Miracle-dz/UniFAR-FTUs huggingface dataset:
On the Propagation of Low-Rate Measurement Error to Subgraph Counts in Large, Sparse Networks

Our work in this paper is inspired by a statistical observation that is both elementary and broadly relevant to network analysis in practice -- that the uncertainty in approximating some true network graph $G=(V,E)$ by some estimated graph $\hat{G}=(V,\hat{E})$ manifests as errors in the status of (non)edges that must necessarily propagate to any estimates of network summaries $\eta(G)$ we seek. Motivated by the common practice of using plug-in estimates $\eta(\hat{G})$ as proxies for $\eta(G)$, our focus is on the problem of characterizing the distribution of the discrepancy $D=\eta(\hat{G}) - \eta(G)$, in the case where $\eta(\cdot)$ is a subgraph count. Specifically, we study the fundamental case where the statistic of interest is $|E|$, the number of edges in $G$. Our primary contribution in this paper is to show that in the empirically relevant setting of large graphs with low-rate measurement errors, the distribution of $D_E=|\hat{E}| - |E|$ is well-characterized by a Skellam distribution, when the errors are independent or weakly dependent. Under an assumption of independent errors, we are able to further show conditions under which this characterization is strictly better than that of an appropriate normal distribution. These results derive from our formulation of a general result, quantifying the accuracy with which the difference of two sums of dependent Bernoulli random variables may be approximated by the difference of two independent Poisson random variables, i.e., by a Skellam distribution. This general result is developed through the use of Stein's method, and may be of some general interest. We finish with a discussion of possible extension of our work to subgraph counts $\eta(G)$ of higher order.
The Book Review Column 1 Coverage Untyped Systems Simple Types Recursive Types Higher-order Systems General Impression 3 Organization, and Contents of the Book

In this column we review the following books. 1. Types and Programming Languages by Benjamin C. Pierce. This is a book about implementing type systems in programming languages. It uses λ-calculus. 3. Verification of Reactive Systems : Formal Methods and Algorithms by Klaus Schneider. This is a book about verification of real time systems. 4. Algorithmic Learning in a Random World by Vovk, Gammerman, and Shafer. This is a book about Machine Learning that takes that randomness of the world into account. 5. The Random Projection Method by Santosh Vempala. The method in the title involves taking a high-dimensional problem and randomly projecting it to one-dimensional. This technique is used in combinatorial optimization, learning, and information retrieval. Books I want Reviewed If you want a FREE copy of one of these books in exchange for a review, then email me at Overview Type systems and type checking are playing an increasingly important role in the development of programming languages. Almost every programming language developed today are developed with type systems as an integral part of the language. The goals of this book are to cover all important core topics of and give useful examples of how to use and implement type systems for programming languages. The book is separated into several parts, each part with coverage of one important core topic. After the introduction of lambda-calculus and some basic formalism for describing languages, the book presents a simple type system for lambda-calculus. In the following parts, the type system is then extended to cover recursive types, subtypes, polymorphic types, and higher-order polymorphic types (of the form that the purely functional language Haskell uses). In the course of defining and extending the type systems, the author gives several detailed examples of how to use them. The examples are interesting and to-the-point. Each important topic contain at least one in-depth study of an either an application or an example type system. In the book, there are case studies of both functional and imperative versions for objects (as in object-oriented programming) and also an introduction to Featherweight Java, which is a minimal core system for modeling Java's type system. The first part of the book introduces a simple language to express untyped arithmetic expressions. The purpose of this part is to introduce fundamental concepts for the description of syntax and semantics of programs. The subjects introduced are basic and can be skipped by …
Sea-ice switches and abrupt climate change

We propose that past abrupt climate changes were probably a result of rapid and extensive variations in sea–ice cover. We explain why this seems a perhaps more likely explanation than a purely thermohaline circulation mechanism. We emphasize that because of the significant influence of sea ice on the climate system, it seems that high priority should be given to developing ways for reconstructing high–resolution (in space and time) sea–ice extent for past climate–change events. If proxy data can confirm that sea ice was indeed the major player in past abrupt climate–change events, it seems less likely that such dramatic abrupt changes will occur due to global warming, when extensive sea–ice cover will not be present.
Isolation and characterization of the human gene encoding I to: further diversity by alternative mRNA splicing.

The transient outward K+ current ( I to) in the heart is responsible for the initial phase of repolarization and for setting the plateau voltage of the ventricular action potential. Recently, Kv4.3 has emerged as the leading candidate α-subunit gene that underlies I to in larger mammals such as dogs and humans. We have cloned the human Kv4.3 homolog and describe a carboxyl-terminal splice variant that inserts 19 amino acids with a consensus protein kinase C (PKC) phosphorylation site into the protein after the last membrane-spanning segment. The coding region of Kv4.3 is comprised of at least five exons and is located on chromosome 1p13.3. In the basal state the basic biophysical properties of both of the splice variants are identical.
Artemis: A System for Analyzing Missing Answers

A central feature of relational database management systems is the ability to define multiple different views over an underlying database schema. Views provide a method of defining access control to the underlying database, since a view exposes a part of the database and hides the rest. Views also provide logical data independence to application programs that access the database. For most cases, the process of specifying the desired views in SQL is typically tedious and error-prone. While numerous tools exist to support developers in debugging program code, we are not aware of any tool that supports developers in verifying the correctness of their views defined in SQL.
STATLOG: COMPARISON OF CLASSIFICATION ALGORITHMS ON LARGE REAL-WORLD PROBLEMS

This paper describes work in the StatLog project comparing classification algorithms on large real-world problems. The algorithms compared were from symbolic learning (CART. C4.5, NewID, AC2,ITrule, Cal5, CN2), statistics (Naive Bayes, k-nearest neighbor, kernel density, linear discriminant, quadratic discriminant, logistic regression, projection pursuit, Bayesian networks), and neural networks (backpropagation, radial basis functions). Twelve datasets were used: five from image analysis, three from medicine, and two each from engineering and finance. We found that which algorithm performed best depended critically on the data set investigated. We therefore developed a set of data set descriptors to help decide which algorithms are suited to particular data sets. For example, data sets with extreme distributions (skew > l and kurtosis > 7) and with many binary/categorical attributes (>38%) tend to favor symbolic learning algorithms. We suggest how classification algorithms can be extended in a number of d.
Wear Behavior of Multiwalled Carbon Nanotube/AZ31 Composite Obtained by Friction Stir Processing

Multiwalled carbon nanotubes were homogenously dispersed into a magnesium alloy (AZ31) using friction stir processing. The microstructural features, mechanical behaviors including microhardness, and wear properties were investigated. The results showed a significant improvement in wear resistance in the friction stir-processed AZ31 alloy containing multiwalled carbon nanotubes compared to that of the as-received alloy. This was attributed to its higher microhardness and lower coefficient of friction due to the presence of finer matrix grains and uniform dispersion of multiwalled carbon nanotubes.
A Discrete-State Spiking Neuron Model and its Learning Potential (Expansion of Integrable Systems)

In this paper we review some of our recent results on discrete‐state spiking neuron models. The discrete‐state spiking neuron model is a wired system of shift registers and can generate various spike‐trains by adjusting the pattern of the wirings. In this paper we show basic relations between the wiring pattern and characteristics of the spike‐train. We also show a learning algorithm which utilizes successive changes of the wiring pattern. It is shown that the learning algorithm enables the neuron to approximate various spike‐trains generated by a chaotic analog spiking neuron.
Thymic involution, a co-morbidity factor in amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a devastating disease, characterized by extremely rapid loss of motor neurons. Our studies over the last decade have established CD4+ T cells as important players in central nervous system maintenance and repair. Those results, together with recent findings that CD4+ T cells play a protective role in mouse models of ALS, led us to the current hypothesis that in ALS, a rapid T‐cell malfunction may develop in parallel to the motor neuron dysfunction. Here, we tested this hypothesis by assessing thymic function, which serves as a measure of peripheral T‐cell availability, in an animal model of ALS (mSOD1 [superoxide dismutase] mice; G93A) and in human patients. We found a significant reduction in thymic progenitor‐cell content, and abnormal thymic histology in 3–4‐month‐old mSOD1 mice. In ALS patients, we found a decline in thymic output, manifested in the reduction in blood levels of T‐cell receptor rearrangement excision circles, a non‐invasive measure of thymic function, and demonstrated a restricted T‐cell repertoire. The morbidity of the peripheral immune cells was also manifested in the increase of pro‐apoptotic BAX/BCXL2 expression ratio in peripheral blood mononuclear cells (PBMCs) of these patients. In addition, gene expression screening in the same PBMCs, revealed in the ALS patients a reduction in key genes known to be associated with T‐cell activity, including: CD80, CD86, IFNG and IL18. In light of the reported beneficial role of T cells in animal models of ALS, the present observation of thymic dysfunction, both in human patients and in an animal model, might be a co‐pathological factor in ALS, regardless of the disease aetiology. These findings may lead to the development of novel therapeutic approaches directed at overcoming the thymic defect and T‐cell deficiency.
Disappointment and regret enhance corrugator reactivity in a gambling task

This study investigated how the corrugator and zygomaticus respond to decision outcomes (i.e., gains and losses). We used a gambling task in which participants were presented with obtained followed by non-obtained outcomes. Activity at the corrugator site was sensitive to decision outcomes, such that higher obtained losses (disappointment) and higher non-obtained gains (regret) both heightened corrugator reactivity. Activity at the zygomaticus site was not responsive to obtained or non-obtained outcomes, but did show sensitivity to emotional images in the same participants, in the form of a positive linear relationship with self-reported emotional valence. Corrugator activity was negatively related to emotional valence. The findings indicate the sensitivity of corrugator to objective decision outcomes and also counterfactual comparisons, highlighting the utility of facial electromyography in research on decision making and gambling behavior.
Method of residual birefringence measurements in interferometer with increased sensitivity

We present a new method for the measurement of a residual birefringence in a polariscopic interferometer. Measured medium inserted into the setup can cause the changes in the polarization state of the propagated beam. Specific orientation of the elements (i.e. the analyzer and the phase retarder) modifies the setup response to the small changes of the azimuth and ellipticity angles of the propagated beam - the sensitivity of the setup is highly increased within the limited measuring range. The sensitivity and the measuring range of the setup can be adjusted by proper mutual orientation of the setup elements. Even though the measurement requires the analysis of the low contrast interferograms, what can be difficult, the application of the Fourier analysis allows the calculations for the interferogram contrast lower than in case of classical interference pattern shift tracking. In the present paper both theoretical considerations and experimental results taken from the experimental model setup are presented. Hundredfold increase in sensitivity was obtained in the presented experiments, which allowed the measurement of phase difference introduced by the birefringent medium with an accuracy of one hundredth degree.
The Cophylogeny Reconstruction Problem Is NP-Complete

The co phylogeny reconstruction problem is that of finding minimum cost explanations of differences between historical associations. The problem arises in parasitology, molecular systematics, and biogeography. Existing software tools for this problem either have worst-case exponential time or use heuristics that do not guarantee optimal solutions. To date, no polynomial time optimal algorithms have been found for this problem. In this article, we prove that the problem is NP-complete, suggesting that future research on algorithms for this problem should seek better polynomial-time approximation algorithms and heuristics rather than optimal solutions.
Evolution of the density profiles of dark matter haloes

We use numerical simulations in a ACDM cosmology to model density profiles in a set of 16 dark matter haloes with resolutions of up to seven million particles within the virial radius. These simulations allow us to follow robustly the formation and evolution of the central cusp over a large mass range of 10 11 -10 14 M○. , down to approximately 0.5 per cent of the virial radius, and from redshift of 5 to the present, covering a larger range in parameter space than previous works. We confirm that the cusp of the density profile is set at redshifts of 2 or greater and remains remarkably stable to the present time, when considered in non-comoving coordinates. Motivated by the diversity and evolution of halo profile shapes, we fit our haloes to the two-parameter profile, p oc 1/((c γ r/r vir ) γ [1 + (c γ r/r vir )] 3-γ }, where the steepness of the cusp is given by the asymptotic inner slope parameter, y, and its radial extent is described by the concentration parameter, c γ (with c γ defined as the virial radius divided by the concentration radius). In our simulations, we find γ ≃ 1.4 - 0.08 log 10 (M/M*) for haloes of 0.01 M*-1000 M*, with a large scatter of Δγ ∼ ±0.3, where M* is the redshift dependent characteristic mass of collapsing haloes; and c γ ≃ 8. (M/M*) -0.15 , with a large M/M* dependent scatter roughly equal to ± cy. Our redshift zero haloes have inner slope parameters ranging approximately from r -1 (Navarro, Frank and White) to r -1.5 (Moore et al.), with a median of roughly r- 1.3 . This two-parameter profile fit works well for all types of haloes in our simulations, whether or not they show evidence of a steep asymptotic cusp. We also model a cluster in power-law cosmologies of P k n , with n = (0, -1, -2, -2.7). Here we find that the concentration radius and the inner cusp slope are both a function of n, with larger concentration radii and shallower cusps for steeper power spectra. We have completed a thorough resolution study and find that the minimum resolved radius is well described by the mean interparticle separation over a range of masses and redshifts. The trend of steeper and more concentrated cusps for smaller M/M* haloes clearly shows that dwarf-sized ACDM haloes have, on average, significantly steeper density profiles within the inner few per cent of the virial radius than inferred from recent observations. Code to reproduce this profile can be downloaded from http://www.icc. dur.ac. uk/ ∼reed/profile.html.
Distributional Semantic Concept Models for Entity Relation Discovery

We present an ad hoc concept modeling approach using distributional semantic models to identify fine-grained entities and their relations in an online search setting. Concepts are generated from user-defined seed terms, distributional evidence, and a relational model over concept distributions. A dimensional indexing model is used for efficient aggregation of distributional, syntactic, and relational evidence. The proposed semi-supervised model allows concepts to be defined and related at varying levels of granularity and scope. Qualitative evaluations on medical records, intelligence documents, and open domain web data demonstrate the efficacy of our approach.
Who Deserves My Trust? Cue-Elicited Feedback Negativity Tracks Reputation Learning in Repeated Social Interactions

Trust and trustworthiness contribute to reciprocal behavior and social relationship development. To make better decisions, people need to evaluate others’ trustworthiness. They often assess this kind of reputation by learning through repeated social interactions. The present event-related potential (ERP) study explored the reputation learning process in a repeated trust game where subjects made multi-round decisions of investment to different partners. We found that subjects gradually learned to discriminate trustworthy partners from untrustworthy ones based on how often their partners reciprocated the investment, which was indicated by their own investment decisions. Besides, electrophysiological data showed that the faces of the untrustworthy partners induced larger feedback negativity (FN) amplitude than those of the trustworthy partners, but only in the late phase of the game. The ERP results corresponded with the behavioral pattern and revealed that the learned trustworthiness differentiation was coded by the cue-elicited FN component. Consistent with previous research, our findings suggest that the anterior cue-elicited FN reflects the reputation appraisal and tracks the reputation learning process in social interactions.
Character of the Lateral Displacement of Soft Soil Foundation under Embankment

In order to analyze the characteristic of lateral displacement of soft soil foundation under embankment, a typical embankment is studied systemically with nonlinear finite element method, and the location of maximal lateral displacement and its measuring method is also discussed. It is pointed that lateral displacement would be reduced possibly at consolidation stage with strong dry crust and thick soft soil layer, which happened synchronously with vertical settlement increased rapidly. This phenomena could not be measured conveniently with inclinometer pipe, for there are many shortcomings within this technique, although which has been used in engineering widely. It is also shown that the location of the maximal lateral displacement is changeable at different construction stages, which more likely lies in the vertical surface between the toe and the middle of slope of embankment. In order to get the maximal lateral displacement reasonably, it is suggested that the inclinometer pipes should be placed in that area of embankment.
Efficient and Truthful Bandwidth Allocation in Wireless Mesh Community Networks

Nowadays, the maintenance costs of wireless devices represent one of the main limitations to the deployment of wireless mesh networks (WMNs) as a means to provide Internet access in urban and rural areas. A promising solution to this issue is to let the WMN operator lease its available bandwidth to a subset of customers, forming a wireless mesh community network, in order to increase network coverage and the number of residential users it can serve. In this paper, we propose and analyze an innovative marketplace to allocate the available bandwidth of a WMN operator to those customers who are willing to pay the higher price for the requested bandwidth, which in turn can be subleased to other residential users. We formulate the allocation mechanism as a combinatorial truthful auction considering the key features of wireless multihop networks and further present a greedy algorithm that finds efficient and fair allocations even for large-scale, real scenarios while maintaining the truthfulness property. Numerical results show that the greedy algorithm represents an efficient, fair, and practical alternative to the combinatorial auction mechanism.
Ebola Response: Modeling the Risk of Heat Stress from Personal Protective Clothing

Introduction A significant number of healthcare workers have responded to aid in the relief and containment of the 2013 Ebola virus disease (EVD) outbreak in West Africa. Healthcare workers are required to wear personal protective clothing (PPC) to impede the transmission of the virus; however, the impermeable design and the hot humid environment lead to risk of heat stress. Objective Provide healthcare workers quantitative modeling and analysis to aid in the prevention of heat stress while wearing PPC in West Africa. Methods A sweating thermal manikin was used to measure the thermal (Rct) and evaporative resistance (Ret) of the five currently used levels of PPC for healthcare workers in the West Africa EVD response. Mathematical methods of predicting the rise in core body temperature (Tc) in response to clothing, activity, and environment was used to simulate different responses to PPC levels, individual body sizes, and two hot humid conditions: morning/evening (air temperature: 25°C, relative humidity: 40%, mean radiant temperature: 35°C, wind velocity: 1 m/s) and mid-day (30°C, 60%, 70°C, 1 m/s). Results Nearly still air (0.4 m/s) measures of Rct ranged from 0.18 to 0.26 m2 K/W and Ret ranged from 25.53 to 340.26 m2 Pa/W. Conclusion Biophysical assessments and modeling in this study provide quantitative guidance for prevention of heat stress of healthcare workers wearing PPC responding to the EVD outbreak in West Africa.
Predictive analytics on evolving data streams anticipating and adapting to changes in known and unknown contexts

Ever increasing volumes of sensor readings, transactional records, web data and event logs call for next generation of big data mining technology providing effective and efficient tools for making use of the streaming data. Predictive analytics on data streams is actively studied in research communities and used in the real-world applications that in turn put in the spotlight several important challenges to be addressed. In this talk I will focus on the challenges of dealing with evolving data streams. In dynamically changing and nonstationary environments, the data distribution can change over time. When such changes can be anticipated and modeled explicitly, we can design context-aware predictive models. When such changes in underlying data distribution over time are unexpected, we deal with the so-called problem of concept drift. I will highlight some of the recent developments in the proactive handling of concept drift and link them to research in context-aware predictive modeling. I will also share some of the insights we gained through the performed case studies in the domains of web analytics, stress analytics, and food sales analytics.