Miracle-dz/UniFAR-FTUs huggingface dataset:
Automatic Visual Bag-of-Words for Online Robot Navigation and Mapping

Detecting already-visited regions based on their visual appearance helps reduce drift and position uncertainties in robot navigation and mapping. Inspired from content-based image retrieval, an efficient approach is the use of visual vocabularies to measure similarities between images. This way, images corresponding to the same scene region can be associated. State-of-the-art proposals that address this topic use prebuilt vocabularies that generally require a priori knowledge of the environment. We propose a novel method for appearance-based navigation and mapping where the visual vocabularies are built online, thus eliminating the need for prebuilt data. We also show that the proposed technique allows efficient loop-closure detection, even at small vocabulary sizes, resulting in a higher computational efficiency.
An Efficient Approach for Fast Turnaround Co-Synthesis of One-Chip Integrated Systems

This paper describes a parameterizable RISC processor core and its associated co-synthesis environment for embedding mixed hardware/software systems in sea-of-gates integrated circuits. The core is fully configurable so that the program and data memory sizes, the number and size of the I/O ports, the stack size and the number and type of its peripheral blocks can be automatically adjusted to the system requirements. In order to satisfy time constraints and/or parallelization requirements, the co-synthesis system automatically selects software components to be migrated to hardware units, which are integrated with the processor core in the same chip. The approach proposed targets single chip system implementation on a quick turnaround sea-of-gates technology, therefore providing a suitable environment and an efficient solution for rapid prototyping and low cost small series production of low to medium complexity embedded digital systems.
GSCMap-A Gene-Set-based version of Connectivity Map and an application using Local Hierarchical Clustering to characterize Bioactive Compounds in terms of Biological Functional Groups

Gene-set-based analysis (GSA), which uses the relative importance of functional gene-sets as units for analysis of genome-wide gene expression data, has exhibited major advantages with respect to greater accuracy, robustness, and biological relevance, over individual gene analysis (IGA), which uses log-ratios of individual genes for analysis. Yet IGA remains the dominant mode of analysis of gene expression data. The Connectivity Map (CMap), an extensive database on genomic profiles of effects of drugs and small molecules and widely used for studies related to repurposed drug discovery, has been mostly employed in IGA mode. Here, we constructed a GSA-based version of CMap, GeneSet Connectivity Map (GSCMap), in which all the genomic profiles in CMap are converted, using gene-sets from the Molecular Signatures Database, to functional profiles. We showed that GSCMap essentially eliminated cell-type dependence, a weakness of CMap in IGA mode, and yielded significantly better performance on sample clustering and drug-target association. As a first application of GSCMap we constructed the platform Gene-Set Local Hierarchical Clustering (GSLHC) for discovering insights on coordinated actions of biological functions and facilitating classification of heterogeneous subtypes on drug-driven responses. GSLHC was shown to tightly clustered drugs of known similar properties. We used GSLHC to identify the therapeutic properties and putative targets of 18 compounds of previously unknown characteristics listed in CMap, eight of which suggest anti-cancer activities. We expect GSCMap and GSLHC to be widely useful in providing new insights in the biological effect of bioactive compounds, in drug repurposing, and in function-based classification of complex diseases.
A Location Aware Service to Minimize Travel Costs Using Dynamic Information

Automotive navigation systems have become common accessories in vehicles manufactured today. However, the information provided by these systems is quite limited in that many systems only provide static information. As a result, manufacturers of such systems have not been able to fully capitalize from the potential applications for mobile commerce (mcommerce) which is critically dependent on providing consumers with dynamic information. The objective of this paper is to discuss a novel method, known as Dynamic Location Cost Minimization (DLCM), which can be used with a vehicle’s navigation system to determine the optimum location to purchase gas. With the increasing cost of gas and the possibility of higher prices due to proposed gas price taxes, providing a means for consumers to minimize their costs to travel could prove to be very beneficial, and potentially help drive down prices due to increased competition. In addition, the proposed method could also be used in conjunction with mobile phones to facilitate real-time decisions for other services or purchases. Anecdotal evidence presented in this paper merits further investigation into the usability and acceptance of this technology.
InAl(Ga)N/GaN/SiC devices delivering 5W/mm output power at 30 GHz

We report on the performances of 0.1-μm gate length InAl(Ga)N/GaN HEMT devices on SiC substrate. Measurements results of DC, pulsed I-V, S-parameters and load-pull power performances are presented. Devices exhibited a maximum DC transconductance of 400mS/mm and drain current of 1.2A/mm at Vgs=1V. Cut-off frequencies Ft and Fmag of 60GHz and 140 GHz were obtained. Load-pull power measurements at 30GHz allowed us to achieve an output power density of 3W/mm with 40% of PAE at Vds=15V. Biased at Vds=20V, a maximum saturated output power density of 5W/mm was achieved.
Behavioral Modeling of Digital Devices Via Composite Local Linear State–Space Relations

This paper addresses the generation of accurate and efficient behavioral models of digital ICs. The proposed approach is based on the approximation of the device port characteristics by means of composite local linear state-space relations whose parameters can effectively be estimated from device port transient responses via well-established system identification techniques. The proposed models have been proven to overcome some inherent limitations of the state-of-the-art models used so far, and they can effectively be implemented in any commercial tool as simulation program with integrated circuit emphasis (SPICE) subcircuits or VHDL-AMS hardware descriptions. A systematic study of the performances of the proposed state-space models is carried out on a synthetic test device. The effectiveness of the proposed approach has been demonstrated on a real application problem involving commercial devices and a data link of a mobile phone.
Old adults perform activities of daily living near their maximal capabilities.

BACKGROUND Old adults' ability to execute activities of daily living (ADLs) declines with age. One possible reason for this decline is that the execution of customary motor tasks requires a substantially greater effort in old compared with young adults relative to their available maximal capacity. METHODS We tested the hypothesis that the relative effort (i.e., the percentage of joint moment relative to maximal joint moment) to execute ADLs is higher in old adults compared with young adults. Healthy young adults (n = 13; mean age, 22 years) and old adults (n = 14; mean age, 74 years) ascended and descended stairs and rose from a chair and performed maximal-effort isometric supine leg press. Using inverse dynamics analysis, we determined knee joint moments in ADLs and computed relative effort. RESULTS Compared with young adults, old adults had 60% lower maximal leg press moments, 53% slower knee angular velocity at peak torque, and 27% lower knee joint moments in the ADLs (all p <.05). Relative effort in ascent was 54% (SD +/- 16%) and 78% (+/-20%) in young and old adults, respectively; in descent, it was 42% (+/-20%) and 88% (+/-43%); and in chair rise, it was 42% (+/-19%) and 80% (+/-34%) (all p <.05). The relative electromyographic activity of the vastus lateralis and the coactivity of the biceps femoris associated with this relative effort were, respectively, 2- and 1.6-fold greater in old compared with young adults in the 3 ADLs (p <.05). CONCLUSIONS For healthy old adults, the difficulty that arises while performing ADLs may be due more to working at a higher level of effort relative to their maximum capability than to the absolute functional demands imposed by the task.
Simultaneous X-ray/radio observations of Cir X-1

We analysed simultaneous X-ray/radio observations of Circinus X-1 collected respectively with RXTE and ATCA in 2000 October and 2002 December and identified radio flares close to phase 0.0 and 0.5 of the orbital period. To date, there is only circumstantial evidence for radio flares near phase 0.5. Moreover, in our data set, we clearly associated both a radio flare and X-ray spectral timing changes with phase 0.0. While for black hole X-ray binaries the picture of the association between the X-ray and the radio bands is quite well understood, for neutron star X-ray binaries a clear and complete picture is still missing.
A Decision-Theoretic Approach for Selecting Tutorial Discourse Actions

We propose a decision-theoretic architecture for selecting tutorial discourse actions. DT Tutor, an action selection engine which embodies our approach, uses a dynamic decision network to consider the tutor’s objectives and uncertain beliefs in adapting to and managing the changing tutorial state. It predicts the effects of the tutor’s discourse actions on the tutorial state, including the student’s internal state, and appears to be unique in explicitly predicting the student’s next action and its effect on the tutorial state. Based on the probabilities of predicted outcomes and their utilities, DT Tutor selects the tutorial action with maximum expected utility. We illustrate our approach with prototype applications for diverse domains: calculus problem-solving and elementary reading. Feasibility evaluations assess DT Tutor’s ability to select optimal actions quickly enough to keep the student engaged.
53BP1 Protects against CtIP-Dependent Capture of Ectopic Chromosomal Sequences at the Junction of Distant Double-Strand Breaks

DNA double-strand breaks (DSB) are very harmful lesions that can generate genome rearrangements. In this study, we used intrachromosomal reporters to compare both the efficiency and accuracy of end-joining occurring with close (34 bp apart) vs. distant DSBs (3200 bp apart) in human fibroblasts. We showed that a few kb between two intrachromosomal I-SceI-induced DSBs are sufficient to foster deletions and capture/insertions at the junction scar. Captured sequences are mostly coupled to deletions and can be partial duplications of the reporter (i.e., sequences adjacent to the DSB) or insertions of ectopic chromosomal sequences (ECS). Interestingly, silencing 53BP1 stimulates capture/insertions with distant but not with close double-strand ends (DSEs), although deletions were stimulated in both case. This shows that 53BP1 protects both close and distant DSEs from degradation and that the association of unprotection with distance between DSEs favors ECS capture. Reciprocally, silencing CtIP lessens ECS capture both in control and 53BP1-depleted cells. We propose that close ends are immediately/rapidly tethered and ligated, whereas distant ends first require synapsis of the distant DSEs prior to ligation. This "spatio-temporal" gap gives time and space for CtIP to initiate DNA resection, suggesting an involvement of single-stranded DNA tails for ECS capture. We therefore speculate that the resulting single-stranded DNA copies ECS through microhomology-mediated template switching.
Mate choice based on a key ecological performance trait

Mate preference for well‐adapted individuals may strengthen divergent selection and thereby facilitate adaptive divergence. We performed mate choice experiments in which we manipulated male red crossbill (Loxia curvirostra complex) feeding rates. Using association time as a proxy for preference, we found that females preferred faster foragers, which reinforces natural selection because poorly adapted males would be less likely to obtain a mate as well as less likely to survive. Although theoretical models predict direct preference for adaptation and performance, to the best of our knowledge this experiment provides the first evidence of individuals directly assessing feeding performance in mate choice. In species where assessing the ecological adaptation of potential mates is possible, females may gain fitness benefits from choosing a well‐adapted mate directly or indirectly, promoting the use of information about ecological adaptation in mate choice.
Optimal formation control of Unmanned Aerial Vehicles with reconfiguration

Unmanned Aerial Vehicles(UAVs) are finding use in military applications, surveillance tasks, for environment monitoring, geological survey, etc. It is beneficial to use a team of coordinated UAVs rather than a single UAV, because multiple UAVs can complete the tasks with ease and more robustness than a single UAV. In this paper, a controller is proposed in optimal control framework for achieving any desired formation. By properly choosing formation vectors any formation can be achieved. A time varying formation vector is proposed which helps in achieving circular formation. In situations like loss of UAVs from formation group, the UAVs have to reconfigure for completing the task optimally maintaining the communication links. Reconfiguration has also been achieved in this framework. The controller is also capable of achieving encirclement of a target/ immobilization of the target. From extensive simulations, it is seen that the UAVs are capable of achieving any formation; the formation can follow any desired trajectory, can achieve reconfiguration and encirclement of a stationary and moving target as well.
An Estimate of the Dispersion of Repolarization Times Based on a Biophysical Model of the ECG

Temporal heterogeneity of ventricular repolarization is a key quantity for the development of ventricular reentrant arrhythmia. In this paper, we introduce the -index, a novel ECG-based estimator of the standard deviation of ventricular myocytes' repolarization times . Differently from other ECG metrics of repolarization heterogeneity, the -index was derived from the analysis of a biophysical model of the ECG, where repolarization is described by the dominant T-wave (DTW) paradigm. The model explains the shape of T-waves in each lead as a projection of a main waveform (the DTW) and its derivatives weighted by scalars, the lead factors. A mathematical formula is derived to link the heterogeneity of ventricular repolarization and the V-index. The formula was verified using synthetic 12-lead ECGs generated with a direct electrophysiological model for increasing values of sθ (in the range 20-70 ms). A linear relationship between the V-index and sθ was observed, V≈ 0.675 sθ + 1.8 ms (R2=0.9992). Finally, 68 ECGs from the E-OTH-12-0068-010 database of the Telemetric and Holter ECG Warehouse were analyzed. The -index coherently increased after sotalol administration, a drug known to have QT-prolonging potential (p ≪ 0.001).
Propagation into and within buildings at 900, 1800 and 2300 MHz

Investigations of propagation into, and within, buildings at 900, 1800, and 2100 MHz were undertaken. The composite Rayleigh-plus-log-normal distribution successfully modeled the measured cumulative distributions of all measurements. The average measured penetration loss at ground floor level was found to be 14.2, 13.4, and 12.8 dB, respectively, at 900, 1800, and 2300 MHz. The rate of change of penetration loss with height was-1.4, dB per floor. The rate of change of mean signal level for signals traveling within buildings was, on average, 8.5 dB per floor. the path loss attenuation factor, that best modeled the within-building measurement was found to be 5.3, 5.5, and 6.0, respectively, for 900, 1800, and 2300 MHz. <<ETX>>
Asymptotic Equipartition Properties for simple hierarchical and networked structures

We prove asymptotic equipartition properties for simple hierarchical structures (modelled as multitype Galton-Watson trees) and networked structures (modelled as randomly coloured random graphs). For example, for large $n$, a networked data structure consisting of $n$ units connected by an average number of links of order $n/log n$ can be coded by about $nH$ bits, where $H$ is an explicitly defined entropy. The main technique in our proofs are large deviation principles for suitably defined empirical measures.
Speculative Bubbles Dynamics and the Role of Anchoring

We investigate the role played by the anchoring-and-adjustment heuristic in the speculative bubbles dynamics. In order to link anchoring bias and price deviations from fundamental value, we develop a stock market equilibrium model with heterogeneous investors: fundamental investor anchoring to past stock market prices and noise traders. The equilibrium model we derive suggests that price is a function of fundamental value, past price, noise and anchoring level. Based on our model, we run a set of Monte Carlo experiments with various anchoring levels: no anchoring, low anchoring and high anchoring. We bring the evidence that large speculative bubbles can only occur when fundamental traders highly anchor to stock market prices. Noise cannot in itself cause such phenomenon. Our findings also suggest that a high anchoring level is consistent with slowly mean reverting bubbles lasting many years.
First-principles investigation of graphene fluoride and graphane

Different stoichiometric configurations of graphane and graphene fluoride are investigated within density functional theory. Their structural and electronic properties are compared, and we indicate the similarities and differences among the various configurations. Large differences between graphane and graphene fluoride are found that are caused by the presence of charges on the fluorine atoms. A new configuration that is more stable than the boat configuration is predicted for graphene fluoride. We also perform GW calculations for the electronic band gap of both graphene derivatives. These band gaps and also the calculated Young's moduli are at variance with available experimental data. This might indicate that the experimental samples contain a large number of defects or are only partially covered with H or F.
Video Games and Hippocampus-Dependent Learning

Research examining the impact of video games on neural systems has largely focused on visual attention and motor control. Recent evidence now shows that video games can also impact the hippocampal memory system. Further, action and 3D-platform video-game genres are thought to have differential impacts on this system. In this review, we examine the specific design elements unique to either action or 3D-platform video games and break down how they could either favor or discourage use of the hippocampal memory system during gameplay. Analysis is based on well-established principles of hippocampus-dependent and non-hippocampus-dependent forms of learning from the human and rodent literature.
1 Asynchronous Multiplay Futures for Casual Multiplayer Experience

Big budget, high commitment 3D MMORPG’s have generated significant revenues and theoretical bounty. But these games still alienate most casual players. This article offers a promising future for multiplayer experience, especially casual experience, in the form of asynchronous multiplayer games, or games in which small or large numbers of players play a game in sequence rather than simultaneously. Author
Forest above Ground Biomass Inversion by Fusing GLAS with Optical Remote Sensing Data

Forest biomass is an important parameter for quantifying and understanding biological and physical processes on the Earth’s surface. Rapid, reliable, and objective estimations of forest biomass are essential to terrestrial ecosystem research. The Geoscience Laser Altimeter System (GLAS) produced substantial scientific data for detecting the vegetation structure at the footprint level. This study combined GLAS data with MODIS/BRDF (Bidirectional Reflectance Distribution Function) and ASTER GDEM data to estimate forest aboveground biomass (AGB) in Xishuangbanna, Yunnan Province, China. The GLAS waveform characteristic parameters were extracted using the wavelet method. The ASTER DEM was used to compute the terrain index for reducing the topographic influence on the GLAS canopy height estimation. A neural network method was applied to assimilate the MODIS BRDF data with the canopy heights for estimating continuous forest heights. Forest leaf area indices (LAIs) were derived from Landsat TM imagery. A series of biomass estimation models were developed and validated using regression analyses between field-estimated biomass, canopy height, and LAI. The GLAS-derived canopy heights in Xishuangbanna correlated well with the field-estimated AGB (R2 = 0.61, RMSE = 52.79 Mg/ha). Combining the GLAS estimated canopy heights and LAI yielded a stronger correlation with the field-estimated AGB (R2 = 0.73, RMSE = 38.20 Mg/ha), which indicates that the accuracy of the estimated biomass in complex terrains can be improved significantly by integrating GLAS and optical remote sensing data.
Occupancy Sensing and Prediction for Automated Energy Savings

The ability to sense and predict occupancy – i.e. to establish when the residents are and will be in a building – represents a basic requirement for the energy-efficient operation of many building automation systems. In residential households, in particular, the absence of all residents allows a heating controller to automatically lower the temperature of the home, thereby saving energy that would have been otherwise wasted on heating an empty building. However, if the home has been thus allowed to cool, a boiler and heat distribution system need a non-negligible time to reheat the home to a comfortable temperature. Therefore, to avoid a loss of comfort, a heating control system also requires a sufficiently accurate prediction of when the occupants are going to return in order to trigger the heating at the right time. Since space heating accounts for a large fraction of residential energy use (e.g. 68% in the European Union member states), heating control systems based on occupancy sensing and prediction – often referred to as smart thermostats – play an important role in reducing energy consumption and carbon dioxide emissions, while at the same time ensuring occupant comfort. The objective of this thesis is thus to investigate how the two main computational components of a smart thermostat – occupancy sensing, based on sensors that typically exist in a residential environment, as well as occupancy prediction from historical occupancy patterns – can be used to automatically reduce the energy consumption of a heating system while trying to maximise thermal comfort. Current smart thermostats require the installation of dedicated hardware to sense whether the occupants are at home or away. This increases installation and maintenance costs and thus prevents widespread adoption of such potentially energy-saving solutions. To overcome this hurdle, we investigate the suitability of opportunistically using devices already existing in households to sense occupancy. This opportunistic sensing approach seeks to utilise available devices to replace or augment dedicated infrastructures. An example are smart electricity meters, which are mandated to be installed in many households worldwide. We hypothesise that the information contained in the electrical load of the