Application of Scirpus grossus fiber as a sound absorber.

The application of Scirpus grossus (SG) fiber as a sound absorber is important to reduce the level of noise affected the physical and mental wellbeing of people. The sound absorption coefficient (SAC) and noise reduction coefficient (NRC) of the SG specimen were evaluated based on a typical model-based design using the data analysis with MATLAB. The results showed that SG specimen with a thickness of 20 mm coated with the perforated aluminum sheet (PAS) compared to that without coating can improve the capability of sound absorption by 14% at the frequency of 4000 Hz. SG specimen coated with PAS that has a NRC value of 0.39 can absorb 39% of sound and thus reflects 61% of sound wave while SG specimen without coating that has a NRC value of 0.23 absorbs 23% of sound and can reflect 77% of sound wave. The sound absorption class of D for SG specimen coated with PAS should be better that of E for SG specimen without coating, which permits us to get better understanding on the applications of SG fiber as a sound adsorber in the future.

Recent Advances in Preparation and Structure of Polyurethane Porous Materials for Sound Absorbing Application.

Various acoustic materials have been developed to resolve noise pollution problem in many industries. Especially, materials with porous structure have been broadly used to absorb sound energy in civil construction and transportation area. Polyurethane (PU) porous materials possess excellent damping properties, good toughness and well-developed pore structures, which have a broad application prospect in sound absorption field. This work aimed to summarize the recent progress of fabrication and structure for PU porous materials in sound absorption application. The sound absorption mechanisms of porous materials were introduced. Different kinds of structure for typical PU porous materials in sound absorption application were covered and highlighted, which included PU foam, modified PU porous materials, aerogel, templated PU and special PU porous materials. Finally, the development direction and existing problems of PU material in sound absorption application were briefly prospected. It can be expected that porous PU with high sound absorption coefficient can be obtained by using some facile methods. The design and accurate regulation of porous structures or construction of multilayer sound absorption structure will be favorably recommended to fulfill the high demand of industrial and commercial applications in the future work. This article is protected by copyright. All rights reserved.

The Environment and Headache: a Narrative Review.

PURPOSE OF REVIEW: In this narrative review, we summarize the peer-reviewed literature published between 2017 and 2022 that evaluated ambient environmental risk factors for primary headache disorders, which affect more than half of the population globally. Primary headache disorders include migraine, tension-type headache (TTH), and trigeminal and autonomic cephalalgias (TAC). RECENT FINDINGS: We identified 17 articles that met the inclusion criteria via PubMed or Google Scholar. Seven studies (41%) relied on data from US populations. The remaining studies were conducted in China, Taiwan, Germany, Ghana, Japan, the Netherlands, South Korea, and Turkey. Air pollution was the most frequently assessed environmental risk factor. Most studies were cross-sectional and focused on all-cause or migraine headaches; one study included TTH, and none included TAC. Short-term exposure to fine particulate matter (PM2.5) was not consistently associated with headache endpoints, but long-term exposure to PM2.5 was associated with migraine headache prevalence and severity across multiple studies. Elevated ambient temperature, changes in weather, oil and gas well exposure, and less natural greenspace, but not noise pollution, were also associated with headache. No studies considered water pollution, metal exposure, ultrafine particulate matter, or wildfire smoke exposure. There is a need for ongoing research focused on headache and the environment. Study designs with the greatest explanatory power may include longitudinal studies that capture the episodic nature of headache and case-crossover analysis, which control for time-invariant individual-level confounders by design. There is also a clear need for research that considers comorbid psychiatric illness and socioeconomic position as powerful modifiers of the effect of the environment on headache.

Comparing pre-industrial and modern ocean noise levels in the Santa Barbara Channel.

To understand the extent of anthropogenic noise in the ocean, it is essential to compare the differences between modern noise environments and their pre-industrial equivalents. The Santa Barbara Channel, off the coast of Southern California, is a corridor for the transportation of goods to and from the busiest shipping ports in the Western hemisphere. Commercial ships introduce high levels of underwater noise into the marine environment. To quantify the extent of noise in the region, we modeled pre-industrial ocean noise levels, driven by wind, and modern ocean noise levels, resulting from the presence of both ships and wind. By comparing pre-industrial and modern underwater noise levels, the low-frequency (50 Hz) acoustic environment was found to be degraded by more than 15 dB. These results can be used to identify regions for noise reduction efforts, as well as to model scenarios to identify those with the greatest potential to support marine conservation efforts.

A pilot study on AI-driven approaches for classification of mental health disorders.

The increasing prevalence of mental disorders among youth worldwide is one of society's most pressing issues. The proposed methodology introduces an artificial intelligence-based approach for comprehending and analyzing the prevalence of neurological disorders. This work draws upon the analysis of the Cities Health Initiative dataset. It employs advanced machine learning and deep learning techniques, integrated with data science, statistics, optimization, and mathematical modeling, to correlate various lifestyle and environmental factors with the incidence of these mental disorders. In this work, a variety of machine learning and deep learning models with hyper-parameter tuning are utilized to forecast trends in the occurrence of mental disorders about lifestyle choices such as smoking and alcohol consumption, as well as environmental factors like air and noise pollution. Among these models, the convolutional neural network (CNN) architecture, termed as DNN1 in this paper, accurately predicts mental health occurrences relative to the population mean with a maximum accuracy of 99.79%. Among the machine learning models, the XGBoost technique yields an accuracy of 95.30%, with an area under the ROC curve of 0.9985, indicating robust training. The research also involves extracting feature importance scores for the XGBoost classifier, with Stroop test performance results attaining the highest importance score of 0.135. Attributes related to addiction, namely smoking and alcohol consumption, hold importance scores of 0.0273 and 0.0212, respectively. Statistical tests on the training models reveal that XGBoost performs best on the mean squared error and R-squared tests, achieving scores of 0.013356 and 0.946481, respectively. These statistical evaluations bolster the models' credibility and affirm the best-fit models' accuracy. The proposed research in the domains of mental health, addiction, and pollution stands to aid healthcare professionals in diagnosing and treating neurological disorders in both youth and adults promptly through the use of predictive models. Furthermore, it aims to provide valuable insights for policymakers in formulating new regulations on pollution and addiction.

Statistical estimation of noise induced hearing loss among the drivers in one of the most polluted cities of India.

In the present study, an attempt has been made to assess the impact of vehicular noise upon the 3-wheeler tempo drivers and to know whether there is any relationship between hearing loss and cumulative noise exposure. For this purpose, 3-wheeler tempo drivers (Exposed group) and non-commercial light motor vehicle car drivers (Unexposed group) were chosen as study subjects. Three traffic routes were selected to assess the noise level during waiting and running time in the exposed and unexposed groups. Among all three routes, the highest mean noise level (Leq) was observed on the Chowk to Dubagga route for waiting and en-route noise measurement. It was measured as 84.13 dB(A) and 86.36 dB(A) for waiting and en-route periods of 7.68 ± 3.46 and 31.05 ± 6.6 min, respectively. Cumulative noise exposure was found to be significantly different (p < 0.001) in all age groups of exposed and unexposed drivers. Audiometric tests have been performed over both exposed and unexposed groups. The regression analysis has been done keeping hearing loss among tempo drivers as the dependent variable and age (years) and Energy (Pa2 Hrs) as the independent variable using three different criteria of hearing loss definitions, i.e., World Health Organization, National Institute for Occupational Safety and Health (NIOSH), Occupational Safety and Health Administration criteria. Among these three criteria, the NIOSH criterion of hearing loss best explained the independent variables. It could explain the total variation in dependent variable by independent variable quite well, i.e., 68.1%. The finding showed a linear relationship between cumulative noise exposures (Pa2 Hrs) and the exposed group's hearing loss (dB), i.e., hearing loss increases with increasing noise dose. Based on the findings, two model equations were developed to identify the safe and unsafe noise levels with exposure time.

Crowdsourced cycling data applications to estimate noise pollution exposure during urban cycling.

This research demonstrates a methodology to integrate freely available datasets to understand the relationship between road traffic noise and cycling experiences in a medium sized city. An illustrative example of the methodology was drawn from data for Dublin, Ireland. We aggregate local environmental data with 81,403 Strava cycle trips, contextualised by feedback from 335 cyclists to estimate exposure levels and infer impacts on experiences and behaviours. Results demonstrate that cyclists recognise that they are subjected to increased noise levels and experience negative psychophysical consequences as a result, but they tend to downplay the impact of noise as merely a minor annoyance. Noise also impacts behaviour, most noticeably through temporal and spatial detours. Geospatial mapping was used to visualise the relationship between noise pollution and cycling activity. Estimating traffic noise levels across two cycle routes, direct vs popular detour, revealed a +10 dB(A) increase in exposure for a saving of approximately 4 min on the direct route compared to the detour. Spatial inequities in exposure levels may have serious health consequences for cyclists in a city such as Dublin. The methodology is demonstrated as suitable for policy level interventions and planning purposes.

Association between occupational noise exposure level and pure-tone audiometry abnormalities among Metropolitan Manila Development Authority employees: A cross-sectional study.

Traffic enforcers are exposed to various occupational health and safety hazards, including noise pollution, which may lead to occupational hearing loss. This cross-sectional study aimed to estimate the prevalence of hearing loss and to assess the relationship between occupational noise exposure level (ONEL) and abnormalities in air conduction thresholds among Metropolitan Manila Development Authority (MMDA) employees along Epifanio delos Santos Avenue, Philippines. Eight-hour ONELs were measured among 108 participants working with greater than 5 years of service. Participants had hearing evaluations using pure tone audiometry (PTA) to calculate the prevalence of hearing loss. Generalized linear models with a Poisson distribution were fitted to estimate the association between ONEL and audiologic abnormalities, controlling for confounding factors. Approximately 16% of employees had hearing loss. The prevalence of hearing loss was higher with ONEL exposures greater than 85 A-weighted decibels (dBA), with traffic enforcers exposed to higher ONELs than office workers. ONELs greater than 85 dBA were related to audiologic abnormalities at different frequencies in PTA. The prevalence of audiologic abnormalities at 4000 Hz and 6000 Hz was 48% higher (adjusted prevalence ratio [aPR], 1.48; 95% CI, 1.12-1.96) and 25% higher (aPR, 1.25; 95% CI, 1.00-1.55), respectively, among participants with ONELs greater than 85 dBA than with ONELs less than or equal to 85 dBA. Participants exposed to ONELs greater than 85 dBA, more likely traffic enforcers, may have increased risk of audiologic abnormalities. Regular ONEL monitoring is warranted for occupational risk assessment of traffic enforcers. A hearing conservation program may need to be considered for this population. Additional studies are needed to determine trends in hearing deterioration among traffic enforcers.

Acoustic performance evaluation of railway boundary walls using a computational fluid dynamics-based simulation approach.

Railway noise has become a significant concern for trackside residents due to increased volume of high-speed passenger and freight train traffic. To address this, active measures, such as reducing noise at the source, and passive measures, such as installing noise barriers along the transmission path, are widely being used. In urban areas, railway boundary walls are constructed to prevent encroachments of railway lands and to avoid pedestrian trespassing of railway tracks. This study aims to evaluate the effectiveness of such a boundary wall for reducing noise and proposes an improved alternative through computational fluid dynamics (CFD) simulations. Various noise barriers with different geometry, shape, and surface materials were simulated and validated with the field conditions based on a rectangular wall of height 2.75 m. Noise attenuation was evaluated by measuring railway noise spectra at different positions, including 0.5 m in front and behind the barrier and at the facade of the residential area. The insertion loss based on field measurements for a rectangular barrier of height 2.75 m was observed to be 5.2 dBA. The simulation results indicated a positive correlation between barrier height and insertion loss, with a maximum attenuation of 17 dBA achieved with a barrier of height 6 m. The most effective noise barrier for reducing railway noise was a T-shaped barrier with a height of 6 m and a projection length of 2 m, with an insertion loss of 22 dBA. This study recommends constructing the barrier with soft materials on its surface to reflect and absorb sound waves effectively. These findings have potential implications for urban planners and policymakers in designing effective noise barriers in residential areas near railway lines.

Tackling Noise: Technology Integration for Improved Noise Pollution Monitoring.

Noise pollution derived from motor vehicles, especially those with noisy engines, constitutes a significant challenge in urban environments, impacting quality of life and public health. In this context, the present study focuses on the implementation of an advanced technological solution: a web-based system specifically designed to monitor and manage noise pollution in Tarapoto, Peru. The execution of this project was structured in 4 key phases. The first phase involved extensive data collection and definition of the project scope. In the second phase, the system architecture was established based on initial observations. The third phase focussed on evaluating and improving system functionalities, while the fourth involved rigorous testing and corrections. The successful implementation of this system led to a significant improvement in the noise pollution monitoring process, reducing reporting times and improving data-driven decision making. This project not only provides a valuable tool for authorities in the management and mitigation of noise pollution, but also encourages community awareness and active participation in the sustainable management of the urban acoustic environment.

The built environment and cancer survivorship: A scoping review.

BACKGROUND: There are more than 32 million cancer survivors worldwide. The built environment is one of the contextual factors that may influence cancer survivorship. However, studies investigating the interdisciplinary field of the built environment and cancer survivorship are lacking. OBJECTIVE: To conduct a systematic review of the existing literature regarding the relationship between the built environment and cancer survivorship, identify any knowledge gaps, and recommend future research directions. METHODS: A systematic literature search was performed by searching OVID Medline, Embase, CINAHL, and Web of Science Core Collection. RESULTS: Of 4235 unique records identified, 26 studies met eligibility criteria. Neighborhood walkability and greenness were the most examined built environment characteristics among the included studies. Walkability was found to be associated with various cancer survivorship experience, including increased levels of physical activity, lowered body mass index, and improved quality of life. The association between greenness and cancer survivorship outcomes were inconsistent across the included studies. Additionally, studies have reported the relationship between light and noise pollution and sleep among cancer survivors. Regarding blue space, in one qualitative study, breast cancer survivors brought up the healing properties of water. CONCLUSION: Our scoping review demonstrated a breadth of current cancer survivorship research in the field of neighborhood walkability and greenness, but fewer studies detailing other aspects of the built environment as defined by this review, such as light pollution, noise pollution, and blue space. We identified future research directions for those interested in this interdisciplinary field, which can provide insights for urban planners and policy makers on how to best leverage the built environment to promote the health and wellbeing of cancer survivors.

Anthropogenic noise limits resource distribution without changing social hierarchies.

Increasing evidence demonstrates that anthropogenic noise is a global pollutant that threatens marine ecosystems. Mounting numbers of studies show its diverse effects on individuals and their behaviour. However, little is known about how individual changes in response to anthropogenic noise could cascade through groups and populations affecting resource distribution vital for survival and fitness. Here we test the hypotheses that anthropogenic noise could alter resource distribution, associated hierarchies and consequently individual benefits. We used groups of hermit crabs, a globally distributed model system for assessing impacts of environmental change on wildlife and measured in controlled laboratory conditions the resource distribution of their reusable shelters (gastropod shells) under ship noise and ambient control playbacks. We applied vacancy chain theory to test three predictions about how new resource units create benefits for a population. A new resource unit leads to (i) a cascade of resource abandonments and acquisitions (= chain of vacancy moves) based on an internal (ii) hierarchy (here size-based) which allows (iii) more than one individual to benefit. All three predictions were supported under control sound. Under anthropogenic noise however, fewer individuals benefitted from the arrival of a new, empty shell, while the size-based hierarchy was maintained. The latter was apparent in chain structures, which were concordant between sound treatments. This experiment shows that anthropogenic noise can affect individual behaviours that cascade through groups. This has the potential to disrupt wider resource distribution in populations.

Avoidance, confusion or solitude? Modelling how noise pollution affects whale migration.

Many baleen whales are renowned for their acoustic communication. Under pristine conditions, this communication can plausibly occur across hundreds of kilometres. Frequent vocalisations may allow a dispersed migrating group to maintain contact, and therefore benefit from improved navigation via the "wisdom of the crowd". Human activities have considerably inflated ocean noise levels. Here we develop a data-driven mathematical model to investigate how ambient noise levels may inhibit whale migration. Mathematical models allow us to simultaneously simulate collective whale migration behaviour, auditory cue detection, and noise propagation. Rising ambient noise levels are hypothesised to influence navigation through three mechanisms: (i) diminished communication space; (ii) reduced ability to hear external sound cues and; (iii) triggering noise avoidance behaviour. Comparing pristine and current soundscapes, we observe navigation impairment that ranges from mild (increased journey time) to extreme (failed navigation). Notably, the three mechanisms induce qualitatively different impacts on migration behaviour. We demonstrate the model's potential predictive power, exploring the extent to which migration may be altered under future shipping and construction scenarios.

Cross-Modal Sensory Boosting to Improve High-Frequency Hearing Loss: Device Development and Validation.

Background: High-frequency hearing loss is one of the most common problems in the aging population and with those who have a history of exposure to loud noises. This type of hearing loss can be frustrating and disabling, making it difficult to understand speech communication and interact effectively with the world. Objective: This study aimed to examine the impact of spatially unique haptic vibrations representing high-frequency phonemes on the self-perceived ability to understand conversations in everyday situations. Methods: To address high-frequency hearing loss, a multi-motor wristband was developed that uses machine learning to listen for specific high-frequency phonemes. The wristband vibrates in spatially unique locations to represent which phoneme was present in real time. A total of 16 participants with high-frequency hearing loss were recruited and asked to wear the wristband for 6 weeks. The degree of disability associated with hearing loss was measured weekly using the Abbreviated Profile of Hearing Aid Benefit (APHAB). Results: By the end of the 6-week study, the average APHAB benefit score across all participants reached 12.39 points, from a baseline of 40.32 to a final score of 27.93 (SD 13.11; N=16; P=.002, 2-tailed dependent t test). Those without hearing aids showed a 10.78-point larger improvement in average APHAB benefit score at 6 weeks than those with hearing aids (t14=2.14; P=.10, 2-tailed independent t test). The average benefit score across all participants for ease of communication was 15.44 (SD 13.88; N=16; P<.001, 2-tailed dependent t test). The average benefit score across all participants for background noise was 10.88 (SD 17.54; N=16; P=.03, 2-tailed dependent t test). The average benefit score across all participants for reverberation was 10.84 (SD 16.95; N=16; P=.02, 2-tailed dependent t test). Conclusions: These findings show that vibrotactile sensory substitution delivered by a wristband that produces spatially distinguishable vibrations in correspondence with high-frequency phonemes helps individuals with high-frequency hearing loss improve their perceived understanding of verbal communication. Vibrotactile feedback provides benefits whether or not a person wears hearing aids, albeit in slightly different ways. Finally, individuals with the greatest perceived difficulty understanding speech experienced the greatest amount of perceived benefit from vibrotactile feedback.

Traffic Noise Assessment in Urban Puducherry, South India.

Background Noise pollution is an emerging global problem that can affect people's well-being and mental and physical health. In India, six percent of people suffer hearing loss, and prolonged exposure leads to irreversible noise-induced hearing loss. Objective To assess the noise levels at selected residential, commercial, industrial, silence zones, traffic junctions, and related noise indices in urban Puducherry and compare them with Central Pollution Control Board (CPCB) standards. Methods The study was conducted using a cross-sectional noise survey based on the 2015 study sites in urban Puducherry using a sound level meter, analyzed the results with limits set by the CPCB standards, and calculated the various noise indices. Results In urban Puducherry, the noise level showing silence zones is more hazardous than industrial, residential, commercial, and traffic junctions. Out of the 36 sites surveyed, 33 locations are above the prescribed daytime limit by CPCB. Conclusions The noise assessment at selected sites in urban Puducherry shows that around 92% of study sites are well above the daytime standards of CPCB, highlighting an urgent need to curb noise levels. The findings revealed that increased noise at study sites could be due to the increased number of vehicles and transportation systems.

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.

Random effect generalized linear model-based predictive modelling of traffic noise.

Noise pollution is one of the negative consequences of growth and development in cities. Traffic noise pollution due to traffic growth is the main aspect that worsens city quality of life. Therefore, research around the world is being conducted to manage and reduce traffic noise. A number of traffic noise prediction models have been proposed employing fixed effect modelling approach considering each observation as independent; however, observations may have spatial and temporal correlations and unobserved heterogeneity. Random effect models overcome these problems. This study attempts to develop a random effect generalized linear model (REGLM) along with a machine learning random forest (RF) model to validate the results, concerning the parameters related to road, traffic and environmental conditions. Models were developed based on the experimental quantities in Delhi in year 2022-2023. Both the models performed comparably well in terms of coefficient of determination. Random forest models with R2= 0.75, whereas random effect generalized linear model had an R2= 0.70. REGLM model has the ability to quantify the effects of explanatory variables over traffic noise pollution and will be more helpful in prioritizing of resources and chalking out control strategies.

Changes in bird assemblages following an outdoor music festival: A BACI (before-after-control-impact) monitoring from central Italy.

An assessment of the short-term effects of an outdoor music festival (Jova Beach Party event; July 2019; central Italy) on bird assemblages has been carried out, adopting a BACI (Before-After-Control-Impact) survey design, and using the point counts method both in the impact site (Impact, I; where the concert was held) and in comparable Control site (C). In the I site, data have been stratified both for urban (U) and agro-mosaic (M) habitats. When comparing before and after the music event, in IU site, the species richness and the Hill diversity index decreased, differently from CU where species richness a species abundance increased. Diversity profiles highlighted the impoverishment of bird assemblages after the event, but only in the Impact urban habitats. After the musical event, individual rarefaction curves for richness were lower in IU after the concert, while, differently in CU curves are higher. These data suggest an impact in bird assemblages limited to the urban site, due to the stress mainly induced by high intensity noise pollution. Musical events may disrupt the structure of synanthropic bird assemblages, inducing a dispersal of individuals towards the surrounding landscape. Starling (Sturnus vulgaris) appeared a particularly sensitive bird. However, further efforts are necessary to study the effects of these events at species level.

Cognition as a neglected mediator of responses to anthropogenic noise.

Anthropogenic noise is an increasingly pervasive global disturbance factor, with diverse biological effects. Yet, most studies have focused on population mean responses to noise pollution, leaving sources of among-individual differences in responses poorly understood. Blackburn et al. (2023) provide the first evidence from free-living animals that cognition might mediate individual differences in responses to noise pollution. In this commentary, we highlight the contribution of this ground-breaking study to stimulate more research on this important topic. We argue that cognition might mediate among-individual differences in the ability to cope with both masking effects and stress associated with noise pollution.

Anthropogenic noise predicts sea turtle behavioural responses.

Anthropogenic noise is a pollutant of global concern. While the effects of underwater noise pollution have been frequently studied in fish and mammals, our understanding of how this anthropogenic stressor affects marine reptiles is scant. Using a multichannel data logger equipped with a camera and hydrophone, we quantified behavioural responses of a free-ranging green turtle (Chelonia mydas) to vessel noise in the Galapagos Archipelago, an important nesting site in the eastern Pacific. We found that while travelling the turtle increased its vigilance with increasing vessel noise. However, when on the seabed the turtle did not increase its vigilance with increasing noise levels. Our findings illustrate that noise pollution has the potential to alter overall time budgets of animals. Identifying real-time responses of wild animals illustrate how in situ approaches allow to assess the effects of human activities on marine systems.