Hypergraph Acyclicity and Propositional Model Counting

We show that the propositional model counting problem #SAT for CNF- formulas with hypergraphs that allow a disjoint branches decomposition can be solved in polynomial time. We show that this class of hypergraphs is incomparable to hypergraphs of bounded incidence cliquewidth which were the biggest class of hypergraphs for which #SAT was known to be solvable in polynomial time so far. Furthermore, we present a polynomial time algorithm that computes a disjoint branches decomposition of a given hypergraph if it exists and rejects otherwise. Finally, we show that some slight extensions of the class of hypergraphs with disjoint branches decompositions lead to intractable #SAT, leaving open how to generalize the counting result of this paper

Effet d'une expérimentation de brassage artificiel epilimnique par aération sur les poussées cyanobactériennes dans la retenue hypereutrophe de Grangent (France)

Dans la retenue hypereutrophe de Grangent, le phytoplancton estival est dominé par la cyanobactérie Microcystis aeruginosa. Dans le but de lutter contre la formation de ces blooms cyanobactériens, une expérimentation de brassage artificiel épilimnique par aération a été réalisée en 1997-1998. Ce dispositif avait pour but de créer des turbulences supprimant l'avantage adaptatif que constitue, chez M. aeruginosa, la faculté de réguler sa flottabilité. Il devait également permettre l'homogénéisation des teneurs en oxygène dissous, la réduction des pics de pH, de la turbidité des eaux superficielles et des teneurs en ammonium.Les résultats escomptés ont été vérifiés pour les paramètres physicochimiques. Les valeurs se sont révélées plus homogènes, mais seulement à proximité des lignes de brassage et uniquement jusqu'à 10 m de profondeur. En revanche, les blooms cyanobactériens n'ont pas été réduits. Il apparaît même au contraire que, sous l'influence du mélange, les cyanobactéries ont eu à leur disposition une plus grande quantité de nutriments qu'elles ont utilisés pour constituer des réserves glucidiques. Ainsi, en aval de la zone brassée, ces réserves ont permis une synthèse protéique plus importante.Sur la retenue de Grangent, le dispositif de brassage peut offrir une solution palliative du point de vue touristique en limitant l'accumulation de cyanobactéries en surface, mais il ne permet pas d'éliminer, ni même de diminuer, les proliférations de M. aeruginosa en période estivale.In the reservoir of Grangent, a highly eutrophic lake located on the upper part of the Loire River, about 10 miles south of Saint-Étienne (France), Microcystis aeruginosa usually dominates the phytoplankton community in late summer and early autumn for many years. Mass developments of this cyanobacterium led to serious difficulties in multi-purpose usage. In order to fight against blooms, an epilimnic artificial mixing was experimented. M. aeruginosa is adapted to stable stratification of the water column. Therefore, partial destratification or bubbling with air are employed to replace M. aeruginosa by better grazable, non- " blooming " and non-toxic species. This cyanobacterium is supposed to lose its advantage of buoyancy and to reduce his growth. This system was also employed to reduce peaks of pH, turbidity of surface waters and concentration of NH4 and to homogenize the dissolved oxygen concentration inside the water column. Three lines of mixing were tested in 1998: one located at "Châtelet", upstream of reservoir, measuring 700 m at 11 m depth; one near the beach of Saint-Victor, with the same length and immersed to 15 m depth and, finally, a line of 400 m, near the port, at 16 m depth (figure 1).Data were collected from representative sites, upstream, near and downstream the artificial mixing. They were sampled weekly since April to November 1998. At each site the vertical profiles of temperature and dissolved oxygen were measured (figure 2). For each sample, the parameters following were analyzed: pH, NO3, NH4, PO4, carbohydrates, proteins, chlorophyll a and phytoplankton enumeration.Concerning the physicochemical parameters, the assumptions were checked: the values appeared more homogeneous near the lines of mixing than at the other stations. For example, the average temperatures varied between 20,6°C (at 10 m depth) and 21,3°C (at 0,5 m depth) at Saint-Victor. This variation reached 1,3°C at the station Camaldules. On the other hand, this effect was perceived only up to 10 m of depth and at a limited distance of mixing.In the same way, the colonies of M. aeruginosa were mixed in the water column but only up 10 m depth and near mixing. Moreover, their growth has not decreased on the whole of reservoir. In period of bloom (August 25), G/P ratio was higher in the mixing zone than in the neighbourhoods, primarily because of an increase in carbohydrates (figure 3). In the mixed zone, M. aeruginosa seemed to benefit greater quantity of mineral elements it could use to constitute carbohydrates reserves (figure 4). In this way, when the conditions that became less favourable, like downstream, cyanobacteria were able to follow their development by synthesizing proteins starting from their reserves in carbohydrates.In the reservoir of Grangent, artificial mixing did not allow to fight effectively against blooms of cyanobacteria. Colonies of M. aeruginosa were simply diluted in the water column near mixing but did not reduce their growth

Physics-informed Gaussian Process for Online Optimization of Particle Accelerators

High-dimensional optimization is a critical challenge for operating large-scale scientific facilities. We apply a physics-informed Gaussian process (GP) optimizer to tune a complex system by conducting efficient global search. Typical GP models learn from past observations to make predictions, but this reduces their applicability to new systems where archive data is not available. Instead, here we use a fast approximate model from physics simulations to design the GP model. The GP is then employed to make inferences from sequential online observations in order to optimize the system. Simulation and experimental studies were carried out to demonstrate the method for online control of a storage ring. We show that the physics-informed GP outperforms current routinely used online optimizers in terms of convergence speed, and robustness on this task. The ability to inform the machine-learning model with physics may have wide applications in science

Electron beam shaping via laser heater temporal shaping

Active longitudinal beam optics can help FEL facilities achieve cutting edge performance by optimizing the beam to: produce multi-color pulses, suppress caustics, or support attosecond lasing. As the next generation of superconducting accelerators comes online, there is a need to find new elements which can both operate at high beam power and which offer multiplexing capabilities at Mhz repetition rate. Laser heater shaping promises to satisfy both criteria by imparting a programmable slice-energy spread on a shot-by-shot basis. We use a simple kinetic analysis to show how control of the slice energy spread translates into control of the bunch current profile, and then we present a collection of start-to-end simulations at LCLS-II in order to illustrate the technique.Comment: 12 pages, 11 figure

Lapses in Responsiveness: Characteristics and Detection from the EEG

Performance lapses in occupations where public safety is paramount can have disastrous consequences, resulting in accidents with multiple fatalities. Drowsy individuals performing an active task, like driving, often cycle rapidly between periods of wake and sleep, as exhibited by cyclical variation in both EEG power spectra and task performance measures. The aim of this project was to identify reliable physiological cues indicative of lapses, related to behavioural microsleep episodes, from the EEG, which could in turn be used to develop a real-time lapse detection (or better still, prediction) system. Additionally, the project also sought to achieve an increased understanding of the characteristics of lapses in responsiveness in normal subjects. A study was conducted to determine EEG and/or EOG cues (if any) that expert raters use to detect lapses that occur during a psychomotor vigilance task (PVT), with the subsequent goal of using these cues to design an automated system. A previously-collected dataset comprising physiological and performance data of 10 air traffic controllers (ATCs) was used. Analysis showed that the experts were unable to detect the vast majority of lapses based on EEG and EOG cues. This suggested that, unlike automated sleep staging, an automated lapse detection system needed to identify features not generally visible in the EEG. Limitations in the ATC dataset led to a study where more comprehensive physiological and performance data were collected from normal subjects. Fifteen non-sleep-deprived male volunteers aged 18-36 years were recruited. All performed a 1-D continuous pursuit visuomotor tracking task for 1 hour during each of two sessions that occurred between 1 and 7 weeks apart. A video camera was used to record head and facial expressions of the subject. EEG was recorded from electrodes at 16 scalp locations according to the 10-20 system at 256 Hz. Vertical and horizontal EOG was also recorded. All experimental sessions were held between 12:30 and 17:00 hours. Subjects were asked to refrain from consuming stimulants or depressants, for 4 h prior to each session. Rate and duration were estimated for lapses identified by a tracking flat spot and/or video sleep. Fourteen of the 15 subjects had one or more lapses, with an overall rate of 39.3 ± 12.9 lapses per hour (mean ± SE) and a lapse duration of 3.4 ± 0.5 s. The study also showed that lapsing and tracking error increased during the first 30 or so min of a 1-h session, then decreased during the remaining time, despite the absence of external temporal cues. EEG spectral power was found to be higher during lapses in the delta, theta, and alpha bands, and lower in the beta, gamma, and higher bands, but correlations between changes in EEG power and lapses were low. Thus, complete lapses in responsiveness are a frequent phenomenon in normal subjects - even when not sleep-deprived - undertaking an extended, monotonous, continuous visuomotor task. This is the first study to investigate and report on the characteristics of complete lapses of responsiveness during a continuous tracking task in non-sleep-deprived subjects. The extent to which non-sleep-deprived subjects experience complete lapses in responsiveness during normal working hours was unexpected. Such findings will be of major concern to individuals and companies in various transport sectors. Models based on EEG power spectral features, such as power in the traditional bands and ratios between bands, were developed to detect the change of brain state during behavioural microsleeps. Several other techniques including spectral coherence and asymmetry, fractal dimension, approximate entropy, and Lempel-Ziv (LZ) complexity were also used to form detection models. Following the removal of eye blink artifacts from the EEG, the signal was transformed into z-scores relative to the baseline of the signal. An epoch length of 2 s and an overlap of 1 s (50%) between successive epochs were used for all signal processing algorithms. Principal component analysis was used to reduce redundancy in the features extracted from the 16 EEG derivations. Linear discriminant analysis was used to form individual classification models capable of detecting lapses using data from each subject. The overall detection model was formed by combining the outputs of the individual models using stacked generalization with constrained least-squares fitting used to determine the optimal meta-learner weights of the stacked system. The performance of the lapse detector was measured both in terms of its ability to detect lapse state (in 1-s epochs) and lapse events. Best performance in lapse state detection was achieved using the detector based on spectral power (SP) features (mean correlation of φ = 0.39 ± 0.06). Lapse event detection performance using SP features was moderate at best (sensitivity = 73.5%, selectivity = 25.5%). LZ complexity feature-based detector showed the highest performance (φ = 0.28 ± 0.06) out of the 3 non-linear feature-based detectors. The SP+LZ feature-based model had no improvement in performance over the detector based on SP alone, suggesting that LZ features contributed no additional information. Alpha power contributed the most to the overall SP-based detection model. Analysis showed that the lapse detection model was detecting phasic, rather than tonic, changes in the level of drowsiness. The performance of these EEG-based lapse detection systems is modest. Further research is needed to develop more sensitive methods to extract cues from the EEG leading to devices capable of detecting and/or predicting lapses

In-situ Apparent Conductivity Measurements and Microbial Population Distribution at a Hydrocarbon-Contaminated Site

We investigated the bulk electrical conductivity and microbial population distribution in sediments at a site contaminated with light nonaqueous-phase liquid (LNAPL). The bulk conductivity was measured using in-situ vertical resistivity probes; the most probable number method was used to characterize the spatial distribution of aerobic heterotrophic and oil-degrading microbial populations. The purpose of this study was to assess if high conductivity observed at aged LNAPL-impacted sites may be related to microbial degradation of LNAPL. The results show higher bulk conductivity coincident with LNAPL-impacted zones, in contrast to geoelectrical models that predict lower conductivity in such zones. The highest bulk conductivity was observed to be associated with zones impacted by residual and free LNAPL. Data from bacteria enumeration from sediments close to the resistivity probes show that oil-degrading microbes make up a larger percentage (5-55%) of the heterotrophic microbial community at depths coincident with the higher conductivity compared to ∼5% at the uncontaminated location. The coincidence of a higher percentage of oil-degrading microbial populations in zones of higher bulk conductivity suggests that the higher conductivity in these zones may result from increased fluid conductivity related to microbial degradation of LNAPL, consistent with geochemical studies that suggest that intrinsic biodegradation is occurring at the site. The findings from this study point to the fact that biogeochemical processes accompanying biodegradation of contaminants can potentially alter geoelectrical properties of the subsurface impacted media

Evidence for Microbial Enhanced Electrical Conductivity in Hydrocarbon-Contaminated Sediments

Bulk electrical conductivity of sediments during microbial mineralization of diesel was investigated in a mesoscale laboratory experiment consisting of biotic contaminated and uncontaminated columns. Population numbers of oil degrading microorganisms increased with a clear pattern of depth zonation within the contaminated column not observed in the uncontaminated column. Microbial community structure determined from ribosomal DNA intergenic spacer analysis showed a highly specialized microbial community in the contaminated column. The contaminated column showed temporal increases in bulk conductivity, dissolved inorganic carbon, and calcium, suggesting that the high bulk conductivity is due to enhanced mineral weathering from microbial activity. The greatest change in bulk conductivity occurred in sediments above the water table saturated with diesel. Variations in electrical conductivity magnitude and microbial populations and their depth distribution in the contaminated column are similar to field observations. The results of this study suggest that geophysical methodologies may potentially be used to investigate microbial activity

DEvIANT: Discovering Significant Exceptional (Dis-)Agreement Within Groups

We strive to find contexts (i.e., subgroups of entities) under which exceptional (dis-)agreement occurs among a group of individuals , in any type of data featuring individuals (e.g., parliamentarians , customers) performing observable actions (e.g., votes, ratings) on entities (e.g., legislative procedures, movies). To this end, we introduce the problem of discovering statistically significant exceptional contextual intra-group agreement patterns. To handle the sparsity inherent to voting and rating data, we use Krippendorff's Alpha measure for assessing the agreement among individuals. We devise a branch-and-bound algorithm , named DEvIANT, to discover such patterns. DEvIANT exploits both closure operators and tight optimistic estimates. We derive analytic approximations for the confidence intervals (CIs) associated with patterns for a computationally efficient significance assessment. We prove that these approximate CIs are nested along specialization of patterns. This allows to incorporate pruning properties in DEvIANT to quickly discard non-significant patterns. Empirical study on several datasets demonstrates the efficiency and the usefulness of DEvIANT. Technical Report Associated with the ECML/PKDD 2019 Paper entitled: "DEvIANT: Discovering Significant Exceptional (Dis-)Agreement Within Groups"

Search for New Physics with Jets and Missing Transverse Momentum in pp collisions at sqrt(s) = 7 TeV

A search for new physics is presented based on an event signature of at least three jets accompanied by large missing transverse momentum, using a data sample corresponding to an integrated luminosity of 36 inverse picobarns collected in proton--proton collisions at sqrt(s)=7 TeV with the CMS detector at the LHC. No excess of events is observed above the expected standard model backgrounds, which are all estimated from the data. Exclusion limits are presented for the constrained minimal supersymmetric extension of the standard model. Cross section limits are also presented using simplified models with new particles decaying to an undetected particle and one or two jets