Miracle-dz/UniFAR-FTUs huggingface dataset:
Low Resource Summarization using Pre-trained Language Models

With the advent of Deep Learning based Artificial Neural Networks models, Natural Language Processing (NLP) has witnessed significant improvements in textual data processing in terms of its efficiency and accuracy. However, the research is mostly restricted to high-resource languages such as English and low-resource languages still suffer from a lack of available resources in terms of training datasets as well as models with even baseline evaluation results. Considering the limited availability of resources for low-resource languages, we propose a methodology for adapting self-attentive transformer-based architecture models (mBERT, mT5) for low-resource summarization, supplemented by the construction of a new baseline dataset (76.5k article, summary pairs) in a low-resource language Urdu. Choosing news (a publicly available source) as the application domain has the potential to make the proposed methodology useful for reproducing in other languages with limited resources. Our adapted summarization model \textit{urT5} with up to 44.78\% reduction in size as compared to \textit{mT5} can capture contextual information of low resource language effectively with evaluation score (up to 46.35 ROUGE-1, 77 BERTScore) at par with state-of-the-art models in high resource language English \textit{(PEGASUS: 47.21, BART: 45.14 on XSUM Dataset)}. The proposed method provided a baseline approach towards extractive as well as abstractive summarization with competitive evaluation results in a limited resource setup.
Bridging the Domain Gap by Clustering-based Image-Text Graph Matching

Learning domain-invariant representations is important to train a model that can generalize well to unseen target task domains. Text descriptions inherently contain semantic structures of concepts and such auxiliary semantic cues can be used as effective pivot embedding for domain generalization problems. Here, we use multimodal graph representations, fusing images and text, to get domain-invariant pivot embeddings by considering the inherent semantic structure between local images and text descriptors. Specifically, we aim to learn domain-invariant features by (i) representing the image and text descriptions with graphs, and by (ii) clustering and matching the graph-based image node features into textual graphs simultaneously. We experiment with large-scale public datasets, such as CUB-DG and DomainBed, and our model achieves matched or better state-of-the-art performance on these datasets. Our code will be publicly available upon publication.
One Clean Qubit Suffices for Quantum Communication Advantage

We study the one-clean-qubit model of quantum communication where one qubit is in a pure state and all other qubits are maximally mixed. We demonstrate a partial function that has a quantum protocol of cost $O(\log N)$ in this model, however, every interactive randomized protocol has cost $\Omega(\sqrt{N})$, settling a conjecture of Klauck and Lim. In contrast, all prior quantum versus classical communication separations required at least $\Omega(\log N)$ clean qubits. The function demonstrating our separation also has an efficient protocol in the quantum-simultaneous-with-entanglement model of cost $O(\log N )$. We thus recover the state-of-the-art separations between quantum and classical communication complexity. Our proof is based on a recent hypercontractivity inequality introduced by Ellis, Kindler, Lifshitz, and Minzer, in conjunction with tools from the representation theory of compact Lie groups.
Active Visual Localization for Multi-Agent Collaboration: A Data-Driven Approach

Rather than having each newly deployed robot create its own map of its surroundings, the growing availability of SLAM-enabled devices provides the option of simply localizing in a map of another robot or device. In cases such as multi-robot or human-robot collaboration, localizing all agents in the same map is even necessary. However, localizing e.g. a ground robot in the map of a drone or head-mounted MR headset presents unique challenges due to viewpoint changes. This work investigates how active visual localization can be used to overcome such challenges of viewpoint changes. Specifically, we focus on the problem of selecting the optimal viewpoint at a given location. We compare existing approaches in the literature with additional proposed baselines and propose a novel data-driven approach. The result demonstrates the superior performance of the data-driven approach when compared to existing methods, both in controlled simulation experiments and real-world deployment.
Evolution of Salt Structures, East Texas Diapir Province, Part 2: Patterns and Rates of Halokinesis

The effects of salt mobilization on Aptian and younger (post-112 Ma) strata in the East Texas basin can be used to illustrate patterns of dome growth through time, and to estimate rates and amounts of salt movement. Pre-Aptian domes grew in three areas around the margin of the diapir province, apparently in pre-Aptian depocenters. Maximum dome growth along the basin axis coincided with maximum regional sedimentation there during the middle Cretaceous (Aptian, Albian, and Cenomanian). In the Late Cretaceous the sites of maximum diapirism migrated to the periphery of the diapir province. Diapirism began after pillows were erosionally breached, leading to salt extrusion and formation of peripheral sinks. The duration of pillow and diapir stages of growth was subequal, ranging from 10 to 30 Ma. Post-diapiric stage of growth continued for more than 112 Ma in some cases. Diapirs grew fastest in the Early Cretaceous, when peak growth rates ranged from 150 to 530 m/Ma (490 to 1,740 ft/Ma), declining in the Early Tertiary to 10 to 60 m/Ma (30 to 200 ft/Ma). Assuming steady-state conditions over periods of 1 to 17 Ma, strain rates for the rise of the East Texas diapirs averaged 6.7 × 10-16/sec; peak gross rate of growth averaged 2.3 × 10-15/sec, similar to slow orogenic rates. The evolution of East Texas salt domes essentially ended in the early Tertiary with uplift rates less than 30 m/Ma (100 ft/Ma).
Multicellular bioprinted skin facilitates human-like skin architecture in vivo

Bioprinting is a promising alternative method to generate skin substitutes because it can replicate the structural organization of the skin into biomimetic layers in vitro. In this study, six primary human skin cell types were used to bioprint a trilayer skin construct consisting of epidermis, dermis, and hypodermis. Transplantation of the bioprinted skin with human cells onto full-thickness wounds of nu/nu mice promoted rapid vascularization and formation of epidermal rete ridges analogous to the native human epidermis, with a normal-looking extracellular matrix. Cell-specific staining confirmed the integration of the implanted cells into the regenerated skin. Using a similar approach, a 5 centimeter–by–5 centimeter bioprinted autologous porcine skin graft was transplanted onto full-thickness wounds in a porcine excisional wound model. The bioprinted skin graft improved epithelialization, reduced skin contraction, and supported normal collagen organization with reduced fibrosis. Differential gene expression demonstrated pro-remodeling protease activity in wounds transplanted with bioprinted autologous skin grafts. These results demonstrate that bioprinted skin can support skin regeneration to allow for nonfibrotic wound healing and suggest that the skin bioprinting technology may be applicable for human clinical use. Description Bioprinted skin with multiple cell types promotes skin regeneration, vascularization, and epidermal rete ridge formation in full-thickness wounds. Editor’s summary Full-thickness skin wounds are often treated with autologous skin grafting, but this option is limited by the volume of skin that can be harvested. Another treatment option consists of dermal skin substitutes, but results are frequently suboptimal. Here, Jorgensen and colleagues incorporated six human skin cell types into a multilayered skin construct through extrusion bioprinting. In vitro, this construct maintained a three-layer structure and matured appropriately. In mice, the construct accelerated wound healing and promoted neovascularization and extracellular matrix remodeling to reduce fibrosis and scar formation. In pigs, grafting with an autologous porcine bioprinted skin contruct led to increased epithelialization and reduced wound contraction, suggesting that bioprinted skin might be an alternative to treat human full-thickness wounds. —Melissa Norton
Stochastic force inference via density estimation

Inferring dynamical models from low-resolution temporal data continues to be a significant challenge in biophysics, especially within transcriptomics, where separating molecular programs from noise remains an important open problem. We explore a common scenario in which we have access to an adequate amount of cross-sectional samples at a few time-points, and assume that our samples are generated from a latent diffusion process. We propose an approach that relies on the probability flow associated with an underlying diffusion process to infer an autonomous, nonlinear force field interpolating between the distributions. Given a prior on the noise model, we employ score-matching to differentiate the force field from the intrinsic noise. Using relevant biophysical examples, we demonstrate that our approach can extract non-conservative forces from non-stationary data, that it learns equilibrium dynamics when applied to steady-state data, and that it can do so with both additive and multiplicative noise models.
Extracellular DNA enhances biofilm integrity and mechanical properties of mucoid Pseudomonas aeruginosa

ABSTRACT Pseudomonas aeruginosa is one of the most common biofilm-forming pathogens responsible for lung infections of individuals with cystic fibrosis (CF). P. aeruginosa becomes tolerant to antimicrobials in the biofilm state and is difficult to treat. Production of extracellular polymeric substances (EPS), such as alginate and extracellular DNA (eDNA), can allow adherence to abiotic and biotic surfaces, antimicrobial evasion, and resilience to environmental pressures. Alginate-producing mucoid variants of P. aeruginosa are frequently isolated from CF airway samples and are associated with worsening patient outcomes. While eDNA is a major structural component of nonmucoid P. aeruginosa biofilms, the potential role of eDNA in mucoid biofilms is unclear. Here, we investigate how eDNA contributes to clinical mucoid biofilm physiology and integrity. We predicted that eDNA plays a structural and mechanical role in mucoid biofilms. To test this, we quantified biofilm eDNA in mucoid biofilms and used microscopy and rheology to visualize eDNA and detect changes in biofilm structure and mechanics upon DNaseI treatment. We showed that biofilm eDNA abundance is diverse across clinical mucoid strains and observed a temporal increase in foci of eDNA within intact mucoid biofilms. Increased cell dispersal and reduced biomass were also observed following DNaseI treatment of mucoid biofilms. Degradation of eDNA also impacted the mechanical integrity of mucoid biofilms by increasing the stiffness and decreasing the cohesion of the biofilm. These findings advance our understanding of clinical mucoid P. aeruginosa biofilms and facilitate the development of new approaches to target biofilms by exploiting the functions of EPS components. IMPORTANCE Understanding the role of eDNA in mucoid Pseudomonas aeruginosa biofilms will lead to therapeutic strategies that combat the biophysical and structural function of EPS for the eradication of bacteria in mucoid biofilms during chronic infections. This knowledge can be used to further identify unknown matrix component interactions within pathogenic biofilm-forming clinical isolates. Understanding the role of eDNA in mucoid Pseudomonas aeruginosa biofilms will lead to therapeutic strategies that combat the biophysical and structural function of EPS for the eradication of bacteria in mucoid biofilms during chronic infections. This knowledge can be used to further identify unknown matrix component interactions within pathogenic biofilm-forming clinical isolates.
The Contribution of Mutation to Variation in Temperature-Dependent Sprint Speed in Zebrafish, Danio rerio

The contribution of new mutations to phenotypic variation and the consequences of this variation for individual fitness are fundamental concepts for understanding genetic variation and adaptation. Here, we investigated how mutation influenced variation in a complex trait in zebrafish, Danio rerio. Typical of many ecologically relevant traits in ectotherms, swimming speed in fish is temperature dependent, with evidence of adaptive evolution of thermal performance. We chemically induced novel germline point mutations in males and measured sprint speed in their sons at six temperatures (between 16°C and 34°C). Heterozygous mutational effects on speed were strongly positively correlated among temperatures, resulting in statistical support for only a single axis of mutational variation, reflecting temperature-independent variation in speed (faster-slower mode). These results suggest pleiotropic effects on speed across different temperatures; however, spurious correlations arise via linkage or heterogeneity in mutation number when mutations have consistent directional effects on each trait. Here, mutation did not change mean speed, indicating no directional bias in mutational effects. The results contribute to emerging evidence that mutations may predominantly have synergistic cross-environment effects, in contrast to conditionally neutral or antagonistic effects that underpin thermal adaptation. We discuss several aspects of experimental design that may affect resolution of mutations with nonsynergistic effects.
Lithium in bipolar depression: A review of the evidence

Lithium is widely used as treatment of acute mania and as prophylactic therapy for bipolar disorder. International and national guidelines also consider lithium as a possible treatment of acute bipolar depression. Research on the use of lithium in bipolar depression, however, seems to be limited compared to the data available for its efficacy in the other phases of bipolar disorder.
Prism- and basal-plane parallel subgrain boundaries in quartz: a microstructural geothermobarometer

Empirical data on quartz subgrain patterns from various metamorphic rocks show that, at least up to 10 kbar in the stability field of low-quartz, prismatic subgrain boundaries are dominant whereas basal subgrain boundaries are not developed. In the high-quartz stability field, both prismatic and basal subgrain boundaries occur and form typical rectangular (‘chessboard’) patterns. The likely reason behind the different occurrence of these subgrain patterns is that in high-quartz prismatic glide becomes as easy as, or probably even easier than, basal glide. The two types of subgrain patterns can be clearly distinguished by optical microscopy. Consequently, the occurrence of chessboard subgrain patterns in quartz represents a practicable geothermobarometer. The possibilities of its application are far reaching and include the specification of deformation conditions at high-grade metamorphism, the recognition of syntectonic intrusions and the distinction between pluton emplacement at lower and at higher crustal levels.
EV-LFV: Synthesizing Light Field Event Streams from an Event Camera and Multiple RGB Cameras

Light field videos captured in RGB frames (RGB-LFV) can provide users with a 6 degree-of-freedom immersive video experience by capturing dense multi-subview video. Despite its potential benefits, the processing of dense multi-subview video is extremely resource-intensive, which currently limits the frame rate of RGB-LFV (i.e., lower than 30 fps) and results in blurred frames when capturing fast motion. To address this issue, we propose leveraging event cameras, which provide high temporal resolution for capturing fast motion. However, the cost of current event camera models makes it prohibitive to use multiple event cameras for RGB-LFV platforms. Therefore, we propose EV-LFV, an event synthesis framework that generates full multi-subview event-based RGB-LFV with only one event camera and multiple traditional RGB cameras. EV-LFV utilizes spatial-angular convolution, ConvLSTM, and Transformer to model RGB-LFV's angular features, temporal features, and long-range dependency, respectively, to effectively synthesize event streams for RGB-LFV. To train EV-LFV, we construct the first event-to-LFV dataset consisting of 200 RGB-LFV sequences with ground-truth event streams. Experimental results demonstrate that EV-LFV outperforms state-of-the-art event synthesis methods for generating event-based RGB-LFV, effectively alleviating motion blur in the reconstructed RGB-LFV.
Understanding Delay Awareness and Mitigation Mechanisms through an Iterative Design and Evaluation of a Prototype Alert System for Complex Teamwork

Almost half of the preventable deaths in emergency care can be associated with a medical delay. Understanding how clinicians experience delays can lead to improved alert designs to increase delay awareness and mitigation. In this paper, we present the findings from an iterative user-centered design process involving 48 clinicians to develop a prototype alert system for supporting delay awareness in complex medical teamwork such as trauma resuscitation. We used semi-structured interviews and card-sorting workshops to identify the most common delays and elicit design requirements for the prototype alert system. We then conducted a survey to refine the alert designs, followed by near-live, video-guided simulations to investigate clinicians' reactions to the alerts. We contribute to CSCW by designing a prototype alert system to support delay awareness in time-critical, complex teamwork and identifying four mechanisms through which teams mitigate delays.
Understanding Design Collaboration Between Designers and Artificial Intelligence: A Systematic Literature Review

Recent interest in design through the artificial intelligence (AI) lens is rapidly increasing. Designers, as a special user group interacting with AI, have received more attention in the Human-Computer Interaction community. Prior work has discussed emerging challenges that persist in designing for AI. However, few systematic reviews focus on AI for design to understand how designers and AI can augment each other's complementary strengths in design collaboration. In this work, we conducted a landscape analysis of AI for design, via a systematic literature review of 93 papers. The analysis first provides a bird's eye view of overall patterns in this area. The analysis also reveals three themes interpreted from the paper corpus associated with AI for design, including AI assisting designers, designers assisting AI, and characterizing designer-AI collaboration. We discuss the implications of our findings and suggested methodological proposals to guide HCI toward research and practices that center on collaborative creativity.
A methodology to estimate wave‐induced coastal flooding hazard maps in Spain

The purpose of the European Flooding Directive (2007/60/CE) is to establish a European framework for the assessment and management of flood risks. The aim is to reduce the adverse flooding consequences on a wide range of topics such as human health, environmental and cultural heritage, and economic activity. In Spain, coastal zone flood hazard and risk maps are managed by the Environment Spanish Ministry (MAGRAMA, Dirección General para la Sostenibilidad de la Costa y el Mar). These maps are designed using the methodology explained in this paper. This methodology allows to perform quick flood hazard maps along the Spanish coast because of the combination of high‐resolution marine climate databases, state‐of‐the‐art numerical models, innovative data‐mining techniques and statistical models.
"Enjoy, but Moderately!": Designing a Social Companion Robot for Social Engagement and Behavior Moderation in Solitary Drinking Context

Socially assistive robots can support people in making behavior changes by socially engaging in or moderating certain behaviors, such as physical exercise and snacking. However, there has not been much work on designing social robots that aim to support both social engagement and behavior moderation, i.e., offering social interactions for engaging in behaviors without over-engagement. This work explores how social robots can moderate alcohol consumption while socially engaging them in a solitary drinking context. As alcohol consumption can have benefits when done in moderation, this companion robot aims to guide the user toward moderate drinking by using social engagement (i.e., creating an enjoyable atmosphere) and drinking moderation (i.e., regulating the drinking pace). Our preliminary user study (n=20) reveals that the robot is perceived as a friendly companion, and its human-likeness is partly attributed to the robot's intervention. Most participants followed the robot's guidance and perceived it as an intelligent friend due to its social interactions and behavior tracking features. We discuss the benefit of physical interactions for social engagement, utilizing interaction rituals for enjoyable but moderate commensality, and ethical considerations in solitary drinking contexts.
TECTONICS OF ICY SATELLITES DRIVEN BY MELTING AND CRYSTALLIZATION OF WATER BODIES INSIDE THEIR ICE SHELLS

Title of Document: TECTONICS OF ICY SATELLITES DRIVEN BY MELTING AND CRYSTALLIZATION OF WATER BODIES INSIDE THEIR ICE SHELLS Stephanie Ann Johnston, Doctor of Philosophy, 2015 Directed By: Associate Professor Laurent Montési, Department of Geology Enceladus and Europa are icy satellites that currently support bodies of liquid water in the outer solar system Additionally, they show signs of being geologically active. Developing numerical models informed by observations of these icy satellites allows for the development of additional constraints and an improved understanding of the tectonics and evolution of icy satellites. The formation mechanisms for both chaos and ridges on Europa are thought to involve water as albedo changes observed in association with them imply the deposition of salt-rich water near these features. Ridges are the most ubiquitous feature on Europa and are described as central troughs flanked by two raised edifices, range in height from tens to hundreds of meters. Europan ridges can extend hundreds of km continuously along strike but are only about 2 km across. A model of a crystallizing dike–like water intrusion is able to match the overall morphology of ridges, and is consistent the long continuous strike. However, the intrusion of a large volume of water is required to match the most common heights of the ridges. Chaos on Europa is defined as a large area of disrupted ice that contain blocks of pre-existing material separated by a hummocky matrix. A proposed mechanism for the formation of Chaos is that a region of heterogeneous ice within the shell is melted and then recrystallizes. Comparing the model results with the geology of Thera Macula, a region where it has been proposed that Chaos is currently forming, suggests that additional processes may be needed to fully understand the development of Chaos. Water-rich plumes erupt from the south pole of Enceladus, suggesting the presence of a pressurized water reservoir. If a pressurized sea is located beneath the south polar terrain, its geometry and size in the ice shell would contribute to the stress state in the ice shell. The geometry and location of such an ocean, as well as the boundary conditions and thickness of an ice shell have important implications for the faulting and tectonic deformation anticipated at the surface. TECTONICS OF ICY SATELLITES DRIVEN BY MELTING AND CRYSTALLIZATION OF WATER BODIES INSIDE THEIR ICE SHELLS.