Miracle-dz/UniFAR-FTUs huggingface dataset:
Recursive Distributed Detection for Composite Hypothesis Testing: Nonlinear Observation Models in Additive Gaussian Noise

This paper studies recursive composite hypothesis testing in a network of sparsely connected agents. The network objective is to test a simple null hypothesis against a composite alternative concerning the state of the field, modeled as a vector of (continuous) unknown parameters determining the parametric family of probability measures induced on the agents’ observation spaces under the hypotheses. Specifically, under the alternative hypothesis, each agent sequentially observes an independent and identically distributed time-series consisting of a (nonlinear) function of the true but unknown parameter corrupted by Gaussian noise, whereas, under the null, they obtain noise only. Two distributed recursive generalized likelihood ratio test type algorithms of the <italic>consensus+innovations</italic> form are proposed, namely, <inline-formula> <tex-math notation="LaTeX">$\mathcal {CIGLRT-L}$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$\mathcal {CIGLRT-NL}$ </tex-math></inline-formula>, in which the agents estimate the underlying parameter and in parallel also update their test decision statistics by simultaneously processing the latest local sensed information and information obtained from neighboring agents. For <inline-formula> <tex-math notation="LaTeX">$\mathcal {CIGLRT-NL}$ </tex-math></inline-formula>, for a broad class of nonlinear observation models and under a global observability condition, algorithm parameters which ensure asymptotically decaying probabilities of errors (probability of miss and probability of false detection) are characterized. For <inline-formula> <tex-math notation="LaTeX">$\mathcal {CIGLRT-L}$ </tex-math></inline-formula>, a linear observation model is considered and upper bounds on large deviations decay exponent for the error probabilities are obtained.
Cortical actin recovery at the immunological synapse leads to termination of lytic granule secretion in cytotoxic T lymphocytes

Significance Cytotoxic T lymphocytes (CTLs) destroy virally infected and tumor cells through the directed secretion of specialized lysosomes called “lytic granules. ” Because a single CTL must direct its cytotoxic activities only against specific targets but can sequentially kill multiple cells, granule secretion must be tightly controlled. We demonstrate here that dynamic regulation of the cortical actin cytoskeleton is critical for both the initiation and termination of secretion. We further link actin dynamics with phosphatidylinositol 4,5-bisphosphate (PIP2) levels and provide evidence that lytic granule delivery initiates cortical actin recovery and the cessation of secretion. Our results suggest that actin both regulates and is regulated by secretion, providing a mechanism by which CTLs control their ability to kill targets serially during immune responses. CD8+ cytotoxic T lymphocytes (CTLs) eliminate virally infected cells through directed secretion of specialized lytic granules. Because a single CTL can kill multiple targets, degranulation must be tightly regulated. However, how CTLs regulate the termination of granule secretion remains unclear. Previous work demonstrated that centralized actin reduction at the immune synapse precedes degranulation. Using a combination of live confocal, total internal reflection fluorescence, and superresolution microscopy, we now show that, after granule fusion, actin recovers at the synapse and no further secretion is observed. Depolymerization of actin led to resumed granule secretion, suggesting that recovered actin acts as a barrier preventing sustained degranulation. Furthermore, RAB27a-deficient CTLs, which do not secrete cytotoxic granules, failed to recover actin at the synapse, suggesting that RAB27a-mediated granule secretion is required for actin recovery. Finally, we show that both actin clearance and recovery correlated with synaptic phosphatidylinositol 4,5-bisphosphate (PIP2) and that alterations in PIP2 at the immunological synapse regulate cortical actin in CTLs, providing a potential mechanism through which CTLs control cortical actin density. Our work provides insight into actin-related mechanisms regulating CTL secretion that may facilitate serial killing during immune responses.
Curvature compensated BiCMOS bandgap with 1 V supply voltage

In this paper we present a bandgap circuit capable of generating a reference voltage of 0.54 V. The circuit, implemented in a submicron BiCMOS technology, operates with a supply voltage of 1 V. In the bandgap circuit proposed we use a non-conventional operational amplifier which achieves virtually zero systematic offset, operating directly from the 1 V power supply. The bandgap architecture used allows a straightforward implementation of the curvature compensation method. The proposed circuit achieves 5 ppm / K of accuracy without requiring additional operational amplifiers or complex circuits.
How Accurate is inv(A)*b?

Several widely-used textbooks lead the reader to believe that solving a linear system of equations Ax = b by multiplying the vector b by a computed inverse inv(A) is inaccurate. Virtually all other textbooks on numerical analysis and numerical linear algebra advise against using computed inverses without stating whether this is accurate or not. In fact, under reasonable assumptions on how the inverse is computed, x = inv(A)*b is as accurate as the solution computed by the best backward-stable solvers. This fact is not new, but obviously obscure. We review the literature on the accuracy of this computation and present a self-contained numerical analysis of it.
Human activity recognition in ambient assisted living environments using a convex optimization problem

Human activity recognition (HAR) is of crucial importance in ambient assisted living (AAL) environments. In such environments, residents' data are collected via unobtrusive sensors to be further interpreted as human activities. Essential services are provided for the users according to the HAR results. In this paper, a novel scheme is represented for HAR, which is based on minimizing a convex objective function. For this purpose, given a sensor data stream, a belief vector (BV) is calculated for each sensor event. A BV is calculated by weighting the posterior probabilities of activities. It denotes the possibility of each activity, given a single sensor event. Then, the BVs are smoothed by minimizing a convex objective function. The objective function is formulated based on common assumptions in AAL environments. The final activity inference is based on the smoothed belief vectors. The proposed method is evaluated using a well-known and publicly available dataset. It is compared to three widely adopted HAR benchmarks, which are based on probabilistic learning graphical models. Simulations show that the proposed method outperforms the benchmarks, having an accuracy of 79.97% and an average F-measure of 78.2%.
Twelve-Month-Old Infants Generalize Novel Signed Labels, but Not Preferences Across Individuals

By the end of the 1st year, infants expect spoken labels to be extended across individuals and thus seem to understand words as shared conventional forms. However, it is unknown whether infants' willingness to extend labels across individuals is constrained to familiar forms, such as spoken words, or whether infants can identify a broader range of symbols as potential conventions. The present study tested whether 12-month-old infants will extend a novel sign label to a new person. Results indicate that 12-month-olds expect signed object–label relations to extend across agents but restrict object preferences to individuals. The results suggest that infants' expectations about conventional behaviors and linguistic forms are likely broad at 12 months. The implications of these findings for infants' early conceptions of conventional behaviors as well as our understanding of the initial state of the learner are considered.
Robust Nonparametric Confidence Intervals for Regression‐Discontinuity Designs

In the regression‐discontinuity (RD) design, units are assigned to treatment based on whether their value of an observed covariate exceeds a known cutoff. In this design, local polynomial estimators are now routinely employed to construct confidence intervals for treatment effects. The performance of these confidence intervals in applications, however, may be seriously hampered by their sensitivity to the specific bandwidth employed. Available bandwidth selectors typically yield a “large” bandwidth, leading to data‐driven confidence intervals that may be biased, with empirical coverage well below their nominal target. We propose new theory‐based, more robust confidence interval estimators for average treatment effects at the cutoff in sharp RD, sharp kink RD, fuzzy RD, and fuzzy kink RD designs. Our proposed confidence intervals are constructed using a bias‐corrected RD estimator together with a novel standard error estimator. For practical implementation, we discuss mean squared error optimal bandwidths, which are by construction not valid for conventional confidence intervals but are valid with our robust approach, and consistent standard error estimators based on our new variance formulas. In a special case of practical interest, our procedure amounts to running a quadratic instead of a linear local regression. More generally, our results give a formal justification to simple inference procedures based on increasing the order of the local polynomial estimator employed. We find in a simulation study that our confidence intervals exhibit close‐to‐correct empirical coverage and good empirical interval length on average, remarkably improving upon the alternatives available in the literature. All results are readily available in R and STATA using our companion software packages described in Calonico, Cattaneo, and Titiunik (2014d, 2014b).
Algorithmic Aspects of Property Testing in the Dense Graphs Model

In this paper we consider two basic questions regarding the query complexity of testing graph properties in the adjacency matrix model. The first question refers to the relation between adaptive and non-adaptive testers, whereas the second question refers to testability within complexity that is inversely proportional to the proximity parameter, denoted e. The study of these questions reveals the importance of algorithmic design in this model. The highlights of our study are: - A gap between the complexity of adaptive and non-adaptive testers. Specifically, there exists a natural graph property that can be tested using O(e-1) adaptive queries, but cannot be tested using o(e-3/2) non-adaptive queries. - In contrast, there exist natural graph properties that can be tested using O(e-1) non-adaptive queries, whereas ω(e-1) queries are required even in the adaptive case. We mention that the properties used in the foregoing conflicting results have a similar flavor, although they are of course different.
A novel semi-supervised Multi-Instance learning approach for scene recognition

We proposes a new image Multi-Instance (MI) bag generating method, which models an image with a Gaussian Mixed Model (GMM). The generated GMM is treated as an MI bag, of which the color and locally stable invariant components (SIFT) are the instances. Agglomerative Information Bottleneck clustering is employed to transform the MIL problem into single-instance learning problem so that single-instance classifiers can be used for classification. Finally, ensemble learning is involved to further enhance classifiers' generalization ability. Experimental results demonstrate that the performance of the proposed framework for image recognition is superior to some common MI algorithms on average in a 5-category scene recognition task.
An integrated ranking algorithm for efficient information computing in social networks

Social networks have ensured the expanding disproportion bet ween the face of WWW stored traditionally in search engine repositories and the actual ever changing face of Web . Exponential growth of web users and the ease with which they can upload contents on web highlights the need of content controls on material published on the web. As definition of search is changing, socially -enhanced interactive search methodologies are the need of the hour. Ranking is pivotal for efficient web search as the search performance mainly depends upon the ranking results.In this paper new integrated ranking model based on fused rank of web object based on popularity factor earned over only valid interlinks from multiple social forums is proposed. This model identifies relationships between web objects in separate social networks based on the object inheritance graph.Experimental study indicates the effectiveness of proposed Fusion based ranking algorithm in terms of better search results.
On the trade-off between mainlobe width and peak sidelobe level of mismatched pulse compression filters for linear chirp waveforms

In [1] the authors introduced a technique for generating mismatched pulse compression filters for linear frequency chirp signals. The technique minimizes the sum of the pulse compression sidelobes in an Lp -norm sense. It was shown that constant, extremely low sidelobe levels (better than 60 dB) can be achieved for minimal mismatch loss but with some broadening of the compression peak. This paper investigates the tradeoff between the sidelobe level and the mainlobe width for mismatched filters designed using Lp -norm techniques.
Guided interactive diagnostic systems

A guided interactive approach to computer-aided medical diagnosis is presented. This approach is based on dynamic taxonomies, a knowledge management model that allows the guided interactive exploration of complex information bases. The problem of the diagnosis of pathologies is recasted as a problem of exploring and thinning out candidate pathologies on the basis of symptoms and other observable features.
A Gene Expression Signature from Human Breast Cancer Cells with Acquired Hormone Independence Identifies MYC as a Mediator of Antiestrogen Resistance

Purpose: Although most patients with estrogen receptor α (ER)-positive breast cancer initially respond to endocrine therapy, many ultimately develop resistance to antiestrogens. However, mechanisms of antiestrogen resistance and biomarkers predictive of such resistance are underdeveloped. Experimental Design: We adapted four ER+ human breast cancer cell lines to grow in an estrogen-depleted medium. A gene signature of estrogen independence was developed by comparing expression profiles of long-term estrogen-deprived (LTED) cells to their parental counterparts. We evaluated the ability of the LTED signature to predict tumor response to neoadjuvant therapy with an aromatase inhibitor and disease outcome following adjuvant tamoxifen. We utilized Gene Set Analysis (GSA) of LTED cell gene expression profiles and a loss-of-function approach to identify pathways causally associated with resistance to endocrine therapy. Results: The LTED gene expression signature was predictive of high tumor cell proliferation following neoadjuvant therapy with anastrozole and letrozole, each in different patient cohorts. This signature was also predictive of poor recurrence-free survival in two studies of patients treated with adjuvant tamoxifen. Bioinformatic interrogation of expression profiles in LTED cells revealed a signature of MYC activation. The MYC activation signature and high MYC protein levels were both predictive of poor outcome following tamoxifen therapy. Finally, knockdown of MYC inhibited LTED cell growth. Conclusions: A gene expression signature derived from ER+ breast cancer cells with acquired hormone independence predicted tumor response to aromatase inhibitors and associated with clinical markers of resistance to tamoxifen. Activation of the MYC pathway was associated with this resistance. Clin Cancer Res; 17(7); 2024–34. ©2011 AACR.
Relationship of microbial communities and suppressiveness of Trichoderma fortified composts for pepper seedlings infected by Phytophthora nicotianae

The understanding of the dynamic of soil-borne diseases is related to the microbial composition of the rhizosphere which is the key to progress in the field of biological control. Trichoderma spp. is commonly used as a biological control agent. The use of next generation sequencing approaches and quantitative PCR are two successful approaches to assess the effect of using compost as substrate fortified with two Trichoderma strains (Trichoderma harzianum or Trichoderma asperellum) on bacterial and fungal communities in pepper rhizosphere infected with Phytophthora nicotianae. The results showed changes in the bacterial rhizosphere community not attributed to the Trichoderma strain, but to the pathogen infection, while, fungi were not affected by pathogen infection and depended on the type of substrate. The Trichoderma asperellum fortified compost was the most effective combination against the pathogen. This could indicate that the effect of fortified composts is greater than compost itself and the biocontrol effect should be attributed to the Trichoderma strains rather than the compost microbiota, although some microorganisms could help with the biocontrol effect.
The Methodological Influence of Peirce's Pragmatism on Knowledge Organization

Information and knowledge organization in Brazil has been historically influenced by theoretical linguistics. However, some aspects related to language theory and its interface with philosophy need to be further investigated, particularly the semiotic interpretation of information and knowledge organization processes. In order to advance a dialogue with the philosophy and semiotics of Charles Peirce (1839-1914), a theoretical and bibliographical study was carried out so as to understand and evaluate the contributions of the Peircean thought to information organization. It was found that several aspects of Peirce’s work, viewed as a whole and not just semiotic concepts, suggest fundamental points to explain issues in information and knowledge organization. Basing on the analysis of Thellefsen’s studies, this research presents some arguments aimed at reframing Peirce’s pragmatism, which should no longer be mistakenly considered as a doctrine of practical results, but as a useful methodological approach for professionals dealing with knowledge organization in the field of Information Science. Received 12 January 2012; Accepted 12 January 2012 Indeed, out of a contribute fallibilism, combined with a high faith in the reality of knowledge, and an intense desire to find things out, all my philosophy has always seemed to me to grow−Peirce 1998, xi, CP 1.14
Hope for Reading in America: Practically Everyone Reads.

NINETY-FOUR percent of the American public age 16 r older reads magazines, newspapers, adven ture books, historical novels, biogra phies or autobiographies e while in the living room, den, family room, bedroom or kitchen e after they have eaten dinner, in the evening, or just before going to bed. The remaining 6% reads nothing at all, in no particular place, at no time. These are but a few results of a consumer research study on reading and book purchasing conducted by Yankelovich, Skelly and White, Inc. for the Book Industry Study Group, a nonprofit, voluntary association whose membership represents diverse sections of the book publishing industry. Through telephone interviews con ducted during May and June of 1978, the research study team acquired consumer-based information con cerning book reading and purchasing in the United States. The survey included 1450 people from 165 U.S. cities, a nationally representative, randomly selected sample of house holds. The information from these households fills a 333-page volume available now for $1500. This paper back makes light bedtime reading, offering a wide range of such scintil lating statistics as: 73% of book readers who read fiction spent on the average $23 for books in six months; 41% of those who like to read prefer action/adventure novels; for 84% of book readers the topic or subject area of a book is the most important selection factor (we could have told them that! ); 31% of the book readers belong to Reader's Digest Book Club; the major reason 28% of nonreaders don't read is because they
Paperproof: a paper-digital proof-editing system

We present PaperProof, a paper-digital proof-editing application that allows users to edit digital documents by means of gesture-based mark-up of their printed versions. This enables users to switch seamlessly back and forth between paper and digital instances of a document throughout the document lifecycle, working with whichever medium is preferred for a given task. Importantly, by maintaining a logical mapping between the printed and digital instances, editing operations on paper can later be integrated into the digital document even if other users have edited the digital version in parallel. The system is based on Anoto digital pen and paper technology and is implemented using the iPaper framework for interactive paper.
Key capacity with limited one-way communication for product sources

We show that for product sources, rate splitting is optimal for secret key agreement using limited one-way communication at two terminals. This yields an alternative proof of the tensorization property of a strong data processing inequality originally studied by Erkip and Cover and amended recently by Anantharam et al. We derive a `water-filling' solution of the communication rate-key rate tradeoff for two arbitrarily correlated vector Gaussian sources, for the case with an eavesdropper, and for stationary Gaussian processes.
Evaluation and Numerical Simulations of GaN HEMTs Electrical Degradation

In this letter, the effects of dc stress on GaN high-electron-mobility transistors' performance are investigated by means of experimental measurements and numerical simulation. A degradation of both dynamic (pulsed I-V) and static characteristics (dc) has been observed on stressed devices, and it has been experimentally related to the formation of an electron trap in the AlGaN barrier layer. Numerical simulations carried out on the tested structure by introducing a trapping region at the gate edge of the device barrier confirm the experimentally observed device degradation. The worsening of the dynamic performance is induced by both an increase in trap concentration and/or depth of the trapping region while the degradation of the dc characteristics can be explained by an increase in the trapping-region depth.
Comparing Space Efficiency of Propositional Knowledge Representation Formalisms

We investigate the space efficiency of a Propositional Knowledge Representation (PKR) formalism. Informally, the space efficiency of a formalism F in representing a certain piece of knowledge α, is the size of the shortest formula of F that represents α. In this paper we assume that knowledge is either a set of propositional interpretations or a set of formulae (theorems). We provide a formal way of talking about the relative ability of PKR formalisms to compactly represent a set of models or a set of theorems. We introduce two new compactness measures, the corresponding classes, and show that the relative space efficiency of a PKR formalism in representing models/theorems is directly related to such classes. In particular, we consider formalisms for nonmonotonic reasoning, such as circumscription and default logic, as well as belief revision operators.