Miracle-dz/UniFAR-FTUs huggingface dataset:
Sex- and Strain-dependent Effects of Bisphenol: A Consumption in Juvenile Mice

Children are directly exposed to bisphenol A (BPA) and other putative environmental obesogens through both diet and household products. The purpose of this study was to investigate sex- and genetic-dependent effects of BPA consumption on traits relevant to obesity and Type 2 diabetes in juveniles, using mice as models. Two strains of mice (C57BL/6J and DBA/2J) were chosen to represent distinct genetic backgrounds that differ in susceptibility to obesity and insulin resistance. Male and female mice of each strain consumed BPA at three doses in drinking water from four to eleven weeks of age. Male but not female mice of each strain consuming BPA were significantly fatter than controls. BPA induced corresponding changes in adipose tissue gene expression and metabolite abundance that indicate effects on adipogenesis and energy utilization. BPA consumption also altered the synthesis of adipokines, circulating factors that modulate insulin sensitivity and atherogenesis, in C57BL/6J but not DBA/2J males. Conversely, effects of BPA on plasma insulin were only observed in female mice, and with opposite effects in the two strains. These results suggest that dietary BPA may exacerbate childhood obesity and its consequences, and that sex and genetic background are important determinants of the physiological impact of BPA.
Comparison of Metabolite Concentrations in the Left Dorsolateral Prefrontal Cortex, the Left Frontal White Matter, and the Left Hippocampus in Patients in Stable Schizophrenia Treated with Antipsychotics with or without Antidepressants. 1H-NMR Spectroscopy Study

Managing affective, negative, and cognitive symptoms remains the most difficult therapeutic problem in stable phase of schizophrenia. Efforts include administration of antidepressants. Drugs effects on brain metabolic parameters can be evaluated by means of proton nuclear magnetic resonance (1H-NMR) spectroscopy. We compared spectroscopic parameters in the left prefrontal cortex (DLPFC), the left frontal white matter (WM) and the left hippocampus and assessed the relationship between treatment and the spectroscopic parameters in both groups. We recruited 25 patients diagnosed with schizophrenia (DSM-IV-TR), with dominant negative symptoms and in stable clinical condition, who were treated with antipsychotic and antidepressive medication for minimum of three months. A group of 25 patients with schizophrenia, who were taking antipsychotic drugs but not antidepressants, was matched. We compared metabolic parameters (N-acetylaspartate (NAA), myo-inositol (mI), glutamatergic parameters (Glx), choline (Cho), and creatine (Cr)) between the two groups. All patients were also assessed with the Positive and Negative Syndrome Scale (PANSS) and the Calgary Depression Scale for Schizophrenia (CDSS). In patients receiving antidepressants we observed significantly higher NAA/Cr and NAA/Cho ratios within the DLPFC, as well as significantly higher mI/Cr within the frontal WM. Moreover, we noted significantly lower values of parameters associated with the glutamatergic transmission—Glx/Cr and Glx/Cho in the hippocampus. Doses of antipsychotic drugs in the group treated with antidepressants were also significantly lower in the patients showing similar severity of psychopathology.
Supporting real-time update of an environment representation for autonomous mobile robots

A model of the environment is a mandatory requirement for the autonomy of a mobile robot. As the environment may change over time, methods are necessary to update the model information, keeping pace with the sensor frame rate. Our approach to cope with this real time problem is to predict virtual sensor images, which are then compared against the real perceptions. Two alternative methods are detailed: model based prediction and history based prediction. <<ETX>>
Ultra wideband channel model for indoor environments

This paper presents an in-depth study of a UWB indoor radio channel between 1 and 9 GHz, which was used for the subsequent development of a new statistical UWB multipath channel model, focusing on short range indoor scenarios. The channel sounding process was carried out covering different indoor environments, such as laboratories, halls or corridors. A combination of new and traditional parameters has been used to accurately model the channel impulse response in order to perform a precise temporal estimation of the received pulse shape. This model is designed specifically for UWB digital systems, where the received pulse is correlated with an estimated replica of itself. The precision of the model has been verified through the comparison with measured data from equivalent scenarios and cases, and highly satisfactory results were obtained.
A Genome-Wide Breast Cancer Scan in African Americans

Abstract : Genome-wide association studies (GWAS) of breast cancer have been completed among populations of European ancestry, and several regions have been identified that appear to contribute susceptibility to this cancer. However, recent data suggest that not all risk alleles for common cancers will be revealed by studies limited to Whites of European ancestry, and that similar efforts in other racial and ethnic populations will be needed to identify the full spectrum of common risk alleles that contribute to disease risk in the population. To identify genetic risk alleles for breast cancer risk among African American women, we are performing a well-powered whole-genome association scan. For this project, we have established a collaborative network of investigators whose careers have been dedicated to studying breast cancer in minority populations. They have contributed samples and covariates from each of their respective studies to identify genetic variants that contribute to the risk of breast cancer in this minority population. We have completed a GWAS of 1.1 SNPs in 3000 African American breast cancer cases and 2700 controls. With these data, we have validated and improved upon markers of risk at the known breast cancer risk regions that better characterize their contribution to breast cancer risk in women of African ancestry. In collaboration with GWAS in populations of European ancestry, we also have revealed a novel risk locus for estrogen receptor negative breast cancer. In this report, we present results for two specific analyses: (1) fine-mapping of the known breast cancer risk loci, and (2) a meta-analyses of GWAS for estrogen receptor negative breast cancer.
Towards an extensive map-oriented trace basis for human mobility modeling

Human mobility analysis and modeling is a very interdisciplinary field of research. Mobility models play an important role particularly in assessing the simulative performance of mobile and opportunistic networks. The mobility traces, which most of these models are based on, however, mostly suffer from several shortcomings. In this paper, we use the extensive Lausanne Data Collection Campaign (LDCC) mobility trace as basis for further map-oriented processing. Map-matching and sensible addition of optimal routes between points mitigate problems like GPS spatial noise, anonymization, and data gaps. Moreover, stay point extraction is performed as a preparation for the analysis of elemental statistical mobility characteristics. An exemplary impact evaluation of contact statistics shows that the resulting map-oriented trace basis is indeed suited for large-scale mobility analysis and simulation.
Content Analysis of Mediated Associations: An Automated Text-Analytic Approach

ABSTRACT Due to the fact that mediated associations are a central aspect of many mass communication theories, their measurement is of central interest for communication research. Mediated associations are defined as the repeated pairing of an object (e.g., social group, political party) with specific attributes (e.g., crime, economy). In this article, we introduce a recently developed, automated text-analytic technique. We present an application of this method in the media stereotyping domain via the content analysis of German news coverage of Islam. As predicted, the analysis revealed substantial mediated associations between Islam-related concepts and violence (e.g., “Koran + violence”), terror (e.g., “Islam + terror”), dehumanization (e.g., “Muslims + animal-related terms”), and general negativity (valence). We discuss the promises and pitfalls of this method, make software suggestions, and provide application-related information for speedy dissemination in communication research.
Second-Order and Dependently-Sorted Abstract Syntax

The paper develops a mathematical theory in the spirit of categorical algebra that provides a model theory for second-order and dependently-sorted syntax. The theory embodies notions such as alpha-equivalence, variable binding, capture-avoiding simultaneous substitution, term metavariable, meta-substitution, mono and multi sorting, and sort dependency. As a matter of illustration, a model is used to extract a second-order syntactic theory, which is thus guaranteed to be correct by construction.
Silverline : Toward Data Confidentiality in Third-Party Clouds

By offering high availability and elastic access to resourc es, thirdparty cloud infrastructures such as Amazon AWS and Microsof t Azure are revolutionizing the way today’s businesses opera te. Unfortunately, taking advantage of their benefits requires bu sinesses to accept a number of serious risks to data security. Factors such as software bugs, operator errors and external attacks can all compromise the confidentiality of sensitive data on external cloud s, making them vulnerable to unauthorized access by malicious partie s. In this paper, we study and seek to improve the confidentialit y of application data stored on third-party computing clouds. W e propose to identify and encrypt all functionally encryptabledata, sensitive data that can be encrypted without limiting the funct ionality of the cloud service. Such data would only be stored on the clo ud in an encrypted form, accessible only to users with the corre t k ys, thus ensuring its confidentiality against unintentional er rors and attacks alike. We describe Silverline, a set of tools that automatically 1) identify all functionally encryptable data in a cloud app lication, 2) assign encryption keys to specific data subsets to minimiz e key management complexity while ensuring robustness to key com pr mise, and 3) provide transparent data access at the user devi ce while preventing key compromise even from malicious clouds. Thro ugh experiments with real applications, we find that many web app lications are dominated by data sharingcomponents that do not require access to raw data. Thus, Silverline can protect the vast maj ority of data on these applications, simplify key management, and protect against key compromise. Together, our techniques prov ide a substantial first step towards simplifying the complex proc ess of incorporating data confidentiality into cloud application s.
Real-time emulation of magnetic suspension system in FPGA

Design, testing and validation of a real-time control hardware and software for active magnetic support of high-speed rotors is a very demanding engineering task. Firstly, this paper introduces the problems of proper diagnostics of a digital control system. Secondly, it presents an alternative way of real-time testing of such a control without the presence of the control plant, e.g. rotating shaft supported by an Active Magnetic Bearing (AMB) control system, itself. The article presents an Field Programmable Gate Array (FPAG) implementation of the AMB-rotor model. Two alternative implementations of an AMB non-linear force field are described. The optimized hardware realization of the rigid rotor in a state-space form is presented. A thorough description of a discrete representation of the state-space model and used per-unitvalues are given. The paper is concluded by a discussion about the implementation of a flexible rotor model.
Evolving Biodiversity

We formulated a mathematical model to study the evolution of biodiversity. Our model describes a collection of sites and incorporates a simple but explicit description of the competitive processes within a site. In our model the characteristics of component species evolve towards an evolutionarily stable state and in this way an evolutionarily stable assemblage of species is formed. We show that the number of species in these assemblages matches two well-documented patterns in biodiversity: the increase in the number of species towards the equator and the dependence of the number of species on the productivity of habitat: the average number of species rises to a maximum and then falls when plotted against increasing productivity of that habitat. Our results show that population dynamical and evolutionary processes can underlie patterns in biodiversity. The distribution of species over the earth is not even or random but seems to follow certain distinct patterns. Probably the best known example of such a pattern is the increase in the number of species towards the equator (Rosenzweig 1995; Gaston & Williams 1998). Another pattern is the dependence of the number of species on the productivity of habitat; the average number of species rises to a maximum and then falls when plotted against increasing productivity of that habitat (Rosenzweig 1995). Such patterns in biodiversity are well documented but as yet not unequivocally explained. Most species do not exist in isolation but coexist and compete with other species. Although communities of competitive species can harbour a large number of species (Zobel 1992), theoretical results predict that the number of competing species is limited by the number of resources. This apparent paradox has been explained by models that describe a collection of sites or patches in which the different species interact. Competing species that cannot coexist in a single site can coexist in a collection of coupled sites, and in this way many species can coexist in the collection of sites, despite the fact that local competition is for a small number of resources The number of species that can coexist somehow depends on the species' characteristics. In most models for biodiversity these characteristics are predefined constants. In real communities, however, the characteristics to a certain extent are formed through evolution. It is still very much an open question how the properties of competitive communities emerge through the evolution of their component species (Levin et al. 1997). Here, we …
New Criteria for the Linear Binary Separability in the Euclidean Normed Space

In this paper, the classical binary classification problem is investigated. Necessary and sufficient criterion is presented to guarantee the linear binary separability of the training data in the Euclidean normed space. A suitable hyperplane that correctly classifies the training data is also constructed provided that the necessary and sufficient is satisfied. Based on the main result, we offer an easy-to-check criterion for the linear binary separability of the training set. Finally, a numerical example is provided to illustrate the feasibility and effectiveness of the obtained result.
A Probabilistic Functional Network of Yeast Genes

A conceptual framework for integrating diverse functional genomics data was developed by reinterpreting experiments to provide numerical likelihoods that genes are functionally linked. This allows direct comparison and integration of different classes of data. The resulting probabilistic gene network estimates the functional coupling between genes. Within this framework, we reconstructed an extensive, high-quality functional gene network for Saccharomyces cerevisiae, consisting of 4681 (∼81%) of the known yeast genes linked by ∼34,000 probabilistic linkages comparable in accuracy to small-scale interaction assays. The integrated linkages distinguish true from false-positive interactions in earlier data sets; new interactions emerge from genes' network contexts, as shown for genes in chromatin modification and ribosome biogenesis.
Identification and functional analysis of the essential and regulatory light chains of the only type II myosin Myo1p in Saccharomyces cerevisiae

Cytokinesis in Saccharomyces cerevisiae involves coordination between actomyosin ring contraction and septum formation and/or targeted membrane deposition. We show that Mlc1p, a light chain for Myo2p (type V myosin) and Iqg1p (IQGAP), is the essential light chain for Myo1p, the only type II myosin in S. cerevisiae. However, disruption or reduction of Mlc1p–Myo1p interaction by deleting the Mlc1p binding site on Myo1p or by a point mutation in MLC1, mlc1-93, did not cause any obvious defect in cytokinesis. In contrast, a different point mutation, mlc1-11, displayed defects in cytokinesis and in interactions with Myo2p and Iqg1p. These data suggest that the major function of the Mlc1p–Myo1p interaction is not to regulate Myo1p activity but that Mlc1p may interact with Myo1p, Iqg1p, and Myo2p to coordinate actin ring formation and targeted membrane deposition during cytokinesis. We also identify Mlc2p as the regulatory light chain for Myo1p and demonstrate its role in Myo1p ring disassembly, a function likely conserved among eukaryotes.
Chapter 5 IMPROVING ROBUSTNESS BY MODELING SPONTANEOUS SPEECH EVENTS

In spontaneous speech, speakers segment their speech into intonational phrases, and make repairs to what they are saying. However, techniques for understanding spontaneous speech tend to treat these events as noise, in the same manner as they handle out-of-grammar constructions and misrecognitions. In our approach, we advocate that these events should be explicitly modeled, and that they must be resolved early in the processing stream. We put forward a statistical language model, which can be used during speech recognition, that models these events. This not only improves speech recognition perplexity and POS tagging, but also results in much richer output from the recognizer, with speech repairs resolved and intonational phrase boundaries identified. Syntactic and semantic processing can thus focus on dealing with out-of-grammar constructions and
Wave propagation and energy model for dynamic Wireless Body Area Networks

Wireless Body Area Network (WBAN) is an emerging research area focuses within Mobile and Ad-hoc Network (MANET). WBAN mainly deals with the remote health observation, depending on the requirements of miniaturized wireless sensors tactfully placed on the human body. These sensors are used to monitor various important parameters related with the human health. There are number of challenging tasks for researchers to address specific requirements of WBAN related with the propagation and energy models for wireless communication on the body. This piece of work consists of two parts: propagation model for static and dynamic nodes with the human body, and proposed energy model for WBAN. Special attention is paid on the node movement issues related to the wave propagation of wireless signals around the body. Path loss of (up to 20dB) is investigated when a node moves with the body in log normal shadow fading environment. An energy model for WBAN based on the values of power received and path loss from the propagation model is also proposed in this paper.
Motivation modelling for human-service interaction

Web services are goal-oriented software systems and often need to influence or motivate particular behaviour of their communication parties: humans and other services. This paper investigates modeling of motivation for human-service interaction. It shows why motivation needs a separate model different from the service process model, how to specify motivation and compose the motivation model with the service process model. Depending on the goals, the same service process model may have different motivation models. We provide an example of a service model with different motivation models that stimulate different behaviour of humans interacting with the web service.
Discrete-time polynomial fuzzy observer designs via a sum of squares approach

In this paper, a sum of squares(SOS) method is proposed to design observers for discrete-time polynomial fuzzy systems. The proposed SOS approach has two improved and innovative results for the existing linear matrix inequality (LMI) method to Takagi-Sugeno(T-S) discrete fuzzy observer designs. Firstly, a polynomial discrete fuzzy model is developed, which is a generation of the well-known T-S fuzzy system. Secondly, the conditions in the proposed approach are obtained in terms of SOS, which is the extension of the LMI method. Therefore, the conditions given in this paper are more general than the existing LMI approaches to T-S fuzzy systems. An example is given to show the effectiveness, which also demonstrate the SOS approaches are more relaxed than the existing LMI approaches. Finally, a conclusion is given to complete the paper.
Identifying the Outflow Driving Sources in Orion-KL

The enigmatic outflows of the Orion-KL region have raised discussions about their potential driving sources for several decades. Here, we present C18O(2-1) observations combined from the Submillimeter Array and the IRAM 30 m telescope. The molecular gas is associated on large scales with the famous northwest-southeast high-velocity outflow, whereas the high-velocity gas on small spatial scales traces back to the recently identified submm source SMA1. Therefore, we infer that SMA1 may host the driving source of this outflow. Based on the previously published thermal and maser SiO data, source I is the prime candidate to drive the northeast-southwest low-velocity outflow. The source SMA1 is peculiar because it is detected only in several submm wavelength bands but neither in the infrared nor cm regime. We discuss that it may be a very young intermediate- to high-mass protostar. The estimated outflow masses are high, whereas the dynamical timescale of the outflow is short, of the order 103 yr.
Fabrication and Testing of an Osmotic Pressure Sensor for Glucose Sensing Application

This paper presents a chemical reaction-free sensor, based on the osmosis principle, fabricated to measure the change in glucose concentration levels. The sensor consists of a square cavity filled with a known concentration of glucose solution and sealed with a semi-permeable membrane. The volume inside the cavity changes in proportion to the glucose concentration outside the device and introduces the displacement in the silicon (Si) membrane on the top. The main considerations targeted for this sensor are better response time, chemical-free nature, improved lifetime and absence of any mechanical excitations. Moreover, as the size of a system plays a major role, efforts have been taken to reduce the dimension of the presented system. The designed glucose sensor is fabricated by employing a bulk micromachining technology on a SOI (silicon on insulator) substrate. This will allow batch fabrication, as well as the integration of the electronic circuit on the same substrate. The output voltage obtained is varied from