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Sensors (Basel, Switzerland) Jan 2023Clean air in cities improves our health and overall quality of life and helps fight climate change and preserve our environment. High-resolution measures of pollutants'...
Clean air in cities improves our health and overall quality of life and helps fight climate change and preserve our environment. High-resolution measures of pollutants' concentrations can support the identification of urban areas with poor air quality and raise citizens' awareness while encouraging more sustainable behaviors. Recent advances in Internet of Things (IoT) technology have led to extensive use of low-cost air quality sensors for hyper-local air quality monitoring. As a result, public administrations and citizens increasingly rely on information obtained from sensors to make decisions in their daily lives and mitigate pollution effects. Unfortunately, in most sensing applications, sensors are known to be error-prone. Thanks to Artificial Intelligence (AI) technologies, it is possible to devise computationally efficient methods that can automatically pinpoint anomalies in those data streams in real time. In order to enhance the reliability of air quality sensing applications, we believe that it is highly important to set up a data-cleaning process. In this work, we propose AIrSense, a novel AI-based framework for obtaining reliable pollutant concentrations from raw data collected by a network of low-cost sensors. It enacts an anomaly detection and repairing procedure on raw measurements before applying the calibration model, which converts raw measurements to concentration measurements of gasses. There are very few studies of anomaly detection in raw air quality sensor data (millivolts). Our approach is the first that proposes to detect and repair anomalies in raw data before they are calibrated by considering the temporal sequence of the measurements and the correlations between different sensor features. If at least some previous measurements are available and not anomalous, it trains a model and uses the prediction to repair the observations; otherwise, it exploits the previous observation. Firstly, a majority voting system based on three different algorithms detects anomalies in raw data. Then, anomalies are repaired to avoid missing values in the measurement time series. In the end, the calibration model provides the pollutant concentrations. Experiments conducted on a real dataset of 12,000 observations produced by 12 low-cost sensors demonstrated the importance of the data-cleaning process in improving calibration algorithms' performances.
Topics: Air Pollutants; Particulate Matter; Artificial Intelligence; Quality of Life; Reproducibility of Results; Environmental Monitoring; Air Pollution; Environmental Pollutants
PubMed: 36679439
DOI: 10.3390/s23020640 -
Environmental Science. Processes &... Mar 2023Current methods to monitor nitrate levels in freshwater systems are outdated because they require expensive equipment and manpower. Punctual sampling on the field or at...
Current methods to monitor nitrate levels in freshwater systems are outdated because they require expensive equipment and manpower. Punctual sampling on the field or at a fixed measuring station is still the accepted monitoring procedure and fails to provide real-time estimation of nitrate levels. Continuous information is of crucial importance to evaluate the health of natural aquatic systems, which can strongly suffer from a nitrogen imbalance. We present here a nitrate-selective potentiometric probe to measure the analyte continuously without requiring maintenance or high-power consumption. Owing to a simple design where the sensors are located directly in contact with the sample, the need for constant pump usage is eliminated, requiring just 0.7 mW power per day instead of 184 mW per day and per pump. It is estimated that with this power consumption, the setup can easily run for more than 97 h on four simple Li-ion batteries. A simple in-line one-point calibration step was implemented to allow for drift correction. At the same time, a symmetrical design was used involving a second nitrate probe as a reference electrode placed in the calibrant compartment. This, combined with an calibration step, allows one to quantify nitrate ion concentrations directly, instead of yielding activities. The dependence on ion activity was removed by using the analysed sample spiked with nitrate as the calibrant. This results in essentially the same activity coefficients and additionally reduces junction potentials to a fraction of a millivolt. In addition, a symmetrical reference element served to compensate for fluctuations caused by environmental factors (temperature, convection, ) to achieve improved stability and signal reproducibility compared to a traditional Ag/AgCl based reference electrode. The final prototype was deployed in the Arve River in Geneva for 75 h without requiring any intervention. The nitrate levels measured using the symmetrical reference element over this period were estimated at 44.0 ± 3.5 M and agreed well with the values obtained with ion chromatography (38.2 ± 2.1 μM) used as the reference method. Thanks to a modular sensing head the potentiometric sensors can be easily exchanged, making it possible to quantify other types of analytes and leading the way to a new monitoring strategy.
Topics: Nitrates; Calibration; Reproducibility of Results; Fresh Water; Potentiometry
PubMed: 36655724
DOI: 10.1039/d2em00341d -
Cell Reports Jan 2023The endoplasmic reticulum (ER) is a tortuous organelle that spans throughout a cell with a continuous membrane containing ion channels, pumps, and transporters. It is...
The endoplasmic reticulum (ER) is a tortuous organelle that spans throughout a cell with a continuous membrane containing ion channels, pumps, and transporters. It is unclear if stimuli that gate ER ion channels trigger substantial membrane potential fluctuations and if those fluctuations spread beyond their site of origin. Here, we visualize ER membrane potential dynamics in HEK cells and cultured rat hippocampal neurons by targeting a genetically encoded voltage indicator specifically to the ER membrane. We report the existence of clear cell-type- and stimulus-specific ER membrane potential fluctuations. In neurons, direct stimulation of ER ryanodine receptors generates depolarizations that scale linearly with stimulus strength and reach tens of millivolts. However, ER potentials do not spread beyond the site of receptor activation, exhibiting steep attenuation that is exacerbated by intracellular large conductance K channels. Thus, segments of ER can generate large depolarizations that are actively restricted from impacting nearby, contiguous membrane.
Topics: Animals; Rats; Calcium; Endoplasmic Reticulum; Hippocampus; Membrane Potentials; Neurons; Ryanodine Receptor Calcium Release Channel; Humans; Cell Line
PubMed: 36640310
DOI: 10.1016/j.celrep.2022.111943 -
Bioengineering (Basel, Switzerland) Dec 2022In this research, a one-dimensional (1D) photonic structure was employed to study the nature of both enamel and dentine teeth at the signal of 1.8 THz. A simple three...
In this research, a one-dimensional (1D) photonic structure was employed to study the nature of both enamel and dentine teeth at the signal of 1.8 THz. A simple three layer one-dimensional crystal is chosen to avoid fabrication intricacy. The materials and methods for sample preparations are discussed. The principle of investigation of caries in the teeth relies on the amount of reflected signal from the structure. Similarly, reflectance is a function of refractive indices and thickness of each layer, the nature of both substrate and infiltrated materials, and the configuration of the structure. Apart from this, the fabrication process of one-dimensional structure and experimental set-up was proposed in this article. The numerical treatment is explained here to obtain reflectance, and subsequently, the output potential. Comparison studies on output potential between enamel and dentine are also shown through graphical representation. The output result in terms of milli-Volt (mV) were obtained at the output end and collected at the photodiode. Interesting results were also observed at the photodetector. For example; the output potential of the reflected signal is around 0.18 mV for both enamel and dentine teeth whereas the potential is more than 0.26 mV and 0.31 mV for caries in dentine and enamel, respectively. Finally, it was inferred that the nature of teeth pertaining to the caries in the enamel and dentine teeth can be investigated by identifying the amount of potential at the output end.
PubMed: 36550994
DOI: 10.3390/bioengineering9120788 -
Sensors (Basel, Switzerland) Dec 2022DAS and geophones are the two most popular sensors for borehole seismic acquisition. As such, it is important to get a good understanding of how these two types of...
DAS and geophones are the two most popular sensors for borehole seismic acquisition. As such, it is important to get a good understanding of how these two types of sensors compare to each other. The natural measurand for the techniques is different; millivolts are approximately proportional to particle velocities for geophones vs. changes in the phase of light linked to the changes in strain on the sensing fibre. This paper focuses on the experimental comparison of absolute values of these measurands derived from a VSP survey acquired in Curtin GeoLab training well. We describe the acquisition setup for the walk-away VSP acquired with DAS and geophones, allowing the direct comparison and the workflow, which we can use to represent the data in strain rate. Albeit this is unlikely to be universal, we find that the absolute values are similar for this experimental setup.
PubMed: 36502212
DOI: 10.3390/s22239510 -
ACS Applied Materials & Interfaces Dec 2022Moisture-activated electric generators (MEGs) that harvest clean energy from atmospheric humidity offer exciting opportunities for upgraded energy conversions. However,...
Moisture-activated electric generators (MEGs) that harvest clean energy from atmospheric humidity offer exciting opportunities for upgraded energy conversions. However, it is challenging to obtain MEGs that are both easy to fabricate and of high output power, due to the requirement for particular functional materials and the cumbersome manufacturing process. Herein, a simple and general method is adopted to prepare MEGs with chemically gradient structures. As a specific example, a gradient distribution of citric acid was successfully constructed inside an A4 printer paper by asymmetric drying, which can generate a continuous voltage of tens of millivolts by ambient humidity, and even to volts (275 mV and 7.6 μA cm) under asymmetric humidity stimulation, and the maximum power density output was 2.1 μW cm. The driving force behind this energy conversion is a self-maintained ionic gradient created within the paper by the asymmetric ionization of gradient organic acids when exposed to gradient or nongradient humid air. This work broadens the class of materials and possibilities for the rapid development of MEGs, shedding new light on the revolution of generators that harvest green and sustainable energy for power generation.
PubMed: 36437545
DOI: 10.1021/acsami.2c12777 -
Nanoscale Advances Mar 2022Harvesting ocean wave energy through carbon-based materials, particularly graphene, is receiving increasing attention. However, the complicated fabrication process and...
Harvesting ocean wave energy through carbon-based materials, particularly graphene, is receiving increasing attention. However, the complicated fabrication process and the low output power of the present monolayer graphene-based wave energy generators limit their further application. Here, we demonstrate the facile fabrication of a new type of wave energy generator based on graphene/TiO nanoparticle composite films using the doctor-blading method. The developed wave energy harvesting device exhibits a high open-circuit voltage of up to 75 millivolts and a high output power up to 1.8 microwatts. A systematic study was conducted to explore the optimal conditions for the energy harvesting performance.
PubMed: 36134363
DOI: 10.1039/d1na00658d -
Chemistry, An Asian Journal Nov 2022Ionic thermoelectric (i-TE) materials have attracted much attention due to their ability to generate ionic Seebeck coefficient of tens of millivolts per Kelvin. In this...
Ionic thermoelectric (i-TE) materials have attracted much attention due to their ability to generate ionic Seebeck coefficient of tens of millivolts per Kelvin. In this work, we demonstrate that the ionic thermopower can be enhanced by the introduction of multiple ions. The multi-ionic hydrogel possesses a record thermal-to-electrical energy conversion factor (TtoE factor) of 89.6 mV K and an ionic conductivity of 6.8 mS cm , which are both better than single salt control hydrogel. Subsequently we build a model to explain thermal diffusion of the ions in multi-ionic hydrogels. Finally, the possibility of large-scale integrated applications of multi-ionic hydrogels is demonstrated. By connecting 7 i-TEs hydrogels, we obtained an open-circuit voltage of 1.86 V at ΔT=3 K. Our work provides a new pathway for the design of i-TEs and low-grade heat harvesting.
PubMed: 36074542
DOI: 10.1002/asia.202200850 -
International Journal For Numerical... Nov 2022Arrhythmogenic right ventricular cardiomyopathy (ARVC) is an inherited heart muscle disease that appears between the second and forth decade of a patient's life, being...
Arrhythmogenic right ventricular cardiomyopathy (ARVC) is an inherited heart muscle disease that appears between the second and forth decade of a patient's life, being responsible for 20% of sudden cardiac deaths before the age of 35. The effective and punctual diagnosis of this disease based on electrocardiograms (ECGs) could have a vital role in reducing premature cardiovascular mortality. In our analysis, we first outline the digitalization process of paper-based ECG signals enhanced by a spatial filter aiming to eliminate dark regions in the dataset's images that do not correspond to ECG waveform, producing undesirable noise. Next, we propose the utilization of a low-complexity convolutional neural network for the detection of an arrhythmogenic heart disease, that has not been studied through the usage of deep learning methodology to date, achieving high classification accuracy, namely 99.98% training and 98.6% testing accuracy, on a disease the major identification criterion of which are infinitesimal millivolt variations in the ECG's morphology, in contrast with other arrhythmogenic abnormalities. Finally, by performing spectral analysis we investigate significant differentiations in the field of frequencies between normal ECGs and ECGs corresponding to patients suffering from ARVC. In 16 out of the 18 frequencies where we encounter statistically significant differentiations, the normal ECGs are characterized by greater normalized amplitudes compared to the abnormal ones. The overall research carried out in this article highlights the importance of integrating mathematical methods into the examination and effective diagnosis of various diseases, aiming to a substantial contribution to their successful treatment.
Topics: Humans; Arrhythmogenic Right Ventricular Dysplasia; Artificial Intelligence; Electrocardiography; Arrhythmias, Cardiac; Neural Networks, Computer
PubMed: 36053812
DOI: 10.1002/cnm.3644 -
Nuclear Medicine Review. Central &... 2022Thyroid cancer is the most common malignant disease of the endocrine system and radioiodine therapy (RAIT) is still very often used, resulting in patients staying...
BACKGROUND
Thyroid cancer is the most common malignant disease of the endocrine system and radioiodine therapy (RAIT) is still very often used, resulting in patients staying hospitalized for a few days alone and without visitors, augmenting their stress and discomfort. Our objective was to find simple ways of improving RAIT patients' feelings and perceived quality of the nuclear medicine (NM) department services.
MATERIAL AND METHODS
We designed a two-year study in order to enhance RAIT patients' perceived quality of the nuclear medicine (NM) department services and expectations' fulfillment. A questionnaire was used in order to capture patients' perceived quality and expectations from their RAIT.
RESULTS
549 replies were collected. Many intrinsic and extrinsic determinants were found to be positively or negatively related to the perceived quality and fulfillment of patients' expectations of receiving RAIT. A 1% increase could be achieved by spending 110 € per RAIT room.
CONCLUSIONS
In this article, we present some easily implemented changes in both personnel behavior and room amenities that could, at least in theory and based on our results, offer a 37.9% improvement in RAIT patients' perceived quality and expectations' fulfillment at a cost of 4169 €.
Topics: Humans; Iodine Radioisotopes; Motivation; Radionuclide Imaging; Thyroid Neoplasms
PubMed: 36047293
DOI: 10.5603/NMR.a2022.0031