Miracle-dz/UniFAR-FTUs huggingface dataset:
Multiphase LLC Series Resonant Converter for Microprocessor Voltage Regulation

In order to further reduce the power loss, and increase the computation speed, future microprocessors desires lower voltage, higher current, tighter voltage regulation, and faster transient from their voltage regulators. In the last decade, interleaved buck converters have been studied and used extensively for powering microprocessors. Due to their inherent limitations in current sharing, capacitor size, step down ratio, and energy flow pattern, it becomes very difficult for interleaved buck converters to keep up with the demands of the future microprocessors. In this paper, a new candidate, a multiphase LLC resonant converter is proposed, which features zero voltage switching for both inverter and rectifier switches; wide load range; limited frequency range; fast dynamic response; high efficiency; and automatic current sharing. These features ensure the proposed multiphase LLC resonant converter a good voltage regulator candidate for the next generation microprocessors. All theoretical analyses are verified by a 1 V 50 W prototype and its experimental results
Cooperative learning on an international masters

ABSTRACT Postgraduate taught provision in Anglophone higher education contexts is becoming increasingly populated by cohorts of students from a wide range of linguistic, cultural and educational backgrounds. However, the voices of these students on their learning experiences remain largely unheard. Little previous research exists on the experiences of higher degree students as they participate in group work in multi-cultural settings. This study investigates the perspectives of students from a variety of educational backgrounds on their experiences of cooperative learning in multi-national groups on a Masters programme at a UK university. Seven focus groups were conducted with students from a range of countries including Confucian Heritage Cultures (CHC) and non-CHC backgrounds. Students perceived group work as often lacking adequate structure, leading to feelings of confusion and insecurity. While it was apparent that a complex interplay of cultural, cognitive, and linguistic factors impacted on the functioning of collaborative learning, the data highlighted the need to provide students with more structure and guidance for cooperative learning environments and the importance of creating intercultural learning opportunities for students to better understand the impact of cultural backgrounds on approaches to cooperative learning in multi-national situations.
A novel meta-heuristic approach for optical monitoring-tree design in WDM networks

Thanks to recent advances in WDM technologies, an optical fiber is capable to carry up to 200 wavelengths operating at 40 Gbps each. In such high speed networks, service disruptions caused by network failures (e.g., fiber cut, amplifier dysfunction) may lead to high data losses. A network operator should be able to promptly locate such failures, in order to perform fast restoration. Hence, an efficient fault detection and localization mechanism is mandatory for reliable network design. In previous work, we have introduced the concept of monitoring-trees (m-trees) to achieve fast link failure detection and localization. We have proposed an integer linear programming (ILP) approach for the design of an m-tree solution that minimizes the number of required optical monitors, while achieving unambiguous failure detection and localization. In this paper, we propose a novel approach, based on the well known simulated annealing meta-heuristic, for the m-tree design in WDM networks. Simulations conducted in this study show the same results as the ILP approach at much lower computation time. Our proposal can thus be applied to large-sized and very large-sized networks.
Variable protection against experimental broiler necrotic enteritis after immunization with the C-terminal fragment of Clostridium perfringens alpha-toxin and a non-toxic NetB variant

ABSTRACT Necrotic enteritis toxin B (NetB) is a pore-forming toxin produced by Clostridium perfringens and has been shown to play a key role in avian necrotic enteritis, a disease causing significant costs to the poultry production industry worldwide. The aim of this work was to determine whether immunization with a non-toxic variant of NetB (NetB W262A) and the C-terminal fragment of C. perfringens alpha-toxin (CPA247–370) would provide protection against experimental necrotic enteritis. Immunized birds with either antigen or a combination of antigens developed serum antibody levels against NetB and CPA. When CPA247–370 and NetB W262A were used in combination as immunogens, an increased protection was observed after oral challenge by individual dosing, but not after in-feed-challenge.
Pyruvate Oxidase Influences the Sugar Utilization Pattern and Capsule Production in Streptococcus pneumoniae

Pyruvate oxidase is a key function in the metabolism and lifestyle of many lactic acid bacteria and its activity depends on the presence of environmental oxygen. In Streptococcus pneumoniae the protein has been suggested to play a major role in metabolism and has been implicated in virulence, oxidative stress survival and death in stationary phase. Under semi-aerobic conditions, transcriptomic and metabolite profiling analysis of a spxB mutant grown on glucose showed minor changes compared to the wild type, apart from the significant induction of two operons involved in carbohydrate uptake and processing. This induction leads to a change in the sugar utilization capabilities of the bacterium, as indicated by the analysis of the growth profiles of the D39 parent and spxB mutant on alternative carbohydrates. Metabolic analysis and growth experiments showed that inactivation of SpxB has no effect on the glucose fermentation pattern, except under aerobic conditions. More importantly, we show that mutation of spxB results in the production of increased amounts of capsule, the major virulence factor of S. pneumoniae. Part of this increase can be attributed to induction of capsule operon (cps) transcription. Therefore, we propose that S. pneumoniae utilizes pyruvate oxidase as an indirect sensor of the oxygenation of the environment, resulting in the adaption of its nutritional capability and the amount of capsule to survive in the host.
BBU-RRH switching schemes for centralized RAN

Mobile data traffic has been increasing at a rapid pace over the past few years due to the rise of both smartphones and tablets. Small cell deployments are one of the most effective ways to increase system capacity by improving the spatial reuse of radio resources for the explosive increase in traffic loads. However, it leads to be a large cost impact for operators. Centralized RAN (C-RAN) has been proposed, which has the potential ability to reduce network costs due to reductions in civil work and/or electricity costs at local base station sites by centralizing baseband units to the center side. Moreover, C-RAN can be expected to further reduce network costs using baseband unit (BBU) pooling functions in which the centralized BBU resources can be dynamically allocated to remote radio heads (RRHs) depending on traffic load. This paper proposes semi-static and adaptive BBU-RRH switching schemes for C-RAN and evaluates their effectiveness through simulations. Under conditions of 100 RRHs, here, a RRH is comparable to a cell, and traffic distribution with a typical traffic profile in office (business) area, we confirmed that the number of BBUs can be reduced by 26% and 47% for semi-static and adaptive schemes, respectively, compared with conventional cell deployment.
Greening of the Arctic: Synthesis and models to examine pan-Arctic vegetation change: climate, sea-ice, and terrain linkages

Greening of the Arctic: Synthesis and models to examine pan-Arctic vegetation change: climate, sea-ice, and terrain linkages Principal Investigators: Donald A. Walker Institute of Arctic Biology and Department of Biology and Wildlife, University of Alaska Fairbanks, Fairbanks, Alaska 99775, 907-474-2460, ffdaw@uaf.edu Howard E. Epstein Department of Environmental Science, University of Virginia, Clark Hall 207, Charlottesville, VA 22904-4123, 804-924-4308, hee2b@virginia.edu Uma Bhatt Atmospheric Science Group, Geophysical Institute, University of Alaska Fairbanks, Fairbanks, Alaska 99775 907474-2662, ubhatt@gi.alaska. edu Major Collaborators: Gensuo J. Jia Department of Forest, Rangeland, and Watershed Stewardship, Colorado State University, Fort Collins, Colorado 80523, (970) 491-0495, jiongjia@cnr.colostate. edu Josefino C. Comiso NASA Goddard Space Flight Center, Oceans and Ice Branch, Code 971, Greenbelt, MD 20771, josefino.c. comiso@nasa.gov Jed O. Kaplan European Commission Joint Research Centre, TP-280, I-21020 Ispra, Italy, jed.Kaplan@jrc.it Carl Markon USGS Alaska Geographic Science Office, 4230 Univerisity Dr., Anchorage, AK 99508-4664, markon@usgs.gov Other Collaborators: Jerry Brown International Permafrost Association, P.O. Box 7, Woods Hole, MA 02543, jerrybrown@igc.org Charles Tarnocai Ag. And Agri-Food Canada, 960 Carling Avenue, Ottawa, K1A OC6 Canada, tarnocaict@agri.gc. ca Evgeny Melnikov and Natalia Moskalenko Earth Cryosphere Institute, 30/8 Vavilov str. Moscow, Russia SB RAS, emelnikov@mtu-net.ru, natmoskalenko@yandex.ru Chien Lu Ping, UAF Agriculture and Forestry Experiment Station, 533 E. Fireweed, Palmer, AK 99645, pfclp@uaa.edu
Voice Recognition Robot for Visually ImpairedPeople

A smart multipurpose human assistance robotic dog is designed to guide the visually impaired and elderly people to some predefined destination avoiding obstacles and traffic. It is also designed to act as an advanced multipurpose human assistance and service robot that is able recognize the words spoken by the user, talk to them and take action according to the spoken voice command. Voice commands are recognized by an android Smartphone and the information is transferred to the main MCU using a Bluetooth serial port that runs Bluetooth SPP protocol stack. The robotic dog has the ability to follow a human when commanded with voice. Touch sensitive e-skin senses human finger touch and helps answering complex user requests such as time, date and weather conditions such as light and temperature. The same can be asked using voice also. It even allows the user to set wake up alarm. A built in audio playback system can play music tracks in MP3 format. One of the music tracks is kept as the alarm tone. It also plays the role of a regular watchdog during night and barks like any normal dog if it finds any abnormal activity. During the day time it can charge itself by moving around within a given region in order to find the maximum sun light, intelligently avoiding the shaded areas, thereby freeing the user completely from maintenance issues such as battery charging.
The proportional mean decomposition: A bridge between the Gaussian and bernoulli ensembles

We consider ill-posed linear inverse problems involving the estimation of structured sparse signals. When the sensing matrix has i.i. d. standard normal entries, there is a full-fledged theory on the sample complexity and robustness properties. In this work, we propose a way of making use of this theory to get good bounds for the i.i. d. Bernoulli ensemble. We first provide a deterministic relation between the two ensembles that relates the restricted singular values. Then, we show how one can get non-asymptotic results with small constants for the Bernoulli ensemble. While our discussion focuses on Bernoulli measurements, the main idea can be extended to any discrete distribution with little difficulty.
Topic detection of an utterance for speech dialogue processing

This paper proposes a method for topic detection of an utterance for speech dialogue processing including speech translation. There are three important points to consider in realizing topic detection of an utterance. The first is to obtain information from a short utterance. The second is to deal with a broad topic. The third is to have robustness against speech recognition errors. Our topic detection method is suitable as a solution to these problems. To deal with the first two problems, our method detects the topic of an utterance according to the relation factor between the topics and the words included in utterances. The third problem is solved by merging words with different surface forms. To verify the performance of our proposed method, we carried out experiments by using a broad-coverage travel conversation corpus. The experimental results show that the proposed method achieved 79.3% topic detection accuracy for correct transcriptions, and 75.6% accuracy for recognizer’s outputs whose WER was 12.8%.
Language Use in Nigerian Spam SMSs: A Linguistic Stylistic Analysis

ABSTRACT Digital marketing is influential to advertising businesses, with a veritable platform being SMSs. SMSs, with their widespread usage, have generated several academic enquiries. They have, however, been abused by telemarketers who inundate subscribers with spam—unsolicited and indiscriminately sent SMSs. A linguistic stylistic analysis of purposively collected spam SMS data provides insight into Nigerian spam SMSs’ unique linguistic features. Nigerian spam SMSs include categories such as network/service provider texts, bank texts, sport texts, health texts, religion texts, and bonanza/jackpot texts. Spam SMSs were primarily employed for advertisement, with phone users, the ultimate “victims,” receiving an average of 3.4 messages per day. Nigerian spam SMSs, despite usually being sent from “official” sources, contain linguistic features like textese, graphological deviation, and non-conformity to punctuation rules, while also employing code-mixing and internet text notations. They are also persuasive thanks to their use of verbal inducement, emotive language, polite salutations and “call-to-action” verbs.
An Uncertain Risk Index Model for Multi-Period Portfolio Selection

This paper discusses a multi-period portfolio problem in the situation where security returns are given mainly by experts' judgment and evaluation. The security return rates are regarded as uncertain variables in the situation and the justification of using them is discussed. An uncertain adjusting Risk Index model is proposed in which optimal portfolio adjustments are determined with the objective of minimizing a cumulative Risk Index over the investment horizon, while satisfying self-financing constraints at each period and achieving a desired incremental wealth target. The adjusting model is converted into its crisp form, enabling the users to effectively solve the multi-period adjusting problem with currently available programming solvers. For the sake of illustration, an example is also provided.
Energy efficient scheduling for hard real-time tasks on dynamic pipeline and voltage scaled processor

This paper addresses an energy optimization problem of pipeline depth and voltage scheduling for hard real-time tasks on a dynamic pipeline and voltage sealed (DPVS) processor, which can adjust its pipeline depth arid operating voltage dynamically depending on the workload characteristics under the timing constraints. For a set of periodic tasks, we formulate the energy optimization problem as a linear programming (LP) problem. Then, we propose the energy efficient version of widely used fixed-priority and dynamic-priority scheduling methods, which produce a feasible task schedule with optimal processor energy consumption. This paper also provides a set of experimental results to show the effectiveness of the proposed techniques in reducing energy over the existing methods.
Predicting Dissertation Methodology Choice Among Doctoral Candidates at a Faith-Based University

Limited research has investigated dissertation methodology choice and the factors that contribute to this choice. Quantitative research is based in mathematics and scientific positivism, and qualitative research is based in constructivism. These underlying philosophical differences posit the question if certain factors predict dissertation methodology choice. Using the theoretical framework of intersectionality, this predictive, correlational study used archival data to determine if biological sex, ethnicity, age, or religious affiliation predicts dissertation methodology choice. A logistics regression analysis was used to review 398 doctoral dissertations and determine if any of the criterion variables predicted dissertation methodology choice. After analysis, it was determined that none of the criterion variables of biological sex, ethnicity, age, and religious affiliation were statistically significant in predicting dissertation methodology choice.
Crtc1 Activates a Transcriptional Program Deregulated at Early Alzheimer's Disease-Related Stages

Cognitive decline is associated with gene expression changes in the brain, but the transcriptional mechanisms underlying memory impairments in cognitive disorders, such as Alzheimer's disease (AD), are largely unknown. Here, we aimed to elucidate relevant mechanisms responsible for transcriptional changes underlying early memory loss in AD by examining pathological, behavioral, and transcriptomic changes in control and mutant β-amyloid precursor protein (APPSw,Ind) transgenic mice during aging. Genome-wide transcriptome analysis using mouse microarrays revealed deregulation of a gene network related with neurotransmission, synaptic plasticity, and learning/memory in the hippocampus of APPSw,Ind mice after spatial memory training. Specifically, APPSw,Ind mice show changes on a cAMP-responsive element binding protein (CREB)-regulated transcriptional program dependent on the CREB-regulated transcription coactivator-1 (Crtc1). Interestingly, synaptic activity and spatial memory induces Crtc1 dephosphorylation (Ser151), nuclear translocation, and Crtc1-dependent transcription in the hippocampus, and these events are impaired in APPSw,Ind mice at early pathological and cognitive decline stages. CRTC1-dependent genes and CRTC1 levels are reduced in human hippocampus at intermediate Braak III/IV pathological stages. Importantly, adeno-associated viral-mediated Crtc1 overexpression in the hippocampus efficiently reverses Aβ-induced spatial learning and memory deficits by restoring a specific subset of Crtc1 target genes. Our results reveal a critical role of Crtc1-dependent transcription on spatial memory formation and provide the first evidence that targeting brain transcriptome reverses memory loss in AD.
Clock gate on abort: Towards energy-efficient hardware Transactional Memory

Transactional Memory (TM) is an emerging technology which promises to make parallel programming easier compared to earlier lock based approaches. However, as with any form of speculation, Transactional Memory too wastes a considerable amount of energy when the speculation goes wrong and transaction aborts. For Transactional Memory this wastage will typically be quite high because programmer will often mark a large portion of the code to be executed transactionally[4].
Modeling Transient Trace

This paper introduces a novel technique to construct an empirical workload model tting time-varying (transient) trace data. The trace can be a categorical or numerical time-series. We model the trace as a Piecewise Independent stochastic process. To estimate the parameters for our model we rst build a Rate Evolution Graph from the trace data. Piecewise linear regression is then used to construct a joint time-dependent probability mass function for the trace data. Two methods are proposed to build a parsimonious model. The modeling approach is demonstrated by the application of our model to twelve traces from the performance analysis domain.
On coresets for k-means and k-median clustering

In this paper, we show the existence of small coresets for the problems of computing k-median and k-means clustering for points in low dimension. In other words, we show that given a point set P in Rd, one can compute a weighted set S ⊆ P, of size O(k ε-d log n), such that one can compute the k-median/means clustering on S instead of on P, and get an (1+ε)-approximation. As a result, we improve the fastest known algorithms for (1+ε)-approximate k-means and k-median. Our algorithms have linear running time for a fixed k and ε. In addition, we can maintain the (1+ε)-approximate k-median or k-means clustering of a stream when points are being only inserted, using polylogarithmic space and update time.
Tissue-Specific Role of Glycogen Synthase Kinase 3β in Glucose Homeostasis and Insulin Action

ABSTRACT Dysregulation of the protein kinase glycogen synthase kinase 3 (GSK-3) has been implicated in the development of type 2 diabetes mellitus. GSK-3 protein expression and kinase activity are elevated in diabetes, while selective GSK-3 inhibitors have shown promise as modulators of glucose metabolism and insulin sensitivity. There are two GSK-3 isoforms in mammals, GSK-3α and GSK-3β. Mice engineered to lack GSK-3β die in late embryogenesis from liver apoptosis, whereas mice engineered to lack GSK-3α are viable and exhibit improved insulin sensitivity and hepatic glucose homeostasis. To assess the potential role of GSK-3β in insulin function, a conditional gene-targeting approach whereby mice in which expression of GSK-3β was specifically ablated within insulin-sensitive tissues were generated was undertaken. Liver-specific GSK-3β knockout mice are viable and glucose and insulin tolerant and display “normal” metabolic characteristics and insulin signaling. Mice lacking expression of GSK-3β in skeletal muscle are also viable but, in contrast to the liver-deleted animals, display improved glucose tolerance that is coupled with enhanced insulin-stimulated glycogen synthase regulation and glycogen deposition. These data indicate that there are not only distinct roles for GSK-3α and GSK-3β within the adult but also tissue-specific phenotypes associated with each of these isoforms.
SLM, a framework for session layer mobility management

This paper describes a novel framework for managing connections to mobile hosts in the Internet. The framework, SLM, integrates the notions of quality of service management and mobility management and forms a base for overall session management. We compare SLM with the currently most widely adopted mobility management framework, Mobile IP, and show how some of Mobile IP's deficiencies are overcome. The paper further presents some initial experimental results and future research.