Miracle-dz/UniFAR-FTUs huggingface dataset:
Downregulation of Spinal G Protein-Coupled Kinase 2 Abolished the Antiallodynic Effect of Electroacupuncture

Acupuncture or electroacupuncture (EA) has been demonstrated to have a powerful antihypernociceptive effect on inflammatory pain. The attenuation of G protein-coupled receptor kinase 2 (GRK2) in spinal cord and peripheral nociceptor has been widely acknowledged to promote the transition from acute to chronic pain and to facilitate the nociceptive progress. This study was designed to investigate the possible role of spinal GRK2 in EA antiallodynic in a rat model with complete Freund's adjuvant (CFA) induced inflammatory pain. EA was applied to ST36 (“Zusanli”) and BL60 (“Kunlun”) one day after CFA injection. Single EA treatment at day 1 after CFA injection remarkably alleviated CFA induced mechanical allodynia two hours after EA. Repeated EA displayed significant antiallodynic effect from 2nd EA treatment and a persistent effect was observed during the rest of treatments. However, downregulation of spinal GRK2 by intrathecal exposure of GRK2 antisense 30 mins after EA treatment completely eliminated both the transient and persistent antiallodynic effect by EA treatment. These pieces of data demonstrated that the spinal GRK2 played an important role in EA antiallodynia on inflammatory pain.
Surface wave tomography from microseisms in Southern California

Since it has already been demonstrated that point‐to‐point seismic propagation Green Functions can be extracted from seismic noise, it should be possible to image Earth structure using the ambient noise field. Seismic noise data from 148 broadband seismic stations in Southern California were used to extract the surface wave arrival‐times between all station pairs in the network. The seismic data were then used in a simple, but densely sampled tomographic procedure to estimate the surface wave velocity structure within the frequency range of 0.1–0.2 Hz for a region in Southern California. The result compares favorably with previous estimates obtained using more conventional and elaborate inversion procedures. This demonstrates that coherent noise field between station pairs can be used for seismic imaging purposes.
Differential Membrane Localization and Intermolecular Associations of α-Dystrobrevin Isoforms in Skeletal Muscle

α-Dystrobrevin is both a dystrophin homologue and a component of the dystrophin protein complex. Alternative splicing yields five forms, of which two predominate in skeletal muscle: full-length α-dystrobrevin-1 (84 kD), and COOH-terminal truncated α-dystrobrevin-2 (65 kD). Using isoform-specific antibodies, we find that α-dystrobrevin-2 is localized on the sarcolemma and at the neuromuscular synapse, where, like dystrophin, it is most concentrated in the depths of the postjunctional folds. α-Dystrobrevin-2 preferentially copurifies with dystrophin from muscle extracts. In contrast, α-dystrobrevin-1 is more highly restricted to the synapse, like the dystrophin homologue utrophin, and preferentially copurifies with utrophin. In yeast two-hybrid experiments and coimmunoprecipitation of in vitro–translated proteins, α-dystrobrevin-2 binds dystrophin, whereas α-dystrobrevin-1 binds both dystrophin and utrophin. α-Dystrobrevin-2 was lost from the nonsynaptic sarcolemma of dystrophin-deficient mdx mice, but was retained on the perisynaptic sarcolemma even in mice lacking both utrophin and dystrophin. In contrast, α-dystrobrevin-1 remained synaptically localized in mdx and utrophin-negative muscle, but was absent in double mutants. Thus, the distinct distributions of α-dystrobrevin-1 and -2 can be partly explained by specific associations with utrophin and dystrophin, but other factors are also involved. These results show that alternative splicing confers distinct properties of association on the α-dystrobrevins.
LIDA: A Systems-level Architecture for Cognition, Emotion, and Learning

We describe a cognitive architecture learning intelligent distribution agent (LIDA) that affords attention, action selection and human-like learning intended for use in controlling cognitive agents that replicate human experiments as well as performing real-world tasks. LIDA combines sophisticated action selection, motivation via emotions, a centrally important attention mechanism, and multimodal instructionalist and selectionist learning. Empirically grounded in cognitive science and cognitive neuroscience, the LIDA architecture employs a variety of modules and processes, each with its own effective representations and algorithms. LIDA has much to say about motivation, emotion, attention, and autonomous learning in cognitive agents. In this paper, we summarize the LIDA model together with its resulting agent architecture, describe its computational implementation, and discuss results of simulations that replicate known experimental data. We also discuss some of LIDA's conceptual modules, propose nonlinear dynamics as a bridge between LIDA's modules and processes and the underlying neuroscience, and point out some of the differences between LIDA and other cognitive architectures. Finally, we discuss how LIDA addresses some of the open issues in cognitive architecture research.
Maternal Anthropometrics in Pregnancy Are Associated with Left Ventricular Mass in Infancy. The Generation R Study

Pregnancy and early life factors may permanently affect left ventricular growth and development in the offspring. The aim of this study was to examine the associations of maternal anthropometrics during pregnancy with left ventricular mass (LVM) in infancy. This study was embedded in the Generation R Study, a population-based prospective cohort study from fetal life onwards. Maternal anthropometrics were obtained in early (gestational age <18 wk), mid- (gestational age 18–25 wk), and late (gestational age >25 wk) pregnancy. Echocardiographic follow-up measurements were performed in 791 infants aged 6 wk and 6 mo. We found no associations of maternal height, weight, or body mass index (BMI) measured in early, mid-, and late pregnancy with longitudinally measured left ventricular mass (LVM) from 6 wk to 6 mo. Maternal weight gain until late pregnancy was associated with an increased growth of LVM from 6 wk to 6 mo [difference 0.46 g per week for the highest tertile of weight gain compared with the lowest tertile (p value <0.05)]. We concluded that maternal weight gain until late pregnancy is associated with larger LVM at the age of 6 mo, suggesting that maternal health status during pregnancy may have permanent consequences for LVM in their children. Further studies are needed to identify the underlying causal mechanisms and the long-term consequences.
Non‐random abnormalities of chromosomes 3, 6, and 8 associated with posterior uveal melanoma

We present ten cases of posterior uveal melanoma which were karyotyped after short‐term culture. One tumour had a normal chromosome complement. The remaining nine tumours were cytogenetically abnormal, with chromosomes 3, 6, 8, 11, and 13 most frequently involved. Abnormalities of chromosome 13 were seen in two cases, chromosome 11 in three cases, and chromosomes 3, 6, and 8 in five cases. Four tumours, all derived from the ciliary body, demonstrated monosomy 3 and i(8q), confirming the involvement of these aberrations with a subgroup of uveal melanomas arising from the ciliary body.
Genetic mouse models for behavioral analysis through transgenic RNAi technology

Pharmacological inhibitors and knockout mice have developed into routine tools to analyze the role of specific genes in behavior. Both strategies have limitations like the availability of inhibitors for only a subset of proteins and the large efforts required to construct specific mouse mutants. The recent emergence of RNA interference (RNAi)‐mediated gene silencing provides a fast alternative that can be applied to any coding gene. We established an approach for the efficient generation of transgenic knockdown mice by targeted insertion of short hairpin (sh) RNA vectors into a defined genomic locus and studied the efficiency of gene silencing in the adult brain and the utility of such mice for behavioral analysis. We generated shRNA knockdown mice for the corticotropin‐releasing hormone receptor type 1 (Crhr1), the leucine‐rich repeat kinase 2 (Lrkk2) and the purinergic receptor P2X ligand‐gated ion channel 7 (P2rx7) genes and show the ubiquitous expression of shRNA and efficient suppression of the target mRNA and protein in the brain of young and 11‐month‐old knockdown mice. Knockdown mice for the Crhr1 gene exhibited decreased anxiety‐related behavior, an impaired stress response, and thereby recapitulate the phenotype of CRHR1 knockout mice. Our results show the feasibility of gene silencing in the adult brain and validate knockdown mice as new genetic models suitable for behavioral analysis.
Fourier Active Appearance Models

Gaining invariance to camera and illumination variations has been a well investigated topic in Active Appearance Model (AAM) fitting literature. The major problem lies in the inability of the appearance parameters of the AAM to generalize to unseen conditions. An attractive approach for gaining invariance is to fit an AAM to a multiple filter response (e.g. Gabor) representation of the input image. Naively applying this concept with a traditional AAM is computationally prohibitive, especially as the number of filter responses increase. In this paper, we present a computationally efficient AAM fitting algorithm based on the Lucas-Kanade (LK) algorithm posed in the Fourier domain that affords invariance to both expression and illumination. We refer to this as a Fourier AAM (FAAM), and show that this method gives substantial improvement in person specific AAM fitting performance over traditional AAM fitting methods.
Ion-ripple laser.

We present a new scheme, the ion-ripple laser, for generating tunable coherent radiation ranging from microwaves to the ultraviolet. A relativistic electron beam obliquely propagating through an ion ripple excites electromagnetic radiation which is coupled to a negative-energy electrostatic wave via backward Raman scattering. The radiation peaks at a resonance frequency of {omega}{similar to}2{gamma}{sup 2}{kappa}{sub {ital i}{ital r}c} cos{theta}. We derive the fluid theory dispersion relation for wave coupling and estimate the nonlinear saturation level. A 1 2/2 D PIC simulation code is used to verify the theory and scaling laws.
A Nonparametric Bayesian Model for Multiple Clustering with Overlapping Feature Views

Most clustering algorithms produce a single clustering solution. This is inadequate for many data sets that are multi-faceted and can be grouped and interpreted in many different ways. Moreover, for high-dimensional data, dierent features may be relevant or irrelevant to each clustering solution, suggesting the need for feature selection in clustering. Features relevant to one clustering interpretation may be dierent from the ones relevant for an alternative interpretation or view of the data. In this paper, we introduce a probabilistic nonparametric Bayesian model that can discover multiple clustering solutions from data and the feature subsets that are relevant for the clusters in each view. In our model, the features in dierent views may be shared and therefore the sets of relevant features are allowed to overlap. We model feature relevance to each view using an Indian Buet Process and the cluster membership in each view using a Chinese Restaurant Process. We provide an inference approach to learn the latent parameters corresponding to this multiple partitioning problem. Our model not only learns the features and clusters in each view but also automatically learns the number of clusters, number of views and number of features in each view.
An Economic Model of the Consumers' Online Shopping Utility and Factors Affecting on Online Shopping

This paper integrates extant literature on retailing and consumer choice to develop an economic model of consumer choice in which a consumer self-selects on-line shopping. Three important factors impacting consumer choice of on-line shopping: (1) the online shopping utility (2) the consumers’ perceived product and service risks (Perceived Privacy Protection, Perceived Security Protection etc.) and (3) consumer and e-vendors qualities (Consumer Disposition to trust, E-vendors’ Positive Reputation etc.) . Our model postulates that consumers derive utility from the online shopping experience and are affected by different factors (familiarity, disposition to trust, e-vendors’ positive reputation, perceived privacy protection and perceived security protection). Consumers are also more likely to shop on-line from familiar websites and evendors than lesser known ones. However, they are less likely to shop on-line from e-vendors or website that does not have explicit privacy and security measures. Empirical verification of the model is carried out using a survey method approach and the results gave support to the postulations based on our theoretical model. Limitations and directions for future research are also discussed.
Holistic run-time parallelism management for time and energy efficiency

The ubiquity of parallel machines will necessitate time- and energy-efficient parallel execution of a program in a wide range of hardware and software environments. Prevalent parallel execution models can fail to be efficient. Unable to account for dynamic changes in operating conditions, they may create non-optimum parallelism, leading to underutilization or contention of resources. We propose ParallelismDial (PD), a model to dynamically, continuously and judiciously adapt a program's degree of parallelism to a given dynamic operating environment. PD uses a holistic metric to measure system-efficiency. The metric is used to systematically optimize the program's execution. We apply PD to two diverse parallel programming models: Intel TBB, an industry standard, and Prometheus, a recent research effort. Two prototypes of PD have been implemented. The prototypes are evaluated on two stock multicore workstations. Dedicated and multiprogrammed environments were considered. Experimental results show that the prototypes outperform the state-of-the-art approaches, on average, by 15% on time and 31% on energy efficiency, in the dedicated environment. In the multiprogrammed environment, the savings are to the tune of 19% and 21% in time and energy, respectively.
General-purpose systolic arrays

The extension of systolic array architecture from fixed- or special-purpose architectures to general-purpose, SIMD (single-instruction stream, multiple-data stream), MIMD (multiple-instruction stream, multiple-data stream) architectures, and hybrid architectures that combine both commercial and FPGA (field-programmable gate array) technologies is chronicled. The authors present a taxonomy for systolic organizations, discuss each architecture's methods of exploiting concurrencies, and compare performance attributes of each. The authors also describe a number of implementation issues that determine a systolic array's performance efficiency, such as algorithms and mapping, system integration through memory subsystems, cell granularity, and extensibility to a wide variety of topologies. <<ETX>>
A queuing network model for wafer fabrication using decomposition without aggregation

Deterministic capacity models and simulation models cannot fully comprehend the modern wafer fabrication facility's need for cycle time (CT) forecasts that are both accurate and rapid. Queuing networks, being stochastic yet analytical models, have the potential of providing sufficiently accurate `on the spot' CT approximations. In this paper, we characterize a queuing network suited for fab modeling and then formulate a queuing network model for a mini-fab, using decomposition without aggregation method to yield CT approximations. Numerical results demonstrate that this proposed approach generates fairly accurate approximations with an average error of 7% compared to simulation results, better than other existing methods to date.
Development of white matter and reading skills

White matter tissue properties are highly correlated with reading proficiency; we would like to have a model that relates the dynamics of an individual’s white matter development to their acquisition of skilled reading. The development of cerebral white matter involves multiple biological processes, and the balance between these processes differs between individuals. Cross-sectional measures of white matter mask the interplay between these processes and their connection to an individual’s cognitive development. Hence, we performed a longitudinal study to measure white-matter development (diffusion-weighted imaging) and reading development (behavioral testing) in individual children (age 7–15 y). The pattern of white-matter development differed significantly among children. In the left arcuate and left inferior longitudinal fasciculus, children with above-average reading skills initially had low fractional anisotropy (FA) that increased over the 3-y period, whereas children with below-average reading skills had higher initial FA that declined over time. We describe a dual-process model of white matter development comprising biological processes with opposing effects on FA, such as axonal myelination and pruning, to explain the pattern of results.
Emancipated pixels: real-world graphics in the luminous room

We describe a conceptual infrastructure – the Luminous Room – for providing graphical display and interaction at each of an interior architectural space's various surfaces, arguing that pervasive environmental output and input is one natural heir to today's rather more limited notion of spatially-confined, output-only display (the CRT). We discuss the requirements of such real-world graphics, including computational & networking demands; schemes for spatially omnipresent capture and display ; and issues of design and interaction that emerge under these new circumstances. These discussions are both illustrated and motivated by five particular applications that have been built for a real, experimental Luminous Room space, and by details of the current technical approach to its construction (involving a two-way optical transducer called an I/O Bulb that projects and captures pixels).
Information retrieval model: A social network extraction perspective

Future Information Retrieval, especially in connection with the internet, will incorporate the content descriptions that are generated with social network extraction technologies and preferably incorporate the probability theory for assigning the semantic. Although there is an increasing interest about social network extraction, but a little of them has a significant impact to information retrieval. Therefore this paper proposes a model of information retrieval from the social network extraction.
Multilingual Annotation and Disambiguation of Discourse Connectives for Machine Translation

Many discourse connectives can signal several types of relations between sentences. Their automatic disambiguation, i.e. the labeling of the correct sense of each occurrence, is important for discourse parsing, but could also be helpful to machine translation. We describe new approaches for improving the accuracy of manual annotation of three discourse connectives (two English, one French) by using parallel corpora. An appropriate set of labels for each connective can be found using information from their translations. Our results for automatic disambiguation are state-of-the-art, at up to 85% accuracy using surface features. Using feature analysis, contextual features are shown to be useful across languages and connectives.
AAEE minimonograph #26: The electrodiagnosis of carpal tunnel syndrome

The electrodiagnosis of carpal tunnel syndrome is reviewed, including discussions of old and new techniques of motor and sensory nerve conduction, anomalous innervation, needle electrode examination, and one method of examining a patient with suspected carpal tunnel syndrome. The results of electromyographic testing of 505 patients with carpal tunnel synddrome in Rochester, Minnesota, from 1961 to 1980 are compared with result from previous studies. In the appendixes, a method of performing median motor and sensory nerve conduction studies and Mayo Clinic normal values are provided.
Exploring Supports Provided for Student ePortfolio Development in a Professional Development Context

This small scale study aimed to explore and establish if support strategies implemented to enhance student ePortfolios were helpful to students and to identify useful ways of supporting ePortfolio development with future cohorts of students. This action research study was informed through focus group discussion and individual interviews with students. The importance of reflection for the development professional practice and of creative abilities is discussed. The substantial benefits of creativity within education are investigated and characteristics of creativity that might be developed with students’ ePortfolios are revealed. Specifically this paper seeks to foster Crafts (2011) four characteristics of creativity, pluralities, playfulness, possibilities and participation within ePortfolios, through student engagement with multimedia and peer-learning. Findings describe how support strategies were perceived by students and if the activities were supportive of reflection and creativity. Recommendations for the future support of the ePortfolio will involve an increase in support for peer-learning; more support on reflective writing; workshops on developing artefacts with multimedia; exploration of meaning and characteristics of creativity with students.
Learning and Teaching Styles in Engineering Education.

When Linda Silverman and I wrote this paper in 1987, our goal was to offer some insights about teaching and learning based on Dr. Silverman’s expertise in educational psychology and my experience in engineering education that would be helpful to some of my fellow engineering professors. When the paper was published early in 1988, the response was astonishing. Almost immediately, reprint requests flooded in from all over the world. The paper started to be cited in the engineering education literature, then in the general science education literature; it was the first article cited in the premier issue of ERIC’s National Teaching and Learning Forum; and it was the most frequently cited paper in articles published in the Journal of Engineering Education over a 10-year period. A self-scoring web-based instrument called the Index of Learning Styles that assesses preferences on four scales of the learning style model developed in the paper currently gets about 100,000 hits a year and has been translated into half a dozen languages that I know about and probably more that I don’t, even though it has not yet been validated. The 1988 paper is still cited more than any other paper I have written, including more recent papers on learning styles.
Habit change as a learning process: Design framework for mobile interventions

Health interventions aim to influence behavior by creating healthy habits that substitute existing unhealthy ones. Habits are often deeply ingrained but also easily disrupted in new situations. This makes changing habits a life-long learning and adaptation process rather than a one-time task of limited duration. Therefore, applying modern understanding of learning could be fruitful in designing effective and sustainable health interventions. This paper presents the initial design framework for interventions based on learning theories, and also introduces a mobile habit change application. The application guides the user in habit formation through small daily changes, supported by a user-selectable cartoonish avatar with varied styles of dialogue.