LLukas22/scidocs huggingface dataset:
SNARKs for C: Verifying Program Executions Succinctly and in Zero Knowledge

We present a proof system that allows efficient verification of NP statements, given proofs produced by an untrusted yet computationally-bounded prover. Our system is publicly verifiable: after a trusted third-party has generated a proving key and a verification key, anyone can use the proving key to generate non-interactive proofs for adaptively-chosen NP statements, and the proofs can be verified by anyone using the verification key. Moreover, our system is statistically zero-knowledge and the generated public parameters are reusable. The NP-complete language we choose is the correct execution of programs on TinyRAM, a minimalistic (nondeterministic) random-access machine that we design. Together with TinyRAM port of gcc compiler this achieves the first practical realization of a zero-knowledge Succinct Non-interactive ARgument of Knowledge (zk-SNARK) for program executions, in the preprocessing model. This cryptographic primitive is a powerful solution for delegating NP computations, and enjoys many features not achieved by primitives implemented in prior works, most importantly, succinct verification and support for arbitrary computations. Our approach builds on recent theoretical work in the area of outsourced verified computation. We present efficiency improvements and implementations of the two main ingredients: 1. A transformation that, given as input a C program, outputs a circuit whose satisfiability encodes the correct execution of the program. We leverage nondeterminism to make the generated circuit’s size merely quasilinear in the size of the computation; in particular, we efficiently handle arbitrary loops, control flow, and random-memory accesses. This is in contrast with existing “circuit compilers”, which produce circuits of quadratic size. 2. A transformation that, given as input a linear PCP for verifying satisfiability of circuits, outputs a corresponding SNARK. Furthermore, by building on recent work about quadratic span programs, using suitable choices of finite field and FFT algorithms, we give a very efficient implementation of a zero-knowledge linear PCP: linear-time query generation and quasilinear-time prover. Thesis Supervisor: Ronald L. Rivest Title: Andrew and Erna Viterbi Professor of Electrical Engineering and Computer Science Thesis Supervisor: Eli Ben-Sasson Title: Associate Professor of Computer Science, Technion – Israel Institute of Technology
Fingerprint ridge orientation estimation based on neural network

Ridge orientation is one of the fundamental features of a fingerprint image. Orientation estimation serves for feature extraction and matching and is the base of fingerprint recognition. Most existing orientation estimation methods are based on the characteristic of pixel intensity in a block. This paper uses neural network to learn the ridge orientation. The trained network has the property of responding to true ridge orientation with a large value and responding to the false ridge orientation with a small value. When estimating fingerprint ridge orientation, the responded values to each orientation at each image block are used to compute the fingerprint orientation field. The proposed method turns out more robust than the existing method. Key-Words: Fingerprint recognition, Ridge orientation, Neural network, Filtering, Orientation setection
Impact that a program to control severe asthma has on the use of Unified Health System resources in Brazil.

OBJECTIVE
To quantify the use of health care resources among patients enrolled in the Bahia State Asthma and Allergic Rhinitis Control Program.


METHODS
As of January of 2006, 1405 patients had enrolled in the program, which is carried out in four referral centers in the city of Salvador. These patients formed the basis of this retrospective/prospective, observational cohort study. The preliminary analysis involved 269 consecutive patients, all above the age of 12 and diagnosed with severe asthma. After being seen by pulmonologists, nurses, pharmacologists and psychologists, the patients received inhaled asthma medications. Based on patient interviews and charts, the year preceding enrollment in the program was compared with the first year enrolled in the program in terms of the following quantifiable parameters: hospital admissions; emergency room visits; courses of oral corticosteroids; and days of school/work missed due to asthma attacks.


RESULTS
In this sample of patients with severe asthma, enrollment in the program resulted in significant reductions in the number of emergency room visits and hospital admissions (of 85% and 90%, respectively). There were also reductions in the number of school/work days missed due to asthma attacks and in the number of courses of oral corticosteroids (of 86% and 67%, respectively).


CONCLUSION
A program designed to control severe asthma in referral outpatient clinics and including pharmacological services at no charge can lead to a pronounced reduction in the demand for Unified Health Care System resources.
Beyond Shovel-Shaped Incisors: Neandertal Dental Morphology in a Comparative Context

Most research on Neandertal teeth has focused on shovel shaped incisors and/or taurodont molars. In the past 15 years there has been a renewed interested in Neandertal dental morphology, especially with regard to how they compare to recent and fossil modern humans. However, no complete description of Neandertal dental morphology has been published since the mid-1950s. Many more Neandertals and other fossil hominins have been discovered since then and are available for a comparative study. This paper provides a description of Neandertal dental morphology and places that morphology in a comparative fossil hominin context. It differs from previous work by focusing on fossil hominin variation (as opposed to contemporary modern human variation) and provides a comparative baseline in which Neandertal dental morphology can be assessed. The four comparative samples include European and West Asian Neandertals, European non-Neandertal archaics, South African/West Asian early modern humans and European early modern humans (e.g., Upper Paleolithic). A mean measure of divergence analysis shows that Neandertals are significantly different from early modern human groups, being four times more divergent from Afro-Asian and European early modern human samples than the early modern human samples are from each other. Moreover, Neandertals are more divergent from early modern Europeans than they are from the early modern Afro-Asians. Contrary to the results of a previous study they are significantly divergent from non-Neandertal archaics. The implications for these results are discussed.
Fraud detection in communication networks using neural and probabilistic methods

Fraud detection refers to the attempt to detect illegitimate usage of a communications network. Three methods to detect fraud are presented. Firstly, a feed-forward neural network based on supervised learning is used to learn a discriminative function to classify subscribers using summary statistics. Secondly, Gaussian mixture model is used to model the probability density of subscribers’ past behavior so that the probability of current behavior can be calculated to detect any abnormalities from the past behavior. Lastly, Bayesian networks are used to describe the statistics of a particular user and the statistics of different fraud scenarios. The Bayesian networks can be used to infer the probability of fraud given the subscribers’ behavior. The data features are derived from toll tickets. The experiments show that the methods detect over 85 % of the fraudsters in our testing set without causing false alarms.
Some New Results on Post Correspondence Problem and Its Modifications

In this work we shall consider some new result on the famous word problem called the Post Correspondence Problem (PCP), initially defined by E. Post. Halava, Hirvensalo and de Wolf [4] proved that the PCP is decidable if we assume that the morphisms are marked. Moreover, Halava, Harju and Hirvensalo [2] proved that even the generalized PCP is decidable in the case of marked morphisms. As a corollary a new shorter proof was achieved for the PCP in the binary case. Here we shall consider the ideas behind these proofs. We also present a proof for the undecidability of the PCP in the case where the morphisms are permutations of each others.
Language-based querying of image collections on the basis of an extensible ontology

The design of a specialised query language for content based image retrieval (CBIR) provides a means of addressing many of the problems associated with commonly used query paradigms such as query-by-example and query-by-sketch. By basing such a language on an extensible ontology which encompasses both high-level and low-level image properties and relations, one can go a long way towards bridging the semantic gap between user models of saliency and relevance and those employed by a retrieval system. This paper discusses these issues and illustrates the design and use of an ontological retrieval language through the example of the OQUEL query language. The retrieval process takes place entirely within the ontological domain defined by the syntax and semantics of the user query. Since the system does not rely on the pre-annotation of images with sentences in the language, the format of text queries is highly flexible. The language is also extensible to allow for the definition of higher level terms such as “cars”, “people”, etc. on the basis of existing language constructs through the use of Bayesian inference networks. The matching process utilises automatically extracted image segmentation and classification information and can incorporate any other feature extraction mechanisms or contextual knowledge available at processing time to satisfy a given user request.
STDP-based spiking deep neural networks for object recognition

Previous studies have shown that spike-timingdependent plasticity (STDP) can be used in spiking neural networks (SNN) to extract visual features of low or intermediate complexity in an unsupervised manner. These studies, however, used relatively shallow architectures, and only one layer was trainable. Another line of research has demonstrated – using rate-based neural networks trained with back-propagation – that having many layers increases the recognition robustness, an approach known as deep learning. We thus designed a deep SNN, comprising several convolutional (trainable with STDP) and pooling layers. We used a temporal coding scheme where the most strongly activated neurons fire first, and less activated neurons fire later or not at all. The network was exposed to natural images. Thanks to STDP, neurons progressively learned features corresponding to prototypical patterns that were both salient and frequent. Only a few tens of examples per category were required and no label was needed. After learning, the complexity of the extracted features increased along the hierarchy, from edge detectors in the first ∗Corresponding author. Email addresses: kheradpisheh@ut.ac.ir (SRK), mgtabesh@ut.ac.ir (MG), simon.thorpe@cnrs.fr (ST) timothee.masquelier@cnrs.fr (TM). layer to object prototypes in the last layer. Coding was very sparse, with only a few thousands spikes per image, and in some cases the object category could be reasonably well inferred from the activity of a single higher-order neuron. More generally, the activity of a few hundreds of such neurons contained robust category information, as demonstrated using a classifier on Caltech 101, ETH-80, and MNIST databases. We think that the combination of STDP with latency coding is key to understanding the way that the primate visual system learns, its remarkable processing speed and its low energy consumption. These mechanisms are also interesting for artificial vision systems, particularly for hardware solutions.
A Bayesian framework for the analysis of microarray expression data: regularized t -test and statistical inferences of gene changes

MOTIVATION
DNA microarrays are now capable of providing genome-wide patterns of gene expression across many different conditions. The first level of analysis of these patterns requires determining whether observed differences in expression are significant or not. Current methods are unsatisfactory due to the lack of a systematic framework that can accommodate noise, variability, and low replication often typical of microarray data.


RESULTS
We develop a Bayesian probabilistic framework for microarray data analysis. At the simplest level, we model log-expression values by independent normal distributions, parameterized by corresponding means and variances with hierarchical prior distributions. We derive point estimates for both parameters and hyperparameters, and regularized expressions for the variance of each gene by combining the empirical variance with a local background variance associated with neighboring genes. An additional hyperparameter, inversely related to the number of empirical observations, determines the strength of the background variance. Simulations show that these point estimates, combined with a t -test, provide a systematic inference approach that compares favorably with simple t -test or fold methods, and partly compensate for the lack of replication.
Terrigenous sedimentation processes along the continental margin off NW Africa: Implications from grain-size analysis of seabed sediments

The terrigenous fraction of seabed sediments recovered along the north-west African continental margin illustrates spatial variability in grain size attributed to different transport mechanisms. Three subpopulations are determined from the grain-size analyses (n 1⁄4 78) of the carbonate-free silt fraction applying an end-member modelling algorithm (G. J. Weltje, 1997). The two coarsest endmembers are interpreted as representing aeolian dust, and the fine-grained end-member is related to fluvial supply. The end-member model thus allows aeolian fallout to be distinguished from fluvial-sourced mud in this area. The relative contributions of the end-members show distinct regional variations that can be related to different transport processes and pathways. Understanding present-day sediment dispersal and mixing is important for a better understanding of older sedimentary records and palaeoclimate reconstructions in the region.
Pre-crash system validation with PRESCAN and VEHIL

This paper presents the tools for design and validation of pre-crash systems: the software tool PRE-crash SCenario ANalyzer (PRESCAN) and the VEhicle-Hardware-In-the-Loop (VEHIL) facility. PRESCAN allows to investigate a pre-crash scenario in simulation. This scenario can then be compared with tests performed in the VEHIL facility for validation of the real sensor and controller of the pre-crash system. Using PRESCAN and VEHIL the development process and more specifically the validation of intelligent vehicles can be carried out safer, cheaper, and more reliable.
Minimum variance modulation filter for robust speech recognition

This paper describes a way of designing modulation filter by datadriven analysis which improves the performance of automatic speech recognition systems that operate in real environments. The filter for each nonlinear channel output is obtained by a constrained optimization process which jointly minimizes the environmental distortion as well as the distortion caused by the filter itself. Recognition accuracy is measured using the CMU SPHINX-III speech recognition system, and the DARPA Resource Management and Wall Street Journal speech corpus for training and testing. It is shown that feature extraction followed by modulation filtering provides better performance than traditional MFCC processing under different types of background noise and reverberation.
The relationship between schizotypal ideation and subjective cognition reflects more than just cognitive disorganisation: introducing the Brief Cognitive Schizotypy Index.

INTRODUCTION
Internet surveys of psychometric schizotypy can usefully explore the relationship between the schizophrenia spectrum and cognition, but significant participant drop-out can be a difficulty. We aimed to identify the aspects of schizotypal thinking associated with self-reported cognitive difficulties with a view to developing a brief index of schizotypy that is maximally sensitive to subjective cognitive complaints.


METHOD
Two online surveys were launched over two years. One explored schizotypal personality and subjective cognition. The other provided data for principal components analyses. The OLIFE was used in both surveys alongside other more specific measures of schizotypal features and a measure of affect.


RESULTS
Fifteen OLIFE cognitive disorganisation items, seven OLIFE unusual experiences items and three OLIFE introvertive anhedonia items were reliably associated with a range of self-reported cognitive difficulties as measured by the Cognitive Failures Questionnaire. The 25 items of the new Brief Cognitive Schizotypy Index (BCSI) loaded on three factors, labelled Unusual experiences, Affect and Cognition. The BCSI correlated strongly with a propensity to hallucinations scale, a persecutory ideation scale and two other measures of everyday cognition. These correlations survived correction for the role of prevailing negative affect.


CONCLUSIONS
Particular aspects of schizotypal ideation, reflecting the full range of such experiences, are related to reports of day-to-day cognitive difficulties. Future work should replicate these findings in a wider sample and explore relationships with objective cognitive measures.
Outcome of ultrasonographic imaging in infants with sacral dimple

Purpose
Sacral dimples are a common cutaneous anomaly in infants. Spine ultrasonography (USG) is an effective and safe screening tool for patients with a sacral dimple. The aim of this study was to determine the clinical manifestations in patients with an isolated sacral dimple and to review the management of spinal cord abnormalities identified with USG.


Methods
We reviewed clinical records and collected data on admissions for a sacral dimple from March 2014 through February 2017 that were evaluated with spine USG by a pediatric radiologist. During the same period, patients who were admitted for other complaints, but were found to have a sacral dimple were also included.


Results
This study included 230 infants under 6-months-old (130 males and 100 females; mean age 52.8±42.6 days). Thirty-one infants with a sacral dimple had an echogenic filum terminale, and 57 children had a filar cyst. Twenty-seven patients had a low-lying spinal cord, and only one patient was suspected of having a tethered cord. Follow-up spine USG was performed in 28 patients, which showed normalization or insignificant change.


Conclusion
In this study, all but one infant with a sacral dimple had benign imaging findings. USG can be recommended in infants with a sacral dimple for its convenience and safety.
Measuring Government's Contingent Positions in Japan's Flow of Funds Accounts: Implications for GFSM

1. Introduction This paper 1 discusses government contingent positions to be recorded in the framework of the System
Does child abuse cause crime ?

Does Child Abuse Cause Crime? Child maltreatment, which includes both child abuse and child neglect, is a major social problem. This paper focuses on measuring the effects of child maltreatment on crime using data from the National Longitudinal Study of Adolescent Health (Add Health). We focus on crime because it is one of the most socially costly potential outcomes of maltreatment, and because the proposed mechanisms linking maltreatment and crime are relatively well elucidated in the literature. Our work addresses many limitations of the existing literature on child maltreatment. First, we use a large national sample, and investigate different types of abuse in a similar framework. Second, we pay careful attention to identifying the causal impact of abuse, by using a variety of statistical methods that make differing assumptions. These methods include: Ordinary Least Squares (OLS), propensity score matching estimators, and twin fixed effects. Finally, we examine the extent to which the effects of maltreatment vary with socio-economic status (SES), gender, and the severity of the maltreatment. We find that maltreatment approximately doubles the probability of engaging in many types of crime. Low SES children are both more likely to be mistreated and suffer more damaging effects. Boys are at greater risk than girls, at least in terms of increased propensity to commit crime. Sexual abuse appears to have the largest negative effects, perhaps justifying the emphasis on this type of abuse in the literature. Finally, the probability of engaging in crime increases with the experience of multiple forms of maltreatment as well as the experience of Child Protective Services (CPS) investigation. JEL Classification: I1, K4
Mie resonance-mediated antireflection effects of Si nanocone arrays fabricated on 8-in. wafers using a nanoimprint technique

UNLABELLED
We fabricated 8-in. Si nanocone (NC) arrays using a nanoimprint technique and investigated their optical characteristics. The NC arrays exhibited remarkable antireflection effects; the optical reflectance was less than 10% in the visible wavelength range. The photoluminescence intensity of the NC arrays was an order of magnitude larger than that of a planar wafer. Optical simulations and analyses suggested that the Mie resonance reduced effective refractive index, and multiple scattering in the NCs enabled the drastic decrease in reflection.


PACS
88.40.H-; 88.40.jp; 81.07.Gf.
Efficacy of a culturally congruent HIV risk-reduction intervention for behaviorally bisexual black men: results of a randomized trial.

OBJECTIVES
Black men who have sex with men and women (MSMW) experience high HIV rates and may not respond to interventions targeting gay-identified men. We tested the efficacy of the Men of African American Legacy Empowering Self (MAALES), a multisession, small-group holistically framed intervention designed to build skills, address sociocultural issues, and reduce risk behaviors in black MSMW.


DESIGN
From 2007 to 2011, we enrolled 437 black MSMW into a parallel randomized controlled trial that compared MAALES to the control condition, a single, individualized HIV risk-reduction session.


METHODS
Participants completed surveys at baseline, 3 months, and 6 months postintervention. We used multiple regressions to compare risk behaviors at follow-up between the intervention and control groups while adjusting for baseline risk behaviors, time between assessments, other covariates, and clustering. We used inverse probability weighting (IPW) to adjust for loss-to-follow-up while carrying out these regressions with the 291 (76.4%) randomized participants who completed at least one follow-up.


RESULTS
Participants were largely low-income (55% reported monthly incomes <$1000); nearly half had previously tested HIV positive. At 6 months of follow-up, unadjusted within-group analyses demonstrated reduced risk behaviors for the MAALES but not the control group. Adjusted results indicated significant intervention-associated reductions in the numbers of total anal or vaginal sex acts [risk ratio = 0.61; 95% confidence interval (CI) 0.49–0.76], unprotected sex acts with women (risk ratio = 0.50; 95% CI 0.37–0.66), and female partners (risk ratio = 0.56; 95% CI 0.44–0.72). Near significant reductions were observed for number of male intercourse partners.


CONCLUSION
The MAALES intervention was efficacious at reducing HIV risk behaviors in black MSMW.