Automated Service Composition Using AI Planning and Beyond

Automated Service Composition is one of the ``grand challenges'' in the area of Service-Oriented Computing. Mike Papazoglou was not only one of the first researchers who identified the importance of the problem, but was also one of the first proposers of formulating it as an AI planning problem. Unfortunately, classical planning algorithms were not sufficient and a number of extensions were needed, e.g., to support extended (rich) goal languages to capture the user intentions, to plan under uncertainty caused by the non-deterministic nature of services; issues that where formulated (and, partially addressed) by Mike, being one of his key contributions to the service community

Energy Consumption Patterns and Load Forecasting with Profiled CNN-LSTM Networks

By virtue of the steady societal shift to the use of smart technologies built on the increasingly popular smart grid framework, we have noticed an increase in the need to analyze household electricity consumption at the individual level. In order to work efficiently, these technologies rely on load forecasting to optimize operations that are related to energy consumption (such as household appliance scheduling). This paper proposes a novel load forecasting method that utilizes a clustering step prior to the forecasting step to group together days that exhibit similar energy consumption patterns. Following that, we attempt to classify new days into pre-generated clusters by making use of the available context information (day of the week, month, predicted weather). Finally, using available historical data (with regard to energy consumption) alongside meteorological and temporal variables, we train a CNN-LSTM model on a per-cluster basis that specializes in forecasting based on the energy profiles present within each cluster. This method leads to improvements in forecasting performance (upwards of a 10% increase in mean absolute percentage error scores) and provides us with the added benefit of being able to easily highlight and extract information that allows us to identify which external variables have an effect on the energy consumption of any individual household

A multi-robot allocation model for multi-object based on Global Optimal Evaluation of Revenue

The problem of global optimal evaluation for multi-robot allocation has gained attention constantly, especially in a multi-objective environment, but most algorithms based on swarm intelligence are difficult to give a convergent result. For solving the problem, we established a Global Optimal Evaluation of Revenue method of multi-robot for multi-tasks based on the real textile combing production workshop, consumption, and different task characteristics of mobile robots. The Global Optimal Evaluation of Revenue method could traversal calculates the profit of each robot corresponding to different tasks with global traversal over a finite set, then an optimization result can be converged to the global optimal value avoiding the problem that individual optimization easy to fall into local optimal results. In the numerical simulation, for fixed set of multi-object and multi-task, we used different numbers of robots allocation operation. We then compared with other methods: Hungarian, the auction method, and the method based on game theory. The results showed that Global Optimal Evaluation of Revenue reduced the number of robots used by at least 17%, and the delay time could be reduced by at least 16.23%.</p

Faster and safer:Research priorities in water and health

The United Nations’ Sustainable Development Goals initiated in 2016 reiterated the need for safe water and healthy lives across the globe. The tenth anniversary meeting of the International Water and Health Seminar in 2018 brought together experts, students, and practitioners, setting the stage for development of an inclusive and evidence-based research agenda on water and health. Data collection relied on a nominal group technique gathering perceived research priorities as well as underlying drivers and adaptation needs. Under a common driver of public health protection, primary research priorities included the socioeconomy of water, risk assessment and management, and improved monitoring methods and intelligence. Adaptations stemming from these drivers included translating existing knowledge to providing safe and timely services to support the diversity of human water needs. Our findings present a comprehensive agenda of topics at the forefront of water and health research. This information can frame and inform collective efforts of water and health researchers over the coming decades, contributing to improved water services, public health, and socioeconomic outcomes

Chromosomal Instability by Inefficient Mps1 Auto-Activation Due to a Weakened Mitotic Checkpoint and Lagging Chromosomes

BACKGROUND: Chromosomal instability (CIN), a feature widely shared by cells from solid tumors, is caused by occasional chromosome missegregations during cell division. Two of the causes of CIN are weakened mitotic checkpoint signaling and persistent merotelic attachments that result in lagging chromosomes during anaphase. PRINCIPAL FINDINGS: Here we identify an autophosphorylation event on Mps1 that is required to prevent these two causes of CIN. Mps1 is phosphorylated in mitotic cells on at least 7 residues, 4 of which by autophosphorylation. One of these, T676, resides in the activation loop of the kinase domain and a mutant that cannot be phosphorylated on T676 is less active than wild-type Mps1 but is not kinase-dead. Strikingly, cells in which endogenous Mps1 was replaced with this mutant are viable but missegregate chromosomes frequently. Anaphase is initiated in the presence of misaligned and lagging chromosomes, indicative of a weakened checkpoint and persistent merotelic attachments, respectively. CONCLUSIONS/SIGNIFICANCE: We propose that full activity of Mps1 is essential for maintaining chromosomal stability by allowing resolution of merotelic attachments and to ensure that single kinetochores achieve the strength of checkpoint signaling sufficient to prevent premature anaphase onset and chromosomal instability. To our knowledge, phosphorylation of T676 on Mps1 is the first post-translational modification in human cells of which the absence causes checkpoint weakening and CIN without affecting cell viability

Live cell dynamics of production, explosive release and killing activity of phage tail-like weapons for Pseudomonas kin exclusion.

Interference competition among bacteria requires a highly specialized, narrow-spectrum weaponry when targeting closely-related competitors while sparing individuals from the same clonal population. Here we investigated mechanisms by which environmentally important Pseudomonas bacteria with plant-beneficial activity perform kin interference competition. We show that killing between phylogenetically closely-related strains involves contractile phage tail-like devices called R-tailocins that puncture target cell membranes. Using live-cell imaging, we evidence that R-tailocins are produced at the cell center, transported to the cell poles and ejected by explosive cell lysis. This enables their dispersal over several tens of micrometers to reach targeted cells. We visualize R-tailocin-mediated competition dynamics between closely-related Pseudomonas strains at the single-cell level, both in non-induced condition and upon artificial induction. We document the fatal impact of cellular self-sacrifice coupled to deployment of phage tail-like weaponry in the microenvironment of kin bacterial competitors, emphasizing the necessity for microscale assessment of microbial competitions

Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition)

In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. For example, a key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process versus those that measure fl ux through the autophagy pathway (i.e., the complete process including the amount and rate of cargo sequestered and degraded). In particular, a block in macroautophagy that results in autophagosome accumulation must be differentiated from stimuli that increase autophagic activity, defi ned as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (inmost higher eukaryotes and some protists such as Dictyostelium ) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the fi eld understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. It is worth emphasizing here that lysosomal digestion is a stage of autophagy and evaluating its competence is a crucial part of the evaluation of autophagic flux, or complete autophagy. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. Along these lines, because of the potential for pleiotropic effects due to blocking autophagy through genetic manipulation it is imperative to delete or knock down more than one autophagy-related gene. In addition, some individual Atg proteins, or groups of proteins, are involved in other cellular pathways so not all Atg proteins can be used as a specific marker for an autophagic process. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field

The Community Structure of Constraint Satisfaction Problems and Its Correlation with Search Time

Constraint satisfaction problems are, in general, NP-complete problems, meaning that the computational complexity increases exponentially with the size of the problem in the worst case, under the assumption that P does not equal NP. The structure of a problem heavily influences its computational complexity, however, and problems with a restricted structure constitute one of the general classes of tractable problems. This paper explores the community structure of constraint satisfaction problems, a type of structure already found to be important for SAT problems that is inherent to certain real-world domains. The community structure of the instances of the MiniZinc Challenge of 2019 was identified, and its correlation with the search times of four state-of-the-art solvers as well as with the tree-width of the instances was analysed. The results reveal the strong community structure of many of the instances, although the strength of the community structure seems to only marginally affect the search times. On the other hand, a strong correlation between the community structure and the tree-width is observed, where stronger community structure suggests better decomposability. Taking community structure into account more explicitly during the search process may, therefore, allow constraints solvers to solve problems with strong community structure more efficiently

Correlating the Community Structure of Constraint Satisfaction Problems with Search Time

A constraint satisfaction problem (CSP) is, in its most general form, an NP-complete problem. One of the several classes of tractable problems that exist contains all the problems with a restricted structure of the constraint scopes. This paper studies community structure, a particular type of restricted structure underpinning a class of tractable SAT problems with potentially similar relevance to CSPs. Using the modularity, it explores the community structure of a wide variety of problems with both academic and industrial relevance. Its impact on the search times of several general solvers, as well as one that uses tree-decomposition, is also analysed to determine whether constraint solvers exploit this type of structure. Nearly all CSP instances have a strong community structure, and those belonging to the same class have comparable modularity values. For the general solvers, strong correlations between the community structure and the search times are not apparent. A more definite correlation exists between the modularity and the search times of the tree-decomposition, suggesting that it might, in part, be able to take advantage of the community structure. However, combined with the relatively strong correlation between the modularity and the tree-width, it could also indicate a similarity between these two measures