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The universal typical-signal estimators of entropy and cross-entropy based on the asymptotics of recurrence and waiting times play an important role in information theory. Building on their construction, we introduce and study universal typical-signal estimators of entropy production in the context of nonequilibrium statistical mechanics of one-sided shifts over finite alphabets.

This paper presents an overview of the second edition of HIPE (Identifying Historical People, Places and other Entities), a shared task on named entity recognition and linking in multilingual historical documents. Following the success of the first CLEF-HIPE-2020 evaluation lab, HIPE-2022 confronts systems with the challenges of dealing with more languages, learning domain-specific entities, and adapting to diverse annotation tag sets. This shared task is part of the ongoing efforts of the natural language processing and digital humanities communities to adapt and develop appropriate technologies to efficiently retrieve and explore information from historical texts. On such material, however, named entity processing techniques face the challenges of domain heterogeneity, input noisiness, dynamics of language, and lack of resources. In this context, the main objective of HIPE-2022, run as an evaluation lab of the CLEF 2022 conference, is to gain new insights into the transferability of named entity processing approaches across languages, time periods, document types, and annotation tag sets. Tasks, corpora, and results of participating teams are presented.

Long short-term memory (LSTM) networks have recently shown remarkable performance in several tasks that are dealing with natural language generation, such as image captioning or poetry composition. Yet, only few works have analyzed text generated by LSTMs in order to quantitatively evaluate to which extent such artificial texts resemble those generated by humans. We compared the statistical structure of LSTM-generated language to that of written natural language, and to those produced by Markov models of various orders. In particular, we characterized the statistical structure of language by assessing word-frequency statistics, long-range correlations, and entropy measures. Our main finding is that while both LSTM- and Markov-generated texts can exhibit features similar to real ones in their word-frequency statistics and entropy measures, LSTM-texts are shown to reproduce long-range correlations at scales comparable to those found in natural language. Moreover, for LSTM networks, a temperature-like parameter controlling the generation process shows an optimal value-for which the produced texts are closest to real language-consistent across different statistical features investigated.

OBJECTIVE: Recent studies suggest mental health in youths is deteriorating. The current policy in the United Kingdom emphasizes the role of schools for mental health promotion and prevention, but little data exist on what aspects of schools influence mental health in pupils. This study explored school-level influences on the mental health of young people in a large school-based sample from the United Kingdom. METHOD: Baseline data from a large cluster randomized controlled trial collected between 2016 and 2018 from mainstream secondary schools selected to be representative in relation to their quality rating, size, deprivation, mixed or single-sex pupil population, and country were analyzed. Participants were pupils in their first or second year of secondary school. The study assessed whether school-level factors were associated with pupil mental health. RESULTS: The study included 26,885 pupils (response rate = 90%; age range, 11‒14 years; 55% female) attending 85 schools in the United Kingdom. Schools accounted for 2.4% (95% CI: 2.0%‒2.8%; p < .0001) of the variation in psychopathology, 1.6% (95% CI: 1.2%‒2.1%; p < .0001) of depression, and 1.4% (95% CI: 1.0%‒1.7%; p < .0001) of well-being. Schools in urban locations, with a higher percentage of free school meals and of White British, were associated with poorer pupil mental health. A more positive school climate was associated with better mental health. CONCLUSION: School-level variables, primarily related to contextual factors, characteristics of pupil population, and school climate, explain a small but significant amount of variability in mental health of young people. This information might be used to identify schools that are in need of more resources to support mental health of young people. CLINICAL TRIAL REGISTRATION INFORMATION: MYRIAD: My Resilience in Adolescence, a Study Examining the Effectiveness and Cost-Effectiveness of a Mindfulness Training Programme in Schools Compared With Normal School Provisi

This paper discusses the time and steps of the introduction of intensive agriculture and evolution of irrigation systems to sustain crops in the palaeo-oasis of Salut in the northern Sultanate of Oman. Various geoarchaeological methods allow reconstructing the exploitation of the natural resources of the region and technological development of irrigation methods since the Mid-Holocene. Intensive agriculture started during the Bronze Age and continued with some spatial and intensity fluctuations up to the Islamic period. Cultivations were initially sustained by surface irrigation systems and later replaced by a dense net of aflaj, the typical surface/underground system adopted in the Levant, Arabian Peninsula and western Asia to collect water from deep piedmont aquifers and redistribute it to the fields located in the lowlands. Our results indicate that the aflaj were in use for a long period in the palaeo-oasis formed along Wadi Sayfam and surrounding the citadel of Salut. Uranium-Thorium dating of calcareous tufa formed in the underground tunnels of the aflaj suggests that they were used between ∼540 BCE and ∼1150 CE. After ∼1150 CE Wadi Sayfam were abandoned and the size of the oasis shrank substantially. During the late Islamic period, a surface aqueduct descending from the piedmont of Jabal Shams secured water supply. Our work confirms that in arid lands archaeological and historical communities were able to actively modulate their response to climate changes by using a variety of technological strategies.

Genetic sequences are known to possess non-trivial composition together with symmetries in the frequencies of their components. Recently, it has been shown that symmetry and structure are hierarchically intertwined in DNA, suggesting a common origin for both features. However, the mechanism leading to this relationship is unknown. Here we investigate a biologically motivated dynamics for the evolution of genetic sequences. We show that a metastable (long-lived) regime emerges in which sequences have symmetry and structure interlaced in a way that matches that of extant genomes.

Biologists have long sought a way to explain how statistical properties of genetic sequences emerged and are maintained through evolution. On the one hand, non-random structures at different scales indicate a complex genome organisation. On the other hand, single-strand symmetry has been scrutinised using neutral models in which correlations are not considered or irrelevant, contrary to empirical evidence. Different studies investigated these two statistical features separately, reaching minimal consensus despite sustained efforts. Here we unravel previously unknown symmetries in genetic sequences, which are organized hierarchically through scales in which non-random structures are known to be present. These observations are confirmed through the statistical analysis of the human genome and explained through a simple domain model. These results suggest that domain models which account for the cumulative action of mobile elements can explain simultaneously non-random structures and symmetries in genetic sequences

Although maltreatment experiences in childhood increase the risk for depression, not all maltreated children become depressed. This review aims to systematically examine the existing literature to identify modifiable factors that increase vulnerability to, or act as a buffer against, depression, and could therefore inform the development of targeted interventions. Thirteen databases (including Medline, PsychINFO, SCOPUS) were searched (between 1984 and 2014) for prospective, longitudinal studies published in English that included at least 300 participants and assessed associations between childhood maltreatment and later depression. The study quality was assessed using an adapted Newcastle-Ottawa Scale checklist. Meta-analyses (random effects models) were performed on combined data to estimate the effect size of the association between maltreatment and depression. Meta-regressions were used to explore effects of study size and quality. We identified 22 eligible articles (N=12 210 participants), of which 6 examined potential modifiable predictors of depression following maltreatment. No more than two studies examined the same modifiable predictor; therefore, it was not possible to examine combined effects of modifiable predictors with meta-regression. It is thus difficult to draw firm conclusions from this study, but initial findings indicate that interpersonal relationships, cognitive vulnerabilities and behavioral difficulties may be modifiable predictors of depression following maltreatment. There is a lack of well-designed, prospective studies on modifiable predictors of depression following maltreatment. A small amount of initial research suggests that modifiable predictors of depression may be specific to maltreatment subtypes and gender. Corroboration and further investigation of causal mechanisms is required to identify novel targets for intervention, and to inform guidelines for the effective treatment of maltreated children.

We perform a statistical study of the distances between successive occurrences of a given dinucleotide in the DNA sequence for a number of organisms of different complexity. Our analysis highlights peculiar features of the CG dinucleotide distribution in mammalian DNA, pointing towards a connection with the role of such dinucleotide in DNA methylation. While the CG distributions of mammals exhibit exponential tails with comparable parameters, the picture for the other organisms studied (e.g. fish, insects, bacteria and viruses) is more heterogeneous, possibly because in these organisms DNA methylation has different functional roles. Our analysis suggests that the distribution of the distances between CG dinucleotides provides useful insights into characterizing and classifying organisms in terms of methylation functionalities.

Spesso definito come "il più misterioso tra i manoscritti", il testo di Voynich è un testo medioevale che ha resistito fino ad oggi ad ogni tentativo di decifrazione ed è considerato un enigma dal punto di vista sia crittografico sia linguistico. La pergamena è stata datata come originaria della seconda metà del XV secolo, ma a parte ciò niente si sa sulla sua natura: il suo scopo e tantomeno il suo significato rimangono ancora del tutto oscuri. A tutt’oggi è ancora dibattuta l'ipotesi che il testo contenga un messaggio e che non sia invece il frutto di un clamoroso falso. In questo contributo si vuole presentare una panoramica su alcune evidenze di tipo statistico che, insieme ad analisi nuove e recenti, supportano l'ipotesi che il manoscritto di Voynich contenga in effetti una struttura linguistica vera e propria. Verranno presentati alcuni approcci matematici, prendendo a prestito metodi e tecniche dalla teoria dell'informazione e dalla statistica, che permettono di quantificare alcune caratteristiche globali della distribuzione delle parole in un testo. In particolare alcuni di questi metodi permettono l'estrazione automatica di possibili reti semantiche tra le parole più importanti del testo. È inoltre possibile mostrare che la rete di relazioni linguistiche tra le sezioni in cui è comunemente suddiviso il manoscritto è coerente con le somiglianze tra le rispettive illustrazioni di quelle sezioni e questo risultato può essere considerato come una prima prova della coerenza tra il livello linguistico e quello pittorico del manoscritto Voynich. Nel complesso, le analisi quantitative riassunte in questo contributo forniscono sostegno all'ipotesi che il manoscritto contenga un messaggio autentico e che sia compatibile con il linguaggio naturale.

Liver progenitor cells (LPCs) are necessary for repair in chronic liver disease because the remaining hepatocytes cannot replicate. However, LPC numbers also correlate with disease severity and hepatocellular carcinoma risk. Thus, the progenitor cell response in diseased liver may be regulated to optimize liver regeneration and minimize the likelihood of tumorigenesis. How this is achieved is currently unknown. Human and mouse diseased liver contain two subpopulations of macrophages with different ontogenetic origins: prenatal yolk sac-derived Kupffer cells and peripheral blood monocyte-derived macrophages. We examined the individual role(s) of Kupffer cells and monocyte-derived macrophages in the induction of LPC proliferation using clodronate liposome deletion of Kupffer cells and adoptive transfer of monocytes, respectively, in the choline-deficient, ethionine-supplemented diet model of liver injury and regeneration. Clodronate liposome treatment reduced initial liver monocyte numbers together with the induction of injury and LPC proliferation. Adoptive transfer of monocytes increased the induction of liver injury, LPC proliferation, and tumor necrosis factor-a production. Conclusion: Kupffer cells control the initial accumulation of monocyte-derived macrophages. These infiltrating monocytes are in turn responsible for the induction of liver injury, the increase in tumor necrosis factor-a, and the subsequent proliferation of LPCs.