Ambient Background Research Articles

Study on Subjective Evaluation of Acoustic Environment in Urban Open Space Based on "Effective Characteristics".

With the continuous expansion of urban scale with dense population and traffic and the gradual improvement of residents’ requirements for environmental quality, the traditional evaluation method relying on acoustic energy is not enough to reflect the feelings of urban crowds about acoustic environment quality. The acoustic environment quality evaluation method based on human subjective perception has gradually become one of the research focuses in the field of environmental noise control. In recent years, various subjective and objective acoustic characteristic parameters have been introduced into the study of acoustic environment assessment in the global literature. However, the extraction of “effective characteristics” from a large number of physical and psychoacoustic characteristics contained in acoustic signals and the creation of a scientific and efficient subjective evaluation model have always been key technical problems in the field of acoustic environment evaluation. Based on subjective human perceptions, the overall acoustic environment quality evaluation of urban open spaces is studied in this paper. Based on the “effective characteristic” parameters and the subjective characteristic proposed in the previous research, including equivalent continuous A-weighted sound pressure level (LA), the difference between median noise and ambient background noise (L50 − L90), Sharpness (Sh), as well as satisfaction (Sat), the multivariable linear regression algorithm is used to further study the intrinsic correlation between the proposed “effective characteristics” and subjective perception. Then, a satisfaction evaluation model of the acoustic environment based on “effective characteristics” is built in this paper. Furthermore, the soundwalk evaluation experiment and the MATLAB numerical simulation experiment are carried out, which verify that the prediction accuracy of the proposed model is more than 92%, the consistency of satisfaction level is more than 88%, as well as the changes in the values of Sh and L50 − L90 have a significant impact on the satisfaction prediction of the proposed model. It shows that the proposed “effective characteristics” more comprehensively describe the quality level of the regional acoustic environment in urban open space compared with a single LA index, and the proposed acoustic environment satisfaction evaluation model based on “effective characteristics” has significant accuracy superiority and regional applicability.

Demonstration of Entanglement-Enhanced Covert Sensing.

The laws of quantum physics endow superior performance and security for information processing: quantum sensing harnesses nonclassical resources to enable measurement precision unmatched by classical sensing, whereas quantum cryptography aims to unconditionally protect the secrecy of the processed information. Here, we present the theory and experiment for entanglement-enhanced covert sensing, a paradigm that simultaneously offers high measurement precision and data integrity by concealing the probe signal in an ambient noise background so that the execution of the protocol is undetectable with a high probability. We show that entanglement offers a performance boost in estimating the imparted phase by a probed object, as compared to a classical protocol at the same covertness level. The implemented entanglement-enhanced covert sensing protocol operates close to the fundamental quantum limit by virtue of its near-optimum entanglement source and quantum receiver. Our work is expected to create ample opportunities for quantum information processing at unprecedented security and performance levels.

Establishing the appropriate maximum sound pressure levels in absence of a noise ordinance for a residential community near an indoor firing range.

Environmental noise surveys assess the ambient noise levels of a specific area, as well as any noise sources deemed inappropriate for the noise environment. Recently, an environmental noise survey was completed to understand the impact of an indoor firing range on adjacent residential properties. Because of the transient nature of the gunfire, day-night equivalent sound pressure level (Ldn), a standard found often in community noise ordinances, was deemed an inappropriate metric to truly determine the intrusiveness of the noise on the surrounding environment. Rather, fast-response maximum sound pressure levels (Lmax) were captured and analyzed in their relation to ambient background noise levels for their effectiveness in translating the impact of the gunfire on adjacent residential properties. Furthermore, multiple frequency-weighting filters were applied to these measurements to fully understand the characteristics of this broadband, high-impact noise. This paper discusses the appropriateness of Lmax when focusing on transient environmental noise levels caused by an indoor firing range as well as how these metrics should be characterized in community noise ordinances.

A Sports Video Behavior Recognition Using Local Spatiotemporal Patterns

These days, many researchers are interested in sports video behavior recognition (SVBR), which has emerged as a core research domain for visual understanding and analysis of athlete performance. Despite significant results in simple scenarios, SVBR remains a difficult task due to numerous challenges such as independence, obstruction, and interclass visual appearance in real situations. Recognizing the sports video behavior is one of the crucial challenges in computer vision for sports video behavior data, with implementation in monitoring, mental illness diagnostics, video information extraction, and multitarget tracking. This paper provides a local pattern activity discrimination model for the detection and localization of active individuals in a video to address issues of multitarget tracking in video behavior recognition caused by mutual occlusion of targets and the complexity of ambient background. This work solves the problem of low recognition accuracy due to incomplete extraction of trajectories or overly complex backgrounds using a trajectory-based approach. Our model is applied to the video segments of 38 matches associated with goal events in Euro 2012, and an average accuracy of 91.3% is obtained. The experimental results verify the high accuracy and applicability of our method for the recognition of target object behavior in the videos.

Radiopurity studies of a rock sample from the Aut region

Efforts are underway to set up an underground laboratory in India for rare event studies like double beta decay, dark matter, etc. For such experiments, mitigation of radiation background is of paramount importance and understanding ambient background at the site, originating from the rock, is one of the crucial factors. With this motivation, the radiopurity studies of a rock sample from the potential laboratory site in the Aut tunnel of Himachal Pradesh (India) have been carried out using the TIFR low background experimental setup (TiLES). The concentration of 40K in Aut rock is observed to be lower by a factor of ∼1000 as compared to the samples from BWH (Bodi West Hill), Tamil Nadu (India), current designated site for India-based Neutrino Observatory. The natural radioactive trace impurity 232Th is lower in the Aut rock, while 238U is somewhat higher than the BWH rock. Overall, the ambient gamma ray background at Aut is expected to be lower than the BWH, while ambient neutron background is expected to be similar. Further, to assess the neutron-induced long lived activity, fast neutron activation studies have been carried out on both the Aut and BWH rock samples at the Pelletron Linac Facility, Mumbai.

Optical noise in a free-space quantum communications link from natural and nuclear disturbed environments* *This manuscript has been authored in part by UT-Battelle LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to

Satellite communications at radio frequencies can experience a ‘blackout’ period following the atmospheric detonation of a nuclear weapon. The wavelengths used for free-space quantum communications will not incur the same ‘blackout’ effects from a nuclear detonation, but the optical systems will suffer from a phenomenon called redout. Redout occurs in an optical detector when ambient light scatters into the optical receiver, causing elevated background photon counts in the detector such that background noise overwhelms the signal. In this work, the duration of the redout effect is quantified from a nuclear disturbed environment on a ground-to-space quantum optical link. In addition, we comment on various techniques for reducing ambient and nuclear disturbed background counts in a quantum free-space optical link. For low-altitude nuclear detonations (i.e., under 50 km), the maximum interference time will be less than 1 min. Implementing a telescope, timing gate, and wavelength filter to the detector can reduce the background counts in the detector significantly. Aerosol levels and ground albedo are major contributors to background noise in a ground-to-satellite quantum channel, and ground station location should factor in both variables.

Dynamic Reliability Evaluation on Foundation of Stone Cutting Machine under Ambient Excitation

Dynamic reliability evaluation on foundation of stone cutting machine is usually affected by ambient background noise. In this paper, a nested evaluation approach of dynamic reliability is conducted for handling this complex situation. After getting the detected data, a fast identified process is available for fastly identifying the dynamic parameter foundation of stone cutting machine by using the peak-picking method, in which the natural frequency of foundation is able to be first identified by the equivalent frequency response function for the self-power spectrum of the foundation; subsequently, the damping ratio of the foundation, on the basis of the previous result of natural frequency, is identified by the half-power broadband technology; eventually, after obtaining these dynamic parameters identified, the failure probability of the foundation and its corresponding dynamic reliability index, under ambient excitation, is capable to be calculated based on the first-passage probability of the maximum response. An example of stone cutting machine foundation with engineering background is investigated in detail, and its result diagrams calculated by the proposed approach can be demonstrated that the foundation of stone cutting machine is safe and reliable in the current environment. The proposed method, in this paper, provides an effective path for evaluating the foundation reliability of stone cutting machine under ambient excitation.

A CNN Based Software Gradiometer for Electromagnetic Background Noise Reduction in Low Field MRI Applications.

The shielding of electromagnetic noise is critical in obtaining magnetic resonance imaging measurements in the ultra-low magnetic field regime where the intrinsic signal-to-noise ratio is very small. The traditional approach of using an enclosure for electromagnetic shielding is expensive and hinders system portability. We describe here the use of a CNN-based software gradiometer to suppress the effect of electromagnetic ambient background noise sources that inductively couple into the signal detection coils. The system involves three ambient noise monitoring coils placed at a distance from the magnetic resonance signal detector. The three coils were used to synthesize the ambient noise captured by the signal detector; a convolutional neural network approach was used. Mathematical foundations are provided to justify the noise suppression framework. The results show that as much as 20-fold noise suppression can be achieved using an optimized convolutional neural network and simultaneous ambient noise measurements. The proposed approach has the potential to replace the requirement for magnetically shielded enclosures and make ultra-low field magnetic resonance imaging truly portable.

Short-range contributions of local sources to ambient air.

Recent developments in aerobiology have enabled the investigation of airborne biomass with high temporal and taxonomic resolution. In this study, we assess the contributions of local sources to ambient air within a 160,000 m2 tropical avian park (AP). We sequenced and analyzed 120 air samples from seven locations situated 160 to 400 m apart, representing distinct microhabitats. Each microhabitat contained a characteristic air microbiome, defined by the abundance and richness of its airborne microbial community members, supported by both, PCoA and Random Forest analysis. Each outdoor microhabitat contained 1% to 18.6% location-specific taxa, while a core microbiome of 27.1% of the total taxa was shared. To identify and assess local sources, we compared the AP dataset with a DVE reference dataset from a location 2 km away, collected during a year-round sampling campaign. Intersection of data from the two sites demonstrated 61.6% of airborne species originated from local sources of the AP, 34.5% from ambient air background, and only 3.9% of species were specific to the DVE reference site. In-depth taxonomic analysis demonstrated association of bacteria-dominated air microbiomes with indoor spaces, while fungi-dominated airborne microbial biomass was predominant in outdoor settings with ample vegetation. The approach presented here demonstrates an ability to identify local source contributions against an ambient air background, despite the prevailing mixing of air masses caused by atmospheric turbulences.

The Social Spaces of Music Traditions in Baghdad before and after Destruction

The Social Spaces of Music Traditions in Baghdad before and after Destruction

Planet population synthesis: the role of stellar encounters.

Depending on the stellar densities, protoplanetary discs in stellar clusters undergo: background heating; disc truncation-driven by stellar encounter; and photoevaporation. Disc truncation leads to reduced characteristic sizes and disc masses that eventually halt gas giant planet formation. We investigate how disc truncation impacts planet formation via pebble-based core accretion paradigm, where pebble sizes were derived from the full grain-size distribution within the disc lifetimes. We make the best-case assumption of one embryo and one stellar encounter per disc. Using planet population synthesis techniques, we find that disc truncation shifts the disc mass distributions to the lower margins. This consequently lowered the gas giant occurrence rates. Despite the reduced gas giant formation rates in clustered discs, the encounter models mostly show as in the isolated field; the cold Jupiters are more frequent than the hot Jupiters, consistent with observation. Moreover, the ratio of hot to cold Jupiters depend on the periastron distribution of the perturbers with linear distribution in periastron ratio showing enhanced hot to cold Jupiters ratio in comparison to the remaining models. Our results are valid in the best-case scenario corresponding to our assumptions of: only one disc encounter with a perturber, ambient background heating, and less rampant photoevaporation. It is not known exactly of how much gas giant planet formation would be affected should disc encounter, background heating, and photoevaporation act in a concert. Thus, our study will hopefully serve as motivation for quantitative investigations of the detailed impact of stellar cluster environments on planet formations.

Measurements of gamma ray, cosmic muon and residual neutron background fluxes for rare event search experiments at an underground laboratory

Ambient radiation background contributed by the penetrating cosmic ray particles and the radionuclides present in the rock materials have been measured at an underground laboratory at Jaduguda, Jharkhand, India, located inside a mine at 555 m depth. The laboratory is being set up to explore rare event search processes, such as direct dark matter search, neutrinoless double beta decay, axion search, supernova neutrino detection, etc., that require specific knowledge of the nature and extent of the radiation environment in order to assess the sensitivity reach and also to plan for its reduction for the targeted experiment. The gamma ray background, which is mostly contributed by the primordial radionuclides and their decay chain products, have been measured inside the laboratory and found to be dominated by rock radioactivity for Eγ≲3MeV. Shielding of these residual gamma rays for the experiment was also evaluated. The cosmic muon flux, measured inside the laboratory using large area plastic scintillator telescope, was found to be: (2.257±0.261±0.042)×10−7cm−2s−1, which agrees reasonably well with simulation results. The neutron background flux has been measured for the radiogenic neutrons and found to be: (1.61±0.03)×10−4cm−2s−1 for no threshold cut. Detailed GEANT4 simulation for the radiogenic neutrons and the cosmogenic neutrons have been carried out. Effects of multiple scattering of both the types of neutrons within the surrounding rock and the cavern walls were studied and the results for the radiogenic neutrons are found to be in reasonable agreement with experimental results. Neutron fluxes contributed by those neutrons of cosmogenic origin have been reported as function of the energy threshold.

Presence of Priority Polycyclic Aromatic Hydrocarbons, Chromium, Copper and Lead in Two selected Brownfield Sites in United Kingdom

In recent years, concerns about adverse effects of increasing land contamination paralleled with the increasing demand for land has emphasized need for sustainable remediation strategies. Soil samples were collected from two brownfield sites, in Saltley, Birmingham and Swansea, South Wales, United Kingdom and analysed to establish the extent of contamination by priority polycyclic aromatic hydrocarbon (PAH) compounds. Saltley site had a total PAH concentration of 41.0 mg kg-1 with high concentrations of phenanthrene, anthracene, fluoranthene, pyrene, benzo[a]anthracene, chrysene and benzo[a]pyrene, total benzo[a]pyrene equivalent value of 6.0 mg kg-1 and total carcinogenic PAH of 19.0 mg kg-1. At the Swansea site, total PAH concentration ranged from 5.0 – 85.0 mg kg-1 with pyrene, fluoranthene, benzo[a]anthracene, chrysene, benzo[a]pyrene as the predominant PAHs, total benzo[a]pyrene equivalent value of 0.9 – 2.0 mg kg-1 and total carcinogenic PAH concentration of 2.6 – 11.0 mg kg-1. Heavy metal concentrations were above the ambient background concentrations for urban/industrial area. Both brownfield sites had a mixture of PAH and heavy metal contamination in varying concentrations with implication for the selection of efficient remedial strategies to enable their redevelopment.

Simulated Hough Transform Model Optimized for Straight-Line Recognition Using Frontier FPGA Devices

The use of the Hough transforms to identify shapes or images has been extensively studied in the past using software for artificial intelligence applications. In this article, we present a generalization of the goal of shape recognition using the Hough transform, applied to a broader range of real problems. A software simulator was developed to generate input patterns (straight-lines) and test the ability of a generic low-latency system to identify these lines: first in a clean environment with no other inputs and then looking for the same lines as ambient background noise increases. In particular, the paper presents a study to optimize the implementation of the Hough transform algorithm in programmable digital devices, such as FPGAs. We investigated the ability of the Hough transform to discriminate straight-lines within a vast bundle of random lines, emulating a noisy environment. In more detail, the study follows an extensive investigation we recently conducted to recognize tracks of ionizing particles in high-energy physics. In this field, the lines can represent the trajectories of particles that must be immediately recognized as they are created in a particle detector. The main advantage of using FPGAs over any other component is their speed and low latency to investigate pattern recognition problems in a noisy environment. In fact, FPGAs guarantee a latency that increases linearly with the incoming data, while other solutions increase latency times more quickly. Furthermore, HT inherently adapts to incomplete input data sets, especially if resolutions are limited. Hence, an FPGA system that implements HT is inefficient for small sets of input data but becomes more cost-effective as the size of the input data increases. The document first presents an example that uses a large Accumulator consisting of 1100 × 600 Bins and several sets of input data to validate the Hough transform algorithm as random noise increases to 80% of input data. Then, a more specifically dedicated input set was chosen to emulate a real situation where a Xilinx UltraScale+ was to be used as the final target device. Thus, we have reduced the Accumulator to 280 × 280 Bins using a clock signal at 250 MHz and a few tens input points. Under these conditions, the behavior of the firmware matched the software simulations, confirming the feasibility of the HT implementation on FPGA.

Extraction and Quantification of Nanoparticulate Mercury in Natural Soils.

Nanoparticulate mercury (Hg-NPs) are ubiquitous in nature. However, the lack of data on their concentration in soils impedes reliable risk assessments. This is due to the analytical difficulties resulting from low ambient Hg concentrations and background interferences of heterogeneous soil components. Here, coupled to single particle inductively coupled plasma-mass spectrometry (spICP-MS), a standardized protocol was developed for extraction and quantification of Hg-NPs in natural soils with a wide range of properties. High particle number-, particle mass-, and total mass-based recoveries were obtained for spiked HgS-NPs (74-120%). Indigenous Hg-NPs across soils were within 107-1011 NPs g-1, corresponding to 3-40% of total Hg on a mass basis. Metacinnabar was the primary Hg species in extracted samples from the Wanshan mercury mining site, as characterized by X-ray absorption spectroscopy and transmission electron microscopy. In agreement with the spICP-MS analysis, electron microscopy revealed comparable size distribution for nanoparticles larger than 27 nm. These indigenous Hg-NPs contributed to 5-65% of the measured methylmercury in soils. This work paves the way for experimental determinations of indigenous Hg-NPs in natural soils, which is critical to understand the biogeochemical cycling of mercury and thereby the methylation processes governing the public exposure to methylmercury.

Panther — the new thermal neutron time-of-flight spectrometer at the ILL

Panther is a new high-flux medium-resolution direct-geometry thermal-neutron time-of-flight spectrometer at the Institut Laue-Langevin (ILL). It is designed for inelastic neutron-scattering measurements of excitations in condensed matter using single crystals, polycrystalline samples, and liquids. Panther uses double focusing graphite or Cu monochromators, a Fermi chopper, and position-sensitive 3He detectors covering 2 steradians of solid angle. A system of disc choppers and an optional sapphire filter are used to reduce the epithermal neutron background. Thermal neutron background is reduced by a radial oscillating collimator, a beam dump, and an elaborate set of Cd shielding inside the evacuated detector tank. The outside of the tank is covered by a 0.3 m thick layer of borated high-density polyethylene to reduce ambient and cosmic background. The design and performance of the instrument in its current status are described, as well as planned developments.

A Class of Pareto Optimal Binaural Beamformers

The objective of binaural multi-microphone speech enhancement algorithms can be viewed as a multi-criteria design problem as there are several requirements to be met. The objective is not only to extract the target speaker without distortion, but also to suppress interfering sources (e.g., competing speakers) and ambient background noise, while preserving the auditory impression of the complete acoustic scene. Such a multi-objective problem (MOP) can be solved using a Pareto frontier, which provides a useful trade-off between the different criteria. In this paper, we propose a unified Pareto optimization framework, which is achieved by defining a generalized mean squared error (MSE) cost function, derived from a MOP. The solution to the multi-criteria problem is grounded on a solid mathematical foundation. The MSE cost function consists of a weighted sum of speech distortion (SD), partial interference reduction (IR), and partial noise reduction (NR) terms with scaling parameters that control the amount of IR and NR. The filter minimizing this generalized cost function, denoted Pareto optimal binaural multichannel Wiener filter (Pareto-BMWF), constitutes a generalization of various binaural MWF-based and binaural MVDR-based beamformers. This solution is optimal for any set of parameters. The improved speech enhancement capabilities are experimentally demonstrated using real-signal recordings when estimation errors are present and the binaural cue preservation capabilities are analyzed.

Design and Implementation of Ultra-Wide Band Antenna for Partial Discharge Detection in High Voltage Power Equipment

Partial discharges (PD) are the most common and harmful threat to the health of electrical insulation of high voltage (HV) and high field (HF) equipment. The occurrence of PD activity in HV and MV equipment is at the same time a cause and a sign of insulation degradation that may eventually result in the breakdown of the HV power equipment. For the safe and reliable operation of HV power equipment, continuous PD monitoring needs to be conducted conveniently to prevent any unplanned power outages and damage to electrical power equipment. The ultra-high frequency (UHF) PD measurement method has been widely used as an effective technique to detect PD activity on HV power equipment due to its non-invasive principle. To enable PD detection accuracy, there is still a need for more sensitive PD sensors that can assist the UHF PD monitoring system by suppressing ambient background noise and low-frequency electromagnetic interferences from telecommunication such as GSM signals. To tackle the sensitivity issues, this article presents a new design of ultra-wideband (UWB) microstrip patch antenna that is capable of effective suppression of low-frequency interference signals. The proposed antenna, designed, simulated, and optimized using the CST Microwave Studio software, has a bandwidth of 3.3GHz, below -10dB, in the operating frequency range of 1.2GHz-4.5GHz. The prototype of this antenna, printed on an FR4 substrate of a thickness of 1.6mm and a dielectric constant of 4.4, featuring a compact size of 100mm <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times100$ </tex-math></inline-formula> mm <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times1.6$ </tex-math></inline-formula> mm, was implemented to detect PD through laboratory experiments. This paper shows that the designed UWB antenna has high sensitivity, good noise rejection and it is, therefore, a promising candidate sensor for PD detection on HV equipment.

Two-year optical site characterization for the Pacific Ocean Neutrino Experiment (P-ONE) in the Cascadia Basin

The STRings for Absorption length in Water (STRAW) are the first in a series of pathfinders for the Pacific Ocean Neutrino Experiment (P-ONE), a future large-scale neutrino telescope in the north-eastern Pacific Ocean. STRAW consists of two 150,mathrm {m} long mooring lines instrumented with optical emitters and detectors. The pathfinder is designed to measure the attenuation length of the water and perform a long-term assessment of the optical background at the future P-ONE site. After 2 years of continuous operation, measurements from STRAW show an optical attenuation length of about 28 m at 450,mathrm {nm}. Additionally, the data allow a study of the ambient undersea background. The overall optical environment reported here is comparable to other deep-water neutrino telescopes and qualifies the site for the deployment of P-ONE.

Discriminating BTX Molecules by the Nonselective Metal Oxide Sensor-Based Smart Sensing System.

Discriminating structurally similar volatile organic compounds (VOCs) molecules, such as benzene, toluene, and three xylene isomers (BTX), remains a significant challenge, especially, for metal oxide semiconductor (MOS) sensors, in which selectivity is a long-standing challenge. Recent progress indicates that temperature modulation of a single MOS sensor offers a powerful route in extracting the features of adsorbed gas analytes than conventional isothermal operation. Herein, a rectangular heating waveform is applied on NiO-, WO3-, and SnO2-based sensors to gradually activate the specific gas/oxide interfacial redox reaction and generate rich (electrical) features of adsorbed BTX molecules. Upon several signal preprocessing steps, the intrinsic feature of BTX molecules can be extracted by the linear discrimination analysis (LDA) or convolutional neural network (CNN) analysis. The combination of three distinct MOS sensors noticeably benefits the recognition accuracy (with a reduced number of training iterations). Finally, a prototype of a smart BTX recognition system (including sensing electronics, sensors, Wi-Fi module, UI, PC, etc.) based on temperature modulation has been explored, which enables a prompt, accurate, and stable identification of xylene isomers in the ambient air background and raises the hope of innovating the future advanced machine olfactory system.