Probabilistic Datalog (PDatalog, proposed in 1995) is a probabilistic variant of Datalog and a nice conceptual idea to model Information Retrieval in a logical, rule-based programming paradigm. Making PDatalog work in real-world applications requires more than probabilistic facts and rules, and the semantics associated with the evaluation of the programs. We report in this paper some of the key features of the HySpirit system required to scale the execution of PDatalog programs. Firstly, there is the requirement to express probability estimation in PDatalog. Secondly, fuzzy-like predicates are required to model vague predicates (e.g. vague match of attributes such as age or price). Thirdly, to handle large data sets there are scalability issues to be addressed, and therefore, HySpirit provides probabilistic relational indexes and parallel and distributed processing. The main contribution of this paper is a consolidated view on the methods of the HySpirit system to make PDatalog applicable in real-scale applications that involve a wide range of requirements typical for data (information) management and analysis.
There is great interest in exploiting the opportunity provided by cloud computing platforms for large-scale analytics. Among these platforms, Apache Spark is growing in popularity for machine learning and graph analytics. Developing efficient complex analytics in Spark requires deep understanding of both the algorithm at hand and the Spark API or subsystem APIs (e.g., Spark SQL, GraphX). Our BigDatalog system addresses the problem by providing concise declarative specification of complex queries amenable to efficient evaluation. Towards this goal, we propose compilation and optimization techniques that tackle the important problem of efficiently supporting recursion in Spark. We perform an experimental comparison with other state-of-the-art large-scale Datalog systems and verify the efficacy of our techniques and effectiveness of Spark in supporting Datalog-based analytics.
Children with profound hearing loss can gain access to sound through cochlear implants (CIs), but these devices must be worn consistently to promote auditory development. Although subjective parent reports have identified several factors limiting long-term CI use in children, it is also important to understand the day-to-day issues which may preclude consistent device use. In the present study, objective measures gathered through datalogging software were used to quantify the following in children: (1) number of hours of CI use per day, (2) practical concerns including repeated disconnections between the external transmission coil and the internal device (termed "coil-offs"), and (3) listening environments experienced during daily use. This study aimed to (1) objectively measure daily CI use and factors influencing consistent device use in children using one or two CIs and (2) evaluate the intensity levels and types of listening environments children are exposed to during daily CI use. Retrospective analysis. Measures of daily CI use were obtained from 146 pediatric users of Cochlear Nucleus 6 speech processors. The sample included 5 unilateral, 40 bimodal, and 101 bilateral CI users (77 simultaneously and 24 sequentially implanted). Daily CI use, duration, and frequency of coil-offs per day, and the time spent in multiple intensity ranges and environment types were extracted from the datalog saved during clinic appointments. Multiple regression analyses were completed to predict daily CI use based on child-related demographic variables, and to evaluate the effects of age on coil-offs and environment acoustics. Children used their CIs for 9.86 ± 3.43 hr on average on a daily basis, with use exceeding 9 hr per day in ∼64% of the children. Daily CI use reduced significantly with increasing durations of coil-off (p = 0.027) and increased significantly with longer CI experience (p < 0.001) and pre-CI acoustic experience (p < 0.001), when controlled for the child's age. Total time in sound (sum of CI and pre-CI experience) was positively correlated with CI use (r = 0.72, p < 0.001). Longer durations of coil-off were associated with higher frequency of coil-offs (p < 0.001). The frequency of coil-offs ranged from 0.99 to 594.10 times per day and decreased significantly with age (p < 0.001). Daily CI use and frequency of coil-offs did not vary significantly across known etiologies. Listening environments of all children typically ranged between 50 and 70 dBA. Children of all ages were exposed to speech in noisy environments. Environment classified as "music" was identified more often in younger children. The majority of children use their CIs consistently, even during the first year of implantation. The frequency of coil-offs is a practical challenge in infants and young children, and demonstrates the need for improved coil retention methods for pediatric use. Longer hearing experience and shorter coil-off time facilitates consistent CI use. Children are listening to speech in noisy environments most often, thereby indicating a need for better access to binaural cues, signal processing, and stimulation strategies to aid listening. Study findings could be useful in parent counseling of young and/or new CI users.
The primary aim was to compare the objective and the subjective assessments of hearing aid use among elderly people at a 6-month follow-up after fitting. A secondary aim was to determine whether advanced knowledge of follow-up impacts hearing aid use. Hearing aid use was assessed by datalogging (objective) and self-report (subjective) 6 months after initial fitting. Participants were also randomised to an intervention (informed of 6-month follow-up at fitting) or control group (informed just prior to follow-up). A total of 181 hearing aid recipients ≥60 years (mean age = 79.2 years). Daily hearing aid use based on datalogging (mean = 6.12 h, SD = 4.94) was significantly less than self-reports (mean = 8.39 h, SD = 5.07). More severe hearing impairment and prior hearing aid experience were associated with increased hearing aid use. Advanced knowledge of the follow-up had no significant impact on use, which did not differ between intervention (n = 93) and control (n = 88) groups. Elderly people typically use their hearing aids for a substantial part of the day in the 6 months after fitting, but tend to overestimate their usage. Datalogging is recommended to identify those who do not use or rarely use their aids so that appropriate rehabilitation and support can be provided.
Objectives: This study sought to determine if children's auditory environments are accurately captured by the automatic scene classification embedded in cochlear implant (CI) processors and to quantify the amount of electronic device use in these environments. Methods: Seven children with CIs, 36.71 (SD = 11.94) months old, participated in this study. Three of the children were male and four were female. Eleven datalogs, containing outcomes from Cochlear's™ Nucleus® 6 (Cochlear Corporation, Australia) CI scene classification algorithm, and seven day-long audio recordings collected with a Language ENvironment Analysis (LENA; LENA Research Foundation, USA) recorder were obtained for analysis. Results: Results from the scene classification algorithm were strongly correlated with categories determined through human coding (ICC = .86, CI = [-0.2, 1], F(5,5.1) = 5.9, P = 0.04) but some differences emerged. Scene classification identified more 'Quiet' (t(8.2) = 4.1, P = 0.003) than human coders, while humans identified more 'Speech' (t(10.6) = -2.4, P = 0.04). On average, 8% (SD = 5.8) of the children's day was spent in electronic sound, which was primarily produced by mobile devices (39.7%). Discussion: While CI scene classification software reflects children's natural auditory environments, it is important to consider how different scenes are defined when interpreting results. An electronic sounds category should be considered given how often children are exposed to such sounds.
Recent growth in public bioinformatic databases has facilitated the analysis of genomic and proteomic data. However, the large size of the datasets makes it hard for nonexpert programmers to perform the analysis. In this paper we present B-Log, a high-level query language for bioinformatic data analysis. Based on Datalog, B-Log can simply express graph analysis algorithms; it is extended with nested tables, recursive aggregations, and foreign functions, which helps quick exploratory analyses. We implemented several analysis algorithms in B-Log; we also implemented a prototype system to explore TCGA dataset. We find B-Log to be useful for exploratory analysis and quick prototyping.
To understand the varying levels of daily cochlear implant (CI) use in children, previous studies have investigated factors that may be of influence. The objective of this study was to investigate the degree with which new child-related and environment-related characteristics were associated with consistent CI use. The design of this study was retrospective. Data were reviewed of 81 children (51% females, mean age 6.4 years with a range of 1.3 to 17.7 years) who received a CI between 2012 and 2019. Developmental status, quantified burden of comorbidity, hearing experience, and hearing environment were investigated for correlation with consistency in daily CI use. The CIs datalog was used to objectively record the wearing times. Associations were examined using univariate correlation analyses and a linear regression analysis. On average, the CI was worn 8.6 hr per day and 59% of the children wore it more than 8 hr daily. The latter children's hearing performance was significantly higher than that of the others. Consistency in CI use correlated significantly with the child-related characteristics chronological age, nonverbal intelligence quotient (IQ), American Society of Anesthesiologists physical status class, pre CI acoustic experience, CI experience, and one of the environment related characteristics "parental communication mode." In a multivariate linear regression model, consistency in CI use was significantly dependent on nonverbal IQ and parental communication mode. These together accounted for 47% of the variation in daily CI use. The findings indicate that children with lower nonverbal IQ scores and low exposure to oral communication by their parents are at risk of inconsistent CI use.
Cochlear implants (CIs) give children with severe to profound hearing loss access to sound. There appears to be a dose effect of sound exposure on speech perception abilities as shown by the positive influence of early implantation and CI experience. The consistency in device use per day could also affect sound dose, potentially affecting perceptual abilities in children with CIs. The objectives of the present study were to identify the impact of consistency in device use on: (1) speech perception abilities and (2) asymmetry in speech perception abilities between bilateral CIs. Retrospective analysis. To achieve the first objective, data from 65 children (age range at speech test: 1.91-18.05 yrs) with one (unilaterally implanted or bimodal) or two CIs (sequentially or simultaneously implanted) were included. A subset of data from 40 children with bilateral CIs was included to achieve the second objective. Of the 40 children with two CIs, 15 received their CIs sequentially. Device use information was extracted from datalogs stored in personal speech processors using custom software. Speech perception scores per CI collected in quiet were also evaluated. Multiple regression was used to assess the impact of daily CI use, while controlling for factors previously identified to affect speech perception: age at speech test, length of pre-CI (acoustic) hearing experience, length of CI hearing experience, and order of CI for the first objective, and CI category (simultaneous/sequential implantation), interimplant delay, and length of CI experience for the second objective. On average, children wore their CIs for 11.59 ± 2.86 hours/day and, with one CI, exhibited 65.07 ± 22.64% accuracy on speech perception tests. Higher monaural speech perception scores were associated with longer everyday CI use and CI experience (p < 0.05). Among children with bilateral CIs, those with simultaneously implanted CIs and similar bilateral hearing experience demonstrated a small but significant right ear advantage with higher speech perception scores when using the right rather than left CI (mean difference = 4.55 ± 9.83%). The asymmetry in speech perception between CIs was larger and more variable in children who received their CIs sequentially (mean difference CI1-CI2 = 27.48 ± 24.87%). These asymmetries decreased with longer/consistent everyday use of the newer CI (p < 0.05). Yet, despite consistent everyday device use of the second CI (>12 hours/day), only a small proportion of children implanted sequentially (one out of seven children) achieved symmetrical function similar to children with simultaneously received bilateral CIs. Consistent everyday CI use contributes to higher speech perception scores. Although consistent CI use can help reduce the asymmetry in speech perception abilities of children with sequentially implanted CIs subsequent to interimplant delay, residual asymmetry often persists.
This study evaluated whether Coronavirus disease 2019 (COVID-19)-related decreases in device use and speech exposure in children with unilateral cochlear implants (CIs) persisted post-pandemic. It was hypothesized that CI use is lower in children with single-sided deafness (SSD) than in children using bimodal devices and that speech exposure has recovered to pre-pandemic levels. Datalogs (n = 608) from children with unilateral CIs (n = 111) and good hearing in their non-implanted ear (unaided pure tone average <60 dB) were analyzed across the pre-pandemic, peri-pandemic (during the pandemic), and post-pandemic periods. Participants were separated into children with single-sided deafness using a CI (SSD-CI group, n = 70), and children using a CI and contralateral hearing aid (bimodal devices group, n = 41). They were further divided by age at the start of the pandemic (preschool-aged and school-aged). Datalogs were collected from October 1, 2013 to April 1, 2024, and included daily CI use, speech duration, and speech-in-noise sounds captured by the CI. CI use was lower in the SSD-CI group (mean ± SD = 5.78 ± 3.06 hours/day) than in the bimodal devices group (7.24 ± 3.75 hours/day, p = 0.013). In addition, of 17 children lost to follow-up, 14 were in the SSD-CI group. Preschool-aged children showed a steeper increase in CI use over time from CI activation in the bimodal devices group (slope ± SE = 0.96 ± 0.14 hours/day per year) than the SSD-CI group (0.15 ± 0.19 hours/day per year, p < 0.001). CI use declined more rapidly over time in school-aged children in the SSD-CI group (-0.63 ± 0.09 hours/day per year) compared to the bimodal devices group (-0.07 ± 0.09 hours/day per year, p < 0.001). Speech exposure was similar in the SSD-CI (3.13 ± 1.83 hours/day) and bimodal devices (3.82 ± 2.11 hours/day) groups ( p = 0.08). In preschool-aged children, speech exposure increased from the pre-pandemic (3.11 ± 1.44 hours/day) to the peri-pandemic (3.51 ± 2.21 hours/day, p = 0.011) and post-pandemic period (4.53 ± 1.84 hours/day, p < 0.001) in line with increased daily CI use. In school-aged children, speech exposure decreased from the pre-pandemic (3.38 ± 1.76 hours/day) to the peri-pandemic period (2.94 ± 2.16 hours/day, p = 0.002), remaining low post-pandemic (2.91 ± 2.45 hours/day, p = 0.69). The proportion of speech exposure measured by the CI decreased from the pre-pandemic period (52.5% ± 12.2%, p = 0.99) to the peri-pandemic period (44.7% ± 16.1%, p = 0.008) and returned to pre-pandemic levels post-pandemic (51.9% ± 17.3%, p = 0.55). Daily CI use varies widely in children with good residual hearing in their non-implanted ear and is at greater risk for decline over time in the SSD-CI group compared to the bimodal device users. Reduced CI use in school-aged children with SSD leads to decreased hours of speech exposure through the CI. The percentage of speech exposure logged by the CI confirms that speech access declined during the pandemic but reveals an encouraging return to pre-pandemic levels after restrictions were lifted.
This study aimed to explore how the consistency of hearing aid (HA) use impacts vocabulary performance in children with moderately severe to profound hearing loss and determine the amount of HA use time associated with better vocabulary outcomes. Personal wear time percentage (WTP) was an indicator of HA use consistency, and the information on HA wear time was collected from both parent reports and datalogs. Pearson's correlations were performed to investigate the associations between hearing loss severity, WTP and vocabulary performance. Standard vocabulary scores among children below and above three WTP cutoff values (80%, 85%, and 90%) were examined to determine the WTP amount that yielded significantly better vocabulary outcomes. Forty-seven children aged 36-79 months and their caregivers. Both parent reports and datalogs WTP significantly correlated with vocabulary outcomes. Parent-reported WTP were found to be predictive of datalogs WTP. Apart from hearing thresholds, HA fitting age and maternal education level, datalogs WTP was a significant independent predictor of vocabulary performance. Children with ≥ 90% WTP were more likely to perform better on vocabulary tests than those with < 90% WTP. The findings support the potential benefits of consistent HA use for vocabulary development.
The individual mapping of cochlear implants (CIs) aims to optimize the user's speech understanding. Recent investigations have shown the importance of soft speech: (1) According to Datalog studies, a large proportion of speech components lies in the range below 60 dB, and (2) soft speech represents a separate category in CI outcome, in addition to supra-threshold speech and speech in noise. Soft-speech understanding can be influenced by optimizing T-values or by global parameters (loudness growth and TSPL in the Nucleus system). This study focussed on improving soft speech below 60 dB by optimizing loudness growth. Speech understanding with varying loudness growth in the speech processor CP11 (Cochlear Ltd.) was compared in 20 experienced adult CI users. The mean soft-speech score based on monosyllabic words at 40 and 50 dB was introduced for quantification. Six of the 20 patients studied showed significant individual improvement for soft speech when loudness growth was optimized, while none showed a significant decrease under quiet or noisy test conditions. Actual CI systems offer a broad loudness range of speech understanding. In addition to suprathreshold speech understanding, additional attention should be paid to soft speech, and the result should therefore be confirmed by speech audiometry at low levels. 2.
The aim of the current study was to investigate the use of manually and automatically switching programs in everyday day life by adult cochlear implant (CI) users. Participants were fitted with an automatically switching sound processor setting and 2 manual programs for 3-week study periods. They received an extensive counselling session. Datalog information was used to analyse the listening environments identified by the sound processor, the program used and the number of program switches. Fifteen adult Cochlear CI users. Average age 69 years (range: 57-85 years). Speech recognition in noise was significantly better with the "noise" program than with the "quiet" program. On average, participants correctly classified 4 out of 5 listening environments in a laboratory setting. Participants switched, on average, less than once a day between the 2 manual programs and the sound processor was in the intended program 60% of the time. Adult CI users switch rarely between two manual programs and leave the sound processor often in a program not intended for the specific listening environment. A program that switches automatically between settings, therefore, seems to be a more appropriate option to optimise speech recognition performance in daily listening environments.
School closures and other COVID-19-related restrictions could decrease children's exposure to speech during important stages of development. To assess whether significant decreases in exposure to spoken communication found during the initial phase of the COVID-19 pandemic among children using cochlear implants are confirmed for a larger cohort of children and were sustained over the first years of the COVID-19 pandemic. This cohort study used datalogs collected from children with cochlear implants during clinical visits to a tertiary pediatric hospital in Toronto, Ontario, Canada, from January 1, 2018, to November 11, 2021. Children with severe to profound hearing loss using cochlear implants were studied because their devices monitored and cataloged levels and types of sounds during hourly use per day (datalogs) and because their hearing and spoken language development was particularly vulnerable to reduced sound exposure. Statistical analyses were conducted between January 2022 and August 2023. Daily hours of sound were captured by the cochlear implant datalogging system and categorized into 6 auditory scene categories, including speech and speech-in-noise. Time exposed to speech was calculated as the sum of daily hours in speech and daily hours in speech-in-noise. Residual hearing in the ear without an implant of children with unilateral cochlear implants was measured by pure tone audiometry. Mixed-model regression analyses revealed main effects with post hoc adjustment of 95% CIs using the Satterthwaite method. Datalogs (n = 2746) from 262 children (137 with simultaneous bilateral cochlear implants [74 boys (54.0%); mean (SD) age, 5.8 (3.5 years)], 38 with sequential bilateral cochlear implants [24 boys (63.2%); mean (SD) age, 9.1 (4.2) years], and 87 with unilateral cochlear implants [40 boys (46.0%); mean (SD) age, 7.9 (4.6) years]) who were preschool aged (n = 103) and school aged (n = 159) before the COVID-19 pandemic were included in analyses. There was a slight increase in use among preschool-aged bilateral cochlear implant users through the pandemic (early pandemic, 1.4 h/d [95% CI, 0.3-2.5 h/d]; late pandemic, 2.3 h/d [95% CI, 0.6-4.0 h/d]) and little change in use among school-aged bilateral cochlear implant users (early pandemic, -0.6 h/d [95% CI, -1.1 to -0.05 h/d]; late pandemic, -0.3 h/d [95% CI, -0.9 to 0.4 h/d]). However, use decreased during the late pandemic period among school-aged children with unilateral cochlear implants (-1.8 h/d [95% CI,-3.0 to -0.6 h/d]), particularly among children with good residual hearing in the ear without an implant. Prior to the pandemic, children were exposed to speech for approximately 50% of the time they used their cochlear implants (preschool-aged children: bilateral cochlear implants, 46.6% [95% CI, 46.5%-47.2%] and unilateral cochlear implants, 52.1% [95% CI, 50.7%-53.5%]; school-aged children: bilateral cochlear implants, 47.6% [95% CI, 46.8%-48.4%] and unilateral cochlear implants, 51.0% [95% CI, 49.4%-52.6%]). School-aged children in both groups experienced significantly decreased speech exposure in the early pandemic period (bilateral cochlear implants, -12.1% [-14.6% to -9.4%]; unilateral cochlear implants, -15.5% [-20.4% to -10.7%]) and late pandemic periods (bilateral cochlear implants, -5.3% [-8.0% to -2.6%]; unilateral cochlear implants, -11.2% [-15.3% to -7.1%]) compared with the prepandemic baseline. This cohort study using datalogs from children using cochlear implants suggests that a sustained reduction in children's access to spoken communication was found during more than 2 years of COVID-19 pandemic-related lockdowns and school closures.
Over the past few years, several efforts have been made to enable specification and enforcement of flexible and dynamic access control policies using traditional access control (such as role based access control (RBAC), etc.) and attribute based access control (ABAC). Recently, a unified framework, named MPBAC (meta-policy based access control), has been developed to enable specification and enforcement of heterogeneous access control policies such as ABAC, RBAC and a combination of policies (such as ABAC and RBAC). However, one significant limitation is that no complete administrative model has been developed for heterogeneous access control policies. In this article, we present a complete role-based administrative model (named as RAMHAC) for managing heterogeneous access control policies. We also introduce a novel methodology for analyzing heterogeneous access control policies in the presence of RAMHAC by modeling the policies through Datalog facts and using the μz tool. The administrative model includes a wide range of administrative relations, commands, pre-constraints and post-constraints. A comprehensive experimental evaluation demonstrates the scalability of the proposed approach.
Proteomic profiles reflect the functional readout of the physiological state of an organism. An increased understanding of what controls and defines protein abundances is of high scientific interest. Saccharomyces cerevisiae is a well-studied model organism, and there is a large amount of structured knowledge on yeast systems biology in databases such as the Saccharomyces Genome Database, and highly curated genome-scale metabolic models like Yeast8. These datasets, the result of decades of experiments, are abundant in information, and adhere to semantically meaningful ontologies. By representing this knowledge in an expressive Datalog database we generated data descriptors using relational learning that, when combined with supervised machine learning, enables us to predict protein abundances in an explainable manner. We learnt predictive relationships between protein abundances, function and phenotype; such as α-amino acid accumulations and deviations in chronological lifespan. We further demonstrate the power of this methodology on the proteins His4 and Ilv2, connecting qualitative biological concepts to quantified abundances. All data and processing scripts are available at the following Github repository: https://github.com/DanielBrunnsaker/ProtPredict.
Gut microbiota plays a crucial role in modulating pig development and health, and gut microbiota characteristics are associated with differences in feed efficiency. To answer open questions in feed efficiency analysis, biologists seek to retrieve information across multiple heterogeneous data sources. However, this is error-prone and time-consuming work since the queries can involve a sequence of multiple sub-queries over several databases. We present an implementation of an ontology-based Swine Gut Microbiota Federated Query Platform (SGMFQP) that provides a convenient, automated, and efficient query service about swine feeding and gut microbiota. The system is constructed based on a domain-specific Swine Gut Microbiota Ontology (SGMO), which facilitates the construction of queries independent of the actual organization of the data in the individual sources. This process is supported by a template-based query interface. A Datalog+-based federated query engine transforms the queries into sub-queries tailored for each individual data source, and an automated workflow orchestration mechanism executes the queries in each source database and consolidates the results. The efficiency of the system is demonstrated on several swine feeding scenarios.
Candidacy criteria for cochlear implantation in the United States has expanded to include children with single-sided deafness (SSD) who are at least 5 years of age. Pediatric cochlear implant (CI) users with SSD experience improved speech recognition with increased daily device use. There are few studies that report the hearing hour percentage (HHP) or the incidence of non-use for pediatric CI recipients with SSD. The aim of this study was to investigate factors that impact outcomes in children with SSD who use CIs. A secondary aim was to identify factors that impact daily device use in this population. A clinical database query revealed 97 pediatric CI recipients with SSD who underwent implantation between 2014 and 2022 and had records of datalogs. The clinical test battery included speech recognition assessment for CNC words with the CI-alone and BKB-SIN with the CI plus the normal-hearing ear (combined condition). The target and masker for the BKB-SIN were presented in collocated and spatially separated conditions to evaluate spatial release from masking (SRM). Linear mixed-effects models evaluated the influence of time since activation, duration of deafness, HHP, and age at activation on performance (CNC and SRM). A separate linear mixed-effects model evaluated the main effects of age at testing, time since activation, duration of deafness, and onset of deafness (stable, progressive, or sudden) on HHP. Longer time since activation, shorter duration of deafness, and higher HHP were significantly correlated with better CNC word scores. Younger age at device activation was not found to be a significant predictor of CNC outcomes. There was a significant relationship between HHP and SRM, with children who had higher HHP experiencing greater SRM. There was a significant negative correlation between time since activation and age at test with HHP. Children with sudden hearing loss had a higher HHP than children with progressive and congenital hearing losses. The present data presented here do not support a cut-off age or duration of deafness for pediatric cochlear implantation in cases of SSD. Instead, they expand on our understanding of the benefits of CI use in this population by reviewing the factors that influence outcomes in this growing patient population. Higher HHP, or greater percentage of time spent each day using bilateral input, was associated with better outcomes in the CI-alone and in the combined condition. Younger children and those within the first months of use had higher HHP. Clinicians should discuss these factors and how they may influence CI outcomes with potential candidates with SSD and their families. Ongoing work is investigating the long-term outcomes in this patient population, including whether increasing HHP after a period of limited CI use results in improved outcomes.
Researchers in neuroscience have a growing number of datasets available to study the brain, which is made possible by recent technological advances. Given the extent to which the brain has been studied, there is also available ontological knowledge encoding the current state of the art regarding its different areas, activation patterns, keywords associated with studies, etc. Furthermore, there is inherent uncertainty associated with brain scans arising from the mapping between voxels-3D pixels-and actual points in different individual brains. Unfortunately, there is currently no unifying framework for accessing such collections of rich heterogeneous data under uncertainty, making it necessary for researchers to rely on ad hoc tools. In particular, one major weakness of current tools that attempt to address this task is that only very limited propositional query languages have been developed. In this paper we present NeuroLang, a probabilistic language based on first-order logic with existential rules, probabilistic uncertainty, ontologies integration under the open world assumption, and built-in mechanisms to guarantee tractable query answering over very large datasets. NeuroLang's primary objective is to provide a unified framework to seamlessly integrate heterogeneous data, such as ontologies, and map fine-grained cognitive domains to brain regions through a set of formal criteria, promoting shareable and highly reproducible research. After presenting the language and its general query answering architecture, we discuss real-world use cases showing how NeuroLang can be applied to practical scenarios.
The coronavirus disease 2019 (COVID-19) lockdowns in Ontario, Canada in the spring of 2020 created unprecedented changes in the lives of all children, including children with hearing loss. To quantify how these lockdowns changed the spoken communication environments of children with cochlear implants by comparing the sounds they were exposed to before the Ontario provincial state of emergency in March 2020 and during the resulting closures of schools and nonessential businesses. This experimental cohort study comprised children with hearing loss who used cochlear implants to hear. These children were chosen because (1) their devices monitor and catalog levels and types of sounds during hourly use per day (datalogs), and (2) this group is particularly vulnerable to reduced sound exposure. Children were recruited from the Cochlear Implant Program at a tertiary pediatric hospital in Ontario, Canada. Children whose cochlear implant datalogs were captured between February 1 and March 16, 2020, shortly before lockdown (pre-COVID-19), were identified. Repeated measures were collected in 45 children during initial easing of lockdown restrictions (stages 1-2 of the provincial recovery plan); resulting datalogs encompassed the lockdown period (peri-COVID-19). Hours of sound captured by the Cochlear Nucleus datalogging system (Cochlear Corporation) in 6 categories of input levels (<40, 40-49, 50-59, 60-69, 70-79, ≥80 A-weighted dB sound pressure levels [dBA]) and 6 auditory scene categories (quiet, speech, speech-in-noise, music, noise, and other). Mixed-model regression analyses revealed main effects with post hoc adjustment of confidence intervals using the Satterthwaite method. A total of 45 children (mean [SD] age, 7.7 [5.0] years; 23 girls [51.1%]) participated in this cohort study. Results showed similar daily use of cochlear implants during the pre- and peri-COVID-19 periods (9.80 mean hours pre-COVID-19 and 9.34 mean hours peri-COVID-19). Despite consistent device use, these children experienced significant quieting of input sound levels peri-COVID-19 by 0.49 hour (95% CI, 0.21-0.80 hour) at 60 to 69 dBA and 1.70 hours (95% CI, 1.42-1.99 hours) at 70 to 79 dBA with clear reductions in speech exposure by 0.98 hour (95% CI, 0.49-1.47 hours). This outcome translated into a reduction of speech:quiet from 1.6:1.0 pre-COVID-19 to 0.9:1.0 during lockdowns. The greatest reductions in percentage of daily speech occurred in school-aged children (elementary, 12.32% [95% CI, 7.15%-17.49%]; middle school, 11.76% [95% CI, 5.00%-18.52%]; and high school, 9.60% [95% CI, 3.27%-15.93%]). Increased daily percentage of quiet (7.00% [95% CI, 4.27%-9.74%]) was most prevalent for children who had fewer numbers of people in their household (estimate [SE] = -1.12% [0.50%] per person; Cohen f = 0.31). The findings of this cohort study indicate a clear association of COVID-19 lockdowns with a reduction in children's access to spoken communication.
Different muscular activities of the quadriceps components for producing necessary torque may change in patients with patellofemoral pain syndrome (PFPS). The aim of the current study, therefore, was to assess the contribution of each component of the quadriceps femoris muscle for producing external torque in patients with PFPS. Twelve females with PFPS (24.7 ± 2.3 years) and twelve healthy matched females (25.4 ± 2.4 years) performed three consecutive knee flexion and extension movements with maximum effort at 45°/s and 300°/s using a Biodex system 3 dynamometer. Simultaneously, electromyographic (EMG) activities of the vastus medialis oblique (VMO), RF (rectus femoris) and vastus lateralis (VL) muscles were recorded using a DataLog instrument. Standard multiple regressions were used to assess the ability of EMG activities of the VMO, RF and VL muscles to predict normalized quadriceps femoris isokinetic concentric and eccentric torques at 45°/s and 300°/s in the normal and patient groups. In the normal group, the VL and the VMO were the good predictors of quadriceps concentric torque at 45°/s and 300°/s, respectively. The VL and the RF were the good predictors of quadriceps eccentric torque at 300°/s in the patient group. No other conditions showed a considerable prediction for quadriceps torque in the normal or patient group. Females with PFPS differ with normal females in terms of the contribution of each component of the quadriceps femoris for producing external torque. Training the VMO for concentric contraction at both high and low velocities should be included in the management of the patients with PFPS.