Miracle-dz/UniFAR-FTUs huggingface dataset:
Are Implicit and Explicit Motive Measures Statistically Independent? A Fair and Balanced Test Using the Picture Story Exercise and a Cue- and Response-Matched Questionnaire Measure

Previous studies that have examined the relationship between implicit and explicit motive measures have consistently found little variance overlap between both types of measures regardless of thematic content domain (i.e., power, achievement, affiliation). However, this independence may be artifactual because the primary means of measuring implicit motives—content-coding stories people write about picture cues—are incommensurable with the primary means of measuring explicit motives: having individuals fill out self-report scales. To provide a better test of the presumed independence between both types of measures, we measured implicit motives with a Picture Story Exercise (PSE; McClelland, Koestner, & Weinberger, 1989) and explicit motives with a cue- and response-matched questionnaire version of the PSE (PSE–Q) and a traditional measure of explicit motives, the Personality Research Form (PRF; Jackson, 1984) in 190 research participants. Correlations between the PSE and the PSE–Q were small and mostly nonsignificant, whereas the PSE–Q showed significant variance overlap with the PRF within and across thematic domains. We conclude that the independence postulate holds even when more commensurable measures of implicit and explicit motives are used.
Handling Communication Disruptions in Distributed Model Predictive Control

Abstract In this work, we deal with distributed model predictive control (DMPC) of nonlinear systems with communication disruptions between the distributed controllers. Specifically, we focus on the design of DMPC systems that take into account communication channel noise and data losses between the distributed controllers explicitly. In contrast to most of the existing DMPC methods which assume flawless communication, we employ a specific channel model to consider a number of realistic data transmission scenarios. In order to ensure the stability of the closed-loop system under communication disruptions, each model predictive controller utilizes a stability constraint which is based on a suitable Lyapunov-based controller. The theoretical results are demonstrated through a nonlinear chemical process example.
Markers of inflammation in periodontal diseases

Periodontitis is a disease of chronic, progressive course and multifactorial etiology. Traditional diagnosis of periodontal disease is based on clinical and radiological examinations. However, clinical experience has shown that such diagnosis is not always sufficient. Numerous studies have attempted to identify – in gingival crevicular fluid, gingival tissue, saliva, and peripheral blood – various substances of both bacterial origin and derived from host cells, which would be pre-clinical indicators of disease progression. A certain level of such markers, or a change in their level within periodontium would be closely correlated with the severity of the disease. In order to determine that a given enzyme or cytokine may be a marker of inflammation, its role in both physiology and pathology of periodontal tissues should be thoroughly understood and analyzed. Currently, interleukin-1 β, prostaglandin E 2, elastase and met alloproteinase 8 are considered the most significant immunological indicators. Extending the diagnos tic procedures and treatment monitoring by methods based on determination of the level of inflamma tory mediators in gingival crevicular fluid or in saliva may facilitate diagnosis, increase treatment effectiveness, and provide data on the pathomechanism of periodontal diseases.
Outline Motivation Dimensionality Reduction Experimental Setup Results Discussion References Dimensionality Reduction for Supervised Learning Based on Fradkin's and Madigan's Experiments with Random Projections for Machine Learning, Acm Sigkdd 2003

Outline Motivation Dimensionality reduction Experimental setup Results Discussion References Outline Motivation Supervised learning High dimensionality Dimensionality reduction Principal component analysis Random projections Experimental setup Algorithms and datasets Procedure Results Discussion Outline Motivation Dimensionality reduction Experimental setup Results Discussion References Motivation: supervised learning We obtain a set T of n examples of a relation {(x, y)}: T = { For (x, y), think of x ∈ R d as the input and y as the label (positive or negative). Call T the training set. We want to infer a classifier˜f such that˜f (x) correctly predicts the label of all x, not just those in T. Outline Motivation Dimensionality reduction Experimental setup Results Discussion References Example n = 200 and d = 2.
A Novel Hypoxia-Inducible Spliced Variant of Mitochondrial Death Gene Bnip3 Promotes Survival of Ventricular Myocytes

Rationale: Alternative splicing provides a versatile mechanism by which cells generate proteins with different or even antagonistic properties. Previously, we established hypoxia-inducible death factor Bnip3 as a critical component of the intrinsic death pathway. Objective: To investigate alternative splicing of Bnip3 pre-mRNA in postnatal ventricular myocytes during hypoxia. Methods and Results: We identify a novel previously unrecognized spliced variant of Bnip3 (Bnip3&Dgr;ex3) generated by alternative splicing of exon3 exclusively in cardiac myocytes subjected to hypoxia. Sequencing of Bnip3&Dgr;ex3 revealed a frame shift mutation that terminated transcription up-stream of exon5 and exon6 ablating translation of the BH3-like domain and critical carboxyl-terminal transmembrane domain crucial for mitochondrial localization and cell death. Notably, although the 26-kDa Bnip3 protein (Bnip3FL) encoded by full-length mRNA was localized to mitochondria and provoked cell death, the 8.2-kDa Bnip3&Dgr;ex3 protein encoded by the truncated spliced mRNA was defective for mitochondrial targeting but interacted with Bnip3FL resulting in less association of Bnip3FL with mitochondria and diminished apoptotic and necrotic cell death. Forced expression of Bnip3FL in cardiac myocytes or Bnip3−/− mouse embryonic fibroblasts triggered widespread cell death that was inhibited by coexpression of Bnip3&Dgr;ex3. Conversely, RNA interference targeted against sequences encompassing the unique exon2-exon4 junction of the Bnip3&Dgr;ex3 sensitized cardiac myocytes to mitochondrial perturbations and cell death induced by Bnip3FL. Conclusions: Given the otherwise lethal consequences of deregulated Bnip3FL expression in postmitotic cells, our findings reveal a novel intrinsic defense mechanism that opposes the mitochondrial defects and cell death of ventricular myocytes that is obligatorily linked and mutually dependent on alternative splicing of Bnip3FL during hypoxia or ischemic stress.
A study of induction motor current control using the complex number representation

A general representation of current controllers using complex number representation is given by means of a consistent block diagram representation of the controller/motor system. The complex number approach allows a consistent representation of control schemes, as is shown by a survey of common current control techniques. It allows insight into the strengths and weaknesses of different algorithms, for example compensation in rotating and stationary reference frames. <<ETX>>
Gene Expression Changes in GABAA Receptors and Cognition Following Chronic Ketamine Administration in Mice

Ketamine is a well-known anesthetic agent and a drug of abuse. Despite its widespread use and abuse, little is known about its long-term effects on the central nervous system. The present study was designed to evaluate the effect of long-term (1- and 3-month) ketamine administration on learning and memory and associated gene expression levels in the brain. The Morris water maze was used to assess spatial memory and gene expression changes were assayed using Affymetrix Genechips; a focus on the expression of GABAA receptors that mediate a tonic inhibition in the brain, was confirmed by quantitative real-time PCR and western blot. Compared with saline controls, there was a decline in learning and memory performance in the ketamine-treated mice. Genechip results showed that 110 genes were up-regulated and 136 genes were down-regulated. An ontology analysis revealed the most significant effects of ketamine were on GABAA receptors. In particular, there was a significant up-regulation of both mRNA and protein levels of the alpha 5 subunit (Gabra5) of the GABAA receptors in the prefrontal cortex. In conclusion, chronic exposure to ketamine impairs working memory in mice, which may be explained at least partly by up-regulation of Gabra5 subunits in the prefrontal cortex.
Regulated expression of cadherin‐11 in human epithelial cells: A role for cadherin‐11 in trophoblast‐endometrium interactions?

Cadherin‐11 is a novel member of the cadherin supergene family. Cadherin‐11 expression is localized to mesenchymal tissue and specific regions of the neural tube during mouse embryogenesis. Here we report that cadherin‐11 is spatiotemporally expressed in the epithelial cells of the human placenta. Cadherin‐11 mRNA levels were low in freshly isolated cytotrophoblast cells but increased as the cytotrophoblast cells aggregated and fused to form syncytiotrophoblast cells in vitro. The increase in cadherin‐11 mRNA levels was concomitant with a decrease in E‐cadherin expression. Cadherin‐11 was localized to the syncytial trophoblast and extravillous cytotrophoblasts, but not the villous cytotrophoblasts of the human placenta by immunohistochemistry. As both of the former cell types have intimate interactions with the endometrium, we examined cadherin‐11 expression in the human endometrium. Cadherin‐11 was detected in the glandular and surface epithelium of the endometrium at all stages of the menstrual cycle. However, cadherin‐11 was abundant only in the stroma in the late secretory stage of the menstrual cycle. The accumulation of cadherin‐11 in the stroma correlated with decidualization. Taken together, our observations demonstrate that cadherin‐11 is expressed in certain epithelial cell lineages and suggest the possibility that cadherin‐11 plays an important role in mediating trophoblast‐endometrium interactions. © 1996 Wiley‐Liss, Inc.
Person Re-identification Based on Human Body Parts Signature

In video surveillance, person re-identification consists in recognizing a person or determine whether a given person has already appeared over a large-scale network of cameras. In general, the human appearance obtained in one camera is usually different from the others obtained in other cameras, because of variations in view angle, illumination, body pose, background clutter and occlusion. To address this problem, we propose a person re-identification approach by using fusing multiple human body parts signature method. Firstly we detect human and human body parts. secondly we extract discriminatingly features on each of the parts. Finally, we map the person re-identification issue to a distance learning problem, which aims to find out the similarity between corresponding body parts. The experimental result on several public benchmark datasets (Prid2011,ViPER,ETHZ) shows that the proposed approach works well and leads to a high accuracy of person re-identification.
Fractals in the Neurosciences, Part II

It has been ascertained that the human brain is a complex system studied at multiple scales, from neurons and microcircuits to macronetworks. The brain is characterized by a hierarchical organization that gives rise to its highly topological and functional complexity. Over the last decades, fractal geometry has been shown as a universal tool for the analysis and quantification of the geometric complexity of natural objects, including the brain. The fractal dimension has been identified as a quantitative parameter for the evaluation of the roughness of neural structures, the estimation of time series, and the description of patterns, thus able to discriminate different states of the brain in its entire physiopathological spectrum. Fractal-based computational analyses have been applied to the neurosciences, particularly in the field of clinical neurosciences including neuroimaging and neuroradiology, neurology and neurosurgery, psychiatry and psychology, and neuro-oncology and neuropathology. After a review of the basic concepts of fractal analysis and its main applications to the basic neurosciences in part I of this series, here, we review the main applications of fractals to the clinical neurosciences for a holistic approach towards a fractal geometry model of the brain.
Neuron NeuroView Designing Tools for Assumption-Proof Brain Mapping

There is much excitement in neuroscience about the potential for tools that might enable scalable mapping of brain circuits at the anatomical, molecular, and activity levels. In parallel, new fundamental mechanisms of neural function -novel transmitters, new cell types and structures, unanticipated genetic and molecular signaling modalities -are being discovered all the time. This raises a question: how should we design brain mapping technologies so that they can scalably acquire knowledge about mechanisms we already know we want to understand, while taking in stride the novel mechanisms as they are uncovered, so that comprehensive and integrative pictures of brain function, in the end, emerge? Here we discuss the design principles governing mapping technologies so that they can meet these somewhat contrary goals – scalability and flexibility.
Reducing extra storage in searchable symmetric encryption scheme

In order to protect the data privacy, cloud users usually outsource the encrypted form of their data to the cloud servers, which brings a challenge when they want to search their encrypted data in cloud. Searchable encryption techniques solve this problem by allowing the cloud servers to search on the encrypted data without decrypting the ciphertext or the searching keywords. In this paper, we propose a construction which can dramatically reduce the size of extra storage in the searchable symmetric encryption schemes and still remain efficiency. And security analysis shows that our construction can achieve non-adaptive secure. Further investigation and experiments show that our construction is suitable for not only single keyword search but also more complex search including conjunctive search, disjunctive search and phrase search.
Adaptive Offset Correction for Intracortical Brain–Computer Interfaces

Intracortical brain-computer interfaces (iBCIs) decode intended movement from neural activity for the control of external devices such as a robotic arm. Standard approaches include a calibration phase to estimate decoding parameters. During iBCI operation, the statistical properties of the neural activity can depart from those observed during calibration, sometimes hindering a user's ability to control the iBCI. To address this problem, we adaptively correct the offset terms within a Kalman filter decoder via penalized maximum likelihood estimation. The approach can handle rapid shifts in neural signal behavior (on the order of seconds) and requires no knowledge of the intended movement. The algorithm, called multiple offset correction algorithm (MOCA), was tested using simulated neural activity and evaluated retrospectively using data collected from two people with tetraplegia operating an iBCI. In 19 clinical research test cases, where a nonadaptive Kalman filter yielded relatively high decoding errors, MOCA significantly reduced these errors (10.6 ±10.1%; p <; 0.05, pairwise t-test). MOCA did not significantly change the error in the remaining 23 cases where a nonadaptive Kalman filter already performed well. These results suggest that MOCA provides more robust decoding than the standard Kalman filter for iBCIs.
Mechanical Properties of Fine-Grained AA1050 after ECAP

The mechanical properties of fine-grained Aluminium AA1050 produced by ECAP at room temperature, have been investigated under various deformation modes. Because ECAP leads to an unstable microstructure, some samples were annealed at 300°C for 10 minutes in order to stabilise the microstructure. For mechanical testing, cylindrical samples were used in three types of monotonic deformation tests: axisymmetric compression, uniaxial tension and simple shear by torsion. The influence of the deformation mode on the yield locus and strain hardening behaviour has been studied and will be discussed for both hot rolled AA1050, ECAP samples without annealing and annealed ECAP samples. To achieve a better understanding of the strain hardening, some preliminary tests with a change in strain path were also performed. The results of tension tests followed by compression will be reported.
Sensory Data Processing Middlewares for Service Mobile Robot Applications

This research is a development of sensory information processing middlewares for a service mobile robot. In this paper the present author describe a development of obstacle detection and localization middlewares these abstract unified models from data of external sensors on a mobile robot. These supports different configuration of external sensors for a mobile robot. The unified model abstracted from external sensors can be used in any application softwares for a service mobile robot independent from the configuration of the sensors. In this paper, development of obstacle detection and localization middleware for service mobile robots, and application of several sensors to this middleware are described
Unicast UDP Usage Guidelines for Application Designers

The User Datagram Protocol (UDP) provides a minimal message-passing transport that has no inherent congestion control mechanisms. Because congestion control is critical to the stable operation of the Internet, applications and upper-layer protocols that choose to use UDP as an Internet transport must employ mechanisms to prevent congestion collapse and to establish some degree of fairness with concurrent traffic. This document provides guidelines on the use of UDP for the designers of unicast applications and upper-layer protocols. Congestion control guidelines are a primary focus, but the document also provides guidance on other topics, including message sizes, reliability, checksums, and middlebox traversal. This document specifies an Internet Best Current Practices for the Internet Community, and requests discussion and suggestions for improvements.
Trust Assessment Using Provenance in Service Oriented Applications

Workflow forms a key part of many existing Service Oriented applications, involving the integration of services that may be made available at distributed sites. It is possible to distinguish between an "abstract" workflow description outlining which services must be involved in a workflow execution and a "physical" workflow description outlining the particular instances of services that were used in a particular enactment. Provenance information provides a useful way to capture the physical workflow description automatically especially if this information is captured in a standard format. Subsequent analysis on this provenance information may be used to evaluate whether the abstract workflow description has been adhered to, and to enable a user executing a workflow-based application to establish "trust" in the outcome.
Simulation and Performance Analysis of Distributed Internet Systems Using TCPNs

This paper presents a Timed Coloured Petri Nets based programming tool that supports modeling and performance analysis of distributed World Wide Web environments. A distributed Internet system model, initially described in compliance with Queueing Theory (QT) rules, is mapped onto the Timed Coloured Petri Net (TCPN) structure by means of queueing system templates. Then, it is executed and analyzed. The proposed distributed Internet systems modeling and design methodology has been applied for evaluation of several system architectures under different external loads. Povzetek: Predstavljeno je orodje na osnovi Petri mreu za modeliranje spletnih okolij.
A high-speed demultiplexer based on a nonlinear optical loop mirror with a photonic crystal fiber

A 50-m-long photonic crystal fiber with zero-dispersion wavelength at 1552 nm is used as the nonlinear medium in a nonlinear optical loop-mirror-based demultiplexer. The successful demultiplexing of an 80-Gb/s optical time-division multiplexing signal transmitted through an 80-km span of standard single-mode fiber and the error-free demultiplexing from 160 Gb/s are achieved.
Improved confidence interval for average annual percent change in trend analysis

This paper considers an improved confidence interval for the average annual percent change in trend analysis, which is based on a weighted average of the regression slopes in the segmented line regression model with unknown change points. The performance of the improved confidence interval proposed by Muggeo is examined for various distribution settings, and two new methods are proposed for further improvement. The first method is practically equivalent to the one proposed by Muggeo, but its construction is simpler, and it is modified to use the t‐distribution instead of the standard normal distribution. The second method is based on the empirical distribution of the residuals and the resampling using a uniform random sample, and its satisfactory performance is indicated by a simulation study. Copyright © 2017 John Wiley & Sons, Ltd.
Approximate Volumetric System Models for MicroSPECT

A microSPECT system has been developed for the purpose of studying murine models of amyloidosis in vivo. The system is equipped with two detector heads, each consisting of a multi-anode photomultiplier tube coupled to a pixellated NaI(Tl) crystal array. Images are reconstructed using an OS-EM algorithm. In this paper, we describe the associated volumetric system models that we have developed in support of both pinhole and parallel hole collimation. These models, which are precomputed and stored to disk prior to reconstruction, are based on simple inner-product computations and a region-growing like search defined by the conic view that each detector pixel has of the image voxels. We provide illustrative experimental results based on phantom and mouse data
Adaptive Power Allocation and Splitting with Imperfect Channel Estimation in Energy Harvesting Based Self-Organizing Networks

As miniature-sized embedded computing platforms are ubiquitously deployed to our everyday environments, the issue of managing their power usage becomes important, especially when they are used in energy harvesting based self-organizing networks. One way to provide these devices with continuous power is to utilize RF-based energy transfer. Previous research in RF-based information and energy transfer builds up on the assumption that perfect channel estimation is easily achievable. However, as our preliminary experiments and many previous literature in wireless network systems show, making perfect estimations of the wireless channel is extremely challenging due to their quality fluctuations. To better reflect reality, in this work, we introduce an adaptive power allocation and splitting (APAS) scheme which takes imperfect channel estimations into consideration. Our evaluation results show that the proposed APAS scheme achieves near-optimal performances for transferring energy and data over a single RF transmission.