Miracle-dz/UniFAR-FTUs huggingface dataset:
DNA methylation in neonates born to women receiving psychiatric care

Prenatal exposure both to maternal psychiatric illness and psychiatric medication has been linked with adverse child outcomes that affect physiological, emotional and psychiatric development. Studies suggest that epigenetic mechanisms, such as DNA methylation, may facilitate these effects. In this report, we explore the association between maternal psychiatric illness and treatment during pregnancy and neonatal DNA methylation patterns in a prospectively-characterized clinical cohort of 201 dyads. Associations between the percent of umbilical cord blood DNA methylated at 27,578 CpG sites and maternal psychiatric diagnosis, symptoms and antidepressant use were evaluated by fitting a separate linear mixed effects model for each CpG site. There were no significant changes in neonatal DNA methylation attributable to maternal psychiatric diagnosis or depressive symptoms during pregnancy. Exposure to an antidepressant medication was associated with differential methylation of CpG sites in TNFRSF21 and CHRNA2 (false discovery rate < 0.05), but the average difference in methylation for both CpG sites was less than 3% between each group. The results were not specific to type of antidepressant or duration of the exposure. This study suggests that there are no large effects of maternal psychiatric illness, depressive symptoms or prenatal exposure to antidepressants on neonatal DNA methylation. Delineation of the influence of maternal psychiatric illness and pharmacological exposures on the developing fetuses has critical implications for clinical care during pregnancy.
3D Pose-by-Detection of Vehicles via Discriminatively Reduced Ensembles of Correlation Filters

Estimating the precise pose of a 3D model in an image is challenging; explicitly identifying correspondences is difficult, particularly at smaller scales and in the presence of occlusion. Exemplar classifiers have demonstrated the potential of detection-based approaches to problems where precision is required. In particular, correlation filters explicitly suppress classifier response caused by slight shifts in the bounding box. This property makes them ideal exemplar classifiers for viewpoint discrimination, as small translational shifts can often be confounded with small rotational shifts. However, exemplar based pose-by-detection is not scalable because, as the desired precision of viewpoint estimation increases, the number of exemplars needed increases as well. We present a training framework to reduce an ensemble of exemplar correlation filters for viewpoint estimation by directly optimizing a discriminative objective. We show that the discriminatively reduced ensemble outperforms the state-of-the-art on three publicly available datasets and we introduce a new dataset for continuous car pose estimation in street scene images.
Brain structural and functional correlates of resilience to Bipolar Disorder

Background: Resilient adaptation can be construed in different ways, but as used here it refers to adaptive brain responses associated with avoidance of psychopathology despite expressed genetic predisposition to Bipolar Disorder (BD). Although family history of BD is associated with elevated risk of affective morbidity a significant proportion of first-degree relatives remain free of psychopathology. Examination of brain structure and function in these individuals may inform on adaptive responses that pre-empt disease expression. Methods: Data presented here are derived from the Vulnerability to Bipolar Disorders Study (VIBES) which includes BD patients, asymptomatic relatives and controls. Participants underwent extensive investigations including brain structural (sMRI) and functional magnetic resonance imaging (fMRI). We present results from sMRI voxel-based-morphometry and from conventional and connectivity analyses of fMRI data obtained during the Stroop Colour Word Test (SCWT), a task of cognitive control during conflict resolution. All analyses were implemented using Statistical Parametric Mapping software version 5 (SPM5). Resilience in relatives was operationalized as the lifetime absence of clinical-range symptoms. Results: Resilient relatives of BD patients expressed structural, functional, and connectivity changes reflecting the effect of genetic risk on the brain. These included increased insular volume, decreased activation within the posterior and inferior parietal regions involved in selective attention during the SCWT, and reduced fronto-insular and fronto-cingulate connectivity. Resilience was associated with increased cerebellar vermal volume and enhanced functional coupling between the dorsal and the ventral prefrontal cortex during the SCWT. Conclusions: Our findings suggests the presence of biological mechanisms associated with resilient adaptation of brain networks and pave the way for the identification of outcome-specific trajectories given a bipolar genotype.
The theta/gamma discrete phase code occuring during the hippocampal phase precession may be a more general brain coding scheme

In the hippocampus, oscillations in the theta and gamma frequency range occur together and interact in several ways, indicating that they are part of a common functional system. It is argued that these oscillations form a coding scheme that is used in the hippocampus to organize the readout from long‐term memory of the discrete sequence of upcoming places, as cued by current position. This readout of place cells has been analyzed in several ways. First, plots of the theta phase of spikes vs. position on a track show a systematic progression of phase as rats run through a place field. This is termed the phase precession. Second, two cells with nearby place fields have a systematic difference in phase, as indicated by a cross‐correlation having a peak with a temporal offset that is a significant fraction of a theta cycle. Third, several different decoding algorithms demonstrate the information content of theta phase in predicting the animal's position. It appears that small phase differences corresponding to jitter within a gamma cycle do not carry information. This evidence, together with the finding that principle cells fire preferentially at a given gamma phase, supports the concept of theta/gamma coding: a given place is encoded by the spatial pattern of neurons that fire in a given gamma cycle (the exact timing within a gamma cycle being unimportant); sequential places are encoded in sequential gamma subcycles of the theta cycle (i.e., with different discrete theta phase). It appears that this general form of coding is not restricted to readout of information from long‐term memory in the hippocampus because similar patterns of theta/gamma oscillations have been observed in multiple brain regions, including regions involved in working memory and sensory integration. It is suggested that dual oscillations serve a general function: the encoding of multiple units of information (items) in a way that preserves their serial order. The relationship of such coding to that proposed by Singer and von der Malsburg is discussed; in their scheme, theta is not considered. It is argued that what theta provides is the absolute phase reference needed for encoding order. Theta/gamma coding therefore bears some relationship to the concept of “word” in digital computers, with word length corresponding to the number of gamma cycles within a theta cycle, and discrete phase corresponding to the ordered “place” within a word. © 2005 Wiley‐Liss, Inc.
Evaluation Of Release Consistent Software Distributed Shared Memory On Emerging Network Technology

We evaluate the effect of processor speed, network characteristics, and software overhead on the performance of release-consistent software distributed shared memory. We examine five different protocols for implementing release consistency: eager update, eager invalidate, lazy update, lazy invalidate, and a new protocol called lazy hybrid. This lazy hybrid protocol combines the benefits of both lazy update and lazy invalidate. Our simulations indicate that with the processors and networks that are becoming available, coarse-grained applications such as Jacobi and TSP perform well, more or less independent of the protocol used. Medium-grained applications, such as Water, can achieve good performance, but the choice of protocol is critical. For sixteen processors, the best protocol, lazy hybrid, performed more than three times better than the worst, the eager update. Fine-grained applications such as Cholesky achieve little speedup regardless of the protocol used because of the frequency of synchronization operations and the high latency involved. While the use of relaxed memory models, lazy implementations, and multiple-writer protocols has reduced the impact of false sharing, synchronization latency remains a serious problem for software distributed shared memory systems. These results suggest that the future work on software DSMs should concentrate on reducing the amount of synchronization or its effect.
LIVE TRACKING OF MUSICAL PERFORMANCES USING ON-LINE TIME WARPING

Dynamic time warping finds the optimal alignment of two time series, but it is not suitable for on-line applications because it requires complete knowledge of both series before the alignment can be computed. Further, the quadratic time and space requirements are limiting factors even for off-line systems. We present a novel on-line time warping algorithm which has linear time and space costs, and performs incremental alignment of two series as one is received in real time. This algorithm is applied to the alignment of audio signals in order to follow musical performances of arbitrary length. Each frame of audio is represented by a positive spectral difference vector, emphasising note onsets. The system was tested on various test sets, including recordings of 22 pianists playing music by Chopin, where the average alignment error was 59ms (median 20ms). We demonstrate one application of the system: the analysis and visualisation of musical expression in real time.
A genetic algorithm for spatiotemporal cluster detection and analysis

Although increased exploration of large-scale databases has provided the impetus for better detection and analysis of spatial clusters, there is slow progress in developing clustering algorithms for classifying space-time multidimensional attributes and spacetime-attribute interactions. The objective of this study is to enhance the genetic algorithm for detecting clusters in spatiotemporal or more complex hyperspace. Our motivation is guided by the idea of representing the gene structure using an elliptic cylinder allowing the detection and analysis of spatial clusters that have space-time components or spacetime-attribute dimensions. A more sophisticated gene representation through elliptic cylinders can model variable of spaces of two dimensions and greater. To assess the method, we employed a published real-world dataset with known spatiotemporal clusters of brain cancer incidence in New Mexico. Experimental results are compared with the results obtained from the very popular cluster detection method, Kulldorff’s space-time scan statistic. The results indicate that the proposed method provides a better representation of clusters in space-time and space-time-attribute interaction at faster and more computationally efficient runtime than Kulldorff’s method.
The design of a versatile, secure P2PSIP communications architecture for the public internet

Communications systems, encompassing VoIP, IM, and other personal media, present different challenges for P2P environments than other P2P applications. In particular, reliable communication implies that each resource (person) is unique and must be reliably located, without false negatives. Because of their prevalence in real deployments, the overlay must use endpoints behind NATs as peers and must be resilient against DoS attacks that attempt to disrupt the system's routing properties or DoS a particular person. We have designed and implemented a P2P communications system that addresses these issues, now deployed as both a commercial and academic project, which has resulted in a leading proposal for a P2PSIP standard in the IETF. We present the design tradeoffs necessary to meet the requirements of a reliable communications system and provide guidance on appropriate choices for designers of other similar systems in the future. In particular, the practical issues of non-transitive routing, NAT traversal required by our endpoints, and the prevention of DoS attacks have proven to be more critical than strict performance metrics in selecting DHT identifiers, topology, and routing algorithms. Where a central authority exists, certificates can be stored in the overlay and allow more efficient DHT algorithms to be used. We explain how security and routing schemes can help preserve the integrity, scalability, and performance of P2PSIP communication Systems.
F1: A Distributed SQL Database That Scales

F1 is a distributed relational database system built at Google to support the AdWords business. F1 is a hybrid database that combines high availability, the scalability of NoSQL systems like Bigtable, and the consistency and usability of traditional SQL databases. F1 is built on Spanner, which provides synchronous cross-datacenter replication and strong consistency. Synchronous replication implies higher commit latency, but we mitigate that latency by using a hierarchical schema model with structured data types and through smart application design. F1 also includes a fully functional distributed SQL query engine and automatic change tracking and publishing.
BRAIN COMPUTER INTERFACE BASED SMART LIVING ENVIRONMENTAL AUTO ADJUSTMENT CONTROL SYSTEM USING INTERNET OF THINGS ( IOT ) NETWORKING

An EEG based smart home environmental auto adjustment system is proposed on this paper. Nowada ys human life is really machine dependant ,so machines are important in human life. Many environmental control systems have been proposed in recent times but only few res arches have done on environmental control systems using hu man cognition state. Based on the advance of our techni que for BCI and the improvement of micro-electro-mechanical-sys tembased (MEMS-based) dry electrode sensors, we combin ed these techniques to demonstrate an auto-adjustable living environment control system, e.g., illumination of l ight and fan speed of air conditioner, depends on the physiologi cal change of the user, even for long-term physiological monit oring. The system consists of wireless physiological signal a cquisition module, an embedded signal processing module, a sim ple control protocol/power line communication environmental controller, and a host system. The proposed system h as been verified in a simulation way so as to control the i llumination of day and night lamps and fan speed can be controlled successfully based on the physiological state of t he user which indicates that it can be implemented in a successfu l way so that it can be used in other applications. Keywords—Brain computer interface BCI, Electro encephalo gram EEG, Micro-electro-mechanical-system (MEMS).
Women Bound to Be Active: A Pilot Study to Explore the Feasibility of an Intervention to Increase Physical Activity and Self-Worth in Women

ABSTRACT Increasing physical activity (PA) has become a national health objective due to its associated health benefits, but low participation rates. Therefore, the purpose of this study was to determine the feasibility of an 8-month (September 2006–April 2007) PA book club (Women Bound to Be Active-WBA) in increasing PA and self-worth (SW) among women. Fifty-six adult women participated in an 8-month intervention consisting of weekly meetings designed to improve PA knowledge, awareness, confidence, and SW. Results indicated a significant increase in PA and SW. The WBA program represents a creative theory-based approach to empowering women to be more active.
CONTOURLET -BASED FINGERPRINT ANTISPOOFING

We propose an image-based method using Contourlet transform [5] to detect liveness in fingerprint biometric systems. We observe that real and spoof fingerprint images exhibit different textural characteristics. Wavelet transform although widely used for liveness detection is not the ideal one. Wavelets are not very effective in representing images containing lines and contours [5]. Recent Contourlet transform allows representing contours in a more efficient way than the wavelets [5]. Fingerprint is made of only contours of ridges; hence Contourlet transform is more suitable for fingerprint processing than the wavelets. Therefore, we use Contourlet energy and co-occurrence signatures to capture textural intricacies of images. After downsizing features with Plus l – take away r method, we test them on various classifiers: logistic regression, support vector machine and AdTree using our databases consisting of 185 real, 90 Fun-Doh (Play-Doh) and 150 Gummy fingerprint images. We then select the best classifier and use at as a base classifier to form an ensemble classifier obtained by fusing a stack of “K” base classifiers using the “Majority Voting Rule” (i.e. bagging). Experimental results indicate that, the new liveness detection approach is very promising as it needs only one fingerprint and no extra hardware to detect vitality.
Identification of the Periplasmic Cobalamin-Binding Protein BtuF of Escherichia coli

ABSTRACT Cells of Escherichia coli take up vitamin B12 (cyano-cobalamin [CN-Cbl]) and iron chelates by use of sequential active transport processes. Transport of CN-Cbl across the outer membrane and its accumulation in the periplasm is mediated by the TonB-dependent transporter BtuB. Transport across the cytoplasmic membrane (CM) requires the BtuC and BtuD proteins, which are most related in sequence to the transmembrane and ATP-binding cassette proteins of periplasmic permeases for iron-siderophore transport. Unlike the genetic organization of most periplasmic permeases, a candidate gene for a periplasmic Cbl-binding protein is not linked to the btuCED operon. The open reading frame termed yadT in the E. coli genomic sequence is related in sequence to the periplasmic binding proteins for iron-siderophore complexes and was previously implicated in CN-Cbl uptake in Salmonella. The E. coli yadT product, renamed BtuF, is shown here to participate in CN-Cbl uptake. BtuF protein, expressed with a C-terminal His6 tag, was shown to be translocated to the periplasm concomitant with removal of a signal sequence. CN-Cbl-binding assays using radiolabeled substrate or isothermal titration calorimetry showed that purified BtuF binds CN-Cbl with a binding constant of around 15 nM. A null mutation in btuF, but not in the flanking genes pfs and yadS, strongly decreased CN-Cbl utilization and transport into the cytoplasm. The growth response to CN-Cbl of the btuF mutant was much stronger than the slight impairment previously described for btuC, btuD, or btuF mutants. Hence, null mutations in btuC and btuD were constructed and revealed that the btuC mutant had a strong impairment similar to that of the btuF mutant, whereas the btuD defect was less pronounced. All mutants with defective transport across the CM gave rise to frequent suppressor variants which were able to respond at lower levels of CN-Cbl but were still defective in transport across the CM. These results finally establish the identity of the periplasmic binding protein for Cbl uptake, which is one of few cases where the components of a periplasmic permease are genetically separated.
Investigation of an isolated PFC converter with bridgeless and single-stage

For traditional AC/DC power factor correction (PFC) converters, the diode bridge rectifier is needed in the front-end. While a large current flowing through the bridge, the conduction voltage drop of diodes can result in large power loss. Bridgeless converter can be adopted to improve efficiency and bipolar gain property makes the function of PFC realizable. In this paper, an isolated PFC converter with bridgeless and single-stage is investigated. The operation principle and steady state characteristics were comprehensively analyzed. Finally, experimental results are provided to verify the theoretical analyses.
Understanding Autism: Parents, Doctors, and the History of a Disorder

Acknowledgments ix Introduction: Love as an Analytic Tool 1 Part One Chapter 1: Research Programs, "Autistic Disturbances,"and Human Difference 29 Chapter 2: Love Is Not Enough: Bruno Bettelheim, Infantile Autism,and Psychoanalytic Childhoods 61 Chapter 3: Expert Amateurs: Raising and Treating Children with Autism 93 Interlude: Parents Speak: The Art of Love and the Ethics of Care 125 Part Two Chapter 4: Brains, Pedigrees, and Promises: Lessons from the Politics of Autism Genetics 141 Chapter 5: Desperate and Rational: Parents and Professionals in Autism Research 167 Chapter 6: Pandora's Box: Immunizations, Parental Obligations,and Toxic Facts 197 Conclusion: What the World Needs Now: Learning About and Acting on Autism Research 229 Notes 237 Bibliography 313 Index 329
Image denoising via sparse approximation using eigenvectors of graph Laplacian

In this paper, a sparse approximation algorithm using eigenvectors of the graph Laplacian is proposed for image denoising, in which the eigenvectors of the graph Laplacian of images are incorporated in the sparse model as basis functions. Here, an eigenvector-based sparse approximation problem is presented under a set of residual error constraints. The corresponding relaxed iterative solution is also provided to efficiently solve such problem in the framework of the double sparsity model. Experiments show that the proposed algorithm can achieve a better performance than some state-of-art denoising methods, especially measured with the SSIM index.
A novel pattern identification scheme using distributed video coding concepts

Pattern-based video coding focusing on moving region in a macroblock has already established its superiority over recent H.264 video coding standard at very low bit rate. Obviously, a large number of pattern templates approximate the moving regions better however, after a certain limit no coding gain is observed due to the increase number of pattern identification bits. Recently, distributed video coding schemes used syndrome coding to predict the original information in decoder using side information. In this paper a novel pattern identification scheme is proposed which predicts the pattern from the syndrome codes and side information in decoder so that actual pattern identification number is not needed in the bitstream. The experimental results confirm that this new scheme successfully improves the rate-distortion performance compared to the existing pattern-based video coding as well as H.264 standard. This new scheme will also open another window of syndrome coding application.
Coupled neural associative memories

We propose a novel architecture to design a neural associative memory that is capable of learning a large number of patterns and recalling them later in presence of noise. It is based on dividing the neurons into local clusters and parallel plains, an architecture that is similar to the visual cortex of macaque brain. The common features of our proposed model with those of spatially-coupled codes enable us to show that the performance of such networks in eliminating noise is drastically better than the previous approaches while maintaining the ability of learning an exponentially large number of patterns. Previous work either failed in providing good performance during the recall phase or in offering large pattern retrieval (storage) capacities. We also present computational experiments that lend additional support to the theoretical analysis.