Miracle-dz/UniFAR-FTUs huggingface dataset:
Prostaglandin E2 down-regulates sirtuin 1 (SIRT1), leading to elevated levels of aromatase, providing insights into the obesity–breast cancer connection

Obesity increases the risk of hormone receptor–positive breast cancer in postmenopausal women. Levels of aromatase, the rate-limiting enzyme in estrogen biosynthesis, are increased in the breast tissue of obese women. Both prostaglandin E2 (PGE2) and hypoxia-inducible factor 1α (HIF-1α) contribute to the induction of aromatase in adipose stromal cells (ASCs). Sirtuin 1 (SIRT1) binds, deacetylates, and thereby inactivates HIF-1α. Here, we sought to determine whether SIRT1 also plays a role in regulating aromatase expression. We demonstrate that reduced SIRT1 levels are associated with elevated levels of acetyl–HIF-1α, HIF-1α, and aromatase in breast tissue of obese compared with lean women. To determine whether these changes were functionally linked, ASCs were utilized. In ASCs, treatment with PGE2, which is increased in obese individuals, down-regulated SIRT1 levels, leading to elevated acetyl–HIF-1α and HIF-1α levels and enhanced aromatase gene transcription. Chemical SIRT1 activators (SIRT1720 and resveratrol) suppressed the PGE2-mediated induction of acetyl–HIF-1α, HIF-1α, and aromatase. Silencing of p300/CBP-associated factor (PCAF), which acetylates HIF-1α, blocked PGE2-mediated increases in acetyl–HIF-1α, HIF-1α, and aromatase. SIRT1 overexpression or PCAF silencing inhibited the interaction between HIF-1α and p300, a coactivator of aromatase expression, and suppressed p300 binding to the aromatase promoter. PGE2 acted via prostaglandin E2 receptor 2 (EP2) and EP4 to induce activating transcription factor 3 (ATF3), a repressive transcription factor, which bound to a CREB site within the SIRT1 promoter and reduced SIRT1 levels. These findings suggest that reduced SIRT1-mediated deacetylation of HIF-1α contributes to the elevated levels of aromatase in breast tissues of obese women.
Management of Event History Data and Episode Splitting Using the AGIPEB-Dataset

Empfohlene Zitierung / Suggested Citation: Baron, D. , & Krüger, C. (2017). Management of Event History Data and Episode Splitting Using the AGIPEB-Dataset. (AGIPEB Working Paper, 6). Aachen: Rheinisch-Westfälische Technische Hochschule Aachen, Philosophische Fakultät, Institut für Soziologie Lehrund Forschungsgebiet Methoden der empirischen Sozialforschung. https://nbnresolving.org/urn:nbn:de:0168-ssoar-53413-4
One Bit Algorithms

Many algorithms in distributed systems assume that the size of a single message depends on the number of processors. In this paper, we assume in contrast that messages consist of a single bit. Our main goal is to explore how the one-bit translation of unbounded message algorithms can be sped up by pipelining. We consider two problems. The first is routing between two processors in an arbitrary network and in some special networks (ring, grid, hypercube). The second problem is coloring a synchronous ring with three colors. The routing problem is a very basic subroutine in many distributed algorithms; the three coloring problem demonstrates that pipelining is not always useful.
Randomized Recurrent Neural Networks

Neural Networks (NNs) with random weights represent nowadays a topic of consolidated use in the Machine Learning research community. In this contribution we focus in particular on recurrent NN models, which in a randomized setting represent a case of particular interest per se, entailing a number of intriguing research challenges primarily related to the control of the developed dynamics for the learning purposes. Framed in the Reservoir Computing paradigm, this paper aims at providing the basic elements and summarizing the recent advances on the topic of randomized recurrent NNs (divided in theoretical, architectural, deep learning and structured domain aspects), and introducing the papers
Offline partial evaluation for shift and reset

This paper presents an offline partial evaluator for the λ-calculus with the delimited continuation constructs shift and reset. Based on Danvy and Filinski's type system for shift and reset, we first present a type system that specifies well-annotated terms. We then show a specializer that receives an annotated term and produces the output in continuation-passing style (CPS). The correctness of our partial evaluator is established using the technique of logical relations. Thanks to the explicit reference to the type of continuations, we can establish the correctness using the standard proof technique of structural induction, despite the fact that the specializer itself is written in CPS. The paper also shows an efficient constraint-based binding-time analysis as well as how to extend the present work to richer language constructs, such as recursion and conditionals.
Learning compact representations for large scale image search. (Apprentissage de représentations compactes pour la recherche d'images à grande échelle)

Cette these aborde le probleme de la recherche d'images a grande echelle. Pour aborder la recherche d'images a grande echelle, il est necessaire de coder des images avec des representations compactes qui peuvent etre efficacement utilisees pour comparer des images de maniere significative. L'obtention d'une telle representation compacte peut se faire soit en comprimant des representations efficaces de grande dimension, soit en apprenant des representations compactes de bout en bout. Le travail de cette these explore et avance dans ces deux directions. Dans notre premiere contribution, nous etendons les approches de quantification vectorielle structuree telles que la quantification de produit en proposant une representation somme ponderee de codewords. Nous testons et verifions les avantages de notre approche pour la recherche approximative du plus proche voisin sur les caracteristiques d'image locales et globales, ce qui est un moyen important d'aborder la recherche d'images a grande echelle. L'apprentissage de la representation compacte pour la recherche d'images a recemment attire beaucoup d'attention avec diverses approches basees sur le hachage profond proposees. Dans de telles approches, les reseaux de neurones convolutifs profonds apprennent a coder des images en codes binaires compacts. Dans cette these, nous proposons une approche d'apprentissage supervise profond pour la representation binaire structuree qui rappelle une approche de quantification vectorielle structuree telle que PQ. Notre approche beneficie de la recherche asymetrique par rapport aux approches de hachage profond et apporte une nette amelioration de la precision de la recherche au meme debit binaire. L'index inverse est une autre partie importante du systeme de recherche a grande echelle en dehors de la representation compacte. A cette fin, nous etendons nos idees pour l'apprentissage de la representation compacte supervisee pour la construction d'index inverses. Dans ce travail, nous abordons l'indexation inversee avec un apprentissage approfondi supervise et essayons d'unifier l'apprentissage de l'indice inverse et de la representation compacte. Nous evaluons minutieusement toutes les methodes proposees sur divers ensembles de donnees accessibles au public. Nos methodes surpassent ou sont competitives avec l'etat de l'art.
Etude mathématique du problème de couplage océan-atmosphère incluant les échelles turbulentes. (Mathematical study of the air-sea coupling problem including turbulent scale effects)

Cette these s'interesse a la modelisation numerique du couplage entre l'ocean et l'atmosphere. Bien que presentant un certain nombre de caracteristiques communes, ces deux milieux physiques sont suffisamment dissemblables pour etre numeriquement simules par des modeles distincts, incluant chacun des specificites propres. Par consequent, leurs interactions sont prises en compte via des algorithmes de couplage multiphysique.La mise en place de tels algorithmes necessite une bonne comprehension des modelisations des milieux oceanique et atmospherique, en particulier au voisinage de leur interface commune. C'est pourquoi une partie consequente de la presente these disseque, analyse et complete les parametrisations turbulentes, qui sont des mecanismes numeriques definis au niveau continu, traitant la couche limite turbulente au voisinage de la surface oceanique. Les travaux entrepris ont permis d'identifier deux sources d'erreurs, theoriquement et numeriquement significatives, dans la modelisation numerique standard de l'interface ocean-atmosphere.La premiere source d'erreur se manifeste dans les formulations continues des parametrisations turbulentes: celles-ci sont actuellement utilisees de maniere incomplete, ce qui se traduit par le caractere mathematiquement irregulier des solutions qu'elles generent. En revenant aux fondements de la theorie dont les parametrisations decoulent, la presente these etend leur domaine d'application, permettant de generer des profils de solution reguliers, dans un cadre theorique uniforme et bi-domaine. Les effets d'une telle extension sont numeriquement evalues sur des cas tests physiquement realistes: celle-ci peut mener a des biais considerables (de l'ordre de 20%) dans les flux echanges entre ocean et atmosphere. D'un point de vue theorique, cette extension permet de definir des criteres simples sous lesquels le couplage ocean-atmosphere peut etre considere comme coherent par rapport aux deux domaines physiques, et surtout aux parametrisations turbulentes.La seconde source d'erreur est de nature algorithmique: elle concerne la discretisation temporelle des mecanismes de couplage. Les methodes actuelles, dites ad hoc, ne garantissent pas une complete coherence des flux d'un modele a l'autre. Les algorithmes de Schwarz globaux en temps, issus de thematiques liees a la decomposition de domaine, constituent une piste interessante pour traiter ces aspects. La mise en place de tels algorithmes sur des modeles physiquement realistes represente un defi considerable. Leur impact numerique sur des cas tests simplifies est evalue. L'etude prealable des parametrisations turbulentes permet de donner des pistes quant au developpement d'algorithmes de couplage, concernant a la fois la coherence du couplage precedemment introduite, et l'incorporation graduelle d'effets physiques plus complexes.
Phrenic motoneuron structural plasticity across models of diaphragm muscle paralysis

Structural plasticity in motoneurons may be influenced by activation history and motoneuron–muscle fiber interactions. The goal of this study was to examine the morphological adaptations of phrenic motoneurons following imposed motoneuron inactivity while controlling for diaphragm muscle inactivity. Well‐characterized rat models were used including unilateral C2 spinal hemisection (SH; ipsilateral phrenic motoneurons and diaphragm muscle are inactive) and tetrodotoxin phrenic nerve blockade (TTX; ipsilateral diaphragm muscle is paralyzed while phrenic motoneuron activity is preserved). We hypothesized that inactivity of phrenic motoneurons would result in a decrease in motoneuron size, consistent with a homeostatic increase in excitability. Phrenic motoneurons were retrogradely labeled by ipsilateral diaphragm muscle injection of fluorescent dextrans or cholera toxin subunit B. Following 2 weeks of diaphragm muscle paralysis, morphological parameters of labeled ipsilateral phrenic motoneurons were assessed quantitatively using fluorescence confocal microscopy. Compared to controls, phrenic motoneuron somal volumes and surface areas decreased with SH, but increased with TTX. Total phrenic motoneuron surface area was unchanged by SH, but increased with TTX. Dendritic surface area was estimated from primary dendrite diameter using a power equation obtained from three‐dimensional reconstructed phrenic motoneurons. Estimated dendritic surface area was not significantly different between control and SH, but increased with TTX. Similarly, TTX significantly increased total phrenic motoneuron surface area. These results suggest that ipsilateral phrenic motoneuron morphological adaptations are consistent with a normalization of motoneuron excitability following prolonged alterations in motoneuron activity. Phrenic motoneuron structural plasticity is likely more dependent on motoneuron activity (or descending input) than muscle fiber activity.
Cost Modelling for Vectorization on ARM

When applying a code transformation to optimize for performance, compilers need to assess its profitability beforehand. For this purpose, they utilize cost models, which compare the cost, an abstract measure of the code, before and after the transformation. If the cost is lower after the transformation, it will be applied. Exact cost modelling is therefore critical to avoid slowdowns or missed opportunities for speedups. In this work, we analyze the accuracy of LLVM's loop-level vectorization (LLV) cost model, and show the benefit of modelling speedup instead of instruction costs for higher vectorization rates and smaller execution times. The presented approach is portable to other compilers and hardwares as well.
Gramm: grammar of graphics plotting in Matlab

Gramm is a data visualization toolbox for Matlab (The MathWorks Inc., Natick, USA) that allows to produce publication-quality plots from grouped data easily and flexibly. Matlab can be used for complex data analysis using a high-level interface: it supports mixed-type tabular data via tables, provides statistical functions that accept these tables as arguments, and allows users to adopt a split-apply-combine approach (Wickham 2011) with rowfun(). However, the standard plotting functionality in Matlab is mostly lowlevel, allowing to create axes in figure windows and draw geometric primitives (lines, points, patches) or simple statistical visualizations (histograms, boxplots) from numerical array data. Producing complex plots from grouped data thus requires iterating over the various groups in order to make successive statistical computations and low-level draw calls, all the while handling axis and color generation in order to visually separate data by groups. The corresponding code is often long, not easily reusable, and makes exploring alternative plot designs tedious (Example code Fig. 1A).
Privacy-Preserving Architectures with Probabilistic Guaranties

Violations of the privacy of users can happen if data protection is not a fundamental part of the development process of a software system. The principle of Privacy by Design (PbD) therefore stipulates the consideration of privacy as a default feature. We have developed an integrated tool environment called CAPVerDE that provides a formal description language of software architectures and helps a designer by automatically verifying data minimization properties at the architectural level. Our logic includes probabilistic properties that introduce uncer- tainty into the architectures. These properties can be used to model attack scenarios that rely on chance. This paper presents the logic of the description language of CAPVerDE and illustrates the verification process by applying it to a smart energy metering scenario.
Prognostic value of 18F-fluorodeoxyglucose bone marrow uptake in patients with solid tumors

Background: Several studies have reported the prognostic value of 18F-fluorodeoxyglucose (18F-FDG) bone marrow uptake (BMU) measured by 18F-FDG positron emission tomography (18F-FDG PET) in various cancers. We performed a meta-analysis to evaluate the prognostic value of 18F-FDG BMU in patients with solid tumors. Methods: Systematic searches of MEDLINE and Embase databases were performed using the keywords “18F-FDG,” “bone marrow,” and “prognosis. ” All published human studies of the prognostic value of 18F-FDG BMU in patients with solid tumors were searched. The primary outcome was event-free survival (EFS), and the secondary endpoint was overall survival (OS); both of these were extracted directly from each study. The effects of 18F-FDG BMU on survival were assessed by using hazard ratios (HRs). Results: Ten studies with 1197 patients (8 studies reporting EFS in 1096 patients and 7 studies reporting OS in 836 patients) were included. In the EFS analysis, the combined HR was 1.75 (95% confidence interval [CI]: 1.45–2.11, P < .00001) in the random effects model (I2 = 51%, P = .05). The combined HR of OS was 1.40 (95% CI: 1.13–1.73, P = .002) in the random effects model (I2 = 52%, P = .05). Conclusion: This meta-analysis has demonstrated that patients with a low level of 18F-FDG BMU have better EFS and OS than those with a high level of 18F-FDG BMU. Based on our results, we suggest that 18F-FDG BMU could be used as a biomarker for stratifying the risk of tumor progression in patients with solid tumors.
First U-Pb zircon ages for late Miocene Ashfall Konservat-Lagerstätte and Grove Lake ashes from eastern Great Plains, USA

This paper documents the first U-Pb zircon ages for Ashfall Fossil Beds (Nebraska, USA), a terrestrial Konservat-Lagerstätte mass-death assemblage that is arguably the most diverse of its type and age. The Ashfall tephra was correlated with ignimbrites from the Bruneau-Jarbidge volcanic field (12.7–10.5 Ma) in southwest Idaho based on geochemical analysis. The methods and geochemical data supporting the original age assessment of the ash bed, however, were never published, and there has been a persistent misconception that dateable heavy minerals (e.g., zircon) are absent. Notwithstanding, we recovered abundant zircons from Ashfall Fossil Beds, and from an ash bed ~6 km to the southeast at Grove Lake, Nebraska, and analyzed them through LA-ICP-MS. Our new zircon U-Pb age of 11.86 ± 0.13 Ma substantiates correlation of the Ashfall Fossil Beds deposit to tuffs originating from the Bruneau-Jarbidge caldera (~12.7–10.5 Ma). Our U-Pb zircon age of 6.42 ± 0.06 Ma for the Grove Lake ash bed coincides with supervolcanic activity in the Heise volcanic field (6.6–4.3 Ma) in eastern Idaho. These new dates improve age constraints of strata comprising the Ogallala Group and the important paleontological site. Moreover, we find that detrital and airfall zircons are unevenly distributed in the stratified ash beds we describe herein and presumably in similar deposits worldwide. Therefore, a higher-resolution sampling scheme is necessary in such cases.
T-ALL leukemia stem cell 'stemness' is epigenetically controlled by the master regulator SPI1

Leukemia stem cells (LSCs) are regarded as the origins and key therapeutic targets of leukemia, but limited knowledge is available on the key determinants of LSC ‘stemness’. Using single-cell RNA-seq analysis, we identify a master regulator, SPI1, the LSC-specific expression of which determines the molecular signature and activity of LSCs in the murine Pten-null T-ALL model. Although initiated by PTEN-controlled β-catenin activation, Spi1 expression and LSC ‘stemness’ are maintained by a β-catenin-SPI1-HAVCR2 regulatory circuit independent of the leukemogenic driver mutation. Perturbing any component of this circuit either genetically or pharmacologically can prevent LSC formation or eliminate existing LSCs. LSCs lose their ‘stemness’ when Spi1 expression is silenced by DNA methylation, but Spi1 expression can be reactivated by 5-AZ treatment. Importantly, similar regulatory mechanisms may be also present in human T-ALL.
Face recognition using feature coding and nonlocal constraint-based sparse representation classifier

Abstract. We propose a face recognition method using distinctive triangle encoding and nonlocal constraint-based sparse representation (TENCSR). With TENCSR, first the pixel values of all images are used as the low-level features. Next, a clustering method is proposed by considering the density distribution of target data, named shared weights support vector data description (SW-SVDD), which makes the obtained decision boundary closer to the optimal. On the basis of SW-SVDD, a more distinctive triangle encoding (MDTE) method is introduced by considering the cluster center information and the size information of cluster, which makes the encoded features more distinctive. Then the high-level features are obtained by encoding those low-level features using MDTE. Meanwhile, a nonlocal constraint-based sparse representation classifier (NC-SRC) is proposed by the biological discovery that dissimilar inputs have dissimilar codes. Finally, those high-level features are classified by the proposed NC-SRC. Experimental results on Georgia Tech, CVL, IMM, FRGC, and AR databases show that our TENCSR outperforms some state-of-the-art algorithms.
I-AHSDT: intrusion detection using adaptive dynamic directive operative fractional lion clustering and hyperbolic secant-based decision tree classifier

ABSTRACT This paper proposes an effective intrusion detection method, named I-AHSDT, which is the combination of the Adaptive Dynamic Directive Operative Fractional Lion clustering (ADDOFL) and Hyperbolic Secant-based Decision Tree classifier (HSDT). The proposed HSDT classifier is based on the inverse hyperbolic secant function and it performs the two level classification to detect the intrusion, which offers robust classification performance. The experimentation is performed using the KDD Cup 1999 data, and the HCR Lab data set, and the experimental results prove that the proposed method outperforms the existing system in terms of the accuracy, which is 0.95.
Spatial pooling as feature selection method for object recognition

This paper reports our work on object recognition by using the spatial pooler of Hierarchical Temporal Memory (HTM) as a method for feature selection. To perform the recognition task, we employed this pooling method to select features from COIL-100 dataset. We bench-marked the results with state-of-the-art feature extraction methods while using diﬀerent amounts of training data (from 5% to 45%). The results indicate that the performed method is eﬀective for object recognition with a low amount of training data in which state-of-the-art feature extraction methods show limitations.
Design of a resilient ring for middle ear’s chamber stapes prosthesis

Abstract This paper presents the process of designing a new elastic element replacing a membrane in the chamber stapes prosthesis (ChSP). The results of the study are volume displacement characteristics obtained for the prosthesis and physiological stapes. Simulation tests on a 3D CAD model have confirmed that a properly designed ring can stimulate perilymph with the same or greater efficacy as the physiological stapes footplate placed on the elastic annular ligament. The ChSP with a new elastic element creates a good chance of improving hearing in patients suffering from otosclerosis.
Multitarget Tracking Algorithm Based on Adaptive Network Graph Segmentation in the Presence of Measurement Origin Uncertainty

To deal with the problem of multitarget tracking with measurement origin uncertainty, the paper presents a multitarget tracking algorithm based on Adaptive Network Graph Segmentation (ANGS). The multitarget tracking is firstly formulated as an Integer Programming problem for finding the maximum a posterior probability in a cost flow network. Then, a network structure is partitioned using an Adaptive Spectral Clustering algorithm based on the Nyström Method. In order to obtain the global optimal solution, the parallel A* search algorithm is used to process each sub-network. Moreover, the trajectory set is extracted by the Track Mosaic technique and Rauch–Tung–Striebel (RTS) smoother. Finally, the simulation results achieved for different clutter intensity indicate that the proposed algorithm has better tracking accuracy and robustness compared with the A* search algorithm, the successive shortest-path (SSP) algorithm and the shortest path faster (SPFA) algorithm.