Multidimensional Scaling Method Research Articles

Nonlinear Reduced Order Modelling for Korteweg-de Vries Equation

Efficient computational techniques that maintain the accuracy and invariant preservation property of the Korteweg-de Vries (KdV) equations have been studied by a wide range of researchers. In this paper, we introduce a reduced order model technique utilizing kernel principle component analysis (KPCA), a nonlinear version of the classical principle component analysis, in a non-intrusive way. The KPCA is applied to the data matrix, which is formed by the discrete solution vectors of KdV equation. In order to obtain the discrete solutions, the finite differences are used for spatial discretization, and linearly implicit Kahan's method for the temporal one. The back-mapping from the reduced dimensional space, is handled by a non-iterative formula based on the idea of multidimensional scaling (MDS) method. Through KPCA, we illustrate that the reduced order approximations conserve the invariants, i.e., Hamiltonian, momentum and mass structure of the KdV equation. The accuracy of reduced solutions, conservation of invariants, and computational speed enhancements facilitated by classical (linear) PCA and KPCA are exemplified through one-dimensional KdV equation.

Multi-Input data ASsembly for joint Analysis (MIASA): A framework for the joint analysis of disjoint sets of variables.

The joint analysis of two datasets [Formula: see text] and [Formula: see text] that describe the same phenomena (e.g. the cellular state), but measure disjoint sets of variables (e.g. mRNA vs. protein levels) is currently challenging. Traditional methods typically analyze single interaction patterns such as variance or covariance. However, problem-tailored external knowledge may contain multiple different information about the interaction between the measured variables. We introduce MIASA, a holistic framework for the joint analysis of multiple different variables. It consists of assembling multiple different information such as similarity vs. association, expressed in terms of interaction-scores or distances, for subsequent clustering/classification. In addition, our framework includes a novel qualitative Euclidean embedding method (qEE-Transition) which enables using Euclidean-distance/vector-based clustering/classification methods on datasets that have a non-Euclidean-based interaction structure. As an alternative to conventional optimization-based multidimensional scaling methods which are prone to uncertainties, our qEE-Transition generates a new vector representation for each element of the dataset union [Formula: see text] in a common Euclidean space while strictly preserving the original ordering of the assembled interaction-distances. To demonstrate our work, we applied the framework to three types of simulated datasets: samples from families of distributions, samples from correlated random variables, and time-courses of statistical moments for three different types of stochastic two-gene interaction models. We then compared different clustering methods with vs. without the qEE-Transition. For all examples, we found that the qEE-Transition followed by Ward clustering had superior performance compared to non-agglomerative clustering methods but had a varied performance against ultrametric-based agglomerative methods. We also tested the qEE-Transition followed by supervised and unsupervised machine learning methods and found promising results, however, more work is needed for optimal parametrization of these methods. As a future perspective, our framework points to the importance of more developments and validation of distance-distribution models aiming to capture multiple-complex interactions between different variables.

Ranking the oil contribution of individual layers in a lacustrine shale oil system based on non-hydrocarbon analysis by FT-ICR MS

Identifying the dominating oil-producing layer(s) within a shaly system, typically characterized by multiple layers with similar properties, is always a critical yet formidable task, as the oil component disparities among these closely adjacent layers are too minor to be resolved by the traditional geochemical fingerprints. This challenge is now likely addressed by high-resolution Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (FT-ICR MS), which can resolve thousands of non-hydrocarbons that could serve as new fingerprints. Taking a typical shaly system in the Ordos Basin in China as an example, the specific proportions of non-hydrocarbon compounds from the retained petroleum of different source rock layers (rock extracts) and the produced oil at the wellhead were identified by FT-ICR MS. Their compositional similarity was calculated using a multidimensional scaling (MDS) method, and the layers hosting the retained petroleum with higher compositional similarity to the produced oils are considered to be the main contributors to oil production. The results show that the main producing layers identified by FT-ICR MS differ from those proposed based on traditional fingerprints like the Rock-Eval parameters. A typical example is that the thick low-TOC shales, conventionally proposed to be unessential to oil production, seem to have a similar contribution, if not higher, to their thick silty counterparts. This divergence may be attributed to the fact that the conventional fingerprints primarily rely on the rock extracts from a vertical well section, which may only represent a limited lateral area, while the non-hydrocarbon similarity approach involving the produced oil appears to be more realistic, as it can consider the engineering processes, like the horizontal well track and the hydraulic fracturing effects. The current approach provides a novel route for identifying the dominating producing layer(s) in a shale oil system, which may have extensive potential for optimizing the production strategy of shale oil wells.

The application of multidimensional scaling of data to determining changes in retailer customers’ preferences

The COVID-19 pandemic has significantly affected several aspects of human activity, including the functioning of different markes, therefore it is important to research its impact. The aim of the study discussed in this paper is to determine which of the three approaches within the method of multidimensional scaling (i.e. multidimensional scaling of classical, symbolic interval-valued or symbolic histogram data) is most adequate for capturing the shifts in retailer customers' preferences that took place during the pandemic. The research concerned the health and beauty market. It was based on the data on orders for beauty products from a Polish producer of cosmetics of a global reach placed by 18 small, mainly family-managed, health and beauty retailers from Lower Silesia. The shops were selected through convenient sampling. Such shops are not a part of large health and beauty retailer chains, therefore they are more vulnerable to all the fluctuations and shifts on the market. The results of this study indicate that in 2020 and 2021, important changes took place on the Lower Silesian health and beauty market as compared to 2019. These changes involved cosmetics for eyes and eybrows gaining popularity at the expense of cosmetics for lips and cheeks. Multidimensional scaling of symbolic histogram data turned out to be the most effective method (in the sense of the measure of fit and the Pearson correlation coefficient) of capturing and analysing changes happening on a market over a period of time.

초등교사의 수업실행 저해요인에 관한 연구

Objectives This study focused on the factors which inhibit the teaching practices as they were perceived by elementary school teachers. Methods Thirty-five elementary school teachers were interviewed, and research materials were analyzed using a concept map approach. From the interview, 44 key sentences were extracted as a final statement, and the concept mapping was completed using the Multidimensional Scaling and Hierarchical Cluster Analysis method. 970 elementary school teachers were asked to answered the 5-point Likert scale questionnaires to check which statement could affect the teaching practices. Results First, the elementary school teachers recognized the factors inhabiting the teaching practices in the “job performance-relationship formation” and “inside-outside the school” dimensions. Second, elementary school teachers recognized the inhabiting factors in 8 clusters; “formalism of educational administration,” “inefficiency of school work,” “lack of trust between teachers and parents,” “lack of efficiency in business processing,” “lack of administrators’ leadership,” “lack of teaching support,” “negative teaching culture,” and “lack of professionalism and teacher’s philosophy” appeared in that order. Conclusions This study will help to identify ways to improve the teaching expertise by identifying the inhibiting factors as perceived by elementary school teachers.

ANALYSIS OF THE SUSTAINABILITY OF THE UTILIZATION OF THREADFIN BREAM (Nemipterus sp.) LANDED AT LEMPASING FISHING PORT, BANDAR LAMPUNG

The waters of Lampung Bay have high potential resources for threadfin bream (Nemipterus sp.). This fish has significant economic value as a diverse food ingredient. However, currently, the body size of threadfin bream found tends to be uniform and even smaller due to continuous overfishing. The research was conducted to assess the status of utilization of threadfin bream resources in the waters of Lampung Bay based on five important aspects, namely ecology, economics, social, technological and institutional. The research was carried out in May 2023 at Lempasing Fishing Port, Bandar Lampung City, with data collection through observation and interviews. Data analysis used the multi-dimensional scaling (MDS) method using the Rapfish (rapid appraisal for fisheries) application to evaluate the sustainability of the use of threadfin bream. The results of the analysis show that the sustainability index value for the use of threadfin bream in the waters of Lampung Bay is as follows: ecological dimension 48.59; economic dimension 36.80; social dimension 75.00; technology dimension 49.91; and ethical dimension 61.64. Based on these results, it can be concluded that the use of threadfin bream in the waters of Lampung Bay is quite sustainable, with an average index value of 54.39.Keywords: Ecological dimension, multi-dimensional scaling, Rapfish, sustainability index.

Multidimensional scaling for big data

AbstractWe present a set of algorithms implementing multidimensional scaling (MDS) for large data sets. MDS is a family of dimensionality reduction techniques using a $$n \times n$$ n × n distance matrix as input, where n is the number of individuals, and producing a low dimensional configuration: a $$n\times r$$ n × r matrix with $$r<<n$$ r < < n . When n is large, MDS is unaffordable with classical MDS algorithms because their extremely large memory and time requirements. We compare six non-standard algorithms intended to overcome these difficulties. They are based on the central idea of partitioning the data set into small pieces, where classical MDS methods can work. Two of these algorithms are original proposals. In order to check the performance of the algorithms as well as to compare them, we have done a simulation study. Additionally, we have used the algorithms to obtain an MDS configuration for EMNIST: a real large data set with more than 800000 points. We conclude that all the algorithms are appropriate to use for obtaining an MDS configuration, but we recommend to use one of our proposals, since it is a fast algorithm with satisfactory statistical properties when working with big data. An package implementing the algorithms has been created.

Sustainability of The Agroforestry Management System on Perhutani Forest Land in Malang Regency, East Java, Indonesia

The Forest Management Program with the Community (PHBM) is a program that provides an opportunity for communities living around forests to participate in managing forests by planting seasonal crops with the concept of agroforestry. However, there are any threats to agricultural sustainability in the form of critical land, pest attacks, institutional functions that are not running well, and non-optimal usage of technology. This study aims to examine the sustainability of farming on Perhutani land which is assessed from the five dimensions of sustainability: ecology, economic, social, institutional, and technology. The data collected by distribute the questionnaires to respondents. Respondents in consist of 67 people in total who divided into 60 farmers, and seven stakeholders. Data analysis used the MDS (Multidimensional Scaling) method and leverage analysis to see the attributes that affect sustainability. The results of the study have a sustainability index value of 53.778%, it is categorized as Sufficiently Sustainable in terms of institutional dimensions about (67.119%), ecology dimensions (61.119%), and economic dimensions (58.332%). Meanwhile, the social dimension (44.597%) and the technology dimension (37.727%) are less sustainable. The leverage analysis shows 25 sensitive attributes that affect the sustainability of farming on Perhutani's land in each dimension.

Navigating Financial Frontiers in the Tourism Economies of Kosovo and Albania during and beyond COVID-19

The problem addressed in this study is the profound impact of the COVID-19 pandemic on the tourism economies of Kosovo (KOS) and Albania (AL), which led to economic–financial stagnation and price increases. The aim was to analyze the financial frontier challenges facing the tourism industry during COVID-19 and beyond and propose effective strategies for shaping a sustainable future for countries within Europe with great potential for tourism development in the current decade. The survey was conducted in 102 locations, including cities, municipalities, regions, villages, and neighborhoods in both countries over the years 2020–2023, while data analysis was performed using a cluster analysis (K-means and hierarchical) and the multidimensional scaling method (Alscal). The results highlighted (a) the severe impact of COVID-19 on both the population and businesses in the tourism sector, which will persist beyond the pandemic, (b) the indispensable role of government intervention in alleviating the financial crisis, (c) the need for innovative approaches and accurate financial management by both the country and businesses to attract tourists, and (d) the importance of control and management for financial sustainability. This paper is of significant importance to tourism destinations as it provides insights into the severe impact of COVID-19 on both the population and businesses in the tourism economies. By highlighting the indispensable role of government intervention, the need for innovative approaches and accurate financial management, and the importance of control and management for financial sustainability, the study offers valuable guidance for tourism destinations in navigating the current crisis and attracting tourists. Furthermore, the paper emphasizes the need for future studies to explore opportunities for long-term financial resilience and growth, contributing to the development of sustainable tourism destinations.

문학 글쓰기의 과제 수행에 대한 분석 연구

Objectives The purpose of this study is to examine what students at G and K universities recognize and make meaning of after appreciating literary works, and to show the performance results.
 Methods For this purpose, this study used students' writing assignments conducted at two universities as analysis data. As a method of statistically analyzing text data, KH-coder 3 (Folder), a corpus research method, was used to conduct K University assignments such as ‘extracted word correspondence analysis, extracted word multidimensional scaling method, hierarchical cluster analysis, network analysis, and self-organizing instruction method.’ was used to present statistical results intuitively, focusing on typical cases by type. As for the analysis method of G University's project, we presented the results of the task analysis through three methods: ‘correspondence analysis, network analysis, and hierarchical cluster analysis’, and presented some conclusions focusing on typical cases by type.
 Results First, through texts, students at K University remember their somewhat turbulent times and learn about where their foundation came from, how they lived in relationships with their family and friends. It showed that they had come. It had the effect of soothing the wounded heart of the present through the experience of writing down past memories and memories. Second, as a result of student responses at G University, there was a tendency to interpret the story as a story about an immature boy, Namu, experiencing loss, accepting the loss and growing, and also interpreting loss as the basis for growth. Additionally, students responded that they understood the two characters as complementary and aimed for a relationship of growth. Third, while watching the character's growth process, students projected their inner self and showed a journey to self-understanding. And, he said that he applied the characters' motifs of innocence, love, and memories to his own life and felt comfort. In addition, positive writing responses were shown regarding the importance of nature and life.
 Conclusions In this study, we applied literary writing teaching and learning activities that can promote self-growth and found the results to be meaningful in literary education.

A multi-criteria model of supply chain sustainability assessment and improvement for sugarcane agroindustry

The sustainability of the sugarcane agro-industry supply chain plays a crucial role in providing economic benefits, minimizing social and environmental impacts, and optimizing resource utilization. This research aims to analyze the sustainability performance of the sugarcane agro-industry supply chain using multi-criteria assessment and formulate strategies for sustainability improvement. The study proposes a multi-criteria assessment model with twenty-eight indicators and four dimensions of sustainability: economic, social, environmental, and resources, which were developed based on previous research. The fuzzy inference system (FIS) and multi-dimensional scaling (MDS) methods were utilized to analyze the multi-criteria indicators of sustainability performance in each dimension and overall supply chain. The Adaptive Neuro Fuzzy Inference System (ANFIS) model was used to aggregate multi-dimension sustainability to achieve overall sustainability performance. A fuzzy cognitive map (FCM) framework was developed to formulate strategies for improving the sustainability performance of the supply chain. The research was verified at two sugar mill locations in Java Island, Indonesia. The FIS and MDS models successfully analyzed the sustainability performance of the two sugar agro-industries, showing an average value of “quite sustainable”. The overall sustainability performance using the ANFIS model for mill A and B were 57.2 and 61.9, respectively. Series of FGDs combined with the FCM model successfully formulated five clusters of strategies as initiatives in improving the sustainability performance, namely raw material provision, harvesting and post-harvest activities, production process optimization, IT-based technology implementation, and institutional aspects. This present work seeks to contributes to the development of multi-criteria of sustainability performance for the food industry's supply chain. It also proposes a comprehensive framework for analyzing and improving sustainable supply chain performance under uncertainty using a combination of conventional and fuzzy assessment modeling approach. A practical initiative strategy in sustainability improvement is revealed for the sugarcane agroindustry's supply chain.

A New and Effective Classification Method for Complex Time Series Based on Information Measure

The growing importance of time series information measure raises questions about how to effectively cluster a large number of nonlinear complex time series data and accurately extract more hidden information from them. In this paper, a clustering measurement and classification method for complex time series, the symmetrical exponential Tsallis relative information (SETRI) measure, is proposed, which aims to address these problems. The intrinsic characteristics of different types of time series information could be validly identified by this method. The modified multidimensional scaling (MDS) method, based on the SETRI measure, has the ability to display the data in the form of graphs for intuitive exhibition and accomplish the process of dimension reduction. The introduction of weighted permutation patterns allows a higher-accuracy classification not only for the time series dissimilarity quantification, but also for avoiding dispensable errors. Besides, the feasibility of the modified MDS classification method is visually and quantitatively verified by the simulated and real-world data. Compared with other MDS methods, the proposed method has better performance, which is reflected in the validity and rationality of the clustering results, thus further verifying the feasibility of the proposed method. Therefore, the new results will be helpful to develop complex data clustering and dimensionality reduction methods.

Local Guitar Position Mapping Based on Consumer Preferences and Perceptions Using Multidimensional Scaling

The potential of the acoustic guitar market in Indonesia has attracted the interest of local businesses in the home industry to create and promote their own acoustic guitar brands within the country. To ensure the appeal of their guitar products to consumers, these businesses must carefully consider product attributes that align with consumer tastes and needs. Conducting a thorough analysis of competitors is also crucial, helping identify strengths and weaknesses to develop effective marketing strategies. Local brands such as Genta, Grande, Stranough, and Avirama have established positive brand images among Indonesian consumers. Recognizing the impact of a strong brand image on consumer loyalty, it is advisable for home industry entrepreneurs to differentiate their acoustic guitars from existing local brands. This research aims to identify the specific attributes that resonate with the tastes and needs of domestic consumers and to position Genta, Grande, Stranough, and Avirama brand acoustic guitars as a reference for designing marketing strategies. The study utilizes the 4P marketing mix approach to identify consumer preferences, collecting data through a questionnaire and applying the Multidimensional Scaling method for analysis. The results highlight that sound quality, price-to-quality ratio, material quality, warranty, ease of purchase, price flexibility, discounts, and completeness of features are crucial factors influencing consumers’ choices in acoustic guitars. Genta excels in price-to-quality ratio, material quality, ease of purchase, price flexibility, and completeness of features. Grande stands out for sound quality and discounts, while Avirama leads in warranty offerings. Stranough shares a similar market segment with Genta due to comparable consumer perceptions, Grande and Avirama occupy distinct segments. This comprehensive understanding of consumer preferences and brand positioning can guide home industry businesses in formulating effective marketing strategies for their acoustic guitar products.

Analysis of mangrove ecosystem sustainability in the Biringkassi mangrove area, Pangkep District, Indonesia

Mangrove forests are found on coastlines in tropical and subtropical areas. The mangrove tree looks strange because its roots are partially above water, making it look like it is standing. Mangrove forests are coastal forests and critical habitats that act as nurseries and protect coasts from erosion. Determining the current status of sustainable management of mangroves is very important as a basis for planning future policies. The purpose of this study was to review the current status of mangroves and analyze the sustainability value of the mangrove ecosystem sustainability in the Biringkassi mangrove area, Pangkep district, Indonesia. This study is descriptive with a quantitative approach to conducting an inventory of mangrove ecosystems, including biophysical, social, economic and institutional data. Analysis of the sustainability of mangrove management The sustainability of the mangrove ecosystem was analyzed using the Rapid Assessment Fisheries (RAPFISH) software with the Multidimensional Scaling Method (MDS) method. The four aspects assessed were ecological, economic, social and institutional. The results of the sustainability analysis from the four dimensions showed that the ecological and institutional aspects have a moderate state of sustainability, but the economic and social aspects have a less sustainable state. Multidimensional analysis showed less sustainable management. Leverage analysis of 24 multidimensional attributes revealed eight highly influential attributes that can lead to change in management if not implemented correctly. Meanwhile, the analysis results should be maintained for properties that achieve low leverage so that the management value does not decrease.

입학 초기 초등학교 1학년의 학교생활 적응 과제에 대한 개념도 분석

Purpose: The purpose of this study was to explore the task of school adjustment in the first grade of elementary school during early entrance and to reveal the importance and performance of such perception.
 Methods: For this purpose, a semi-structured focus group interview was conducted with eleven first-grade homeroom teachers with significant field experience in elementary school. According to the process of the conceptual analysis, sixty-one conceptual statements were derived on school adjustment during early admission, and thirty-eight key statements were finalized after the agreement of the three researchers. The confirmed statements were conducted a classification method of similarity for twenty-six people. Following this, a multi-dimensional scaling method and hierarchical cluster analysis, and importance and performance evaluation were conducted in the stated orde.
 Results: Finally, a two-dimensional concept map including six clusters (adaptation in the environment vs. internal control, adaptation in the group vs. individual adaptation) was derived. The final clusters are specifically about acclimatizing to the environment and routine of an elementary school that is different from an early childhood education institution (cluster 1), overcoming anxiety and fear in unfamiliar situations and maintaining psychological stability (cluster 2), and cultivating basic learning abilities and basic lifestyle habits (cluster 3), concentrating attention and controlling impulsiveness(cluster 4), getting along well with friends and being considerate (cluster 5), and living safely by following school rules (cluster 6).
 Conclusion: This study is meaningful in that it empirically explored the core concept at a time when the importance of school adjustment during early admission of first graders in elementary school, who are experiencing ecological transfer from early childhood education to the elementary education, has garnered attention.

Virgin Coconut Oil (VCO) Business Analysis in Terms of Economic Income

High fluctuations in coconut prices have resulted in coconut farmers in North Minahasa Regency experiencing uncertainty about their economic conditions, so derivative products from coconuts, such as Virgin Coconut Oil (VCO), which can be processed, are needed. This study aims to calculate the feasibility of making Virgin Coconut Oil (VCO), which is processed traditionally, and analyze sensitive indicators from each aspect studied. Traditionally processed Virgin Coconut Oil (VCO) quality highly depends on raw materials and processing. The business feasibility analysis parameters used are marketing, technological, management, legal, and economic. The method used is the Multidimensional Scaling (MDS) Method. The analysis showed that the financial aspect obtained Net Present Value NVP value = IDR 482,378,746, IRR = 93.88%, Gross B/C Ratio = 2.193, PR = 3.64, PBP = 1 year eight days. The feasibility index assessment of five aspects obtained values: marketing aspects 83.50%, technology aspects 52.28%, management aspects 60.91%, legal aspects 65.39%, and economics 74.83%. The average value of the feasibility index shows that the traditional VCO manufacturing business in North Minahasa Regency can be declared feasible.

Analysis of locus estimates of allelic diversity of STR markers in a sample of breeding bulls

Genotypes of the 11 DNA microsatellite loci of 84 bulls of seven breeds were used to evaluate 14 indicators of allelic diversity/differentiation. Traditional and multidimensional statistical methods were applied to the data matrices from the original and transformed estimates (11×14). Estimates of heterozygosity had coefficients of variability of 8-14 %, the number of alleles per locus and indicators of differentiation of breeds at the level of 20-26 %, fixation indices – 38-44 %. Statistically significant Kendall correlations (0.8-1.0) between indicators of allelic richness and heterozygosity, fixation indices, and differentiation indicators were established. The variability of the transformed estimates of diversity/differentiation indicators by loci was in the range of 6-32 %. Including by loci Eth3, Tgla122, Eth225, Bm2113 – 6-12 %, loci Inra23, Tgla126, Eth10 – 15-20 %, loci Tgla227, Sps115, Tgla53, Bm1824 – 28-32 %. The nonparametric Mann-Whitney-Wilcoxon test showed statistically significant differences in the medians of the Eth3 locus with the Bm2113 locus, the Tgla126 locus with the Eth3, Inra23, Tgla122, Eth225, Bm2113, Bm1824, Eth10 loci. The principal component analysis (PCA) identified two components with a total information content of 95,2 %. The first one took into account 59.4 % of the total variance, had the highest loads in intra-breed diversity data and was defined as an «alpha component». The second accounted for 35.8 % of the total variance, had the highest loads in inter-breed differentiation data and was defined as a «beta component». 2D-PCA-ordination showed that a characteristic grouping of loci took place for the analyzed breeds (samples), loci and measures of diversity. Loci Tgla227 and Tgla53 formed group A, group B – loci Tgla122, Eth225, Eth10, group C – loci Inra23, Bm2113 and Bm1824. The loci of the conditional group D (Eth3, Tgla126, Sps115) were defined as «untypical». Validation of ordination was confirmed by calculations on reduced data (dimension 11×7) and the method of non-metric multidimensional scaling (nMDS). The consistency of ordinations according to the Procrust test was 96 % (pperm <0.001). A similar classification of loci was obtained by cluster analysis (UPGMA) with butstrap probabilities of cluster: A – 73, B – 100, C – 73, D – 47 %. The distances and similarity indicators (S) between the profiles of loci and the «true» summary estimates for 11 loci were calculated. Loci Tgla126 and Sps115 had S ≈ 40 %, loci Tgla53 and Bm1824 – at the level of 60 %, loci Inra23, Tgla227 and Bm2113 – 70-75 %, loci Eth3, Tgla122, Eth225 and Eth10 – 84-88 %. The average absolute deviation of the estimates of diversity indicators for the four loci with S≥84 % from the «true» estimates was 3.4 %, for the four loci with S≤60 % – 12.4 %. According to component scores, a general diversity index, γLV, was calculated for each locus. Its correlation with the estimates of the Shannon/Sherwin′s γ-diversity with a 95 % probability value was in the range of 0.73-0.98, Kendall's rank correlation was 0.67 (pvalue = 0.005). The conducted research makes a certain contribution to the expansion of tools for processing molecular genetic data in the analysis of allelic diversity in subdivided populations.

Sustainability Status of Fresh Water White Shrimp (Litopenaeus vannamei) Culture in Glagah District, Lamongan Regency, East Java

Glagah District is the main area for white shrimp culture with freshwater rearing media in Lamongan Regency, so it is necessary to conduct research to determine the sustainability status of freshwater white shrimp culture in Glagah District. The research locations are in seven villages, namely Soko, Pasi, Margoanyar, Glagah, Jatirenggo, Bapuhbaru, and Karangturi. Sustainability status can be measured by considering five aspects of sustainability which include ecology, economy, social, technology, and institutions. In this study, the analysis was carried out using the RAPFISH (Rapid Appraisal for Fisheries) application with the Multi Dimensional Scaling (MDS) method. This study adopted a quantitative descriptive method, with data collection conducted through a survey. The results of the analysis using the Multidimensional Scaling (MDS) approach to 20 cultivation attributes in the ecological, economic, social, technological and institutional dimensions yielded the following sustainability indexes: 52.23% for the ecological dimension, 58.51% for the economic dimension, 78.47 % for the social dimension, 53.77% for the technological dimension, and 40.46% for the institutional dimension. With an average sustainability index value of 56.69%, it can be concluded that the freshwater white shrimp culture in Glagah District is quite sustainable.

A novel clustering method for complex signals and feature extraction based on advanced information-based dissimilarity measure

In this paper, a new dissimilarity measure for more accurate feature extraction and clustering is put forward. The method is proposed from the perspective of the weighted-probability distribution of dispersion patterns and their rank order statistics, where an effective quantization procedure is provided and the loss of information can be reduced. The proposed dissimilarity is applied in the multidimensional scaling (MDS) method to investigate simulated and reality-based signals. The comparative experiment shows that the clustering results of the proposed technique are clearer and more appropriate. State-of-the-art techniques and conventional methods are both included in the comparative experiments. In particular, for the heartbeat signals, it is discovered that the distribution of the weighted-probabilities of the dispersion patterns can discriminate subjects with different physiological conditions and exhibit visible changes of the subject’s dynamical features when aging and disease attacks are taken place, which can be regarded as a microscopic insight of the dynamical mechanisms.

Morphological variability in Chondrilla taxon populations in European Russia and adjacent territories

The morphological variability in populations of Chondrilla taxa is poorly studied, and features of its distribution, both spatially and between taxa, are not obvious. The article presents the results of our comparative analysis of the nature of this variability on the example of 28 populations of eight taxa of the genus in the southeastern European Russia and northwestern Kazakhstan. The variability of eight morphological traits, most of which are still used to determine the species of plants, was analyzed. It is shown that the variability level of these characters, four of which are taxonomically significant, in one year of monitoring is so wide that it completely overlaps the boundaries of their variability of all Eastern European taxa. At the same time, populations of different taxa growing side by side in similar environmental conditions demonstrated a very similar (just identical in some cases) range of morphological variability. It was concluded that the causes of this very dynamic and peculiar variability of traits are most likely the local conditions of population growth in a particular year of monitoring. Our comparative analysis of the interannual (2015, 2016 and 2022) variability of these quantitative traits in 14 populations of five Chondrilla taxa showed its significant dynamics over years as well. Using the method of non-metric multidimensional scaling of quantitative morphometric parameters, it is shown that the gradient of their variability takes place in the direction from the conditions of minimum moisture and maximum temperature to that of increasing humidity and decreasing temperature. At the same time, the combinations of these climatic factors in specific habitats of populations affect the values of morphological parameters to a greater extent than their geographical gradients or taxonomic affiliation.