Miracle-dz/UniFAR-FTUs huggingface dataset:
Relative clustering and the joint halo occupation distribution of red sequence and blue-cloud galaxies in COMBO-17

This paper studies the relative spatial distribution of red-sequence and blue-cloud galaxies, and their relation to the dark matter distribution in the COMBO-17 survey as function of scale down to z ~ 1. We measure the second-order auto- and cross-correlation functions of galaxy clustering and express the relative biasing by using aperture statistics. Also estimated is the relation between the galaxies and the dark matter distribution exploiting galaxy-galaxy lensing (GGL). All observables are further interpreted in terms of a halo model. To fully explain the galaxy clustering cross-correlation function with a halo model, we introduce a new parameter, R, that describes the statistical correlation between numbers of red and blue galaxies within the same halo. We find that red and blue galaxies are clearly differently clustered, a significant evolution of the relative clustering with redshift is not found. There is evidence for a scale-dependence of relative biasing: the linear relative bias factor varies slightly between b ~ 1.7 ± 0.5 and ~2.2 ± 0.1 on spatial scales between roughly 100 h -1 kpc and 7h -1 Mpc, respectively. The linear correlation coefficient of galaxy number densities drops from a value near unity on large scales to r ~ 0.6 ± 0.15. Both biasing trends, the GGL and with some tension the galaxy numbers can be explained consistently within a halo model. Red galaxies typically start to populate haloes with masses starting from ≥10 12.1 ±0.2 h -1 M ⊙ , blue galaxies from ≥10 11.2±0.1 h -1 M ⊙ . For the cross-correlation function, one requires a halo occupation distribution (HOD) variance that becomes Poisson even for relatively small occupancy numbers. This rules out for our samples with high confidence a 'Poisson satellite' scenario, as found in semi-analytical models. We compare different model flavours, with and without galaxies at the halo centres, using Bayesian evidence. The result is inconclusive. However, red galaxies have to be concentrated towards the halo centre either by a red central galaxy or by a concentration parameter above that of dark matter. The value of R depends on the presence or absence of central galaxies: if no central galaxies or only red central galaxies are allowed, R is consistent with zero, whereas a positive correlation R = +0.5 ± 0.2 is needed if both blue and red galaxies can have central galaxies.
3D object tracking in driving environment: A short review and a benchmark dataset

Research in autonomous driving has matured significantly with major automotive companies making important efforts to have their autonomous or highly automated cars available in the near future. As driverless cars move from laboratories to complex real-world environments, the perception capabilities of these systems to acquire, model and interpret the 3D spatial information must become more robust. Object tracking is one of the challenging problems of autonomous driving in 3D dynamic environments. Although different approaches are proposed for object tracking with demonstrated success in driving environments, it is very difficult to evaluate and compare them because they are defined with various constraints and boundary conditions. The appearance modeling for object tracking in the driving environments, using a multimodal perception system of autonomous cars and advanced driver assistance systems (ADASs), and the evaluation of such object trackers are the research focus of this paper. A benchmark dataset, called 3D Object Tracking in Driving Environment (3D-OTD), is also proposed to facilitate the evaluation of object appearance modeling in object tracking methods.
On Scheduling Mesh-Structured Computations on Unreliable Computers on the Internet

This work studies the problem of improving the effectiveness of computing dependent tasks over the Internet. The distributed system is composed of a reliable server that coordinates the computation of a massive number of unreliable workers. It is known that the server cannot always ensure that the result of a task is correct without computing the task itself. This fact has significant impact on computing interdependent tasks. Since the computational capacity of the server may be restricted, along with the time to complete to the computation, the server may be able to compute only selected tasks, without knowing whether the remaining tasks were computed by workers correctly. But an incorrectly computed task may render the results of all dependent tasks incorrect. Thus it may become important for the server to compute judiciously selected tasks, so as to maximize the number of correct results. We assume that any worker computes correctly with probability $p<1$. Any incorrectly computed task corrupts all dependent tasks. The goal is to determine which tasks should be computed by the (reliable) server and which by the (unreliable) workers, and when, so as to maximize the expected number of correct results, under a constraint $d$ on the computation time. We show that this optimization problem is NP-hard. Then we study optimal scheduling algorithms for the mesh with the tightest deadline. We present combinatorial arguments that completely describe optimal solutions for two ranges of values of worker reliability $p$, when $p$ is close to zero and when $p$ is close to one. This research is joint work with Grzegorz Malewicz. Its extended abstract will appear in OPODIS’04.
Expression of cyclooxygenase-1 and cyclooxygenase-2 in human breast cancer.

BACKGROUND Numerous studies have demonstrated that the levels of prostaglandins are greater in various cancers, including breast cancer and colon cancer, than in normal tissues. In particular, the inducible form of cyclooxygenase (COX), the rate-limiting enzyme in prostaglandin biosynthesis, is overexpressed in colon tumors. Epidemiologic studies have demonstrated that the use of aspirin or other nonsteroidal anti-inflammatory drugs (NSAIDs) can reduce the risk of colon cancer and, to a lesser extent, the risk of breast cancer. NSAIDs are known to inhibit COX, suggesting that the beneficial effect of NSAIDs in colon cancer may be related to COX overexpression in this disease. This possibility led us to ask whether COX is also overexpressed in breast cancers. METHODS Surgical specimens from 44 patients with breast cancer who had undergone lumpectomy or mastectomy were analyzed by immunoblot analysis and immunohistochemical analysis to determine the expression profile of the constitutively expressed form of cyclooxygenase (COX-1) and the inducible form (COX-2); the specimens from 14 patients included normal breast tissue. RESULTS Expression of COX-1 protein was substantially higher in 30 of 44 tumor samples than in any of the 14 normal tissue specimens. Immunoblot analysis revealed extremely high levels of COX-2 protein in two tumor samples. Immunohistochemical staining of specimens that expressed COX-1 and/or COX-2 revealed that COX-1 was localized in stromal cells adjacent to the tumor but not in tumor cells. In contrast, COX-2 was localized primarily in tumor cells but also appeared in stromal cells. CONCLUSION Our results suggest that overexpression of COX may not be unique to colon cancer and may be a feature common to other epithelial tumors.
Lin-spiration: using a mixture of spiral and linear visualization layouts to explore time series

Time series data is pervasive in many domains and interactive visualization of such data is useful for a wide range of tasks including analysis and prediction. In spite of the importance of visualizing time series data and the fact that time series data is often easily interpretable, traditional approaches are either very simple and limited, or are aimed at domain experts. In this paper, we propose a novel interactive visualization paradigm for exploring and comparing multiple sets of time series data. In particular, we propose a focus+context approach, where a "focus" segment of a time series is zoomed into and visualized using a linear layout at one scale, while the remaining segments of the time series (i.e., the context) are visualized using spiral data layouts. Our paradigm allows the user to dynamically select and compare different sections of each time series independently, facilitating the exploration of time series data in a fun and engaging way.
Modulation of Ras/ERK and Phosphoinositide Signaling by Long-Chain n-3 PUFA in Breast Cancer and Their Potential Complementary Role in Combination with Targeted Drugs

A potential complementary role of the dietary long-chain n-3 polyunsaturated fatty acids (LCn-3 PUFA) in combination with innovative mono-targeted therapies has recently been proposed. These compounds are thought to act pleiotropically to prevent the development and progression of a variety of cancers, including breast cancer. We hereinafter critically analyze the reports investigating the ability of LCn-3 PUFA to modulate the Ras/ERK and the phosphoinositide survival signaling pathways often aberrantly activated in breast cancer and representing the main targets of innovative therapies. The in vitro or in vivo animal and human interventional studies published up to January 2017 investigating the effects of LCn-3 PUFA on these pathways in normal and cancerous breast cells or tissues were identified through a systematic search of literature in the PubMed database. We found that, in most cases, both the in vitro and in vivo studies demonstrated the ability of LCn-3 PUFA to inhibit the activation of these pro-survival pathways. Altogether, the analyzed results strongly suggest a potential role of LCn-3 PUFA as complementary agents in combination with mono-targeted therapies. Moreover, the results indicate the need for further in vitro and human interventional studies designed to unequivocally prove the potential adjuvant role of these fatty acids.
Proposal of an improved motion estimation module for SVC

In October 2007 ITU-T and MPEG organizations published the Scalable Video Coding (SVC) specification as an addendum to the H.264 standard. Basically SVC enables H.264 video encoders to support temporal, spatial and SNR scalability. This new functionalities lead to more flexibility on bandwidth management and robustness against packet losses. It is therefore more suitable for heterogeneous multimedia applications like IPTV and mobile networks. However implementations of SVC specification are still limited due the augmented computational complexity. One of the most critical SVC algorithms is the motion estimation module, which allows identification of extra intra and inter-layer redundancies. The great computation demand of this module is responsible for the large SVC encoder latency time, restraining its use in real-time applications. We propose in this paper a new motion estimation approach specially designed to reduce memory accesses and data comparisons in order to increase performance. Experimental results prove significant gains in speed (up to 6 times faster) with small effects on quality (less than 0.2 dB).
NH(2)-terminal truncated HER-2 protein but not full-length receptor is associated with nodal metastasis in human breast cancer.

BACKGROUND The full-length receptor p185HER-2 undergoes a metalloprotease-dependent cleavage producing a membrane-associated fragment (p95HER-2) in cultured breast cancer cells. P95HER-2 has potentially enhanced signaling activity, but its expression and role in human breast cancer is poorly characterized. PURPOSE The purpose of this project was to characterize the expression of p95HER-2 in primary breast cancers and nodal metastasis, and to study association with clinicopathological factors. EXPERIMENTAL DESIGN P95HER-2 and p185HER-2 were examined in 337 primary breast tumors and 81 metastatic lymph nodes by Western blot analysis, and tested for associations with other clinicopathological factors. RESULTS P95HER-2 was present in 20.9% of primary tumors from node-negative patients, in 29.1% from patients with one to three metastatic nodes, and in 36.7% from patients with four or more metastatic nodes (P = 0.027). Whereas p185HER-2 overexpression was unrelated to nodal disease (P = 0.63), the odds of lymph node metastasis were enhanced 2.9-fold by the presence of p95HER-2 (48.8% of node-negative versus 73.5% of node-positive patients; P = 0.03; odds ratio = 2.9). P95HER-2 was more frequent in metastatic lymph nodes than in primary tumors (45.7% versus 26.7%; P = 0.0009), whereas p185HER-2 overexpression was similar in both (22.3% versus 23.5%; P = 0.933). P95HER-2 did not significantly correlate with patient age, tumor size, stage, histotype, or hormone receptor status. CONCLUSIONS P95HER-2 in primary tumors was related to extent of lymph node involvement and was enhanced in nodal tissue suggesting an important role as a marker or cause in breast cancer metastasis. Examination of the prognostic value of p95HER-2 in breast cancer and its coexpression with metalloprotease activity seem warranted.
Efficient Implementation of high-level parallel programs

The efficiency of a parallel program is related to the implementation of its data structures on the distributed (or shared) memory of a specific architecture. This paper describes a declarative approach that may be used to modify the mapping of the program data on a specific architecture. The ideas are developed in the context of a new language called UC and its implementation on the Connection Machine. The paper aim contains measurements on sample programs to illustrate the effectiveness of data mappings in improving the execution efficiency of example programs.
An All-digital UWB Transmitter in 90-nm CMOS

Pulsed ultra-wideband (UWB) transceivers offer the potential for ultra-low-energy/bit operation because the signals are inherently duty-cycled. By eliminating components with long startup times, such as a phase-locked loop, all components in a pulsed-UWB transceiver can be disabled during the interval between pulses. This work focuses on an all-digital, pulsed-UWB transmitter that requires no analog bias currents, in which the energy is dissipated only in switching events, i.e., CV2, and by sub-threshold leakage currents.
Mining MEDLINE Metadata to Explore Genes and their Connections

Biomedical scientists are faced with enormous challenges when tracking new discoveries made and research produced in their domain of interest. These challenges are exacerbated by the need to track research in other domains that might possibly be relevant to one’s own research. Tools that support researchers by mining appropriate information from text collections would be of immense value. In this context we present a system that may be used by scientists to explore topics and their relationships using a collection such as MEDLINE. Several kinds of analyses are supported. One may study the features of an individual topic or those of a group of topics where these features are identified from the text collection. Functions are provided to examine topic co-occurrence and topic similarity based associations. The user may also explore indirect connections between topics by using a closed discovery process that is part of the system. In this paper we describe our system which offers a common framework for these functions. We illustrate the design of the system with a dataset of topics from the pediatrics genetics domain.
A Flexible Convex Optimization Model for Semi-supervised Clustering with Instance-level Constraints

Clustering is a common task in many applications e.g. digital image processing, text mining and bioinformatics. Many techniques such as k-means, hierarchical clustering and spectral clustering, have been proposed. In a previous study, we proposed a quadratic programming model to address the fuzzy binary clustering problem in the unsupervised setting and then extended it to the general clustering problem. In this paper, we extend further the model in the semi-supervised setting. It has three salient characteristics. First, both the label and link information of known samples can be integrated easily. Second, it illustrates the linkage between the hard binary clustering and fuzzy binary clustering in one framework, suggesting the benefits of fuzzy binary clustering theoretically. Third, a fast iterative algorithm is proposed, which can be applied to very large data sets. Numerical experiments on two data sets suggest its practical effectiveness and efficiency.
Oncotargets and Therapy Dovepress Prognostic and Clinicopathological Significance of Serum Interleukin-6 Expression in Colorectal Cancer: a Systematic Review and Meta-analysis

1 cancer institute, Key laboratory of cancer Prevention and intervention, Key laboratory of Molecular Biology in Medical sciences, china national Ministry of education, Purpose: Interleukin-6 (IL-6) plays an important role in human colorectal cancer (CRC) development. However, the exact clinical and prognostic significance of IL-6 in CRC is still unclear. Here, we conducted this meta-analysis to explore this issue in detail. Methods: A meta-analysis was performed to clarify the association between serum IL-6 expression and clinical outcomes in articles published up to June 2015. Weighted mean difference (WMD) and its corresponding 95% confidence interval (CI) were used to assess the association between serum IL-6 expression and the clinicopathological characteristics of CRC. Hazard ratio (HR) with 95% CI was used to quantify the predictive value of IL-6 on CRC prognosis. Results: Fourteen studies comprising 1,245 patients were included. Analysis of these data showed that serum IL-6 expression was highly correlated with poor 5-year overall survival (OS) rate (HR =0.43, 95% CI: 0.31–0.59, P=0.755). Simultaneously, we also found that serum IL-6 expression was associated with certain clinical parameters of CRC, such as tumor invasion Conclusion: A high serum IL-6 expression is associated with adverse OS in CRC. The IL-6 expression can be an important supplement in establishing prognostic score for clinical decision.
A hierarchical statistical model for object classification

In many applications it is necessary to be able to classify images in a database accurately and with acceptable speed. The main problem is to assign different images to right categories. The later problem becomes more challenging while dealing with large databases with many categories and subcategories. In this paper we propose a novel classification method based on an adopted hierarchical Dirichlet generative model, previously proposed for corpora document classification. In order to adopt the model to work with image data we use the bag of visual words model. We show that if properly applied the model can achieve adequate results for hierarchical image classification. Experimental results are presented and discussed to show the merits of the proposed approach.
First-principles calculations of the structural, electronic, optical and elastic properties of the CuYS2 semiconductor

The ternary semiconductor CuYS2 is studied by using the first-principles methods in the density functional theory (DFT) framework. The structural, electronic, optical and elastic properties were calculated at the ambient and elevated hydrostatic pressures. The compound was shown to have an indirect band gap of about 1.342/1.389 eV (in the generalized gradient and local density approximations, respectively). The anisotropy of the optical properties was studied by calculating the absorption spectra, dielectric function and index of refraction for different polarizations. The anisotropy of the elastic properties was visualized by plotting the three-dimensional dependence of the Young’s moduli on the direction in the crystal lattice. The obtained results, which are reported for the first time to the best of the author’s knowledge, can facilitate assessment of possible applications of the title material.
Die politische Kontrolle der Ministerialbürokratie des Bundes: Die Bedeutung der Landesebene

In diesem Aufsatz möchte ich anhand des deutschen Falls einer Frage nachgehen, die beim Thema Parteienpatronage aus der Konfrontation von empirischen Ist-Werten und theoretisch erwarteten Soll-Werten herrührt. Kurz gesagt: In Deutschland scheint es im Bereich der zentralen Staatsverwaltung wesentlich weniger Parteienpatronage zu geben, als theoretisch zu erwarten wäre. Wie ist das zu erklären? Zunächst zu den theoretischen Erwartungen. Das Verhältnis zwischen politischer Führung und Ministerialbürokratie ist ein durch Informationsasymmetrien gekennzeichnetes Delegationsverhältnis. Mit weniger Jargon formuliert: Die Ministerin ist im politischen Tagesgeschäft auf den Sachverstand ihrer Bürokraten angewiesen. Sie kann sich aber nicht vollständig sicher sein, ob die Bürokraten auch gemäß den politischen Anweisungen handeln oder ob sie nicht vielleicht eine eigene persönliche und/oder politische Agenda verfolgen (von bloßer Faulheit bis zur Sabotage; Brehm/Gates 1999). Zu erwarten ist daher, dass die politische Führungsebene zur Absicherung dieses politischen Delegationsverhältnisses verschiedene Kontrolltechniken verwendet. Eine dieser Techniken ist Parteienpatronage. Das Parteibuch kann ein entscheidendes Selektionskriterium bei der Einstellung und Beförderung beziehungsweise bei der Versetzung und Entlassung (in den Ruhestand) von Ministerialbürokraten sein, da es die Wahrscheinlichkeit verringert, dass der betreffende Beamte in einer Weise handelt, die den politischen Intentionen der Regierung entgegensteht. Das Parteibuch signalisiert
College for All? Is There Too Much Emphasis on Getting a 4-Year College Degree? Research Synthesis.

AUTHOR Boesel, David; Fredland, Eric TITLE College for All? Is There Too Much Emphasis on Getting a 4-Year College Degree? Research Synthesis. INSTITUTION Wisconsin Univ., Madison. Medical Center. SPONS AGENCY National Library of Education (ED/OERI), Washington, DC. REPORT NO NLE-1999-2024 PUB DATE 1999-01-00 NOTE 96p. PUB TYPE Information Analyses (070) Numerical/Quantitative Data (110) EDRS PRICE MF01/PC04 Plus Postage. DESCRIPTORS Academic Ability; *Bachelors Degrees; *College Graduates; Community Colleges; Debt (Financial); Dropouts; Higher Education; *Labor Market; *Research; Salaries; School Holding Power; Tables (Data); Vocational Education
The 2dF QSO Redshift Survey– XV. Correlation analysis of redshift‐space distortions

We analyse the redshift-space (z-space) distortions of quasi-stellar object (QSO) clustering in the 2-degree field instrument (2dF) QSO Redshift Survey (2QZ). To interpret the z-space correlation function, ξ(σ, π), we require an accurate model for the QSO real-space correlation function, ξ(r). Although a single power-law ξ(r) oc r -γ model fits the projected correlation function [ω p (σ)] at small scales, it implies somewhat too shallow a slope for both w p (σ) and the z-space correlation function, ξ(s), at larger scales (? 20 h -1 Mpc). Motivated by the form for ξ(r) seen in the 2dF Galaxy Redshift Survey (2dFGRS) and in standard A cold dark matter (CDM) predictions, we use a double power-law model for ξ(r), which gives a good fit to ξ(s) and w p (σ). The model is parametrized by a slope of y = 1.45 for 1 < r < 10 h -1 Mpc and y = 2.30 for 10 < r < 40 h -1 Mpc. As found for the 2dFGRS, the value of β determined from the ratio of ξ(s)/ξ(r) depends sensitively on the form of ξ(r) assumed. With our double power-law form for ξ(r), we measure β(z = 1.4) = 0.32 +0.09 -0.11 . Assuming the same model for ξ(r), we then analyse the z-space distortions in the 2QZ ξ(σ, π) and put constraints on the values of Ω 0 m and β(z = 1.4), using an improved version of the method of Hoyle et al. The constraints we derive are Ω 0 m = 0.35 +0.19 -0.13 , β(z = 1.4) = 0.50 +0.13 -0.15 , in agreement with our ξ(s)/ξ(r) results at the ∼ 1σ level.