Miracle-dz/UniFAR-FTUs huggingface dataset:
The relationship between shifts in the rhizosphere microbial community and root rot disease in a continuous cropping American ginseng system

The root rot disease causes a great economic loss, and the disease severity usually increases as ginseng ages. However, it is still unclear whether the disease severity is related to changes in microorganisms during the entire growing stage of American ginseng. The present study examined the microbial community in the rhizosphere and the chemical properties of the soil in 1–4-year-old ginseng plants grown in different seasons at two different sites. Additionally, the study investigated ginseng plants' root rot disease index (DI). The results showed that the DI of ginseng increased 2.2 times in one sampling site and 4.7 times in another during the 4 years. With respect to the microbial community, the bacterial diversity increased with the seasons in the first, third, and fourth years but remained steady in the second year. The seasonal changing of relative abundances of bacteria and fungi showed the same trend in the first, third, and fourth years but not in the second year. Linear models revealed that the relative abundances of Blastococcus, Symbiobacterium, Goffeauzyma, Entoloma, Staphylotrichum, Gymnomyces, Hirsutella, Penicillium and Suillus spp. were negatively correlated with DI, while the relative abundance of Pandoraea, Rhizomicrobium, Hebeloma, Elaphomyces, Pseudeurotium, Fusarium, Geomyces, Polyscytalum, Remersonia, Rhizopus, Acremonium, Paraphaeosphaeria, Mortierella, and Metarhizium spp. were positively correlated with DI (P < 0.05). The Mantel test showed that soil chemical properties, including available nitrogen, phosphorus, potassium, calcium, magnesium, organic matter, and pH, were significantly correlated to microbial composition. The contents of available potassium and nitrogen were positively correlated with DI, while pH and organic matter were negatively correlated with DI. In summary, we can deduce that the second year is the key period for the shift of the American ginseng rhizosphere microbial community. Disease aggravation after the third year is related to the deterioration of the rhizosphere microecosystem.
Extending Power and Sample Size Approaches Developed for McNemar's Procedure to General Sign Tests

Current software and textbooks present procedures to estimate power and sample size for sign tests that only apply to settings where positive (i.e., X= 1) or negative (i.e., X=−1), but not neutral (i.e., X= 0) outcomes occur. However, many studies analyzed by sign tests involve the more general setting where significant amounts of neutral outcomes can occur. This paper illustrates extension of existing power/sample size approaches and software that have been developed for matched binary responses (McNemar's discordant pairs) to general sign tests with neutral outcomes occurring. An application is made to a recent study that the author collaborated on.
Principal component analysis and genetic divergence studies for yield and quality-related attributes of rice restorer lines

A study on genetic diversity and principal component analysis (PCA) in a set of 90 fertility restorer lines of rice was conducted to identify potential parents for producing high-yielding hybrids. The D2 statistics uncovered the maximum inter-cluster distance between the clusters having different genotypes. The genotypes PS 2, PRR 828, JR-4322-2, and JR-4322-2 belonging to these diversified gene pools may produce heterotic hybrid combinations involving the most suitable parents mentioned above. The PCA reduces dimensional complexity into nine principle axes with PC1 account maximum variable genotypes, namely, JR-1009, ANP-553, JR-1062-1, JR-1103-1, JR-1023-1, JR-1054-4, IR09N 261, JR-1008, NPT-3806, and JR-81. Considering the magnitude of genetic distance, the per cent contribution of traits towards divergence (fertile spikelet/plant and total spikelet/plant) along with the highest cluster means of these traits reflected by the genotypes belonging to clusters, IX and X. The most quality attributes were included in PC4 and PC5 containing genotypes NPT 10, R710, and JR1301. The diversified gene pool and intensive selection designed for varietal development followed by molecular characterization give a precise idea about the upcoming utilization of existing genetic diversity.
The Role of Protein-Rich Extracts from Chondrus crispus as Biostimulant and in Enhancing Tolerance to Drought Stress in Tomato Plants

The application of seaweed extract-based biostimulants is a promising approach for achieving sustainable agriculture, with an enormous potential of improving crop yield and mitigating climate change effects. Abiotic stressors, such as drought, are major factors resulting in tomato (Solanum lycopersicum L.) yield losses and seaweed-based biostimulants have been proposed as an eco-friendly strategy to counteract this negative impact. Chondrus crispus is a common red seaweed widely used as source of carrageenans, not yet explored as a plant biostimulant. In this study, a protein hydrolysate-rich C. crispus extract, by-products of the carrageenan extraction, was tested on tomato plants under well-watered condition and water shortage. The foliar application of the protein-rich C. crispus extract conferred drought tolerance to tomato plants resulting in less noticeable visual stress symptoms. Treated plants showed higher shoot height and biomass under both well-watered and water deficit conditions, evidencing the double effect exerted by this new biostimulant, as plant growth promoter and drought stress protector. The treatment with the biostimulant had an effect on levels of abscisic acid and proline, and triggered the expression of Solyc02g084840, a drought marker gene. Finally, a label-free mass spectrometric approach allowed us to identify phycoerythrins and phycocyanins as major bioactive proteins contained in the extract. Altogether, these results indicate that the foliar application of protein hydrolysate-rich extracts from C. crispus improved tomato plant growth and tolerance to drought stress, suggesting a new opportunity for further applications in the agriculture and horticultural sectors.
Prediction of paroxysmal atrial fibrillation by footprint analysis

This study presents a simple algorithm named footprint analysis to predict risk and onset of paroxysmal atrial fibrillation (PAF) from single channel surface electrocardiogram. The approach is based on hypothesis that subject who has risk of PAF would display a specific pattern in change of heart rate and could be applied as a predictor to identify the risk and onset of PAF. To quantify patterns of heart rate dynamics, the triplet codes (0, 1, 2) is assigned according to difference of adjacent R-R intervals to represent equal, acceleration, and deceleration of successive RR intervals, respectively. A R-R interval series is then continuously weighted by a 7 heartbeats window, which results in a set of 6-bits number. Each number represents a specific pattern of heart rate dynamics. The strategies for both events of competition are to determine which number has higher possibility to be present in PAF patients, and to identify the number that only present before onset of PAF. A set of number determined by the algorithm from learning dataset was then applied as footprint to the testing dataset. Score for event 1 was 33/50 (entry 20010422.030701) and score for event 2 was 38/50 (CinC Challenge 2001 entry 20010423.045638, entrant 2). The successful of this algorithm is to find hidden pattern embedded in the highly dimensional phase space of R-R intervals. We look forward to understanding the link between microscopic variation in R-R intervals and macroscopic physiologic conditions.
Adaptive Bandwidth Management Model for Wireless Mobile Ad-hoc Network

The quality of service (QoS) component in a mobile ad-hoc network has an active role in the current network scenario. In a dynamic mobile ad hoc network, ensuring optimum QoS with a scarce network resource is a significant challenge. To achieve QoS, it is essential to adopt some effective and efficient mechanisms. We have proposed an adaptive bandwidth manager model (ABMM) which uses a bandwidthsharing concept along with the flexible bandwidth reservation algorithm (FBRA) for an effective, quick and authentic data transfer. During real-time data transfer, to make communication effective, we make use of bandwidth-sharing network design problems and the concept of reserving bandwidth in high-performance networks. In our proposed model we are concentrating on the maximum utilization of resources, and using the scheduling concept to provide the minimum required bandwidth guarantee to QoS flows. Our goal is to reduce the delay in data transfer and enhance the throughput while properly utilizing the system resources. Our simulation result also shows that our model improves the network performance.
The Ericksen number and Deborah number cascades in sheared polymeric nematics

Abstract Samples of liquid crystalline poly(γ-benzyl-glutamate) solutions are sheared between glass surfaces with gaps, d = 10–500 μ, and shearing velocities, V = 0·05–10 000 μs−1 so that the Ericksen number E [tbnd] Vdγ 1/K is varied over a large range, E ≈ 1–107. Here γ1 is the rotational viscosity and K 1 is the Frank splay constant, with γ1/K 1 estimated to be approximately 1 s μ−2 for our samples. We observe by polarizing microscopy a sequence of transitions with increasing Ericksen number analogous to that observed in small molecule tumbling nematics: namely rotation of the director out of the shearing plane and into the vorticity direction at Vd ≈ 25 μ2 s−1, and formation of roll cells at Vd ≈ 50 μ2 s−1. The roll cells become finer with increased Vd in accord with predictions of linear stability theory using the Leslie-Ericksen equations, and at Vd ≳ 500 μ2 s−1, the cells become very irregular, producing director turbulence. The turbulence becomes finer in scale as Vd increases, reaching sub-micron.
Mid‐infrared dual‐comb polarimetry of anisotropic samples

The mid-infrared (mid-IR) anisotropic optical response of a material probes vibrational ﬁngerprints and absorption bands sensitive to order, structure and direction dependent stimuli. Such anisotropic properties play a fundamental role in catalysis, optoelectronic, photonic, polymer and biomedical research and applications. Infrared dual-comb polarimetry (IR-DCP) is introduced as a powerful new spectroscopic method for the analysis of complex dielectric functions and anisotropic samples in the mid-IR range. IR DCP enables novel hyperspectral and time-resolved applications far beyond the technical possibilities of classical Fourier-transform IR (FTIR) approaches. The method unravels structure–spectra relations at high spectral bandwidth (100 cm–1) and short integration times of 65 μ s, with previously unattainable time resolutions for spectral IR polarimetric measurements for potential studies of noncyclic and irreversible processes. The polarimetric capabilities of IR-DCP are demonstrated by investigating an anisotropic inhomogeneous free-standing nanoﬁber scaﬀold for neural tissue applications. Polarization sensitive multi-angle dual-comb transmission amplitude and absolute phase measurements (separately for ss-, pp-, ps-and sp-polarized light) allow the in-depth probing of the samples’ orientation dependent vibrational absorption properties. Mid-IR anisotropies can be quickly identiﬁed by cross-polarized IR-DCP polarimetry.
Low emittance lattice for LEP

In order to obtain the largest luminosity with LEP2, it is attractive to make the beam emittance as small as possible because the beam-beam effect is not a limitation at the energy of E/spl ap/90 GeV for the obtained bunch currents. This can be achieved with a high tune lattice. Two possible candidates are lattices with a horizontal phase advance of 108/spl deg/ or 135/spl deg/ per cell. Both have a vertical phase advance of 60/spl deg/. These lattices were developed during 1994 and the results are presented. Tests to reach high intensity for the 108/spl deg/ lattice were performed and the bunch current achieved is compared with expectations. For this lattice the detuning vs. intensity and several optics parameters were measured as well.
Adaptive optics and vision

It has long been recognised that the optical quality of the human eye is far from diffraction limited. This affects our visual acuity and severely limits the resolution at which images of the living retina can be obtained. Adaptive optics is a technique that can correct for the eye's aberrations and provide diffraction limited resolution. The origins of the technique lie in astronomy, but it was successfully adapted to the human eye just over 10 years ago. Since then there have been rapid developments in the field of adaptive optics and vision science. In vivo images of the retina can now be routinely achieved with unprecedented resolution. Sophisticated experiments can be performed to gain a deeper knowledge of the interaction of neural retinal architecture and visual perception. This article presents the theory behind adaptive optics for the human eye and reviews the developments in this field to date.
Investigating the mechanical properties and morphology of novalac phenolic resin nanocomposite/hybrid short fibers carbon and glass reinforced with silica nanoparticles

The purpose of this research is to make a nanocomposite with combined fibers in order to achieve two integrated mechanical characters including strength and plastic deformation in an optimal way. Novalac type phenolic resin (PF), short fibers carbon (CF) and glass (GF) and silica (SiO2) nanoparticles were used for making. The results showed that with the hybrid of carbon and glass fibers (CGF) in the composite, the ultimate strength and Plastic deformation increased compared to the samples without a combination, and it was modified as an optimal sample. Also, the results showed that the composite sample with hybrid fibers with 2 wt% SiO2 nanoparticles increased the tensile strength by 25%, the bending strength by 48% and the buckling strength by 37%. From the X-ray diffraction and EDX tests, the dispersion of nanoparticles in the composite was determined, and the SEM images showed that with the presence of SiO2 nanoparticles, The amount of adhesion and penetration between resin and fibers has increased. One of the main applications of hybrid nanocomposite can be mentioned portable light structures on land, sea and air, sports goods and orthopedic equipment.
A Hybrid Machine Learning Approach to Screen Optimal Predictors for the Classification of Primary Breast Tumors from Gene Expression Microarray Data

The high dimensionality and sparsity of the microarray gene expression data make it challenging to analyze and screen the optimal subset of genes as predictors of breast cancer (BC). The authors in the present study propose a novel hybrid Feature Selection (FS) sequential framework involving minimum Redundancy-Maximum Relevance (mRMR), a two-tailed unpaired t-test, and meta-heuristics to screen the most optimal set of gene biomarkers as predictors for BC. The proposed framework identified a set of three most optimal gene biomarkers, namely, MAPK 1, APOBEC3B, and ENAH. In addition, the state-of-the-art supervised Machine Learning (ML) algorithms, namely Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Neural Net (NN), Naïve Bayes (NB), Decision Tree (DT), eXtreme Gradient Boosting (XGBoost), and Logistic Regression (LR) were used to test the predictive capability of the selected gene biomarkers and select the most effective breast cancer diagnostic model with higher values of performance matrices. Our study found that the XGBoost-based model was the superior performer with an accuracy of 0.976 ± 0.027, an F1-Score of 0.974 ± 0.030, and an AUC value of 0.961 ± 0.035 when tested on an independent test dataset. The screened gene biomarkers-based classification system efficiently detects primary breast tumors from normal breast samples.
Simultaneous Predictions of Chemical and Phase Equilibria in Systems with an Esterification Reaction Using PC-SAFT

The study of chemical reactions in multiple liquid phase systems is becoming more and more relevant in industry and academia. The ability to predict combined chemical and phase equilibria is interesting from a scientific point of view but is also crucial to design innovative separation processes. In this work, an algorithm to perform the combined chemical and liquid–liquid phase equilibrium calculation was implemented in the PC-SAFT framework in order to predict the thermodynamic equilibrium behavior of two multicomponent esterification systems. Esterification reactions involve hydrophobic reacting agents and water, which might cause liquid–liquid phase separation along the reaction coordinate, especially if long-chain alcoholic reactants are used. As test systems, the two quaternary esterification systems starting from the reactants acetic acid + 1-pentanol and from the reactants acetic acid + 1-hexanol were chosen. It is known that both quaternary systems exhibit composition regions of overlapped chemical and liquid–liquid equilibrium. To the best of our knowledge, this is the first time that PC-SAFT was used to calculate simultaneous chemical and liquid–liquid equilibria. All the binary subsystems were studied prior to evaluating the predictive capability of PC-SAFT toward the simultaneous chemical equilibria and phase equilibria. Overall, PC-SAFT proved its excellent capabilities toward predicting chemical equilibrium composition in the homogeneous composition range of the investigated systems as well as liquid–liquid phase behavior. This study highlights the potential of a physical sound model to perform thermodynamic-based modeling of chemical reacting systems undergoing liquid–liquid phase separation.
Star Formation in Molecular Clouds: Observation and Theory

Star-formation (SF) processes occurring on the scale of giant molecular clouds (10 to the 6th solar masses and 10 to the 20th cm) or smaller are discussed, reviewing the results of recent theoretical and observational investigations. Topics examined include the origin of stellar masses; bimodal SF; initial mass functions; binary stars, bound clusters, and hierarchical fragmentation; and the efficiency of SF. The properties of molecular clouds and the origin of substructures in molecular clumps are explored in detail, and consideration is given to gravitational collapse and protostars, bipolar outflows from young stellar objects, visible young stellar objects, and the implications for binary-star and planetary-system formation.
Diurnal Valley Winds in a Deep Alpine Valley: Model Results

Thermally driven local winds are ubiquitous in deep Alpine valleys during fair weather conditions resulting in a unique wind climatology for any given valley. The accurate forecasting of these local wind systems is challenging, as they are the result of complex and multi-scale interactions. Even more so, if the aim is an accurate forecast of the winds from the near-surface to the free atmosphere, which can be considered a prerequisite for the accurate prediction of mountain weather. This study combines the evaluation of the simulated surface winds in several Alpine valleys with a more detailed evaluation of the wind evolution for a particular location in the Swiss Rhone valley, at the town of Sion during the month of September 2016. Four numerical simulations using the COSMO model are evaluated, two using a grid spacing of 1.1 km and two with a grid spacing of 550 m. For each resolution, one simulation is initialised with the soil moisture from the COSMO analysis and one with an increased soil moisture (+30%). In a first part, a comparison with observations from the operational measurement network of MeteoSwiss is used to evaluate the model performance, while, in a second part, data from a wind profiler stationed at Sion airport is used for a more detailed evaluation of the valley atmosphere near the town of Sion. The analysis focuses on 18 valley wind days observed in the Sion region in September 2016. Only the combination of an increased soil moisture and a finer grid spacing resulted in a significant improvement of the simulated flow patterns in the Sion region. This includes a stronger and more homogeneous along-valley wind in the Wallis and a more realistic cross-valley wind and temperature profile near the town of Sion. It is shown that the remaining differences between the observed and simulated near-surface wind are likely due to very local topographic features. Small-scale hills, not resolved on even the finer model grid, result in a constriction of the valley cross section and an acceleration of the observed low-level up-valley wind in the region of Sion.
ANS ultraviolet observations of external galaxies. I - Exciting stars of H II regions in the Large Magellanic Cloud

We present UV observations in the wavelength range 1550--33000 A of the star clusters in several H II regions belonging to the Large Magellanic Cloud (LMC). The early type stars (spectral types O, B, and A) in these clusters are characterized by a moderately steep luminosity function that is close to the Salpeter-Sandage initial luminosity function for early type stars. We confirm the general shape of the reddening law as derived earlier by the use of a different method. The total luminosity of the 30 Dor star cluster is about 10/sup 8/ L/sub sun/, while the luminosities of the other observed regions are 0.5--1.0 x 10/sup 7/ L/sub sun/. The central object R136 contributes significantly to the excitation of 30 Dor.
Experimental verification of Förster energy transfer between semiconductor quantum dots

In recent years, energy transfer (ET) using semiconductor quantum dots (QDs) is getting increased attention. However, it has been postulated that ET between QDs is based on the F\"orster model, which is a well-established model of ET mechanism in organic dye systems, without verification. In this work, we have investigated ET mechanism in colloidal CdS QDs measuring photoluminescence dynamics of a bilayer structure consisting of differently sized CdS QDs. In the bilayer structure, the distance between the monolayer of donor QDs and that of acceptor QDs was controlled precisely by a spacer layer that is layer-by-layer assembly of polyelectrolytes. The bilayer structure enabled us to systematically measure the spacer-layer dependence of photoluminescence dynamics reflecting the ET process between QDs. It is demonstrated that ET between the donor and acceptor QDs is conclusively dominated by the dipole-dipole interaction, which verifies the appropriateness of the F\"orster model.