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

Effectiveness of dolutegravir-based regimens as either first-line or switch antiretroviral therapy: data from the Icona cohort

Introduction: Concerns about dolutegravir (DTG) tolerability in the real-life setting have recently arisen. We aimed to estimate the risk of treatment discontinuation and virological failure of DTG-based regimens from a large cohort of HIV-infected individuals. Methods: We performed a multicentre, observational study including all antiretroviral therapy (ART)-naïve and virologically suppressed treatment-experienced (TE) patients from the Icona (Italian Cohort Naïve Antiretrovirals) cohort who started, for the first time, a DTG-based regimen from January 2015 to December 2017. We estimated the cumulative risk of DTG discontinuation regardless of the reason and for toxicity, and of virological failure using Kaplan–Meier curves. We used Cox regression model to investigate predictors of DTG discontinuation. Results: About 1679 individuals (932 ART-naïve, 747 TE) were included. The one- and two-year probabilities (95% CI) of DTG discontinuation were 6.7% (4.9 to 8.4) and 11.5% (8.7 to 14.3) for ART-naïve and 6.6% (4.6 to 8.6) and 7.6% (5.4 to 9.8) for TE subjects. In both ART-naïve and TE patients, discontinuations of DTG were mainly driven by toxicity with an estimated risk (95% CI) of 4.0% (2.6 to 5.4) and 2.5% (1.3 to 3.6) by one year and 5.6% (3.8 to 7.5) and 4.0% (2.4 to 5.6) by two years respectively. Neuropsychiatric events were the main reason for stopping DTG in both ART-naïve (2.1%) and TE (1.7%) patients. In ART-naïve, a concomitant AIDS diagnosis predicted the risk of discontinuing DTG for any reason (adjusted relative hazard (aRH) = 3.38, p = 0.001), whereas starting DTG in combination with abacavir (ABC) was associated with a higher risk of discontinuing because of toxicity (aRH = 3.30, p = 0.009). TE patients starting a DTG-based dual therapy compared to a triple therapy had a lower risk of discontinuation for any reason (adjusted hazard ratio (aHR) = 2.50, p = 0.037 for ABC-based triple-therapies, aHR = 3.56, p = 0.012 for tenofovir-based) and for toxicity (aHR = 5.26, p = 0.030 for ABC-based, aHR = 6.60, p = 0.024 for tenofovir-based). The one- and two-year probabilities (95% CI) of virological failure were 1.2% (0.3 to 2.0) and 4.6% (2.7 to 6.5) in the ART naïve group and 2.2% (1.0 to 3.3) and 2.9% (1.5 to 4.3) in the TE group. Conclusions: In this large cohort, DTG showed excellent efficacy and optimal tolerability both as first-line and switching ART. The low risk of treatment-limiting toxicities in ART-naïve as well as in treated individuals reassures on the use of DTG in everyday clinical practice

Exposure to Air Pollution in Transport Microenvironments

People spend approximately 90% of their day in confined spaces (at home, work, school or in transit). During these periods, exposure to high concentrations of atmospheric pollutants can pose serious health risks, particularly to the respiratory system. The objective of this paper is to define a framework of the existing literature on the assessment of air quality in various transport microenvironments. A total of 297 papers, published from 2002 to 2021, were analyzed with respect to the type of transport microenvironments, the pollutants monitored, the concentrations measured and the sampling methods adopted. The analysis emphasizes the increasing interest in this topic, particularly regarding the evaluation of exposure in moving cars and buses. It specifically focuses on the exposure of occupants to atmospheric particulate matter (PM) and total volatile organic compounds (TVOCs). Concentrations of these pollutants can reach several hundreds of µg/m3 in some cases, significantly exceeding the recommended levels. The findings presented in this paper serve as a valuable resource for urban planners and decision-makers in formulating effective urban policies

Post-Occupancy Evaluation’s (POE) Applications for Improving Indoor Environment Quality (IEQ)

To improve buildings and their characteristics, the feedback provided directly by users is generally fundamental in order to be able to adapt the technical and structural functions to the well-being of users. The post-occupancy evaluation (POE) fits perfectly into this context. The POE, through qualitative and quantitative information on the interior environment, makes it possible to identify the differences between the performances modeled in the design phase and the real performances experienced by the occupants. This review of 234 articles, published between 2006 and 2022, aims to analyze and compare the recent literature on the application of the POE methodology. The aim was to provide both a qualitative and quantitative assessment of the main factors that comprise the indoor environmental quality (IEQ). The study highlighted the factors that comprise the quality of the indoor environment, as well as the variables that are usually analyzed to describe the well-being of the occupants. The results suggested which are the most common approaches in carrying out POE studies and will identify the factors that most influence the determination of the good quality of an indoor environment

wGrapeUNIPD-DL: An open dataset for white grape bunch detection

National and international Vitis variety catalogues can be used as image datasets for computer vision in viticulture. These databases archive ampelographic features and phenology of several grape varieties and plant structures images (e.g. leaf, bunch, shoots). Although these archives represent a potential database for computer vision in viticulture, plant structure images are acquired singularly and mostly not directly in the vineyard. Localization computer vision models would take advantage of multiple objects in the same image, allowing more efficient training. The present images and labels dataset was designed to overcome such limitations and provide suitable images for multiple cluster identification in white grape varieties. A group of 373 images were acquired from later view in vertical shoot position vineyards in six different Italian locations at different phenological stages. Images were then labelled in YOLO labelling format. The dataset was made available both in terms of images and labels. The real number of bunches counted in the field, and the number of bunches visible in the image (not covered by other vine structures) was recorded for a group of images in this dataset

Biorefinery development in livestock production systems: Applications, challenges, and future research directions

Sustainable development and reducing natural and energy resource consumption are the focus of the policies of many institutions. In this context, livestock farming is one of the major anthropogenic sources of GHG and acidifying gas emissions and requires comprehensive analysis to minimise its ecological footprint. For this reason, it is beneficial to analyse the various processes within this production sector to reduce the consumption of resources, particularly water and soil consumption; reduce energy consumption; and try to valorise the biowaste produced, especially manure, byproducts and wastewater. Reusing residual bioresource and organic waste offers the possibility of valorising a discarded product and, at the same time, reducing the consumption of natural resources. For this purpose, biorefinery processes allow bioresources to be transformed into bioproducts or bioenergy. Therefore, this study investigates the application of biorefinery processes to animal-derived waste, aiming to extract valuable resources while curbing resource consumption. This review analysed 293 scientific papers on biorefinery processes published in the last 11 years applied to livestock biomass to extract relevant information to understand the evolution of this topic and formulate hypotheses regarding future research di- rections. The analysis strongly emphasizes energy production and a growing interest in insect cultivation. In the coming years, one of the most significant challenges will be the successful transfer of technologies and processes from experimental research to the applied industry. To do this, it will be necessary to reduce costs, exploit economies of scale, improve process management, and develop synergies between different industrial sectors to implement smart circular economy systems. Overall, this review aims to clarify the hypothesis driving research in this area and emphasizes the tangible applications of findings within the broader context of sustainable resource management

Monitoring within-field variability of corn yield using sentinel-2 and machine learning techniques

Monitoring and prediction of within-field crop variability can support farmers to make the right decisions in different situations. The current advances in remote sensing and the availability of high resolution, high frequency, and free Sentinel-2 images improve the implementation of Precision Agriculture (PA) for a wider range of farmers. This study investigated the possibility of using vegetation indices (VIs) derived from Sentinel-2 images and machine learning techniques to assess corn (Zea mays) grain yield spatial variability within the field scale. A 22-ha study field in North Italy was monitored between 2016 and 2018; corn yield was measured and recorded by a grain yield monitor mounted on the harvester machine recording more than 20,000 georeferenced yield observation points from the study field for each season. VIs from a total of 34 Sentinel-2 images at different crop ages were analyzed for correlation with the measured yield observations. Multiple regression and two different machine learning approaches were also tested to model corn grain yield. The three main results were the following: (i) the Green Normalized Difference Vegetation Index (GNDVI) provided the highest R2 value of 0.48 for monitoring within-field variability of corn grain yield; (ii) the most suitable period for corn yield monitoring was a crop age between 105 and 135 days from the planting date (R4-R6); (iii) Random Forests was the most accurate machine learning approach for predicting within-field variability of corn yield, with an R2 value of almost 0.6 over an independent validation set of half of the total observations. Based on the results, within-field variability of corn yield for previous seasons could be investigated from archived Sentinel-2 data with GNDVI at crop stage (R4-R6)

Order Picking Systems: A Queue Model for Dimensioning the Storage Capacity, the Crew of Pickers, and the AGV Fleet

Designing an order picking system can be very complex, as several interrelated control variables are involved. We address the sizing of the storage capacity of the picking bay, the crew of pickers, and the AGV fleet, which are the most important variables from a tactical viewpoint in a parts-to-pickers system. Although order picking is a widely explored topic in the literature, no analytical model that can simultaneously deal with these variables is currently available. To bridge this gap, we introduce a queue model for Markovian processes, which enables us to jointly optimise the aforementioned control variables. A discrete-event simulation is then used to validate our model, and we then test our proposal with real data under different operative scenarios, with the aim of assessing the usefulness of the proposal in real settings

Downscaling atmospheric emission inventories with “top–down” approach: the support of the literature in choosing proxy variables

The management and improvement of air quality are global challenges aimed at protecting human health and environmental resources. For this purpose, in addition to legislative and scientific indications, numerous tools are available: measurement methods and tools for estimating and forecasting. As a collection of data presenting an emission of a pollutant (to air), emission inventories support the knowledge of sources impacting air quality by estimating atmospheric emissions within a specific (wide or limited) reference area. There are several methodological approaches for their definition, which can be classified into bottom–up or top–down methods. This paper aims to review the methodological approaches described in the literature that apply the top–down approach for the disaggregation of atmospheric emissions with high spatial and temporal resolution. The proxy variables used to apply this approach are identified, as well as the spatial and temporal resolution obtained by the authors. The results show that population density and land use are the most common parameters with respect to most of the emission sources and for numerous atmospheric pollutants. The spatial resolution of the disaggregation described in the literature varies from a few hundred metres to several kilometres, in relation to the territorial extension of the study areas. The results of the review help support the selection of the best and most popular proxy variables used to scale emissions inventories

A comparison of low-cost techniques for three-dimensional animal body measurement in livestock buildings

Data about health and development of animals are still now mostly collected through manual measurements or visual observations but these kinds of methods of collecting data are causes of several problems. Alternatively, optical sensing techniques can be implemented in order to overcome limitations arising from manual contact measurements. The present research discusses metrological analysis of Structure from motion (SfM) photogrammetry approach, low-cost LiDAR scanning and Microsoft Kinect v1 depth camera to three- dimensional animal body measurement, with specific reference to pigs. Analyses were carried out on fiberglass model to get rid of animal movements. Scans were captured based on a segmented approach, where different portion of the body have been imaged during different frames acquisition tasks. The obtained results demonstrate the high potential of 3D Kinect. LiDAR show a higher RMS value respect to Kinect and SfM most probably due to the collection approach based on single profiles rather than on surfaces. Anyway, the RMS of relative noise ranges between 0.7 and 4 mm, showing a high accuracy of reconstructions even for the others techniques