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Weakly interacting massive particles (WIMPs) are well-motivated candidates for dark matter. One signature of galactic WIMPs is the annual modulation expected in a detector's interaction rate, which arises from Earth's revolution around the Sun. Over two decades, the DAMA/LIBRA experiment has observed such modulation with 250 kg of NaI(Tl) scintillators, in accordance with WIMP expectations but inconsistent with the negative results of other experiments. The signal depends on the target material, so to validate or refute the DAMA result, the experiment must be replicated using the same material. This is the goal of the ANAIS-112 experiment, currently underway since August 2017 with 112.5 kg of NaI(Tl). In this work, we present a reanalysis of three years of data employing an improved analysis chain to enhance the experimental sensitivity. The results presented here are consistent with the absence of modulation and inconsistent with DAMA's observation at nearly 3$\sigma$ confidence level, with the potential to reach a 5$\sigma$ level within 8 years from the beginning of the data collection. Additionally, we explore the impact of different scintillation quenching factors in the comparison between ANAIS-112 and DAMA/LIBRA., Comment: 16 pages, 10 figures, 1 table

Aspect-based Sentiment Analysis (ABSA) is a task whose objective is to classify the individual sentiment polarity of all entities, called aspects, in a sentence. The task is composed of two subtasks: Aspect Term Extraction (ATE), identify all aspect terms in a sentence; and Sentiment Orientation Extraction (SOE), given a sentence and its aspect terms, the task is to determine the sentiment polarity of each aspect term (positive, negative or neutral). This article presents we present our participation in Aspect-Based Sentiment Analysis in Portuguese (ABSAPT) 2022 at IberLEF 2022. We submitted the best performing systems, achieving new state-of-the-art results on both subtasks., Comment: 11 pages, 3 figures, In Proceedings of the Iberian Languages Evaluation Forum (IberLEF 2022), Online. CEUR. org

In this paper, we delineate the strategy employed by our team, DeepLearningBrasil, which secured us the first place in the shared task DepSign-LT-EDI@RANLP-2023, achieving a 47.0% Macro F1-Score and a notable 2.4% advantage. The task was to classify social media texts into three distinct levels of depression - "not depressed," "moderately depressed," and "severely depressed." Leveraging the power of the RoBERTa and DeBERTa models, we further pre-trained them on a collected Reddit dataset, specifically curated from mental health-related Reddit's communities (Subreddits), leading to an enhanced understanding of nuanced mental health discourse. To address lengthy textual data, we used truncation techniques that retained the essence of the content by focusing on its beginnings and endings. Our model was robust against unbalanced data by incorporating sample weights into the loss. Cross-validation and ensemble techniques were then employed to combine our k-fold trained models, delivering an optimal solution. The accompanying code is made available for transparency and further development.

The ANAIS experiment is intended to search for dark matter annual modulation with ultrapure NaI(Tl) scintillators in order to provide a model independent confirmation or refutation of the long-standing DAMA/LIBRA positive annual modulation signal in the low energy detection rate, using the same target and technique. Other experiments exclude the region of parameters singled out by DAMA/LIBRA. However, these experiments use different target materials, so the comparison of their results depends on the models assumed for the dark matter particle and its distribution in the galactic halo. ANAIS-112, consisting of nine 12.5 kg NaI(Tl) modules produced by Alpha Spectra Inc., disposed in a 3$\times$3 matrix configuration, is taking data smoothly with excellent performance at the Canfranc Underground Laboratory, Spain, since August, 2017. Last published results corresponding to three-year exposure were compatible with the absence of modulation and incompatible with DAMA/LIBRA for a sensitivity above 2.5$\sigma$ C.L. Present status of the experiment and a reanalysis of the first 3 years data using new filtering protocols based on machine-learning techniques are reported. This reanalysis allows to improve the sensitivity previously achieved for the DAMA/LIBRA signal. Updated sensitivity prospects are also presented: with the improved filtering, testing the DAMA/LIBRA signal at 5$\sigma$ will be within reach in 2025., Comment: Contributed to the TAUP2023 Conference, August-September 2023. To be published in Proceeding of Science. arXiv admin note: substantial text overlap with arXiv:2110.10649, arXiv:2209.14113

Strong coupling enables a diverse set of applications that include optical memories, non-magnetic isolators, photonic state manipulation, and signal processing. To date, strong coupling in integrated platforms has been realized using narrow-linewidth high-Q optical resonators. In contrast, here we demonstrate wideband strong coupling between two photonic bands. The indirect interband photonic transition is controlled by electrically driving phonons in a linear silicon waveguide. Under large acoustic drive, the system features a Rabi-like energy exchange between two waveguide modes, demonstrating strong coupling. When tuned to unity energy conversion, our system unlocks a set of powerful applications, including optical modulators, routers and filters. In particular, we demonstrate a low loss (-2.08 dB) acousto-optic modulator (AOM) with pump suppression ratio > 55 dB. We also reconfigure our system to demonstrate a non-magnetic, low-loss (< 1 dB) and broadband (59 GHz 10 dB isolation bandwidth) optical isolator.

In a world where capture and separation processes represent above 10% of global energy consumption, novel porous materials, such as Metal-Organic Frameworks (MOFs) used in adsorption-based processes are a promising alternative to dethrone the high-energy-demanding distillation. Shape and size tailor-made pores in combination with Lewis acidic sites can enhance the adsorbate-adsorbent interactions. Understanding the underlying mechanisms of adsorption is essential to designing and optimizing capture and separation processes. Herein, we analyze the adsorption behaviour of light hydrocarbons (methane, ethane, ethylene, propane, and propylene) in two synthesized copper-based MOFs, Cu-MOF-74 and URJC-1. The experimental and computational adsorption curves reveal a limited effect of the exposed metal centers on the olefins. The lower interaction Cu-olefin is also reflected in the calculated enthalpy of adsorption and binding geometries. Moreover, the diamond-shaped pores' deformation upon external stimuli is first reported in URJC-1. This phenomenon is highlighted as the key to understanding the adsorbent's responsive mechanisms and potential in future industrial applications.

Observed reactor and atmospheric neutrino oscillation mixing values appear to be related to the neutrino scale ratio $\sqrt{\Delta m^2_{sol}/\Delta^2_{ATM}}$ in a way that suggest that the neutrino mass matrix can be expanded as a power series by using this ratio as the smallness parameter. This approach provides a simple and natural way to expose the inner hierarchies among neutrino mass terms, which amounts to also explain the solar oscillation mixing as well as solar oscillation scale. We explore a class of mass matrix textures that realize this scenario, for both normal and inverted neutrino mass hierarchies, as well as CP violation and their stability under renormalization scaling., Comment: 18 pages, 5 figures