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This paper discusses the content of the cadre file of Henri H. Stahl preserved in the Archives of the University of Bucharest’s Rectorate. In the form in which it has been preserved after 1989, the personnel file of H.H. Stahl seems, from several points of view, atypical. If we compare it with the cadre files of the 1950s, it surprises by the apparent “goodwill” of the communist cadres towards H.H. Stahl. This ideological solicitude is manifested in the interpretation given to main cultural and political events in H.H. Stahl’s life. In other circumstances such political past could be labeled as unusable in a communist context. Equally curious and noteworthy is the issue of the ethnic origin attributed (and not necessarily real or assumed by the one described in the file), more precisely the issue of Stahl’s nationality ( Jewish) which was recorded in the file. Analyzing Stahl cadre file we can wonder if the integrity of this dossier has not been compromised by removing, extracting or modifying documents by the personel staff services or by someone else. [ABSTRACT FROM AUTHOR]

The paper uses letters – some unpublished – from the mid-1940s and the second half of the 1970s exchanged by Mattei Dogan and Henri H. Stahl, to render the way sociological education was organized at the University of Bucharest immediately after the Second World War. [ABSTRACT FROM AUTHOR]

The paper proposes a Reading of Schillers' letters On the aesthetic Education of Man from the viewpoint of the concept "sociability" with which Schiller situates, in the last letter, the territory where the aesthetic way towards "freedom" would break through. It is pointed to the propagation of the sociability concept via the kantian anthropology and the sociology of Simmel. It is postulated the affinity of this approach with the contemporary thinking of the event. [ABSTRACT FROM AUTHOR]

Stochastic gradient descent (SGD) has become the method of choice for training highly complex and nonconvex models since it can not only recover good solutions to minimize training errors but also generalize well. Computational and statistical properties are separately studied to understand the behavior of SGD in the literature. However, there is a lacking study to jointly consider the computational and statistical properties in a nonconvex learning setting. In this paper, we develop novel learning rates of SGD for nonconvex learning by presenting high-probability bounds for both computational and statistical errors. We show that the complexity of SGD iterates grows in a controllable manner with respect to the iteration number, which sheds insights on how an implicit regularization can be achieved by tuning the number of passes to balance the computational and statistical errors. As a byproduct, we also slightly refine the existing studies on the uniform convergence of gradients by showing its connection to Rademacher chaos complexities. [ABSTRACT FROM AUTHOR]

Group testing refers to the process of testing pooled samples to reduce the total number of tests. Given the current pandemic, and the shortage of test supplies for COVID-19, group testing can play a critical role in time and cost efficient diagnostics. In many scenarios, samples collected from users are also accompanied with auxiliary information (such as demographics, history of exposure, onset of symptoms). Such auxiliary information may differ across patients, and is typically not considered while designing group testing algorithms. In this paper, we abstract such heterogeneity using a model where the population can be categorized into clusters with different prevalence rates. The main result of this work is to show that exploiting knowledge heterogeneity can further improve the efficiency of group testing. Motivated by the practical constraints and diagnostic considerations, we focus on two-stage group testing algorithms, where in the first stage, the goal is to detect as many negative samples by pooling, whereas the second stage involves individual testing to detect any remaining samples. For this class of algorithms, we prove that the gain in efficiency is related to the concavity of the number of tests as a function of the prevalence. We also show how one can choose the optimal pooling parameters for one of the algorithms in this class, namely, doubly constant pooling. We present lower bounds on the average number of tests as a function of the population heterogeneity profile, and also provide numerical results and comparisons. [ABSTRACT FROM AUTHOR]

The basic goal of threshold group testing is to identify up to $d$ defective items among a population of $n$ items, where $d$ is usually much smaller than $n$. The outcome of a test on a subset of items is positive if the subset has at least $u$ defective items, negative if it has up to $\ell $ defective items, where $0 \leq \ell < u$ , and arbitrary otherwise. This is called threshold group testing. The parameter $g = u - \ell - 1$ is called the gap. In this paper, we focus on the case $g > 0$ , i.e., threshold group testing with a gap. Note that the results presented here are also applicable to the case $g = 0$ ; however, the results are not as efficient as those in related work. Currently, a few reported studies have investigated test designs and decoding algorithms for identifying defective items. Most of the previous studies have not been feasible because there are numerous constraints on their problem settings or the decoding complexities of their proposed schemes are relatively large. Therefore, it is compulsory to reduce the number of tests as well as the decoding complexity, i.e., the time for identifying the defective items, for achieving practical schemes. The work presented here makes five contributions. The first is a more accurate theorem for a non-adaptive algorithm for threshold group testing proposed by Chen and Fu. The second is an improvement in the construction of disjunct matrices, which are the main tools for tackling (threshold) group testing and other tasks such as constructing cover-free families or learning hidden graphs. Specifically, we present a better exact upper bound on the number of tests for disjunct matrices compared with that in related work. The third and fourth contributions are a reduced exact upper bound on the number of tests and a reduced asymptotic bound on the decoding time for identifying defective items in a noisy setting on test outcomes. The fifth contribution is a simulation on the number of tests of the resulting improvements for previous work and the proposed theorems. [ABSTRACT FROM AUTHOR]

In response to calls for greater interdisciplinary involvement from the social sciences and humanities in the development, governance, and study of artificial intelligence systems, this paper presents one sociologist's view on the problem of algorithmic bias and the reproduction of societal bias. Discussions of bias in AI cover much of the same conceptual terrain that sociologists studying inequality have long understood using more specific terms and theories. Concerns over reproducing societal bias should be informed by an understanding of the ways that inequality is continually reproduced in society—processes that AI systems are either complicit in, or can be designed to disrupt and counter. The contrast presented here is between conservative and radical approaches to AI, with conservatism referring to dominant tendencies that reproduce and strengthen the status quo, while radical approaches work to disrupt systemic forms of inequality. The limitations of a conservative approach to racial bias are discussed through the specific example of biased criminal risk assessments and Indigenous overrepresentation in Canada's criminal justice system. This illustrates the dangers of treating racial bias as a generalizable problem and equality as a generalizable solution, emphasizing the importance of considering inequality in context. Societal issues can no longer be out of scope for AI and machine learning, given the impact of these systems on human lives. This requires engagement with a growing body of critical AI scholarship that goes beyond biased data to analyze structured ways of perpetuating inequality, opening up the possibility for interdisciplinary engagement and radical alternatives. [ABSTRACT FROM AUTHOR]

This paper aims to revisit the Pauline peristasis catalogues in his second letter to the Corinthians. There, a new perspective is found, based on the interdisciplinary dialogue between the Bible, Psychology and Spirituality, useful for understanding resilience from a Christian perspective, as deduced from the ministry of the apostle to the nations. The concept of resilience, used first in physics and later in Psychology, Psychoanalysis and Sociology, is today found in various hermeneutical approaches to individual and group realities in which people are called to face adverse situations such as difficult relationships, diseases, problems, etc. An analysis of the Pauline peristasis catalogues not only demonstrates that the apostle is a model of resilient behavior but reveals, also, the sides of a hermeneutic arch whose origin is the vocation he received from Christ and whose goal to be reached is the consolation and salvation of Corinthians by him. This finding recalls once again the relevance of Paul's teachings for an interior life anchored in a spirituality of resilience in current times. [ABSTRACT FROM AUTHOR]

Despite the fruitful evidence to support the emergence of cooperation, irrational decisions are still an essential part of promoting cooperation. Among the many factors that affect human rational decision-making, peer pressure is unique to social organisms and directly affects individual cooperative behaviors in the process of social interaction. This kind of pressure psychologically forces individuals to behave consistently with their partners, and partners with inconsistent behaviors may suffer psychological blows. As feedback, this psychological harm may in turn affect individual cooperative decisions. There is evidence that when peer pressure exists, partnerships can reduce free-riding in enterprise. Based on interdependent networks, this paper studies the impact of peer pressure on cooperation dynamics when the strategies of corresponding partners from different layers of the networks are inconsistent. We assume that when individuals are under peer pressure, their payoffs will be compromised. The simulation results show that the punishment effect will force the expulsion of partners with different strategies, which will further reduce the proportion of partners with inconsistent strategies in the system. However, in most cases, only moderate fines are most conductive to the evolution of cooperation, and the punishment mechanisms can effectively promote the interdependent network reciprocity. The results on the small world and random network prove the robustness of the result. In addition, under this mechanism, the greater the payoff dependence between partners, the better the effect of interdependent network reciprocity. [ABSTRACT FROM AUTHOR]

This paper studies the problem of developing an efficient signal sampling framework for distributed blind spectrum sensing, together with the corresponding local cognitive radio (CR) decision and fusion rules. A novel collaborative sampling and binary output (CSBO) generating scheme is proposed to overcome the disadvantage of traditional energy detectors for blind spectrum sensing, in which the signal-to-noise ratio (SNR) and level of noise power at the CRs are unknown and thus the decision threshold of local energy detectors cannot be specified. In designing the fusion rule in conjunction with the proposed CSBO scheme, both fixed-sample-size tests and sequential tests are considered. It is theoretically shown that the proposed CSBO scheme outperforms traditional blind cooperative energy detectors with uniform sampling schemes in terms of its ability to increase the amount of information acquired under a given number of samples. Simulation results confirm the theoretical analyses, and demonstrate that, compared with the fixed-sample-size test, the sequential test requires fewer observations on average to achieve comparable detection performance. The reduction in the expected sample size needed in the sequential CSBO test when compared to the fixed-sample-size CSBO can reach 50% when primary signal is present. [ABSTRACT FROM AUTHOR]

Power cables are critical assets for the reliable operation of the grid. The cable lifetime is generally estimated from the conductor temperature, and associated lifetime reduction. However, these tasks are intricate due to the complex physics-of-failure (PoF) degradation mechanism of the cable. This is further complicated with the different sources of uncertainty that affect the cable lifetime estimation. Generally, simplified or deterministic PoF models are adopted resulting in non-accurate decision-making under uncertainty. In contrast, the integration of uncertainties leads to a probabilistic decision-making process impacting directly on the flexibility to adopt decisions. Accordingly, this paper presents a novel cable lifetime estimation framework that connects data-driven probabilistic uncertainty models with PoF-based operation, and degradation models through Bayesian state-estimation techniques. The framework estimates the cable health state, and infers confidence intervals to aid decision-making under uncertainty. The proposed approach is validated with a case study with different configuration parameters, and the effect of measurement errors on cable lifetime are evaluated with a sensitivity analysis. Results demonstrate that ambient temperature measurement errors influence more than load measurement errors, and the greater the cable conductor temperature the greater the influence of uncertainties on the lifetime estimate. [ABSTRACT FROM AUTHOR]

In many diagnostic imaging settings, including positron emission tomography (PET), images are typically used for multiple tasks such as detecting disease and quantifying disease. Unlike conventional image reconstruction that optimizes a single objective, this work proposes a multi-objective optimization algorithm for PET image reconstruction to identify a set of images that are optimal for more than one task. This work is reliant on a genetic algorithm to evolve a set of solutions that satisfies two distinct objectives. In this paper, we defined the objectives as the commonly used Poisson log-likelihood function, typically reflective of quantitative accuracy, and a variant of the generalized scan-statistic model, to reflect detection performance. The genetic algorithm uses new mutation and crossover operations at each iteration. After each iteration, the child population is selected with non-dominated sorting to identify the set of solutions along the dominant front or fronts. After multiple iterations, these fronts approach a single non-dominated optimal front, defined as the set of PET images for which none the objective function values can be improved without reducing the opposing objective function. This method was applied to simulated 2D PET data of the heart and liver with hot features. We compared this approach to conventional, single-objective approaches for trading off performance: maximum likelihood estimation with increasing explicit regularization and maximum a posteriori estimation with varying penalty strength. Results demonstrate that the proposed method generates solutions with comparable to improved objective function values compared to the conventional approaches for trading off performance amongst different tasks. In addition, this approach identifies a diverse set of solutions in the multi-objective function space which can be challenging to estimate with single-objective formulations. [ABSTRACT FROM AUTHOR]

Ageing well has been associated with the responsibility to age actively, successfully, or healthily in public and research discourses. This connection of individual responsibility with ageing has been criticised in Social Gerontology for neglecting the access to social, economic, and health resources. This paper investigates (individual) responsibility, informal support, and public initiatives in discourses on older immigrants in Germany. The research framework employs a sociology of knowledge approach to discourse, which guided the discourse analysis of German policy reports, guidelines and handbooks on ageing and migration from 2000 to 2019 (43 documents in total). The results reveal that besides public initiatives concerning long-term care, health promotion, and social services, informal solutions through social networks are frequently emphasised in the data. The focus, thereby, is on long-term care, which is presented as a responsibility of the extended family. Thus, resources are situated in the family, social networks, and ethnic group, which should be opened and connected with public services; however, the focus is shifting from older immigrants towards local municipalities. This study provides a discourse perspective on the construction of resources and challenges for older immigrants concerning health, care, and social services and offers an assessment of the cultural and integrating/excluding qualities in active ageing discourses. [ABSTRACT FROM AUTHOR]

"There is no such Revival. Around the Philosophical Disquisitions on Alienation in the late Twentieth Century". The following paper proposes to give arguments to relativize the extensive account that the concept of alienation lost theoretical attention in the field of philosophy during the eighties of the last century, and that a revival of the study of the concept occurred in the nineties. The conclusion is that there was no such loss of attention, but that furthermore, the presumed premises in the discussion concerning alienation from the nineties up to the present were delineated during the eighties. This conclusion has two supporters: the type of approach regarding alienation carried out by analytical Marxism and the philosophical incursions into the concept in the context of North American sociology. Based on this, the text offers a systematization of the history of the philosophical study of the concept in two sections or stages. And it concerns itself with two -and not three- stages because, for what was argued, philosophy did not stop talking about alienation in the eighties, although it did so to a much lesser extent than before (specifically, during the sixties and seventies, considered the boom in the philosophical treatment of alienation). [ABSTRACT FROM AUTHOR]

This paper aims to analyze the process of (dis)legitimacy of artistic-sociological consciences in Russia during the early years of Stalinist rule, in order to recover the history of language studies and the context of production of Bakhtinian writings. The method that underlies the reflection undertaken is based on the theoretical-methodological assumptions of Bakhtin (2006 [1979]; 2010 [1920-24]), Medviédev (2016 [1928]) and Volóchinov (2017 [1929], 2013), among others, which present criticisms of the formalist model, prevailing in Stalinist Russia. Historical sources are also used (Deutscher, 2006; Fitzpatrick, 2017) to investigate the political-ideological context of the post-revolution of 1917. The relevance of this manuscript is realized in the contribution of a contemporary but not anachronistic look, which brings to light a critical reading about the construction of philosophical and ethical (aesthetic) approaches on artistic-sociological consciences in Russia. The results show that, despite the execrable situation to which the members of the Bakhtin Circle were subjected amid attempts to (un)artistic legitimacy by the Russian state, researchers and intellectuals resisted and proposed to (re)think the aesthetic object (literary) as conceived by Stalin, whose primary proposal was the unification of the Russian language. Thus, this is not only language movements for the implementation of a linguistic system conception, but also a sociohistorical-cultural reality. [ABSTRACT FROM AUTHOR]

The control of rail signalling is known to be highly dependent on local knowledge and local factors. It is also known to be highly cognitive in its nature involving a constant balancing of system performance within the constraints of safety. In the current paper, data generated through field work with signallers were used to understand the role of local knowledge, set against the background of an existing Local Knowledge Framework (Pickup et al., 2013) that was proposed to help determine the contents and mechanisms behind local knowledge in rail signalling. The field work included interviews with signallers and operations managers along with observations of signaller work. The results showed that the local knowledge framework needs to be expanded to include aspects related to the general public at user worked crossings and level crossings. In addition, the analysis highlights some of the issues with the transmission of local knowledge. The paper then discusses some of the gaps in the current framework, highlighting the importance not only of local knowledge for specific functions of signalling, but how these interact to support trade-offs to balance performance with safety. The implications for the design of signaller work are discussed. [ABSTRACT FROM AUTHOR]

The reconstruction or reformation of society needs social engineering that employs social experiment and theories to society. According to Popper, there are two types of social engineering; utopian and piecemeal. The objective of utopian engineering is to change the whole fabric of society by bringing about revolutionary changes. 'Piecemeal' engineering does not attempt to change the whole society; it focuses on specific problems and tries to solve each through trial and error. Popper is of the view that we should reconstruct or plan the society in the light of factual knowledge of society and should focus on of existing problems. He believes that his method of social sciences is analogous to science for the reason that in sciences scientists deals with existing problems rather than ultimate aims. Popper believes in unity method of science and social science. Critics of Karl Popper identify problems in unity method. Science deals with observable object. Here criterion of rationality is predetermined and 'problem situation' is easy to understand. Social science deals with individual action. Individual has his own perception and background those are not directly observable, so criterion of rationality cannot be predetermined. The aim of this paper is to look into the matter of possibility of scientific sociology by working out limitations of idea of unity method. This study will help in understanding of the theoretical issues regarding Popper's method of social science. [ABSTRACT FROM AUTHOR]

In this paper, I investigate a connection between a common characterisation of freedom and how uncertainty is managed in a Bayesian hierarchical model. To do this, I consider a distributed factorization of a group's optimization of free energy, in which each agent is attempting to align with the group and with its own model. I show how this can lead to equilibria for groups, defined by the capacity of the model being used, essentially how many different datasets it can handle. In particular, I show that there is a "sweet spot" in the capacity of a normal model in each agent's decentralized optimization, and that this "sweet spot" corresponds to minimal free energy for the group. At the sweet spot, an agent can predict what the group will do and the group is not surprised by the agent. However, there is an asymmetry. A higher capacity model for an agent makes it harder for the individual to learn, as there are more parameters. Simultaneously, a higher capacity model for the group, implemented as a higher capacity model for each member agent, makes it easier for a group to integrate a new member. To optimize for a group of agents then requires one to make a trade-off in capacity, as each individual agent seeks to decrease capacity, but there is pressure from the group to increase capacity of all members. This pressure exists because as individual agent's capacities are reduced, so too are their abilities to model other agents, and thereby to establish pro-social behavioural patterns. I then consider a basic two-level (dual process) Bayesian model of social reasoning and a set of three parameters of capacity that are required to implement such a model. Considering these three capacities as dependent elements in a free energy minimization for a group leads to a "sweet surface" in a three-dimensional space defining the triplet of parameters that each agent must use should they hope to minimize free energy as a group. Finally, I relate these three parameters to three notions of freedom and equality in human social organization, and postulate a correspondence between freedom and model capacity. That is, models with higher capacity, have more freedom as they can interact with more datasets. [ABSTRACT FROM AUTHOR]