Miracle-dz/UniFAR-FTUs huggingface dataset:
An Invitation to Model-Theoretic Galois Theory

Abstract We carry out some of Galois' work in the setting of an arbitrary first-order theory T. We replace the ambient algebraically closed field by a large model M of T, replace fields by definably closed subsets of M, assume that T codes finite sets, and obtain the fundamental duality of Galois theory matching subgroups of the Galois group of L over F with intermediate extensions F ≤ K ≤ L. This exposition of a special case of [10] has the advantage of requiring almost no background beyond familiarity with fields, polynomials, first-order formulae, and automorphisms.
Global network modelling based on mininet approach.

The problem of the Global network operation analysis has a variety of applications. In this paper we show an approach to this problem on example of malware propagation in the Global networks (Wide Area Network). It is very important to be able to make accurate prediction of the consequences of such propagation. This paper introduces a new approach to malware propagation prediction based on the ideas presented by Mininet network rapid prototyping approach. The major barriers to use simulation techniques for malware propagation analysis are enormous network size and low level granularity in protocol data unit processing. Mininet cannot be used for this purpose too because of its low level scalability. In this paper, we propose a new system called Mininet CE (Cluster Edition) which is based on the ideas of existent Mininet. Mininet CE offers the solution of the Global network functionality analysis problems. In this paper, we focus on propagation analysis of a malware as network worm. The experiments with the worm Sasser demonstrate the ability of Mininet CE to be useful tool for worm propagation analysis in the Global network.
Improved Approximation Algorithms for PRIZE-COLLECTING STEINER TREE and TSP

We study the prize-collecting versions of the Steiner tree, traveling salesman, and stroll (a.k.a. Path-TSP) problems (PCST, PCTSP, and PCS, respectively): given a graph (V, E) with costs on each edge and a penalty (a.k.a. prize) on each node, the goal is to find a tree (for PCST), cycle (for PCTSP), or stroll (for PCS) that minimizes the sum of the edge costs in the tree/cycle/stroll and the penalties of the nodes not spanned by it. In addition to being a useful theoretical tool for helping to solve other optimization problems, PCST has been applied fruitfully by AT&T to the optimization of real-world telecommunications networks. The most recent improvements for the first two problems, giving a 2-approximation algorithm for each, appeared first in 1992. (A 2-approximation for PCS appeared in 2003.) The natural linear programming (LP) relaxation of PCST has an integrality gap of 2, which has been a barrier to further improvements for this problem. We present (2-epsilon)-approximation algorithms for all three problems, connected by a unified technique for improving prize-collecting algorithms that allows us to circumvent the integrality gap barrier.
Inter-cell coordination in wireless data networks

Over the past few years, the design and performance of channel-aware scheduling strategies have attracted huge interest. In the present paper, we examine a somewhat different notion of scheduling, namely coordination of transmissions among base stations, which has received little attention so far. The inter-cell coordination comprises two key elements: (i) interference avoidance and (ii) load balancing. The interference avoidance involves coordinating the activity phases of interfering base stations so as to increase transmission rates. The load balancing aims at diverting traffic from heavily loaded cells to lightly loaded cells. Numerical experiments demonstrate that inter-cell scheduling may provide significant capacity gains.
Quantifying spatial classification uncertainties of the historical Wisconsin landscape (USA)

Landscape feature can be classified by creating categories based on aggregation of spatially explicit information. However, many landscape features appear continuous rather than discrete. The aggregation process likely involves loss of information and introduces a variety of uncertainties whose degree and extent may differ spatially. Since landscape classifications have found wide application in e.g. natural resource policies or ecological research, assessments of spatial classification uncertainties are required. We present a quantitative framework to identify the degree of landscape continuity (fuzziness) and structure (categorization) based on fuzzy classification and offer measures to quantify uncertainties originating from aggregating features into categories. Fuzzy classification is a non-hierarchical, quantitative method of assessing class definitions using degrees of association between features and class. This results in classes which are well defined and compositionally distinct, as well as classes which are less clearly defined but which, to various degrees, share characteristics with some or all classes. The spatial variation in the degree of class definition on the landscape is used to assess classification uncertainties. The two aspects of uncertainty investigated are the degree of association of a feature with the overall class definitions (membership diffusion), and the class-specific degree of association of each pixel on the landscape with each class (membership saturation). Three classification scenarios, one fuzzy and one discrete, of the historical landscape of Wisconsin (USA) were compared for spatial classification uncertainties. Membership diffusion is highest in topographically heterogeneous environments, or areas characterized by many species occupying similar ecological niches. Classification uncertainties for individual classes show that differentiated species distributions can be identified, not only distribution centers.
Discrete medial axis transform for discrete thin and elongated objects

Skeletons are compact shape descriptions of discrete images. They have been extensively studied because of their utility in various applications such as data compression, shape abstraction, navigation and features detection. In this article, a new Euclidean skeletal definition for 2D discrete objects based on the Distance Map (DMAT) is being proposed. As a novel feature, it is shown that this skeleton is a connected subset of the discretization of the continuous medial axis of the object. Because of this property, the DMAT is 8-connected, it reflects all the features of the object and it preserves its topological characteristics. In addition, it provides dimensionality reduction, symmetry detection and invertibility. Moreover, it has a reasonable size and it guarantees low thickness.
Robust Risk Adjustment in Health Insurance

Objectives. To create risk scores in a manner that incorporates uncertainty in the models used to redistribute payments to payers based on the risk of their enrollee population, to offset the cost of some payers' providing health insurance to relatively high-risk individuals. Study Design. We propose a methodology based on worst-case optimization over an appropriate uncertainty set . Data Sources. We use Federal Register data to create a realistic case study. Principal Findings. Our approach to compute robust risk scores involves solving a series of linear problems and thus can be done using standard analytical tools such as Excel Solver. Conclusions. There is an important need for the "robustification" of risk scores so that health payers can be properly compensated for the risk they take in providing insurance to relatively high-risk individuals. Our model presents one possible way to do so in a tractable manner.
Towards faster method search through static ecosystem analysis

Software developers are often unsure of the exact name of the method they need to use to invoke the desired behavior in a given context. This results in a process of searching for the correct method name in documentation, which can be lengthy and distracting to the developer. We can decrease the method search time by enhancing the documentation of a class with the most frequently used methods. Usage frequency data for methods is gathered by analyzing other projects from the same ecosystem -- written in the same language and sharing dependencies. We implemented a proof of concept of the approach for Pharo Smalltalk and Java. In Pharo Smalltalk, methods are commonly searched for using a code browser tool called "Nautilus", and in Java using a web browser displaying HTML based documentation -- Javadoc. We developed plugins for both browsers and gathered method usage data from open source projects, in order to increase developer productivity by reducing method search time. A small initial evaluation has been conducted showing promising results in improving developer productivity.
An investigation of predictors of mental health in single men and women experiencing homelessness in three Canadian cities

ABSTRACT Homelessness is related to poorer mental health, yet, there is limited understanding of the predictors of mental health of men and women experiencing homelessness. To support service providers in identifying individuals who might be at particular risk of poor mental health, this study investigated the predictors of mental health in 501 single men and women experiencing homelessness in Vancouver, Toronto, and Ottawa, Canada. Data were obtained via in-person, structured interviews. In order to identify whether predictors differ by gender, multiple linear regressions were conducted separately for men and women. Mental health status was measured by the Mental Component Summary score of the 12-item Short-Form Health Survey. Better mental health for men and women was associated with the presence of fewer chronic health conditions and a higher level of social support. An older age, not having experienced a recent physical attack, and absence of a mental health diagnosis were related to better mental health for women. The absence of unmet mental health needs within the past 12 months was associated with better mental health for men. The study highlights differences in factors associated with mental health for men and women. Service providers should be aware of the association of these factors with mental health to guide assessment and service planning.
Virtual Datagloves: Interacting with Virtual Environments Through Computer Vision

This paper outlines a system design and implementation of a 3D input device for graphical applications. It is shown how computer vision can be used to track a users movements within the image frame allowing interaction with 3D worlds and objects. Point Distribution Models (PDMs) have been shown to be successful at tracking deformable objects. This system demonstrates how these ‘smart snakes’ can be used in real time with real world applications, demonstrating how computer vision can provide a low cost, intuitive interface that has few hardware constraints. The compact mathematical model behind the PDM allows simple static gesture recognition to be performed providing the means to communicate with an application. It is shown how movement of both the hand and face can be used to drive 3D engines. The system is based upon Open Inventor and designed for use with Silicon Graphics Indy Workstations but allowances have been made to facilitate the inclusion of the tracker within third party applications. The reader is also provided with an insight into the next generation of HCI and Multimedia. Access to this work can be gained through the above web address.
Cooperation toward Environmental Innovation: An Empirical Investigation

This paper explores the relationship between firms cooperation and their propensity toward environmental innovation. Previous literature has emphasized the peculiarities of such innovations based on their drivers, their positive spill-overs and the importance of regulation to trigger them. This paper contributes to the literature by focusing on the importance of cooperation and of vertical, horizontal and lateral cooperative agreements on environmental innovation propensity. I test these hypotheses through a large scale dataset, the Community Innovation Survey for Spanish firms (PITEC), through the use of estimation techniques that allow to control for possible selection bias. The econometric estimations suggest that environmental innovative firms cooperate on innovation to an higher extent than other innovative firms. Furthermore, cooperation with suppliers, KIBS and universities is more relevant than for other innovative firms, whereas cooperation with clients does not seem to be differentially important.
WSNs Performance Evaluation Using Non-equilibrium Statistical Mechanics Method

In recent years, with the further development and more applications emerging, WSNs is no longer confined to the traditional area. Because WSNs is dynamic, distribution, resource constrained, uncertainty, complexity and heterogeneity, meanwhile distinct WSNs applications have distinct characteristics and requirements in the respective field, which both urge us to further research, especially performance evaluation of WSNs. In this paper, we expand the range of performance index which exceeds time delay, packet loss rate, and throughput. Meanwhile, put forward a non-equilibrium statistical mechanics model for integrated WSNs performance evaluation from an evolutionary perspective. A non-linear information dynamics mode is introduced based on the maximum flux principle during the modeling process. The integrated performance evaluation of WSNs can be done by giving reasonable weights of each evaluation index to stabilize the system. The new model reveals the formation pattern and the dynamics law of evolution. The proposed method has been serviced in complex simulation, and the results have indicated that the model is objective and effective.
Specifying Associations Between Conscientiousness and Executive Functioning: Mental Set Shifting, Not Prepotent Response Inhibition or Working Memory Updating.

Conscientiousness is characterized by self-control, organization, and goal orientation and is positively related to a number of health and professional outcomes. Thus, it is commonly suggested that conscientiousness should be related to superior executive functioning (EF) abilities, especially prepotent response inhibition. However, little empirical support for this notion has emerged, perhaps due to oversimplified and underspecified modeling of EF. The current study sought to fill this gap by testing relations between conscientiousness and three facets of EF using a nested factors latent variable approach. Participants (N = 420; Mage = 22.5; 50% male; 91% Caucasian) completed a measure of conscientiousness and nine EF tasks designed to tap three related yet distinguishable facets of EF: working memory updating, mental set shifting, and prepotent response inhibition. Structural equation models showed that conscientiousness is positively associated with the EF facet of mental set shifting but not response inhibition or working memory updating. Despite the common notion that conscientiousness is associated with cognitive abilities related to rigid control over impulses (i.e., inhibition), the current results suggest the cognitive ability most associated with conscientiousness is characterized by flexibility and the ability to adapt to changing environmental contingencies and task demands.
Realizing autonomics for future networks

While there has been undeniable progress in the field of autonomic networking research over the past several years, widespread deployments of self-management techniques are still missing. At the same time the need for techniques enabling the transformation of operational models, the evolution towards more flexible networks is becoming more and more evident. Further, most efforts have been focused on solving manageability bottlenecks in a given technological domain, while communication services extend anywhere, regardless of the technological boundaries (e.g. wireline/wireless). This paper presents an end-to-end and modular approach for the realization of future autonomic networks, focusing on common management and information substrates semantically enriched, on network empowerment mechanisms providing reasoning embodiment right into the network systems, and on the establishment of a reference trust framework for large-scale deployment and adoption.
CVD Diamond - The Next Generation Electronic Material

The status of diamond electronic device structures for high power, high temperature and high frequency is reviewed and latest data are highlighted. First results on the operation in harsh environment and very high temperature suggest that besides the power handling capability, the stability, robustness and reliability may be superior to that of all other semiconductors
CPEB controls oocyte growth and follicle development in the mouse

CPEB is a sequence-specific RNA-binding protein that regulates polyadenylation-induced translation. In Cpeb knockout mice, meiotic progression is disrupted at pachytene due to inhibited translation of synaptonemal complex protein mRNAs. To assess the function of CPEB after pachytene, we used the zona pellucida 3 (Zp3) promoter to generate transgenic mice expressing siRNA that induce the destruction of Cpeb mRNA. Oocytes from these animals do not develop normally; they undergo parthenogenetic cell division in the ovary, exhibit abnormal polar bodies, are detached from the cumulus granulosa cell layer, and display spindle and nuclear anomalies. In addition, many follicles contain apoptotic granulosa cells. CPEB binds several oocyte mRNAs, including Smad1, Smad5, spindlin, Bub1b, Mos, H1foo, Obox1, Dnmt1o, TiParp, Trim61 and Gdf9, a well described oocyte-expressed growth factor that is necessary for follicle development. In Cpeb knockdown oocytes, Gdf9 RNA has a shortened poly(A) tail and reduced expression. These data indicate that CPEB controls the expression of Gdf9 mRNA, which in turn is necessary for oocyte-follicle development. Finally, several phenotypes, i.e. progressive oocyte loss and infertility, elicited by the knockdown of CPEB in oocytes resemble those of the human premature ovarian failure syndrome.
Consciousness and the Prefrontal Parietal Network: Insights from Attention, Working Memory, and Chunking

Consciousness has of late become a “hot topic” in neuroscience. Empirical work has centered on identifying potential neural correlates of consciousness (NCCs), with a converging view that the prefrontal parietal network (PPN) is closely associated with this process. Theoretical work has primarily sought to explain how informational properties of this cortical network could account for phenomenal properties of consciousness. However, both empirical and theoretical research has given less focus to the psychological features that may account for the NCCs. The PPN has also been heavily linked with cognitive processes, such as attention. We describe how this literature is under-appreciated in consciousness science, in part due to the increasingly entrenched assumption of a strong dissociation between attention and consciousness. We argue instead that there is more common ground between attention and consciousness than is usually emphasized: although objects can under certain circumstances be attended to in the absence of conscious access, attention as a content selection and boosting mechanism is an important and necessary aspect of consciousness. Like attention, working memory and executive control involve the interlinking of multiple mental objects and have also been closely associated with the PPN. We propose that this set of cognitive functions, in concert with attention, make up the core psychological components of consciousness. One related process, chunking, exploits logical or mnemonic redundancies in a dataset so that it can be recoded and a given task optimized. Chunking has been shown to activate PPN particularly robustly, even compared with other cognitively demanding tasks, such as working memory or mental arithmetic. It is therefore possible that chunking, as a tool to detect useful patterns within an integrated set of intensely processed (attended) information, has a central role to play in consciousness. Following on from this, we suggest that a key evolutionary purpose of consciousness may be to provide innovative solutions to complex or novel problems.
Boosting Bioluminescence Neuroimaging: An Optimized Protocol for Brain Studies

Bioluminescence imaging is widely used for optical cell tracking approaches. However, reliable and quantitative bioluminescence of transplanted cells in the brain is highly challenging. In this study we established a new bioluminescence imaging protocol dedicated for neuroimaging, which increases sensitivity especially for noninvasive tracking of brain cell grafts. Different D-Luciferin concentrations (15, 150, 300 and 750 mg/kg), injection routes (iv, ip, sc), types of anesthesia (Isoflurane, Ketamine/Xylazine, Pentobarbital) and timing of injection were compared using DCX-Luc transgenic mice for brain specific bioluminescence. Luciferase kinetics was quantitatively evaluated for maximal photon emission, total photon emission and time-to-peak. Photon emission followed a D-Luciferin dose-dependent relation without saturation, but with delay in time-to-peak increasing for increasing concentrations. The comparison of intravenous, subcutaneous and intraperitoneal substrate injection reflects expected pharmacokinetics with fastest and highest photon emission for intravenous administration. Ketamine/Xylazine and Pentobarbital anesthesia showed no significant beneficial effect on maximal photon emission. However, a strong difference in outcome was observed by injecting the substrate pre Isoflurane anesthesia. This protocol optimization for brain specific bioluminescence imaging comprises injection of 300 mg/kg D-Luciferin pre Isoflurane anesthesia as an efficient and stable method with a signal gain of approx. 200% (compared to 150 mg/kg post Isoflurane). Gain in sensitivity by the novel imaging protocol was quantitatively assessed by signal-to-noise calculations of luciferase-expressing neural stem cells grafted into mouse brains (transplantation of 3,000–300,000 cells). The optimized imaging protocol lowered the detection limit from 6,000 to 3,000 cells by a gain in signal-to-noise ratio.
RAB26 coordinates lysosome traffic and mitochondrial localization

ABSTRACT As they mature, professional secretory cells like pancreatic acinar and gastric chief cells induce the transcription factor MIST1 (also known as BHLHA15) to substantially scale up production of large secretory granules in a process that involves expansion of apical cytoplasm and redistribution of lysosomes and mitochondria. How a scaling factor like MIST1 rearranges cellular architecture simply by regulating expression levels of its transcriptional targets is unknown. RAB26 is a MIST1 target whose role in MIST1-mediated secretory cell maturation is also unknown. Here, we confirm that RAB26 expression, unlike most Rabs which are ubiquitously expressed, is tissue specific and largely confined to MIST1-expressing secretory tissues. Surprisingly, functional studies showed that RAB26 predominantly associated with LAMP1/cathepsin D lysosomes and not directly with secretory granules. Moreover, increasing RAB26 expression – by inducing differentiation of zymogen-secreting cells or by direct transfection – caused lysosomes to coalesce in a central, perinuclear region. Lysosome clustering in turn caused redistribution of mitochondria into distinct subcellular neighborhoods. The data elucidate a novel function for RAB26 and suggest a mechanism for how cells could increase transcription of key effectors to reorganize subcellular compartments during differentiation.