Radio recombination lines from obscured quasars with the SKA

We explore the possibility of detecting hydrogen radio recombination lines from 0 < z < 10 quasars. We compute the expected Hnalpha flux densities as a function of absolute magnitude and redshift by considering (i) the range of observed AGN spectral indices from UV to X-ray bands, (ii) secondary ionizations from X-ray photons, and (iii) stimulated emission due to nonthermal radiation. All these effects are important to determine the line fluxes. We find that the combination of slopes: alpha_X,hard = -1.11, alpha_X,soft = -0.7, alpha_EUV = -1.3, alpha_UV = -1.7, maximizes the expected flux, f_Hnalpha = 10 microJy for z = 7 quasars with M_AB = -27 in the n = 50 lines; allowed SED variations produce variations by a factor of 3 around this value. Secondaries boost the line intensity by a factor of 2 to 4, while stimulated emission in high-z quasars with M_AB = -26 provides an extra boost to RRL flux observed at nu = 1 GHz if recombinations arise in HII regions with T_e = 10^3-5 K, n_e = 10^3-5 cm^-3. We compute the sensitivity required for a 5sigma detection of Hnalpha lines using the SKA, finding that the SKA-MID could detect sources with M_AB < -27 (M_AB < -26) at z < 8 (z < 3) in less than 100 hrs of observing time. These observations could open new paths to searches for obscured SMBH progenitors, complementing X-ray, optical/IR and sub-mm surveys.Comment: 11 pages, 9 figures; to be published in Monthly Notices of the Royal Astronomical Society Main Journa

Leveraging Large Language Models to Detect Influence Campaigns in Social Media

Social media influence campaigns pose significant challenges to public discourse and democracy. Traditional detection methods fall short due to the complexity and dynamic nature of social media. Addressing this, we propose a novel detection method using Large Language Models (LLMs) that incorporates both user metadata and network structures. By converting these elements into a text format, our approach effectively processes multilingual content and adapts to the shifting tactics of malicious campaign actors. We validate our model through rigorous testing on multiple datasets, showcasing its superior performance in identifying influence efforts. This research not only offers a powerful tool for detecting campaigns, but also sets the stage for future enhancements to keep up with the fast-paced evolution of social media-based influence tactics

Qualitative Analysis of a Retarded Mathematical Framework with Applications to Living Systems

This paper deals with the derivation and the mathematical analysis of an autonomous and nonlinear ordinary differential-based framework. Specifically, the mathematical framework consists of a system of two ordinary differential equations: a logistic equation with a time lag and an equation for the carrying capacity that is assumed here to be time dependent. The qualitative analysis refers to the stability analysis of the coexistence equilibrium and to the derivation of sufficient conditions for the existence of Hopf bifurcations. The results are of great interest in living systems, including biological and economic systems

The Time Delays' Effects on the Qualitative Behavior of an Economic Growth Model

A further generalization of an economic growth model is the main topic of this paper. The paper specifically analyzes the effects on the asymptotic dynamics of the Solow model when two time delays are inserted: the time employed in order that the capital is used for production and the necessary time so that the capital is depreciated. The existence of a unique nontrivial positive steady state of the generalized model is proved and sufficient conditions for the asymptotic stability are established. Moreover, the existence of a Hopf bifurcation is proved and, by using the normal form theory and center manifold argument, the explicit formulas which determine the stability, direction, and period of bifurcating periodic solutions are obtained. Finally, numerical simulations are performed for supporting the analytical results

Unveiling the Dynamics of Censorship, COVID-19 Regulations, and Protest: An Empirical Study of Chinese Subreddit r/china_irl

The COVID-19 pandemic has intensified numerous social issues that warrant academic investigation. Although information dissemination has been extensively studied, the silenced voices and censored content also merit attention due to their role in mobilizing social movements. In this paper, we provide empirical evidence to explore the relationships among COVID-19 regulations, censorship, and protest through a series of social incidents occurred in China during 2022. We analyze the similarities and differences between censored articles and discussions on r/china\_irl, the most popular Chinese-speaking subreddit, and scrutinize the temporal dynamics of government censorship activities and their impact on user engagement within the subreddit. Furthermore, we examine users' linguistic patterns under the influence of a censorship-driven environment. Our findings reveal patterns in topic recurrence, the complex interplay between censorship activities, user subscription, and collective commenting behavior, as well as potential linguistic adaptation strategies to circumvent censorship. These insights hold significant implications for researchers interested in understanding the survival mechanisms of marginalized groups within censored information ecosystems

Paradigmi della temporalità in Kant e Bergson

Il nostro lavoro ha assunto come oggetto di indagine la nozione di tempo in Kant e Bergson. Nel primo capitolo viene analizzato in modo attento la bibliografia secondaria sul complesso tema del confronto tra Kant e Bergson, pervenendo alla necessità di superare l’impostazione metodologica degli unici due studiosi (Clifford Wellington Webb e Barthélemy-Madalue ) che si sono cimentati in un lavoro affine a quello svolto dal dottorando nella sua tesi. Inoltre, viene prestata particolare attenzione ai diversi paradigmi della temporalità, sedimentatisi nel corso della storia del pensiero occidentale. Nel secondo capitolo, viene studiato il rapporto tra tempo e spazio, come è teorizzato in Kant e Bergson, tenendo presente a riguardo la teorizzazione dei rispettivi autori del concetto di numero e le antinomie nelle interpretazioni dei due filosofi. Poi, nel terzo capitolo, quello più denso speculativamente, ho proposto una lettura dei due filosofi, facendo leva, da un lato sul rapporto tra tempo e coscienza, da un altro sulla relazione tra la coscienza e le sue stratificazioni. Infine, viene presentata in appendice una traduzione di un significativo inedito bergsoniano, sia da un punto di vista filologico, sia teoretico, che riguarda le Lezioni sulla filosofia moderna di Bergson dedicate alla Critica della ragion pura di Kant, dove sono anche elencate analiticamente tutte le occorrenze kantiane nei testi bergsoniani

Center Manifold Reduction and Perturbation Method in a Delayed Model with a Mound-Shaped Cobb-Douglas Production Function

Matsumoto and Szidarovszky (2011) examined a delayed continuous-time growth model with a special mound-shaped production function and showed a Hopf bifurcation that occurs when time delay passes through a critical value. In this paper, by applying the center manifold theorem and the normal form theory, we obtain formulas for determining the direction of the Hopf bifurcation and the stability of bifurcating periodic solutions. Moreover, Lindstedt's perturbation method is used to calculate the bifurcated periodic solution, the direction of the bifurcation, and the stability of the periodic motion resulting from the bifurcation

Complexity in action: Untangling latent relationships between land quality, economic structures and socio-spatial patterns in Italy

Land quality, a key economic capital supporting local development, is affected by biophysical and anthropogenic factors. Taken as a relevant attribute of economic systems, land quality has shaped the territorial organization of any given region influencing localization of agriculture, industry and settlements. In regions with long-established human-landscape interactions, such as the Mediterranean basin, land quality has determined social disparities and polarization in the use of land, reflecting the action of geographical gradients based on elevation and population density. The present study investigates latent relationships within a large set of indicators profiling local communities and land quality on a fine-grained resolution scale in Italy with the aim to assess the potential impact of land quality on the regional socioeconomic structure. The importance of land quality gradients in the socioeconomic configuration of urban and rural regions was verified analyzing the distribution of 149 socioeconomic and environmental indicators organized in 5 themes and 17 research dimensions. Agriculture, income, education and labour market variables discriminate areas with high land quality from areas with low land quality. While differential land quality in peri-urban areas may reflect conflicts between competing actors, moderate (or low) quality of land in rural districts is associated with depopulation, land abandonment, subsidence agriculture, unemployment and low educational levels. We conclude that the socioeconomic profile of local communities has been influenced by land quality in a different way along urban-rural gradients. Policies integrating environmental and socioeconomic measures are required to consider land quality as a pivotal target for sustainable development. Regional planning will benefit from an in-depth understanding of place-specific relationships between local communities and the environment

Understanding the Spatial Distribution of Forest Fires in a Growing Urban Region: Socioeconomic Indicators Tell You More

The present study analyzes the spatial distribution of 881 forest fires recorded during four recent years (2009-2012) in 59 municipalities of a Mediterranean region (Attica, Greece) characterized by high fire risk and relevant human pressure due to uneven urban expansion. The hypothesis that a defined fire profile (in terms of density, severity and land-use selectivity) on a local scale was associated to a specific set of socioeconomic and territorial variables, was tested explicitly using six fires’ indicators and eight contextual indicators under a multivariate analysis framework. Analysis identified two main dimensions for both forest fires (dimension and selectivity) and the socioeconomic context (demographic variables associated to the urban-rural gradient and average income). Fire density and forest/pastures burnt areas did not correlated to any socioeconomic variable. At the same time, average declared income and elevation of each municipality did not correlated to any fires’ variable. To the contrary, the average fire size, the percentage of burnt area per municipality and the proportion of cropland affected by fires correlated positively with the distance from the inner city and the total surface area of each municipality and negatively with the proportion of compact settlements, population density and growth. These results confirm the importance of the urban-rural divide determining the spatial distribution of forest fires in Attica while pointing out the modest influence of variables such as the socioeconomic status of resident population

Unmasking the Web of Deceit: Uncovering Coordinated Activity to Expose Information Operations on Twitter

Social media platforms, particularly Twitter, have become pivotal arenas for influence campaigns, often orchestrated by state-sponsored information operations (IOs). This paper delves into the detection of key players driving IOs by employing similarity graphs constructed from behavioral pattern data. We unveil that well-known, yet underutilized network properties can help accurately identify coordinated IO drivers. Drawing from a comprehensive dataset of 49 million tweets from six countries, which includes multiple verified IOs, our study reveals that traditional network filtering techniques do not consistently pinpoint IO drivers across campaigns. We first propose a framework based on node pruning that emerges superior, particularly when combining multiple behavioral indicators across different networks. Then, we introduce a supervised machine learning model that harnesses a vector representation of the fused similarity network. This model, which boasts a precision exceeding 0.95, adeptly classifies IO drivers on a global scale and reliably forecasts their temporal engagements. Our findings are crucial in the fight against deceptive influence campaigns on social media, helping us better understand and detect them.Comment: Accepted at the 2024 ACM Web Conferenc