Dissimilarity Analysis Research Articles

Functional Meta-Analysis of the Proteomic Responses of Arabidopsis Seedlings to the Spaceflight Environment Reveals Multi-Dimensional Sources of Variability across Spaceflight Experiments.

The human quest for sustainable habitation of extraterrestrial environments necessitates a robust understanding of life's adaptability to the unique conditions of spaceflight. This study provides a comprehensive proteomic dissection of the Arabidopsis plant's responses to the spaceflight environment through a meta-analysis of proteomics data from four separate spaceflight experiments conducted on the International Space Station (ISS) in different hardware configurations. Raw proteomics LC/MS spectra were analyzed for differential expression in MaxQuant and Perseus software. The analysis of dissimilarities among the datasets reveals the multidimensional nature of plant proteomic responses to spaceflight, impacted by variables such as spaceflight hardware, seedling age, lighting conditions, and proteomic quantification techniques. By contrasting datasets that varied in light exposure, we elucidated proteins involved in photomorphogenesis and skotomorphogenesis in plant spaceflight responses. Additionally, with data from an onboard 1 g control experiment, we isolated proteins that specifically respond to the microgravity environment and those that respond to other spaceflight conditions. This study identified proteins and associated metabolic pathways that are consistently impacted across the datasets. Notably, these shared proteins were associated with critical metabolic functions, including carbon metabolism, glycolysis, gluconeogenesis, and amino acid biosynthesis, underscoring their potential significance in Arabidopsis' spaceflight adaptation mechanisms and informing strategies for successful space farming.

The Distributed HTAP Architecture for Real-Time Analysis and Updating of Point Cloud Data

Updating the most recent set of point cloud data is critical in autonomous driving environments. However, existing systems for point cloud data management often fail to ensure real-time updates or encounter situations in which data cannot be effectively refreshed. To address these challenges, this study proposes a distributed hybrid transactional/analytical processing architecture designed for the efficient management and real-time processing of point cloud data. The proposed architecture leverages both columnar and row-based tables, enabling it to handle the substantial workloads associated with its hybrid architecture. The construction of this architecture as a distributed database cluster ensures real-time online analytical process query performance through query parallelization. A dissimilarity analysis algorithm for point cloud data, built by utilizing the capabilities of the spatial database, updates the point cloud data for the relevant area whenever the online analytical process query results indicate high dissimilarity. This research contributes to ensuring real-time hybrid transactional/analytical processing workload processing in dynamic road environments, helping autonomous vehicles generate safe, optimized routes.

Dissimilarity analysis based on diffusion maps

Compositional measurements from species assemblages define a high dimensional dataspace in which the data can form complex structures, termed manifolds. Comparing assemblages in this dataspace is difficult because the data is often sparse relative to its dimensionality and the complex structure of the manifold introduces bias and error in measurements of distance. Here, we apply diffusion maps, a manifold learning method, to find and characterize manifolds in high‐dimensional compositional data. We show that diffusion maps embed the data in reduced dimensions in which the Euclidean distance between data points approximates the distance between them along the manifold. This is especially useful when species turnover is high, as it provides a way to measure meaningful distances between assemblages even when they harbor disjoint sets of species. We anticipate diffusion maps will therefore be particularly useful for characterizing community change over large spatial and temporal scales.

Impact of urbanization on the ant diversity: a case study on teak plantation in South Sulawesi, Indonesia

Ant communities play an important role in a teak agroecosystem. However, ant diversity is affected by urbanization. The purpose of this study was to determine the diversity and composition of ants in teak plantations in urban and rural areas. This study was conducted in July 2022 at three plantations in two regencies (Gowa and Maros) and one city (Makassar) in South Sulawesi, Indonesia. Gowa and Maros are located in rural areas, while Makassar is located in urban areas. Ants were sampled using a pitfall canopy. At each plantation, 20 trees were sampled randomly for pitfall installation. Ants were identified to the genera level and morphospecies. Ant’s diversity was analyzed using the Shannon Wiener, Simpson, and Evenness index and analysis of dissimilarity (Anosim). Total 273 individual ants samples were collected from 10 species and four subfamilies from three teak plantations in South Sulawesi. Crematogaster sp.1 was the most abundant ant among all the collected samples. Based upon the different indexes, the highest ant diversity was found in Gowa followed by Maros, while the lowest diversity was found in Makassar. The level of ant dominance in Makassar was higher than other two studied areas. The highest species evenness index was also found in Gowa and followed by Maros. The species composition in the three teak plantations was also not similar. Each location had their unique species composition than the other locations. This indicated that urbanization causes negative impacts on ants diversity and evenness as well as increase the dominance of ant species in teak plantations.

Ambient air pollution-related environmental inequality and environmental dissimilarity in Helsinki Metropolitan Area, Finland

Most studies suggest that people with lower socio-economic status (SES) are exposed to higher air pollution levels. Research from Europe, on the other hand, have shown mixed results, often indicating non-linear patterns, necessitating a better understanding of the context-specific manifestation of the relationship between SES and air pollution. The results of our generalized additive model show that median income of inhabitants has an inverted U-shaped relationship with air pollution in Helsinki Metropolitan Area, Finland. However, when the spatial distribution of people belonging to certain income groups is considered in applying an environmental dissimilarity analysis, low-income people are found to be more adversely dispersed compared to other income groups. By contrasting additional built environment and socio-economic characteristics of the total population and of the low-income people's hotspots for environmental dissimilarity, we present further indications of environmental injustice regarding car ownership, heating types and ownership structure of the building stock.

Impact of clomazone on bacterial communities in two soils.

Bacterial communities are important for soil functions, but the effect of clomazone on network complexity, composition, and stability is not well studied. In this study, two agricultural soils were used to test the impact of clomazone on bacterial communities, and the two soils were treated with three concentrations of clomazone (0, 0.8, 8, and 80 mg kg1) in an incubator. Bacterial network nodes, links, and average degrees were all decreased by 9-384, 648-829, and 0.703-2.429, respectively. Based on keystone nodes, the topological roles of the nodes were also influenced by clomazone. Bacterial network composition was also impacted based on the analysis of similarity (ANOSIM) and network dissimilarity. Compared with control and clomazone treatments in both soils, the ANOSIM between control and all clomazone treatments was higher than 0.6, network dissimilarities were 0.97-0.98, shared nodes were 131-260, and shared links were 12-100. The bacterial network stability was decreased by clomazone, with decreased robustness by 0.01-0.016 and increased vulnerability by 0.00023-0.00147 in both soils. There were fewer bacterial network modules preserved after clomazone treatment, and the bacterial network community functions were also impacted in both soils. Based on these results, soil bacterial species connections, modularization, and network stability were significantly impacted by clomazone.

Topsoil and subsoil bacterial community assemblies across different drainage conditions in a mountain environment

BackgroundHigh mountainous environments are of particular interest as they play an essential role for life and human societies, while being environments which are highly vulnerable to climate change and land use intensification. Despite this, our knowledge of high mountain soils in South America and their microbial community structure is strikingly scarce, which is of more concern considering the large population that depends on the ecosystem services provided by these areas. Conversely, the Central Andes, located in the Mediterranean region of Chile, has long been studied for its singular flora, whose diversity and endemism has been attributed to the particular geological history and pronounced environmental gradients in short distances. Here, we explore soil properties and microbial community structure depending on drainage class in a well-preserved Andean valley on the lower alpine vegetation belt (~2500 m a.s.l.) at 33.5˚S. This presents an opportunity to determine changes in the overall bacterial community structure across different types of soils and their distinct layers in a soil depth profile of a highly heterogeneous environment.MethodsFive sites closely located (<1.5 km) and distributed in a well preserved Andean valley on the lower alpine vegetation belt (~2500 m a.s.l.) at 33.5˚S were selected based on a pedological approach taking into account soil types, drainage classes and horizons. We analyzed 113 soil samples using high-throughput sequencing of the 16S rRNA gene to describe bacterial abundance, taxonomic composition, and co-occurrence networks.ResultsAlmost 18,427 Amplicon Sequence Variant (ASVs) affiliated to 55 phyla were detected. The bacterial community structure within the same horizons were very similar validating the pedological sampling approach. Bray-Curtis dissimilarity analysis revealed that the structure of bacterial communities in superficial horizons (topsoil) differed from those found in deep horizons (subsoil) in a site-specific manner. However, an overall closer relationship was observed between topsoil as opposed to between subsoil microbial communities. Alpha diversity of soil bacterial communities was higher in topsoil, which also showed more bacterial members interacting and with higher average connectivity compared to subsoils. Finally, abundances of specific taxa could be considered as biological markers in the transition from topsoil to subsoil horizons, like Fibrobacterota, Proteobacteria, Bacteroidota for shallower soils and Chloroflexi, Latescibacterota and Nitrospirota for deeper soils.ConclusionsThe results indicate the importance of the soil drainage conditions for the bacterial community composition, suggesting that information of both structure and their possible ecological relationships, might be useful in clarifying the location of the edge of the topsoil-subsoil transition in mountainous environments.

Examining the evolution of access to Alaska's halibut IFQ fishery

In fishing communities, livelihoods and well-being depend on sustaining access to key fisheries through changes in natural resource management. In Alaska, the rationalization of the commercial fishery for Pacific halibut (Hippoglossus stenolepis) in 1995 led to the consolidation of the halibut fleet. The high cost of halibut catch shares have since become a crucial barrier to prospective entrants, especially small-scale operations with few options for portfolio diversification. However, quantitative approaches to understanding that barrier face an information gap: datasets on harvest and catch share ownership in fisheries lack common identifiers for individuals. We match individuals across harvest and catch share ownership data from 1991 through 2019, enabling a detailed examination of entrants and non-entrants – those who acquire or do not acquire halibut catch shares over the time series. We compare fisheries portfolios in terms of participation and earnings through duration, dissimilarity, and network analyses. Differences over time and between entrants and non-entrants emerge across analyses. For both groups, cohorts of participants shrink and real individual earnings increase over the time series. However, entrants' cohorts have decreased further relative to historical participation, while entrants' real earnings and fisheries portfolio compositions have diverged from those of non-entrants. Our results reveal broad differences in Alaska fisheries participants' access to a critical fishery, underscoring the role of catch shares in shaping fishing communities’ opportunities and resilience in the face of social and environmental change.

Combining current and historical biodiversity surveys reveals order of magnitude greater richness in a British Columbia marine protected area

The value of biodiversity and of documented biodiversity surveys is well established. Extracting historical biodiversity data and synthesizing them with current data can provide a more comprehensive estimate of total diversity and guide future monitoring. We demonstrate the utility of compiling historical and recent biodiversity data to better characterize taxon richness and composition. Our focus is an otherwise unmonitored habitat in an unmonitored British Columbia provincial park, in a heavily impacted region of the Salish Sea that was designated a United Nation Biosphere Reserve in 2021. We conducted surveys and compiled historical records that together spanned three intertidal habitats and 43 years. From these combined data we report a total of 99 taxa, an order of magnitude increase over the number listed in the park’s Master Plan. These include seven non-native species, of which four are newly reported here. Rarefaction, extrapolation, and multivariate dissimilarity analyses revealed the roles of methods and habitat types in contributing to differences in taxon richness and composition among surveys. This data compilation illustrates many of the challenges and opportunities in aligning and assembling independent space-time snapshots of alpha (i.e., local) diversity to better understand the gamma (i.e., regional) diversity of a marine protected area and provides the foundational data needed to design effective future monitoring at molecular to ecosystem scales.

The impact of vitamin D3 supplementation on the faecal and oral microbiome of dairy calves indoors or at pasture

Vitamin D (VitD) is emerging as an immune regulator in addition to its established role in metabolism and mineral homeostasis. This study sought to determine if in vivo VitD modulated the oral and faecal microbiome in Holstein–Friesian dairy calves. The experimental model consisted of two control groups (Ctl-In, Ctl-Out) which were fed with a diet containing 6000 IU/Kg of VitD3 in milk replacer and 2000 IU/Kg in feed, and two treatment groups (VitD-In, VitD-Out) with 10,000 IU/Kg of VitD3 in milk replacer and 4000 IU/Kg in feed. One control and one treatment group were moved outdoors post-weaning at approximately 10 weeks of age. Saliva and faecal samples were collected after 7 months of supplementation and analysis of the microbiome was performed using 16S rRNA sequencing. Bray–Curtis dissimilarity analysis identified that both sampling site (oral vs. faecal) and housing (indoor vs. outdoor) had significant influences on the composition of the microbiome. The calves housed outdoors had greater microbial diversity in the faecal samples based on Observed, Chao1, Shannon, Simpson and Fisher measures in comparison to calves housed indoors (P < 0.05). A significant interaction between housing and treatment was observed for the genera Oscillospira, Ruminococcus, CF231 and Paludibacter in faecal samples. The genera Oscillospira and Dorea were increased while Clostridium and Blautia were decreased following VitD supplementation in the faecal samples (P < 0.05). An interaction between VitD supplementation and housing was detected in the abundance of the genera Actinobacillus and Streptococcus in the oral samples. VitD supplementation increased the genera Oscillospira, Helcococcus and reduced the genera Actinobacillus, Ruminococcus, Moraxella, Clostridium, Prevotella, Succinivibrio and Parvimonas. These preliminary data suggest that VitD supplementation alters both the oral and faecal microbiome. Further research will now be conducted to establish the significance of microbial alterations for animal health and performance.

Effects of global change on bird and beetle populations in boreal forest landscape: An assemblage dissimilarity analysis

AbstractAimDespite an increasing number of studies highlighting the impacts of climate change on boreal species, the main factors that will drive changes in species assemblages remain ambiguous. We study how species community composition would change following anthropogenic and natural disturbances. We determine the main drivers of assemblage dissimilarity for bird and beetle communities.LocationCôte‐Nord, Québec, Canada.MethodsWe quantify two climate‐induced pathways based on direct and indirect effects on species occurrence under different forest harvest management scenarios. The direct climate effects illustrate the impact of climate variables while the indirect effects are reflected through habitat‐based climate change. We develop empirical models to predict the distribution of 127 and 108 species under climate‐habitat and habitat‐only models, respectively, over the next century. We analyse the regional and the latitudinal species assemblage dissimilarity by decomposing it into balanced variation in species occupancy and occurrence and occupancy and occurrence gradient.ResultsBoth pathways increased dissimilarity in species assemblage. At the regional scale, both effects have an impact on decreasing the number of winning species. Yet, responses are much larger in magnitude under mixed climate effects. Regional assemblage dissimilarity reached 0.77 and 0.69 under mixed effects versus 0.09 and 0.10 under indirect effects for beetles and birds, respectively, between RCP8.5 and baseline climate scenarios when considering forest harvesting. Latitudinally, assemblage dissimilarity increased following the climate conditions pattern.Main conclusionsThe two pathways are complementary and alter biodiversity, mainly caused by species turnover. Yet, responses are much larger in magnitude under mixed climate effects. Therefore, inclusion of climatic variables considers aspects other than just those related to forest landscapes, such as life cycles of animal species. Moreover, we expect differences in occupancy between the two studied taxa. This could indicate the potential range of change in boreal species concerning novel environmental conditions.

Spatial and Temporal Diversity Variation in the Anopheles Communities in Malaria-Endemic Regions of Colombia.

This study aimed to evaluate at a temporospatial scale, the influence of anthropogenic land cover changes in the Anopheles species community composition and diversity in two Colombian malaria-endemic regions, Bajo Cauca and Pacific. To determine variations over time, mosquitoes were collected in two time periods; land cover types were characterized on orthorectified aerial photographs, and landscape metrics were estimated for each locality and period. A temporal dissimilarity analysis to evaluated species replacement and the nestedness species loss/gain showed the influence of the species loss or gain component on Anopheles species assemblage (23%). The relationship between land cover variation and Anopheles beta diversity, evaluated by regression analysis, showed the effect of forest variation in the Anopheles community (βsim and forest r2 = 0.9323; βsne and forest r2 = 0.9425). Furthermore, a canonical correspondence analysis showed that the land cover types associated with Anopheles species presence were bare soil, shrub, wet areas, and forest. Results demonstrated the impact of land cover changes attributed to human activities on Anopheles population dynamics, over time; this was evidenced as species loss or gain, which was specific to each locality. Notably, the main malaria vectors were dominant in most localities over time, suggesting their tolerance to anthropogenic transformations; alternatively, the environmental changes are providing adequate ecological conditions for their persistence. Finally, the data generated are relevant for understanding the impact that environmental change may have on the dynamics of the neotropical malaria vectors. Thus, this research has potential implications for vector control interventions.

Effect of oxygen deficiency on organic matter decomposition during the early stage of composting.

This study aimed to elucidate the recovery of organic matter decomposition after oxygen deficiency in the early stage was replaced by aerobic conditions during composting. Oxygen deficiency at the early stage was created by supplying nitrogen gas into the composting for 3days (LN3dA) and 5days (LN5dA). Subsequently, air was introduced until the end of composting instead of nitrogen gas. Runs LN3dA and LN5dA had lower organic matter decomposition by 10% and 19%, respectively, compared with fully aerobic composting (LA) after oxygen deficiency was changed to aerobic conditions. Compared with fully aerobic composting, composting with oxygen deficiency at the early thermophilic stage had a different bacterial community, as analyzed by high-throughput sequencing. During vigorous organic matter decomposition, Bacillus was dominant in Run LA, whereas Caldibacillus proliferated in Runs LN3dA and LN5dA. Bacillus thermoamylovorans, Bacillus arbutinivorans, and Bacillus kokeshiiformis were hypothesized to be inhibited by Caldibacillus. Moreover, dissimilarity analysis indicated that different bacterial communities remained until the end of composting, which could be a reason for the incomplete recovery of organic matter decomposition. As analyzed by the API-ZYM kit, the enzymatic activities were also different between all composting runs. One of the characterized enzymes, α-galactosidase, displayed low activity during oxygen deficiency and could not achieve high activity with sufficient oxygen until composting was completed. Overall, our study showed that oxygen deficiency at the early thermophilic stage caused incomplete recovery of organic matter decomposition.

Abundant denitrifying taxa rather than rare taxa responded more sensitively to temperature change in acidic paddy soils

Climate change has strong effects on the distribution of soil denitrifying bacterial communities; however, how temperature alter the stability of the abundant and rare denitrifying biosphere remains unknown. In this study, paddy soils were incubated under four temperatures (5 °C, 15 °C, 25 °C, and 35 °C) in 125% water-filled pore space for 96 h and nirS and nosZ genes were then sequenced via high-throughput sequencing. The results showed that both abundant and rare denitrifers responded to varying temperature, however, the abundant taxa were more sensitive. Firstly, for α-diversities of soil denitrifiers, temperature increase affected both abundant and rare taxa by reducing the richness (Chao1 index) of rare taxa and the evenness (Pielou index) of abundant taxa. When the temperature increased from 5 °C to 35 °C, the above indexes decreased about by 30%. However, with regard to community distribution pattern and co-occurrence network, abundant taxa apparently displayed higher sensitivity than rare taxa. Principal co-ordinate analysis (PCoA) indicated an obvious separation of the abundant nirS and nosZ genes with different temperatures, however, the clear separation of the rare taxa was only observed as temperature changed significantly. Bray-Curtis dissimilarity analysis further proved that the community structure differentiation was more significant for abundant taxa under the four temperature conditions. Co-occurrence network analysis revealed that abundant denitrifiers occupied more central locations in the network assembly. More importantly, the edge/node ratio and positive association percentage among abundant taxa increased with temperature increase, implying that abundant taxa possessed more frequent, presumably, more positive interaction under higher temperature. Whereas, the response of the above network topological properties of rare taxa was much weaker. Collectively, these results indicated that increasing temperature significantly affected soil abundant denitrifying taxa by lowering α-diversity, increasing interaction and changing the community structure. Whereas rare taxa were less vulnerable to warming. Accordingly, the abundant denitrifiers could act as “key indicators” to predict the response strategy of soil microorganisms to future global warming, while rare taxa no longer need excessive in-depth analysis.

Australian soil microbiome: A first sightseeing regional prediction driven by cycles of soil temperature and pedogenic variations.

Declines in soil multifunctionality (e.gsoil capacity to provide food and energy) are closely related to changes in the soil microbiome (e.g., diversity) Determining ecological drivers promoting such microbiome changes is critical knowledge for protecting soil functions. However, soil-microbe interactions are highly variable within environmental gradients and may not be consistent across studies. Here we propose that analysis of community dissimilarity (β-diversity) is a valuable tool for overviewing soil microbiome spatiotemporal changes. Indeed, β-diversity studies at larger scales (modelling and mapping) simplify complex multivariate interactions and refine our understanding of ecological drivers by also giving the possibility of expanding the environmental scenarios. This study represents the first spatial investigation of β-diversity in the soil microbiome of New South Wales (800,642 km2 ), Australia. We used metabarcoding soil data (16S rRNA and ITS genes) as exact sequence variants (ASVs) and UMAP (Uniform Manifold Approximation and Projection) as the distance metric. β-Diversity maps (1000-m resolution)-concordance correlations of 0.91-0.96 and 0.91-0.95 for bacteria and fungi, respectively-showed soil biome dissimilarities driven primarily by soil chemistry-pH and effective cation exchange capacity (ECEC)-and cycles of soil temperature-land surface temperature (LST-phase and LST-amplitude). Regionally, the spatial patterns of microbes parallel the distribution of soil classes (e.g., Vertosols) beyond spatial distances and rainfall, for example. Soil classes can be valuable discriminants for monitoring approaches, for example pedogenons and pedophenons. Ultimately, cultivated soils exhibited lower richness due to declines in rare microbes which might compromise soil functions over time.

Effects of altitude on the gut microbiome and metabolomics of Sanhe heifers.

Extreme environments at high altitudes pose a significant physiological challenge to animals. We evaluated the gut microbiome and fecal metabolism in Sanhe heifers from different altitudes. Twenty Sanhe heifers (body weight: 334.82 ± 13.22 kg, 15-month-old) selected from two regions of China: the Xiertala Cattle Breeding Farm in Hulunbeier, Inner Mongolia [119°57' E, 47°17' N; approximately 700 m altitude, low altitude (LA)] and Zhizhao Dairy Cow Farm in Lhasa, Tibet [91°06' E, 29°36' N; approximately 3,650 m altitude, high altitude (HA)], were used in this study. Fecal samples were collected and differences in the gut microbiota and metabolomics of Sanhe heifers were determined using 16S rRNA gene sequencing and metabolome analysis. The results showed that altitude did not significantly affect the concentrations of fecal volatile fatty acids, including acetate, propionate, butyrate, and total volatile fatty acids (p > 0.05). However, 16S rRNA gene sequencing showed that altitude significantly affected gut microbial composition. Principal coordinate analysis based on Bray-Curtis dissimilarity analysis revealed a significant difference between the two groups (p = 0.001). At the family level, the relative abundances of Peptostreptococcaceae, Christensenellaceae, Erysipelotrichaceae, and Family_XIII were significantly lower (p < 0.05) in LA heifers than in HA heifers. In addition, the relative abundances of Lachnospiraceae, Domibacillus, Bacteroidales_S24-7_group, Bacteroidales_RF16_group, Porphyromonadaceae, and Spirochaetaceae were significantly higher in HA heifers than in LA heifers (p < 0.05). Metabolomic analysis revealed the enrichment of 10 metabolic pathways, including organismal systems, metabolism, environmental information processing, genetic information processing, and disease induction. The genera Romboutsia, Paeniclostridium, and g_unclassified_f_Lachnospiraceae were strongly associated with the 28 differential metabolites. This study is the first to analyze the differences in the gut microbiome and metabolome of Sanhe heifers reared at different altitudes and provides insights into the adaptation mechanism of Sanhe heifers to high-altitude areas.

Application of the Law of Minimum and Dissimilarity Analysis to Regression Test Case Prioritization

Regression testing is one of the most expensive processes in testing. Prioritizing test cases in regression testing is critical for the goal of detecting the faults sooner within a large set of test cases. We propose a test case prioritization (TCP) technique for regression testing called <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LoM-Score</i> inspired by the Law of Minimum (LoM) from biology. This technique calculates the impact probabilities of methods calculated by change impact analysis with forward slicing and orders test cases according to LoM. However, this ordering doesn’t consider the possibility that consecutive test cases may be covering the same methods repeatedly. Thereby, such ordering can delay the time of revealing faults that exist in other methods. To solve this problem, we enhance the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LoM-Score</i> TCP technique with an adaptive approach, namely with a dissimilarity-based coordinate analysis approach. The dissimilarity-based coordinate analysis uses Jaccard Similarity for calculating the similarity coefficients between test cases in terms of covered methods and the enhanced technique called Dissimilarity-LoM-Score ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Dis-LoM-Score</i> ) applies a penalty with respective on the ordered test cases. We performed our case study on 10 open-source Java projects from Defects4J, which is a dataset of real bugs and an infrastructure for controlled experiments provided for software engineering researchers. Then, we hand-seeded multiple mutants generated by Major, which is a mutation testing tool. Then we compared our TCP techniques <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LoM-Score</i> and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Dis-LoM-Score</i> with the four traditional TCP techniques based on their Average Percentage of Faults Detected (APFD) results.

Dynamic monitoring and anomaly tracing of the quality in tobacco strip processing based on improved canonical variable analysis and transfer entropy.

Multivariate statistical monitoring methods are proven to be effective for the dynamic tobacco strip manufacturing process. However, the traditional methods are not sensitive enough to small faults and the practical tobacco processing monitoring requires further root cause of quality issues. In this regard, this study proposed a unified framework of detection-identification-tracing. This approach developed a dissimilarity canonical variable analysis (CVA), namely, it integrated the dissimilarity analysis concept into CVA, enabling the description of incipient relationship among the process variables and quality variables. We also adopted the reconstruction-based contribution to separate the potential abnormal variable and form the candidate set. The transfer entropy method was used to identify the causal relationship between variables and establish the matrix and topology diagram of causal relationships for root cause diagnosis. We applied this unified framework to the practical operation data of tobacco strip processing from a tobacco factory. The results showed that, compared with traditional contribution plot of anomaly detection, the proposed approach cannot only accurately separate abnormal variables but also locate the position of the root cause. The dissimilarity CVA proposed in this study outperformed traditional CVA in terms of sensitiveness to faults. This method would provide theoretical support for the reliable abnormal detection and diagnosis in the tobacco production process.

A PMF-SSD based approach for the source apportionment and source-specific ecological risk assessment of Le'an river in Jiangxi Province, China

Identifying the contamination characteristics of trace metals in river and targeting their corresponding potential contamination sources and source-specific ecological risk are of very importance for putting forward effective river environment protection strategies. Here, a detailed investigation was conducted to recognize the contamination and ecological risk characteristics of trace metals in Le'an River. To attain this objective, a PMF-SSD model (Positive Matrix Factorization-Species Sensitivity Distribution) was proposed to evaluate the ecological risk of trace metals in Le'an River. The positive matrix factorization (PMF) was employed to identify the potential source of trace metals in surface water and their corresponding contributions. The ecological risks of the sources were quantitatively calculated by PMF-SSD. In addition, the spatial dissimilarity analysis of the source contribution distributions was also conducted in this study. Results showed that the water environment in Jiangxi were considerably contaminated by trace metals (Cd, Cr, Co, Al, Mn, Cu, Zn and Ni). The concentrations of these trace metals in surface water demonstrated significant spatial variations and the ecological risk lay in high level. Mining activities were identified as the main anthropogenic sources, which should to be strictly regulated.

Bacterial communities vary across populations and tissue type in red mangroves (Rhizophora mangle, Rhizophoraceae) along an expanding front.

Plant-associated microbial communities may be important sources of functional diversity and genetic variation that influence host evolution. Bacteria provide benefits for their hosts, yet in most plant systems we know little about their taxonomic composition or variation across tissues and host range. Red Mangrove (Rhizophora mangle L.) is a vital coastal plant species that is currently expanding poleward and with it, perhaps, its microbiome. We explored variability in bacterial communities across tissues, individuals, and populations. We collected samples from six sample types from 5 to 10 individuals at each of three populations and used 16S rRNA gene (iTag) sequencing to describe their bacterial communities. Core community members and dominant bacterial classes were determined for each sample type. Pairwise PERMANOVA of Bray-Curtis dissimilarity and Indicator Species Analysis revealed significant differences in bacterial communities between sample types and populations. We described the previously unexplored microbiome of the reproductive tissues of R. mangle. Populations and most sample types were associated with distinct communities. Bacterial communities associated with R. mangle are influenced by host geography and sample type. Our study provides a foundation for future work exploring the functional roles of these microbes and their relevance to biogeochemical cycling.