Temperature-dependent electronic structure and ferromagnetism in the d=oo Hubbard model studied by a modfied perturbation theory

The infinite-dimensional Hubbard model is studied by means of a modified perturbation theory. The approach reduces to the iterative perturbation theory for weak coupling. It is exact in the atomic limit and correctly reproduces the dispersions and the weights of the Hubbard bands in the strong-coupling regime for arbitrary fillings. Results are presented for the hyper-cubic and an fcc-type lattice. For the latter we find ferromagnetic solutions. The filling-dependent Curie temperature is compared with the results of a recent Quantum Monte Carlo study.Comment: RevTeX, 5 pages, 6 eps figures included, Phys. Rev. B (in press), Ref. 16 correcte

Drude weight and dc-conductivity of correlated electrons

The Drude weight $D$ and the dc-conductivity $\sigma_{dc} (T)$ of strongly correlated electrons are investigated theoretically. Analytic results are derived for the homogeneous phase of the Hubbard model in $d = \infty$ dimensions, and for spinless fermions in this limit with $1/d$-corrections systematically included to lowest order. It is found that $\sigma_{dc}(T)$ is finite for all $T > 0$, displaying Fermi liquid behavior, $\sigma_{dc} \propto 1/T^2$, at low temperatures. The validity of this result for finite dimensions is examined by investigating the importance of Umklapp scattering processes and vertex corrections. A finite dc-conductivity for $T > 0$ is argued to be a generic feature of correlated lattice electrons in not too low dimensions.Comment: 15 pages, uuencoded compressed PS-fil

Effect of the fat composition of a single high-fat meal on inflammatory markers in healthy young women

The aim of the present study was to examine the effect of a single high-fat meal with different fat quality on circulating inflammatory markers and gene expression in peripheral blood mononuclear cells (PBMC) to elucidate the role of fat quality on postprandial inflammation. A postprandial study with fourteen healthy females consuming three test meals with different fat quality was performed. Test days were separated by 2 weeks. Fasting and postprandial blood samples at 3 and 6 h after intake were analysed. The test meal consisted of three cakes enriched with coconut fat (43 % energy as saturated fat and 1 % energy as a-linolenic acid (ALA)), linseed oil (14 % energy as ALA and 30 % energy as saturated fat) and cod liver oil (5 % energy as EPA and DHA and 5 % energy as ALA in addition to 31 % energy as saturated fat). In addition, ex vivo PBMC experiments were performed in eight healthy subjects investigating the effects of EPA and ALA on release and gene expression of inflammatory markers. The IL-8 mRNA level was significantly increased after intake of the cod liver oil cake at 6 h compared with fasting level, which was significantly different from the effect observed after the intake of linseed cake. In contrast, no effect was seen on circulating level of IL-8. In addition, ALA and EPA were shown to elicit different effects on the release and mRNA expression levels of inflammatory markers in PBMC cultured ex vivo, with EPA having the most prominent proinflammatory potentia

Conductivity in a symmetry broken phase: Spinless fermions with 1/d1/d corrections

The dynamic conductivity $\sigma(\omega)$ of strongly correlated electrons in a symmetry broken phase is investigated in the present work. The model considered consists of spinless fermions with repulsive interaction on a simple cubic lattice. The investigated symmetry broken phase is the charge density wave (CDW) with wave vector $Q=(\pi,\pi,\pi)^\dagger$ which occurs at half-filling. The calculations are based on the high dimensional approach, i.e. an expansion in the inverse dimension $1/d$ is used. The finite dimensionality is accounted for by the inclusion of linear terms in $1/d$ and the true finite dimensional DOS. Special care is paid to the setup of a conserving approximation in the sense of Baym/Kadanoff without inconsistencies. The resulting Bethe-Salpeter equation is solved for the dynamic conductivity in the non symmetry broken and in the symmetry broken phase (AB-CDW). The dc-conductivity is reduced drastically in the CDW. Yet it does not vanish in the limit $T \to 0$ due to a subtle cancellation of diverging mobility and vanishing DOS. In the dynamic conductivity $\sigma(\omega)$ the energy gap induced by the symmetry breaking is clearly discernible. In addition, the vertex corrections of order $1/d$ lead to an excitonic resonance lying within the gap.Comment: 23 pages, 19 figures included with psfig, Revtex; Physical Review B15, in press (October/November 1996) depending on the printer/screen driver, it might be necessary to comment out figures 3,4,5,10,11,12,19 and have them printed separatel

Accuracy of CT Colonography for Detection of Large Adenomas and Cancers

Background Computed tomographic (CT) colonography is a noninvasive option in screening for colorectal cancer. However, its accuracy as a screening tool in asymptomatic adults has not been well defined. Methods We recruited 2600 asymptomatic study participants, 50 years of age or older, at 15 study centers. CT colonographic images were acquired with the use of standard bowel preparation, stool and fluid tagging, mechanical insufflation, and multidetector-row CT scanners (with 16 or more rows). Radiologists trained in CT colonography reported all lesions measuring 5 mm or more in diameter. Optical colonoscopy and histologic review were performed according to established clinical protocols at each center and served as the reference standard. The primary end point was detection by CT colonography of histologically confirmed large adenomas and adenocarcinomas (10 mm in diameter or larger) that had been detected by colonoscopy; detection of smaller colorectal lesions (6 to 9 mm in diameter) was also evaluated. Results Complete data were available for 2531 participants (97%). For large adenomas and cancers, the mean (±SE) per-patient estimates of the sensitivity, specificity, positive and negative predictive values, and area under the receiver-operating-characteristic curve for CT colonography were 0.90±0.03, 0.86±0.02, 0.23±0.02, 0.99± Conclusions In this study of asymptomatic adults, CT colonographic screening identified 90% of subjects with adenomas or cancers measuring 10 mm or more in diameter. These findings augment published data on the role of CT colonography in screening patients with an average risk of colorectal cancer. (ClinicalTrials.gov number, NCT00084929; American College of Radiology Imaging Network [ACRIN] number, 6664.

Dynamical mean-field study of ferromagnetism in the periodic Anderson model

The ferromagnetic phase diagram of the periodic Anderson model is calculated using dynamical mean-field theory in combination with the modified perturbation theory. Concentrating on the intermediate valence regime, the phase boundaries are established as function of the total electron density, the position of the atomic level and the hybridization strength. The main contribution to the magnetic moment stems from the f-electrons. The conduction band polarization is, depending on the system parameters either parallel or antiparallel to the f-magnetization. By investigating the densities of states, one observes that the change of sign of the conduction band polarization is closely connected to the hybridization gap, which is only apparent in the case of almost complete polarization of the f-electrons. Finite-temperature calculations are also performed, the Curie temperature as function of electron density and f-level position are determined. In the intermediate-valence regime, the phase transitions are found to be of second order.Comment: 12 pages, 11 figures, accepted by Phys. Rev.

Supervised Anomaly Detection in Univariate Time-Series Using 1D Convolutional Siamese Networks

In time-series data analysis, identifying anomalies is crucial for maintaining data integrity and ensuring accurate analyses and decision-making. Anomalies can compromise data quality and operational efficiency. The complexity of time-series data, with its temporal dependencies and potential non-stationarity, makes anomaly detection challenging but essential. Our research introduces ADSiamNet, a 1D Convolutional Neural Network-based Siamese network model for anomaly detection and rectification. ADSiamNet effectively identifies localized patterns in time-series data and smooths detected anomalies using a quantile-based technique. In tests with physical activity data from Actigraph watches and MOX2-5 sensors, ADSiamNet achieved accuracies of 98.65% and 85.0%, respectively, outperforming other supervised anomaly detection methods. The model uses a contrastive loss function to compare input sequences and adjusts network weights iteratively during training to recognize intricate patterns. Additionally, we evaluated various univariate time-series forecasting algorithms on datasets with and without anomalies. Results show that anomaly-smoothed data reduces forecasting errors, highlighting our approach’s effectiveness in enhancing time-series data analysis’s integrity and reliability. Future research will focus on multivariate time-series datasets.publishedVersio

Neil3-dependent base excision repair regulates lipid metabolism and prevents atherosclerosis in Apoe-deficient mice

Increasing evidence suggests that oxidative DNA damage accumulates in atherosclerosis. Recently, we showed that a genetic variant in the human DNA repair enzyme NEIL3 was associated with increased risk of myocardial infarction. Here, we explored the role of Neil3/NEIL3 in atherogenesis by both clinical and experimental approaches. Human carotid plaques revealed increased NEIL3 mRNA expression which significantly correlated with mRNA levels of the macrophage marker CD68. Apoe−/−Neil3−/− mice on high-fat diet showed accelerated plaque formation as compared to Apoe−/− mice, reflecting an atherogenic lipid profile, increased hepatic triglyceride levels and attenuated macrophage cholesterol efflux capacity. Apoe−/−Neil3−/− mice showed marked alterations in several pathways affecting hepatic lipid metabolism, but no genotypic alterations in genome integrity or genome-wide accumulation of oxidative DNA damage. These results suggest a novel role for the DNA glycosylase Neil3 in atherogenesis in balancing lipid metabolism and macrophage function, potentially independently of genome-wide canonical base excision repair of oxidative DNA damage

DivergentNets: Medical Image Segmentation by Network Ensemble

Detection of colon polyps has become a trending topic in the intersecting fields of machine learning and gastrointestinal endoscopy. The focus has mainly been on per-frame classification. More recently, polyp segmentation has gained attention in the medical community. Segmentation has the advantage of being more accurate than per-frame classification or object detection as it can show the affected area in greater detail. For our contribution to the EndoCV 2021 segmentation challenge, we propose two separate approaches. First, a segmentation model named TriUNet composed of three separate UNet models. Second, we combine TriUNet with an ensemble of well-known segmentation models, namely UNet++, FPN, DeepLabv3, and DeepLabv3+, into a model called DivergentNets to produce more generalizable medical image segmentation masks. In addition, we propose a modified Dice loss that calculates loss only for a single class when performing multi-class segmentation, forcing the model to focus on what is most important. Overall, the proposed methods achieved the best average scores for each respective round in the challenge, with TriUNet being the winning model in Round I and DivergentNets being the winning model in Round II of the segmentation generalization challenge at EndoCV 2021. The implementation of our approach is made publicly available on GitHub.publishedVersio