Miracle-dz/UniFAR-FTUs huggingface dataset:
Architecture and Network-on-Chip Implementation of a New Hierarchical Interconnection Network

A Midimew-connected Mesh Network (MMN) is a minimal distance mesh with wrap-around links network of multiple basic modules (BMs), in which the BMs are 2D-mesh networks that are hierarchically interconnected for higher-level networks. In this paper, we present the architecture of the MMN, addressing of node, routing of message, and evaluate the static network performance of MMN, TESH, mesh and torus networks. In addition, we propose the network-on-chip (NoC) implementation of MMN. With innovative combination of diagonal and hierarchical structure, the MMN possesses several attractive features, including constant degree, small diameter, low cost, small average distance, moderate bisection width and high fault tolerant performance than that of other conventional and hierarchical interconnection networks. The simple architecture of MMN is also highly suitable for NoC implementation. To implement all the links of level-3 MMN, only four layers are needed which is feasible with current and future VLSI technologies.
Mindfulness-Based Stress Reduction as a Stress Management Intervention for Healthy Individuals

Stress is a global public health problem with several negative health consequences, including anxiety, depression, cardiovascular disease, and suicide. Mindfulness-based stress reduction offers an effective way of reducing stress by combining mindfulness meditation and yoga in an 8-week training program. The purpose of this study was to look at studies from January 2009 to January 2014 and examine whether mindfulness-based stress reduction is a potentially viable method for managing stress. A systematic search from Medline, CINAHL, and Alt HealthWatch databases was conducted for all types of quantitative articles involving mindfulness-based stress reduction. A total of 17 articles met the inclusion criteria. Of the 17 studies, 16 demonstrated positive changes in psychological or physiological outcomes related to anxiety and/or stress. Despite the limitations of not all studies using randomized controlled design, having smaller sample sizes, and having different outcomes, mindfulness-based stress reduction appears to be a promising modality for stress management.
Tracking of cell population from time lapse and end point confocal microscopy images with multiple hypothesis Kalman smoothing filters

This paper describes an automated visual tracking system combining time-lapse and end-point confocal microscopy to aid the interpretations of cell behaviors and interactions, with the focus on understanding the sprouting mechanism during angiogenesis. These multiple cells exhibit stochastic motion and are subjected to photo-bleaching and the images acquired are of low signal to noise ratio. Hence, following time-lapse imaging, high resolution end-point images are acquired. Our approach applies a probabilistic motion filter (a backward Kalman filtering followed by track smoothing) which incorporates end-point and all available time-lapse information in a mathematically consistent manner to obtain trajectory and phenotype information of multiple individual cells simultaneously. An extension of this algorithm, track smoothing with a Multiple Hypothesis Testing (MHT) data association, is proposed to improve association of multiple close contact and proliferating cells across images acquired from different time points to existing track trajectories. Our methodology was applied to tracking endothelial cell sprouting in three-dimensional micro-fluidic devices.
Energy-efficient k-class coverage for collaborative classification in Wireless Audio Sensor Networks

Object/event classification is an important aspect in the applications of Wireless Audio Sensor Networks (WASNs). In order to reduce the computational burdens of individual sensors, distributed classification method is adopted, i.e., the individual sensors only perform binary classification and send out a binary decision to the fusion center. However, it brings about a new coverage problem, namely, how to deploy sensors so that all locations in the surveillance region are covered by multiple types of sensors with different sensing radii for collaborative classification. We call it k-class coverage problem. In this paper, we propose two algorithms: straight-forward algorithm and divide-and-conquer algorithm. The first algorithm converts the problem into ? -class set cover problem, and the second algorithm converts the problem into solving set 1-cover problem k times. Greedy strategies are used in both of two algorithms. Performance analysis and simulation results are provided for evaluating two algorithms.
RAMS and BlackSheep: Inferring White-box Application Behavior Using Black-box Techniques (CMU-PDL-08-103)

A significant challenge in developing automated problem-diagnosis tools for distributed systems is the ability of these tools to differentiate between changes in system behavior due to workload changes from those due to faults. To address this challenge, current, typically white-box, techniques extract semantically-rich knowledge about the target application through fairly invasive, high-overhead instrumentation. We propose and explore two scalable, low-overhead, non-invasive techniques to infer semantics about target distributed systems, in a black-box manner, to facilitate problem diagnosis. RAMS applies statistical analysis on hardware performance counters to predict whether a given node in a distributed system is faulty, while BlackSheep corroborates multiple system metrics with application-level logs to determine whether a given node is faulty. In addition, we have developed and demonstrated a novel technique to extract, from existing application-level logs, semantically-rich behavior that is immediately amenable to analysis and synthesis with other numerical, black-box metrics. We have evaluated the efficacy of RAMS and BlackSheep in diagnosing real-world problems in the Hadoop distributed parallel programming system. Submitted in partial fulfillment of the requirements for the Senior Honors Thesis program in the School of Computer Science at Carnegie Mellon University Acknowledgements: I would like to thank Priya Narasimhan for her advice, constant encouragement and inspiring thoughts, and Xinghao Pan for enduring many animated descriptions of this work, without which this project would not have been possible. This work is also dedicated to my parents and sister, for their unwavering, whole-hearted support for me to pursue my dreams.
Corporate Entrepreneurship: A Strategic and Structural Perspective

Recently there has been a growing interest in the use of corporate entrepreneurship as a means for corporations to enhance the innovative abilities of their employees and, at the same time, increase corporate success through the creation of new corporate ventures. However, the creation of corporate activity is difficult since it involves radically changing internal organisational behaviour patterns. Researchers have attempted to understand the factors that stimulate or impede corporate entrepreneurship. They examined the effect of a firm’s strategy, organisation and external environment. It appears that the environment plays a profound role is influencing corporate entrepreneurship whereas there is consensus that the external environment is an important antecedent of corporate entrepreneurship. Focus on the environment, the literature highlights two research questions that deserve examination. First, how do firms that compete in different environments vary in the corporate entrepreneurship activities? Second, which corporate entrepreneurship activities are conductive to superior performance in different environments? This paper develops the theoretical foundation of theses questions and focuses on the relationship between corporate entrepreneurship and strategic management in a integrating model of corporate entrepreneurship, giving special attention to the strategic behaviour, corporate context and organisational types.
Understanding and Modeling User-Perceived Brand Personality from Mobile Application UIs

Designers strive to make their mobile apps stand out in a competitive market by creating a distinctive brand personality. However, it is unclear whether users can form a consistent impression of brand personality by looking at a few user interface (UI) screenshots in the app store, and if this process can be modeled computationally. To bridge this gap, we first collect crowd assessment on brand personalities depicted by the UIs of 318 applications, and statistically confirm that users can reach substantial agreement. To further model how users process mobile UI visually, we compute UI descriptors including Color, Organization, and Texture at both element and page levels. We feed these descriptors to a computational model, achieving a high accuracy of predicting perceived brand personality (MSE = 0.035 and R^2 = 0.78). This work could benefit designers by highlighting contributing visual factors to brand personality creation and providing quick, low-cost design feedback.
Reward Guides Vision when It's Your Thing: Trait Reward-Seeking in Reward-Mediated Visual Priming

Reward-related mesolimbic dopamine is thought to play an important role in guiding animal behaviour, biasing approach towards potentially beneficial environmental stimuli and away from objects unlikely to garner positive outcome. This is considered to result in part from an impact on perceptual and attentional processes: dopamine initiates a series of cognitive events that result in the priming of reward-associated perceptual features. We have provided behavioural and electrophysiological evidence that this mechanism guides human vision in search, an effect we refer to as reward priming. We have also demonstrated that there is substantial individual variability in this effect. Here we show that behavioural differences in reward priming are predicted remarkably well by a personality index that captures the degree to which a person's behaviour is driven by reward outcome. Participants with reward-seeking personalities are found to be those who allocate visual resources to objects characterized by reward-associated visual features. These results add to a rapidly developing literature demonstrating the crucial role reward plays in attentional control. They additionally illustrate the striking impact personality traits can have on low-level cognitive processes like perception and selective attention.
Can anti-Mullerian hormone replace ultrasonographic evaluation in polycystic ovary syndrome? A review of current progress

Several studies over the past decade have now consistently indicated that the serum anti-Mullerian hormone (AMH) levels are at least 2–3-fold higher in the patients with polycystic ovary syndrome (PCOS), which also corresponds to the increased number of AMH producing preantral and small antral follicles. Moreover, AMH levels have been found to be associated in direct proportion to the follicle numbers per ovary or antral follicular count, assessed by the transvaginal ultrasound (TVS). Furthermore, AMH correlates directly with the rising serum testosterone and luteinizing hormone levels in PCOS. Hence, serum AMH in women with oligo-anovulation and/or hyperandrogenemia could indicate the presence of underlying PCOS, when reliable TVS is not feasible, or not acceptable, either due to the virginal status or psycho-social issue. In addition, the imaging quality of abdominal ultrasound is often impaired by obesity, which typically occurs in PCOS women. Indeed, PCOS occurs most commonly in young females who cannot be subjected to invasive TVS for various reasons; therefore, a desirable alternative to TVS is urgently required to diagnose the most prevalent endocrine abnormality of young women. This review will analyze the currently available evidence regarding the role of AMH in the diagnosis of PCOS.
Sleep disturbances in older adults with mild cognitive impairment

ABSTRACT Background: Normal aging and dementia are characterized by increased prevalence of sleep disorders and alterations of both sleep continuity and architecture. However, little is still known about the nature of sleep in mild cognitive impairment (MCI), which is presumably situated on the continuum from healthy aging to dementia. This unsystematic review summarizes the current literature on the prevalence and severity of sleep disturbances in MCI. Methods: Eighteen studies addressing sleep/night-time disturbances among other neuropsychiatric symptoms in individuals with MCI were identified through a search of databases and an examination of reference lists of selected papers. Fifteen of those studies reported data on prevalence or severity of sleep/night-time disturbances. Results: Results indicated that 14–59% of patients with MCI had sleep disturbances. These disturbances were often identified as one of the four most prevalent neuropsychiatric symptoms of MCI and were considered as clinically significant in some studies. In addition, there was some evidence that the prevalence of sleep disturbances in MCI is intermediate between that of normal aging and dementia. Longitudinal data suggest that sleep problems are associated with both incident MCI and dementia. Conclusions: These findings support the hypothesis that sleep disturbances are one of the core non-cognitive symptoms of MCI. It remains to be known whether sleep problems could help to identify those individuals with MCI who will eventually develop dementia. Studies characterizing sleep more systematically are needed to verify this proposition and to clarify the associations between sleep disturbances and other neuropsychiatric symptoms of MCI.
Interaction Chain Patterns of Online Text Construction with Lexical Cohesion

This study aims at arousing college students’ metacognition in detecting lexical cohesion during online text construction as WordNet served as a lexical resource. A total of 83 students were requested to construct texts through sequences of actions identified as interaction chains in this study. Interaction chains are grouped and categorized as a meaningful entity in order to investigate the students’ thinking process and behavior in general and to understand the interaction between the computer and the students in particular. From the interaction chains, it was found that some students revised incorrect sentences to correct ones. In making correct revision, they needed to assess incoming information, interpret and organize textual information, engage in thinking what they know, monitor their own meaning construction process, and take remedial actions to reach comprehension. The rate of correct sentence selection increased from 34.04% to 55.02% in three sequential text construction tasks. The recognition of lexical cohesion was found to be a determining factor for successful construction of a text.
ECS

Emerging nonvolatile memories (NVMs) suffer from low write endurance, resulting in early cell failures (hard errors), which reduce memory lifetime. It was recognized early on that conventional error-correcting codes (ECCs), which are designed for soft errors, are a poor choice for addressing hard errors in NVMs. This led to the evolution of hard error correction schemes like dynamically replicated memory (DRM), error-correcting pointers (ECPs), SAFER, FREE-p, PAYG, and Zombie memory to improve NVM lifetime. Whereas these approaches made significant inroads in addressing hard errors and low memory lifetime in NVMs, overcoming the challenges of underutilization of error-correcting resources and/or implementation overhead (e.g., codec latency, hardware support) remain areas of active research and development. This article proposes error-correcting strings (ECSs) as a high-utilization, low-latency solution for hard error correction in single-/multi-/triple-level cell (SLC/MLC/TLC) NVMs. At its core, ECS adopts a base-offset approach to store pointers to the failed memory cells; in this work, base is the address of the first failed cell in a memory block and offsets are the distances between successive failed cells in that memory block. Unlike ECP, which uses fixed-length pointers, ECS uses variable-length offsets to point to the failed cells, thereby realizing more pointers to tolerate more hard errors per memory block. Further, this article proposes eXtended-ECS (XECS), a page-level error correction architecture, which employs dynamic on-demand ECS allocation and opportunistic pattern-based data compression to improve NVM lifetime by 2× over ECP-6 for comparable overhead and negligible impact to system performance. Finally, this article demonstrates that ECS is a drop-in replacement for ECP to extend the lifetime of state-of-the-art ECP-based techniques like PAYG and Zombie memory; ECS is also compatible with MLC/TLC NVMs, where it complements drift-induced soft error reduction techniques like ECC and incomplete data mapping to simultaneously extend NVM lifetime.
Fairness measures for resource allocation

In many optimization problems, one seeks to allocate a limited set of resources to a set of individuals with demands. Thus, such allocations can naturally be viewed as vectors, with one coordinate representing each individual. Motivated by work in network routing and bandwidth assignment, we consider the problem of producing solutions that simultaneously approximate all feasible allocations in a coordinate-wise sense. This is a very strong type of "global" approximation guarantee, and we explore its consequences in a range of discrete optimization problems, including facility location, scheduling, and bandwidth assignment in networks. A fundamental issue-one not encountered in the traditional design of approximation algorithms-is that good approximations in this global sense need not exist for every problem instance; there is no a priori reason why there should be an allocation that simultaneously approximates all others. As a result, the existential questions concerning such good allocations lead to a new perspective on a number of basic problems in resource allocation, and on the structure of their feasible solutions.
An Essential Role for Katanin in Severing Microtubules in the Neuron

Several lines of evidence suggest that microtubules are nucleated at the neuronal centrosome, and then released for transport into axons and dendrites. Here we sought to determine whether the microtubule-severing protein known as katanin mediates microtubule release from the neuronal centrosome. Immunomicroscopic analyses on cultured sympathetic neurons show that katanin is present at the centrosome, but is also widely distributed throughout the neuron. Microinjection of an antibody that inactivates katanin results in a dramatic accumulation of microtubules at the centrosome, indicating that katanin is indeed required for microtubule release from the centrosome. However, the antibody also causes an inhibition of axon outgrowth that is more immediate than expected on this basis alone. It may be that katanin severs microtubules throughout the cell body to keep them sufficiently short to be efficiently transported into developing processes. Consistent with this idea, there were significantly fewer free ends of microtubules in the cell bodies of neurons that had been injected with the katanin antibody compared with controls. These results indicate that microtubule-severing by katanin is essential for releasing microtubules from the neuronal centrosome, and also for regulating the length of the microtubules after their release.
Polyphonic music transcription using note event modeling

This paper proposes a method for the automatic transcription of real-world music signals, including a variety of musical genres. The method transcribes notes played with pitched musical instruments. Percussive sounds, such as drums, may be present but they are not transcribed. Musical notations (i.e., MIDI files) are produced from acoustic stereo input files using probabilistic note event modeling. Note events are described with a hidden Markov model (HMM). The model uses three acoustic features extracted with a multiple fundamental frequency (FO) estimator to calculate the likelihoods of different notes and performs temporal segmentation of notes. The transitions between notes are controlled with a musicological model involving musical key estimation and bigram models. The final transcription is obtained by searching for several paths through the note models. Evaluation was carried out with a realistic music database. Using strict evaluation criteria, 39% of all the notes were found (recall) and 41% of the transcribed notes were correct (precision). Taken the complexity of the considered transcription task, the results are encouraging.
Certainties and uncertainties : ethics and professional identities of early childhood educators

This study is an inquiry into the professional identity constructions of early childhood educators, where identity is conceptualised as social and contextual. Through a genealogical analysis of narratives of four Queensland early childhood teachers, the thesis renders as problematic universal and fixed notions of what it is to be an early childhood professional. The data are the four teachers’ professional life history narratives recounted through a series of conversational interviews with each participant. As they spoke about professionalism and ethics, these teachers struggled to locate themselves as professionals, as they drew on a number of dominant discourses available to them. These dominant discourses were located and mapped through analysis of the participants’ talk about relationships with parents, colleagues and authorities. Genealogical analysis enabled multiple readings of the ways in which the participants’ talk held together certainties and uncertainties, as they recounted their experiences and spoke of early childhood expertise, relational engagement and ethics. The thesis concludes with suggestions for ways to support early childhood teachers and pre-service teachers to both engage with and resist normative processes and expectations of professional identity construction. In so doing, multiple and contextual opportunities can be made available when it comes to being professional and ‘doing’ ethics. The thesis makes an argument for new possibilities for thinking and speaking professional identities that include both certainty and uncertainty, comfort and discomfort, and these seemingly oppositional terms are held together in tension, with an insistence that both are necessary and true. The use of provocations offers tools through which pre-service teachers, teachers and teacher educators can access new positions associated with certainties and uncertainties in professional identities. These new positions call for work that supports experiences of ‘de-comfort’ – that is, experiences that encourage early childhood educators to step away from the comfort zones that can become part of expertise, professional relationships and ethics embedded within normative representations of what it is to be an early childhood professional.
AN INTEGRATED , LOW POWER , ULTRA-WIDEBAND TRANSCEIVER ARCHITECTURE FOR LOW-RATE , INDOOR WIRELESS SYSTEMS

This paper describes the system architecture and circuit design constraints for a proposed Ultra-Wideband radio transceiver. Targeting a sensor network application, the radio supports peer-to-peer communication at greater than 100kbps over 5 meters with a 1mW total (TX+RX) power budget. A narrow pulse (approximately 1ns wide) is transmitted using simple digital switches; spreading the energy over a Gigahertz of bandwidth. Reception, after gain and filtering, occurs in a bank of A/D converters which capture the received pulse in an adjustable window of 16 to 64ns. This window is composed of 32 to 128 data samples at a 2GHz rate and is repeated at the pulse broadcast frequency which may range from 62.5MHz to 1MHz. The implementation issues of this system, including clock generation, conversion bit-widths, gain, and the choice of pulse rate versus pulse amplitude will be discussed along with the subject of interference and the idea of “imperceptible” operation.