Ammonia Emission in Various Star-forming Environments: A Pilot Study of Planck Galactic Cold Clumps

The Planck Catalogue of Galactic Cold Clumps provides an all-sky sample of potential star-forming regions based on the submillimeter emission of their dust content. Around 1000 of these Planck objects were mapped with the James Clerk Maxwell telescope in the submillimeter range during the SCOPE survey, identifying prestellar and protostellar dense clumps inside them. We used the Effelsberg 100 m telescope to observe the emission lines of the NH3 inversion transitions toward a sample of 97 dense objects in varying environments in order to assess the physical parameters of their gas content. We derive their temperature, density, and velocity dispersion, correlating the resulting parameters with the environmental and evolutionary characteristics of the targets and with regard to their distance and physical size. We examine the dependence of physical parameters on distance and Galactic position and compare the gas-based and dust-continuum-based temperatures and densities. Together with the presence of maser emission and higher inversion transitions of ammonia, we may differentiate between certain groups of targets, e.g., filamentary, protostellar clumps, and high-latitude, core-sized, starless sources.

The costs and benefits of dispersal in small populations

Dispersal has three major effects on adaptation. First, the gene flow mixes alleles adapted to different environments, potentially hindering (swamping) adaptation. Second, it inflates genetic variance: this aids adaptation to spatially (and temporally) varying environments but if selection is hard, it lowers the mean fitness of the population. Third, neighbourhood size, which determines how weak genetic drift is, increases with dispersal -- when genetic drift is strong, increase of neighbourhood size with dispersal aids adaptation. In this note I focus on the role of dispersal in environments which change smoothly across space, and when local populations are quite small such that genetic drift has a significant effect. Using individual-based simulations, I show that in small populations, even leptokurtic dispersal benefits adaptation, by reducing the power of genetic drift. This has implications for management of small marginal populations: increased gene flow appears beneficial as long as adaptations involves a quantitative, rather than a discrete, trait. However, heavily leptokurtic dispersal will swamp continuous adaptation along steep environmental gradients so that only patches of locally adapted subpopulations remain.

Detection of pig based on improved RESNET model in natural scene

The behaviours of the pig are often closely related to their health. Pig recognition is very important for pig behaviour analysis and digital breeding. Currently, the early signs and abnormal behaviours of sick pigs in breeding farms are mainly completed by human observation. However, visual inspection is labour intensive and time-consuming, and it suffers from the problems of individual experiences and varying environments. An improved ResNet model was proposed and applied to detect individual pigs in this study based on deep learning knowledge. The developed model captured the features of pigs applying across layer connections, and the ability of feature expression was improved by adding a new residual module. The number of layers was reduced to minimise the net complexity. Generally, the ResNet frame was developed by reducing the number of convolution layers, constructing different types of the residual module and adding the number of convolution kernels. The training accuracy and testing accuracy reached 98.2% and 96.4%, respectively, when using the improved model. The experiment results showed that the method proposed in this paper for checking living situations and disease prevention of commercial pigs in pig farms is potential.

Ideal free flows of optimal foragers: Vertical migrations in the ocean

We consider the collective motion of animals in time-varying environments, using as a case diel vertical migration in the ocean. The animals are distributed in space such that each animal moves optimally, seeking regions which offer high growth rates and low mortalities, subject to costs on excessive movements as well as being in regions with high densities of conspecifics. The model applies to repeated scenarios such as diel or seasonal patterns, where the animals are aware of both current and future environmental conditions. We show that this problem can be viewed as a differential game of mean field type, and that the evolutionary stable solution, i.e. the Nash equilibrium, is characterized by partial differential equations, which govern the distributions and migration velocities of animals. These equations have similarities to equations that appear in the fluid dynamics, specifically the Euler equations for compressible inviscid fluids. If the environment is constant, the ideal free distribution emerges as an equilibrium. We illustrate the theory with a numerical example of vertical animal movements in the ocean, where animals are attracted to nutrient-rich surface waters while repulsed from light during daytime due to the presence of visual predators, aiming to reduce both proximity to conspecifics and swimming efforts. For this case, we show that optimal movements are diel vertical migrations in qualitative agreement with observations.

Definite Advantages of Utilizing Integrated Multiple Indirect Inspection (IDi) Technologies to Survey a Newly Laid 3LPE Coated Cross Country Pipeline: A Case Study

Every scientific or engineering assessment made in today’s life is with respect to a specific approach — prescriptive or performance-based. In India for a newly laid pipeline (approx. 443 Km) — there are various prescriptive regulations ascertained by OISD and PNGRB for the pipelines’ safe routine operations. In a prescriptive system, it becomes mandatory for a pipeline owner to have the most accurate coatings and Cathodic Protection (CP) data irrespective of the external soil environmental conditions. This will also require the other external aggravators such as AC interference, Railway Crossings, Temporal phenomena etc. to be taken into consideration while the survey data is being collected. Only then sufficient data is available for the Owner to make correct integrity-based decisions and step forward towards a performance-based integrity management program. Hindustan Petroleum Corporation Limited (HPCL)-Rewari Kanpur Pipeline (RKPL) started the external line inspection (XLI) program as a prescriptive procedure for ascertaining the health of the in-place CP system and assess the integrity of the coating.This pipeline with length of approx. 443 Kms stretching across three (3) states of Haryana, Rajasthan, and Uttar Pradesh traverses through a truly varying surrounding soil and ambient environmental conditions. As per NACE Standard Practice SP0502, it is known that different aboveground survey tools are to be utilized by the pipeline owner for varying soil conditions. To overcome the complexity of dealing with varying environments, weather conditions (resulting in varying soil resistivity) for specific pipeline lengths to be surveyed by the various different technologies that may be applicable, HPCL-RKPL opted to deploy an integrated indirect inspection system which allows to perform the following aboveground surveys simultaneously, at the same time: DCVG, ACVG, ACCA (CAT), CIPS – AC & DC with all recorded raw logs for authenticity. Using these raw logs, HPCL-RKPL were able to ascertain few intricate concerns with the in-place CP system which would have otherwise been veiled. This was possible due to the extremely high frequency of data capture on several times per second basis. The integrated CP and Coating Integrity data also aligned and correlated very well with the historically conducted in-line inspection information. This paper shall discuss the unique findings obtained during the survey.

A mechanism for migrating bacterial populations to non-genetically adapt to new environments

Populations of chemotactic bacteria can rapidly expand into new territory by consuming and chasing an attractant cue in the environment, increasing the population's overall growth in nutrient-rich environments. Although the migrating fronts driving this expansion contain cells of multiple swimming phenotypes, the consequences of non-genetic diversity for population expansion are unknown. Here, through theory and simulations, we predict that expanding populations non-genetically adapt their phenotype composition to migrate effectively through multiple physical environments. Swimming phenotypes in the migrating front are spatially sorted by chemotactic performance, but the mapping from phenotype to performance depends on the environment. Therefore, phenotypes that perform poorly localize to the back of the group, causing them to selectively fall behind. Over cell divisions, the group composition dynamically enriches for high-performers, enhancing migration speed and overall growth. Furthermore, non-genetic inheritance controls a trade-off between large composition shifts and slow responsiveness to new environments, enabling a diverse population to out-perform a non-diverse one in varying environments. These results demonstrate that phenotypic diversity and collective behavior can synergize to produce emergent functionalities. Non-genetic inheritance may generically enable bacterial populations to transiently adapt to new situations without mutations, emphasizing that genotype-to-phenotype mappings are dynamic and context-dependent.

Generalized Empirical Regret Bounds for Control of Renewable Energy Systems in Spatiotemporally Varying Environments

This paper focuses on the empirical derivation of regret bounds for mobile systems that can optimize their locations in real time within a spatiotemporally varying renewable energy resource. The case studies in this paper focus specifically on an airborne wind energy system, where the replacement of towers with tethers and a lifting body allows the system to adjust its altitude continuously, with the goal of operating at the altitude that maximizes net power production. While prior publications have proposed control strategies for this problem, often with favorable results based on simulations that use real wind data, they lack any theoretical or statistical performance guarantees. In the present work, we make use of a very large synthetic data set, identified through parameters from real wind data, to derive probabilistic bounds on the difference between optimal and actual performance, termed regret. The results are presented for a variety of control strategies, including maximum probability of improvement, upper confidence bound, greedy, and constant altitude approaches. In addition, we use dimensional analysis to generalize the aforementioned results to other spatiotemporally varying environments, making the results applicable to a wider variety of renewably powered mobile systems. Finally, to deal with more general environmental mean models, we introduce a novel approach to modify calculable regret bounds to accommodate any mean model through what we term an "effective spatial domain."

Sulfation modification of dopamine in brain regulates aggregative behavior of animals

Behavioral plasticity and the underlying neuronal plasticity represent a fundamental capacity of animals to cope with environmental stimuli. Behavioral plasticity is controlled by complex molecular networks that act under different layers of regulation. While various molecules have been found to be involved in the regulation of plastic behaviors across species, less is known about how organisms orchestrate the activity of these molecules as part of a coherent behavioral response to varying environments. Here we discover a mechanism for the regulation of animal behavioral plasticity involving molecular sulfation in brain, a modification of substrate molecules by sulfotransferase (ST)-catalyzed addition of a sulfonate group (SO3) from an obligate donor, 3’-phosphoadenosine 5’-phosphosulfate (PAPS) to the substrates. We investigated aggregation behaviors of the migratory locusts, which are well-known for extreme phase change plasticity triggered by population density. The processes of PAPS biosynthesis acted efficiently on induction of locust behavioral transition: Inhibition of PAPS synthesis solicited a behavioral shift from gregarious to solitarious states; external PAPS dosage, by contrast, promoted aggregation in solitarious locusts. Genetic or pharmacological intervention in the sulfation catalyzation resulted into pronounced solitarizing effects. Analysis of substrate-specific STs suggests a widespread involvement of sulfated neurotransmitters in the behavioral response. Dopamine in brain was finally identified to be actively sulfate conjugated, and the sulfate conjugation enhanced the free DA-mediated behavioral aggregation. Similar results in Caenorhabditis elegans and mouse indicate that sulfation may be involved more broadly in the modulation of animal aggregation. These findings revealed a general mechanism that effectively regulates animal social-like behavioral plasticity possibly through sulfation-mediated modification of neural networks.