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Among various portfolio insurance strategies, option-based portfolio insurance (OBPI) stands out as the unique strategy offering both downside protection and minimum upside participation. Its implementation, however, is challenging for public funds, whose investors have different entry points and uncertain holding periods. In this article, the author extends OBPI to ensure downside protection over a rolling window. Such an objective reflects the common practice in which the performance of funds is regularly monitored over fixed time intervals. The author shows how to derive the optimal strategy using methods of reinforcement learning and demonstrates that it provides a more effective portfolio protection than the existing methods on both simulated and real-life data. [ABSTRACT FROM AUTHOR]

One of the research directions in Internet of Things (IoT) is the field of Context Management Platforms (CMPs) which is a specific type of IoT middleware. CMPs provide horizontal connectivity between vertically oriented IoT silos resulting in a noticeable difference in how IoT data streams are processed. As these context data exchanges can be monetised, there is a need to model and predict the context metrics and operational costs of this exchange to provide relevant and timely context in a large-scale IoT ecosystem. In this paper, we argue that caching all transient context information to satisfy this necessity requires large amounts of computational and network resources, resulting in tremendous operational costs. Using Service Level Agreements (SLAs) between the context providers, CMP, and context consumers, where the level of service imperfection is quantified and linked to the associated costs, we show that it is possible to find efficient caching and prefetching strategies to minimize the context management cost. So, this paper proposes a novel method to find the optimal rate of IoT data prefetching and caching. We show the main context caching strategies and the proposed mathematical models, then discuss how a correctly chosen proactive caching strategy and configurations can help to maximise the profit of CMP operation when multiple SLAs are defined. Our model is accurate up to 0.0016 in Root Mean Square Percentage Error against our simulation results when estimating the profits to the system. We also show our model is valid using the t-test value tending to 0 for all the experimental scenarios. [ABSTRACT FROM AUTHOR]

Making internet-of-things (IoT)-based applications context-aware demands large amounts of raw data to be collected, interpreted, stored, and reused or repurposed if needed from many domains and applications. Context is transient but interpreted data can be distinguished from IoT data in many aspects. Managing context in cache is a novel area of research that has been given very little attention. Performance metric-driven adaptive context caching (ACOCA) can have a profound impact on the performance and cost efficiency of context-management platforms (CMPs) when responding to context queries in realtime. Our paper proposes an ACOCA mechanism to maximize both the cost and performance efficiency of a CMP in near realtime. Our novel mechanism encompasses the entire context-management life cycle. This, in turn, distinctively addresses the problems of efficiently selecting context for caching and managing the additional costs of context management in the cache. We demonstrate that our mechanism results in long-term efficiencies for the CMP that have not been observed in any previous study. The mechanism employs a novel, scalable, and selective context-caching agent implemented using the twin delayed deep deterministic policy gradient method. It further incorporates an adaptive context-refresh switching policy, a time-aware eviction policy, and a latent caching decision management policy. We point out in our findings that the additional complexity of adaptation introduced to the CMP through ACOCA is significantly justified, considering the cost and performance gains achieved. Our algorithm is evaluated using a real-world inspired heterogeneous context-query load and a data set based on parking-related traffic in Melbourne, Australia. This paper presents and benchmarks the proposed scheme against traditional and context-aware caching policies. We demonstrate that ACOCA outperforms the benchmarks in both cost and performance efficiency, i.e., up to 68.6%, 84.7%, and 67% more cost efficient compared to traditional data caching policies to cache context, redirector mode, and context-aware adaptive data caching under real-world-like circumstances. [ABSTRACT FROM AUTHOR]

We successfully synthesized bulk Ba0.6Na0.4Fe2As2 and Sr0.5Na0.5Fe2As2 compounds by high-energy mechanical alloying (MA) technique. The MA process results in homogeneous amorphous phases of BaFe2As2 and SrFe2As2. It was found that the optimum time for high-energy milling in all cases is about 1.5–2 h, and the maximum amount of amorphous phase could be obtained when energy of 50–100 MJ/kg was absorbed by the powder. After a short-term heat treatment, we obtained nearly optimum sodium-doped Ba1−xNaxFe2As2 and Sr1−xNaxFe2As2 superconducting bulk samples. Therefore, MA is a potential scalable method to produce bulk superconducting material for industrial needs. [ABSTRACT FROM AUTHOR]

The article presents design and methodology of a novel benchmark suite named IMB-ASYNC. The presented suite and method are aimed at measuring and comparing practical communication-computation overlap levels for Message Passing Interface standard (MPI) implementations with a special accent to some applicable use cases. Some typical MPI communication patterns implying communication-computation overlap are analyzed, and their reflection on a benchmark structure is proposed. We also analyze the previous works on overlap benchmarking and their best practices. We present a new benchmarking approach for non-blocking neighborhood collectives overlap and clarify the overlap estimation methodology. After a short overview of some technical details of currently available MPI asynchronous progress implementations, two benchmarking case studies are presented to illustrate the relevance of the methodology. [ABSTRACT FROM AUTHOR]

Railway systems form an important means of transport across the world. However, congestions or disruptions may significantly decrease these systems' efficiencies, making predicting and understanding the resulting train delays a priority for railway organisations. Delays are studied in a wide variety of models, which usually simulate trains as discrete agents carrying delays. In contrast, in this paper, we define a novel model for studying delays, where they spread across the railway network via a diffusion-like process. This type of modelling has various advantages such as quick computation and ease of applying various statistical tools like spectral methods, but it also comes with limitations related to the directional and discrete nature of delays and the trains carrying them. We apply the model to the Belgian railways and study its performance in simulating the delay propagation in severely disrupted railway situations. In particular, we discuss the role of spatial aggregation by proposing to cluster the Belgian railway system into sets of stations and adapt the model accordingly. We find that such aggregation significantly increases the model's performance. For some particular situations, non-trivial optimal levels of spatial resolution are found on which the model performs best. Our results show the potential of this type of delay modelling to understand large-scale properties of railway systems. [ABSTRACT FROM AUTHOR]

DJ-1, also known as Parkinson's disease protein 7, is a multifunctional protein ubiquitously expressed in cells and tissues. Interacting with proteins of various intracellular compartments, DJ-1 plays an important role in maintaining different cellular functions. Mutant DJ-1 forms containing amino acid substitutions (especially L166P), typical of Parkinson's disease, are characterized by impaired dimerization, stability, and folding. DJ-1 exhibits several types of catalytic activity; however, in the enzyme classification it exists as protein deglycase (EC 3.5.1.124). Apparently, in different cell compartments DJ-1 exhibits catalytic and non-catalytic functions, and their ratio still remains unknown. Oxidative stress promotes dissociation of cytoplasmic DJ-1 dimers into monomers, which are translocated to the nucleus, where this protein acts as a coactivator of various signaling pathways, preventing cell death. In mitochondria, DJ-1 is found in the synthasome, where it interacts with the β ATP synthase subunit. Downregulation of the DJ-1 gene under conditions of experimental PD increases sensitivity of the cells to neurotoxins, and introduction of the recombinant DJ-1 protein attenuates manifestation of this pathology. The thirteen-membered fragment of the DJ-1 amino acid sequence attached to the heptapeptide of the TAT protein penetrating into the cells exhibited neuroprotective properties in various PD models both in cell cultures and after administration to animals. Low molecular weight DJ-1 ligands also demonstrate therapeutic potential, providing neuroprotective effects seen during their incubation with cells and administration to animals. [ABSTRACT FROM AUTHOR]

We derive an asymptotic expansion formula for option implied volatility under a two-factor jump-diffusion stochastic volatility model when time-to-maturity is small. We further propose a simple calibration procedure of an arbitrary parametric model to short-term near-the-money implied volatilities. An important advantage of our approximation is that it is free of the unobserved spot volatility. Therefore, the model can be calibrated on option data pooled across different calendar dates to extract information from the dynamics of the implied volatility smile. An example of calibration to a sample of S&P 500 option prices is provided. [ABSTRACT FROM AUTHOR]

Internet boards are platforms for online discussion about a variety of topics. On these boards, individuals may start a new thread on a specific matter or leave comments in an existing discussion. The resulting collective process leads to the formation of 'discussion trees', where nodes represent a post and comments, and an edge represents a 'reply-to' relation. The structure of discussion trees has been analysed in previous works, but mainly from a static perspective. In this article, we focus on the structural and dynamical properties of discussion trees by modelling their formation as a self-exciting Hawkes process with a branching structure. We first study a Reddit data set of all posts and comments submitted between 2008 and 2014 to show that the structure of the trees resemble those produced by a Galton–Watson process with a special root offspring distribution. The dynamical aspect of the model is then used to predict future commenting activity and the final size of a discussion tree. We compare the efficiency of our approach with previous works and show its superiority for the prediction of discussion dynamics. In particular, we find that the Reddit discussion trees, being fundamentally broader than for example the Twitter cascades and developing with a qualitatively different dynamics, require appropriate models. The tree structure and the dynamics are influenced mainly by the age of the discussion, rather than by the number of acquired comments. The post and the comments are further commented by different processes, which is a key ingredient in modelling of discussions. [ABSTRACT FROM AUTHOR]

The population of the Earth is moving towards urban areas forming smart cities (SCs). Waste management is a component of SCs. We consider a SC which contains a distribution of waste bins and a distribution of waste trucks located in the SC sectors. Bins and trucks are enabled with Internet of Things (IoT) sensors and actuators. Prior approaches focus mainly on the dynamic scheduling and routing issues emerging from IoT-enabled waste management. However, less research has been done in the area of the stochastic reassignment process during the four seasons of the year over a period of two years. In this paper we aim to stochastically reassign trucks to collect waste from bins through time. We treat this problem with a multi-agent system for stochastic analyses. [ABSTRACT FROM AUTHOR]

We present an approach to build of real time continuous seam finder module with waveform generator (arbitrary signal can be generated), which allows automatic coordinate correction within 2ms on the go. Module is made for electron beam welding facility developed at Institute of nuclear physics SB RAS. Hard real time subsystem is implemented on hybrid CPU+FPGA architecture. ADC data from secondary emission electrode processed with program written on domain specific language Caph (program calculates seam position within 20us). [ABSTRACT FROM AUTHOR]

The Pancake graph $$P_n,\,n\geqslant 3$$ , is a Cayley graph on the symmetric group generated by prefix-reversals. It is known that $$P_n$$ contains any $$\ell $$ -cycle for $$6\leqslant \ell \leqslant n!$$ . In this paper we construct a family of maximal (covering) sets of even independent (vertex-disjoint) cycles of lengths $$\ell $$ bounded by $$O(n^2)$$ . We present the new concept of prefix-reversal Gray codes based on independent cycles which extends the known greedy prefix-reversal Gray code constructions given by Zaks and Williams. Cases of non-existence of codes based on the presented family of independent cycles are provided using the fastening cycle approach. We also give necessary condition for existence of greedy prefix-reversal Gray codes based on the independent cycles with arbitrary even lengths. [ABSTRACT FROM AUTHOR]

A series of novel crown ether-containing photochromic comb-shaped liquid crystalline polyacrylates with different macromolecular structure of side groups were synthesized and investigated. Phase behavior, optical and photo-optical properties of thin spin-coated films of these polymers were studied. A special attention was paid to a comparative study of the photo-orientation phenomena occurring in the polymer films under a polarized light action. It was shown that complex formation with the potassium ions results in the decrease in degree of the photoinduced order that can be used for the creation of new materials for sensor devices. © 2010 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem, 2011 [ABSTRACT FROM AUTHOR]

Satisfying a context consumer's quality of context (QoC) requirements is important to context management platforms (CMPs) in order to have credibility. QoC indicates the contextual information's quality metrics (e.g., accuracy, timeliness, completeness). The outcomes of these metrics depend on the functional and quality characteristics associated with all actors (context consumers (or) context-aware applications, CMPs, and context providers (or) IoT-data providers) in context-aware IoT environments. This survey identifies and studies such characteristics and highlights the limitations in actors' current functionalities and QoC modelling approaches to obtain adequate QoC and improve context consumers' quality of experience (QoE). We propose a novel concept system based on our critical analysis; this system addresses the functional limitations in existing QoC modelling approaches. Moreover, we highlight those QoC metrics affected by quality of service (QoS) metrics in CMPs. These recommendations provide CMP developers with a reference system they could incorporate, functionalities and QoS metrics to maintain in order to deliver an adequate QoC. [ABSTRACT FROM AUTHOR]

As the Internet of Things (IoT) is evolving at a fast pace, the need for contextual intelligence has become more crucial for delivering IoT intelligence, efficiency, effectiveness, performance, and sustainability. Contextual intelligence enables interactions between IoT devices such as sensors/actuators, smartphones and connected vehicles, to name but a few. Context management platforms (CMP) are emerging as a promising solution to deliver contextual intelligence for IoT. However, the development of a generic solution that allows IoT devices and services to publish, consume, monitor, and share context is still in its infancy. In this paper, we propose, validate and explain the details of a novel mechanism called Context Query Engine (CQE), which is an integral part of a pioneering CMP called Context-as-a-Service (CoaaS). CQE is responsible for efficient execution of context queries in near real-time. We present the architecture of CQE and illuminate its workflows. We also conduct extensive experimental performance and scalability evaluation of the proposed CQE. Results of experimental evaluation convincingly demonstrate that CoaaS outperforms its competitors in executing complex context queries. Moreover, the advanced functionality of the embedded query language makes CoaaS a decent candidate for real-life deployments. [ABSTRACT FROM AUTHOR]

Prostacyclin synthase (PTGIS; EC 5.3.99.4) catalyzes isomerization of prostaglandin H2 to prostacyclin, a potent vasodilator and inhibitor of platelet aggregation. At present, limited data exist on functional coupling and possible ways of regulating PTGIS due to insufficient information about protein–protein interactions in which this crucial enzyme is involved. The aim of this study is to isolate protein partners for PTGIS from rat tissue lysates. Using CNBr-activated Sepharose 4B with covalently immobilized PTGIS as an affinity sorbent, we confidently identified 58 unique proteins by mass spectrometry (LC-MS/MS). The participation of these proteins in lysate complex formation was characterized by SEC lysate profiling. Several potential members of the PTGIS subinteractome have been validated by surface plasmon resonance (SPR) analysis. SPR revealed that PTGIS interacted with full-length cytochrome P450 2J2 and glutathione S-transferase (GST). In addition, PTGIS was shown to bind synthetic peptides corresponding to sequences of for GSTA1, GSTM1, aldo-keto reductase (AKR1A1), glutaredoxin 3 (GLRX3) and histidine triad nucleotide binding protein 2 (HINT2). Prostacyclin synthase could potentially be involved in functional interactions with identified novel protein partners participating in iron and heme metabolism, oxidative stress, xenobiotic and drugs metabolism, glutathione and prostaglandin metabolism. The possible biological role of the recognized interaction is discussed in the context of PTGIS functioning. [ABSTRACT FROM AUTHOR]

As IoT grows at a staggering pace, the need for contextual intelligence is a fundamental and critical factor for IoT intelligence, efficiency, effectiveness, performance, and sustainability. As the standardisation efforts for IoT are fast progressing, efforts in standardising context management platforms led by the European Telecommunications Standards Institute (ETSI) are gaining more attention from both academic and industrial research organizations. These standardisation endeavours will enable intelligent interactions between 'things', where things could be devices, software components, web-services, or sensing/actuating systems. Therefore, having a generic platform to describe and query context is crucial for the future of IoT applications. In this paper, we propose Context Definition and Query Language (CDQL), an advanced approach that enables things to exchange, reuse and share context between each other. CDQL consists of two main parts, namely: context definition model, which is designed to describe situations and high-level context; and Context Query Language (CQL), which is a powerful and flexible query language to express contextual information requirements without considering details of the underlying data structures. An important feature of the proposed query language is its ability to query entities in IoT environments based on their situation in a fully dynamic manner where users can define situations and context entities as part of the query. We exemplify the usage of CDQL on three different smart city use cases to highlight how CDQL can be utilised to deliver contextual information to IoT applications. Performance evaluation has demonstrated scalability and efficiency of CDQL in handling a fairly large number of concurrent context queries. [ABSTRACT FROM AUTHOR]