Miracle-dz/UniFAR-FTUs huggingface dataset:
MAPP: a Scalable Multi-Agent Path Planning Algorithm with Tractability and Completeness Guarantees

Multi-agent path planning is a challenging problem with numerous real-life applications. Running a centralized search such as A* in the combined state space of all units is complete and cost-optimal, but scales poorly, as the state space size is exponential in the number of mobile units. Traditional decentralized approaches, such as FAR and WHCA*, are faster and more scalable, being based on problem decomposition. However, such methods are incomplete and provide no guarantees with respect to the running time or the solution quality. They are not necessarily able to tell in a reasonable time whether they would succeed in finding a solution to a given instance. We introduce MAPP, a tractable algorithm for multi-agent path planning on undirected graphs. We present a basic version and several extensions. They have low-polynomial worst-case upper bounds for the running time, the memory requirements, and the length of solutions. Even though all algorithmic versions are incomplete in the general case, each provides formal guarantees on problems it can solve. For each version, we discuss the algorithm's completeness with respect to clearly defined subclasses of instances. Experiments were run on realistic game grid maps. MAPP solved 99.86% of all mobile units, which is 18-22% better than the percentage of FAR and WHCA*. MAPP marked 98.82% of all units as provably solvable during the first stage of plan computation. Parts of MAPP's computation can be re-used across instances on the same map. Speed-wise, MAPP is competitive or significantly faster than WHCA*, depending on whether MAPP performs all computations from scratch. When data that MAPP can re-use are preprocessed offline and readily available, MAPP is slower than the very fast FAR algorithm by a factor of 2.18 on average. MAPP's solutions are on average 20% longer than FAR's solutions and 7-31% longer than WHCA*'s solutions.
Increased Cortico-striatal Synchronization over Hemispheres in the Hemiparkinsonian Rat Manuscript in Preparation

In Parkinson’s disease (PD), changes in oscillatory brain activity occur over a wide range of cortical regions and in the basal ganglia. However, it is unknown how dopamine depletion in the 6-OHDA lesioned rat model of PD affects the oscillatory brain activity within and the synchronization of this activity between different cortical areas and the basal ganglia. In the current study, we performed multielectrode recordings in a freely moving rat model of parkinsonism to explore changes in local synchrony of oscillatory brain activity and synchronization between brain regions. Local field potentials were recorded simultaneously from 12 cortical areas and the left and right striatum. Serial recordings were performed in awake, behaving rats before and after a unilateral 6-hydroxydopamine injection into the medial forebrain bundle. We computed spectral power and synchronization between brain regions using the Phase Lag Index in two behavioural conditions: at rest and during locomotion. Our recordings revealed an increase in relative beta power over a wide range of areas at rest, and in a limited number of areas during locomotion. Synchronization between brain regions was moderately increased in the beta frequency band. In addition, we observed excessive gamma band synchronization between many of the recorded brain regions in the resting condition. Our results demonstrate that the changes in local oscillatory brain activity and in the synchronization between brain regions in hemiparkinsonian rats are in many ways similar to the changes observed in PD patients. B. N. Jávor-Duray1, L. Douw1, M. van der Roest1,J.J. Geurts 1, H. W. Berendse2, P. Voorn1 1 Department of Anatomy and Neurosciences, Neuroscience Campus Amsterdam; 2 Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Ce1nter, Amsterdam, the Netherlands Manuscript in preparation Multiregional connectivity patterns: translational approach
Commitment decisions with partial information updating

In this paper, we extend the results of Ferguson M. Naval Research Logistics 50, 2003, 917–936 . on an end‐product manufacturer's choice of when to commit to an order quantity from its parts supplier. During the supplier's lead‐time, information arrives about end‐product demand. This information reduces some of the forecast uncertainty. While the supplier must choose its production quantity of parts based on the original forecast, the manufacturer can wait to place its order from the supplier after observing the information update. We find that a manufacturer is sometimes better off with a contract requiring an early commitment to its order quantity, before the supplier commits resources. On the other hand, the supplier sometimes prefers a delayed commitment. The preferences depend upon the amount of demand uncertainty resolved by the information as well as which member of the supply chain sets the exchange price. We also show conditions where demand information updating is detrimental to both the manufacturer and the supplier. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2005
Automatic Performance Setting for Dynamic Voltage Scaling

The emphasis on processors that are both low power and high performance has resulted in the incorporation of dynamic voltage scaling into processor designs. This feature allows one to make fine granularity tradeoffs between power use and performance, provided there is a mechanism in the OS to control that tradeoff. In this paper, we describe a novel software approach to automatically controlling dynamic voltage scaling in order to optimize energy use. Our mechanism is implemented in the Linux kernel and requires no modification of user programs. Unlike previous automated approaches, our method works equally well with irregular and multiprogrammed workloads. Moreover, it has the ability to ensure that the quality of interactive performance is within user specified parameters. Our experiments show that as a result of our algorithm, processor energy savings of as much as 75% can be achieved with only a minimal impact on the user experience.
Tidal Behavior and Water‐Level Changes in Gravel Aquifers in Response to Multiple Earthquakes: A Case Study From New Zealand

Earthquakes have been inferred to induce hydrological changes in aquifers on the basis of either changes to well water‐levels or tidal behavior, but the relationship between these changes remains unclear. Here, changes in tidal behavior and water‐levels are quantified using a hydrological network monitoring gravel aquifers in Canterbury, New Zealand, in response to nine earthquakes (of magnitudes Mw 5.4 to 7.8) that occurred between 2008 and 2015. Of the 161 wells analyzed, only 35 contain water‐level fluctuations associated with “Earth + Ocean” (7) or “Ocean” (28) tides. Permeability reduction manifest as changes in tidal behavior and increased water‐levels in the near field of the Canterbury earthquake sequence of 2010–2011 support the hypothesis of shear‐induced consolidation. However, tidal behavior and water‐level changes rarely occurred simultaneously (~2%). Water‐level changes that occurred with no change in tidal behavior reequilibrated at a new postseismic level more quickly (on timescales of ~50 min) than when a change in tidal behavior occurred (~240 min to 10 days). Water‐level changes were more than likely to occur above a peak dynamic stress of ~50 kPa and were more than likely to not occur below ~10 kPa. The minimum peak dynamic stress required for a tidal behavior change to occur was ~0.2 to 100 kPa.
Multirate DSP and its technique to reduce the cost of the analog signal conditioning filters

There are many reasons to change the sample rate of a sampled data signal. Here we discuss the two basic operations in a multirate system i.e. decreasing (decimation) and (increasing) the sampling rate of a signal. Also the use of multirate filters at the interfaces of continuous & sampled data which results in a cost reduction of the analog signal conditioning components as well as improvement of signal quality.
Lateral Inhibition Map Updating Method to Prevent Map Deformation for Simultaneous Localization and Mapping in Natural Environment

In this paper, a novel real time map updating algorithm using a concept of lateral inhibition was proposed and it was evaluated by simple 2D mapping experiment. For long time and difficult map creation process of simultaneous localization and mapping (SLAM) algorithm, stable map updating is one of the important topics. By using the lateral inhibition process to the map updating process, it is able to reduce the complexity of the map updating process of the SLAM. It could reduce the noise around the wall and emphasize the border (such a wall). The experimental result of map updating process of 6.0 x 3.5 m 2D room with many obstacles shows the x-y positional and the rotational estimation precision would be measured as x,y= 1.8 ×10-6 m (less than the LIDAR measurement error about 0.04 m) and the = - 1.9×10-2 deg (1 hour measurement), and the map was updated real time when the LIDAR sensor was moving from a position to another room position with low speed. After the 38 min outdoor experiment, the occupancy map was stably maintained, and there is also slight rotation and position estimation errors (x,y = 0.0 m, = 8.3 ×10-2 deg). The proposed method could suppress the wall existence probability distribution creeping induced by the natural environment vibration such as tree or leaves.
Control of dissected leaf morphology by a Cys(2)His(2) zinc finger transcription factor in the model legume Medicago truncatula

Plant leaves are diverse in their morphology, reflecting to a large degree the plant diversity in the natural environment. How different leaf morphology is determined is not yet understood. The leguminous plant Medicago truncatula exhibits dissected leaves with three leaflets at the tip. We show that development of the trifoliate leaves is determined by the Cys(2)His(2) zinc finger transcription factor PALM1. Loss-of-function mutants of PALM1 develop dissected leaves with five leaflets clustered at the tip. We demonstrate that PALM1 binds a specific promoter sequence and down-regulates the expression of the M. truncatula LEAFY/UNIFOLIATA orthologue SINGLE LEAFLET1 (SGL1), encoding an indeterminacy factor necessary for leaflet initiation. Our data indicate that SGL1 is required for leaflet proliferation in the palm1 mutant. Interestingly, ectopic expression of PALM1 effectively suppresses the lobed leaf phenotype from overexpression of a class 1 KNOTTED1-like homeobox protein in Arabidopsis plants. Taken together, our results show that PALM1 acts as a determinacy factor, regulates the spatial-temporal expression of SGL1 during leaf morphogenesis and together with the LEAFY/UNIFOLIATA orthologue plays an important role in orchestrating the compound leaf morphology in M. truncatula.
Precision Spectroscopy of Polarized Molecules in an Ion Trap

Toward a New Physics The search for physics beyond the Standard Model is carried out at accelerator facilities such as the Large Hadron Collider but also on a smaller scale in atomic and molecular physics experiments. One of the signatures of this “new physics” would be a nonvanishing electric dipole moment of the electron, but experiments designed to look for it need to distinguish between the signal and many potential artifacts. Loh et al. (p. 1220) introduce a method based on the spectroscopy of polarized molecular ions that avoids some of the sources of systematic error. A method to measure the electric dipole moment of the electron is demonstrated by using polarized trapped molecular ions. Polar molecules are desirable systems for quantum simulations and cold chemistry. Molecular ions are easily trapped, but a bias electric field applied to polarize them tends to accelerate them out of the trap. We present a general solution to this issue by rotating the bias field slowly enough for the molecular polarization axis to follow but rapidly enough for the ions to stay trapped. We demonstrate Ramsey spectroscopy between Stark-Zeeman sublevels in 180Hf19F+ with a coherence time of 100 milliseconds. Frequency shifts arising from well-controlled topological (Berry) phases are used to determine magnetic g factors. The rotating-bias-field technique may enable using trapped polar molecules for precision measurement and quantum information science, including the search for an electron electric dipole moment.
Computational study on the effects of exhaust gas recirculation on thermal and emission characteristics of HCCI diesel engine

Received: 04 Jun 2018 Accepted: 20 Nov 2018 Published: 01 Dec 2018 In this paper, a computational in-cylinder analysis of HCCI diesel engine was carried out using IC Engine FORTE (ANSYS 18.2) software package. The analysis used pre-defined industry standard CHEMKIN format for specifying a chemical reaction mechanism during the combustion duration. The investigation was carried out for the effects of various EGR mass percentages on the thermal and emission characteristics of a diesel engine running on HCCI mode of combustion. It was observed that an increase in EGR concentration resulted in the decrease in peak in-cylinder pressure and temperature and it was also found that when the EGR rates were increased beyond 75% there was no combustion happening within the cylinder. A considerable decrease in the NOx emissions was found with an increase in EGR mass percentage with almost negligible values when the EGR rates were increased beyond 50%, however there was a slight increase in un-burnt hydrocarbons.
Effect of the kappa opioid agonist R-84760 on cocaine-induced increases in striatal dopamine levels and cocaine-induced place preference in C57BL/6J mice.

RATIONALE While the effects of several kappa opioid receptor agonists on cocaine-induced reward have been studied, such effects of R-84760, a novel non-peptidic, potent and selective kappa opioid agonist that has been studied in humans, are not yet known. OBJECTIVE To study the effects of R-84760 on basal levels of dopamine, cocaine-induced increases in dopamine levels, cocaine-induced conditioned place preference and locomotor activity in mice. METHODS In the first experiment, R-84760 was administered i.p. (0, 0.01, 0.05 or 0.1 mg/kg) to C57BL/6J mice. Its effect on basal dopamine levels in the caudate putamen was measured with in vivo microdialysis. In the second experiment, the effect of pretreatment with 0.1 mg/kg R-84760 on cocaine-induced increases in dopamine levels was studied. The third experiment examined the effect of R-84760 (0.1 mg/kg) on the development of cocaine-induced conditioned place preference and locomotor activity in the conditioning chamber. RESULTS R-84760 decreased dopamine levels in a dose-dependent manner. The highest dose of R-84760 (0.1 mg/kg, i.p.) significantly decreased dopamine levels relative to vehicle, an effect completely blocked by pre-injection with 10 mg/kg of the kappa-opioid receptor antagonist nor-binaltorphimine (nor-BNI). The same dose of R-84760 blocked cocaine-induced increases in dopamine levels, cocaine-induced conditioned place preference and attenuated cocaine-induced locomotor response. CONCLUSION These findings suggest that R-84760 decreases dopamine levels in the caudate putamen through kappa-opioid receptors. The inhibitory effect of R-84760 on striatal dopamine may contribute to its blockade of cocaine-induced increases in dopamine levels, cocaine-induced conditioned place preference and the associated increases in locomotor activity.
A New Knn Categorization Algorithm for Harmful Information Filtering

The prediction result of classifier is biased towards the class with more samples, when the harmful text information is filtered. This is because that the samples that including the harmful information were difficult to gain. Construct virtual samples is an effective means to solve the problem of pattern recognition in the small sample, using the up-sampling method to construct virtual samples in the data layer, the traditional KNN algorithm has been improved: a small sample set is divided into clusters by using the K-means clustering, the virtual samples are generated and verified the validity in the cluster. The experimental results show that this method can construct the virtual samples which are similar to the real sample characteristics, and improved the classification effect of KNN algorithm.
Random access heterogeneous MIMO networks

This paper presents the design and implementation of 802.11n+, a fully distributed random access protocol for MIMO networks. 802.11n+ allows nodes that differ in the number of antennas to contend not just for time, but also for the degrees of freedom provided by multiple antennas. We show that even when the medium is already occupied by some nodes, nodes with more antennas can transmit concurrently without harming the ongoing transmissions. Furthermore, such nodes can contend for the medium in a fully distributed way. Our testbed evaluation shows that even for a small network with three competing node pairs, the resulting system about doubles the average network throughput. It also maintains the random access nature of today's 802.11n networks.
Topological phases of fermions in one dimension

In this paper we show how the classification of topological phases in insulators and superconductors is changed by interactions, in the case of one-dimensional systems. We focus on the time-reversal-invariant Majorana chain (BDI symmetry class). While the band classification yields an integer topological index k, it is known that phases characterized by values of k in the same equivalence class modulo 8 can be adiabatically transformed one to another by adding suitable interaction terms. Here we show that the eight equivalence classes are distinct and exhaustive, and provide a physical interpretation for the interacting invariant modulo 8. The different phases realize different Altland-Zirnbauer classes of the reduced density matrix for an entanglement bipartition into two half chains. We generalize these results to the classification of all one-dimensional gapped phases of fermionic systems with possible antiunitary symmetries, utilizing the algebraic framework of central extensions. We use matrix product state methods to prove our results.
Role of IL-17 and regulatory T lymphocytes in a systemic autoimmune disease

To explore the interactions between regulatory T cells and pathogenic effector cytokines, we have developed a model of a T cell–mediated systemic autoimmune disorder resembling graft-versus-host disease. The cytokine responsible for tissue inflammation in this disorder is interleukin (IL)-17, whereas interferon (IFN)-γ produced by Th1 cells has a protective effect in this setting. Because of the interest in potential therapeutic approaches utilizing transfer of regulatory T cells and inhibition of the IL-2 pathway, we have explored the roles of these in the systemic disease. We demonstrate that the production of IL-17 and tissue infiltration by IL-17–producing cells occur and are even enhanced in the absence of IL-2. Regulatory T cells favor IL-17 production but prevent the disease when administered early in the course by suppressing expansion of T cells. Thus, the pathogenic or protective effects of cytokines and the therapeutic capacity of regulatory T cells are crucially dependent on the timing and the nature of the disease.
A Signal Processing Analysis of Purkinje Cells in vitro

Cerebellar Purkinje cells in vitro fire recurrent sequences of Sodium and Calcium spikes. Here, we analyze the Purkinje cell using harmonic analysis, and our experiments reveal that its output signal is comprised of three distinct frequency bands, which are combined using Amplitude and Frequency Modulation (AM/FM). We find that the three characteristic frequencies – Sodium, Calcium and Switching – occur in various combinations in all waveforms observed using whole-cell current clamp recordings. We found that the Calcium frequency can display a frequency doubling of its frequency mode, and the Switching frequency can act as a possible generator of pauses that are typically seen in Purkinje output recordings. Using a reversibly photo-switchable kainate receptor agonist, we demonstrate the external modulation of the Calcium and Switching frequencies. These experiments and Fourier analysis suggest that the Purkinje cell can be understood as a harmonic signal oscillator, enabling a higher level of interpretation of Purkinje signaling based on modern signal processing techniques.
A Choice Relation Framework for Supporting Category-Partition Test Case Generation

We describe in this paper a choice relation framework for supporting category-partition test case generation. We capture the constraints among various values (or ranges of values) of the parameters and environment conditions identified from the specification, known formally as choices. We express these constraints in terms of relations among choices and combinations of choices, known formally as test frames. We propose a theoretical backbone and techniques for consistency checks and automatic deductions of relations. Based on the theory, algorithms have been developed for generating test frames from the relations. These test frames can then be used as the basis for generating test cases. Our algorithms take into consideration the resource constraints specified by software testers, thus maintaining the effectiveness of the test frames (and hence test cases) generated.
High speciation rate at temperate latitudes explains unusual diversity gradients in a clade of ectomycorrhizal fungi

Understanding the patterns of biodiversity through time and space is a challenging task. However, phylogeny‐based macroevolutionary models allow us to account and measure many of the processes responsible for diversity buildup, namely speciation and extinction. The general latitudinal diversity gradient (LDG) is a well‐recognized pattern describing a decline in species richness from the equator polewards. Recent macroecological studies in ectomycorrhizal (EM) fungi have shown that their LDG is shifted, peaking at temperate rather than tropical latitudes. Here we investigate this phenomenon from a macroevolutionary perspective, focusing on a well‐sampled group of edible EM mushrooms from the genus Amanita—the Caesar's mushrooms, which follow similar diversity patterns. Our approach consisted in applying a suite of models including (1) nontrait‐dependent time‐varying diversification (Bayesian analysis of macroevolutionary mixtures [BAMM]), (2) continuous trait‐dependent diversification (quantitative‐state speciation and extinction [QuaSSE]), and (3) diversity‐dependent diversification. In short, results give strong support for high speciation rates at temperate latitudes (BAMM and QuaSSE). We also find some evidence for different diversity‐dependence thresholds in “temperate” and “tropical” subclades, and little differences in diversity due to extinction. We conclude that our analyses on the Caesar's mushrooms give further evidence of a temperate‐peaking LDG in EM fungi, highlighting the importance and the implications of macroevolutionary processes in explaining diversity gradients in microorganisms.