ALBERT

Description: An increasing number of people are interested in following a dietary pattern that is environmentally sustainable and water saving. However, consumers are mostly unable to recognize evidence-based information on food and nutrition and efficiently manage their diet. We conducted a narrative review aiming to support professionals to guide their assisted people that decide to follow a dietary pattern chosen for environmental or ethical reasons. We reviewed three scientific databases and Google Scholar, searching for papers that deal with the water consumption of widespread and well known dietary patterns (Healthy and Balanced Diet, Western Diet, and Vegan and Vegetarian diets). Our results suggest that moving toward a low-animal-based diet favors a reduction in water consumption, but current evidence is not sufficient to establish which is the winner in terms of water saving by comparing Vegetarian and Vegan diets.

Description: The microwave drying process has a wide application in industry, including drying polymer foams after the impregnation process for sealings in the construction industry. The objective of the drying process is to reach a certain moisture in the foam by adjusting the power levels of the microwave sources. A moisture controller can be designed to achieve this goal; however, a process model is required to design model-based controllers. Since complex physics governs the microwave drying process, system identification tools are employed in this paper to exploit the process input and output information and find a simplified yet accurate model of the process. The moisture content of the foam that is the process output is measured using a designed electrical capacitance tomography (ECT) sensor. The ECT sensor estimates the 2D permittivity distribution of moving foams, which correlates with the foam moisture. Experiments are conducted to collect the ECT measurements while giving different inputs to the microwave sources. A state-space model is estimated using one of the collected datasets and is validated using the other datasets. The comparison between the model response and the actual measurements shows that the model is accurate enough to design a controller for the microwave drying process.

Description: High dynamic performance of a deep-sea electric oil-filled joint actuator is an important premise to guarantee the working performance of an electric underwater manipulator. However, the unfavorable factors (i.e., extremely high water pressure, near freezing temperature) brought by the deep-sea working environment seriously affect the characteristic and dynamic performance of the electric oil-filled joint actuator, which mainly includes oil stirring viscos loss, output shaft dynamic seal loss, and core loss. In this paper, a novel observer-based robust control method named prescribed performance non-singular fast-terminal sliding-mode control (PP-NFTSMC-ESO) was synthesized for improving the dynamic performance of a deep-sea electric oil-filled joint actuator. The extended state observer (ESO) was employed to observe the unmeasured joint velocity signal and estimate the lumped uncertainties, while the prescribed performance function (PPF) was applied to constrain the instantaneous and steady-state performance of the trajectory-tracking error. The robust NFTSMC control method was then established by integrating the function of ESO and PPF through backstepping methodology. The stability of the proposed PP-NFTSMC-ESO strategy was analyzed and proved by the Lyapunov’s stability theory. It was proven that under the proposed controller, all the closed-loop signals are bounded and the trajectory tracking errors will converge to a small neighborhood of the origin with appropriate design parameters. The effectiveness of the proposed control scheme was illustrated by comparative simulation studies.

Description: The increase of the global population and shortage of renewable water resources urges the development of possible remedies to improve the quality and reusability of waste and contaminated water supplies. Different water pollutants, such as heavy metals, dyes, pesticides, endocrine disrupting compounds (EDCs), and pharmaceuticals, are produced through continuous technical and industrial developments that are emerging with the increasing population. Molecularly imprinted polymers (MIPs) represent a class of synthetic receptors that can be produced from different types of polymerization reactions between a target template and functional monomer(s), having functional groups specifically interacting with the template; such interactions can be tailored according to the purpose of designing the polymer and based on the nature of the target compounds. The removal of the template using suitable knocking out agents renders a recognition cavity that can specifically rebind to the target template which is the main mechanism of the applicability of MIPs in electrochemical sensors and as solid phase extraction sorbents. MIPs have unique properties in terms of stability, selectivity, and resistance to acids and bases besides being of low cost and simple to prepare; thus, they are excellent materials to be used for water analysis. The current review represents the different applications of MIPs in the past five years for the detection of different classes of water and wastewater contaminants and possible approaches for future applications.

Description: Advancements in smart technology, wearable and mobile devices, and Internet of Things, have made smart health an integral part of modern living to better individual healthcare and well-being. By enhancing self-monitoring, data collection and sharing among users and service providers, smart health can increase healthy lifestyles, timely treatments, and save lives. However, as health data become larger and more accessible to multiple parties, they become vulnerable to privacy attacks. One way to safeguard privacy is to increase users’ anonymity as anonymity increases indistinguishability making it harder for re-identification. Still the challenge is not only to preserve data privacy but also to ensure that the shared data are sufficiently informative to be useful. Our research studies health data analytics focusing on anonymity for privacy protection. This paper presents a multi-faceted analytical approach to (1) identifying attributes susceptible to information leakages by using entropy-based measure to analyze information loss, (2) anonymizing the data by generalization using attribute hierarchies, and (3) balancing between anonymity and informativeness by our anonymization technique that produces anonymized data satisfying a given anonymity requirement while optimizing data retention. Our anonymization technique is an automated Artificial Intelligent search based on two simple heuristics. The paper describes and illustrates the detailed approach and analytics including pre and post anonymization analytics. Experiments on published data are performed on the anonymization technique. Results, compared with other similar techniques, show that our anonymization technique gives the most effective data sharing solution, with respect to computational cost and balancing between anonymity and data retention.

Description: Fresh vegetables are an essential part of a healthy diet, but microbial contamination of fruits and vegetables is a serious concern to human health, not only for the presence of foodborne pathogens but because they can be a vehicle for the transmission of antibiotic-resistant bacteria. This work aimed to investigate the importance of fresh produce in the transmission of extended-spectrum β-lactamases (ESBL)-producing Enterobacteriaceae. A total of 174 samples of vegetables (117) and farm environment (57) were analysed to determine enterobacterial contamination and presence of ESBL-producing Enterobacteriaceae. Enterobacterial counts above the detection limit were found in 82.9% vegetable samples and 36.8% environmental samples. The average count was 4.2 log cfu/g or mL, with a maximum value of 6.2 log cfu/g in a parsley sample. Leafy vegetables showed statistically significant higher mean counts than other vegetables. A total of 15 ESBL-producing isolates were obtained from vegetables (14) and water (1) samples and were identified as Serratia fonticola (11) and Rahnella aquatilis (4). Five isolates of S. fonticola were considered multi-drug resistant. Even though their implication in human infections is rare, they can become an environmental reservoir of antibiotic-resistance genes that can be further disseminated along the food chain.

Description: Pressure-Sensitive Paint (PSP) is a powerful measurement technique to obtain pressure distribution on a model of interest by measuring the emission intensity of the PSP coating with a camera. Since a PSP coating is prepared by applying a solution containing an organic solvent, generally, by sprayer, the properties such as the pressure- and the temperature-sensitivity depends on the skill of the person applying it. This fabrication process is one of the barriers to use of the PSP technique because of the legal restrictions on the use of organic solvents. Thus, a sticker-like PSP coating is useful because it does not require the use of organic solvent and the applying skill. In this study, we have fabricated freestanding Pressure-Sensitive Nano-Sheet (PSNS) by a sacrificial layer process using a spin-coating method. We employed Pt(II) meso-tetra(pentafluorophenyl)porphine (PtTFPP) as a pressure-sensitive dye and poly(1-trimethylsilyl-propyne) (PTMSP) and poly(L-lactic acid) (PLLA) as a polymer binder; thus, the PSNS samples based on PTMSP and PLLA were prepared. The pressure- and the temperature-sensitivity, the lifetime of the luminescence, and the quantum yield of the fabricated PSNS have been investigated. The pressure-sensitivity of PTMSP-based PSNS is higher than that of PLLA-based PSNS. Conversely, the quantum yield of PLLA-based PSNS is higher than that of PTMSP-based PSNS.

Description: Learned image reconstruction techniques using deep neural networks have recently gained popularity and have delivered promising empirical results. However, most approaches focus on one single recovery for each observation, and thus neglect information uncertainty. In this work, we develop a novel computational framework that approximates the posterior distribution of the unknown image at each query observation. The proposed framework is very flexible: it handles implicit noise models and priors, it incorporates the data formation process (i.e., the forward operator), and the learned reconstructive properties are transferable between different datasets. Once the network is trained using the conditional variational autoencoder loss, it provides a computationally efficient sampler for the approximate posterior distribution via feed-forward propagation, and the summarizing statistics of the generated samples are used for both point-estimation and uncertainty quantification. We illustrate the proposed framework with extensive numerical experiments on positron emission tomography (with both moderate and low-count levels) showing that the framework generates high-quality samples when compared with state-of-the-art methods.

Description: Background and objectives: The main purpose of this study was to evaluate the survival and success rates of dental implants with a double acid-etched surface treatment with evaluation times up to 10 years post-loading. Materials and Methods: This study was conducted at a hospital oral surgery and implantology unit. It included 111 dental implants with a double acid-etched surface. Three groups were created: Group 1 (1–3 years loading), Group 2 (3–5 years loading), and Group 3 (over 5 years loading). Probing depth, resonance frequency analysis (ISQ value), and marginal bone loss were evaluated. Results: The data obtained underwent statistical analysis. Overall, 78 patients were included in the study, who received, in total, 111 dental implants, all replacing single teeth. Mean probing depth was 3.03 mm and mean ISQ was 65.54. Regarding marginal bone loss, in Group 1, 67.6% of implants did not undergo any thread loss, in Group 2, 48.3%, and in Group 3, 59.6%; 59.10% of all implants did not present thread loss with a mean bone loss of 0.552 mm. The implant survival rate was 99.1%, and the success rate was 96.37%. Conclusions: Implants with a double acid-etched surface showed excellent success rates in terms of marginal bone loss, ISQ, and probing depth after up to 10 years of loading, making them a clinically predictable treatment option. Future studies are needed to compare this implant surface with other types in different restorative situations.

Description: Focused Ion Beam-Induced Deposition (FIBID) is a single-step nanopatterning technique that applies a focused beam of ions to induce the decomposition of a gaseous precursor. The processing rate of FIBID increases by two orders of magnitude when the process is performed at cryogenic temperatures (Cryo-FIBID): the precursor forms a condensed layer on the surface of the cooled substrate, greatly enhancing the amount of material available for decomposition. Cryo-FIBID has been achieved so far by making use of liquid nitrogen-based cooling circuits, which require the passage of a flowing gas as a cooling agent. Here, the Cryo-FIBID of the W(CO)6 precursor is performed using a coolant-free thermoelectric plate utilizing the Peltier effect. Performed at -60 ºC, the procedure yields a W–C-based material with structural and electrical properties comparable to those of its counterpart grown in coolant-based Cryo-FIBID. The use of the thermoelectric plate significantly reduces the vibrations and sample drift induced by the flow of passing coolant gas and allows for the fabrication of similar nanostructures. In summary, the reported process represents a further step towards the practical implementation of the Cryo-FIBID technique, and it will facilitate its use by a broader research community.