A Forward-Backward Iterative Procedure for Improving the Resolution of Resonant Microwave Sensors

This paper sets out a method for improving the resolution of resonant microwave sensors. Usually, the frequency response of these devices is associated with a low quality factor, and consequently with a low resolution in terms of tracking capacity of the resonance frequency shift. Furthermore, since only a finite number of samples can be acquired during the measurement process, the “true” resonance frequency may not be included in the set of acquired data. In order to have an accurate estimate of the resonance frequency, high performance systems with very fine frequency sampling are thus required. To limit these drawbacks, an iterative algorithm is presented which aims to refine the response of resonant microwave sensors by means of a suitable post-processing. The algorithm evaluation is first carried out on synthetic data, and then applied on experimental data referring to a practical scenario, which is inherent to return loss measurements performed by a microwave patch antenna immersed in a water-glucose solution with different concentrations.

Low-frequency sampling rates are effective to record bottlenose dolphins

Acoustic monitoring in cetacean studies is an effective but expensive approach. This is partly because of the high sampling rate required by acoustic devices when recording high-frequency echolocation clicks. However, the proportion of echolocation clicks recorded at different frequencies is unknown for many species, including bottlenose dolphins. Here, we investigated the echolocation clicks of two subspecies of bottlenose dolphins in the western South Atlantic Ocean. The possibility of recording echolocation clicks at 24 and 48 kHz was assessed by two approaches. First, we considered the clicks in the frequency range up to 96 kHz. We found a loss of 0.95–13.90% of echolocation clicks in the frequency range below 24 kHz, and 0.01–0.42% below 48 kHz, to each subspecies. Then, we evaluated these recordings downsampled at 48 and 96 kHz and confirmed that echolocation clicks are recorded at these lower frequencies, with some loss. Therefore, despite reaching high frequencies, the clicks can also be recorded at lower frequencies because echolocation clicks from bottlenose dolphins are broadband. We concluded that ecological studies based on the presence–absence data are still effective for bottlenose dolphins when acoustic devices with a limited sampling rate are used.

How does investor sentiment impact stock volatility? New evidence from Shanghai A-shares market

PurposeThe focus of the current research is to examine whether mixed-frequency investor sentiment affects stock volatility in the China A-shares stock market.Design/methodology/approachMixed-frequency sampling models are employed to find the relationship between stock market volatility and mixed-frequency investor sentiment. Principal analysis and MIDAS-GARCH model are used to calibrate the impact of investor sentiment on the large-horizon components of volatility of Shanghai composite stocks.FindingsThe results show that the volatility in Chinese stock market is positively influenced by B–W investor sentiment index, when the sentiment index encompasses weighted mixed frequencies with different horizons. In particular, the impact of mixed-frequency investor sentiment is most significantly on the large-horizon components of volatility. Moreover, it is demonstrated that mixed-frequency sampling model has better explanatory powers than exogenous regression models when accounting for the relationship between investor sentiment and stock volatility.Practical implicationsGiven the various unique features of Chinese stock market and its importance as the major representative of world emerging markets, the findings of the current paper are of particularly scholarly and practical significance by shedding lights to the applicableness GARCH-MIDAS in the focused frontiers.Originality/valueA more accurate and insightful understanding of volatility has always been one of the core scholarly pursuits since the influential structural time series modeling of Engle (1982) and the seminal work of Engle and Rangel (2008) attempting to accommodate macroeconomic factors into volatility models. However, the studies in this regard are so far relatively scarce with mixed conclusions. The current study fills such gaps with improved MIDAS-GARCH approach and new evidence from Shanghai A-share market.

Importance of light status on phytoplankton biomass in the turbid Bisan Strait, Japan: results from a high-frequency sampling study

The dynamics of phytoplankton biomass in the vertically mixed south-eastern part of the Bisan Strait, in the Seto Inland Sea of Japan, may be considered to be strongly dependent not only on nutrients but also on light status. This was investigated by examining variations in chlorophyll-a (Chl-a), nutrients, and Secchi-disc depth through high-frequency sampling (a mean of once every 1.7 days) at the same station from April to October 2019. Precipitation during the Japanese rainy season (East Asian monsoon rains) was associated with a decrease in salinity from 32 to 31 in late July. The highest concentration of dissolved inorganic nitrogen (DIN), the most deficient nutrient, also was recorded in late July in association with seasonal precipitation. However, the measured Chl-a peak (max. 4 μg l−1) in early August was not as high as expected, possibly due to low water clarity. A relatively small but substantial peak of DIN (max. 4 μM) was recorded in mid-August, which coincided with the passing of a typhoon. The small peak of DIN coupled with higher water clarity thereafter was followed by a phytoplankton bloom from mid-August to early September, at which the highest Chl-a (7 μg l−1) occurred. It is suggested that increased light penetration enhanced the efficiency of nutrient assimilation and thereby triggered the late-summer phytoplankton bloom. In contrast to the adjacent stratified areas, light rather than nutrient status appears to be the key determinant for the onset of phytoplankton blooms in the Bisan Strait.

Responses of abundant and rare bacterioplankton to temporal change in a subtropical urban reservoir

ABSTRACT Investigation of bacterial community dynamics across different time scales is important for understanding how environmental conditions drive community change over time. Bacterioplankton from the surface waters of a subtropical urban reservoir in southeast China were analyzed through high-frequency sampling over 13 months to compare patterns and ecological processes between short (0‒8 weeks), medium (9‒24 weeks) and long (25‒53 weeks) time intervals. We classified the bacterial community into different subcommunities: abundant taxa (AT); conditionally rare taxa (CRT); rare taxa (RT). CRT contributed > 65% of the alpha-diversity, and temporal change of beta-diversities was more pronounced for AT and CRT than RT. The bacterial community exhibited a directional change in the short- and medium-time intervals and a convergent dynamic during the long-time interval due to a seasonal cycle. Cyanobacteria exhibited a strong succession pattern than other phyla. CRT accounted for > 76% of the network nodes in three stations. The bacteria–environment relationship and deterministic processes were stronger for large sample size at station G (n = 116) than small sample size at stations C (n = 12) and L (n = 22). These findings suggest that a high-frequency sampling approach can provide a better understanding on the time scales at which bacterioplankton can change fast between being abundant or rare, thus providing the facts about environmental factors driving microbial community dynamics. Patterns and processes in alpha- and beta-diversities and community assembly of bacterioplankton differ among different time intervals (short-, medium- and long-time intervals) and different subcommunities (abundant, conditionally rare and rare taxa) in a subtropical urban reservoir, demonstrating the importance of temporal scale and high-frequency sampling in microbial community ecology.

Exploring applications of Frozen Newton Method in the design of digital filter

Digital filters are popularly used in digital signal processing. The design of these filters can be done using different methods of which the rectangular window method and Frequency sampling methods are commonly used. Filter design using wavelet coefficients also shows better response. In this paper, we explore the use of the Frozen Newton method in improving the response of the filter designed using these methods. This iterative computing is applied considering the Taylor series expansion of the function up to the first order term called the Jacobian

Low-Frequency Signal Sampling Method Implemented in a PLC Controller Dedicated to Applications in the Monitoring of Selected Electrical Devices

High requirements for power systems, and hence for electrical devices used in industrial processes, make it necessary to ensure adequate power quality. The main parameters of the power system include the rms-values of the current, voltage, and active and reactive power consumed by the loads. In previous articles, the authors investigated the use of low-frequency sampling to measure these parameters of the power system, showing that the method can be easily implemented in simple microcontrollers and PLCs. This article discusses the methods of measuring electrical quantities by devices with low computational efficiency and low sampling frequency up to 1 kHz. It is not obvious that the signal of 50–500 Hz can be processed using the sampling frequency of fs = 47.619 Hz because it defies the Nyquist–Shannon sampling theorem. This theorem states that a reconstruction of a sampled signal is only guaranteed possible for a bandlimit fmax < fs, where fmax is the maximum frequency of a sampled signal. Therefore, theoretically, neither 50 nor 500 Hz can be identified by such a low-frequency sampling. Although, it turns out that if we have a longer period of a stable multi-harmonic signal, which is band-limited (from the bottom and top), it allows us to map this band to the lower frequencies, thus it is possible to use the lower sampling ratio and still get enough precise information of its harmonics and rms value. The use of aliasing for measurement purposes is not often used because it is considered a harmful phenomenon. In our work, it has been used for measurement purposes with good results. The main advantage of this new method is that it achieves a balance between PLC processing power (which is moderate or low) and accuracy in calculating the most important electrical signal indicators such as power, RMS value and sinusoidal-signal distortion factor (e.g., THD). It can be achieved despite an aliasing effect that causes different frequencies to become indistinguishable. The result of the research is a proposal of error reduction in the low-frequency measurement method implemented on compact PLCs. Laboratory tests carried out on a Mitsubishi FX5 compact PLC controller confirmed the correctness of the proposed method of reducing the measurement error.