Network Strengths Research Articles

Connectome-based prediction of global cognitive performance in people with HIV

Global cognitive performance plays an important role in the diagnosis of HIV-associated neurocognitive disorders (HAND), yet to date, there is no simple way to measure global cognitive performance in people with HIV (PWH). Here, we performed connectome-based predictive modeling (CPM) to pursue a neural biomarker of global cognitive performance in PWH based on whole-brain resting-state functional connectivity. We built a CPM model that successfully predicted individual differences in global cognitive performance in the training set of 67 PWH by using leave-one-out cross-validation. This model generalized to both 33 novel PWH in the testing set and a subset of 39 PWH who completed a follow-up visit two years later. Furthermore, network strengths identified by the CPM model were significantly different between PWH with HAND and without HAND. Together, these results demonstrate that whole-brain functional network strengths could serve as a potential neural biomarker of global cognitive performance in PWH.

A multi-criteria assessment of alternative sustainable solid waste management of flexible packaging

Purpose The purpose of this paper is to examine the issues affecting end of life (EOL) management of flexible packaging. It focuses on Sustainable Solid Waste Management by using multi-criteria decision making, analytic network process (ANP), and Strengths, Weaknesses, Opportunities, and Threats (SWOT). Design/methodology/approach Data were collected from 33 expert stakeholders, though a series of interviews and questionnaires. The subject seven aspects were applied from integrated sustainable waste management with 19 sub-criteria identified. Criteria were prioritized by using ANP and SWOT to the internal and external environments of organizations directly responsible for waste management. Findings The five most important factors in the management of flexible packaging waste include: techniques for waste management, material and design, management support, legislation and rule, and environmental care and environmental health, respectively. Solutions addressing flexible packaging waste were identified, including reuse and recycle, waste to energy, biopolymers, new innovative materials and material recovery. Research limitations/implications Data were derived from the national authorities and large companies. The findings may not represent local authorities and small-scale manufacturers. Future research should be conducted, in order to investigate and focus around small manufacturing enterprises. Practical implications The findings provide a strategic framework for policy makers and industrial manufacturers. The benefits of this will enable them to address flexible packaging waste, by using qualitative and quantitative criteria. Originality/value This is the first paper developing a multi-criteria assessment model to specifically manage EOL flexible packaging, a possible pioneering piece of research in this field.

Dissociable neural substrates of opioid and cocaine use identified via connectome-based modelling.

Opioid use disorder is a major public health crisis. While effective treatments are available, outcomes vary widely across individuals and relapse rates remain high. Understanding neural mechanisms of treatment response may facilitate the development of personalized and/or novel treatment approaches. Methadone-maintained, polysubstance-using individuals (n=53) participated in fMRI scanning before and after substance-use treatment. Connectome-based predictive modeling (CPM)—a recently developed, whole-brain approach—was used to identify pre-treatment connections associated with abstinence during the 3-month treatment. Follow-up analyses were conducted to determine the specificity of the identified opioid abstinence network across different brain states (cognitive vs. reward task vs. resting-state) and different substance use outcomes (opioid vs. cocaine abstinence). Post-treatment fMRI data were used to assess network changes over time and within-subject replication. To determine further clinical relevance, opioid abstinence network strength was compared to healthy subjects (n=38). CPM identified an opioid abstinence network (p=.018), characterized by stronger within-network motor/sensory connectivity, and reduced connectivity between the motor/sensory network and medial frontal, default mode and frontoparietal networks. This opioid abstinence network was anatomically distinct from a previously identified cocaine abstinence network. Relationships between abstinence and opioid and cocaine abstinence networks replicated across multiple brain states but did not generalize across substances. Network connectivity measured at post-treatment related to abstinence at 6-month follow-up (p<.009). Healthy comparison subjects displayed intermediate network strengths relative to treatment responders and non-responders. These data indicate dissociable anatomical substrates of opioid versus cocaine abstinence. Results may inform the development of novel opioid-specific treatment approaches to combat the opioid epidemic.

Multivariate graph learning for detecting aberrant connectivity of dynamic brain networks in autism.

Alterations in static functional brain networks have previously been reported in Autistic Spectrum Disorder (ASD). Although functional brain networks are known to be time-varying, alterations in time-varying or dynamic brain networks in ASD is largely unknown. Hence, in this study, we analyze resting-state fMRI data of ASD group versus Typically Developing Control (TDC) group to understand alterations in dynamic functional brain networks in ASD vis-à-vis healthy controls. We introduce a new framework for extracting overlapping dynamic functional brain networks to study these alterations. We utilize sliding window approach along with the recent Multivariate Vector Regression-based Connectivity (MVRC) method to construct functional connectivity (FC) matrices in each time-window. Further, we build three-mode subject-summarized spatio-temporal tensor in both ASD and TDC groups. This tensor is utilized to determine a set of overlapping dynamic functional brain networks and their temporal profiles. This helps us in studying alterations in dynamic brain networks in ASD subjects at the group-level. The proposed framework is tested on two publicly available resting-state fMRI dataset of ASD and normal controls. Our analyses on resting-state fMRI data indicate that dynamic functional brain networks of ASD subjects are altered compared to the TDC group. Two-sample t-test is used to establish the statistical significance of the differences observed in network strengths of the two groups. Compared to the TDC subjects, autistic subjects showed alterations in multiple functional brain networks including cognitive control, subcortical, auditory, visual, bilateral limbic, and default mode network. The proposed methodology is able to provide information on alterations in dynamic functional brain networks in ASD and may provide potential biomarkers for studying human brain disorders.

Evaluation of hydrometric network efficacy and user requirements in the Republic of Ireland via expert opinion and statistical analysis

Decreased funding and shifting governmental priorities have resulted in a contraction of hydrometric measurement in many regions over the past two decades. Moreover, concerns exist with respect to appropriate data usage and (transboundary) exchange, in addition to the compatibility and extent of existing hydrometric datasets. These issues are undoubtedly magnified due to enhanced data demands and increased financial pressures on network managers, thus requiring new approaches to optimising the societal benefits and overall efficacy of hydrometric information for future socio-hydrological resilience.The current study employed a quantitative cross-sectional expert elicitation of 203 respondents to collate, analyse and assess hydrometric network users’ opinions, knowledge and experience. Current usage patterns, perceived network strengths, requirements, and limitations have been identified and discussed within the context of hydrometric resilience in a changing social, economic and natural environment. Findings indicate that small (<30 km2) catchment data are most frequently employed in the Republic of Ireland, particularly with respect to extreme event prediction and flood management. Similarly, small catchments and areas characterised by previous/recent flooding were prioritised for resilience management via network amendment. Over half of those surveyed (50.5%) reported the current network as inadequate for their professional requirements. Conversely, respondents indicated network efficacy has improved (53.2%) or remained stable (26.6%) over the course of their professional career, however, improvements (as defined by individual respondents i.e. network density, data quality, data availability) have not occurred at a sufficient rate. User-defined efficacy (adequacy, resilience) was found to be a somewhat vague, multivariate concept, with no individual predictor identified, however, general data quality, network density, and urban catchment data were the most significant issues among respondents. A significant majority (85.4%) of respondents indicate that future resilience would be best achieved via network density amendment, with over 60% favouring geographically and/or categorically focused network increases, as opposed to more general national increases.

Effects of an Online Mind\u2013Body Training Program on the Default Mode Network: An EEG Functional Connectivity Study

Online mind–body training (MBT) programs can improve the psychological capabilities of practitioners. Although there has been a lot of effort to understand the neural mechanisms underlying the therapeutic effects of meditation, little is known about changes in electroencephalographic (EEG) functional connectivity that accompany mind-body training. The present study aimed to investigate how an online MBT program alters EEG functional connectivity in the default mode network (DMN). We assessed a group of healthcare providers, including 14 females who participated in the 4-week MBT program and 15 females who underwent a 4-week of waiting period. EEG data and information about psychological states were obtained at baseline and 4 weeks. The result was that the intervention group showed significant reductions in anxiety and trait anger that were accompanied by increased global DMN network strengths in the theta and alpha (but not beta and delta) frequency bands; these changes were not observed in the control group. Other variables including state anger, positive and negative affect, and self-esteem have not been changed over time in both groups. These findings suggest that practicing the mind-body training could have a relevance to the functional differences in network related to stress and anxiety reaction.

Dedifferentiation Does Not Account for Hyperconnectivity after Traumatic Brain Injury.

Changes in functional network connectivity following traumatic brain injury (TBI) have received increasing attention in recent neuroimaging literature. This study sought to understand how disrupted systems adapt to injury during resting and goal-directed brain states. Hyperconnectivity has been a common finding, and dedifferentiation (or loss of segregation of networks) is one possible explanation for this finding. We hypothesized that individuals with TBI would show dedifferentiation of networks (as noted in other clinical populations) and these effects would be associated with cognitive dysfunction. Graph theory was implemented to examine functional connectivity during periods of task and rest in 19 individuals with moderate/severe TBI and 14 healthy controls (HCs). Using a functional brain atlas derived from 83 functional imaging studies, graph theory was used to examine network dynamics and determine whether dedifferentiation accounts for changes in connectivity. Regions of interest were assigned to one of three groups: task-positive, default mode, or other networks. Relationships between these metrics were then compared with performance on neuropsychological tests. Hyperconnectivity in TBI was most commonly observed as increased within-network connectivity. Network strengths within networks that showed differences between TBI and HCs were correlated with performance on five neuropsychological tests typically sensitive to deficits commonly reported in TBI. Hyperconnectivity within the default mode network (DMN) during task was associated with better performance on Digit Span Backward, a measure of working memory [R2(18) = 0.28, p = 0.02]. In other words, increased differentiation of networks during task was associated with better working memory. Hyperconnectivity within the task-positive network during rest was not associated with behavior. Negative correlation weights were not associated with behavior. The primary hypothesis that hyperconnectivity occurs through dedifferentiation was not supported. [corrected]. Instead, enhanced connectivity post injury was observed within network. Results suggest that the relationship between increased connectivity and cognitive functioning may be both state (rest or task) and network dependent. High-cost network hubs were identical for both rest and task, and cost was negatively associated with performance on measures of psychomotor speed and set-shifting.

Social network analysis as an analytical archetype of R&amp;D national networks: Case study in culture collections of Brazil and Japan

The lack of analytical mechanisms of R&amp;amp;D national networks is a significant problem for policy makers. This paper presents an analytical archetype for performance evaluation of national co-authoring networks based on Social Network Analysis parameters. The model evaluates paper co-authoring data of professionals responsible for culture collections in Brazil and Japan. Were identified professionals from the World Federation for Culture Collections data bank and co-authoring identified from international bibliographic databases. The Brazilian network is the focus of the analysis and the Japanese is the reference network. The Research and Development networks in culture collections are fundamental to the performance of the biotechnological innovation chain in areas such as health, agriculture and industry, and thus fundamental to emerging countries such as Brazil. This country has the fifth largest population in the world, being most of this population user of public health services and it has in the agribusiness one of its main sources of wealth. The model allows a performance evaluation of the networks and identifies improvement paths for the Brazilian network. SNA parameters combined with a reference network showed meaningful elements to the understanding of a R&amp;amp;D networks. This proved helpful for the strategic analysis of the network weaknesses and strengths. The model also proposes policy implications for the three analysis of sub-levels, namely cohesion, subgroups and centralization.

An analysis model of tourism academic networks: a Swedish case study triangulated with an EU research project

ABSTRACTThe purpose of this research is to investigate and develop an analysis model of a tourism department network using an explorative approach. Strategic stakeholders have been identified for the tourism department and organised into partner groups. An analysis model has been developed based on four network types: formal organisation, informal organisation, formal individual and informal individual. For every type, the following six network content dimensions were found relevant to analyse: stakeholders, reciprocal relations, relation exchange, network driving forces, network management and network purpose. The investigations have shown some focused network strengths such as network permanency, with corresponding weaknesses such as rigid relations. Some typical implications of the strengths and weaknesses for the department have been identified, and some network techniques to handle the implications have been proposed. An annual network development process for a tourism department is suggested. The resulting network is summarised as the Professional Tourism Academic Network (PTAN).

Establishing an oncology quality dashboard for improvement.

223 Background: Cancer Treatment Centers of America (CTCA), a national network of five hospitals, formed a Quality Improvement Committee to bring together both clinical and administrative leadership (physician, nursing, pharmacy and quality) across the enterprise vested in the oversight of quality and patient safety. Tasked with facilitating and driving measurement and improvement the group established a Quality dashboard housing metrics of importance given current performance, evidence-based practice, and evolving external standards. The dashboard includes a mix of outcome, process, and structure measures with targets, both externally driven and CTCA established. Methods: The dashboard houses data sourced from a multitude of systems and is segmented into clinically relevant categories such as Infection Prevention, Nursing, Medication Management, and Medical Oncology to name a few. These categories are further broken down into specific measures, reported by quarter, and color-coded (red/yellow/green) to display progress. Targets are established based upon external benchmarks, where data is available. Each metric is also graphically displayed, trending the 6 most recent quarters of data as another visual reference. Finally, a glossary was created to standardize key measure details across the enterprise for accurate data collection including documentation of source, numerator, denominator, references, inclusions, exclusions and rationale. Data is updated monthly to reflect most current performance and promote timely intervention. Results: Since development of the Quality dashboard, CTCA has experienced various red to yellow to green progressions as well as upped its targets indicating significant advancement in performance. Standard data collection and visual identifiers within one repository has enabled CTCA to accurately focus time and resources where needed in order to continually improve care. Conclusions: The establishment of the enterprise-wide quality dashboard has led to great collaboration within CTCA’s network of hospitals. The display of the data allows both a focus upon individual and network strengths and opportunities for improvement as well as a mechanism for communicating shared goals.

A New Tool for Measuring Biosolids Floc Strength

The ability to measure sludge network strength is important in sludge dewatering applications because it can be used to determine optimum polymer dose for conditioning to achieve good dewaterability. This was demonstrated in laboratory and in full-scale dewatering and thickening. The network strength increased as the polymer dose was increased, however, at the optimum dose a 'drop' in the network strength occurred. Further research is needed to verify this concept at full scale and to provide a robust technology to the water and wastewater treatment industry. A second phase is sought through WERF funding. Rheometry was used for determining the sludge network strength. This report also formulated and demonstrated a standard protocol for measuring network strength in terms of energy dissipated in a certain volume of sludge. Two protocols for measuring network strengths by either torque or concentric cylinder rheometers are described in this report. A mathematical derivation has shown that area under rheograms, namely the curves which were developed by plotting shear rate (1/sec) versus shear stress (Pa) and time (sec) versus torque (mNm), indicated the rate of energy dissipation within the sludge system and the total dissipated energy was related to the network strength. The research did not intend to measure the 'absolute' network strength, rather a comparative strength of different aggregates using the same instrument and under the same measuring conditions. Thus, the measured strength is relative. This title belongs to WERF Research Report Series ISBN: 9781780404158 (eBook) ISBN: 9781843397137 (Print)

Hyper-brain networks support romantic kissing in humans.

Coordinated social interaction is associated with, and presumably dependent on, oscillatory couplings within and between brains, which, in turn, consist of an interplay across different frequencies. Here, we introduce a method of network construction based on the cross-frequency coupling (CFC) and examine whether coordinated social interaction is associated with CFC within and between brains. Specifically, we compare the electroencephalograms (EEG) of 15 heterosexual couples during romantic kissing to kissing one’s own hand, and to kissing one another while performing silent arithmetic. Using graph-theory methods, we identify theta–alpha hyper-brain networks, with alpha serving a cleaving or pacemaker function. Network strengths were higher and characteristic path lengths shorter when individuals were kissing each other than when they were kissing their own hand. In both partner-oriented kissing conditions, greater strength and shorter path length for 5-Hz oscillation nodes correlated reliably with greater partner-oriented kissing satisfaction. This correlation was especially strong for inter-brain connections in both partner-oriented kissing conditions but not during kissing one’s own hand. Kissing quality assessed after the kissing with silent arithmetic correlated reliably with intra-brain strength of 10-Hz oscillation nodes during both romantic kissing and kissing with silent arithmetic. We conclude that hyper-brain networks based on CFC may capture neural mechanisms that support interpersonally coordinated voluntary action and bonding behavior.

Reduced executive and default network functional connectivity in cigarette smokers.

Altered functional connectivity has been associated with acute and chronic nicotine use. Connectivity alterations, specifically in the right and left executive control networks (RECN/LECN) and the default mode network (DMN), may contribute to the addiction cycle. The objective of this study was to determine if executive control network (ECN) and DMN connectivity is different between non-smokers and smokers and whether reductions in connectivity are related to chronic cigarette use. The RECN, LECN, and DMN were identified in resting state functional magnetic resonance imaging data in 650 subjects. Analyses tested for group differences in network connectivity strength, controlling for age and alcohol use. There was a significant group effect on LECN and DMN connectivity strength with smokers (n = 452) having lower network strengths than non-smokers (n = 198). Smokers had lower connectivity than non-smokers associated with key network hubs: the dorsolateral prefrontal cortex, and parietal nodes within ECNs. Further, ECN connectivity strength was negatively associated with pack years of cigarette use. Our data suggest that chronic nicotine use negatively impacts functional connectivity within control networks that may contribute to the difficulty smokers have in quitting.

Source of Unimin kaolin rheological variation–Ca2+ concentration

The variations in rheological-pH behaviors between suspensions of low and high calcium (Ca) kaolin were evaluated via zeta potential, yield stress and sedimentation methods. Elemental analysis via x-ray fluorescence (XRF) showed that Riedel kaolin (0.028%) carries ∼18.0 times lesser Ca concentrations than Unimin kaolin where Riedel slurries displayed a maximum yield stress at ∼pH 2.0 when Riedel particles carried low negative zeta potential magnitudes while Unimin slurries exhibited a maximum yield stress at pH 8.6 when Unimin particles were highly negatively charged. With Ca2+ cations added to Riedel slurries at sufficiently high concentrations, Riedel's negative zeta potential magnitudes decreased especially along high pH, maximum yield stress peaks shifted to high pH and solids content obtained during consolidation increased by ∼14.0 weight percentages (wt%) at pH 8.0 to be similar to Unimin. These changes in Riedel's behaviors and the reasons for Unimin's behaviors is due to the adsorption of hydrolyzed Ca(OH)+ hydroxy complexes onto these particles, which reduced particle negativity and induced unlike charge attractions between these particles to improve consolidation and increase slurry network strengths, and the presence of hydrolyzed Ca(OH)2 precipitates, which increased yield stresses of these kaolin slurries at high pH. The hydrolysis-pH behaviors of Ca2+ cations varied via acid and base titration paths to correspondingly affect and cause the rheological-pH behaviors of Unimin slurries to be varied via acid and base titration paths. Overall, this study explains the effect of elemental variations between kaolin particles that affects the rheological-pH behaviors between the respective kaolin slurries.

Motor Imagery Learning Modulates Functional Connectivity of Multiple Brain Systems in Resting State

BackgroundLearning motor skills involves subsequent modulation of resting-state functional connectivity in the sensory-motor system. This idea was mostly derived from the investigations on motor execution learning which mainly recruits the processing of sensory-motor information. Behavioral evidences demonstrated that motor skills in our daily lives could be learned through imagery procedures. However, it remains unclear whether the modulation of resting-state functional connectivity also exists in the sensory-motor system after motor imagery learning.Methodology/Principal FindingsWe performed a fMRI investigation on motor imagery learning from resting state. Based on previous studies, we identified eight sensory and cognitive resting-state networks (RSNs) corresponding to the brain systems and further explored the functional connectivity of these RSNs through the assessments, connectivity and network strengths before and after the two-week consecutive learning. Two intriguing results were revealed: (1) The sensory RSNs, specifically sensory-motor and lateral visual networks exhibited greater connectivity strengths in precuneus and fusiform gyrus after learning; (2) Decreased network strength induced by learning was proved in the default mode network, a cognitive RSN.Conclusions/SignificanceThese results indicated that resting-state functional connectivity could be modulated by motor imagery learning in multiple brain systems, and such modulation displayed in the sensory-motor, visual and default brain systems may be associated with the establishment of motor schema and the regulation of introspective thought. These findings further revealed the neural substrates underlying motor skill learning and potentially provided new insights into the therapeutic benefits of motor imagery learning.

Compressive consolidation of strongly aggregated particle gels

The compressive yield stress of particle gels shows a highly nonlinear dependence on the packing fraction. We have studied continuous compression processes, and discussed the packing fraction dependence with the particle scale rearrangements. The 2D simulation of uniaxial compression was applied to fractal networks, and the required compressive stresses were evaluated for a wide range of packing fractions that approached close packing. The compression acts to reduce the size of the characteristic structural entities (i.e. the correlation length of the structure). We observed three stages of compression: (I) elastic-dominant regime; (II) single-mode plastic regime, where the network strengths are determined by the typical length scale and the rolling mode; and (III) multi-mode plastic regime, where sliding mode and connection breaks are important. We also investigated the way of losing the fractal correlation under compression. It turns out that both fractal dimension $D_{\mathrm{f}}$ and correlation length $\xi$ start to change from the early stage of compression, which is different from the usual assumption in theoretical models.

The Influence of the Amplitude of Low-Frequency Fluctuations on Resting-State Functional Connectivity

Studies of brain functional connectivity have provided a better understanding of organization and integration of large-scale brain networks. Functional connectivity using resting-state functional magnetic resonance imaging (fMRI) is typically based upon the correlations of the low-frequency fluctuation of fMRI signals. Reproducible spatial maps in the brain have also been observed using the amplitude of low-frequency fluctuations (ALFF) in resting-state. However, little is known about the influence of the ALFF on the functional connectivity measures. In the present study, we analyzed resting-state fMRI data on 79 healthy old individuals. Spatial independent component analysis and regions of interest (ROIs) based connectivity analysis were performed to obtain measures of functional connectivity. ALFF maps were also calculated. First, voxel-matched inter-subject correlations were computed between back-reconstructed IC and ALFF maps. For all the resting-state networks, there was a consistent correlation between ALFF variability and network strengths (within regions that had high IC strengths). Next, inter-subject variance of correlations across 160 functionally defined ROIs were correlated with the corresponding ALFF variance. The connectivity of several ROIs to other regions were more likely to correlate with its own regional ALFF. These regions were mainly located in the anterior cingulate cortex, medial prefrontal cortex, precuneus, insula, basal ganglia, and thalamus. These associations may suggest a functional significance of functional connectivity modulations. Alternatively, the fluctuation amplitudes may arise from physiological noises, and therefore, need to be controlled when studying resting-state functional connectivity.

Scale-free dynamics and critical phenomena in cortical activity

Scale-free dynamics and critical phenomena in cortical activity

AN-WOT Model for Designation and Analysis of Sustainable Development Strategies in Abroud Village

Establishment of sustainable development needs to develop new techniques. Which they can develop strategies and solutions to be applied strategies. One of the tools that help managers and planners to develop these strategies, that is using a SWOT analysis. In this study, by making use of the analytical network method, strengths and weaknesses due to internal factors and opportunities and threats caused by external factors were identified. Based on the findings, relevant strategies for the sustainable development of the Jam Abroud village and the executive programs needed for their implementation were designed. These strategies are limited for operational programs and priority. At this straight by using of Analytic Network process, which is one of multi action methods for deciding the strategies were graded. In the final the graded programs for doing the action programs in a period of ten years, with assigning the elements of responsible of these programmers was given. Results show that although the presented offensive patterns ranked best among strategies, followed by conservative, competitive and defensive patterns, but it was found that the use of a combination of the above-mentioned patterns and strategies with attention to their rankings provides the best opportunity to establish sustainable development in Jam Abroud vill.

Strengthening Network Ties through Mentoring of Alienated Personnel

This study examines the social network aspects of mentoring in order to suggest ways to manage alienated public employees. It also explores the impact of mentoring that requires closer relationships between mentors and mentees to develop network ties. Networks of trust, respect, and friendship among soldiers in four barracks of the Republic of Korea Army (two experimental groups and two control groups) were measured using a social network survey. Alienated soldiers in the experimental groups were mentored by fellow soldiers with stronger ties, while no such mentoring was conducted in the control groups. After three months of mentoring, changes in network strengths were found among alienated soldiers in the experimental groups, while no significant changes were found among alienated soldiers in the control groups. This study is expected to contribute to human resource management by suggesting ways to strengthen the network ties of alienated personnel through mentoring.