Cross-domain Relationships Research Articles

Acoustic and Kinematic Predictors of Intelligibility and Articulatory Precision in Parkinson's Disease.

This study investigated relationships within and between perceptual, acoustic, and kinematic measures in speakers with and without dysarthria due to Parkinson's disease (PD) across different clarity conditions. Additionally, the study assessed the predictive capabilities of selected acoustic and kinematic measures for intelligibility and articulatory precision ratings. Forty participants, comprising 22 with PD and 18 controls, read three phrases aloud using conversational, less clear, and more clear speaking conditions. Acoustic measures and their theoretical kinematic parallel measures (i.e., acoustic and kinematic distance and vowel space area [VSA]; second formant frequency [F2] slope and kinematic speed) were obtained from the diphthong /aɪ/ and selected vowels in the sentences. A total of 368 listeners from crowdsourcing provided ratings for intelligibility and articulatory precision. The research questions were examined using correlations and linear mixed-effects models. Intelligibility and articulatory precision ratings were highly correlated across all speakers. Acoustic and kinematic distance, as well as F2 slope and kinematic speed, showed moderately positive correlations. In contrast, acoustic and kinematic VSA exhibited no correlation. Among all measures, acoustic VSA and kinematic distance were robust predictors of both intelligibility and articulatory precision ratings, but they were stronger predictors of articulatory precision. The findings highlight the importance of measurement selection when examining cross-domain relationships. Additionally, they support the use of behavioral modifications aimed at eliciting larger articulatory gestures to improve intelligibility in individuals with dysarthria due to PD. https://doi.org/10.23641/asha.27011281.

PHONETIC UNDERPINNINGS OF SOUND SYMBOLISM ACROSS MULTIPLE DOMAINS OF MEANING.

Sound symbolism occurs when the sound of a word alone can convey its meaning, e.g. 'balloon' and 'spike' sound rounded and pointed, respectively. Sound-symbolic correspondences are widespread in natural languages, but it is unclear how they are instantiated across different domains of meaning. Here, participants rated auditory pseudowords on opposing scales of seven different sound-symbolic domains: shape (rounded-pointed), texture (hard-soft), weight (light-heavy), size (small-big), brightness (bright-dark), arousal (calming-exciting), and valence (good-bad). Ratings showed cross-domain relationships, some mirroring those between corresponding physical domains, e.g. size and weight ratings were associated, reflecting a physical size-weight relationship, while others involved metaphorical mappings, e.g., bright/dark mapped onto good/bad, respectively. The phonetic features of the pseudowords formed unique sets with characteristic feature weightings for each domain and tended to follow the cross-domain ratings relationships. These results suggest that sound-symbolic correspondences rely on domain-specific patterns of phonetic features, with cross-domain correspondences reflecting physical or metaphorical relationships.

The effects of word and beat priming on Mandarin lexical stress recognition: an event-related potential study

Abstract Music and language are unique communication tools in human society, where stress plays a crucial role. Many studies have examined the recognition of lexical stress in Indo-European languages using beat/rhythm priming, but few studies have examined the cross-domain relationship between musical and linguistic stress in tonal languages. The current study investigates how musical stress and lexical stress influence lexical stress recognition in Mandarin. In the auditory priming experiment, disyllabic Mandarin words with initial or final stress were primed by disyllabic words or beats with either congruent or incongruent stress patterns. Results showed that the incongruent condition elicited larger P2 and the late positive component (LPC) amplitudes than the congruent condition. Moreover, the Strong-Weak primes elicited larger N400 amplitudes than the Weak-Strong primes, and the Weak-Strong primes yielded larger LPC amplitudes than the Strong-Weak primes. The findings reveal the neural correlates of the cross-domain influence between music and language during lexical stress recognition in Mandarin.

Crossing the domain: Unintended consequences of safety and service climates.

Domain-specific roles of service climate and safety climate are well-established, but little is known about their cross-domain roles. In this study, we examined the cross-domain main roles of service climate (on safety performance) and safety climate (on service performance) and their joint roles in predicting service and safety performance. Drawing on the exploration-exploitation framework, we further introduced team exploration and team exploitation as explanatory mechanisms for the cross-domain relationships. We conducted two multiwave, multisource field studies using nursing teams in hospitals. Results from Study 1 showed that service climate had a positive relationship with service performance but a nonsignificant relationship with safety performance. Safety climate, though, had a positive relationship with safety performance but a negative relationship with service performance. Study 2 found support for all main relationships and also revealed that safety climate moderated the indirect relationships that service climate had with safety and service performance through team exploration. Moreover, service climate moderated the indirect relationships that safety climate had with service and safety performance through team exploitation. We extend the climate literature by uncovering the missing cross-domain relationships between service and safety climates. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Transfer Graph-Driven Rotating Machinery Diagnosis Considering Cross-Domain Relationship Construction

Transfer learning-based fault diagnosis methods borrow source-domain knowledge to achieve diagnosis task for the unlabeled target domain. However, existing research articles mainly lie in feature mapping and model transfer, ignoring the relationship between cross-domain samples. Once connections between cross-domain samples with the same label can be constructed, label propagation will be easier even if there is a cross-domain distribution discrepancy. In this article, a transfer graph-driven rotating machinery diagnosis considering cross-domain relationship construction is proposed. Specifically, signal spectrum is extracted by fast Fourier transform mapping raw signals to identical feature space. Transfer graphs are constructed by the Euclidean distance between nodes, where the relationships between the same domain samples, even cross-domain samples, are established. Then, the graph convolutional network (GCN), trained by source-domain samples and less target-domain samples, is utilized for cross-domain diagnosis tasks. The experimental results demonstrate the effectiveness of the proposed method. In addition, trained GCN enables diagnosing on newly constructed target-domain graphs. It shows the ability to continuously learn new transferable knowledge.

Sub- and Supra-Second Timing in Auditory Perception: Evidence for Cross-Domain Relationships.

Previous studies indicate that there are at least two levels of temporal processing: the sub- and supra-second domains. The relationship between these domains remains unclear. The aim of this study was to test whether performance on the sub-second level is related to that on the supra-second one, or whether these two domains operate independently. Participants were 118 healthy adults (mean age = 23 years). The sub-second level was studied with a temporal-order judgment task and indexed by the Temporal Order Threshold (TOT), on which lower values corresponded to better performance. On the basis of TOT results, the initial sample was classified into two groups characterized by either higher temporal efficiency (HTE) or lower temporal efficiency (LTE). Next, the efficiency of performance on the supra-second level was studied in these two groups using the subjective accentuation task, in which participants listened to monotonous sequences of beats and were asked to mentally accentuate every n-th beat to create individual rhythmic patterns. The extent of temporal integration was assessed on the basis of the number of beats being united and better performance corresponded to longer units. The novel results are differences between groups in this temporal integration. The HTE group integrated beats in significantly longer units than did the LTE group. Moreover, for tasks with higher mental load, the HTE group relied more on a constant time strategy, whereas the LTE group relied more on mental counting, probably because of less efficient temporal integration. These findings provide insight into associations between sub- and supra-second levels of processing and point to a common time keeping system, which is active independently of temporal domain.

Secure Conflicts Avoidance in Multidomain Environments: A Distributed Approach

In a multidomain application environment, it is of paramount importance for different organizations to collaborate with each other to facilitate secure interoperation. However, various types of conflicts related to access control constraints may arise as a result of integrating access control policies for individual domains, such as role inheritance violations (RIVs) and separation of duty violations (SoDVs). Current methods solve the conflicts in a centralized way by withdrawing or removing all crossdomain relationships resulting in the violations with the knowledge of all domains. However, these methods are inappropriate for large-scale systems due to their high computational complexity. In this article, we propose a distributed approach to avoid secure conflicts in a multidomain environment. We first model the role inheritance hierarchies of multiple domains as an interoperation graph. We then develop RIVs and SoDVs avoidance algorithms based on the interoperation graph and the communications among different domains. Each domain can execute the algorithms autonomously and in real time by evaluating whether its succeeding activated role can result in RIVs and SoDVs. We show that the new algorithms perform well in contrast to the existing algorithms.

Integrating work–family conflict and enrichment: understanding the moderating role of demographic variables

PurposeFor more than a decade, efforts to integrate the two major perspectives of work–family studies, namely, work–family conflict and work–family enrichment have started advancing not only in western context but also in non-western contexts as well. However, both conflict and enrichment emerging from the family front have often been neglected in previous studies. The purpose of this paper is to test the integration of two major work–family perspectives, that is, work–family conflict and work–family enrichment in an Indian context.Design/methodology/approachThe current study involves a multi-sectoral survey of sales employees belonging to manufacturing, information technology, fast-moving consumer goods, pharmaceuticals and financial services using standard scales. The sample consisted of 330 sales employees working in some of the major firms coming under these sectors. Structural equation modelling (SEM) using analysis of a moment structures was used to test the integrated model. In addition, multi-group SEM was used to test the impact of select demographic variables on the integrated model.FindingsResults of SEM suggested that for sales employees in Indian organizations, work–family conflict follows a matching domain principle, whereas, work–family enrichment follows both matching and cross-domain principles. Further, it was found that marital status and annual salary emerge as moderators in the integrated model.Research limitations/implicationsThe present study confirmed that similar-domain relationships are stronger than cross-domain relationships, supporting findings from previous research with regard to work–family conflict. In addition, the results contradicted the studies conducted in western countries wherein the same domain effect is observed with respect to both types of enrichment, that is, work to family enrichment (WFE) and family to work enrichment (FWE). The present study confirms a similar and cross-domain relationship in the case of both types of enrichment. It means that both WFE and FWE have a positive impact on both jobs and family satisfaction.Practical implicationsOrganizations so far have been trying ways to reduce stress to reduce work to family conflict. However, there is a need to incorporate policies that facilitate work–family enrichment. Such policies may focus more on support for both married and unmarried employees’ sales employees.Originality/valueThis study contributes to work–family literature by attempting to integrate both conflict and enrichment perspectives, which has rarely been done in the Indian context.

An Explorative Study on the Relationship between Learning Opportunities at School and at Work and Adolescents' Mental Health.

Based on the Job Demands-Resources model, this study examined the association of learning opportunities of adolescents at school and work with their mental health, operationalized in terms of life satisfaction and depression. Intrinsic motivation at school and at work were studied as potential mediators. Within a representative sample of adolescents (n = 474), the results supported within domain relationships in the sense that learning opportunities at school and at work were positively related to intrinsic motivation at school and at work, respectively, which in turn were related to higher levels of life satisfaction and lower levels of depression. Cross-domain relationships were not significant, except for a negative relationship between learning opportunities at work and intrinsic motivation at school, suggesting that having a good job can pull students away from school.

Microbiome and antibiotic resistome in household dust from Beijing, China

We spend ever-increasing time indoors along with urbanization; however, the geographical distribution patterns of microbiome and antibiotic resistome, and their driving forces in household environment remains poorly characterized. Here, we surveyed the bacterial and fungal communities, and the resistome in settled dust gathered from 82 homes located across Beijing, China, employing Illumina sequencing and high-throughput quantitative PCR techniques. There was no clear geographical distribution pattern in dust-related bacterial communities although a slight but significant (P < 0.05) distance-decay relationship occurred in its community similarity; by contrast, a relatively distinct geographical clustering and a stronger distance-decay relationship were observed in fungal communities at the local scale. The cross-domain (bacteria versus fungi) relationships in the microbiome of the dust samples were mostly observed as robust co-occurrence correlations. The bacterial communities were dominated by Proteobacteria and Actinobacteria phyla, with human skin, soil and plants being potential major sources. The fungal communities largely comprised potential allergens (a median 61% of the fungal sequences), with Alternaria genus within Ascomycota phylum being the most predominant taxa. The profile of dust-related bacterial communities was mainly affected by housing factors related to occupants and houseplants, while that of fungal communities was determined by georeferenced environmental factors, particularly vascular plant diversity. Additionally, a great diversity (1.96 on average for Shannon index) and normalized abundance (2.22 copies per bacterial cell on average) of antibiotic resistance genes were detected across the dust samples, with the dominance of genes resistant to vancomycin and Macrolide-Lincosamide-Streptogramin B. The resistome profile exhibited no distinct geographical pattern, and was primarily driven by certain bacterial phyla and occupancy-related factors. Overall, we underline the significance of anthropogenic impacts and house location in structuring bacterial and fungal communities inside homes, respectively, and suggest that household dust is an overlooked reservoir for antibiotic resistance.

Cross-Domain Relationship Prediction by Efficient Block Matrix Completion for Social Media Applications

Cross-Domain Relationship Prediction by Efficient Block Matrix Completion for Social Media Applications

Deep conditional adaptation networks and label correlation transfer for unsupervised domain adaptation

Unsupervised domain adaptation aims to improve the performance of an unknown target domain by utilizing the knowledge learned from a related source domain. Given that the target label information is unavailable in the unsupervised situation, it is challenging to match the domain distributions and to transfer the source model to target applications. In this paper, a Deep Conditional Adaptation Networks (DCAN) is proposed to address the unsupervised domain adaptation problem. DCAN is implemented based on a deep neural network and attempts to learn domain invariant features based on the Wasserstein distance. A conditional adaptation strategy is presented to reduce the domain distribution discrepancy and to address category mismatch and class prior bias, which are usually ignored in marginal adaptation approaches. Furthermore, we propose a label correlation transfer algorithm to address the unsupervised issues, by generating more effective pseudo target labels based on the underlying cross-domain relationship. A set of comparative experiments were performed on standard domain adaptation benchmarks and the results demonstrate that the proposed DCAN outperforms previous adaptation methods.

From job crafting to home crafting: A daily diary study among six European countries

The actions that individuals take to proactively craft their jobs are important to help create more meaningful and personally enriching work experiences. But do these proactive behaviors have implications beyond working life? Inspired by the suggestion that individuals aim for a meaningful life we examine whether on days when individuals craft their jobs, they are more likely to craft non-work activities. It also seems likely that characteristics of the home environment moderate these cross-domain relationships. We suggest that crafting crosses domains particularly when individuals gain resources through high autonomy and high workload at home. We partly supported our model through a daily diary study, in which 139 service sector employees from six European countries (Belgium, Denmark, Germany, Netherlands, Spain, UK) reported their experiences twice a day for five consecutive workdays. Home autonomy and home workload strengthened the positive relationship between seeking resources at work and at home. Moreover, home autonomy strengthened the positive association between seeking challenges at work and at home, and the negative relation between reducing demands at work and at home. These findings suggest that the beneficial implications of job crafting transcend life boundaries thereby providing advice for how individuals can experience greater meaning in their lives.

Information Leakage-Aware Computer-Aided Cyber-Physical Manufacturing

Cyber-physical additive manufacturing systems consist of tight integration of cyber and physical domains. This union, however, induces new cross-domain vulnerabilities that pose unique security challenges. One of these challenges is preventing confidentiality breach, caused by physical-to-cyber domain attacks. In this form of attack, attackers utilize the side-channels (such as acoustics, power, electromagnetic emissions, and so on) in the physical-domain to estimate and steal cyber-domain data (such as G/M-codes). Since these emissions depend on the physical structure of the system, one way to minimize the information leakage is to modify the physical-domain. However, this process can be costly due to added hardware modification. Instead, we propose a novel methodology that allows the cyber-domain tools [such as computer aided-manufacturing (CAM)] to be aware of the existing information leakage. Then, we propose to change either machine process or product design parameters in the cyber-domain to minimize the information leakage. Our methodology aids the existing cyber-domain and physical-domain security solution by utilizing the cross-domain relationship. We have implemented our methodology in a fused-deposition modeling-based Cartesian additive manufacturing system. Our methodology achieves reduction of mutual information by 24.94% in acoustic side-channel, 32.91% in power side-channel, 32.29% in magnetic side-channel, and 55.65% in vibration side-channel. As a case study, to help understand the implication of mutual information drop, we have also presented the calculation of success rate and the reconstruction of the 3D object based on an attack model. For the given attack model, our leakage-aware CAM tool decreases the success rate of an attacker by 8.74% and obstructs the reconstruction of finer geometry details.

Women entrepreneurs and work-family conflict: an analysis of the antecedents

Over the years, academic attention towards work-family conflict (WFC) issues has been constantly growing due to the socio-economic changes occurring in society. In line with this, great effort has been devoted to investigating WFC experienced by employees, while still almost untapped is the conversation with reference to women entrepreneurs. Moreover, the few studies that deal with women entrepreneurs’ WFC have mainly analysed its negative consequences rather than its predictors. Thus, this study aims to fill such research gap by analysing women entrepreneurs’ WFC antecedents. Based on the bidimensional conceptualization of WFC, distinguishing between work interference with family (WIF) and family interference with work (FIW), this study verifies an expanded model of the WFC which takes into consideration either the within-domain effects or the cross-domain effects of work and family stressors on WIF and FIW experienced by women entrepreneurs. In doing so, an analysis based on data from 669 women entrepreneurs has been conducted. Results show that both within-domain relationships and cross-domain relationships play a key role in explaining the WFC experienced by women entrepreneurs.

Co-development of internalizing and externalizing behavior problems during early childhood among child welfare-involved children

Using parallel-process latent growth curve modeling, we examine developmental trajectories of internalizing and externalizing behavior problems and identify early risk factors for behavior problems among 329 child welfare-involved children followed from age 2years to 5 years. Data are drawn from the National Survey of Child and Adolescent Well-Being II. On average, internalizing behavior problems remained stable, while externalizing behavior problems decreased over time. Higher initial levels of internalizing behavior problems were associated with higher initial levels of externalizing behavior problems. Rates of change also had positive cross-domain relationships. Child neglect, exposure to intimate partner violence (IPV), insecure caregiver-child attachment, and caregiver mental health problems were associated with higher initial levels of internalizing and externalizing behavior problems. Exposure to IPV, out-of-home care, and caregiver drug use predicted rates of change in behavior problems. Our findings highlight the importance of comprehensive assessment and treatment for co-occurring internalizing and externalizing behavior problems in young children involved in the child welfare system. Results also indicate the need for identifying and addressing early risk factors to prevent early onset and continued development of behavior problems in high-risk children.

Experiments using Semantic Web technologies to connect IUGONET, ESPAS and GFZ ISDC data portals

E-science on the Web plays an important role and offers the most advanced technology for the integration of data systems. It also makes available data for the research of more and more complex aspects of the system earth and beyond. The great number of e-science projects founded by the European Union (EU), university-driven Japanese efforts in the field of data services and institutional anchored developments for the enhancement of a sustainable data management in Germany are proof of the relevance and acceptance of e-science or cyberspace-based applications as a significant tool for successful scientific work. The collaboration activities related to near-earth space science data systems and first results in the field of information science between the EU-funded project ESPAS, the Japanese IUGONET project and the GFZ ISDC-based research and development activities are the focus of this paper. The main objective of the collaboration is the use of a Semantic Web approach for the mashup of the project related and so far inoperable data systems. Both the development and use of mapped and/or merged geo and space science controlled vocabularies and the connection of entities in ontology-based domain data model are addressed. The developed controlled vocabularies for the description of geo and space science data and related context information as well as the domain ontologies itself with their domain and cross-domain relationships will be published in Linked Open Data.

CGC: A Flexible and Robust Approach to Integrating Co-Regularized Multi-Domain Graph for Clustering.

Multi-view graph clustering aims to enhance clustering performance by integrating heterogeneous information collected in different domains. Each domain provides a different view of the data instances. Leveraging cross-domain information has been demonstrated an effective way to achieve better clustering results. Despite the previous success, existing multi-view graph clustering methods usually assume that different views are available for the same set of instances. Thus instances in different domains can be treated as having strict one-to-one relationship. In many real-life applications, however, data instances in one domain may correspond to multiple instances in another domain. Moreover, relationships between instances in different domains may be associated with weights based on prior (partial) knowledge. In this paper, we propose a flexible and robust framework, CGC (Co-regularized Graph Clustering), based on non-negative matrix factorization (NMF), to tackle these challenges. CGC has several advantages over the existing methods. First, it supports many-to-many cross-domain instance relationship. Second, it incorporates weight on cross-domain relationship. Third, it allows partial cross-domain mapping so that graphs in different domains may have different sizes. Finally, it provides users with the extent to which the cross-domain instance relationship violates the in-domain clustering structure, and thus enables users to re-evaluate the consistency of the relationship. We develop an efficient optimization method that guarantees to find the global optimal solution with a given confidence requirement. The proposed method can automatically identify noisy domains and assign smaller weights to them. This helps to obtain optimal graph partition for the focused domain. Extensive experimental results on UCI benchmark data sets, newsgroup data sets and biological interaction networks demonstrate the effectiveness of our approach.

Cross-Domain Relationships with Assistant and Head Coaches: Comparing Levels and Correlates

Cross-domain relationships (CDRs) involve coaches knowing and caring about aspects of athletes’ lives beyond the sport context (e.g., family, school, relationships). Purposes of the current study included (a) comparing athletes’ levels of cross-domain relationships with head and assistant coaches, (b) evaluating gender, roster size, and sport type as correlates of CDRs with head and assistant coaches, and (c) examining relationships between CDRs with head and assistant coaches and motivational variables. Collegiate athletes (N = 294, 139 male, 155 female) completed surveys assessing study constructs. Results indicated that levels of CDRs with head coaches and assistant coaches did not differ. Male athletes had stronger CDRs with head coaches than female athletes did. While female athletes with female head coaches had moderate levels of CDRs with head coaches regardless of assistant coach gender, female athletes with male head coaches had stronger CDRs with head coaches when the assistant coach was female than when the assistant coach was male. Stronger CDRs with head coaches were related to greater perceived competence, enjoyment, and sport commitment, while CDRs with assistant coaches were not related. Findings suggest that researchers should not assume that CDRs with assistant and head coaches are similarly related to athletes’ motivational outcomes.

Robust Multi-Network Clustering via Joint Cross-Domain Cluster Alignment.

Network clustering is an important problem that has recently drawn a lot of attentions. Most existing work focuses on clustering nodes within a single network. In many applications, however, there exist multiple related networks, in which each network may be constructed from a different domain and instances in one domain may be related to instances in other domains. In this paper, we propose a robust algorithm, MCA, for multi-network clustering that takes into account cross-domain relationships between instances. MCA has several advantages over the existing single network clustering methods. First, it is able to detect associations between clusters from different domains, which, however, is not addressed by any existing methods. Second, it achieves more consistent clustering results on multiple networks by leveraging the duality between clustering individual networks and inferring cross-network cluster alignment. Finally, it provides a multi-network clustering solution that is more robust to noise and errors. We perform extensive experiments on a variety of real and synthetic networks to demonstrate the effectiveness and efficiency of MCA.