ClassCut for Unsupervised Class Segmentation

Abstract. We propose a novel method for unsupervised class segmentation on a set of images. It alternates between segmenting object instances and learning a class model. The method is based on a segmentation energy defined over all images at the same time, which can be optimized efficiently by techniques used before in interactive segmentation. Over iterations, our method progressively learns a class model by integrating observations over all images. In addition to appearance, this model captures the location and shape of the class with respect to an automatically determined coordinate frame common across images. This frame allows us to build stronger shape and location models, similar to those used in object class detection. Our method is inspired by interactive segmentation methods [1], but it is fully automatic and learns models characteristic for the object class rather than specific to one particular object/image. We experimentally demonstrate on the Caltech4, Caltech101, and Weizmann horses datasets that our method (a) transfers class knowledge across images and this improves results compared to segmenting every image independently; (b) outperforms Grabcut [1] for the task of unsupervised segmentation; (c) offers competitive performance compared to the state-of-the-art in unsupervised segmentation and in particular it outperforms the topic model [2].

Image Co-localization by Mimicking a Good Detector's Confidence Score Distribution

Given a set of images containing objects from the same category, the task of image co-localization is to identify and localize each instance. This paper shows that this problem can be solved by a simple but intriguing idea, that is, a common object detector can be learnt by making its detection confidence scores distributed like those of a strongly supervised detector. More specifically, we observe that given a set of object proposals extracted from an image that contains the object of interest, an accurate strongly supervised object detector should give high scores to only a small minority of proposals, and low scores to most of them. Thus, we devise an entropy-based objective function to enforce the above property when learning the common object detector. Once the detector is learnt, we resort to a segmentation approach to refine the localization. We show that despite its simplicity, our approach outperforms state-of-the-art methods.Comment: Accepted to Proc. European Conf. Computer Vision 201

Cycles of Police Reform in Latin America.

yesOver the last quarter century post-conflict and post-authoritarian transitions in Latin America have been accompanied by a surge in social violence, acquisitive crime, and insecurity. These phenomena have been driven by an expanding international narcotics trade, by the long-term effects of civil war and counter-insurgency (resulting in, inter alia, an increased availability of small arms and a pervasive grammar of violence), and by structural stresses on society (unemployment, hyper-inflation, widening income inequality). Local police forces proved to be generally ineffective in preventing, resolving, or detecting such crime and forms of “new violence”3 due to corruption, frequent complicity in criminal networks, poor training and low pay, and the routine use of excessive force without due sanction. Why, then, have governments been slow to prioritize police reform and why have reform efforts borne largely “limited or nonexistent” long-term results? This chapter highlights a number of lessons suggested by various efforts to reform the police in Latin America over the period 1995-2010 . It focuses on two clusters of countries in Latin America. One is Brazil and the Southern Cone countries (Chile, Argentina, and Uruguay), which made the transition to democracy from prolonged military authoritarian rule in the mid- to late 1980s. The other is Central America and the Andean region (principally El Salvador, Guatemala, Honduras, Peru, and Colombia), which emerged/have been emerging from armed conflict since the mid- 1990s. The chapter examines first the long history of international involvement in police and security sector reform in order to identify long-run tropes and path dependencies. It then focuses on a number of recurring themes: cycles of de- and re-militarization of the policing function; the “security gap” and “democratization dilemmas” involved in structural reforms; the opportunities offered by decentralization for more community-oriented police; and police capacity to resist reform and undermine accountability mechanisms

The disruption of proteostasis in neurodegenerative diseases

Cells count on surveillance systems to monitor and protect the cellular proteome which, besides being highly heterogeneous, is constantly being challenged by intrinsic and environmental factors. In this context, the proteostasis network (PN) is essential to achieve a stable and functional proteome. Disruption of the PN is associated with aging and can lead to and/or potentiate the occurrence of many neurodegenerative diseases (ND). This not only emphasizes the importance of the PN in health span and aging but also how its modulation can be a potential target for intervention and treatment of human diseases.info:eu-repo/semantics/publishedVersio

Comparison of carbon and water fluxes and the drivers of ecosystem water use efficiency in a temperate rainforest and a peatland in southern South America

The variability and drivers of carbon and water fluxes and their relationship to ecosystem water use efficiency (WUE) in natural ecosystems of southern South America are still poorly understood. For 8 years (2015–2022), we measured carbon dioxide net ecosystem exchange (NEE) and evapotranspiration (ET) using eddy covariance towers in a temperate rainforest and a peatland in southern Chile. NEE was partitioned into gross primary productivity (GPP) and ecosystem respiration (Reco), while ET was partitioned into evaporation (E) and transpiration (T) and used to estimate different expressions of ecosystem WUE. We then used the correlation between detrended time series and structural equation modelling to identify the main environmental drivers of WUE, GPP, ET, E and T. The results showed that the forest was a consistent carbon sink (−486 ± 23 g C m−2 yr−1), while the peatland was, on average, a small source (33 ± 21 g C m−2 yr−1). WUE is low in both ecosystems and likely explained by the high annual precipitation in this region (∼ 2100 mm). Only expressions of WUE that included atmospheric water demand showed seasonal variation. Variations in WUE were related more to changes in ET than to changes in GPP, while T remained relatively stable, accounting for around 47 % of ET for most of the study period. For both ecosystems, E increased with higher global radiation and higher surface conductance and when the water table was closer to the surface. Higher values for E were also found with increased wind speeds in the forest and higher air temperatures in the peatland. The absence of a close relationship between ET and GPP is likely related to the dominance of plant species that either do not have stomata (i.e. mosses in the peatland or epiphytes in the forest) or have poor stomatal control (i.e. anisohydric tree species in the forest). The observed increase in potential ET in the last 2 decades and the projected drought in this region suggests that WUE could increase in these ecosystems, particularly in the forest, where stomatal control may be more significant.</p

Review article: Drought as a continuum – memory effects in interlinked hydrological, ecological, and social systems

Droughts are often long-lasting phenomena, without a distinct start or end and with impacts cascading across sectors and systems, creating long-term legacies. Nevertheless, our current perceptions and management of droughts and their impacts are often event-based, which can limit the effective assessment of drought risks and reduction of drought impacts. Here, we advocate for changing this perspective and viewing drought as a hydrological–ecological–social continuum. We take a systems theory perspective and focus on how “memory” causes feedback and interactions between parts of the interconnected systems at different timescales. We first discuss the characteristics of the drought continuum with a focus on the hydrological, ecological, and social systems separately, and then we study the system of systems. Our analysis is based on a review of the literature and a study of five cases: Chile, the Colorado River basin in the USA, northeast Brazil, Kenya, and the Rhine River basin in northwest Europe. We find that the memories of past dry and wet periods, carried by both bio-physical (e.g. groundwater, vegetation) and social systems (e.g. people, governance), influence how future drought risk manifests. We identify four archetypes of drought dynamics: impact and recovery, slow resilience building, gradual collapse, and high resilience–big shock. The interactions between the hydrological, ecological, and social systems result in systems shifting between these types, which plays out differently in the five case studies. We call for more research on drought preconditions and recovery in different systems, on dynamics cascading between systems and triggering system changes, and on dynamic vulnerability and maladaptation. Additionally, we advocate for more continuous monitoring of drought hazards and impacts, modelling tools that better incorporate memories and adaptation responses, and management strategies that increase societal and institutional memory. This will help us to better deal with the complex hydrological–ecological–social drought continuum and identify effective pathways to adaptation and mitigation

Search for Light Dark Matter with NA64 at CERN

Thermal dark matter models with particle χ masses below the electroweak scale can provide an explanation for the observed relic dark matter density. This would imply the existence of a new feeble interaction between the dark and ordinary matter. We report on a new search for the sub-GeV χ production through the interaction mediated by a new vector boson, called the dark photon A′, in collisions of 100 GeV electrons with the active target of the NA64 experiment at the CERN SPS. With 9.37×1011 electrons on target collected during 2016-2022 runs NA64 probes for the first time the well-motivated region of parameter space of benchmark thermal scalar and fermionic dark matter models. No evidence for dark matter production has been found. This allows us to set the most sensitive limits on the A′ couplings to photons for masses mA′≲0.35 GeV, and to exclude scalar and Majorana dark matter with the χ-A′ coupling αD≤0.1 for masses 0.001≲mχ≲0.1 GeV and 3mχ≤mA′

Myo-Guide: A Machine Learning-Based Web Application for Neuromuscular Disease Diagnosis With MRI

\ua9 2025 The Author(s). Journal of Cachexia, Sarcopenia and Muscle published by Wiley Periodicals LLC.Background: Neuromuscular diseases (NMDs) are rare disorders characterized by progressive muscle fibre loss, leading to replacement by fibrotic and fatty tissue, muscle weakness and disability. Early diagnosis is critical for therapeutic decisions, care planning and genetic counselling. Muscle magnetic resonance imaging (MRI) has emerged as a valuable diagnostic tool by identifying characteristic patterns of muscle involvement. However, the increasing complexity of these patterns complicates their interpretation, limiting their clinical utility. Additionally, multi-study data aggregation introduces heterogeneity challenges. This study presents a novel multi-study harmonization pipeline for muscle MRI and an AI-driven diagnostic tool to assist clinicians in identifying disease-specific muscle involvement patterns. Methods: We developed a preprocessing pipeline to standardize MRI fat content across datasets, minimizing source bias. An ensemble of XGBoost models was trained to classify patients based on intramuscular fat replacement, age at MRI and sex. The SHapley Additive exPlanations (SHAP) framework was adapted to analyse model predictions and identify disease-specific muscle involvement patterns. To address class imbalance, training and evaluation were conducted using class-balanced metrics. The model\u27s performance was compared against four expert clinicians using 14 previously unseen MRI scans. Results: Using our harmonization approach, we curated a dataset of 2961 MRI samples from genetically confirmed cases of 20 paediatric and adult NMDs. The model achieved a balanced accuracy of 64.8% \ub1 3.4%, with a weighted top-3 accuracy of 84.7% \ub1 1.8% and top-5 accuracy of 90.2% \ub1 2.4%. It also identified key features relevant for differential diagnosis, aiding clinical decision-making. Compared to four expert clinicians, the model obtained the highest top-3 accuracy (75.0% \ub1 4.8%). The diagnostic tool has been implemented as a free web platform, providing global access to the medical community. Conclusions: The application of AI in muscle MRI for NMD diagnosis remains underexplored due to data scarcity. This study introduces a framework for dataset harmonization, enabling advanced computational techniques. Our findings demonstrate the potential of AI-based approaches to enhance differential diagnosis by identifying disease-specific muscle involvement patterns. The developed tool surpasses expert performance in diagnostic ranking and is accessible to clinicians worldwide via the Myo-Guide online platform

Un examen actualizado de la percepción de las barreras para la implementación de la farmacogenómica y la utilidad de los pares fármaco/gen en América Latina y el Caribe

La farmacogenómica (PGx) se considera un campo emergente en los países en desarrollo. La investigación sobre PGx en la región de América Latina y el Caribe (ALC) sigue siendo escasa, con información limitada en algunas poblaciones. Por lo tanto, las extrapolaciones son complicadas, especialmente en poblaciones mixtas. En este trabajo, revisamos y analizamos el conocimiento farmacogenómico entre la comunidad científica y clínica de ALC y examinamos las barreras para la aplicación clínica. Realizamos una búsqueda de publicaciones y ensayos clínicos en este campo en todo el mundo y evaluamos la contribución de ALC. A continuación, realizamos una encuesta regional estructurada que evaluó una lista de 14 barreras potenciales para la aplicación clínica de biomarcadores en función de su importancia. Además, se analizó una lista emparejada de 54 genes/fármacos para determinar una asociación entre los biomarcadores y la respuesta a la medicina genómica. Esta encuesta se comparó con una encuesta anterior realizada en 2014 para evaluar el progreso en la región. Los resultados de la búsqueda indicaron que los países de América Latina y el Caribe han contribuido con el 3,44% del total de publicaciones y el 2,45% de los ensayos clínicos relacionados con PGx en todo el mundo hasta el momento. Un total de 106 profesionales de 17 países respondieron a la encuesta. Se identificaron seis grandes grupos de obstáculos. A pesar de los continuos esfuerzos de la región en la última década, la principal barrera para la implementación de PGx en ALC sigue siendo la misma, la "necesidad de directrices, procesos y protocolos para la aplicación clínica de la farmacogenética/farmacogenómica". Las cuestiones de coste-eficacia se consideran factores críticos en la región. Los puntos relacionados con la reticencia de los clínicos son actualmente menos relevantes. Según los resultados de la encuesta, los pares gen/fármaco mejor clasificados (96%-99%) y percibidos como importantes fueron CYP2D6/tamoxifeno, CYP3A5/tacrolimus, CYP2D6/opioides, DPYD/fluoropirimidinas, TMPT/tiopurinas, CYP2D6/antidepresivos tricíclicos, CYP2C19/antidepresivos tricíclicos, NUDT15/tiopurinas, CYP2B6/efavirenz y CYP2C19/clopidogrel. En conclusión, aunque la contribución global de los países de ALC sigue siendo baja en el campo del PGx, se ha observado una mejora relevante en la región. La percepción de la utilidad de las pruebas PGx en la comunidad biomédica ha cambiado drásticamente, aumentando la concienciación entre los médicos, lo que sugiere un futuro prometedor en las aplicaciones clínicas de PGx en ALC.Pharmacogenomics (PGx) is considered an emergent field in developing countries. Research on PGx in the Latin American and the Caribbean (LAC) region remains scarce, with limited information in some populations. Thus, extrapolations are complicated, especially in mixed populations. In this paper, we reviewed and analyzed pharmacogenomic knowledge among the LAC scientific and clinical community and examined barriers to clinical application. We performed a search for publications and clinical trials in the field worldwide and evaluated the contribution of LAC. Next, we conducted a regional structured survey that evaluated a list of 14 potential barriers to the clinical implementation of biomarkers based on their importance. In addition, a paired list of 54 genes/drugs was analyzed to determine an association between biomarkers and response to genomic medicine. This survey was compared to a previous survey performed in 2014 to assess progress in the region. The search results indicated that Latin American and Caribbean countries have contributed 3.44% of the total publications and 2.45% of the PGx-related clinical trials worldwide thus far. A total of 106 professionals from 17 countries answered the survey. Six major groups of barriers were identified. Despite the region’s continuous efforts in the last decade, the primary barrier to PGx implementation in LAC remains the same, the “need for guidelines, processes, and protocols for the clinical application of pharmacogenetics/pharmacogenomics”. Cost-effectiveness issues are considered critical factors in the region. Items related to the reluctance of clinicians are currently less relevant. Based on the survey results, the highest ranked (96%–99%) gene/drug pairs perceived as important were CYP2D6/tamoxifen, CYP3A5/tacrolimus, CYP2D6/opioids, DPYD/fluoropyrimidines, TMPT/thiopurines, CYP2D6/tricyclic antidepressants, CYP2C19/tricyclic antidepressants, NUDT15/thiopurines, CYP2B6/efavirenz, and CYP2C19/clopidogrel. In conclusion, although the global contribution of LAC countries remains low in the PGx field, a relevant improvement has been observed in the region. The perception of the usefulness of PGx tests in biomedical community has drastically changed, raising awareness among physicians, which suggests a promising future in the clinical applications of PGx in LAC