Miracle-dz/UniFAR-FTUs huggingface dataset:
Soil properties and silage quality in response to oat and pea seeding ratios and harvest stage on the Qinghai-Tibetan Plateau

Livestock intensification improves production efficiency and enhances the demand for quality forage to feed ruminants. Novel combinations of forage plants, especially including Gramineae and Leguminous plants, benefit both ruminant animals and contribute to a sustainable environment. This study explored an oat-pea mixed seeding strategy as an approach to improving silage quality. Before ensialing, lactic acid bacteria (Lactobacillus plantarum and Lactobacillus brucelli) were added to forage from five different mixed seeding proportions of oats (O) and peas (P) (10:0, 8:2, 7:3, 5:5, and 0:10 oat to pea ratio) at two harvesting periods (the early flowering stage and the milk ripening stage for the oats). The results showed that mixed seeding changed the soil quality parameters. Moreover, the silage from the O5P5 (5:5 oat to pea ratio) group showed the lowest pH values (4.16) and highest LA contents (7.74% DM) after ensiling for 7d (p < 0.05) in early flowering stage. Also, the O5P5 group increased the number of tillers/branches and produced silage with the highest CP content (13.14–14.06) after ensiling for 7d in early flowering stage and both 7d and 30d in early flowering stage and milk ripening stage (p < 0.05). In conclusion, this study found that the selection of oat-pea mixed seeding as O5P5 and harvesting at the milk ripening stage of oat is recommended as a desirable oat-pea mixed seeding strategy for producing high quality silage.
Evaluation of the immunogenicity and efficacy of an rVSV vaccine against Zika virus infection in macaca nemestrina

Zika virus (ZIKV) is a mosquito-borne flavivirus that causes an acute febrile illness. ZIKV can be transmitted between sexual partners and from mother to fetus. Infection is strongly associated with neurologic complications in adults, including Guillain-Barré syndrome and myelitis, and congenital ZIKV infection can result in fetal injury and congenital Zika syndrome (CZS). Development of an effective vaccine is imperative to protect against ZIKV vertical transmission and CZS. Recombinant Vesicular Stomatitis virus (rVSV) is a highly effective and safe vector for the delivery of foreign immunogens for vaccine purposes. Here, we evaluate an rVSV vaccine expressing the full length pre-membrane (prM) and ZIKV envelope (E) proteins (rVSVΔM-ZprME), shown to be immunogenic in murine models of ZIKV infection, for its capacity to induce immune responses in nonhuman primates. Moreover, we assess the efficacy of the rVSVΔM-ZprME vaccine in the protection of pigtail macaques against ZIKV infection. Administration of the rVSVΔM-ZprME vaccine was safe, but it did not induce robust anti-ZIKV T-cell responses, IgM or IgG antibodies, or neutralizing antibodies in most animals. Post ZIKV challenge, animals that received the rVSVΔM control vaccine lacking ZIKV antigen had higher levels of plasma viremia compared to animals that received the rVSVΔM-ZprME vaccine. Anti-ZIKV neutralizing Ab titers were detected in a single animal that received the rVSVΔM-ZprME vaccine that was associated with reduced plasma viremia. The overall suboptimal ZIKV-specific cellular and humoral responses post-immunization indicates the rVSVΔM-ZprME vaccine did not elicit an immune response in this pilot study. However, recall antibody response to the rVSVΔM-ZprME vaccine indicates it may be immunogenic and further developments to the vaccine construct could enhance its potential as a vaccine candidate in a nonhuman primate pre-clinical model.
Deep Eutectic Liquids as a Topical Vehicle for Tadalafil: Characterisation and Potential Wound Healing and Antimicrobial Activity

Deep eutectic solvents (DESs) and ionic liquids (ILs) offer novel opportunities for several pharmaceutical applications. Their tunable properties offer control over their design and applications. Choline chloride (CC)-based DESs (referred to as Type III eutectics) offer superior advantages for various pharmaceutical and therapeutic applications. Here, CC-based DESs of tadalafil (TDF), a selective phosphodiesterase type 5 (PDE-5) enzyme inhibitor, were designed for implementation in wound healing. The adopted approach provides formulations for the topical application of TDF, hence avoiding systemic exposure. To this end, the DESs were chosen based on their suitability for topical application. Then, DES formulations of TDF were prepared, yielding a tremendous increase in the equilibrium solubility of TDF. Lidocaine (LDC) was included in the formulation with TDF to provide a local anaesthetic effect, forming F01. The addition of propylene glycol (PG) to the formulation was attempted to reduce the viscosity, forming F02. The formulations were fully characterised using NMR, FTIR and DCS techniques. According to the obtained characterisation results, the drugs were soluble in the DES with no detectable degradation. Our results demonstrated the utility of F01 in wound healing in vivo using cut wound and burn wound models. Significant retraction of the cut wound area was observed within three weeks of the application of F01 when compared with DES. Furthermore, the utilisation of F01 resulted in less scarring of the burn wounds than any other group including the positive control, thus rendering it a candidate formula for burn dressing formulations. We demonstrated that the slower healing process associated with F01 resulted in less scarring potential. Lastly, the antimicrobial activity of the DES formulations was demonstrated against a panel of fungi and bacterial strains, thus providing a unique wound healing process via simultaneous prevention of wound infection. In conclusion, this work presents the design and application of a topical vehicle for TDF with novel biomedical applications.
DSR-GCN: Differentiated-Scale Restricted Graph Convolutional Network for Few-Shot Hyperspectral Image Classification

Graph convolutional networks (GCNs) have shown great potential for few-shot hyperspectral image (HSI) classification. Mainstream GCNs construct graphs according to single-scale segmentation, which usually ignores subtle adjacency relations between small regions, leading to an unreliable initial local graph. To overcome the above issue, we propose a differentiated-scale restricted GCN (DSR-GCN) for HSI classification. First, we propose a differentiated-scale graph construction method considering both the subtle and relative wider range spectral–spatial relation. Second, restricted fusion loss is designed to restrict the fusion of features extracted with differentiated-scale GCN branches. Finally, we design a lightweight spectral-spatial siamese network (S3Net) to remedy local pixel-level features. The proposed DSR-GCN can better model spatial structure with a reliable and refined graph, and it can capture more discriminate features in few-shot learning (FSL) scenarios. Extensive experiments conducted on four benchmark datasets demonstrate that DSR-GCN outperforms the other deep learning methods in terms of classification accuracy and generalization performance, with improvements in terms of overall accuracy (OA) around 6.20%<inline-formula> <tex-math notation="LaTeX">$\sim $ </tex-math></inline-formula>23.41% (Indian Pines), 4.45%<inline-formula> <tex-math notation="LaTeX">$\sim $ </tex-math></inline-formula>16.48% (University of Pavia), 4.25%<inline-formula> <tex-math notation="LaTeX">$\sim $ </tex-math></inline-formula>11.85% (Salinas), and 2.0%<inline-formula> <tex-math notation="LaTeX">$\sim $ </tex-math></inline-formula>17.23% (University of Houston) under five labeled samples per class.
The Influence of Preparation Parameters on Structural and Optical Properties of N-Type Porous Silicon

In this paper, we describe the formation of macroporous silicon (MPS) formed anodically polarized on n type Si (100) substrates at a constant current density under front side illumination using two electrolytes, HF/Ethanol and HF/Ethanol/H2O2. The effect of adding H2O2 in the solution on the resulting pores were investigated by scanning electron microscopy (SEM), infrared spectroscopy (FTIR), contact angle measurements and UV-vis spectrophotometry. The results showed that for the anodization conditions the MPS formed in peroxide based (H2O2)/HF/Ethanol solution exhibited structures with larger pore size and different pore morphologies depending on the etching time than those formed in HF/Ethanol. The pore density and the pore size of the MPS samples increased with the etching time. The infrared absorption spectrum (FTIR) carried out on the freshly prepared sample indicates that the MPS contains Si-Hx bonds which decrease with increasing the etching time. Finally, measurements of contact angle indicate that the formed MPS samples are highly hydrophobic.
Low complexity user selection algorithms for multi-user MIMO systems

The combined Block Diagonalization and Geometric Mean Decomposition(BD-GMD) is a precoding scheme that is asymptotically optimal for(moderately) high Signal-to-Noise Ratio(SNR) in terms of both channel throughput and the Symbol Error Rate(SER) performance in downlink Multi-User Multiple-Input-Multiple-Output(MU-MIMO) systems.The number of simultaneously supportable users 1with BD-GMD is limited by the number of transmitting and receiving antennas.In a downlink MU-MIMO system with a large number of users,the basestation may select a subset of users to serve in order to maximize the total throughput.The brute-force search for the optimal user set,however,is computationally prohibitive.We propose a low complexity suboptimal user selection algorithm for downlink MU-MIMO systems with BD-GMD.We show that the proposed algorithm has linear complexity in the number of users and achieves around 95% of the total throughput of the complete search method in simulations.
Control Systems for Low-Inertia Power Grids: A Survey on Virtual Power Plants

Virtual Power Plants (VPPs) have emerged as a modern real-time energy management architecture that seeks to synergistically coordinate an aggregation of renewable and non-renewable generation systems to overcome some of the fundamental limitations of traditional power grids dominated by synchronous machines. In this survey paper, we review the different existing and emerging feedback control mechanisms and architectures used for the real-time operation of VPPs. In contrast to other works that have mostly focused on the optimal dispatch and economical aspects of VPPs in the hourly and daily time scales, in this paper we focus on the dynamic nature of the system during the faster sub-hourly time scales. The virtual (i.e., software-based) component of a VPP, combined with the power plant (i.e., physics-based) components of the power grid, make VPPs prominent examples of cyber-physical systems, where both continuous-time and discrete-time dynamics play critical roles in the stability and transient properties of the system. We elaborate on this interpretation of VPPs as hybrid dynamical systems, and we further discuss open research problems and potential research directions in feedback control systems that could contribute to the safe development and deployment of autonomous VPPs.
Smoothing Algorithm for Nonlinear Systems Using Gaussian Mixture Models

A smoothing method for nonlinear systems using Gaussian mixture models is presented. Problems of interest include applications with highly nonlinear dynamics and/or measurement models, and sparse measurements. Two new smoothing methods are presented that incorporate adaptive Gaussian splitting in the forward path, and condensation in the backward path. A nonlinear forward–backward smoothing algorithm with Gaussian mixture models is also enabled by a novel technique to estimate the “backward corrector. ” An experiment of a robot performing indoor navigation in a sparse featured environment demonstrates the performance of the smoothing algorithms in typical applications. Experimental results demonstrate that the new smoothing algorithms give more accurate and consistent estimates than a traditional Kalman smoother, even in the presence of a sparse featured environment and sparse measurements.
Color selection in the consideration of color harmony for interior design

A color selection method that considers subjective principles is becoming more and more necessary in a computer-based color management system. However, one from an engineering perspective has received limited attention. Previously, we developed an approach to measure the degree of color harmony by the similarity of a pleasure-related function, CLD (color linguistic distribution), to a RHD (reference harmony distribution) on a one-dimensional image scale of EXCITING–CALM. Following this approach, a new color selection system is presented in this article by modulating the CLD on the image scale. The procedure used is to encode an inharmonious image as a CLD, then it is modulated and referred to as a RHD, called an imagery specification. Finally, the specified CLD is decoded and reconstructed as a harmonious image in an operated color space. Four types of RHD are compared: three ideal fuzzy sets scaled to extremely calm, quite calm, and slightly calm, and the practical one measured from social trends. For verification, the harmony grade of the decoded image can be measured based on the referred RHD. As a result, four times the harmonic degree of the decoded image is gained than the originally encoded one. For application purposes, the proposed system is suitable for applications related to human subjectivity. © 2000 John Wiley & Sons, Inc. Col Res Appl, 25, 20–31, 2000
Real‐time trust aware scheduling in fog‐cloud systems

Fog computing offers cloud‐like facilities at the network edge, delivering reduced response times to latency sensitive applications. It comprises of fog devices/micro data centers/cloudlets located between users and the cloud data center. Fog devices are generally susceptible to privacy, security, and trust issues. We propose RT‐TADS (Real Time‐Trust Aware Dynamic Scheduling), a scheduling algorithm that accounts for privacy, trust and real‐time performance. To compute the trustworthiness of fog devices, we propose a trust computation model. This model factors in direct and recommended trust techniques for each fog device, and updates their aggregated trust values at regular intervals. User tasks are tagged as: private, semi‐private, and public. Fog devices are classified as: extremely highly trusted, highly trusted, normal trusted, low trusted, and untrusted. RT‐TADS maps the input jobs according to their privacy constraints on trustworthy fog devices, which increases the overall Success Ratio, hence improving real‐time performance. Using the Bitbrain dataset, the real‐time performance of RT‐TADS has been demonstrated, versus comparable algorithms. The results indicate that the proposed RT‐TADS offers an average improvement of 13%, 45%, and 71% in task success ratio compared to RLTCM, no‐trust, and cdc‐only respectively.
Extended-Range Forecasts of Atlantic Tropical Cyclone Events during 2012 Using the ECMWF 32-Day Ensemble Predictions*

AbstractPrevious studies have demonstrated the capability of the European Centre for Medium-Range Weather Forecasts (ECMWF) 51-member, 32-day ensemble to forecast tropical cyclone (TC) events (formation and tracks) in the western North Pacific on the extended range (5–30 days). In this study, the performance of the ECMWF ensemble in extended-range forecasting of Atlantic TCs during May–December 2012 is evaluated using similar approaches. The conclusion from this evaluation is that Atlantic TC events have lower forecastability using the ECMWF ensemble than in the western North Pacific. Hurricanes Kirk and Leslie and Tropical Storms (TSs) Joyce and Oscar were successfully forecast in weeks 1–4 and, thus, are labeled as highly forecastable. Somewhat forecastable storms that are only forecast in three of the four weeks include Hurricanes Ernesto, Isaac, Nadine, and Sandy plus TS Florence. The limited forecastable storms that were successful in only the first two weeks include Hurricanes Gordon and Rafael plus.
Implementation of GAN-Based, Synthetic T2-Weighted Fat Saturated Images in the Routine Radiological Workflow Improves Spinal Pathology Detection

(1) Background and Purpose: In magnetic resonance imaging (MRI) of the spine, T2-weighted (T2-w) fat-saturated (fs) images improve the diagnostic assessment of pathologies. However, in the daily clinical setting, additional T2-w fs images are frequently missing due to time constraints or motion artifacts. Generative adversarial networks (GANs) can generate synthetic T2-w fs images in a clinically feasible time. Therefore, by simulating the radiological workflow with a heterogenous dataset, this study’s purpose was to evaluate the diagnostic value of additional synthetic, GAN-based T2-w fs images in the clinical routine. (2) Methods: 174 patients with MRI of the spine were retrospectively identified. A GAN was trained to synthesize T2-w fs images from T1-w, and non-fs T2-w images of 73 patients scanned in our institution. Subsequently, the GAN was used to create synthetic T2-w fs images for the previously unseen 101 patients from multiple institutions. In this test dataset, the additional diagnostic value of synthetic T2-w fs images was assessed in six pathologies by two neuroradiologists. Pathologies were first graded on T1-w and non-fs T2-w images only, then synthetic T2-w fs images were added, and pathologies were graded again. Evaluation of the additional diagnostic value of the synthetic protocol was performed by calculation of Cohen’s ĸ and accuracy in comparison to a ground truth (GT) grading based on real T2-w fs images, pre- or follow-up scans, other imaging modalities, and clinical information. (3) Results: The addition of the synthetic T2-w fs to the imaging protocol led to a more precise grading of abnormalities than when grading was based on T1-w and non-fs T2-w images only (mean ĸ GT versus synthetic protocol = 0.65; mean ĸ GT versus T1/T2 = 0.56; p = 0.043). (4) Conclusions: The implementation of synthetic T2-w fs images in the radiological workflow significantly improves the overall assessment of spine pathologies. Thereby, high-quality, synthetic T2-w fs images can be virtually generated by a GAN from heterogeneous, multicenter T1-w and non-fs T2-w contrasts in a clinically feasible time, which underlines the reproducibility and generalizability of our approach.
Age-related reference intervals for ambulatory electrocardiographic parameters in healthy individuals

Background The advent of novel monitoring technologies has dramatically increased the use of ambulatory electrocardiography (AECG) devices. However, few studies have conducted detailed large-scale investigations on the incidence of arrhythmias over 24 h, especially ectopy, in healthy individuals over a wide age range. Objectives This study aimed to investigate the incidence of arrhythmias detected using AECG and associated factors, in healthy individuals, over a wide age range. Methods In this cross-sectional study, we performed AECG on 365 healthy volunteers (median [interquartile range]: 48 [36, 67], 20–89 years, 165 men) under free-running conditions for 24 h. Ultrasonic echocardiography and heart rate variability analysis were performed to explore the factors associated with the incidence of arrhythmias. Results The 97.5th percentile of single ventricular ectopy (VE) was 149/day, 254/day, and 1,682/day in the 20–39-, 40–59- and 60–89-year age groups, respectively; that of single supraventricular ectopy (SVE) was 131/day, 232/day, and 1,063/day, respectively. Multivariate analysis revealed that aging was the only independent significant factor influencing the frequency of VE (β = 0.207, P = 0.001). Age (β = 0.642, P < 0.001), body mass index (BMI) (β = −0.112, P = 0.009), and the root mean square of successive differences in RR intervals (β = 0.097, P = 0.035) were factors significantly associated with SVE frequency. Conclusions Age-specific reference intervals of VE and SVE in a large population of healthy participants over a wide age range were generated. VE and SVE increased with age; SVE was influenced by BMI and the aging-induced decrease in parasympathetic tone activity.
Trait Mindfulness and Problematic Smartphone Use in Chinese Early Adolescent: The Multiple Mediating Roles of Negative Affectivity and Fear of Missing Out

This study used a cross-sectional study design to investigate whether the mindfulness trait was a protective factor against problematic smartphone use (PSPU) of early adolescents, and whether negative affectivity and fear of missing out (FoMO) mediated this relationship. The study selected a sample of middle school students (N = 517, 46.03% males, Mage = 13.81, SD = 1.40) in China. The results of the structural equation modelling indicated that (a) mindfulness significantly and negatively predicted PSPU, (b) FoMO played a mediating role between mindfulness and PSPU, (c) negative affectivity (including depression and anxiety) played a mediating role between mindfulness and PSPU, but loneliness did not, and (d) negative affectivity and FoMO played a chain-mediated role, and depression, anxiety, and loneliness played a chain-mediated role with FoMO between mindfulness and PSPU. We discuss the possibility that high levels of mindfulness in early adolescents may reduce the short-term effects of problematic smartphone use by reducing negative emotions and FoMO and relate our results to an emphasis on the role of enhanced mindfulness in long-term internal self-regulation and well-being. Findings have implications for individuals and schools for PSPU prevention and intervention.
Distribution‐Free Methods in Regression1

Summary A modification to the least-squares estimating equations in simple linear regression, leading to exact distribution-free inference about slope, is outlined. The modification involves a general residual-transformation iψ and the cases of ψ— sign, rank, and the identity are discussed in some detail. It is also shown how exact inference about individual parameters in regressions with more than one design variable can be carried out by a restricted permutation argument coupled with a suitable design.
Towards Area Efficient Logic Circuit: Exploring Potential of Reconfigurable Gate by Generic Exact Synthesis

In this article, we propose a generic design methodology to achieve area-efficient reconfigurable logic circuits by using exact synthesis based on Boolean satisfiability (SAT) solver. The proposed methodology better leverages the high representation ability of emerging reconfigurable logic gates (RLGs) to achieve reconfigurable circuits with fewer gates. In addition, we propose a fence-based acceleration method to provide >10× speed up for the synthesis without an observable loss of optimality. Furthermore, four sets of RLGs are developed based on a recently proposed valley-spin device as a case study to demonstrate the advantage of the proposed circuit. Simulations have been performed to analyze the impact of the fence searching algorithm and combination of operators. Based on disjoint-support decomposable (DSD) benchmarks, up to 38% and 73% reductions are observed in the area and energy-delay-area product (EDAP), respectively, compared to CMOS counterparts. Compared to the two existing synthesis methods, the proposed scheme provides 40% and 26.3% reduction in EDAP based on MCNC benchmark.