Uncovering latent behaviors in ant colonies

Many biological systems exhibit collective behaviors that strengthen their adaptability to their environment, compared to more solitary species. Describing these behaviors is challenging yet necessary in order to understand these biological systems. We propose a probabilistic model that enables us to uncover the collective behaviors observed in a colony of ants. This model is based on the assumption that the behavior of an individual ant is a time-dependent mixture of latent behaviors that are specific to the whole colony. We apply this model to a large-scale dataset obtained by observing the mobility of nearly 1000 Camponotus fellah ants from six different colonies. Our results indicate that a colony typically exhibits three classes of behaviors, each characterized by a specific spatial distribution and a level of activity. Moreover, these spatial distributions, which are uncovered automatically by our model, match well with the ground truth as manually annotated by domain experts. We further explore the evolution of the behavior of individual ants and show that it is well captured by a second order Markov chain that encodes the fact that the future behavior of an ant depends not only on its current behavior but also on its preceding one

Dynamic control strategies for a solar-ORC system using first-law dynamic and data-driven machine learning models

In this study, we developed and assessed the potential of dynamic control strategies for a domestic scale 1-kW solar thermal power system based on a non-recuperated organic Rankine cycle (ORC) engine coupled to a solar energy system. Such solar-driven systems suffer from part-load performance deterioration due to diurnal and inter-seasonal fluctuations in solar irradiance and ambient temperature. Real-time control strategies for adjusting the operating parameters of these systems have shown great potential to optimise their transient response to time-varying conditions, thus allowing significant gains in the power output delivered by the system. Dynamic model predictive control strategies rely on the development of computationally efficient, fast-solving models. In contrast, traditional physics-based dynamic process models are often too complex to be used for real-time controls. Machine learning techniques (MLTs), especially deep learning artificial neural networks (ANN), have been applied successfully for controlling and optimising nonlinear dynamic systems. In this study, the solar system was controlled using a fuzzy logic controller with optimised decision parameters for maximum solar energy absorption. For the sake of obtaining the optimal ORC thermal efficiency at any instantaneous time, particularly during part-load operation, the first-law ORC model was first replaced by a fast-solving feedforward network model, which was then integrated with a multi-objective genetic algorithm, such that the optimal ORC operating parameters can be obtained. Despite the fact that the feedforward network model was trained using steady-state ORC performance data, it showed comparable results compared with the first-principle model in the dynamic context, with a mean absolute error of 3.3 percent for power prediction and 0.186 percentage points for efficiency prediction

C-myc, not HER-2/neu, can predict recurrence and mortality of patients with node-negative breast cancer

BACKGROUND: At present, node-negative, high-risk breast cancer patients cannot be identified with sufficient accuracy. Consequently, further strong prognostic factors are needed. METHODS: Among 181 node-negative breast cancer (NNBC) patients, c-myc and HER-2/neu oncogenes were identified prospectively using double differential PCR. The possible impact of amplification of those oncogenes on disease-free survival (DFS) and overall survival was examined. Furthermore, the possible effects of adjuvant therapies on rate of recurrence and mortality in oncogene-amplified NNBC patients were investigated. RESULTS: The prevalence rates for amplification of c-myc and HER-2/neu were 21.5% and 30.4%, respectively. On univariate analysis, c-myc-amplified NNBCs were associated with significantly shorter DFS at 36 months after the initial diagnosis (85.3% versus 97.3%). As compared with nonamplified cancers, HER-2/neu-amplified NNBCs did not exhibit any significant differences after 36 months and 95 months. Multivariate analysis indicated that c-myc amplification and tumour size, in contrast to HER-2/neu amplification, oestrogen receptor status, grading and age, were the only independent parameters for DFS. During the period of observation, we found no evidence for an impact of amplification of the oncogenes on overall survival in all cases. With respect to various adjuvant systemic therapies such as chemotherapy (cyclophosphamide, methotrexate, 5-fluorouracil; fluorouracil, epirubicin, cyclophosphamide) and endocrine therapy (tamoxifen), no significant differences were identified in oncogene-amplified NNBC patients in terms of DFS and overall survival. However, those c-myc-amplified NNBC patients who did not receive adjuvant systemic therapy exhibited significantly shorter DFS and overall survival as compared with c-myc-nonamplified patients. CONCLUSION: C-myc amplification appears to be a strong prognostic marker with which to predict early recurrence in NNBC patients. C-myc-amplified NNBC patients without adjuvant systemic therapy experienced shorter DFS and overall survival

Spontaneous Ca(2+) transients in mouse microglia

Microglia are the resident immune cells in the central nervous system and many of their physiological functions are known to be linked to intracellular calcium (Ca2+) signaling. Here we show that isolated and purified mouse microglia-either freshly or cultured-display spontaneous and transient Ca2+ elevations lasting for around ten to twenty seconds and occurring at frequencies of around five to ten events per hour and cell. The events were absent after depletion of internal Ca2+ stores, by phospholipase C (PLC) inhibition or blockade of inositol-1,4,5-trisphosphate receptors (IP3Rs), but not by removal of extracellular Ca2+, indicating that Ca2+ is released from endoplasmic reticulum intracellular stores. We furthermore provide evidence that autocrine ATP release and subsequent activation of purinergic P2Y receptors is not the trigger for these events. Spontaneous Ca2+ transients did also occur after stimulation with Lipopolysaccharide (LPS) and in glioma-associated microglia, but their kinetics differed from control conditions. We hypothesize that spontaneous Ca2+ transients reflect aspects of cellular homeostasis that are linked to regular and patho-physiological functions of microglia

Helicase activity promoted through dynamic interactions between a ssDNA translocase and a diffusing SSB protein

Replication protein A (RPA) is a eukaryotic single-stranded (ss) DNA-binding (SSB) protein that is essential for all aspects of genome maintenance. RPA binds ssDNA with high affinity but can also diffuse along ssDNA. By itself, RPA is capable of transiently disrupting short regions of duplex DNA by diffusing from a ssDNA that flanks the duplex DNA. Using single-molecule total internal reflection fluorescence and optical trapping combined with fluorescence approaches, we show tha

Techno-economic comparison of hydrogen- and electricity-driven technologies for the decarbonisation of domestic heating

Sustainable transition pathways currently being proposed for moving away from the use of natural gas and oil in domestic heating focus on two main energy vectors: electricity and hydrogen. The former transition would most likely be implemented using electric vapour-compression heat pumps, which are currently experiencing market growth in many industrialised countries. Electric heat pumps have proven to be an efficient alternative to gas boilers under certain conditions, but their techno-economic potential is highly dependent on the local climate conditions. Hydrogen-based heating systems, which could potentially utilise existing natural gas infrastructure, are being proposed as providing an attractive opportunity to maximise the use of existing assets to facilitate the energy-system transition. In this case, hydrogen can substitute natural gas in boilers or in thermally driven absorption heat pumps. Both heating system transition pathways may involve either installing new technologies at the household level or producing heat in centralised hubs and distributing it via district-heating systems. Although the potential of hydrogen in the context of heating decarbonisation has been explored in the past, a comprehensive comparison of electricity- and hydrogen-driven domestic heating options is lacking in literature. In this paper, a thermodynamic and economic methodology is developed to assess the competitiveness of a domestic-scale ammonia-water absorption heat pump driven by heat from a hydrogen boiler compared to a standalone hydrogen boiler, a classic vapour-compression heat pump and district heating, all from a homeowner’s perspective. Using a previously developed electric heat pump model, the different systems are compared for various climate conditions and fuel-price scenarios under a unified framework. The coefficient of performance of the absorption heat pump system under design conditions and the total system cost are found to be 1.4 and £5400, respectively. Comparing the annualised total costs of the options under consideration, it is shown that, assuming the future price of hydrogen for domestic end-users can be below 0.12 £/kWh, absorption heat pumps and hydrogen boilers can become competitive domestic heating technologies, and otherwise, electrification and the use of vapour-compression heat pump will be preferred

Automated computer-based detection of encounter behaviours in groups of honeybees.

Honeybees form societies in which thousands of members integrate their behaviours to act as a single functional unit. We have little knowledge on how the collaborative features are regulated by workers' activities because we lack methods that enable collection of simultaneous and continuous behavioural information for each worker bee. In this study, we introduce the Bee Behavioral Annotation System (BBAS), which enables the automated detection of bees' behaviours in small observation hives. Continuous information on position and orientation were obtained by marking worker bees with 2D barcodes in a small observation hive. We computed behavioural and social features from the tracking information to train a behaviour classifier for encounter behaviours (interaction of workers via antennation) using a machine learning-based system. The classifier correctly detected 93% of the encounter behaviours in a group of bees, whereas 13% of the falsely classified behaviours were unrelated to encounter behaviours. The possibility of building accurate classifiers for automatically annotating behaviours may allow for the examination of individual behaviours of worker bees in the social environments of small observation hives. We envisage that BBAS will be a powerful tool for detecting the effects of experimental manipulation of social attributes and sub-lethal effects of pesticides on behaviour

Die Evolution einer Standardarchitektur für Betriebliche Informationssysteme

Echterhoff D, Grasmugg S, Mersch S, Mönckemeyer M, Spitta T, Wrede S. Die Evolution einer Standardarchitektur für Betriebliche Informationssysteme. In: Spitta T, Borchers J, Sneed HM, eds. Software-Management 2002. LNI. Vol P-23. Bonn: GI e.V.; 2002: 131-142.The paper outlines the history of a standard architecture for small and medium sized administrative systems. It has been developped 1985 in the Schering AG / Berlin, and applied in several firms over more than 15 years. Some of the about 150 applications, developped and maintained by more than 100 programmers, are still in operation. In 1999 a revision of the architecture and a new implementation in Java was started. The latest version is a four-level-architecture for distributed systems with a browser as user interface. Aside architectural considerations we discuss some of our design and implementation experiences with java

Role of Energy Storage in Residential Energy Demand Decarbonization: System-Level Techno-Economic Comparison of Low-Carbon Heating and Cooling Solutions

Item #: 069564-0208This paper explores various combinations of electric heat pumps (EHPs), hydrogen boilers (HBs), electric boilers (EBs), hydrogen absorption heat pumps (AHPs) and energy storage technologies (electric and thermal) to assess their potential for matching heating and cooling demand at low cost and with low carbon footprint. Thermodynamic and component-costing models of various heating and cooling technologies are integrated into a whole-energy system cost optimisation model to determine cost-effective configurations of heating and cooling systems that minimise the overall investment and operation cost for both the system and the end-user. Case studies presented in the paper focus on two archetypal systems that differ in terms of heating and cooling demand and availability profiles of solar and wind generation. The proposed approach quantifies how the costefficient portfolios of low-carbon heating and cooling solutions are driven by the characteristics of the system such as share of variable renewables or heating and cooling demand. Modelling results suggest that capacity choices for heating and cooling technologies will vary significantly depending on system properties. More specifically, air-to-air EHPs, with their cost and efficiency advantages over air-to-water EHPs, could make a significant contribution to low-carbon heat supply as well as cooling, although their contribution may be constrained by the compatibility with existing heating systems. They are found to be a useful supplementary source of space heating that is able to displace between 20 and 33 GWth of capacity of other heating technologies compared to the case where they do not contribute to space heatingUK Engineering and Physical Sciences Research Council (EPSRC) [grant number EP/R045518/1] (IDLES Programme)

Haltungshygiene und Eutergesundheit im ökologisch geführten Milchviehbetrieb

Im Rahmen einer interdisziplinären Studie wurden in der der Zeit von Januar 2008 bis April 2010 Daten auf 106 Betreiben in Deutschland erhoben. In diesem Teilprojekt wurde der Zusammenhang zwischen Hygeine und Eutergesundheit oim Rahmen einer ersten Asuwertung untersucht. Die Analyse macht deutlich, dass es einen Zusammenhang zwischen Halltungs- une Tierhygiene gibt. zudem gibt es einen Zusammenhang zwischen der Sauberkeit der Laufgänge und der subklinsichen Eutergesundheit sowie der Sauberkeit der Etuer und der Eutergesundheit der Färsen