Miracle-dz/UniFAR-FTUs huggingface dataset:
Preliminary Pioneer 10 Encounter Results from the Ames Research Center Plasma Analyzer Experiment

Preliminary results from the Ames Research Center plasma analyzer experiment for the Pioneer 10 Jupiter encounter indicate that Jupiter has a detached bow shock and magnetopause similar to the case at Earth but much larger in spatial extent. In contrast to Earth, Jupiter's outer magnetosphere appears to be highly inflated by thermal plasma and therefore highly responsive in size to changes in solar wind dynamic pressure.
Performance analysis of beacon-enabled IEEE 802.15.4 MAC for emergency response applications

IEEE 802.15. 4 standard provides a viable MAC and PHY specification for wireless sensor networks. Performance evaluation of these networks has been reported in literature. Previous works focus largely on analyzing the CSMA/CA traffic and frame delay due to Guaranteed Time Slots (GTS) allocations. In this work, we propose a analytical model to understand and characterize the performance of GTS traffic in IEEE 802.15. 4 networks for emergency response situations.We study two crucial performance metrics, latency and frame drop rate, for GTS frames. The results from our analysis closely match with those from simulations of IEEE 802.15. 4 MAC reported earlier.
Microbial Diversity and Cyanobacterial Production in Dziani Dzaha Crater Lake, a Unique Tropical Thalassohaline Environment

This study describes, for the first time, the water chemistry and microbial diversity in Dziani Dzaha, a tropical crater lake located on Mayotte Island (Comoros archipelago, Western Indian Ocean). The lake water had a high level of dissolved matter and high alkalinity (10.6–14.5 g L-1 eq. CO32-, i.e. 160–220 mM compare to around 2–2.5 in seawater), with salinity up to 52 psu, 1.5 higher than seawater. Hierarchical clustering discriminated Dziani Dzaha water from other alkaline, saline lakes, highlighting its thalassohaline nature. The phytoplankton biomass was very high, with a total chlorophyll a concentration of 524 to 875 μg chl a L-1 depending on the survey, homogeneously distributed from surface to bottom (4 m). Throughout the whole water column the photosynthetic biomass was dominated (>97% of total biovolume) by the filamentous cyanobacteria Arthrospira sp. with a straight morphotype. In situ daily photosynthetic oxygen production ranged from 17.3 to 22.2 g O2 m-2 d-1, consistent with experimental production / irradiance measurements and modeling. Heterotrophic bacterioplankton was extremely abundant, with cell densities up to 1.5 108 cells mL-1 in the whole water column. Isolation and culture of 59 Eubacteria strains revealed the prevalence of alkaliphilic and halophilic organisms together with taxa unknown to date, based on 16S rRNA gene analysis. A single cloning-sequencing approach using archaeal 16S rDNA gene primers unveiled the presence of diverse extremophilic Euryarchaeota. The water chemistry of Dziani Dzaha Lake supports the hypothesis that it was derived from seawater and strongly modified by geological conditions and microbial activities that increased the alkalinity. Dziani Dzaha has a unique consortium of cyanobacteria, phytoplankton, heterotrophic Eubacteria and Archaea, with very few unicellular protozoa, that will deserve further deep analysis to unravel its uncommon diversity. A single taxon, belonging to the genus Arthrospira, was found responsible for almost all photosynthetic primary production.
FttC-Based Fronthaul for 5G Dense/Ultra-Dense Access Network: Performance and Costs in Realistic Scenarios

One distinctive feature of the next 5G systems is the presence of a dense/ultra-dense wireless access network with a large number of access points (or nodes) at short distances from each other. Dense/ultra-dense access networks allow for providing very high transmission capacity to terminals. However, the deployment of dense/ultra-dense networks is slowed down by the cost of the fiber-based infrastructure required to connect radio nodes to the central processing units and then to the core network. In this paper, we investigate the possibility for existing FttC access networks to provide fronthaul capabilities for dense/ultra-dense 5G wireless networks. The analysis is realistic in that it is carried out considering an actual access network scenario, i.e., the Italian FttC deployment. It is assumed that access nodes are connected to the Cabinets and to the corresponding distributors by a number of copper pairs. Different types of cities grouped in terms of population have been considered. Results focus on fronthaul transport capacity provided by the FttC network and have been expressed in terms of the available fronthaul bit rate per node and of the achievable coverage.
Topic Discovery for Short Texts Using Word Embeddings

Discovering topics in short texts, such as news titles and tweets, has become an important task for many content analysis applications. However, due to the lack of rich context information in short texts, the performance of conventional topic models on short texts is usually unsatisfying. In this paper, we propose a novel topic model for short text corpus using word embeddings. Continuous space word embeddings, which is proven effective at capturing regularities in language, is incorporated into our model to provide additional semantics. Thus we model each short document as a Gaussian topic over word embeddings in the vector space. In addition, considering that background words in a short text are usually not semantically related, we introduce a discrete background mode over word types to complement the continuous Gaussian topics. We evaluate our model on news titles from data sources like abcnews, showing that our model is able to extract more coherent topics from short texts compared with the baseline methods and learn better topic representation for each short document.
Etude de propriétés dynamiques linéaires et non-linéaires de deux liquides colloïdaux modèles par rhéologie: DGEBA/Al2O3 et DGEBA/SiO2

The dynamic mechanical behaviors of two model colloidal suspensions are compared in order to highlight microstructural changes in the suspensions. differentiate between the topological and physico-chemical impact of nanoparticles. For both systems the matrix material consists of the technologically relevant epoxy resin diglycidil ether of bisphenol A (DGEBA). The suspended nanoparticles are hydrophilic alumina and hydrophobic silica respectively. It will be shown that beside the classical α process an additional low-frequency relaxator exists whose qualitative frequency behavior is attributed to the pure presence of nanoparticles. The fine structure of the low-frequency relaxator depends on the physico-chemical surface properties of the nanoparticles. Similar to the α process the additional low-frequency relaxator shows cooperative behavior. Astonishingly, on the lines of the pure resin DGEBA, both colloidal suspensions show terminal behavior at very low frequency excitations. The nanoparticles are also shown to be responsible for non-linear dynamic and flow behaviors as well as for the emergence of free surface and volume instabilities. The transient character of flow is induced.
Draft Genome Sequence of Marinobacter vinifirmus Type Strain FB1

ABSTRACT The gammaproteobacterium Marinobacter vinifirmus is associated with moderately saline environments and is often found in marine ecosystems. Here, we report the draft genome sequence of M. vinifirmus type strain FB1 (3.8 Mbp, 3,588 predicted genes). The presented sequence will improve our understanding of the taxonomy and evolution of the genus Marinobacter.
Game theory of pre-emptive vaccination before bioterrorism or accidental release of smallpox

Smallpox was eradicated in the 1970s, but new outbreaks could be seeded by bioterrorism or accidental release. Substantial vaccine-induced morbidity and mortality make pre-emptive mass vaccination controversial, and if vaccination is voluntary, then there is a conflict between self- and group interests. This conflict can be framed as a tragedy of the commons, in which herd immunity plays the role of the commons, and free-riding (i.e. not vaccinating pre-emptively) is analogous to exploiting the commons. This game has been analysed previously for a particular post-outbreak vaccination scenario. We consider several post-outbreak vaccination scenarios and compare the expected increase in mortality that results from voluntary versus imposed vaccination. Below a threshold level of post-outbreak vaccination effort, expected mortality is independent of the level of response effort. A lag between an outbreak starting and a response being initiated increases the post-outbreak vaccination effort necessary to reduce mortality. For some post-outbreak vaccination scenarios, even modest response lags make it impractical to reduce mortality by increasing post-outbreak vaccination effort. In such situations, if decreasing the response lag is impossible, the only practical way to reduce mortality is to make the vaccine safer (greater post-outbreak vaccination effort leads only to fewer people vaccinating pre-emptively).
ˆ Ales Ordinateurs Et L'intelligencê a Universal Turing Machine

The synthesis of consistent hashing is a key quagmire. This is an important point to understand. in fact, few biologists would disagree with the evaluation of the lookaside buffer, which embodies the practical principles of steganography. In order to achieve this ambition, we concentrate our efforts on disproving that online algorithms and RPCs can collaborate to accomplish this objective.
THE EVOLUTION OF DUSTY STAR FORMATION IN GALAXY CLUSTERS TO z = 1: SPITZER INFRARED OBSERVATIONS OF THE FIRST RED-SEQUENCE CLUSTER SURVEY

We present the results of an infrared (IR) study of high-redshift galaxy clusters with the MIPS camera on board the Spitzer Space Telescope. We have assembled a sample of 42 clusters from the Red-Sequence Cluster Survey-1 over the redshift range 0.3 < z < 1.0 and spanning an approximate range in mass of 1014–15 M☉. We statistically measure the number of IR-luminous galaxies in clusters above a fixed inferred IR luminosity of 2 × 1011 M☉, assuming a star forming galaxy template, per unit cluster mass and find it increases to higher redshift. Fitting a simple power-law we measure evolution of (1 + z)5.1 ± 1.9 over the range 0.3 < z < 1.0. These results are tied to the adoption of a single star forming galaxy template; the presence of active galactic nuclei, and an evolution in their relative contribution to the mid-IR galaxy emission, will alter the overall number counts per cluster and their rate of evolution. Under the star formation assumption we infer the approximate total star formation rate per unit cluster mass (ΣSFR/Mcluster). The evolution is similar, with ΣSFR/Mcluster ∼ (1 + z)5.4 ± 1.9. We show that this can be accounted for by the evolution of the IR-bright field population over the same redshift range; that is, the evolution can be attributed entirely to the change in the in-falling field galaxy population. We show that the ΣSFR/Mcluster (binned over all redshift) decreases with increasing cluster mass with a slope (ΣSFR/) consistent with the dependence of the stellar-to-total mass per unit cluster mass seen locally. The inferred star formation seen here could produce ∼5%–10% of the total stellar mass in massive clusters at z = 0, but we cannot constrain the descendant population, nor how rapidly the star-formation must shut-down once the galaxies have entered the cluster environment. Finally, we show a clear decrease in the number of IR-bright galaxies per unit optical galaxy in the cluster cores, confirming star formation continues to avoid the highest density regions of the universe at z ∼ 0.75 (the average redshift of the high-redshift clusters). While several previous studies appear to show enhanced star formation in high-redshift clusters relative to the field we note that these papers have not accounted for the overall increase in galaxy or dark matter density at the location of clusters. Once this is done, clusters at z ∼ 0.75 have the same or less star formation per unit mass or galaxy as the field.
Application of the Newton–Raphson Method to Lifetime Spectroscopy for Extraction of Defect Parameters

Defect parameter solution surface is a widely accepted method to determine the values of the energy level and the carrier capture cross sections of a defect from injection-dependent lifetime measurements. Results of the defect parameter solution surface come from the recognition of intersection points, which can be difficult when the doping or the temperature range of the measurement is narrow. In this paper, we introduce a new method to extract the defect parameters from lifetime spectroscopy data. After linearization of the Shockley–Read–Hall (SRH) lifetime equation, the problem is transformed into a mathematical form, which can be solved by the Newton–Raphson method. This method requires a much shorter computing time and directly provides the possible values of the defect parameters without user interaction, even for measurements with narrow doping and temperature ranges.
Statistical analysis of the mismatch negativity: To a dilemma, an answer

This paper offers a new innovative outlook on mismatch negativity (MMN) analysis. Indeed, researchers in this field encounter difficulties when attempting to objectively quantify the MMN component waveform. Advantages taken from already existing amplitude and area under the curve measures were used in order to thwart weaknesses from each individual measure. The present paper can also be used as a guideline that describes each step required in the execution of the proposed technique to MMN analysis.
I Have Seen Enough: Transferring Parts Across Categories

The recent successes of deep learning have been possible due to the availability of increasingly large quantities of annotated data. A natural question, therefore, is whether further progress can be indeﬁnitely sustained by annotating more data, or whether there is a saturation point beyond which a problem is essentially solved, or the capacity of a model is saturated. In this paper we examine this question from the viewpoint of learning shareable semantic parts, a fundamental building block to generalize visual knowledge between object categories. We ask two research questions often neglected: whether semantic parts are also visually shareable between classes, and how many annotations are required to learn them. In order to answer such questions, we collect 15,000 images of 100 animal classes and annotate them with parts. We then thoroughly test active learning and domain adaptation techniques to generalize to unseen classes parts that are learned from a limited number of classes and example images. Our experiments show that, for a majority of the classes, part annotations transfer well, and that performance reaches 98% of the accuracy of the fully annotated scenario by providing only a few thousand examples.
Portfolio theory of information retrieval

This paper studies document ranking under uncertainty. It is tackled in a general situation where the relevance predictions of individual documents have uncertainty, and are dependent between each other. Inspired by the Modern Portfolio Theory, an economic theory dealing with investment in financial markets, we argue that ranking under uncertainty is not just about picking individual relevant documents, but about choosing the right combination of relevant documents. This motivates us to quantify a ranked list of documents on the basis of its expected overall relevance (mean) and its variance; the latter serves as a measure of risk, which was rarely studied for document ranking in the past. Through the analysis of the mean and variance, we show that an optimal rank order is the one that balancing the overall relevance (mean) of the ranked list against its risk level (variance). Based on this principle, we then derive an efficient document ranking algorithm. It generalizes the well-known probability ranking principle (PRP) by considering both the uncertainty of relevance predictions and correlations between retrieved documents. Moreover, the benefit of diversification is mathematically quantified; we show that diversifying documents is an effective way to reduce the risk of document ranking. Experimental results in text retrieval confirm performance.
Automatic region of interest extraction in food baking images

This paper presents a novel approach to automatically detect the region of interest (ROI) in food baking images. In addition to common ROI extraction and saliency extraction problems, food baking images are also subject to lighting noise, glass reflection and shadow effects. In this paper, the HSV color map is employed to effectively eliminate oven lighting effects, then a one-bit transform (1BT) with global adaptive thresholding method is performed to obtain preliminary ROI segmentation results. Further, a local contour refinement algorithm is designed to reduce glass reflection and shadow effects for extracting the ROI contour more precisely. The ROI extraction results presented in this paper can be used in compression and transmission of food baking images and videos for further analysis.
International Conference on Intelligent Robots and Systems Reinforcement Learning for a Vision Based Mobile Robot

Reinforcement learning systems improve behaviour based on scalar rewards from a critic. In this work vision based behaviours, servoing and Wandering, are learned through a Q-learning method which handles continuous states and actions. There is no requirement for camera calibration, an actuator model, or a knowledgeable teacher. Learning thmugh observing the actions of other behaviours improves learning speed. Experiments were performed on a mobile robot wing a real-time vision system.
Multi-Touch Interface for Character Motion Control Using Model-Based Approach

In this paper, we propose a new method for interactive motion control with a multi-touch interface. A user of our system can touch and drag character's body parts to control its motion. The character's full body motion is driven by our interactive motion control model based on the movement of a few body parts which are directly manipulated by the user via the multi-touch interface. We propose a method for determining 3-dimensional positions of controlled body parts from 2-dimensional touch inputs based on the character's local coordinates and drag speed. We introduce a point-based pose representation which consists of the positions or orientations of a small number of primary body parts. Based on the representation, we develop a motion control model that includes modules for tracking, balance, inter-body interaction, relaxing and self-collision avoidance. The character's pose is reconstructed from the point-based pose representation. We present our experimental results to show that our framework can realize various natural-looking motions.
Pitch contour modelling and modification for expressive Marathi speech synthesis

In this paper, we have measured and analyzed features of speech signal such as fundamental frequency, jitter and shimmer its statistical modeling for Marathi. These models can be used for modifying prosody of the neutral speech further. Jitter and shimmer are measures of cycle-to-cycle variations of fundamental frequency and amplitude respectively. It characterizes the emotion and differs in values as emotion varies. An emotion or target model mentioned here is in the form of interrogate. A pitch target model is developed to model and modify the prosody of the Marathi words. The study comprises the study of existing pitch contour of words whose prosody is to be modified and target pitch contour. Its statistical analysis is done. At the end Gaussian normalization is employed to modify the prosody with help of analyzed data. Result of the subjective experiments satisfies the native listeners.
ForceDROID: Extracting Hidden Information in Android Apps by Forced Execution Technique

Malware analysis technology is important for Android security. However, existing Android malware analysis approaches, both static approaches and dynamic approaches, have their own advantages and drawbacks. In this paper, by combining static and dynamic approaches, we propose the forced execution technique for Android apps to automatically extract their hidden information such as encoded URLs, promoting the security evaluation of Android apps. Our approach firstly searches some execution paths leading to critical functions based on static analysis. Then, by monitoring the control flow conditions of the target app, code on the selected paths is forcedly executed. In this process, an exception-tolerated execution sandbox is designed to ensure that selected execution flows finally reach the critical functions. Thus, important parameters related to the functions can be extracted with high probability. The main advantage of our approach is that the whole process is completely automatic and does not require complicated input contexts for the execution. We have implemented the prototype system ForceDROID. And two scenarios aiming at network connections and shell commands are designed to evaluate the effectiveness of our approach.
Determination of Plasmid Copy Number Reveals the Total Plasmid DNA Amount Is Greater than the Chromosomal DNA Amount in Bacillus thuringiensis YBT-1520

Bacillus thuringiensis is the most widely used bacterial bio-insecticide, and most insecticidal crystal protein-coding genes are located on plasmids. Most strains of B. thuringiensis harbor numerous diverse plasmids, although the plasmid copy numbers (PCNs) of all native plasmids in this host and the corresponding total plasmid DNA amount remains unknown. In this study, we determined the PCNs of 11 plasmids (ranging from 2 kb to 416 kb) in a sequenced B. thuringiensis subsp. kurstaki strain YBT-1520 using real-time qPCR. PCNs were found to range from 1.38 to 172, and were negatively correlated to plasmid size. The amount of total plasmid DNA (∼8.7 Mbp) was 1.62-fold greater than the amount of chromosomal DNA (∼5.4 Mbp) at the mid-exponential growth stage (OD600 = 2.0) of the organism. Furthermore, we selected three plasmids with different sizes and replication mechanisms to determine the PCNs over the entire life cycle. We found that the PCNs dynamically shifted at different stages, reaching their maximum during the mid-exponential growth or stationary phases and remaining stable and close to their minimum after the prespore formation stage. The PCN of pBMB2062, which is the smallest plasmid (2062 bp) and has the highest PCN of those tested, varied in strain YBT-1520, HD-1, and HD-136 (172, 115, and 94, respectively). These findings provide insight into both the total plasmid DNA amount of B. thuringiensis and the strong ability of the species to harbor plasmids.