Miracle-dz/UniFAR-FTUs huggingface dataset:
A case study on the application of real phase-change RAM to main memory subsystem

Phase-change RAM (PCM) has the advantages of better scaling and non-volatility compared with the DRAM which is expected to face its scaling limit in the near future. There have been many studies on applying the PCM to main memory in order to complement or replace the DRAM. One common limitation of these studies is that they are based on synthetic PCM models. In our study, we investigate the feasibility and issues of applying a real PCM to main memory. In this paper, we report our case study of characterizing the PCM and evaluating its usefulness in the main memory. Our results show that the PCM/DRAM hybrid main memory with a modest DRAM size can give comparable performance to that of the DRAM only main memory. However, the hybrid memory with small DRAMs or large footprint programs can suffer from performance degradation due to the long latency of both PCM writes and write preemption penalty, which requires architectural innovations for exploiting the full potential of PCM write performance.
Skills, Computerization, and Earnings in the Postwar U.S. Economy

Using both time-series and pooled cross-section, time-series data for 44 industries over the period 1947-1997 in the United States, no evidence is found to support the idea that the growth of skills or educational attainment had any statistically significant effect on growth of earnings. On the other hand, earnings growth is found to be positively related to overall productivity growth and equipment investment, while computerization and international trade both had a retardant effect on earnings.
Improved decoder design for LDPC codes based on selective node processing

This paper proposes a low complexity decoder design for low density parity check (ldpc) codes. The design primarily comprises a novel decoding algorithm and semi parallel high throughput architecture. Based on the observation that nodes with high log likelihood ratio provide almost same information in every iteration and can be deemed as static, we propose an algorithm in which the parity check matrix H is updated to a reduced form every time a static node is encountered resulting in lesser number of computations in subsequent iterations. Also the design greatly benefits from the area efficient semi-parallel architecture and the various improvisations introduced at different levels of abstraction in the decoder design. The decoder design is implemented for a ldpc code compliant with WLAN 802.11n standard using sum product algorithm. The simulation results showed a significantly higher throughput with an easily controllable increase in bit error rate.
Dual‐energy CT in gout – A review of current concepts and applications

Dual‐energy computed tomography (DECT) is a relatively recent development in the imaging of gouty arthritis. Its availability and usage have become increasingly widespread in recent years. DECT is a non‐invasive method for the visualisation, characterisation and quantification of monosodium urate crystal deposits which aids the clinician in the early diagnosis, treatment and follow‐up of this condition. This article aims to give an up to date review and summary of existing literature on the role and accuracy of DECT in the imaging of gout. Techniques in image acquisition, processing and interpretation will be discussed along with pitfalls, artefacts and clinical applications.
ExATO - High Quality Term Extraction for Portuguese and English

This paper presents a novel version of ExATO, a term extractor originally designed to extract relevant terms from corpora in Portuguese. In this new version not only corpora in Portuguese can be handled, but also texts in English are accepted. This extension is likely to offer the same quality pattern already achieved for Portuguese. In this paper, we draw the analysis of results in parallel corpora with respect to the intrinsic differences between Portuguese and English languages, and also the environment of usage for ExATO for Portuguese and English corpora. A brief comparison of ExATO and other similar tool is presented to illustrate the higher quality of ExATO extraction from English corpora.
A CHAT-Based Annotation Scheme for Case and Noun-Phrase Inflection in Child Language Data

This paper describes a coding scheme and a set of semi-automatic procedures for the annotation of complex noun phrases and their morpho-syntactic properties in child language data. These tools are based on the CHAT conventions of the Child Language Data Exchange System (MacWhinney 2000; CHILDES: http://childes.psy.cmu.edu/; CHAT: http://childes.psy.cmu.edu/manuals/chat.pdf). The coding scheme presented here focuses on the order and grammatical category of the individual elements in the noun phrase and their gender, number and case marking. It also provides information about the category and lexical identity of the element that assigns case to the respective noun phrase (e.g. the dative preposition mit ‘with’). The coding scheme was developed for German child language, but it can be adapted to other languages and populations.
Critical requirements for NMDA receptors in experience-dependent plasticity in the visual cortex

NMDA receptors play an essential role in many forms of experience-dependent plasticity in the visual system. NMDA receptors support the ocular dominance (OD) shift, development of receptive field properties in cortical neurons, and learning tasks associated with the visual cortex, as well as the cellular correlates of such plasticity measurements, ie long-term potentiation (LTP) and long-term depression (LTD). Complete removal of NMDA receptors abolishes plasticity, while selective removal of NMDA receptors from distinct circuits in the visual system can reveal a more specific requirement and identify circuits required for plasticity. Using this approach, I aimed to delineate the brain circuits involved in two forms of experience-dependent plasticity. First, I determined a layer-specific requirement for NMDA receptors in stimulus-specific response potentiation (SRP), which is a model for the plastic changes that may underlie perceptual learning. SRP acquisition requires NMDA receptors in the cortex, and it can be supported by expression of NMDA receptors in only deep layer 4 and layer 5. In contrast, this minimal expression of NMDA receptors did not support a paradigm for OD plasticity in adult mice. The contrasting requirements for NMDA receptors in these two forms of experience-dependent plasticity suggest that distinct forms of plasticity can be supported in separate cortical circuits. Thesis Supervisor: Susumu Tonegawa Title: Professor of Biology
Regression models for ordinal responses: a review of methods and applications.

BACKGROUND Epidemiologists are often interested in estimating the risk of several related diseases as well as adverse outcomes, which have a natural ordering of severity or certainty. While most investigators choose to model several dichotomous outcomes (such as very low birthweight versus normal and moderately low birthweight versus normal), this approach does not fully utilize the available information. Several statistical models for ordinal responses have been proposed, but have been underutilized. In this paper, we describe statistical methods for modelling ordinal response data, and illustrate the fit of these models to a large database from a perinatal health programme. METHODS Models considered here include (1) the cumulative logit model, (2) continuation-ratio model, (3) constrained and unconstrained partial proportional odds models, (4) adjacent-category logit model, (5) polytomous logistic model, and (6) stereotype logistic model. We illustrate and compare the fit of these models on a perinatal database, to study the impact of midline episiotomy procedure on perineal lacerations during labour and delivery. Finally, we provide a discussion on graphical methods for the assessment of model assumptions and model constraints, and conclude with a discussion on the choice of an ordinal model. The primary focus in this paper is the formulation of ordinal models, interpretation of model parameters, and their implications for epidemiological research. CONCLUSIONS This paper presents a synthesized review of generalized linear regression models for analysing ordered responses. We recommend that the analyst performs (i) goodness-of-fit tests and an analysis of residuals, (ii) sensitivity analysis by fitting and comparing different models, and (iii) by graphically examining the model assumptions.
Detection of faint extended sources in hyperspectral data and application to HDF-S MUSE observations

Circum-Galactic Medium surrounding galaxies has been punctually detected, but its morphology remains largely unknown. The Multi-Unit Spectroscopic Explorer (MUSE) spectro-imager provides for the first time both spectral and spatial resolution to spatially map such features. The problem lies in the statistical detection of faint spatially-extended sources in massive hyperspectral images such as provided by MUSE, and has not been previously handled. This paper presents a statistical detection method based on hypothesis testing tackling this problem. The proposed strategy is step-by-step validated over alternative ways with simulations. Then, results on MUSE observations are presented.
Nutrient limitation reduces land carbon uptake in simulations with a model of combined carbon, nitrogen and phosphorus cycling

Terrestrial carbon (C) cycle models applied for cli- mate projections simulate a strong increase in net primary productivity (NPP) due to elevated atmospheric CO2 concen- tration during the 21st century. These models usually neglect the limited availability of nitrogen (N) and phosphorus (P), nutrients that commonly limit plant growth and soil carbon turnover. To investigate how the projected C sequestration is altered when stoichiometric constraints on C cycling are considered, we incorporated a P cycle into the land surface model JSBACH (Jena Scheme for Biosphere-Atmosphere Coupling in Hamburg), which already includes representa- tions of coupled C and N cycles. The model reveals a distinct geographic pattern of P and N limitation. Under the SRES (Special Report on Emissions Scenarios) A1B scenario, the accumulated land C uptake be- tween 1860 and 2100 is 13 % (particularly at high latitudes) and 16 % (particularly at low latitudes) lower in simulations with N and P cycling, respectively, than in simulations with- out nutrient cycles. The combined effect of both nutrients re- duces land C uptake by 25 % compared to simulations with- out N or P cycling. Nutrient limitation in general may be biased by the model simplicity, but the ranking of limita- tions is robust against the parameterization and the inflex- ibility of stoichiometry. After 2100, increased temperature and high CO2 concentration cause a shift from N to P limita- tion at high latitudes, while nutrient limitation in the tropics declines. The increase in P limitation at high-latitudes is in- duced by a strong increase in NPP and the low P sorption capacity of soils, while a decline in tropical NPP due to high autotrophic respiration rates alleviates N and P limitations. The quantification of P limitation remains challenging. The poorly constrained processes of soil P sorption and biochem- ical mineralization are identified as the main uncertainties in the strength of P limitation. Even so, our findings indicate that global land C uptake in the 21st century is likely over- estimated in models that neglect P and N limitations. In the long term, insufficient P availability might become an impor- tant constraint on C cycling at high latitudes. Accordingly, we argue that the P cycle must be included in global models used for C cycle projections.
An Attentional Neural Conversation Model with Improved Specificity

In this paper we propose a neural conversation model for conducting dialogues. We demonstrate the use of this model to generate help desk responses, where users are asking questions about PC applications. Our model is distinguished by two characteristics. First, it models intention across turns with a recurrent network, and incorporates an attention model that is conditioned on the representation of intention. Secondly, it avoids generating non-specific responses by incorporating an IDF term in the objective function. The model is evaluated both as a pure generation model in which a help-desk response is generated from scratch, and as a retrieval model with performance measured using recall rates of the correct response. Experimental results indicate that the model outperforms previously proposed neural conversation architectures, and that using specificity in the objective function significantly improves performances for both generation and retrieval.
Dynamic Asset Allocation with Regime Shifts

In a dynamic context, portfolio management is a sequential process in which an investor revises his allocation periodically with respect to changing endogenous conditions and to the ongoing evolution on the financial markets. In this paper, we present a stochastic multistage optimization model for the portfolio revision problem. We consider rebalancing activities, transaction costs, stochastic volatilities and many others. Furthermore, we introduce a general framework for the generation of the asset returns. The regime switching model proposed allows to capture fat tails, contagion, decoupling, volatility clustering and many other empirical properties of asset returns. Such a true dynamic approach to portfolio management leads to undisputable advantages in practical applications.
Managing Sustainable Non-Profit Network Organizations

Government services have been privatised in Australia and many other countries, yet the transition from government ‘hierarchy’ to service delivery by non-government providers has proven to be challenging. Organizations have to deliver the same services, but they struggle to find ways to improve their performance while still conforming to government regulations. In this paper we draw upon a case study conducted within one such organization, which consists of collaborating but autonomous organizations networked together. We propose that five dualities are central to understanding the challenges to effective management of non-profit network organizations. We explain these dualities and then examine some strategies that address these difficulties and may lead to improvement of the performance of non-profit networks.
Tri-layer-cluster Generation Model for Activity Prediction

We propose a topic model capable of generating tri-layer clusters, each of which is composed of a topic layer, an activity layer and a word layer. The objective is to better predict activities involved in documents by considering general topics of the activities for clustering. The proposed model is a supervised topic model based on the Latent Dirichlet Allocation (LDA). As a follow-up study of word-pair generation LDA (wpLDA) model, the model introduces the topic-specific activity distribution as an external input, with an activity node inserted into the main generation thread. In addition, we refer to D. Ramage et al.'s one-to-one correspondence to directly learn word-activity tags. An experiment was conducted to prove the feasibility of this model. We chose ten top-listed activities from the wish clusters obtained by the previous wpLDA research, and used each as the key words to extract thirty tweets for training and five for testing, respectively, tagging the tweets with the corresponding activities. By applying the proposed model, we obtained the expected tri-layer clusters in the training phase. Then, in the testing phase, we utilized the activity-specific word distribution derived from the training results to learn the activities of the testing documents. The Stanford Classifier was put forward as the control group, and the activity prediction accuracy demonstrates that the proposed model exhibits the superiority in multi-activity prediction.
Passive frontal plane coupling in 3D walking

This paper explores the use of a single passive design to stabilize frontal plane dynamics for 3D biped walking across a range of forward velocities and/or step lengths. Particular goals are to determine if design of sagittal plane control can be done independently from design of frontal plane stabilization mechanisms, and to explore how dynamic coupling between the two planned motions affects energetic efficiency of walking. Passive dynamic walkers have long utilized curved feet for low energy frontal plane stabilization in 3D walking, with the current design practice of matching the linearized resonance of the curvature to match a particular, steady-state walking gait to achieve stable coupled limit cycle in 3D dynamics. However, practical legged walking systems should operate across a range of velocities and step widths. We examine aspects of the nonlinear dynamics that contribute to the energy efficiency and stability of the system through simulations. Specifically, we focus on the tight coupling between the frontal plane dynamics and stepping speed. We find that roll velocity is strongly coupled to the stepping speed and energy consumption. Our decoupled analysis explains some aspects of the 3D motions; however, the actual effects on cost of transport demonstrate interesting phenomena we had not anticipated. Specifically, while a general trend of increasing cost of transport for 3D vs 2D gaits with stride time does hold in our simulations, the 3D gaits sometimes require less energy than their constrained 2D counterparts, which was a surprising and encouraging result. This work provides a promising direction for the development of practical methods to utilize control designed for planar 2D walking models on more sophisticated 3D dynamic models using little or no additional active control.
From sequence to structure to literature: the protocol approach to bioinformation.

Until the recent advent of high-throughput experimental data-acquisition in biology, the computational analysis of the biological data was predominantly on an ad hoc basis--i.e., the application of a given piece of software on the biological data depended on the need of the moment. This "functional approach" often resulted in piecemeal computational analysis with large amount of intervening "dead-time". The present high-throughput availability of experimental biological data requires a more streamlined and integrated "protocol approach". In this work, we illustrate such a user-friendly protocol using a common question frequently faced by a wet-lab bench-biologist--"Now that I have a DNA or protein sequence, what can I do with it using a computer? " As phrased, this question is steeped in the functional approach. In contrast, the protocol approach would re-phrase the same question as "Now that I have a DNA or protein sequence, what can a computer do for me? " Our integrating tool can start with a sequence and build a substantial custom data-warehouse of computationally derived sequence information, structure information and relevant published literature, that is continually updated.
A set cover based algorithm for Cell Switch-Off with different cell sorting criteria

The traffic distribution in cellular networks fluctuates in both time and space. This fluctuation results in some base stations (cells) being underutilized in light traffic conditions. Despite being underutilized, these cells still consume substantial amount of their energy. One possible technique to preserve this wasted energy is implementing the Cell Switch-Off (CSO) approach. In this approach, a common practice is to switch off cells based on their current loads. However, not only the cell load affects the switch-off procedure but also the order in which the cells are switched off (cell sorting). Hence, in this paper, we investigated different cell sorting criteria. The results illustrated that more energy can be preserved when sorting cells based on the number of users they can serve compared with the case of sorting cells based on their current load. To implement the CSO approach, we proposed a centralized greedy-add algorithm devised from the well known set cover problem. Simulation results showed that our algorithm outperformed the benchmark algorithm when the number of users per cell is large. The two algorithms were compared using the Urban-Micro (UMi) evaluation scenario.
Critical Thinking in Asynchronous Online Discussions: A Systematic Review | La pensée critique dans les discussions asynchrones en ligne : examen systématique

Enhancing critical thinking is a common goal of higher education. Designing and facilitating learning environments in which critical thinking may develop is a key responsibility for instructors. In this paper, we seek to inform future research and practice by investigating instructional strategies that could be used to promote critical and reflective thinking in asynchronous online discussions. Our literature review was qualitative and systematic, and focused specifically on strategies that were effective in fully-online higher education contexts. Thematic analysis was used to synthesize the findings and conclusions from the various studies into recurrent themes and sub-themes. The results of the analysis indicated that practitioners should employ a multi-step approach to facilitating critical thinking and reflection in asynchronous online discussions. Implications for future research and practice are discussed. Améliorer la pensée critique est un objectif courant de l’éducation supérieure. Concevoir et faciliter des environnements d’apprentissage dans lesquels la pensée critique peut se développer est une responsabilité importante pour les instructeurs. Dans cet article, nous cherchons à renseigner les études et les pratiques futures en examinant les stratégies didactiques qui pourraient être utilisées pour promouvoir une pensée critique et réfléchie dans les discussions asynchrones en ligne. Notre examen des publications a été qualitatif et systématique. Il a été particulièrement axé sur les stratégies qui étaient efficaces dans les contextes d’éducation supérieure entièrement en ligne. L’analyse thématique a servi à synthétiser les résultats et les conclusions des différentes études en thèmes et thèmes sous-jacents récurrents. Les résultats de l’analyse indiquent que les intervenants devraient se servir d’une approche en plusieurs étapes pour promouvoir la pensée critique et réfléchie dans les discussions asynchrones en ligne. Une discussion de ce que cela implique pour les recherches et la mise en pratique est incluse.
Optimizing spatio-temporal filters for improving Brain-Computer Interfacing

Brain-Computer Interface (BCI) systems create a novel communication channel from the brain to an output device by bypassing conventional motor output pathways of nerves and muscles. Therefore they could provide a new communication and control option for paralyzed patients. Modern BCI technology is essentially based on techniques for the classification of single-trial brain signals. Here we present a novel technique that allows the simultaneous optimization of a spatial and a spectral filter enhancing discriminability of multi-channel EEG single-trials. The evaluation of 60 experiments involving 22 different subjects demonstrates the superiority of the proposed algorithm. Apart from the enhanced classification, the spatial and/or the spectral filter that are determined by the algorithm can also be used for further analysis of the data, e.g., for source localization of the respective brain rhythms.