Effective Sampling Rate Research Articles

Extrema-Triggered Conversion for Non-Stationary Signal Acquisition in Wireless Sensor Nodes

While wireless sensor node (WSNs) have proliferated with the rise of the Internet of Things (IoT), uniformly sampled analog–digital converters (ADCs) have traditionally reigned paramount in the signal processing pipeline. The large volume of data generated by uniformly sampled ADCs while capturing most real-world signals, which are highly non-stationary and sparse in information content, considerably strains the power budget of WSNs during data transmission. Given the pressing need for intelligent sampling, this work proposes an extrema pulse generator devised to trigger ADCs at significant signal extrema, thereby curbing the volume of data points collected and transmitted, and mitigating transmission power draw. After providing a comprehensive signal-theoretic rationale, we construct and experimentally validate these circuits on a system-on-chip field-programmable analog array in a 350 nm complementary metal-oxide-semiconductor (MOS) process. Operating within a power range of 4.3–12.3 µW (contingent on the input bandwidth requirements), the extrema pulse generator has proven to be capable of effectively sampling both synthetic and natural signals, achieving significant reductions in data volume and signal reconstruction error. Using a nonideality-resilient reconstruction algorithm, that we develop in this work, experimental comparisons between extrema and uniform sampling show that extrema sampling achieves an 18-fold lower normalized root mean square reconstruction error for a quadratic chirp signal, despite requiring 5-fold fewer sample points. Similar improvements in both the reconstruction error and effective sampling rate objectives are found experimentally for an electrocardiogram signal. Using both theoretical and experimental methods, this work demonstrates the potential of extrema-triggered systems for extending Pareto frontiers in modern, resource-constrained sensing scenarios.

Nonlinear frequency modulation for Fourier transform ion mobility mass spectrometry improves experimental efficiency

Through optimization of terminal frequencies and effective sampling rates, we have developed nonlinear sawtooth-shaped frequency sweeps for efficient Fourier transform ion mobility mass spectrometry (FT-IM-MS) experiments. This is in contrast to conventional FT-IM-MS experiments where ion gates are modulated according to a linear frequency sweep. Linear frequency sweeps are effective but can be hindered by the amount of useful signal obtained using a single sweep over a large frequency range imposed by ion gating inefficiencies, particularly small ion packets, and gate depletion. These negative factors are direct consequences of the inherently low gate pulse widths of high-frequency ion gating events, placing an upper bound on FT-IM-MS performance. Here, we report alternative ion modulation strategies. Sawtooth frequency sweeps may be constructed for the purpose of either extending high-SNR transients or conducting efficient signal-averaging experiments for low-SNR transients. The data obtained using this approach show high-SNR signals for a set of low-mass tetraalkylammonium salts (<1000 m/z) where resolving powers in excess of 500 are achieved. Data for low-SNR obtained for multimeric protein complexes streptavidin (53 kDa) and GroEL (800 kDa) also reveal large increases in the signal-to-noise ratio for reconstructed arrival time distributions.

SOF-RRT*: An improved path planning algorithm using spatial offset sampling

Recently, sampling-based algorithms have demonstrated advantages in complex and high-dimensional environments. The RRT* algorithm, as the best variant of RRT, provides progressive optimality. It is shown that the RRT* algorithm has a slow convergence speed and a high initial path cost that result in the low efficiency of the algorithm, due to the low probability of adequate sampling caused by the invalid expansion of the tree and redundant sampling. To overcome these limitations, the SOF-RRT* algorithm is proposed to generate better initial solutions with higher stability and faster convergence. The SOF-RRT* algorithm is an improvement on the F-RRT* algorithm. The SOF-RRT* algorithm introduces a spatial probability weight sampling strategy into sampling, which makes the sampling probability higher in the area with a large feasible area. It reduces redundant sampling and increases the effective sampling rate. In the aspect of tree expansion, the strategy of target bias and obstacle tangential bias is introduced to improve the tree expansion efficiency, which makes tree expansion away from obstacles and bias to the target point. The proposed algorithm improves the expansion efficiency of sampling and tree. Finally, the initial path generation and convergence speed are simulated and compared, which proves that the algorithm has been greatly optimized in terms of the number of iterations, path quality, and convergence speed.

A Surface-Integrated Sensor Network for Personalized Multifunctional Catheters.

Augmenting the sensing/actuating capabilities of multifunctional catheters used for minimally invasive interventions has been fostered by the reduction of transducers' sizes. However, increasing the number of transducers to benefit from the entire catheter surface is challenging due to the number of connections and/or the required integrated circuits dedicated for multiplexing the transducer signals. Modular concepts enabling personalized catheters are lacking, at all. In this work, we investigated the feasibility of a simple and daisy-chainable transducer node network for active catheters, which overcomes these limitations. Sequentially accessible nodes enabling analog interaction (including signal buffering) with transducers were designed and fabricated using miniature components suited for catheter integration. The effective sampling rate (ESR) per node for acquiring bio-signals from 10 nodes was examined for various signal-to-noise ratios. Thanks to the low circuit complexity, an ESR up to 20 kHz was achieved, which is high enough for many bio-signals.Clinical relevance- Typical daisy-chaining features, namely theoretically indefinite node extension and simple reconfiguration facilitates modularization of the catheter design. The proposed network consequently ensures application and patient-specific requirements while incorporating transducer functions over the entire catheter surface, both may improve minimally invasive interventions.

Graduates from China's Private Undergraduate Institutions: An Analysis of Employer Satisfaction

Despite the tremendous growth of higher education in China, persistent social obstacles make it difficult for college graduates to obtain employment. Employment quality is a key determinant of a nation's level of economic development and prosperity. The expansion of the employment theory dialogue among Chinese college students is aided by a discussion on how to accurately boost the employment quality of private college graduates. The goal of this survey is to do exploratory factor analysis on the employer satisfaction model established for graduates of private colleges. This survey is directed toward employers who recruit graduates from private schools and colleges with over 20,000 pupils. 500 questionnaires were mailed out, 462 were returned, and ineligible samples were deleted, leaving 451 valid samples and an effective sampling rate of 90.2%. This article uses SPSS to demonstrate empirically the model of employer satisfaction based on expectation confirmation and employability. It demonstrates that enhancing the employability of private college graduates is one of the most successful strategies for enhancing employer satisfaction. This study will boost employer satisfaction based on the perspectives of the three levels of government, schools, and students. The sample size chosen for this study is still somewhat little, and the structure's reasoning is relatively weak. Due to their hectic schedules, the vast majority of employers decline to participate in the survey, resulting in an enormous burden on the scale collectors. How to integrate research on employer satisfaction, the quality of higher education, and the career development of graduates requires additional consideration.

False alarms induced by Gaussian noise in gravitational wave detectors

Gaussian noise is an irreducible component of the background in gravitational wave (GW) detectors. Although stationary Gaussian noise is uncorrelated in frequencies, we show that there is an important correlation in time when looking at the matched filter signal to noise ratio (SNR) of a template, with a typical autocorrelation time that depends on the template and the shape of the noise power spectral density (PSD). Taking this correlation into account, we compute from first principles the false alarm rate (FAR) of a template in Gaussian noise, defined as the number of occurrences per unit time that the template's matched filter SNR goes over a threshold $\rho$. We find that the Gaussian FAR can be well approximated by the usual expression for uncorrelated noise, if we replace the sampling rate by an effective sampling rate that depends on the parameters of the template, the noise PSD and the threshold $\rho$. This results in a minimum SNR threshold that has to be demanded to a given GW trigger, if we want to keep events generated from Gaussian noise below a certain FAR. We extend the formalism to multiple detectors and to the analysis of GW events. We apply our method to the GW candidates added in the GWTC-3 catalog, and discuss the possibility that GW200308\_173609 and GW200322\_091133 could be generated by Gaussian noise fluctuations.

Assessment of the potential for quantifying multi-period suspended sediment concentration variations using satellites with different temporal resolution

Suspended sediment concentration (SSC) is a crucial indicator for coastal health and geomorphological evolution, featured by complex periodic processes on multiple timescales in response to different cyclic forcing factors. Although remote sensing has functioned as an important means for SSC estimation with sufficient spatio-temporal coverage, the low effective sampling rates and resulting unevenly spaced characteristics of the retrieved time series would hamper the extraction of the representative SSC portrayal (amplitude and phase) on multiple timescales, especially for low-resolution satellites. Here, we retrieved a 9-year hourly GOCI SSC time series (January 2012 to December 2020) at two coastal sites in China (Haimen and Haizhou Bay) as reference cases, and utilized them to obtain MODIS, Sentinel and Landsat sequences with average temporal resolutions of 0.5, 5.6 and 11.2 days as preliminary investigations into amplitude and phase extractions. Furthermore, we generated GOCI-based hypothetical satellite time series with temporal resolutions ranging from 1 to 16 days (1088 subsets) and their mutual combination (591,328 subsets) to explore general laws when extracting amplitudes and phases from satellites with different temporal resolutions by application of the Lomb-Scargle Periodogram and phase-folded diagram methods. The amplitude and phase deviations were found to increase with decreasing temporal resolution on seasonal and fortnightly timescales at Haimen and in Haizhou Bay, while by mutual combination of satellites the errors could be reduced as more data were utilized for the extraction. It is shown that larger amplitude and phase deviations occur on the seasonal timescale in comparison to the fortnightly timescale at Haimen, whereas the situation reverses in the case of Haizhou Bay. These results demonstrate that temporal resolution, data characteristics on the target timescale and absolute SSC amplitude codetermine the extraction accuracy. This further indicates that satellites with lower temporal resolutions can potentially be used on a global scale for extracting the feature changes of multi-period SSC variations, in particular as continuous improvements in data quantity and quality can be expected in the future.

Identification, extraction and interpretation of multi-period variations of coastal suspended sediment concentration based on unevenly spaced observations

Suspended sediment concentration (SSC) is an important indicator for coastal morphodynamics and health, exhibiting significant periodic variations at multiple timescales in response to various cyclic forcing factors. Identification of key periods and the extraction of corresponding amplitudes and phases can greatly aid effort to characterize the representative portrayal of SSC, which contributes to further physical interpretation. Remote sensing missions are intended to satisfy the retrieval of long-term SSC variations. However, the unevenly spaced characteristic and low effective sampling rates of the retrieved time series would hamper the extraction and interpretation of the feature changes. Here, we retrieved a 9-year SSC time series in a coastal tidal basin of Jiangsu coast, China, based on hourly GOCI satellite images from 2011 to 2019, and applied the Lomb-Scargle periodogram with the phase-folded method to extract their periodic information. On the basis of the unevenly spaced data with effective rate of 6.9%, the semidiurnal, diurnal, fortnightly, and seasonal cycles were successfully identified as the main periods, with amplitudes of 33.1, 23.4, 54.1, and 71.4 mg/L, respectively. In accordance with investigations into phase lags between SSC and forcing factors, we found that the unimodal SSC pattern at the semidiurnal timescale was induced by flood dominance, while the diurnal inequality of water level and wave intensity accounts for the SSC variation at the diurnal timescale. Tidal ranges vary consistently with the SSC in the fortnightly scale while background wave dominates the SSC variation in the seasonal timescale, the latter resulting in the seasonal difference in semidiurnal and fortnightly SSC cycles. The annual semidiurnal SSC variations experience a regime shift from 2014 to 2016, which is in consistency with the sequential reclamation. The research presents a typical application of long-term unevenly spaced observations into coastal SSC, and the proposed methodology can be extended to similar studies aiming at uncovering the mechanism of SSC variations at multiple timescales.

Probabilistic Occlusion Culling using Confidence Maps for High-Quality Rendering of Large Particle Data.

Achieving high rendering quality in the visualization of large particle data, for example from large-scale molecular dynamics simulations, requires a significant amount of sub-pixel super-sampling, due to very high numbers of particles per pixel. Although it is impossible to super-sample all particles of large-scale data at interactive rates, efficient occlusion culling can decouple the overall data size from a high effective sampling rate of visible particles. However, while the latter is essential for domain scientists to be able to see important data features, performing occlusion culling by sampling or sorting the data is usually slow or error-prone due to visibility estimates of insufficient quality. We present a novel probabilistic culling architecture for super-sampled high-quality rendering of large particle data. Occlusion is dynamically determined at the sub-pixel level, without explicit visibility sorting or data simplification. We introduce confidence maps to probabilistically estimate confidence in the visibility data gathered so far. This enables progressive, confidence-based culling, helping to avoid wrong visibility decisions. In this way, we determine particle visibility with high accuracy, although only a small part of the data set is sampled. This enables extensive super-sampling of (partially) visible particles for high rendering quality, at a fraction of the cost of sampling all particles. For real-time performance with millions of particles, we exploit novel features of recent GPU architectures to group particles into two hierarchy levels, combining fine-grained culling with high frame rates.

Altered Blood Flow in the Ophthalmic and Internal Carotid Arteries in Patients with Age-Related Macular Degeneration Measured Using Noncontrast MR Angiography at 7T.

Age-related macular degeneration is associated with reduced perfusion of the eye; however, the role of altered blood flow in the upstream ophthalmic or internal carotid arteries is unclear. We used ultra-high-field MR imaging to investigate whether the diameter of and blood flow in the ophthalmic artery and/or the ICA are altered in age-related macular degeneration and whether any blood flow changes are associated with disease progression. Twenty-four patients with age-related macular degeneration and 13 similarly-aged healthy controls participated. TOF and high-resolution dynamic 2D phase-contrast MRA (0.26 × 0.26 × 2mm3, 100-ms effective sampling rate) was acquired at 7T. Vessel diameters were calculated from cross-sectional areas in phase-contrast acquisitions. Blood flow time-series were measured across the cardiac cycle. The ophthalmic artery vessel diameter was found to be significantly smaller in patients with age-related macular degeneration than in controls. Volumetric flow through the ophthalmic artery was significantly lower in patients with late age-related macular degeneration, with a significant trend of decreasing volumetric ophthalmic artery flow rates with increasing disease severity. The resistance index was significantly greater in patients with age-related macular degeneration than in controls in the ophthalmic artery. Flow velocity through the ophthalmic artery and ICA was significantly higher in patients with age-related macular degeneration. Ophthalmic artery blood flow as a percentage of ipsilateral ICA blood flow was nearly double in controls than in patients with age-related macular degeneration. These findings support the hypothesis that vascular changes upstream to the eye are associated with the severity of age-related macular degeneration. Additional investigation into the potential causality of this relationship and whether treatments that improve ocular circulation slow disease progression is warranted.

Feasibility and Safety of Transjugular Liver Biopsy for Japanese Patients with Chronic Liver Diseases.

Background and study aim: Transjugular liver biopsy (TJLB) can be used in patients who are ineligible for percutaneous liver biopsy (PLB) with acute and chronic hepatic disease. This study aimed to evaluate the usefulness and safety of TJLB in patients who were not indicated for PLB. Methods: Between July 2014 and February 2019, a total of 134 patients underwent liver biopsies at our institution. Among these, PLB was performed in 110 patients and TJLB in 24 patients. A retrospective comparison of clinical results in these patients was then performed. The primary endpoints of this study were the utility and safety of TJLB in patients who were not indicated for PLB. Results: The procedural success rate was 100% in both groups. The clinical response rate and the effective tissue sampling rate were 100% in the TJLB group and 97% in the PLB group (p = 0.55). There was no difference in the number of portal fields examined retrospectively between the two groups. No serious adverse events were observed in either group. Conclusions: It is suggested that TJLB is useful because it can be safely performed in patients with poor general condition who are not indicated for PLB.

Analysis of Time and Frequency Response for Single/Multi-Tone Stimulus Harmonic Phase-Reference Based on Prime Number Algorithm

We present a spectrally-dense phase-reference and its calibration for nonlinear vector network analyzers (NVNAs) using a step recovery diode (SRD) comb-generator with a multi-tone stimulus. Frequency selection for multi-tone stimulus based on prime number algorithms was used with the Digital Real-Time Oscilloscope (DRTO) to avoid the sub-Nyquist spurs components and to increase the effective sampling rate so that the waveform can be observed in greater detail. The measured results were calibrated to minimize drift and jitter and achieved excellent agreement between the prime number and the exact frequency strategies except at the sub-Nyquist frequencies. The analysis indicates that the prime number selected frequencies show significantly improved performance by avoiding the DRTO distortion components. We have verified the validity of the method described in this paper by experimental measurement results.

A TD-ADC for IR-UWB Radars With Equivalent Sampling Technology and 8-GS/s Effective Sampling Rate

A high-speed time domain analog-to-digital converter (ADC) customized for impulse radio ultra-wideband (IR-UWB) radars is proposed in this brief. It adopts a power efficient architecture combining time domain implementation and equivalent sampling technology. The equivalent sampling rate is high up to 8 GS/s. Compared to time interleaved (TI) ADC, the proposed time domain ADC (TD-ADC) not only has less power consumption and silicon area, but also is free from complicated digital calibration. The prototype ADC was fabricated in a 65nm CMOS technology. The achieve area is 320 μm × 300 μm. With the Nyquist middle frequency input of 1.376 GHz, the measured spurious free dynamic range (SFDR) and signal to noise and distortion ratio (SNDR) are over 57.6 dB and 43.0 dB, while the real time power consumption is only 8.2 mW. The figure of merit (FOM) is about 147 fJ/step.

Noise-Coupled Time-Interleaved Delta–Sigma Modulator with Reduced Hardware Complexity

Developing an analog-to-digital converter (ADC) based on the time-interleaved delta–sigma modulator (TIDSM) is an appropriate technique to attain high-speed ADCs. TIDSMs can be successfully accomplished with the aid of developing the block digital filtering (BDF) method. In this approach, [Formula: see text] mutually cross-connection delta–sigma modulators are used, whereby each one of them operates at a sampling rate of [Formula: see text], leading to an effective sampling rate of [Formula: see text]. In this study, a novel structure is proposed based on the Noise Coupled time-interleaved delta–sigma modulator (NC-TIDSM) with reduced hardware complexity. This structure not only increases the overall noise transfer function (NTF) order, but also reduces the hardware element counts. The simulation results demonstrate that the SNDRs of the first-order two-channel and four-channel NC-TIDSM with reduced hardware are 13 and 15 dB better than those of their BDF technique counterparts; also, the SNDR of the second-order two-channel NC-TIDSM with reduced hardware is 8 dB better than that of their BDF technique counterpart; also, the hardware element quantities are reduced dramatically. Moreover, some practical challenges such as the finite op-amp’s gain and mismatching effects that directly affect the circuit implementation of the proposed structure have been described. Furthermore, the hardware complexity of the proposed structures is reduced considerably in comparison to that of the BDF technique with the NC-TIDSM structure.

Post-hoc physiological waveform extraction from motion estimation in simultaneous multislice (SMS) functional MRI using separate stack processing.

Motion estimation is an essential step in functional MRI (fMRI) preprocessing. Usually, fMRI processing software packages (eg, FSL and AFNI) automatically estimate motion parameters in order to counteract the effects of motion. However, the time courses of the motion estimation for fMRI data also contain information about physiological processes. Here, we show that respiration and cardiac signals can be extracted from motion estimation at significantly higher bandwidth than is possible with current methods. To detect motion at high effective temporal resolution (HighRes), the motion parameters of stacks of simultaneously acquired slices were estimated separately, then combined. This method was validated by extracting physiological motion signals from resting state fMRI (rsfMRI) data (Enhanced Nathan Kline Institute-Rockland Sample) and comparing them to respiration belt and pulse oximeter signals. HighRes motion time-courses with an effective sampling rate of 15.5 and 11.4 Hz were extracted from repetition time (TR) = 0.645 and 1.4 s data, respectively. Respiration waveforms were extracted with significantly higher accuracy than the original motion parameters. Even cardiac waveforms could be extracted, despite the fact that the sampling time or TR values were too long to sample cardiac frequencies. HighRes motion traces provide insight into the subjects' motion at higher frequencies than can be estimated using standard techniques. In its simplest form, this technique can recover accurate respiration signals and may reveal additional complexity in brain motion.

Field- and model-based calibration of polyurethane foam passive air samplers in different climate regions highlights differences in sampler uptake performance

Abstract Polyurethane foam (PUF) passive air samplers (PAS) are widely used for measurements of persistent organic pollutants (POPs) and other semi-volatile organic compounds (SVOCs) in large-scale monitoring networks as well as in case studies around the globe. Calibration of PUF-PAS is performed by field-based calibration studies or passive sampler uptake models, but both these are typically performed and/or validated in temperate zones, while the sampling rates are more widely applied, including in tropical and polar zones. Here, we present field-based calibrations results for MONET PUF-PAS from a subtropical and tropical site (Nairobi, Kenya and Accra, Ghana) based on side-by-side deployment of PUF-PAS and active air samplers (AAS), as well as model PAS uptake from available passive sampler uptake models. By comparing these results with a similar calibration from a temperate site (Brno, Czech Republic), we show that the higher ambient temperatures result in higher effective sampling rates for intermediate molecular weight SVOCs (logKOA of 7–11) as a result of lower particle-bound fraction, and in lower sample volumes for lighter SVOCs (logKOA

A 12-Bit 2.4 GS/s Four-Channel Pipelined ADC with a Novel On-Chip Timing Mismatch Calibration

This paper presents a 12-bit 2.4 GS/s analog-to-digital converter (ADC) employing four time-interleaved (TI) pipelined channels with a novel on-chip timing mismatch calibration in 40 nm CMOS process. TI architecture can increase the effective sampling rate of ADC but the dynamic performance of TI-ADC system is seriously degraded by offset, gain, and timing mismatches among the channels. Timing mismatch is the most challenging barrier among these mismatches due to the difficulty and complexity of its detection and correction. An automatic wideband timing mismatch detection algorithm is proposed for achieving a wide frequency range of timing mismatch detection without complex calculations. By adopting the proposed mismatch-free variable delay line (VDL), the full-scale traversal timing mismatch correction accomplishes an accurate result without missing codes. Measurement results show that the spurious free dynamic range (SFDR) of the prototype ADC is improved from 55.2 dB to 72.8 dB after calibration at 2.4 GS/s with a 141 MHz input signal. It can achieve an SFDR above 60 dB across the entire first Nyquist band based on the timing mismatch calibration and retiming technology. The prototype ADC chip occupies an area of 3 mm × 3 mm and it consumes 420 mW from a 1.8 V supply.

Distributed fiber vibration sensing with single-shot measurement and moving time-gating method

The single-shot measurement method is proposed to improve measurement accuracy in distributed dynamic strain sensing by using time-resolved optical frequency domain reflectometry (OFDR). Time-domain information can be obtained without reference scan by single-shot measurement with standard polarization-maintaining fiber as the sensing fiber via auto-correlation calculation to measure Rayleigh backscatter spectrum in different wavelength ranges. Experimental results verify that the information of vibrated and non-vibrated state can be determined by monitoring the side peak shifts in the local Rayleigh backscatter spectrum along the sensing fiber. Furthermore, moving time-gating method is illustrated and used to broaden the detection bandwidth. The effective sampling rate can be increased so that the measurable frequency range can be further increased. In the further proof of concept experiment, for a conventional OFDR system, the measurable frequency of vibration event can be achieved up to 30Hz along the polarization-maintaining fiber with a tunable laser sweeping rate of 40nm/s by single-shot measurement and moving time-gating method. The measurable frequency range could be further broadened by using tunable laser sources with higher sweeping speeds. The proposed schemes provide new approach to enhance the measurement accuracy via single-shot measurement in the OFDR system which is of great significance in distributed dynamic signal detection system.

Systematic low bias of passive samplers in characterizing nitrogen isotopic composition of atmospheric ammonia

Identifying the sources of increased ammonia (NH3) in the atmosphere has important implications for air quality, ecosystems, and climate. While analysis of the nitrogen isotopic composition (δ15N) can aid in the apportionment of NH3 emission sources, the widely-used passive collection methods have not been verified for their ability to accurately characterize δ15N-NH3. In this study, three types of passive samplers (ALPHA, Analyst, and Radiello) were employed and collocated with a denuder based active sampler (DELTA, serves as a reference method) to compare and contrast their ability in collecting atmospheric NH3 for subsequent concentration and δ15N-NH3 analysis in urban Beijing during the summer of 2018. The results showed that NH3 concentrations determined using passive collection samplers that included ALPHA (n = 11), Analyst (n = 12), and Radiello (n = 7) samplers were 13.4%, 14.4%, and 27.5% lower than that of the active sampler (n = 12), respectively. The low NH3 concentration bias in the passive collection samplers was suggested to be the result of inaccurate effective sampling rates due to incorrect mass transfer correction factors for the environmental conditions of this study. The δ15N-NH3 values did not show significant differences between passive samplers, with weekly means of −31.0 ± 1.0‰ (n = 4), −28.4 ± 5.5‰ (n = 4), and −29.1 ± 0.9‰ (n = 4) for the ALPHA, Analyst, and Radiello, respectively. Notably, the overall mean δ15N-NH3 values collected by these passive samplers (−29.5 ± 3.2‰, n = 12) was significantly lower than that of the active sampler (−14.1 ± 1.6‰, n = 4), with a difference of 15.4 ± 3.5‰. The large underestimation of δ15N-NH3 values by passive samplers can be explained by the diffusive isotope fractionation of NH3 isotopologues, which is driven by relative mass differences of 14NH3 and 15NH3. Overall, these findings highlight a potential low bias in NH3 concentrations and a substantial uncertainty in previous source interpretation using δ15N-NH3 as previous studies have almost exclusively characterized δ15N-NH3 using passive samplers. We suggest that the denuder-based active sampler should be used in the future for characterizing δ15N-NH3 whether at the source or in an atmospheric environment with mixed sources. This work also has important implications for characterizing δ15N of other gaseous nitrogen compounds.

An Empirical Study of Brand Fan Page Engagement Behaviors

Nowadays, numerous companies present themselves on social networking sites (SNSs) by establishing brand communities to maintain continuous interaction with existing and potential customers to influence their brand choices, promote the products and services, and cultivate brand loyalty. However, the research into online brand communities is mainly centered on that utilizing the platforms of websites instead of using social media platforms. Thus, it calls for more studies to investigate consumer brand fan page engagement behavior to increase their fan base and further induce a fan’s purchase behavior. By adopting the perspectives of co-production and social identity theory, this study endeavors to investigate the impact of customer perceived value derived from engaging in brand fan pages on their identification with and stickiness to an online brand community in the SNS-based context. The target population of this study is consumers who have ever participated in an online brand community. Data was collected through a web-based survey. After deleting 36 incomplete responses, 524 usable responses remained for further analysis, with an effective sample rate of 93.57%. The results revealed that utilitarian value, hedonic value, and monetary value separately exerted a significantly positive effect on community identification. Utilitarian value and hedonic value also had significantly positive effects on community stickiness. Moreover, community identification was positively related to community stickiness. Community identification was found to have significantly positive influences on both word-of-mouth and repurchase intention. Furthermore, community stickiness exerted a significantly positive effect on word-of-mouth and repurchase intention. This study confirms the importance of perceived value on enhancing consumers’ identification with and their stickiness to online brand communities. Therefore, businesses should provide consumers with the value they desired to cultivate customer loyalty to their brand fan pages.