VideoAgent: Long-form Video Understanding with Large Language Model as Agent

Long-form video understanding represents a significant challenge within computer vision, demanding a model capable of reasoning over long multi-modal sequences. Motivated by the human cognitive process for long-form video understanding, we emphasize interactive reasoning and planning over the ability to process lengthy visual inputs. We introduce a novel agent-based system, VideoAgent, that employs a large language model as a central agent to iteratively identify and compile crucial information to answer a question, with vision-language foundation models serving as tools to translate and retrieve visual information. Evaluated on the challenging EgoSchema and NExT-QA benchmarks, VideoAgent achieves 54.1% and 71.3% zero-shot accuracy with only 8.4 and 8.2 frames used on average. These results demonstrate superior effectiveness and efficiency of our method over the current state-of-the-art methods, highlighting the potential of agent-based approaches in advancing long-form video understanding

The Biodiversity of the Mediterranean Sea: Estimates, Patterns, and Threats

The Mediterranean Sea is a marine biodiversity hot spot. Here we combined an extensive literature analysis with expert opinions to update publicly available estimates of major taxa in this marine ecosystem and to revise and update several species lists. We also assessed overall spatial and temporal patterns of species diversity and identified major changes and threats. Our results listed approximately 17,000 marine species occurring in the Mediterranean Sea. However, our estimates of marine diversity are still incomplete as yet—undescribed species will be added in the future. Diversity for microbes is substantially underestimated, and the deep-sea areas and portions of the southern and eastern region are still poorly known. In addition, the invasion of alien species is a crucial factor that will continue to change the biodiversity of the Mediterranean, mainly in its eastern basin that can spread rapidly northwards and westwards due to the warming of the Mediterranean Sea. Spatial patterns showed a general decrease in biodiversity from northwestern to southeastern regions following a gradient of production, with some exceptions and caution due to gaps in our knowledge of the biota along the southern and eastern rims. Biodiversity was also generally higher in coastal areas and continental shelves, and decreases with depth. Temporal trends indicated that overexploitation and habitat loss have been the main human drivers of historical changes in biodiversity. At present, habitat loss and degradation, followed by fishing impacts, pollution, climate change, eutrophication, and the establishment of alien species are the most important threats and affect the greatest number of taxonomic groups. All these impacts are expected to grow in importance in the future, especially climate change and habitat degradation. The spatial identification of hot spots highlighted the ecological importance of most of the western Mediterranean shelves (and in particular, the Strait of Gibraltar and the adjacent Alboran Sea), western African coast, the Adriatic, and the Aegean Sea, which show high concentrations of endangered, threatened, or vulnerable species. The Levantine Basin, severely impacted by the invasion of species, is endangered as well

Systemic hormonal and physiological abnormalities in anxiety disorders

Among the studies of systemic hormonal and physiological abnormalities associated with anxiety disorders, the most consistent and extensive findings suggest (a) peripheral adrenergic hyperactivity (including increases in norepinephrine but not epinephrine) and functional dysregulation, (b) increased incidence of mitral valve prolapse in panic patients, and (c) normal suppressibility of the hypothalamic-pituitary-adrenal cortical endocrine system with dexamethasone in panic patients. Other less-certain findings include (a) increased circulating concentrations of plasma ACTH and/or cortisol, and prolactin, in panic patients, (b) increased platelet monoamine oxidase activity in generalized anxiety and/or panic patients, (c) decreased gonadal axis activity in some anxious individuals, (d) decreased nighttime melatonin plasma concentrations in panic patients, and (e) peripheral [alpha]2 and [beta]-adrenoreceptor down-regulation, with normal serotonin binding parameters. These findings, taken together, provide tentative support for dysfunction in adrenergic and GABAergic central nervous system mechanisms in people with anxiety disorders. Abnormal anxiety and normal stress both show evidence of adrenergic hyperactivity; however, there appear to be differences in hormonal profiles, especially the apparent lack of increase of epinephrine during panic attacks, as well as differences in the reactivity of the system, and in the "trigger" mechanisms which determine when the response occurs.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/27526/1/0000570.pd

MAMBA: an Effective World Model Approach for Meta-Reinforcement Learning

Meta-reinforcement learning (meta-RL) is a promising framework for tackling challenging domains requiring efficient exploration. Existing meta-RL algorithms are characterized by low sample efficiency, and mostly focus on low-dimensional task distributions. In parallel, model-based RL methods have been successful in solving partially observable MDPs, of which meta-RL is a special case. In this work, we leverage this success and propose a new model-based approach to meta-RL, based on elements from existing state-of-the-art model-based and meta-RL methods. We demonstrate the effectiveness of our approach on common meta-RL benchmark domains, attaining greater return with better sample efficiency (up to $15\times$) while requiring very little hyperparameter tuning. In addition, we validate our approach on a slate of more challenging, higher-dimensional domains, taking a step towards real-world generalizing agents

Synthesis, characterization, and humidity-responsiveness of guar gum xanthate and its nanocomposite with copper sulfide covellite

A novel conjugation of guar gum with xanthate groups via facile aqueous xanthation reaction has been reported. Density of grafted xanthate on guar gum product (GG-X) is as high as 4.4%, thus GG-X is conceivably characterized and confirmed by various spectrometric, electrochemical, thermogravimetric, and microscopic methods. Complexation of GG-X with numerous borderline and soft metal ions (e.g. Fe2+, Co2+, Ni2+, Cu2+, Pb2+, Pt2+ and Cd2+) yields hydrophilic gel-like materials and shows good agreement with hard and soft acid and base (HSAB) theory. This indicates tremendous potential of GG-X in metal ion extraction, removal and hydrogel cross-linking. GG-X is also employed to formulate an aqueous colloidal dispersion of copper sulfide covellite (GG-X/CuS) nanocomposites. GG-X therefore behaves as a surfactant, allowing formation of electronically conductive nanocomposites. XRD indicates apparent beneficial effects of GG-X in the synthesis of CuS with a crystallite size of 15.6 nm. This novel nanocomposite is a promising material for humidity sensing, showing reversible linear responses to relative humidity changes within 10 to 80% range. The interaction between GG-X and water might cause changes in electrical permittivity of GG-X/CuS nanocomposite and/or electrical hopping conductivity between CuS nanoparticles.Peer reviewe

CuS‐Carrageenan Composite Grown from the Gel/Liquid Interface

The aim of this study is to highlight novel CuS-carrageenan nanocomposites grown from the interface between sulfide solutions (liquid phases) and Cu-iota-carrageenan gels. Several parameters including pH, copper and carrageenan concentration of the hydrogel that influence the growth of the nanocomposite have been examined. The most effective parameter is the initial pH of the liquid phase, hence, three growing samples at pH 7, 10 and 13 were selected for further studies and referred as LPH7, LPH10 and LPH13. Three CuS-carrageenan nanocomposites obtained from the three pH conditions were purified and examined in detail using several characterization techniques such as X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), scanning electron microscopy (SEM) and X-ray photoelectron spectroscopy (XPS). The structure, composition, properties as well as the growth mechanism of the nanocomposite have been studied. Additionally, the electrical conductivity of the nanocomposite was exploited to be used as a sensor of relative humidity and temperature.Peer reviewe

Modification of a Single Atom Affects the Physical Properties of Double Fluorinated Fmoc-Phe Derivatives

Supramolecular hydrogels formed by the self-assembly of amino-acid based gelators are receiving increasing attention from the fields of biomedicine and material science. Self-assembled systems exhibit well-ordered functional architectures and unique physicochemical properties. However, the control over the kinetics and mechanical properties of the end-products remains puzzling. A minimal alteration of the chemical environment could cause a significant impact. In this context, we report the effects of modifying the position of a single atom on the properties and kinetics of the self-assembly process. A combination of experimental and computational methods, used to investigate double-fluorinated Fmoc-Phe derivatives, Fmoc-3,4F-Phe and Fmoc-3,5F-Phe, reveals the unique effects of modifying the position of a single fluorine on the self-assembly process, and the physical properties of the product. The presence of significant physical and morphological differences between the two derivatives was verified by molecular-dynamics simulations. Analysis of the spontaneous phase-transition of both building blocks, as well as crystal X-ray diffraction to determine the molecular structure of Fmoc-3,4F-Phe, are in good agreement with known changes in the Phe fluorination pattern and highlight the effect of a single atom position on the self-assembly process. These findings prove that fluorination is an effective strategy to influence supramolecular organization on the nanoscale. Moreover, we believe that a deep understanding of the self-assembly process may provide fundamental insights that will facilitate the development of optimal amino-acid-based low-molecular-weight hydrogelators for a wide range of applications