Comparison of the effects of reef and anthropogenic soundscapes on oyster larvae settlement.

Settlement is a critical period in the life cycle of marine invertebrates with a planktonic larval stage. For reef-building invertebrates such as oysters and corals, settlement rates are predictive for long-term reef survival. Increasing evidence suggests that marine invertebrates use information from ocean soundscapes to inform settlement decisions. Sessile marine invertebrates with a planktonic stage are particularly reliant on environmental cues to direct them to ideal habitats. As gregarious settlers, oysters prefer to settle amongst members of the same species. It has been hypothesized that oyster larvae from species Crassostrea virginica and Ostrea angasi use distinct conspecific oyster reef sounds to navigate to ideal habitats. In controlled laboratory experiments we exposed Pacific Oyster Magallana gigas larvae to anthropogenic sounds from conspecific oyster reefs, vessels, combined reef-vessel sounds as well as off-reef and no speaker controls. Our findings show that sounds recorded at conspecific reefs induced higher percentages of settlement by about 1.44 and 1.64 times compared to off-reef and no speaker controls, respectively. In contrast, the settlement increase compared to the no speaker control was non-significant for vessel sounds (1.21 fold), combined reef-vessel sounds (1.30 fold), and off-reef sounds (1.18 fold). This study serves as a foundational stepping stone for exploring larval sound feature preferences within this species.

Classification of Targets and Distractors in an Audiovisual Attention Task Based on Electroencephalography.

Within the broader context of improving interactions between artificial intelligence and humans, the question has arisen regarding whether auditory and rhythmic support could increase attention for visual stimuli that do not stand out clearly from an information stream. To this end, we designed an experiment inspired by pip-and-pop but more appropriate for eliciting attention and P3a-event-related potentials (ERPs). In this study, the aim was to distinguish between targets and distractors based on the subject's electroencephalography (EEG) data. We achieved this objective by employing different machine learning (ML) methods for both individual-subject (IS) and cross-subject (CS) models. Finally, we investigated which EEG channels and time points were used by the model to make its predictions using saliency maps. We were able to successfully perform the aforementioned classification task for both the IS and CS scenarios, reaching classification accuracies up to 76%. In accordance with the literature, the model primarily used the parietal-occipital electrodes between 200 ms and 300 ms after the stimulus to make its prediction. The findings from this research contribute to the development of more effective P300-based brain-computer interfaces. Furthermore, they validate the EEG data collected in our experiment.

Learnable axonal delay in spiking neural networks improves spoken word recognition.

Spiking neural networks (SNNs), which are composed of biologically plausible spiking neurons, and combined with bio-physically realistic auditory periphery models, offer a means to explore and understand human auditory processing-especially in tasks where precise timing is essential. However, because of the inherent temporal complexity in spike sequences, the performance of SNNs has remained less competitive compared to artificial neural networks (ANNs). To tackle this challenge, a fundamental research topic is the configuration of spike-timing and the exploration of more intricate architectures. In this work, we demonstrate a learnable axonal delay combined with local skip-connections yields state-of-the-art performance on challenging benchmarks for spoken word recognition. Additionally, we introduce an auxiliary loss term to further enhance accuracy and stability. Experiments on the neuromorphic speech benchmark datasets, NTIDIDIGITS and SHD, show improvements in performance when incorporating our delay module in comparison to vanilla feedforward SNNs. Specifically, with the integration of our delay module, the performance on NTIDIDIGITS and SHD improves by 14% and 18%, respectively. When paired with local skip-connections and the auxiliary loss, our approach surpasses both recurrent and convolutional neural networks, yet uses 10 × fewer parameters for NTIDIDIGITS and 7 × fewer for SHD.

The Influence of Everyday Acoustic Environments on the Challenging Behavior in Dementia: A Participatory Observation Study in Nursing Homes.

Challenging behavior (CB) is a group of behaviors, reactions and symptoms due to dementia, which can be challenging for the caregivers. The study aims to research the influence of acoustics on CB in people with dementia (PwD). An ethnographic method was used to study the daily life of PwD in their nursing homes with a specific focus on how people react to everyday environmental sounds. Thirty-five residents were included in the sample based on purposeful, homogeneous group characteristics and sampling. Empirical data were collected using 24/7 participatory observations. The collected data were analyzed using a phenomenological-hermeneutical method: a naïve understanding, a structural analysis and a comprehensive understanding. The result shows that the onset of CB depends on whether the resident feels safe and is triggered by an excess or lack of stimuli. The excess or shortage of stimuli and whether and when it affects a person is personal. It depends on various factors, the person's state and the time of day, the nature of the stimuli, familiarity, or strangeness is also a determining factor for the onset and progression of CB. The results can form an essential basis for developing soundscapes to make the PwD feel safe and reduce CB.

With No Attention Specifically Directed to It, Rhythmic Sound Does Not Automatically Facilitate Visual Task Performance.

In a century where humans and machines-powered by artificial intelligence or not-increasingly work together, it is of interest to understand human processing of multi-sensory stimuli in relation to attention and working memory. This paper explores whether and when supporting visual information with rhythmic auditory stimuli can optimize multi-sensory information processing. In turn, this can make the interaction between humans or between machines and humans more engaging, rewarding and activating. For this purpose a novel working memory paradigm was developed where participants are presented with a series of five target digits randomly interchanged with five distractor digits. Their goal is to remember the target digits and recall them orally. Depending on the condition support is provided by audio and/or rhythm. It is expected that the sound will lead to a better performance. It is also expected that this effect of sound is different in case of rhythmic and non-rhythmic sound. Last but not least, some variability is expected across participants. To make correct conclusions, the data of the experiment was statistically analyzed in a classic way, but also predictive models were developed in order to predict outcomes based on a range of input variables related to the experiment and the participant. The effect of auditory support could be confirmed, but no difference was observed between rhythmic and non-rhythmic sounds. Overall performance was indeed affected by individual differences, such as visual dominance or perceived task difficulty. Surprisingly a music education did not significantly affect the performance and even tended toward a negative effect. To better understand the underlying processes of attention, also brain activation data, e.g., by means of electroencephalography (EEG), should be recorded. This approach can be subject to a future work.

IoT snoring sound detector prototype as a model of future participatory healthcare.

BACKGROUND: Traditional healthcare is centred around providing in-hospital services using hospital owned medical instruments. The COVID-19 pandemic has shown that this approach lacks flexibility to insure follow-up and treatment of common medical problems. In an alternative setting adapted to this problem, participatory healthcare can be considered centred around data provided by patients owning and operating medical data collection equipment in their homes. OBJECTIVE: In order to trigger such a shift reliable and price attractive devices need to become available. Snoring, as a human sound production during sleep, can reflect sleeping behaviour and indicate sleep problems as an element of the overall health condition of a person. METHODS: The use of off-the-shelf hardware from Internet of Things platforms and standard audio components allows the development of such devices. A prototype of a snoring sound detector with this purpose is developed. RESULTS: The device, controlled by the patient and with specific snoring recording and analysing functions is demonstrated as a model for future participatory healthcare. CONCLUSIONS: Design of monitoring devices following this model could allow market introduction of new equipment for participatory healthcare, bringing a care complementary to traditional healthcare to the reach of patients, and could result in benefits from enhanced patient participation.

Designing Supportive Soundscapes for Nursing Home Residents with Dementia.

Sound and its resulting soundscape is a major appraisal component of the living environment. Where environmental sounds (e.g., outdoor traffic sounds) are often perceived as negative, a soundscape (e.g., containing natural sounds) can also have a positive effect on health and well-being. This supportive effect of a soundscape is getting increasing attention for use in practice. This paper addresses the design of a supportive sonic environment for persons with dementia in nursing homes. Starting from a review of key mechanisms related to sonic perception, cognitive deficits and related behavior, a framework is derived for the composition of a sonic environment for persons with dementia. The proposed framework is centered around using acoustic stimuli for influencing mood, stimulating the feeling of safety and triggering a response in a person. These stimuli are intended to be deployed as added sounds in a nursing home to improve the well-being and behavior of the residents.

Cognitive impairment screening using m-health: an android implementation of the mini-mental state examination (MMSE) using speech recognition.

PURPOSE: This paper describes an implementation of an Android application that allows cognitive functions to be tested. METHODS: The application consists of a slightly modified Mini Mental state Examination (MMSE) test that provides examiner assistance in diagnosing cognitive impairments. The application deploys speech recognition techniques to allow easy and automated scoring of the test. The test results and test-related information are stored in a database providing easy access to data for follow-up and analysis, resulting in overall benefits to the examiner workflow. A small-scale pilot study of 5 months duration was conducted in a nursing home where 15 residents were tested with the MMSE app test and with the (paper) MMSE test with the aim of determining the agreement between the two test methods. RESULTS: The final MMSE test scores, with a maximum score of 30, agree; the differences have a mean of 0.1, a standard deviation of 2.1 and fall in a [- 4, + 4] range as is illustrated in a Bland-Altman analysis. From examiner reflections, the motoric skills of the participant are indicated to contribute strongly to the time benefit of the assessment itself. CONCLUSIONS: The findings of this study suggest that the mobile digital version of the slightly modified MMSE test has the potential to be used as an attractive alternative for the conventional paper version of the test.

Dickeya aquatica sp. nov., isolated from waterways.

Pectinolytic Gram-negative bacteria were isolated from different waterways in the UK and Finland. Three strains (174/2(T), 181/2 and Dw054) had the same 16S rRNA gene sequences which shared 99% sequence similarity to species of the genus Dickeya, and a phylogeny of related genera confirmed attribution to this genus. Fatty acid profile analysis of all three strains found a high proportion of C16 : 1ω7c/C16 : 1ω7c and C16 : 0 fatty acids, and library profile searches found closest matches to Dickeya chrysanthemi. Production of a concatenated phylogeny using six loci, recA, gapA, atpD, gyrB, infB and rpoB, provided a high-resolution phylogeny which placed strains 174/2(T) and 181/2 as a distinct clade, separated from the other species of the genus Dickeya by a relatively long branch-length. DNA-DNA hybridization analysis with a limited number of reference species also supported the distinctiveness of strains 174/2(T) and 181/2 within the genus Dickeya. All three strains could be phenotypically distinguished from other species of the genus by fermentation of melibiose and raffinose but not D-arabinose or mannitol. The name Dickeya aquatica sp. nov. is proposed for the new taxon; the type strain is 174/2(T) ( = NCPPB 4580(T) = LMG 27354(T)).

Numerical assessment of the impact of a flow wire on its velocity measurements.

Blood flow velocities can be measured using a Doppler flow wire. This numerical study evaluates the impact of a 0.014" flow wire on the measured frequencies in a straight artery with diameters of 3 mm and 4 mm, under steady and pulsatile flow conditions. Simulations were performed with the wires positioned differently in the artery (perfectly centred and at an offset of 0.5 mm from the wall) and with different types of wire (tilted and straight). Measurements were taken at range gates from 4 mm to 10 mm. During simulations using a 3-mm vessel under pulsatile flow conditions, the relative error between the measured and reference maximum frequency (occurring in absence of the wire) decreased from 17.7% to 11.6% (with a mean value of 14.9%). During simulations using an off-centre 1.5 degree tilted wire, the mean error was approximately 5%. Therefore, our study suggests that that a centrally positioned flow wire is unfavourable for measuring flow velocities.

Polyphasic characterization of Bacillus coagulans strains, illustrating heterogeneity within this species, and emended description of the species.

Because of its food spoiling capacity on the one hand and its significant role in the production of industrially valuable products on the other, Bacillus coagulans is of economic concern. Several studies have revealed a great deal of diversity within the species and this has led to a number of taxonomic adjustments. The present study aims to clarify the diversity within Bacillus coagulans sensu stricto and determine the taxonomic status of the species. Therefore, a polyphasic study was performed on a set of B. coagulans strains from diverse habitats. Techniques as ARDRA, SDS-PAGE of whole cell proteins, FAME analysis, routine phenotypic tests and rep-PCR illustrate considerable intra-species heterogeneity, while 16S rDNA sequence comparison and DNA-DNA relatedness support the accommodation of these strains in one species. Although most techniques demonstrate appreciable heterogeneity among the Bacillus coagulans strains, the intraspecies groupings are not consistent throughout all the methods applied and are not supported by any economic, historic or practical traits. Therefore, a division in subspecies seems inappropriate. In attempt to achieve a better species delineation, an emended description of Bacillus coagulans is included.