Search Mode Research Articles

Single molecule iSCAT imaging reveals a fast, energy efficient search mode for the DNA repair protein UvrA.

Exposure to UV radiation results in numerous DNA lesions, which threaten genome integrity. The nucleotide excision DNA repair pathway detects and repairs a range of such UV-induced DNA lesions. In bacteria, initial damage detection and verification is carried out by two proteins: UvrA and UvrB. Despite decades of study, the process of how these proteins locate damage remains unclear. Here we use high-speed interferometric scattering (iSCAT) microscopy, in combination with a surface-bound-DNA assay, to investigate early damage detection by UvrA. We have discovered that UvrA interacts with DNA in two phases; a slow phase (∼1.3 s−1) that correlates with an ATP-consuming state previously identified, and a second, much faster search mode. These faster interactions persist for ∼130 ms and using ATP analogues we determine this phase does not require ATP consumption. Including this new fast-search state in a model of the DNA search process reveals that only with this state is it possible for basal levels of UvrA to explore 99% of the E. coli genome within a single division cycle. Altogether, this work uncovers the presence of a rapid, energy efficient search mechanism, which allows UvrA alone to search the entirety of the E. coli genome within a single division cycle.

Q-learning embedded sine cosine algorithm (QLESCA)

Sine Cosine Algorithm (SCA) was recognized as a lightweight, efficient, and has a clear math principal optimizer. However, SCA still suffers from a set of problems such as stagnation at local optima, a slow convergence curve, and a lack of efficient balancing between exploration and exploitation search modes. To mitigate these limitations and improve SCA performance, this study introduces a new version of SCA called QLESCA that smartly controls SCA parameters through an embedded Q-learning algorithm at run time. Each QLESCA agent evolves independently, and it has its own Q-table. The Q-table contains nine different states computed based on population density and distance from the micro population leader. As such, nine different actions are generated by Q-table to control QLESCA parameters, namely r1 and r3. These QLESCA parameters are responsible for adaptive switching from exploration/exploitation and vice versa. For each Q-table action, a reward value is given to a well-performing agent and a penalty to a non-performing agent. To verify the proposed algorithm's performance, QLESCA was evaluated with 23 continuous benchmarks, 20 large scale benchmark optimization functions, and three engineering design problems. In addition, the conducted analysis was compared with various SCA variant algorithms and other state-of-the-art swarm-based optimization methods. The numerical results demonstrate that the QLESCA was superior in terms of achieved fitness value. Statistical results confirm that QLESCA significantly outperforms other optimization algorithms. Additionally, the convergence curve outcomes show that the proposed QLESCA optimization obtains fast convergence against other conducted algorithms.

Research on drivers' hazard perception in plateau environment based on visual characteristics

A good visual search mode is an important prerequisite for a driver to perceive the hazard in the traffic environment timely and accurately. However, hypoxia conditions in the plateau environment might affect drivers' cognitive and judgment ability, posing potential threats to safe driving. This study analyzed the eye movement behaviors of drivers when faced with traffic hazards in the plateau environment, to examine the impact level of altitude on drivers’ perception and reaction. Nine typical traffic hazard scenarios were investigated at four locations with four different altitudes, including Linzhi, Lhasa, Naqu, and Yanghu Scenic Area based on UC-WIN / ROAD driving simulation software. Then, drivers’ visual search modes were analyzed according to drivers’ eye movement data collected by ASL Mobile Eye monocular eye tracker. As the altitude increased, the drivers’ first fixation time and the average saccade amplitude decreased, while the fixation duration percentage increased. Drivers with fewer years of driving experience had a larger percentage of fixation duration and a smaller saccade amplitude. In addition, a shorter acclimation period also negatively influenced the percentage of fixation time. The increase of altitude would weaken the drivers' visual sensitivity and cognitive processing ability of hazard information, which would reduce drivers' hazard perception skills, and the increase of driving experience might help alleviate such negative impacts to some extent. Based on the visual characteristics of traffic hazard scenarios obtained in this paper, the training of highly accident-prone drivers can be guided specifically to improve their visual search strategies, thereby improving driving safety.

Design of integrated searching and tracking optical systems based on freeform mirrors.

Target searching and tracking photoelectric systems are widely used in civil and military fields. Achieving both efficient search and fine-observation imaging while minimizing the volume and weight of the system is the most concerning problem. In this paper, a dual-mode integrated optical system is proposed, which shares large size components between large field of view (FOV) search module and high-resolution tracking module by using the Biconic Zernike freeform mirrors. Compared with the traditional searching and tracking system utilizing multi-camera matching, this scheme significantly reduces the volume and weight of the remote sensing payload. At the orbit altitude of 500 km, this proposed system has a swath of 87.5 km with a ground resolution of 10 m in search mode. In tracking mode, it can observe an area of 19 km2 with a ground resolution of 1 m. It can meet the requirements of wide-area search and focus tracking simultaneously, providing a feasible scheme for the lightweight design of space optical cameras.

How Headline Strategies and News Sources Affect Number of User Clicks on WeChat

ABSTRACT This study used 2,623 WeChat article headlines on the Chengdu school food safety event and employed quantitative content analysis to explore the dynamic relationship of headline strategy (i.e., headline style and headline frame) and news source with user clicks at distinct phases of the issue–attention cycle. The results first revealed that various types of headline styles affect the number of user clicks based on the issue–attention phase, but no single type dominates public attention at any phase. Second, reader attention could be attracted using the information with the singleton detection mode. However, the feature search mode could filter official-oriented discourse. Third, the “treatment recommendation” headline frame, which clearly summarises the core of texts, generally lacked executability and had a poor effect on audience mobilisation. Fourth, readers depended on certain media channels under low-choice media environment, and information issued by administrative sources was not widely spread because of the limitation on their functions and specific targets. Finally, news from traditional mainstream media, online communities, and independent sources were more click-attractive news than the news from other sources, thus demonstrating a complementary relationship between official reports and social media discourses.

Is more diverse always the better? External knowledge source clusters and innovation performance in Germany

ABSTRACT This study gives a new identity to a knowledge search mode named search diversity and investigates how it is more rigorous in capturing knowledge heterogeneity in comparison to general assessment of search breadth. By distinguishing between diversifying and expanding search domain as building blocks of broadening search scope, this study proposes a hybrid search strategy when it comes to analysis of the link between external search and innovation performance. While a positive trend is found for search breadth and innovation in this article, search diversity indicates a curvilinear pattern but with a steeper positivity than search breadth. A prerequisite extension of this article is to use a clustering method among different external sources acting as a reference to codify a diversity index for measuring the new search scheme. In addition, the effect of usage of each cluster on innovation is empirically illustrated. This article suggests that the optimal hybrid search outlook in respect to innovation is built up by initially increasing diversity in search up to the downturn point and then shifting into usage of same source clusters without helping diversity. This analysis provides practitioners with additional insights for managing external sourcing strategies and leveraging innovativeness.

Motor development: from dynamical system approach to a neo-developmental application

The aim of this study was to present a dynamical view of motor development and a few factors affecting the developmental course and rate of motor changes. The acquisition of motor skills involves one’s exploration of many body segmental configurations, followed by the selection of those that are most useful to achieve the task demands. Exploration and selection are attained through searching and the evolution and dissolution of the stable dynamical regions of coordination modes for a given task. Development then involves an interaction between the learner and environment, dissolving relatively successful dynamics in search of even more rewarding dynamics for the new task, based upon repetitive perception-action cycles. Developmental changes can occur naturally, but can also be deterministically influenced by, for example, teachers enhancing the probability of systematic change in performance over time. This influence can be through the planned introduction of interventions and providing information that drives the learner to transition to stable modes of performance and search for new body configuration dynamics required for the new task. Teachers play an important role in guiding learners through this complex developmental journey.

Credibilistic fuzzy clustering based on evolutionary method of crazy cats

The problem of fuzzy clustering of large datasets that are sent for processing in both batch and online modes, based on a credibilistic approach, is considered. To find the global extremum of the credibilistic fuzzy clustering goal function, the modification of the swarm algorithm of crazy cats swarms was introduced, that combined the advantages of evolutionary algorithms and a global random search. It is shown that different search modes are generated by a unified mathematical procedure, some cases of which are known algorithms for both local and global optimizations. The proposed approach is easy to implement and is characterized by the high speed and reliability in problems of multi-extreme fuzzy clustering.

A Lane Level Bi-Directional Hybrid Path Planning Method Based on High Definition Map

A global reference path generated by a path search algorithm based on a road-level driving map cannot be directly used to complete the efficient autonomous path-following motion of autonomous vehicles due to the large computational load and insufficient path accuracy. To solve this problem, this paper proposes a lane-level bidirectional hybrid path planning method based on a high-definition map (HD map), which effectively completes the high-precision reference path planning task. First, the global driving environment information is extracted from the HD map, and the lane-level driving map is constructed. Real value mapping from the road network map to the driving cost is realized based on the road network information, road markings, and driving behavior data. Then, a hybrid path search method is carried out for the search space in a bidirectional search mode, where the stopping conditions of the search method are determined by the relaxation region in the two search processes. As the search process continues, the dimension of the relaxation region is updated to dynamically adjust the search scope to maintain the desired search efficiency and search effect. After the completion of the bidirectional search, the search results are evaluated and optimized to obtain the reference path with the optimal traffic cost. Finally, in an HD map based on a real scene, the path search performance of the proposed algorithm is compared with that of the simple bidirectional Dijkstra algorithm and the bidirectional BFS search algorithm. The results show that the proposed path search algorithm not only has a good optimization effect, but also has a high path search efficiency.

Differential equation model for central-place foragers with memory: implications for bumble bee crop pollination.

Bumble bees provide valuable pollination services to crops around the world. However, their populations are declining in intensively farmed landscapes. Understanding the dispersal behaviour of these bees is a key step in determining how agricultural landscapes can best be enhanced for bumble bee survival. Here we develop a partial integro-differential equation model to predict the spatial distribution of foraging bumble bees in dynamic heterogeneous landscapes. In our model, the foraging population is divided into two subpopulations, one engaged in an intensive search mode (modeled by diffusion) and the other engaged in an extensive search mode (modeled by advection). Our model considers the effects of resource-dependent switching rates between movement modes, resource depletion, central-place foraging behaviour, and memory. We use our model to investigate how crop pollination services are affected by wildflower enhancements. We find that planting wildflowers such that the crop is located in between the wildflowers and the nest site can benefit crop pollination in two different scenarios. If the bees do not have a strong preference for wildflowers, a small or low density wildflower patch is beneficial. If, on the other hand, the bees strongly prefer the wildflowers, then a large or high density wildflower patch is beneficial. The increase of the crop pollination services in the later scenario is of remarkable magnitude.

Intravascular Crawling of Patrolling Monocytes: A Lèvy-Like Motility for Unique Search Functions?

Patrolling monocytes (PMo) are the organism’s preeminent intravascular guardians by their continuous search of damaged endothelial cells and harmful microparticles for their removal and to restore homeostasis. This surveillance is accomplished by PMo crawling on the apical side of the endothelium through regulated interactions of integrins and chemokine receptors with their endothelial ligands. We propose that the search mode governs the intravascular motility of PMo in vivo in a similar way to T cells looking for antigen in tissues. Signs of damage to the luminal side of the endothelium (local death, oxidized LDL, amyloid deposits, tumor cells, pathogens, abnormal red cells, etc.) will change the diffusive random towards a Lèvy-like crawling enhancing their recognition and clearance by PMo damage receptors as the integrin αMβ2 and CD36. This new perspective can help identify new actors to promote unique PMo intravascular actions aimed at maintaining endothelial fitness and combating harmful microparticles involved in diseases as lung metastasis, Alzheimer’s angiopathy, vaso-occlusive disorders, and sepsis.

Improved cat swarm optimization for permutation flow shop scheduling problem

To minimize the maximum make span of permutation flow shop scheduling problem, this paper proposed a cat swarm optimization algorithm based on estimation of distribution algorithms. This article Take the cat swarm optimization as the framework, embedded in the Estimation Distribution Algorithm, in the search mode, mining the excellent gene link in the solution sequence by using the probability matrix to combination blocks, speed and position tracking mode using characteristics of cat swarm optimization updates in the cat in order to update the excellent solution sequence generator group. Finally, through the simulation test and result comparison of Carlier and Reeves standard example set, the good robustness and global searching ability of the algorithm are verified.

Global research productivity in cybersecurity: a scientometric study

PurposeThe purpose of the study is to conduct a scientometric analysis of cybersecurity literature indexed in the core collection of the Web of Science for a period of ten years (2011–2020).Design/methodology/approachCybersecurity is a focused topic of research across the globe. To identify the global research productivity in the field, the terms “cybersecurity, cyber-security, web security, information security, computer security, etc.” were used for retrieving the publications in the advanced search mode of the database “Web of Science”, limiting the time frame for 2011– 2020. The results retrieved were downloaded in the Excel file for further analysis and interpretation. The harvested data was analysed by using scientometric techniques to measure the progress such as growth rate, doubling time and author collaborations. Besides, the Biblioshiny and VOSviewer software were used for mapping networks.FindingsThe research output in the field of cybersecurity has shown an increasing trend during 2011–2020, and the maximum number of scholarly publications was published in 2020 (1,581), i.e. more than 715% of 2011 (221). A good number of countries (93) have contributed globally in cybersecurity research, and the highest share in research publications was reported by the USA (23.55%), followed by China (23.24%), South Korea (5.31%), UK (5.28%) and India (4.25%). The authorship patterns in cybersecurity publications show a collaborative trend, as most articles have been published by multiple authors. Total 5,532 (90.14%) articles have been published in co-authorship, whereas only 605 (9.86%) articles have been published by single authors. Keyword analysis shows that the most common keyword research by the authors is cybersecurity and its variants such as “cyber security” and “cyber-security” (1,698) followed by security (782), computer security (680) and information security (329).Research limitations/implicationsThe database studied for the work does not represent the total literary output available on the theme. There are plenty of other databases, such as Scopus, Compendex, INSPEC, IEEE Xplore, arXiv, contributing to the same theme as well.Practical implicationsThe findings of the study may help researchers, information technologists, library professionals and information specialists to identify the research progress, authorship patterns, collaborative networks and hot topics of research in the field of cybersecurity. Besides, it will assess the global response to the cybersecurity issue.Originality/valueThe study is the scientometric analysis of the cybersecurity based on current literature and will highlight the progress and development of global research in the said field.

Diversity collaboratively guided random drift particle swarm optimization

The random drift particle swarm optimization (RDPSO) algorithm is an effective random search technique inspired by the trajectory analysis of the canonical PSO and the free electron model in metal conductors placed in an external electric field. However, like other PSO variants, the RDPSO algorithm also inevitably encounters premature convergence when solving multimodal problems. To address this issue, this paper proposes a novel diversity collaboratively guided (DCG) strategy for the RDPSO algorithm that enhances the search ability of the algorithm. In this strategy, two kinds of diversity measures are defined and modified in a collaborative manner. Specifically, the whole search process of the RDPSO is divided into three phases based on the changes in the two diversity measures. In each phase, different values are selected for the key parameters of the update equation in the RDPSO to make the particle swarm perform different search modes. Consequently, the improved RDPSO algorithm with the DCG strategy (DCG-RDPSO) can maintain its diversity dynamically at a certain level, and thus can search constantly without stagnation until the search process terminates. The performance evaluation of the proposed algorithm is done on the CEC-2013 benchmark suite, in comparison with several versions of RDPSO, different variants of PSO and several non-PSO evolutionary algorithms. Experimental results show that the proposed DCG strategy can significantly improve the performance and robustness of the RDPSO algorithm for most of the multimodal problems. Further experiments on economic dispatch problems also verify the effectiveness of the DCG strategy.

RONIN

Dataset discovery can be performed using search (with a query or keywords) to find relevant data. However, the result of this discovery can be overwhelming to explore. Existing navigation techniques mostly focus on linkage graphs that enable navigation from one data set to another based on similarity or joinability of attributes. However, users often do not know which data set to start the navigation from. RONIN proposes an alternative way to navigate by building a hierarchical structure on a collection of data sets: the user navigates between groups of data sets in a hierarchical manner to narrow down to the data of interest. We demonstrate RONIN, a tool that enables user exploration of a data lake by seamlessly integrating the two common modalities of discovery: data set search and navigation of a hierarchical structure. In RONIN, a user can perform a keyword search or joinability search over a data lake, then, navigate the result using a hierarchical structure, called an organization , that is created on the fly. While navigating an organization, the user may switch to the search mode, and back to navigation on an organization that is updated based on search. This integration of search and navigation provides great power in allowing users to find and explore interesting data in a data lake.

Real-parameter constrained optimization using enhanced quality-based cultural algorithm with novel influence and selection schemes

Hybridization in context to Evolutionary Computation (EC) strives to combine operators, components, and the best merits of different EC paradigms, to form a new evolutionary algorithm that enjoys a statistically superior performance, compared to its ancestors, over a wide range of application-specific optimization problems. In this paper, we propose a simple yet powerful amalgam composed of a modified Cultural Algorithm (CA) that is supported with an Enhanced Levy Flight Search (ELFS) to guide the search and further promote the harmony between the explorative and exploitative capacities of the conventional techniques. The novel amalgam, denoted by q-aCA + mIS, utilizes a balanced search scheme where it employs an adapted Influence Function (IF) with a novel quality function that establishes a harmony between the Knowledge Sources (KSs) in the Belief Space (BS), and between the BS and other components in the hybrid to produce the most suitable knowledge needed for a certain search mode. The CA framework is reinforced with an updated Selection Function (SF) that employs a successful selection strategy that uses the extended situational knowledge for the future selection of individuals. The proposed algorithm is tested using more than 50 benchmark functions that are taken from the IEEE CEC’06, and the IEEE CEC’19 competitions on constrained real-parameter optimization. Moreover, three well-known engineering design problems are used to test the validity of the algorithm for the solution of complex real-life problems. The comparative study indicates that the q-aCA + mIS algorithm was able to obtain a statistically superior performance and scalability behavior over most of the considered functions in comparison with other state-of-the-art algorithms.

ВИКОРИСТАННЯ ІННОВАЦІЙНИХ ФОРМ НАВЧАННЯ НА УРОКАХ АНГЛІЙСЬКОЇ МОВИ

Nowadays foreign language is not just a part of nation's culture, it is also the guarantee of student’s successful career in the future. The achievement of high level proficiency of foreign language is not possible without fundamental language training in higher education institution. Most of them in our country provide students with at least two or even three foreign languages. In the context of higher school reforming, important changes in the educational technologies of foreign language teaching are envisaged. Modern language education is also gradually being modernized, introducing a modular rating system for teaching foreign languages. Interdisciplinary integration, democratization and economization of education determine the manifestation of innovative components in the teaching of the foreign languages. All this requires the formulation of the new claims for teaching and a foreign language teacher in the Free Economic Zone. At the current stage of society development, the purpose of foreign language teaching in higher education institutions is students' mastering of communicative competencies that will allow them to implement their knowledge, skills and abilities to solve specific communicative tasks in real life situations. The introduction of the new effective methods of foreign language teaching in the process of preparing students of humanities and technical specialties has become not only desirable but also necessary. Innovative orientation requires teachers to master and apply the pedagogical innovations, as well as stimulate the search for new forms and methods of educational process organization. High-quality language training of students is impossible without the use of modern educational technologies. The most effective are the professionally-oriented foreign language learning, the project work in teaching, the application of information and telecommunication technologies, the work with educational computer programs in foreign languages (multimedia system), the distance technologies in foreign language learning, the use of Internet resources, the foreign language teaching in the computer environment (forums, blogs, e-mail, etc.). Nowadays, the methodology of the use of computer programs is being developed actively getting more used. Computer programs offer ample opportunities to improve the process of foreign language learning, increasing its efficiency. The computer program provides the perception of information through auditory and visual channels, so it also allows you to organize teaching and control the foreign language acquisition in different modes of independent search and at different levels of complexity. Foreign language teaching means are important to ensure the full and effective organization of students' learning in the classroom to master foreign language activities.

LigAdvisor: a versatile and user-friendly web-platform for drug design.

Although several tools facilitating in silico drug design are available, their results are usually difficult to integrate with publicly available information or require further processing to be fully exploited. The rational design of multi-target ligands (polypharmacology) and the repositioning of known drugs towards unmet therapeutic needs (drug repurposing) have raised increasing attention in drug discovery, although they usually require careful planning of tailored drug design strategies. Computational tools and data-driven approaches can help to reveal novel valuable opportunities in these contexts, as they enable to efficiently mine publicly available chemical, biological, clinical, and disease-related data. Based on these premises, we developed LigAdvisor, a data-driven webserver which integrates information reported in DrugBank, Protein Data Bank, UniProt, Clinical Trials and Therapeutic Target Database into an intuitive platform, to facilitate drug discovery tasks as drug repurposing, polypharmacology, target fishing and profiling. As designed, LigAdvisor enables easy integration of similarity estimation results with clinical data, thereby allowing a more efficient exploitation of information in different drug discovery contexts. Users can also develop customizable drug design tasks on their own molecules, by means of ligand- and target-based search modes, and download their results. LigAdvisor is publicly available at https://ligadvisor.unimore.it/.

Interactive Search vs. Automatic Search

This article conducts user evaluation to study the performance difference between interactive and automatic search. Particularly, the study aims to provide empirical insights of how the performance landscape of video search changes, with tens of thousands of concept detectors freely available to exploit for query formulation. We compare three types of search modes: free-to-play (i.e., search from scratch), non-free-to-play (i.e., search by inspecting results provided by automatic search), and automatic search including concept-free and concept-based retrieval paradigms. The study involves a total of 40 participants; each performs interactive search over 15 queries of various difficulty levels using two search modes on the IACC.3 dataset provided by TRECVid organizers. The study suggests that the performance of automatic search is still far behind interactive search. Furthermore, providing users with the result of automatic search for exploration does not show obvious advantage over asking users to search from scratch. The study also analyzes user behavior to reveal insights of how users compose queries, browse results, and discover new query terms for search, which can serve as guideline for future research of both interactive and automatic search.

MiRTargetLink 2.0-interactive miRNA target gene and target pathway networks.

Which genes, gene sets or pathways are regulated by certain miRNAs? Which miRNAs regulate a particular target gene or target pathway in a certain physiological context? Answering such common research questions can be time consuming and labor intensive. Especially for researchers without computational experience, the integration of different data sources, selection of the right parameters and concise visualization can be demanding. A comprehensive analysis should be central to present adequate answers to complex biological questions. With miRTargetLink 2.0, we develop an all-in-one solution for human, mouse and rat miRNA networks. Users input in the unidirectional search mode either a single gene, gene set or gene pathway, alternatively a single miRNA, a set of miRNAs or an miRNA pathway. Moreover, genes and miRNAs can jointly be provided to the tool in the bidirectional search mode. For the selected entities, interaction graphs are generated from different data sources and dynamically presented. Connected application programming interfaces (APIs) to the tailored enrichment tools miEAA and GeneTrail facilitate downstream analysis of pathways and context-annotated categories of network nodes. MiRTargetLink 2.0 is freely accessible at https://www.ccb.uni-saarland.de/mirtargetlink2.