Photon and di-photon production at ATLAS

The latest ATLAS measurements of the cross section for the inclusive production of isolated prompt photons in $pp$ collisions at a centre-of-mass energy $\sqrt{s}$ = 7 TeV at the LHC are presented, as well as the measurement of the di-photon production cross section.Comment: 4 pages, 2 figures. Proceedings of the 15th Lomonosov Conference on Elementary Particle Physics, 18-24 August 2011, Moscow (Russia

Searches for the Higgs boson at the LHC

The search strategy for the Standard Model Higgs boson at the Large Hadron Collider is reviewed, with a particular emphasis on its potential observation by the ATLAS and CMS detectors in the $\gamma\gamma$, $\tau^+\tau^-$, $ZZ^{*}$ and $WW^{*}$ final states. The combined Higgs discovery potential of ATLAS and CMS is discussed, as well as the expected exclusion limits on the production rate times the branching ratio as a function of the Higgs mass and the collected luminosity.Comment: 4 pages, 6 figures, Proceedings of the 'XXIeme Rencontres de Blois', 21st - 26th June 200

Quality factor analysis and optimization of digital filtering signal reconstruction for liquid ionization calorimeters

The Optimal Filtering (OF) reconstruction of the sampled signals from a particle detector such as a liquid ionization calorimeter relies on the knowledge of the normalized pulse shapes. This knowledge is always imprecise, since there are residual differences between the true ionization pulse shapes and the predicted ones, whatever the method used to model or fit the particle--induced signals. The systematic error introduced by the residuals on the signal amplitude estimate is analyzed, as well as the effect on the quality factor provided by the OF reconstruction. An analysis method to evaluate the residuals from a sample of signals is developed and tested with a simulation tool. The correction obtained is showed to preserve the original amplitude normalization, while restoring the expected $\chi^2$--like behavior of the quality factor.Comment: Accepted for publication in Nuclear Inst. and Methods in Physics Research,

Inside the black box of collective reputation

The literature on collective reputation is still in its infancy. Despite the existence of a (limited) number of valuable theoretical works studying the process of collective reputation building, there is still no comprehensive analysis of this concept. In addition, due to data limitation, there are no empirical studies testing the determinants of group reputation. This work intends to provide a comprehensive analysis of reputational equilibria within coalitions of agents. In order to do so, we design a static and dynamic (over 30 years) study on the universe of coalitions of companies, within the wine market, looking at the role exerted by the characteristics of the coalition itself (its age and size), the rules set and the actions put forward by the group of agents in order to reach and maintain a certain level of collective reputation, and the context in which they operate. Results shed new lights into this ubiquitous phenomenon.reputation, collective reputation, asymmetric information, quality standards, wine.

Individual and Collective Reputation: Lessons from the Wine Market

The concept of reputation has been used in every field of economic research, given its capacity to affect the outcome of all economic and financial transactions. The theoretical debate on reputation is very rich, but the mechanisms of reputation building have not been explored enough from the empirical viewpoint. In this paper we investigate the determinants of firm reputation taking into consideration the interactions between individual and collective reputation. This paper is one of the first attempts to provide robust evidence on the determinants of firm reputation using a large set of controls applied to a database not affected by self-selection bias. In fact, we constructed a new database containing the universe of wineries located in four regions of the North-West of Italy with an established national reputation and focus on the determinants of the “jump” from national to international reputation. Our research confirms the prediction of the theoretical literature and shows the positive effect of firm age, size, investments and producer’s intrinsic motivations, and of collective reputation on individual firm reputation. Cooperatives seem to decrease their reputation when the number of associated members rises, due to free-riding and traceability problems. In contrast with previous research, relying on well-known external consultants does not acquire any outside reputation. Finally, by comparing the regression results on the determinants of national and international reputation it emerges the relevance of the mechanisms of the evaluation process: the higher proximity to the wineries of a national observer permits a better and more technical knowledge of the quality provided, allowing small niche producers with very low productivity to emerge and be known. For the same reason, the national classification system (i.e. the DOCG system) exerts a significant effect only on the international reputation of wineries, but not on the national one where the effect of collective reputation (i.e. the reputation of single denominations like Barolo) seems to prevail.reputation, credibility, asymmetric information, quality standards, Industrial Organization, L14, L15,

Shedding new light on the organization : an empirical analysis of some key aspects of business organizations

There is a striking difference between the large number of theoretical papers on firm organization and the lack of quantitative empirical evidence. If on the one side economists are increasingly concerned with organization of firms, on the other side organization still remains an ambiguous concept, hardly analyzed empirically. In this thesis I develop a new empirical methodology based upon business history (see Chapter 1) and previous theoretical work which allows me to describe (some aspects of) the organization of firms in quantitative terms. This approach is instrumental to analyzing the hierarchical structure and the allocation of decision-making activities in a sample composed of 438 Italian metalworking plants. I also study the dynamics of firm organization in the 1980s and 1990s. The results of Chapter 2 show that the (static) choice of the organizational form crucially relies upon the "loss of control phenomenon". They also illustrate that the dynamics of hierarchical structure follows an inertial process, characterized by incremental adjustments. Lastly, both the organization and, more interestingly, its evolution differ from one category of plant to another depending crucially on plant size. Moreover, I test (some of) the predictions of economic theory on the size of the management hierarchy (Chapter 3), the allocation of real and formal authority (Chapter 4), and structural inertia (Chapter 6) through the estimates of econometric models (i. e., multinomial logit, ordered logit, and survival). The findings of Chapter 3 show that the plant size, the characteristics (i. e., vintage and extent of use) of the production and communication technology in use, the plant's ownership status (i. e., State versus private ownership, and differences in the nationality of firms to which plants belong) are key in explaining the complexity of a plant's management hierarchy. In addition, in accordance with theoretical work, the findings of Chapter 4 show that the size of a plant's organization, the characteristics of the production and communication technologies in use, the urgency of decisions, and the presence of monetary incentive schemes aligning plant manager's objectives with those of the firm as a whole figure prominently in explaining whether authority is delegated to the plant manager or not. The structural and organizational characteristics of a plant's parent firm do also play a role, with the likelihood of decentralization of decision-making increasing with parent firm's size and decreasing with the adoption by the parent firm of a M-form type of organization. Lastly, the nature of the decision turns out to affect the allocation of formal authority, with decisions concerning the labor force being more frequently delegated to plant managers than those related to investments in capital equipment. On the contrary, it does not influence the allocation of real authority when the formal right to decide remains with the corporate superior. Finally in Chapter 61 find that both influence activities and technology adoptions are key in explaining the evolution of business organizations. Influence activities tend to inhibit organizational change causing structural inertia, whilst the technology adoptions increase the likelihood of changing the structure of the management hierarchy

nirs footprint of bio fertilizers from hay litter bags

The biofertilization of cropsusing microbial biota in the soil (MBS) is a modern practice that is used to sustain fertility. MBS agents can promote the yield and health of crops, by luxuriating in the shoot as well as in the root systems. Farmers devoted to systematic MBS fertilization are creating a "Symbiotic" (S) form of agriculture, which offers a greater advantage of resilience than Conventional (C) or organic farming. Since MBS is involved in organic matter degradation, hay-litter-bag probes can be used to reflect a global functionality of the active soil, in the short-medium term. It is here shown that the NIRS hay-litter-bag technique, intended not as mass decay but as a quality evolution of the hay probes, can be modelled as a valid footprint of S vs. C soils. A patented MBS was used in eight experiments in which litter-bags from an S treated thesis were compared with equivalent litter-bags from a non-inoculated C thesis. The chemical signature of the S vs. C in the litter-bag composition was a percentage decrease of sugars and fibres. A smart NIRS device was used to discriminate the origin of the S vs. C litter-bags and a sensitivity of 71% (P<0.0001) was obtained. External validations on 37 S farms showed that three NIRS models discriminated the true positive S spectra, with a sensitivity of 90% as single and 98% as compound probabilities The NIRS radiation of the hay-litter-bags confirmed the results of the S vs. C agriculture soil footprint. Moreover, the SCIO-NIR devices also made it possible to connect the S farms in a smart network

A Transfer Learning and Explainable Solution to Detect mpox from Smartphones images

In recent months, the monkeypox (mpox) virus -- previously endemic in a limited area of the world -- has started spreading in multiple countries until being declared a ``public health emergency of international concern'' by the World Health Organization. The alert was renewed in February 2023 due to a persisting sustained incidence of the virus in several countries and worries about possible new outbreaks. Low-income countries with inadequate infrastructures for vaccine and testing administration are particularly at risk. A symptom of mpox infection is the appearance of skin rashes and eruptions, which can drive people to seek medical advice. A technology that might help perform a preliminary screening based on the aspect of skin lesions is the use of Machine Learning for image classification. However, to make this technology suitable on a large scale, it should be usable directly on mobile devices of people, with a possible notification to a remote medical expert. In this work, we investigate the adoption of Deep Learning to detect mpox from skin lesion images. The proposal leverages Transfer Learning to cope with the scarce availability of mpox image datasets. As a first step, a homogenous, unpolluted, dataset is produced by manual selection and preprocessing of available image data. It will also be released publicly to researchers in the field. Then, a thorough comparison is conducted amongst several Convolutional Neural Networks, based on a 10-fold stratified cross-validation. The best models are then optimized through quantization for use on mobile devices; measures of classification quality, memory footprint, and processing times validate the feasibility of our proposal. Additionally, the use of eXplainable AI is investigated as a suitable instrument to both technically and clinically validate classification outcomes.Comment: Submitted to Pervasive and Mobile Computin