Miracle-dz/UniFAR-FTUs huggingface dataset:
Measuring tropical rainforest resilience under non-Gaussian disturbances

The Amazon rainforest is considered one of the Earth's tipping elements and may lose stability under ongoing climate change. Recently a decrease in tropical rainforest resilience has been identified globally from remotely sensed vegetation data. However, the underlying theory assumes a Gaussian distribution of forest disturbances, which is different from most observed forest stressors such as fires, deforestation, or windthrow. Those stressors often occur in power-law-like distributions and can be approximated by α-stable Lévy noise. Here, we show that classical critical slowing down indicators to measure changes in forest resilience are robust under such power-law disturbances. To assess the robustness of critical slowing down indicators, we simulate pulse-like perturbations in an adapted and conceptual model of a tropical rainforest. We find few missed early warnings and few false alarms are achievable simultaneously if the following steps are carried out carefully: First, the model must be known to resolve the timescales of the perturbation. Second, perturbations need to be filtered according to their absolute temporal autocorrelation. Third, critical slowing down has to be assessed using the non-parametric Kendall-τ slope. These prerequisites allow for an increase in the sensitivity of early warning signals. Hence, our findings imply improved reliability of the interpretation of empirically estimated rainforest resilience through critical slowing down indicators.
Evaluation of various relationships of reaeration rate coefficient for modeling dissolved oxygen in a river with extreme flow variations in Pakistan

Mathematical relationships have been developed for reaeration rate coefficient (Ka) by various researchers. These relationships have a number of variables such as depth, velocity, width, slope, Froud number, molecular diffusion coefficient, kinematic viscosity and the gas‐transfer Reynolds number. From these variables, 29 relations have been developed and divided into four groups. To evaluate their predictive capability for highly variable flow rivers receiving high pollution loads form large cities, these relationships have been used to model dissolved oxygen (DO) in the River Ravi. Such rivers are either saturated with DO during high flows or anaerobic during critical low‐flow conditions. The evaluation is based on the agreement between model DO values calculated using Ka obtained from the available equations and the measured DO concentrations in the river samples in terms of sum of square of residuals (SSR) and coefficient of determination (R2). It has been found that in general, the group of equations containing depth and velocity as the only two variables affecting Ka performed better than the equations in other groups as reflected by lower SSR and higher R2 values. The study results also reveal that the turbulence‐based reaeration rate coefficient equation containing additional variables also resulted in close agreement between DO model results and the measured values. The study results identify the most important parameters affecting the reaeration rate coefficient and the suitability of various Ka relationships as well for rivers with highly variable flows. Copyright © 2012 John Wiley & Sons, Ltd.
The most stringent upper limit from dynamical models on the mass of a central black hole in 47 Tucanae

Globular clusters (GCs) were proposed as promising sites for discovering intermediate-mass black holes (IMBHs), possibly providing crucial insights into the formation and evolution of these elusive objects. The Galactic GC 47 Tucanae (also known as NGC 104) has been suggested as a potential IMBH host, but, previous studies have yielded conflicting results. We, therefore, present self-consistent dynamical models based on distribution functions (DFs) that depend on action integrals to assess the presence (or absence) of an IMBH in 47 Tucanae. Leveraging state-of-the-art Multi Unit Spectroscopic Explorer and Hubble Space Telescope data, we analyzed the three-dimensional (3D) kinematics of the cluster's central regions, fitting individual star velocities down to the sub-arcsec scale (approximately $10^{-2}$ pc). According to our analysis, the inner kinematics of 47 Tucanae is incompatible with a central BH more massive than 578 M$_\odot$ (at $3\sigma$). This is the most stringent upper limit on the mass of a putative IMBH in 47 Tucanae that has been put by any dynamical study.
On-chip topological transport of optical frequency combs in silicon-based valley photonic crystals

The generation and control of optical frequency combs in integrated photonic systems enables complex, high-controllable, and large-scale devices. In parallel, harnessing topological physics in multipartite systems has allowed them with compelling features such as robustness against fabrication imperfections. Here we experimentally demonstrate on-chip topological transport for optical frequency combs at telecommunication wavelengths, both in classical and nonclassical domains. We access both the quantum frequency combs and dissipative Kerr soliton combs with a micro-resonator. The quantum frequency comb, that is, a coherent superposition of multiple frequency modes, is proven to be a frequency-entangled qudit state. We also show that dissipative Kerr soliton combs are highly coherent and mode-locked due to the collective coherence or self-organization of solitons. Moreover, the valley kink states allow both quantum frequency combs and dissipative Kerr soliton combs with robustness against sharp bends. Our topologically protected optical frequency combs could enable the inherent robustness in integrated complex photonic systems.
Function Vectors in Large Language Models

We report the presence of a simple neural mechanism that represents an input-output function as a vector within autoregressive transformer language models (LMs). Using causal mediation analysis on a diverse range of in-context-learning (ICL) tasks, we find that a small number attention heads transport a compact representation of the demonstrated task, which we call a function vector (FV). FVs are robust to changes in context, i.e., they trigger execution of the task on inputs such as zero-shot and natural text settings that do not resemble the ICL contexts from which they are collected. We test FVs across a range of tasks, models, and layers and find strong causal effects across settings in middle layers. We investigate the internal structure of FVs and find while that they often contain information that encodes the output space of the function, this information alone is not sufficient to reconstruct an FV. Finally, we test semantic vector composition in FVs, and find that to some extent they can be summed to create vectors that trigger new complex tasks. Our findings show that compact, causal internal vector representations of function abstractions can be explicitly extracted from LLMs. Our code and data are available at https://functions.baulab. info.
Early Planet Formation in Embedded Disks (eDisk). X. Compact Disks, Extended Infall, and a Fossil Outburst in the Class I Oph IRS43 Binary

We present the first results from the Early Planet Formation in Embedded Disks Atacama Large Millimeter/submillimeter Array Large Program toward Oph IRS43, a binary system of solar mass protostars. The 1.3 mm dust continuum observations resolve a compact disk, ∼6 au radius, around the northern component and show that the disk around the southern component is even smaller, ≲3 au. CO, 13CO, and C18O maps reveal a large cavity in a low-mass envelope that shows kinematic signatures of rotation and infall extending out to ∼2000 au. An expanding CO bubble centered on the extrapolated location of the source ∼130 yr ago suggests a recent outburst. Despite the small size of the disks, the overall picture is of a remarkably large and dynamically active region.
Modelling the impacts of male alternative reproductive tactics on population dynamics

Observations of male alternative reproductive tactics (ARTs) in a variety of species have stimulated the development of mathematical models that can account for the evolution and stable coexistence of multiple male phenotypes. However, little attention has been given to the population dynamic consequences of ARTs. We present a population model that takes account of the existence of two male ARTs (guarders and sneakers), assuming that tactic frequencies are environmentally determined and tactic reproductive success depends on the densities of both types. The presence of sneakers typically increases overall population density. However, if sneakers comprise a sufficiently large proportion of the population—or, equivalently, if guarders are sufficiently rare—then it is possible for the total population to crash to extinction (in this extreme regime, there is also an Allee effect, i.e. a threshold density below which the population will go extinct). We apply the model to the example of the invasive round goby (Neogobius melanostomus). We argue that ARTs can dramatically influence population dynamics and suggest that considering such phenotypic plasticity in population models is potentially important, especially for species of conservation or commercial importance.
Validation of Language Agnostic Models for Discourse Marker Detection

Using language models to detect or predict the presence of language phenomena in the text has become a mainstream research topic. With the rise of generative models, experiments using deep learning and transformer models trigger intense interest. Aspects like precision of predictions, portability to other languages or phenomena, scale have been central to the research community. Discourse markers, as language phenomena, perform important functions, such as signposting, signalling, and rephrasing, by facilitating discourse organization. Our paper is about discourse markers detection, a complex task as it pertains to a language phenomenon manifested by expressions that can occur as content words in some contexts and as discourse markers in others. We have adopted language agnostic model trained in English to predict the discourse marker presence in texts in 8 other unseen by the model languages with the goal to evaluate how well the model performs in different structure and lexical properties languages. We report on the process of evaluation and validation of the model’s performance across European Portuguese, Hebrew, German, Polish, Romanian, Bulgarian, Mace-donian, and Lithuanian and about the results of this validation. This research is a key step towards multilingual language processing.
Towards ELTeC-LLOD: European Literary Text Collection Linguistic Linked Open Data

This paper describes a case study on the generation of Linked Data text corpora using the NLP Interchange Format (NIF). The ELTEC corpus subset, which consists of 900 novels from the period 1840-1920 for 9 European languages, served as the basis for this research. The annotated version of the novels, in the so-called TEI level-2 format, was transformed into NIF, an RDF/OWL-based format that aims to achieve interoperability between NLP tools, language resources, and annotations. In this paper, we present our approach for transformation, and the implemented pipeline, and offer the code and results for similar use cases.
Clinical pharmacy as a guarantee of safety in times of crisis: evolution and relevance of the continued presence of clinical pharmacists in frontline medical units during the first wave of COVID-19

Background The COVID-19 pandemic has had a major impact on the organisation of health services worldwide. In the first wave, many therapeutic options were explored, exposing patients to significant iatrogenic risk. In a context in which patient management was not well defined by clear recommendations and in which healthcare professionals were under great stress, was it still relevant to maintain pharmaceutical care or did it bring an additional factor of disorganisation? Objective The aim of our study was to compare the relevance of pharmaceutical care practices before and during the COVID-19 crisis. Methods A retrospective, comparative, observational analysis was conducted in two medical units in a French university hospital that were receiving patients with COVID-19 and benefiting from pharmaceutical care prior to the crisis. This study compared clinical pharmacy performance between two 1.5-month periods before and during the COVID-19 crisis. Performance was assessed according to the CLEO scale, rating the clinical, economic and organisational impacts of the accepted pharmaceutical interventions (PIs) performed in these units. Results Of the 675 accepted PIs carried out in the two medical units over the entire study period, PIs performed during the COVID-19 period had a greater significant clinical impact (72% vs 56%, p˂0.0001), a more positive economic impact (38% vs 23%, p˂0.0001) and a more favourable organisational impact (52% vs 20%, p˂0.0001) than those performed prior to the COVID-19 period. Conclusions The health crisis generated important changes in care practices. Our study demonstrates the sustained relevance of pharmaceutical care during a health crisis. This local experience confirms the major interest in improving the integration of pharmaceutical expertise within French healthcare teams.
Predictors of transitioning to adult mental health services and associated costs: a cross-country comparison

Background Young people are at risk of falling through the care gap after leaving child and adolescent mental health services (CAMHS) despite an ongoing need for mental health support. Currently, little is known about the predictors of transitioning to adult mental health services (AMHS), and associated healthcare and societal costs as young people cross the transition boundary. Objective To conduct a secondary data analysis exploring predictors of transitioning or falling through the gap and associated costs. Methods Data were used from a longitudinal study, which followed young people from seven European countries for 2 years after reaching their CAMHS boundary. Predictors of transitioning (including sociodemographic and clinical variables) and longitudinal resource use were compared for 488 young people who transitioned to AMHS versus those who fell through the gap. Findings Young people were more likely to transition to AMHS if they were severely ill. Those from Italy, the Netherlands and the UK were more likely to fall through the gap than transition to AMHS. Healthcare costs fell for all young people over the study, with a sharper decrease for those who fell through the gap. Conclusions Total healthcare costs fell for all participants, indicating that the intensity of mental health support reduces for all young people as they cross the CAMHS boundary, regardless of clinical need. Clinical implications It is important that alternative forms of mental health support are available for young people who do not meet the AMHS care threshold but still have mental health needs after leaving CAMHS.
Criterion-based Heterogeneous Collaborative Filtering for Multi-behavior Implicit Recommendation

XIAO LUO, Department of Computer Science, University of California, Los Angeles, USA DAQING WU, School of Mathematical Sciences, Peking University, China YIYANG GU, National Key Laboratory for Multimedia Information Processing, School of Computer Science, Peking University, China CHONG CHEN, Terminus Group, China LUCHEN LIU, National Key Laboratory for Multimedia Information Processing, School of Computer Science, Peking University, China JINWEN MA, School of Mathematical Sciences, Peking University, China MING ZHANG, National Key Laboratory for Multimedia Information Processing, School of Computer Science, Peking University, China MINGHUA DENG, School of Mathematical Sciences, Peking University, China JIANQIANG HUANG, Nanyang Technological University, Singapore XIAN-SHENG HUA, Terminus Group, China
"Do touch!" - 3D Scanning and Printing Technologies for the Haptic Representation of Cultural Assets: A Study with Blind Target Users

Visiting museums can be challenging for visually impaired people, as many objects are hidden behind glass walls and information is limited to descriptions. One of the best ways to increase accessibility and inclusion in museums and other cultural heritage institutions is through the use of 3D-printed replicas. However, there are several different scanning and printing processes that not only differ in terms of effort and cost but can also produce very different results. This paper evaluates two different scanning techniques and four different printing processes in terms of these aspects and includes feedback from a group of blind and partially sighted users on the aesthetic quality and fidelity of the printed objects. We found differences between the scanning methods mainly regarding their ease of use. Of the printing methods tested, stereolithography was preferred by the majority of participants for use in the museum. Additionally, we include user comments which touch on the general aspects of presenting museum artefacts using haptic devices. Our study thus provides valuable insights into the preferences of the target users, which can be used to inform decisions about more inclusive museum experiences.
Beyond Built Year Prediction: The Bag of Time Model and a Case Study of Buddha Images

In this work, we propose a novel approach to the dating of cultural heritage objects using a bag-of-time (BoT) model, which combines visual and temporal information. The BoT model extends the traditional bag-of-words (BoW) representation, allowing multiple cultural elements in an image to be associated with different time points. We introduce the concept of cultural elements as stable and distinct data patterns, enabling the BoT model to encode time information efficiently. Furthermore, we present an aggregated bag-of-time (ABoT) model that captures the temporal distribution of image contents. Our experiments on a Buddha image dataset demonstrate the effectiveness of the proposed approach in predicting built years and enabling fine-grained dating. Additionally, we explore the applications of multi-modal image retrieval and time-based visualization, showcasing the versatility of our models in cultural heritage research and analysis.
SniffyArt: The Dataset of Smelling Persons

Smell gestures play a crucial role in the investigation of past smells in the visual arts yet their automated recognition poses significant challenges. This paper introduces the SniffyArt dataset, consisting of 1941 individuals represented in 441 historical artworks. Each person is annotated with a tightly fitting bounding box, 17 pose keypoints, and a gesture label. By integrating these annotations, the dataset enables the development of hybrid classification approaches for smell gesture recognition. The dataset's high-quality human pose estimation keypoints are achieved through the merging of five separate sets of keypoint annotations per person. The paper also presents a baseline analysis, evaluating the performance of representative algorithms for detection, keypoint estimation, and classification tasks, showcasing the potential of combining keypoint estimation with smell gesture classification. The SniffyArt dataset lays a solid foundation for future research and the exploration of multi-task approaches leveraging pose keypoints and person boxes to advance human gesture and olfactory dimension analysis in historical artworks.
Video Referring Expression Comprehension via Transformer with Content-conditioned Query

Video Referring Expression Comprehension (REC) aims to localize a target object in videos based on the queried natural language. Recent improvements in video REC have been made using Transformer-based methods with learnable queries. However, we contend that this naive query design is not ideal given the open-world nature of video REC brought by text supervision. With numerous potential semantic categories, relying on only a few slowupdated queries is insufficient to characterize them. Our solution to this problem is to create dynamic queries that are conditioned on both the input video and language to model the diverse objects referred to. Specifically, we place a fixed number of learnable bounding boxes throughout the frame and use corresponding region features to provide prior information. Also, we noticed that current query features overlook the importance of cross-modal alignment. To address this, we align specific phrases in the sentence with semantically relevant visual areas, annotating them in existing video datasets (VID-Sentence and VidSTG). By incorporating these two designs, our proposed model (called ConFormer) outperforms other models on widely benchmarked datasets. For example, in the testing split of VID-Sentence dataset, ConFormer achieves 8.75% absolute improvement on Accu. @0.6 compared to the previous state-of-the-art model.
Measuring the Urban Expansion Process of Yogyakarta City in Indonesia:Urban expansion process and spatial and temporal characteristics of growing cities

: Urbanization patterns in rapidly growing cities are complex. Such patterns reflect historic policy outcomes, economic characteristics and changing lifestyles. This research examined urban growth in Yogyakarta City in Indonesia to understand its urban expansion process. Several attributes of urbanization were measured to understand the city’s urbanization pattern. Land-use data for 1997, 2002, and 2013 were derived from remote-sensing data; in addition, other supporting data of urbanization were measured with several spatial metrics. Analysis was performed for the whole city and for transections across the city to understand macro and local scale characteristics of the urbanization process. Urban land-use changes between 2002 and 2013 were studied to understand the land-use conversion process. Thereafter, the measurements were analyzed to understand temporal and spatial characteristics of urbanization in Yogyakarta City. It was observed that the urban expansion process in Yogyakarta has several distinct stages. Essentially, in the periphery of the city, urbanization has been fragmented. Over time, these fragmented urban patches develop into stable and less complex shapes.
New insects (Paoliida, Dictyoptera) from the Carboniferous outcrop of Tante Victoire in Var, France

Abstract We introduce a novel paoliid, Carbonidelia gallica gen. et sp. nov., which may share close affinities with the ‘ideliid’ genus Sojanidelia Storozhenko, 1992. This new taxon is described from Gzhelian strata exposed at Tante Victoire in Var, France. Additionally, we present a remarkably well-preserved forewing from the same outcrop belonging to the phyloblattid genus and species Anthracoblattina ensifer cf. ‘variety desguini’. This species was previously known from the Gzhelian of Commentry in Allier, France. Therefore, this finding strengthens the Gzhelian age derived from the study of the palaeoflora at this outcrop. In this study, we also briefly delve into the inter- and intraspecific variability in the forewing venation of the ‘Anthracoblattina gigantea-ensifera group’. Furthermore, we challenge the classification of two Mesozoic roachoids, Sobytie tungusicum Vršanský, 2010 and Pozabudnutie antiquorum Hinkelman and Vršanský, 2022, which, in our view, do not belong to the Phyloblattidae family. Instead, they should be regarded as Dictyoptera of uncertain family affinities. A comprehensive revision of these species will be necessary to establish their precise taxonomic positions. André Nel [ anel@mnhn.fr ], Romain Garrouste [ romain.garrouste@mnhn.fr ], Corentin Jouault [ jouaultc0@gmail.com ], Institut de Systématique, Évolution, Biodiversité (ISYEB) Muséum national d’Histoire naturelle, CNRS, Sorbonne Université, EPHE, Université des Antilles, CP50, 45 rue Buffon 75005, Paris, France; Univ. Rennes, CNRS, Géosciences Rennes, UMR 6118, F-35000, Rennes, France; Institut des Sciences de l’Évolution (UMR 5554), Université de Montpellier, CNRS, F-34095 Montpellier, France.