Miracle-dz/UniFAR-FTUs huggingface dataset:
Phonon screening and dissociation of excitons at finite temperatures from first principles

The properties of excitons, or correlated electron-hole pairs, are of paramount importance to optoelectronic applications of materials. A central component of exciton physics is the electron-hole interaction, which is commonly treated as screened solely by electrons within a material. However, nuclear motion can screen this Coulomb interaction as well, with several recent studies developing model approaches for approximating the phonon screening to the properties of excitons. While these model approaches tend to improve agreement with experiment for exciton properties, they rely on several approximations that restrict their applicability to a wide range of materials, and thus far they have neglected the effect of finite temperatures. Here, we develop a fully first-principles, parameter-free approach to compute the temperature-dependent effects of phonon screening within the ab initio GW-Bethe Salpeter equation framework. We recover previously proposed models of phonon screening as well-defined limits of our general framework, and discuss their validity by comparing them against our first-principles results. We develop an efficient computational workflow and apply it to a diverse set of semiconductors, specifically AlN, CdS, GaN, MgO and SrTiO3. We demonstrate under different physical scenarios how excitons may be screened by multiple polar optical or acoustic phonons, how their binding energies can exhibit strong temperature dependence, and the ultrafast timescales on which they dissociate into free electron-hole pairs.
Cognitive Dissonance: Why Do Language Model Outputs Disagree with Internal Representations of Truthfulness?

Neural language models (LMs) can be used to evaluate the truth of factual statements in two ways: they can be either queried for statement probabilities, or probed for internal representations of truthfulness. Past work has found that these two procedures sometimes disagree, and that probes tend to be more accurate than LM outputs. This has led some researchers to conclude that LMs"lie"or otherwise encode non-cooperative communicative intents. Is this an accurate description of today's LMs, or can query-probe disagreement arise in other ways? We identify three different classes of disagreement, which we term confabulation, deception, and heterogeneity. In many cases, the superiority of probes is simply attributable to better calibration on uncertain answers rather than a greater fraction of correct, high-confidence answers. In some cases, queries and probes perform better on different subsets of inputs, and accuracy can further be improved by ensembling the two. Code is available at github.com/lingo-mit/lm-truthfulness.
LEGO: Learning EGOcentric Action Frame Generation via Visual Instruction Tuning

Generating instructional images of human daily actions from an egocentric viewpoint serves as a key step towards efficient skill transfer. In this paper, we introduce a novel problem -- egocentric action frame generation. The goal is to synthesize an image depicting an action in the user's context (i.e., action frame) by conditioning on a user prompt and an input egocentric image. Notably, existing egocentric action datasets lack the detailed annotations that describe the execution of actions. Additionally, existing diffusion-based image manipulation models are sub-optimal in controlling the state transition of an action in egocentric image pixel space because of the domain gap. To this end, we propose to Learn EGOcentric (LEGO) action frame generation via visual instruction tuning. First, we introduce a prompt enhancement scheme to generate enriched action descriptions from a visual large language model (VLLM) by visual instruction tuning. Then we propose a novel method to leverage image and text embeddings from the VLLM as additional conditioning to improve the performance of a diffusion model. We validate our model on two egocentric datasets -- Ego4D and Epic-Kitchens. Our experiments show substantial improvement over prior image manipulation models in both quantitative and qualitative evaluation. We also conduct detailed ablation studies and analysis to provide insights in our method. More details of the dataset and code are available on the website (https://bolinlai.github.io/Lego_EgoActGen/).
OpenAsp: A Benchmark for Multi-document Open Aspect-based Summarization

The performance of automatic summarization models has improved dramatically in recent years. Yet, there is still a gap in meeting specific information needs of users in real-world scenarios, particularly when a targeted summary is sought, such as in the useful aspect-based summarization setting targeted in this paper. Previous datasets and studies for this setting have predominantly concentrated on a limited set of pre-defined aspects, focused solely on single document inputs, or relied on synthetic data. To advance research on more realistic scenarios, we introduce OpenAsp, a benchmark for multi-document \textit{open} aspect-based summarization. This benchmark is created using a novel and cost-effective annotation protocol, by which an open aspect dataset is derived from existing generic multi-document summarization datasets. We analyze the properties of OpenAsp showcasing its high-quality content. Further, we show that the realistic open-aspect setting realized in OpenAsp poses a challenge for current state-of-the-art summarization models, as well as for large language models.
Stiff deployable structures via coupling of thick Miura-ori tubes along creases

Origami-based structures play an important role in the realization of deployable mechanisms and unique mechanical properties via programmable deformation by folding. Among origami-based structures, tessellation by the coupling of origami tubes enriches the variations in geometry and mechanical properties. However, thickness accommodation is a critical problem in engineering applications involving the coupling of thick origami tubes. To solve this problem, this study proposes the coupling of thick Miura-ori tubes along the creases for facile fabrication, which sustains the one-degree-of-freedom (DOF) motion of thick Miura-ori tubes owing to the local mirror symmetry around the coupling interfaces. Furthermore, the coupling method contributes to the high stiffness of the coupled Miura-ori tubes, as evidenced by the wide gap in the eigenvalues between the one-DOF mode and the elastic modes obtained by the bar-and-hinge models. Finally, meter-scale coupled Miura-ori tubes were fabricated to demonstrate one-DOF motion and high stiffness. The findings of this study enable the rapid construction of structures by one-DOF motion and enhancement of transportability via flat-foldability.
American Psychologist White Fragility: An Emotion Regulation Perspective

To address anti-Black Racism, systemic change across many domains in American life will be necessary. There are many barriers to change, however, and progress requires identifying these barriers and developing tools to overcome them. Given that White individuals disproportionately occupy “ gatekeeping ” positions of power, one key barrier to systemic change is rooted in White individuals ’ emotional (and emotion-regulatory) responses when considering their own role in racism (e.g., involvement in racist systems, biased actions). White people often experience such moments as a jeopardy to their valued goals and are consequently highly motivated to reduce the negative emotions that they feel by denying or avoiding the issue — a multifaceted response known as a White fragility response. When White individuals enact a White fragility response, they can further damage the well-being of Black members of their community and weaken their own motivation for systemic change. Given its stark costs, it is critical to understand White fragility responses. In this article, we argue that White fragility can be usefully viewed through the lens of emotion and emotion regulation theory. In particular, we describe the emotion and emotion regulation responses that characterize White fragility, summarize the wide-ranging consequences of White fragility responses, highlight more sustainable ways forward, and end by considering a broader fragility framework that acknowl-edges multiple dimensions of power. Although emotion regulation lies at the heart of White fragility, emotion regulation is also a tool that can be leveraged for greater justice.
Iterated invariance principle for random dynamical systems

We prove a weak iterated invariance principle for a large class of non-uniformly expanding random dynamical systems. In addition, we give a quenched homogenization result for fast-slow systems in the case when the fast component corresponds to a uniformly expanding random system. Our techniques rely on the appropriate martingale decomposition.
Cross-codex Learning for Reliable Scribe Identification in Medieval Manuscripts

Historic scribe identification is a substantial task for obtaining information about the past. Uniform script styles, such as the Carolingian minuscule, make it a difficult task for classification to focus on meaningful features. Therefore, we demonstrate in this paper the importance of cross-codex training data for CNN based text-independent off-line scribe identification, to overcome codex dependent overfitting. We report three main findings: First, we found that preprocessing with masked grayscale images instead of RGB images clearly increased the F1-score of the classification results. Second, we trained different neural networks on our complex data, validating time and accuracy differences in order to define the most reliable network architecture. With AlexNet, the network with the best trade-off between F1-score and time, we achieved for individual classes F1-scores of up to 0,96 on line level and up to 1.0 on page level in classification. Third, we could replicate the finding that the CNN output can be further improved by implementing a reject option, giving more stable results. We present the results on our large scale open source dataset -- the Codex Claustroneoburgensis database (CCl-DB) -- containing a significant number of writings from different scribes in several codices. We demonstrate for the first time on a dataset with such a variety of codices that paleographic decisions can be reproduced automatically and precisely with CNNs. This gives manifold new and fast possibilities for paleographers to gain insights into unlabeled material, but also to develop further hypotheses.
Adaptations to infer fitness interdependence promote the evolution of cooperation

Significance Much theory on the evolution of cooperation has focused on interactions described by a single payoff matrix. However, human social ecologies involve a great variety of interdependent interactions, some of which involve a conflict of interests (e.g., prisoner’s dilemma) and others that involve more corresponding interests. In heterogeneous social landscapes, a mechanism to infer interdependence could be advantageous and impact the evolution of cooperation. Here, we introduce a theoretical model to investigate the evolution of these psychological adaptations and their impact on cooperation in environments varying in conflict of interests. We found that natural selection favors the evolution of inference of fitness interdependence, especially in heterogeneous environments, promoting cooperation even when defection is the dominant strategy in the average interaction.
Easy Data Augmentation in Sentiment Analysis of Cyberbullying

Instagram, a social media platform, has in the vicinity of 2 billion active users in 2023. The platform allows users to post photos and videos with one another. However, cyberbullying remains a significant problem for about 50% of young Indonesians. To address this issue, sentiment analysis for comment filtering uses a Support Vector Machine (SVM) and Easy Data Augmentation (EDA). EDA will augment the dataset, enabling robust prediction and analysis of cyberbullying by introducing more variation. Based on the tests, SVM combination with EDA results in a 2.52% increase in the k-Fold Cross Validation score. Our proposed approach shows an improved accuracy of 92.5%, 2.5% higher than that of the existing state-of-the-art method. To maintain the reproducibility and replicability of this research, the source code can be accessed at uns.id/eda_svm.
DreamInpainter: Text-Guided Subject-Driven Image Inpainting with Diffusion Models

This study introduces Text-Guided Subject-Driven Image Inpainting, a novel task that combines text and exemplar images for image inpainting. While both text and exemplar images have been used independently in previous efforts, their combined utilization remains unexplored. Simultaneously accommodating both conditions poses a significant challenge due to the inherent balance required between editability and subject fidelity. To tackle this challenge, we propose a two-step approach DreamInpainter. First, we compute dense subject features to ensure accurate subject replication. Then, we employ a discriminative token selection module to eliminate redundant subject details, preserving the subject's identity while allowing changes according to other conditions such as mask shape and text prompts. Additionally, we introduce a decoupling regularization technique to enhance text control in the presence of exemplar images. Our extensive experiments demonstrate the superior performance of our method in terms of visual quality, identity preservation, and text control, showcasing its effectiveness in the context of text-guided subject-driven image inpainting.
Biophysical characterization of the Plasmodium falciparum circumsporozoite protein's N‐terminal domain

The circumsporozoite protein (CSP) is the main surface antigen of the Plasmodium sporozoite (SPZ) and forms the basis of the currently only licensed anti‐malarial vaccine (RTS,S/AS01). CSP uniformly coats the SPZ and plays a pivotal role in its immunobiology, in both the insect and the vertebrate hosts. Although CSP's N‐terminal domain (CSPN) has been reported to play an important role in multiple CSP functions, a thorough biophysical and structural characterization of CSPN is currently lacking. Here, we present an alternative method for the recombinant production and purification of CSPN from Plasmodium falciparum (PfCSPN), which provides pure, high‐quality protein preparations with high yields. Through an interdisciplinary approach combining in‐solution experimental methods and in silico analyses, we provide strong evidence that PfCSPN is an intrinsically disordered region displaying some degree of compaction.
Candida albicans exhibits heterogeneous and adaptive cytoprotective responses to 1 anti-fungal compounds 2

20 Candida albicans, an opportunistic human pathogen, poses a significant threat to human health and is 21 associated with significant socio-economic burden. Current antifungal treatments fail, at least in part, 22 because C. albicans can initiate a strong drug tolerance response that allows some cells to grow at drug 23 concentrations above their minimal inhibitory concentration. To better characterize this cytoprotective 24 tolerance program at the molecular single cell level, we used a nano-liter droplet-based transcriptomics 25 platform to profile thousands of individual fungal cells and establish their subpopulation characteristics 26 in the absence and presence of antifungal drugs. Profiles of untreated cells exhibit heterogeneous 27 expression that correlates with cell cycle stage with distinct metabolic and stress responses. At two days 28 post-fluconazole exposure (a time when tolerance is measurable), surviving cells bifurcate into two 29 major subpopulations: one characterized by the upregulation of genes encoding ribosomal proteins, 30 rRNA processing machinery and mitochondrial cellular respiration capacity, termed the Ribo-dominant 31 ( Rd ) state; and the other enriched for genes encoding stress responses and related processes, termed the 32 Stress-dominant ( Sd ) state. This bifurcation persists at 3 and 6 days post treatment. We provide evidence
Effect of Topographical Irregularities on Seismic Earthquake Response of Construction Site – 2D Numerical Analysis of Trapezoidal Valley Under Real Motion

Documented observation of destruction distribution after seismic events suggest to topography effects on earthquake intensity. But there exist very few –if anywell documented case studies where topography effects are illustrated for strong ground motion. This is due to complex nature of seismic scattered wave by topographical structures to medium. Although some empirical correlations, obtained from statistical analyses, were proposed in different studies to consider this issue, but these correlations also may not be applicable in general or may be overestimation of what happen in reality. These difficulties and disadvantages can only be solved accurately, economically and under realistic conditions by advanced numerical methods. In this paper a powerful FE program (PLAXIS v.8.2) applied to carry out site response analysis of two dimensional topographic structures (trapezoidal non-alluvium valley) subjected to an earthquake (Manjil earthquake, IRAN, 1990). The applicability and efficiency of the program have been verified through some examples of site response analysis that their solutions are available in literature. At last, the results have been diagramed.
Plant Archives

Cape gooseberry is exotically famous for its nutritional and medicinal properties all over the world. This research analysis is perpetuated on qualitative analysis based on some physiochemical parameters of Physalis peruviana L . or cape gooseberry procured from local market of Kolkata. To illustrate, the experiment was based on estimation of qualitative factors such as fruit diameter and circumference, reducing sugar content, total soluble solids, total titratable acidity, ascorbic acid content and total phenolic content. It was obtained from the experiment that fruit obtained from the market of Kolkata showed satisfying results with respect to various attributes taken.
Targeted Immunisation Thresholds for the Contact Process on Power-Law Trees

The popular scale-free configuration model of a social network has a local limit primarily a Galton-Watson tree with some power law offspring distribution $X$, having tail exponent parameter $\tau>2$ such that $\mathbb{P}(X>x) \sim A x^{2-\tau}$. It is known that contact process epidemics can propagate on these trees and therefore these networks for arbitrarily small infection rates, and uniformly at random immunising a small positive proportion of vertices will have no effect on this result. So, to reduce the possibility of survival of the contact process on these trees we instead remove (immunise) those with largest degree. For small $\lambda$ we find sharp thresholds in the maximum permissible degree for the survival probability through three distinct $\tau$ regimes, which by duality would correspond to a transition in the metastable density of the associated network after this targeted removal. Above a threshold, we recover the survival probabilities of Mountford, Valesin and Yao (2013) and thus the epidemic with immunisation is similar to without, but below a threshold on the same order the survival probability is severely reduced or zero.
Systematic comparison of sequencing-based spatial transcriptomic methods

Recent advancements of sequencing-based spatial transcriptomics (sST) have catalyzed significant advancements by facilitating transcriptome-scale spatial gene expression measurement. Despite this progress, efforts to comprehensively benchmark different platforms are currently lacking. The extant variability across technologies and datasets poses challenges in formulating standardized evaluation metrics. In this study, we established a collection of reference tissues and regions characterized by well-defined histological architectures, and used them to generate data to compare six sST methods. We highlighted molecular diffusion as a variable parameter across different methods and tissues, significantly impacting the effective resolutions. Furthermore, we observed that spatial transcriptomic data demonstrate unique attributes beyond merely adding a spatial axis to single-cell data, including an enhanced ability to capture patterned rare cell states along with specific markers, albeit being influenced by multiple factors including sequencing depth and resolution. Our study assists biologists in sST platform selection, and helps foster a consensus on evaluation standards and establish a framework for future benchmarking efforts that can be used as a gold standard for the development and benchmarking of computational tools for spatial transcriptomic analysis.
Optical transparency in 2D ferromagnetic WSe2/1T-VSe2/WSe2 multilayer with strain induced large anomalous Nernst conductivity

Transparent two-dimensional (2D) magnetic materials may bring intriguing features and are indispensable for transparent electronics. However, it is rare to find both optical transparency and room-temperature ferromagnetism simultaneously in a single 2D material. Herein, we explore the possibility of both these features in 2D WSe2/1T-VSe2 (1ML)/WSe2 and WSe2/1T-VSe2 (2ML)/WSe2 heterostructures by taking one monolayer (1ML) and two monolayers (2ML) of 1T-VSe2 using first-principles calculations. Further, we investigate anomalous Hall conductivity (AHC) and anomalous Nernst conductivity (ANC) using a maximally localized Wannier function. The WSe2/1T-VSe2 (1ML)/WSe2 and WSe2/1T-VSe2 (2ML)/WSe2 systems show Curie temperatures of 328 and 405 K. Under biaxial compressive strain, the magnetic anisotropy of both systems is switched from in-plane to out-of-plane. We find a large AHC of 1.51 e2/h and 3.10 e2/h in the electron-doped region for strained WSe2/1T-VSe2 (1ML)/WSe2 and WSe2/1T-VSe2 (2ML)/WSe2 systems. Furthermore, we obtain a giant ANC of 3.94 AK−1 m−1 in a hole-doped strained WSe2/1T-VSe2 (2ML)/WSe2 system at 100 K. Both WSe2/1T-VSe2 (1ML)/WSe2 and WSe2/1T-VSe2 (2ML)/WSe2 are optically transparent in the visible ranges with large refractive indices of 3.2–3.4. Our results may suggest that the WSe2/1T-VSe2/WSe2 structure possesses multifunctional physical properties and these features can be utilized for spintronics and optoelectronics device applications such as magnetic sensors, memory devices, and transparent magneto-optic devices at room temperature.
Scale-driven clustering of geographical point data

This thesis is protected by copyright, with all rights reserved. By reading and using the thesis, the reader understands and agrees to the following terms: 1. The reader will abide by the rules and legal ordinances governing copyright regarding the use of the thesis. 2. The reader will use the thesis for the purpose of research or private study only and not for distribution or further reproduction or any other purpose. 3. The reader agrees to indemnify and hold the University harmless from and against any loss, damage, cost, liability or expenses arising from copyright infringement or unauthorized usage.