Coffee capsule impacts and recovery techniques: A literature review

The recently developing coffee market has been characterized by profound changes caused by new solutions and technologies for coffee preparation. The polylaminate materials that compose most popular capsules make them a type of waste that is difficult to manage and recycle. This paper analyses the scientific references that deal with studying and improving the management processes of waste coffee capsules, as well as the studies that have analysed their environmental impact. Through a bibliographic review, some encouraging aspects emerged in the recovery of materials that can be adequately recycled (plastics and metals), as well as their possible use for the production of biogas and energy recovery. The need to manually separate the components that make up the capsule still represents one of the main challenges. Many efforts are still needed to favour the environmental sustainability of this waste from a strategic, technological and consumer empowerment point of view

Visual complexity, player experience, performance and physical exertion in motion-based games for older adults

Motion-based video games can have a variety of benefits for the players and are increasingly applied in physical therapy, rehabilitation and prevention for older adults. However, little is known about how this audience experiences playing such games, how the player experience affects the way older adults interact with motion-based games, and how this can relate to therapy goals. In our work, we decompose the player experience of older adults engaging with motion-based games, focusing on the effects of manipulations of the game representation through the visual channel (visual complexity), since it is the primary interaction modality of most games and since vision impairments are common amongst older adults. We examine the effects of different levels of visual complexity on player experience, performance, and exertion in a study with fifteen participants. Our results show that visual complexity affects the way games are perceived in two ways: First, while older adults do have preferences in terms of visual complexity of video games, notable effects were only measurable following drastic variations. Second, perceived exertion shifts depending on the degree of visual complexity. These findings can help inform the design of motion-based games for therapy and rehabilitation for older adults

EDTA and Taurolidine Affect Pseudomonas aeruginosa Virulence In Vitro-Impairment of Secretory Profile and Biofilm Production onto Peritoneal Dialysis Catheters

Peritoneal catheter-associated biofilm infection is reported to be the main cause of refractory peritonitis in peritoneal dialysis patients. The application of antimicrobial lock therapy, based on results on central venous catheters, may be a promising option for treatment of biofilm-harboring peritoneal catheters. This study investigated the effects of two lock solutions, EDTA and taurolidine, on an in vitro model of Pseudomonas aeruginosa biofilm-related peritoneal catheter infection. Silicone peritoneal catheters were incubated for 24 h with a bioluminescent strain of P. aeruginosa. Then, serial dilutions of taurolidine and/or EDTA were applied (for 24 h) once or twice onto the contaminated catheters, and P. aeruginosa viability/persistence were evaluated in real time up to 120 h using a Fluoroskan reader. On selected supernatants, high-performance liquid chromatography mass spectrometry (HPLC-MS) analysis was performed to measure the production of autoinducers (AI), phenazines, and pyocyianines. Taurolidine alone or in combination with EDTA caused a significant decrease of bacterial load and biofilm persistence on the contaminated catheters. The treatment did not lead to the sterilization of the devices, yet it resulted in a substantial destructuration of the catheter-associated P. aeruginosa biofilm. HPLC-MS analysis showed that the treatment of biofilm-harboring catheters with taurolidine and EDTA also affected the secretory activity of the pathogen. EDTA and taurolidine affect P. aeruginosa biofilm produced on peritoneal catheters and profoundly compromise the microbial secretory profile. Future studies are needed to establish whether such lock solutions can be used to render peritoneal catheterrelated infections more susceptible to antibiotic treatment

A human-machine learning curve for stochastic assembly line balancing problems

The Assembly Line Balancing Problem (ALBP) represents one of the most explored research topics in manufacturing. However, only a few contributions have investigated the effect of the combined abilities of humans and machines in order to reach a balancing solution. It is well-recognized that human beings learn to perform assembly tasks over time, with the effect of reducing the time needed for unitary tasks. This implies a need to re-balance assembly lines periodically, in accordance with the increased level of human experience. However, given an assembly task that is partially performed by automatic equipment, it could be argued that some subtasks are not subject to learning effects. Breaking up assembly tasks into human and automatic subtasks represents the first step towards more sophisticated approaches for ALBP. In this paper, a learning curve is introduced that captures this disaggregation, which is then applied to a stochastic ALBP. Finally, a numerical example is proposed to show how this learning curve affects balancing solutions

Machine learning for multi-criteria inventory classification applied to intermittent demand

Multi-criteria inventory classification groups inventory items into classes, each of which is managed by a specific re-order policy according to its priority. However, the tasks of inventory classification and control are not carried out jointly if the classification criteria and the classification approach are not robustly established from an inventory-cost perspective. Exhaustive simulations at the single item level of the inventory system would directly solve this issue by searching for the best re-order policy per item, thus achieving the subsequent optimal classification without resorting to any multi-criteria classification method. However, this would be very time-consuming in real settings, where a large number of items need to be managed simultaneously. In this article, a reduction in simulation effort is achieved by extracting from the population of items a sample on which to perform an exhaustive search of best re-order policies per item; the lowest cost classification of in-sample items is, therefore, achieved. Then, in line with the increasing need for ICT tools in the production management of Industry 4.0 systems, supervised classifiers from the machine learning research field (i.e. support vector machines with a Gaussian kernel and deep neural networks) are trained on these in-sample items to learn to classify the out-of-sample items solely based on the values they show on the features (i.e. classification criteria). The inventory system adopted here is suitable for intermittent demands, but it may also suit non-intermittent demands, thus providing great flexibility. The experimental analysis of two large datasets showed an excellent accuracy, which suggests that machine learning classifiers could be implemented in advanced inventory classification systems

Renewable energy in eco-industrial parks and urban-industrial symbiosis: A literature review and a conceptual synthesis

Replacing fossil fuels with renewable energy sources is considered as an effective means to reduce carbon emissions at the industrial level and it is often supported by local authorities. However, individual firms still encounter technical and financial barriers that hinder the installation of renewables. The eco-industrial park approach aims to create synergies among firms thereby enabling them to share and efficiently use natural and economic resources. It also provides a suitable model to encourage the use of renewable energy sources in the industry sector. Synergies among eco-industrial parks and the adjacent urban areas can lead to the development of optimized energy production plants, so that the excess energy is available to cover some of the energy demands of nearby towns. This study thus provides an overview of the scientific literature on energy synergies within eco-industrial parks, which facilitate the uptake of renewable energy sources at the industrial level, potentially creating urban-industrial energy symbiosis. The literature analysis was conducted by arranging the energy-related content into thematic categories, aimed at exploring energy symbiosis options within eco-industrial parks. It focuses on the urban-industrial energy symbiosis solutions, in terms of design and optimization models, technologies used and organizational strategies. The study highlights four main pathways to implement energy synergies, and demonstrates viable solutions to improve renewable energy sources uptake at the industrial level. A number of research gaps are also identified, revealing that the energy symbiosis networks between industrial and urban areas integrating renewable energy systems, are under-investigated

The dilaton-dominated supersymmetry breaking scenario in the context of the non-minimal supersymmetric model

The phenomenological consequences of the dilaton-type soft supersymmetry breaking terms in the context of the next to minimal supersymmetric standard model are investigated. We always find a very low top quark mass. As a consequence such string vacua are excluded by recent experimental results. The viability of the solution of the $\mu$ term through the introduction of a gauge singlet field is also briefly discussed.Comment: 10 pages,LATE

An Action-Based Approach to Presence: Foundations and Methods

This chapter presents an action-based approach to presence. It starts by briefly describing the theoretical and empirical foundations of this approach, formalized into three key notions of place/space, action and mediation. In the light of these notions, some common assumptions about presence are then questioned: assuming a neat distinction between virtual and real environments, taking for granted the contours of the mediated environment and considering presence as a purely personal state. Some possible research topics opened up by adopting action as a unit of analysis are illustrated. Finally, a case study on driving as a form of mediated presence is discussed, to provocatively illustrate the flexibility of this approach as a unified framework for presence in digital and physical environment

Iron metabolism and lymphocyte characterisation during Covid-19 infection in ICU patients: An observational cohort study

Background: Iron metabolism and immune response to SARS-CoV-2 have not been described yet in intensive care patients, although they are likely involved in Covid-19 pathogenesis. Methods: We performed an observational study during the peak of pandemic in our intensive care unit, dosing D-dimer, C-reactive protein, troponin T, lactate dehydrogenase, ferritin, serum iron, transferrin, transferrin saturation, transferrin soluble receptor, lymphocyte count and NK, CD3, CD4, CD8 and B subgroups of 31 patients during the first 2 weeks of their ICU stay. Correlation with mortality and severity at the time of admission was tested with the Spearman coefficient and Mann-Whitney test. Trends over time were tested with the Kruskal-Wallis analysis. Results: Lymphopenia is severe and constant, with a nadir on day 2 of ICU stay (median 0.555 109/L; interquartile range (IQR) 0.450 109/L); all lymphocytic subgroups are dramatically reduced in critically ill patients, while CD4/CD8 ratio remains normal. Neither ferritin nor lymphocyte count follows significant trends in ICU patients. Transferrin saturation is extremely reduced at ICU admission (median 9%; IQR 7%), then significantly increases at days 3 to 6 (median 33%, IQR 26.5%, p value 0.026). The same trend is observed with serum iron levels (median 25.5 μg/L, IQR 69 μg/L at admission; median 73 μg/L, IQR 56 μg/L on days 3 to 6) without reaching statistical significance. Hyperferritinemia is constant during intensive care stay: however, its dosage might be helpful in individuating patients developing haemophagocytic lymphohistiocytosis. D-dimer is elevated and progressively increases from admission (median 1319 μg/L; IQR 1285 μg/L) to days 3 to 6 (median 6820 μg/L; IQR 6619 μg/L), despite not reaching significant results. We describe trends of all the abovementioned parameters during ICU stay. Conclusions: The description of iron metabolism and lymphocyte count in Covid-19 patients admitted to the intensive care unit provided with this paper might allow a wider understanding of SARS-CoV-2 pathophysiology