Exact Similarity Research Articles

A graph similarity measurement algorithm combining global and local fine-grained features

Graph Similarity Computation (GSC) is not only a basic operation of graph similarity search, but also plays an important role in many application fields, including drug design, program analysis and social group identification. Since calculating the exact distance or similarity between two graphs is usually an NP-hard problem, the tradeoff between precision and speed needs to be addressed. In this paper, a pooling-based graph neural network method is proposed, which effectively integrates the coarse-grained interaction features of the two graph data and the fine -grained interaction features of the nodes between the subgraphs, and further reduce the computational cost while ensuring the accuracy. The experimental results show that the proposed method has good performance on real graph data sets. Compared with previous methods, the proposed method not only improves the accuracy but also improves the computational efficiency.

Decellularized Antler Cancellous Bone Matrix Material Can Serve as Potential Bone Tissue Scaffold.

Due to the limited supply of autologous bone grafts, there is a need to develop more bone matrix materials to repair bone defects. Xenograft bone is expected to be used for clinical treatment due to its exact structural similarity to natural bone and its high biocompatibility. In this study, decellularized antler cancellous bone matrix (DACB) was first prepared, and then the extent of decellularization of DACB was verified by histological staining, which demonstrated that it retained the extracellular matrix (ECM). The bioactivity of DACB was assessed using C3H10T1/2 cells, revealing that DACB enhanced cell proliferation and facilitated cell adhesion and osteogenic differentiation. When evaluated by implanting DACB into nude mice, there were no signs of necrosis or inflammation in the epidermal tissues. The bone repair effect of DACB was verified in vivo using sika deer during the antler growth period as an animal model, and the molecular mechanisms of bone repair were further evaluated by transcriptomic analysis of the regenerated tissues. Our findings suggest that the low immunogenicity of DACB enhances the production of bone extracellular matrix components, leading to effective osseointegration between bone and DACB. This study provides a new reference for solving bone defects.

DIDS: Double Indices and Double Summarizations for Fast Similarity Search

Data series has been one of the significant data forms in various applications. It becomes imperative to devise a data series index that supports both approximate and exact similarity searches for large data series collections in high-dimensional metric spaces. The state-of-the-art works employ summarizations and indices to reduce the accesses to the data series. However, we discover two significant flaws that severely limit performance enhancement. Firstly, the state-of-the-art works often employ segment-based summarizations, whose lower bound distances decrease significantly when representing a data series collection, resulting in numerous invalid accesses. Secondly, the disk-based indices for the exact search mainly rely on tree-based indices, which results in low-quality approximate answers, consequently impacting the exact search. To address these problems, we propose a novel solution, Double Indices and Double Summarizations (DIDS). Besides segment-based summarizations, DIDS introduces reference-point-based summarizations to improve the pruning rate by the sorted-based representation strategy. Moreover, DIDS employs reference points and a cost model to cluster similar data series, and uses a graph-based approach to interconnect various regions, enhancing approximate search capabilities. We conduct experiments on extensive datasets, validating the superior search performance of DIDS.

Time-Aware Dual LSTM Neural Network with Similarity Graph Learning for Remote Sensing Service Recommendation.

Technological progress has led to significant advancements in Earth observation and satellite systems. However, some services associated with remote sensing face issues related to timeliness and relevance, which affect the application of remote sensing resources in various fields and disciplines. The challenge now is to help end-users make precise decisions and recommendations for relevant resources that meet the demands of their specific domains from the vast array of remote sensing resources available. In this study, we propose a remote sensing resource service recommendation model that incorporates a time-aware dual LSTM neural network with similarity graph learning. We further use the stream push technology to enhance the model. We first construct interaction history behavior sequences based on users' resource search history. Then, we establish a category similarity relationship graph structure based on the cosine similarity matrix between remote sensing resource categories. Next, we use LSTM to represent historical sequences and Graph Convolutional Networks (GCN) to represent graph structures. We construct similarity relationship sequences by combining historical sequences to explore exact similarity relationships using LSTM. We embed user IDs to model users' unique characteristics. By implementing three modeling approaches, we can achieve precise recommendations for remote sensing services. Finally, we conduct experiments to evaluate our methods using three datasets, and the experimental results show that our method outperforms the state-of-the-art algorithms.

Kogan Scale – Attitudes toward old people: tradução, adaptação transcultural e validação no Brasil

Abstract Objective To present the translation, cross-cultural adaptation and validation of the Kogan’s Attitude towards Older People Scale (KAOP) into Portuguese in Brazil. Methods Methodological research into the translation, cross-cultural adaptation and validation of the Kogan scale on attitudes towards the older adult. Following international recommendations, the scale was translated by three native Brazilians and then a single version was drawn up by consensus considering semantic and cultural equivalences; it was back-translated and evaluated by a native British consultant for similarity analysis. The final version was applied to thirty students regularly enrolled in undergraduate courses as a pre-test. To validate the instrument, a cross-sectional study was carried out with 904 undergraduate students, including health courses, and the Cronbach’s alpha index was obtained. Results In 47% (16) of the items there were exact similarities between the translations and in 53% (18) the similarities prevailed in terms of content, with few semantic differences. In relation to the pre-test, the majority of students were aged up to 25 (60%), female (76.6%) and single (70%), reporting adequate understanding of the Portuguese version, with no need for changes. The scale’s internal consistency (Cronbach’s alpha) was 0.70. Conclusion The process of translating, cross-culturally adapting and validating the Kogan scale from English into Brazilian Portuguese carefully followed the steps recommended in the literature. The resulting instrument was evaluated as comprehensible and with good internal consistency.

Scalable neighbour search and alignment with uvaia.

Despite millions of SARS-CoV-2 genomes being sequenced and shared globally, manipulating such data sets is still challenging, especially selecting sequences for focused phylogenetic analysis. We present a novel method, uvaia, which is based on partial and exact sequence similarity for quickly extracting database sequences similar to query sequences of interest. Many SARS-CoV-2 phylogenetic analyses rely on very low numbers of ambiguous sites as a measure of quality since ambiguous sites do not contribute to single nucleotide polymorphism (SNP) differences. Uvaia overcomes this limitation by using measures of sequence similarity which consider partially ambiguous sites, allowing for more ambiguous sequences to be included in the analysis if needed. Such fine-grained definition of similarity allows not only for better phylogenetic analyses, but could also lead to improved classification and biogeographical inferences. Uvaia works natively with compressed files, can use multiple cores and efficiently utilises memory, being able to analyse large data sets on a standard desktop.

DForest: A Minimal Dimensionality-Aware Indexing for High-Dimensional Exact Similarity Search

DForest: A Minimal Dimensionality-Aware Indexing for High-Dimensional Exact Similarity Search

A graph theory based similarity metric enables comparison of subpopulation psychometric networks.

Network psychometrics leverages pairwise Markov random fields to depict conditional dependencies among a set of psychological variables as undirected edge-weighted graphs. Researchers often intend to compare such psychometric networks across subpopulations, and recent methodological advances provide invariance tests of differences in subpopulation networks. What remains missing, though, is an analogue to an effect size measure that quantifies differences in psychometric networks. We address this gap by complementing recent advances for investigating whether psychometric networks differ with an intuitive similarity measure quantifying the extent to which networks differ. To this end, we build on graph-theoretic approaches and propose a similarity measure based on the Frobenius norm of differences in psychometric networks' weighted adjacency matrices. To assess this measure's utility for quantifying differences between psychometric networks, we study how it captures differences in subpopulation network models implied by both latent variable models and Gaussian graphical models. We show that a wide array of network differences translates intuitively into the proposed measure, while the same does not hold true for customary correlation-based comparisons. In a simulation study on finite-sample behavior, we show that the proposed measure yields trustworthy results when population networks differ and sample sizes are sufficiently large, but fails to identify exact similarity when population networks are the same. From these results, we derive a strong recommendation to only use the measure as a complement to a significant test for network similarity. We illustrate potential insights from quantifying psychometric network similarities through cross-country comparisons of human values networks. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

A molecular networking-assisted automatic database screening strategy for comprehensive annotation of small molecules in complex matrices

Liquid chromatography-tandem with high-resolution mass spectrometry (LCHRMS) has proven challenging for annotating multiple small molecules within complex matrices due to the complexities of chemical structure and raw LCHRMS data, as well as limitations in previous literatures and reference spectra related to those molecules. In this study, we developed a molecular networking assisted automatic database screening (MN/auto-DBS) strategy to examine the combined effect of MS1 exact mass screening and MS2 similarity analysis. We compiled all previously reported compounds from the relevant literatures. With the development of a Python software, the in-house database (DB) was created by automatically calculating the m/z and data from experimental MS1 hits were rapid screened with DB. We then performed a feature-based molecular network analysis on the auto-MS2 data for supplementary identification of unreported compounds, including clustered FBMN and annotated GNPS compounds. Finally, the results from both strategies were merged and manually curated for correct structural assignment. To demonstrate the applicability of MN/auto-DBS, we selected the Huangqi-Danshen herb pair (HD), commonly used in prescriptions or patent medicines to treat diabetic nephropathy and cerebrovascular disease. A total of 223 compounds were annotated, including 65 molecules not previously reported in HD, such as aromatic polyketides, coumarins, and diarylheptanoids. Using MN/auto-DBS, we can profile and mine a wide range of complex matrices for potentially new compounds.

Hiemenz flow for a micropolar nanofluid with bidirectional flexible surface and heat transfer

The steady Hiemenz stagnation-point flow of a flexible membrane moving bidirectionally, for a micropolar copper–water nanofluid model is studied. The flow field is a unison of wall transpiration, velocity slip and stagnation-point flow for a 2D case, generating unique or dual form of exact similarity solutions. The results reveal that a unique solution exists for the stretching sheet, depending entirely on a given set of parameters, while two solutions fall within the physically recognizable region for the case of a shrinking sheet. A set of new exact solutions characterized by the stretching/shrinking strength parameter d are also found with d considering different values. It is found that the numerical integration for skin friction, couple stress friction and temperature gradient leads to twofold solutions.

POLA KOMUNIKASI PENYELESAIAN KONFLIK PENDIRIAN GEREJA YASMIN BOGOR

Conflict is a social phenomenon that is present in social life, so that conflict is inherently means conflict will always exist in every space and time, anywhere and anytime. In this view, society is an arena of conflict or an arena of conflict and integration that is always going on. Therefore, conflict and social integration is a symptom that always fill every social life. Things that encourage the emergence of conflict and integration is the existence of similarities and differences of social interests . In every social life there is not a single human having the exact similarity, whether of ethnicity, interests, will, will, purpose and so on. From each conflict there are some that can be resolved, but some can not be resolved resulting in some acts of violence. Violence is a symptom that can not overcome the root of the conflict, causing violence from the smallest model of violence to war. Good communication is needed in problem solving and is important in achieving the success of a life in the community.Conflicts can be resolved well if communication is harmoniously established between the community, both verbal and non verbal. Effective communication patterns are one of the most important conditions in relation to resolving conflicts among conflict resolution societies that arise in marriage life especially in different national marriages, the subject of education because women and men are distinctly different in terms of communication. This is what then makes researchers want to know more deeply about how the picture polakomunikasi in conflict resolution Keywords: Patterns, Communication, and Conflict.

Embracing ambiguity: Improving similarity-oriented tasks with contextual synonym knowledge

Contextual synonym knowledge is crucial for those similarity-oriented tasks whose core challenge lies in capturing semantic similarity between entities in their contexts, such as entity linking and entity matching. However, most Pre-trained Language Models (PLMs) lack synonym knowledge due to inherent limitations of their pre-training objectives such as masked language modeling (MLM). Existing works which inject synonym knowledge into PLMs often suffer from two severe problems: (i) Neglecting the ambiguity of synonyms, and (ii) Undermining semantic understanding of original PLMs, which is caused by inconsistency between the exact semantic similarity of the synonyms and the broad conceptual relevance learned from the original corpus. To address these issues, we propose PICSO, a flexible framework that supports the injection of contextual synonym knowledge from multiple domains into PLMs via a novel entity-aware Adapter which focuses on the semantics of the entities (synonyms) in the contexts. Meanwhile, PICSO stores the synonym knowledge in additional parameters of the Adapter structure, which prevents it from corrupting the semantic understanding of the original PLM. Extensive experiments demonstrate that PICSO can dramatically outperform the original PLMs and the other knowledge and synonym injection models on four different similarity-oriented tasks. In addition, experiments on GLUE prove that PICSO also benefits general natural language understanding tasks. Codes and data will be public.

Numerical approximations for fluid flow and heat transfer in the boundary layer with radiation through multiple Lie similarity transformations

The dependent or independent variables of differential equations may be reduced by applying its associated Lie point symmetries. Seven-dimensional Lie point symmetry algebra exists for differential equations representing heat transfer in a boundary layer flow in the presence of radiation. The linear combinations of these seven Lie symmetries are used first to deduce the invariants and then derive the Lie similarity transformations for the original set of partial differential equations (PDEs). This procedure is repeated for the set of transformed equations to further reduce the system of PDEs into the system of ordinary differential equations (ODEs). Multiple exact similarity transformations are obtained using this procedure. All these transformations map the system of three PDEs with three independent variables of flow and heat transfer under the specified set of conditions into two-dimensional systems of equations with only one independent variable, the system of ODEs. Approximate solutions for these reduced systems are established using the finite difference method to illustrate the effects of unsteadiness, Prandtl number, and radiation on the boundary layer thickness, flow, and heat transfer. This type of study was conducted under the effect of these parameters previously with a different set of similarity transformations. However, the Lie similarity transformations deduced in this work, which have not been employed, lead to different types of reduced systems of ODEs, thereby providing different velocities and temperature profiles and providing valid solutions for previously unexplored regions for unsteadiness in the fluid flow and heat transfer. Some of these transformations and their resulting systems provide results that contradict the flow and heat transfer in real fluids.

The complete plastid genome and characteristics analysis of Achillea millefolium.

Achillea is a crop with Chinese herbal characteristics and horticultural values. Its leaves and flowers contain aromatic oil, and the ripe herb can also be used as medicine to induce sweat and relieve rheumatic pains. It is seen cultivated in gardens all over China. Currently, the most comprehensive chloroplast genome sample involved in the study refers to New World clades of Achillea, which are used for marker selection and phylogenetic research. We completely sequenced the chloroplast genomes of Achillea millefolium. These sequencing results showed that the plastid genome is 149,078 bp in size and possesses a typical quadripartite structure containing one large single copy (LSC) with 82,352 bp, one small single copy (SSC) with 18,426 bp, and a pair of inverted repeat (IR) regions with 24,150 bp in Achillea millefolium. The chloroplast genome encodes a common number of genes, of which 88 are protein-coding genes, 37 transfer ribonucleic acid genes, and 8 ribosomal ribonucleic acid genes, which are highly similar in overall size, genome structure, gene content, and sequence. The exact similarity was observed when compared to other Asteraceae species. However, there were structural differences due to the restriction or extension of the inverted repeat (IR) regions-the palindromic repeats being the most prevalent form. Based on 12 whole-plastomes, 3 hypervariable regions (rpoB, rbcL, and petL-trnP-UGG) were discovered, which could be used as potential molecular markers.

Dumpy: A Compact and Adaptive Index for Large Data Series Collections

Data series indexes are necessary for managing and analyzing the increasing amounts of data series collections that are nowadays available. These indexes support both exact and approximate similarity search, with approximate search providing high-quality results within milliseconds, which makes it very attractive for certain modern applications. Reducing the pre-processing (i.e., index building) time and improving the accuracy of search results are two major challenges. DSTree and the iSAX index family are state-of-the-art solutions for this problem. However, DSTree suffers from long index building times, while iSAX suffers from low search accuracy. In this paper, we identify two problems of the iSAX index family that adversely affect the overall performance. First, we observe the presence of a proximity-compactness trade-off related to the index structure design (i.e., the node fanout degree), significantly limiting the efficiency and accuracy of the resulting index. Second, a skewed data distribution will negatively affect the performance of iSAX. To overcome these problems, we propose Dumpy, an index that employs a novel multi-ary data structure with an adaptive node splitting algorithm and an efficient building workflow. Furthermore, we devise Dumpy-Fuzzy as a variant of Dumpy which further improves search accuracy by proper duplication of series. Experiments with a variety of large, real datasets demonstrate that the Dumpy solutions achieve considerably better efficiency, scalability and search accuracy than its competitors.

Boundary layer formations over a stretchable heated cylinder in a viscoelastic fluid with partial slip and viscous dissipation effects

An exact similarity solution is worked out for fluid motion in the vicinity of a cylindrical surface in an electrically conducting viscoelastic fluid obeying the Jeffrey model. Cylindrical surface expands axially with linear velocity and has a prescribed surface temperature. The present analysis focuses on the partial slip assumption which gives rise to a nonlinear case Robin-type (mixed) boundary condition in axial velocity. In contrast to a previously published study (J. Mech., vol 31, pp. 69–78, 2015) which only reported local similarity solutions in no-slip case, the present work provides an exact similarity analysis by defining a quadratic surface temperature. The effects of the magnetic field and Joule heating on the momentum and thermal transport phenomena are also scrutinized. A numerical routine is used to solve the equation accurately for a wide range of fluid parameters, including ranges that could not be handled by previous approximate analytical methods that were limited to the no-slip limit. The influences of viscoelasticity and partial slip on the flow behavior are investigated, and the coefficient of skin friction for a Jeffrey fluid is calculated. Obtained results are consistent with the previously published works under special situations. The case of flat surface, which can be obtained as a limiting case of the model, is not even explored in the past.

Thermo-solutal migrating heat producing and radiative Casson nanofluid flow via bidirectional stretching surface in the presence of bilateral reactions

A two-phase nanofluid model flowing through a bidirectional stretching sheet by imposing novel bilateral reactions was developed. Further convective heat and mass conditions at the boundary are imposed. We analyzed all possible situations, which give the exact similarities, and the system of partial differential equations and boundary conditions are exactly transformed into ordinary differential equations on the basis of similarity variables. The transmuted ordinary differential equations are then solved via the implementation of the finite difference method algorithm embedded in MATLAB software. The graphical profiles were exhibited to investigate the impact of physical parameters as well as engineering quantities near the surface given the important physical stream features. The results reveal that the velocity of nanofluid improves with a stronger stretching parameter and reduces with Casson parameter toward horizontal velocity in the x and y directions. Skin friction coefficients dwindle with increasing Casson parameter values for the specified magnetic parameter values. Sherwood number depletes by growing values of activation energy. Furthermore, the present simulations are completely matched with previously published work for appropriate choices of parameters.

Analysis of unsteady thin film flows over the porous and moving surfaces of variable thickness: Unsteady and non-linear kinematics of sheet

Thin film flows over porous and moving sheets of variable thickness have been reconsidered here. New and multiple dimensions of classical problems of such type flow are analyzed. Here, we categorically emphasized on the nature and kinds of injection (suction) and moving velocities of the sheet, whereas, variable size of the sheet is also taken into account. We formed and investigated different cases and checked different options for kinematics of sheet, variable sizes of thin film and that of sheet. All possible cases of exact similarities are noticed by which the system of partial differential equations and boundary conditions are exactly transformed into ordinary differential equations. The final systems of exact equations are solved by bvp4c technique. The present simulations are exactly matched with the previously published analyses for special choices of functions and parameters. Strict behavioral changes have been observed in the velocity profiles by changing the nature of sheet’s kinematics.

Uncertainty-based decision support system for gaming applications

A dynamic world has different uncertainties. These uncertainties always impact adversely while making decisions. Existing systems sometimes fail as they are trained without considering uncertainty inclusion due to the dynamic nature of the problem. This is quite observed in gaming, which is most dynamic and contributes adversely while deciding for the next move. Strategic games have fewer uncertainties rather than ground sports. Many types of factors add uncertainty to the system. There is a need of handling the required uncertainty which will help in making the decision. Also while finding similarities between games or matches, player and playing style results don’t depict exact similarities between them. There is a need to measure uncertainty-based similarities as it helps in deciding the situation of the game or player. Here Uncertainty based decision support system is proposed which takes uncertainty as input rather than only considering patterns of input. Patterns always help if the system is more static while considering a dynamic system where we need to consider patterns and uncertainties in the scenarios. Results are shown on limited types of moves in game data and how uncertainty-based similarity and next move selection are improved.

«Философия» в культуре исторической Индии: систематизация источников В.К. Шохин

The author enters an already old dispute, that is whether a countеrepart of the no­tion of philosophy could be encountered in the traditional India, upholds the view that the term ānvīkşikī (lit. “investigation”) was nearest to it and traces its meaning along the texts on dharma (from the Gautama-dharmasûtra, i.e. the 2nd century B.C., to the later medieval commentaries on the Mānavadharmaśāstra), politics (the Arthaśāstra and Kamandaki’s Nītisāra), poetics (Rājaśekhara’s Kāvyamīmāňsā) and philosophy properly (the basic commentary and subcom­mentary on the Nyāya-sûtras by Vātsyāyana and Uddyotakara, i.e. from the 5th to 7th centuries A.D.). Two main avenues to the understanding of philosophy’s vocations in India have been paved in the Mānavadharmaśāstra, along with commentaries thereon and by Kamandaki (as the knowledge of Ātman) and in the Arthaśāstra and the texts of the Nyāya school (as a metascience helping the other branches of knowledge bear their fruits). Therefore philosophy in India as well was regarded as the duality of ideological and methodological con­stituents, and it was Vātsyāyana who in all clarity pointed out that his science of Nyāya was not “the mere knowledge of Ātman” in the manner of the Upanişads but the same knowledge as realized in the context of professional investigation of 16 categorial topics. It is the significance of ānvīkşikī as examination of con­cepts with the philosophers of Nyāya and as polemical debate with Rājaśekhara that leads one to conclude that in classical India philosophy has been regarded not as a body of doctrines but as analytical practice (with the exact similarities to Wittgensteins’s understanding of it) as realized in controversy and that unfolds very meaningful horizons for comparative philosophy