Miracle-dz/UniFAR-FTUs huggingface dataset:
Information Technology Resources, Complementaries and Capabilities: Towards a Deeper Understanding of Leveraging Business Value from IT

Organisations devote substantial resources to acquire information technology (IT), and explaining the important issue of how IT can affect performance has posed a significant challenge to information system (IS) researchers. Owing to the importance of expanding our understanding on how and where IT and IT-related resources impact organisational performance, this study investigates the differential effects of IT resources and IT-related capabilities, in the presence of platform-related complementarities, on business process performance. We test these relationships empirically via a field survey of 216 firms. The findings suggest that IT resources and IT-related capabilities explain variance in performance. Of interest is the finding that IT resources and IT-related capabilities ability to explain variance in business process is further enhanced by the presence of the platform-related complementarities. Our findings are largely consistent with the resource-based and complementarity arguments of sources of IT-related business value.
24 channels colorless WDM-PON with L-band 10 Gb/s downstream and C-band 2.5 Gb/s upstream using multiple-wavelengths seeding sources based on mode-locked lasers

A novel WDM-PON delivering 10-Gb/s downstream based on L-band loss-less reflective-amplified-modulator and 2.5-Gb/s upstream based on C-band injection-locked Fabry-Perot laser is experimentally demonstrated for 24 channels over 25-km, using quantum-dash mode-locked laser-based multiple-wavelengths seeding sources.
Brain-Derived Neurotrophic Factor Plays a Critical Role in Contextual Fear Conditioning

In this study, brain-derived neurotrophic factor (BDNF) heterozygous knock-outs were tested on fear conditioning, and their wild-type littermates were used as controls. Results showed that BDNF+/- mice are impaired in contextual learning, whereas tone learning remains intact. Because BDNF is involved in synaptic transmission and contextual learning is hippocampal dependent, we hypothesized that this deficit is attributable to abnormal BDNF-modulated synaptic plasticity in the hippocampus. A “gain-of-function” experiment was performed next by infusing recombinant BDNF protein into the hippocampal formation to investigate whether this deficit can be rescued. Infusion of BDNF protein into the hippocampus appeared to partially restore contextual fear learning of BDNF+/- mice. In conclusion, the present study suggests that BDNF plays a critical role in fear conditioning. Loss of one copy of the BDNF gene leads to impairment of contextual fear learning in BDNF+/-. This deficit can be partially rescued by infusing BDNF protein into the hippocampus. Other brain regions interacting with the hippocampus in the context conditioned stimulus pathway, for example, the amygdala, may also require normal BDNF expression levels to fully rescue this impairment.
Understanding of photosynthesis concepts related to students’ age

In Croatian schools, the complex photosynthesis concept is presented several times during primary and secondary school, each time with more detail. The problems in understanding photosynthesis processes are known from many previous studies and our own research ; thus we aimed to investigate how the students’ understanding of the basic photosynthesis concepts increases during the schooling period, and is it enhanced by gradual introduction of new contents. The present study was conducted on 269 students from 6 schools and 35 students preparing to be biology teachers. To test the students’ conceptual understanding, we implemented a question about the trends of O2 and CO2 gas concentrations during the night, which was expected to lead students to a correct explanation of photosynthesis, including the issues of the plants’ respiration and the absence of photosynthesis. Students of all age groups gave mainly incomplete explanations. The best result was achieved by the youngest participants in the age of 11, who have relied on the freshly acquired and well trained, but reproductive knowledge. Older students’ answers (aged 15, 17 and 22), which include more detail about the light-dependent and light-independent reactions, suggested that they developed misconceptions such as the belief that “oxygen is produced in Calvin cycle during the night” and that “CO2 converts to O2”. Student's explanations indicate the consistency of their understanding of the process, which does not change with gradual introduction of new contents as they are older. The observed misunderstanding could be linked to the cumulative introduction of the complex theoretical contents, but excluding research- based learning, as well as to inadequate time dedicated to establishing connections between students’ pre-conceptions and novel information. Our research results might be a strong argument supporting the upcoming change in the national curriculum.
MuTT: A Multi-Threaded Tracer for Java Programs

Tracing is an important technique for program comprehension and software maintenance. Existing trace tools have some limitations, such as requiring instrumentation. This paper presents a tracer, MuTT, which can be used to collect the run-time information of multi-threaded Java programs without source code or JVM instrumentation. We also propose guidelines to use MuTT for feature location in Object-Oriented Systems, particularly in the Event-Driven Systems. We conduct two case studies and the result demonstrates that MuTT can provide effective tracing and can be used for feature location, especially with the help of GREP.
Geometrical positioning with selective hybrid RSSD/AOA weighting AML algorithm for NLOS localization

In Wireless communications, one of the main problems of uncooperative emitters localization based on Received Signal Strength (RSS) measurements is the Non-Line-of-Sight (NLOS) propagation. The weighting approach is among the important NLOS mitigation approaches whereby the system attempts to localize with both Line-of-Sight (LOS) and NLOS measurements. In the frame of uncooperative emitters and in intra cell environnement, an Approximate Maximum Likelihood (AML) based solution is proposed. This solution uses the relative RSSs observed at different locations. The proposed inta cell localization algorithm consists of a selective and hybrid AML estimator which combines the weighted ranges to the best three nodes with the angular beam seen at the serving BS. Numerical results prove that the proposed algorithm gives better performance compared to previous approaches.
From Semantic to Emotional Space

This paper proposes an effective approach to model the emotional space of words to infer their Sense Sentiment Similarity (SSS). SSS reflects the distance between the words regarding their senses and underlying sentiments. We propose a probabilistic approach that is built on a hidden emotional model in which the basic human emotions are considered as hidden. This leads to predict a vector of emotions for each sense of the words, and then to infer the sense sentiment similarity. The effectiveness of the proposed approach is investigated in two Natural Language Processing tasks: Indirect yes/no Question Answer Pairs Inference and Sentiment Orientation Prediction.
Understanding the Role of Dynamics in Brain Networks: Methods, Theory and Application

OF THE DISSERTATION Understanding the Role of Dynamics in Brain Networks: Methods, Theory and Application by MohammadMehdi Kafashan Doctor of Philosophy in Electrical Engineering Washington University in St. Louis, December 2016 Research Advisor: Professor ShiNung Ching The brain is inherently a dynamical system whose networks interact at multiple spatial and temporal scales. Understanding the functional role of these dynamic interactions is a fundamental question in neuroscience. In this research, we approach this question through the development of new methods for characterizing brain dynamics from real data and new theories for linking dynamics to function. We perform our study at two scales: macro (at the level of brain regions) and micro (at the level of individual neurons). In the first part of this dissertation, we develop methods to identify the underlying dynamics at macro-scale that govern brain networks during states of health and disease in humans. First, we establish an optimization framework to actively probe connections in brain networks when the underlying network dynamics are changing over time. Then, we extend this framework to develop a data-driven approach for analyzing neurophysiological recordings without active stimulation, to describe the spatiotemporal structure of neural activity at different timescales. The overall goal is to detect how the dynamics of brain networks may change within and between particular cognitive states. We present the efficacy of this xviii approach in characterizing spatiotemporal motifs of correlated neural activity during the transition from wakefulness to general anesthesia in functional magnetic resonance imaging (fMRI) data. Moreover, we demonstrate how such an approach can be utilized to construct an automatic classifier for detecting different levels of coma in electroencephalogram (EEG) data. In the second part, we study how ongoing function can constraint dynamics at micro-scale in recurrent neural networks, with particular application to sensory systems. Specifically, we develop theoretical conditions in a linear recurrent network in the presence of both disturbance and noise for exact and stable recovery of dynamic sparse stimuli applied to the network. We show how network dynamics can affect the decoding performance in such systems. Moreover, we formulate the problem of efficient encoding of an afferent input and its history in a nonlinear recurrent network. We show that a linear neural network architecture with a thresholding activation function is emergent if we assume that neurons optimize their activity based on a particular cost function. Such an architecture can enable the production of lightweight, history-sensitive encoding schemes.
Working with Business Patterns & Frameworks: A Case Study for Fuzzy Logic Control

Frameworks are generic applications, described by a set of abstract classes and the way instances of their subclasses collaborate. They allow a rapid development of new applications through customization. However, two main problems are related to frameworks. First, designing a framework is a highly complex, time-consuming work and secondly, understanding the overall architecture and how to use it is difficult. One way to improve this situation is to include business and design patterns in the framework’s architecture. Indeed, each pattern provides a concise and useful architectural guidance to a related problem. Moreover, the (re)use of patterns in software developments allows the integration of flexible modular adaptable well-engineered solutions at a higher level than classes. Business patterns are domain-specific patterns. Integrating these patterns into frameworks – both related to the same business – makes it possible to exploit the generic architecture of frameworks along with the high level abstractions, business knowledge and documentation of the patterns. A fuzzy logic control framework is outlined in the present paper to demonstrate the synergetic approaches of business patterns and frameworks.
Braceforce: a middleware enabling novice programmers to integrate sensing in CPS applications

Even as the use of sensor networks to support CPS applications grows, our ability to seamlessly and efficiently incorporate sensor network capabilities remains astoundingly difficult. Today, accessing remote sensing data and integrating this data into the adaptive behavior of a dynamic user-facing CPS application requires interacting with multiple sensor platform languages, data formats, and communication channels and paradigms. We present BraceForce, an open and extensible middleware that allows developers to access the myriad remote sensing capabilities inherent to cyber-physical systems using very minimal code. Further, BraceForce incorporates eventand model-driven data acquisition as firstclass concepts to provide efficient access to sensing while retaining expressiveness and flexibility for applications. This paper presents the BraceForce middleware architecture and key abstractions, describes their implementations, and provides an empirical study using BraceForce to support CPS applications.
Differential Excitability and Modulation of Striatal Medium Spiny Neuron Dendrites

The loss of striatal dopamine (DA) in Parkinson's disease (PD) models triggers a cell-type-specific reduction in the density of dendritic spines in D2 receptor-expressing striatopallidal medium spiny neurons (D2 MSNs). How the intrinsic properties of MSN dendrites, where the vast majority of DA receptors are found, contribute to this adaptation is not clear. To address this question, two-photon laser scanning microscopy (2PLSM) was performed in patch-clamped mouse MSNs identified in striatal slices by expression of green fluorescent protein (eGFP) controlled by DA receptor promoters. These studies revealed that single backpropagating action potentials (bAPs) produced more reliable elevations in cytosolic Ca2+ concentration at distal dendritic locations in D2 MSNs than at similar locations in D1 receptor-expressing striatonigral MSNs (D1 MSNs). In both cell types, the dendritic Ca2+ entry elicited by bAPs was enhanced by pharmacological blockade of Kv4, but not Kv1 K+ channels. Local application of DA depressed dendritic bAP-evoked Ca2+ transients, whereas application of ACh increased these Ca2+ transients in D2 MSNs, but not in D1 MSNs. After DA depletion, bAP-evoked Ca2+ transients were enhanced in distal dendrites and spines in D2 MSNs. Together, these results suggest that normally D2 MSN dendrites are more excitable than those of D1 MSNs and that DA depletion exaggerates this asymmetry, potentially contributing to adaptations in PD models.
ON THE ECONOMIC VALUE OF ENSEMBLE BASED WEATHER FORECASTS

The potential economic benefit associated with the use of an ensemble of forecasts vs. an equivalent or higher resolution control forecast is discussed. Neither forecast systems are postprocessed, except a simple calibration that is applied to make them reliable. A simple decision making model is used where all potential users of weather forecasts are characterized by the ratio between the cost of their action to prevent weather related damages, and the loss that they incur in case they do not protect their operations. It is shown that the ensemble forecast system can be used by a much wider range of users. Furthermore, for many, and beyond 4 days lead time for all users the ensemble provides greater potential economic benefit than a control forecast, even if the latter is run at a higher horizontal resolution. It is argued that the added benefits derive from (1) the fact that the ensemble provides a more detailed forecast probability distribution, allowing the users to tailor their weather forecast related actions to their particular cost/loss situation, and (2) the ensemble's ability to differentiate between high and low predictability cases. While single forecasts can statistically be supplemented by more detailed probability distributions, it is not clear whether with more sophisticated postprocessing they can identify more and less predictable forecast cases as successfully as ensembles do.
Random NL-Means to Restoration of Colour Images

In this paper we propose a new method of denoising of colour images. We use non local means algorithm considered on non square searching window which is driven by anisotropic stochastic process. This modification allow us to adapt the idea from famous non local means and anisotropic diffusion approaches. Experimental results show that this new method gives encouraging results and can be successfully applied to denoising of high ISO images.
Multi-band optical micro-variability observations of the BL Lac object S4 0954+658

We have observed S4 0954+658 in the B, V, R and I bands for one night in March and two nights in April, 2001, and in the B and I bands for four nights in May, 2002. The observations resulted in almost evenly sampled light curves, 3-8 h long, with an average sampling interval of ∼5-15 min. Because of the dense sampling and the availability of light curves in more than one optical band we are able to study the intra-night flux and spectral variability of the source in detail. Significant observations were observed in all but one case. On average, the flux variability amplitude, on time scales of min/h, increases from ∼2-3% in the I, to ∼3.5-5.5% in the B band light curves. We do not detect any flares within the individual light curves. However, there is a possibility that the April 2001 and late May 2002 observations sample two flares which lasted longer than ∼1-3 days. The evidence is only suggestive though, due to the limited length of the present light curves with regard to the duration of the assumed flares. No spectral variations are detected during the April 2001 observations. The source flux rises and decays with the same rate, in all bands. This variability behaviour is typical of S4 0954+658, and is attributed to geometrical effects. However, significant spectral variations are observed in May 2002. We find that the spectrum hardens/softens as the flux increases/decreases, respectively. Furthermore, the hardening rate of the energy spectrum is faster than the rate at which the spectrum becomes redder as the flux decays. We also find evidence (although of low statistical significance) that the I band variations are delayed with respect to the B band variations. If the May 2002 observations sample a flaring event, these results suggest that the variations are caused by energetic processes which are associated with the particle cooling and the source light travel time scales.
Learning From More Than One Data Source: Data Fusion Techniques for Sensorimotor Rhythm-Based Brain–Computer Interfaces

Brain-computer interfaces (BCIs) are successfully used in scientific, therapeutic and other applications. Remaining challenges are among others a low signal-to-noise ratio of neural signals, lack of robustness for decoders in the presence of inter-trial and inter-subject variability, time constraints on the calibration phase and the use of BCIs outside a controlled lab environment. Recent advances in BCI research addressed these issues by novel combinations of complementary analysis as well as recording techniques, so called hybrid BCIs. In this paper, we review a number of data fusion techniques for BCI along with hybrid methods for BCI that have recently emerged. Our focus will be on sensorimotor rhythm-based BCIs. We will give an overview of the three main lines of research in this area, integration of complementary features of neural activation, integration of multiple previous sessions and of multiple subjects, and show how these techniques can be used to enhance modern BCI systems.
Crossing the Boundaries of East and West: Texts and Their Interpretation through Bourdieu's Theory and Social Philosophy +

Explanations of difference across East and West are often over-simplified, invoking unquestioned assumptions about traditional culture and about current global geo-politics. This paper seeks alternative explanations, based upon text analysis and upon the social theory of Pierre Bourdieu. Two texts, arising out the United Nations Copenhagen climate summit (7th-18th December 2009), are chosen representing two sides of an argument about summit outcomes. These texts are analyzed using a three-dimensional model, firstly at the level of text and secondly at the level of discursive practice, through extended meanings from the text itself and then through meanings from the literature on East-West analysis. Thirdly, it is analyzed at the level of social practice, through the theory and social philosophy of Pierre Bourdieu. This identifies “East” and “West” having distinct field-habitus arrangements, but explains how differences may be viewed as “misrecognitions” and how a common logic applies across both.
Scalable Optimization Methods for Distribution Networks With High PV Integration

This paper proposes a suite of algorithms to determine the active- and reactive-power setpoints for photovoltaic (PV) inverters in distribution networks. The objective is to optimize the operation of the distribution feeder according to a variety of performance objectives and ensure voltage regulation. In general, these algorithms take a form of the widely studied ac optimal power flow (OPF) problem. For the envisioned application domain, nonlinear power-flow constraints render pertinent OPF problems nonconvex and computationally intensive for large systems. To address these concerns, we formulate a quadratic constrained quadratic program (QCQP) by leveraging a linear approximation of the algebraic power-flow equations. Furthermore, simplification from QCQP to a linearly constrained quadratic program is provided under certain conditions. The merits of the proposed approach are demonstrated with simulation results that utilize realistic PV-generation and load-profile data for illustrative distribution-system test feeders.
Relationship between force and intracellular [Ca2+] in tetanized mammalian heart muscle

To determine features of the steady state [Ca2+]-tension relationship in intact heart, we measured steady force and intracellular [Ca2+] ([Ca2+]i) in tetanized ferret papillary muscles. [Ca2+]i was estimated from the luminescence emitted by muscles that had been microinjected with aequorin, a Ca2+-sensitive, bioluminescent protein. We found that by raising extracellular [Ca2+] and/or by exposing muscles to the Ca2+ channel agonist Bay K 8644, tension development could be varied from rest to an apparently saturating level, at which increases in [Ca2+]i produced no further rise in force. 95% of maximal Ca2+-activated force was reached at a [Ca2+]i of 0.85 +/- 0.06 microM (mean +/- SEM; n = 7), which suggests that the sensitivity of the myofilaments to [Ca2+]i is far greater than anticipated from studies of skinned heart preparations (or from previous studies using Ca2+-sensitive microelectrodes in intact heart). Our finding that maximal force was reached by approximately 1 microM also allowed us to calculate that the steady state [Ca2+]i-tension relationship, as it might be observed in intact muscle, should be steep (Hill coefficient of greater than 4), which is consistent with the Hill coefficient estimated from the entire [Ca2+]i-tension relationship derived from families of variably activated tetani (6.08 +/- 0.68; n = 7). Finally, with regard to whether steady state measurements can be applied directly toward understanding physiological contractions, we found that the relation between steady force and [Ca2+]i obtained during tetani was steeper than that between peak force and peak [Ca2+]i observed during physiological twitches.
Task Ranking and Allocation Heuristics for Efficient Workflow Schedules

Task ranking and allocation are two major steps in list-based workflow scheduling. This paper explores various possibilities, evaluates recent approaches in the literature, and proposes several new task ranking and allocation heuristics. A series of simulation experiments have been conducted to evaluate the proposed heuristics. Experimental results indicate that effectiveness of task ranking and allocation heuristics largely depends on the characteristics of workflows to be scheduled, and our new scheduling heuristics can outperform previous methods when dealing with workflows of high CCR (Communication-to-Computation Ratio) values.