Similarity Properties Research Articles

Synthesis, Characterization and Anti-Inflammatory Study of New Heterocyclic Coumarin Derivatives

The inflammation is one of the most central processes in animal cells defense versus certain injuries orinfections of microbes. The most essential metabolic precursor for many inflammatory pathways is PGH2(prostaglandin), which catalytic synthesis from the AA (arachidonic acid) by COX enzymes. COX can bedivided in to three isomer COX-1 has important role in many physiological function like hemostasis, plateletaggregation, and protection of gastric mucosa, COX-2 when stimulate cause formation of PGE2 excessively,with other prostaglandin then decrease the pain threshold and nerve ending sensitization, which inducepain, increase permeability of vascular and then enhance the inflammatory associated diseases pathway, andCOX-3 has special characteristic, its higher sensitivity to acetaminophen and present in brain. The NSAIDsare therapeutic agents used for the treatment of inflammation, pain, and fever, they work by decreasing theproduction of prostaglandins due to inhibiting the function of the cyclooxygenase (COX) enzyme, we havetwo types nonselective and selective COX-2 inhibitors. In order to design new agents with no or low sideeffect, the COX-2 selectivity should be increased, this achieved by design molecule structurally similar toapproved selective COX-2 inhibitors. The synthetic compound in this study contain three pharmacophores,a nucleus of coumarin and substituted oxazole moiety, separated by a hydrazonoethyl spacer, which havestructural similarity properties to selective COX-2 inhibitors.

Evolution of Chi motifs in Proteobacteria.

Homologous recombination is a key pathway found in nearly all bacterial taxa. The recombination complex not only allows bacteria to repair DNA double-strand breaks but also promotes adaption through the exchange of DNA between cells. In Proteobacteria, this process is mediated by the RecBCD complex, which relies on the recognition of a DNA motif named Chi to initiate recombination. The Chi motif has been characterized in Escherichia coli and analogous sequences have been found in several other species from diverse families, suggesting that this mode of action is widespread across bacteria. However, the sequences of Chi-like motifs are known for only five bacterial species: E. coli, Haemophilus influenzae, Bacillus subtilis, Lactococcus lactis, and Staphylococcus aureus. In this study, we detected putative Chi motifs in a large dataset of Proteobacteria and identified four additional motifs sharing high sequence similarity and similar properties to the Chi motif of E. coli in 85 species of Proteobacteria. Most Chi motifs were detected in Enterobacteriaceae and this motif appears well conserved in this family. However, we did not detect Chi motifs for the majority of Proteobacteria, suggesting that different motifs are used in these species. Altogether these results substantially expand our knowledge on the evolution of Chi motifs and on the recombination process in bacteria.

ГИДРОДИНАМИКА ТИПИЧНЫХ РАЗДАЮЩИХ КОЛЛЕКТОРНЫХ СИСТЕМ ЯЭУ: СОВРЕМЕННЫЕ ПРЕДСТАВЛЕНИЯ И ПЕРСПЕКТИВЫ ИССЛЕДОВАНИЯ

The paper considers the issues of hydrodynamics of typical distribution header systems (DHS) in heat exchangers and reactors of nuclear power plants (NPP). The analysis of hydrodynamic properties of coolant flow in DHS has been carried out. The paper presents typical flow patterns of a coolant in the flow paths of the specified DHS. The classification of different types of DHS is presented. The coolant flow is shown to have a jet nature in a relatively confined and unconfined DHS. Consideration is given to several types of jets and processes of transformation of some types of jets into other types. The paper presents a brief description and formula of the fluid distribution regularity (registered as a scientific discovery) at the outlet from the flat and cylindrical DHS with central and side fluid supply. Consideration is given to the similarity property of hydrodynamics in the flat and cylindrical RHS with different points of fluid supply to the header. Advanced areas of research into revealing hydrodynamic effects in DHS and obtaining additional information on the influence of various factors on the fluid flow in them are proposed.

Forecast of demand for the rmal energy for buildings of secondary educational institutions based on the properties of heteromorphism of their energy systems

THE PURPOSE. Improving the accuracy of forecast calculations of demand for energy resources is an urgent task, especially in the light of the Digital Energy of the Russian Federation program. Prediction is also required for he at supply systems. The complexity of the analysis is the lack of confirmation of the similarity properties of energy systems and complexes for buildings with similar functionality. On the example of buildings of secondary educational institutions located i n the territory of Moscow, the assumption of heteromorphism of thermal systems is proved. METHODS. In the work, an assumption was made that there were no significant changes in the data on the heat consumption of the energy facilities of schools, which was confirmed by the absence of changes in the average annual heat consumption and jumps in the monthly heat consumption diagrams. The amount of heat energy consumption measured and transferred to the IS is influenced by a number of additional factors: accura cy drift of heat energy metering devices; aging and overgrowing of the internal surfaces of the building's heating network equipment; physical aging and deterioration of the building envelope and deterioration of their thermal insulation performance. When compiling predicted energy consumption, this means that it is permissible to use not only statistical data about the analyzed object itself, but also about a variety of objects similar to those analyzed in structure and functionality. RESULTS. A set of input factors is proposed that makes it possible to accurately determine the predicted demand for thermal energy for buildings of secondary educational institutions. The possibility and similar accuracy of the results of forecasting the demand for thermal ene rgy is shown both through the use of multivariate regression analysis and artificial neural networks. CONCLUSION. ЭBased on the combined use of various mathematical approaches, it is proposed to use the methodology for forecasting energy demand by energy complexes and systems as a mechanism for determining the correctness of the transmitted meter readings.

Fine Motor Skills and Unsystematic Spatial Binding in the Common Region Test: Under-Inclusivity in Autism Spectrum Disorder and Over-Inclusivity in Attention-Deficit Hyperactivity Disorder

Introduction:The Common Region Test (CRT) is useful for predicting children’s visual memory as individual object-place binding predicted better object memory while objects-region coding predicted better place memory.Aim:To test children with autism spectrum disorder (ASD) and attention-deficit hyperactivity disorder (ADHD) with regards to spatial binding in the CRT.Methods:19 children with ASD and 20 children with ADHD were gender-matched with 39 typically developing children by chronological age and with another 39 children by verbal mental age as control groups (N = 117) and tested with the CRT and Bender Gestalt test. Results:Children with ASD and ADHD showed more unsystematic coding than typically developing children. This was due to lower fine motor skills, and in children with ADHD also because of reduced verbal naming. Almost all children with ASD presented the less mature under-inclusive Type I unsystematic coding which included object-place binding, while children with ADHD showed the over-inclusive Type II unsystematic coding that was overriding the Gestalt-like properties of proximity and similarity.Conclusions:It was demonstrated that the CRT is a useful screening instrument for ASD and ADHD that shows that their spatial categorization varies in their unsystematic visuo-spatial classification due to fine motor skill deficiencies.

Recovery of image and video based on compressive sensing via tensor approximation and Spatio-temporal correlation

In recent years, block-based compressive sensing (BCS) has been extensively studied because it can reduce computational complexity and data storage by dividing the image into smaller patches, but the performance of the reconstruction algorithm is not satisfactory. In this paper, a new reconstruction model for image and video is proposed. The model makes full use of spatio-temporal correlation and utilizes low-rank tensor approximation to improve the quality of the reconstructed image and video. For image recovery, the proposed model obtains a low-rank approximation of a tensor formed by non-local similar patches, and improves the reconstruction quality from a spatial perspective by combining non-local similarity and low-rank property. For video recovery, the reconstruction process is divided into two phases. In the first phase, each frame of the video sequence is regarded as an independent image to be reconstructed by taking advantage of spatial property. The second phase performs tensor approximation through searching similar patches within frames near the target frame, to achieve reconstruction by putting the spatio-temporal correlation into full play. The resulting model is solved by an efficient Alternating Direction Method of Multipliers (ADMM) algorithm. A series of experiments show that the quality of the proposed model is comparable to the current state-of-the-art recovery methods.

Quantitative similarity assessment of construction projects using WBS-based metrics

Lessons learned from completed projects are valuable resources for planning of new projects. A quantitative similarity measurement between construction projects can improve knowledge reuse practices. The information and documents of a similar past project can be retrieved to resolve the challenges in a new project. This paper introduces a novel method for measuring the similarity of construction projects based on semantic comparison of their work breakdown structure (WBS). WBS of a project should theoretically encompass a hierarchical decomposition of the total scope of project’s works, thus it could be used as an appropriate representative of the projects. The proposed method measures the semantic similarity between WBS of projects by means of natural language processing techniques. This method was implemented based on three metrics: node, structural, and total similarity. Each of these metrics calculate a quantitative similarity score between 0 and 1. The method was assessed using fifteen test samples with promising results in compliance with similarity properties. In addition, precision and recall of the method were evaluated in retrieving similar past projects. The results illustrate that the structural similarity slightly outperforms the other metrics.

Strong solution for Korteweg system in bmo−1(RN) with initial density in L∞

In this paper we investigate the question of the existence of strong solution in finite time for the Korteweg system for small initial data provided that the initial momentum ρ 0 u 0 belongs to bmo −1 T (R N) for T > 0 and the initial density ρ 0 is in L ∞ (R N) with N ≥ 1 and far away from the vacuum. This result extends the so called Koch-Tataru theorem for the Korteweg system. It is also interesting to observe that any initial shock on the density is instantaneously regularized inasmuch as the density becomes Lipschitz for any ρ(t, ·) with t > 0. We also prove the existence of global strong solution for initial data (ρ 0 − 1, ρ 0 u 0) ∈ (B N 2 −1 2,∞ (R N) ∩ B N 2 2,∞ (R N)∩L ∞ (R N))×(B N 2 −1 2,∞ (R N)) N. This result allows in particular to extend the notion of Oseen solution (corresponding to particular solution of the incompressible Navier Stokes system in dimension N = 2) to the Korteweg system provided that the vorticity of the momentum ρ 0 u 0 is a Dirac mass αδ 0 with α sufficiently small. IHowever unlike the Navier Stokes equations the property of self similarity is not conserved for the Korteweg system since there is no invariance by scaling because the term of pressure.

Bi-parametric distance and similarity measures of picture fuzzy sets and their applications in medical diagnosis

The concept of picture fuzzy sets (PFS) is a generalization of ordinary fuzzy sets and intuitionistic fuzzy sets, which is characterized by positive membership, neutral membership, and negative membership functions. Keeping in mind the importance of similarity measures and applications in data mining, medical diagnosis, decision making, and pattern recognition, several studies have been proposed in the literature. Some of those, however, cannot satisfy the axioms of similarity and provide counter-intuitive cases. In this paper, we propose new similarity measures for PFSs based on two parameters t and p, where t identifies the level of uncertainty and p is the Lp norm. The properties of the bi-parametric similarity and distance measures are discussed. We provide some counterexamples for existing similarity measures in the literature and show how our proposed similarity measure is important and applicable to the pattern recognition problems. In the end, we provide an application of a proposed similarity measure for medical diagnosis.

Rigidity of similarity-based formation and formation shape stabilization

In this paper, a novel formation, i.e., similarity-based formation, is proposed and its rigidity is explored. Based on the concept of geometric similarity, the definition of similarity-based formation is given. As the inherent property of geometric similarity, the proposed formation has the adaptability of similarity transformations, including translation, rotation and scaling, which provides great flexibility of formation control. To describe the expected formation shape mathematically, three different approaches with two different geometric variables are proposed, and the corresponding conditions of uniquely determining the formation shape are derived. The distributed formation control laws with different kinds of similarity constraints are designed to make the formation locally converge to the desired formation shape with desired orientation and scale. Simulations demonstrate the validity of the approaches of defining similarity-based formation and the effectiveness of formation control laws.

Dampak Perkuliahan Geometri Pada Penalaran Deduktif Mahasiswa: Kasus Pembelajaran Teorema Ceva

Geometry is one of branches of mathematics that can develop deductive thinking ability for anyone, including students of prospective mathematics teachers, who learning it. This deductive thinking ability is needed by prospective mathematics teachers for their future careers as mathematics educators. This research therefore aims to investigate the influence of the learning process of a geometry course toward deductive reasoning ability of students of prospective mathematics teachers. To do so, this qualitative research was carried out through an observation of the learning process and assessment of the geometry course, involving 56 students of prospective mathematics teachers, in one of mathematics education program, in one of state universities in Bandung. A geometry topic observed in the learning process was the Ceva’s theorem, and the assessment was in the form of an individual written test on the application of the Ceva’s theorem in a proving process. The results showed that the learning process emphasizes on proving of theorems and mathematical statements. In addition, the test revealed that ten students are able to use the Ceva’s theorem in a proving process and different strategies of proving are found, including the use of properties of similarity between triangles and of the concept of trigonometry. This indicates a creativity of student deductive thinking in proving process. In conclusion, the geometry course that emphasizes on proving of theorems and mathematical statements has influenced on filexibility of student deductive thinking in proving processes.

On the Approximation of the Resource Equivalences in Petri Nets with the Invisible Transitions

Two resources (submarkings) are called similar if in any marking any one of them can be replaced by another one without affecting the observable behavior of the net (regarding marking bisimulation). It is known that resource similarity is undecidable for general labelled Petri nets. In this paper we study the properties of the resource similarity and resource bisimulation (a subset of complete similarity relation closed under transition firing) in Petri nets with invisible transitions (where some transitions may be labelled with an invisible label (τ) that makes their firings unobservable for an external observer). It is shown that for a proper subclass (p-saturated nets) the resource bisimlation can be effectively checked. For a general class of Petri net with invisible transitions it is possible to construct a sequence of so-called (n, m)-equivalences approximating the largest τ-bisimulation of resources.

Local and nonlocal constraints for compressed sensing video and multi-view image recovery

In compressed sensing (CS) signal recovery tasks, employing prior constraints to exploit the inherent properties in the signal is critical to the recovery performance. Recently, multiple constraints were employed to improve the reconstruction for video sequence and multi-view image CS reconstruction since they can exploit intra- and inter-image properties simultaneously. However, correlation and dependencies among constraints were not taken into account in existing methods. This drawback prevents the multi-constraint technique from improving the reconstruction performance further. In this paper, we propose to employ local and nonlocal constraints in the CS recovery model to reconstruct video sequences and multi-view images. In the proposed CS recovery model, a pixel-wise total variation constraint is utilized to exploit the spatial local piecewise smoothness in the image. Meanwhile, a patch-based low-rank constraint is applied for the nonlocal inter-image similarity property. These two types of constraints are proposed to be applied in different dimensions with different granularities so as to alleviate the dependency and correlation between the constraints and exploit the intra- and inter-image features in images sufficiently. Besides, an efficient augmented Lagrange multipliers and alternating direction method is presented to solve the proposed local and nonlocal constraint-based CS recovery model (LNLC-CS). Experiments on test video sequences and multi-view images at various sampling rates have demonstrated the great advantages of applying independent constraints in different granularities and dimensions. The proposed method can outperform the existing state-of-the-art CS recovery approaches a lot in both the objective and the subjective quality of the recovered image. Experiments also show the proposed method has made a remarkable improvement over other competing constraint-based methods in the convergence speed and reconstruction time.

Turnpike Properties in Discrete-Time Mixed-Integer Optimal Control

This note discusses properties of parametric discrete-time Mixed-Integer Optimal Control Problems (MIOCPs) as they often arise in model predictive control with discrete controls. We argue that, in want for a handle on similarity properties of parametric MIOCPs, the turnpike phenomenon known in optimal control is helpful. We provide sufficient turnpike conditions based on a dissipativity notion of MIOCPs, and we prove that the turnpike phenomenon allows specific and accurate guesses for the discrete controls. We also derive an easily checkable sufficient condition for dissipativity of linear-quadratic MIOCPs. Moreover, we show how the turnpike property can be used to derive efficient node-weighted branch-and-bound schemes tailored to parametric MIOCPs. We draw upon numerical examples to illustrate our findings.

Borderline Disorder: (De facto) Historical Ethnic Borders and Contemporary Conflict in Africa

We explore the effect of historical ethnic borders on contemporary non-civil conflict in Africa. Exploiting variations across artificial regions (i.e., grids of 50x50km) within an ethnicity's historical homeland, we document that both the intensive and extensive margins of contemporary conflict are concentrated close to historical ethnic borders. Following a theory-based instrumental variable approach, which generates a plausibly exogenous ethno-spatial partition of Africa, we find that grid cells with historical ethnic borders have 27 percentage points higher probability of conflict and 7.9 percentage points higher probability of being the initial location of a conflict. We uncover several key underlying mechanisms: competition for agricultural land, population pressure, cultural similarity and weak property rights.

Magneto-optical properties of Fibonacci graphene superlattices

We have studied the transition strength and magneto-optical absorption in Fibonacci graphene superlattices under the effects of perpendicularly applied magnetic field. It is shown that the former quantity present self-similarity and anti-self-similarity behavior at magnetic field strengths connected via τ4 and τ2, respectively, τ being the golden mean. In order to be able to observe this effect, it is necessary that for a particular field the transition strength curve is displaced laterally as a rigid body so that the adjustment is achieved with that corresponding to the other field. It was found that this shifting is determined by the symmetry and scaling properties of the Fibonacci structure. For all the magnetic fields and polarizations of the incident radiation considered here, it is observed that the absorption spectra have the characteristic of self-similarity and also that they show resonant peak structures that satisfy selection rules that keep, in very good approximation, the same characteristics of graphene monolayers. We showed analytically that the similarity properties of both the transition strength and optical absorption are a direct consequence of those of the magnetic subbands.

Measures of Similarity

AbstractThis article analyses the relationship between the concept of single aspect similarity and proposed measures of similarity. More precisely, it compares eleven measures of similarity in terms of how well they satisfy a list of desiderata, chosen to capture common intuitions concerning the properties of similarity and the relations between similarity and dissimilarity. Three types of measures are discussed: similarity as commonality, similarity as a function of dissimilarity, and similarity as a joint function of commonality and difference. Relative to the desiderata, it is found that a measure of the second type fares the best. However, rather than recommend this measure alone as a measure of similarity, it is suggested that there are at least three separate concepts of single aspect similarity, corresponding to the three types of measures. In light of this proposal, three of the eleven measures (and variants of these) are deemed acceptable.

Regression analysis and statistical examination of Knoop Hardness on abrasion resistance in Lyca Beige Marbles

Marbles are secondary decomposition products formed by metamorphism of limestone. Effective classification of marble quarries in terms of quality enables the selection of a sustainable production method and safety application. This evaluation is based on physico-mechanical properties of the samples. Obtained results of physico-mechanical properties of the marbles were statistically analyzed using Stata 14 and SPSS 21 software. The marbles indicated mostly normal physical and mechanical properties. A strong inverse relationship exists between Abrasion Value and Knoop Hardness Determination that indicates a significant nonlinear relationship. Samples were distinguished into 3 groups of close similarity and related properties. The estimated value of the parameters is in the 95 % confidence interval. The equation obtained by regression analysis was used for the determination of resistance to abrasion.

Online Signature Verification Based on a Single Template via Elastic Curve Matching.

Person verification using online handwritten signatures is one of the most widely researched behavior-biometrics. Many signature verification systems typically require five, ten, or even more signatures for an enrolled user to provide an accurate verification of the claimed identity. To mitigate this drawback, this paper proposes a new elastic curve matching using only one reference signature, which we have named the curve similarity model (CSM). In the CSM, we give a new definition of curve similarity and its calculation method. We use evolutionary computation (EC) to search for the optimal matching between two curves under different similarity transformations, so as to obtain the similarity distance between two curves. Referring to the geometric similarity property, curve similarity can realize translation, stretching and rotation transformation between curves, thus adapting to the inconsistency of signature size, position and rotation angle in signature curves. In the matching process of signature curves, we design a sectional optimal matching algorithm. On this basis, for each section, we develop a new consistent and discriminative fusion feature extraction for identifying the similarity of signature curves. The experimental results show that our system achieves the same performance with five samples assessed with multiple state-of-the-art automatic signature verifiers and multiple datasets. Furthermore, it suggests that our system, with a single reference signature, is capable of achieving a similar performance to other systems with up to five signatures trained.

BIA: Behavior Identification Algorithm Using Unsupervised Learning Based on Sensor Data for Home Elderly.

Behavior identification plays an important role in supporting homecare for the elderly living alone. In literature, plenty of algorithms have been designed to identify behaviors of the elderly by learning features or extracting patterns from sensor data. However, most of them adopted probabilistic models or supervised learning to identify behaviors based on labeled sensor data. This paper proposes a behavior identification algorithm (BIA) using unsupervised learning based on unlabeled sensor data for the elderly living alone in smart home. This paper presents the observation of elder behaviors with three features: Event Order, Time Length Similarity and Time Interval Similarity features. Based on these features of behavior observations, two properties of behaviors, including the Event Shift and Histogram Shape Similarity properties, are presented. According to these properties, the proposed BIA is developed. Finally, performance results show that the proposed BIA outperforms the existing unsupervised machine learning mechanisms in terms of the behavior identification precision and recall.