Miracle-dz/UniFAR-FTUs huggingface dataset:
Life-Space Mobility in a Sample of Independent Living Residents within a Continuing Care Retirement Community with an Embedded Wellness Program

ABSTRACT Objective: This article examines life-space mobility within one year of relocation to a continuing care retirement community (CCRC) with an embedded wellness program. Methods: Ninety-six independent living (IL) residents self-repor`ted life-space mobility and physical, cognitive, and psychosocial variables. ` Results: Mean life-space mobility of the current sample was 56.65 (SD = 16.92), suggesting the majority of residents moved independently inside the community but rarely traveled beyond the CCRC campus. Residents who were largely limited to the CCRC showed lower cognitive ability, t(94) = −3.37, p = . 001, d = -. 69, functional ability, t(94) = −4.85, p < . 001, d = . 88, and functional mobility, t(94) = 5.22, p < . 001, d = 1.07, but did not report higher levels of depression, t(80) = 1.15, p = . 254, or loneliness, t(94) = . 63, p = . 532, compared to residents who travelled beyond the CCRC campus. Conclusions: Results suggest that the majority of IL residents limited mobility to the CCRC campus, without compromising psychological well-being. Overall, the current study gives insight into the relationship between IL residents and an enhanced socio-physical environment.
Low Loss Electro-Optic Polymer Based Fast Adaptive Phase Shifters Realized in Silicon Nitride and Oxynitride Waveguide Technology

We present a comprehensive study on how to design and fabricate low loss electro-optic phase shifters based on an electro-optic polymer and the silicon nitride and silicon oxynitride waveguide material systems. The loss mechanisms of phase shifters with an electro-optic (EO) polymer cladding are analyzed in detail and design solutions to achieve lowest losses are presented. In order to verify the low loss design a proof of concept prototype phase shifter was fabricated, which exhibits an attenuation of 0.8 dB/cm at 1550 nm and an electro-optic efficiency factor of 27%. Furthermore, the potential of this class of phase shifters is evaluated in numerical simulations, from which the optimal design parameters and achievable figures of merit were derived. The presented phase shifter design has its potential for application in fast adaptive multi stage devices for optical signal processing.
Distributed training of multiclass conic-segmentation support vector machines on communication constrained networks

We present a distributed algorithm for training multiclass conic-segmentation support vector machines (CS-SVMs) on communication-constrained networks. The proposed algorithm takes advantage of the sparsity of the CS-SVM to minimise the communication overhead between nodes during training to obtain classifiers at each node which closely approximate the optimal (centralised) classifier. The proposed algorithm is also suited for wireless sensor networks where inter-node communication is limited by power restrictions and bandwidth. We demonstrate our algorithm by applying it to two datasets, one simulated and one benchmark dataset, to show that the global decision functions found by the nodes closely approximate the optimal decision function found by a centralised algorithm possessing all training data in one batch.
Self-organization of Syllable Structure: a Coupled Oscillator Model

It has been generally claimed that every language has syllables with onsets (CV structure), while languages may or may not allow coda consonants (VC structure). While recent work on Arrernte (Breen & Pensalfini, 1999) has cast doubt on the absolute universality of onsets, it is clear that there is a significant cross-linguistic preference for CV structure (Clements & Key-ser, 1983; Clements, 1990). In addition, evidence from phonological development shows that CV structure is typically acquired before VC for CV structure in distribution and acquisition has been understood as due to universal grammar (UG: Chomsky, 1965) where CV is the unmarked core syllable structure. Yet, the UG hypothesis does not answer to the question " Why is CV the most unmarked structure? " This study aims to provide a rationale, grounded in dynamical systems theory, for why CV is favored across languages by simulating the self-organization of syllable structure in phonological development using a model in which syllable structures are defined by the coupling graph in a system of gestural planning oscillators that control patterns of intergestural relative timing. The simulation shows that, due to the hypothesized stronger coupling inherent in CV compared to graphs, CVs emerge earlier than VC graph. The model of syllable structure based on coupled planning oscillators (see section 2 below) has been developed to account for a variety of empirical observations about speech production (Nam & Saltzman, 2003; Goldstein et al., 2006; Nam et al, submitted a, b), independently of any consideration of acquisition facts. In addition to the explanatory weakness of the UG hypothesis, two additional empirical observations about phonological development are not easily accommodated by the UG hypothesis. One is that the delay in the emergence of coda consonants varies across languages as a function of the
LoopingRegulates Transcription through Gene Lymphoid Enhancer Binding Factor 1

Efﬁcient transcription depends upon efﬁcient physical and functional interactions between transcriptosome complexes and DNA. We have previously shown that IL-1 (cid:1) -induced lymphoid enhancer binding factor 1 (Lef1) regulates the transcription of its target genes COX2 and MMP13 in mouse chondrocytes by binding to the Lef1 binding sites located in the 3 (cid:1) region. In this study, we investigated how the 3 (cid:1) region-bound Lef1 regulates expression of target genes. IL-1 (cid:1) stimulation induced gene looping in COX2 and MMP13 genomic loci, which is mediated by the physical interaction of Lef1 with its binding partners, including (cid:1) -catenin, AP-1, and NF- (cid:2) B. As shown by chromosome conformation capture (3C) assay, the 5 (cid:1) and 3 (cid:1) genomic regions of these genes were juxtaposed in an IL-1 (cid:1) -stimulation dependent manner. Lef1 played a pivotal role in this gene looping; Lef1 knockdown decreased the incidence of gene looping, while Lef1 overexpression induced it. Physical interactions between the 3 (cid:1) region-bound Lef1 and promoter-bound transcription factors AP-1 or NF- (cid:2) B in COX2 and MMP13 , respectively, were increased upon stimulation, leading to synergistic up-regulation of gene expression. Knockdown of RelA or c-Jun decreased the formation of gene loop and down-regulated cyclooxygenase 2 (COX2) or matrix metalloproteinase 13 (MMP13) transcription levels. However, overexpression of RelA or c-Jun along with Lef1 increased the looping and their expression levels. Our results indicate a novel function of Lef1, as a mediator of gene looping between 5 (cid:1) and 3 (cid:1) regions. Gene looping may preparation Immunoprecipitation transfecting constitutively S37A HA-tagged c-Jun combination of chondrocytes Abs Lef1, RelA, phospho-c-Jun. A-Sepharose
Identifying Evaluative Sentences in Online Discussions

Much of opinion mining research focuses on product reviews because reviews are opinion-rich and contain little irrelevant information. However, this cannot be said about online discussions and comments. In such postings, the discussions can get highly emotional and heated with many emotional statements, and even personal attacks. As a result, many of the postings and sentences do not express positive or negative opinions about the topic being discussed. To find people’s opinions on a topic and its different aspects, which we call evaluative opinions, those irrelevant sentences should be removed. The goal of this research is thus to identify evaluative opinion sentences. A novel unsupervised approach is proposed to solve the problem, and our experimental results show that it performs well.
Guest Editor's Introduction Interconnection Networks for Parallel and Distributed Processing

With the rapid advances in technology, it is now feasible to build a system consisting of hundreds or thousands of processors. Processors in such a parallel/distributed system may spend a considerable amount of time just communicating among themselves unless an efficient interconnection network (IN) connects them. A complete interconnection such as crossbar may be cost prohibitive, but a shared-bus interconnection may be inefficient and unreliable. The authors need to design INs with both cost and performance between these two extremes. Parallel or distributed computers can generally be divided into two categories: multiprocessors and multicomputers. The main difference between the two lies in the level at which interactions between the processors occur.
Finite-Set Model-Based Predictive Control for Flying-Capacitor Converters: Cost Function Design and Efficient FPGA Implementation

Recently, there has been an increase in the use of finite-set model-based predictive control (FS-MBPC) for power-electronic converters. However, the computational burden for this control scheme is very high and often restrictive for a good implementation. This means that a suitable technology and design approach should be used. In this paper, the implementation of FS-MBPC for flying-capacitor converters in field-programmable gate arrays (FPGAs) is discussed. The control is fully implemented in programmable digital logic by using a high-level design tool. This allows us to obtain very good performances (both in control quality, speed, and hardware utilization) and have a flexible, modular control configuration. The good performance is obtained by exploiting the FPGA's strong points: parallelism and pipelining. Furthermore, an improved cost function for the voltage control of the flying capacitors is proposed in this paper. Typical cost functions result in tracking control for the flying-capacitor voltages, although this does not correspond with the desired system behavior. The improved cost function offers a capacitor voltage control that corresponds more closely with the desired behavior and adds a limitation on the capacitor voltage deviation. Furthermore, the selection of the weight factor in the cost function becomes less critical.
Clinical Performance and Skill Retention after Simulation‐based Education for Nephrology Fellows

We previously demonstrated that simulation‐based education (SBE) improved temporary hemodialysis catheter (THDC) insertion skills by nephrology fellows. SBE, featuring deliberate practice and rigorous achievement standards, was a powerful method to enhance THDC insertion skills in nephrology fellows. However, experts have called for further research to evaluate skill transfer from the simulated environment to actual clinical care and skill retention. This is a prospective observational cohort study of THDC insertion skills. Twelve nephrology fellows from three academic centers in Chicago were evaluated using a skills checklist from July 2008 to June 2009. Simulator‐trained fellows were tested after the SBE intervention and expected to meet or exceed a minimum passing score (MPS) set by an expert panel. To assess transfer of skill to clinical care, three simulator‐trained fellows were assessed at 6 months on actual patient THDC insertions using the checklist. To assess retention of skill, 11 of 12 simulator‐trained fellows were reassessed at 1 year using the checklist and central venous catheter simulator. Outcomes were determined by THDC insertion skill performance. Simulator‐trained fellows scored similarly during 6‐month THDC insertions on actual patients and immediate posttest (M = 86.2%, SD = 22.3% vs. M = 93.5%, SD = 5.3%, p = 0.32). However, 1 year after SBE, simulated THDC insertion scores were significantly lower than at immediate posttest (M = 73.4%, SD = 22.2% vs. M = 93.5%, SD = 5.3%, p = 0.01). Our results show that nephrology fellows who completed SBE displayed high levels of performance during THDC insertions on actual patients 6 months later. At 1 year, there was statistically significant skills decay. We recommend booster training at 6 months.
Analysis of the Transcriptional Regulation and Molecular Function of the Aryl Hydrocarbon Receptor Repressor in Human Cell Lines

The aryl hydrocarbon receptor repressor (AhRR) is a member of the aryl hydrocarbon receptor (AhR) signaling cascade, which mediates dioxin toxicity and is involved in regulation of cell growth and differentiation. The AhRR was described as a feedback modulator, which counteracts AhR-dependent gene expression. We investigated the molecular mechanisms of transcriptional regulation of the human AhRR by cloning its regulatory DNA region located in intron I of the AhRR. By means of reporter gene analyses and generation of deletion variants, we identified a functional, 3-methylcholanthrene-sensitive xenobiotic response element (XRE) site. Chromatin immunoprecipitation analyses revealed that the AhRR binds to this XRE, displaying an autoregulatory loop of AhRR expression. In addition we show that an adjacent GC-box is of functional relevance for AhRR transcription, since blocking of this GC-box resulted in a decrease of constitutive and inducible AhRR gene activity. The differences in constitutive AhRR mRNA level observed in HepG2, primary fibroblast, and HeLa cells are directly correlated with CYP1A1 inducibility. We show that the nonresponsiveness of high AhRR-expressing cells toward AhR-agonists is associated with a constitutive binding of the AhRR to XRE sites of CYP1A1. Treatment with the histone deacetylase inhibitor sodium butyrate restored the responsiveness of CYP1A1 in these cell lines, due to the dissociation of AhRR from the XREs. Furthermore, transient AhRR mRNA silencing in untreated HeLa cells was accompanied by an increase of basal CYP1A1 expression, pointing to a constitutive role of the AhRR in regulation of CYP1A1. The functional relevance of the AhRR in high AhRR-expressing primary fibroblasts is discussed.
An Effective CALL System for Strongly Accented Mandarin Speech

In this paper, we investigate some specific acoustic problems of the computer assisted language learning (CALL) system by modifying the acoustic model and feature under the speech recognition framework. At first, in order to alleviate the distortion of channel and speaker, speaker-dependent Cepstrum Mean Normalization (Speaker CMN) is adopted, by which the average correlation coefficient (ACC) between human and machine scores is improved from 78.00% to 84.14%. Then, Heteroscedastic Linear Discriminate Analysis (HLDA) is applied to enhance the discrimination ability of acoustic model, which successfully increases ACC from 84.14% to 84.62%. Additionally, HLDA can lessen the great human-machine scoring difference of speeches that have very good or too bad quality, and so leads to an increase of the correctly-rank rate from 85.59% to 90.99%. Finally, we use the technology of Maximum a Posteriori (MAP) to tune the acoustic model to match the strongly accented testing speech. As the result, ACC is improved from 84.62% to 86.57%.
Supervised Kernel Locally Principle Component Analysis for Face Recognition

In this paper, a novel algorithm for feature extraction, named supervised kernel locally principle component analysis (SKLPCA), is proposed. The SKLPCA is a non-linear and supervised subspace learning method, which maps the data into a potentially much higher dimension feature space by kernel trick and preserves the geometric structure of data according to prior class-label information. SKLPCA can discover the nonlinear structure of face images and enhance local within-class relations. Experimental results on ORL, Yale, CAS-PEAL and CMU PIE databases demonstrate that SKLPCA outperforms EigenFaces, LPCA and KPCA.
Characterization of Immunostimulatory CpG-Rich Sequences from Different Bifidobacterium Species

ABSTRACT The beneficial effects of Bifidobacterium are partly due to its immunostimulatory properties. These immunostimulatory properties may be linked to the presence of unmethylated CpG motifs specific to bacterial DNA, which may induce a TH1 response by activating Toll-like receptors (TLR). Using in silico analyses, PCR amplification, and dot blotting, we characterized the CpG content of various bifidobacterial strains and evaluated the immunostimulatory properties and genomic heterogeneity of these motifs in the genus. Our in silico study, based on entire genome sequences from five bifidobacterial strains, showed that Bifidobacterium genomes contain numerous CpG motifs, including 5′-purine-purine-CG-pyrimidine-pyrimidine-3′ and 5′-purine-TCG-pyrimidine-pyrimidine-3′ motifs, and biologically active sequences previously identified in lactic acid bacteria. We identified four CpG-rich sequences with Bifidobacterium longum NCC2705. Two sequences with a percent G+C of about 68% included 14 and 16 CpG motifs. Two sequences with a percent G+C of about 60% included 16 and 6 CpG motifs. These sequences induce the production of monocyte chemoattractant protein 1 (MCP-1) and tumor necrosis factor alpha (TNF-α) through a pattern of TLR9 stimulation on RAW 264.7 macrophages. No link could be established between their immunostimulatory properties, the number of CpG motifs, and percent G+C. We investigated inter- and intraspecies heterogeneity in 71 strains of various origins. These sequences were highly conserved in the genus. No link was found between the presence of the CpG-rich sequence and the origin of the strains (healthy, allergic, or preterm infants). The high frequency of CpG motifs in the DNA of Bifidobacterium may play an important role in the immunostimulatory properties of commensal or probiotic bifidobacterial strains.
Segmentation of Sloped Roofs from Airborne LiDAR Point Clouds Using Ridge-Based Hierarchical Decomposition

This paper presents a new approach for roof facet segmentation based on ridge detection and hierarchical decomposition along ridges. The proposed approach exploits the fact that every roof can be composed of a set of gabled roofs and single facets which are separated by the gabled roofs. In this work, firstly, building footprints stored in OpenStreetMap are used to extract 3D points on roofs. Then, roofs are segmented into roof facets. The algorithm starts with detecting roof ridges using RANSAC since they are parallel to the horizon and situated on the top of the roof. The roof ridges are utilized to indicate the location and direction of the gabled roof. Thus, points on the two roof facets along a roof ridge can be identified based on their connectivity and coplanarity. The results of the segmentation benefit the further process of roof reconstruction because many parameters, including the position, angle and size of the gabled roof can be calculated and used as priori knowledge for the model-driven approach, and topologies among the point segments are made known for the data-driven approach. The algorithm has been validated in the test sites of two towns next to Bavaria Forest national park. The experimental results show that building roofs can be segmented with both high correctness and completeness simultaneously.
Scratchpad memory optimizations for digital signal processing applications

Modern digital signal processors (DSPs) need to support a diverse array of applications ranging from digital filters to video decoding. Many of these applications have drastically different precision and on-chip memory requirements. Moreover, DSPs often employ aggressive dynamic voltage and frequency scaling (DVFS) techniques to minimize power consumption. However, at reduced voltages, process variations can significantly increase the failure rate of on-chip SRAMs designed with small transistors to achieve high integration density, resulting in low yields. Consequently, the size of transistors in SRAM cells and cell size needs to be increased to satisfy the target yield. However, this can result in high area overhead since on-chip memories consume a significant portion of the die area. In this paper, we present a scratchpad memory design that exploits the tradeoffs between SRAM cell sizes, their failure rates, the minimum operating voltage for target yield (Vddmin), and application characteristics to achieve an on-chip memory area reduction of up to 17%. Our approach reduces Vddmin, which allows dynamic and leakage power savings of 42% and 36% respectively with DVFS. Moreover, for error-tolerant DSP applications we allow voltage scaling below Vddmin to achieve further power savings while incurring lower mean error as compared to short word-length memory. Finally, for error-sensitive applications, we propose a reconfigurable memory organization that trades memory capacity for higher precision at a lower Vddmin.
AQP9 Expression in Glioblastoma Multiforme Tumors Is Limited to a Small Population of Astrocytic Cells and CD15+/CalB+ Leukocytes

Aquaporin-9 (AQP9) is a membrane protein channel that is permeable to a range of small solutes, including glycerol, urea and nucleobases. Expression of AQP9 in normal brain is limited, while widespread AQP9 expression has previously been reported in human glioblastoma. However, the specific cellular expression of AQP9 in glioblastoma remains unclear. In this study, we have examined microarrays to corroborate AQP9 mRNA expression in glioma. These analyses suggested that AQP9 mRNA expression in glioblastoma is primarily explained by tumor infiltration with AQP9 expressing leukocytes. Immunolabeling confirmed that within tumor regions, AQP9 was expressed in CD15+ and Calgranulin B+ leukocytes, but also in larger cells that morphologically resembled glioma cells. Specificity of immunoreagents was tested in recombinant cell lines, leukocyte preparations, and sections of normal human brain and liver tissue. Apparent AQP9+ glioma cells were frequently observed in proximity to blood vessels, where brain tumor stem cells have been observed previously. A fraction of these larger AQP9 expressing cells co-expressed the differentiated astrocyte marker GFAP. AQP9 expressing glioma cells were negative for the brain tumor stem cell marker CD15, but were observed in proximity to CD15+ glioma cells. AQP9 expression may therefore require signals of the perivascular tumor environment or alternatively it may be restricted to a population of glioma stem cell early progenitor cells.