Dissimilarity Values Research Articles

Detailed multivariate comparisons of environments with mobility oriented parity

Multivariate model projections onto conditions that differ from those under which the models were calibrated can result in uncertainty owing to response extrapolation. Therefore, interpretations of models transferred to conditions not analogous to those of model calibration must be done carefully to avoid misleading conclusions. A good practice when producing model transfers is to assess the degree of dissimilarity between calibration and transfer conditions. The mobility oriented parity (MOP) metric is a tool commonly used to quantify such dissimilarities. Our study elucidated the details of MOP, and expanded the interpretability of results when transfer conditions are not analogous to those of model calibration. We implemented a more detailed characterization of non-analogous conditions previously only identified as outside calibration ranges. In addition, we quantified the sensitivity of MOP to the density and position of reference conditions in environmental space, and explored the effect of sample size on MOP results. We show that detailed characterizations of non-analogous conditions can help to determine which variables are different between the two areas and how. This information can be used to understand causes of environmental dissimilarity and to identify variables that could be excluded from ecological niche modeling owing to extrapolation risks associated with them. Our results also show that dissimilarity values calculated in comparisons offer good indicators of how reliable interpretations can be in areas with conditions not analogous to those of reference. The tools developed and implemented in this study provide a useful, quantitatively efficient means of characterizing extrapolation uncertainty in model transfer studies, a best practice when using multivariate ecological niche models to make predictions about species’ distributions. An extended version of the mobility oriented parity metric helps identify variables for which risks of model extrapolations can be expected. Distinct MOP metrics used to characterize dissimilarity show comparable general patterns in transfer areas, despite differences in values. As MOP results are influenced by background sampling size, the definition of this sample should be aimed to appropriately characterize calibration areas.

Abstract A057: Superfund sites and cancer risk: Cluster analysis in Puerto Rican municipalities between 2010 and 2020

Abstract Introduction: Living within proximity to hazardous waste (superfund) sites can pose an increased risk of exposure to chemicals of concern, including cancerogenic substances. Per- square mile, Puerto Rico has a high density of contaminated sites, including the designation of 19 superfund sites by the Environmental Protection Agency across the archipelago. Understanding how living within proximity to superfund sites can help recognize communities that are at greater health risks, such as increased cancer risks. Objectives: Identify clusters and outliers for all types of cancer, to assess ecological risk, by the presence of superfund sites across Puerto Rico. Methods: All types of cancer were recorded and provided by the Puerto Rico Central Cancer Registry for the period of 2010-2020. This data was summarized by municipalities (n=78). Cancer cases in each county were aggregated and divided by population in 2020 to show prevalence of cases. Using geographical information systems (ArcGIS), a Local Moran’s I was run to identify potential municipalities that have clusters; location with similar high (hot spots) or low values (cold spots) and outliers; locations with dissimilar values from their surrounding neighbors. A layer representing municipalities with superfund sites was also applied to the map to see if there was a relationship between living in a superfund site and cancer risk. This study was approved by UPRCCC IRB Protocol #2023-11-124. Results: Between 2010 and 2020, a total of 114,560 diagnosis occurred for all types of cancer in PR, from which 48.06% accounted for females and 51.93% for males, with breast and prostate as the primary cancer sites, respectively. Our analyses showed one hotspot and three cold spots with statistically significant differences from their neighboring municipalities. One hotspot was in Canovanas (p=0.03) which has a superfund site related to pharmaceutical chemicals. The three coldspots were in Cataño (p=0.04), Trujillo Alto (p=0.04), and Guánica (p=0.03). Additionally, four high and low outliers were identified. Across the municipalities, in the lower outliers Vega Alta (p=0.04), Corozal (p=0.002) are the only ones with current Superfund sites. Cabo Rojo (p=0.002) and San German (p=0.006) are included in the list of higher outliers, which are places with superfund sites. However, Hormigueros (p=0.03), and Arroyo (p=0.03), are also in this category. Conclusion: The results identify the key cancer clusters and outliers across municipalities in comparison to neighboring municipalities on the island. Results show municipalities with and without Superfund sites as part of the higher outliers list, which additional research could help establish other contributing factors. Further analysis is needed to consider what factors affect the clusters such as age range, type of cancer, and presence of other environmental contaminants in the area. Acknowledgements: This research was supported by award 1R25CA240120-01 (Cancer Prevention & Control Research Training Program) from the National Cancer Institute. Citation Format: Sailing JT Tang, Nancy R. Cardona, Ana P. Ortiz. Superfund sites and cancer risk: Cluster analysis in Puerto Rican municipalities between 2010 and 2020 [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr A057.

The Use of MATLAB Programming to Compare Experimental vs Modeled PEMFCs using the Nernst and Butler-Volmer’s Equation-Based Mathematical Models

For the analysis of Proton Exchange Membrane Fuel Cell (PEMFC’s) efficiency, the Nernst equation and Butler-Volmer's concepts were used. The mathematical models using both equations were developed in MATLAB and compiled. The results generated by the output current based on the input parameters of the experimental data were compared with the experimental results for the two modelled PEMFCs. The parameters temperature, pressure, hydrogen concentration, and oxygen concentration at different values of external resistance were used to determine the change in output current in both models built in MATLAB. This sensitivity analysis generated negative output current values and highly dissimilar values with the experimental results for the same input parameters for both models due to the less use of input parameters in the model. The results showed that the PEMFC's performance is affected by most parameters, and many influencing parameters must be used to develop a perfect mathematical model of the PEMFC.

Dissimilarities of the demi-plié movement trajectory in its different roles in classical ballet

ABSTRACT Demi-plié is a coordinated dance movement involving knees bent while keeping hips turned out and heels grounded. It consists of descending and ascending phases, the latter often preparing for the next move. Task goals may influence its trajectory. Ten classical dancers (eight females, two males), aged 20–45 years old performed demi-plié itself and prior to pirouette en dehors, relevé, sauté, and sissonne fermée de côté. Lower limb and hip trajectory data were collected through a motion capture system. Time-series data were aligned across all conditions using a dynamic time warping algorithm. The Euclidean distance measured the hip trajectory between each ballet movement, providing a continuous dissimilarity function over time. Descriptive analysis focused on each participant’s maximum dissimilarity values across conditions. Results showed maximum hip trajectory differences of 40% for demi-plié before sauté, 30% before sissonne, 20% before relevé, and 10% before pirouette. Dissimilarities began in the descending phase of the demi-plié. ANOVAs for repeated measures and Bonferroni’s post-hoc showed that the standard deviation of dissimilarity had the largest effect size for the demi-plié – demi-plié before sauté, and the smallest for the demi-plié – demi-plié before pirouette. Demi-plié prior to jumps demands plyometric forces and has open-loop motor planning, requiring acceleration, whereas demi-plié is closed-loop, relying on proprioceptive updating.

MinION Sequencing of Fungi in Sub-Saharan African Air and a Novel LAMP Assay for Rapid Detection of the Tropical Phytopathogenic Genus Lasiodiplodia.

To date, there have been no DNA-based metabarcoding studies into airborne fungi in tropical Sub-Saharan Africa. In this initial study, 10 air samples were collected onto Vaseline-coated acrylic rods mounted on drones flown at heights of 15-50 meters above ground for 10-15 min at three sites in Ghana. Purified DNA was extracted from air samples, the internal transcribed spacer (ITS) region was amplified using fungal-specific primers, and MinION third-generation amplicon sequencing was undertaken with downstream bioinformatics analyses utilizing GAIA cloud-based software (at genus taxonomic level). Principal coordinate analyses based on Bray-Curtis beta diversity dissimilarity values found no clear evidence for the structuring of fungal air communities, nor were there significant differences in alpha diversity, based on geographic location (east vs. central Ghana), underlying vegetation type (cocoa vs. non-cocoa), or height above ground level (15-23 m vs. 25-50 m), and despite the short flight times (10-15 min), ~90 operational taxonomic units (OTUs) were identified in each sample. In Ghanaian air, fungal assemblages were skewed at the phylum taxonomic level towards the ascomycetes (53.7%) as opposed to basidiomycetes (24.6%); at the class level, the Dothideomycetes were predominant (29.8%) followed by the Agaricomycetes (21.8%). The most common fungal genus in Ghanaian air was cosmopolitan and globally ubiquitous Cladosporium (9.9% of reads). Interestingly, many fungal genera containing economically important phytopathogens of tropical crops were also identified in Ghanaian air, including Corynespora, Fusarium, and Lasiodiplodia. Consequently, a novel loop-mediated isothermal amplification (LAMP) assay, based on translation elongation factor-1α sequences, was developed and tested for rapid, sensitive, and specific detection of the fungal phytopathogenic genus Lasiodiplodia. Potential applications for improved tropical disease management are considered.

Genome identification and diversity analysis of banana (Musa spp.) from Jember based on morphological characters

Introduction: Banana plants are easy to find and grow in Indonesia, including in Jember. Banana production in Jember in 2020 increased by 50% and has the potential to be inventoried and developed. Information regarding the characteristics of various banana cultivars is needed for future banana breeding. This research was conducted to identify and classify the genome of bananas growing in Jember and determine the level of banana diversity. Methods: The banana exploration using a purposive sampling method. The observation of 15 morphological characters followed the method of Simmonds and Shepherd. Determination of the genome followed the method of Silayoi & Chamchalow and Singh & Uma. The kinship analysis uses cluster analysis using the average linkage method and Gower distance, by R Studio software. Results: There were 23 banana cultivars obtained in this research, consisting of 35% dessert bananas and 65% plantain types. Genome identification results in four genome groups, namely AA/AAA, AAB, ABB, and BB. Cluster analysis produces three main groups, where its branch is generally consistent with the genome grouping. The closest relationship is between Rayap and Seribu bananas (0.96), while the furthest is between Gaje and Agung bananas (0.38). The dissimilarity value for 23 banana cultivars is 0.36, or the similarity is 0.64. Conclusion: The 23 banana cultivars are closely related or have low diversity based on the 15 morphological characters observed. Further identification can be carried out with a greater number of morphological characters, accompanied by molecular identification.

Geomorphic Imprints of Active Tectonics of the Bikaner-Nagaur Petroliferous Rift Basin and its Surroundings (Western Rajasthan, India)

Abstract Geology of sedimentary rift-basins require strong geomorphic input for a proper interpretation of active tectonics. Rift-related sedimentation took place in western Rajasthan of the Indian shield, which includes the Bikaner-Nagaur basin (BNB) and a few other adjacent basins. The sedimentation history of the BNB includes Proterozoic, Cambrian, Permo-Carboniferous and from Paleocene to the Recent. This study analyses river profiles with the best-fit curve (R2) model for the BNB and the surrounding regions. The research shows that the watershed 3 within the study area is most active tectonically, through which multiple faults and lineaments pass. Hypsometric Curves (HCs) of watersheds 1, 2 and 3 indicate that these watersheds are tectonically active. This inference is based on the concave profiles of HCs at the head, and convex profiles of HCs at the body and toe sections. Clustering of sixty segments (S) of the considered rivers based on linear-scale morphometric parameters, e.g., sinuosity index (SI), stream length gradient index (SL) and concavity (θ) enabled segment-wise comparison of river profiles with similar values. These segments were compared pair-wise, and Euclidean-based dissimilarity (dR) values were calculated between each such pair. The findings too imply that tectonic activeness exists in parts of watersheds 1, 2 and 3. The channel flow lines are controlled by faults/lineaments as per the micro-scale examination of the drainage network and faults/ lineaments analysis. Under structural control, nine major geomorphic units emerged with distinct erosional surfaces, denudational hillocks, dissected hills and inselbergs. Detailed geomorphic map with micro-scale studies revealed a slope retreat process that resulted in landforms viz., pediment, pediment slope and active flood plains.

Combined benthic and stream edge sampling better represent macroinvertebrate assemblages than benthic sampling alone along an aridity gradient

AbstractStudies of stream macroinvertebrates traditionally use sampling methods that target benthic habitats. These methods could underestimate biodiversity if important assemblage components exist outside of the benthic zone. To test the efficacy of different sampling methods, we collected paired reach‐wide benthic and edge samples from up to 10 study reaches in nine basins spanning an aridity gradient across the United States. Edge sampling targeted riparian‐adjacent microhabitats not typically sampled, including submerged vegetation, roots, and overhanging banks. We compared observed richness, asymptotic richness, and assemblage dissimilarity between benthic samples alone and different combinations of benthic and edge samples to determine the magnitude of increased diversity and assemblage dissimilarity values with the addition of edge sampling. We also examined how differences in richness and assemblage composition varied across an aridity gradient. The addition of edge sampling significantly increased observed richness (median increase = 29%) and asymptotic richness (median increase = 173%). Similarly, median Bray–Curtis dissimilarity values increased by as much as 0.178 when benthic and edge samples were combined. Differences in richness metrics were generally higher in arid basins, but assemblage dissimilarity either increased or decreased across the aridity gradient depending on how benthic and edge samples were combined. Our results suggest that studies that do not sample stream edges may significantly underestimate reach diversity and misrepresent assemblage compositions, with effects that can vary across climates. We urge researchers to carefully consider sampling methods in field studies spanning climatic zones and the comparability of existing data sets when conducting data synthesis studies.

Methods for evaluation of corrosion rate on magnesium alloys: a review

The major drawback of some magnesium alloys is their low corrosion resistance. Therefore, the evaluation of corrosion resistance is a critical factor in developing new alloys and surface treatments. The techniques employed for the determination of corrosion rate include mass loss assessment, hydrogen evolution, potentiodynamic polarization, and electrochemical impedance spectroscopy (EIS). However, there are still difficulties in precisely estimating this parameter in Mg alloys. In this review, the reported applications, advantages, and disadvantages of the techniques mentioned above were analyzed. On the other hand, a large number of corrosion rate values reported for various Mg alloys in 3 different media (NaCl, Hanks´ solution and SBF), using mass loss, hydrogen evolution, and PP, were compared and analyzed. Generally, corrosion rates obtained from mass loss are higher than those obtained from hydrogen evolution. On the other hand, it is not possible to obtain correlations between corrosion rates obtained from PP and those obtained from mass loss and hydrogen evolution. Even more, dissimilar corrosion rate values are reported for the same alloy, implying that the measuring procedures are not well standardized.

Factors affecting abundance and primary productivity of phytoplankton in a wetland ecosystem of Bangladesh

Wetlands are the most productive, economically important and hydrologically variable ecosystems. In this study, the abundance of phytoplankton and its primary productivity were evaluated in Dingapota Haor of Bangladesh. A total of 41 phytoplankton genera belong to Chlorophyceae (15), Bacillariaophyceae (14), Cyanophyceae (8) and Euglenophyceae (4) were recorded whereas Bacillariaophyceae (37.02%) was the most dominant. The highest cell density (22.71×104 cell L–1) was recorded in pre-monsoon. Diversity indices were also significantly higher in pre-monsoon. The species diversity, evenness and richness varied from 2.51–3.79, 0.57–0.90 and 4.65–7.50 respectively. Difference in phytoplankton assemblage with an overall average dissimilarity value of 52.56 % was recorded. Cyclotella (3.60%), Bacillaria (3.13%), Volvox (2.95%), Spirulina (2.92%) and Euglena (2.88%) were the five most contributory species to the seasonal variation. Gross Primary Production, Net Primary Production and Community Respiration values ranged from 0.90–2.49, 0.68–1.60 and 0.35–0.89 mgCm–3day–1 respectively. Alkalinity and Chl-a showed significant positive correlation with GPP, NPP and CR. Pre-monsoon was the most productive phase whereas the monsoon season was the least productive. The current study produced valuable baseline data that will aid in the formulation of wetland conservation and management strategies.

One-Shot Learning Menggunakan Siamese Neural Network Untuk Pendeteksian Wajah

One-Shot Learning using Siamese Neural Network is a method used for facial recognition, this method implements a deep learning algorithm which allows facial detection using one single image. This research aims to extract features from the images and calculate the dissimilarity of each compared images. This research uses Convolutional Neural Network (CNN) to perform feature extraction, where the images will be divided into two pairs and fed into two different CNN networks, then calculate the Eucledian Distance to measure similarity, calculate Contrastive Loss, and train Siamese Network to produce accurate results. The results of this research show that the algorithm can produce accurate results with high mean dissimilarity value for non-similar images and low mean dissimilarity value for similar images.

Empirical evidence supporting the inclusion of multi-axes segregation in assessing US county health

To facilitate community action toward health equity, the County Health Rankings & Roadmaps program (CHR&R) assigns health rankings to US counties. The CHR&R conceptual model considers White-Black and White-non-White dissimilarity values to represent residential segregation as part of the family and social support subcomponent. As the US is greying and becoming more multi-racial-ethnic, the two-group White-centered segregation measures are inadequate to capture segregation among population subgroups in the US. Thus, we evaluate the relevancy of segregation measures that consider multiple racial, ethnic, and age groups in assessing US county health. Besides using the two-group dissimilarity index to measure White-centered racial segregation as conceptualized by CHR&R, the study also uses the multi-group generalized dissimilarity index to measure racial-ethnic-age segregation by counties, employing both aspatial and spatial versions of these measures. These indices are computed for counties using the 2015–2019 American Community Survey data at the census tract level. Descriptive statistics and regressions controlling for sociodemographic factors and healthcare access are used to assess the contributions of individual segregation measures to mortality (life expectancy, years of potential life lost and premature mortality) and morbidity (frequent mental distress, frequent physical distress, and low birth weight) indicators representing county health.Overall, correlations between these indicators and most segregation measures are significant but weak. Regression results show that many segregation measures are not significantly related to mortality indicators, but most are significantly associated with morbidity indicators, with the magnitudes of these associations higher for the multi-group racial-ethnic-age segregation index and its spatial version. Results provide evidence that racial-ethnic-age segregation is associated with county-level morbidity and that spatial measures capturing segregation of multiple population axes should be considered for ranking county health.

Beyond fallacies: violent conflicts globally and in muslim countries

This article explores the relationship between key economic development indicators and the occurrence of violent civil conflicts. It examines public policy failures and mistakes which link with onset of conflicts. Two sets of 160 countries are included to empirically analyse the determinants of conflicts. This analysis extends to two distinctive subsets of Muslim countries. The paper establishes that the classification procedure of violent conflicts matters—varying classifications offer dissimilar values to similar predictors. Here, our conclusions are contrary to the much emphasized ‘greed motivation’ to rebel, which dismisses strong linkages of ‘grievances’ like low income, economic development failures and political repression with intrastate violent conflicts. The paper also infers limitations in country level data—which cross-country studies employ—income and unemployment data are non-reflective of conflict regions and of horizontal inequalities. We stress region and country specific research.

The effect modification of greenspace and impervious surface on the heat-mortality association: Differences by the dissimilarity index

Recent studies have shown that heat-mortality risk differs by level of greenspace and impervious surface. However, these studies do not consider both green spaces and impervious surfaces simultaneously, and further did not fully consider community- and individual-level characteristics. In this study we explored the effect modification of greenspace and impervious surface on the association between heat and mortality and how it differs by race/ethnicity dissimilarity index levels in North Carolina, USA. We aggregated datasets for greenspace, impervious surface estimates, temperature, and mortality for 1275 census tracts for North Carolina, USA, for 2000 to 2016 for 5 warm months (May to September). We used distributed lag non-linear models to estimate the heat-mortality relationship in each census tract. Heat-mortality relative risk (RR) was higher for census tracts with low greenspace than high greenspace (RR comparing risk at 99th temperature and minimum mortality temperature: 1.08 (1.02, 1.15) for low greenspace and 0.97 (0.87, 1.08) for high greenspace). Heat-mortality RR was higher for tracts with high impervious surface than low impervious surface (1.04 (1.00, 1.09) for high impervious surface and 0.94 (0.84, 1.05) for low impervious surface). Census tracts with high dissimilarity value and low greenspace had the highest heat-mortality risk compared to the tracts with high dissimilarity value with and high greenspace (1.13 (1.02, 1.24) for high dissimilarity index and 0.97 (0.86, 1.09) for low dissimilarity index). Communities with low greenspace or high impervious surfaces had higher heat-mortality associations, and this effect modification was higher for high race/ethnicity dissimilarity regions.

Evaluating diffusion in policy designs: A study of net metering policies in the United States

AbstractIn the United States, some of the most important environmental policy innovations of the past decades have occurred at the state level. Net metering policy is one kind of policy that states have widely adopted in support of decarbonization goals. The widespread adoption of net metering policies varying in policy design, defined here as policy content, offers an opportunity to investigate to what extent policies that diffuse widely bear comparable designs, and furthermore, what factors influence diffusion in policy designs. Availing these opportunities, in this paper, we investigate (1) how (dis‐)similar the designs of American states' original net metering policies were; and (2) what factors explain the diffusion of policies that share similar design elements. To support our investigation, we model using event history analysis in a directed dyad setting, the factors that explain differential duration to adoption of net metering legislation containing specific elements of design by policy receiver states. We find that bipartisan legislatures are more likely to adopt the majority of design elements. This suggests that net metering appeals to policy makers across the political spectrum and that the latter compromise in integrating elements of policy design that benefit or burden different constituents. We also find that over time, states become less likely to emulate policy designs from jurisdictions whose citizenry embraces dissimilar values, suggesting that policy makers learn to tailor incentives to their local policy targets.

Self-Disclosure and Respect: Understanding the Engagement of Value Minorities

Organizations benefit from including employees with dissimilar values and perspectives, but their ability to realize these benefits is constrained by the degree to which those holding the dissimilar values (i.e., value minorities) feel comfortable engaging with their colleagues and the work of the collective. We extend theory on value dissimilarity by directly examining the experience of individuals whose values are dissimilar from those of their colleagues, and factors driving their engagement in work. Our examination spanned three studies: a laboratory experiment, a vignette study of employed adults, and a three-wave survey of student project groups. We found that the negative relationship between holding dissimilar values from one’s colleagues and engagement was lessened when value minorities disclosed personal information unrelated to their dissimilar values (Studies 1–3). Self-disclosure also moderated the negative relationship between value dissimilarity and feeling respected by one’s colleagues (Studies 2 and 3). Furthermore, felt respect mediated the effect of value dissimilarity on engagement, and this indirect effect was moderated by self-disclosure (Studies 2 and 3). Overall, this research is relevant to organizations seeking to capitalize upon the benefits of minority perspectives in the workforce but suggests that a critical first step is to prioritize the experience of value minorities and the decreased sense of social worth that can accompany this experience. By fostering an environment conducive to self-disclosure, organizations can help to alleviate the discomfort associated with value dissimilarity, thereby ensuring that all people, including the value minority, feel respected and are maximally engaged at work. Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2021.15768 .

Prevalence of yam nematodes in diverse soil communities, and their morphometrics in the Krachi-Nchumuru District of Ghana

Yam (Dioscorea spp.) is susceptible to dry rot disease, which limits its yields in farmers fields in West Africa.The objective of this study was to assess the occurrence and characteristics of the plant-parasitic nematode (Scutellonema bradys) on yam from the Volta Region of Ghana. A survey was conducted in KrachiI-Nchummuru District in the Volta region in Ghana, using a semi-structured questionnaire in ten communities. Majority of the farmers (62%) were unaware of nematodes and their damage caused to yam. Most interviewees (84%) mentioned the ‘pona’ yam variety as the most susceptible genotype to rot, especially in storage. Twelve nematode genera were identified in soils, and eight under storage conditions. Soil samples had, for relative abundance, 31.5% of nematodes as Scutellonema bradys and 16.8% as Meloidogyne spp. On the other hand, relative abundances in yam peels for S. bradys, Meloidogyne spp. and Pratylenchus spp. were 88.4, 6.0 and 3.3%, respectively. Body lenghts of female S. bradys ranged from 747.3 to 861.9 um. There was a strong positive correlation between tail length and head region diameter (r = 0.81); and stylet knob height and vulva position (r= 0.68). Agglomerative hierarchical clustering (AHC) showed 5 major groups at a dissimilarity of 90%, with sub-groups formed at dissimilarity value of 50%. In-depth survey of communities in the Krachi Nchumuru district revealed that, Scutellonema bradys is a threat to yam production in this region, and results in considerable dry rot disease and yield losses.

A survey of testicular texture in canine ultrasound images.

Computer-based texture analysis provides objective data that can be extracted from medical images, including ultrasound images. One popular methodology involves the generation of a gray-level co-occurrence matrix (GLCM) from the image, and from that matrix, texture fractures can be extracted. We performed texture analysis on 280 ultrasound testicular images obtained from 70 dogs and explored the resulting texture data, by means of principal component analysis (PCA). Various abnormal lesions were identified subjectively in 35 of the 280 cropped images. In 16 images, pinpoint-to-small, well-defined, hyperechoic foci were identified without acoustic shadowing. These latter images were classified as having "microliths." The remaining 19 images with other lesions and areas of non-homogeneous testicular parenchyma were classified as "other." In the PCA scores plot, most of the images with lesions were clustered. These clustered images represented by those scores had higher values for the texture features entropy, dissimilarity, and contrast, and lower values for the angular second moment and energy in the first principal component. Other data relating to the dogs, including age and history of treatment for prostatomegaly or chemical castration, did not show clustering on the PCA. This study illustrates that objective texture analysis in testicular ultrasound correlates to some of the visual features used in subjective interpretation and provides quantitative data for parameters that are highly subjective by human observer analysis. The study demonstrated a potential for texture analysis in prediction models in dogs with testicular abnormalities.

Ecological habitat quality assessment of a highly urbanized estuary using macroinvertebrate community diversity and structure

Urban estuaries are subject to a variety of ecological crises caused by humans as a result of rising shore-based human activities. In this study, environmental variables, community composition, structure and diversity indices of benthic macroinvertebrate were studied to assess the ecological health status of an urbanized estuary, Karnaphuli river estuary. The results revealed that dissolved oxygen (DO) was very low, and organic matter was much higher in the estuary. There were significant (p < 0.05) differences among the environmental variables across the sites. 31 taxa were identified yielding a total of 49167 Ind./m2 with overall mean density (±SD) of 159 (±327) Ind./m2. Annelida (61.8%) were the most abundant taxonomic group followed by Polychaeta (34.88%) and Oligochaeta (26.92%). The high abundance of pollution indicator taxa (Tubificidae, Capitellidae) and low abundance of pollution sensitive taxa (Lumbrinidae, Sabellidae, Maldanidae, Nephtyide) indicated detrimental ecological condition. The values of Shannon-Wiener diversity index (1.95–2.63), Pielou’s evenness index (0.60–0.81) and the Margalef diversity index (1.03–2.12) suggested moderate pollution status with extremely low species richness and low abundance in polluted areas. A PERMANOVA showed significant differences in faunal assemblages (F = 2.189, p < 0.001) among sites. Species abundance and density were higher (p = 0.32) at the upper estuary (where pH and salinity were low) and reduced in the middle and lower portion of the estuary which reflected the gradient of pollution level. Cluster analysis (CA) demarcated three distinct communities in terms of species similarity. SIMPER identified the highest average dissimilarity value (66.66%) across all the stations. The Canonical Correspondence Analysis (CCA) results suggested benthic macroinvertebrate community was influenced by environmental variables, for instance, salinity, dissolve oxygen, soil and water pH, total dissolved solids, and sediment texture.

A comprehensive array of gray matter labels for the MIITRA atlas: Interoperability with complementary atlases

AbstractBackgroundA comprehensive array of gyral‐based,cytoarchitecture‐based,and functional connectivity‐based gray matter labels were constructed in the Multichannel Illinois Institute of Technology &amp; Rush university Aging (MIITRA) atlas space in order to enhance the functionality of the atlas and its interoperability with complementary atlases.MethodT1w images from the 400 older adults included in the construction of the MIITRA atlas (50%male;64.9‐98.9 years of age) were processed with Freesurfer’s standard recon‐all pipeline. The Freesurfer outputs for all images were manually edited. Parcellations from Yeo,Desikan‐Killiany,HCP‐MMP,Brainnetome,Brodmann,Destrieux,Campbell,Flechsig,Mindboggle,Kleist,Smith,and EconomoCT atlases were projected onto the surface of each image and then converted to volumetric labels. The T1w images were also nonlinearly registered using ANTs‐SyN to the MNI152‐6thgen,MNI‐Colin,and the MNI‐2009b templates, and volumetric labels from Harvard‐Oxford,Julich,AAL3,Buckner,CoBrALab,CAREN,Striatum‐subdivision and Hippocampal‐subfields atlases were warped to the space of each image. The ANTs‐derived transformations applied on individual T1w images to build the MIITRA T1w template were used to map the corresponding gray matter labels from raw space to exact physical locations in the final MIITRA space. The performance of the MIITRA gray matter labels in segmentation of the gray matter of a separate group of 100 older adult individuals was evaluated in terms of label overlap, geometry, and dissimilarity when comparing the MIITRA labels warped to each individual’s space, to the respective reference labels from the source atlases.ResultExamples of the gray matter labels in MIITRA space are shown in Figure1. The measures of overlap between the warped and reference labels for each set of labels were generally high, with an average Dice coefficient of 0.78±0.3, average Jaccard coefficient of 0.59±0.27(Fig.2), sensitivity of 0.74±0.1, and specificity of 0.86±0.35(Fig.3). The label geometry showed a high correlation both in terms of the average volume of each label(correlation coefficient = 0.997,p‐value&lt;10−10) and in terms of the average surface area of each label(correlation coefficient = 0.991,p‐value&lt;10−10)(Fig.4). The values of dissimilarity were low, with an average volume error of 0.38±0.2(Fig.5).ConclusionThe gray matter labels in the MIITRA, in combination with the high‐resolution T1w template of the atlas, allowed segmentation of the gray matter of older adults that is in good agreement with the reference labels from the source atlases.