Droplet and cluster formation in freely falling granular streams

Particle beams are important tools for probing atomic and molecular interactions. Here we demonstrate that particle beams also offer a unique opportunity to investigate interactions in macroscopic systems, such as granular media. Motivated by recent experiments on streams of grains that exhibit liquid-like breakup into droplets, we use molecular dynamics simulations to investigate the evolution of a dense stream of macroscopic spheres accelerating out of an opening at the bottom of a reservoir. We show how nanoscale details associated with energy dissipation during collisions modify the stream's macroscopic behavior. We find that inelastic collisions collimate the stream, while the presence of short-range attractive interactions drives structure formation. Parameterizing the collision dynamics by the coefficient of restitution (i.e., the ratio of relative velocities before and after impact) and the strength of the cohesive interaction, we map out a spectrum of behaviors that ranges from gas-like jets in which all grains drift apart to liquid-like streams that break into large droplets containing hundreds of grains. We also find a new, intermediate regime in which small aggregates form by capture from the gas phase, similar to what can be observed in molecular beams. Our results show that nearly all aspects of stream behavior are closely related to the velocity gradient associated with vertical free fall. Led by this observation, we propose a simple energy balance model to explain the droplet formation process. The qualitative as well as many quantitative features of the simulations and the model compare well with available experimental data and provide a first quantitative measure of the role of attractions in freely cooling granular streams

The Transformation of Sediment Into Rock : Insights From IODP Site U1352, Canterbury Basin, New Zealand

ACKNOWLEDGMENTS We thank the crew of the RV JOIDES Resolution for professional seamanship, excellent drilling, and the scientific support on board. GHB and SCG thank the Australia–New Zealand IODP Consortium (ANZIC), and KMM thanks the Consortium for Ocean Leadership U.S. Science Support Program for partly funding this work. Thanks also to funding agencies of the respective authors, and Mark Lawrence (GNS Science) and Cam Nelson (University of Waikato) for their thoughtful comments on an earlier draft. Karsten Kroeger (GNS Science) helped by providing compaction data for New Zealand basins, and Michelle Kominz (Western Michigan University) provided data on which Figure 8 was developed. Further improvements were the result of thoughtful detailed reviews by Gemma Barrie, Bill Heins, Stan Paxton, Associate Editor Joe Macquaker, and Editor Leslie Melim.Peer reviewedPostprin

Presynchronizing PGF2α and GnRH injections before timed artificial insemination CO-Synch + CIDR program

Fixed-time artificial insemination is an effective management tool that reduces the labor associated with more conventional artificial insemination programs requiring detection of estrus. The 7-day CO-Synch + controlled internal drug release (CIDR) insert protocol has been shown to effectively initiate estrus and ovulation in cycling and non-cycling suckled beef cows, producing pregnancy rates at or greater than 50% in beef cows. The gonadotropin-releasing hormone (GnRH) injection that begins the CO-Synch + CIDR program initiates ovulation in a large proportion of cows, particularly anestrous cows. The CIDR, which releases progesterone intravaginally, prevents short estrous cycles that usually follow the first postpartum ovulation in beef cows. Our hypothesis was that inducing estrus with a prostaglandin injection followed 3 days later with a GnRH injection, 7 days before applying the 7-day CO-Synch + CIDR protocol, might increase the percentage of cycling cows that would exhibit synchronous follicular waves after the onset of the CO-Synch + CIDR protocol. We also hypothesized that the additional GnRH injection would increase the percentage of anestrous cows that would ovulate, thereby increasing pregnancy outcomes

Role of N-methyl-D-aspartate receptors in action-based predictive coding deficits in schizophrenia

Published in final edited form as:Biol Psychiatry. 2017 March 15; 81(6): 514–524. doi:10.1016/j.biopsych.2016.06.019.BACKGROUND: Recent theoretical models of schizophrenia posit that dysfunction of the neural mechanisms subserving predictive coding contributes to symptoms and cognitive deficits, and this dysfunction is further posited to result from N-methyl-D-aspartate glutamate receptor (NMDAR) hypofunction. Previously, by examining auditory cortical responses to self-generated speech sounds, we demonstrated that predictive coding during vocalization is disrupted in schizophrenia. To test the hypothesized contribution of NMDAR hypofunction to this disruption, we examined the effects of the NMDAR antagonist, ketamine, on predictive coding during vocalization in healthy volunteers and compared them with the effects of schizophrenia. METHODS: In two separate studies, the N1 component of the event-related potential elicited by speech sounds during vocalization (talk) and passive playback (listen) were compared to assess the degree of N1 suppression during vocalization, a putative measure of auditory predictive coding. In the crossover study, 31 healthy volunteers completed two randomly ordered test days, a saline day and a ketamine day. Event-related potentials during the talk/listen task were obtained before infusion and during infusion on both days, and N1 amplitudes were compared across days. In the case-control study, N1 amplitudes from 34 schizophrenia patients and 33 healthy control volunteers were compared. RESULTS: N1 suppression to self-produced vocalizations was significantly and similarly diminished by ketamine (Cohen’s d = 1.14) and schizophrenia (Cohen’s d = .85). CONCLUSIONS: Disruption of NMDARs causes dysfunction in predictive coding during vocalization in a manner similar to the dysfunction observed in schizophrenia patients, consistent with the theorized contribution of NMDAR hypofunction to predictive coding deficits in schizophrenia.This work was supported by AstraZeneca for an investigator-initiated study (DHM) and the National Institute of Mental Health Grant Nos. R01 MH-58262 (to JMF) and T32 MH089920 (to NSK). JHK was supported by the Yale Center for Clinical Investigation Grant No. UL1RR024139 and the US National Institute on Alcohol Abuse and Alcoholism Grant No. P50AA012879. (AstraZeneca for an investigator-initiated study (DHM); R01 MH-58262 - National Institute of Mental Health; T32 MH089920 - National Institute of Mental Health; UL1RR024139 - Yale Center for Clinical Investigation; P50AA012879 - US National Institute on Alcohol Abuse and Alcoholism)Accepted manuscrip

Advances in Biologically Inspired Reservoir Computing

The interplay between randomness and optimization has always been a major theme in the design of neural networks [3]. In the last 15 years, the success of reservoir computing (RC) showed that, in many scenarios, the algebraic structure of the recurrent component is far more important than the precise fine-tuning of its weights. As long as the recurrent part of the network possesses a form of fading memory of the input, the dynamics of the neurons are enough to efficiently process many spatio-temporal signals, provided that their activations are sufficiently heterogeneous. Even if today it is feasible to fully optimize deep recurrent networks, their implementation still requires a vast degree of experience and practice, not to mention vast computational resources, limiting their applicability in simpler architectures (e.g., embedded systems) or in areas where time is of key importance (e.g., online systems). Not surprisingly, then, RC remains a powerful tool for quickly solving dynamical problems, and it has become an invaluable tool for modeling and analysis in neuroscience

EFFECT OF AVITROL BAITING ON BIRD DAMAGE TO RIPENING SUNFLOWER WITHIN A 144-SECTION BLOCK OF NORTH DAKOTA

The chemical frightening agent 4-aminopyridine (4-AP) has been repeatedly tested as a means of protecting both ripening corn (De Grazio et al. 1971, 1972; Besser et al. 1973; Besser 1976; Dolbeer et al. 1976; Stickley et al. 1972, 1976; Woronecki et al. 1979) and sunflower (Besser and Guarino 1976; Besser and Pfeifer 1978; Henne et al. 1979; Besser et al. in press) from depredating blackbirds. It was reported that less than one percent of a flock need ingest the treated baits and respond with distress symptoms in order to move birds from a corn field (De Grazio et al. 1972) or even shift roosting aggregations from night roosts (Cummings 1979). However, there is still conflicting evidence as to whether frightened blackbirds will subsequently avoid nearby fields, or even the same treated fields, resulting in efficient protection. The efficacy of 4-AP has not been resolved because of questions about the presentation and formulation of the treated baits and the difficulty of conducting a valid, unambiguous field test. This study was a large-scale evaluation of AvitroⓇ (HCI) FC-Corn Chops-99S1, where all commercial sunflower fields were monitored within a 144-sq mi block centered around a major concentration of roosting blackbirds; and all those fields with significant bird pressure were baited. The test was designed to answer two questions: can selective baiting (1) reduce damage overall when compared with pre-treatment damage from 1981, and (2) disperse it within the block? In other words, can the treatment keep blackbirds out of preferred fields? If so, is the result an overall reduction in damage within the surrounding area, or is it a redistribution of the damage

Dosimetric verification of the anisotropic analytical algorithm for radiotherapy treatment planning

BACKGROUND AND PURPOSE: To investigate the accuracy of photon dose calculations performed by the Anisotropic Analytical Algorithm, in homogeneous and inhomogeneous media and in simulated treatment plans. MATERIALS AND METHODS: Predicted dose distributions were compared with ionisation chamber and film measurements for a series of increasingly complex situations. Initially, simple and complex fields in a homogeneous medium were studied. The effect of inhomogeneities was investigated using a range of phantoms constructed of water, bone and lung substitute materials. Simulated treatment plans were then produced using a semi-anthropomorphic phantom and the delivered doses compared to the doses predicted by the Anisotropic Analytical Algorithm. RESULTS: In a homogeneous medium, agreement was found to be within 2% dose or 2mm dta in most instances. In the presence of heterogeneities, agreement was generally to within 2.5%. The simulated treatment plan measurements agreed to within 2.5% or 2mm. Conclusions: The accuracy of the algorithm was found to be satisfactory at 6MV and 10MV both in homogeneous and inhomogeneous situations and in the simulated treatment plans. The algorithm was more accurate than the Pencil Beam Convolution model, particularly in the presence of low density heterogeneities