Miracle-dz/UniFAR-FTUs huggingface dataset:
Architecture of submarine channel levees.

Levee architecture of six submarine channel-levee systems was investigated using seismic reflection profiles, piston cores, and boreholes. The systems span a wide range of geological environments and comprise the Northwestern Atlantic Mid-Ocean Channel (NAMOC), and Hueneme, Reserve, Amazon, Var, and Laurentian fans. Quantitative measures of architecture were defined and used to investigate the spatial and stratigraphic evolution of levees. Depositional sequences on levees display regular variations in thickness both across-levee and downchannel. Perpendicular to channel trend, depositional sequences thin following an exponential trend that can be quantified by a spatial decay parameter, k. Along the upper reaches of a system, downchannel exponential thinning of levee sediment is quantified by a second spatial decay parameter, lambda. Stratigraphically, the growth of sediment waves and the evolution of levee crests followed consistent patterns not previously recognized. No significant stratigraphic pattern was observed for k.
Electrically tunable flat bands with layer-resolved charge distribution in twisted monolayer-bilayer graphene

At a small twist angle, exotic electronic properties emerge in twisted monolayer-bilayer graphene (aAB), including electrically switchable magnetic order and correlated insulating states. These fascinating many-body phenomena manifest when the low-energy bands feature a narrow band width. In this study, we examine the electronic structure of aAB using first-principles calculations combined with an accurate tight-binding model. We find that the presence of an intrinsic polarization greatly modifies the low-energy bands of aAB. Furthermore, the low-energy bands reach a minimum width at a quasi-magic angle and feature a layer-dependent charge localization and delocalization pattern. In the presence of an electric field, an energy gap opens only if lattice relaxation is taken into account. The particle-hole asymmetry in aAB further leads to flatter conduction bands compared with the valence bands, with an electrically tunable band width and band gap, and a switchable sublattice-dependent charge localization and delocalization pattern.
Telling stories with data - A systematic review

The exponential growth of data has outpaced human ability to process information, necessitating innovative approaches for effective human-data interaction. To transform raw data into meaningful insights, storytelling, and visualization have emerged as powerful techniques for communicating complex information to decision-makers. This article offers a comprehensive, systematic review of the utilization of storytelling in visualizations. It organizes the existing literature into distinct categories, encompassing frameworks, data and visualization types, application domains, narrative structures, outcome measurements, and design principles. By providing a well-structured overview of this rapidly evolving field, the article serves as a valuable guide for educators, researchers, and practitioners seeking to harness the power of storytelling in data visualization.
Boosting Object Detection with Zero-Shot Day-Night Domain Adaptation

Detecting objects in low-light scenarios presents a persistent challenge, as detectors trained on well-lit data exhibit significant performance degradation on low-light data due to low visibility. Previous methods mitigate this issue by exploring image enhancement or object detection techniques with real low-light image datasets. However, the progress is impeded by the inherent difficulties about collecting and annotating low-light images. To address this challenge, we propose to boost low-light object detection with zero-shot day-night domain adaptation, which aims to generalize a detector from well-lit scenarios to low-light ones without requiring real low-light data. Revisiting Retinex theory in the low-level vision, we first design a reflectance representation learning module to learn Retinex-based illumination invariance in images with a carefully designed illumination invariance reinforcement strategy. Next, an interchange-redecomposition-coherence procedure is introduced to improve over the vanilla Retinex image decomposition process by performing two sequential image decompositions and introducing a redecomposition cohering loss. Extensive experiments on ExDark, DARK FACE, and CODaN datasets show strong low-light generalizability of our method. Our code is available at https://github.com/ZPDu/DAI-Net.
On the stability of fractional Sobolev trace inequality and corresponding profile decomposition

In this paper, we study the stability of fractional Sobolev trace inequality within both the functional and critical point settings. In the functional setting, we establish the following sharp estimate: $$C_{\mathrm{BE}}(n,m,\alpha)\inf_{v\in\mathcal{M}_{n,m,\alpha}}\left\Vert f-v\right\Vert_{D_\alpha(\mathbb{R}^n)}^2 \leq \left\Vert f\right\Vert_{D_\alpha(\mathbb{R}^n)}^2 - S(n,m,\alpha) \left\Vert\tau_mf\right\Vert_{L^{q}(\mathbb{R}^{n-m})}^2,$$ where $0\leq m<n$, $\frac{m}{2}<\alpha<\frac{n}{2}, q=\frac{2(n-m)}{n-2\alpha}$ and $\mathcal{M}_{n,m,\alpha}$ denotes the manifold of extremal functions. Additionally, We find an explicit bound for the stability constant $C_{\mathrm{BE}}$ and establish a compactness result ensuring the existence of minimizers. In the critical point setting, we investigate the validity of a sharp quantitative profile decomposition related to the Escobar trace inequality and establish a qualitative profile decomposition for the critical elliptic equation \begin{equation*} \Delta u= 0 \quad\text{in }\mathbb{R}_+^n,\quad\frac{\partial u}{\partial t}=-|u|^{\frac{2}{n-2}}u \quad\text{on }\partial\mathbb{R}_+^n. \end{equation*} We then derive the sharp stability estimate: $$ C_{\mathrm{CP}}(n,\nu)d(u,\mathcal{M}_{\mathrm{E}}^{\nu})\leq \left\Vert \Delta u +|u|^{\frac{2}{n-2}}u\right\Vert_{H^{-1}(\mathbb{R}_+^n)}, $$ where $\nu=1,n\geq 3$ or $\nu\geq2,n=3$ and $\mathcal{M}_{\mathrm{E}}^\nu$ represents the manifold consisting of $\nu$ weak-interacting Escobar bubbles. Through some refined estimates, we also give a strict upper bound for $C_{\mathrm{CP}}(n,1)$, which is $\frac{2}{n+2}$.
Statistics of Extreme Synoptic-Scale Wind Speeds in Ensemble Simulations of Current and Future Climate

Abstract Statistical analysis of the wind speeds, generated by a climate model of intermediate complexity, indicates the existence of areas where the extreme value distribution of extratropical winds is double populated, the second population becoming dominant for return periods of order 103 yr. Meteorological analysis of the second population shows that it is caused when extratropical cyclones merge in an extremely strong westerly jet stream such that conditions are generated that are favorable for occurrence of strong diabatic feedbacks. Doubling of the greenhouse gas concentrations changes the areas of second population and increases its frequency. If these model results apply to the real world, then in the exit areas of the jet stream the extreme wind speed with centennial-to-millennial return periods is considerably larger than extreme value analysis of observational records implies.
Highly Accelerated Weighted MMSE Algorithms for Designing Precoders in FDD Systems with Incomplete CSI

In this work, we derive a lower bound on the training-based achievable downlink (DL) sum rate (SR) of a multi-user multiple-input-single-output (MISO) system operating in frequency-division-duplex (FDD) mode. Assuming linear minimum mean square error (LMMSE) channel estimation is used, we establish a connection of the derived lower bound on the signal-to-interference-noise-ratio (SINR) to an average MSE that allows to reformulate the SR maximization problem as the minimization of the augmented weighted average MSE (AWAMSE). We propose an iterative precoder design with three alternating steps, all given in closed form, drastically reducing the computation time. We show numerically the effectiveness of the proposed approach in challenging scenarios with limited channel knowledge, i.e., we consider scenarios with a very limited number of pilots. We additionally propose a more efficient version of the well-known stochastic iterative WMMSE (SIWMMSE) approach, where the precoder update is given in closed form.
Relative Rota-Baxter operators of weight 0 on groups, pre-groups, braces, the Yang-Baxter equation and $T$-structures

In this paper, we study relative Rota-Baxter operators of weight $0$ on groups and give various examples. In particular, we propose different approaches to study Rota-Baxter operators of weight $0$ on groups and Lie groups. We establish various explicit relations among relative Rota-Baxter operators of weight $0$ on groups, pre-groups, braces, set-theoretic solutions of the Yang-Baxter equation and $T$-structures.
TIBET: Identifying and Evaluating Biases in Text-to-Image Generative Models

Text-to-Image (TTI) generative models have shown great progress in the past few years in terms of their ability to generate complex and high-quality imagery. At the same time, these models have been shown to suffer from harmful biases, including exaggerated societal biases (e.g., gender, ethnicity), as well as incidental correlations that limit such model's ability to generate more diverse imagery. In this paper, we propose a general approach to study and quantify a broad spectrum of biases, for any TTI model and for any prompt, using counterfactual reasoning. Unlike other works that evaluate generated images on a predefined set of bias axes, our approach automatically identifies potential biases that might be relevant to the given prompt, and measures those biases. In addition, our paper extends quantitative scores with post-hoc explanations in terms of semantic concepts in the images generated. We show that our method is uniquely capable of explaining complex multi-dimensional biases through semantic concepts, as well as the intersectionality between different biases for any given prompt. We perform extensive user studies to illustrate that the results of our method and analysis are consistent with human judgements.
Spotted-wing drosophila, Drosophila suzukii (Diptera: Drosophilidae), exhibits large-scale spatial genetic structure across Canada but not fruit host–associated genetic structure

Abstract Spotted-wing drosophila, Drosophila suzukii, is a global pest of soft fruits that is capable of reproducing on a wide range of cultivated and wild plant species. In Canada, D. suzukii was first reported in British Columbia in 2009 and is now widespread across the country. Understanding the genetic structure of D. suzukii populations could be important for pest management if there are phenotypic differences between genetically distinct populations. For example, insect pest populations could respond differently to directional selection imposed by insecticides, differ in their host plant preferences, and vary in their susceptibility to biological control agents. Here, we used double-digest restriction site–associated DNA sequencing to examine large- and fine-scale patterns of the genetic structure of D. suzukii reared from fruit hosts in Canada. We found that this species has a large-scale spatial genetic structure; the flies collected formed two distinct genetic clusters, one of which was distinct to western Canada and the other to eastern Canada. At the local scale, D. suzukii populations showed no evidence of host-associated structuring in British Columbia, suggesting that pest management tactics may be best applied at the landscape level. Our results highlight the need to investigate phenotypic differences between western and eastern D. suzukii populations in Canada.
Top-Down Versus Bottom-Up Approaches to Aspect: The Case of the Dutch Prepositional Progressive

Progressive constructions in Germanic are usually studied as progressive constructions—that is, exclusively so. I characterize this as a top-down approach to aspect, which, I argue, harbors the risk of overlooking relevant language-specific structures that are similar in form and meaning. This paper, therefore, advocates taking a bottom-up approach. Based on a case study of the prepositional progressive in Dutch (aan het-progressive), I claim that this approach is of added empirical and theoretical value. Drawing on construction-based theories, the relevant patterns—dubbed situational constructions—are analyzed in terms of horizontal constructional links. *
Feedback from reservoir sedimentation on the flow pattern in rectangular basins

Despite simple geometries, flow in shallow rectangular reservoirs show complex recirculation patterns, which strongly influence the sediment deposits and, in practice, affect the operation and maintenance costs of such facilities. Based on composite modelling, this research characterizes flow and sedimentation patterns in geometric conditions which have not been investigated so far. Velocity fields developing in rectangular shallow reservoirs (h = 0.2 m) with different asymmetric locations of the inlet and the outlet channels were experimentally investigated. Tests were performed in a reservoir geometry (4.5 m x 4 m) characterized by a stable symmetric flow pattern in the basic symmetric configuration, at constant hydraulic conditions; the aim was to evaluate exclusively the effect of channels displacing on the flow patterns and on the sedimentation of suspended solids. Horizontal velocity components were measured by ultrasound velocity profilers in the entire reservoir and maps of velocity vectors were obtained. Velocity measurements were performed both with clear water and with an inflowing suspended load. At the end of the experiments sediments deposits thickness on the entire reservoir bottom was measured by a laser light method, and maps of sediments deposits thickness were produced. Reservoir trapping efficiency was evaluated, but no significant influence of inlet and outlet channels location on trapping efficiency was observed. Numerical simulations were performed with the depth-averaged model WOLF 2D, in order to assess the ability of the model to reproduce the different types of flow patterns found in the experiments. In particular, a sensitivity analysis on bottom roughness as well as on the turbulence closure model and parameter was performed, in order to analyze a possible feedback effect of sediment deposits and/or suspended load on the type of flow pattern.
Sand strength for back-analysis of pull-out tests at large displacement

Pull-out test data are reported for two textured, planar inclusions embedded in sand. Comparison of measured and back-calculated values of pull-out resistance, and also of the lateral stress on the front wall of the box due to pull-out, support the belief that a plane strain condition prevails at large displacement. The study demonstrates that it is important to account for stress dependency of the friction angle in analysis of tests performed at a normal effective stress less than 50 kPa.
AlexNet-Based Feature Extraction for Cassava Classification: A Machine Learning Approach

Cassava, a significant crop in Africa, Asia, and South America, is a staple food for millions. However, classifying cassava species using conventional color, texture, and shape features is inefficient, as cassava leaves exhibit similarities across different types, including toxic and non-toxic varieties. This research aims to overcome the limitations of traditional classification methods by employing deep learning techniques with pre-trained AlexNet as the feature extractor to accurately classify four types of cassava: Gajah, Manggu, Kapok, and Beracun. The dataset was collected from local farms in Lamongan Indonesia. To collect images with agricultural research experts, the dataset consists of 1,400 images, and each type of cassava has 350 images. Three fully connected (FC) layers were utilized for feature extraction, namely fc6, fc7, and fc8. The classifiers employed were support vector machine (SVM), k-nearest neighbors (KNN), and Naive Bayes. The study demonstrated that the most effective feature extraction layer was fc6, achieving an accuracy of 90.7% with SVM. SVM outperformed KNN and Naive Bayes, exhibiting an accuracy of 90.7%, sensitivity of 83.5%, specificity of 93.7%, and F1-score of 83.5%. This research successfully addressed the challenges in classifying cassava species by leveraging deep learning and machine learning methods, specifically with SVM and the fc6 layer of AlexNet. The proposed approach holds promise for enhancing plant classification techniques, benefiting researchers, farmers, and environmentalists in plant species identification, ecosystem monitoring, and agricultural management.
Utility of Magnetic Activated Cell Sorting (MACS) in Assisted Utility of Magnetic Activated Cell Sorting (MACS) in Assisted Reproduction Reproduction

Background: Magnetic activated cell sorting ( MACS) has mechanisms to reduce the degrees of Deoxyribonucleic acid (DNA) fragmentation done to the sperm sample in sperm processing pre-injection since no density gradient is involved or heavy centrifugation steps involved. If DNA fragmentation is not eliminated from sperms, poor cleavage rate, bad embryo quality, poor implantation and low pregnancy rates may occur. A MACS is a nano-sized mixture of particles with high magnetic properties coated with glycoproteins for morbid/DNA fragmented spermatozoa depletion before Intra Cytoplasmic Sperm Injection (ICSI). Several investigations have demonstrated that employing the MACS approach improves the outcomes of ICSI in patients who have significant levels of sperm DNA fragmentation. Aim of the study: To prove that the assessing Utility of Clemente Magnetic Activated Cell Sorting in ICSI cycle (especially recurrent implantation failure) would improve cleavage rate, Embryo quality, implantation and hopefully pregnancy rates. Patients and Methods: We determined if MACS is suitable for male factor having a high DNA Fragmentation Index (DFI), undertaking ICSI or in vitro fertilization (IVF), recurrent miscarriage attributable to male factor, and early pregnancy loss caused by male factor. Result: The use of MACS techniques in ICSI resulted in increasing fertilization rate, cleavage rate, blastocyst formation rate, number of Grade A embryos and rates of pregnancy as the use of MACS in sperm processing helps in increasing motility, especially progressive motility, and reducing sperm with abnormal morphological defects. Conclusion: The study's findings showed that using the MACS approach improved ICSI results in patients who had high levels of sperm DNA fragmentation.
JOURNAL OF COASTAL AND HYDRAULIC STRUCTURES

The transport and accumulation of driftwood, large wood, or large woody debris (LWD) in mountain streams is a natural part of catchment health and river connectivity. At hydraulic structures, the presence of driftwood has impacts on total discharge and up-stream energy. Driftwood has been studied at a variety of spillways and weir types; however, little is known about its interaction at rock weirs. This study seeks to determine what factors affect the transport of driftwood and potential upstream impacts of driftwood accumulations at rock weirs through field-informed scaled model testing. Observations of driftwood at rock weirs located on the Blacksmith Fork River, a mountain stream located in Utah, USA, were used to replicate driftwood dynamics in V-and I-shaped rock weirs in a large flume. The river response to rock weirs on the corresponding section of the Blacksmith Fork River was also investigated using historic aerial imagery and field data. Approaches to driftwood management typically prioritize either natural processes or hydraulic structure safety and flow conveyance. A new hybrid approach should consider both aspects for rock weirs in mountain streams.
Ni/Co-based nanosheet arrays for e ﬃ cient oxygen evolution reaction

E ﬃ cient oxygen evolution reaction (OER) catalysts composed of earth-abundant elements are crucial to the development of practical and environmentally friendly water splitting systems. Herein, NiCoO 2 /CoO/Ni 3 N na-nosheet arrays (NiCoON NSAs/NF) are fabricated in situ on the 3D nickel foam. In the alkaline solution, the NiCoON nanocomposite has excellent catalytic OER properties such as a small overpotential of 247mV (at 10mAcm − 2 ) and Tafel slope of 35mVdec − 1 , which are better than those of Ni x Co 3-x O 4 and most Ni-and Co-based catalysts. There are more active sites with oxygen vacancies on NiCoON NSAs after the treatment with NH 3 and the face-centered cubic NiCoO 2 enhances the formation of active Ni-Co layered hydroxide/oxyhydr-oxide species (NiOOH) in comparison with spinal Ni x Co 3-x O 4 during the electrochemical process. In addtion, the Ni 3+ -rich surface together with Co incorporation facilitates the formation of β -NiOOH. Our study reveals that control of active species on NiCoON NSAs/NF leads to high activity and stability in OER catalysis.
Anthropogenic and natural contributions to the Southeast Pacific precipitation decline and recent megadrought in central Chile

Within large uncertainties in the precipitation response to greenhouse gas forcing, the Southeast Pacific drying stands out as a robust signature within climate models. A precipitation decline, of consistent direction but of larger amplitude than obtained in simulations with historical climate forcing, has been observed in central Chile since the late 1970s. To attribute the causes of this trend, we analyze local rain gauge data and contrast them to a large ensemble of both fully coupled and sea surface temperature‐forced simulations. We show that in concomitance with large‐scale circulation changes, the Pacific Decadal Oscillation explains about half of the precipitation trend observed in central Chile. The remaining fraction is unlikely to be driven exclusively by natural phenomena but rather consistent with the simulated regional effect of anthropogenic climate change. We particularly estimate that a quarter of the rainfall deficit affecting this region since 2010 is of anthropogenic origin. An increased persistence and recurrence of droughts in central Chile emerges then as a realistic scenario under the current socioeconomic pathway.
Experiences of Students with Disabilities During the COVID-19 Interruption of In-Person Instruction

The COVID-19 pandemic resulted in nearly every postsecondary institution in the United States rapidly shifting to remote learning during the spring 2020 semester This study presents the results of a survey of a national sample of college students with disabilities, the first such study specific to students with disabilities beyond a single institution Students reported feeling supported by their institutions, faculty, and disability services offices, while also noting shifts in accommodation needs, as well as personal, health, and financial concerns Implications and future research needs are presented