Neighborhood Density Research Articles

Phonological neighbourhood effects in Italian speech production: Evidence from healthy and neurologically impaired populations

ABSTRACT In two speech production studies conducted in Italian, we investigated the impact of phonological neighbourhood properties such as the neighbourhood density and the mean frequency of the neighbours on speech processing. Two populations of healthy (Study 1) and neurologically impaired (Study 2) individuals were tested. We employed multi-regression methods to analyse naming latencies in Study 1 and accuracy rates in Study 2 while controlling for various psycholinguistic predictors. In Study 1, pictures with words from high-density neighbourhoods were named faster than those from low-density neighbourhoods. Additionally, words with high-frequency neighbours were named faster in Study 1 and yielded higher accuracy rates in Study 2. The results suggest facilitatory effects of both the phonological neighbourhood density and frequency neighbourhood variables. Furthermore, we observed interactions between these two phonological neighbourhood variables and name agreement and repetition. Specifically, the facilitation effect was more pronounced for pictures with lower name agreement and during the initial presentation of the pictures. These findings are discussed in the context of previous literature and within the framework of interactive models of speech production.

Persons in contexts: The role of social networks and social density for the dynamic regulation of face-to-face interactions in daily life.

Current psychological theories on daily social interactions emphasize individual differences yet are underspecified regarding contextual factors. We aim to extend this research by examining how two context factors shape social interactions in daily life: how many relationships people maintain and how densely people live together. In Study 1, 307 German participants (Mage = 39.44 years, SDage = 14.14) answered up to 20 experience sampling questionnaires regarding their social interactions over 2 days. In Study 2, 313 German participants (Mage = 48.96 years, SDage = 15.54) summarized their daily interactions in daily diaries for 14 days. Participants reported on their social network size and the social density (i.e., household and neighborhood density) of their living situations. Mobile sensing provided additional measures of social interactions and network size. The results showed that participants living in densely populated households transitioned faster from solitude to social interactions but slower from social interactions to solitude. Participants living in dwellings with more homes also transitioned slower from solitude to social interactions. Contrary to the hypothesis, social network size was inconsistently linked with transitions from solitude to social interactions and vice versa. Furthermore, current social desires predicted subsequent social interactions within days, but not across days-irrespective of individuals' social network size or social density. Together the results point out that people live their daily life in social contexts, which contribute to how they engage in social interactions. The findings thus call for a greater integration of contextual factors in personality theories of social interactions. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Agent-Based Modeling of COVID-19 Transmission: A Case Study of Housing Densities in Sankalitnagar, Ahmedabad

The differential transmission of COVID-19 depending on the socio-economic status of a neighborhood is well established. For example, several studies have shown that COVID-19 transmission was higher in poorer and denser neighborhoods than in wealthier ones. However, what is less well known is how this varied rate of transmission interacted with established health measures, i.e., face masks and lockdowns, in the context of developing countries to reduce pandemic cases and hence resulted in fewer deaths. This study uses an Agent-Based Model (ABM) simulation to examine the context and impacts of COVID-19 mitigation efforts (i.e., lockdowns combined with masks) on the transmission of COVID-19 across a single neighborhood in Ahmedabad, a city in the state of Gujarat, India. The model is parameterized using real-world population data, which allows us to simulate the spread of COVID-19 to find conditions that most closely match the realities of COVID-19 in the spring of 2020. Consequently, the simulation can be used to understand the impact of nation-wide lockdown on the spread of COVID cases across Ahmedabad as a function of housing density. Thus, invaluable insight into the effectiveness of a lockdown as a mitigation measure can be derived. Further information about how the effectiveness of the lockdown varied by neighborhood, as well as other factors that impacted it, can be ascertained.

Commute and built environment: What matters for subjective well-being in a household context?

Much of prior research has shown a growing interest in determinants of subjective well-being (SWB). However, relatively less research has explored the causal effects of commute and built environment (BE) on SWB, and there is little knowledge regarding how these connections differ between household members. The study examines both cross-sectional and longitudinal connections between commute, BE, and SWB, as well as the variations in these connections between couples, by analyzing longitudinal survey data of dual-earner households from Chinese cities. The results indicate that the increase in commute duration results in lower SWB. Shifting to active modes is shown to increase SWB. Nonetheless, shifting in the opposite direction shows no significant effect. All BE changes are correlated with the husbands' SWB changes, whereas only changes in neighborhood categories and neighborhood density appear to matter for wives. The findings indicate that planning strategies can complement transport policies aimed at enhancing SWB.

Oaks enhance early life stage longleaf pine growth and density in a subtropical xeric savanna.

The interplay of positive and negative species interactions controls species assembly in communities. Dryland plant communities, such as savannas, are important to global biodiversity and ecosystem functioning. Sandhill oaks in xeric savannas of the southeastern United States can facilitate longleaf pine by enhancing seedling survival, but the effects of oaks on recruitment and growth of longleaf pine have not been examined. We censused, mapped, and monitored nine contiguous hectares of longleaf pine in a xeric savanna to quantify oak-pine facilitation, and to examine other factors impacting recruitment, such as vegetation cover and longleaf pine tree density.We found that newly recruited seedlings and grass stage longleaf pines were more abundant in oak-dominated areas where densities were 230% (newly recruited seedlings) and 360% (grass stage) greater from lowest to highest oak neighborhood densities. Longleaf pine also grew faster under higher oak density. Longleaf pine recruitment was lowest under longleaf pine canopies. Mortality of grass stage and bolt stage longleaf pine was low (~1.0%yr-1) in the census interval without fire. Overall, our findings highlight the complex interactions between pines and oaks-two economically and ecologically important genera globally. Xeric oaks should be incorporated as a management option for conservation and restoration of longleaf pine ecosystems.

Do households value lower density: Theory, evidence, and implications from Washington, DC

A substantial literature demonstrates that zoning restrictions on building height or density lower supply and increase housing prices. However, negative externalities due to household preferences for lower neighborhood density could justify restrictions on private developers. Thus building density in a laissez-faire city may be above the welfare maximizing level. The potential external costs of height and density are tested here and found to be substantial. Increased building separation appears to mitigate the external cost of height. This implies that some level of density or floor regulation (FAR) may be welfare-enhancing, and that the gap between price and marginal construction cost may overstate the social cost of zoning because households value lower density. The analysis considers residential density and not employment density which can give rise to other types of externalities.

Measuring Phonological Complexity Using the Perfect Rhymes Dictionary (PeRDict)

This paper examines links between perfect rhymes and text readability and decoding using a measure of English rhymes called the Perfect Rhymes Dictionary (PeRDict). PeRDict is based on the Carnegie Mellon University Pronouncing Dictionary (the CMUdict) and provides rhyme counts for ∼48,000 words in English and for the most frequent 1,000, 2,500, 5,000, and 10,000 rhymes within the dictionary as measured by the Corpus of American English (COCA). Two assessments of PeRDICT are presented. The first examines the strength of rhyme features to predict text readability in conjunction with word neighborhood density effects reported by the English Lexicon Project (ELP) and a word frequency measure. The second examines the strength of rhyme features to predict word decoding in conjunction with word neighborhood effects and a word frequency measure. In both assessments, the number of rhymes per word was predictive of text or word processing beyond features related to word neighborhood effects and word frequency. Word rhyme counts performed more strongly in predicting text processing versus word processing.

An adaptive reference vector guided many-objective optimization algorithm based on the pareto front density estimation

The performance of evolutionary algorithms using reference vectors to guide the evolution process mainly depends on the adaptive reference vector update strategy. In order to solve the challenging many-objective optimization problems with irregular Pareto fronts, this paper proposes an adaptive reference vector update strategy based on the Pareto front density estimation, which estimates the true Pareto front by finding sparse regions while ensuring the uniform distribution of reference vectors. In addition, an improved environmental selection strategy using the angle-based neighborhood density estimation has been proposed for estimating the neighborhood density to effectively guide the population evolution. On this basis, this paper proposes an adaptive reference vector guided many-objective optimization algorithm based on Pareto front density estimation (MaOEA-PDE). Experimental results on a large number of benchmark problems show MaOEA-PDE achieves better performance compared with some state-of-the-art algorithms in the literature.

Identification of an algorithm for the analysis and study of urban road network trajectories

The object of this study is a clustering algorithm using various technologies. This paper compares clustering algorithms that are more commonly used to analyze urban road network trajectories, the growth curve model, with the elbow method and the x-means algorithm. Experiments were conducted with various volumes of big data to determine calculation time, accuracy, and ways to increase calculation time. These results can be used to manage traffic jams in congested areas and city streets. Considering the widespread use of clustering algorithms for solving various problems, this study proposes to introduce GCM, SPGK methods for monitoring and analyzing the state of congestion on city roads. The work was carried out in the following steps: research and selection of methods based on efficiency and time, implementation of parallel computing technologies to improve computation speed, demonstration of the selected method based on collected data from a real city with visualization of the results. The growth curve model algorithm has been proven to be almost 5 times more effective than the elbow method and the x-means algorithm. The time allocated for data processing has been calculated. An increase in the volume of processed data showed an almost stable execution time t = 3 s for the GCM algorithm for data with a volume of up to almost 2,000 units. The effectiveness of SPGK-means was shown for different values of the number of points. Models of the Chengdu transport network obtained using a clustering algorithm with maximum grid density of neighborhoods are presented. There are some deviations between the grid and the road network due to the large grid size. This error is explained by an error of up to one between the points and the real grid. The results obtained clearly show how optimization of congested roads can be influenced. They provide information to obtain data on available routes, which allows you to analyze the road network individually and as a whole

Risk factors of hazardous alcohol use among adult males: A systematic review

Background & Aim: Hazardous alcohol use is the most prevalent form of alcohol misuse, distinct from harmful or dependent use. This drinking behavior is a widespread practice among males, leading to a myriad of health and social challenges. Preventing hazardous alcohol use is crucial to reducing negative consequences and avoiding more severe forms of alcohol misuse. There has been no systematic review of its risk factors. This study aims to provide comprehensive information on hazardous alcohol use risk factors in adult males by systematically summarizing current evidence. Methods & Materials: The protocol was registered with PROSPERO. PubMed, Scopus, Science Direct, EBSCOhost (APA PsycArticles), and Google Scholar were searched. The inclusion criteria were English-language observational studies published between 2012 and 2022 with male participants aged 18 to 65. Two reviewers carried out the quality assessment. A narrative synthesis was conducted to synthesize the findings. Results: Out of 6,842 records yielded from the systematic search, 20 studies were included. All of these were cross-sectional studies with 19 out of 20 classified as high quality and one as moderate. The included studies identified several factors that increased the risk of hazardous alcohol use including lower education level, positive family history of alcohol use, smoking, high alcohol density neighborhoods, depressive symptoms, drinking motives, and negative life events. Little research has been done on other variables that may also play a role. Conclusion: Several risk factors for hazardous alcohol use were identified. Future research, particularly longitudinal studies, is recommended to validate these findings.

Association of Park Renovation With Park Use in New York City

Equity-driven citywide park redesign and renovation, such as the Community Parks Initiative (CPI), has the potential to increase park use and opportunities for physical activity in underserved communities. To evaluate changes in patterns of park use following park redesign and renovation in low-income New York City (NYC) neighborhoods. The Physical Activity and Redesigned Community Spaces study was a prospective quality improvement preintervention-postintervention study design with matched control parks. Thirty-three intervention and 21 control neighborhood parks were selected based on specific criteria related to poverty rates, population growth, and population density in park neighborhoods and not having received more than $250 000 in investment in the past 2 decades. Data were collected at baseline (prerenovation) and 2 follow-up points (3 months and 1 year post renovation) between June 5 and December 4 from 2016 to 2022. Participants were individuals observed as users of study parks. The CPI, which involved the redesign and renovation of neighborhood parks by the municipal government of New York City. Main outcomes encompassed park use and physical activity levels assessed using the well-validated System for Observing Play and Recreation in Communities. Park use was quantified by total number of park users, categorized by age group (≤20 years vs ≥21 years), sex, and physical activity level (sitting or standing vs walking or vigorous activity). Changes in outcomes between groups were compared via the generalized estimation equation. A total of 28 322 park users were observed across 1458 scans. At baseline, 6343 of 10 633 users (59.7%) were 20 years or younger, 4927 of 10 632 (46.3%) were female and 5705 (53.7%) were male, and 4641 of 10 605 (43.8%) were sitting or standing. Intervention parks showed more net park users compared with control parks from baseline to the final follow-up (difference-in-difference relative rate ratio, 1.69 [95% CI, 1.22-2.35] users/scan; P = .002). The association was driven by a significant increase in adult users at intervention parks and overall decrease in all users at control parks. Park users engaging in sitting or standing at intervention parks increased (difference, 4.68 [95% CI, 1.71-7.62] users/scan; P = .002) and park users engaging in walking or vigorous physical activity at control parks decreased (difference, -7.30 [95% CI, -10.80 to -4.26] users/scan; P < .001) over time. In this quality improvement study, park redesign and renovation were positively associated with park use in low-income neighborhoods. However, park renovations may need to be accompanied by other programmatic strategies to increase physical activity.

Assessing the influence of seasonal precipitation patterns on groundwater quality in the coal rich environment of Enugu, Nigeria

As the impacts of climate change continue to be felt around the world, understanding the effects on groundwater quality and quantity has become an important area of investigation. As a global source of water that contributes to preserving the environment, a better understanding of the effect of precipitation seasonal pattern on these systems is crucial; though studies connected to groundwater quality in this era of environmental crisis are at infancy. This study aims to evaluate the effect of precipitation seasonal pattern on groundwater quality in a coal enriched environment of developing city of west African sub-region with particular reference to Enugu, a coal city in Nigeria. Three residential areas (Abakpa, Achara, and Independence Layout) were randomly selected from high, medium, and low neighbourhood densities in the metropolis. Within the period spanning from April 2018 to March 2019, a physiochemical analysis was conducted on twelve deep wells utilizing weighted arithmetic index method. This technique was implemented in order to facilitate the assessment of the degree of water quality by translating a number of variables to just one metric value. The results of the investigation showed that the groundwater resources in the study region are mildly acidic, presumably as a result of the presence of pyrite, which is a byproduct of coal weathering, and chloride-ion-charged rains. Additionally, noticeable distinctions in the properties of water samples were observed between the dry and rainy seasons. Specifically, just 1% of the sampled water had excellent ratings, while 58.3% were considered good, 29.1% were deemed poor, and 8.3% of samples were categorized as very poor. The study concluded that coupled with climate crisis, seasonal precipitation patterns affect groundwater resources by reducing recharge, discharge, and the overall quality of water. These results have important implications for the management of groundwater resources in the region and highlight the need for continued monitoring and assessment of water quality in the face of ongoing environmental changes.

Graded phonological neighborhood effects on lexical retrieval: Evidence from Mandarin Chinese

How phonological neighborhood affects lexical retrieval can shed important light on lexical organization and processing. Yet these effects are unclear, particularly in Mandarin Chinese. This is likely because the working definition of phonological neighbors (i.e., the one-phoneme edit rule) used in Indo-European languages inadequately characterizes the phonological similarity among Mandarin words, which have simpler syllable structures and lexical tones. The current study proposes a graded Mandarin phonological neighborhood and investigates the impacts of near-to-distant Mandarin phonological neighbors on lexical retrieval. In Study 1, we investigated how Mandarin phonological similarity is influenced by the editing of lexical tone, constituent (onset/rime, initial/final) and phoneme. Native Mandarin speakers rated the similarity between the edited monosyllabic words. We found that constituent-edit neighbors were rated as the most dissimilar, followed by phoneme-edit neighbors, while tone-edit neighbors were the most similar. In Study 2, we calculated the constituent-, phoneme- and tone-edit phonological neighborhood densities and frequencies for 4,706 monosyllabic Mandarin words. We then utilized extant datasets to examine how the density and frequency of neighbors at varied distances, as well as of homophonic neighbors, impact response latencies in word naming, visual lexical decision, and picture naming tasks. The results showed that graded phonological neighbors had differential impacts on lexical retrieval efficiency: distant (constituent-edit) neighbors facilitated word retrieval, while near (phoneme-, tone-edit and homophonic) neighbors had inhibitory effects. We discuss these findings within an interactive activation and competition framework and suggest future directions to study the representation and processing of the Mandarin phonological lexicon.

Post-wildfire neighborhood change: Evidence from the 2018 Camp Fire

As the number of highly destructive wildfires grows, it is increasingly important to understand the long-term changes that occur to fire-affected places. Integrating approaches from social and biophysical science, we document two forms of neighborhood change following the 2018 Camp Fire in the United States, examining the more than 17,000 residential structures within the burn footprint. We found that mobile or motor homes, lower-value residences, and absentee owner residences had a significantly higher probability of being destroyed, providing evidence that housing stock filtering facilitated socially stratified patterns of physical damage. While the relationship between building value and destruction probability could be explained by measures of building density and distance to nearby roads, building type remained an independent predictor of structure loss that we could not fully explain by adding environmental covariates to our models. Using a geospatial machine learning technique, we then identified buildings that had been reconstructed within the burn footprint 20 months after the fire. We found that reconstructed buildings were more likely to have been owner-occupied prior to the fire and had higher average pre-fire property value, suggesting an emerging pattern of cost-burden gentrification. Our findings illustrate the importance of examining the built environment as a driver of socially uneven disaster impacts. Wildfire mitigation strategies are needed for mobile and motor home residents, renters, low-income residents, and dense neighborhoods.

Urban-canopy airflow dynamics: A numerical investigation of drag forces and distribution for generic neighborhoods, and their relationships with breathability

Thorough investigations of urban-canopy drag primarily stemming from pressure drag on building surfaces are necessary given the turbulent flows within complex urban areas. Moreover, a gap persists regarding the relationships between canopy drag and breathability. Therefore, this work delves into the canopy-layer airflow dynamics for generic urban neighborhoods by performing three-dimensional Reynolds-Averaged Navier-Stokes simulations. A total of 32 subcases are examined, encompassing uniform- and varying-height and diverse plan area densities (λp, categorized into groups of sparse: 0.0625/0.067, medium: 0.23/0.25, and dense: 0.53/0.56). Results for the drag distribution highlight the windward-row shelter effect for the medium and the dense, local shelter by taller buildings, and distinct shapes of sectional drag forces (F⁎Z). Local velocity and mean age of air are found strongly positively and negatively correlated to F⁎Z, respectively, with distinct slopes in relation to λp. For the uniform-height, the normalized bulk drag (F⁎bulk, referred to as drag coefficient in literature) peaks for the medium with wake-interference regime; F⁎bulk demonstrates a maximum increase of over two times with height variation; moreover, F⁎bulk for varying-height groups exhibits a marked increase from the sparse to the medium, while remaining comparable values for the dense. The frontal area averaged drag (FAf,ave) exhibits a decreasing trend against λp across all cases. Further, FAf,ave exhibits strong correlations with λp and porosity, and with bulk ventilation indices such as spatially averaged velocity, air change rate, and normalized net escape velocity. Throughout the ‘suburban-urban-suburban’ canopy, medium neighborhoods exerting larger drag cause greater streamwise outdoor pressure drops and flow reductions compared to the sparse. However, dense neighborhoods with lower drag exhibit even larger pressure losses, which should be carefully scrutinized. The findings can inform urban planners in designing more aerodynamically efficient neighborhoods and guide strategies for improving air quality within urban environments.

A motif-based probabilistic approach for community detection in complex networks

Community detection in complex networks is an important task for discovering hidden information in network analysis. Neighborhood density between nodes is one of the fundamental indicators of community presence in the network. A community with a high edge density will have correlations between nodes that extend beyond their immediate neighbors, denoted by motifs. Motifs are repetitive patterns of edges observed with high frequency in the network. We proposed the PCDMS method (Probabilistic Community Detection with Motif Structure) that detects communities by estimating the triangular motif in the network. This study employs structural density between nodes, a key concept in graph analysis. The proposed model has the advantage of using a probabilistic generative model that calculates the latent parameters of the probabilistic model and determines the community based on the likelihood of triangular motifs. The relationship between observing two pairs of nodes in multiple communities leads to an increasing likelihood estimation of the existence of a motif structure between them. The output of the proposed model is the intensity of each node in the communities. The efficiency and validity of the proposed method are evaluated through experimental work on both synthetic and real-world networks; the findings will show that the community identified by the proposed method is more accurate and dense than other algorithms with modularity, NMI, and F1score evaluation metrics.

An XGBoost-assisted evolutionary algorithm for expensive multiobjective optimization problems

Many expensive optimization problems exist in various real-world applications. However traditional evolutionary algorithms are inadequate for solving these problems directly. Surrogate-assisted evolutionary algorithm (SAEA) can effectively solve expensive optimization problems using computationally inexpensive surrogate models. However, both the Kriging and ensemble models most SAEAs adopted have limited uncertainty of prediction, especially for expensive multiobjective optimization problems (EMOPs). To enhance the optimization performance of SAEA for EMOPs, this paper proposes a new XGBoost-assisted evolutionary algorithm, calling XGBEA. Specifically, XGBoost is used as the surrogate model, and a neighborhood density selection strategy based on a mixed population and archive space (NDS-MPA) is proposed to measure the uncertainties of individuals. XGBoost helps to best fit objective functions with different fitness landscapes. NDS-MPA selects non-dominated individuals with minimal density for re-evaluation, incorporating considerations of convergence, diversity and uncertainty. Experimental results on two well-studied benchmarks demonstrated the superiority of XGBEA over seven state-of-the-art SAEAs.

Lexical effects on talker discrimination in adult cochlear implant usersa).

The lexical and phonological content of an utterance impacts the processing of talker-specific details in normal-hearing (NH) listeners. Adult cochlear implant (CI) users demonstrate difficulties in talker discrimination, particularly for same-gender talker pairs, which may alter the reliance on lexical information in talker discrimination. The current study examined the effect of lexical content on talker discrimination in 24 adult CI users. In a remote AX talker discrimination task, word pairs-produced either by the same talker (ST) or different talkers with the same (DT-SG) or mixed genders (DT-MG)-were either lexically easy (high frequency, low neighborhood density) or lexically hard (low frequency, high neighborhood density). The task was completed in quiet and multi-talker babble (MTB). Results showed an effect of lexical difficulty on talker discrimination, for same-gender talker pairs in both quiet and MTB. CI users showed greater sensitivity in quiet as well as less response bias in both quiet and MTB for lexically easy words compared to lexically hard words. These results suggest that CI users make use of lexical content in same-gender talker discrimination, providing evidence for the contribution of linguistic information to the processing of degraded talker information by adult CI users.

Exploring auditory recognition: Native Japanese listeners' perception of frequent and infrequent English words in noise with varied phonological neighborhood densities

Native Japanese listeners identified English words embedded in noise (SNR + 6dB) produced by native American English and Japanese speakers. The identical word list used in our previous study (Nozawa and Wayland 2023) was employed. Listeners responded by typing the words they heard. The findings revealed no discernible impacts of phonological neighborhood density, possibly due to the small vocabulary size limiting competition from other words. However, frequent words exhibited greater precision in recognition compared to infrequent words. Despite the introduction of noise, the overall accuracy of responses did not experience a substantial impact. Nevertheless, specific words like “class” and “club,” initially nearly perfect in accuracy without noise, dropped to 0% accuracy. Most errors included phoneme substitution rather than phoneme addition or deletion, and in / CVC/ words, the onset consonant was identified substantially better than the vowel and the coda consonant. Initial consonant clusters, such as /br/, / kl/, and /pl/, were frequently perceived as /l/ or /r/, leading to the initial stops or fricatives being missed. Errors encompassed the substitution of phonemes with others that are not typically perceptually assimilated into the same native language (L1) categories, which would not be revealed through predefined multiple-choice identification or discrimination tasks.

Learnability Advantage of Segmental Repetitions in Word Learning.

To date, research on wordform learning biases has mostly focused on language-dependent factors, such as the phonotactics and neighborhood density of the language(s) known by the learner. Domain-general biases, by contrast, have received little attention. In this study, we focus on one such bias-an advantage for string-internal repetitions-and examine its effects on wordform learning. Importantly, we consider whether any type of segmental repetition is equally beneficial for word recall, or whether learning is favored more or only by repeated consonants, in line with previous research indicating that consonants play a larger role than vowels in lexical processing. In Experiment 1, adult English speakers learned artificial consonant-vowel-consonant-vowel words containing either a repeated consonant (e.g., /sesu/, "c-rep"), a repeated vowel (e.g., /sepe/, "v-rep"), or dissimilar consonants and vowels (e.g., /sepu/, "no-rep"). Recall results showed no advantage for v-reps but higher accuracy for c-reps compared with no-reps. In Experiment 2, participants performed a label preference task with the same stimuli. The results showed dispreference for both c-reps and v-reps relative to no-reps, indicating that the results of Experiment 1 are independent of wordlikeness effects. These outcomes reveal that there is a form-learning bias for words with identical consonants but not for words with identical vowels, suggesting that a domain-general advantage for repetitions within strings is modulated by a language-specific processing bias for consonants.