Search

Automotive fans, small wind turbines, and manned and unmanned aerial vehicles (MAVs/UAVs) are just a few examples in which noise generated by the flow’s interaction with aerodynamic surfaces is a major concern. The current work shows the potential of a new airfoil shape to minimize noise generation, maintaining a high lift-to-drag ratio in a prescribed Reynolds regime. This investigation uses a multifidelity approach: a low-fidelity semiempirical model is exploited to evaluate the sound pressure level (SPL). Fast evaluation of a low-cost function enables the computation of a large range of possible profiles, and accuracy is added to the low-fidelity response surface with high-fidelity CFD data. The constraint of maintaining a predefined range of the lift coefficient and lift-to-drag ratio ensures the possibility of using this profile in usual design procedures.

Developing a method for the growth of ultrathin metal chalcogenides, potentially targeting the two-dimensional (2D) limit, has a pivotal impact on various nanotechnological device applications. Here, we employed a vapor deposition scheme, based on tellurization, to induce the heterogenous chemical reaction between solid Ag and Au precursors, in the form of ultrathin films, and Te vapors. We characterized the morphological and structural properties of the grown tellurides by using atomic force microscopy, Raman spectroscopy, X-ray photoelectron spectroscopy and X-ray diffraction techniques. The developed tellurization methodology provides a key advancement in the picture of growing ultrathin noble metal tellurides and holds great potential for applications in different technological fields.

Hemoglobin is one of the proteins that are more susceptible to S-glutathionylation and the levels of its modified form, glutathionyl hemoglobin (HbSSG), increase in several human pathological conditions. The scope of the present review is to provide knowledge about how hemoglobin is subjected to S-glutathionylation and how this modification affects its functionality. The different diseases that showed increased levels of HbSSG and the methods used for its quantification in clinical investigations will be also outlined. Since there is a growing need for precise and reliable methods for markers of oxidative stress in human blood, this review highlights how HbSSG is emerging more and more as a good indicator of severe oxidative stress but also as a key pathogenic factor in several diseases.

In recent times, pollution has emerged as a significant global concern, with European regulations stipulating limits on PM 2.5 particle levels. Addressing this challenge necessitates innovative approaches. Smart low-cost sensors suffer from imprecision, and can not replace legal stations in terms of accuracy, however, their potential to amplify the capillarity of air quality evaluation on the territory is not under discussion. In this paper, we propose an AI system to correct PM 2.5 levels in low-cost sensor data. Our research focuses on data from Turin, Italy, emphasizing the impact of humidity on low-cost sensor accuracy. In this study, different Neural Network architectures that vary the number of neurons per layer, consecutive records and batch sizes were used and compared to gain a deeper understanding of the network’s performance under various conditions. The AirMLP7-1500 model, with an impressive R-squared score of 0.932, stands out for its ability to correct PM 2.5 measurements. While our approach is tailored to the city of Turin, it offers a systematic methodology for the definition of those models and holds the promise to significantly improve the accuracy of air quality data collected from low-cost sensors, increasing the awareness of citizens and municipalities about this critical environmental information.

Selecting drought-tolerant and more water-efficient wheat genotypes is a research priority, specifically in regions with irregular rainfall or areas where climate change is expected to result in reduced water availability. The objective of this work was to use high-throughput measurements with morphophysiological traits to characterize wheat genotypes in relation to water stress. Field experiments were conducted from May to September 2018 and 2019, using a sprinkler bar irrigation system to control water availability to eighteen wheat genotypes: BRS 254; BRS 264; CPAC 01019; CPAC 01047; CPAC 07258; CPAC 08318; CPAC 9110; BRS 394 (irrigated biotypes), and Aliança; BR 18_Terena; BRS 404; MGS Brilhante; PF 020037; PF 020062; PF 120337; PF 100368; PF 080492; and TBIO Sintonia (rainfed biotypes). The water regimes varied from 22 to 100% of the crop evapotranspiration replacement. Water stress negatively affected gas exchange, vegetation indices, and grain yield. High throughput variables TCARI, NDVI, OSAVI, SAVI, PRI, NDRE, and GNDVI had higher yield and morphophysiological measurement correlations. The drought resistance index indicated that genotypes Aliança, BRS 254, BRS 404, CPAC 01019, PF 020062, and PF 080492 were more drought tolerant.

The research on molybdenum disulphide (MoS2) has progressed remarkably in the last decade, prompted by the increasing interest for this material as a potential candidate in future ultrathin optoelectronic devices. MoS2 is a layered semiconductor with a gap in the visible region, which can be exfoliated down to the mono-layer form. Since the discovery of the exceptional optoelectronic properties of 2D MoS2, Raman spectroscopy has been extensively used as a tool to characterize the structure and thickness of MoS2 films. Recent works on MoS2-metal interfaces have shown that Raman spectra are significantly affected by the interaction with metals. However, a complete understanding of how such interaction modifies the MoS2 vibrational properties is still lacking. Studying this subject with both experimental and theoretical methods will provide fundamental insight into the interface physics of MoS2-metal systems, which is crucial for the fabrication of metal contacts and for the development of metal-assisted synthesis methods. This review summarizes the main results concerning Raman spectroscopy studies of heterosystems between MoS2 and transition metals, providing both a basis and directions for future research.

This work aimed to assess the potential of unmanned aerial vehicle (UAV) multi- and hyper-spectral platforms to estimate chlorophyll-a (Chl-a) and cyanobacteria in experimental fishponds in Brazil. In addition to spectral resolutions, the tested platforms differ in the price, payload, imaging system, and processing. Hyperspectral airborne surveys were conducted using a push-broom system 276-band Headwall Nano-Hyperspec camera onboard a DJI Matrice 600 UAV. Multispectral airborne surveys were conducted using a global shutter-frame 4-band Parrot Sequoia camera onboard a DJI Phantom 4 UAV. Water quality field measurements were acquired using a portable fluorometer and laboratory analysis. The concentration ranged from 14.3 to 290.7 µg/L and from 0 to 112.5 µg/L for Chl-a and cyanobacteria, respectively. Forty-one Chl-a and cyanobacteria bio-optical retrieval models were tested. The UAV hyperspectral image achieved robust Chl-a and cyanobacteria assessments, with RMSE values of 32.8 and 12.1 µg/L, respectively. Multispectral images achieved Chl-a and cyanobacteria retrieval with RMSE values of 47.6 and 35.1 µg/L, respectively, efficiently mapping the broad Chl-a concentration classes. Hyperspectral platforms are ideal for the robust monitoring of Chl-a and CyanoHABs; however, the integrated platform has a high cost. More accessible multispectral platforms may represent a trade-off between the mapping efficiency and the deployment costs, provided that the multispectral cameras offer narrow spectral bands in the 660–690 nm and 700–730 nm ranges for Chl-a and in the 600–625 nm and 700–730 nm spectral ranges for cyanobacteria.

Future predictions due to climate change are of decreases in rainfall and longer drought periods. The search for new tolerant crops is an important strategy. The objective of this study was to evaluate the effect of water stress on the physiology and productivity of crops with potential for growing in the off-season period in the Cerrado, and evaluate correlations with the temperature of the canopy obtained by means of thermography. The experiment was conducted under field conditions, with experimental design in randomized blocks, in a split-plot scheme and four replications. The plots were: common bean (Phaseolus vulgaris); amaranth (Amaranthus cruentus); quinoa (Chenopodium quinoa); and buckwheat (Fagopyrum esculentum). The subplots were composed of four water regimes: maximum water regime (WR 535 mm), high-availability regime (WR 410 mm), off-season water regime (WR 304 mm) and severe water regime (WR 187 mm). Under WR 304 mm, the internal concentration of CO2 and photosynthesis were reduced by less than 10% in amaranth. Common bean and buckwheat reduced 85% in photosynthesis. The reduction in water availability increased the canopy temperature in the four crops and, in general, common bean was the most sensitive species, while quinoa had the lowest canopy temperatures. Furthermore, canopy temperature correlated negatively with grain yield, biomass yield and gas exchange across all plant species, thus thermal imaging of the canopy represents a promising tool for monitoring crop productivity for farmers, For the identification of crops with high water use management for research.

In recent years, CFD has proven to be a very useful asset to help with predicting complex flows in a wide range of situations, including multiphase and gas-particle flows. On this track, numerical modelling of particle-laden flows in multistage turbomachinery has become an important step in helping to analyse the behaviour of a discrete phase in gas turbines. Furthermore, unsteady effects due, for example, to rotor–stator interaction may have an effect on trajectories and capture efficiencies of the discrete phase. Unfortunately, computational times for transient simulations can be exceedingly high, especially if a discrete-phase needs also to be simulated. For this reason, this work reports a new method for the efficient and accurate simulation of particle-laden flows in gas turbine engines components. The Harmonic Balance Method is exploited to gain orders of magnitude speedup exploiting the idea that once the flow field has been embedded in the spectral basis, it can be reconstructed at any desired time. In this way, not only can the computational time needed to reach convergence of the flow field be dramatically reduced, but there is also no need to keep simulating the flow field during particle tracking. On the contrary, the continuous phase field can be retrieved at any desired time through flow reconstruction. This technique is conceptually simple, but, to the authors’ knowledge, has never been applied so far in particle-laden flow simulations and represents a novelty in the field. First, the implementation of the method is described, and details are given on how phase-lagged boundary conditions can be applied to flow and particles to further speed up the calculation. Then, some relevant case studies are presented to highlight the performance of the method.

In industrial applications such as chemical plants, cement factories, and glassmakers, large-sized centrifugal fans are commonly used for dust-laden flow processing. In many cases, the contamination is due to solid particles responsible for fouling and erosion issues. Erosion induces the reduction of mechanical resistance and, at the same time, the modification of the geometry and the surface characteristics of the internal flow path. The process works according to the characteristics of the erodent particles, such as dimension and hardness, which have to be coupled with the mechanical properties of the substrate, like hardness and roughness level. In addition to this, the intensity of the erosion depends on the dynamic characteristics of particles, especially velocity and impact angle. For these reasons, erosion-related issues are difficult predict and reduce. In an attempt to preserve the structural integrity of the internal walls, wear-resistant plates are positioned where the impacting contaminants are supposed to be more detrimental. In the present work, a combined experimental and numerical approach is proposed to evaluate the proper setup of wear-resistance plates over the flow path of a large-sized centrifugal fan. The results show how different regions (rotating and stationary walls) are subjected to different impact behavior, determining that the design of the position of the wear-resistant plate is not straightforward. Suggestions related to reducing the erosion intensity are reported, highlighting the possibility of designing the best compromise between erosion, performance, and costs.

Early work by Muller and McClintock discovered that the physical ends of linear chromosomes, named telomeres, possess an inherent ability to escape unwarranted fusions. Since then, extensive research has shown that this special feature relies on specialized proteins and structural properties that confer identity to the chromosome ends, thus allowing cells to distinguish them from intrachromosomal DNA double-strand breaks. Due to the inability of conventional DNA replication to fully replicate the chromosome ends and the downregulation of telomerase in most somatic human tissues, telomeres shorten as cells divide and lose this protective capacity. Telomere attrition causes the activation of the DNA damage checkpoint that leads to a cell-cycle arrest and the entering of cells into a nondividing state, called replicative senescence, that acts as a barrier against tumorigenesis. However, downregulation of the checkpoint overcomes this barrier and leads to further genomic instability that, if coupled with re-stabilization of telomeres, can drive tumorigenesis. This review focuses on the key experiments that have been performed in the model organism Saccharomyces cerevisiae to uncover the mechanisms that protect the chromosome ends from eliciting a DNA damage response, the conservation of these pathways in mammals, as well as the consequences of their loss in human cancer.

Background and Objectives: Solid-organ transplant recipients (SOTRs) are notably considered at risk for developing cutaneous malignancies. However, most of the existing literature is focused on kidney transplant-related non-melanoma skin cancers (NMSCs). Conflicting data have been published so far on NMSC incidence among liver transplant recipients (LTRs), and whether LTRs really should be considered at lower risk remains controversial. The aim of the present study was to prospectively collect data on the incidence of cutaneous neoplasms in an LTR cohort. Materials and Methods: All LTRs transplanted at the Hepato-Pancreato-Biliary Surgery and Liver Transplantation Unit of Modena University Hospital from October 2015 to June 2021 underwent a post-transplant periodic skin check at the Dermatology Unit according to our institutional integrated care pathway. Data on the presence of cutaneous malignant and premalignant lesions were collected at every timepoint. Results: A total of 105 patients were enrolled in the present study. Nearly 15% of the patients developed cutaneous cancerous and/or precancerous lesions during the follow-up period. Almost half of the skin cancerous lesions were basal cell carcinomas. Actinic keratoses (AKs) were observed in six patients. Four patients developed in situ squamous cell carcinomas, and one patient was diagnosed with stage I malignant melanoma. Otherwise, well-established risk factors for the occurrence of skin tumors, such as skin phototype, cumulative sun exposure, and familial history of cutaneous neoplasms, seemed to have no direct impact on skin cancer occurrence in our cohort, as well as an immunosuppressive regimen and the occurrence of non-cutaneous neoplasms. Conclusions: Close dermatological follow-up is crucial for LTRs, and shared protocols of regular skin checks in this particular subset of patients are needed in transplant centers.

The automatic classification of fish species appearing in images and videos from underwater cameras is a challenging task, albeit one with a large potential impact in environment conservation, marine fauna health assessment, and fishing policy. Deep neural network models, such as convolutional neural networks, are a popular solution to image recognition problems. However, such models typically require very large datasets to train millions of model parameters. Because underwater fish image and video datasets are scarce, non-uniform, and often extremely unbalanced, deep neural networks may be inadequately trained, and undergo a much larger risk of overfitting. In this paper, we propose small convolutional neural networks as a practical engineering solution that helps tackle fish image classification. The concept of “small” refers to the number of parameters of the resulting models: smaller models are lighter to run on low-power devices, and drain fewer resources per execution. This is especially relevant for fish recognition systems that run unattended on offshore platforms, often on embedded hardware. Here, established deep neural network models would require too many computational resources. We show that even networks with little more than 12,000 parameters provide an acceptable working degree of accuracy in the classification task (almost 42% for six fish species), even when trained on small and unbalanced datasets. If the fish images come from videos, we augment the data via a low-complexity object tracking algorithm, increasing the accuracy to almost 49% for six fish species. We tested the networks with images obtained from the deployments of an experimental system in the Mediterranean sea, showing a good level of accuracy given the low quality of the dataset.

The Harmonic Balance Method is one of the most commonly employed Reduced Order Models for turbomachinery calculations, since it leverages the signal sparsity in the frequency domain to cast the transient equations into a coupled set of steady-state ones. The present work aims at detailing the development and validation of a new framework for the application of the Harmonic Balance Method in the open-source software OpenFOAM. The paper is conceptually divided into building blocks for the implementation of the code. For each of these, theoretical notions and coding strategies are given, and an ad hoc validation test case is presented. This structure has been chosen with the aim of easing the reader in the understanding and implementation of such a method in a generic fluid dynamics solver. In a fully open source philosophy, the library files are freely accessible in the authors’ repository (link provided below in the text).

In Winter 2020, Italy, and in particular the Lombardy region, was the first country in the Western hemisphere to be hit by the COVID-19 pandemic. Plasma from individuals recovered from COVID-19 (COVID-19 convalescent plasma, CCP) was the first therapeutic tool adopted to counteract the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). In this retrospective cohort study, we report the experience of the city hospital of Mantua, Lombardy region, on the compassionate use of CCP in patients hospitalized for severe COVID-19. Between April 2020 and April 2021, 405 consecutive COVID-19 patients received 657 CCP units with a median anti-SARS-CoV-2 neutralizing antibody (nAb) titer of 160 (interquartile range (IQR), 80–320). Their median age was 68 years (IQR, 56–78 years), and 62% were males. At enrollment, 55% of patients had an increased body mass index (BMI), and 25.6% had at least three comorbidities. The 28-day crude mortality rate was 12.6% (51/405). Young age (

Biomass represents a programmable renewable energy source that is useful for reducing issues related to the transfer from fossil fuels to the renewable energy era. The exploitation of biomass is strongly related to the development of power technologies that are designed to improve efficiency; however, at the same time, they have to be designed to improve the life cycle of the entire installation—especially in relation to maintenance operations. In this paper, a numerical analysis is proposed to assess the performance of a heat exchanger used for separating condensing tar from syngas generated by the gasification of lignocellulosic wood chips and pellets. The analysis included clean, fouled, and clogged conditions. Flow maldistribution characterized the inlet section of shell-and-tube configurations and was responsible for clogging phenomena. Starting from field detection, analyses of fouled and clogged conditions showed a reduction in the effectiveness of the heat exchanger, causing dangerous conditions for the internal combustion engine used to exploit the syngas flow.

Rainfall is among the climatic factors that most affect production, as in the Brazilian Cerrado. Non-destructive and automated phenotyping methods are fast and efficient for genotype selection. The objective of this work was to evaluate, under field conditions, the morphophysiological changes, yield, and grain quality of soybean (Glycine max L. Merrill) under water stress in the Brazilian Cerrado. The plots comprised six soybean cultivars and the subplots of four water regimes, corresponding to 31, 44, 64 and 100% of crop evapotranspiration replacement. The experiments were conducted from May to September 2018 and 2019. An irrigation system with a bar of sprinklers with different flow rates was used. Gas exchange, vegetation indices (measured using a hyperspectral sensor embedded in a drone), yield and grain quality were evaluated. Water stress had different effects on gas exchange, vegetation indices, grain yield and chemical composition among the cultivars. Embrapa cultivar BRS 7280 Roundup ready (RR) and Nidera cultivar NA 5909 RG (glyphosate resistant) are yield stable and have a greater tolerance to drought. BRS 7280RR showed a higher tolerance to drought and higher water use efficiency (WUE) than all other tested cultivars. Vegetation indices, such as the NDVI (Normalized Difference Vegetation Index), correlated with the morphophysiological traits, such as plant height, were the most responsive variables to water stress. The NDVI can be used to predict soybean yield as a tool in a selection program under drought.

User-friendly devices for detecting low gliadin content in commercial foods are of extreme importance for people with gluten diseases. With this concern, the present work proposes a rapid and sensitive optical nanostructured microarrays platform for the detection of gliadin using specific anti-gliadin IgG antibodies immobilized on annealed gold nanostructures (AuNPs) obtained after the high annealing process (550 °C) of gold thin films evaporated on commercial glass coverslips. Localized Surface Plasmon Resonance (LSPR) immunosensing of gliadin in the range of 0.1 ppm to 1000 ppm is successfully achieved. In addition, the biofunctionalization protocol was used for gluten screening in five food complex products.

Quinoa stands out as an excellent crop in the Cerrado region for cultivation in the off-season or irrigated winter season. Here, we tested the effects of different water regimes on the agronomic characteristics, physiology, and grain quality of different elite quinoa genotypes under field conditions. The experiment was conducted under field conditions at Embrapa Cerrados (Planaltina, DF, Brazil). The experimental design was in randomized blocks, in a split-plot scheme, with four replications. The plots were composed of 18 quinoa genotypes and modified BRS Piabiru (the currently used genotype), and the split-plots were divided into 4 different water regimes. The following variables were evaluated: productivity and productivity per unit of applied water (PUAA), plant height, flavonoids, anthocyanins, gas exchange, chlorophyll, leaf proline, and relative water content. Our results showed that water regimes between 309 and 389 mm can be recommended for quinoa in the Cerrado region. CPAC6 and CPAC13 presented the highest yield and PUAA under high and intermediate WRs, and hence were the most suitable for winter growth under irrigation. CPAC17 is most suitable for off-season growth under rainfed conditions, as it presented the highest PUAA under the low WRs (247 and 150). CPAC9 stood out in terms of accumulation of flavonoids and anthocyanins in all WRs. Physiological analyses revealed different responses of the genotypes to water restriction, together with symptoms of stress under lower water regimes. Our study reinforces the importance of detailed analyses of the relationship between productivity, physiology, and water use when choosing genotypes for planting and harvest in different seasons.

A miniaturized quartz crystal microbalance (QCM) genosensor is proposed for sensitive and real-time detection of short ssDNA sequences (53 bp) or DNA extracted from Brettanomyces bruxellensis (Brett) yeast cells. The presence of Brett yeast causes a depreciation of the quality of aged fine wines, producing molecules of unpleasant odors and biogenic amines that are harmful to human health. More specifically, standard quartz crystal (S-QCM) and homemade 4 nm gold transmission electron microscopy (TEM)-grid patterned quartz (multi-TEM QCM) are herein proposed for biofunctionalization steps with different ssDNA sequences. By employing a rapid and efficient drop and collect protocol, the specific detection of 1 pg/µL ssDNA Brett of a short sequence and 100 ng/μL DNA of B. bruxellensis extracted from a wine sample (VR2008) is reported.

In many complex systems one observes the formation of medium-level structures, whose detection could allow a high-level description of the dynamical organization of the system itself, and thus to its better understanding. We have developed in the past a powerful method to achieve this goal, which however requires a heavy computational cost in several real-world cases. In this work we introduce a modified version of our approach, which reduces the computational burden. The design of the new algorithm allowed the realization of an original suite of methods able to work simultaneously at the micro level (that of the binary relationships of the single variables) and at meso level (the identification of dynamically relevant groups). We apply this suite to a particularly relevant case, in which we look for the dynamic organization of a gene regulatory network when it is subject to knock-outs. The approach combines information theory, graph analysis, and an iterated sieving algorithm in order to describe rather complex situations. Its application allowed to derive some general observations on the dynamical organization of gene regulatory networks, and to observe interesting characteristics in an experimental case.

The pervasiveness of online social networks has reshaped the way people access information. Online social networks make it common for users to inform themselves online and share news among their peers, but also favor the spreading of both reliable and fake news alike. Because fake news may have a profound impact on the society at large, realistically simulating their spreading process helps evaluate the most effective countermeasures to adopt. It is customary to model the spreading of fake news via the same epidemic models used for common diseases; however, these models often miss concepts and dynamics that are peculiar to fake news spreading. In this paper, we fill this gap by enriching typical epidemic models for fake news spreading with network topologies and dynamics that are typical of realistic social networks. Specifically, we introduce agents with the role of influencers and bots in the model and consider the effects of dynamical network access patterns, time-varying engagement, and different degrees of trust in the sources of circulating information. These factors concur with making the simulations more realistic. Among other results, we show that influencers that share fake news help the spreading process reach nodes that would otherwise remain unaffected. Moreover, we emphasize that bots dramatically speed up the spreading process and that time-varying engagement and network access change the effectiveness of fake news spreading.

Helicopters often operate in dusty sites, ingesting huge amounts of contaminants during landing, take-off, hover-taxi, and ground operations. In specific locations, the downwash of the rotor may spread soil particles from the ground into the environment and, once ingested by the engine, may stick to the compressor airfoils. In the present work, the Allison 250 C18 engine’s multistage axial-flow compressor is employed to study the fouling rate on rotor blades and stator vanes from both numerical and experimental standpoints. The compressor is operated in a typical ground-idle operation, in terms of the rotational regime and contaminant concentration, in laboratory-controlled conditions. The mass of deposits is collected from the airfoil surfaces at the end of the test and compared to that estimated through the numerical model. The experimental test shows that the airfoils collect almost 1.6% of the engine’s total mass ingested during a ground-idle operation. The capability of numerical methods to predict the fouling rate on the rotating and stationary airfoils of a multistage compressor is tested through the implementation of literature based deposition models. Sticking models show a good agreement in terms of the relative results; nevertheless, an overestimation of the deposited mass predicted is observed.

Underwater sensing and remote telemetry tasks necessitate the accurate geo-location of sensor data series, which often requires underwater acoustic arrays. These are ensembles of hydrophones that can be jointly operated in order to, e.g., direct acoustic energy towards a given direction, or to estimate the direction of arrival of a desired signal. When the available equipment does not provide the required level of accuracy, it may be convenient to merge multiple transceivers into a larger acoustic array, in order to achieve better processing performance. In this paper, we name such a structure an “array of opportunity” to signify the often inevitable sub-optimality of the resulting array design, e.g., a distance between nearest array elements larger than half the shortest acoustic wavelength that the array would receive. The most immediate consequence is that arrays of opportunity may be affected by spatial ambiguity, and may require additional processing to avoid large errors in wideband direction of arrival (DoA) estimation, especially as opposed to narrowband processing. We consider the design of practical algorithms to achieve accurate detections, DoA estimates, and position estimates using wideband arrays of opportunity. For this purpose, we rely jointly on DoA and rough multilateration estimates to eliminate spatial ambiguities arising from the array layout. By means of emulations that realistically reproduce underwater noise and acoustic clutter, we show that our algorithm yields accurate DoA and location estimates, and in some cases it allows arrays of opportunity to outperform properly designed arrays. For example, at a signal-to-noise ratio of –20 dB, a 15-element array of opportunity achieves lower average and median localization error (27 m and 12 m, respectively) than a 30-element array with proper λ / 2 element spacing (33 m and 15 m, respectively). We confirm the good accuracy of our approach via emulation results, and through a proof-of-concept lake experiment, where our algorithm applied to a 10-element array of opportunity achieves a 90th-percentile DoA estimation error of 4 ∘ and a 90th-percentile total location error of 5 m when applied to a real 10-element array of opportunity.

The recent and continuous development of unmanned aerial vehicles (UAV) and small cameras with different spectral resolutions and imaging systems promotes new remote sensing platforms that can supply ultra-high spatial and temporal resolution, filling the gap between ground-based surveys and orbital sensors. This work aimed to monitor siltation in two large rural and urban reservoirs by recording water color variations within a savanna biome in the central region of Brazil using a low cost and very light unmanned platform. Airborne surveys were conducted using a Parrot Sequoia camera (~0.15 kg) onboard a DJI Phantom 4 UAV (~1.4 kg) during dry and rainy seasons over inlet areas of both reservoirs. Field measurements of total suspended solids (TSS) and water clarity were made jointly with the airborne survey campaigns. Field hyperspectral radiometry data were also collected during two field surveys. Bio-optical models for TSS were tested for all spectral bands of the Sequoia camera. The near-infrared single band was found to perform the best (R2: 0.94; RMSE: 7.8 mg L−1) for a 0–180 mg L−1 TSS range and was used to produce time series of TSS concentration maps of the study areas. This flexible platform enabled monitoring of the increase of TSS concentration at a ~13 cm spatial resolution in urban and rural drainages in the rainy season. Aerial surveys allowed us to map TSS load fluctuations in a 1 week period during which no satellite images were available due to continuous cloud coverage in the rainy season. This work demonstrates that a low-cost configuration allows dense TSS monitoring at the inlet areas of reservoirs and thus enables mapping of the sources of sediment inputs, supporting the definition of mitigation plans to limit the siltation process.

Celiac diseases are a group of gluten ingestion-correlated pathologies that are widespread and, in some cases, very dangerous for human health. The only effective treatment is the elimination of gluten from the diet throughout life. Nowadays, the food industries are very interested in cheap, easy-to-handle methods for detecting gluten in food, in order to provide their consumers with safe and high-quality food. Here, for the first time, the manufacture of controlled micropatterns of annealed gold nanoislands (AuNIs) on a single QCM crystal (QCM-color) and their biofunctionalization for the specific detection of traces of gliadin is reported. In addition, the modified quartz crystal with a TEM grid and 30 nm Au (Q-TEM grid crystal) is proposed as an acoustic sensitive biosensing platform for the rapid screening of the gliadin content in real food products.

The spread of the organic rankine cycle applications has driven researchers and companies to focus on the improvement of their performance. In small to medium-sized plants, the expander is the component that has typically attracted the most attention. One of the most used types of machine in this scenario is the scroll. Among the other methods, numerical analyses have been increasingly exploited for the investigation of the machine’s behaviour. Nonetheless, there are major challenges for the successful application of computational fluid dynamics (CFD) to scrolls. Specifically, the dynamic mesh treatment required to capture the movement of working chambers and the nature of the expanding fluids require special care. In this work, a mesh generator for scroll machines is presented. Given few inputs, the software described provides the mesh and the nodal positions required for the evolution of the motion in a predefined mesh motion approach. The mesh generator is developed ad hoc for the coupling with the open-source CFD suite OpenFOAM. A full analysis is then carried out on a reverse-engineered commercial machine, including the refrigerant properties calculations via CoolProp. It is demonstrated that the proposed methodology allows for a fast simulation and achieves a good agreement with respect to former analyses.

Micro-ORC systems are usually equipped with positive displacement machines such as expanders and pumps. The pumping system has to guarantee the mass flow rate and allows a pressure rise from the condensation to the evaporation pressure values. In addition, the pumping system supplies the organic fluid, characterized by pressure and temperature very close to the saturation. In this work, a CFD approach is developed to analyze from a novel point of view the behavior of the pumping system of a regenerative lab-scale micro-ORC system. In fact, starting from the liquid receiver, the entire flow path, up to the inlet section of the evaporator, has been numerically simulated (including the Coriolis flow meter installed between the receiver and the gear pump). A fluid dynamic analysis has been carried out by means of a transient simulation with a mesh morphing strategy in order to analyze the transient phenomena and the effects of pump operation. The analysis has shown how the accuracy of the mass flow rate measurement could be affected by the pump operation being installed in the same circuit branch. In addition, the results have shown how the cavitation phenomenon affects the pump and the ORC system operation compared to control system actions.

In recent years, the influence of Ni on high-temperature mechanical properties of casting Al alloys has been extensively examined in the literature. In the present study, room temperature mechanical properties of an A356 alloy with Ni additions from 0.5 to 2 wt % were investigated. The role of Ni-based compounds and eutectic Si particles in reinforcing the Al matrix was studied with image analysis and was then related to tensile properties and microhardness. In the as-cast condition, the formation of the 3D network is not sufficient to determine an increase of mechanical properties of the alloys since fracture propagates by cleavage through eutectic Si particles and Ni aluminides or by the debonding of brittle phases from the aluminum matrix. After T6 heat treatment the increasing amount of Ni aluminides, due to further addition of Ni to the alloy, together with their brittle behavior, leads to a decrease of yield strength, ultimate tensile strength, and Vickers microhardness. Despite the fact that Ni addition up to 2 wt % hinders spheroidization of eutectic Si particles during T6 heat treatment, it also promotes the formation of a higher number of brittle Ni-based compounds that easily promote fracture propagation.

This paper gives a detailed technical overview of some of the activities carried out in the context of the “Wireless Sensor networks for city-Wide Ambient Intelligence (WISEWAI)” project, funded by the Cassa di Risparmio di Padova e Rovigo Foundation, Italy. The main aim of the project is to demonstrate the feasibility of large-scale wireless sensor network deployments, whereby tiny objects integrating one or more environmental sensors (humidity, temperature, light intensity), a microcontroller and a wireless transceiver are deployed over a large area, which in this case involves the buildings of the Department of Information Engineering at the University of Padova. We will describe how the network is organized to provide full-scale automated functions, and which services and applications it is configured to provide. These applications include long-term environmental monitoring, alarm event detection and propagation, single-sensor interrogation, localization and tracking of objects, assisted navigation, as well as fast data dissemination services to be used, e.g., to rapidly re-program all sensors over-the-air. The organization of such a large testbed requires notable efforts in terms of communication protocols and strategies, whose design must pursue scalability, energy efficiency (while sensors are connected through USB cables for logging and debugging purposes, most of them will be battery-operated), as well as the capability to support applications with diverse requirements. These efforts, the description of a subset of the results obtained so far, and of the final objectives to be met are the scope of the present paper.