV-1 is noninfectious. To become an infectious virus, Gag and GagPol polyproteins in the particles need to be cleaved by mature HIV protease (PR). PR is initially translated as an inactive embedded enzyme in a GagPol polyprotein. The embedded PR in homodimerized GagPol polyproteins catalyzes a proteolytic reaction to release the mature PR. This excision step by a self-cleavage is called autoprocessing. Here, during the evaluation of roles of naturally emerging non-synonymous SNPs in HIV RNA, we found that autoprocessing is inhibited by Met-to-Ile change at codon 50 in integrase in GagPol which increases the efficiency of heterodimerization with Gag. This defect was recovered by co-existing of other SNPs: Ser-to-Asn change at codon 17 in integrase or Asn-to-Ser mutation at codon 79 in RNase H, suggesting that autoprocessing is regulated by not only integrase but also RNase H in GagPol polyprotein.
Non-linearity matters: a deep learning solution to generalization of hidden brain patterns across population cohorts Preprocessing image data and Model architecture selection:

The increasing number of neuroimaging scans in recent years has facilitated the use of complex nonlinear approaches to analyzing such data. More specifically, deep learning, which has been previously hindered by the curse of dimensionality is now feasible. However, it remains challenging to use these techniques develop reliable biomarkers and find an optimal representation of data that explains the biological underpinnings of the mental disorders Here, we employed a 3-dimensional autoencoder with an architecture designed from the ground up for task-fMRI data. Our study presented a coherent strategy for optimizing model parameters and architecture and a method for visualizing and interpreting the latent space representation. We trained our model with multi-task fMRI data derived from the Human Connectome Project (HCP) that provides whole-brain coverage across a range of cognitive tasks. Next, in a transfer learning setting, we tested the generalization of our latent space on UK Biobank data as an independent dataset. We showed that the model did not only learn salient features such as age but also high-level behavioral characteristics and that this representation was highly generic and generalizable to an independent dataset. Furthermore, we demonstrated that the projection of latent space back into the original space is meaningful and interpretable. Finally, our results show that with careful implementation, nonlinear features can provide complementary information that accessible to purely linear methods. Our results provide an important step toward learning interpretable and generalizable latent representations that link cognition with underlying brain systems. with a careful implementation, nonlinear features can provide complementary information that accessible to purely linear methods.
Insights Into the Genetic Architecture of Complex Traits in Napier Grass (Cenchrus purpureus) and QTL Regions Governing Forage Biomass Yield, Water Use Efficiency and Feed Quality Traits

Napier grass is the most important perennial tropical grass native to Sub-Saharan Africa and widely grown in tropical and subtropical regions around the world, primarily as a forage crop for animal feed, but with potential as an energy crop and in a wide range of other areas. Genomic resources have recently been developed for Napier grass that need to be deployed for genetic improvement and molecular dissection of important agro-morphological and feed quality traits. From a diverse set of Napier grass genotypes assembled from two independent collections, a subset of 84 genotypes that best represents the genetic diversity of the collections were selected and evaluated for two years in dry (DS) and wet (WS) seasons under three soil moisture conditions: moderate water stress in DS (DS-MWS); severe water stress in DS (DS-SWS) and, under rainfed (RF) conditions in WS (WS-RF). Data for agro-morphological and feed quality traits, adjusted for the spatial heterogeneity in the experimental blocks, were collected over a two-year period from 2018 to 2020. A total of 135,706 molecular markers were filtered, after removing markers with missing values > 10% and a minor allele frequency (MAF) < 5 %, from the high-density genome-wide markers generated previously using the genotyping by sequencing (GBS) method of the DArTseq platform. A genome-wide association study (GWAS), using two different mixed linear model algorithms, identified more than 58 QTL regions and markers associated with agronomic, morphological and water-use efficiency traits. QTL regions governing purple pigmentation and feed quality traits were also identified. The identified markers will be useful in the genetic improvement of Napier grass through the application of marker-assisted selection and for further characterization and map-based cloning of the QTLs.
Bottom-up in situ formation of Fe3O4 nanocrystals in a porous carbon foam for lithium-ion battery anodes

A facile and scalable process for the in situ formation of Fe3O4 nanocrystals in a pre-formed carbon foam (CF) (Fe3O4/CF) was developed, which involved impregnation of an aqueous iron nitrate solution onto CF followed by controlled thermal treatment in an inert atmosphere. N2adsorption/desorption and BET measurements showed that the CF was a mesoporous carbon with a high pore volume and specific surface area. Transmission electron microscopy, scanning electron microscopy, X-ray diffraction measurement, thermogravimetric analysis, and X-ray photoelectron spectroscopy (XPS) revealed that 5–50 nm Fe3O4 nanocrystals at a high loading of 78.7 wt% were formed preferentially in the confined pores of CF. When tested for anode material in a Li ion half-cell, the Fe3O4/CF composite was far superior to unsupported Fe3O4 nanocrystals, exhibiting significantly improved Coulombic efficiencies and cycling stability and achieving >780 mA h g−1 after 50 deep charge–discharge cycles with >95% cycling efficiency.