A survey on C 1,1 fuctions: theory, numerical methods and applications

In this paper we survey some notions of generalized derivative for C 1,1 functions. Furthermore some optimality conditions and numerical methods for nonlinear minimization problems involving C1,1 data are studied.

Mean value theorem for continuous vector functions by smooth approximations

In this note a mean value theorem for continuous vector functions is introduced by mollified derivatives and smooth approximations

C 1,1 functions and optimality conditions

In this work we provide a characterization of C 1,1 functions on Rn (that is, differentiable with locally Lipschitz partial derivatives) by means of second directional divided differences. In particular, we prove that the class of C 1,1 functions is equivalent to the class of functions with bounded second directional divided differences. From this result we deduce a Taylor's formula for this class of functions and some optimality conditions. The characterizations and the optimality conditions proved by Riemann derivatives can be useful to write minimization algorithms; in fact, only the values of the function are required to compute second order conditions.divided differences, Riemann derivatives, C 1,1 functions, nonlinear optimization, generalized derivatives

Second-order mollified derivatives and optimization

The class of strongly semicontinuous functions is considered. For these functions the notion of mollified derivatives, introduced by Ermoliev, Norkin and Wets, is extended to the second order. By means of a generalized Taylor's formula, second order necessary and sufficient conditions are proved for both unconstrained and constrained optimizationMollifiers, optimization, smooth approximations, strong semicontinuity

Statistical sampling applied to the radiological characterization of historical waste

International audienceThe evaluation of the activity of radionuclides in radioactive waste is required for its disposal in final repositories. Easy-to-measure nuclides, like g-emitters and high-energy X-rays, can be measured via non-destructive nuclear techniques from outside a waste package. Some radionuclides are difficult-to-measure (DTM) from outside a package because they are a-or b-emitters. The present article discusses the application of linear regression, scaling factors (SF) and the so-called "mean activity method" to estimate the activity of DTM nuclides on metallic waste produced at the European Organization for Nuclear Research (CERN). Various statistical sampling techniques including simple random sampling, systematic sampling, stratified and authoritative sampling are described and applied to 2 waste populations of activated copper cables. The bootstrap is introduced as a tool to estimate average activities and standard errors in waste characterization. The analysis of the DTM Ni-63 is used as an example. Experimental and theoretical values of SFs are calculated and compared. Guidelines for sampling historical waste using probabilistic and non-probabilistic sampling are finally given

The role of technology on adherence to physical activity programs in patients with chronic diseases experiencing fatigue: a systematic review

Background The beneficial role of physical activity (PA) to manage the health condition of patients with chronic diseases is well known. However, adherence to PA guidelines in this group is still low. Monitoring and user-interface technology could represent a significant tool to increase exercise adherence to those particular groups who experience difficulties in adhering to regular and substantial physical activity, and could be supportive in increasing the success of PA programs and interventions. This systematic review aimed at evaluating the effect of physical activity monitoring technology in improving adherence to a PA program in patients with chronic diseases experiencing fatigue. Methods This systematic review was conducted according to PRISMA guidelines. The literature search was performed in Embase, Medline, Biosis, Scopus, and SPORTDiscus. We filtered the literature according to the question: “Does monitoring technology affect adherence to physical activity and exercise programs in patients with chronic diseases perceiving fatigue?”. Results The search resulted in 1790 hits; finally, eight studies were included, with a total number of 205 patients. Study quality was moderate except for one study of high quality. Only three disease types emerged, COPD, HF, and cancer. PA programs were rather short (from 8 to 13 weeks) except for one 3-year-long study. Five studies employed pedometers and two an activity monitor. Three studies based their adherence on steps, the remaining studies focused on active minutes. Adherence was explicitly reported in two studies, and otherwise derived. Four studies showed high adherence levels (85% week-10, 89% week-8, 81% week-13, 105% week-13, 83% average week-1–12) and three low levels (56% week-12, 41% year-2, 14 year-3). Conclusion The small number of studies identified did not allow to establish whether the use of monitoring technology could improve adherence to PA programs in patients with chronic diseases experiencing fatigue, but the current evidence seems to suggest that this is a field warranting further study, particularly into how monitoring technology can help to engage patients to adhere to PA programs

The Global Reporting Initiative’s (GRI) past, present and future : critical reflections and a research agenda on sustainability reporting (standard-setting)

https://www.emerald.com/insight/publication/issn/0114-0582hj2023Accountin

The effects of MgO, Na2O and SO3 on industrial clinkering process: phase composition, polymorphism, microstructure and hydration, using a multidisciplinary approach

Preprint publicado en: Materials Characterization Volume 155, September 2019, 109809The present investigation deals with how minor elements (their oxides: MgO, Na2O and SO3) in industrial kiln feeds affect (i) chemical reactions upon clinkering, (ii) resulting phase composition and microstructure of clinker, (iii) hydration process during cement production. Our results show that all these points are remarkably sensitive to the combination and interference effects between the minor chemical species mentioned above. Upon clinkering, all the industrial raw meals here used exhibit the same formation temperature and amount of liquid phase. Minor elements are preferentially hosted by secondary phases, such as periclase. Conversely, the growth rate of the main clinker phases (alite and belite) is significantly affected by the nature and combination of minor oxides. MgO and Na2O give a very fast C3S formation rate at T > 1450 K, whereas Na2O and SO3 boost C2S After heating, if SO3 occurs in combination with MgO and/or Na2O, it does not inihibit the C3S crystallisation as expected. Rather, it promotes the stabilisation of M1-C3S, thus indirectly influencing the aluminate content, too. MgO increseases the C3S amount and promotes the stabilisation of M3-C3S, when it is in combination with Na2O. Na2O seems to be mainly hosted by calcium aluminate structure, but it does not induce the stabilisation of the orhtorhombic polymorph, as supposed to occur. Such features play a key role in predicting the physicalmechanical performance of a final cement (i.e. rate of hydration and hardening) when used as a bulding material.The present study has been partly funded by the project PRIN 2017 (2017L83S77), of the Italian Ministry for Education, University and Research (MIUR)

Calculative practices, social movements and the rise of collective identity: how #istayathome mobilised a nation

Purpose – The Italian government addressed the first wave of its COVID-19 outbreak with a series of social restrictions and calculative practices, all branded with the slogan #istayathome. The hashtag quickly went viral, becoming both a mandate and a mantra and, as the crisis played out, we witnessed the rise of the Italian social movement #istayathome. This study examines how the government’s calculative practices led to #istayathome and the constituents that shaped this social movement. Design/methodology/approach – The authors embrace social movement theory and the collective identity perspective to examine #istayathome as a collective action and social movement. Using passive netnography, text mining and interpretative text analysis enhanced by machine learning, the authors analysed just over 350,000 tweets made during the period March to May 2020, each brandishing the hashtag #istayathome. Findings – The #istayathome movement gained traction as a response to the Italian government’s call for collective action. Thus, people became an active part of mobilising collective responsibility, enhancing the government’s plans. A collective identity on the part of the Italian people sustained the mass mobilisation, driven by cohesion, solidarity and a deep cultural trauma from COVID-19’s dramatic effects. Popular culture and Italy’s long traditions also helped to form the collective identity of #istayathome. This study found that calculative practices acted as a persuasive technology in forming this collective identity and mobilising people’s collective action. Numbers stimulated the cognitive, moral and emotional connections of the social ties shaping collective identity and responsibility. Thus, through collective identity, calculative practices indirectly influenced mass social behaviors and the social movement. Originality/value – This study offers a novel theoretical perspective and empirical knowledge to explain how government power affects people’s culture and everyday life. It unveils the sociological drivers that mobilise collective behaviors and enriches the accounting literature on the effects of calculative practices in managing emergencies. The study contributes to theory by providing an understanding of how calculative practices can influence collective behaviors and can be used to construct informal networks that go beyond the government’s traditional formalities