Wearable Health Devices (WHDs) are increasingly helping people to better monitor their health status both at an activity/fitness level for self-health tracking and at a medical level providing more ...data to clinicians with a potential for earlier diagnostic and guidance of treatment. The technology revolution in the miniaturization of electronic devices is enabling to design more reliable and adaptable wearables, contributing for a world-wide change in the health monitoring approach. In this paper we review important aspects in the WHDs area, listing the state-of-the-art of wearable vital signs sensing technologies plus their system architectures and specifications. A focus on vital signs acquired by WHDs is made: first a discussion about the most important vital signs for health assessment using WHDs is presented and then for each vital sign a description is made concerning its origin and effect on heath, monitoring needs, acquisition methods and WHDs and recent scientific developments on the area (electrocardiogram, heart rate, blood pressure, respiration rate, blood oxygen saturation, blood glucose, skin perspiration, capnography, body temperature, motion evaluation, cardiac implantable devices and ambient parameters). A general WHDs system architecture is presented based on the state-of-the-art. After a global review of WHDs, we zoom in into cardiovascular WHDs, analysing commercial devices and their applicability versus quality, extending this subject to smart t-shirts for medical purposes. Furthermore we present a resumed evolution of these devices based on the prototypes developed along the years. Finally we discuss likely market trends and future challenges for the emerging WHDs area.
Electrocoagulation was investigated as a method for treating wastewater containing polyvinyl acetate (PVAc) from the furniture industry. The study evaluated the evolution of iron concentration and ...passivation during the treatment process. Laboratory-scale experiments were conducted to evaluate the effects of inter-electrode distance (d), current density, and mode on treatment performance. Three values of d (0.3, 0.6, and 0.9 cm) were studied and found to have no significant effect on performance. However, lower d values resulted in reduced energy consumption due to a decrease in applied voltage. Three values of current density (132, 158, and 197 A m−2) were studied under two current modes, Direct Current (DC) and Alternating Pulsed Current (APC). The best treatment performance for DC occurred under 158 A m−2 (the treated wastewater was characterized by pH = 4.59 ± 0.02, conductivity = 996 ± 21 μS cm−1, COD = 1940 ± 55 mgO2 L−1, TSS = 105 ± 14 mg L−1, and Fe = 50.39 ± 1.87 mgFe L−1). For APC, the best performance was achieved under 197 A m−2 (the treated wastewater was characterized by pH = 6.33 ± 0.06, conductivity = 988 ± 17 μS cm−1, COD = 1942 ± 312 mgO2 L−1, TSS = 199 ± 55 mg L−1, and Fe = 44.68 ± 4.60 mgFe L−1). Despite the promising results, treatment performance was insufficient to meet the legal requirements for water discharge. APC was found to be a more economically viable approach, as it reduced anode wear, electrode passivation, and energy consumption. The quantity of iron released increased with d, and the effect of current density on iron concentration was found to be non-linear. However, applying APC reduced the iron content for all tested current densities. The tests showed that EC was effective in removing chemical oxygen demand (COD) and total suspended solids (TSS), achieving removal efficiencies above 92% and 99%, respectively. However, the studied treatment procedures were insufficient to meet the EU legal requirements for water discharge. Therefore, the obtained wastewater should undergo a post-treatment process.
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•Lower inter-electrode distance (d) values reduced energy consumption and costs.•Higher d reduces the formation of a passivation layer on the cathode's surface.•COD reduction >92% and TSS reduction >99%.•Alternating pulse current (APC) decreases passivation and treatment costs.•Iron concentration increases with d and reduces with APC.
This paper investigates the reliability of free and open-source algorithms used in the geographical object-based image classification (GEOBIA) of very high resolution (VHR) imagery surveyed by ...unmanned aerial vehicles (UAVs). UAV surveys were carried out in a cork oak woodland located in central Portugal at two different periods of the year (spring and summer). Segmentation and classification algorithms were implemented in the Orfeo ToolBox (OTB) configured in the QGIS environment for the GEOBIA process. Image segmentation was carried out using the Large-Scale Mean-Shift (LSMS) algorithm, while classification was performed by the means of two supervised classifiers, random forest (RF) and support vector machines (SVM), both of which are based on a machine learning approach. The original, informative content of the surveyed imagery, consisting of three radiometric bands (red, green, and NIR), was combined to obtain the normalized difference vegetation index (NDVI) and the digital surface model (DSM). The adopted methodology resulted in a classification with higher accuracy that is suitable for a structurally complex Mediterranean forest ecosystem such as cork oak woodlands, which are characterized by the presence of shrubs and herbs in the understory as well as tree shadows. To improve segmentation, which significantly affects the subsequent classification phase, several tests were performed using different values of the range radius and minimum region size parameters. Moreover, the consistent selection of training polygons proved to be critical to improving the results of both the RF and SVM classifiers. For both spring and summer imagery, the validation of the obtained results shows a very high accuracy level for both the SVM and RF classifiers, with kappa coefficient values ranging from 0.928 to 0.973 for RF and from 0.847 to 0.935 for SVM. Furthermore, the land cover class with the highest accuracy for both classifiers and for both flights was cork oak, which occupies the largest part of the study area. This study shows the reliability of fixed-wing UAV imagery for forest monitoring. The study also evidences the importance of planning UAV flights at solar noon to significantly reduce the shadows of trees in the obtained imagery, which is critical for classifying open forest ecosystems such as cork oak woodlands.
The açaí seed corresponds to approximately 85% of the fruit's weight and represents ~1.1 million metric tons of residue yearly accumulated in the Amazon region, resulting in an acute environmental ...and urban problem. To extract the highest value from this residue, this study aimed to evaluate its chemical composition to determine the appropriate applications and to develop conversion methods. First, mannan was confirmed as the major component of mature seeds, corresponding to 80% of the seed's total carbohydrates and about 50% of its dry weight. To convert this high mannan content into mannose, a sequential process of dilute-acid and enzymatic hydrolysis was evaluated. Among different dilute-H
SO
hydrolysis conditions, 3%-acid for 60-min at 121 °C resulted in a 30% mannan hydrolysis yield and 41.7 g/L of mannose. Because ~70% mannan remained in the seed, a mannanase-catalyzed hydrolysis was sequentially performed with 2-20% seed concentration, reaching 146.3 g/L of mannose and a 96.8% yield with 20% solids. As far as we know, this is the highest reported concentration of mannose produced from a residue. Thus, this work provides fundamental data for achieving high concentrations and yields of mannose from açaí seeds, which could add commercial value to the seeds and improve the whole açaí productive chain.
Laccase Activation in Deep Eutectic Solvents Toledo, Mariah L; Pereira, Matheus M; Freire, Mara G ...
ACS sustainable chemistry & engineering,
07/2019, Letnik:
7, Številka:
13
Journal Article
Recenzirano
Odprti dostop
The research on alternative solvents and cosolvents is relevant when envisioning the improvement of biocatalytic reactions. Among these solvents and cosolvents, deep eutectic solvents (DES) may be ...considered as customizable new reaction media for biocatalysis. Accordingly, in this work, 16 DES aqueous solutions, as well as the individual DES components at the same conditions, have been investigated in laccase-catalyzed reactions. Cholinium- and betaine-based DES formed with polyols at different molar ratios and concentrations were evaluated. The results reported show that in the presence of most DES the laccase activity is preserved and, with a particular DES, enhanced up to 200%. Molecular docking studies demonstrated that while most DES components establish hydrogen bonds with the enzyme amino acids, those that establish stronger interactions with the enzyme (expressed by absolute values of docking affinity energies) lead to an enhanced laccase activity. Finally, the laccase stability was evaluated in additional tests under extreme storage temperatures (60 °C and −80 °C). Although no significant protection to high temperatures was afforded by DES, an enhanced laccase activity when stored at low temperatures was found, at least up to 20 days. Combining experimental results and molecular docking, this work shows that DES can be designed as cosolvents to improve biocatalytic reactions.
Visual assessment of the percentage diameter stenosis (%DS
) of lesions is essential in coronary angiography (CAG) interpretation. We have previously developed an artificial intelligence (AI) model ...capable of accurate CAG segmentation. We aim to compare operators' %DS
in angiography versus AI-segmented images.
Quantitative coronary analysis (QCA) %DS (%DS
) was previously performed in our published validation dataset. Operators were asked to estimate %DS
of lesions in angiography versus AI-segmented images in separate sessions and differences were assessed using angiography %DS
as reference.
A total of 123 lesions were included. %DS
was significantly higher in both the angiography (77% ± 20% vs. 56% ± 13%, p < 0.001) and segmentation groups (59% ± 20% vs. 56% ± 13%, p < 0.001), with a much smaller absolute %DS difference in the latter. For lesions with %DS
of 50%-70% (60% ± 5%), an even higher discrepancy was found (angiography: 83% ± 13% vs. 60% ± 5%, p < 0.001; segmentation: 63% ± 15% vs. 60% ± 5%, p < 0.001). Similar, less pronounced, findings were observed for %DS
< 50% lesions, but not %DS
> 70% lesions. Agreement between %DS
/%DS
across %DS
strata (<50%, 50%-70%, >70%) was approximately twice in the segmentation group (60.4% vs. 30.1%; p < 0.001). %DS
inter-operator differences were smaller with segmentation.
%DS
was much less discrepant with segmentation versus angiography. Overestimation of %DS
< 70% lesions with angiography was especially common. Segmentation may reduce %DS
overestimation and thus unwarranted revascularization.
A non-transgenic approach based on RNA interference was employed to induce protection against tomato mosaic virus (ToMV) infection in tomato plants. dsRNA molecules targeting the cp gene of ToMV were ...topically applied on plants prior to virus inoculation. Protection was dose-dependent and sequence-specific. While no protection was achieved when 0-16 µg dsRNA were used, maximum rates of resistance (60 and 63%) were observed in doses of 200 and 400 µg/plant, respectively. Similar rates were also obtained against potato virus Y when targeting its cp gene. The protection was quickly activated upon dsRNA application and lasted for up to 4 days. In contrast, no detectable antiviral response was triggered by the dsRNA from a begomovirus genome, suggesting the method is not effective against phloem-limited DNA viruses. Deep sequencing was performed to analyze the biogenesis of siRNA populations. Although long-dsRNA remained in the treated leaves for at least 10 days, its systemic movement was not observed. Conversely, dsRNA-derived siRNA populations (mainly 21- and 22-nt) were detected in non-treated leaves, which indicates endogenous processing and transport through the plant. Altogether, this study provides critical information for the development of novel tools against plant viruses; strengths and limitations inherent to the systems are discussed.
Spent coffee grounds (SCG), the residual materials obtained during the processing of raw coffee powder to prepare instant coffee, are the main coffee industry residues. In the present work, this ...material was chemically characterized and subsequently submitted to a dilute acid hydrolysis aiming to recover the hemicellulose sugars. Reactions were performed according to experimental designs to verify the effects of the variables H
2SO
4 concentration, liquid-to-solid ratio, temperature, and reaction time, on the efficiency of hydrolysis. SCG was found to be rich in sugars (45.3%, w/w), among of which hemicellulose (constituted by mannose, galactose, and arabinose) and cellulose (glucose homopolymer) correspond to 36.7% (w/w) and 8.6% (w/w), respectively. Optimal conditions for hemicellulose sugars extraction consisted in using 100
mg acid/g dry matter, 10
g liquid/g solid, at 163
°C for 45
min. Under these conditions, hydrolysis efficiencies of 100%, 77.4%, and 89.5% may be achieved for galactan, mannan, and arabinan, respectively, corresponding to a hemicellulose hydrolysis efficiency of 87.4%.
This paper discusses the use of networks of Inertial Measurement Units (IMUs) for the reconstruction of trajectories from sensor data. Logistics is a natural application domain to verify the quality ...of the handling of goods. This is a mass application and the economics of logistics impose that the IMUs to be used must be low-cost and use basic computational devices. The approach in this paper converts a strategy from the literature, used in the multi-target following problem, to reach a consensus in a network of IMUs. This paper presents results on how to achieve the consensus in trajectory reconstruction, along with covariance intersection data fusion of the information obtained by all the nodes in the network.
It is well recognized that security will play a major role in enabling most of the applications envisioned for the Internet of Things (IoT). We must also note that most of such applications will ...employ sensing and actuating devices integrated with the Internet communications infrastructure and, from the minute such devices start to support end-to-end communications with external (Internet) hosts, they will be exposed to all kinds of threats and attacks. With this in mind, we propose an IDS framework for the detection and prevention of attacks in the context of Internet-integrated CoAP communication environments and, in the context of this framework, we implement and experimentally evaluate the effectiveness of anomaly-based intrusion detection, with the goal of detecting Denial of Service (DoS) attacks and attacks against the 6LoWPAN and CoAP communication protocols. From the results obtained in our experimental evaluation we observe that the proposed approach may viably protect devices against the considered attacks. We are able to achieve an accuracy of 93% considering the multi-class problem, thus when the pattern of specific intrusions is known. Considering the binary class problem, which allows us to recognize compromised devices, and though a lower accuracy of 92% is observed, a recall and an F_Measure of 98% were achieved. As far as our knowledge goes, ours is the first proposal targeting the usage of anomaly detection and prevention approaches to deal with application-layer and DoS attacks in 6LoWPAN and CoAP communication environments.
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