Miracle-dz/UniFAR-FTUs huggingface dataset:
Foreword: special issue on information systems in developing countries

The developing countries account for the majority of the world’s population, and are important for this reason alone. In addition, developing countries contain millions of people who lack access to resources such as clean water, adequate housing, and education for satisfying basic human needs. Moreover, many people in developing countries lack the freedom to make choices in their own lives (Sen 1999). These conditions present a moral issue with which we should all be concerned. A further reason to take seriously the “majority world,” from a business and policy perspective, is that the world is becoming increasingly interconnected in economic, social, and cultural terms. Whatever view one takes of trends toward globalization, global business, or global outsourcing, there is agreement that these present important issues and problems, even if one lives in the richer countries. There was at one time some debate as to whether information and communication technologies (ICTs) were relevant to the developing countries, but this debate has been resolved with a clear “yes” answer. The question has now become not whether, but how ICTs can benefit development. ICTs have high potential value across both public and private enterprises; and at multiple levels, for example from software businesses in urban areas to health delivery in rural villages. The application of ICTs to development goals has not always succeeded to date, and indeed there are many examples of partial or complete failure (e.g., Avgerou and Walsham 2000). One particular issue concerns the need to bridge the so-called “digital divide” between those people with the ability to access and use technologies effectively, and those without. The challenge remains to tackle such difficulties and to resolve them.
On the use of the unscented transform for failure prognostics

Dealing with uncertainty is of uttermost importance in the failure prognostics task. The difficulties in estimating current health state and the unknown future operational conditions are among the reasons that make this consideration so important. Random variables (RV) are the most usual way to represent such uncertainty. In the case of health state of a monitored system, or its trend, one usual way of propagating the uncertainty into the estimate of the remaining useful life (RUL) is based on Monte Carlo (MC) simulations. Despite being adequate for this task, MC simulations present some drawbacks: the calculations are computationally intensive and there is no consistent way of defining an adequate number of samples to simulate. This paper presents and evaluates alternative means to perform this task using the unscented transform (UT). The UT is a method that yields the probability distribution of a RV which results from a nonlinear transformation of another RV. If the latter is associated with the current health state of a monitored system, or its trend, and the former represents the RUL, the UT can be applied for failure prognostics. The advantages of using such approach are the necessity of a much smaller number of samples compared to MC and the straightforward definition of this number. This work presents novel applications of the UT for prognostics and performance evaluations that indicate the adequacy of this approach.1 2
Real-Time Frame-Layer H.264 Rate Control for Scene-Transition Video at Low Bit Rate

An abrupt scene-transition frame is one that is hardly correlated with the previous frames. In that case, because an intra-coded frame has less distortion than an inter-coded one, almost all macroblocks are encoded in intra mode. This breaks up the rate control flow and increases the number of bits used. Since the reference software for H.264 takes no special action for a scene-transition frame, several studies have been conducted to solve the problem using the quadratic R-D model. However, since this model is more suitable for inter frames, they are unsuitable for computing the QP of the scene-transition intra frame. In this paper, a modified algorithm for detecting scene transitions is presented, and a real-time rate control scheme accounting for the characteristics of intra coding is proposed for scene- transition frames. The proposed scheme was validated using 16 test sequences. The results showed that the proposed scheme performed better than the existing H.264 rate control schemes. The PSNR was improved by an average of 0.4-0.6 dB and a maximum of 1.1-1.6 dB. The PSNR fluctuation was also improved by an average of 18.6 %. 1
Aerosol-Cloud interactions : a new perspective in precipitation enhancement

Increased industrialization and human activity modified the atmospheric aerosol composition and size-distribution during the last several decades. This has affected the structure and evolution of clouds, and precipitation from them. The processes and mechanisms by which clouds and precipitation are modified by changes in aerosol composition and size-distribution are very intricate. The objective of this thesis is to improve the understanding of the processes and mechanisms through which the changes in aerosol concentrations impact the evolution of deep convective clouds and precipitation formation. We develop a new coupled model in which a very detailed model of aerosol activation is coupled to a three-dimensional cloud resolving model. This coupled model can accurately represent different kinds of aerosol populations. This coupled model is used to investigate the impact of changing aerosol concentrations on the dynamics, microphysical evolution and precipitation formation in deep convective clouds. We examine the theories of aerosol activation, and the representation of aerosol activation in cloud models. The limitations of the extant methods of representation of aerosol activation in cloud models are evaluated. Then we descibe the components of the coupled model - Modified Eulerian and Lagrangian Aerosol Model (MELAM) and the Cloud Resolving Model (CRM). The features of these two component models with respect to aersol activation and cloud formation are discussed. The evaluation of the coupled model by simulation of a deep convertive event observed during the INDian Ocean EXperiment (INDOEX) by statistcal comparison of observed and simulated cloud fields shows that the coupled model can simulate deep convective events reasonably well. We present a study of the senstivity of the model to initial thermodynamic conditions (CAPE). Different initial thermodynamic conditons sampled during the INDOEX are used to initialize the coupled model and, the structure and evolution of the deep convective event are discussed. The study sheds new light on the respone of deep convection to CAPE. It is found that when the atmosphere has moderate CAPE, the precipitation forming processes are very active and when the CAPE is (cont.) low or high, they are comparatively less efficient. ; As the most important part of our study, we examine the response of deep convection to changing initial aerosol concentration. Different aerosol concentrations from those representing pristine to polluted atmospheres are considered. We look at the buoyancy of the cloud and the microphysical evolution. It is found that the dynamics and microphysics are tightly coupled and we infer that to understand aerosol-cloud interactions in deep convective clouds, both - dynamics and microphysics - and their interaction have to be taken into consideration. Our results show that the response of a deep convective cloud to changing aerosol concentration is very different from the much well understood reponse of shallow clouds or small cumulus clouds. In general, increase…
Distinct cerebellar engrams in short-term and long-term motor learning

Significance Long-term depression (LTD) of parallel fiber (PF) to Purkinje cell (PC) synapses has been postulated to cause cerebellar motor learning and extensively studied using in vitro preparations. However, there has been no in vivo evidence showing its occurrence after physiological learning, and much controversy on its role has persisted. We demonstrate that LTD as a form of AMPA receptor decrease does occur in PF–PC synapses after adaptation of horizontal optokinetic response. However, it lasted less than a day and was followed by elimination of these synapses. Our findings indicate distinct in vivo engrams for short-term and long-term memory in cerebellar motor learning, and open new mechanistic investigations of how the short-term memory is stabilized through structural reorganization of synaptic connections. Cerebellar motor learning is suggested to be caused by long-term plasticity of excitatory parallel fiber-Purkinje cell (PF–PC) synapses associated with changes in the number of synaptic AMPA-type glutamate receptors (AMPARs). However, whether the AMPARs decrease or increase in individual PF–PC synapses occurs in physiological motor learning and accounts for memory that lasts over days remains elusive. We combined quantitative SDS-digested freeze-fracture replica labeling for AMPAR and physical dissector electron microscopy with a simple model of cerebellar motor learning, adaptation of horizontal optokinetic response (HOKR) in mouse. After 1-h training of HOKR, short-term adaptation (STA) was accompanied with transient decrease in AMPARs by 28% in target PF–PC synapses. STA was well correlated with AMPAR decrease in individual animals and both STA and AMPAR decrease recovered to basal levels within 24 h. Surprisingly, long-term adaptation (LTA) after five consecutive daily trainings of 1-h HOKR did not alter the number of AMPARs in PF–PC synapses but caused gradual and persistent synapse elimination by 45%, with corresponding PC spine loss by the fifth training day. Furthermore, recovery of LTA after 2 wk was well correlated with increase of PF–PC synapses to the control level. Our findings indicate that the AMPARs decrease in PF–PC synapses and the elimination of these synapses are in vivo engrams in short- and long-term motor learning, respectively, showing a unique type of synaptic plasticity that may contribute to memory consolidation.
The Neurophysiological Correlates of Choice on Engagement, Motivation, and Motor Skill Learning

ii Acknowledgments . iv List of Tables . ix List of Figures . x List of Abbreviations . xi Chapter 1 . 1 General Introduction and Applied Impacts . 1 Motivation . 2 Intrinsic motivation and learning . 3 Autonomy and learning . 4 Engagement . 5 Engagement and learning . 5 The Relationship Between Intrinsic Motivation and Engagement . 7 Summary of Experiments . 8 Chapter 2 . 10 Experiment 1 . 10 Methods. 13 Participants . 13 Game apparatus . 14
Chariots: A Scalable Shared Log for Data Management in Multi-Datacenter Cloud Environments

Web-based applications face unprecedented workloads demanding the processing of a large number of events reaching to the millions per second. That is why developers are increasingly relying on scalable cloud platforms to implement cloud applications. Chariots exposes a shared log to be used by cloud applications. The log is essential for many tasks like bookkeeping, recovery, and debugging. Logs offer linearizability and simple append and read operations of immutable records to facilitate building complex systems like stream processors and transaction managers. As a cloud platform, Chariots offers fault-tolerance, persistence, and high-availability, transparently. Current shared log infrastructures suffer from the bottleneck of serializing log records through a centralized server which limits the throughput to that of a single machine. We propose a novel distributed log store, called the Fractal Log Store (FLStore), that overcomes the bottleneck of a single-point of contention. FLStore maintains the log within the datacenter. We also propose Chariots, which provides multi-datacenter replication for shared logs. In it, FLStore is leveraged as the log store. Chariots maintains causal ordering of records in the log and has a scalable design that allows elastic expansion of resources.
Perturbation Predictability Can Influence the Long-Latency Stretch Response

Perturbations applied to the upper limbs elicit short (M1: 25–50 ms) and long-latency (M2: 50–100 ms) responses in the stretched muscle. M1 is produced by a spinal reflex loop, and M2 receives contribution from multiple spinal and supra-spinal pathways. While M1 is relatively immutable to voluntary intention, the remarkable feature of M2 is that its size can change based on intention or goal of the participant (e.g., increasing when resisting the perturbation and decreasing when asked to let-go or relax following the perturbation). While many studies have examined modulation of M2 between passive and various active conditions, through the use of constant foreperiods (interval between warning signal and a perturbation), it has also been shown that the magnitude of the M2 response in a passive condition can change based on factors such as habituation and anticipation of perturbation delivery. To prevent anticipation of a perturbation, most studies have used variable foreperiods; however, the range of possible foreperiod duration differs between experiments. The present study examined the influence of different variable foreperiods on modulation of the M2 response. Fifteen participants performed active and passive responses to a perturbation that stretched wrist flexors. Each block of trials had either a short (2.5–3.5 seconds; high predictability) or long (2.5–10.5 seconds; low predictability) variable foreperiod. As expected, no differences were found between any conditions for M1, while M2 was larger in the active rather than passive conditions. Interestingly, within the two passive conditions, the long variable foreperiods resulted in greater activity at the end of the M2 response than the trials with short foreperiods. These results suggest that perturbation predictability, even when using a variable foreperiod, can influence circuitry contributing to the long-latency stretch response.
Behavioral/systems/cognitive Functional Imaging Reveals Visual Modulation of Specific Fields in Auditory Cortex

Merging the information from different senses is essential for successful interaction with real-life situations. Indeed, sensory integration can reduce perceptual ambiguity, speed reactions, or change the qualitative sensory experience. It is widely held that integration occurs at later processing stages and mostly in higher association cortices; however, recent studies suggest that sensory convergence can occur in primary sensory cortex. A good model for early convergence proved to be the auditory cortex, which can be modulated by visual and tactile stimulation; however, given the large number and small size of auditory fields, neither human imaging nor microelectrode recordings have systematically identified which fields are susceptible to multisensory influences. To reconcile findings from human imaging with anatomical knowledge from nonhuman primates, we exploited high-resolution imaging (functional magnetic resonance imaging) of the macaque monkey to study the modulation of auditory processing by visual stimulation. Using a functional parcellation of auditory cortex, we localized modulations to individual fields. Our results demonstrate that both primary (core) and nonprimary (belt) auditory fields can be activated by the mere presentation of visual scenes. Audiovisual convergence was restricted to caudal fields [prominently the core field (primary auditory cortex) and belt fields (caudomedial field, caudolateral field, and mediomedial field)] and continued in the auditory parabelt and the superior temporal sulcus. The same fields exhibited enhancement of auditory activation by visual stimulation and showed stronger enhancement for less effective stimuli, two characteristics of sensory integration. Together, these findings reveal multisensory modulation of auditory processing prominently in caudal fields but also at the lowest stages of auditory cortical processing.
Enterprise Risk Management: From Incentives to Controls

Preface. Acknowledgments. SECTION I. RISK MANAGEMENT IN CONTEXT. Chapter 1. Introduction. Chapter 2. Lessons Learned. Chapter 3. Concepts and Processes. SECTION II. THE ENTERPRISE RISK MANAGEMENT FRAMEWORK. Chapter 4. What Is Enterprise Risk Management? Chapter 5. Corporate Governance. Chapter 6. Line Management. Chapter 7. Portfolio Management. Chapter 8. Risk Transfer. Chapter 9. Risk Analytics. Chapter 10. Data and Technology. Chapter 11. Stakeholder Management. SECTION III. RISK MANAGEMENT APPLICATIONS. Chapter 12. Credit Risk Management. Chapter 13. Market Risk Management. Chapter 14. Operational Risk Management. Chapter 15. Business Applications. Chapter 16. Financial Institutions. Chapter 17. Energy Firms. Chapter 18. Nonfinancial Corporations. SECTION IV. A LOOK TO THE FUTURE. Chapter 19. Predictions. Chapter 20. Everlast Financial. Index.
Clinical monitoring using otoacoustic emissions.

Damaging influences to the cochlea are a leading cause of sensorineural hearing loss. Examples include acute or chronic noise exposure and cochleotoxic drugs such as aminoglycosides. Typically, once damage has occurred, the cochlea cannot recover. Therefore, prevention is critical. If damaging influences cannot be avoided, then secondary prevention or early detection of cochlear hearing loss becomes important. Ideally, methods for the detection of cochlear damage should be as specific and as sensitive as possible. Otoacoustic emissions satisfy these criteria and offer a means of testing aspects of cochlear function in a non-invasive and objective way. Evoked otoacoustic emissions measured either after transient stimuli or during two-tone stimulation (distortion-product otoacoustic emissions) are the types most commonly used for clinical purposes. They are stable over time within individual ears and their repeatability has been established under conditions of clinical testing using commercial equipment. Thus, they are well suited as an effective means of monitoring subtle changes in cochlear status. The possibility of making non-invasive repeated measures of cochlear function has led to the widespread use of otoacoustic emissions in animal experiments. Influences of development, anoxia, anaesthesia, noise, and drugs have been monitored. Preliminary studies in humans demonstrate that cochlear damage due to ototoxic drugs such as aminoglycosides or cisplatin and due to noise exposure can be detected using otoacoustic emissions. Comparison of such results to those available using pure-tone audiometry indicates a greater sensitivity of otoacoustic emissions for detecting early cochlear damage. (ABSTRACT TRUNCATED AT 250 WORDS)
Taxonomic sampling, phylogenetic accuracy, and investigator bias.

These recommendations, taken at face val? ue, appear to be in direct conflict with re? gard to advice on taxon sampling. The pa? pers in this issue extend these studies and modify these recommendations on the ba? sis of analyses of real data sets (Soltis et al., 1998; Poe, 1998), simulations (Graybeal, 1998), and theoretical considerations (Kim, 1998). One conclusion from reading these papers is that whether increased taxonom? ic sampling helps or hinders the process of accurate phylogenetic estimation depends to a great extent on how accuracy is eval? uated and what is meant by "taxonomic sampling. "
Sea Level Change Through the Last Glacial Cycle

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Cyclic spectrum reconstruction from sub-Nyquist samples

Communication signals are often cyclostationary, that is they have statistical characteristics that vary periodically in time. In the frequency domain, this translates into correlation between spectral components of the signal. As a result, the cyclic spectrum, a characteristic function of the second-order moment of such signals, exhibits spectral peaks at certain locations, called cyclic frequencies. Exploiting the cyclostationarity of communication signals allows to better model them and describe their properties. Moreover, it improves robustness to noise when processing such signals. The traditional signal processing task of spectrum sensing has been recently challenged by Cognitive Radios (CRs) into dealing with wideband signals in an efficient and reliable way. CR receivers deal with signals with high Nyquist rates and low Signal to Noise Ratios (SNRs). On the one hand, sub-Nyquist sampling of such signals alleviates the burden both on the analog and the digital side. On the other hand, it increases the sensitivity to noise due to its aliasing. In this paper, we derive a method to reconstruct the cyclic spectrum of cyclostationary signals from sub-Nyquist samples rather than their spectrum or power spectrum, in order to better deal with noise. Any processing such as signal detection can then be performed on the reconstructed cyclic spectrum.