Risk assessment in a materials recycling facility: Perspectives for reducing operational issues

Mechanical separation of light packaging waste is a useful practice for improving the quality of the recyclable waste flows and its exploitation in a frame of the circular economy. Materials Recovery Facilities can treat from 3000 to 5000 tons per year of light packaging waste. Concerning the plastic content, this is divided in four flows: PET, HDPE, other plastics, and waste rejects. The last two are generally used for energy recovery. For improving the quality of the recyclable plastic waste, a manual separation is required for reducing the impurities detectable in the final products. However, this practice could enhance the risk at work of the operators, which should be constantly monitored. This article explores the main differences of a manual separation and of a mechanical separation, assessing the costs and the health risk for the workers. The analysis started from the situation in an Italian Materials Recovery Facility, generalizing the context; a future scenario with the application of a mechanical separation is theoretically introduced. The main results obtained suggest that the manual separation plant improves the quality of the material, though increasing the risk of the operators due to the possible contact with sharp waste, sanitary danger, and risk of injuries for the mismanagement of machines, among others. The mechanical separation can be considered a real advantage from an economic point of view, since the operating costs are lower and the investment could be recovered in around 10 years, in an Italian-like context. On balance, on the one hand, the article provides indications for the private sector for improving the management of a Materials Recovery Facility, while, on the other hand, it detects the main pros and cons of both methodologies. © 2018 by the authors

Robust Dropping Criteria for F-norm Minimization Based Sparse Approximate Inverse Preconditioning

Dropping tolerance criteria play a central role in Sparse Approximate Inverse preconditioning. Such criteria have received, however, little attention and have been treated heuristically in the following manner: If the size of an entry is below some empirically small positive quantity, then it is set to zero. The meaning of "small" is vague and has not been considered rigorously. It has not been clear how dropping tolerances affect the quality and effectiveness of a preconditioner $M$. In this paper, we focus on the adaptive Power Sparse Approximate Inverse algorithm and establish a mathematical theory on robust selection criteria for dropping tolerances. Using the theory, we derive an adaptive dropping criterion that is used to drop entries of small magnitude dynamically during the setup process of $M$. The proposed criterion enables us to make $M$ both as sparse as possible as well as to be of comparable quality to the potentially denser matrix which is obtained without dropping. As a byproduct, the theory applies to static F-norm minimization based preconditioning procedures, and a similar dropping criterion is given that can be used to sparsify a matrix after it has been computed by a static sparse approximate inverse procedure. In contrast to the adaptive procedure, dropping in the static procedure does not reduce the setup time of the matrix but makes the application of the sparser $M$ for Krylov iterations cheaper. Numerical experiments reported confirm the theory and illustrate the robustness and effectiveness of the dropping criteria.Comment: 27 pages, 2 figure

Periodicities in the Daily Proton Fluxes from 2011 to 2019 Measured by the Alpha Magnetic Spectrometer on the International Space Station from 1 to 100 GV

We present the precision measurement of the daily proton fluxes in cosmic rays from May 20, 2011 to October 29, 2019 (a total of 2824 days or 114 Bartels rotations) in the rigidity interval from 1 to 100 GV based on 5.5 ×109 protons collected with the Alpha Magnetic Spectrometer aboard the International Space Station. The proton fluxes exhibit variations on multiple timescales. From 2014 to 2018, we observed recurrent flux variations with a period of 27 days. Shorter periods of 9 days and 13.5 days are observed in 2016. The strength of all three periodicities changes with time and rigidity. The rigidity dependence of the 27-day periodicity is different from the rigidity dependences of 9-day and 13.5-day periods. Unexpectedly, the strength of 9-day and 13.5-day periodicities increases with increasing rigidities up to ∼10 GV and ∼20 GV , respectively. Then the strength of the periodicities decreases with increasing rigidity up to 100 GV

Hemoxygenase-1 Promotes Head and Neck Cancer Cell Viability

Head and neck squamous cell carcinoma (HNSCC) is a remarkably heterogeneous disease with around 50% mortality, a fact that has prompted researchers to try new approaches to improve patient survival. Hemoxygenase-1 (HO-1) is the rate-limiting step for heme degradation into carbon monoxide, free iron and biliverdin. We have previously reported that HO-1 protein is upregulated in human HNSCC samples and that it is localized in the cytoplasmic and nuclear compartments; additionally, we have demonstrated that HO-1 nuclear localization is associated with malignant progression. In this work, by using pharmacological and genetic experimental approaches, we begin to elucidate the mechanisms through which HO-1 plays a role in HNSCC. We found that high HO-1 mRNA was associated with decreased patient survival in early stages of HNSCC. In vitro experiments have shown that full-length HO-1 localizes in the cytoplasm, and that, depending on its enzymatic activity, it increases cell viability and promotes cell cycle progression. Instead, HO-1 does not alter migration capacity. Furthermore, we show that C-terminal truncated HO-1 localizes into the nucleus, increases cell viability and promotes cell cycle progression. In conclusion, we herein demonstrate that HO-1 displays protumor activities in HNSCC that depend, at least in part, on the nuclear localization of HO-1.Centro de Investigaciones Inmunológicas Básicas y Aplicada

Familial aggregation of MATRICS Consensus Cognitive Battery scores in a large sample of outpatients with schizophrenia and their unaffected relatives

Background The increased use of the MATRICS Consensus Cognitive Battery (MCCB) to investigate cognitive dysfunctions in schizophrenia fostered interest in its sensitivity in the context of family studies. As various measures of the same cognitive domains may have different power to distinguish between unaffected relatives of patients and controls, the relative sensitivity of MCCB tests for relative-control differences has to be established. We compared MCCB scores of 852 outpatients with schizophrenia (SCZ) with those of 342 unaffected relatives (REL) and a normative Italian sample of 774 healthy subjects (HCS). We examined familial aggregation of cognitive impairment by investigating within-family prediction of MCCB scores based on probands' scores.Methods Multivariate analysis of variance was used to analyze group differences in adjusted MCCB scores. Weighted least-squares analysis was used to investigate whether probands' MCCB scores predicted REL neurocognitive performance.Results SCZ were significantly impaired on all MCCB domains. REL had intermediate scores between SCZ and HCS, showing a similar pattern of impairment, except for social cognition. Proband's scores significantly predicted REL MCCB scores on all domains except for visual learning.Conclusions In a large sample of stable patients with schizophrenia, living in the community, and in their unaffected relatives, MCCB demonstrated sensitivity to cognitive deficits in both groups. Our findings of significant within-family prediction of MCCB scores might reflect disease-related genetic or environmental factors

Social cognition in people with schizophrenia: A cluster-analytic approach

Background The study aimed to subtype patients with schizophrenia on the basis of social cognition (SC), and to identify cut-offs that best discriminate among subtypes in 809 out-patients recruited in the context of the Italian Network for Research on Psychoses. Method A two-step cluster analysis of The Awareness of Social Inference Test (TASIT), the Facial Emotion Identification Test and Mayer-Salovey-Caruso Emotional Intelligence Test scores was performed. Classification and regression tree analysis was used to identify the cut-offs of variables that best discriminated among clusters. Results We identified three clusters, characterized by unimpaired (42%), impaired (50.4%) and very impaired (7.5%) SC. Three theory-of-mind domains were more important for the cluster definition as compared with emotion perception and emotional intelligence. Patients more able to understand simple sarcasm (14 for TASIT-SS) were very likely to belong to the unimpaired SC cluster. Compared with patients in the impaired SC cluster, those in the very impaired SC cluster performed significantly worse in lie scenes (TASIT-LI <10), but not in simple sarcasm. Moreover, functioning, neurocognition, disorganization and SC had a linear relationship across the three clusters, while positive symptoms were significantly lower in patients with unimpaired SC as compared with patients with impaired and very impaired SC. On the other hand, negative symptoms were highest in patients with impaired levels of SC. Conclusions If replicated, the identification of such subtypes in clinical practice may help in tailoring rehabilitation efforts to the person's strengths to gain more benefit to the person