Miracle-dz/UniFAR-FTUs huggingface dataset:
Electroweak Baryogenesis and Dark Matter in the nMSSM

We examine the possibility of electroweak baryogenesis and dark matter in the nMSSM, a minimal extension of the MSSM with a singlet ﬁeld. This extension avoids the usual domain wall problem of the NMSSM, and also appears as the low energy theory in models of dynamical electroweak symmetry breaking with a so-called fat-Higgs boson. We demonstrate that a strong, ﬁrst order electroweak phase transition, necessary for electroweak baryogenesis, may arise in regions of parameter space where the lightest neutralino provides an acceptable dark matter candidate. We investigate the parameter space in which these two properties are fulﬁlled and discuss the resulting phenomenology. In particular, we show that there are always two light CP-even and one light CP-odd Higgs bosons with masses smaller than about 250 GeV. Moreover, in order to obtain a realistic relic density, the lightest neutralino mass tends to be smaller than M Z / 2, in which case the lightest Higgs boson decays predominantly into neutralinos.
Sex Bias in Graduate Admissions: Data from Berkeley

Examination of aggregate data on graduate admissions to the University of California, Berkeley, for fall 1973 shows a clear but misleading pattern of bias against female applicants. Examination of the disaggregated data reveals few decision-making units that show statistically significant departures from expected frequencies of female admissions, and about as many units appear to favor women as to favor men. If the data are properly pooled, taking into account the autonomy of departmental decision making, thus correcting for the tendency of women to apply to graduate departments that are more difficult for applicants of either sex to enter, there is a small but statistically significant bias in favor of women. The graduate departments that are easier to enter tend to be those that require more mathematics in the undergraduate preparatory curriculum. The bias in the aggregated data stems not from any pattern of discrimination on the part of admissions committees, which seem quite fair on the whole, but apparently from prior screening at earlier levels of the educational system. Women are shunted by their socialization and education toward fields of graduate study that are generally more crowded, less productive of completed degrees, and less well funded, and that frequently offer poorer professional employment prospects.
Context-Aware Profile Analyzer for Android

In this thesis we endeavor to develop a prototype of a mobile application that focuses on context-aware computing, trying to deploy it in a new and novel way and investigate unexplored dimensions of context-awareness. As users receive calls and texts, browse the web, play games and use applications, information aggregates in the phone. Our scope is to try to extract this information from communication log files of mobile device as well as from device’s sensors. Incoming and outgoing calls, messages or emails from several installed applications on mobile phone can be considered really useful for profile analysis of mobile owner. By combining this information with traditional context-aware information from sensors and build in data stores in the phone, an extensive user profile can be built an analyzed. Furthermore, we try to enlighten the reader regarding the concept of context and context-awareness in order to provide her a general knowledge for various frameworks which application developers used in order to develop context-aware application and finally we present several prototype applications. Furthermore, we focus on defining the problem together with the approach and the methodology which will be used. In addition, we present the tools that we used for the completion of this thesis together with the core implementation of the prototype application. The conclusion shows that the given approach is feasible to create a context-aware application based on simple design methodology using as essential information data from mobile sensors and user’s communication log. Kotsopoulos Dimitrios 11/12/2015
Do Celebrity Endorsements Benefit Familiar Luxury Brands? A Perspective From Social Adaptation Theory

Abstract From the perspective of social adaptation theory, this study empirically tests the effectiveness of celebrity endorsements of familiar luxury brands compared to that of noncelebrity endorsements. Two separate 2 (celebrity vs. non celebrity) × 2 (luxury vs. nonluxury brands) between-subjects-design experiments are conducted based on female college students (Study 1) and average female consumers (Study 2), respectively. The results show that celebrity endorsements are more effective than noncelebrity endorsements only in attitudes toward advertisements, but not in brand luxuriousness, brand attitudes, and purchase intention. A structural equation model identifies the significance of congruence between an endorser and an ad for luxury brand in generating brand luxuriousness and that greater brand luxuriousness does not warrant the high estimated price for the product featured in the ad. Theoretical contributions and practical implications are discussed at the end.
α-synuclein and synapsin III cooperatively regulate synaptic function in dopamine neurons

ABSTRACT The main neuropathological features of Parkinson's disease are dopaminergic nigrostriatal neuron degeneration, and intraneuronal and intraneuritic proteinaceous inclusions named Lewy bodies and Lewy neurites, respectively, which mainly contain α-synuclein (α-syn, also known as SNCA). The neuronal phosphoprotein synapsin III (also known as SYN3), is a pivotal regulator of dopamine neuron synaptic function. Here, we show that α-syn interacts with and modulates synapsin III. The absence of α-syn causes a selective increase and redistribution of synapsin III, and changes the organization of synaptic vesicle pools in dopamine neurons. In α-syn-null mice, the alterations of synapsin III induce an increased locomotor response to the stimulation of synapsin-dependent dopamine overflow, despite this, these mice show decreased basal and depolarization-dependent striatal dopamine release. Of note, synapsin III seems to be involved in α-syn aggregation, which also coaxes its increase and redistribution. Furthermore, synapsin III accumulates in the caudate and putamen of individuals with Parkinson's disease. These findings support a reciprocal modulatory interaction of α-syn and synapsin III in the regulation of dopamine neuron synaptic function. Summary: Absence or aggregation of α-synuclein induces a selective increase and redistribution of synapsin III, reorganizing synaptic vesicle pools, which could have implications for dopamine neuron degeneration in Parkinson's disease.
Outcomes of Estrogen Receptor Negative and Progesterone Receptor Positive Breast Cancer

Purpose To describe the clinical features and outcomes of estrogen receptor negative (ER-) and progesterone receptor positive (PgR+) breast cancer. Methods We retrospectively reviewed a well-characterized database of sequential patients diagnosed with early stage invasive breast carcinoma. Outcomes of interest were time to relapse (TTR) and overall survival (OS). Multivariable Cox proportional hazards analysis was conducted to assess the association of ER-/PgR+ with TTR and OS in comparison to ER+ and to ER- and PgR negative (ER-/PgR-) tumors irrespective of HER2 status. ER and PgR expression was conservatively defined as 10% or greater staining of cancer cells. Results 815 patients were followed for a median of 40.5 months; 56 patients (7%) had ER-/PgR+, 624 (77%) had ER+ and 136 (17%) had ER-/PgR- phenotypes. Compared with ER+ tumors, ER-/PgR+ tumors were associated with younger age (50 versus 59 years, p=0.03), high grade (50% versus 24%, p<0.001) and more frequent HER2 overexpression/amplification (43% versus 14%, p<0.001). TTR for ER-/PgR+ was intermediate between ER+ and ER-/PgR- tumors, but was not significantly different from ER+ tumors. Recurrences in the ER-/PgR+ and ER-/PgR- groups occurred early in follow-up while in ER+ tumors recurrences continued to occur over the duration of follow-up. OS of ER-/PgR+ was similar to ER+ tumors and better than that of ER-/PgR- tumors. Conclusions The ER-/PgR+ phenotype is associated with higher grade with HER2 overexpression/amplification and occurs more commonly in younger women. Risk of relapse and death more closely resembles ER+ than ER-/PgR- tumors suggesting this phenotype represents a group of more aggressive hormone receptor positive tumors.
Functional Analysis of Avr9/Cf-9 Rapidly Elicited Genes Identifies a Protein Kinase, ACIK1, That Is Essential for Full Cf-9–Dependent Disease Resistance in Tomatow⃞

Tomato (Lycopersicon esculentum) Cf genes confer resistance to the fungal pathogen Cladosporium fulvum through recognition of secreted avirulence (Avr) peptides. Plant defense responses, including rapid alterations in gene expression, are immediately activated upon perception of the pathogen. Previously, we identified a collection of Avr9/Cf-9 rapidly (15 to 30 min) elicited (ACRE) genes from tobacco (Nicotiana tabacum). Many of the ACRE genes encode putative signaling components and thus may play pivotal roles in the initial development of the defense response. To assess the requirement of 42 of these genes in the hypersensitive response (HR) induced by Cf-9/Avr9 or by Cf-4/Avr4, we used virus-induced gene silencing (VIGS) in N. benthamiana. Three genes were identified that when silenced compromised the Cf-mediated HR. We further characterized one of these genes, which encodes a Ser/Thr protein kinase called Avr9/Cf-9 induced kinase 1 (ACIK1). ACIK1 mRNA was rapidly upregulated in tobacco and tomato upon elicitation by Avr9 and by wounding. Silencing of ACIK1 in tobacco resulted in a reduced HR that correlated with loss of ACIK1 transcript. Importantly, ACIK1 was found to be required for Cf-9/Avr9- and Cf-4/Avr4-mediated HRs but not for the HR or resistance mediated by other resistance/Avr systems, such as Pto/AvrPto, Rx/Potato virus X, or N/Tobacco mosaic virus. Moreover, VIGS of LeACIK1 in tomato decreased Cf-9–mediated resistance to C. fulvum, showing the importance of ACIK1 in disease resistance.
Survey of mobile object tracking protocols in wireless sensor networks: a network-centric perspective

Mobile object tracking in Wireless Sensor Networks (WSNs) has gained much attention during recent years owing to its growing application potential for the ubiquitous society. In this paper, we present an investigation and taxonomy of the state-of-the-art in tracking moving objects in WSNs. To this end, we define the target tracking problem in general and introduce the major design considerations for an efficient Object Tracking Sensor Network (OTSN) in particular. We typify a complete object tracking solution as a system of signal processing-based algorithms in charge of target identification/classification and network-centric protocols as the communication substrate. Our special highlight would be on the discussion of the network-centric protocols built around the notion of OTSN. We outline the advantages as well as the performance issues in relevant schemes and conduct a brief comparative study. The survey concludes with several key open problems together with a summary of directions for future works.
A computer model of simple forms of learning in infants

Many workers have studied the problem of getting machines to exhibit aspects of intelligent behavior. It has become clear that a major limitation of the artificial intelligence field is the cost and difficulty of programming, which remains essentially a handicraft technique. What we need in artificial intelligence research are methods for the machine to be self-programming in a much deeper sense than the compilation process in use today. Briefly, we would like for the machine to "learn" to solve a problem, rather than being programmed in the usual laborious way. This report presents a computer program, using what I will call an "experience-driven compiler," which is able to program itself to solve a restricted class of problems involving cause-and-effect relationships. Although the program is not yet able to learn to solve problems of practical significance, it is hoped that the technique will be developed to the point where this can be done. I am in agreement with Turing's suggestion (1950) that the best way to achieve artificial intelligence is to find out what an infant has in his brain that allows him to become intelligent, put this capability into a computer, then allow the machine to "grow up" in much the same way as the baby does. (Of course, this is a statement of the problem rather than an explanation of how to solve it.) An additional purpose of the work is in psychology: we would like to have computer methods for testing theories of how learning might occur in living creatures.
Cell-free Tumor DNA in Blood Plasma As a Marker for Circulating Tumor Cells in Prostate Cancer

Purpose: Circulating cell-free DNA in the blood of cancer patients harbors tumor-specific aberrations. Here, we investigated whether this DNA might also reflect the presence of circulating tumor cells (CTC). Experimental Design: To identify the source of cell-free DNA in blood, plasma derived from 81 patients with prostate cancer was examined for CTCs and cell-free DNA. An epithelial immunospot assay was applied for detection of CTCs, and a PCR-based fluorescence microsatellite analysis with a panel of 14 polymorphic markers was used for detection of allelic imbalances (AI). Results: The plasma DNA levels significantly correlated with the diagnosis subgroups of localized (stage M0, n = 69) and metastasized prostate cancer (stage M1, n = 12; P = 0.03) and with the tumor stage of these patients (P < 0.005). AI was found on cell-free DNA in plasma from 45.0% and 58.5% of M0 and M1 patients, respectively. Detection of CTCs showed that 71.0% or 92.0% of the M0 and M1 patients harbored 1 to 40 CTCs in their blood, respectively. The occurrence of CTCs correlated with tumor stage (P < 0.03) and increasing Gleason scores (P = 0.04). Notably, significant associations of the number of CTCs with the AI frequencies at the markers D8S137 (P = 0.03), D9S171 (P = 0.04), and D17S855 (P = 0.02) encoding the cytoskeletal protein dematin, the inhibitor of the cyclin-dependent kinase CDKN2/p16 and BRCA1, respectively, were observed. Conclusions: These findings show, for the first time, a relationship between the occurrence of CTCs and circulating tumor-associated DNA in blood, which, therefore, might become a valuable new source for monitoring metastatic progression in cancer patients.
Two-Microphone Dereverberation for Automatic Speech Recognition of Polish

Reverberation is a common problem for many speech technologies, such as automatic speech recognition (ASR) systems. This paper investigates the novel combination of precedence, binaural and statistical independence cues for enhancing reverberant speech, prior to ASR, under these adverse acoustical conditions when two microphone signals are available. Results of the enhancement are evaluated in terms of relevant signal measures and accuracy for both English and Polish ASR tasks. These show inconsistencies between the signal and recognition measures, although in recognition the proposed method consistently outperforms all other combinations and the spectral-subtraction baseline.
Combretastatin A-4 Phosphate Affects Tumor Vessel Volume and Size Distribution as Assessed Using MRI-Based Vessel Size Imaging

Purpose: Combretastatin A-4 disodium phosphate (CA4P) is a promising vascular disrupting agent (VDA) in clinical trials. As CA4P acts on dividing endothelial cells, we hypothesize that CA4P affects vessels of certain sizes. The aim of this study was to evaluate the effect of CA4P by the MRI-based vessel size imaging (VSI). Experimental Design: C3H mammary carcinomas were grown to 200 mm3 in the right rear foot of female CDF1 mice. A control group of mice received no treatment, and a treatment group had CA4P administered intraperitoneally at a dose of 250 mg/kg. VSI was conducted on a 3 Tesla MR scanner to estimate the tumor blood volume (ζ0) and mean vessel radius (R). Vascularization was also estimated histologically by endothelial and Hoechst 33342 staining. Results: ζ0 and R showed different spatial heterogeneity. Tumor median and quartile values of ζ0 were all significantly reduced by about 35% in the CA4P-treated group as compared with the control group, and the median and upper quartile of R were significantly increased. Histograms of ζ0 and R showed a general decrease in ζ0 following treatment, and values of R in a certain range (≈20–30 μm) were decreased in the treatment group. The drug-induced change in ζ0 was in agreement with histology and our previous dynamic contrast enhanced MRI (DCE-MRI) data. Conclusions: Tumor blood volume and mean vessel radius showed a clear response following treatment with CA4P. VSI may prove valuable in estimation of tumor angiogenesis and prediction of response to VDAs. Clin Cancer Res; 18(23); 6469–77. ©2012 AACR.
Text Mining for Retrieving Reusable Code Blocks from Software Knowledge Base

This research paper presents a natural language processing based system that extracts the reusable code components from a software knowledge base. The extracted reusable software components can be used in the design and development of new software applications to save cost and time of the developer. The key issues involved in the research are reuse of software components, identification of these components from software code. The newly designed rule based framework is fairly efficient in analyzing the given scenario and extract the required reusable components to assist the developers according to the given guidelines. This research has been conducted to incorporate this obvious capability of the designed framework of analyzing the given scenario and extract the required reusable components to assist the developers according to the given guidelines. The designed system provides a quick and reliable way to extract required components that are used for reuse purposed on later stages. The application with such abilities can be more intelligent and pertinent specifically for the user to save the time.
Satisficing Negotiation for Resource Allocation with Disputed Resources

Satisficing decision making provides a more malleable framework for negotiation than conventional techniques based on optimization of a utility function. In this paper we summarize satisficing decision theory, which provides a mechanism for determining decision options which are "good enough" as as tradeoff between a selectability function and a rejectability function, with an index of caution as a decision control parameter. Single agent satisficing is extended to multi-agent satisficing, by which group rationality can be represented; option vectors for the entire group are obtained as a result of this decision process. Multi-agent satisficing provides the stage upon which negotiation takes place. Negotiation. in this context, is the process by which all agents determine a set of options which are both individually satisficing and jointly satisficing; through the course of negotiation agents can accommodate the needs of the group -- compromise -- through lowering their index of caution. An example is presented of resource allocation with disputed resources.
Event-Driven Optimal Control of Integral Continuous-Time Hybrid Automata

This paper proposes an event-driven optimal control strategy for hybrid systems composed of continuous-time integral dynamics with inputs and of Anite state machines triggered by endgenous and exogenous events. Endogenous events are caused by continuous states or continuous inputs crossing certain linear thresholds or by the elapse of time intervals, while exogenous events are forced by changes of binary and continuous inputs. The advantages of the proposed strategy are the reduction of the amount of computation required to solve optimal control problems, and the reduction of approximation errors typical of discrete-time approaches. We examine several performance objectives and constraints that lead to mixed-integerlinear or quadratic optimization problems and we exemplify the approach on a simple example.
Systematical Approach for Detecting the Intention and Intensity of Feelings on Social Network

Online posts not only represent the records of people's lives but also reveal their satisfaction with life and relationships as well as potential mental illnesses. The detection of (strong or general) negative as well as (strong or general) positive feelings of people from online posts can keep us from carelessly missing their important moments, difficult or great, due to the overloaded information in the daily life and lead to a better society. Therefore, in this paper, we build a Feeling Distinguisher system based on supervised Latent Dirichlet Allocation (sLDA), Latent Dirichlet Allocation, and SentiWordNet methodologies for detecting a person's intention and intensity of feelings through the analysis of his/her online posts. Experimental results on posts collected from five social network websites demonstrate the effectiveness of FeD. The performance of FeD is about 1.08-1.18 folds that of SVM and sLDA.
Ju l 2 00 1 hep-th / 0107173 Horizon Holography

A holographic correspondence between data on horizon and space-time physics is investigated. We find similarities with the AdS/CFT correspondence, based on the observation that the optical metric near the horizon describes a Euclidean asymptotically anti-de Sitter space. This picture emerges for a wide class of static space-times with a non-degenerate horizon, including Schwarzschild black holes as well as de Sitter space-time. We reveal a asymptotic conformal symmetry at the horizon. We compute the conformal weights and 2-point functions for a scalar perturbation and discuss possible connections with a (non-unitary) conformal field theory located on the horizon. We then reconstruct the scalar field and the metric from the data given on the horizon. We show that the solution for the metric in the bulk is completely determined in terms of a specified metric on the horizon. From the General Relativity point of view our solutions present a new class of space-time metrics with non-spherical horizons. The horizon entropy associated with these solutions is also discussed. 1 e-mail: ivo@theorie.physik. uni-muenchen.de 2 e-mail: soloduk@theorie.physik. uni-muenchen.de
Invisible Brain: Knowledge in Research Works and Neuron Activity

If the market has an invisible hand, does knowledge creation and representation have an “invisible brain”? While knowledge is viewed as a product of neuron activity in the brain, can we identify knowledge that is outside the brain but reflects the activity of neurons in the brain? This work suggests that the patterns of neuron activity in the brain can be seen in the representation of knowledge-related activity. Here we show that the neuron activity mechanism seems to represent much of the knowledge learned in the past decades based on published articles, in what can be viewed as an “invisible brain” or collective hidden neural networks. Similar results appear when analyzing knowledge activity in patents. Our work also tries to characterize knowledge increase as neuron network activity growth. The results propose that knowledge-related activity can be seen outside of the neuron activity mechanism. Consequently, knowledge might exist as an independent mechanism.