High Similarity Values Research Articles

Recommendation System for Selecting Electronic Products Using Content-Based Filtering Method

This study aims to develop a recommendation system for electronic products using the Content-Based Filtering method. In this research, calculations were performed to identify 12 products that exhibit similarity based on their respective categories. The method employed for these calculations was cosine similarity, which measures the degree of similarity between products. The analysis results indicate that there are three products with the highest similarity values, specifically 73, 71.15, and 64.89. These products were selected based on their relevant characteristic similarities and features, thereby providing accurate recommendations for consumers. This recommendation system is expected to significantly enhance the online shopping experience by assisting consumers in finding products that align closely with their preferences and needs. Consequently, this research offers substantial contributions to companies seeking to improve customer satisfaction and operational efficiency, ultimately leading to better consumer engagement and increased sales in the competitive electronic market.

Camping Equipment Recommendation System Using Content-Based Filtering Method: A Case Study of Berkah Outdoor45

Camping is a favorite activity for various age groups carried out in the open air to enjoy the beauty of nature and get away from the noise of the city. The high cost of camping equipment encourages many people to prefer renting rather than buying, making Berkah Outdoor45 the main choice for nature lovers to rent camping equipment. This study aims to develop a recommendation system for selecting camping equipment using a content-based filtering mechanism with a TF-IDF approach to help users choose equipment that suits their needs. This study uses a waterfall system development model which includes the stages of analysis, design, implementation, and testing. Testing is carried out using the Blackbox method to evaluate the effectiveness of the system. The results showed that from 18 datasets, the system can provide four recommendations with the highest similarity values, namely D11 (0.377), D18 (0.354), D2 (0.320), D5 (0.311), and D1 (0.287) based on a predetermined formula. The recommendation system developed successfully provided accurate recommendations that were in accordance with user preferences, while reducing ordering errors and increasing efficiency in selecting camping equipment.

Website-Based Liquid Selection Recommendation System Using Content-Based Filtering Method at Morevapor Gading Store

Liquid is a favorite product among various vape lovers. This product provides a variety of unique and refreshing flavors, attracting the attention of vaping lovers to always try new variants. The high cost of purchasing vape liquid makes many people prefer to buy products recommended according to their preferences, making MoreVapor Gading the main choice. This study aims to develop a recommendation system for selecting vape liquid using a content-based filtering mechanism with the TF-IDF approach. The TF-IDF approach was chosen because of its ability to provide more precise weighting to relevant but not too common words, resulting in more accurate recommendations compared to other methods. In practice, the results of this study provide significant benefits for MoreVapor Gading, namely increasing the accuracy of product recommendations that can minimize ordering errors and increase customer satisfaction and loyalty. This research method uses a waterfall model consisting of the analysis, design, implementation, and testing stages. The results of the study show that from 21 datasets, the system can provide five recommendations with the highest similarity values, namely Cair Grape 0.1445, American Winter Grape Candy Magic 0.1243, Paradewa Grape Athena 0.1151, American Winter Magic Fanta Float 0.0923, and Foom Breeze Series Guava 0.0918 based on user preferences. The recommendation system developed aims to provide accurate recommendations and in accordance with user preferences in choosing vape liquid.

Facivitalis istanbulensis gen. nov., sp. nov., a novel member of the family Sphingomonadaceae with the potential for aromatic-degradation isolated from Jet A1 fuel.

A novel gram-stain-indeterminate, rod-shaped, endospore-forming, motile, aerobic bacterium, designated JETA1-E2T, was isolated from aircraft fuel Jet A1 sample. The strain showed high pairwise similarity values of partial 16S rRNA gene sequences to Sphingomonas paucimobilis (MT367853) (99.42%), Sphingomonas sanguinis (MF319771) (99.34%), and Sphingomonas pseudosanguinis (HE716953) (99.27%) within the family Sphingomonadaceae. However, API test results revealed that the strain JETA1-E2T differed from these type strains. The phylogenetic tree based on the whole genome and the phylogenomic tree generated with the UBCG tool showed that the strain JETA1-E2T formed a distinct monophyletic clade within the family Sphingomonadaceae, and clustered distantly with the genera Sphingomonas and Sphingobium. The predominant respiratory quinone is Q-10. The major fatty acids are C16:0 and summed feature 8 (C18:1ω7c and/or C18:1ω6c). C19:0 is present in small amounts. The polar lipids are diphosphatidylglycerol, phosphatidylethanolamine, phosphatidylglycerol, phosphatidylcholine, aminophospholipid, unidentified glycolipid, and two unidentified sphingoglycolipids. The only polyamine is putrescine in minor amounts. The DNA G + C content of the type strain is 66.5mol%. Several unique genes in the strain JETA1-E2T may contribute to fight against various stressors, virulence and pathogenicity, as well as survival in challenging conditions. The strain JETA1-E2T contains 100 of the characterised proteins available in the HADEG database of which 58% of these are involved in metabolic process of aromatics degradation. The findings indicate that the strain JETA1-E2T has the potential to metabolise hydrocarbons such as fuel, especially aromatic compounds. Based on the results of polyphasic taxonomic analyses, the strain JETA1-E2T represents a novel species in a new genus in the family Sphingomonadaceae for which the name Facivitalis istanbulensis gen. nov., sp. nov. is proposed. The type strain of Facivitalis istanbulensis is JETA1-E2T (DSM 117971T = LMG 33634T = KUEN 1206 (B) F3-1-1T).

Morpho-Molecular and Genomic Characterization of Penicillium mexicanum Isolates Retrieved from a Forsaken Gold Mine

During the ongoing studies designed to examine the fungal diversity present within the abandoned and flooded Escádia Grande gold mine (Góis, Portugal), we repeatedly isolated several specimens belonging to a Penicillium species. Molecular phylogenetic analysis, coupled with morphological observations, positioned this fungus within subgen. Penicillium sect. Paradoxa, series Atramentosa, pinpointing its identity as Penicillium mexicanum (the first record for mining soils and the country). Given the limited research conducted on Penicillia isolated from similar environments, the species genome was sequenced utilizing the Oxford Nanopore® MinION™ methodology and studied through bioinformatic analysis. The obtained genome has a size of 29.62 Mb, containing a 47.72% GC content, 10,156 genes, with 44 rRNAs and 178 tRNAs/tmRNAs, providing the first genomic resource for this microorganism. Bioinformatic analysis allowed us to identify multiple genomic traits that can contribute towards this species survival in these extreme environments, including the presence of high levels of major facilitator transporters (MFS), Zn (2)-C6 fungal-type DNA-binding domains, P-loop containing nucleoside triphosphate hydrolases, specific fungal transcription factors and sugar transporters. Furthermore, putative advantageous metabolic traits, such as methylotrophy, assimilatory nitrate and sulfate reduction abilities, were also detected. In addition, the results also highlighted a strong genomic and metabolic organization and investment towards arsenic detoxification (transport and oxidation). Lastly, thirty-two putative biosynthetic gene clusters were predicted, including some with high similarity values to monascorubrin, nidulanin A, histidyltryptophanyldiketopiperazine/dehydrohistidyltryptophanyldiketopiperazine/roquefortine D/roquefortine C/glandicoline A/glandicoline B/meleagrine, YWA1 and choline. Overall, this study expands the current Penicillia knowledge from mining environments while also enhancing our understanding regarding fungal arsenic resistance.

New Insights on the Information Content of the Normalized Difference Vegetation Index Sentinel-2 Time Series for Assessing Vegetation Dynamics

The Sentinel-2 NDVI time series information content from 2017 to 2023 at a 10 m spatial resolution was evaluated based on the NDVI temporal dependency in five scenarios in central Spain. First, time series were interpolated and then filtered using the Savitzky–Golay, Fast Fourier Transform, Whittaker, and Maximum Value filters. Temporal dependency was assessed using the Q-Ljung-Box and Fisher’s Kappa tests, and similarity between raw and filtered time series was assessed using Correlation Coefficient and Root Mean Square Error. An Interpolating Efficiency Indicator (IEI) was proposed to summarize the number and temporal distribution of low-quality observations. Type of climate, atmospheric disturbances, land cover dynamics, and management were the main sources of variability in five scenarios: (1) rainfed wheat and barley presented high short-term variability due to clouds (lower IEI in winter and spring) during the growing cycle and high interannual variability due to precipitation; (2) maize showed stable summer cycles (high IEI) and low interannual variability due to irrigation; (3) irrigated alfalfa was cut five to six times during summer, resulting in specific intra-annual variability; (4) beech forest showed a strong and stable summer cycle, despite the short-term variability due to clouds (low IEI); and (5) evergreen pine forest had a highly variable growing cycle due to fast responses to temperature and precipitation through the year and medium IEI values. Interpolation after removing non-valid observations resulted in an increase in temporal dependency (Q-test), particularly a short term in areas with low IEI values. The information improvement made it possible to identify hidden periodicities and trends using the Fisher’s Kappa test. The SG filter showed high similarity values and weak influence on dynamics, while the MVF showed an overestimation of the NDVI values.

Comprehensive analysis and implications of Veronica persica germination and growth traits in their invasion ecology

Invasive alien species implications in ecological threats are attributed to their unique characteristics that are linked to their invasion. Veronica persica (Plantaginaceae family) is an alien weed species in Egypt. Regardless of its widespread globally in various regions, the growth traits and behavior of V. persica remain poorly understood. The comprehensive analysis, reveals the optimal germination (Gmax) was detected at 10/20 °C, 15/20 °C, and 20/25 °C at the moderate temperature regimes. The rapid germination rate (G rate) peaked at 10/20 °C regime, with a rate of 0.376 per day. Furthermore, under stress conditions, V. persica has 50% germination inhibition (G50) and 50% of growth inhibition occurred at − 0.91 MPa and 0.75 MPa of osmotic pressure and 3225.81 ppm and 2677.1 ppm of salt stress (NaCl) respectively. The germination ranged from 6 to 9 pH, with the highest germination percentage occurring at a pH of 7 & 8, reaching 88.75% compared to the control group. There is a strong interaction effect between habitats and plant stages, the plant stages and habitats have significant effects (p ≤ 0.00) on V. persica growth. There was high and moderate plasticity in the response of morphological and growth features between stages. During the seedling-juvenile interval and the juvenile-flowering stages, respectively, there was a noticeable increase in both Relative Growth Rate and Net Assimilation Rate. Demographic surveys identified approximately 24 species across 11 families associated with V. persica in invaded areas. The Sorenson indices of qualitative index exhibited high similarity values in the invaded sites by (82.35%) compared to (72.72%) in non-invaded sites. However, interactions with native communities were reflected in lower richness, diversity, and evenness, displaying slightly higher Simpson index 1 (λ) values compared to invaded and non-invaded sites (0.043 and 0.0290) vs. (0.0207 and 0.268), in rangelands and F. carica orchards respectively. These results emphasize the substantially higher adaptability of V. persica to variable environmental conditions and abilities to invade a new community. This knowledge about invasive V. persica weeds germination and growth is itemized as the consistent predictive base for future invasion and informs strategic management priorities.

Scientific paper recommender system using deep learning and link prediction in citation network

Scientific paper recommender system using deep learning and link prediction in citation network

Medical Record Document Search with TF-IDF and Vector Space Model (VSM)

The growth of medical record documents is increasing over time, and the various types of diseases and therapies needed are increasing. However, this has not been followed by an effective and efficient search process. This study aims to deal with search problems that often take a long time with search results that are not necessarily as expected by building a search model for medical record documents using the vector space model (VSM) and TF-IDF methods. The VSM method allows retrieval of results that are not the same as the search queries entered by the user but are expected to provide still results relevant to the user's desired needs. The model development process was taken based on the data in the FS_ANAMNESA and FS_DIAGNOSA columns, followed by preprocessing, which consists of deleting blank lines, lowercase, removing punctuation marks, HTML tags, stop words, excess spaces between words, and normalizing typo words, then forming a TF-IDF matrix based on the frequency of occurrence of each word feature, and followed by the calculation of the similarity value of the search query compared to medical record documents based on the cosine similarity formula. The retrieval results were all columns of each existing medical record document and were sorted based on 10 rows with the highest similarity value. The model evaluation results were based on 1000 medical record documents and tested with 20 search queries in this study, which gave an average precision value of 0.548 and an average recall value of 0.796.

Microbiological quality of irrigation water on highly diverse fresh produce smallholder farms: elucidating environmental routes of contamination.

To evaluate the microbiological safety, potential multidrug-resistant bacterial presence and genetic relatedness (DNA fingerprints) of Escherichia coli isolated from the water-soil-plant nexus on highly diverse fresh produce smallholder farms. Irrigation water (n=44), soil (n=85), and fresh produce (n=95) samples from six smallholder farms with different production systems were analysed for hygiene indicator bacterial counts and the presence of shigatoxigenic E. coli and Salmonella spp. using standard microbiological methods. Identities of isolates were confirmed using matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS), and the genetic relatedness of the E. coli isolates determined using enterobacterial repetitive intergenic consensus polymerase chain reaction (ERIC-PCR) analysis. Irrigation water E. coli levels ranged between 0 and 3.45 log MPN/100 ml-1 with five farms having acceptable levels according to the World Health Organization limit (3 log MPN/100 ml-1). Fresh produce samples on four farms (n=65) harboured E. coli at low levels (<1 log CFU/g-1) except for one sample from kale, spring onion, green pepper, onion, and two tomato samples, which exceeded international acceptable limits (100 CFU/g-1). Only one baby carrot fresh produce sample tested positive for Salmonella spp. Of the 224 samples, E. coli isolates were identified in 40% (n=90) of all water, soil, and fresh produce types after enrichment. Additionally, the DNA fingerprints of E. coli isolates from the water-soil-plant nexus of each respective farm clustered together at high similarity values (>90%), with all phenotypically characterized as multidrug-resistant. The clustering of E. coli isolated throughout the water-soil-plant nexus, implicated irrigation water in fresh produce contamination. Highlighting the importance of complying with irrigation water microbiological quality guidelines to limit the spread of potential foodborne pathogens throughout the fresh produce supply chain.

Actinomycetospora termitidis sp. nov., an insect-derived actinomycete isolated from termite (Odontotermes formosanus).

Strain Odt1-22T, an insect-derived actinomycete was isolated from a termite (Odontotermes formosanus) that was collected from Chanthaburi province, Thailand. Strain Odt1-22T was aerobic, Gram-stain-positive, and produced bud-like spore chain on the substrate hypha. According to chemotaxonomic analysis, strain Odt1-22T contained meso-diaminopimelic acid in peptidoglycan and the whole-cell hydrolysates contained arabinose, galactose, glucose, and ribose. The major menaquinone was MK-8(H4). The diagnostic phospholipids were diphosphatidylglycerol, hydroxyphosphatidylethanolamine, phosphatidylethanolamine and phosphatidylglycerol. Phylogenetic analysis based on 16 S rRNA gene sequence revealed that strain Odt1-22T was identified to the genus Actinomycetospora and showed high similarity values with A. chiangmaiensis DSM 45062 T (99.24%), A. soli SF1T (99.24%) and A. corticicola 014-5 T (98.17%). The genomic size of strain Odt1-22T was 6.6 Mbp with 73.8% G + C content and 6355 coding sequences (CDSs). The genomic analysis, strain Odt1-22T and closely related species A. chiangmaiensis DSM 45062 T, A. soli SF1T and A. corticicola DSM 45772 T displayed the values of average nucleotide identity-blast (ANIb) at 83.7-84.1% and MUMmer (ANIm) at 86.6-87.0%. Moreover, the results of digital DNA-DNA hybridization values between strain Odt1-22T and related Actinomycetospora species were 45.8-50.5% that lower than the threshold value of commonly used to delineate separated species level. On the basis of phenotypic, chemotaxonomic, and genotypic data, strain Odt1-22T represented a novel species within the genus Actinomycetospora, for which the name Actinomycetospora termitidis sp. nov. is proposed. The type strain of the species is Odt1-22T (= TBRC 16192 T = NBRC 115965 T).

Biogeographic response to major extinction events: The case of Triassic bivalves

Biogeographic response to major extinction events: The case of Triassic bivalves

Matching Scientific Article Titles using Cosine Similarity and Jaccard Similarity Algorithm

Matching Scientific Article Titles using Cosine Similarity and Jaccard Similarity Algorithm

Expert System for Detecting Genset Engine Faults Using the Case Based Reasoning Method

PT. Sabindo Raya Gemilang is an exporter of shrimp and fish in Indonesia. This company requires an enormous flow of electricity to support activities so that it is not bothered by blackouts from the PLN. A generator set or genset is a substitute for a voltage source. The problem is that genset damage requires reliable mechanical handling. Junior mechanics sometimes misanalyze damage, requiring the supervision of a senior mechanic. This study applies an expert system with the Case-Based Reasoning (CBR) method to detect genset damage. It meets the case researched for having old cases to compare to new ones through the Retrieve, Reuse, Revise, and Retain so that problems are solved easily and quickly. The validity test showed that 5 of 6 test data were equal to the expert's diagnosis. Expert system accuracy 83%. There was a system diagnosis different from experts because the system’s diagnosis was based on the symptoms weight calculation and made a diagnosis with the highest similarity value. Meanwhile, experts observed the genset damage directly.

Bicluster Analysis of Cheng and Church's Algorithm to Identify Patterns of People's Welfare in Indonesia

Biclustering is a method of grouping numerical data where rows and columns are grouped simultaneously. The Cheng and Church (CC) algorithm is one of the bi-clustering algorithms that try to find the maximum bi-cluster with a high similarity value, called MSR (Mean Square Residue). The association of rows and columns is called a bi-cluster if the MSR is lower than a predetermined threshold value (delta). Detection of people's welfare in Indonesia using Bi-Clustering is essential to get an overview of the characteristics of people's interest in each province in Indonesia. Bi-Clustering using the CC algorithm requires a threshold value (delta) determined by finding the MSR value of the actual data. The threshold value (delta) must be smaller than the MSR of the actual data. This study's threshold values are 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, and 0.8. After evaluating the optimum delta by considering the MSR value and the bi-cluster formed, the optimum delta is obtained as 0.1, with the number of bi-cluster included as 4.

Application of the Minkowski Distance Similarity Method in Case-Based Reasoning for Stroke Diagnosis

A Stroke is a cerebrovascular disease characterized by impaired brain function due to damage or death of brain tissue caused by reduced or blocked blood and oxygen flow to the brain. Expert systems can be used as learning aids for medical students to diagnose stroke. Medical records of stroke cases can be reused as a reference for diagnosing stroke when there are new cases, known as the case-based reasoning (CBR) method. This study implements the Minkowski distance similarity method in CBR to calculate the similarity value between cases, where each similar case has the same solution. This study uses the Minkowski distance similarity method in CBR to obtain the most optimal value of r and the most appropriate threshold value in the expert system for stroke diagnosis. The diagnosis process is carried out by inputting the patient's condition, symptoms, and risk factors. Then the system will calculate the similarity value and take the case with the highest similarity value as the solution, providing that the similarity value must be greater than or equal to the threshold value. Based on system testing, the best accuracy value was achieved by applying a threshold value of 75 with an r value of 3 or 4, with an accuracy rate of 88,89%, a recall value of 88%, and a precision of 100%.

The Potential Genetic Effect for Yield and Foliar Disease Resistance in Faba Bean (Vicia faba L.) Assessed via Morphological and SCoT Markers.

Faba bean is considered one of the most prominent grain legumes, with high protein content for human food consumption and livestock feed. The present study evaluated the nature of gene action and determined the genetic diversity among different populations of three crosses for resistance to foliar diseases at the molecular level. Analysis of variance exposed significant differences among the generations for all measured traits. Both dominance and additive gene effects were essential, but dominance genes, for the most part, exhibited greater effects than additive ones. This indicates an essential role for dominant genes alongside the additives one in inheriting such traits. The third cross (Marina × Giza 40) gave desired significant and positive (additive × additive) values for the number of pods/plant, seeds/plant, and seed yield/plant, in addition to desirable negative values for chocolate spot and rust characteristics. Furthermore, assessing the lines under study using seven SCoT primers disclosed three bands with recorded molecular weights of 260, 207, and 178 bp, generated by SCoT-1, SCoT-4, and SCoT-7 primers, respectively. These bands exist in the resistant parent (Marina), which could be attributed to the high-disease-resistance phenotypes, and they are absent in the sensitive parent (Giza 40) and other putative sensitive lines. Based on the molecular profiles and the genetic similarity between parents and the selected lines, the highest similarity value (0.91) was detected between Marina genotype and BC1, revealing a high foliar disease resistance. Meanwhile, Giza 40 (susceptible to foliar diseases) exhibited the maximum value (0.93) with F2. Additionally, cluster analysis based on genetic relationships was performed, and a high level of correlation between the results of PCR-based SCoT analysis and the foliar disease reactions was observed in the field. Consequently, this study concluded that SCoT markers created reliable banding profiles for evaluating genetic polymorphism among faba bean lines, which could be a foundation for developing an efficient breeding program.

Static Hilbert convex set clustering for web services aggregation

&lt;span&gt;Web services' high levels of duplicate textual structures have caused network bottlenecks and congestion. Clustering and then aggregating similar web services as one compressed message can potentially achieve network traffic reduction. In this paper, a static Hilbert clustering as new model for clustering web services based on convex set similarity is proposed. Mathematically, the proposed model calculates similarity among simple object access protocol (SOAP) messages and then cluster them based on higher similarity values. Next, each cluster is aggregated as a compact message. The experiments have explained the proposed model performance as it has outperformed the convention clustering strategies in both compression ratio and clustering time. The best results have been achievable by the proposed model has reached up to (15) with fixed-length and up to (21) with Huffman.&lt;/span&gt;

Fish Diversity in Extreme Flood in Epie Creek, Bayelsa State, Niger delta

Floods have been of great concern in the Niger Delta in the recent years, precipitating this study. The research was conducted to investigate diversity of fish species in the October 2022 extreme flood in the Niger Delta. Samples were collected randomly from landings of artisanal fishers in five sample locations, sorted and identified to species level. Diversity was estimated using Shannon-Wiener's diversity H' and Simpson's diversity D indices. Richness R, Evenness E and Similarity between stations were analyzed accordingly. From the results, R was from 4.255-4.535, E was 0.789 to 0.899 and H’ 1.734-1.974. Simpson’s index D was between 0.162 and 0.226, while Simpson’s index of diversity 1-D was from 0.774 to 0.838. Highest similarity value between stations was 0.286. Results from the study indicate the creek experienced a stable system during the October 2022 flood.

Improving taxonomic classification of marine zooplankton by molecular approach: registration of taxonomically verified 18S and 28S rRNA gene sequences.

Zooplankton plays an important role in the marine ecosystem. A high level of taxonomic expertise is necessary for accurate species identification based on morphological characteristics. As an alternative method to morphological classification, we focused on a molecular approach using 18S and 28S ribosomal RNA (rRNA) gene sequences. This study investigates how the accuracy of species identification by metabarcoding improves when taxonomically verified sequences of dominant zooplankton species are added to the public database. The improvement was tested by using natural zooplankton samples. rRNA gene sequences were obtained from dominant zooplankton species from six sea areas around Japan and registered in the public database for improving the accuracy of taxonomic classifications. Two reference databases with and without newly registered sequences were created. Comparison of detected OTUs associated with single species between the two references was done using field-collected zooplankton samples from the Sea of Okhotsk for metabarcoding analysis to verify whether or not the newly registered sequences improved the accuracy of taxonomic classifications. A total of 166 sequences in 96 species based on the 18S marker and 165 sequences in 95 species based on the 28S marker belonging to Arthropoda (mostly Copepoda) and Chaetognatha were registered in the public database. The newly registered sequences were mainly composed of small non-calanoid copepods, such as species belonging to Oithona and Oncaea. Based on the metabarcoding analysis of field samples, a total of 18 out of 92 OTUs were identified at the species level based on newly registered sequences in the data obtained by the 18S marker. Based on the 28S marker, 42 out of 89 OTUs were classified at the species level based on taxonomically verified sequences. Thanks to the newly registered sequences, the number of OTUs associated with a single species based on the 18S marker increased by 16% in total and by 10% per sample. Based on the 28S marker, the number of OTUs associated with a single species increased by 39% in total and by 15% per sample. The improved accuracy of species identification was confirmed by comparing different sequences obtained from the same species. The newly registered sequences had higher similarity values (mean >0.003) than the pre-existing sequences based on both rRNA genes. These OTUs were identified at the species level based on sequences not only present in the Sea of Okhotsk but also in other areas. The results of the registration of new taxonomically verified sequences and the subsequent comparison of databases based on metabarcoding data of natural zooplankton samples clearly showed an increase in accuracy in species identification. Continuous registration of sequence data covering various environmental conditions is necessary for further improvement of metabarcoding analysis of zooplankton for monitoring marine ecosystems.