Understanding Zipf's law of word frequencies through sample-space collapse in sentence formation

The formation of sentences is a highly structured and history-dependent process. The probability of using a specific word in a sentence strongly depends on the ‘history’ of word usage earlier in that sentence. We study a simple history-dependent model of text generation assuming that the sample-space of word usage reduces along sentence formation, on average. We first show that the model explains the approximate Zipf law found in word frequencies as a direct consequence of sample-space reduction. We then empirically quantify the amount of sample-space reduction in the sentences of 10 famous English books, by analysis of corresponding word-transition tables that capture which words can follow any given word in a text. We find a highly nested structure in these transition tables and show that this ‘nestedness’ is tightly related to the power law exponents of the observed word frequency distributions. With the proposed model, it is possible to understand that the nestedness of a text can be the origin of the actual scaling exponent and that deviations from the exact Zipf law can be understood by variations of the degree of nestedness on a book-by-book basis. On a theoretical level, we are able to show that in the case of weak nesting, Zipf''s law breaks down in a fast transition. Unlike previous attempts to understand Zipf''s law in language the sample-space reducing model is not based on assumptions of multiplicative, preferential or self-organized critical mechanisms behind language formation, but simply uses the empirically quantifiable parameter ‘nestedness’ to understand the statistics of word frequencies.     

Design of dynamic genetic memory

In electronic systems, dynamic random access memory (DRAM) is one of the core modules in the modern silicon computer. As for a bio‐computer, one would need a mechanism for storage of bio‐information named ‘data’, which, in binary logic, has two levels, logical high and logical low, or in the normalised form, ‘1’ and ‘0’. This study proposes a possible genetic DRAM based on the modified electronic configuration, which uses the biological reaction to fulfil an equivalent RC circuit constituting a memory cell. The authors implement fundamental functions of the genetic DRAM by incorporating a genetic toggle switch for data hold. The results of simulation verify that the basic function can be used on a bio‐storage module for the future bio‐computer.Inspec keywords: DRAM chips, genetic engineering, biocomputers, bioinformatics, equivalent circuits, RC circuitsOther keywords: dynamic genetic memory design, electronic systems, dynamic random access memory, modern silicon computer, biocomputer, bioinformation, binary logic, logical high level, logical low level, normalised form, genetic DRAM, modified electronic configuration, biological reaction, equivalent RC circuit, memory cell, fundamental functions, genetic toggle switch, data hold, biostorage module     

Improving Chinese Word Representation with Conceptual Semantics

The meaning of a word includes a conceptual meaning and a distributive meaning. Word embedding based on distribution suffers from insufficient conceptual semantic representation caused by data sparsity, especially for low-frequency words. In knowledge bases, manually annotated semantic knowledge is stable and the essential attributes of words are accurately denoted. In this paper, we propose a Conceptual Semantics Enhanced Word Representation (CEWR) model, computing the synset embedding and hypernym embedding of Chinese words based on the Tongyici Cilin thesaurus, and aggregating it with distributed word representation to have both distributed information and the conceptual meaning encoded in the representation of words. We evaluate the CEWR model on two tasks: word similarity computation and short text classification. The Spearman correlation between model results and human judgement are improved to 64.71%, 81.84%, and 85.16% on Wordsim297, MC30, and RG65, respectively. Moreover, CEWR improves the F1 score by 3% in the short text classification task. The experimental results show that CEWR can represent words in a more informative approach than distributed word embedding. This proves that conceptual semantics, especially hypernymous information, is a good complement to distributed word representation.     

The virtue of innovation: innovation through the lenses of biological evolution

We rehearse the processes of innovation and discovery in general terms, using as our main metaphor the biological concept of an evolutionary fitness landscape. Incremental and disruptive innovations are seen, respectively, as successful searches carried out locally or more widely. They may also be understood as reflecting evolution by mutation (incremental) versus recombination (disruptive). We also bring a platonic view, focusing on virtue and memory. We use ‘virtue’ as a measure of efforts, including the knowledge required to come up with disruptive and incremental innovations, and ‘memory’ as a measure of their lifespan, i.e. how long they are remembered. Fostering innovation, in the evolutionary metaphor, means providing the wherewithal to promote novelty, good objective functions that one is trying to optimize, and means to improve one''s knowledge of, and ability to navigate, the landscape one is searching. Recombination necessarily implies multi- or inter-disciplinarity. These principles are generic to all kinds of creativity, novel ideas formation and the development of new products and technologies.     

Single molecule dynamics in a virtual cell: a three-dimensional model that produces simulated fluorescence video-imaging data

The analysis of single molecule imaging experiments is complicated by the stochastic nature of single molecule events, by instrument noise and by the limited information which can be gathered about any individual molecule observed. Consequently, it is important to cross check experimental results using a model simulating single molecule dynamics (e.g. movements and binding events) in a virtual cell-like environment. The output of such a model should match the real data format allowing researchers to compare simulated results with the real experiments. The proposed model exploits the advantages of ‘object-oriented’ computing. First of all, the ability to create and manipulate a number of classes, each containing an arbitrary number of single molecule objects. These classes may include objects moving within the ‘cytoplasm’; objects moving at the ‘plasma membrane’; and static objects located inside the ‘body’. The objects of a given class can interact with each other and/or with the objects of other classes according to their physical and chemical properties. Each model run generates a sequence of images, each containing summed images of all fluorescent objects emitting light under given illumination conditions with realistic levels of noise and emission fluctuations. The model accurately reproduces reported single molecule experiments and predicts the outcome of future experiments.     

认知科学与信息认识论指导下的单词记忆软件信息设计方法

目的目前市场上的单词记忆软件没能将用户体验与记忆规律进行深度结合,希望通过人们在认知过程中的信息活动层次来构建单词记忆应用软件的信息架构,结合必应词典的背单词功能设计,提升手机词典背单词用户背单词的个性化与针对性,保证用户使用的有效性、效率及满意度。方法通过对人的信息活动层次理论分析与用户研究,同时以数据挖掘与知识发现为主要手段,利用自然语言理解技术,更大程度地获取用户的个性需求。结论认知科学与信息认识论对于认知记忆类软件的交互流程和信息架构的设计,具有极强的指导作用,符合用户的认知规律的应用流程,能够极大提高用户的心流体验,增强信息产品的可用性目标及用户体验目标的达成;智能化的算法可帮助用户形成以需求与兴趣为中心的个性化学习方案。     

Dual-resolution molecular dynamics simulation of antimicrobials in biomembranes

Triclocarban and triclosan, two potent antibacterial molecules present in many consumer products, have been subject to growing debate on a number of issues, particularly in relation to their possible role in causing microbial resistance. In this computational study, we present molecular-level insights into the interaction between these antimicrobial agents and hydrated phospholipid bilayers (taken as a simple model for the cell membrane). Simulations are conducted by a novel ‘dual-resolution’ molecular dynamics approach which combines accuracy with efficiency: the antimicrobials, modelled atomistically, are mixed with simplified (coarse-grain) models of lipids and water. A first set of calculations is run to study the antimicrobials'' transfer free energies and orientations as a function of depth inside the membrane. Both molecules are predicted to preferentially accumulate in the lipid headgroup–glycerol region; this finding, which reproduces corresponding experimental data, is also discussed in terms of a general relation between solute partitioning and the intramembrane distribution of pressure. A second set of runs involves membranes incorporated with different molar concentrations of antimicrobial molecules (up to one antimicrobial per two lipids). We study the effects induced on fundamental membrane properties, such as the electron density, lateral pressure and electrical potential profiles. In particular, the analysis of the spontaneous curvature indicates that increasing antimicrobial concentrations promote a ‘destabilizing’ tendency towards non-bilayer phases, as observed experimentally. The antimicrobials'' influence on the self-assembly process is also investigated. The significance of our results in the context of current theories of antimicrobial action is discussed.     

Structural performance of a climbing cactus: making the most of softness

Climbing plants must reach supports and navigate gaps to colonize trees. This requires a structural organization ensuring the rigidity of so-called ‘searcher’ stems. Cacti have succulent stems adapted for water storage in dry habitats. We investigate how a climbing cactus Selenicereus setaceus develops its stem structure and succulent tissues for climbing. We applied a ‘wide scale’ approach combining field-based bending, tensile and swellability tests with fine-scale rheological, compression and anatomical analyses in laboratory conditions. Gap-spanning ‘searcher’ stems rely significantly on the soft cortex and outer skin of the stem for rigidity in bending (60–94%). A woody core contributes significantly to axial and radial compressive strength (80%). Rheological tests indicated that storage moduli were consistently higher than loss moduli indicating that the mucilaginous cortical tissue behaved like a viscoelastic solid with properties similar to physical or chemical hydrogels. Rheological and compression properties of the soft tissue changed from young to old stages. The hydrogel–skin composite is a multi-functional structure contributing to rigidity in searcher stems but also imparting compliance and benign failure in environmental situations when stems must fail. Soft tissue composites changing in function via changes in development and turgescence have a great potential for exploring candidate materials for technical applications.     

New functionalities in abundant element oxides: ubiquitous element strategy

While most ceramics are composed of ubiquitous elements (the ten most abundant elements within the Earth''s crust), many advanced materials are based on rare elements. A ‘rare-element crisis’ is approaching owing to the imbalance between the limited supply of rare elements and the increasing demand. Therefore, we propose a ‘ubiquitous element strategy’ for materials research, which aims to apply abundant elements in a variety of innovative applications. Creation of innovative oxide materials and devices based on conventional ceramics is one specific challenge. This review describes the concept of ubiquitous element strategy and gives some highlights of our recent research on the synthesis of electronic, thermionic and structural materials using ubiquitous elements.     

First carrot,then stick: how the adaptive hybridization of incentives promotes cooperation

Social institutions often use rewards and penalties to promote cooperation. Providing incentives tends to be costly, so it is important to find effective and efficient policies for the combined use of rewards and penalties. Most studies of cooperation, however, have addressed rewarding and punishing in isolation and have focused on peer-to-peer sanctioning as opposed to institutional sanctioning. Here, we demonstrate that an institutional sanctioning policy we call ‘first carrot, then stick’ is unexpectedly successful in promoting cooperation. The policy switches the incentive from rewarding to punishing when the frequency of cooperators exceeds a threshold. We find that this policy establishes and recovers full cooperation at lower cost and under a wider range of conditions than either rewards or penalties alone, in both well-mixed and spatial populations. In particular, the spatial dynamics of cooperation make it evident how punishment acts as a ‘booster stage’ that capitalizes on and amplifies the pro-social effects of rewarding. Together, our results show that the adaptive hybridization of incentives offers the ‘best of both worlds’ by combining the effectiveness of rewarding in establishing cooperation with the effectiveness of punishing in recovering it, thereby providing a surprisingly inexpensive and widely applicable method of promoting cooperation.     

A search game model of the scatter hoarder's problem

Scatter hoarders are animals (e.g. squirrels) who cache food (nuts) over a number of sites for later collection. A certain minimum amount of food must be recovered, possibly after pilfering by another animal, in order to survive the winter. An optimal caching strategy is one that maximizes the survival probability, given worst case behaviour of the pilferer. We modify certain ‘accumulation games’ studied by Kikuta & Ruckle (2000 J. Optim. Theory Appl.) and Kikuta & Ruckle (2001 Naval Res. Logist.), which modelled the problem of optimal diversification of resources against catastrophic loss, to include the depth at which the food is hidden at each caching site. Optimal caching strategies can then be determined as equilibria in a new ‘caching game’. We show how the distribution of food over sites and the site-depths of the optimal caching varies with the animal''s survival requirements and the amount of pilfering. We show that in some cases, ‘decoy nuts’ are required to be placed above other nuts that are buried further down at the same site. Methods from the field of search games are used. Some empirically observed behaviour can be shown to be optimal in our model.     

Preventable H5N1 avian influenza epidemics in the British poultry industry network exhibit characteristic scales

Epidemics are frequently simulated on redundantly wired contact networks, which have many more links between sites than are minimally required to connect all. Consequently, the modelled pathogen can travel numerous alternative routes, complicating effective containment strategies. These networks have moreover been found to exhibit ‘scale-free’ properties and percolation, suggesting resilience to damage. However, realistic H5N1 avian influenza transmission probabilities and containment strategies, here modelled on the British poultry industry network, show that infection dynamics can additionally express characteristic scales. These system-preferred scales constitute small areas within an observed power law distribution that exhibit a lesser slope than the power law itself, indicating a slightly increased relative likelihood. These characteristic scales are here produced by a network-pervading intranet of so-called hotspot sites that propagate large epidemics below the percolation threshold. This intranet is, however, extremely vulnerable; targeted inoculation of a mere 3–6% (depending on incorporated biosecurity measures) of the British poultry industry network prevents large and moderate H5N1 outbreaks completely, offering an order of magnitude improvement over previously advocated strategies affecting the most highly connected ‘hub’ sites. In other words, hotspots and hubs are separate functional entities that do not necessarily coincide, and hotspots can make more effective inoculation targets. Given the ubiquity and relevance of networks (epidemics, Internet, power grids, protein interaction), recognition of this spreading regime elsewhere would suggest a similar disproportionate sensitivity to such surgical interventions.     

A minimal model of predator–swarm interactions

We propose a minimal model of predator–swarm interactions which captures many of the essential dynamics observed in nature. Different outcomes are observed depending on the predator strength. For a ‘weak’ predator, the swarm is able to escape the predator completely. As the strength is increased, the predator is able to catch up with the swarm as a whole, but the individual prey is able to escape by ‘confusing’ the predator: the prey forms a ring with the predator at the centre. For higher predator strength, complex chasing dynamics are observed which can become chaotic. For even higher strength, the predator is able to successfully capture the prey. Our model is simple enough to be amenable to a full mathematical analysis, which is used to predict the shape of the swarm as well as the resulting predator–prey dynamics as a function of model parameters. We show that, as the predator strength is increased, there is a transition (owing to a Hopf bifurcation) from confusion state to chasing dynamics, and we compute the threshold analytically. Our analysis indicates that the swarming behaviour is not helpful in avoiding the predator, suggesting that there are other reasons why the species may swarm. The complex shape of the swarm in our model during the chasing dynamics is similar to the shape of a flock of sheep avoiding a shepherd.     

A discrete spectral analysis for determining quasi-linear viscoelastic properties of biological materials

The viscoelastic behaviour of a biological material is central to its functioning and is an indicator of its health. The Fung quasi-linear viscoelastic (QLV) model, a standard tool for characterizing biological materials, provides excellent fits to most stress–relaxation data by imposing a simple form upon a material''s temporal relaxation spectrum. However, model identification is challenging because the Fung QLV model''s ‘box’-shaped relaxation spectrum, predominant in biomechanics applications, can provide an excellent fit even when it is not a reasonable representation of a material''s relaxation spectrum. Here, we present a robust and simple discrete approach for identifying a material''s temporal relaxation spectrum from stress–relaxation data in an unbiased way. Our ‘discrete QLV’ (DQLV) approach identifies ranges of time constants over which the Fung QLV model''s typical box spectrum provides an accurate representation of a particular material''s temporal relaxation spectrum, and is effective at providing a fit to this model. The DQLV spectrum also reveals when other forms or discrete time constants are more suitable than a box spectrum. After validating the approach against idealized and noisy data, we applied the methods to analyse medial collateral ligament stress–relaxation data and identify the strengths and weaknesses of an optimal Fung QLV fit.     

Evolving random fractal Cantor superlattices for the infrared using a genetic algorithm

Ordered and chaotic superlattices have been identified in Nature that give rise to a variety of colours reflected by the skin of various organisms. In particular, organisms such as silvery fish possess superlattices that reflect a broad range of light from the visible to the UV. Such superlattices have previously been identified as ‘chaotic’, but we propose that apparent ‘chaotic’ natural structures, which have been previously modelled as completely random structures, should have an underlying fractal geometry. Fractal geometry, often described as the geometry of Nature, can be used to mimic structures found in Nature, but deterministic fractals produce structures that are too ‘perfect’ to appear natural. Introducing variability into fractals produces structures that appear more natural. We suggest that the ‘chaotic’ (purely random) superlattices identified in Nature are more accurately modelled by multi-generator fractals. Furthermore, we introduce fractal random Cantor bars as a candidate for generating both ordered and ‘chaotic’ superlattices, such as the ones found in silvery fish. A genetic algorithm is used to evolve optimal fractal random Cantor bars with multiple generators targeting several desired optical functions in the mid-infrared and the near-infrared. We present optimized superlattices demonstrating broadband reflection as well as single and multiple pass bands in the near-infrared regime.     

Semantic word shifts in a scientific domain

Understanding semantic word shifts in scientific domains is essential for facilitating interdisciplinary communication. Using a data set of published papers in the field of information retrieval (IR), this paper studies the semantic shifts of words in IR based on mining per-word topic distribution over time. We propose that semantic word shifts not only occur over time, but also over topics. The shifts are examined from two perspectives, the topic-level and the context-level. According to the over-time word-topic distribution, stable words and unstable words are recognized. The diverging and converging trends in the unstable type reveal characteristics of the topic evolution process. The context-level shifts are further detected by similarities between word vectors. Our work associates semantic word shifts with the evolving of topics, which facilitates a better understanding of semantic word shifts from both topics and contexts.     

基于语义量化匹配的汽车外观显著性意象挖掘

目的 为解决传统感性设计研究中意象实验耗时大以及小样本偶然性等问题,依托现有网络评价文本信息提取了用户意象认知。方法 首先,爬取大规模汽车外观评论文本,构建语义分析词汇库,构建word2vec词向量模型;然后,基于模型获取词库内部的语义联系,计算高频关键形容词之间的语义离散性,以构建代表性意象词空间;最后,通过语义量化匹配将评论映射到意象词空间,得到大规模用户对各车型的显著性意象表征,明确了指定意象词汇下的汽车外观匹配结果。结果 运用该方法挖掘汽车外观显著性意象与基于人工评价的实验结果无显著性差异且具有高度相关性,证明了该方法的有效性。结论 以该方法挖掘用户意象认知,运用了现有的大批量用户反馈知识,提高了意象分析效率,有助于决策者快速理解消费者对汽车外观的感性知识,在设计迭代中可使产品更符合市场期望;对比相关研究,基于语义量化匹配的方式无需对超高维向量进行降维和聚类,避免了以往研究因特征降维而可能导致的词向量语义联系的损失,以得到更为准确的意象挖掘结果。     

Force transformation in spider strain sensors: white light interferometry

Scanning white light interferometry and micro-force measurements were applied to analyse stimulus transformation in strain sensors in the spider exoskeleton. Two compound or ‘lyriform’ organs consisting of arrays of closely neighbouring, roughly parallel sensory slits of different lengths were examined. Forces applied to the exoskeleton entail strains in the cuticle, which compress and thereby stimulate the individual slits of the lyriform organs. (i) For the proprioreceptive lyriform organ HS-8 close to the distal joint of the tibia, the compression of the slits at the sensory threshold was as small as 1.4 nm and hardly more than 30 nm, depending on the slit in the array. The corresponding stimulus forces were as small as 0.01 mN. The linearity of the loading curve seems reasonable considering the sensor''s relatively narrow biological intensity range of operation. The slits'' mechanical sensitivity (slit compression/force) ranged from 106 down to 13 nm mN⁻¹, and gradually decreased with decreasing slit length. (ii) Remarkably, in the vibration-sensitive lyriform organ HS-10 on the metatarsus, the loading curve was exponential. The organ is thus adapted to the detection of a wide range of vibration amplitudes, as they are found under natural conditions. The mechanical sensitivities of the two slits examined in this organ in detail differed roughly threefold (522 and 195 nm mN⁻¹) in the biologically most relevant range, again reflecting stimulus range fractionation among the slits composing the array.     

Semantic-enhanced topic evolution analysis: a combination of the dynamic topic model and word2vec

The combination of the topic model and the semantic method can help to discover the semantic distributions of topics and the changing characteristics of the semantic distributions, further providing a new perspective for the research of topic evolution. This study proposes a solution for quantifying the semantic distributions and the changing characteristics based on words in topic evolution through the Dynamic topic model (DTM) and the word2vec model. A dataset in the field of Library and information science (LIS) is utilized in the empirical study, and the topic-semantic probability distribution is derived. The evolving dynamics of the topics are constructed. The characteristics of evolving dynamics are used to explain the semantic distributions of topics in topic evolution. Then, the regularities of evolving dynamics are summarized to explain the changing characteristics of semantic distributions in topic evolution. Results show that no topic is distributed in a single semantic concept, and most topics correspond to various semantic concepts in LIS. The three kinds of topics in LIS are the convergent, diffusive, and stable topics. The discovery of different modes of topic evolution can further prove the development of the field. In addition, findings indicate that the popularity of topics and the characteristics of evolving dynamics of topics are irrelevant.

     

Fish and robots swimming together: attraction towards the robot demands biomimetic locomotion

The integration of biomimetic robots in a fish school may enable a better understanding of collective behaviour, offering a new experimental method to test group feedback in response to behavioural modulations of its ‘engineered’ member. Here, we analyse a robotic fish and individual golden shiners (Notemigonus crysoleucas) swimming together in a water tunnel at different flow velocities. We determine the positional preference of fish with respect to the robot, and we study the flow structure using a digital particle image velocimetry system. We find that biomimetic locomotion is a determinant of fish preference as fish are more attracted towards the robot when its tail is beating rather than when it is statically immersed in the water as a ‘dummy’. At specific conditions, the fish hold station behind the robot, which may be due to the hydrodynamic advantage obtained by swimming in the robot''s wake. This work makes a compelling case for the need of biomimetic locomotion in promoting robot–animal interactions and it strengthens the hypothesis that biomimetic robots can be used to study and modulate collective animal behaviour.