Central Difference Research Articles

Abnormal sensory processing cortex in insomnia disorder: a degree centrality study.

Insomnia disorder is a significant global health concern. This research aimed to explore the pathogenesis of insomnia disorder using static and dynamic degree centrality methods at the voxel level. A total of 29 patients diagnosed with insomnia disorder and 28 healthy controls were ultimately included to examine differences in degree centrality between the two groups. Additionally, the relationship between altered degree centrality values and various clinical indicators was analyzed. The results revealed that patients with insomnia disorder exhibited higher static degree centrality in brain regions associated with sensory processing, such as the occipital gyrus, inferior temporal gyrus, and supramarginal gyrus. In contrast, lower static degree centrality was observed in the parahippocampal gyrus, amygdala, insula, and thalamus. Changes in dynamic degree centrality were identified in regions including the parahippocampal gyrus, anterior cingulum, medial superior frontal gyrus, inferior parietal gyrus, and precuneus. Notably, a negative correlation was found between dynamic degree centrality in the inferior parietal gyrus and the Pittsburgh Sleep Quality Index, while a positive correlation was observed between static degree centrality in the inferior temporal gyrus and the Hamilton Depression Scale. These findings suggest that dysfunction in centrality within the sensory processing cortex and subcortical nuclei may be associated with the sleep-wake imbalance in individuals with insomnia disorder, contributing to our understanding of hyperarousal mechanisms in insomnia. Moreover, the abnormalities observed in the default mode network and the salience network provide insights into understanding the neuropathogenesis of insomnia from both static and dynamic centrality perspectives. The clinical trial registration number: ChiCTR2200058768. Date: 2022-04-16.

Aging disrupts the link between network centrality and functional properties of prefrontal neurons during memory-guided behavior

The prefrontal cortex (PFC) is vital for higher cognitive functions and displays neuronal heterogeneity, with neuronal activity varying significantly across individual neurons. Using calcium imaging in the medial PFC (mPFC) of mice, we investigate whether differences in degree centrality—a measure of connectivity strength within local circuits—could explain this neuronal diversity and its functional implications. In young adults, neurons with high degree centrality, inferred from resting-state activity, exhibit reliable and stable action-plan selectivity during memory-guided tasks, suggesting that connectivity strength is closely linked to functional heterogeneity. This relationship, however, deteriorates in middle-aged and older mice. A computational model simulating age-related declines in synaptic plasticity reproduces these results. In young adults, degree centrality also predicts cross-modal action-plan selectivity, but this predictive power diminishes with age. Furthermore, neurons with high action-plan selectivity are spatially clustered, a pattern that fades with aging. These findings reveal the significant aging impact on the network properties in parallel with the functional and spatial organization of the mPFC.

Robot-assisted technique can achieve accurate screw placement in four-corner fusion and reduce operative difficulty: a cadaver study

BackgroundThe purpose of this study is to explore the feasibility and accuracy of a robot-assisted technique in four-corner fusion compared with traditional freehand operation.MethodsTwenty cadaver specimens were randomly assigned to the robot-assisted group and freehand groups. Three screws were placed percutaneously to fix the capitate-lunate joint, lunate-triquetrum joint, and triquetrum-hamate-capitate joint in each specimen by robot-assisted or freehand technique. The offset between the actual and planned screw positions was determined by merging the images of intraoperative and postoperative CT scans in the robot-assisted group. The centrality of the screw, time-consuming, drilling attempts, and radiation exposure were compared between the two groups.ResultsThe mean offset between the actual and planned screw position was 1.09 (SD: 0.56) mm. The offset at the start point of the screw was significantly lower than that at the endpoint. There was no significant difference in the centrality of the screws, surgical time between the two groups. The number of drilling attempts and the radiation dose received by surgeons were significantly lower in the robot-assisted group.ConclusionsAlthough there was no significant difference in screw centrality between the two groups, the slight offset between the actual and planned screw positions confirmed the feasibility of the robot-assisted technique in four-corner fusion. The robot-assisted technique has advantages in reducing the difficulty of surgery and protecting the surgeon from exposure to large doses of radiation.

Dispositional Traits, Characteristic Adaptations, and Narrative Identity Reconstructions in Individuals With Depersonalization and Derealization.

Depersonalization and derealization disorder (DPDR) is a debilitating condition. To date, little was known about the role of personality structure and of perceived social support and loneliness in DPDR. Three studies investigated, respectively: (i) broadband personality traits (five-factor model), maladaptive trait domains (PID-5), and perceived support and loneliness in individuals with self-reported DPDR (N = 160) versus a general population sample (N = 303), using network modeling; (ii) structure and interconnectivity of personality, perceived support and loneliness, and DPDR traits (frequency/duration) in individuals with self-reported DPDR (N = 160); (iii) characteristic adaptations and narrative identities in individuals with self-reported DPDR (N = 19), using thematic analysis. Study 1 found between-samples differences across several traits, especially psychoticism and negative affect. Differences in networks' global centrality, but not structures or edges, were also found. The graphical model in Study 2 showed a community of dissociative tendencies including DPDR traits and psychoticism. Study 3 highlighted the development of DPDR as a key life transition for those experiencing it, with narratives focusing on feelings of poor agency, isolation, and a disrupted sense of self. Individual differences in personality characterize DPDR, especially in psychoticism. Implications for theory and research are discussed.

Network Analysis of Women in Otolaryngology and Demographic Trends.

This study analyzes gender disparities between men and women otolaryngology faculty in the top 20 otolaryngology departments ranked by research output and discusses the implications of these disparities. This was a cross-sectional study of all articles published by faculty from January 2020 to December 2021 at the top 20 otolaryngology departments as ranked by Doximity's 2022 research output report. Integrated data from Web of Science, faculty directories, and NIH RePORT were used to collect data on faculty. Social network analysis was performed using ORA-LITE. Student's and Welch's t-tests and Pearson chi-squared tests were used to evaluate gender differences in academic metrics. The findings revealed significant gender disparities, with men holding higher academic positions (men = 3.16, women = 2.69, p < 0.0001), higher H-indices (22.4, 13.8, p < 0.0001), more NIH grants (0.15, 0.07, p = 0.0032), and greater total degree centrality (3.98E-4, 2.4E-4, p < 0.0001) and betweenness centrality (4.47E-3, 3.00E-3, p = 0.0021). Men also had more publications (9.8, 6.8, p < 0.0001) with more distinct co-authors, both within (4, 3.1, p = 0.0074) and across (38.1, 25.8, p < 0.0001) institutions. Disparities persisted after accounting for career length. Notably, total degree centrality differences between men and women were statistically significant from 1991 to 2017 (p < 0.0001), but not from 2018 to 2022 (p = 0.83). This study highlights gender inequities in otolaryngology, encouraging mentors to foster new collaborations with female peers. Importantly, it identifies a trend toward narrowing the gender gap within the specialty, particularly over the past 5 years, emphasizing the need to sustain these positive changes for enhanced gender equity. NA Laryngoscope, 2024.

Altered static brain activity and functional connectivity after heat stroke.

This study aimed to investigate the alteration of brain function based on resting-state functional MRI in patients after heat stroke. This study included 10 cases of patients after heat stroke and 10 cases of healthy controls. Abnormal brain function was calculated using amplitude of low-frequency fluctuations (ALFF) and degree centrality analysis, as well as functional connectivity analysis based on regions of interest (ROI). Correlation analyses were performed to evaluate the association between brain function changes and clinical scales. Combining ALFF and degree centrality results, the decreased brain regions included the left cuneus and the right angular gyrus, while the increased brain regions included the right cerebellar_Crus1. Using the left cuneus with significant differences in ALFF and degree centrality as ROI, the functional connectivity results revealed decreased brain regions including bilateral lingual gyrus, bilateral postcentral cingulate gyrus, and left precentral gyrus. The degree centrality value of the right cerebellar_Crus1 was positively correlated with glasgow coma scale (GCS) scores ( r = 0.726, P = 0.027), and the functional connectivity value of the right posterior cingulate gyrus was positively correlated with GCS scores ( r = 0.717, P = 0.030). Heat stroke patients exhibit abnormal activity in multiple brain regions, which has important clinical significance for evaluating the severity of the disease.

A cell-centered implicit finite difference scheme to study wave propagation in acoustic media: A numerical modeling

In the present paper, we present a Cell-Centered Implicit Finite Difference (CCIFD) operator-based numerical scheme for the propagation of acoustic waves that is very effective, accurate, and small in size. This scheme requires fewer estimation points than the traditional central difference derivative operator. Any numerical simulation is significantly impacted by the precision of a numerical derivative. Long stencils can deliver excellent accuracy while also minimizing numerical anisotropy error. However, a long stencil requires a lot of computational resources, and as these derivatives get bigger, they could start to look physically unrealistic due to contributions from nodes located extremely far, wherein the derivative is local in nature. Furthermore, using such lengthy stencils at boundary nodes may result in errors. The present article investigates a cell-centered fourth order finite difference scheme to model acoustic wave propagation which utilizes a lesser number of nodes in comparison to the traditional Central Difference (CD) operator. However, in general the implicit derivative operator has high computational cost and therefore despite its significant advantages it is generally avoided to be implemented in applications. This serves as a motivation for the present paper to explore a technique called CCIFD that significantly decreases the computational expense by nearly fifty percent. Additionally, spectral characterization of the CCIFD derivative operator has been analyzed and discussed. Finally, the wave propagation has been numerically simulated in 2-dimensional homogeneous and Marmousi model using CCIFD scheme to validate the applicability and stability of the scheme.

텍스트 마이닝을 활용한 국가수준 유치원 교육과정 분석

This study aims to examine the changes in the national kindergarten curriculum text through text mining. Semantic network analysis using R was employed for this purpose, yielding the following results. Firstly, consistently High-centrality keywords from the 1st kindergarten curriculum of the 2019 revised Nuri Curriculum were ‘child’ and ‘curriculum,’ with ‘kindergarten,’ ‘operation,’ and ‘development’ also showing general centrality. Secondly, keywords reflecting differences in centrality emphasized in each curriculum period included ‘community,’ ‘play,’ ‘welfare,’ ‘construction,’ and ‘parents.’ The keyword ‘community’ showed High-Centrality in the 1st, 5th, and 6th kindergarten curricula and the 2007 revised kindergarten curriculum. The keywords ‘welfare’ and ‘construction’ displayed High-Centrality in the 3rd kindergarten curriculum. Additionally, the keyword ‘play’ showed High-Centrality in the 2019 revised Nuri Curriculum, and the keyword ‘parents’ showed High-Centrality in the 6th and 2007 revised kindergarten curricula. This study offers implications for future revisions of the early childhood curriculum as a theoretical reference.

A multigrid waveform relaxation method for solving the nonlinear silicon problem with relaxing boundary conditions

This paper introduces a multigrid FAS Waveform Relaxation method (FAS-MGWR) for solving a heat transfer model in a thin and homogeneous silicon bar with constant density and heat capacity. This method exhibits versatility, making it applicable to a range of problems including electronic device engineering, numerical simulation of nanofluids, among others. The Finite Difference Method with central differences (CDS) for spatial discretization and the Crank-Nicolson method for temporal approximation were utilized. Comparison with literature results and code verification demonstrated that irrespective of the combinations of physical and numerical parameters, the apparent order of discretization error converges to the theoretical asymptotic order. The study underscores the superior performance of the proposed FAS-MGWR method, notable for its parallel architecture, particularly in terms of computational time, compared to existing literature. Notably, the FAS-MGWR method was found to have excellent convergence factor and speed-up in relation to its singlegrid version, underscoring its efficiency and practical advantage in addressing complex thermal problems.

Trauma behind the keyboard: Exploring disparities in child sexual abuse materials exposure and mental health factors among investigators and forensic examiners – A network analysis

BackgroundDespite acknowledging the detrimental impact of child sexual abuse material (CSAM) exposure on the mental and physical well-being of investigators and forensic examiners, there is a need for comprehensive exploration into the complex relationship between CSAM exposure, its various dimensions, mental health (i.e., anxiety, depression, and PTSD), and burnout, as well as the presence of positive attitudes towards the job. ObjectiveTo understand how CSAM exposure, mental health and burnout interconnect and cluster within distinct networks of police investigators and forensic examiners. Participants and settingPolice investigators and forensic examiners from across the United States who were exposed to CSAM as part of their professions (N = 470). MethodsParticipants, recruited through connections with the National Criminal Justice Training Center, completed an anonymous online survey. ResultsThe network analysis revealed differences in centrality between investigators and forensic examiners, particularly in their associations with exposure factors and mental health variables. Edges invariance tests showed differences in the strength of these associations, with some factors being more strongly linked to PTSD avoidance symptoms among investigators and others among forensic examiners. Stability analyses suggested potentially greater heterogeneity among investigators, while both groups displayed high stability in other centrality indices. ConclusionsThis study contributes to our comprehension of the distinct experiences and challenges faced by CSAM investigators and forensic examiners, and specifically the nuanced disparities between CSAM investigators and forensic examiners in terms of their exposure to CSAM content and the associated mental health factors. These insights highlight the imperative need for tailored support mechanisms and interventions that can effectively address the unique challenges encountered by individuals working tirelessly in this critical field.

Methodological moderators of average outdegree centrality: A meta-analysis of child and adolescent friendship networks

AbstractEmpirical articles vary considerably in how they measure child and adolescent friendship networks. This meta-analysis examines four methodological moderators of children’s and adolescents’ average outdegree centrality in friendship networks: boundary specification, operational definition of friendship, unlimited vs. fixed choice design, and roster vs. free recall design. Specifically, multi-level random effects models were conducted using 261 average outdegree centrality estimates from 71 English-language peer-reviewed articles and 55 unique datasets. There were no significant differences in average outdegree centrality for child and adolescent friendship networks bounded at the classroom, grade, and school-levels. Using a name generator focused on best/close friends yielded significantly lower average outdegree centrality estimates than using a name generator focused on friends. Fixed choice designs with under 10 nominations were associated with significantly lower estimates of average outdegree centrality while fixed choice designs with 10 or more nominations were associated with significantly higher estimates of average outdegree centrality than unlimited choice designs. Free recall designs were associated with significantly lower estimates of average outdegree centrality than roster designs. Results are discussed within the context of their implications for the future measurement of child and adolescent friendship networks.

Brain connectivity for subtypes of parkinson's disease using structural MRI.

Objective. Delineating Parkinson's disease (PD) into distinct subtypes is a major challenge. Most studies use clinical symptoms to label PD subtypes while our work uses an imaging-based data-mining approach to subtype PD. Our study comprises two major objectives - firstly, subtyping Parkinson's patients based on grey matter information from structural magnetic resonance imaging scans of human brains; secondly, comparative structural brain connectivity analysis of PD subtypes derived from the former step.Approach. Source-based-morphometry decomposition was performed on 131 Parkinson's patients and 78 healthy controls from PPMI dataset, to derive at components (regions) with significance in disease and high effect size. The loading coefficients of significant components were thresholded for arriving at subtypes. Further, regional grey matter maps of subtype-specific subjects were separately parcellated and employed for construction of subtype-specific association matrices using Pearson correlation. These association matrices were binarized using sparsity threshold and leveraged for structural brain connectivity analysis using network metrics.Main results. Two distinct Parkinson's subtypes (namely A and B) were detected employing loadings of two components satisfying the selection criteria, and a third subtype (AB) was detected, common to these two components. Subtype A subjects were highly weighted in inferior, middle and superior frontal gyri while subtype B subjects in inferior, middle and superior temporal gyri. Network metrics analyses through permutation test revealed significant inter-subtype differences (p < 0.05) in clustering coefficient, local efficiency, participation coefficient and betweenness centrality. Moreover, hubs were obtained using betweenness centrality and mean network degree.Significance. MRI-based data-driven subtypes show frontal and temporal lobes playing a key role in PD. Graph theory-driven brain network analyses could untangle subtype-specific differences in structural brain connections showing differential network architecture. Replication of these initial results in other Parkinson's datasets may be explored in future. Clinical Relevance- Investigating structural brain connections in Parkinson's disease may provide subtype-specific treatment.

Effects of Apex Size on Dissolution Profiles in the USP II Paddle Apparatus

The use of apex vessels may solve coning problems associated with dissolution testing. However, excessive dissolution acceleration can reduce the discriminatory power. This study aimed to clarify how different apex vessel sizes affect the dissolution behavior of cone-forming formulations. Five apex vessels with different heights, centralities, and compendial vessels were used. The paddle rotation speed at which the coning phenomenon resolved was measured using standard particles of different densities. Three model formulations—USP prednisone tablets, atorvastatin calcium hydrate tablets, and levofloxacin fine granules—were selected, and dissolution tests were conducted at 30–100 revolutions per minute (rpm). Compared to the compendial vessels, the disappearance of standard particles at the apex base at lower paddle speeds in apex vessels was observed. Standard particles tended to remain in the center of the apex vessels and disappear at rotational speeds comparable to those of the compendial vessels. Dissolution increased in an apex height-dependent manner in the model formulations, except for the atorvastatin calcium hydrate tablets at 50 rpm. For levofloxacin fine granules, dissolution was also improved by reducing the paddle agitation speed to 30 rpm in the compendial vessels. Differences in apex centrality by 3 mm did not affect the dissolution rate. Our results indicate that apex vessels with low apex heights have a mount-resolving effect, but the degree of dissolution improvement by avoiding the coning phenomenon depends on the formulation characteristics used in the dissolution tests.Graphical abstract

Alteration of functional connectivity network in population of objectively-defined subtle cognitive decline.

The objectively-defined subtle cognitive decline individuals had higher progression rates of cognitive decline and pathological deposition than healthy elderly, indicating a higher risk of progressing to Alzheimer's disease. However, little is known about the brain functional alterations during this stage. Thus, we aimed to investigate the functional network patterns in objectively-defined subtle cognitive decline cohort. Forty-two cognitive normal, 29 objectively-defined subtle cognitive decline and 55 mild cognitive impairment subjects were included based on neuropsychological measures from the Alzheimer's disease Neuroimaging Initiative dataset. Thirty cognitive normal, 22 objectively-defined subtle cognitive declines and 48 mild cognitive impairment had longitudinal MRI data. The degree centrality and eigenvector centrality for each participant were calculated by using resting-state functional MRI. For cross-sectional data, analysis of covariance was performed to detect between-group differences in degree centrality and eigenvector centrality after controlling age, sex and education. For longitudinal data, repeated measurement analysis of covariance was used for comparing the alterations during follow-up period among three groups. In order to classify the clinical significance, we correlated degree centrality and eigenvector centrality values to Alzheimer's disease biomarkers and cognitive function. The results of analysis of covariance showed significant between-group differences in eigenvector centrality and degree centrality in left superior temporal gyrus and left precuneus, respectively. Across groups, the eigenvector centrality value of left superior temporal gyrus was positively related to recognition scores in auditory verbal learning test, whereas the degree centrality value of left precuneus was positively associated with mini-mental state examination total score. For longitudinal data, the results of repeated measurement analysis of covariance indicated objectively-defined subtle cognitive decline group had the highest declined rate of both eigenvector centrality and degree centrality values than other groups. Our study showed an increased brain functional connectivity in objectively-defined subtle cognitive decline individuals at both local and global level, which were associated with Alzheimer's disease pathology and neuropsychological assessment. Moreover, we also observed a faster declined rate of functional network matrix in objectively-defined subtle cognitive decline individuals during the follow-ups.

Teacher prototypes in technology-enhanced instruction in elementary school second language acquisition: Comparing routine and emergency learning in different cultures

Over the past decade, learning cultures worldwide have been affected differently by the rapid spread of educational technology. During emergency distance learning, teachers had to adapt themselves to a new mode of learning. The purpose of this study was to compare technology-integrated instructional strategies and teacher prototypes in three learning cultures during routine and emergency learning based on the Five Spaces for Design in Education framework (Weiner et al., 2020). The participants were 31 teachers from three regions - Eastern Europe, Western Europe, and Northern America, all integrating the same adaptive digital learning environment in second language instruction. Participants' interviews were coded according to a three level tier of instructional strategies (n = 938) denoting the student's place in the learning process and level of independence, as well as a categorization of four teacher prototypes representing the degree of teacher centrality in the classroom (n = 764): sage, facilitator, guide, and partner. Chi-square tests highlighted the differences in instructional strategies and teacher centrality between the learning cultures in the three regions. The findings of the teacher prototype analysis showed a similar distribution of prototypes among the three regions, both in routine learning and emergency times. Regarding instructional strategies, each culture showed a unique tendency to specific strategies, while in the transition to emergency learning there was a convergence to strategies with the medium level of teacher control over students and a certain degree of student independence.

QOL-01. VARIABILITY IN ANXIETY AND DEPRESSION SYMPTOMS AFTER ELOQUENT GLIOMA RESECTION IS ASSOCIATED WITH CHANGES IN FUNCTIONAL CONNECTOMIC PROPERTIES

Abstract Little is known regarding how treatment-related changes in cerebral networks relate to symptoms of anxiety and depression in patients with glioma. Fifteen patients with left perisylvian glioma underwent resting-state fMRI and neuropsychological evaluation before and 1 month after resection. Symptoms of depression and anxiety were characterized with Beck Depression Inventory-II (BDI) and Beck Anxiety Inventory (BAI) Total scores and rates of clinically significant symptom burden. Change scores and reliable change classifications were also examined. Graph theoretical analysis was applied to fMRI connectivity matrices to calculate brain network properties. Comparison of pre- and postoperative measures were performed with Wilcoxon tests. Correlations between changes in anxiety and depression symptom measures and network properties were examined. Pre- and postoperative Total scores did not significantly differ though postoperative symptom burden trended toward reduction [Change: BDI=-1.93(5.73), BAI=-5.80(8.19)] with considerable interindividual variability noted [Change: BDI range=-12 to +6; BAI range=-18 to +6]. Preoperatively, at least mild symptoms were found in 27% of patients on BDI and 60% on BAI. Postoperatively, rates were the same for BDI while BAI was 33%. Using reliable change criteria, improvement was found in 13% of patients on BDI and 33% on BAI without any significant worsening. Significant postoperative connectivity decreases were observed in betweenness centrality [Change = -5.56(12.07), p = .031] and assortativity [Change=-.062(.096), p = .027]. Strong associations were found between pre- to postoperative differences in betweenness centrality and assortativity and changes in BDI [ρ(13)=.58 and .67, p&amp;lt; .02] and BAI Total scores [ρ(13)=.62 and .68, p&amp;lt; .01]. Anxiety and depression symptoms vary considerably postoperatively, though most patients do not show significant worsening. Variability in symptom change appears related to alterations in functional connectomics, with those showing increases in certain connectomic properties exhibiting worse postoperative anxiety and depression symptoms. Surgically-induced connectomic changes may coincide with or potentially contribute to psychological symptom differences in the postoperative setting.

Sex Differences in Complex Posttraumatic Stress Disorder Network among Chinese Young Adults.

Evidence suggests that sex differences commonly occur in trauma-related disorders. The current study aims to explore sex differences in complex posttraumatic stress disorder (CPTSD) symptom networks among Chinese young adults with childhood trauma. The current study utilized a representative sample of college students in Beijing and included 1416 participants (409 men and 907 women) who had childhood trauma experience. CPTSD symptoms were evaluated using the International Trauma Questionnaire. Regularized partial correlation network analysis and Bayesian network analysis were used to estimate the network structure and possible causality of CPTSD symptoms for both sexes. Male and female CPTSD symptom networks had differences in strength centrality and bridge centrality. Nightmares and feelings of failure had the highest strength centrality, and long-term upset and nightmares had the highest bridge centrality for men. Hypervigilance and feelings of failure had the highest strength centrality, and long-term upset and exaggerated startle response had the highest bridge centrality for women. The current study provides the first evidence of sex differences in the CPTSD symptom network among Chinese young adults with childhood trauma. Young men and women differed in highly central symptoms, which may speak to sex specificity in the main manifestations of CPTSD symptoms.

Chronic exposure to pesticides disrupts the bacterial and fungal co-existence and the cross-kingdom network characteristics of honey bee gut microbiome

Gut microbiome communities have a significant impact on bee health and disease and have been shown to be shaped by a variety of factors, including exposure to pesticides and inhive chemicals. However, it is unknown whether pesticide exposure affects the coexistence and cross-kingdom network parameters of bee gut microbiome communities because microbes may compete in the gut environment under different stressors. Therefore, we conducted additional analysis of the microbiome data from our previous study in which we discovered that exposure to two novel insecticides flupyradifurone (FPF) and sulfoxaflor (Sulf) or/and a fungicide, azoxystrobin (Azoxy) caused dysbiosis of bee gut microbiota that was associated with an increase in the relative abundance of opportunistic pathogens such as Serratia marcescens. We investigated for the first time the potential cross-kingdom fungal-bacterial interactions using co-occurrence pattern correlation and network analysis. We discovered that exposure to FPF or Sulf alone or in combination with Azoxy fungicide influenced the co-existence patterns of fungal and bacterial communities. Significant differences in degree centrality, closeness centrality, and eigenvector centrality distribution indices were also found in single and double-treatment groups compared to controls. The effects of FPF and Sulf alone on cross-kingdom parameters (bacterial to fungal node ratio, degree of centrality, closeness centrality, and eigenvector centrality) were distinct, but this was reversed when they were combined with Azoxy fungicide. The fungal and bacterial hub taxa identified differed, with only a few shared hubs across treatments, suggesting microbial cross-kingdom networks may be disrupted differently under different stressors. Our findings add to our understanding of pesticide effects on the bee gut microbiome and bee health in general, while also emphasizing the importance of cross-kingdom network analysis in future microbiome research.

Numerical study of heat transfer across in-line circular cylinders for low to moderate Reynolds numbers

A computational fluid dynamics (CFD) model is generated to study the fluid flow and heat transfer from a series of six cylinders arranged in a horizontal row. The momentum and energy equations were solved using the finite volume method, with convective terms discretized using a second-order upwind method and diffusion terms discretized using central differencing. A second-order implicit technique was used for time integration. Simulations were run with four different values of the free stream Reynolds numbers 100, 200, 300, 400 and three different values of the longitudinal pitch (SL ) 1.5D, 2D, 2.5D to analyze the heat transfer behavior with fluid flow over a series of horizontal cylinders. First the grid independence test and CFD model validation are performed with the exact relation available in the literature. Next, the numerical results obtained from the developed CFD model for the row of cylinders were compared with the previously published analytical model, and correlation available in the literature, and were found to be in good agreement. The average Nusselt number calculated from the analytical and numerical models falls in the range of 8 to 10 for free stream Reynolds number equal to 100 for all values of dimensionless longitudinal pitches. Moreover, for the free stream Reynolds number equal to 400 with longitudinal pitch of 2.5D, the values of the average Nusselt number reach up to double the above-mentioned range. The maximum percentage error between the average Nusselt number obtained from the numerical and analytical solutions was less than 20% for larger free stream Reynolds number. The study found that the average Nusselt number for the array of cylinders increases with both the free stream Reynolds number and the dimensionless longitudinal pitch ratio increments. This information can be used to design more efficient heat exchangers or other fluid systems involving arrays of cylinders.

Sampling variability and centrality score comparisons in archaeological network analysis: A case study of the San Pedro Valley, Arizona

Archaeological network analysis often focuses on networks in which ties between sites reflect some sort of similarity, such as in artifact assemblages. Site centrality is often of interest, but an apparent difference in two sites’ centrality may not be meaningful once sampling variability is considered. We investigate bootstrap assessments of sampling variability in centrality scores of a set of late pre-Hispanic archaeological sites in the San Pedro Valley, U.S. Southwest, for which ceramic assemblage data can be transformed into networks of ceramic similarity. We considered a variety of bootstrap confidence intervals for site eigenvector centrality scores and the implications of these intervals for interpretation of the site’s structural importance. In analysis of the San Pedro Valley for CE 1300–1349, small differences among site centrality were not statistically distinguishable, but moderate to large differences were, with conclusions consistent across methods of constructing bootstrap confidence intervals. Similar patterns were evident when examining a broader region in which the Valley is located. It appears that substantive interpretation of site centrality differences often will be justified.