The Dynamical State of Barnard 68: A Thermally Supported, Pulsating Dark Cloud

We report sensitive, high resolution molecular-line observations of the dark cloud Barnard 68 obtained with the IRAM 30-m telescope. We analyze spectral-line observations of C18O, CS(2--1), C34S(2--1), and N2H+(1--0) in order to investigate the kinematics and dynamical state of the cloud. We find extremely narrow linewidths in the central regions of the cloud. These narrow lines are consistent with thermally broadened profiles for the measured gas temperature of 10.5 K. We determine the thermal pressure to be a factor 4 -- 5 times greater than the non-thermal (turbulent) pressure in the central regions of the cloud, indicating that thermal pressure is the primary source of support against gravity in this cloud. This confirms the inference of a thermally supported cloud drawn previously from deep infrared extinction measurements. The rotational kinetic energy is found to be only a few percent of the gravitational potential energy, indicating that the contribution of rotation to the overall stability of the cloud is insignificant. Finally, our observations show that CS line is optically thick and self-reversed across nearly the entire projected surface of the cloud. The shapes of the self-reversed profiles are asymmetric and are found to vary across the cloud in such a manner that the presence of both inward and outward motions are observed within the cloud. Moreover, these motions appear to be globally organized in a clear and systematic alternating spatial pattern which is suggestive of a small amplitude, non-radial oscillation or pulsation of the outer layers of the cloud about an equilibrium configuration.Comment: To appear in the Astrophysical Journal; 23 pages, 8 figures; Manuscript and higher resolution images can be obtained at http://cfa-www.harvard.edu/~ebergin/pubs_html/b68_vel.htm

The HSV-1 Latency-Associated Transcript Functions to Repress Latent Phase Lytic Gene Expression and Suppress Virus Reactivation from Latently Infected Neurons

open access articleHerpes simplex virus 1 (HSV-1) establishes life-long latent infection within sensory neurons, during which viral lytic gene expression is silenced. The only highly expressed viral gene product during latent infection is the latency-associated transcript (LAT), a non-protein coding RNA that has been strongly implicated in the epigenetic regulation of HSV-1 gene expression. We have investigated LAT-mediated control of latent gene expression using chromatin immunoprecipitation analyses and LAT-negative viruses engineered to express firefly luciferase or β-galactosidase from a heterologous lytic promoter. Whilst we were unable to determine a significant effect of LAT expression upon heterochromatin enrichment on latent HSV-1 genomes, we show that reporter gene expression from latent HSV-1 genomes occurs at a greater frequency in the absence of LAT. Furthermore, using luciferase reporter viruses we have observed that HSV-1 gene expression decreases during long-term latent infection, with a most marked effect during LAT-negative virus infection. Finally, using a fluorescent mouse model of infection to isolate and culture single latently infected neurons, we also show that reactivation occurs at a greater frequency from cultures harbouring LAT-negative HSV-1. Together, our data suggest that the HSV-1 LAT RNA represses HSV-1 gene expression in small populations of neurons within the mouse TG, a phenomenon that directly impacts upon the frequency of reactivation and the maintenance of the transcriptionally active latent reservoir

A Fast Algorithm For Sparse Multichannel Blind Deconvolution

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)We have addressed blind deconvolution in a multichannel framework. Recently, a robust solution to this problem based on a Bayesian approach called sparse multichannel blind deconvolution (SMBD) was proposed in the literature with interesting results. However, its computational complexity can be high. We have proposed a fast algorithm based on the minimum entropy deconvolution, which is considerably less expensive. We designed the deconvolution filter to minimize a normalized version of the hybrid l(1)/l(2)-norm loss function. This is in contrast to the SMBD, in which the hybrid l(1)/l(2)-norm function is used as a regularization term to directly determine the deconvolved signal. Results with synthetic data determined that the performance of the obtained deconvolution filter was similar to the one obtained in a supervised framework. Similar results were also obtained in a real marine data set for both techniques.811V7V16CAPESCNPqPetrobrasCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq

Chandra HRC Localization of the Low Mass X-ray Binaries X1624-490 and X1702-429: The Infrared Counterparts

We report on the precise localization of the low mass X-ray binaries X1624-490 and X1702-429 with the Chandra HRC-I. We determine the best positions to be 16:28:02.825 -49:11:54.61 (J2000) and 17:06:15.314 -43:02:08.69 (J2000) for X1624-490 and X1702-429, respectively, with the nominal Chandra positional uncertainty of 0.6". We also obtained deep IR observations of the fields of these sources in an effort to identify the IR counterparts. A single, faint (Ks=18.3 +/- 0.1) source is visible inside the Chandra error circle of X1624-490, and we propose this source as its IR counterpart. For X1702-429, a Ks=16.5 +/- 0.07 source is visible at the edge of the Chandra error circle. The brightness of both counterpart candidates is comparable to that of other low mass X-ray binary IR counterparts when corrected for extinction and distance.Comment: 5 pages, 2 figures, accepted for publication in Ap

The nature of the dense core population in the pipe nebula: core and cloud kinematics from C18O observations

We present molecular-line observations of 94 dark cloud cores identified in the Pipe nebula through near-IR extinction mapping. Using the Arizona Radio Observatory 12m telescope, we obtained spectra of these cores in the J=1-0 transition of C18O. We use the measured core parameters, i.e., antenna temperature, linewidth, radial velocity, radius and mass, to explore the internal kinematics of these cores as well as their radial motions through the larger molecular cloud. We find that the vast majority of the dark extinction cores are true cloud cores rather than the superposition of unrelated filaments. While we identify no significant correlations between the core's internal gas motions and the cores' other physical parameters, we identify spatially correlated radial velocity variations that outline two main kinematic components of the cloud. The largest is a 15pc long filament that is surprisingly narrow both in spatial dimensions and in radial velocity. Beginning in the Stem of the Pipe, this filament displays uniformly small C18O linewidths (dv~0.4kms-1) as well as core to core motions only slightly in excess of the gas sound speed. The second component outlines what appears to be part of a large (2pc; 1000 solar mass) ring-like structure. Cores associated with this component display both larger linewidths and core to core motions than in the main cloud. The Pipe Molecular Ring may represent a primordial structure related to the formation of this cloud.Comment: Accepted to ApJ. 14 pages, 11 figures. Complete table at end of documen

Intelligent Sensors for Real-Time Decision-Making

The simultaneous integration of information from sensors with business data and how to acquire valuable information can be challenging. This paper proposes the simultaneous integration of information from sensors and business data. The proposal is supported by an industrial imple mentation, which integrates intelligent sensors and real-time decision-making, using a combination of PLC and PC Platforms in a three-level architecture: cloud-fog-edge. Automatic identification intelligent sensors are used to improve the decision-making of a dynamic scheduling tool. The proposed platform is applied to an industrial use-case in analytical Quality Control (QC) laborato ries. The regulatory complexity, the personalized production, and traceability requirements make QC laboratories an interesting use case. We use intelligent sensors for automatic identification to improve the decision-making of a dynamic scheduling tool. Results show how the integration of intelligent sensors can improve the online scheduling of tasks. Estimations from system processing times decreased by over 30%. The proposed solution can be extended to other applications such as predictive maintenance, chemical industry, and other industries where scheduling and rescheduling are critical factors for the production.This work was supported by FCT, through IDMEC, under LAETA, project UIDB/50022/2020

Dual-resource Constrained Scheduling for Quality Control Laboratories

This work presents a novel formulation for quality control laboratory scheduling considering both equipment and analysts as constraints. The problem is modelled as a dualresource constrained exible job shop problem. The formulation considers analyst's tasks in multiple time points during the processing of samples. The mathematical model is implemented as a mixed integer linear programming model (MILP) aiming to minimize makespan. Two sets of instances for the scheduling problem are developed and solved. The rst instance consists on a small example that illustrates the proposed formulation and is solved to optimality. The second instance mimics the real industrial problem and shows the challenges resulting from growing complexity

Parallel synthesis and high throughput dissolution testing of biodegradable polyanhydride copolymers

We have demonstrated that polycondensation reactions can be carried out in a combinatorial fashion and that the polymer library can be screened at high throughput using a rapid prototyping technique to fabricate multiwell substrates. A linearly varying compositional library of 100 different biodegradable polyanhydride random copolymers that are promising carriers for controlled drug delivery was designed, fabricated, and characterized by IR microscopy within a few hours. The polyanhydride copolymer library was based on 1,6-bis(p-carboxyphenoxy)hexane (CPH) and sebacic anhydride (SA) and was characterized with infrared microspectroscopy to determine the composition within each well. Since degradation and release rates depend on copolymer composition, we also developed new high-throughput methods to investigate drug release from this library of copolymers by designing specific wells for each task. A subset of this library was chosen, and a substrate was designed and fabricated to enable the synthesis and monitoring of dye dissolution from a range of polyanhydride copolymers in a parallel fashion using a CCD camera. Multisample substrates were fabricated with a novel rapid prototyping method that consists of an organic solvent-resistant array of 10 x 10 microwells of 2-μL volume each. The libraries were deposited with a custom-built liquid dispensing system consisting of a series of computer-controlled volume-dispensing pumps and XYZ motion stages. The parallel dye dissolution study displayed a decreasing rate of release with increasing CPH content. This result agrees with previously published data for dye release from poly(CPH-co-SA) copolymers. The methodology described in this work is amenable to numerous applications in the arenas of high-throughput polymer synthesis and characterization

The impact of intelligent automation in internal supply chains

Nowadays, industry is being forced to produce smaller and more diverse batches, increasing the complexity of internal supply chains. Data has become a valuable asset, supporting the development of intelligent automation solutions. Decision support systems, which leverage data, require the automation pyramid to be more flexible, as information needs to be exchanged simultaneously and in real-time with all automation layers. This paper proposes a framework for intelligent automation to deal with current challenges in acquisition and management of data in industrial settings, towards feeding decision support systems. It frames the topic within the scope of internal supply chains, addressing the framework impact on work practices within the organisation. Two real industrial implementation cases are examined, in the wood and chemical industries. Results help practitioners address the most impactful challenges affecting the performance of internal supply chains, by developing systems which are faster, more flexible, efficient and with improved quality.This work was supported by FCT, through IDMEC, under LAETA, project UIDB/50022/2020