Miracle-dz/UniFAR-FTUs huggingface dataset:
Spot blotch disease resistance and heat stress tolerance in spring wheat (Triticum aestivum L.)

Spot blotch caused by Bipolaris sorokiniana is a major disease of wheat in warm and humid regions of Nepal. The fungus has a worldwide distribution but as a pathogen, it is the most aggressive under the conditions of high relative humidity and temperature associated with the low fertility of soils in Nepal. The yield loss due to the disease is very significant in Nepal. This experiment was conducted to identify the genotypes having a good level of resistance against spot blotch. Canopy temperature measurements using infrared thermometry, to assess variation in foliar blight resistance along with heat tolerance as an integrative selection criterion. The experiment set was comprising 52 genotypes and arranged in alpha lattice design with two replications in 2017/-2018 Directorate of agricultural research center, Parwanipur, Bara, Nepal. Each plot size was 8 rows of 3 meters long. Three times disease scoring was done in Flag leaf, and Penultimate leaf method and calculated the Area under the disease progress curve (AUDPC). Other data were analyzed by using R software (4.2.2). Canopy temperature, heading days, days to maturity, plant height, number of grains per spike (NGPS), number of tillers per meter square (NTPM), thousand-grain weight (TGW), and grain yield were found highly significant. The genotype 32 was found the highest yielder (5141 kg/ha) and canopy temperature 16.50 C with a 279; 610 F; F-1AUDPC, respectively.
Hyperglycemia Aggravates Periodontitis via Autophagy Impairment and ROS-Inflammasome-Mediated Macrophage Pyroptosis

Macrophage pyroptosis drives the secretion of IL-1β, which has been recently reported to be a featured salivary biomarker for discriminating periodontitis in the presence of diabetes. This study aimed to explore whether macrophage pyroptosis plays a role in the development of diabetes mellitus–periodontitis, as well as potential therapeutic strategies. By establishing a model of experimental diabetes mellitus–periodontitis in rats, we found that IL-1β and gasdermin D were highly expressed, leading to aggravated destruction of periodontal tissue. MCC950, a potent and selective molecule inhibitor of the NLRP3 inflammasome, effectively inhibited macrophage pyroptosis and attenuated alveolar bone losses in diabetes mellitus–periodontitis. Consistently, in vitro, high glucose could induce macrophage pyroptosis and thus promoted IL-1β production in macrophages stimulated by lipopolysaccharide. In addition, autophagy blockade by high glucose via the mTOR-ULK1 pathway led to severe oxidative stress response in macrophages stimulated by lipopolysaccharide. Activation of autophagy by rapamycin, clearance of mitochondrial ROS by mitoTEMPO, and inhibition of inflammasome by MCC950 could significantly reduce macrophage pyroptosis and IL-1β secretion. Our study demonstrates that hyperglycemia promotes IL-1β production and pyroptosis in macrophages suffered by periodontal microbial stimuli. Modulation of autophagy activity and specific targeting of the ROS-inflammasome pathway may offer promising therapeutic strategies to alleviate diabetes mellitus–periodontitis.
Evaluating the utility of facial identification information: Accuracy versus precision

Facial identification evidence obtained from eyewitnesses, such as person descriptions and facial composites, plays a fundamental role in criminal investigations and is regularly regarded as valuable evidence for apprehending and prosecuting perpetrators. However, the reliability of such facial identification information is often queried. Person descriptions are frequently reported in the research literature as being vague and generalisable, whilst facial composites often exhibit a poor likeness to an intended target face. This raises questions regarding the accuracy of eyewitness facial identification information and its ability to facilitate efficient searches for unknown perpetrators of crimes. More specifically, it questions whether individuals, blind to the appearance of a perpetrator of a crime (i.e. the public), can correctly identify the intended target face conveyed by facial identification information recalled from eyewitness memory, and which of the two traditional facial identification formats would be better relied upon by law enforcement to enable such searches. To investigate this, in the current study (N=167) we employed two metrics – identification accuracy and identification precision – to assess the utility of different formats of eyewitness facial identification information in enabling participants to correctly identify an unknown target face across three different formats: facial descriptions, facial composites and computer-generated description-based synthetic faces. A statistically significant main effect for the format of facial identification information on identification accuracy (p<0.001) was found, with a higher target identification accuracy yielded by facial descriptions in comparison to composites and description-based synthetic faces. However, the reverse relationship was established for identification precision, where composites and description-based synthetic faces enabled significantly greater precision in the narrowing down of a suspect pool than did facial descriptions, but did not necessarily result in the retainment of the intended target face (p<0.001).
MSRFNet for skin lesion segmentation and deep learning with hybrid optimization for skin cancer detection

ABSTRACT Skin cancer is the irregular growth of skin cells, which is most often termed as cancer, developed by exposure of ultraviolet rays from sun. In this research paper, deep learning enabled hybrid optimization is followed for skin cancer detection and lesion segmentation. Two optimization algorithms are followed for skin lesion segmentation and cancer detection. Here, pre-processing is done by anisotropic diffusion followed by skin lesion segmentation. Here, Multi-Scale Residual Fusion Network (MSRFNet) is utilized for skin lesion segmentation, which is trained by proposed Average Subtraction Student Psychology Based Optimization (ASSPBO). After skin lesion segmentation, necessary features are extracted, followed by skin cancer detection. Skin cancer is detected by Deep Residual Network (DRN) trained by proposed Fractional ASSPBO (FrASSPBO). Moreover, performance of proposed FrASSPBO-DRN is analysed by three performance metrics like testing accuracy, True Positive Rate (TPR), and False Positive Rate (FPR) with values of 93.4%, 94%, and 8.2%.
Applying a risk governance approach to examine how professionals perceive the benefits and risks of clinical genomics in Australian healthcare

Clinical genomics is a system of multiple stakeholders and institutions. Yet, studies focusing on the comparative perspectives of these stakeholders are limited. This study engages four groups of professionals (clinical geneticists, genetic counselors, laboratory professionals, and researchers) working in clinical genomics to investigate their perceptions of the benefits and risks of using genomics in Australian healthcare. The study is underpinned by a risk governance approach. For data collection, qualitative semi-structured interviews were used. Our results show that all professionals unanimously identified that the benefit of clinical genomics lies in improving health outcomes for patients. However, the risks associated with delivering this benefit differed by professional category. We found that the further the profession was from the patient (e.g. researcher) the narrower the perceived risks were amongst the individuals interviewed. However, “privacy” as a perceived risk was ranked highly by all professions indicating a shared desire for responsible data governance practices.
Reachability and controllability of switched linear systems

Investigates the reachability and controllability issues for switched linear discrete-time systems. Geometric characterization of controllability is presented. For reversible systems, the controllable sets and the reachable sets are identified in Wonham's (1974) geometric approach. Verifiable conditions for reachability and controllability of switched linear continuous-time systems are also presented.
Reticulocalbin 3 Is a Novel Mediator of Glioblastoma Progression

Simple Summary Glioblastoma is the deadliest primary brain tumor. Current treatment strategies for glioblastoma are not effective, and patients exhibit poor survival rates. Emerging studies implicated glioma stem cells (GSCs) in tumor initiation, progression, and therapy resistance. There is an unmet need to identify new therapeutic candidates for glioblastoma. Our study showed that reticulocalbin 3 (RCN3), an ER lumen residing Ca2+ binding protein, is overexpressed in glioblastoma and associated with poor survival rates. The reduction in RCN3 expression using shRNA or gRNA resulted in reduced proliferation and self-renewal of GSCs. The RNA-seq results showed that RCN3 knockdown altered the expression of several genes related to translation, ribosome, stem cell differentiation, and extracellular matrix. In silico analysis of glioblastoma patient datasets demonstrated a positive correlation of RCN3 with ribosomal pathway genes. Importantly knockdown of RCN3 significantly enhanced the survival of tumor-bearing mice. Our study suggests that RCN3 could be a potential therapeutic target in glioblastoma. Abstract Glioblastoma is the most common malignant primary brain tumor. Molecular mechanisms underlying the pathobiology of glioblastoma are incompletely understood, emphasizing an unmet need for the identification of new therapeutic candidates. Reticulocalbin 3 (RCN3), an ER lumen-residing Ca2+ binding protein, plays an essential role in protein biosynthesis processes via the secretory pathway. Emerging studies demonstrated that RCN3 is a target for therapeutic intervention in various diseases. However, a knowledge gap exists about whether RCN3 plays a role in glioblastoma. Publicly available datasets suggest RCN3 is overexpressed in glioblastoma and portends poor survival rates. The knockdown or knockout of RCN3 using shRNA or CRISPR/Cas9 gRNA, respectively, significantly reduced proliferation, neurosphere formation, and self-renewal of GSCs. The RNA-seq studies showed downregulation of genes related to translation, ribosome, and cytokine signaling and upregulation of genes related to immune response, stem cell differentiation, and extracellular matrix (ECM) in RCN3 knockdown cells. Mechanistic studies using qRT-PCR showed decreased expression of ribosomal and increased expression of ER stress genes. Further, in silico analysis of glioblastoma patient datasets showed RCN3 expression correlated with the ribosome, ECM, and immune response pathway genes. Importantly, the knockdown of RCN3 using shRNA significantly enhanced the survival of tumor-bearing mice in orthotopic glioblastoma models. Our study suggests that RCN3 could be a potential target for the development of a therapeutic intervention in glioblastoma.
Effect of adatom surface diffusivity on microstructure and intrinsic stress evolutions during Ag film growth

The effect of the adatom surface diffusivity on the evolution of the microstructure and the intrinsic stress of thin metal films was investigated for the case of growth of polycrystalline Ag films on amorphous SiO2 (a-SiO2) and amorphous Ge (a-Ge) substrates, with high and low Ag adatom surface diffusivity, respectively. The surface diffusivity of the deposited Ag adatoms on the a-Ge substrate is suppressed also after coalescence of Ag islands due to the continuous (re)segregation of Ge at the surface of the growing film as evidenced by in-situ XPS. An assessment could be made of the role of adatom surface diffusivity on the microstructural development and the intrinsic stress evolution during film growth. As demonstrated by ex-situ TEM and ex-situ XRD, the Ag films grown on the a-SiO2 and a-Ge substrates possess strikingly different microstructures in terms of grain shape, grain size, and crystallographic texture. Nevertheless, the real-time in-situ stress measurements revealed a compressive → tensile → .
Kinetic study of ion-acoustic plasma vortices

The kinetic theory of electron plasma waves with finite orbital angular momentum has recently been introduced by Mendonca. This model shows possibility of new kind of plasma waves and instabilities. We have extended the theory to ion-acoustic plasma vortices carrying orbital angular momentum. The dispersion equation is derived under paraxial approximation which exhibits a kind of linear vortices and their Landau damping. The numerical solutions are obtained and compared with analytical results which are in good agreement. The physical interpretation of the ion-acoustic plasma vortices and their Landau resonance conditions are given for typical case of Maxwellian plasmas.
Chaos Forecast for Traffic Conflict Flow

The fundamentals of the chaos theory were introduced from the chaotic phase-space reconstruction,then the chaos forecasting method and its application in the traffic conflict flow forecast were studied.Then a case study of a crossroad traffic conflict flow by means of the chaos forecasting method was performed,and the forecasting method and results were evaluated by the gray error checking.The evaluated results show that the chaos forecasting method is effective in forecasting the traffic conflict flow.
Improving Leaf Area Index Estimation With Chlorophyll Insensitive Multispectral Red-Edge Vegetation Indices

As an essential vegetation biophysical trait that determines the plant's structure and photosynthetic capacity, characterizing of leaf area index (LAI) is important for vegetation growth and health monitoring. The empirical models based on vegetation indices (VIs) from remote sensing images are an effective method for deriving LAI. However, due to the coupled impacts of LAI and leaf chlorophyll content (LCC) on canopy reflectance and saturation effect, most VIs cannot achieve a good accuracy of LAI estimation. The remotely sensed red-edge reflectance can provide valuable information to delineate the LAI, therefore a series of leaf chlorophyll insensitive red-edge VIs by using the Sentinel-2 and GaoFen-6 (GF-6) multispectral images are developed in this work to improve the LAI estimation accuracy. The potentials of reflecting LAI variations and sensitivity to LCC changes for each Sentinel-2 and GF-6 red-edge band are comprehensively analyzed based on the PROSAIL model to select the optimal band in VIs design. The proposed VIs are then evaluated in multiple ways, including with PROSAIL simulated datasets, ground measured LAI with canopy spectra, and real satellite images. The evaluation results based on field LAI measurements indicate that the proposed red-edge VIs can effectively improve crop LAI estimation accuracy with the best regression coefficient (R2 = 0.81 for Sentinel-2 and R2 = 0.65 for GF-6) among all comparative VIs. Our work showcases incorporating red-edge bands with suitable formula is promising for improving VI-based LAI retrieval, and they offer a practicable solution to fast achieve decameter LAI maps by using the Sentinel-2 or GF-6 images.
Vertical Parameters Estimation of Forest with Compact Polarimetric SAR Interferometry Data

Vertical parameters estimation of forest is one of the most important applications in the Polarimetric Interferometric SAR(Pol In SAR). On the basis of the Radom Volume over Ground(RVo G) model, the topographical phase and the tree height in forest area can be successfully estimated with the Pol In SAR data. In this paper, the topographical phase and forest heights are obtained with single-baseline Compact Polarimetric Interferometric SAR(C-Pol In SAR) data. This paper introduces the complex coherence coefficients and the coherence region of the single-baseline C-Pol In SAR. Firstly, line-fitting technique is performed on the basis of the coherence region, then the criterion for estimating the topography, and the only volume de-correlation are proposed with the compact polarimetric SAR interferometry datasets. Finally, the topography and the forest heights are proposed. The simulated L, and P band data is used to validate the proposed method, and the topography and tree heights are obtained successfully. Since the transmit wave polarization state of the compact polarimetric system is not unique, this paper analyzes the influence of the elliptic-polarization with different elliptical parameters on the topographical phase and the forest heights. Results show that elliptic-polarization has a little impact on vertical parameters, which also validates the stability of the estimation method.
The Novel Compound SUL-138 Counteracts Endothelial Cell and Kidney Dysfunction in Sepsis by Preserving Mitochondrial Function

Sepsis is defined as a dysregulated host response leading to organ dysfunction, which may ultimately result in the patient’s death. Mitochondrial dysfunction plays a key role in developing organ dysfunction in sepsis. In this study, we explored the efficacy of the novel mitochondrial protective compound, SUL-138, in sepsis models in HUVECs and mice. In LPS-challenged HUVECs, SUL-138 preserved mitochondrial membrane potential and oxygen consumption and limited mitochondrial oxidative stress, resulting in increased survival at 48 h. Further, SUL-138 dampened the LPS-induced expression of IL-1β, but not of NLRP3, and IL-18 in HUVECs. Sepsis in mice induced by cecal ligation and puncture (CLP) led to a lower mitochondrial membrane potential and increased levels of mitochondrial oxidative stress in the kidney, which SUL-138 limited. In addition, SUL-138 mitigated the CLP-induced increase in kidney dysfunction markers NGAL and urea. It dampened the rise in kidney expression of IL-6, IL-1β, and ICAM-1, but not TNF-α and E-selectin. Yet, SUL-138 limited the increase in plasma levels of IL-6 and TNF-α of CLP mice. These results demonstrate that SUL-138 supports mitochondrial function, resulting in a limitation of systemic inflammation and preservation of kidney function.
Numerical simulation under-expanded supersonic impinging jet

Supersonic impinging jet was predicted by axisymmetric compressible Navier Stokes equations. A finite volume method with unstructured meshes and S A turbulence model were employed in the calculation. The computation was processed for under expanded supersonic impinging jet under pressure ratio 3 and 4 separately. The wave patterns were shown. The numerical results are in good agreement with experimental data. For higher pressure ratio, the pressure of the impinging region on the plate is lower and keep the same nearly along the radius direction. The position of the maxim pressure shifts from the impinging point. The reverse secondary flow occurs near the solid boundary.
Influence of Stress Jump Condition at the Interface Region of a Two-Layer Nanofluid Flow in a Microchannel with EDL Effects

The influence of stress jump conditions on a steady, fully developed two-layer magnetohydrodynamic electro-osmotic nanofluid in the microchannel, is investigated numerically. A nanofluid is partially filled into the microchannel, while a porous medium, saturated with nanofluid, is immersed into the other half of the microchannel. The Brinkmann-extended Darcy equation is used to effectively explain the nanofluid flow in the porous region. In both regions, electric double layers are examined, whereas at the interface, Ochoa-Tapia and Whitaker’s stress jump condition is considered. The non-dimensional velocity, temperature, and volume fraction of the nanoparticle profiles are examined, by varying physical parameters. Additionally, the Darcy number, as well as the coefficient in the stress jump condition, are investigated for their profound effect on skin friction and Nusselt number. It is concluded that, taking into account the change in shear stress at the interface has a significant impact on fluid flow problems.
A fuzzy rule changing algorithm for an adaptive fuzzy controller

In this paper we describe a novel fuzzy adaptation method to construct or change the rules in the fuzzy controller rule base table. The objective of the fuzzy logic adaptation mechanism (FLAM) is to change the rules definition in the FLC rule base table, according to the comparison between a reference model output signal and the system output. So, the learning algorithm constructs the rule base table based on a desired trajectory. We show the efficiency of this method in a TMS320C30 DSP-based speed fuzzy control of a permanent magnet synchronous motor (PMSM). The fuzzy logic adaptive strategy can be readily implemented. It has very fast learning features and very good tracking characteristics even under severe variations of the system parameters. At each sample instant the FLAM will affect only the active rules.
Large eddy simulation of flow field and particle dispersion in a ventilated model room using a parallel lattice Boltzmann method

Abstract The present paper addresses the use of a parallel lattice Boltzmann solver for large eddy simulation of particulate matter flow in a single ventilated model room. The formulation of lattice Boltzmann method (LBM), implementation of large eddy simulation (LES), description of finite volume method (FVM) and then integration of Lagrangian particle tracking in the present algorithm are outlined. A parallel processing method, known as decomposed domain method, for flow and particle phases is defined. Combined stream and collision step technique is employed to reduce CPU runtime and memory usage. The ultimate objective is validation and comparison of prediction accuracy and speed up between present LBM-LES results, FVM-LES results based on Navier–Stokes equations, and available experimental data. Results of flow field show acceptable accuracy for the present LBM-LES method when using high-resolution lattices. It is revealed that in order to achieve an accuracy almost equal to FVM, LBM requires twice the number of lattices but still provides a higher speed. Also, it is shown that the present model is well capable of predicting vortex core and vortex lines and it can capture the features and structure of the turbulence flow field reasonably well. In the particle field, it can capture concentration patterns and particle dispersion with an admissible discrepancy. The use of presently developed algorithm dramatically reduces computational time, such that speed can increase by up to four times in flow and eight times in particle simulations. Copyright © 2023 American Association for Aerosol Research Graphical Abstract
CONVECTIVE COOLING OF TANDEM HEATED TRIANGULAR CYLINDERS PLACED IN A CHANNEL

Numerical simulations of forced convective incompressible flow in a horizontal plane channel with adiabatic walls over two isothermal tandem triangular cylinders of equal size are presented to investigate the effect of wall proximity of obstacles, gap space (i. e. gap between two squares), and Reynolds number. Computations have been carried out for Reynolds numbers of (based on triangle width) 100, 250, and 350 . Results show that, wall proximity has different effect on first and second triangle in fluid characteristics especially in lower gap spaced, while for heat transfer a fairly same behavior was seen.