Recent analyses of Fermi-LAT data have identified a nearly spherical, halo-like excess of gamma rays peaking at E_gamma ~ 20 GeV. If interpreted as dark matter annihilation, the excess directly probes the thermal freeze-out epoch and therefore any non-standard corrections to the early-Universe expansion rate. In this work we examine the implications of this tentative signal for CET Omega, an informational and modular extension of relativistic quantum field theory and cosmology. CET Omega predicts a universal state-dependent modification to the radiation energy density of the early Universe, characterized by a doubly logarithmic correction originating from renormalized modular fluctuations in the spectral triple of the theory. The correction is negligible during Big Bang nucleosynthesis and recombination but becomes relevant during thermal WIMP freeze-out. We derive the correction from the modular two-point function, justify the onset scale associated with the informational sector, and compute its quantitative impact on freeze-out through numerical solutions. We also analyze the evolution of the informational field Phi_Omega(x) and show that it freezes in before the freeze-out epoch and survives to the present time under gravitational advection. The resulting modification induces percent-level shifts in the relic abundance and sub-percent morphological corrections to the annihilation gamma-ray flux. We compare the scenario with Early Dark Energy, kination, and varying N_eff models, and show that the parameter range 10^{-4} < alpha_log < 10^{-2} remains consistent with Planck, BBN, and BAO constraints while predicting potentially observable deviations in the gamma-ray morphology accessible to next-generation MeV-GeV missions.
Tien Rahayu Tulili, Ayushi Rastogi, Andrea Capiluppi
Burnout is an occupational syndrome that, like many other professions, affects the majority of software engineers. Past research studies showed important trends, including an increasing use of machine learning techniques to allow for an early detection of burnout. This paper is a systematic literature review (SLR) of the research papers that proposed machine learning (ML) approaches, and focused on detecting burnout in software developers and IT professionals. Our objective is to review the accuracy and precision of the proposed ML techniques, and to formulate recommendations for future researchers interested to replicate or extend those studies. From our SLR we observed that a majority of primary studies focuses on detecting emotions or utilise emotional dimensions to detect or predict the presence of burnout. We also performed a cross-sectional study to detect which ML approach shows a better performance at detecting emotions; and which dataset has more potential and expressivity to capture emotions. We believe that, by identifying which ML tools and datasets show a better performance at detecting emotions, and indirectly at identifying burnout, our paper can be a valuable asset to progress in this important research direction.
Augustyn rekonstruował strukturę arki Noego na podstawie Rdz 6,14-16 oraz pism kilku swoich poprzedników. Rekonstrukcja ta wywarła bardzo duży wpływ na następne pokolenia łacińskich pisarzy kościelnych. Biskup Hippony z jednej strony zebrał dorobek swych poprzedników w tej materii, z drugiej zaś dodał wiele istotnych, nowych elementów. W ten sposób stworzył on swój własny obraz struktury arki Noego. Obraz ten jest jednak rozproszony po wielu jego pismach. Można by rzec, że Augustyn kilkakrotnie powracał do zagadnienia struktury arki Noego. Najważniejsze opisy tej struktury zostały przedstawione w czterech jego dziełach. W porządku chronologicznym są to: „Contra Faustum”, „De baptismo”, „De civitate Dei” i „Quaestiones in Heptateuchum”. Godne uwagi fragmenty poświęcone strukturze arki są również w (porządek alfabetyczny): „Contra Secundinum”, „De doctrina christiana”, „Enarrationes in Psalmos”, „Epistula ad Catholicos de secta Donatistorum”, „In Ioannis Evangelium tractatus CXXIV” i w „Sermones”. Generalnie Augustyński obraz struktury arki, miał na celu nie tylko „zadowolenie” ówczesnych znawców teologii biblijnej, lecz także obraz ten miał zaspokoić ciekawość zwykłych ludzi, przez których arka Noego mogła być postrzegana jako swego rodzaju interesujący, biblijny szczegół techniczny.
Early Christian literature. Fathers of the Church, etc., Philosophy of religion. Psychology of religion. Religion in relation to other subjects
Christian Schlarmann, Francesco Croce, Nicolas Flammarion
et al.
Contrastive language-image pre-training aligns the features of text-image pairs in a common latent space via distinct encoders for each modality. While this approach achieves impressive performance in several zero-shot tasks, it cannot natively handle multimodal inputs, i.e., encoding image and text into a single feature vector. As a remedy, it is common practice to use additional modules to merge the features extracted by the unimodal encoders. In this work, we present FuseLIP, an alternative architecture for multimodal embedding. Leveraging recent progress in discrete image tokenizers, we propose to use a single transformer model which operates on an extended vocabulary of text and image tokens. This early fusion approach allows the different modalities to interact at each depth of encoding and obtain richer representations compared to common late fusion. We collect new datasets for multimodal pre-training and evaluation, designing challenging tasks for multimodal encoder models. We show that FuseLIP outperforms other approaches in multimodal embedding tasks such as VQA and text-guided image transformation retrieval, while being comparable to baselines on unimodal tasks.
Despite its musicological, cultural, and religious significance, the Ethiopian Orthodox Tewahedo Church (EOTC) chant is relatively underrepresented in music research. Historical records, including manuscripts, research papers, and oral traditions, confirm Saint Yared's establishment of three canonical EOTC chanting modes during the 6th century. This paper attempts to investigate the EOTC chants using music information retrieval (MIR) techniques. Among the research questions regarding the analysis and understanding of EOTC chants, Yaredawi YeZema Silt, namely the mode of chanting adhering to Saint Yared's standards, is of primary importance. Therefore, we consider the task of Yaredawi YeZema Silt classification in EOTC chants by introducing a new dataset and showcasing a series of classification experiments for this task. Results show that using the distribution of stabilized pitch contours as the feature representation on a simple neural network-based classifier becomes an effective solution. The musicological implications and insights of such results are further discussed through a comparative study with the previous ethnomusicology literature on EOTC chants. By making this dataset publicly accessible, we aim to promote future exploration and analysis of EOTC chants and highlight potential directions for further research, thereby fostering a deeper understanding and preservation of this unique spiritual and cultural heritage.
In this work, we study early-warning signs for stochastic partial differential equations (SPDEs), where the linearization around a steady state has continuous spectrum. The studied warning sign takes the form of qualitative changes in the variance as a deterministic bifurcation threshold is approached via parameter variation. Specifically, we focus on the scaling law of the variance near the transition. Since we are dealing here, in contrast to previous studies, with the case of continuous spectrum and quantitative scaling laws, it is natural to start with linearizations that are multiplication operators defined by analytic functions. For a one-dimensional spatial domain we obtain precise rates of divergence. In the case of the two- and three-dimensional domains an upper bound to the rate of the early-warning sign is proven. These results are cross-validated by numerical simulations. Our theory can be generically useful for several applications, where stochastic and spatial aspects are important in combination with continuous spectrum bifurcations.
Lucia S. Layritz, Ilya Pavlyukevich, Anja Rammig
et al.
Statistical early warning signs can be used to identify an approaching bifurcation in stochastic dynamical systems and are now regularly employed in applications concerned with the identification of potential rapid, non-linear change or tipping points. However, the reliability of these early warning signs relies on a number of key mathematical assumptions, most notably the presence of Gaussian noise. We here show that for systems driven by non-Gaussian, $α$-stable noise, the classical early warning signs of rising variance and autocorrelation are not supported by mathematical theory and their use poses the danger of spurious, false-positive results. To address this, we provide a generalized approach by introduce the scaling factor $γ_X$ as an alternative early warning sign. We show that in the case of the Ornstein-Uhlenbeck process, there exists a direct inverse relationship between $γ_{X}$ and the bifurcation parameter, telling us that $γ_{X}$ will increase as we approach the bifurcation. Our numerical simulations confirm theoretical results and show that our findings generalize well to non-linear, non-equilibrium systems. We thus provide a generalized, robust and applicable statistical early warning sign for systems driven by Gaussian and non-Gaussian $α$-stable noise.
Estudiamos el hallazgo de tres cruces latinas del tipo horquillado, grabadas en la necrópolis rupestre tardoantigua de Tiermes. Para determinar su cronología hemos analizado el propio contexto cementerial en el que fueron realizadas. Los restos recuperados en el transcurso de las excavaciones allí practicadas se pueden fechar entre finales del siglo V y mediados del siglo VI. A su vez, hemos corroborado cómo el tipo de cruces reproducido tuvieron un momento de esplendor justamente en ese momento cronológico, de uso cementerial del espacio; existiendo múltiples paralelos tanto en Oriente como en la Península Ibérica. Aquí no son extrañas en estaciones rupestres de distinto cariz, incluidos eremitorios y/o necrópolis, entre otros.
Early Christian literature. Fathers of the Church, etc.
The Fathers Refounded, Elizabeth Clark's magnificent sequel to Founding the Fathers, describes in abundant detail how the overlapping disciplines of early church history and patristics became established in several American universities. It examines the work of three historians of early Christianity and their accomplishments and difficulties—and along the way it reminds its readers more than once that historical investigation poses a danger to the security of religious dogmatists. Take, for instance, the work of George LaPiana: As an Italian exile and historical scholar whose investigations of early Christian associations in Rome undermined the accustomed Roman Catholic story of apostolic succession and episcopal authority, his work could be ignored during his lifetime by the triumphalist representatives of seemingly unquestioned dogma. An example is the work of LaPiana's American contemporary, Monsignor Joseph (“Butch”) Fenton, writing only a few years before the Second Vatican Council would vindicate the historical approach when it endorsed patristic theology as an inspiration for aggiornamento, the “updating” of Catholic thought.
La naturaleza de la realeza visigoda, sus orígenes, su evolución, sus atributos y sus símbolos de poder han sido el objeto de estudio de diversos historiadores, resultando algunos de ellos muy reveladores al respecto203. Por el contrario, no encontramos el mismo número de trabajos que se refi eran al rebelde, al tyrannus que se alza contra el poder legal encarnado en la fi gura legitimada del monarca, de ahí que sea nuestra intención revalorizar la fi gura del tyrannusen nuestro trabajo.
Early Christian literature. Fathers of the Church, etc.
Sergio G. Burdisso, Marcelo Errecalde, Manuel Montes-y-Gómez
A recently introduced classifier, called SS3, has shown to be well suited to deal with early risk detection (ERD) problems on text streams. It obtained state-of-the-art performance on early depression and anorexia detection on Reddit in the CLEF's eRisk open tasks. SS3 was created to deal with ERD problems naturally since: it supports incremental training and classification over text streams, and it can visually explain its rationale. However, SS3 processes the input using a bag-of-word model lacking the ability to recognize important word sequences. This aspect could negatively affect the classification performance and also reduces the descriptiveness of visual explanations. In the standard document classification field, it is very common to use word n-grams to try to overcome some of these limitations. Unfortunately, when working with text streams, using n-grams is not trivial since the system must learn and recognize which n-grams are important "on the fly". This paper introduces t-SS3, an extension of SS3 that allows it to recognize useful patterns over text streams dynamically. We evaluated our model in the eRisk 2017 and 2018 tasks on early depression and anorexia detection. Experimental results suggest that t-SS3 is able to improve both current results and the richness of visual explanations.
A key stepping stone in the development of an artificial general intelligence (a machine that can perform any task), is the production of agents that can perform multiple tasks at once instead of just one. Unfortunately, canonical methods are very prone to catastrophic forgetting (CF) - the act of overwriting previous knowledge about a task when learning a new task. Recent efforts have developed techniques for overcoming CF in learning systems, but no attempt has been made to apply these new techniques to evolutionary systems. This research presents a novel technique, weight protection, for reducing CF in evolutionary systems by adapting a method from learning systems. It is used in conjunction with other evolutionary approaches for overcoming CF and is shown to be effective at alleviating CF when applied to a suite of reinforcement learning tasks. It is speculated that this work could indicate the potential for a wider application of existing learning-based approaches to evolutionary systems and that evolutionary techniques may be competitive with or better than learning systems when it comes to reducing CF.
Mirko Myllykoski, Carl Christian Kjelgaard Mikkelsen
In this paper, we present the StarNEig library for solving dense non-symmetric (generalized) eigenvalue problems. The library is built on top of the StarPU runtime system and targets both shared and distributed memory machines. Some components of the library support GPUs. The library is currently in an early beta state and only real arithmetic is supported. Support for complex data types is planned for a future release. This paper is aimed for potential users of the library. We describe the design choices and capabilities of the library, and contrast them to existing software such as ScaLAPACK. StarNEig implements a ScaLAPACK compatibility layer that should make it easy for a new user to transition to StarNEig. We demonstrate the performance of the library with a small set of computational experiments.
This paper proposes a combination of a convolutional and a LSTM network to improve the accuracy of OCR on early printed books. While the standard model of line based OCR uses a single LSTM layer, we utilize a CNN- and Pooling-Layer combination in advance of an LSTM layer. Due to the higher amount of trainable parameters the performance of the network relies on a high amount of training examples to unleash its power. Hereby, the error is reduced by a factor of up to 44%, yielding a CER of 1% and below. To further improve the results we use a voting mechanism to achieve character error rates (CER) below $0.5%$. The runtime of the deep model for training and prediction of a book behaves very similar to a shallow network.