Intragroup Homogeneity Research Articles

An Algorithm Based on An Efficient Cost Model to Form Learning Groups

The purpose of this research is to form learning groups that are intra-homogeneous (a high level of similarity across student GPAs inside a group), inter-homogeneous (similarity or balance in the degree of homogeneity between groups), and balanced in size. The algorithm proposed for this purpose treats the learning group formation as an assignment-type optimization problem where it seeks to find a feasible least-cost assignment of a given set of students to a given set of learning groups. It is referred to as GAGF (Generalized Assignment Strategy for Group Formation). It is based on an efficient cost model, which performs three tasks: measuring the cost of assigning students to a learning group, relating each improvement in assignment cost to increased intra-group homogeneity and group size balance, and bringing the intra-homogeneity of the groups to a reference value (a specific level of homogeneity), which improves inter-homogeneity. Experimental results have shown that the GAGF algorithm is effective at constructing intra- and inter-homogeneous learning groups with balanced sizes. It was found that using GAGF attained an improvement of more than 29% in intra-group homogeneity when compared to both related work and self-formation methods. It significantly improved inter-group homogeneity, outperforming related works by 79.75%.

DRG payment for major pancreatic surgery: analysis of resource consumption and suggestions from a tertiary hospital in China.

To investigate the cost homogeneity within the Diagnosis-Related Group (DRG) "major operation of pancreas and liver, with general complications or comorbidities" (HB13), its cost-influencing factors, and to propose suggestions for better grouping efficacy. Medical and insurance settlement data of inpatients covered by the DRG payment system at the author's institution were collected from March 15, 2022 to December 31, 2023. The cost homogeneity of group HB13 was assessed using the coefficient of variation (CV). Clinical factors that may have an impact on hospitalization cost for patients undergoing pancreatic surgery were identified through a semi-structured interview administered to the pancreatic surgeons in author's department, their significance was analyzed using multiple linear regression, along with their impact on the cost of different service categories. A proposal to subdivide HB13 was made and evaluated by CV and t-test. The CV of the HB13 group was 0.4. Robotic-assisted surgery and pancreaticoduodenectomy were two independent factors that significantly affected the total cost. Patients undergoing robotic-assisted surgery have an average increase of 41,873 CNY in total cost, primarily derived from operation fee. Patients undergoing pancreaticoduodenectomy have an average increase of 37,487 CNY in total cost, with significant increases across all service categories. HB13 was subdivided based on whether pancreaticoduodenectomy was performed. The newly formed groups exhibited lower CVs than the original HB13. The cost homogeneity of HB13 was lower than that of other DRG groups in author's department. It is recommended to introduce a supplementary payment for patients requiring robotic-assisted surgery, to guarantee their access to this advanced technology. It is recommended to establish a new group with higher payment standard for patients undergoing pancreaticoduodenectomy. A tiered CV criterion for the evaluation of grouping efficacy is recommended to increase intra-group homogeneity, facilitating a better allocation of health insurance funds, and the prevention of unintended negative outcomes such as service cuts and cherry-picking.

Group-Based Federated Knowledge Distillation Intrusion Detection

Intrusion detection based on federated learning allows the sharing of more high-quality attack samples to improve the intrusion detection performance of local models while preserving the privacy of local data. Most research on federated learning intrusion detection requires local models to be homogeneous. However, in practical scenarios, local models often include both homogeneous and heterogeneous models due to differences in hardware capabilities and business requirements among nodes. Additionally, there is still room for improvement in the accuracy of recognizing novel attacks in existing researches. To address the challenges mentioned above, we propose a Group-based Federated Knowledge Distillation Intrusion Detection approach. First, through a step-by-step grouping method, we achieve the grouping effect of intra-group homogeneity and inter-group heterogeneity, laying the foundation for reducing the aggregation difficulty in intra-group homogenous aggregation and inter-group heterogeneous aggregation. Second, in intra-group homogenous aggregation, a dual-objective optimization model is employed to quantify the learning quality of local models. Weight coefficients are assigned based on the learning quality to perform weighted aggregation. Lastly, in inter-group heterogeneous aggregation, the group leader model’s learning quality is used to classify and aggregate local soft labels, generating global soft labels. Group leader models utilize global soft labels for knowledge distillation to acquire knowledge from heterogeneous models. Experimental results on NSL-KDD and UNSW-NB datasets demonstrate the superiority of our proposed method over other algorithms.

A Group-Based Approach to Measuring Polarization

Despite polarization’s growing importance in social science, its quantitative measurement has lagged behind its conceptual development. Political and social polarization are group-based phenomena characterized by intergroup heterogeneity and intragroup homogeneity, but existing measures capture only one of these features or make it difficult to compare across cases or over time. To bring the concept and measurement of polarization into closer alignment, I introduce the cluster-polarization coefficient (CPC), a measure of multimodality that allows scholars to incorporate multiple variables and compare across contexts with varying numbers of parties or social groups. Three applications to elite and mass polarization demonstrate that the CPC returns substantively sensible results, and an open-source software package implements the measure.

L1 Transfer in Chinese EFL Learners’ Use of Thematic Progression in English Argumentative Writing

This study addresses L1 transfer in Chinese EFL learners’ use of thematic progression in English argumentative writing. Through a series of statistical analyses of the data collected from argumentative essays written by Chinese and American university students, the study finds that the overuse of thematic progression patterns in English writing is under the influence of Chinese EFL learners’ native language both linguistically and conceptually. Tests of potential effects of intra-group homogeneity and intra-L1-group congruity provide convincing evidence for the identification of L1 transfer. In addition, the study further explores the underlying causes of L1 transfer both at linguistic and conceptual levels.

Heterogeneity, coordination and competition: the distribution of individual preferences in organisations

This paper experimentally investigates how inter- and intragroup heterogeneity (related to individual cooperative preferences) influences intergroup coordination. Coordination incentives are implemented through an intergroup rank-order competition. A pre-competition phase determines how individual heterogeneity is distributed across groups within an organisation. Two treatments are compared: a horizontal-heterogeneity treatment (H-Hetero, baseline), where individual differences are randomly distributed within and between groups, and a vertical-heterogeneity treatment (V-Hetero), in which groups are internally homogeneous but differ considerably from each other. In contrast to expectations, I find that vertical (intergroup) heterogeneity, when being accompanied by intragroup homogeneity, does not reduce the ability of groups to coordinate and keeps overall performance at very high levels. Indeed, subjects react more strongly to the coordination/competition incentives in vertically heterogenous organisations. Further analysis suggests that group dynamics are mainly driven by a positive orientation towards inequality (distributional preferences) of the members of the initially least cooperative groups, and their non-conditional cooperative behaviour. These results have implications for the design of group-based incentives and governance in organisations and societies.

Determining the Area of Ancestral Origin for Individuals From North Eurasia Based on 5,229 SNP Markers.

Currently available genetic tools effectively distinguish between different continental origins. However, North Eurasia, which constitutes one-third of the world’s largest continent, remains severely underrepresented. The dataset used in this study represents 266 populations from 12 North Eurasian countries, including most of the ethnic diversity across Russia’s vast territory. A total of 1,883 samples were genotyped using the Illumina Infinium Omni5Exome-4 v1.3 BeadChip. Three principal components were computed for the entire dataset using three iterations for outlier removal. It allowed the merging of 266 populations into larger groups while maintaining intragroup homogeneity, so 29 ethnic geographic groups were formed that were genetically distinguishable enough to trace individual ancestry. Several feature selection methods, including the random forest algorithm, were tested to estimate the number of genetic markers needed to differentiate between the groups; 5,229 ancestry-informative SNPs were selected. We tested various classifiers supporting multiple classes and output values for each class that could be interpreted as probabilities. The logistic regression was chosen as the best mathematical model for predicting ancestral populations. The machine learning algorithm for inferring an ancestral ethnic geographic group was implemented in the original software “Homeland” fitted with the interface module, the prediction module, and the cartographic module. Examples of geographic maps showing the likelihood of geographic ancestry for individuals from different regions of North Eurasia are provided. Validating methods show that the highest number of ethnic geographic group predictions with almost absolute accuracy and sensitivity was observed for South and Central Siberia, Far East, and Kamchatka. The total accuracy of prediction of one of 29 ethnic geographic groups reached 71%. The proposed method can be employed to predict ancestries from the populations of Russia and its neighbor states. It can be used for the needs of forensic science and genetic genealogy.

EXPLORING CROSSLINGUISTIC INFLUENCE IN GENDER MARKING IN SPANISH

AbstractIn the current study, we examined the role of first-language (L1) influence on the additional-language development of grammatical gender marking in Spanish. The participants were L1 speakers of English or French (N = 215), who were learning Spanish and who were at three instructional levels. The data came from their use of gender marking in noun-modifier pairs in an argumentative essay. We adopted the unified methodological framework developed by Scott Jarvis and we applied insights from variationist second language acquisition to contribute to the discussion about whether learners’ L1 impacts variability in targetlike gender marking in additional-language Spanish. Specifically, we designed our study to investigate four types of evidence that Jarvis identified (intragroup homogeneity, intergroup heterogeneity, cross-language congruity, and intralingual contrasts), and we used variationist methods to account for other factors that are known to impact variable use of gender marking. The quantitative analyses supported each type of evidence, consequently demonstrating that these learners’ L1 influenced their variable use of gender marking in Spanish. We concluded by reflecting on the contributions that the current study has made to the understanding of gender marking in additional-language Spanish and to research on L1 influence more generally.

Parsing the Mechanisms Underlying Ingroup Facial Resemblance.

People prefer to form relationships with people like themselves—a tendency that extends even to facial appearance, resulting in groups whose members look alike. Here, we investigated the mechanisms underlying homophilic resemblance using facial photos of fraternity/sorority members from two time points: before joining the group and after belonging to the group for three years. Analyses of both subjective trait impressions and objective face-shape measurements revealed that not only did group members look alike, they resembled one another even before joining the group. Moreover, photos of potential fraternity recruits revealed that facial appearance predicted both the group that individuals sought to join and the group’s likelihood of accepting them. Individuals, therefore, seek to join groups consisting of people who look like them, and the groups preferentially accept new members who resemble those already in the group. This bidirectional preference for homophily likely perpetuates intragroup homogeneity, suggesting potential implications beyond appearance.

Women's knowledge and attitudes towards cervical cancer prevention: A qualitative study in the Spanish context.

To explore the knowledge, attitudes and practices related to cervical cancer and its prevention in Spain. Worldwide, women's knowledge about cervical cancer is low, and their attitudes towards its prevention are good, but they do not correlate with the screening uptake. Although the rates of Spanish women performing cervical cancer screening are mostly acceptable, their knowledge and attitudes about it have not been explored. Qualitative descriptive study. Three focus groups were conducted, with 21 women aged 25 to 65years. Participants were recruited through convenience sampling. For intragroup homogeneity, women participated in age groups. The COREQ reporting guidelines were used. Women expressed their knowledge about cervical cancer was low. None of the participants identified the human papillomavirus as a cause of cervical cancer, nor did they mention the vaccine as a preventive measure. They all knew about the screening existence, but not about its frequency nor target population. About the attitudes and practice, 18 women had an appropriate screening, and they were favourable to this health check, claiming an increase in its frequency. Nineteen women claimed they had not received enough information from the healthcare system and a lack of social awareness in comparison with breast cancer. They demanded from the professionals more health education, a reminder of their appointments and a report of the Pap test results. There was a self-perceived low level of knowledge about cervical cancer risk factors and its prevention in the participants. However, they expressed favourable attitudes towards screening, and they demanded more information about cervical cancer and its prevention measures, and they regretted its low social awareness. Midwives, general nurses and other nurse specialists may have a leading position in health education for cervical cancer prevention in different population levels.

Network analysis on Fourier-transform infrared (FTIR) spectroscopic data sets in an Eigen space layout: Introducing a novel approach for analysing wine samples

In the present work, Eigen-directed network analysis for Fourier-transform infrared (FTIR) spectroscopic data sets of wine samples was introduced. A network can generally be viewed as a collection of nodes connected to each other through links, often also called edges. Herein, each node in the network represents a sample and the dissimilarity weight associated with the difference between the two connected nodes is described by the edge. The utility of the approach was tested by analysing a collection of 148 wine samples. The networking on FTIR data sets of these samples in the Eigen space layout was found to impart required aesthetic values as well as the chemical significance to the nodes positioning. The proposed approach successfully captured the compositional differences among the analysed wine samples and classified them in two groups. The Eigen-directed network analysis also allowed a swift assessment regarding inter- and intra-group homogeneity. Homogeneous groups were found to contain nodes with high degree of adjacency and edges with smaller lengths. In comparative study, the proposed approach was found to outperform the network analysis in force-directed layout and principal component analysis. In summary, the proposed Eigen-directed network analysis provided a simplified illustration of highly correlated spectral data sets enabling a swift and intuitive interpretation.

Population-based biobank for analyzing the frequencies of clinically relevant DNA markers in the Russian population: bioinformatic aspects

One of the tasks of population-based biobanks is to determine the frequencies of clinically relevant genetic polymorphisms in the population. The population of Russia is very heterogeneous both ethnically and genetically. Therefore, the frequencies of genetic markers are in demand not in one sample, but in a series of samples reflecting the heterogeneity of the gene pool of different peoples and regions.Aim. To divide the population of Russia and neighboring countries into population groups meeting certain conditions, as well as having a representative sample in existing data and biobanks.Material and methods. We developed a method for combining populations into larger groups with maintaining intragroup homogeneity based on the principal components analysis with K-means clustering, followed by refinement of clustering for higher homogeneity and a more equal distribution of group sizes using FST distances. The technology has been adjusted using the example of the Biobank of Northern Eurasia. Therefore, the material was the genome-wide data on 4.5 million genetic markers for 1,883 samples representing 247 populations of Russia and neighboring countries from this biobank. The developed approach, the resulting set of populations and related map can be applied for other collections of biomaterials from Russian populations.Results. Application of this approach made it possible to divide the entire population of Russia and neighboring countries into 29 ethnogeographic groups, characterized by relative genetic homogeneity. This set of populations is recommended as a baseline for population screenings to identify the frequency of any genetic markers among the population of Russia. A map has been constructed showing the division of population into 29 ethnogeographic areas.Conclusion. On the basis of a reliable genome-wide data, the zoning of gene pool of the Russian population was carried out. We identified ethnogeographic groups with intergroup contrasting allele frequencies, but at the same time with relatively homogeneous intragroup parameters. The resulting map and register of groups can be used in population genetic, medical genetic and pharmacogenetic studies.

The impact of social capital-based selection practices on talent management: evidence from telecom MNCs in Bangladesh

The purpose of this paper is to explore how social capital-based selection practices influence talent management (TM) in multinational companies (MNC). To date, little is known about how this relationship fulfills business priorities. The study collected empirical data through in-depth interviews with 12 managers from three telecommunication firms in Bangladesh. Our study found a significant influence of social capital-based selection practices on TM. We found that the relational and cognitive dimensions of social capital were the major drivers of selection practices that influenced a talent search process. Trust and cultural norms especially within networking relationships through shared narratives, codes and language, and vision affected TM involving selection practices. Therefore, the role of existing human resource management (HRM) system for selection practices was found inadequate without the integration of social capital. We report that upper-level managers have the capability to shape and implement a TM system that benefits candidates with network ties of informal social relationships, which consequently marginalized formal HRM practices. HRM system is only an administrative function alongside the dominant social capital-based TM selection practices. For practical implications, upper-level managers used social capital-based selection practices beyond HRM systems that were deemed pragmatic in selecting the right candidates for positions in organizations favoring intra-group homogeneity.

Patterns recognition methods to study genotypic similarity in flood-irrigated rice

ABSTRACT Genetic diversity studies are performed based on information on a set of traits measured in a group of genotypes, considering one or more environments. The pattern recognition methods allow classifying genotypes from a set of important agronomic information. Thus, this study aimed to present and compare pattern recognition methods to inquire about the similarity of environments and genotypes in flood-irrigated rice for the recommendation of cultivars. The experim>ents were performed in the municipalities of Leopoldina, Lambari, and Janauba, state of Minas Gerais, Brazil. To evaluate the pattern of similarity, 25 rice genotypes in three environments belonging to the flood-irrigated rice breeding program were used. Among these genotypes, five cultivars were used as an experimental control for the grain yield, the height of the plant, flowering, panicle length, grains filled by panicles, percentages of grains filled by panicles, in the 2012/2013 agricultural year. The methods us>ed were mixtures of multivariate normal distributions and density-based clustering algorithm. It was observed, therefore, that the genotypes are distributed in three distinct groups, in which there are intragroup homogeneity and intergroup heterogeneity for the agronomic traits of the flooded rice culture. The methods >used to assess the dissimilarity of environments using pattern recognition methods were efficient in classifying flooded rice irrigated environments.

Label-Free Infrared Spectral Histology of Skin Tissue Part I: Impact of Lumican on Extracellular Matrix Integrity.

Proteoglycans (PG) play an important role in maintaining the extracellular matrix (ECM) integrity. Lumican, a small leucine rich PG, is one such actor capable of regulating such properties. In this study, the integrity of the dermis of lumican-deleted Lum–/– vs. wild-type mice was investigated by conventional histology and by infrared spectral histology (IRSH). Infrared spectroscopy is a non-invasive, rapid, label-free and sensitive technique that allows to probe molecular vibrations of biomolecules present in a tissue. Our IRSH results obtained on control (WT, n = 3) and Lum–/– (n = 3) mice showed that different histological structures were identified by using K-means clustering and validated by hematoxylin eosin saffron (HES) staining. Furthermore, an important increase of the dermis thickness was observed in Lum–/– compared to WT mice. In terms of structural information, analysis of the spectral images also revealed an intra-group homogeneity and inter-group heterogeneity. In addition, type I collagen contribution was evaluated by HES and picrosirius red staining as well as with IRSH. Both techniques showed a strong remodeling of the ECM in Lum–/– mice due to the looseness of collagen fibers in the increased dermis space. These results confirmed the impact of lumican on the ECM integrity. The loss of collagen fibers organization due to the absence of lumican can potentially increase the accessibility of anti-cancer drugs to the tumor. These results are qualitatively interesting and would need further structural characterization of type I collagen fibers in terms of size, organization, and orientation.

Dentofacial biometry as a discriminant factor in the identification of remote Amazon indigenous populations

This study aimed to examine the role of dentofacial morphology in discriminating semi-isolated indigenous groups. These populations present a similar pattern of dietary habits. Studies in human genetics have reported a large intertribal genetic distance and low intratribal variation. This study was conducted following the Strengthening the Reporting of Observational Studies in Epidemiology guidelines. Face dimensions were measured through facial photogrammetry, and dental arches and tooth size were evaluated using plaster models. A total of 98 subjects in the permanent dentition and belonging to 4 indigenous groups were analyzed: Arara-Iriri (n=20), Arara-Laranjal (n=33), Assurini (n=25), and Xicrin-Kayapó (n=20). The random and systematic errors were verified using the Dahlberg formula and the intraclass correlation coefficient (ICC), respectively. In order to evaluate the discrimination of the variables to identify the indigenous groups, a discriminant analysis was performed (P<0.05). A small causal error (Dahlberg, 0.13-1.81) and excellent replicability (ICC, 0.75-0.99) for face dimensions as well as for models (Dahlberg, 0.10-0.68; ICC, 0.94-0.99) were observed. The discriminant analysis allowed the identification of 4 populations by facial and dental arch dimensions and tooth size. Dentofacial biometry revealed an accuracy of 98% for females and 100% for males, which confirms a high intragroup homogeneity and considerable intergroup heterogeneity for dentofacial features. Biometric measurements of the human face added with tooth size and dental arch dimensions are very useful to identify remote indigenous populations with high accuracy. Supported by previous studies in human genetics, these findings reinforce the role of genetic variation in the determination of dentofacial features.

A Genetic Algorithm Approach for Inter and Intra Homogeneous Grouping Considering Multi-student Characteristics

This paper addresses the problem of group formation in collaborative learning by considering the students’ characteristics. The proposed solution is based on a Genetic Algorithm (GA), which minimizes an objective function that has two main aims. Indeed, the proposed GA’s fitness function helps to achieve two objectives: Fairness in the formation of different groups, resulting in intergroup homogeneity, and a low gap in the levels of students within a group, which corresponds to intragroup homogeneity. Exhaustive experiments were conducted using three different sizes of randomly generated data sets and several crossover operators. Indeed, the order crossover and the crossovers based on random keys representation are experimented. The reported results show that the proposed approach guarantees the efficient grouping of students. In addition, comparisons with existing approaches based on GA confirm the ability of the proposed approach to provide greater intergroup and intragroup homogeneity. In addition, the uniform crossover based on random keys representation ensures better grouping quality than do the other experimented crossover operators.

Изменчивость репродуктивной способности Lonicera caerulea (Caprifoliaceae) в сейсмоактивной зоне Горного Алтая (Северо-Чуйский хр., р. Кызыл-Ярык)

Seismically active areas of tectonic faults create specific inhomogeneous living conditions of plant populations and can thereby determine their structure. Studies of the reaction of plant reproductive structures to geoecological anomalies associated with active tectonic processes are practically absent. The aim of this work was to study the variability of the reproductive characteristics of Lonicera caerulea subsp. altaica plants in the local seismic zone of the Altai Mountains. We carried out studies in 2017 in the valley of the Kyzyl-Yaryk river (Altai Republic, Kosh-Agachsky district) (See Fig. 1), which was formed in the junction zone of seismic-generating faults active in the Holocene that are the boundaries of the North Chuy Range, Kurai intermountain basin and Chagan-Uzun massif and separating the Kurai and Chuysky depressions. We isolated 5 micropopulations of the Altai subspecies of blue honeysuckle - L. caerulea subsp. altaica in areas differing in volumetric activity of the radon emanation field (262-1162 Bq / m3) for research. Fifty fruits were selected in each micropopulation of L. caerulea subsp. altaica from 20 plants. We examined the morphometric characteristics and taste of the fruits, the number of full seeds and immature ovules in the fruits, the ratio of the number of full seeds to the total number of seeds and ovules, the correlation between the characters, as well as the seed germination capacity and germination readiness. The taste of the fruits was evaluated by the organoleptic method on a 5-point scale of taste variations based on the degree of bitterness in the fruits. To determine seed germinating capacity and germination readiness, germination was performed in Petri dishes at room temperature. We evaluated germination readiness on the 5th day, where n is the number of seeds and N is the number of seeds germinated during this period. For each micropopulation, we analyzed data for intragroup homogeneity using the χ2 method. Student’s t-test, Fisher’s exact test and one-way ANOVA analysis were used to test statistically significant differences in reproductive characteristics, as well as to assess the correlation between them. The analysis of variance (ANOVA) showed that the values of the Fisher criterion for the length, width, index, weight of the fruit and the number of seeds in them considerably exceed the critical value, which indicates a reliable effect of the place of plant growth on all these parameters at a 95-99% probability level. For individual test micropopulations, significant differences were found in the morphometric characteristics and seed productivity of plant fruits in comparison to the control micropopulation (the area with the lowest level of radon emanation field) (See Fig. 2, 3, 4 and 5). An analysis of the frequency of occurrence of plants with different weight and seed productivity of the fruits from the studied micropopulations showed a shift in the distribution of these parameters towards larger values, compared to the control micropopulation (See Fig. 6). The seeds collected in the control micropopulation were characterized by the least germination (See Fig. 8) and the shortest germination period (See Fig. 9). In the studied population, the average and close degree of correlation between the weight of the fruit and the number of full seeds was established; the reliability of the correlation varied depending on the place of plant growth. Plants in the L. caerulea subsp. altaica in the valley of the Kyzyl-Yaryk river were characterized by high polymorphism of the fruit shape. The frequency of occurrence of plants with oval fruits was significantly lower than in populations of L. caerulea subsp. altaica in other areas of the Altai Mountains. In micropopulations under the influence of a higher level of volumetric activity of subsoil radon, the variety of fruit shapes (See Fig. 3) and their taste variations (See Fig. 7) increased, including an increase in the expression of the recessive trait L. caerulea, the absence of bitter fruits (bitter-free fruits). The correlation between the level of radon emanation and the frequency of occurrence of plants with bitter fruits was significant at p &lt;0.01. The influence of the level of radon emanation on the variability of morphometric characteristics of the fruit, seed productivity, germination and germination energy of the seeds was not significant. The heterogeneity of the population of the L. caerulea subsp. altaica, according to the features of the generative sphere, suggests a possible influence of a complex of factors associated with active tectonic processes on the formation and development of plant reproductive organs.

Severe and uniform bi-atrial remodeling measured by dominant frequency analysis in persistent atrial fibrillation unresponsive to ablation.

High values of ECG and intracardiac dominant frequency (DF) are indicative of significant atrial remodeling in persistent atrial fibrillation (peAF). We hypothesized that patients with peAF unresponsive to ablation display higher ECG and intracardiac DFs than those remaining in sinus rhythm (SR) on the long term. Forty consecutive patients underwent stepwise ablation for peAF (sustained duration 19 ± 11months). Electrograms were recorded before ablation at 13 left atrium (LA) sites and at the right atrial appendage (RAA) and coronary sinus (CS) synchronously to the ECG. DF was defined as the highest peak within the power spectrum. peAF was terminated within the LA in 28 patients (left-terminated [LT]), whereas 12 patients remaining in AF after ablation (not left-terminated [NLT]) were cardioverted. Over a mean follow-up of 34 ± 14months, all 12 NLT patients had a recurrence. Of the LT patients, 71% had a recurrence (20/28, LT_Rec), while 29% remained in SR throughout the follow-up (8/28, LT_SR). DF values and correlations between pairs of LA appendage (LAA), RAA, and CS DFs showed distinctive patterns among the subgroups. The NLT subgroup displayed the highest ECG and intracardiac DFs, with strong intragroup homogeneity between pairs of CS and LAA DFs, and to a lesser extent between pairs of CS and RAA DFs. Conversely, the LT_SR subgroup showed the lowest DFs, with significant intragroup heterogeneity between pairs of CS and both LAA and RAA DFs. Patients with peAF unresponsive to ablation show high surface and intracardiac DFs indicative of severe and uniform bi-atrial remodeling.

Relative Price Dynamics in the Euro Area: Where Do We Stand?

We propose a novel metric to evaluate price developments within the euro area (EA), which involves the decomposition of the overall variability of cross country inflation rates into common and idiosyncratic labor cost and markup components. The analysis yields several interesting results. First, over the period 1978-2015, inflation variability in the EA reflects most of all idiosyncratic (country-specific) developments in unit labor costs (ULC). This sharply contrasts with what we find for the US states, where price dynamics to a much greater extent reflects common developments in costs and profits, consistently with the role played by the greater mobility of capital and labor. Second, when we apply our approach to data for two subgroups of countries, namely Core and Non-core countries, we find that they both display higher intra-group homogeneity, in that the role of the subgroup-specific common components in explaining inflation variability increases, while idiosyncratic developments in ULC become correspondingly less relevant. Third, over the more recent period (1999-2015) in the Core countries the idiosyncratic component due to price markups has become the dominant driver of the variability of inflation, a pattern similar to the one we detect for the US. Our analysis also sheds light on the adjustment mechanisms to asymmetric, or country specific, shocks. Using a panel VAR approach we find that price changes driven by diverging developments of ULC are reflected into trade balance adjustments that are costly from the point of view of the smooth functioning of the currency area.