Deep UV-LED induced nitrate-to-nitrite conversion for total dissolved nitrogen determination in water samples through persulfate digestion and capillary electrophoresis.

BACKGROUND: Capillary electrophoresis (CE) with capacitively coupled contactless conductivity detection (C4D) is widely used for water quality monitoring. However, there is currently no reported CE method for detecting total dissolved nitrogen (TDN), a crucial parameter for assessing water eutrophication. One challenge is the high sulfate concentration (100 mM) introduced during persulfate digestion, leading to overlap of nitrate (from TDN) and poor electrical stacking of nitrate in CE-C4D analysis. RESULTS: We introduced an in-capillary UV-LED induced photoreaction to convert nitrate to nitrite, which can be baseline-separated from sulfate via the CE method, enabling accurate quantification of nitrate concentration derived from nitrite. A 2 nL post-persulfate digested sample solution within a fused silica capillary was exposed to UV-LED irradiation at the capillary tip. Subsequently, photoreduction-produced nitrite was electrophoretically separated from sulfate in an acidic buffer (pH = 3.7) within the same capillary, followed by contactless conductivity detection. The nitrate-to-nitrite conversion efficiency was influenced by irradiation wavelength, power, and duration, reaching a maximum efficiency of 77.4% when employing two 230 nm LEDs for 5 min. For more general applications, two 255 nm LEDs were used, providing a conversion efficiency of (66.4 ± 3.3)% (n = 11) for 5 min of irradiation. The proposed CE-C4D method exhibits a detection limit of 13 µM (0.18 mg N/L) and has been successfully employed for TDN determination in lake water samples. SIGNIFICANCE: This innovative approach not only enhances the attractiveness of the CE-C4D method for the determination of water quality indicators but also highlights the potential for integrating deep-UV LEDs into environmental analysis.

The Time-of-Arrival Offset Estimation in Neural Network Atomic Denoising in Wireless Location.

With the increasing demand for wireless location services, it is of great interest to reduce the deployment cost of positioning systems. For this reason, indoor positioning based on WiFi has attracted great attention. Compared with the received signal strength indicator (RSSI), channel state information (CSI) captures the radio propagation environment more accurately. However, it is necessary to take signal bandwidth, interferences, noises, and other factors into account for accurate CSI-based positioning. In this paper, we propose a novel dictionary filtering method that uses the direct weight determination method of a neural network to denoise the dictionary and uses compressive sensing (CS) to extract the channel impulse response (CIR). A high-precision time-of-arrival (TOA) is then estimated by peak search. A median value filtering algorithm is used to locate target devices based on the time-difference-of-arrival (TDOA) technique. We demonstrate the superior performance of the proposed scheme experimentally, using data collected with a WiFi positioning testbed. Compared with the fingerprint location method, the proposed location method does not require a site survey in advance and therefore enables a fast system deployment.

An Indoor Navigation Algorithm Using Multi-Dimensional Euclidean Distance and an Adaptive Particle Filter.

The inertial navigation system has high short-term positioning accuracy but features cumulative error. Although no cumulative error occurs in WiFi fingerprint localization, mismatching is common. A popular technique thus involves integrating an inertial navigation system with WiFi fingerprint matching. The particle filter uses dead reckoning as the state transfer equation and the difference between inertial navigation and WiFi fingerprint matching as the observation equation. Floor map information is introduced to detect whether particles cross the wall; if so, the weight is set to zero. For particles that do not cross the wall, considering the distance between current and historical particles, an adaptive particle filter is proposed. The adaptive factor increases the weight of highly trusted particles and reduces the weight of less trusted particles. This paper also proposes a multidimensional Euclidean distance algorithm to reduce WiFi fingerprint mismatching. Experimental results indicate that the proposed algorithm achieves high positioning accuracy.

A Novel Energy-Efficient Approach for Human Activity Recognition.

In this paper, we propose a novel energy-efficient approach for mobile activity recognition system (ARS) to detect human activities. The proposed energy-efficient ARS, using low sampling rates, can achieve high recognition accuracy and low energy consumption. A novel classifier that integrates hierarchical support vector machine and context-based classification (HSVMCC) is presented to achieve a high accuracy of activity recognition when the sampling rate is less than the activity frequency, i.e., the Nyquist sampling theorem is not satisfied. We tested the proposed energy-efficient approach with the data collected from 20 volunteers (14 males and six females) and the average recognition accuracy of around 96.0% was achieved. Results show that using a low sampling rate of 1Hz can save 17.3% and 59.6% of energy compared with the sampling rates of 5 Hz and 50 Hz. The proposed low sampling rate approach can greatly reduce the power consumption while maintaining high activity recognition accuracy. The composition of power consumption in online ARS is also investigated in this paper.

Role of electronic correlation in high-low temperature phase transition of hexagonal nickel sulfide: a comparative density functional theory study with and without correction for on-site Coulomb interaction.

The structural, electronic, magnetic, and elastic properties of hexagonal nickel sulfide (NiS) have been investigated comparatively by Density Functional theory (DFT) and DFT plus correction for on-site Coulomb interaction (DFT+U), in which two different exchange correlation functionals local density approximations (LDA) and general gradient approximations (GGA) in the form of Perdew-Burke-Ernzerhof (PBE) are used. Our results indicate LDA and PBE methods predict hexagonal NiS to be a paramagnetic metal whereas LDA(PBE)+U calculations with reasonable on-site Coulomb interaction energy give the antiferromagnetic insulating state of low temperature hexagonal NiS successfully. Meanwhile, compared with LDA(PBE) results, LDA(PBE)+U methods give larger lattice parameters, crystal volume, and shear constant c44, consistent with the experimental picture during high-low temperature phase transition of hexagonal NiS, in which an increase of the shear constant c44 and lattice parameters were found in the low-temperature antiferromagnetic phase. The present DFT and DFT+U calculations provide a reasonable description for the properties of high temperature and low temperature hexagonal NiS respectively, which indicates that electronic correlation is responsible for this high-low temperature phase transition.

Kinetic and equilibrium studies for the adsorption process of cadmium(II) and copper(II) onto Pseudomonas aeruginosa using square wave anodic stripping voltammetry method.

A novel method for the simultaneous determination of cadmium(II) and copper(II) during the adsorption process onto Pseudomonas aeruginosa was developed. The concentration of the free metal ions was successfully detected by square wave anodic stripping voltammetry (SWASV) on the mercaptoethane sulfonate (MES) modified gold electrode, while the P. aeruginosa was efficiently avoided approaching to the electrode surface by the MES monolayer. And the anodic stripping peaks of Cd(2+) and Cu(2+) appear at -0.13 and 0.34V respectively, at the concentration range of 5-50 microM, the peak currents of SWASV present linear relationships with the concentrations of cadmium and copper respectively. As the determination of Cd(2+) and Cu(2+) was in real time and without pretreatment, the kinetic characteristics of the adsorption process were studied and all the corresponding regression parameters were obtained by fitting the electrochemical experimental data to the pseudo-second-order kinetic model. Moreover, Langmuir and Freundlich models well described the biosorption isotherms. And there were some differences in the amount of metal ion adsorbed at equilibrium (q(e)) and other kinetics parameters when the two ions coexisted were compared with the unaccompanied condition, which were also discussed in this paper. The proposed electrode system provides excellent platform for the simultaneous determination of trace metals in complex biosorption process.

Stability of the polar NiO(111) surface.

Based on density functional theory and thermodynamic model, we compile a phase diagram for the polar NiO(111) surface as a function of temperature and oxygen pressure. The electronic correlation between Ni-3d electrons has also been included in the form of GGA+U method. Consistent with recent experiments, present GGA+U calculation indicates that over a broad range of oxygen partial pressure, the most stable phases are the oxygen and Ni terminated octopolar structures, which are almost degenerate in energy. We also show that the stabilization of the NiO(111) surface goes together with remarkable changes in the geometrical and electronic structure.

A monitoring technique of piezoelectric impedance analysis used in tea polyphenols (TP) antimutagenic characteristics.

A new method was proposed for studying antimutagenic characteristics of tea polyphenols (TP) using piezoelectric impedance analysis during the Salmonella typhimurium strain TA100 growth process in the presence of mutagen 4-methylnitrosamino-1-(3-pyridyl)-1-butanone (abbreviated NNK). Compared with the general method of antimutagenic investigation, the proposed method provided real-time, multidimensional response information about the antimutagenic characteristics during the bacterial growth process. The results showed that TP was allowed to be antimutagenic at the lowest concentration of 0.25 microg/ml, and the inhibitory effect of TP presented a linear relationship with its dosage in the range of 0.25-2.5 microg/ml. And the relationship between the bacterial growth kinetic parameters and the TP dosage was also obtained. The present method provided a new approach for studying microbial antimutagenic characteristics.

Quantum scattering calculation of the O(1D)+HBr reaction.

Three-dimensional time-dependent quantum wave packet calculation for the O((1)D)+HBr reaction has been carried out using an accurate ab initio global potential energy surface [K. A. Peterson, J. Chem. Phys. 113, 4598 (2000)]. The calculations show that the initial state-selected reaction probabilities are dominated by resonance structures, and the lifetime of the resonance is generally in the subpicosecond time scale. The energy dependence of the reaction cross section is computed, which manifests still resonance structures, and is a decreasing function of the translational energy. The thermal rate constants are also computed, which are nearly independent on the temperature. The calculation results are discussed and compared to similar reaction with deep well.