Algorithms for Finding Diameter Cycles of Biconnected Graphs

In this paper, we first coin a new graph theoretic problem called the diameter cycle problem with numerous applications. A longest cycle in a graph G = (V, E) is referred to as a diameter cycle of G iff the distance in G of every vertex on the cycle to the rest of the on-cycle vertices is maximal. We then present two algorithms for finding a diameter cycle of a biconnected graph. The first algorithm is an abstract intuitive algorithm that utilizes a brute-force mechanism for expanding an initial cycle by repeatedly replacing paths on the cycle with longer paths. The second algorithm is a concrete algorithm that uses fundamental cycles in the expansion process and has the time and space complexity of O(n^6) and O(n^2), respectively. To the best of our knowledge, this problem was neither defined nor addressed in the literature. The diameter cycle problem distinguishes itself from other cycle finding problems by identifying cycles that are maximally long while maximizing the distances between vertices in the cycle. Existing cycle finding algorithms such as fundamental and longest cycle algorithms do not discover cycles where the distances between vertices are maximized while also maximizing the length of the cycle.

Optimal ligand discrimination by asymmetric dimerization and turnover of interferon receptors

In multicellular organisms, antiviral defense mechanisms evoke a reliable collective immune response despite the noisy nature of biochemical communication between tissue cells. A molecular hub of this response, the interferon I receptor (IFNAR), discriminates between ligand types by their affinity regardless of concentration. To understand how ligand type can be decoded robustly by a single receptor, we frame ligand discrimination as an information-theoretic problem and systematically compare the major classes of receptor architectures: allosteric, homodimerizing, and heterodimerizing. We demonstrate that asymmetric heterodimers achieve the best discrimination power over the entire physiological range of local ligand concentrations. This design enables sensing of ligand presence and type, and it buffers against moderate concentration fluctuations. In addition, receptor turnover, which drives the receptor system out of thermodynamic equilibrium, allows alignment of activation points for ligands of different affinities and thereby makes ligand discrimination practically independent of concentration. IFNAR exhibits this optimal architecture, and our findings thus suggest that this specialized receptor can robustly decode digital messages carried by its different ligands.

Yielding stability of early maturing potato varieties: Bayesian analysis

Field trials conducted in multiple years across several locations play an essential role in plant breeding and variety testing. Usually, the analysis of the series of field trials is performed using a two-stage approach, where each combination of year and site is treated as environment. In variety testing based on the results from the analysis, the best varieties are recommended for cultivation. Under a Bayesian approach, the variety recommendation process can be treated as a formal decision theoretic problem. In the present study, we describe Bayesian counterparts of two stability measures and compare the varieties in terms of the posterior expected utility. Using the described methodology, we identify the most stable and highest tuber yielding varieties in the Polish potato series of field trials conducted from 2016 to 2018. It is shown that variety Arielle was the highest yielding, the third most stable variety and was the second best variety in terms of the posterior expected utility. In the present work, application of the Bayesian approach allowed us to incorporate the prior knowledge about the tested varieties and offered a possibility of treating the variety recommendation process as a formal decision process.

Residually finite dimensional algebras and polynomial almost identities

Let [Formula: see text] be a residually finite dimensional algebra (not necessarily associative) over a field [Formula: see text]. Suppose first that [Formula: see text] is algebraically closed. We show that if [Formula: see text] satisfies a homogeneous almost identity [Formula: see text], then [Formula: see text] has an ideal of finite codimension satisfying the identity [Formula: see text]. Using well known results of Zelmanov, we conclude that, if a residually finite dimensional Lie algebra [Formula: see text] over [Formula: see text] is almost [Formula: see text]-Engel, then [Formula: see text] has a nilpotent (respectively, locally nilpotent) ideal of finite codimension if char [Formula: see text] (respectively, char [Formula: see text]). Next, suppose that [Formula: see text] is finite (so [Formula: see text] is residually finite). We prove that, if [Formula: see text] satisfies a homogeneous probabilistic identity [Formula: see text], then [Formula: see text] is a coset identity of [Formula: see text]. Moreover, if [Formula: see text] is multilinear, then [Formula: see text] is an identity of some finite index ideal of [Formula: see text]. Along the way we show that if [Formula: see text] has degree [Formula: see text], and [Formula: see text] is a finite [Formula: see text]-algebra such that the probability that [Formula: see text] (where [Formula: see text] are randomly chosen) is at least [Formula: see text], then [Formula: see text] is an identity of [Formula: see text]. This solves a ring-theoretic analogue of a (still open) group-theoretic problem posed by Dixon,

Characterization of solvable spin models via graph invariants

Exactly solvable models are essential in physics. For many-body spin-1/2 systems, an important class of such models consists of those that can be mapped to free fermions hopping on a graph. We provide a complete characterization of models which can be solved this way. Specifically, we reduce the problem of recognizing such spin models to the graph-theoretic problem of recognizing line graphs, which has been solved optimally. A corollary of our result is a complete set of constant-sized commutation structures that constitute the obstructions to a free-fermion solution. We find that symmetries are tightly constrained in these models. Pauli symmetries correspond to either: (i) cycles on the fermion hopping graph, (ii) the fermion parity operator, or (iii) logically encoded qubits. Clifford symmetries within one of these symmetry sectors, with three exceptions, must be symmetries of the free-fermion model itself. We demonstrate how several exact free-fermion solutions from the literature fit into our formalism and give an explicit example of a new model previously unknown to be solvable by free fermions.

A Novelty in Blahut-Arimoto T ype Algorithms: Optimal Control over Noisy Commu nication Channels

A probability-theoretic problem under information constraints for the concept of optimal control over a noisy-memoryless channel is considered. For our \textit{Observer-Controller} block, i.e., the lossy joint-source-channel-coding (JSCC) scheme, after providing the relative mathematical expressions, we propose a \textit{Blahut-Arimoto}-type algorithm $-$ which is, to the best of our knowledge, for the first time. The algorithm efficiently finds the probability-mass-functions (PMFs) required for .......................................

A Novelty in Blahut-Arimoto T ype Algorithms: Optimal Control over Noisy Commu nication Channels

A probability-theoretic problem under information constraints for the concept of optimal control over a noisy-memoryless channel is considered. For our \textit{Observer-Controller} block, i.e., the lossy joint-source-channel-coding (JSCC) scheme, after providing the relative mathematical expressions, we propose a \textit{Blahut-Arimoto}-type algorithm $-$ which is, to the best of our knowledge, for the first time. The algorithm efficiently finds the probability-mass-functions (PMFs) required for .......................................

Penalty Based Control Mechanism for Strategic Prosumers in a Distribution Network

The distribution side of the traditional power grid is changing as the users (known as prosumers) can inject power to the grid. However, uncontrollable injection of power can destabilize the grid. Thus, the stability of the grid must be maintained. Since the prosumers are self-interested entities, they will take their actions to maximize their own pay-offs. We formulate the problem as a non-cooperative game theoretic problem where the magnitude of the voltage must be within an acceptable limit at each node of the power network. Since the power-flow equations must be satisfied at each node, it becomes a coupled constrained game where the constraints are the same across the prosumers. We propose a distributed penalty based algorithm which converges to an equilibrium. In this mechanism, the prosumers are quoted a price based on the active and reactive power drawn or injected to the power grid. The algorithm is easy to implement and it converges to an efficient solution which maximizes the sum of the utilities of the prosumers while maintaining the grid’s stability.

Degree of a Vertex in Max-Product of Intuitionistic Fuzzy Graph

Graph theory has applications in many areas of computer science, including data mining, image segmentation, clustering and networking. Product on graphs has a wide range of application in networking system, automata theory, game theory and structural mechanics. In many cases, some aspects of a graph-theoretic problem may be uncertain. Intuitionistic fuzzy models provide more compatible to the system compared to the fuzzy models. An intuitionistic fuzzy graph can be derived from two given intuitionistic fuzzy graphs using max-product. In this paper, we studied the degree of vertex in intuitionistic fuzzy graph by the max-product of two given intuitionistic fuzzy graph. Also find the necessary and sufficient condition for max-product of two intuitionistic fuzzy graphs to be regular.

Physical limit to concentration sensing in a changing environment

Cells adapt to changing environments by sensing ligand concentrations using specific receptors. The accuracy of sensing is ultimately limited by the finite number of ligand molecules bound by receptors. Previously derived physical limits to sensing accuracy have assumed that the concentration was constant and ignored its temporal fluctuations. We formulate the problem of concentration sensing in a strongly fluctuating environment as a non-linear field-theoretic problem, for which we find an excellent approximate Gaussian solution. We derive a new physical bound on the relative error in concentration c which scales as δc/c ~ (Dacτ)−1/4 with ligand diffusivity D, receptor cross-section a, and characteristic fluctuation time scale τ, in stark contrast with the usual Berg and Purcell bound δc/c ~ (DacT)−1/2 for a perfect receptor sensing concentration during time T. We show how the bound can be achieved by a simple biochemical network downstream the receptor that adapts the kinetics of signaling as a function of the square root of the sensed concentration.