THE VALENCE OF CORPUSCULAR PROTEINS

By the use of two extreme models: a hydrated sphere and an unhydrated rod the valence (net charge) of corpuscular proteins can be successfully calculated from electric mobility data by the Debye-Hückel theory (modified to include the effect of the ions in the ion atmosphere) in conjunction with the electrophoretic theory of Henry. As pointed out by Abramson, this permits a comparison with values for the valence from titration data. Electrometric titration measurements of serum albumin B (Kekwick) have been determined at several ionic strengths. These results, together with the available data in the literature for serum albumin B, egg albumin, and β-lactoglobulin have been used to compare values for the valence calculated from measurements of titration, electrophoresis, and membrane potentials. The results indicate that the usual interpretation of titration curves is open to serious question. By extrapolation of the titration data to zero ionic strength and protein concentration, there results an "intrinsic" net charge curve describing the binding of H+ (OH-) ion alone. This curve agrees closely, in each case, with values of the valence calculated from mobility data (which in turn are in close accord with those estimated from membrane potential measurements). The experimental titration curves in the presence of appreciable quantities of ions and protein deviate widely from the ideal curve. It is suggested that, under these conditions, binding of undissociated acid (base) leads to erroneous values for the net charge. This binding would not affect the electrophoretic mobility. Values of the net charge obtained by the two extreme models from electrophoretic data are in agreement within 15 to 20 per cent. The agreement between the cylindrical model and the titration data is somewhat better in each case than with the sphere; i.e., this comparison enables a choice to be made between asymmetry and hydration in the interpretation of results from sedimentation and diffusion measurements on proteins. It is concluded that the proteins discussed here are somewhat asymmetric and also hydrated

Goal Space Abstraction in Hierarchical Reinforcement Learning via Reachability Analysis

Open-ended learning benefits immensely from the use of symbolic methods for goal representation as they offer ways to structure knowledge for efficient and transferable learning. However, the existing Hierarchical Reinforcement Learning (HRL) approaches relying on symbolic reasoning are often limited as they require a manual goal representation. The challenge in autonomously discovering a symbolic goal representation is that it must preserve critical information, such as the environment dynamics. In this work, we propose a developmental mechanism for subgoal discovery via an emergent representation that abstracts (i.e., groups together) sets of environment states that have similar roles in the task. We create a HRL algorithm that gradually learns this representation along with the policies and evaluate it on navigation tasks to show the learned representation is interpretable and results in data efficiency

Nonlinear hydro turbine model having a surge tank.

yesThis paper models a hydro turbine based on the dynamic description of the hydraulic system having a surge tank and elastic water hammer. The dynamic of the hydraulic system is transformed from transfer function form into the differential equation model in relative value. This model is then combined with the motion equation of the main servomotor to form the nonlinear model of the hydro turbine, in which the power of the hydro turbine is calculated using algebraic equation. A new control model is thus proposed in which the dynamic of the surge tank is taken as an additional input of control items. As such, the complex hydraulic system is decomposed into a classical one penstock and one machine model with an additional input control. Therefore, the order of the system is descended. As a result, the feasibility of the system is largely improved. The simulated results show that the additional input of the surge tank is effective and the proposed method is realizable.National Natural Science Foundation of China (50839003, 50949037, 51179079), Natural Science Foundation of Yunnan Province (No. 2008GA027

Lifestate: Event-Driven Protocols and Callback Control Flow

Developing interactive applications (apps) against event-driven software frameworks such as Android is notoriously difficult. To create apps that behave as expected, developers must follow complex and often implicit asynchronous programming protocols. Such protocols intertwine the proper registering of callbacks to receive control from the framework with appropriate application-programming interface (API) calls that in turn affect the set of possible future callbacks. An app violates the protocol when, for example, it calls a particular API method in a state of the framework where such a call is invalid. What makes automated reasoning hard in this domain is largely what makes programming apps against such frameworks hard: the specification of the protocol is unclear, and the control flow is complex, asynchronous, and higher-order. In this paper, we tackle the problem of specifying and modeling event-driven application-programming protocols. In particular, we formalize a core meta-model that captures the dialogue between event-driven frameworks and application callbacks. Based on this meta-model, we define a language called lifestate that permits precise and formal descriptions of application-programming protocols and the callback control flow imposed by the event-driven framework. Lifestate unifies modeling what app callbacks can expect of the framework with specifying rules the app must respect when calling into the framework. In this way, we effectively combine lifecycle constraints and typestate rules. To evaluate the effectiveness of lifestate modeling, we provide a dynamic verification algorithm that takes as input a trace of execution of an app and a lifestate protocol specification to either produce a trace witnessing a protocol violation or a proof that no such trace is realizable

Goal Space Abstraction in Hierarchical Reinforcement Learning via Set-Based Reachability Analysis

Open-ended learning benefits immensely from the use of symbolic methods for goal representation as they offer ways to structure knowledge for efficient and transferable learning. However, the existing Hierarchical Reinforcement Learning (HRL) approaches relying on symbolic reasoning are often limited as they require a manual goal representation. The challenge in autonomously discovering a symbolic goal representation is that it must preserve critical information, such as the environment dynamics. In this paper, we propose a developmental mechanism for goal discovery via an emergent representation that abstracts (i.e., groups together) sets of environment states that have similar roles in the task. We introduce a Feudal HRL algorithm that concurrently learns both the goal representation and a hierarchical policy. The algorithm uses symbolic reachability analysis for neural networks to approximate the transition relation among sets of states and to refine the goal representation. We evaluate our approach on complex navigation tasks, showing the learned representation is interpretable, transferrable and results in data efficient learning

Lifestate: Event-Driven Protocols and Callback Control Flow (Artifact)

Developing interactive applications (apps) against event-driven software frameworks such as Android is notoriously difficult. To create apps that behave as expected, developers must follow complex and often implicit asynchronous programming protocols. Such protocols intertwine the proper registering of callbacks to receive control from the framework with appropriate application-programming interface (API) calls that in turn affect the set of possible future callbacks. An app violates the protocol when, for example, it calls a particular API method in a state of the framework where such a call is invalid. What makes automated reasoning hard in this domain is largely what makes programming apps against such frameworks hard: the specification of the protocol is unclear, and the control flow is complex, asynchronous, and higher-order. In this paper, we tackle the problem of specifying and modeling event-driven application-programming protocols. In particular, we formalize a core meta-model that captures the dialogue between event-driven frameworks and application callbacks. Based on this meta-model, we define a language called lifestate that permits precise and formal descriptions of application-programming protocols and the callback control flow imposed by the event-driven framework. Lifestate unifies modeling what app callbacks can expect of the framework with specifying rules the app must respect when calling into the framework. In this way, we effectively combine lifecycle constraints and typestate rules. To evaluate the effectiveness of lifestate modeling, we provide a dynamic verification algorithm that takes as input a trace of execution of an app and a lifestate protocol specification to either produce a trace witnessing a protocol violation or a proof that no such trace is realizable

Symbolic Model Checking and Safety Assessment of Altarica models

Altarica is a language used to describe critical systems. In this paper we present a novel approach to the analysis of Altarica models, based on a translation into an extended version of NuSMV. This approach opens up the possibility to carry out functional verification and safety assessment with symbolic techniques. An experimental evaluation on a set of industrial case studies demonstrates the advantages of the approach over currently available tools.

IC3 modulo theories via implicit predicate abstraction

We present a novel approach for generalizing the IC3 algorithm for invariant checking from finite-state to infinite-state transition systems, expressed over some background theories. The procedure is based on a tight integration of IC3 with Implicit (predicate) Abstraction, a technique that expresses abstract transitions without computing explicitly the abstract system and is incremental with respect to the addition of predicates. In this scenario, IC3 operates only at the Boolean level of the abstract state space, discovering inductive clauses over the abstraction predicates. Theory reasoning is confined within the underlying SMT solver, and applied transparently when performing satisfiability checks. When the current abstraction allows for a spurious counterexample, it is refined by discovering and adding a sufficient set of new predicates. Importantly, this can be done in a completely incremental manner, without discarding the clauses found in the previous search. The proposed approach has two key advantages. First, unlike current SMT generalizations of IC3, it allows to handle a wide range of background theories without relying on ad-hoc extensions, such as quantifier elimination or theory-specific clause generalization procedures, which might not always be available, and can moreover be inefficient. Second, compared to a direct exploration of the concrete transition system, the use of abstraction gives a significant performance improvement, as our experiments demonstrate

PHAEOCHROMOCYTOMA

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/72570/1/j.1445-2197.1988.tb01080.x.pd