Sampling Frequency Research Articles

A neural network‐based error correction in the first‐stage residue of pipelined analog to digital converters

SummaryAn analog background calibration approach is presented for the full calibration of pipeline analog‐to‐digital converters (ADCs). A well‐trained neural network acts close to the ideal 1.5‐bit stage, and its residue is compared with the real 1.5‐bit stage including gain error and amplifier nonlinearities. The detected error is used to compensate for the imperfect residue using four calibration polynomial coefficients. The corrected residue enters the second stage of the pipeline ADC and follows a normal path to achieve high resolution. The introduced structure is verified in a 12‐bit pipelined ADC composed of 11 stages; the first 10 stages have a 1.5‐bit structure, while the last stage is a 2‐bit flash. The sampling frequency is 100 MHz, and 10% non‐ideal factors (5% for each of the nonlinear and gain errors and 10% for the aggregated error) are considered for the first stage, while the input is 19.5 MHz sinusoidal waveform. A random noise is applied to the input to limit the effective number of bits (ENOB) to almost 11.8. The evaluation parameters of the ADC are extracted, signal‐to‐noise and distortion ratio increases from 39.14 to 72.91 dB, spurious free dynamic range improves from 40.94 to 79.69 dB, and the ENOB enhances from 6.2 to 11.82. The presented mechanism shows an acceptable accuracy in the high‐speed and high‐resolution ADCs.

Quasi-random frequency sampling for optical turbulence simulations

Optical turbulence modeling and simulation are crucial for developing astronomical ground-based instruments, laser communication, laser metrology, or any application where light propagates through a turbulent medium. In the context of spectrum-based optical turbulence Monte-Carlo simulations, we present an alternative approach to the methods based on the fast Fourier transform (FFT) using a quasi-random frequency sampling heuristic. This approach provides complete control over the spectral information expressed in the simulated measurable without the drawbacks encountered with FFT-based methods such as high-frequency aliasing, low-frequency under-sampling, and static sampling statistics. The method’s heuristics, implementation, and an application example from the study of differential piston fluctuations are discussed.

Determination of parameters generating the reference pressure in the primary level dynamic pressure measurement system based on the drop weight method

For some industries such as automotive, defence, aerospace, pharmaceutical manufacturing, dynamic pressure measurement is an important requirement. In a primary level dynamic pressure measurement system with a drop weight method, the dynamic pressure value is calculated using parameters such as the effective area value depending on the piston cylinder unit, the maximum acceleration value measured by a laser interferometer. On the other hand, the type of liquid used in the measuring head is another important factor affecting repeatability and providing ease of measurement. In this study, a new measurement head, piston and cylinders were designed, manufactured and the Taguchi method was used to accurately determine some parameters affecting the measurements in a dynamic primary pressure measurement system operating with the drop weight method. In the studies carried out, four pistons, four cylinders, four sampling frequency values and two liquid types were considered. By using the Taguchi method, the optimum parameters of the dynamic pressure measurement system with drop weight method were determined with only sixteen experiments instead of one hundred and twenty-eight.

In-situ measurement of subway train-induced vibration and noise of steel spring floating slab with MEMS-based sensing units

The concrete floating slab, as a widely-used measure to reduce the subway-induced vibration and noise, can deteriorate with the accumulation of trainload. To monitor the dynamic performance of the floating slab during operation, this study develops a lightweight sensing unit based on microelectromechanical systems (MEMS). This sensing unit, which can be easily mounted on the concrete slab, enables synchronous monitoring of vibration and noise at different sampling frequencies with a very low power consumption. With the advantage of easy installation, the sensing units are mounted on various concrete slabs and tunnel walls to collect massive vibration and noise data. With the monitoring data, the dynamic performance and vibration reduction capability of the floating slab can be assessed. A case study is conducted on two floating slab sections: one section has a floating slab with a potential defect on its shear hinge and the other has a normal floating slab. The monitoring results show that: (1) the train condition has a significant effect on the amplitude of the track-side vibration; (2) the train-induced noise data last longer than vibration data during the passage of trains; (3) for the floating slab with shear hinge defect, the vibration levels at edge points are much higher than that in the middle. Through the monitoring test, the performance of the MEMS-based sensing unit and its adaptability in subway circumstances are verified.

An Empirical Study On Imaging Sensitivity Of SKA1-LOW Based on Point Source Sensitivity

The Square Kilometre Array (SKA) radio telescope will achieve unparalleled sensitivity and angular resolution, substantially progressing our research into the formation and development of the early universe. Sensitivity is one of the most critical telescope metrics, often used to determine the observing mode and observing time of a radio source. It is also used to determine imaging parameters to balance imaging sensitivity and spatial resolution during data processing. In this paper, to meet the needs of continuum imaging pipeline data processing for the SKA1-LOW telescope, we derive equations for point-source-sensitivity (PSS) calculations under multichannel, multipolarization, discrete frequency sampling, discrete time sampling, and different weighting schemes. After validating the correctness of the equation, we improved and refined the sensitivity calculation application in the Radio Astronomy Simulation, Calibration, and Imaging Library, and further calculated the variation of the PSS versus angular resolution for the full-scale SKA1-LOW with different weighting schemes, and provided SKA1-LOW broadband image performance as functions of angular scale for four frequencies. These results can provide not only a theoretical basis for the construction and commissioning of the SKA1-LOW telescope but also guidance for imaging processing in future scientific data processing.

Physicochemical properties of water in the Nida valley, Poland

The investigation of Nida Valley water aimed to assess fluctuations in physicochemical properties. In this study, environmental monitoring method was utilized to evaluate the changes in physicochemical properties of water. Over a 24-month period, from June 2021 to May 2023, a total of 228 water samples were collected from 10 sampling sites, with a monthly sampling frequency. Statistical analyses were utilized including the Shapiro–Wilk test (α = 0.05), Kruskal–Wallis test and Wilcoxon (Mann–Whitney) rank sum test (α = 0.05), Pearson correlation analysis (α = 0.001) and principal component analysis (PCA). Statistical analyses revealed significant differences between months in GW samples for for temperature, dissolved oxygen, pH, total nitrogen, total phosphorus, chloride, manganese, and zinc in GW samples and for T and DO in SW samples. Pearson correlation coefficient analysis (α = 0.001) identified strong positive correlations within the SW dataset. Similarly, significant positive correlations were observed among the GW dataset. Noteworthy positive correlations were also detected between the GW and SW datasets. Principal component analysis (PCA) revealed a substantial dissimilarity between GW2 samples compared to others, characterized by elevated manganese, iron, and Sulfate content. Two distinct groups emerged: Group 1 included samples at GW1, GW2, GW3, GW5, and SW2, while Group 2 comprised all other samples. This study demonstrated the stability in the physicochemical properties of SW and underscore a discernible correlation between the hydrochemical compositions of both SW and GW in the riparian area. Outstanding characteristics in hydrochemical component of sample waters have been indicated.

Autocalibration based on dilution of a single concentrated standard is used for the determination of silicate in sea water by the modified molybdenum blue method

The silicate (Si) molybdenum blue method was modified by combining oxalate and ascorbic acid into a single reagent and was used for determining Si in sea water samples. The first step of this automated assay protocol was designed to perform either a calibration by a single Si standard prepared in deionized (DI) water, or to dilute samples in the range of 0–160 μM Si to fit into 0–20 μM Si calibration range using a 20 cm flow cell. By designing the assay protocol to function in batch mode, the influence of salinity on calibration was eliminated, thus making the method suitable for analysis of samples collected in the open ocean, coastal areas, or rivers. Reproducibility and accuracy of this method were evaluated by analysis of certified sea water reference materials. Phosphate (P) does not interfere significantly if the Si:P ratio is 4:1 or larger. The limit of detection was 514 nM Si, r.s.d. 2.1 %, sampling frequency 40 s/h, reagent consumption 700 μL/sample, and using deionized water as the carrier solution.

Response patterns of moss to atmospheric nitrogen deposition and nitrogen saturation in an urban–agro–forest transition

Abstract. Increasing trends of atmospheric nitrogen (N) deposition resulting from a large number of anthropogenic emissions of reactive N are dramatically altering the global biogeochemical cycle of N. Nitrogen uptake by mosses occurs mainly from the atmosphere, making it a competent bio-indicator of N deposition. However, high uncertainties exist when using mosses to indicate N deposition, especially in choosing sampling periods and sampling frequencies. In this study, atmospheric N deposition and moss N content in the urban–agro–forest transition, a region with a high N deposition level of 27.46–43.70 kg N hm−2 yr−1, were monitored, and the method for monitoring atmospheric N deposition by mosses was optimized. We found that the optimal sampling frequency is within 6 months per time, and the optimal sampling times are winter (January and February), autumn (October and November), and summer (July and August), which provides us with a more accurate estimation of atmospheric N deposition than other scenarios. In addition, the moss N content serves as a more reliable N species. This study eventually allowed mosses to be used more effectively and sensibly as an indicator of atmospheric N deposition and helped to improve the accuracy of the model for quantifying N deposition.

Data augmentation for generating synthetic electrogastrogram time series.

To address an emerging need for large number of diverse datasets for rigor evaluation of signal processing techniques, we developed and evaluated a new method for generating synthetic electrogastrogram time series. We used electrogastrography (EGG) data from an open database to set model parameters and statistical tests to evaluate synthesized data. Additionally, we illustrated method customization for generating artificial EGG time series alterations caused by the simulator sickness. Proposed data augmentation method generates synthetic EGG data with specified duration, sampling frequency, recording state (postprandial or fasting state), overall noise and breathing artifact injection, and pauses in the gastric rhythm (arrhythmia occurrence) with statistically significant difference between postprandial and fasting states in > 70% cases while not accounting for individual differences. Features obtained from the synthetic EGG signal resembling simulator sickness occurrence displayed expected trends. The code for generation of synthetic EGG time series is not only freely available and can be further customized to assess signal processing algorithms but also may be used to increase data diversity for training artificial intelligence (AI) algorithms. The proposed approach is customized for EGG data synthesis but can be easily utilized for other biosignals with similar nature such as electroencephalogram.

Frequency Offset Estimation for UWB-OFDM System using Weight and Exhaustiveness based Monarch Butterfly Optimization Approach

The performance of an OFDM system has limitation because the carrier frequency offset (CFO) and sampling frequency offset (SFO) is not estimated correctly. Current methods propose the way of obtaining frequency estimation by using the evolutionary algorithm, but the evolution algorithm suffers from the premature convergence problem. In order to provide efficient frequency offset estimation, this paper proposed weight and exhaustiveness based monarch butterfly optimization approach. First, on the transmitter block, for modulating an input symbol, the Hybrid-Quadrature Phase-Shift Keying modulation scheme is used. Brunn’s IFFT is done at each transmitter for symbol mapping and then in each transmitter block cyclic prefix is inserted. After that, WE-MBO algorithm estimates the frequency offset. On receiver side, the inverse operation of the transmitter is performed. After comparison of proposed system with the existing system, the proposed system gave better performance.

Technical note: Two-component electrical-conductivity-based hydrograph separation employing an exponential mixing model (EXPECT) provides reliable high-temporal-resolution young water fraction estimates in three small Swiss catchments

Abstract. The young water fraction represents the portion of water molecules in a stream that have entered the catchment relatively recently, typically within 2–3 months. It can be reliably estimated in spatially heterogeneous and nonstationary catchments from the amplitude ratio of seasonal isotope (δ18O or δ2H) cycles of stream water and precipitation, respectively. Past studies have found that young water fractions increase with discharge (Q), thus reflecting the higher direct runoff under wetter catchment conditions. The rate of increase in the young water fraction with increasing Q, defined as the discharge sensitivity of the young water fraction (Sd*), can be useful for describing and comparing catchments' hydrological behaviour. However, the existing method for estimating Sd*, which only uses biweekly isotope data, can return highly uncertain and unreliable Sd* when stream water isotope data are sparse and do not capture the entire flow regime. Indeed, the information provided by isotope data depends on when the respective sample was taken. Accordingly, the low sampling frequency results in information gaps that could potentially be filled by using additional tracers sampled at a higher temporal resolution. By utilizing high-temporal-resolution and cost-effective electrical conductivity (EC) measurements, along with information obtainable from seasonal isotope cycles in stream water and precipitation, we develop a new method that can estimate the young water fraction at the same resolution as EC and Q measurements. These high-resolution estimates allow for improvements in the estimates of the Sd*. Our so-called EXPECT (Electrical-Conductivity-based hydrograph separaTion employing an EXPonential mixing model) method is built upon the following three key assumptions: We construct a mixing relationship consisting of an exponential decay of stream water EC with increasing young water fraction. This has been obtained based on the relationship between flow-specific young water fractions and EC. We assume that the two-component EC-based hydrograph separation technique, using the above-mentioned exponential mixing model, can be used for a time-source partitioning of stream water into young (transit times < 2–3 months) and old (transit times > 2–3 months) water. We assume that the EC value of the young water endmember (ECyw) is lower than that of the old water endmember (ECow). Selecting reliable values from measurements of ECyw and ECow to perform this unconventional EC-based hydrograph separation is challenging, but the combination of information derived from the two tracers allows for the estimation of endmembers' values. The two endmembers have been calibrated by constraining the unweighted and flow-weighted average young water fractions obtained with the EC-based hydrograph separation to be equal to the corresponding quantities derived from the seasonal isotope cycles. We test the EXPECT method in three small experimental catchments in the Swiss Alptal Valley using two different temporal resolutions of Q and EC data: sampling resolution (i.e. we only consider Q and EC measurements during dates of isotope sampling) and daily resolution. The EXPECT method has provided reliable young water fraction estimates at both temporal resolutions, from which a more accurate discharge sensitivity of the young water fraction (SdEXP) could be determined compared with the existing approach. Also, the method provided new information on ECyw and ECow, yielding calibrated values that fall outside the range of measured EC values. This suggests that stream water is always a mixture of young and old water, even under very high or very low wetness conditions. The calibrated endmembers revealed a good agreement with both endmembers obtained from an independent method and EC measurements from groundwater wells. For proper use of the EXPECT method, we have highlighted the limitations of EC as a tracer, identified certain catchment characteristics that may constrain the reliability of the current method and provided recommendations about its adaptation for future applications in catchments other than those investigated in this study.

Satellite-derived equilibrium shoreline modelling at a high-energy meso-macrotidal beach

Modelling and predicting the future of sandy shorelines is a key challenge in coastal research and is critical for sustainable coastal management. However, currently the most skillful shoreline models strongly rely on data to calibrate the free parameters, and are thus restricted to a few well monitored sites in the world. Here we address the challenges and opportunities offered by optical satellite imagery to provide useful information for equilibrium shoreline model calibration on cross-shore transport dominated sites. We focus on Truc Vert beach, southwest France, where previous work showed good equilibrium model skill to reproduce shoreline change from the time scales of hours (storms) to decades. Satellite derived waterlines are extracted over 11 years (2009–2020) and further transformed into satellite derived shorelines (SDS) with different water level corrections (e.g. tide and/or run up) and varying alongshore averaging lengths, and thus different uncertainties, in order to test model performance. Successively the timeseries duration and sampling frequency required for model calibration were also investigated. The model calibrated using the SDS data showed similar skill as the model calibrated using in-situ alongshore averaged shoreline positions, even for the uncorrected SDS dataset which Root Mean Square Error (RMSE) are approximately 30 m. Alongshore averaging was found to be the only necessary processing of the SDS data while any other site-specific corrections did not significantly improve model skill. Finally to further investigate the effect of sampling frequency and noise in the dataset we performed an analysis using a synthetic shoreline. Our results suggest that the effect of noise is negligible as long as the sampling frequency remains high (dt ≤ 30 days). Pending further validation, results show the strong potential of using uncorrected SDS dataset for shoreline model calibration at cross-shore transport dominated sandy coasts.

Structural intensity in thin plates and beams under transient and stationary forces using time-resolved, full-field optical slope measurements

Structural intensity, or structure-borne intensity or power flow, was introduced in the 1970s and implemented at that time using contact sensors like accelerometers. Point and contactless measurement methods removed added mass and sensor size constraints. Time-resolved and full-field vibration measurement techniques now open new perspectives for the estimation of structural intensity, but these prospects also come with many challenges. In this work, we study the applicability of optical deflectometry measurements to calculate the structural intensity in thin plates or beams under transient and stationary loadings. Since deflectometry directly provides slope fields, a slope formulation of structural intensity is proposed and evaluated. The effect of various parameters like frame rate (sampling frequency) and spatial resolution is studied from a numerical point of view on a simply-supported plate. Experimental results are then presented on a simply-supported plate and on a cantilever beam. Numerical and experimental results allow identifying the main challenges related to the implementation of structure intensity estimation using full-field and time-resolved data.

Low/Middle-Frequency Positive External- Damping Design Under Self-Stability Constraint for Inner Control Loop of Grid-Forming Converters

The inner voltage control loop and inductor current active damping loop of grid-forming (GFM) converters perform the output voltage control and filter resonance damping, and their stability design has been widely developed in the literature. However, the equivalent external-damping characteristics have not been fully explored. In this paper, the analysis shows that inappropriate design focusing only on self-stability would lead to negative external-damping in a wide low/middle-frequency band when LC resonant frequency is greater than one-sixth sampling frequency and less than one-third sampling frequency, which may cause system instability when interacting with loads or grids. Therefore, a low/middle-frequency positive external-damping design method under self-stability constraint is proposed for inner control loop of GFM converters. Detailed design process is presented with simple implementation. The key feature is the use of negative proportional gain of voltage controller. Through the proposed design method, the GFM converters can improve system damping capability, which is beneficial to promoting large-scale integration of distributed generation systems based on power electronics. Simulation and experimental results are finally provided to verify the feasibility and effectiveness of the design method.

Optical Spectroscopy of Type Ia Supernovae by the Carnegie Supernova Projects I and II

We present the second and final release of optical spectroscopy of Type Ia supernovae (SNe Ia) obtained during the first and second phases of the Carnegie Supernova Project (CSP-I and CSP-II). The newly released data consist of 148 spectra of 30 SNe Ia observed in the course of CSP-I and 234 spectra of 127 SNe Ia obtained during CSP-II. We also present 216 optical spectra of 46 historical SNe Ia, including 53 spectra of 30 SNe Ia observed by the Calán/Tololo Supernova Survey. We combine these observations with previously published CSP data and publicly available spectra to compile a large sample of measurements of spectroscopic parameters at maximum light, consisting of pseudo-equivalent widths and expansion velocities of selected features for 232 CSP and historical SNe Ia (including more than 1000 spectra). Finally, we review some of the strongest correlations between spectroscopic and photometric properties of SNe Ia. Specifically, we define two samples: one consisting of SNe Ia discovered by targeted searches (most of them CSP-I objects) and the other composed of SNe Ia discovered by untargeted searches, which includes most of the CSP-II objects. The analyzed correlations are similar for both samples. We find a larger incidence of SNe Ia belonging to the cool and broad-line Branch subtypes among the events discovered by targeted searches, shallow-silicon SNe Ia are present with similar frequencies in both samples, while core normal SNe Ia are more frequent in untargeted searches.

High frequency of BCP, but less CPP crystal-mediated calcification in cartilage and synovial membrane of osteoarthritis patients

ObjectiveEctopic articular calcification is a common phenomenon of osteoarthritic joints, and closely related with disease progression. Identification of the involved calcium crystal types represents an important topic in research and clinical practice. Difficulties in accurate detection and crystal type identification have led to inconsistent data on the prevalence and spatial distribution of BCP and CPP deposition. MethodCombining multiple imaging methods including conventional radiography, histology and Raman spectroscopy, this study provides a comprehensive analysis of BCP and CPP based calcification, its frequency and distribution in cartilage and synovial membrane samples of 92 OA patients undergoing knee replacement surgery. ResultsConventional radiography showed calcifications in 35% of patients. Von Kossa staining detected calcified deposits in 88% and 57% of cartilage and synovial samples, respectively. BCP crystals presented as brittle deposits on top of the cartilage surface or embedded in synovial tissue. CPP deposits appeared as larger granular needle-shaped clusters or dense circular pockets below the cartilage surface or within synovial tissue. Spectroscopic analysis detected BCP crystals in 75% of cartilage and 43% of synovial samples. CPP deposition was only detected in 18% of cartilage and 15% of synovial samples, often coinciding with BCP deposits. ConclusionBCP is the predominant crystal type in calcified cartilage and synovium while CPP deposition is rare, often coinciding with BCP. Distinct and qualitative information on BCP and CPP deposits in joint tissues give rise to the speculation that different disease entities are involved that might need different treatment strategies.

Detection of Vancomycin Resistant Genes in Intrinsically Antibiotic Resistant Bacteria from the Gut Microbiota of Indonesian Individuals.

Antibiotic resistance is a global public health concern that has been exacerbated by the overuse and misuse of antibiotics, leading to the emergence of resistant bacteria. The gut microbiota, often influenced by antibiotic usage, plays a crucial role in overall health. Therefore, this study aimed to investigate the prevalence of antibiotic resistant genes in the gut microbiota of Indonesian coastal and highland populations, as well as to identify vancomycin-resistant bacteria and their resistant genes. Stool samples were collected from 22 individuals residing in Pacet, Mojokerto, and Kenjeran, Surabaya Indonesia in 2022. The read count of antibiotic resistant genes was analyzed in the collected samples, and the bacterium concentration was counted by plating on the antibiotic-containing agar plate. Vancomycin-resistant strains were further isolated, and the presence of vancomycin-resistant genes was detected using a multiplex polymerase chain reaction (PCR). The antibiotic resistant genes for tetracycline, aminoglycosides, macrolides, beta-lactams, and vancomycin were found in high frequency in all stool samples (100%) of the gut microbiota. Meanwhile, those meant for chloramphenicol and sulfonamides were found in 86% and 16% of the samples, respectively. Notably, vancomycin-resistant genes were found in 16 intrinsically resistant Gram-negative bacterial strains. Among the detected vancomycin-resistant genes, vanG was the most prevalent (27.3%), while vanA was the least prevalent (4.5%). The presence of multiple vancomycin resistance genes in intrinsically resistant Gram-negative bacterial strains demonstrated the importance of the gut microbiota as a reservoir and hub for the horizontal transfer of antibiotic resistant genes.

Non pilot data-aided carrier and sampling frequency offsets estimation in fast time-varying channel

This paper considers the non pilot data-aided estimation of the carrier frequency offset (CFO) and sample frequency offset (SFO) of orthogonal frequency division multiplexing (OFDM) signals in fast time-varying channel. The main obstacle is the time-variant channel response, which deteriorates the estimation validity. A practical approach to mitigate this impact is to reduce the time consumption of one-shot estimation. In this way, we propose a method to reduce the time consumption to within one OFDM symbol duration. The maximum likelihood (ML) estimator is derived based on the observations of frequency domain constellations output of two FFTs on one symbol; its closed-form approximation is then derived to reduce the calculation burden. Remarkably, our method does not require any training symbol or pilot tone embedded in the signal spectrum, therefore achieves the highest spectral efficiency. Theoretical analysis and simulation results are employed to assess the performance of proposed method in comparison with existing alternatives.

Sampling Frequency Offset Estimation and Compensation for Asynchronous Optical IMDD FBMC Systems

Sampling Frequency Offset Estimation and Compensation for Asynchronous Optical IMDD FBMC Systems

Low Frequency Sampling in Model Predictive Path Integral Control

Low Frequency Sampling in Model Predictive Path Integral Control