Miracle-dz/UniFAR-FTUs huggingface dataset:
Methods in Ecology and Evolution Accuracy of image analysis tools for functional root traits: A comment on Delory et al., 2017

Tweetable Abstract: Root analyses tools WinRhizo TM and IJ_Rhizo estimate traits with comparable accuracy at high but not low resolution Abstract : Root traits get increasing attention as functional equivalents of aboveground traits. Image analysis software such as WinRhizo TM and IJ_Rhizo facilitate root trait analyses. Delory et al., 2017 presented a comparison between the accuracy of WinRhizo TM and IJ_Rhizo for measuring root length. We complement their analyses with a comparison of diameter and volume estimates and a comparison of different image resolutions with manual and automatic threshold. We analysed 100 images of fibrous and tap-root systems, which were obtained by using the root model ArchiSimple. a result, for each image, diameter, length and volume were known. The images were analysed with WinRhizo and IJ_Rhizo and we compared the estimates of diameter, length, and volume to ground-truth values. We further computed relative errors and their magnitude and analysed their dependency on image characteristics and root system properties. root length, overlap and root length density TM The magnitude of of the volume (WinRhizo TM ) with volume. It was higher for tap-root than for fibrous root systems. All errors increased with lower resolution. Our results confirm the results of Delory et al., 2017 regarding the accuracy for length. They further confirm that estimates derived from different software packages or at different resolution should not be compared directly. The characteristics of root systems should be standardized for image analysis. The dependency of errors on the response variable of interest can influence the effect size and increase the probability of errors. Validation of methods should be conducted for each analysed dataset. New image analysis tools should be validated against a real ground-truth. Auflösungen gemacht wurden, nicht direkt vergleichbar sind. Die Eigenschaften von Bildern sollten möglichst weitgehend standardisiert werden. Die Abhängigkeit der Fehler von der Antwortvariable kann sowohl die Effektgröße als auch die Fehlerwahrscheinlichkeit beeinflussen. Dementsprechend sollte jede Validierung der Methoden datensatzspezifisch erfolgen. Neue Analysemethoden sollten anhand direkter Referenzwerte, nicht nur anderer Programme, getestet werden.
Algorithmic Graph Theory

Preface 1. Introducing graphs and algorithmic complexity 2. Spanning-trees, branchings and connectivity 3. Planar graphs 4. Networks and flows 5. Matchings 6. Eulerian and Hamiltonian tours 7. Colouring graphs 8. Graph problems and intractability Appendix Author Index Subject Index.
Effects of the solar wind conditions on the global magnetospheric configuration as deduced from data-based field models

The results of data based modeling of the magnetospheric configuration and its response to changes in the solar wind dynamical pressure and the interplanetary magnetic field (IMF) are described. Previous models did not have a pre-defined magnetopause and were calibrated by the Kp index, and therefore did not correctly model the solar wind effects. Models are presented which include the effects of the solar wind-controlled magnetopause, the region 1 and 2 Birkeland currents, and the interconnection of the magnetospheric and solar wind fields at the boundary. They predict the most significant effects of solar wind variation on the global magnetospheric structure. On the dayside, the region 1 Birkeland currents cause major changes of the magnetic configuration as the IMF turns southward. The tail current intensity is controlled mainly by the pressure of the solar wind, although the influence of the southward IMF is clearly seen. The effects of the IMF-induced interconnection field were found to be significant.
Natural Variation Can Signiﬁcantly Alter the Sensitivity of Inﬂuenza A (H5N1) Viruses to Oseltamivir (cid:1)

Geographic spread of highly pathogenic avian H5N1 inﬂuenza viruses may give rise to an inﬂuenza pandemic. During the ﬁrst months of a pandemic, control measures would rely mainly on antiviral drugs, such as the neuraminidase (NA) inhibitors oseltamivir and zanamivir. In this study, we compare the sensitivities to oseltamivir of the NAs of several highly pathogenic H5N1 viruses isolated in Asia from 1997 to 2005. The corresponding 50% inhibitory concentrations were determined using a standard in vitro NA inhibition assay. The K m for the substrate and the afﬁnity for the inhibitor ( K i ) of NA were determined for a 1997 and a 2005 virus, using an NA inhibition assay on cells transiently expressing the viral enzyme. Our data show that the sensitivities of the NAs of H5N1 viruses isolated in 2004 and 2005 to oseltamivir are about 10-fold higher than those of earlier H5N1 viruses or currently circulating H1N1 viruses. Three-dimensional modeling of the N1 protein predicted that Glu248Gly and Tyr252His changes could account for increased sensitivity. Our data indicate that genetic variation in the absence of any drug-selective pressure may result in signiﬁcant variations in sensitivity to anti-NA drugs. Although the clinical relevance of a 10-fold increase in the sensitivity of NA to oseltamivir needs to be investigated further, the possibility that sensitivity to anti-NA drugs could increase (or possibly decrease) signiﬁcantly, even in the absence of treatment, underscores the need for continuous evaluation of the impact of genetic drift on this parameter, especially for inﬂuenza viruses with pandemic potential.
Hamiltonian Formulation of Mimetic Gravity

The Hamiltonian formulation of Mimetic Gravity is formulated. Although there are two more equations than those of general relativity, these are proved to be the constraint equation and the conservation of energy-momentum tensor. The Poisson brackets are then computed and closure is proved. At the end, Wheeler-DeWitt equation was solved for a homogeneous and isotropic universe. This was done first for a vanishing potential where agreement with the dust case was shown, and then for a constant potential.
Rejective subcategories of artin algebras and orders

We will study the resolution dimension of functorially finite subcategories. The subcategories with the resolution dimension zero correspond to ring epimorphisms, and rejective subcategories correspond to surjective ring morphisms. We will study a chain of rejective subcategories to construct modules with endomorphisms rings of finite global dimension. We apply these result to study a function $r_\Lambda:\mod\Lambda\to\nnn_{\ge0}$ which is a natural extension of Auslander's representation dimension.
Quantum Chromodynamics: High Energy Experiments and Theory

1. Introduction 2. The development of QCD 3. The theory of QCD 4. Monte Carlo models 5. Experimental setup 6. QCD analyses 7. Structure functions and Parton distributions 8. The strong coupling constant 9. Tests of the structure of QCD 10. Tests of the gauge structure of QCD: Colour factors 11. Leading-log QCD 12. Differences Between Quark and Gluon Jets 13. Fragmentation 14. Summary A. Elements of group theory B. Building blocks of theoretical predictions C. Dimensional Regularization D. R(ital) gamma(ital lowercase subset), R(ital)iota(lowercase ital subset) and R(ital)tau(ital lowercase subset) for arbitrary colour factors E. Scaling Violations in fragmentation functions F. Solutions References
Observed and Modeled Tritium Concentrations in the Terrestrial Food Chain near a Continuous Atmospheric Source

Tritium concentrations were measured in a large number of environmental and biological samples collected during 2002 at two dairy farms and a hobby farm near Pickering Nuclear Generating Station in Ontario, Canada. The data cover most compartments of the terrestrial food chain in an agricultural setting and include detailed information on the diets of the local farm animals. Ratios of plant OBT concentration to air moisture HTO varied between 0.12 and 0.56, and were generally higher for the forage crops collected at the dairy farms than for the garden vegetables sampled at the hobby farm. Animal OBT to air HTO ratios were more uniform, ranging from 0.18 to 0.45, and were generally higher for the milk and beef samples from the dairy farms than for the chicken products from the hobby farm. The observed OBT concentrations in plants and animals were compared with predictions of IMPACT, the model used by the Canadian nuclear industry to calculate annual average doses due to routine releases. The model performed well on average for the animal endpoints but overestimated concentrations in plants by a factor of 2.
INDEPENDENT SETS IN HYPERGRAPHS AND RAMSEY OF GRAPHS

Many important problems in combinatorics and other related areas can be phrased in the language of independent sets in hypergraphs. Recently Balogh, Morris, and Samotij [ J. Amer. Math. Soc. , 28 (2015), pp. 669--709], and independently Saxton and Thomason [ Invent. Math. , 201 (2015), pp. 925--992], developed very general container theorems for independent sets in hypergraphs, both of which have seen numerous applications to a wide range of problems. In this paper we use the container method to give relatively short and elementary proofs of a number of results concerning Ramsey (and Tur\'an) properties of (hyper)graphs and the integers. In particular we do the following: (a) We generalize the random Ramsey theorem of R\"odl and Ruci\'nski [ Combinatorics, Paul Erd\H os Is Eighty , Vol. 1, Bolyai Soc. Math. Stud. , J\'anos Bolyai Mathematical Society, Budapest, 1993, pp. 317--346; Random Structures Algorithms , 5 (1994), pp. 253--270; J. Amer. Math. Soc. , 8 (1995), pp. 917--942] by providing a resilience analogue. Our result unifies and generalizes several fundamental results in the area including the random version of Tur\'an's theorem due to Conlon and Gowers [ Ann. of Math. , 184 (2016), pp. 367--454] and Schacht [ Ann. of Math. , 184 (2016), pp. 331--363]. (b) The above result also resolves a general subcase of the asymmetric random Ramsey conjecture of Kohayakawa and Kreuter [ Random Structures Algorithms , 11 (1997), pp. 245--276].
in Research Androgen Metabolism and Prostate Cancer: Establishing a Model of Genetic Susceptibility1

The prostate Â¡san androgen-regulated organ, which has led to long standing interest in the role of androgens in prostate carcinogenesis. Although evidence of a hormonal etiology for prostate cancer is strong, it is almost entirely circumstantial. Much of the problem in proving a causal relationship relates to the continued difficulties in reliably measuring human tissue-specific exposure to endogenous steroid hormones. The international and racial-ethnic variations in prostate cancer inci dence, combined with the effects of migration on risk patterns, have suggested that whereas environmental factors are likely to be important, genetic factors might also play a central role in determining prostate cancer risk. We are developing a polygenic model of prostate carcinogen esis focused around a series of genes involved in androgen biosynthesis and androgen activation, transport, and metabolism in the prostate. In this developing model, we have initially targeted four genes based on three main criteria: (a) all encode products that play important roles in induc ing androgen stimulation in the prostate; (In all are polymorphic; and (c) all show substantial allelic variation in the polymorphic marker among the racial-ethnic groups of greatest interest in terms of prostate cancer risk. In addition to studying how the polymorphic markers of interest are related to prostate cancer development within and between racial-ethnic groups, we are concurrently evaluating whether genotypic variations correlate in the anticipated direction with biochemical parameters in vitro and I'Mvivo. We summarize the development of this model and the state of knowl edge related to each of the genes comprising the current model. We discuss the extent to which the current model can explain demographic variation in prostate cancer risk as well as the potential for future expansion of the model to incorporate environmental risk factors as well as additional genes. The model, when fully developed, can potentially provide a basis for targeting populations for screening interventions and/or preventive strat egies aimed at the multigene products or at the genes themselves.
An Implementation of Exercise and Performance Learning Assistant System Platform Using Node.js

To assist practicing exercises or learning performances by themselves at home under pandemic of COVID-19, we have studied the Exercise and Performance Learning Assistant System (EPLAS) and implemented the user interface using a web browser for practicing Yoga poses. EPLAS offers a video content of model actions by an instructor to be followed by the user, and automatically takes the photos of the critical poses. Then, it rates each critical pose by differences of body key points extracted by OpenPose between the user photo and the instructor one. In this paper, we implement the EPLAS platform using Node.js as the web application server to run the rating function automatically on the server when it is requested on the browser. For evaluations, we asked 10 students in Okayama University to practice 10 Yoga poses using the interface, and confirmed its correctness.
Cellular Manipulation Using Rolling Microrobots

Many biomedical applications, such as targeted drug delivery or cell manipulation, are well suited for the deployment of microrobots, untethered devices that are capable of carrying out tasks at the microscale. One biocompatible means of driving microrobots relies on magnetic actuation. In particular, micro-robots driven using rotating fields rather than magnetic field gradients are especially practical for real-word applications. Many biological applications involve enclosed environments, such as blood vessels, in which surfaces are abundant, therefore, surface rolling is a particularly pertinent method of transportation. In this paper we demonstrate manipulation and transportation of cells using two types of magnetically driven rolling microrobots. We find that the microrobots are able to manipulate the cells by physically pushing or by first adhering to the cells and then carrying them. Microrobots spinning at high rates also can transport cells via the induced fluid flows.
An Ultra-sparse View CT Imaging Method Based on X-ray2CTNet

The prediction of the internal ballistic performance of solid rocket motors (SRMs) mainly depends on the observation of burning surface regression. The existing techniques have not yet achieved real-time, accurate and intuitive observations of the grain structural dynamic changes under hot conditions. Computed tomography (CT) imaging based on X-ray can be directly used to analyze the burning surface of SRM. However, neither the conventional CT imaging mode nor the current reconstruction algorithms, including full-view and sparse-view reconstruction methods, can be used in ignition tests. It is necessary to break through the limitation of sparse sampling and research ultra-sparse view reconstruction. Although computer vision technology has shown that 3D shapes can be estimated from very few 2D RGB images via deep learning, it remains challenging to reconstruct volumes from two 2D X-ray images. To tackle this issue here, we propose a 3D reconstruction network based on ultra-sparse projection views, namely X-ray2CTNet, which takes the 2D projections of any two orthogonal views as inputs to implement cross-dimensional inverse mapping from 2D (X-rays) to 3D (CT). In addition, to solve the insufficient dataset problem, training sets are constructed by simulating different models of grain regression for a certain type of propellant and utilizing a CT simulation platform. We pour fake grains that are the same as those of the simulation models to acquire the actual projections of two views for reconstructing the 3D volume. The obtained results prove the feasibility of our method. The proposed method provides a possibility for dynamic monitoring of burning surface regressions for SRMs in ground ignition tests.
The Effect of integrating Peer Tutoring Strategy in Programming Learning

Programming ability is a fundamental skill for engineers. The purpose of this study was to integrate the peer tutoring strategy in Scratch programming learning for students. This study designed six learning modules including three procedure-oriented structures, procedure definition and call, game design, and debug. A quasi experiment design was adopted for conducting a learning experiment in a junior high school in Taipei city. The learning experiment lasted for one and half month. The research results revealed that peer tutoring strategy has significant positive impact on Scratch achievement. In addition, Programming learning can enhance the students' computational thinking abilities by peer tutoring or general teaching method significantly.
Robust Lane Detection via Filter Estimator and Data Augmentation

Lane detection is an important topic in the self-driving system. Having a stable lane detection system will assist the self-driving cars to make decisions in order to bring a more comfortable and safe driving environment to the driver. In this paper, we use a network architecture composed of Encoder-Decoder with a Feature Shift Aggregator between them to make the prediction more comprehensive; through our dataset, we found that some problems such as glitches occur when changing lanes. In this regard, we use Data Augmentation and Filter respectively to solve the problem. Finally, the network achieves the result accuracy rate of SOTA on the TuSimple dataset.
Influence of Brightness on Anticipated Effects of Collision Caused by the Motion-in-depth of Objects in Three-dimensional Space

Motion-in-depth generally refers to the movement of objects in three-dimensional space. There may be many factors that affect the anticipated effects of collision within motion-in-depth simulations. In order to elucidate the anticipated effects of collision, it is necessary to comprehensively identify the factors that will enhance these effects. In this study, we summarized the factors affecting the anticipated effects of collision within a continuous motion-in-depth simulation. Two samples were designed for each condition after evaluating various combinations of two factors each. Through an expert interview, it was found that a combination of gradual lightening with the anticipated effects of collision showed the strongest anticipated effects of collision in continuous motion-in-depth simulations.
Machine Learning-Based Real-Time Localization and Automatic Trapping of Multiple Microrobots in Optical Tweezer

Optical Tweezer (OT) is an attractive tool for biological studies, which has been used for cell manipulation and tissue engineering. However, the high intensity of laser beam may damage the target biological objects or specimens. To this end, indirect optical manipulation using optical microrobots has become a promising research direction. To enhance the efficiency of indirect manipulation, automatic localization and trapping of multiple microrobots is significant, which paves a way for closed-loop control. For microrobots localization, a modified YOLOv4-tiny neural network model is developed by integrating ConvNext block for feature extraction, while Gaussian modelling is used to optimize the coordinates of the output of the detection head. To avoid expensive manual annotation for model training, self-supervised learning method is employed with Mosaic data augmentation to eliminate the need of collecting a large amount of data. To determine the optimal trapping points for the laser spots, a machine learning-based ellipse detection method is developed based on arc-support groups and k-means algorithm. We conducted experiments to evaluate the effectiveness of the proposed methods. Compared to mainstream object detection algorithms, our proposed mi-crorobot localization method has higher accuracy and enhanced computational efficiency. The proposed ellipse detection method can detect spherical structures of localized microrobots effectively with 96.77% of success rate. The code is open-source and released on: https://github.com/ClouseYunxiao/MicrorobotsDetection_TrappingPoints
A 40-Gb/s Modulator Driver Using Cascade Swing Compensation in 90 nm CMOS

This letter presents a high-speed optical modulator driver with a large output swing in 90-nm CMOS technology. A new topology of cascade swing compensation (CSC) output stage is proposed for protecting the transistors from breakdown using dynamic gate biasing without extra <italic>RC</italic> networks. To enhance the bandwidth and gain, the active feedback with T-coil peaking and the negative capacitance with series peaking are employed in the preamplifier and main driver, respectively. Under a power consumption of 767 mW, the measured results demonstrate an operating data rate up to 40 Gb/s with a maximum differential output swing of <inline-formula> <tex-math notation="LaTeX">$4.5~V_{\mathrm {ppd}}$ </tex-math></inline-formula> obtained at 32 Gb/s.
A Highly Secure FPGA-Based Dual-Hiding Asynchronous-Logic AES Accelerator Against Side-Channel Attacks

Encryption in field-programmable gate array (FPGA) often provides a good security solution to protect data privacy in Internet-of-Things systems, but this security solution can be compromised by side-channel attacks (SCAs). In this article, we present an FPGA-based dual-hiding asynchronous-logic (async-logic) advanced encryption standard (AES) accelerator, which is highly resistant against SCAs and yet low area/energy overheads. The proposed AES accelerator achieves vertical (amplitude) SCA hiding via an area-efficient dual-rail mapping approach and a zero-value (ZV) compensated substitution-box (S-Box), while enhancing the horizontal (temporal) SCA hiding of async-logic operations via a timing-boundary-free input arrival-time randomizer and a skewed-delay controller. A comprehensive SCA evaluation is performed with 11 SCA models, and we show that our proposed design can offer a strong SCA resistance with measurement-to-disclosure (MTD) of >20 million traces. To our best knowledge, our design is the most secure AES design evaluated with the largest number of traces in FPGA. To compare the design overheads for security, we quantify the figure of merit as normalized (Area <inline-formula> <tex-math notation="LaTeX">$\times $ </tex-math></inline-formula> Energy/MTD(All) <inline-formula> <tex-math notation="LaTeX">$\times 10^{6}$ </tex-math></inline-formula>). The figure of merit of our proposed design is <inline-formula> <tex-math notation="LaTeX">$403\times $ </tex-math></inline-formula> smaller than the benchmark dual-rail synchronous-logic design and <inline-formula> <tex-math notation="LaTeX">$95\times $ </tex-math></inline-formula> smaller than a reported async-logic design.