Cell segregation caused by collective cell migration (CCM) is crucial for morphogenesis, functional development of tissue parts, and is an important aspect in other diseases such as cancer and its metastasis process. Efficiency of the cell segregation depends on the interplay between: (1) biochemical processes such as cell signaling and gene expression and (2) physical interactions between cells. Despite extensive research devoted to study the segregation of various co-cultured systems, we still do not understand the role of physical interactions in cell segregation. Cumulative effects of these physical interactions appear in the form of physical parameters such as: (1) tissue surface tension, (2) viscoelasticity caused by CCM, and (3) solid stress accumulated in multicellular systems. These parameters primarily depend on the interplay between the state of cell–cell adhesion contacts and cell contractility. The role of these physical parameters on the segregation efficiency is discussed on model systems such as co-cultured breast cell spheroids consisting of two subpopulations that are in contact. This review study aims to: (1) summarize biological aspects related to cell segregation, mechanical properties of cell collectives, effects along the biointerface between cell subpopulations and (2) describe from a biophysical/mathematical perspective the same biological aspects summarized before. So that overall it can illustrate the complexity of the biological systems that translate into very complex biophysical/mathematical equations. Moreover, by presenting in parallel these two seemingly different parts (biology vs. equations), this review aims to emphasize the need for experiments to estimate the variety of parameters entering the resulting complex biophysical/mathematical models.

Data-pushed projects are common in companies and consist in the design of a model in order to deliver a desirable output. The design of data science models appears at the intersection of optimisation and creativity logic, with in both cases the presence of anomalies to a various extent but no clear design process.

This paper therefore proposes to study the possible design processes in data-pushed projects, highlighting distinct knowledge exploration logics and the role of anomalies in each. This research introduces a theoretical framework to study data-pushed projects and is based on design theory. Three case studies complete this theoretical work to examine each of the processes and test our hypothesis.

As a result, this paper derives three design processes adapted to data-pushed projects and put forward for each of them: 1) the various knowledge leveraged and generated and 2) the specific role of anomalies.

In the IT landscape, DevOps is the preferred approach for developing and maintaining rapidly evolving systems that require continuous improvements. Yet, DevOps frameworks do not entirely prevent the accumulation of Technical Debt (TD), and under certain circumstances DevOps can even contribute to generating TD. This paper focuses on a specific type of TD, Entangled Technical Debt (ETD), that corresponds to the implicit complexification of a system's design and the appearance of unintentional couplings in its architecture over time. Our work seeks to inform methods for Diagnosing and Locating ETD in DevOps frameworks. Through a research partnership with Ubisoft's IT branch, an experimental case-study was conducted. It takes the form of an assessment of 6 innovative IT projects and a subsequent in-depth architecture analysis of an individual IT system, which enabled the characterization of the mechanisms linking DevOps to ETD. This allowed us to develop and test practical methods for diagnosing and locating ETD in IT systems.

Let $\psi : \mathbb {N} \to [0,1/2]$ be given. The Duffin–Schaeffer conjecture, recently resolved by Koukoulopoulos and Maynard, asserts that for almost all reals $\alpha$ there are infinitely many coprime solutions $(p,q)$ to the inequality $|\alpha - p/q| < \psi (q)/q$, provided that the series $\sum _{q=1}^\infty \varphi (q) \psi (q) / q$ is divergent. In the present paper, we establish a quantitative version of this result, by showing that for almost all $\alpha$ the number of coprime solutions $(p,q)$, subject to $q \leq Q$, is of asymptotic order $\sum _{q=1}^Q 2 \varphi (q) \psi (q) / q$. The proof relies on the method of GCD graphs as invented by Koukoulopoulos and Maynard, together with a refined overlap estimate from sieve theory, and number-theoretic input on the ‘anatomy of integers’. The key phenomenon is that the system of approximation sets exhibits ‘asymptotic independence on average’ as the total mass of the set system increases.

During the last decade, there has been a great debate on the social role and political function of the social sciences. This debate has brought into focus certain types of research that had not been considered valid before, each with its respective theoretical framework. As I see them, the most interesting and productive of these new perspectives for the social sciences in Latin America today are (1) modesty in research, (2) primacy of the qualitative, (3) autonomous development of theoretical models, (4) interdisciplinary research, and (5) broader acceptance of individual action and commitment as validating elements for research. None of these is strictly new: on the contrary, some of them (e.g., 5) are cyclical and have quite respectable ancestors; some have been presented by other colleagues, and myself, in many places and at many times. Nevertheless, they are worthy of repetition in view of their considerable implications for research policy and social action.

This article focuses on the challenges of ‘long-delayed’ prosecutions, that is, criminal prosecutions that begin decades after the conflict, using the experience of the International Criminal Tribunal for Bangladesh (ICT-BD) as a case study. This issue is still an insufficiently discussed topic even though such prosecutions are likely to become more common in the future. The focus of this article is mainly on the legal and broader, transitional justice challenges of long-delayed prosecutions at the ICT-BD. The article examines how such prosecutions have had a contradictory, two-fold effect: on the one hand, they have partially broken the endemic culture of impunity that was allowed to prevail for decades in Bangladesh. On the other hand, however, they have been highly controversial and may have served to deepen alienation of the Islamist opposition in Bangladesh. The article concludes that the question of whether long-delayed prosecutions are desirable for a particular society remains highly context-dependent and, in some cases, mechanisms other than criminal trials may be better suited to dealing with the past.

Patient-specific surgical simulations require the patient-specific identification of the constitutive parameters. The sparsity of the experimental data and the substantial noise in the data (e.g., recovered during surgery) cause considerable uncertainty in the identification. In this exploratory work, parameter uncertainty for incompressible hyperelasticity, often used for soft tissues, is addressed by a probabilistic identification approach based on Bayesian inference. Our study particularly focuses on the uncertainty of the model: we investigate how the identified uncertainties of the constitutive parameters behave when different forms of model uncertainty are considered. The model uncertainty formulations range from uninformative ones to more accurate ones that incorporate more detailed extensions of incompressible hyperelasticity. The study shows that incorporating model uncertainty may improve the results, but this is not guaranteed.

The search space for new thermoelectric oxides has been limited to the alloys of a few known systems, such as ZnO, SrTiO3, and CaMnO3. Notwithstanding the high power factor, their high thermal conductivity is a roadblock in achieving higher efficiency. In this paper, we apply machine learning (ML) models for discovering novel transition metal oxides with low lattice thermal conductivity ($ {k}_L $). A two-step process is proposed to address the problem of small datasets frequently encountered in material informatics. First, a gradient-boosted tree classifier is learnt to categorize unknown compounds into three categories of $ {k}_L $: low, medium, and high. In the second step, we fit regression models on the targeted class (i.e., low $ {k}_L $) to estimate $ {k}_L $ with an $ {R}^2>0.9 $. Gradient boosted tree model was also used to identify key material properties influencing classification of $ {k}_L $, namely lattice energy per atom, atom density, band gap, mass density, and ratio of oxygen by transition metal atoms. Only fundamental materials properties describing the crystal symmetry, compound chemistry, and interatomic bonding were used in the classification process, which can be readily used in the initial phases of materials design. The proposed two-step process addresses the problem of small datasets and improves the predictive accuracy. The ML approach adopted in the present work is generic in nature and can be combined with high-throughput computing for the rapid discovery of new materials for specific applications.

Health data have enormous potential to transform healthcare, health service design, research, and individual health management. However, health data collected by institutions tend to remain siloed within those institutions limiting access by other services, individuals or researchers. Further, health data generated outside health services (e.g., from wearable devices) may not be easily accessible or useable by individuals or connected to other parts of the health system. There are ongoing tensions between data protection and the use of data for the public good (e.g., research). Concurrently, there are a number of data platforms that provide ways to disrupt these traditional health data siloes, giving greater control to individuals and communities. Through four case studies, this paper explores platforms providing new ways for health data to be used for personal data sharing, self-health management, research, and clinical care. The case-studies include data platforms: PatientsLikeMe, Open Humans, Health Record Banks, and unforgettable.me. These are explored with regard to what they mean for data access, data control, and data governance. The case studies provide insight into a shift from institutional to individual data stewardship. Looking at emerging data governance models, such as data trusts and data commons, points to collective control over health data as an emerging approach to issues of data control. These shifts pose challenges as to how “traditional” health services make use of data collected on these platforms. Further, it raises broader policy questions regarding how to decide what public good data should be put towards.

Les déficits neuropsychologiques consécutifs à l’alcoolo-dépendance affectent principalement la mémoire épisodique, la mémoire de travail et les capacités visuospatiales, ainsi que les fonctions exécutives et motrices [1,2]. Ces déficits présents notamment en début de sevrage peuvent conduire à un bénéfice limité des ateliers psychothérapeutiques et entraver le maintien de l’abstinence des patients alcoolo-dépendants [3,4]. Ainsi, une évaluation neuropsychologique étendue conduite après sevrage semble essentielle afin d’orienter la prise en charge clinique de ces patients. Cependant, peu de services d’addictologie ont les ressources humaines et financières pour conduire une telle évaluation chez chaque patient. L’objectif de cette étude était donc d’examiner la validité et les qualités psychométriques d’un outil de dépistage : le BEARNI (pour Brief Examination of Alcohol-Related Neuropsychological Impairments). Cet outil a été spécialement développé pour être accessible au personnel soignant non psychologue dans l’objectif de conduire un dépistage rapide des déficits neuropsychologiques consécutifs à l’alcoolo-dépendance. Une batterie neuropsychologique étendue a servi de référence (gold standard) pour déterminer le profil cognitif des patients alcoolo-dépendants et examiner les qualités psychométriques du BEARNI. L’analyse factorielle exploratoire a permis de valider la structure interne de BEARNI en mettant en évidence 5 facteurs expliquant 60 % de la variabilité et reflétant les capacités visuospatiales, les fonctions exécutives, la mémoire verbale et la mémoire de travail verbale. La standardisation de chacun des sub-tests et des scores totaux à BEARNI, conduite par l’intermédiaire de courbes ROC, a mis en évidence que cet outil de dépistage présente une bonne efficacité diagnostique dans le dépistage des atteintes cognitives et motrices présentes chez les patients alcoolo-dépendants après sevrage. Cette étude montre la pertinence de l’utilisation de BEARNI en pratique clinique pour détecter la présence de troubles neuropsychologiques chez les patients alcoolo-dépendants et permettre d’orienter ceux ayant besoin d’une évaluation neuropsychologique étendue.

It is known that pigs can acquire flavour preferences by brief social interactions with conspecifics that previously consumed a flavoured solid feed. However, there is no information about whether a flavoured solution could support flavour preferences through social transmission. Ninety-six pigs (49 days old) were housed in 12 pens (8 pigs/pen). Four animals per pen were randomly selected to act as observers and four as demonstrators. Demonstrator animals were temporarily moved to an empty pen where a protein solution was offered (porcine digestive peptides (PDPs), 4% weight/volume) with the addition of 0.075% aniseed (six pens) or garlic (six pens) powdered artificial flavours for 30 min. Afterwards, demonstrators were returned to interact with observer animals for 30 min. A choice test (30 min) between aniseed and garlic PDP was performed for each observer group after the interaction. Observers showed a higher intake of solutions previously consumed by their demonstrator conspecifics (648 v. 468 ml; SEM 61.36, P < 0.05). As with flavoured solid feeds, protein solutions containing artificial flavours can create preferences in pigs for those flavours through social transmission from conspecifics.

Species of Anisakis typically infect the stomach of cetaceans worldwide, often causing ulcerative lesions that may compromise the host's health. These nematodes also cause anisakiasis or allergic reactions in humans. To assess the risks of this emerging zoonosis, data on long-term changes in Anisakis infections in cetaceans are necessary. Here, we compare the prevalence and severity of ulcerative lesions caused by Anisakis spp. in five cetacean species stranded along the north-west Spanish coast in 2017–2018 with published data from 1991–1996. Open ulcers were found in 32/43 short-beaked common dolphins, Delphinus delphis; 3/5 striped dolphins, Stenella coeruleoalba; 1/7 bottlenose dolphins, Tursiops truncatus; and 1/3 harbour porpoises, Phocoena phocoena meridionalis; a single individual of long-finned pilot whale, Globicephala melas, was found uninfected. In common dolphins, the mean abundance of open ulcers per host was 1.1 (95% confidence interval: 0.8–1.3), with a maximum diameter (mean ± standard deviation) of 25.4 ± 16.9 mm. Stomachs with scars or extensive fibrosis putatively associated with Anisakis were detected in 14 and five animals, respectively. A molecular analysis based on the mitochondrial cytochrome c oxidase II gene using 18 worms from three cetacean species revealed single or mixed infections of Anisakis simplex sensu stricto and Anisakis pegreffii. Compared with the period 1991–1996, we found a strong increase of prevalence, abundance and extension of ulcerative lesions in most cetacean species. Anisakis populations could have increased in the study area over the last decades, although we cannot rule out that a higher environmental stress has also boosted the pathological effects of these parasites.

In 1657, the marquis of Villagarcía was appointed as president of the Audiencia of Charcas. Although, he eventually declined the post, his nomination generated an unusual trail of private documents. Using my study of this correspondence as a base, I will discuss how the networks of patronage were built and sustained, how they operated, and how they impacted the global mobility of imperial officials. Patronage networks were indispensable to itinerant officials who relied on their clients, patrons, and brokers to help them govern distant regions by gathering resources and information, and implementing their objectives. Moreover, this particular case gives us a glimpse into the relationship between Villagarcía as husband and his wife, and the private assessments and negotiations surrounding the transatlantic journey.