Miracle-dz/UniFAR-FTUs huggingface dataset:
Elucidating the role of key physio-biochemical traits and molecular network conferring heat stress tolerance in cucumber

Cucumber is an important vegetable crop grown worldwide and highly sensitive to prevailing temperature condition. The physiological, biochemical and molecular basis of high temperature stress tolerance is poorly understood in this model vegetable crop. In the present study, a set of genotypes with contrasting response under two different temperature stress (35/30°C and 40/35°C) were evaluated for important physiological and biochemical traits. Besides, expression of the important heat shock proteins (HSPs), aquaporins (AQPs), photosynthesis related genes was conducted in two selected contrasting genotypes at different stress conditions. It was established that tolerant genotypes were able to maintain high chlorophyll retention, stable membrane stability index, higher retention of water content, stability in net photosynthesis, high stomatal conductance and transpiration in combination with less canopy temperatures under high temperature stress conditions compared to susceptible genotypes and were considered as the key physiological traits associated with heat tolerance in cucumber. Accumulation of biochemicals like proline, protein and antioxidants like SOD, catalase and peroxidase was the underlying biochemical mechanisms for high temperature tolerance. Upregulation of photosynthesis related genes, signal transduction genes and heat responsive genes (HSPs) in tolerant genotypes indicate the molecular network associated with heat tolerance in cucumber. Among the HSPs, higher accumulation of HSP70 and HSP90 were recorded in the tolerant genotype, WBC-13 under heat stress condition indicating their critical role. Besides, Rubisco S, Rubisco L and CsTIP1b were upregulated in the tolerant genotypes under heat stress condition. Therefore, the HSPs in combination with photosynthetic and aquaporin genes were the underlying important molecular network associated with heat stress tolerance in cucumber. The findings of the present study also indicated negative feedback of G-protein alpha unit and oxygen evolving complex in relation to heat stress tolerance in cucumber. These results indicate that the thermotolerant cucumber genotypes enhanced physio-biochemical and molecular adaptation under high-temperature stress condition. This study provides foundation to design climate smart genotypes in cucumber through integration of favorable physio-biochemical traits and understanding the detailed molecular network associated with heat stress tolerance in cucumber.
Rapid Screening of Methamphetamine in Hair by Ambient Ionization Mass Spectrometry (AIMS)

Abstract Ambient ionization mass spectrometry (AIMS) is an emerging onsite rapid detection technique that has been applied in the area of public security. AIMS measurements of samples with complex matrices are characterized by poor reproducibility and complexity. Low reproducibility and complex background cause imprecise screening for trace drugs in hair. In this work, a rapid screening method of methamphetamine in hair is proposed. Firstly, the generalized weighted robust principal component analysis (GWRPCA) algorithm is used to remove background and extract the analytical signals. The similarity scores between the analytical signals and standard mass spectrum of methamphetamine were calculated based upon an improved Pearson’s correlation coefficient combined with the preset matching threshold to achieve rapid screening of methamphetamine in hair. The results show that this method accurately screens for this drug hair and identifies actual false positives with 100% accuracy when the analyte threshold was 0.1 ng/mg and the matching threshold was 0.6. This study provides technical support for the rapid screening for drug abuse by AIMS.
The Northern Eurasia Earth Science Partnership: An Example of Science Applied to Societal Needs

Abstract Northern Eurasia, the largest land-mass in the northern extratropics, accounts for ∼20% of the global land area. However, little is known about how the biogeochemical cycles, energy and water cycles, and human activities specific to this carbon-rich, cold region interact with global climate. A major concern is that changes in the distribution of land-based life, as well as its interactions with the environment, may lead to a self-reinforcing cycle of accelerated regional and global warming. With this as its motivation, the Northern Eurasian Earth Science Partnership Initiative (NEESPI) was formed in 2004 to better understand and quantify feedbacks between northern Eurasian and global climates. The first group of NEESPI projects has mostly focused on assembling regional databases, organizing improved environmental monitoring of the region, and studying individual environmental processes. That was a starting point to addressing emerging challenges in the region related to rapidly and simultaneously.
Mechanisms of Physical Exercise Effects on Anxiety in Older Adults during the COVID-19 Lockdown: An Analysis of the Mediating Role of Psychological Resilience and the Moderating Role of Media Exposure

The purpose of this study was to explore the effects of physical exercise on anxiety in older adults during the COVID-19 pandemic lockdown, as well as the mediating role of psychological resilience and the moderating role of media exposure. An online questionnaire was used to survey older adults in Chengdu, Southwest China. A total of 451 older adults aged 60 years and older participated in the study (209 males and 242 females). The results suggest that physical exercise negatively influenced anxiety symptoms in older adults; psychological resilience mediated the effect of physical exercise on anxiety in older adults and negatively predicted it; furthermore, media exposure moderated the effects of physical exercise and psychological resilience on anxiety, and low levels of media exposure strengthened these effects. This study suggests that participation in physical exercise and reduced media exposure during the COVID-19 pandemic lockdown may have reduced anxiety in older adults.
Adaptive beamforming using Van Cittert-Zernicke criterion

This paper proposes a phase aberration correction technique, which copes with the issue related to the classical correlation method, which widens images of punctual coherent scatters. This artifact is due to the fact that the correlation maximization process realigns strong echoes coming from these targets even when the beam formed line is adjacent to the target. Our approach chooses to apply this correlation in selected areas, where there is only speckle. To identify these regions, we use a criterion derived from the Van Cittert-Zernicke (VCZ) theorem, which distinguishes between coherent and diffuse scattering. The result of the delay estimation in areas corresponding to punctual targets is then deduces from delays estimated within speckle regions using interpolation. Results of the proposed method, applied on string phantoms as well as on excised breast tissue samples containing microcalcifications, show improvement in contrast and lateral resolution of punctual scatterers.
Analysis of Prospective Wind Energy Sites in Bangladesh Utilizing Weibull Distribution Method

The major objective of this study is to employ the Weibull distribution function to determine the chance of utilizing wind energy in several locations in Bangladesh and to propose a wind turbine model with appropriate specifications. It has been used in this work to assess the wind speed data from NASA meteorological site. Calculations have been made using the Moments of Method (MOM), the Empirical Method (EM), and the Power Density Method (PDM), to determine the Weibull Factors of the provided data with the goal of evaluating the wind energy potential. This paper shows the comparison among the three approaches to k/c ratios. The MOM technique was determined to be the most efficient way for estimating Weibull parameters out of the three investigated methods. Finally, a horizontal axis wind turbine model specification has been suggested based on the available data analysis.
Stratification of three-dimensional vision: projective, affine, and metric representations

A conceptual framework is provided in which to think of the relationships between the three-dimensional structure of physical space and the geometric properties of a set of cameras that provide pictures from which measurements can be made. We usually think of physical space as being embedded in a three-dimensional Euclidean space, in which measurements of lengths and angles do make sense. It turns out that for artificial systems, such as robots, this is not a mandatory viewpoint and that it is sometimes sufficient to think of physical space as being embedded in an affine or even a projective space. The question then arises of how to relate these models to image measurements and to geometric properties of sets of cameras. It is shown that, in the case of two cameras, a stereo rig, the projective structure of the world can be recovered as soon as the epipolar geometry of the stereo rig is known and that this geometry is summarized by a single 3 × 3 matrix, which is called the fundamental matrix. The affine structure can then be recovered if to this information is added a projective transformation between the two images that is induced by the plane at infinity. Finally, the Euclidean structure (up to a similitude) can be recovered if to these two elements is added the knowledge of two conics (one for each camera) that are the images of the absolute conic, a circle of radius -1 in the plane at infinity. In all three cases it is shown how the three-dimensional information can be recovered directly from the images without explicit reconstruction of the scene structure. This defines a natural hierarchy of geometric structures, a set of three strata that is overlaid upon the physical world and that is shown to be recoverable by simple procedures that rely on two items, the physical space itself together with possibly, but not necessarily, some a priori information about it, and some voluntary motions of the set of cameras.
Fluid–structure interaction modeling of parachute clusters

We address some of the computational challenges involved in fluid–structure interaction (FSI) modeling of clusters of ringsail parachutes. The geometric complexity created by the construction of the parachute from ‘rings’ and ‘sails’ with hundreds of gaps and slits makes this class of FSI modeling inherently challenging. There is still much room for advancing the computational technology for FSI modeling of a single raingsail parachute, such as improving the Homogenized Modeling of Geometric Porosity (HMGP) and developing special techniques for computing the reefed stages of the parachute and its disreefing. While we continue working on that, we are also developing special techniques targeting cluster modeling, so that the computational technology goes beyond the single parachute and the challenges specific to parachute clusters are addressed. The rotational‐periodicity technique we describe here is one of such special techniques, and we use that for computing good starting conditions for FSI modeling of parachute clusters. In addition to reporting our preliminary FSI computations for parachute clusters, we present results from those starting‐condition computations. In the category of more fundamental computational technologies, we discuss how we are improving the HMGP by increasing the resolution of the fluid mechanics mesh used in the HMGP computation and also by increasing the number of gores used. Also in that category, we describe how we use the multiscale sequentially coupled FSI techniques to improve the accuracy in computing the structural stresses in parts of the structure where we want to report more accurate values. All these special techniques are used in conjunction with the Stabilized Space–Time Fluid–Structure Interaction (SSTFSI) technique. Therefore, we also present in this paper a brief stability and accuracy analysis for the Deforming‐Spatial‐Domain/Stabilized Space–Time (DSD/SST) formulation, which is the core numerical technology of the SSTFSI technique. Copyright © 2010 John Wiley & Sons, Ltd.
Learning Optimal Topology for Ad-Hoc Robot Networks

In this letter, we synthesize a data-driven method to predict the optimal topology of an ad-hoc robot network. This problem is technically a multi-task classification problem. However, we divide it into a class of multi-class classification problems that can be more efficiently solved. For this purpose, we first compose an algorithm to create ground-truth optimal topologies associated with various configurations of a robot network. This algorithm incorporates a complex collection of optimality criteria that our learning model successfully manages to learn. This model is an stacked ensemble whose output is the topology prediction for a particular robot. Each stacked ensemble instance constitutes three low-level estimators whose outputs will be aggregated by a high-level boosting blender. Applying our model to a network of 10 robots displays over 80% accuracy in the prediction of optimal topologies corresponding to various configurations of the cited network.
BackProx: Secure Backscatter-Assisted Proximity Detection for Passive Keyless Entry and Start Systems

A passive keyless entry and start (PKES) system is an electronic lock for an automobile that provides the great convenience of opening the door when the user is in proximity. However, the system suffers from relay attacks. Recent studies revealed that relayed signals result in valid packets that are sufficient to unlock doors. In particular, the adversary causes proximity errors by injecting a certain time delay before relaying to manipulate the phase rotation in the response signal. To this end, we present a novel relay-resilient proximity detection solution, BackProx, which uses pseudo-random frequency hopping with the assistance of a reference backscattering device. Since the relay adversary transmits the relayed signals from the key fob at long distances, the signals should propagate over longer distances, resulting in inevitable significant phase rotation with different frequencies. Inspired by this finding, BackProx uses an additional backscattering device to ensure the proximity of the key fob using the invariant characteristics of radio frequency signals in the physical layer (i.e., phase rotation). Our evaluation demonstrates the effectiveness of BackProx in resisting three types of relay attacks. The results show that it achieved a 98% true positive rate at close range and a 0.3% false positive rate at long range.
Developmental Autonomous Behavior: An Ethological Perspective to Understanding Machines

Developmental autonomous behavior refers to the general ability of a machine to acquire new skills and behavior from its birth to maturity on its own without human intervention. This article describes the principles of behavior development in machines, providing a practical framework to analyze and synthesize machines with developmental capabilities. Inspired by biological views of behavioral causation, the work emphasizes principled explanations to, not only the “how” question on mechanisms but also the “why” question on causation of behavior development. This ethology-oriented perspective offers a renewed opportunity to construct a theoretical framework from the ground up, overcoming the age-old problems of intrinsic motivation and symbol emergence in autonomous machines. One of the key contributions of this article is the logical explanation of why and how value systems drive successive development of memory functions, resulting in progressive changes in behavior from innate reflexive to episodic, procedural, and autonomic behavior. Another notable contribution is the logical and plausible explanation of why and how a physical sensorimotor system becomes a symbol processor, fostering conceptual and social behavior development. This article provides an extensive review of prior research, followed by detailed descriptions of the causality and mechanisms of behavior development, and concludes with discussions on criticism, future work, ethics, and system architecture.
Three‐dimensional Stokes flow caused by a translating–rotating sphere bisected by a free surface bounding a semi‐infinite micropolar fluid

Explicit velocity and microrotation components and systematic calculation of hydrodynamic quasistatic drag and couple in terms of nondimensional coefficients are presented for the flow problem of an incompressible asymmetrical steady semi‐infinite micropolar fluid arising from the motion of a sphere bisected by a free surface bounding a semi‐infinite micropolar fluid. Two asymmetrical cases are considered for the motion of the sphere: parallel translation to the free surface and rotation about a diameter which is lying in the free surface. The speed of the translational motion and the angular speed for the rotational motion of the sphere are assumed to be small so that the nonlinear terms in the equations of motion can be neglected under the usual Stokesian approximation. A linear slip, Basset‐type, boundary condition has been used. The variation of the resistance coefficients is studied numerically and plotted versus the micropolarity parameter and slip parameter. The two limiting cases of no‐slip and perfect slip are then recovered. Copyright © 2008 John Wiley & Sons, Ltd.
State-space approach to discrete-time H/sub 2/-optimal control with a causality constraint

Controller design with a causality constraint arises in periodic or multirate control systems. In this paper complete state-space solutions to the optimal and suboptimal H/sub 2/ control problems are developed with a causality constraint on controller feedthrough terms. Explicit formulas for the controllers are given in terms of solutions of two Riccati equations. The results are more implementable than existing frequency-domain solutions.
PASS: A System-Driven Evaluation Platform for Autonomous Driving Safety and Security

—Safety and security play critical roles for the success of Autonomous Driving (AD) systems. Since AD systems heavily rely on AI components, the safety and security research of such components has also received great attention in recent years. While it is widely recognized that AI component-level (mis)behavior does not necessarily lead to AD system-level impacts, most of existing work still only adopts component-level evaluation. To fill such critical scientific methodology-level gap from component-level to real system-level impact, a system-driven evaluation platform jointly constructed by the community could be the solution. In this paper, we present PASS (Platform for Auto-driving Safety and Security), a system-driven evaluation prototype based on simulation. By sharing our platform building concept and preliminary efforts, we hope to call on the community to build a uniform and extensible platform to make AI safety and security work sufficiently meaningful at the system level.
Active power-based event detection algorithm for real-time load monitoring systems

Non-intrusive load monitoring (NILM) has recently become a promising and trending topic in energy management. Although several NILM-based solutions were proposed, a commercial-grade universal solution is yet to be developed due to inherent limitations in the event detection and appliance identification algorithms. This work proposes a novel real-time event detection algorithm specifically designed to be effective in NILM-based solutions developed for residential loads. Real-world experimental results indicate that the proposed algorithm can detect a change in the operating state of a device with a 98 percent accuracy within 1.35 milliseconds, on average.
SUBGROUP DISTORTIONS IN NILPOTENT GROUPS

The explicit formula for the distortion function of a connected Lie subgroup in a connected simply connected nilpotent Lie group is obtained. In particular, we prove that a function f: N → R can be realized (up to equivalence) as the distortion function of a connected Lie subgroup in a connected simply connected nilpotent Lie group if and only if f ∼ nr for some nonnegative r ∈ Q. Considering lattices in Lie groups, we establish the analogous results for finitely generated nilpotent groups.
Clinical Utility of Genomic Tests Evaluating Homologous Recombination Repair Deficiency (HRD) for Treatment Decisions in Early and Metastatic Breast Cancer

Simple Summary Breast cancer is the most frequently occurring cancer worldwide. With the help of next-generation sequencing, the development of biomedical technologies and the use of bioinformatics, it is now possible to identify specific molecular alterations in tumor cells, such as homologous recombination deficiencies, enabling us to consider using DNA-damaging agents such as platinum salts or PARP inhibitors. In this review, we summarize current knowledge on the clinical utility of genomic tests evaluating homologous recombination repair deficiency for treatment decisions in early and metastatic breast cancer. Abstract Breast cancer is the most frequently occurring cancer worldwide. With its increasing incidence, it is a major public health problem, with many therapeutic challenges such as precision medicine for personalized treatment. Thanks to next-generation sequencing (NGS), progress in biomedical technologies, and the use of bioinformatics, it is now possible to identify specific molecular alterations in tumor cells—such as homologous recombination deficiencies (HRD)—enabling us to consider using DNA-damaging agents such as platinum salts or PARP inhibitors. Different approaches currently exist to analyze impairment of the homologous recombination pathway, e.g., the search for specific mutations in homologous recombination repair (HRR) genes, such as BRCA1/2; the use of genomic scars or mutational signatures; or the development of functional tests. Nevertheless, the role and value of these different tests in breast cancer treatment decisions remains to be clarified. In this review, we summarize current knowledge on the clinical utility of genomic tests, evaluating HRR deficiency for treatment decisions in early and metastatic breast cancer.
High mass Class I sources in M 17

The region of M 17 has been imaged at 10.5 and 20.0 μ m with the groundbased infrared camera MANIAC. In addition to a prominent diffuse emission bar (4$\farcm$5$\times$0$\farcm$ 3) extending southeast to northwest at the interface between the Hii region and the southwestern molecular cloud, the mosaic of 133 single frames at each wavelength revealed 22 compact sources. One of these sources is the Kleinmann-Wright-Object and another was previously identified as the ultra-compact Hii region M 17-UC1. Combining the N -band and Q -band data with near infrared data yielded spectral energy distributions that classifies all sources to be of Class I. The observed luminosities were between 55 and 4775 $L_\odot$, which suggests that these sources represent the youngest generation of massive early type stars in M 17 and are surrounded by relics of their protostellar clouds. The morphology of the 10.5 and 20.0 μ m emission towards some of the sources reveals flattened structures and may be the first evidence of the presence of circumstellar disks around massive stars.
Characterization of classical type orthogonal polynomials

We characterize the classical type orthogonal polynomials {P n (x)} 0 ∞ satisfying a fourth-order differential equation of type ∑ i=0 4 l i (x)y (i) (x) = λ n y(x) where l i (x) are polynomials of degree ≤ i and λ n is a constant. They are only the orthogonal polynomials satisfying an orthogonality of the form + + = 0 for m ¬= n where τ 0 , τ 1 , and τ 2 are moment functionals