scholarly journals Real Time Monitoring of Calcium Oxalate Precipitation Reaction by Using Corrosion Resistant Magnetoelastic Resonance Sensors

Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2802 ◽  
Author(s):  
Beatriz Sisniega ◽  
Ariane Sagasti Sedano ◽  
Jon Gutiérrez ◽  
Alfredo García-Arribas
Keyword(s):  
Corrosion Resistance ◽  
Calcium Oxalate ◽  
Real Time ◽  
Excitation Frequency ◽  
Resonance Curve ◽  
Time Interval ◽  
Precipitation Reaction ◽  
Oxalate Precipitation ◽  
Pre Treatment ◽  
Magnetoelastic Resonance

The magnetoelastic resonance is used to monitor the precipitation reaction of calcium oxalate ( C a C 2 O 4 ) crystals in real-time, by measuring the shift of the resonance frequency caused by the mass increase on the resonator. With respect to previous work on the same matter, the novelty lies in the adoption of an amorphous ferromagnetic alloy, of composition F e 73 C r 5 S i 10 B 12 , as resonator, that replaces the commercial Metglas® 2826 alloy (composition F e 40 N i 38 M o 4 B 18 ). The enhanced corrosion resistance of this material allows it to be used in biological environments without any pre-treatment of its surface. Additionally, the measurement method, which has been specifically adapted to this application, allows quick registration of the whole resonance curve as a function of the excitation frequency, and thus enhances the resolution and decreases the detection noise. The frequency shift is calibrated by the static deposition of well-known masses of C a C 2 O 4 . The resonator dimensions have been selected to improve sensitivity. A 20 mm long, 2 mm wide and 25 μ m thick magnetoelastic resonator has been used to monitor the precipitation reaction of calcium oxalate in a 500 s time interval. The results of the detected precipitated mass when oxalic acid and calcium chloride are mixed in different concentrations (30 mM, 50 mM and 100 mM) are presented as a function of time. The results show that the sensor is capable of monitoring the precipitation reaction. The mass sensitivity obtained, and the corrosion resistance of the material, suggest that this material can perform excellently in monitoring this type of reaction.

scholarly journals Improved Determination of Q Quality Factor and Resonance Frequency in Sensors Based on the Magnetoelastic Resonance Through the Fitting to Analytical Expressions

Materials ◽  
2020 ◽  
Vol 13 (21) ◽  
pp. 4708
Author(s):  
Beatriz Sisniega ◽  
Jon Gutiérrez ◽  
Virginia Muto ◽  
Alfredo García-Arribas
Keyword(s):  
Quality Factor ◽  
Resonance Curve ◽  
Peak Position ◽  
Precipitation Reaction ◽  
Magnetoelastic Sensors ◽  
Resonance Curves ◽  
Quality Factor Q ◽  
Magnetoelastic Resonance ◽  
Analytical Expressions

The resonance quality factor Q is a key parameter that describes the performance of magnetoelastic sensors. Its value can be easily quantified from the width and the peak position of the resonance curve but, when the resonance signals are small, for instance when a lot of damping is present (low quality factor), this and other simple methods to determine this parameter are highly inaccurate. In these cases, numerical fittings of the resonance curves allow to accurately obtain the value of the quality factor. We present a study of the use of different expressions to numerically fit the resonance curves of a magnetoelastic sensor that is designed to monitor the precipitation reaction of calcium oxalate. The study compares the performance of both fittings and the equivalence of the parameters obtained in each of them. Through these numerical fittings, the evolution of the different parameters that define the resonance curve of these sensors is studied, and their accuracy in determining the quality factor is compared.

scholarly journals Time-to-Treatment in Oral Cancer: Causes and Implications for Survival

Cancers ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 1321
Author(s):  
Constanza Saka-Herrán ◽  
Enric Jané-Salas ◽  
Antoni Mari-Roig ◽  
Albert Estrugo-Devesa ◽  
José López-López
Keyword(s):  
Oral Cancer ◽  
Previous Treatment ◽  
Diagnostic Procedures ◽  
Original Data ◽  
Primary Treatment ◽  
Medical Attention ◽  
Time Interval ◽  
Pre Treatment ◽  
The Impact ◽  
Lack Of Knowledge

The purpose of this review was to identify and describe the causes that influence the time-intervals in the pathway of diagnosis and treatment of oral cancer and to assess its impact on prognosis and survival. The review was structured according to the recommendations of the Aarhus statement, considering original data from individual studies and systematic reviews that reported outcomes related to the patient, diagnostic and pre-treatment intervals. The patient interval is the major contributor to the total time-interval. Unawareness of signs and/or symptoms, denial and lack of knowledge about oral cancer are the major contributors to the process of seeking medical attention. The diagnostic interval is influenced by tumor factors, delays in referral due to higher number of consultations and previous treatment with different medicines or dental procedures and by professional factors such as experience and lack of knowledge related to the disease and diagnostic procedures. Patients with advanced stage disease, primary treatment with radiotherapy, treatment at an academic facility and transitions in care are associated with prolonged pre-treatment intervals. An emerging body of evidence supports the impact of prolonged pre-treatment and treatment intervals with poorer survival from oral cancer.

scholarly journals Improving the Stochastic Model of Ionospheric Delays for BDS Long-Range Real-Time Kinematic Positioning

2021 ◽  
Vol 13 (14) ◽  
pp. 2739
Author(s):  
Huizhong Zhu ◽  
Jun Li ◽  
Longjiang Tang ◽  
Maorong Ge ◽  
Aigong Xu
Keyword(s):  
Real Time ◽  
Long Range ◽  
Ionospheric Delay ◽  
Time Interval ◽  
Short Time Interval ◽  
Dual Frequency ◽  
Triple Frequency ◽  
Ambiguity Fixing ◽  
Power Spectral ◽  
Observation Noise

Although ionosphere-free (IF) combination is usually employed in long-range precise positioning, in order to employ the knowledge of the spatiotemporal ionospheric delays variations and avoid the difficulty in choosing the IF combinations in case of triple-frequency data processing, using uncombined observations with proper ionospheric constraints is more beneficial. Yet, determining the appropriate power spectral density (PSD) of ionospheric delays is one of the most important issues in the uncombined processing, as the empirical methods cannot consider the actual ionosphere activities. The ionospheric delays derived from actual dual-frequency phase observations contain not only the real-time ionospheric delays variations, but also the observation noise which could be much larger than ionospheric delays changes over a very short time interval, so that the statistics of the ionospheric delays cannot be retrieved properly. Fortunately, the ionospheric delays variations and the observation noise behave in different ways, i.e., can be represented by random-walk and white noise process, respectively, so that they can be separated statistically. In this paper, we proposed an approach to determine the PSD of ionospheric delays for each satellite in real-time by denoising the ionospheric delay observations. Based on the relationship between the PSD, observation noise and the ionospheric observations, several aspects impacting the PSD calculation are investigated numerically and the optimal values are suggested. The proposed approach with the suggested optimal parameters is applied to the processing of three long-range baselines of 103 km, 175 km and 200 km with triple-frequency BDS data in both static and kinematic mode. The improvement in the first ambiguity fixing time (FAFT), the positioning accuracy and the estimated ionospheric delays are analysed and compared with that using empirical PSD. The results show that the FAFT can be shortened by at least 8% compared with using a unique empirical PSD for all satellites although it is even fine-tuned according to the actual observations and improved by 34% compared with that using PSD derived from ionospheric delay observations without denoising. Finally, the positioning performance of BDS three-frequency observations shows that the averaged FAFT is 226 s and 270 s, and the positioning accuracies after ambiguity fixing are 1 cm, 1 cm and 3 cm in the East, North and Up directions for static and 3 cm, 3 cm and 6 cm for kinematic mode, respectively.

scholarly journals An LSTM-Based Method Considering History and Real-Time Data for Passenger Flow Prediction

2020 ◽  
Vol 10 (11) ◽  
pp. 3788 ◽  
Author(s):  
Qi Ouyang ◽  
Yongbo Lv ◽  
Jihui Ma ◽  
Jing Li
Keyword(s):  
Feature Extraction ◽  
Real Time ◽  
Short Term Memory ◽  
Historical Data ◽  
Time Interval ◽  
Information Coding ◽  
Time Data ◽  
Passenger Flow ◽  
Flow Prediction ◽  
Real Time Data

With the development of big data and deep learning, bus passenger flow prediction considering real-time data becomes possible. Real-time traffic flow prediction helps to grasp real-time passenger flow dynamics, provide early warning for a sudden passenger flow and data support for real-time bus plan changes, and improve the stability of urban transportation systems. To solve the problem of passenger flow prediction considering real-time data, this paper proposes a novel passenger flow prediction network model based on long short-term memory (LSTM) networks. The model includes four parts: feature extraction based on Xgboost model, information coding based on historical data, information coding based on real-time data, and decoding based on a multi-layer neural network. In the feature extraction part, the data dimension is increased by fusing bus data and points of interest to improve the number of parameters and model accuracy. In the historical information coding part, we use the date as the index in the LSTM structure to encode historical data and provide relevant information for prediction; in the real-time data coding part, the daily half-hour time interval is used as the index to encode real-time data and provide real-time prediction information; in the decoding part, the passenger flow data for the next two 30 min interval outputs by decoding all the information. To our best knowledge, it is the first time to real-time information has been taken into consideration in passenger flow prediction based on LSTM. The proposed model can achieve better accuracy compared to the LSTM and other baseline methods.

A New Method for Phase Difference Estimation Based on Time-Varying Signal Model

2013 ◽  
Vol 333-335 ◽  
pp. 650-655
Author(s):  
Peng Hui Niu ◽  
Yin Lei Qin ◽  
Shun Ping Qu ◽  
Yang Lou
Keyword(s):  
Signal Processing ◽  
Real Time ◽  
Phase Difference ◽  
Time Signal ◽  
Time Interval ◽  
Time Varying ◽  
Signal Model ◽  
Time Frequency ◽  
Mass Flowmeter ◽  
Coriolis Mass Flowmeter

A new signal processing method for phase difference estimation was proposed based on time-varying signal model, whose frequency, amplitude and phase are time-varying. And then be applied Coriolis mass flowmeter signal. First, a bandpass filtering FIR filter was applied to filter the sensor output signal in order to improve SNR. Then, the signal frequency could be calculated based on short-time frequency estimation. Finally, by short window intercepting, the DTFT algorithm with negative frequency contribution was introduced to calculate the real-time phase difference between two enhanced signals. With the frequency and the phase difference obtained, the time interval of two signals was calculated. Simulation results show that the algorithms studied are efficient. Furthermore, the computation of algorithms studied is simple so that it can be applied to real-time signal processing for Coriolis mass flowmeter.

Nephrolithiasis

2018 ◽  
Author(s):  
José Luiz Nishiura ◽  
Ita Pfeferman Heilberg
Keyword(s):  
Uric Acid ◽  
Calcium Oxalate ◽  
Dietary Habits ◽  
Stone Formation ◽  
Urine Volume ◽  
First Episode ◽  
Dietary Advice ◽  
Dietary Recommendations ◽  
Genetic Traits ◽  
Oxalate Precipitation

Nephrolithiasis is a highly prevalent condition, but its incidence varies depending on race, gender, and geographic location. Approximately half of patients form at least one recurrent stone within 10 years of the first episode. Renal stones are usually composed of calcium salts (calcium oxalate monohydrate or dihydrate, calcium phosphate), uric acid, or, less frequently, cystine and struvite (magnesium, ammonium, and phosphate). Calcium oxalate stones, the most commonly encountered ones, may result from urinary calcium oxalate precipitation on the Randall plaque, which is a hydroxyapatite deposit in the interstitium of the kidney medulla. Uric acid nephrolithiasis, which is common among patients with metabolic syndrome or diabetes mellitus, is caused by an excessively acidic urinary pH as a renal manifestation of insulin resistance. The medical evaluation of the kidney stone patient must be focused on identifying anatomic abnormalities of the urinary tract, associated systemic diseases, use of lithogenic drugs or supplements, and, mostly, urinary risk factors such as low urine volume, hypercalciuria, hyperuricosuria, hypocitraturia, hyperoxaluria, and abnormalities in urine pH that can be affected by dietary habits, environmental factors, and genetic traits. Metabolic evaluation requires a urinalysis, stone analysis (if available), serum chemistry, and urinary parameters, preferably obtained by two nonconsecutive 24-hour urine collections under a random diet. Targeted medication and dietary advice are effective to reduce the risk of recurrence. Clinical, radiologic, and laboratory follow-ups are needed to prevent stone growth and new stone formation, to assess treatment adherence or effectiveness to dietary recommendations, and to allow adjustment of pharmacologic treatment. This review contains 5 highly rendered figure, 3 tables, and 105 references.

Control of cell shape by calcium in the euglenophyceae

1981 ◽  
Vol 49 (1) ◽  
pp. 99-117 ◽  
Author(s):  
J.M. Murray
Keyword(s):  
Endoplasmic Reticulum ◽  
Atpase Activity ◽  
Calcium Oxalate ◽  
Cell Shape ◽  
Motor Units ◽  
Astasia Longa ◽  
Oxalate Precipitation ◽  
Entire Cell ◽  
The Individual ◽  
Euglenoid Movement

The euglenoid flagellates are able to change their shape rapidly in response to a variety of stimuli, or sometimes spontaneously. Two extremes of shape can be identified: the “relaxed” form is cylindrical; the contracted form is a somewhat distorted disc. These 2 forms can be interconverted by treatments that alter the Ca2+ concentration of the entire cell. The level of Ca2+ is believed to be normally controlled by a system of calcium-accumulating membranes, identified in Astasia longa by the technique of calcium oxalate precipitation. The system forms a set of parallel tubes of endoplasmic reticulum, one of which lies immediately below each of the ridges of the pellicle. The individual ridges, each with its associated reticulum, microtubules and other elements are suggested to be independent motor units. Local activation of a small number of these units by Ca2+ is made possible by the arrangement of Ca2+ -sequestering reticulum, producing the characteristic squirming euglenoid movement. Uniform activation or suppression of all units produces the 2 extremes of shape. The pellicle of A. longa with its associated microtubules has been purified and shown to contain a Ca2+ -binding site and ATPase activity.

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