Miracle-dz/UniFAR-FTUs huggingface dataset:
Free Riding on Gnutella

An extensive analysis of user traffic on Gnutella shows a significant amount of free riding in the system. By sampling messages on the Gnutella network over a 24-hour period, we established that almost 70% of Gnutella users share no files, and nearly 50% of all responses are returned by the top 1% of sharing hosts. Furthermore, we found out that free riding is distributed evenly between domains, so that no one group contributes significantly more than others, and that peers that volunteer to share files are not necessarily those who have desirable ones. We argue that free riding leads to degradation of the system performance and adds vulnerability to the system. If this trend continues copyright issues might become moot compared to the possible collapse of such systems.
Intellectual capital and the capital market: the circulability of intellectual capital

This paper argues that intellectual capital and intangible assets are difficult resources for two different reasons. First, intellectual capital and intangibles assets are not (yet) disentangled by the institutions of the capital markets, and therefore they are not (yet) translatable with any degree of confidence into predictions about stock price behaviour. Second, intellectual capital and intangibles are not absent from capital market intelligence; they are just typically translated into financial form, when they are presented to actors in the capital markets, even if in forms that are themselves “invisible”. The capital market may have limited understanding of intellectual capital, but it is also always seeking to understand the complexity of business and (im)possible futures. Its appreciation of intellectual capital is therefore fragile.
Predicting Home and Work Locations Using Public Transport Smart Card Data by Spectral Analysis

Knowledge of home and work locations of population is essential for transport planning and urban development. We present a method to predict and validate home and work locations of commuters using their public transport smart card data. Existing works rely on statistical techniques to interpret public transport transactions. Our method goes one step further by exploring the underlying repeated travelling patterns between home and work place. It first uses several features extracted from a card holder's ride records (i.e., the length of time that he/she stays at a location, the times he/she visits a place, etc.) to evaluate the likelihood of a location is associated with the card holder's home/work places. Rank aggregation technique is then applied to derive a comprehensive location ranking list. A few top ranked locations are picked out for further analysis, where the travel records between any two of them are arranged as a time series. Spectral analysis is applied on the time series in attempt to identify periodic travelling patterns. The most likely home/work pair is selected based on a proper period and dominant frequency which implies regular travelling activities between the card holder's home and work place. Finally, home and work locations are discriminated based on the assumption that a person goes to his/her work place mostly on weekdays and rarely on weekends. We apply our method on a three-month Singapore smart card dataset and evaluate the result against a ground truth obtained from Singapore urban planning programme. Validation results show that the proposed method is able to predict meaningful home and work places.
High speed and highly efficient S-band 20 W mixerless vector power modulator

This paper presents a performance evaluation of an original highly efficient and linear GaN-HEMT Vector Power Modulator (VPM) based on the design of a two-stage saturated variable gain (SVG) amplifier and a multi-level discrete supply modulator (SM). The proposed novel architecture for transforming a digital baseband data stream into an RF Vector modulated power waveform (RF Power DAC) is validated using a specific laboratory test bench. The main objective of this study is to merge signal modulation and DC to RF energy conversion functions into a single and compact GaN based mixer-less circuit. Using high-voltage 50 V GaN technology, a 20 W S-band vector power modulator having overall average PAE of around 40 % is reported. The concept demonstrator is experimentally validated up to 100 Msymbols/sec 16-QAM modulation scheme. Functional time alignment with phase and amplitude compensation procedure focusing on measured constellation at 40 Msymbols/sec enables to reach excellent EVM performances of around 3.2 %.
Dynamic properties of the lamprey's neuronal circuits as it drives a two-wheeled robot

In order to study the neurobiological mechanisms of learning, we developed a research tool that includes the brainstem of a lamprey and a two-wheeled robot interconnected in a closed loop. Two electrodes applied stimulations to the neural tissue. The stimulation frequency was set to be proportional to the light intensity measured by sensors on the right and left sides of the mobile robot. The velocity commands to the right and left wheels were proportional to the population spike rates recorded by two recording electrodes. In most cases, the robot moved approximately in the direction of the source of light. We fitted ten two-input/two-output neural network models and observed the generalization error of each model. We found that a dynamic model was significantly superior to a static model even when the number of parameters was smaller. Additional findings led us to conclude that the main origin of this dynamic behavior is local ipsilateral influence of the previous state on the current state. An analysis of the model that fits adaptive behavior of the preparation showed a significant change in one of the recurrent connections. We discuss these results in the context of possible cellular mechanisms that might explain the behavior of this neuro-robotic preparation.
Influence of the segmentation on the characterization of cerebral networks of structural damage for patients with disorders of consciousness

Disorders of consciousness (DOC) are a consequence of a variety of severe brain injuries. DOC commonly results in anatomical brain modifications, which can affect cortical and sub-cortical brain structures. Postmortem studies suggest that severity of brain damage correlates with level of impairment in DOC. In-vivo studies in neuroimaging mainly focus in alterations on single structures. Recent evidence suggests that rather than one, multiple brain regions can be simultaneously affected by this condition. In other words, DOC may be linked to an underlying cerebral network of structural damage. Recently, geometrical spatial relationships among key sub-cortical brain regions, such as left and right thalamus and brain stem, have been used for the characterization of this network. This approach is strongly supported on automatic segmentation processes, which aim to extract regions of interests without human intervention. Nevertheless, patients with DOC usually present massive structural brain changes. Therefore, segmentation methods may highly influence the characterization of the underlying cerebral network structure. In this work, we evaluate the level of characterization obtained by using the spatial relationships as descriptor of a sub-cortical cerebral network (left and right thalamus) in patients with DOC, when different segmentation approaches are used (FSL, Free-surfer and manual segmentation). Our results suggest that segmentation process may play a critical role for the construction of robust and reliable structural characterization of DOC conditions.
Barium ions selectively activate BK channels via the Ca2+-bowl site

Activation of Ca2+-dependent BK channels is increased via binding of micromolar Ca2+ to two distinct high-affinity sites per BK α-subunit. One site, termed the Ca2+ bowl, is embedded within the second RCK domain (RCK2; regulator of conductance for potassium) of each α-subunit, while oxygen-containing residues in the first RCK domain (RCK1) have been linked to a separate Ca2+ ligation site. Although both sites are activated by Ca2+ and Sr2+, Cd2+ selectively favors activation via the RCK1 site. Divalent cations of larger ionic radius than Sr2+ are thought to be ineffective at activating BK channels. Here we show that Ba2+, better known as a blocker of K+ channels, activates BK channels and that this effect arises exclusively from binding at the Ca2+-bowl site. Compared with previous estimates for Ca2+ bowl–mediated activation by Ca2+, the affinity of Ba2+ to the Ca2+ bowl is reduced about fivefold, and coupling of binding to activation is reduced from ∼3.6 for Ca2+ to about ∼2.8 for Ba2+. These results support the idea that ionic radius is an important determinant of selectivity differences among different divalent cations observed for each Ca2+-binding site.
Neurosystems: brain rhythms and cognitive processing

Neuronal rhythms are ubiquitous features of brain dynamics, and are highly correlated with cognitive processing. However, the relationship between the physiological mechanisms producing these rhythms and the functions associated with the rhythms remains mysterious. This article investigates the contributions of rhythms to basic cognitive computations (such as filtering signals by coherence and/or frequency) and to major cognitive functions (such as attention and multi‐modal coordination). We offer support to the premise that the physiology underlying brain rhythms plays an essential role in how these rhythms facilitate some cognitive operations.
Designing Animal Habitats Within an Immersive VE

The authors present an immersive design application for educational use that takes a different approach. First, they focus on the small, highly specific domain of animal habitat design. Second, the system's users don't have a blank slate-they begin with an existing design. Finally, the design tools don't allow general manipulation of all design features. Instead, they're task-specific and well constrained.
O6-Methylguanine-DNA Methyltransferase in Tumors and Cells of the Oligodendrocyte Lineage

Abstract Background: Oligodendrogliomas respond to nitrosourea-based chemotherapy and are induced in rats following transplacental exposure to ethylnitrosourea, observations suggesting that neoplastic and normal cells of the oligodendrocyte lineage are “sensitive” to nitrosoureas. Nitrosoureas alkylate DNA at O6-guanine with repair mediated by O6-methyIguanine-DNA methyltransferase (MGMT). The cytotoxic and carcinogenic properties of the nitrosoureas appear related to MGMT activity. Methods: To explore why oligodendrogliomas respond to chemotherapy, we measured MGMT activity in five chemosensitive human oligodendrogliomas and in rat oligodendrocyte lineage cells. We also measured MGMT activity in rat astrocytes and compared the cytotoxic effects of carmustine (BCNU) on oligodendrocyte lineage cells and astrocytes. Results: Low levels of MGMT activity were found in five of five human oligodendrogliomas. Cultures of neonatal rat glia enriched for oligodendrocyte lineage cells also had low levels of MGMT activity, approximately one-third that found in astrocytes (p < 0.02), and oligodendrocyte lineage cells were more sensitive to BCNU than astrocytes. Conclusions: Low MGMT activity may contribute to the chemosensitivity of some human oligodendrogliomas and rat oligodendrocyte lineage cells also have low levels. If drug resistance mechanisms in tumors reflect the biochemical properties of their cells of origin, then normal glia may serve as a laboratory substitute for human glioma.
Recollection reduces unitised familiarity effect

Two types of encoding tasks have been employed in previous research to investigate the beneficial effect of unitisation on familiarity-based associative recognition (unitised familiarity effect), namely the compound task and the interactive imagery task. Here we show how these two tasks could differentially engage subsequent recollection-based associative recognition and consequently lead to the turn-on or turn-off of the unitised familiarity effect. In the compound task, participants studied unrelated word pairs as newly learned compounds. In the interactive imagery task, participants studied the same word pairs as interactive images. An associative recognition task was used in combination with the Remember/Know procedure to measure recollection-based and familiarity-based associative recognition. The results showed that the unitised familiarity effect was present in the compound task but was absent in the interactive imagery task. A comparison of the compound and the interactive imagery task revealed a dramatic increase in recollection-based associative recognition for the interactive imagery task. These results suggest that unitisation could benefit familiarity-based associative recognition; however, this effect will be eliminated when the memory trace formed is easily accessed by strong recollection without the need for a familiarity assessment.
Matchings vs hitting sets among half-spaces in low dimensional euclidean spaces

Let $\mathcal{F}$ be any collection of linearly separable sets of a set $P$ of $n$ points either in $\mathbb{R}^2$, or in $\mathbb{R}^3$. We show that for every natural number $k$ either one can find $k$ pairwise disjoint sets in $\mathcal{F}$, or there are $O(k)$ points in $P$ that together hit all sets in $\mathcal{F}$. The proof is based on showing a similar result for families $\mathcal{F}$ of sets separable by pseudo-discs in $\mathbb{R}^2$. We complement these statements by showing that analogous result fails to hold for collections of linearly separable sets in $\mathbb{R}^4$ and higher dimensional euclidean spaces.
Implementing and Evaluating a Wireless Body Sensor System for Automated Physiological Data Acquisition at Home

Advances in embedded devices and wireless sensor networks have resulted in new and inexpensive health care solutions. This paper describes the implementation and the evaluation of a wireless body sensor system that monitors human physiological data at home. Specifically, a waist-mounted triaxial accelerometer unit is used to record human movements. Sampled data are transmitted using an IEEE 802.15. 4 wireless transceiver to a data logger unit. The wearable sensor unit is light, small, and consumes low energy, which allows for inexpensive and unobtrusive monitoring during normal daily activities at home. The acceleration measurement tests show that it is possible to classify different human motion through the acceleration reading. The 802.15. 4 wireless signal quality is also tested in typical home scenarios. Measurement results show that even with interference from nearby IEEE 802.11 signals and microwave ovens, the data delivery performance is satisfactory and can be improved by selecting an appropriate channel. Moreover, we found that the wireless signal can be attenuated by housing materials, home appliances, and even plants. Therefore, the deployment of wireless body sensor systems at home needs to take all these factors into consideration.
Fluorescent sensors based on bacterial fusion proteins

Fluorescence proteins are widely used as markers for biomedical and technological purposes. Therefore, the aim of this project was to create a fluorescent sensor, based in the green and cyan fluorescent protein, using bacterial S-layers proteins as scaffold for the fluorescent tag. We report the cloning, expression and purification of three S-layer fluorescent proteins: SgsE-EGFP, SgsE-ECFP and SgsE-13aa-ECFP, this last containing a 13-amino acid rigid linker. The pH dependence of the fluorescence intensity of the S-layer fusion proteins, monitored by fluorescence spectroscopy, showed that the ECFP tag was more stable than EGFP. Furthermore, the fluorescent fusion proteins were reassembled on silica particles modified with cationic and anionic polyelectrolytes. Zeta potential measurements confirmed the particle coatings and indicated their colloidal stability. Flow cytometry and fluorescence microscopy showed that the fluorescence of the fusion proteins was pH dependent and sensitive to the underlying polyelectrolyte coating. This might suggest that the fluorescent tag is not completely exposed to the bulk media as an independent moiety. Finally, it was found out that viscosity enhanced the fluorescence intensity of the three fluorescent S-layer proteins.
Evaluating Information Dispersal Algorithms

The explosion in data acquisition and storage has led to the emergence of data-intensive applications that are used to process enormous quantity of information using methods such as the MapReduce paradigm. Data-Intensive Distributed File Systems (DI-DFS) have been designed to support these kinds of applications. These large-scale storage systems require faulttolerance mechanisms to handle failures, which are a norm rather than an exception when working at a scale that will shortly reach exascale. A new trend among large-scale systems is the implementation of information dispersal algorithms, called erasure codes. The overhead introduced by the encoding and decoding can be a limiting factor for the integration at large-scale. This work compares two different approaches of erasure code computing on GPU and CPU. Our work in erasure coding serves as the foundation for the next step: integrating an information dispersal algorithm that eventually outperforms current state-ofthe-art approaches in DI-DFSs.
Image parsing with a wide range of classes and scene-level context

This paper presents a nonparametric scene parsing approach that improves the overall accuracy, as well as the coverage of foreground classes in scene images. We first improve the label likelihood estimates at superpixels by merging likelihood scores from different probabilistic classifiers. This boosts the classification performance and enriches the representation of less-represented classes. Our second contribution consists of incorporating semantic context in the parsing process through global label costs. Our method does not rely on image retrieval sets but rather assigns a global likelihood estimate to each label, which is plugged into the overall energy function. We evaluate our system on two large-scale datasets, SIFTflow and LMSun. We achieve state-of-the-art performance on the SIFTflow dataset and near-record results on LMSun.
The Past Recaptured: Mongin on the Problem of Realism in Economics

Philippe Mongin’s ’Le r6alisme des hypotheses et la Partial Interpretation View’1 is a learned recapitulation of the successive strategies philosophers have employed in order to understand the character of scientific theorizing. As he notes, economists have exploited these strategies in order to deal with the apparent problem that their theory shows little of what we would ordinarily expect by way of explanatory and predictive improvement. Though he begins with Friedman’s famous approach to this problem,’ he notes (pp. 282-83) that Friedman’s question about the realism of hypotheses is a broader one, which touches on theorizing in all the sciences. Thus, his discussion does not consist in another examination of the detailed argumentation of this paper. Rather, he approaches the general question of the role of theoretical idealizations through an examination of standard ’moves’ in the philosophy of science over the last sixty years or so. Mongin’s solution to the problem of idealization in scientific theorizing is a pretty sensible one. But it has the vices of its virtue. Because his conclusions do not address the special problems of economic theorizing, they only recapitulate the traditional discussion of this problem, without advancing on it. Mongin notes that on the most natural reading of the ’assumptions of economic theory’, claims like ’consumers maximize utility’, ’producers maximize profit’, such statements are false. In order to make any use of them in explaining and predicting economic phenomenon, they must be interpreted in such a way as to restrict their domains. But these restrictions must satisfy reasonable constraints on empirical content and testability. One proposed constraint is that the domains to which they are applied must be independently identified; in Mongin’s s
Doppler radar vital signs monitoring using wavelet transform

An algorithm using wavelets is used to detect heartbeat rate from a phase modulated Doppler radar signal. It is shown that the heartbeat rate can be detected up to 1.5m from the radar in a noisy environment without the need of filtering. Also the property of wavelet transform to preserve both time and frequency information is utilized to analyze the phase modulated Doppler radar signal giving information about changes in heart beat over very small intervals of time.
Robustness analyses for repeated mobility surveys in outdoor advertising

A growing number of companies use mobility data in their day-to-day business. However, as the data grows older, new data has to be collected in order to keep applications up-to-date. Consequently, it is of great importance to know the impact that a different mobility sample may cause. This aspect of analysis has been largely neglected in mobility data mining research so far. In this paper we therefore analyze the robustness of performance measures with respect to a changed GPS sample in outdoor advertisement. The evaluation of outdoor advertising campaigns is a challenging application because it requires the evaluation of mobility data on a very fine spatial level. Thus, the application has a higher dependency on routes of individual test persons than classical mobility surveys. In our robustness analysis we apply bootstrapping and subsampling in order to measure the effect of a) a repeated mobility survey and b) a mobility survey of smaller size. We conduct our experiments on a real-world data set from Swiss outdoor advertising. Our results show that the effect is comparably small for a typical campaign and may be mitigated further by increasing the campaign size.
Specific Rab GTPase-activating proteins define the Shiga toxin and epidermal growth factor uptake pathways

Rab family guanosine triphosphatases (GTPases) together with their regulators define specific pathways of membrane traffic within eukaryotic cells. In this study, we have investigated which Rab GTPase-activating proteins (GAPs) can interfere with the trafficking of Shiga toxin from the cell surface to the Golgi apparatus and studied transport of the epidermal growth factor (EGF) from the cell surface to endosomes. This screen identifies 6 (EVI5, RN-tre/USP6NL, TBC1D10A–C, and TBC1D17) of 39 predicted human Rab GAPs as specific regulators of Shiga toxin but not EGF uptake. We show that Rab43 is the target of RN-tre and is required for Shiga toxin uptake. In contrast, RabGAP-5, a Rab5 GAP, was unique among the GAPs tested and reduced the uptake of EGF but not Shiga toxin. These results suggest that Shiga toxin trafficking to the Golgi is a multistep process controlled by several Rab GAPs and their target Rabs and that this process is discrete from ligand-induced EGF receptor trafficking.