Political Participation of Local Publics in the Unemployment Field: A Comparison of Lyon and Turin

This article focuses on political participation of local publics in the unemployment field, examining networks of collective actors in Lyon and Turin. Our main question is: Is the participation of local publics fostered under conditions of more developed governance that increases bottom-up access (formal or informal) to elites and institutions in the policy domain? Drawing upon the most recent developments in literatures on social movement theory, governance and network analysis, this article discusses the main variations in terms of political participation of local publics in Lyon and Turin. It then enquires into the main explanatory factors accounting for these variations, thus showing that the openness of governance does influence the level of political participation of local publics. The main argument is that in an open context participation is low, while in a closed (or underdeveloped) context local publics participate more, with differential access to decision-making according to their resources

Precarious voice?: Types of "political citizens" and repertoires of action among European youth

In spite of cross national differences, one of the most relevant concerns for young European people nowadays, is represented by job insecurity. In this contribution, the authors aim to shed light on the triggering role of job precariousness and unemployment on individual repertoires of political actions among young people in three European cities (Lyon in France, Turin in Italy, Cologne in Germany). Theoretically, the paper addresses the existing limitations in the literature on precarious workers' political participation by proposing a new comprehensive framework which includes a broad set of actions, including institutionalized and non-institutionalized forms of political action (e.g. petitions, public demonstrations, disruptive actions). Empirically, a quantitative descriptive technique - Latent Class Cluster Analysis (LCCA)- is deployed allowing to take into account different variables (e.g. socio-demographic conditions, educational attainment, age, employment status and political beliefs) to portray, for each city under analysis and for each "mode" of participation, a set of ideal-typical individual profiles

A model‐based design floating‐point accumulator. Case of study: FPGA implementation of a support vector machine kernel function

Recent research in wearable sensors have led to the development of an advanced platform capable of embedding complex algorithms such as machine learning algorithms, which are known to usually be resource‐demanding. To address the need for high computational power, one solution is to design custom hardware platforms dedicated to the specific application by exploiting, for example, Field Programmable Gate Array (FPGA). Recently, model‐based techniques and automatic code generation have been introduced in FPGA design. In this paper, a new model‐based floating‐point accumulation circuit is presented. The architecture is based on the state‐of‐the‐art delayed buffering algorithm. This circuit was conceived to be exploited in order to compute the kernel function of a support vector machine. The implementation of the proposed model was carried out in Simulink, and simulation results showed that it had better performance in terms of speed and occupied area when compared to other solutions. To better evaluate its figure, a practical case of a polynomial kernel function was considered. Simulink and VHDL post‐implementation timing simulations and measurements on FPGA confirmed the good results of the stand‐alone accumulator

A statistical approach for modeling individual vertical walking forces

This paper proposes a statistical approach for modeling vertical walking forces induced by single pedestrians. To account for the random nature of human walking, the individual vertical walking force is modeled as a series of steps and the gait parameters are assumed to vary at each step. Walking parameters are statistically calibrated with respect to the results of experimental tests performed with a force plate system. Results showed that the walking parameters change during walking and are correlated with each other. The force model proposed in this paper is a step-by-step model based on the description of the multivariate distribution of the walking features through a Gaussian Mixture model. The performance of the proposed model is compared to that of a simplified load model and of two force models proposed in the literature in a numerical case study. Results demonstrate the importance of an accurate modeling of both the single step force and the variability of the individual walking force

Interaction of Water and Oxygen Molecules with Phosphorene: An Ab Initio Study

Phosphorene, the 2D form of black phosphorus, has recently attracted interest for optoelectronic and tribological applications. However, its promising properties are affected by the strong tendency of the layers to oxidize in ambient conditions. A significant effort has been made to identify the role of oxygen and water in the oxidation process. In this work, we introduce a first-principles study of the phosphorene phase diagram and provide a quantitative estimate of the interaction of pristine and fully oxidized phosphorene layers with oxygen and water molecules. Specifically, we study oxidized layers with oxygen coverages of 25% and 50% that keep the typical anisotropic structure of the layers. We found that hydroxilated and hydrogenated phosphorene layers are both energetically unfavorable, leading to structural distortions. We also studied the water physisorption on both pristine and oxidized layers, finding that the adsorption energy gain doubled on the oxidized layers, whereas dissociative chemisorption was always energetically unfavorable. At the same time, further oxidation (i.e., the dissociative chemisorption of O (Formula presented.)) was always favorable, even on oxidized layers. Ab initio molecular dynamics simulations of water intercalated between sliding phosphorene layers showed that even under harsh tribological conditions water dissociation was not activated, thus further strengthening the results obtained from our static calculations. Overall, our results provide a quantitative description of the interaction of phosphorene with chemical species that are commonly found in ambient conditions at different concentrations. The phase diagram that we introduced confirms the tendency of phosphorene layers to fully oxidize due to the presence of O (Formula presented.), resulting in a material with improved hydrophilicity, a piece of information that is relevant for the application of phosphorene, e.g., as a solid lubricant. At the same time, the structural deformations found for the H- and OH- terminated layers undermine their electrical, mechanical, and tribological anisotropic properties and, therefore, the usage of phosphorene

Environmental sustainability of orthopedic devices produced with powder bed fusion

Additive manufacturing consists in melting metallic powders to produce objects from 3D data, layer upon layer. Its industrial applications range from automotive, biomedical (e.g., prosthetic implants for dentistry and orthopedics), aeronautics and others. This study uses life cycle assessment to evaluate the possible improvement in environmental performance of laser-based powder bed fusion additive manufacturing systems on prosthetic device production. Environmental impacts due to manufacturing, use, and end of life of the designed solution were assessed. In addition, two powder production technologies, gas atomization (GA) and plasma atomization (PA), were compared in order to establish the most sustainable one. Production via traditional subtractive technologies and the additive manufacturing production were also compared. 3D building was found to have a significant environmental advantage compared to the traditional technology. The powder production process considerably influences on a damage point of view the additive manufacturing process; however, its impact can be mitigated if GA powders are employed

Pyomyositis associated with abscess formation caused by streptococcus pneumoniae in children: a case report and review of literature

Background: Pyomyositis is an unusual bacterial infection but potential severe in children. Staphylococcus Aureus is the main caused of this disease (70–90%), following by Streptococcus Pyogenes (4–16%). Streptococcus Pneumoniae rarely caused invasive muscular infections. We describe a case of pyomyositis caused by Streptococcus Pneumonia in an adolescent 12-year-old female. Case presentation: I.L. referred to our hospital for high fever associated with right hip and abdominal pain. The blood exams showed increase of leukocytes with prevalence of neutrophils with high level of inflammatory markers (CRP 46,17 mg/dl; Procalcitonin 25,8 ng/ml). The abdomen ultrasonography was unremarkable. The CT and MRI of the abdomen and right hip revealed pyomyositis of the iliopsoas, piriformis and internal shutter associated with collection of pus between the muscular planes (Fig. 1). The patient was admitted to our paediatric care unit, and she was initially treatment with intravenous Ceftriaxone (100 mg/kg/day) and Vancomycin (60 mg/kg/day). On day 2, a pansensitive Streptococcus Pneumoniae was isolated from the blood culture, and the antibiotic treatment was changed to only IV Ceftriaxone. She was successively treated with IV Ceftriaxone for 3 weeks, then continued with oral Amoxicillin for a total of 6 weeks of therapy. The follow up showed a complete resolution of the pyomyositis and psoas abscess after 2 months. Conclusion: Pyomyositis associate with abscess is a rare and very dangerous disease in children. The clinical presentation can mimic symptoms of other pathologies like osteomyelitis or septic arthritis, so many times is hard to identify. The main risk factors include story of recent trauma and immunodeficiency, not present in our case report. The therapy involves the antibiotics and, if possible, abscess drainage. In literature there is much discussion about duration of antibiotic therapy

Improving diagnostic accuracy of dermoscopically equivocal pink cutaneous lesions with reflectance confocal microscopy in telemedicine settings : double reader concordance evaluation of 316 cases

Solitary pink lesions in differential diagnosis with hypopigmented/amelanotic melanoma present a diagnostic challenge in daily practice and are regularly referred for second expert opinion. Reflectance confocal microscopy (RCM) has been shown to improve diagnostic accuracy of dermoscopically equivocal pink lesions. No studies have been performed to evaluate the effect of adding a second expert reader and automatic removal of lesions with discordant management recommendations and its potential effect on diagnostic sensitivity and final management of these lesions in retrospective or telemedicine settings.To improve diagnostic accuracy and reduce potential mismanagement of dermoscopically equivocal pink cutaneous lesions by implementing double reader concordance evaluation of RCM images.316 dermoscopically equivocal pink lesions with dermoscopy-RCM image sets were evaluated retrospectively. Accuracy of three readers was evaluated by single reader evaluation of dermoscopy only and dermoscopy-RCM image sets and finally by double reader evaluation of dermoscopy-RCM image sets. Lesions with discordant diagnosis between two readers were automatically recommended for excision.Dermoscopy only evaluation resulted in an overall sensitivity of 95.9% and specificity of 33.6%, with 1 of 12 amelanotic melanomas mismanaged. Dermoscopy-RCM image set single reader evaluation resulted in an overall sensitivity of 93.9% and overall specificity of 54.2%, with 1 of 12 melanomas mismanaged. Dermoscopy-RCM image set double reader concordance evaluation resulted in an overall sensitivity of 98.3% and specificity of 42.7%, with no amelanotic melanoma mismanagement.Evaluation of dermoscopy-RCM image sets of equivocal pink lesions by a single reader in telemedicine settings is limited by the potential for misdiagnosis of dangerous malignant lesions. Double reader concordance evaluation with automatic referral of lesions for removal in the case of discordant diagnosis improves the diagnostic sensitivity in this subset of lesions and reduce potential misdiagnosis in settings where a second expert opinion may be employed

Multiphoton Laser Microscopy and Fluorescence Lifetime Imaging for the Evaluation of the Skin

Multiphoton laser microscopy is a new, non-invasive technique providing access to the skin at a cellular and subcellular level, which is based both on autofluorescence and fluorescence lifetime imaging. Whereas the former considers fluorescence intensity emitted by epidermal and dermal fluorophores and by the extra-cellular matrix, fluorescence lifetime imaging (FLIM), is generated by the fluorescence decay rate. This innovative technique can be applied to the study of living skin, cell cultures and ex vivo samples. Although still limited to the clinical research field, the development of multiphoton laser microscopy is thought to become suitable for a practical application in the next few years: in this paper, we performed an accurate review of the studies published so far, considering the possible fields of application of this imaging method and providing high quality images acquired in the Department of Dermatology of the University of Modena

Bitter or not? BitterPredict, a tool for predicting taste from chemical structure

Bitter taste is an innately aversive taste modality that is considered to protect animals from consuming toxic compounds. Yet, bitterness is not always noxious and some bitter compounds have beneficial effects on health. Hundreds of bitter compounds were reported (and are accessible via the BitterDB http://bitterdb.agri.huji.ac.il/dbbitter.php), but numerous additional bitter molecules are still unknown. The dramatic chemical diversity of bitterants makes bitterness prediction a difficult task. Here we present a machine learning classifier, BitterPredict, which predicts whether a compound is bitter or not, based on its chemical structure. BitterDB was used as the positive set, and non-bitter molecules were gathered from literature to create the negative set. Adaptive Boosting (AdaBoost), based on decision trees machine-learning algorithm was applied to molecules that were represented using physicochemical and ADME/Tox descriptors. BitterPredict correctly classifies over 80% of the compounds in the hold-out test set, and 70-90% of the compounds in three independent external sets and in sensory test validation, providing a quick and reliable tool for classifying large sets of compounds into bitter and non-bitter groups. BitterPredict suggests that about 40% of random molecules, and a large portion (66%) of clinical and experimental drugs, and of natural products (77%) are bitter