Population Dynamics in Diffusive Coupled Insect Population

A variety of ecological models exhibit chaotic dynamics because of nonlinearities in population growth and interactions. Here, we will study the LPA model (beetle Tribolium). The LPA model is known to exhibit chaos. In this project, we investigate two things which are the effect of noise constant and the effect of diffusion combined with the LPA model. The effect of noise is not only to change the dynamics of total population density but also to blur the bifurcation diagram. Numerical simulations of the model have shown that diffusion can drive the total population of insects into complex patterns of variability in time. We will compare these simulations with simulations without diffusion. And we conclude that the diffusion coefficient is a bifurcation parameter and that there exist parameter regions with chaotic behavior and periodic solutions. This study demonstrates how diffusion term can be used to influence the chaotic dynamics of an insect population

A Nonlinear Optimization Model of Advertising Budget Allocation across Multiple Digital Media Channels

The goal of advertisers in the digital marketing industry is to optimize their advertising budgets. Such a budget allocation problem plays a key role in maximizing advertising performance from different marketing channels under planned advertising investment. This study aimed to design a budget-performance-based nonlinear programming model to find an optimized solution for the advertising budget allocation problem. The empirical analysis results of a leading e-business company’s advertising performance data show that the proposed non-LP model generates an optimized solution. The proposed model allows marketers to simulate expected advertising returns, such as conversions or revenues from different channels within their budget constraints

Lithium Ion Storage Characteristics of Mechanically Fractured Titanate Nanotubes

The effect of mechanical milling on the formation of short titanate nanotube and structural change induced is investigated. Mechanical milling produces the short nanotubes with the length of 30–160 nm. The lithium ion intercalation characteristics of the obtained short titanate nanotube were studied to verify the effect of the newly formed cross-sections of nanotubes. It was found that the protonated titanate nanotubes maintained long shapes until 30 min of mechanical milling and were transformed into agglomerated nanosheets and finally anatase granules depending on the treatment duration. Through galvanostatic investigation, the nanotubes with milling of 15 min exhibited the highest discharge capacity of 336 mAh·g−1 in first cycle, 12.4% larger than pristine

Dichlorinated organic‐salt terahertz sources for THz spectroscopy

Although in terahertz (THz) source materials molecular anions significantly influence the performance of THz generation, only limited classes of molecular counter anions have been reported. Here, utilizing dichlorinated molecular anions in THz generators is reported for the first time, to the best of our knowledge. In these new crystals, two dichlorinated molecular anions with different molecular symmetries, asymmetric 3,4-dichlorobenzenesulfonate (34DCS) and symmetric 3,5-dichlorobenzenesulfonate (35DCS), are incorporated with a 2-(4-hydroxystyryl)-1-methylquinolinium (OHQ) cation possessing top-level molecular optical nonlinearity. OHQ-34DCS exhibits a strong nonlinear optical response, in contrast to OHQ-35DCS. In OHQ-34DCS crystals, the dichlorinated groups form strong halogen bonds (XBs) and hydrogen bonds (HBs), which are beneficial for suppressing molecular (phonon) vibrations. The optical-to-THz conversion efficiency of the OHQ-34DCS crystals is extremely high, comparable to that of the benchmark organic THz generators. Moreover, the THz emission spectra from the OHQ-34DCS crystals, compared to those of previously reported benchmark analogous crystals, are stronger modulated toward a flatter shape, but possess substantially reduced spectral dimples. Therefore, the introduction of dichlorinated molecular anions is an efficient approach for the design of highly efficient electro-optic salt crystals as efficient broadband THz wave sources

Phonon-suppressing intermolecular adhesives : catechol-based broadband organic THz generators

Solid-state molecular phonons play a crucial role in the performance of diverse photonic and optoelectronic devices. In this work, new organic terahertz (THz) generators based on a catechol group that acts as a phonon suppressing intermolecular adhesive are developed. The catechol group is widely used in mussel-inspired mechanical adhesive chemistry. Newly designed organic electro-optic crystals consist of catechol-based nonlinear optical 4-(3,4-dihydroxystyryl)-1-methylpyridinium (DHP) cations and 4-(trifluoromethyl)benzenesulfonate anions (TFS), which both have multiple interionic interaction capability. Interestingly, compared to benchmark organic crystals for THz generators, DHP-TFS crystals concomitantly achieve top level values of the lowest void volume and the highest crystal density, resulting in an exceptionally small amplitude of solid-state molecular phonons. Simultaneously achieving small molecular phonon amplitude, large optical nonlinearity and good phase matching at infrared optical pump wavelengths, DHP-TFS crystals are capable of generating broadband THz waves of up to 16 THz with high optical-to-THz conversion efficiency; one order of magnitude higher than commercial inorganic THz generators

Clustering cliques for graph-based summarization of the biomedical research literature

BACKGROUND: Graph-based notions are increasingly used in biomedical data mining and knowledge discovery tasks. In this paper, we present a clique-clustering method to automatically summarize graphs of semantic predications produced from PubMed citations (titles and abstracts). RESULTS: SemRep is used to extract semantic predications from the citations returned by a PubMed search. Cliques were identified from frequently occurring predications with highly connected arguments filtered by degree centrality. Themes contained in the summary were identified with a hierarchical clustering algorithm based on common arguments shared among cliques. The validity of the clusters in the summaries produced was compared to the Silhouette-generated baseline for cohesion, separation and overall validity. The theme labels were also compared to a reference standard produced with major MeSH headings. CONCLUSIONS: For 11 topics in the testing data set, the overall validity of clusters from the system summary was 10% better than the baseline (43% versus 33%). While compared to the reference standard from MeSH headings, the results for recall, precision and F-score were 0.64, 0.65, and 0.65 respectively

Adaptive Algorithms for Ordinal Optimisation and Dynamic Pricing in E-commerce

In Chapters 2 and 3, given a finite number of populations, henceforth referred to as systems, we are concerned with the problem of dynamically learning the statistical characteristics of the systems to ultimately select the best system. This is an instance of ordinal optimization where probability distributions governing each system's performance are not known, but can be learned via sequential sampling. In Chapter 2 we study the classical setting where the ultimate goal is to choose the system with the highest mean, while in Chatper 3 the systems are compared based on quantiles. The latter setting is appropriate when downside or upside risk is more crucial than the mean performance. In both settings, we use large deviations theory to derive key structural insights on near-optimal allocation of the sampling budget, which are leveraged to design dynamic sampling policies that are practically implementable. We rigorously provide (asymptotic) performance guarantees for these policies. Further, we show via numerical testing that the proposed (nonparametric) policies perform competitively compared to other benchmark policies. In Chapter 4, we investigate how the presence of product reviews affects a dynamic-pricing monopolist. A salient feature of our problem is that the demand function evolves over time in conjunction with the dynamics of the review system. The monopolist strives to maximize its total expected revenue over a finite horizon by adjusting prices in response to the review dynamics. To formulate the problem in tractable form, we study a fluid model, which is a good approximation when the volume of sales is large. This formulation lends itself to key structural insights, which are leveraged to design a well-performing pricing policy for the underlying revenue maximization problem. The proposed policy allows a closed-form expression for price and its performance is asymptotically near-optimal. We show via simulation and counterfactual analysis the effectiveness of the proposed policy in online markets with product reviews

A Distributed and Concurrent Environment of an Object Based System

Introduction From the past, object oriented programming has been conceived as useful in developing large software. In another dimension, concurrency has been emerged as a notion for modelling various activities that take place concurrently in the real world. Recently, these two notions have been naturally raising an another programming paradigm, concurrent object oriented programming. So far, several concurrent object oriented programming languages have been proposed. Actor[1], ABCL[7], and Concurrent Smalltalk[6] are typical examples. Among these, ABCL (An Object Based Concurrent Language) developed by A. Yonezawa has great potential in real domains, mainly due to its proper granularity of object and easy computation model to understand. It is a language that underlies object and asynchronous message passing between them. A. Yonezawa et al. have been implementing ABCL on two multiprocessor systems, EM-4 and AP1000[5, 8]. EM-4 is a packet-driven multiprocessor developed by ET