Effect of low-frequency noise exposure on cognitive function: a systematic review and meta-analysis.

BACKGROUND: Low-frequency noise may cause changes in cognitive function. However, there is no established consensus on the effect of low-frequency noise on cognitive function. Therefore, this systematic review and meta-analysis aimed to explore the relationship between low-frequency noise exposure and cognitive function. METHODS: We conducted a systematic review and identified original studies written in English on low-frequency noise and cognition published before December 2022 using the PsycINFO, PubMed, Medline, and Web of Science databases. The risk of bias was evaluated according to established guidelines. A random-effects meta-analysis was performed where appropriate. To explore the association between low-frequency noise exposure and cognitive function, we reviewed eight relevant studies. These studies covered cognitive functions grouped into four domains: attention, executive function, memory, and higher-order cognitive functions. The data extraction process was followed by a random-effects meta-analysis for each domain, which allowed us to quantify the overall effect. RESULTS: Our analysis of the selected studies suggested that interventions involving low-frequency noise only had a negative impact on higher-order cognitive functions (Z = 2.42, p = 0.02), with a standardized mean difference of -0.37 (95% confidence interval: -0.67, -0.07). A moderate level of heterogeneity was observed among studies (p = 0.24, I2 = 29%, Tau2 = 0.03). CONCLUSIONS: Our study findings suggest that low-frequency noise can negatively impact higher-order cognitive functions, such as logical reasoning, mathematical calculation, and data processing. Therefore, it becomes important to consider the potential negative consequences of low-frequency noise in everyday situations, and proactive measures should be taken to address this issue and mitigate the associated potential adverse outcomes.

Reversible Photomodulation of Two-Dimensional Electron Gas in LaAlO3/SrTiO3 Heterostructures.

Long-lived photoinduced conductance changes in LaAlO3/SrTiO3 (LAO/STO) heterostructures enable their use in optoelectronic memory applications. However, it remains challenging to quench the persistent photoconductivity (PPC) instantly and reproducibly, which limits the reversible optoelectronic switching. Herein, we demonstrate a reversible photomodulation of two-dimensional electron gas (2DEG) in LAO/STO heterostructures with high reproducibility. By irradiating UV pulses, the 2DEG at the LAO/STO interface is gradually transformed to the PPC state. Notably, the PPC can be completely removed by water treatment when two key requirements are met: (1) the moderate oxygen deficiency in STO and (2) the minimal band edge fluctuation at the interface. Through our X-ray photoelectron spectroscopy and electrical noise analysis, we reveal that the reproducible change in the conductivity of 2DEG is directly attributed to the surface-driven electron relaxation in the STO. Our results provide a stepping-stone toward developing optically tunable memristive devices based on oxide 2DEG systems.

Analysis of single vehicle noise emissions in the frequency domain for two different motorizations.

Environmental noise, primarily attributed to the road transportation system, poses a significant challenge in Europe, impacting the quality of life for millions. Therefore, a thorough characterization of noise emissions from road transportation sources is needed to stem this problem. This investigation aims to fill a gap in the literature regarding single-vehicle noise emissions in the frequency domain. The emphasis is on motorization (i.e., fuel type), with particular attention to Low-Frequency components, due to their potential impact on human health and ecosystems. Two probe vehicles, a diesel and a Liquefied Petroleum Gas-powered, were employed to collect data for noise emission curves in the frequency domain (from 63 to 8000 Hz) and compare them with those furnished in the CNOSSOS-EU, Harmonoise, and REMEL models. Moreover, data in terms of exhaust noise emissions (at the tailpipe) were also gathered and analyzed in the frequency domain. The analysis highlighted motorization's influence on noise emissions, revealing differences in frequency component contributions to the overall sound power level at different speeds. Low-frequency components were found to be predominant for both vehicles, especially at lower speeds, where the engine noise contribution dominates. This finds its endorsement in the frequency analysis on the noise emission curves provided in the examined models. The evaluation of the exhaust noise emissions revealed resonance phenomena at 63 Hz and showcased the dominance of low-frequency components in the exhaust spectrum (despite the penalization introduced by the A-weighting procedure), opening avenues for understanding and lowering noise emissions during vehicle idling and low-speed operations.

Study on the Voltage Reference Noise at Sub-Millihertz Frequencies for Developing an Ultra-Stable Temperature Measurement Subsystem.

A temperature measurement subsystem (TMS) is a critical piece of infrastructure of the space gravitational wave detection platform, necessary for monitoring minuscule temperature changes at the level of 1µK/Hz1/2 within the electrode house, in the frequency range of 0.1mHz to 1Hz. The voltage reference (VR), a key component of the TMS, must possess low noise characteristics in the detection band to minimize the impact on temperature measurements. However, the noise characteristics of the voltage reference in the sub-millihertz range have not been documented yet and require further study. This paper reports a dual-channel measurement method for measuring the low-frequency noise of VR chips down to 0.1mHz. The measurement method makes use of a dual-channel chopper amplifier and an assembly thermal insulation box to achieve a normalized resolution of 3×10-7/Hz1/2@0.1mHz in the VR noise measurement. The seven best-performance VR chips documented at a common frequency range are tested. The results show that their noise at sub-millihertz frequencies can significantly differ from that around 1Hz.

A Passive Noise Attenuation Earplug Designed to Minimise Unwanted Air Turbine Driven High-Speed Dental Drill Noise.

INTRODUCTION: Air turbine dental drill noise contains high-frequency components that are of concern for patients and dental staff. Meanwhile, verbal communication between the dentist and patient is essential. Conventional active noise-cancelling headphones are ineffective for dental drill noise and simply suppress all sound and hinder communication. METHOD: A compact passive earplug device was designed specifically to attenuate broadband high-frequency noise ranges from 5 to 8 kHz employing an array of quarter wavelength (QW) resonators. This device was 3D printed and tested against white noise to enhance the objectivity of analysis, using a calibrated ear and cheek simulator to effectively measure its performance. RESULTS: The results showed that the resonators produced an average reduction of 27 dB across the targeted frequency range. When compared with two proprietary passive earplugs, this developed passive device prototype was able to attenuate an average of 9 dB more across the target frequency range whilst delivering louder speech signals of 14 dB more. The results also show that using an array of resonators exhibits an accumulated effect of individual resonator performance. CONCLUSIONS: This low-cost passive device could have a place in the dental clinic to reduce unwanted drill noise equivalent to the white noise high frequency spectra tested.

Environmental sources of radio frequency noise: potential impacts on magnetoreception.

Radio frequency electromagnetic noise (RF) of anthropogenic origin has been shown to disrupt magnetic orientation behavior in some animals. Two sources of natural RF might also have the potential to disturb magnetic orientation behavior under some conditions: solar RF and atmospheric RF. In this review, we outline the frequency ranges and electric/magnetic field magnitudes of RF that have been shown to disturb magnetoreceptive behavior in laboratory studies and compare these to the ranges of solar and atmospheric RF. Frequencies shown to be disruptive in laboratory studies range from 0.1 to 10 MHz, with magnetic magnitudes as low as 1 nT reported to have effects. Based on these values, it appears unlikely that solar RF alone routinely disrupts magnetic orientation. In contrast, atmospheric RF does sometimes exceed the levels known to disrupt magnetic orientation in laboratory studies. We provide a reference for when and where atmospheric RF can be expected to reach these levels, as well as a guide for quantifying RF measurements.

Effect of low-frequency noise on the survival rate and immunity of infected Vibrio parahaemolyticus sea slug (Onchidium reevesii).

Anthropogenic noise in the marine environment has become a global environmental pollutant that affects the behavior, physiology and immunity of marine animals. However, the resistance of marine animals to pathogens while under the influence of noise is a topic that has received little attention. To assess the immune defense response of sea slugs against pathogens when exposed to low frequency noise, we performed 120 h exposure experiments on sea slugs after a Vibrio parahaemolyticus application in low frequency noise at 500 Hz and 1000 Hz. We found that after the infection with V. parahaemolyticus, the survival rate of the sea slugs decreased, the apoptosis rate and reactive oxygen species (ROS) production of hemocytes increased significantly (P < 0.05), the proliferation of hemocytes accelerated, the activities of enzymes such as superoxide dismutase (SOD), catalase (CAT), alkaline phosphatase (AKP), alanine transaminase (ALT) and lysozyme (LZM) in the hepatopancreas increased significantly, and the expression of TNF signaling pathway-related genes (TNF-α, FADD, Caspase 8, Caspase 3) and Hsp70 genes were generally upregulated. In addition, exposure of sea slug after infected with V. parahaemolyticus to low frequency noise resulted in a significant increase in both antioxidant and immune parameters, which were positively correlated with frequency. The results showed that noise frequency and exposure time had an interactive effect on the above indicators. In summary, low-frequency noise exposure increases the risk of pathogenic infections in sea slugs and exacerbates the negative effects on the antioxidant capacity and immune metabolism of the organism.

A 1-µm-Band Injection-Locked Semiconductor Laser with a High Side-Mode Suppression Ratio and Narrow Linewidth.

We demonstrate a narrow-linewidth, high side-mode suppression ratio (SMSR) semiconductor laser based on the external optical feedback injection locking technology of a femtosecond-apodized (Fs-apodized) fiber Bragg grating (FBG). A single frequency output is achieved by coupling and integrating a wide-gain quantum dot (QD) gain chip with a Fs-apodized FBG in a 1-µm band. We propose this low-cost and high-integration scheme for the preparation of a series of single-frequency seed sources in this wavelength range by characterizing the performance of 1030 nm and 1080 nm lasers. The lasers have a maximum SMSR of 66.3 dB and maximum output power of 134.6 mW. Additionally, the lasers have minimum Lorentzian linewidths that are measured to be 260.5 kHz; however, a minimum integral linewidth less than 180.4 kHz is observed by testing and analyzing the power spectra of the frequency noise values of the lasers.

Electrical and Low Frequency Noise Characterization of Graphene Chemical Sensor Devices Having Different Geometries.

Chemiresistive graphene sensors are promising for chemical sensing applications due to their simple device structure, high sensitivity, potential for miniaturization, low-cost, and fast response. In this work, we investigate the effect of (1) ZnO nanoparticle functionalization and (2) engineered defects onto graphene sensing channel on device resistance and low frequency electrical noise. The engineered defects of interest include 2D patterns of squares, stars, and circles and 1D patterns of slots parallel and transverse to the applied electric potential. The goal of this work is to determine which devices are best suited for chemical sensing applications. We find that, relative to pristine graphene devices, nanoparticle functionalization leads to reduced contact resistance but increased sheet resistance. In addition, functionalization lowers 1/f current noise on all but the uniform mesa device and the two devices with graphene strips parallel to carrier transport. The strongest correlations between noise and engineering defects, where normalized noise amplitude as a function of frequency f is described by a model of AN/fγ, are that γ increases with graphene area and contact area but decreases with device total perimeter, including internal features. We did not find evidence of a correlation between the scalar amplitude, AN, and the device channel geometries. In general, for a given device area, the least noise was observed on the least-etched device. These results will lead to an understanding of what features are needed to obtain the optimal device resistance and how to reduce the 1/f noise which will lead to improved sensor performance.

Assessment of in-cabin noise of wide-body aircrafts.

The aviation industry has seen dramatic growth over the decades till the recent disruption due to the COVID-19 pandemic. Moreover, long-haul routes with a distance of more than 4000 km are common for major airlines worldwide. Therefore, aircraft cabin noise assessment is essential, especially in long-haul flights, for passenger and flight crew health wellness. In this paper, the cabin noise of five wide-body aircraft, namely Airbus A330-300ER, A350-900, A380-800, and Boeing B777-200ER and B787-900, was recorded using a calibrated in-house developed smartphone application. The sound pressure levels of in-cabin noise have been measured on two different decibel scales, namely, A-weighted [dB(A)] and C-weighted scales [dB(C)]. The sound pressure levels of Airbus A380-800 were lowest among selected models, while the in-cabin pressure level values of Airbus A350-900 were maximum. However, the difference in decibel levels between the aircraft is minimal as it is within 3 dB.

A Two-Channel DFT Spectrum Analyzer for Fluctuation Enhanced Sensing Based on a PC Audio Board.

The main requirement for using the Fluctuation Enhanced Sensing technique is the ability to perform low-frequency noise measurements. The portability of the measurement system is also a quite desirable feature not limited to this specific application. In this paper, an approach for the realization of a dual channel spectrum analyzer that is capable of exploring frequencies down to DC, although based on a USB sound card, is proposed. The lower frequency range of the input signals, which is outside the frequency range of the sound board, is upconverted to higher frequencies by means of a very simple modulation board. Then, the entire spectrum is reconstructed numerically by proper elaboration. With the exception of the modulation board, the approach we propose does not rely on any specific hardware. Thanks to the efficiency of the spectra estimation and reconstruction software, which is based on a public domain library, the system can be built on a low-cost computer single board computer, such as the Raspberry PI3. Moreover, when equipped with an optical TCP/IP link, it behaves as a compact spectrum analyzer that along with the device under test can be placed into a shielded environment, thus being isolated from external electromagnetic interferences.

The Role of Noise in Specific Detectivity of InAs/GaSb Superlattice MWIR Bariodes.

In this paper, the results of the electrical, noise, and optical characterization of p-i-n and p-B-i-n diodes with AlSb and 4 ML AlSb/8 ML GaSb superlattice barriers in High-Operating Temperature conditions, are presented. Experimental and theoretical noise parameters were compared. Both dark current and noise analysis showed that the p-Bp_bulk-i-n bariode had the best performance. P-i-n photodiodes had the highest experimental value of specific detectivity (D*) of 6.16 × 109 Jones at 210 K and zero bias. At about -1 V reverse bias, the bariode with AlSb/GaSb electron barrier caught up to it and both devices achieved D* = (1-1.1) × 108 Jones. Further optimization of the superlattice-based electron barrier should result in the improvement of bariode performance at a smaller bias, at which better noise performance is more pronounced. It was shown that neglecting the low-frequency noise component can lead to a significant overestimation of detectivity. The simple method of incorporation of low-frequency noise contribution in the detectivity calculation, without time-consuming measurements, has been proposed.

A new method with an explant culture of the utricle for assessing the influence of exposure to low-frequency noise on the vestibule.

Health risks attributed to low-frequency noise (LFN) exposure are a serious global issue. Therefore, the development of a method for a prevention based upon risk assessments for LFN is important. Previously in vivo exposure of mice to LFN at 100 Hz, 95 dB for 1 hr produced imbalance with breakage of the otoconial membrane, which covers hair cells as well as impaired activity of hair cells in the vestibule. However, methods for inhibition of LFN-mediated imbalance have not been developed. At present, there are no apparent techniques available with in vitro or ex vivo assessments to evaluate LFN-mediated imbalance by direct administration of preventive chemicals into the vestibule. Our findings demonstrated the usefulness of an explant culture of the utricle with a fluorescent styryl dye, FM1-43FX. In addition, examination of the morphology of the otoconial membrane with explant cultures of utricles was conducted to determine the risk of LFN. Ex vivo exposure of the utricle to LFN at 100 Hz, 95 dB for 1 hr induced breaks in the otoconial membrane as well as decreased uptake of FM1-43FX in hair cells. Taken together, the results of this study provide a novel technique for assessing the risk of LFN exposure using an ex vivo experiment.

Distribution Transformer Parameters Detection Based on Low-Frequency Noise, Machine Learning Methods, and Evolutionary Algorithm.

The paper proposes a method of automatic detection of parameters of a distribution transformer (model, type, and power) from a distance, based on its low-frequency noise spectra. The spectra are registered by sensors and processed by a method based on evolutionary algorithms and machine learning. The method, as input data, uses the frequency spectra of sound pressure levels generated during operation by transformers in the real environment. The model also uses the background characteristic to take under consideration the changing working conditions of the transformers. The method searches for frequency intervals and its resolution using both a classic genetic algorithm and particle swarm optimization. The interval selection was verified using five state-of-the-art machine learning algorithms. The research was conducted on 16 different distribution transformers. As a result, a method was proposed that allows the detection of a specific transformer model, its type, and its power with an accuracy greater than 84%, 99%, and 87%, respectively. The proposed optimization process using the genetic algorithm increased the accuracy by up to 5%, at the same time reducing the input data set significantly (from 80% up to 98%). The machine learning algorithms were selected, which were proven efficient for this task.

A Triode Device with a Gate Controllable Schottky Barrier: Germanium Nanowire Transistors and Their Applications.

Electrical contacts often dominate charge transport properties at the nanoscale because of considerable differences in nanoelectronic device interfaces arising from unique geometric and electrostatic features. Transistors with a tunable Schottky barrier between the metal and semiconductor interface might simplify circuit design. Here, germanium nanowire (Ge NW) transistors with Cu3 Ge as source/drain contacts formed by both buffered oxide etching treatments and rapid thermal annealing are reported. The transistors based on this Cu3 Ge/Ge/Cu3 Ge heterostructure show ambipolar transistor behavior with a large on/off current ratio of more than 105 and 103 for the hole and electron regimes at room temperature, respectively. Investigations of temperature-dependent transport properties and low-frequency current fluctuations reveal that the tunable effective Schottky barriers of the Ge NW transistors accounted for the ambipolar behaviors. It is further shown that this ambipolarity can be used to realize binary-signal and data-storage functions, which greatly simplify circuit design compared with conventional technologies.

Heat shock protein 70 is a key molecule to rescue imbalance caused by low-frequency noise.

A previous study showed that people living in urban areas are generally exposed to low-frequency noise (LFN) with frequencies below 100 Hz and sound levels of 60-110 dB in daily and occupational environments. Exposure to LFN has been shown to affect balance in humans and mice. However, there is no information about prevention of LFN-mediated imbalance because of a lack of information about the target region based on health risk assessment of LFN exposure. Here, we show that acute exposure to LFN at 100 Hz, 95 dB, but not at 85 dB or 90 dB, for only 1 h caused imbalance in mice. The exposed mice also had decreased cervical vestibular-evoked myogenic potential (cVEMP) with impaired activity of vestibular hair cells. Since imbalance in the exposed mice was irreversible, morphological damage in the vestibules of the exposed mice was further examined. The exposed mice had breakage of the otoconial membrane in the vestibule. LFN-mediated imbalance and breakage of the otoconial membrane in mice were rescued by overexpression of a stress-reactive molecular chaperone, heat shock protein 70 (Hsp70), which has been shown to be induced by exposure of mice to 12 h per day of LFN at 95 dB for 5 days. Taken together, the results of this study demonstrate that acute exposure to LFN at 100 Hz, 95 dB for only 1 h caused irreversible imbalance in mice with structural damage of the otoconial membrane as the target region for LFN-mediated imbalance, which can be rescued by Hsp70.

Low-Frequency Noise Evaluation on a Commercial Magnetoimpedance Sensor at Submillihertz Frequencies for Space Magnetic Field Detection.

The purpose of this study was to measure the low-frequency noise and basic performance of a commercial magnetoimpedance (MI) sensor at sub-millihertz frequencies for use in space missions. Normally, space missions require measuring very weak magnetic fields with a long integration time, such as the space gravitational wave detection mission requiring sub-millihertz frequencies. We set up a platform for measuring the performance on this MI sensor, including low-frequency noise, measurement limit, linearity, and temperature stability. The results show that the low-frequency noise of the MI sensor is below 10 nT/√Hz at 1 mHz and below 100 nT/√Hz at 0.1 mHz; its measurement limit is 600 pT. The MI sensor is characterized by high precision, small size, and low noise, demonstrating considerable potential for application in magnetically sensitive experiments requiring long integration time. This is an effect way to solve the problem that there is on one suitable magnetic sensor at space magnetic field detection, but the sensor requires improvements in temperature stability.

Classification of Low Frequency Signals Emitted by Power Transformers Using Sensors and Machine Learning Methods.

This paper proposes a method of automatically detecting and classifying low frequency noise generated by power transformers using sensors and dedicated machine learning algorithms. The method applies the frequency spectra of sound pressure levels generated during operation by transformers in a real environment. The spectra frequency interval and its resolution are automatically optimized for the selected machine learning algorithm. Various machine learning algorithms, optimization techniques, and transformer types were researched: two indoor type transformers from Schneider Electric and two overhead type transformers manufactured by ABB. As a result, a method was proposed that provides a way in which inspections of working transformers (from background) and their type can be performed with an accuracy of over 97%, based on the generated low-frequency noise. The application of the proposed preprocessing stage increased the accuracy of this method by 10%. Additionally, machine learning algorithms were selected which offer robust solutions (with the highest accuracy) for noise classification.

A Novel Differential High-Frequency Current Transformer Sensor for Series Arc Fault Detection.

Fault arc detection is an important technology to ensure the safe operation of electrical equipment and prevent electrical fires. The high-frequency noise of the arc current is one of the typical arc characteristics of almost all loads. In order to accurately detect arc faults in a low-voltage alternating-current (AC) system, a novel differential high-frequency current transformer (D-HFCT) sensor for collecting high-frequency arc currents was proposed. The sensitivity and frequency band of the designed sensor were verified to ensure that the acquisition requirements of the high-frequency current were satisfied. A series arc fault simulation experiment system was built, and resistive, inductive, and non-linear load and high-power shielding load experiments were carried out. Experiments showed that the sensor output signal was close to zero in the non-arc state, and the sensor output response was a high-frequency glitch in the arc state. The results were consistent for different loads, and the discrimination between normal and fault states was obvious, which proved that the sensor is suitable for series arc fault detection.

Low-Frequency Current Fluctuations and Sliding of the Charge Density Waves in Two-Dimensional Materials.

We investigated low-frequency noise in two-dimensional (2D) charge density wave (CDW) systems, 1 T-TaS2 thin films, as they were driven from the nearly commensurate (NC) to incommensurate (IC) CDW phases by voltage and temperature stimuli. This study revealed that noise in 1 T-TaS2 has two pronounced maxima at the bias voltages, which correspond to the onset of CDW sliding and the NC-to-IC phase transition. We observed unusual Lorentzian features and exceptionally strong noise dependence on electric bias and temperature, leading to the conclusion that electronic noise in 2D CDW systems has a unique physical origin different from known fundamental noise types. We argue that noise spectroscopy can serve as a useful tool for understanding electronic transport phenomena in 2D CDW materials characterized by coexistence of different phases and strong pinning.