Miracle-dz/UniFAR-FTUs huggingface dataset:
Fetal Testosterone and Early Autism Spectrum Disorder Related Neurodevelopmental Outcomes

Fetal Testosterone and Early Autism Spectrum Disorder Related Neurodevelopmental Outcomes Bo Y. Park, MPH Craig J. Newschaffer, PhD Aims: Despite widely acknowledged sex bias in Autism Spectrum Disorders (ASD), the underlying mechanisms are largely unknown. The goal of this dissertation was to examine whether differences in prenatal testosterone levels are a possible mechanism underlying the observed ASD sex difference. This was accomplished through three specific aims. First, meconium was examined as a novel prenatal androgen matrix to compare androgen levels across alternate matrices obtained at the delivery time point. Second, the association between cord blood testosterone and ASD-related 12 month phenotype was estimated in a high ASD risk cohort of multiplex families. Last, we investigated the relationship between widely used antimicrobials product use with potential androgenic activity and early autistic phenotypes. Methods: Studies were based in the Early Autism Risk Longitudinal Investigation (EARLI) cohort, an enriched risk cohort following pregnant mothers who previously had a child with ASD diagnosis. Prenatal information on potential exposures, confounders, effect modifiers and two relevant biologic samples, cord blood and meconium, and early ASD-related behavioral phenotypes in the children born into the cohort were available for analysis. Results: Testosterone (T) sex difference was observed in both cord blood and meconium and there was weak correlation between cord blood and meconium androgens. Umbilical cord blood T had a weak positive association with ASD related phenotype at 12 months. We found that the association of prenatal testosterone and early ASD-related phenotype varied by the sex of older child with ASD (proband). 12 month autistic traits were unrelated to either prenatal or postpartum use of products that contain TCS or TCC. Conclusion: Meconium and cord blood were both good media to measure prenatal androgen levels may be capturing different prenatal exposure windows. The association of prenatal testosterone early ASD-related phenotype was substantially different by proband sex indicating that androgen mediated mechanisms might be more important in families with female ASD in the pedigree. We found no evidence of an association between exposure to TCS/TCC and early ASD-related phenotype.
Imprecise Probabilities in Quantum Mechanics

In his entry on “Quantum Logic and Probability Theory” in the Stanford Encyclopedia of Philosophy, Alexander Wilce (2012) writes that “it is uncontroversial (though remarkable) that the formal apparatus of quantum mechanics reduces neatly to a generalization of classical probability in which the role played by a Boolean algebra of events in the latter is taken over by the ‘quantum logic’ of projection operators on a Hilbert space. ” For a long time, Patrick Suppes has opposed this view (see, for example, the papers collected in Suppes and Zanotti 1996). Instead of changing the logic and moving from a Boolean algebra to a non-Boolean algebra, one can also ‘save the phenomena’ by weakening the axioms of probability theory and work instead with upper and lower probabilities. However, it is fair to say that despite Suppes’ efforts upper and lower probabilities are not particularly popular in physics as well as in the foundations of physics, at least so far. Instead, quantum logics is booming again, especially since quantum information and computation became hot topics. Interestingly, however, imprecise probabilities are becoming more and more popular in formal epistemology as recent work by authors such as James Joyce (2010) and Roger White (2010) demonstrates. In this essay I would like to give one more reason for the use of upper and lower probabilities in quantum mechanics and outline the research program that they inspire. The remainder of this essay is organized as follows. Sec. 2 introduces upper and lower probabilities. Sec. 3 turns to quantum mechanics and presents the CHSH inequality. We show that there is not always a joint probability distribution that reproduces observed quantum correlations. Sec. 4 argues that imprecise probabilities can be defined in these cases, and Sec. 5 concludes with a number of open questions.
Sub-100 nm organic light-emitting diodes patterned with room temperature imprint lithography

We demonstrate fabrication of structurally regular, nanoscale organic light-emitting diodes (OLEDs) using room temperature imprint lithography (RTIL). An insulating polymer layer spin-coated onto indium-tin oxide (ITO) glass is patterned by RTIL, followed by etching with an oxygen plasma to define the light-emitting area for the fabrication of OLEDs with 80 nm linewidth. The process of etching by oxygen plasma leads to an oxygen treatment of the exposed ITO surface and brings about the beneficial effects of the treatment. A regular periodic structure of the polymer that results from the patterning scatters the emitted light, resulting in a small shift in the electroluminescence spectrum and anisotropic far-field radiation intensity. The nanoscale patterning is found not to affect the luminance.
Object Reorientation with Finger Gaiting

Coordinated object manipulation is a fundamental problem in the study of multingered robotic hands. The conventional study has been focused on deriving control algorithms for nger joints to implement a speci ed object trajectory and recently more e ort has been put into the study of automatic object trajectory planning. This paper discusses how to plan large-scale object reorientation with ngers of limited workspace. The relevant theories of contact kinematics, nonholonomic motion planning, grasp stability and nger gaiting are incorporated to develop a general framework of object reorientation with rolling contacts and nger gaiting. Our approach is illustrated by an example of reorienting a sphere with three hemi-spherical ngertips. The simulation results are presented.
Improving Xtract for Chinese collocation extraction

We present a system which extracts word-based bigram and n-gram collocation information from a 60MB corpus and then locates bigram pairs using strength and spread as defined in the Xtract system. In order for Xtract to work effectively with Chinese, we have readjusted the parameters. To obtain a higher recall rate, we have modified the algorithm to identify collocations with low-frequency of occurrence, a method which works particularly well in the case of bigrams in which one word is high-frequency and the other low-frequency. In preliminary experiments, our system extracts bigram collocations with a precision of 61%, an 8% improvement over the direct use Smadja' Xtract on Chinese. Further, we have improved the recall rate by 4.5% while extracting multiword collocations with 92% precision.
Aspect-Oriented Software Development based Solution for Intervention Concerns Problems:Case Study

All existing methods for Developing Software Systems, most insist on a separate system to keep the components together till they have been had the least overlapping. But these methods in the management system those have some parts and are using use case, and involved in the other parts of the systems, are inefficient. With arriving the Aspect-Oriented Programming, programmers were able to Implement the overcome some of these requirements and Implement them in a separate unit, but there are still some of the analysis requirements and design, because of the wrong analysis and design they cannot be implemented as a measure. In this article we want to prominent the phase of analysis and design of this work using the Aspect-Oriented Software, in order to implement them in the Implementation phase as a cupon.
Implementing an educational platform of constructivist learning into elementary mathematics classrooms

In Mexico, the conventional teaching approach, when applied specifically to elementary school, seems to fall short of attaining the overall quality objective. The main consequence of this problem is when teachers are not sure that their students really understand the dynamic nature of concepts and mechanism since an early age, particularly in elementary school. This paper presents a pedagogical/technological platform, based on constructivism ideas, as a means of making the learning process in elementary school more efficient and interesting. The constructivist platform presented here uses graphical simulators developed for Web 2.0 as a support tool, creating a teaching and learning environment in which practical experiments can be undertaken as each topic is introduced and explained.
Hybrid Object Detection and Image Recovery Techniques

the change of time arise the need to work on image processing. This paper gives work on two aspects of image. One Recovery or reconstruction of image and at the other end it is for object detection.This paper investigates the possibility of reconstruction of images. This paper is concerned with a removing corruption of an image and remove problem in image. We propose a new algorithm for solving one of the image restorations and reconstruction algorithm. At another end we also concentrate on object detection. The principal component of image analysis technique is image matching. This principal component became of extreme importance in different area of applications such as in navigation, guidance, automatic surveillance, robot vision. Experiments on a set of image restoration and reconstruction along with object detection show that proposed algorithm performs well enough.
Some new results on the stability of Markovian stochastic network models

In this paper we provide some new insights on the stability of some Markovian stochastic network models. More precisely we show how a variation of a positive recurrence criterion for multidimensional Markov chains due to Rosberg (JAP, Vol. 17, No. 3, 1980) can be developed to generalize the necessary and sufficient conditions for stability for multiclass Markovian networks with class independent routing and any work conserving service discipline. We also discuss the stability of a coupled processor model of interest in wireless networks.
A solution of splittable large flow scheduling based on MCMF in software defined network

The Software Defined Network (SDN) is a new networking paradigm, which separates the control plane and data plane. In this paper, we study two efficient large flow scheduling problems using SDN. We firstly present problem definitions, then we propose two algorithms based on Minimize-Cost Maximize-Flow (MCMF) model. One is for static model and the other for dynamic model. We show how to determine the undetermined factors and then how to use those factors to design efficient algorithms. Simulation results demonstrates the effectiveness of our proposed algorithms.
Rendering techniquesfor multimodal data

Many different direct volume rendering methods have been developed to visualize 3D scalar fields on uniform rectilinear grids. However, little work has been done on rendering simultaneously various properties of the same 3D region measured with different registration devices or at different instants of time. The demand for this type of visualization is rapidly increasing in scientific applications such as medicine in which the visual integration of multiple modalities allows a better comprehension of the anatomy and a perception of its relationships with activity. This paper presents different strategies of Direct Multimodal Volume Rendering (DMVR). It is restricted to voxel models with a known 3D rigid alignment transformation. The paper evaluates at which steps of the rendering pipeline must the data fusion be realized in order to accomplish the desired visual integration and to provide fast re-renders when some fusion parameters are modified. In addition, it analyzes how existing monomodal visual-ization algorithms can be extended to multiple datasets and it compares their efficiency and their computational cost.
Spatial Data Mining : A Recent Survey and New Discussions

The main objective of the spatial data mining is to discover hidden complex knowledge from spatial and not spatial data despite of their huge amount and the complexity of spatial relationships computing. However, the spatial data mining methods are still an extension of those used in conventional data mining. Spatial data is a highly demanding field because huge amounts of spatial data have been collected in various applications, ranging from remote sensing, to geographical information systems (GIS), computer cartography, environmental assessment and planning, etc. The collected data far exceeded human's ability to analyze. Recent studies on data mining have extended the scope of data mining from relational and transactional databases to spatial databases. This paper summarizes recent works on spatial data mining, from spatial data generalization, to spatial data clustering, mining spatial association rules, etc. It shows that spatial data mining is a promising field, with fruitful research results and many challenging issues. The main aim of this paper shows the existing methods of clustering and association rules based on spatial data, i.e collected from large amount of spatial data bases.
Unsupervised and Lightly Supervised Part-of-Speech Tagging Using Recurrent Neural Networks

In this paper, we propose a novel approach to induce automatically a Part-Of-Speech (POS) tagger for resource-poor languages (languages that have no labeled training data). This approach is based on cross-language projection of linguistic annotations from parallel corpora without the use of word alignment information. Our approach does not assume any knowledge about foreign languages, making it applicable to a wide range of resource-poor languages. We use Recurrent Neural Networks (RNNs) as multilingual analysis tool. Our approach combined with a basic cross-lingual projection method (using word alignment information) achieves comparable results to the state-of-the-art. We also use our approach in a weakly supervised context, and it shows an excellent potential for very low-resource settings (less than 1k training utterances).
Question Classification using Multiple Kernel Learning and Semantic Information

Question Classification is an important stage in Question Answering, and it has been a hot topic in the field of Information Retrieval in recent years. In this paper we explore the role of semantic features and propose two separate tree kernel functions incorporating the semantic features into the Support Vector Machine model. Then Multiple Kernel Learning approach is proposed to combine the two kernels and gather their advantages together. Experimental results show that using the method proposed in this paper is very effective and the accuracy reaches 95.8% which significantly outperforms the state-of-the-art approaches.
Evaluation of electro conductive film and strain gage as displacement sensor for pneumatic artificial muscle

For safety contact between humans and machines, Soft actuators are very useful. This reason is that soft actuators have flexibility, light weight and safety. However, it is difficult to realize accuracy control. The aim of this research is to develop a pneumatic soft actuator that has a flexible displacement sensor. The soft actuator is a pneumatic artificial muscle that can generate contracting motion. It consists of a silicone rubber tube and PET plates. Additionally it has a displacement sensor on constructional material. In this research, we have verified two types of sensors, strain gages and conductive film sensors. The both sensors can detect the change of their electrical resistance when the PET plate in the actuator is deformed. Through the experiments we have compared with each sensor's feature.
Automated graph-based analysis and correction of cortical volume topology

The human cerebral cortex is topologically equivalent to a sheet and can be considered topologically spherical if it is closed at the brainstem. Low-level segmentation of magnetic resonance (MR) imagery typically produces cerebral volumes whose tessellations are not topologically spherical. The authors present a novel algorithm that analyzes and constrains the topology of a volumetric object. Graphs are formed that represent the connectivity of voxel segments in the foreground and background of the image. These graphs are analyzed and minimal corrections to the volume are made prior to tessellation. The authors apply the algorithm to a simple test object and to cerebral white matter masks generated by a low-level tissue identification sequence. The authors tessellate the resulting objects using the marching cubes algorithm and verify their topology by computing their Euler characteristics. A key benefit of the algorithm is that it localizes the change to a volume to the specific areas of its topological defects.
Detecting anomalous network hosts by means of PCA

This paper focuses on the identification of anomalous hosts within a computer network with the motivation to detect attacks and/or other unwanted and suspicious traffic. The proposed detection method does not use content of packets, which enables the method to be used on encrypted networks. Moreover, the method has very low computational complexity allowing fast detection and response important for limitation of potential damages. The proposed method uses entropies of IP addresses and ports to build two complementary models of host's traffic based on principal component analysis. These two models are coupled with two orthogonal anomaly definitions, which gives four different detectors. The methods are evaluated and compared to prior art on one week long capture of traffic on university network. The experiments reveals that no single detector can detect all types of anomalies, which is expected and stresses the importance of ensemble approach towards intrusion detection.
CTCP: Coded TCP using Multiple Paths

We introduce CTCP, a novel multi-path transport protocol using network coding. CTCP is designed to incorporate TCP's good features, such as congestion control and reliability, while improving on TCP's performance in lossy and/or dynamic networks. CTCP builds upon the ideas of TCP/NC introduced by Sundararajan et al. and uses network coding to provide robustness against losses. We introduce the use of multiple paths to provide robustness against mobility and network failures. We provide an implementation of CTCP (in userspace) to demonstrate its performance.
Notice of RetractionAn empirical study on the impact of listed tourism companies TMT demographic characteristics on institutional investors' stockholding

Based on data of listed Tourism enterprises' in China, the focus of this study is the impact TMT demographic characteristics on institutional investors' stockholding. Key findings are: (1) institutional investors were willing to hold listed tourism companies shares with lower TMT average age and higher average education level; (2) TMT average tenure and occupational background heterogeneity had a significant impact on IIS.
Videogame play and the effectiveness of virtual environments for training

The Sensory Environments Evaluation (SEE) project set out to examine the effects of emotional valence of a virtual training scenario on learning and memory. Emotional arousal is well-established as having enhancing effects on memory (McGaugh, 2000). A virtual scenario called DarkCon was created to resemble a night-time reconnaissance mission. Priming of subjects was the first experimental variable. Subjects were randomly assigned to receive their mission briefing in a serious style, suggesting a serious military mission, or in a lighter style, suggesting a fun roleplaying game. The influence of videogame experience was included in analysis of subjects’ recall of the environment and of their physiology. In the present study, 34 Army Rangers from Fort Benning, GA underwent the DarkCon mission. Significant effects of priming condition and videogame play were discovered in subjects’ recollection of the mission, and in their physiological reactions to highly exciting material. This paper is primarily concerned with the effects of videogame play frequency on subjects’ behavior, recall, and physiology. The effects of priming will be cursorily discussed here as they relate to videogame play habits, and explored in more detail on their own in future publications. Directions for future research into the effects of videogame play experience on training are discussed. The project described herein has been sponsored by the U.S. Army Research, Development, and Engineering Command (RDECOM). Statements and opinions expressed do not necessarily reflect the position or the policy of the U.S. Government; no official endorsement should be inferred.
Multicenter Study With a Direct Acoustic Cochlear Implant

Objective To confirm the clinical efficacy and safety of a direct acoustic cochlear implant. Study Design Prospective multicenter study. Setting The study was performed at 3 university hospitals in Europe (Germany, The Netherlands, and Switzerland). Patients Fifteen patients with severe-to-profound mixed hearing loss because of otosclerosis or previous failed stapes surgery. Intervention Implantation with a Codacs direct acoustic cochlear implant investigational device (ID) combined with a stapedotomy with a conventional stapes prosthesis Main Outcome Measures Preoperative and postoperative (3 months after activation of the investigational direct acoustic cochlear implant) audiometric evaluation measuring conventional pure tone and speech audiometry, tympanometry, aided thresholds in sound field and hearing difficulty by the Abbreviated Profile of Hearing Aid Benefit questionnaire. Results The preoperative and postoperative air and bone conduction thresholds did not change significantly by the implantation with the investigational Direct Acoustic Cochlear Implant. The mean sound field thresholds (0.25–8 kHz) improved significantly by 48 dB. The word recognition scores (WRS) at 50, 65, and 80 dB SPL improved significantly by 30.4%, 75%, and 78.2%, respectively, after implantation with the investigational direct acoustic cochlear implant compared with the preoperative unaided condition. The difficulty in hearing, measured by the Abbreviated Profile of Hearing Aid Benefit, decreased by 27% after implantation with the investigational direct acoustic cochlear implant. Conclusion Patients with moderate-to-severe mixed hearing loss because of otosclerosis can benefit substantially using the Codacs investigational device.
Design of low actuation voltage RF MEMS cantilever switch

This paper presents the design and RF characterization of micro electromechanical system (MEMS) switches realized on elevated coplanar waveguide for high-speed applications. The capacitive air gap between signal line and the cantilever is 1 um. The lowest actuation voltage obtained is 6 V. The insertion loss of switch and its associated transmission line is -0.31 dB (mainly contributed by the transmission line itself) and the isolation was around -21.67 dB at 40 GHz.