Miracle-dz/UniFAR-FTUs huggingface dataset:
Effective Optimization Technique for a Nonlinear Rainfall-Runoff Model

AbstractThe purpose of this paper is to propose an effective optimization technique that can overcome the local minimum problem resulting from the nonlinear construction of the rainfall-runoff model. First, this technique attempts to approximate the nonlinear function by using a finite number of terms of linear functions, referred to as the linearization process. Then, these linear functions would be optimized by the sum of squared errors (MSSE). Finally, the optimized parameters of a nonlinear function using the step-iterative algorithm were obtained. Its features and capabilities are demonstrated by means of a binary function and a conceptual rainfall-runoff model (Xinanjiang model). To optimize the model parameters, 10 years of historical data in the Changzhao basin are applied, whereas the most recent three years are utilized to verify these parameters. With reference to the binary function, the proposed linearlized search technique (LST) converge quickly from any starting point. With regard to the hy.
CRISPR-Cas9 system applications in cancer models

Clustered regularly interspaced short palindromic repeats (CRISPR) is a technology of gene editing. CRISPR/Cas9 technology can rapidly and accurately edit the target gene. At present, the development of human illness simulations and the genetic enhancement of cattle and poultry have both benefited from CRISPR/Cas9 gene editing technologies, but there are still a large number of coding or non-coding sequence functions and disease resistance mechanisms still need to be further explored. This technology has great advances and advantages in gene editing and related therapeutics. There have been a large number of related studies at the cellular and biological levels, and many researchers have obtained many good results. Scientists have found some viable CRISPR solutions and some real applications, but the risks and uncertainties are high, there are some ethical issues, and it will still take a long time to turn it into a routine clinical treatment tool.
Quantitatively linking collagen alteration and epithelial tumor progression by second harmonic generation microscopy

Collagen alteration is critical for epithelial tumor initiation and progression. Quantitatively linking collagen alteration and epithelial tumor progression is essential for developing an optical endoscopy to evaluate epithelial tumor progression. In this work, we established a quantitative link between collagen alteration and epithelial tumor progression using second harmonic generation (SHG) microscopy. It was found that SHG microscopy can provide quantitative features to effectively evaluate epithelial tumor progression, and to locate tumor and determine the margin of tumor regions. These results suggest that SHG microscopy has the potential in offering a noninvasive in vivo imaging tool to quantify epithelial tumor progression.
Low writing field with large writing margin in toggle magnetic random access memories using synthetic antiferromagnet ferromagnetically coupled with soft magnetic layers

The authors propose free layer structures that can simultaneously reduce the writing field and enlarge the writing margin in toggle magnetic random access memories. In the free layers, two soft magnetic layers of NiFe and a synthetic antiferromagnet trilayer of NiFe∕Ru∕NiFe were ferromagnetically coupled through two ferromagnetic coupling layers (FCLs). The FCLs were composed of ultrathin Ta-based layers. As the coupling strength through the FCLs decreased, the spin-flop field (Hflop) decreased and the saturation field increased in these free layers, by which the Hflop could be freely decreased within the allowable range of its variation even for the 0.24-μm-wide bits.
Abundant molecular gas and inefficient SF in intra-cluster regions of a ram pressure stripped tail

Abstract For the first time in any ram pressure stripped galaxy, we detect large amounts of cold molecular gas in the X-ray bright, and star forming tail of ESO 137-001 in the Norma cluster. We find very low star formation efficiency in the stripped gas, similar to values found in the outer spiral disks where however molecular gas is mostly undetected. The results were recently published in Jáchym et al. (2014).
Speckle tracking in high frequency ultrasound images with application to intravascular imaging

Speckle tracking calibration studies have been performed using a 42 MHz intravascular imaging probe in order to investigate the potential of correlation based speckle tracking techniques for detecting small differential displacements in intravascular ultrasound images. Serial images were acquired of a tissue phantom material subjected to incremental displacements produced by a two-axis motion stage. Tracking performance was best for displacements in the axial beam direction over the range of 0 to 200 mm and somewhat worse for lateral displacements. The tracking performance was also assessed in tissue-equivalent vessel phantom models deformed by incremental changes in intraluminal pressure. Differential displacements on the order of 30 mm were successfully measured in a two-component phantom with elastic moduli differing by a factor of three
Textural Features of Mouse Glioma Models Measured by Dynamic Contrast-Enhanced MR Images with 3D Isotropic Resolution

This paper investigates the effect of anisotropic resolution on the image textural features of pharmacokinetic (PK) parameters of a murine glioma model using dynamic contrast-enhanced (DCE) MR images acquired with an isotropic resolution at 7T with pre-contrast T1 mapping. The PK parameter maps of whole tumors at isotropic resolution were generated using the two-compartment exchange model combined with the three-site-two-exchange model. The textural features of these isotropic images were compared with those of simulated, thick-slice, anisotropic images to assess the influence of anisotropic voxel resolution on the textural features of tumors. The isotropic images and parameter maps captured distributions of high pixel intensity that were absent in the corresponding anisotropic images with thick slices. A significant difference was observed in 33% of the histogram and textural features extracted from anisotropic images and parameter maps, compared to those extracted from corresponding isotropic images. Anisotropic images in different orthogonal orientations demonstrated 42.1% of the histogram and textural features to be significantly different from those of isotropic images. This study demonstrates that the anisotropy of voxel resolution needs to be carefully considered when comparing the textual features of tumor PK parameters and contrast-enhanced images.
On the interpretation of Andrews’ theorem

Abstract Andrews (1984) has shown that any flow satisfying Arnol'd's (1965, 1966) sufficient conditions for stability must be zonally-symmetric if the boundary conditions on the flow are zonally-symmetric. This result appears to place very strong restrictions on the kinds of flows that can be proved to be stable by Arnol'd's theorems. In this paper, Andrews’ theorem is re-examined, paying special attention to the case of an unbounded domain. It is shown that, in that case, Andrews’ theorem generally fails to apply, and Arnol'd-stable flows do exist that are not zonally-symmetric. The example of a circular vortex with a monotonic vorticity profile is a case in point. A proof of the finite-amplitude version of the Rayleigh stability theorem for circular vortices is also established; despite its similarity to the Arnol'd theorems it seems not to have been put on record before.
Regulator problem for linear discrete-time systems with non-symmetrical constrained control

The regulator problem is studied for linear discrete-time systems with non-symmetrical constrained control, i.e. systems described by the state equation x k+1 = Ax k + Bu k, where u k ∊ Ω, and u k = Fx k. Necessary and sufficient conditions allowing us to obtain the largest non-symmetrical polyhedral domain of positive invariance and contractivity with respect to motions of the system in the closed loop are established. The case of symmetrically constrained control is obtained as a particular case.
Prolonged maternal exposure to glucocorticoids alters selenoprotein expression in the developing brain

Aberrant activation of the stress-response system in early life can alter neurodevelopment and cause long-term neurological changes. Activation of the hypothalamic–pituitary–adrenal axis releases glucocorticoids into the bloodstream, to help the organism adapt to the stressful stimulus. Elevated glucocorticoid levels can promote the accumulation of reactive oxygen species, and the brain is highly susceptible to oxidative stress. The essential trace element selenium is obtained through diet, is used to synthesize antioxidant selenoproteins, and can mitigate glucocorticoid-mediated oxidative damage. Glucocorticoids can impair antioxidant enzymes in the brain, and could potentially influence selenoprotein expression. We hypothesized that exposure to high levels of glucocorticoids would disrupt selenoprotein expression in the developing brain. C57 wild-type dams of recently birthed litters were fed either a moderate (0.25 ppm) or high (1 ppm) selenium diet and administered corticosterone (75 μg/ml) via drinking water during postnatal days 1 to 15, after which the brains of the offspring were collected for western blot analysis. Glutathione peroxidase 1 and 4 levels were increased by maternal corticosterone exposure within the prefrontal cortex, hippocampus, and hypothalamus of offspring. Additionally, levels of the glucocorticoid receptor were decreased in the hippocampus and selenoprotein W was elevated in the hypothalamus by corticosterone. Maternal consumption of a high selenium diet independently decreased glucocorticoid receptor levels in the hippocampus of offspring of both sexes, as well as in the prefrontal cortex of female offspring. This study demonstrates that early life exposure to excess glucocorticoid levels can alter selenoprotein levels in the developing brain.
A Method for Numerical Computation of Jordan Canonical Form of Matrix

The Jordan canonical form of a matrix plays an important role in control system theory. But the numerically stable computation method has not been established. In this paper, we propose a numerical algorithm for the computation of Jordan canonical form of matrix. The transformation matrix consists of principal vectors obtained by the intersection of the kernel of the eigen-vector spaces. And we define the numerical Jordan canonical form of matrix and propose a more stable numerical method. The numerical example shows that the proposed method is more reliable than the well-known commercially available software.
Effect of pre-grazing herbage mass and post-grazing sward height on herbage production and intake and performance of suckler-bred steers within a weanling-to-beef production system

The current study investigated the effects of pre-grazing herbage mass (PGHM, 1500 or 2500 kg dry matter (DM)/ha) and post-grazing sward height (PGSH, 4 or 6 cm) on herbage production and its nutritive value and DM intake, grazing behaviour and growth of Charolais steers ( n = 96; 12 months of age; 396 ± 19.0 kg) during a 222-day grazing season, and the subsequent effect of an indoor finishing diet (grass silage alone or supplemented with concentrates) for 146 days, on performance and carcass traits. Steers were assigned to one of 12 grazing groups and group was assigned to a 2 (PGHM) × 2 (PGSH) factorial arrangement of treatments. At the end of the grazing season, live-weight was 16 kg heavier for PGHM-1500 than PGHM-2500 and 34 kg heavier for PGSH-6 than PGSH-4. After indoor finishing, there was no difference in carcass weight between PGHM treatments, but PGSH-6 had a 19 kg heavier carcass than PGSH-4. Herbage production was 881 and 517 kg DM/ha greater for PGHM-2500 than PGHM-1500 and for PGSH-4 than PGSH-6, respectively. Grazing stocking rate did not differ between PGHM treatments but PGSH-4 carried 1.35 more steers/ha than PGSH-6. Supplementing concentrates during the indoor period increased carcass weight (42 kg) and fat score (2.10 units). In conclusion, grazing to 6 rather than 4 cm, increased individual carcass weight but not carcass weight gain/ha. Compared to PGHM-2500, grazing PGHM-1500 increased steer live-weight gain at pasture, but did not affect carcass weight following indoor finishing.
Childhood Maltreatment and Creativity among Chinese College Students: A Serial Mediation Model

Creativity plays a very crucial impact on our cultural life and has also been important to the improvement of human civilization. Numerous studies have indicated that family circumstance plays an important role in the development of individual creativity. However, little is known about the mediating mechanisms underlying the association between childhood maltreatment and creativity. This study intended to explore the serial multiple mediation model in which undergraduates’ cognitive flexibility and self-efficacy were proposed to mediate the potential influence of childhood maltreatment on their creativity. Participants were 1069 undergraduates (573 males and 496 females, mean age was 20.57 ± 1.24 years ranging from 17 to 24) from a university in Shandong Province, China. Participants were required to complete an internet survey including the Short Form of Childhood Trauma Questionnaire (CTQ-SF), General Self-Efficacy Scale (GSES), Cognitive Flexibility Inventory (CFI), and Williams Creativity Aptitude Test (WCAT). Serial multiple mediation analysis and the bootstrap method were used to investigate the mediation effects of cognitive flexibility and self-efficacy. The results showed that childhood maltreatment indirectly influenced undergraduates’ creativity through three indirect paths: childhood maltreatment→cognitive flexibility→creativity, childhood maltreatment→self-efficacy→creativity, and childhood maltreatment→cognitive flexibility→self-efficacy→creativity. The ratios of the total indirect effects and branch-indirect effects to the total effects were 92.73%, 34.61%, 35.68%, and 22.44%, respectively. These results indicated that cognitive flexibility and self-efficacy could completely mediate the potential impact of childhood maltreatment on individuals creativity.
Coherent combining of multi-wavelength fiber amplifiers using a stochastic parallel gradient descent algorithm

Multi-wavelength and non-single-frequency seed lasers can be used to suppress stimulated Brillouin scattering and improve the ultimate output power of a fiber laser amplifier. Coherent combining of non-single-frequency and/or multi-wavelength lasers/amplifiers is a promising way to obtain much higher total output power than from coherent combining of single-frequency lasers/amplifiers. Using a stochastic parallel gradient descent algorithm, we demonstrate coherent combining of four-channel multi-wavelength lasers in a master oscillator power amplifier (MOPA) configuration. Four lasers with different wavelengths, namely two non-single-frequency and two single-frequency lasers, are used. The mean power of the main lobe in the closed-loop case is three times that for the open-loop case, approaching 75% of its ideal value. The coherent combining of multi-wavelength and non-single-frequency lasers in a MOPA configuration is validated, and a feasible approach for scaling to high power coherent combining is provided.
Attachment in Couples Coping with Cancer: Associations with Observed Communication and Long-Term Health

Cancer poses a threat to well-being that may activate the attachment system and influence interpersonal dynamics, such as communication. Research indicates that avoidant and anxious attachment, as well as communication, are independently associated with poorer psychosocial well-being, yet studies examining links between attachment, communication, and long-term physical well-being are lacking. We examined (a) associations between patient and partner attachment (measured with the adult attachment scale [AAS-Revised]) and observed communication (across affect [the Relational Affective Topography System (RATS) coding system] and behavior [the Asymmetric Behavior Coding System (ABCS) coding system]) and (b) the extent to which attachment and communication independently predicted long-term physical well-being (measured by the Functional Assessment of Cancer Therapy-General Population [FACT-GP]). Participants were 134 couples [mean age 53.9 (SD = 13.4), 86.2% Caucasian, 66% of patients, 36% of partners female]. Patient participants had either breast, colorectal, or lung cancer. Couples individually completed self-report measures of attachment (baseline) and physical well-being (baseline and 4, 8, and 12 months later). At baseline, couples engaged in a 15 min videorecorded cancer-related conversation coded for communication behavior and affective expression. Patients and partners with higher anxious and avoidant attachment exhibited more negative affect and negative approach behaviors. A greater avoidant attachment was associated with less positive affective expression. Attachment insecurity and affective expression were prospectively linked with physical well-being. Findings indicate that attachment is associated with overt communication behaviors and that insecure attachment and affective expression may be risk factors for poorer health outcomes.
pixel-Interpretable Motion Planner for Urban Driving via Hierarchical Imitation Learning

 Abstract —Learning-based approaches have achieved impressive performance for autonomous driving and an increasing number of data-driven works are being studied in the decision-making and planning module. However, the reliability and the stability of the neural network is still full of challenges. In this paper, we introduce a hierarchical imitation method including a high-level grid-based behavior planner and a low-level trajectory planner, which is not only an individual data-driven driving policy and can also be easily embedded into the rule-based architecture. We evaluate our method both in closed-loop simulation and real world driving, and demonstrate the neural network planner has outstanding performance in complex urban autonomous driving scenarios.
Performance investigations of two channel readout configurations on the cross-strip cadmium zinc telluride detector

Multiple application-specific integrated circuits (ASIC) are required for the detectors if their readout channels are larger than that of ASIC channels. For a system with such a readout scheme, there is a need to configure channels among ASICs to achieve the lowest electronics noise and highest count rate. In this work, experiments were performed to investigate the performance of two different readout configurations between two ASICs in a cross-strip cadmium zinc telluride detector. A lower electronic noise level, better FWHM energy resolution performance, and higher count rate was found for the anode electrode strips with each ASIC allocating half of the detector area when compared to allocating each ASIC channel to alternate anode channels.
PIAT: Parameter Interpolation based Adversarial Training for Image Classification

Adversarial training has been demonstrated to be the most effective approach to defend against adversarial attacks. However, existing adversarial training methods show apparent oscillations and overfitting issue in the training process, degrading the defense efficacy. In this work, we propose a novel framework, termed Parameter Interpolation based Adversarial Training (PIAT), that makes full use of the historical information during training. Specifically, at the end of each epoch, PIAT tunes the model parameters as the interpolation of the parameters of the previous and current epochs. Besides, we suggest to use the Normalized Mean Square Error (NMSE) to further improve the robustness by aligning the clean and adversarial examples. Compared with other regularization methods, NMSE focuses more on the relative magnitude of the logits rather than the absolute magnitude. Extensive experiments on several benchmark datasets and various networks show that our method could prominently improve the model robustness and reduce the generalization error. Moreover, our framework is general and could further boost the robust accuracy when combined with other adversarial training methods.
Decoupled Multimodal Distilling for Emotion Recognition

Human multimodal emotion recognition (MER) aims to perceive human emotions via language, visual and acoustic modalities. Despite the impressive performance of previous MER approaches, the inherent multimodal heterogeneities still haunt and the contribution of different modalities varies significantly. In this work, we mitigate this issue by proposing a decoupled multimodal distillation (DMD) approach that facilitates flexible and adaptive crossmodal knowledge distillation, aiming to enhance the discriminative features of each modality. Specially, the representation of each modality is decoupled into two parts, i.e., modality-irrelevant/-exclusive spaces, in a self-regression manner. DMD utilizes a graph distillation unit (GD-Unit) for each decoupled part so that each GD can be performed in a more specialized and effective manner. A GD-Unit consists of a dynamic graph where each vertice represents a modality and each edge indicates a dynamic knowledge distillation. Such GD paradigm provides a flexible knowledge transfer manner where the distillation weights can be automatically learned, thus enabling diverse crossmodal knowledge transfer patterns. Experimental results show DMD consistently obtains superior performance than state-of-the-art MER methods. Visualization results show the graph edges in DMD exhibit meaningful distributional patterns w.r. t. the modality-irrelevant/-exclusive feature spaces. Codes are re leased at https://github.com/mdswyz/DMD.
sparseDFM: An R Package to Estimate Dynamic Factor Models with Sparse Loadings

sparseDFM is an R package for the implementation of popular estimation methods for dynamic factor models (DFMs) including the novel Sparse DFM approach of Mosley et al. (2023). The Sparse DFM ameliorates interpretability issues of factor structure in classic DFMs by constraining the loading matrices to have few non-zero entries (i.e. are sparse). Mosley et al. (2023) construct an efficient expectation maximisation (EM) algorithm to enable estimation of model parameters using a regularised quasi-maximum likelihood. We provide detail on the estimation strategy in this paper and show how we implement this in a computationally efficient way. We then provide two real-data case studies to act as tutorials on how one may use the sparseDFM package. The first case study focuses on summarising the structure of a small subset of quarterly CPI (consumer price inflation) index data for the UK, while the second applies the package onto a large-scale set of monthly time series for the purpose of nowcasting nine of the main trade commodities the UK exports worldwide.
Efficient Execution of SPARQL Queries with OPTIONAL and UNION Expressions

The proliferation of RDF datasets has resulted in studies focusing on optimizing SPARQL query processing. Most existing work focuses on basic graph patterns (BGPs) and ignores other vital operators in SPARQL, such as UNION and OPTIONAL. SPARQL queries with these operators, which we abbreviate as SPARQL-UO, pose serious query plan generation challenges. In this paper, we propose techniques for executing SPARQL-UO queries using BGP execution as a building block, based on a novel BGP-based Evaluation (BE)-Tree representation of query plans. On top of this, we propose a series of cost-driven BE-tree transformations to generate more efficient plans by reducing the search space and intermediate result sizes, and a candidate pruning technique that further enhances efficiency at query time. Experiments confirm that our method outperforms the state-of-the-art by orders of magnitude.