Self-supported metal-organic framework-based nanostructures as binder-free electrodes for supercapacitors

Metal-organic framework (MOF), an interesting class of functional inorganic material, has recently emerged as a suitable electrode material or template/percursor of electrode material for supercapacitors (SCs). The key in utilizing...

The SAMME.C2 Algorithm for Severely Imbalanced Multi-class Classification

Classification predictive modeling involves the accurate assignment of observations in a dataset to target classes or categories. There is an increasing growth of real-world classification problems with severely imbalanced class distributions. In this case, minority classes have much fewer observations to learn from than those from majority classes. Despite this sparsity, a minority class is often considered the more interesting class yet developing a scientific learning algorithm suitable for the observations presents countless challenges. In this article, we suggest a novel multi-class classification algorithm specialized to handle severely imbalanced classes based on the method we refer to as SAMME.C2. It blends the flexible mechanics of the boosting techniques from SAMME algorithm, a multi-class classifier, and Ada.C2 algorithm, a cost-sensitive binary classifier designed to address highly class imbalances. Not only do we provide the resulting algorithm but we also establish scientific and statistical formulation of our proposed SAMME.C2 algorithm. Through numerical experiments examining various degrees of classifier difficulty, we demonstrate consistent superior performance of our proposed model.

Understanding complex multiple sublattice magnetism in double double perovskites

Understanding magnetism in multiple magnetic sublattice system, driven by the interplay of varied nature of magnetic exchanges, is on one hand challenging and on other hand intriguing. Motivated by the recent synthesis of AA$$^{\prime }$$ ′ BB$$^{\prime }$$ ′ O$$_6$$ 6 double double perovskites with multiple magnetic ions both at A- and B-sites, we investigate the mechanism of magnetic behavior in these interesting class of compounds. We find that the magnetism in such multiple sublattice compounds is governed by the interplay and delicate balance between two distinct mechanisms, (a) kinetic energy-driven multiple sublattice double exchange mechanism and (b) the conventional super-exchange mechanism. The derived spin Hamiltonian based on first-principles calculations is solved by classical Monte Carlo technique which reproduces the observed magnetic properties. Finally, the influence of off-stoichiometry, as in experimental samples, is discussed. Some of these double double perovskite compounds are found to possess large total magnetic moment and also are found to be half-metallic with reasonably high transition temperature, which raises the hope of future applications of these large magnetic moment half-metallic oxides in spintronics and memory devices.

Small instantons in weakly-gauged holographic models

Small instantons can play an important role in Yang-Mills theories whose gauge couplings are sizeable at small distances. An interesting class of theories where this could occur is in weakly-gauged holographic models (dual to Yang-Mills theories interacting with strongly-coupled CFTs), since gauge couplings are indeed enhanced towards the UV boundary of the 5D AdS space. However, contrary to expectations, we show that small instantons in these non-asymptotically-free models are highly suppressed and ineffective. This is due to the conservation of topological charge that forbids instantons to be localized near the UV boundary. Despite this fact we find non-trivial UV localized instanton-anti-instanton solutions of the Yang-Mills equations where the topological charges annihilate in the AdS bulk. These analytic solutions arise from a 5D conformal transformation of the uplifted 4D instanton. Our analysis therefore reveals unexpected nonperturbative configurations of Yang-Mills theories when they interact with strongly-coupled CFTs.

Selection of a Nuclease-Resistant RNA Aptamer Targeting CD19

The transmembrane glycoprotein cluster of differentiation 19 (CD19) is a B cell–specific surface marker, expressed on the majority of neoplastic B cells, and has recently emerged as a very attractive biomarker and therapeutic target for B-cell malignancies. The development of safe and effective ligands for CD19 has become an important need for the development of targeted conventional and immunotherapies. In this regard, aptamers represent a very interesting class of molecules. Additionally referred to as ‘chemical antibodies’, they show many advantages as therapeutics, including low toxicity and immunogenicity. Here, we isolated a nuclease-resistant RNA aptamer binding to the human CD19 glycoprotein. In order to develop an aptamer also useful as a carrier for secondary reagents, we adopted a cell-based SELEX (Systematic Evolution of Ligands by EXponential Enrichment) protocol adapted to isolate aptamers able to internalise upon binding to their cell surface target. We describe a 2′-fluoro pyrimidine modified aptamer, named B85.T2, which specifically binds to CD19 and shows an exquisite stability in human serum. The aptamer showed an estimated dissociation constant (KD) of 49.9 ± 13 nM on purified human recombinant CD19 (rhCD19) glycoprotein, a good binding activity on human B-cell chronic lymphocytic leukaemia cells expressing CD19, and also an effective and rapid cell internalisation, thus representing a promising molecule for CD19 targeting, as well as for the development of new B-cell malignancy-targeted therapies.

BVPs Codes for Solving Optimal Control Problems

Optimal control problems arise in many applications and need suitable numerical methods to obtain a solution. The indirect methods are an interesting class of methods based on the Pontryagin’s minimum principle that generates Hamiltonian Boundary Value Problems (BVPs). In this paper, we review some general-purpose codes for the solution of BVPs and we show their efficiency in solving some challenging optimal control problems.

Time-critical decentralised situational awareness in emergencies: an adversarial biosecurity scenario

Crises in a global setting of interdependencies call for time-critical coordinated responses. However, it is often the case that the mechanisms responsible for these actions do not agree across all their hierarchies. This can be roughly attributed to personal estimations of the situation and to social influence. An ensuing lack of consensus against crises can be dire and echo across entire populations. One such instance is the case of biosecurity threats. A particularly interesting class of threats lie within urban environments, which tend to fall within the scope of bad actors. With this work we aim to computationally contribute to the understanding of the dynamics of perceived danger formation among agents responsible for responding to ongoing biological attacks in urban settings. We assume this perception is a function of a personal estimation of local information about the danger and of social influence stemming from the agents in question framed in an agent-based model. The simulations point towards a high dependence of perceived dangers on the personal estimations of the agents. The conditions under which the perceived dangers deviate from the real ones are explored over a range of assumptions on personal measurements and several dispositions towards the influencing environment. The insight provided by these results at the individual and collective level set the tone for further investigation on such behavioural phenomena, providing a flexible computational framework addressing generic threats (true dangers) in a time-critical context.

A Complete Description of the Dynamics of Legal Outer-totalistic Affine Continuous Cellular Automata

We present an investigation into the evolution and dynamics of the simplest generalization of binary cellular automata: Affine Continuous Cellular Automata (ACCAs), with [0,1] as state set and local rules that are affine in each variable. We focus on legal outer-totalistic ACCAs, an interesting class of dynamical systems that show some properties that do not occur in the binary case. A unique combination of computer simulations (sometimes quite advanced) and a panoply of analytical methods allow to lay bare the dynamics of each and every one of these cellular automata.

Reasoning about Beliefs and Meta-Beliefs by Regression in an Expressive Probabilistic Action Logic

In a recent paper Belle and Lakemeyer proposed the logic DS, a probabilistic extension of a modal variant of the situation calculus with a model of belief based on weighted possible worlds. Among other things, they were able to precisely capture the beliefs of a probabilistic knowledge base in terms of the concept of only-believing. While intuitively appealing, the logic has a number of shortcomings. Perhaps the most severe is the limited expressiveness in that degrees of belief are restricted to constant rational numbers, which makes it impossible to express arbitrary belief distributions. In this paper we will address this and other shortcomings by extending the language and modifying the semantics of belief and only-believing. Among other things, we will show that belief retains many but not all of the properties of DS. Moreover, it turns out that only-believing arbitrary sentences, including those mentioning belief, is uniquely satisfiable in our logic. For an interesting class of knowledge bases we also show how reasoning about beliefs and meta-beliefs after performing noisy actions and sensing can be reduced to reasoning about the initial beliefs of an agent using a form of regression.

The Complexity of Approximately Counting Retractions to Square-free Graphs

A retraction is a homomorphism from a graph G to an induced subgraph H of G that is the identity on H . In a long line of research, retractions have been studied under various algorithmic settings. Recently, the problem of approximately counting retractions was considered. We give a complete trichotomy for the complexity of approximately counting retractions to all square-free graphs (graphs that do not contain a cycle of length 4). It turns out there is a rich and interesting class of graphs for which this problem is complete in the class #BIS. As retractions generalise homomorphisms, our easiness results extend to the important problem of approximately counting homomorphisms. By giving new #BIS-easiness results, we now settle the complexity of approximately counting homomorphisms for a whole class of non-trivial graphs that were previously unresolved.