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The by-products of the wine industry represent a global production of 10.5 to 13.1 million tons of wine pomace annually. This study examines the chemical composition and energy potential of wine pomace and distillation stillage, evaluating their suitability for pellet production within ENplus® standards. Proximate analysis, elemental analysis, and calorimetric analysis were conducted on samples of the two by-products collected in a local Distillery in Portugal. The results reveal that wine pomace has a higher volatile matter content (62.695%) than distillation stillage, which, however, has lower ash content (3.762%) and higher fixed carbon (31.813%). Calorimetric analyses show that distillation stillage has a superior low heating value compared to wine pomace, with values exceeding 19 MJ/kg. Both by-products, however, exceed ENplus® limits for ash (≤0.70), nitrogen (≤0.3), and sulfur (≤0.04) content, presenting challenges for use as high-quality fuel pellets. Combining these biomasses with other materials could reduce the pollutant content of the pellet and improve efficiency. This study highlights the need for pre-treatment strategies to lower ash content and enhance combustion. Policy support for sustainable practices is essential to optimize the use of wine pomace and distillation stillage as renewable energy sources. [ABSTRACT FROM AUTHOR]

Caffeine (CAF) is widely detected in aquatic environments, serving as an indicator of anthropogenic contamination. Its high consumption, and persistence raise environmental concerns. This study was to evaluate the chronic effects in terms of growth rate, weight, behavior, and biochemical parameters of environmental concentrations of CAF on adult zebrafish. Adult zebrafish were exposed, for 30 d, to 0, 0.5, 1.5, and 300 µg L−1 CAF, with behavior (feeding latency, exploration, aggression, sociability, sound response) and biochemical endpoints (acetylcholinesterase (AChE), lactate dehydrogenase (LDH), and cortisol levels) assessed at the end of the exposure. CAF 0.5 µg L−1 increased feeding latency time, while 300 µg L−1 reduced growth and weight. Exposure to CAF affect fish behavior in terms of vertical exploration, aggressiveness, shoaling, and sound responses although were concentration specific. All concentrations tested increased social behavior, with fish swimming closer to the shoal. At a biochemical level, CAF exposed showed reduced AChE activity, while LDH activity, and cortisol levels increased at 300 µg L−1. Low concentrations of CAF caused neurotoxicity in zebrafish which may compromise their feeding behavior, and social interactions in the wild. These changes suggest potential ecological impacts of chronic exposure to CAF, such as impaired feeding and stress responses. [ABSTRACT FROM AUTHOR]

With the rise in popularity of different human-centred applications using 3D reconstruction data, the problem of generating photo-realistic models has become an important task. In a multiview acquisition system, particularly for large indoor scenes, the acquisition conditions will differ along the environment, causing colour differences between captures and unappealing visual artefacts in the produced models. We propose a novel neural-based approach to colour correction for indoor 3D reconstruction. It is a lightweight and efficient approach that can be used to harmonize colour from sparse captures over complex indoor scenes. Our approach uses a fully connected deep neural network to learn an implicit representation of the colour in 3D space, while capturing camera-dependent effects. We then leverage this continuous function as reference data to estimate the required transformations to regenerate pixels in each capture. Experiments to evaluate the proposed method on several scenes of the MP3D dataset show that it outperforms other relevant state-of-the-art approaches. [ABSTRACT FROM AUTHOR]

This paper presents a collaborative manufacturing cell implemented in a laboratory setting, focusing on developing learning-based interaction abilities to enhance versatility and ease of use. The key components of the system include 3D real-time volumetric monitoring for safety, visual recognition of hand gestures for human-to-robot communication, classification of physical-contact-based interaction primitives during handover operations, and detection of hand–object interactions to anticipate human intentions. Due to the nature and complexity of perception, deep-learning-based techniques were used to enhance robustness and adaptability. The main components are integrated in a system containing multiple functionalities, coordinated through a dedicated state machine. This ensures appropriate actions and reactions based on events, enabling the execution of specific modules to complete a given multi-step task. An ROS-based architecture supports the software infrastructure among sensor interfacing, data processing, and robot and gripper controllers nodes. The result is demonstrated by a functional use case that involves multiple tasks and behaviors, paving the way for the deployment of more advanced collaborative cells in manufacturing contexts. [ABSTRACT FROM AUTHOR]

Biopolymeric nanoparticles (NPs) have gained significant attention in several areas as an alternative to synthetic polymeric NPs due to growing environmental and immunological concerns. Among the most promising biopolymers is poly(lactic acid) (PLA), with a reported high degree of biocompatibility and biodegradability. In this work, PLA NPs were synthesized according to a controlled gelation process using a combination of single-emulsion and nanoprecipitation methods. This study evaluated the influence of several experimental parameters for accurate control of the PLA NPs' size distribution and aggregation. Tip sonication (as the stirring method), a PLA concentration of 10 mg/mL, a PVA concentration of 2.5 mg/mL, and low-molecular-weight PLA (Mw = 5000) were established as the best experimental conditions to obtain monodisperse PLA NPs. After gelification process optimization, flutamide (FLU) was used as a model drug to evaluate the encapsulation capability of the PLA NPs. The results showed an encapsulation efficiency of 44% for this cytostatic compound. Furthermore, preliminary cell viability tests showed that the FLU@PLA NPs allowed cell viabilities above 90% up to a concentration of 20 mg/L. The comprehensive findings showcase that the PLA NPs fabricated using this straightforward gelification method hold promise for encapsulating cytostatic compounds, offering a novel avenue for precise drug delivery in cancer therapy. [ABSTRACT FROM AUTHOR]

Computer simulation is a crucial element in the design of chemical processes. Although numerous commercial software options are widely recognized, the expense associated with acquiring and sustaining valid software licenses can be prohibitive. In contrast, open-source software, being freely available, provides an opportunity for individuals to study, review, and modify simulation models. This accessibility fosters technology transfer and facilitates knowledge dissemination, benefiting both academic and industrial domains. In this study, a thermodynamic equilibrium steady-state analysis of steam methane reforming using a natural-gas-like intake fuel was conducted. An analytical method was developed on the Microsoft Excel platform, utilizing the material balance equations system. The obtained results were compared to numerical methods employing the free-of-charge chemical process simulation software COCO and DWSIM. The investigation explored the influence of temperature, pressure, and steam-to-carbon ratio to determine optimal operating conditions. The findings suggest that higher temperatures and lower pressures are highly favorable for this process, considering that the choice of steam-to-carbon ratio depends on the desired conversion, with a potential disadvantage of coke formation at lower values. Consistent results were obtained through both analytical and numerical methods. Notably, simulations performed using DWSIM showed a deviation of 6.42% on average compared to COCO values. However, it was observed that the analytical method tended to overestimate the results by an average of 3.01% when compared to the simulated results from COCO, highlighting the limitations of this analytical approach. [ABSTRACT FROM AUTHOR]