Population Centers Research Articles

Temporal and Spatial Dynamics of Carbon, Nitrogen, and Phosphorus in a Subtropical Urban River (Tamanduateí River, São Paulo, Brazil)

Water quality in urban streams often reflects the broader environmental challenges posed by dense population centers, where pollution from untreated sewage and runoff can significantly degrade ecosystems. This study examines the spatial and temporal variations of carbon, nitrogen, and phosphorus concentrations in the Tamanduateí River, which runs through the Metropolitan Region of São Paulo, Brazil. Data were sourced from the annual reports of the Environmental Company of the State of São Paulo (CETESB) covering the period from 2011 to 2022. Between 2011 and 2017, carbon and phosphorus concentrations declined, likely due to sanitation improvements. However, since 2017, these concentrations have been rising again, indicating renewed pollution inputs, primarily from untreated sewage. Nitrogen levels remained consistently high, with elevated concentrations observed upstream, linked especially to domestic effluent discharges. The recent increase in phosphorus levels is also of concern. The absence of spatial variation in phosphorus suggests diffuse pollution from urban areas, while nitrogen decreases downstream, possibly due to biological assimilation. The study underscores the pressing need for enhanced sewage management. Drawing from the successful revitalization of the Cheonggyecheon stream in Seoul, implementing nature-based solutions and regular maintenance could effectively reduce nutrient pollution and improve water quality, facilitating the restoration of the Tamanduateí River.

Analysis of Building Distribution and Accessibility of Kanigoro Urban Roads

The Kanigoro Settlement Area's land is mostly utilized for residential and agricultural purposes. Modifications to the city's construction and development are necessary to turn Kanigoro into a sustainable urban region, particularly in the field of urban morphological pattern development. City or area morphology may be analyzed using three primary components: building density, land use patterns, and road network patterns. This research aims to investigate the urban morphology pattern in Kanigoro Urban Area, focusing on road accessibility and building dispersion. In order to accomplish this goal, land use and building distribution were identified using satellite image data from 2011, 2015, 2019 and 2023, along with questionnaire data on residential location selection. The findings demonstrate that elongated patterns dominate settlement patterns in Kanigoro, with group patterns and the main road network following closely behind. Kinship and historical factors also play a role in this pattern. During the study, there was a notable increase in settlement growth, particularly on main transportation routes. The population density analysis shows that there is a concentration of population in the city center and some rapidly developing residential areas as a result of this rapid settlement growth. According to the road accessibility analysis, most areas are served by arterial roads, but there are still some areas with limited accessibility, especially with regard to collector roads. Based on the research results, there is a need for sustainable integrated spatial planning, adequate infrastructure, improving the quality of the collector road network and developing integrated public transportation.

A critical comparative study of the performance of three AI-assisted programs for bone age determination.

To date, AI-supported programs for bone age (BA) determination for medical use in Europe have almost only been validated separately, according to Greulich and Pyle (G&P). Therefore, the current study aimed to compare the performance of three programs, namely BoneXpert, PANDA, and BoneView, on a single Central European population. For this retrospective study, hand radiographs of 306 children aged 1-18 years, stratified by gender and age, were included. A subgroup consisting of the age group accounting for 90% of examinations in clinical practice was formed. The G&P BA was estimated by three human experts-as ground truth-and three AI-supported programs. The mean absolute deviation, the root mean squared error (RMSE), and dropouts by the AI were calculated. The correlation between all programs and the ground truth was prominent (R2 ≥ 0.98). In the total group, BoneXpert had a lower RMSE than BoneView and PANDA (0.62 vs. 0.65 and 0.75 years) with a dropout rate of 2.3%, 20.3% and 0%, respectively. In the subgroup, there was less difference in RMSE (0.66 vs. 0.68 and 0.65 years, max. 4% dropouts). The standard deviation between the AI readers was lower than that between the human readers (0.54 vs. 0.62 years, p < 0.01). All three AI programs predict BA after G&P in the main age range with similar high reliability. Differences arise at the boundaries of childhood. Question There is a lack of comparative, independent validation for artificial intelligence-based bone age estimation in children. Findings Three commercially available programs estimate bone age after Greulich and Pyle with similarly high reliability in a central European cohort. Clinical relevance The comparative study will help the reader choose a software for bone age estimation approved for the European market depending on the targeted age group and economic considerations.

Cities Shape the Diversity and Spread of Nonnative Species

The globalization of trade and increased human mobility have facilitated the introduction and spread of nonnative species, posing significant threats to biodiversity and human well-being. As centers of global trade and human populations, cities are foci for the introduction, establishment, and spread of nonnative species. We present a global synthesis of urban characteristics that drive biological invasions within and across cities, focusing on four axes: (a) connectivity, (b) physical properties, (c) culture and socioeconomics, and (d) biogeography and climate. Urban characteristics such as increased connectivity within and among cities, city size and age, and wealth emerged as important drivers of nonnative species diversity and spread, while the relative importance of biogeographic and climate drivers varied considerably. Elaborating how these characteristics shape biological invasions in cities is crucial for designing and implementing strategies to mitigate the impacts of invasions on ecological systems and human well-being.

Delineating genomic features for wild guanaco conservation

Abstract The South American fauna has endured challenges such as illegal hunting, cattle expansion, climate change, and landscape fragmentation. Despite ongoing conservation efforts that aim to address these issues, genetic diversity remains overlooked. We genotyped 126 Lama guanicoe individuals from an area of 2 million km2 in Patagonia and Cuyo using the 60K SNPs Axiom-Camelids, and we assessed population viability through genetic diversity, inbreeding, and population size. We then explored population connectivities through network analyses, genetic differentiation, and Bayesian approaches. Our findings reveal six genetic clusters: Cuyo, Somuncura, North Patagonia, Central Patagonia, South Patagonia, and Tierra del Fuego Island (TDFI). Cuyo and TDFI guanacos differed from others due to isolation-by-distance and geographical barriers, respectively. Cuyo exhibited the highest degree of allele conservation, but TDFI faced heightened vulnerability due to isolation and increased homozygosity. Sharp bottlenecks in Cuyo and North Patagonia coincided with the expansion of sheep farming, while bottlenecks in the other populations occurred during the Little Ice Age. North Patagonia acted as a probable contact zone, facilitating mixing of the Cuyo, Somuncura, and Central Patagonia populations. The Central and South Patagonian populations presented the highest gene flow. Thus, genomic advances help to define distinct conservation units (genetic stocks) to guide management practices and decisions.

Stability and reliability of regional cumulative impact mapping: A Canadian Pacific case study

Cumulative impact mapping is a commonly applied spatial representation of the impacts of human activities on the ocean. This spatial model has been applied at varying scales around the world, in part due to its ability to visually communicate complicated information in a simple way. The application of the model to decision-making processes requires an understanding of the reliability and stability of its outputs. This paper represents both an updated regional application in Pacific Canada and an evaluation of the tool over two iterations, 2015 and 2023. The regional application utilised higher model resolution and new and improved data inputs including 38 habitats and 46 activities across five sectors. High impact hotspots were found around major population centres and ports, as well as in fishing and shipping areas along the continental shelf. Commercial fishing, shipping, and climate change (sea surface temperature change) remained the major drivers of cumulative impacts in the region, and cumulative impacts per unit area continued to be highest in kelp and seagrass. Results suggest evidence of decreased impacts where improved protection for sponge reefs were implemented but show an overall increase in cumulative impacts for the region. Results showed consistency and reliability in the location of cumulative impact hotspots. Refinements in data quality and resolution of spatial data inputs contributed towards increasing the spatial precision of hot spot areas identified. Confidence in the cumulative impact mapping outputs and applications for marine spatial planning, marine protected area designation and management, research, and decision support are discussed.

The legality of roads in Chile, 1842–1969: A historical overview

Currently, no academic work examines the history of the legality of roads in Chile during its independent existence as a sovereign country. Addressing this gap in the literature, this paper focuses specially on the period from 1842 to 1969, when different actors articulated a set of guiding ideas about the duties of the state and the legal powers of the administrative authority in terms of planning, construction and management of road infrastructure that would allow connectivity between population centers and across regions, according to the ideas and resources available at their historical time. This historical overview of Chilean “road law” is done in the light of insights and questions of contemporary intellectual history and institutional history. In this regard, it is argued that the evolution of road infrastructure norms and institutions during the period under study can be divided into three historical regimes, based on their fundamental legislative milestones, guiding ideas, institutional settings, and strategies of state action: from 1842 to 1887, a period of a decentralized “minimal road state” with precarious roads characterized by both material and juridical uncertainty; from 1887 to 1920, the emergence of a “proto-developmentalist road state” intent on strengthening its grip on the nationwide road infrastructure; and from 1920 to 1969, a period of a “techno-developmentalist road state” that created a nationwide paved road network for the new technology of mobile vehicles.

Modelling monetary and non-monetary flows of recreational ecosystem services in Germany.

While policy interest and research on recreational ecosystem services (RES) has increased substantially, insights into the actual flows of benefits to people have remained scarce, especially at levels beyond local communities. This paper aims to model RES Flows and Benefits for Germany in monetary and non-monetary terms. We use Germany as a case study due its diversity of landscapes and availability of relevant spatial and empirical data. We develop and apply an assessment approach that considers RES Demand and Supply based on user preferences. Our results show distinct demand-supply matches and mismatches, for example in southwest Germany, and highest flows near population centres. Monetary benefits are highest in counties with high RES Supply that are close to densely populated areas. Our results can usefully inform planning and decision-making, for example to improve and further justify destination management, landscape development, and investments in RES at local, regional, and national levels.

Incident atrial fibrillation prediction using ECG-based deep learning at a specialized tertiary cardiac care center

Abstract Background Deep learning (DL) applied to electrocardiograms (ECG) is an emerging modality in the prediction of incident atrial fibrillation or atrial flutter (AF). The generalizability of such methods to a tertiary heart center (THC) population has not yet been formally explored. Purpose Evaluate the performance of DL in predicting 5-year incident AF using a resting 12-lead ECG in sinus rhythm acquired at a THC. Methods In a retrospective study, we examined 1.4 million ECGs acquired from over 250,000 adults at a THC between 2004 and 2022. ECGs were excluded if they were performed within 30 days of cardiac surgery, captured a rhythm other than sinus rhythm, or were acquired in patients with pre-existing AF. Incident AF at 5 years was modelled as a binary outcome and was determined on the basis of available outpatient and inpatient clinical databases and ECG diagnoses. Included ECGs were randomly split by distributing patients into training (70%), validation (10%), and test (20%) sets. A ResNet-50 model was trained using the training set. Hyperparameters were optimized using the validation set. The tuned model's performance is reported on the test set. The results at the patient level were derived by averaging the model's probability outputs for ECGs grouped according to both their AF outcome and the patient's identity. Bootstrapping was used to report confidence intervals (CI). Sensitivity and specificity are reported at a classification threshold based on the Matthews correlation coefficient. Saliency maps were used to enhance the model’s explainability. Results A total of 669,782 ECGs (47% of the screened ECGs) were included among 145,323 patients. Mean age was 63±15 years and 62% were male. The 5-year incident AF outcome was observed in 12% of ECGs and 16% of patients. The performance of the tuned model was first evaluated at the ECG level on the test set demonstrating an area under the receiver operating curve (AUC) of 0.75 (95% CI: 0.745-0.753) and an integrated calibration index of 0.009 (95% CI: 0.008-0.011). When testing the model at the patient level to simulate a deployment scenario, the AUC improved to 0.78 (95% CI: 0.768-0.783) with a sensitivity of 50% (95% CI: 49-52) and specificity of 87% (95% CI: 86.5-87.3). Stratified results by sex showed a better AUC in females, 0.81 (95% CI: 0.80-0.82), compared to males, 0.75 (95% CI: 0.74-0.76). Subgroup analyses revealed a trend of improved performance at the patient level with an increasing number of ECGs. Saliency maps highlighted the P-wave area as having the highest influence on the model’s prediction, thereby enhancing the model’s plausibility and explainability. Conclusion A unimodal ECG-based deep learning model showed promising 5-year incident AF prediction performance in a cohort of all-comer patients at a tertiary heart center. Further studies could explore the use of multimodal prediction models that integrate ECGs with other clinical and imaging data.

Global invasion history with climate-related allele frequency shifts in the invasive Mediterranean fruit fly (Diptera, Tephritidae: Ceratitis capitata)

The Mediterranean fruit fly (Ceratitis capitata) is a globally invasive species and an economically significant pest of fruit crops. Understanding the evolutionary history and local climatic adaptation of this species is crucial for developing effective pest management strategies. We conducted a comprehensive investigation using whole genome sequencing to explore (i) the invasion history of C. capitata with an emphasis on historical admixture and (ii) local climatic adaptation across African, European, Central, and South American populations of C. capitata. Our results suggest a stepwise colonization of C. capitata in Europe and Latin America in which Mediterranean and Central American populations share an ancestral lineage. Conversely, South American invasion history is more complex, and our results partly suggest an old secondary invasion into South America from Europe or a colonization of South America directly from Africa, followed by admixture with an European lineage. Throughout its invasive range, C. capitata is challenged with diverse climatic regimes. A genome wide association study identified a relationship between allele frequency changes and specific bioclimatic variables. Notably, we observed a significant allele frequency shift related to adaptation to cold stress (BIO6), highlighting the species’ ability to rapidly adapt to seasonal variations in colder climates.

Proposing new lipoprotein (a) cut off value for Kazakhstan: pilot study.

There is no consensus on the optimal concentration of lipoprotein(a) (Lp(a)) for the risk of atherosclerotic cardiovascular diseases (ASCVD) and aortic valve stenosis. In various clinical guidelines and agreed documents, the threshold level of Lp (a) is 30 mg/dl or 50 mg/dl. We estimated the cut-off value of Lp (a) associated with the risk of developing various localizations of atherosclerosis for the Central Asia, including Kazakhstani population. This study was conducted at National Research Cardiac Surgery Center, Kazakhstan. 487 patients were included, of which 61.3% were men. The mean age of all participants was 57.3 ± 12.6 years. Bivariate and multivariable logistic regression analysis was used to study the relationship between risk factors and plasma lipoprotein (a) levels. The threshold value of lipoprotein (a) was predicted using the Youden index. For Kazakhstani population the lipoprotein (a) cut offs for the risk of developing atherosclerotic CVD and aortic valve calcification was 21.1 mg/dl (p < 0.05). There was no relationship with the level of lipoprotein (a) and low-density lipoprotein cholesterol (LDL-C), which suggests that lipoprotein (a) is an independent risk factor for the development of ASCVD. This study offers new insights into the threshold value of lipoprotein (a) in Kazakhstan, highlighting its role as a risk factor for atherosclerotic cardiovascular diseases and aortic valve calcification. The findings suggest that the internationally recommended Lp(a) cutoffs may not be suitable for Central Asian populations, as the threshold in our study is significantly lower at 21.2 mg/dL. These results emphasize the need for further research with larger sample sizes to establish more region-specific cutoffs.

Human biomonitoring of essential and toxic trace elements (heavy metals and metalloids) in urine of children, teenagers, and young adults from a Central European Cohort in the Czech Republic.

Exposure to toxic trace elements, which include metals and metalloids, can induce adverse health effects, including life-threatening diseases. Conversely, essential trace elements are vital for bodily functions, yet their excessive (or inadequate) intake may pose health risks. Therefore, identifying levels and determinants of exposure to trace elements is crucial for safeguarding human health. The present study analyzed urinary concentrations of 14 trace elements (arsenic, cadmium, cobalt, chromium, copper, mercury, manganese, molybdenum, nickel, lead, antimony, selenium, thallium, and zinc) and their exposure determinants in 711 individuals, spanningfrom children to young adults from a Central European population from the Czech Republic. Multivariate linear regression and non-parametric Kruskal-Wallis ANOVA were used to investigate exposure determinants. Estimates of 95th percentile concentrations and confidence intervals were carried out to establish reference values(RV95). The study also assessed the percentage of population exceeding health-based guidance values (GVs) to gauge health risks. Young adults showed elevated toxic element concentrations, whereas children exhibited higher concentrations of essential elements. Mercury concentrations were associated with both dental amalgam filling count and seafood intake; arsenic concentrations were associated with seafood, rice, and mushroom consumption. Mushroom consumption also influenced lead concentrations. Sex differences were found for cadmium, zinc, nickel, and cobalt. Between 17.9% and 25% of the participants exceeded recommended GV for arsenic, while 2.4% to 2.8% exceeded GV for cadmium. Only one participant exceeded the GV for mercury, and none exceeded GVs for chromium and thallium. Essential trace elements' GVs were surpassed by 38% to 68.5% participants for zinc, 1.3% to 1.8% for molybdenum, and 0.2% to 0.3% for selenium. The present study examines trace element exposure in a Central European population from the Czech Republic, unveiling elevated exposure levels of toxic elements in young adults and essential elements in children. It elucidates key determinants of trace element exposure, including dietary and lifestyle indicators as well as dental amalgam fillings. Additionally, the study establishes novel reference values and acomparison with established health-based human biomonitoring guidance values, which are crucial for public health decision-making. This comprehensive biomonitoring study provides essential data to inform public health policies and interventions.

Age trend in the mortality from diseases of the circulatory system during the pandemic under a decrease in air pollution

Introduction. The results of large-scale studies of the mortality from diseases of the circulatory system (DCS) during the pandemic require further analysis of the data and the search for modifying factors. The purpose is to identify the features of the trend in the mortality from DCS in the population of an industrial center during a pandemic under changes in air pollution. Materials and methods. The research was carried out in the industrial center – Bratsk. Age-specific mortality rates were studied using exponential models in the background (2017) and pandemic (2021) periods. The contribution of atmospheric air pollution to the mortality rate was calculated in accordance with the “Guidelines for assessing the risk to public health from exposure to chemical substances that pollute the environment.” Results. The age-related increase in the mortality rate from DCS over 2017 was 125%, and during 2021 – 172%. During the pandemic, the excess mortality rate was in cases older 80 years – 35.92‰, 70–79 – 8.48‰, 60–69 – 1.03‰. PM10 levels in the air decreased from high to alarming levels in 2021, resulting in a reduction in excess PM10-related deaths from 194 (CI: 193.6–195.1) to 5.0 (CI: 4.8–5.1) cases. Limitations are associated with incomplete epidemiological knowledge about the dependence of mortality from DCS on exposure to air pollutants. Conclusion. The use of nonlinear regression analysis made it possible to demonstrate changes in trends in age-specific mortality during the background period and during the pandemic. During the pandemic, the level of excess mortality was revealed to relate with PM10 air pollution decreased.

Comment on Risk factors for reoperation of inflatable penile prosthesis among an ethnically diverse urban population in a high-volume center

Comment on Risk factors for reoperation of inflatable penile prosthesis among an ethnically diverse urban population in a high-volume center

Heatwave Intensifications in Armenia: Evidence From Temporal and Spatial Analysis of Observational Data Over the Last Decades

ABSTRACTIncreasing temperatures cause the weather to become more severe. Studying how heatwaves (HWs) impact individual heat exposure and susceptibility is vital for building climate change mitigation and adaptation measures. So, this study explores the impact of HWs on individual heat exposure and susceptibility. The assessment was based on the highly complex topographic region contribution to HWs in the Republic of Armenia (RA) using data from 16 meteorological stations for the extended warm season (May–September). We developed a regional HW catchment program to estimate the HW indices' responses to climatic change and to present them in terms of topography changes. The Mann–Kendall (MK) test was used to determine the statistical significance of the trends for 10 distinct HW indicators using linear and exponential trends along with graphical interpretations. This study reveals a large‐scale, significant increasing trend in annual maximum temperatures (Tmax) and observed HWs over the period 1955–2019. The rising temperature is accompanied by an increase in HW indices, particularly at low altitudes up to 1250 m above sea level (ASL), where the main population centres and national crop production are concentrated. According to our classification, the above‐mentioned areas have faced extreme and severe increases in HW intensity, covering more than 60% of the country's territory. Moreover, not only the intensity and frequency have been identified but the HW period extension as well. This extreme increase has been found in the low‐lying highly populated and intensively cultivated areas, such as in the Ararat valley. These results have implications for future climate assessments, adaptation strategies, agriculture and public health in Armenia. The development of targeted mitigation measures and adaptation strategies informed by these findings is essential for addressing the escalating challenges posed by HWs in the region.

The Distribution of Reniform Nematode (Rotylenchulus reniformis) in Cotton Fields in Central Queensland and Population Dynamics in Response to Cropping Regime.

Reniform nematode (Rotylenchulus reniformis) causes significant yield loss in cotton worldwide. In 2012, its detection in the Dawson-Callide region of Central Queensland prompted extensive surveys of cotton fields. The nematode was confirmed in 68% of sampled fields, with populations ranging from 2 to 3870 R. reniformis/200 mL of soil. Soil monitoring revealed increasing populations associated with consecutive cotton crops. However, when corn or sorghum replaced cotton, soil nematode populations significantly decreased. A two-year replicated field trial demonstrated that growing a non-host crop (such as biofumigant sorghum 'Fumig8tor', grain sorghum, or corn) significantly reduced nematode populations in the top 15 cm of soil compared to cotton. Unfortunately, when cotton was replanted the following season, nematode populations rebounded regardless of the previous crop. Only the 'Fumig8tor'-cotton rotation resulted in significantly lower nematode populations than continuous cotton. Vertical soil sampling showed that rotating with a non-host crop significantly reduced nematode densities to a depth of 100 cm compared to cotton. However, when the field was replanted with cotton, nematode populations recovered, unaffected by cropping or soil depth. This study emphasises the importance of monitoring reniform nematodes in cotton soils for early detection and defining distribution patterns within a field, which may improve the effectiveness of management practices. These results suggest that one rotation out of cotton is not sufficient, as populations return to high levels when cotton is grown again. Therefore, two or more rotations out of cotton should be considered to manage this nematode.

National-Scale Geospatial Modelling of Pyrrhotite in Bedrock Across Canada: A Pilot Study

The most abundant iron sulphide minerals in igneous, metamorphic, and some sedimentary rocks are FeS2 (pyrite/marcasite) and Fe1-xS (pyrrhotite). The oxidation of pyrite and pyrrhotite in bedrock aggregates and mine tailings is undesirable to infrastructure and the environment because such chemical reactions are linked with concrete deterioration and acid mine drainage, respectively. The oxidation rate of pyrrhotite is up to one hundred times greater than that of pyrite; thus, pyrrhotite oxidation is of particular concern to society. Pyrrhotite-bearing concrete aggregates may lead to rapid expansion cracking and failure of critical concrete infrastructure including bridges, buildings, and houses, posing a significant safety concern. Additionally, premature disintegration of concrete requires replacement of concrete, leading to excessive aggregate resource extraction and associated increases in CO2 emissions. Considering the widespread concrete infrastructure across Canada, the distribution of pyrrhotite in bedrock used for aggregate is of fundamental importance to the short- and long-term safety of Canadians at the national, regional, and local scales. This pilot study details the initial steps taken to generate national-scale geospatial models of pyrrhotite occurrences in bedrock across Canada and illustrates the associated map products. In total, 12,577 known pyrrhotite occurrences were identified from publicly available provincial and territorial mineral occurrence datasets. The overall modelling strategy involved normalizing the number of pyrrhotite occurrences with respect to the total surface area of major bedrock types and characterizing three different classes of pyrrhotite occurrence density (&lt; 1, 1–4, and 4–10 occurrences/1000 km2). The maps illustrate that pyrrhotite occurrence density is highest in volcanic rocks and undifferentiated sedimentary and volcanic rocks, moderate in intrusive and unknown rocks, and lowest in sedimentary and metamorphic rocks. Sedimentary rocks with no pyrrhotite occurrences span large surface areas across central-western Canada thus resulting in an overall low pyrrhotite occurrence density (&lt; 1 occurrence/1000 km2) for this rock type, despite the fact that numerous pyrrhotite occurrences are identified in sedimentary rocks and may be abundant locally or regionally. Volcanic, undifferentiated sedimentary and volcanic, intrusive, and unknown rocks occur throughout the Canadian Shield of central and northern Canada, the Cordillera of western Canada, and the Appalachians of eastern Canada, but bedrock type and associated occurrence density are highly variable within these geological domains. Comparison of pyrrhotite occurrence density maps for Canada with pyrrhotite permissive geology maps for the United States of America illustrates that rocks with a high pyrrhotite occurrence density in Canada (volcanic rocks and undifferentiated sedimentary and volcanic rocks), are contiguous overall with areas of pyrrhotite potential in the United States. Inconsistencies across the international border reflect the differing methodologies and assumptions consisting of a statistically based approach for Canada and a qualitative approach for the United States. In the Cordillera and Appalachians, such discontinuities across the international border may reflect the underestimation of pyrrhotite occurrences in sedimentary rocks of Canada because of the impact of high surface area on the pyrrhotite occurrence density calculations. The maps presented herein are a first step in illustrating the distribution of pyrrhotite-bearing bedrock across Canada and greater North America. These national-scale map products are useful first-order references for selecting regions for follow-up studies on bedrock pyrrhotite occurrences. Regional and local geospatial analysis combined with field work for ground truthing will be important aspects of future research, especially in the vicinity of population centres where bedrock is utilized for concrete aggregate. Detailed regional and local studies of pyrrhotite occurrences in bedrock will help guide the extraction of safe concrete aggregate and contribute to the long-term sustainability of bedrock resources, safe infrastructure, and a habitable climate.

DINÁMICA Y VULNERABILIDAD ECOLÓGICA DE LA RESERVA ESTATAL SIERRA DEL TENTZO, MÉXICO

&lt;p&gt;&lt;strong&gt;Background:&lt;/strong&gt; Knowledge and evaluation of ecological changes in Protected Natural Areas is important for their planning and management. The use of tools such as land use change prediction models and satellite image analysis are low-cost and high-precision alternatives that can contribute to this purpose. &lt;strong&gt;Objective:&lt;/strong&gt; Estimate the trend of land use change and vulnerability of the ecosystems of the Sierra del Tentzo State Reserve (REST), Mexico. &lt;strong&gt;Methodology:&lt;/strong&gt; The REST sites with the highest probability of change in their ecosystems were identified according to phases of the adaptive cycles of the Panarchy theory; the use of Landsat images to classify land use and vegetation types, and the identification of areas of greatest vulnerability with a Markov chain model. &lt;strong&gt;Results:&lt;/strong&gt; The trend of change from a state of conservation to a state of growth predominates in the reserve, which indicates a deterioration of the ecosystems with primary vegetation that are being transformed into grasslands and crop areas. While, in the future projection, the areas with greater ecological vulnerability are grouped in a pattern associated with human settlements in population centers. &lt;strong&gt;Implications:&lt;/strong&gt; The study was on a regional scale, so changes and vulnerability at the local level were not explored. &lt;strong&gt;Conclusion:&lt;/strong&gt; In the Sierra del Tentzo State Reserve there is a process of ecosystem degradation and some areas, particularly those most susceptible to human activities, are more vulnerable to this degradation. These areas should be considered in the reserve management program as priority attention.&lt;/p&gt;

Creating a Learning Health System in a Cancer Center: Generalizability of an Electronic Health Record Phenotype for Advanced Solid Cancer.

To test the generalizability of an electronic health record (EHR) phenotype for patients with advanced solid cancer, which was previously developed in a single cancer center. We compared an algorithm to identify patients with advanced solid cancer from a random sample of patients with active cancer in the Veterans Health Administration (VA) and an academic cancer center with a human-coded reference standard between January 1, 2016, and December 31, 2019. Compared with the human-coded reference standard, the algorithm had high specificity (93%; 95% CI, 87 to 99 and 97%; 95% CI, 93 to 100) and reasonable sensitivity (85%; 95% CI, 76 to 94 and 87%; 95% CI, 77 to 97) in the VA and academic cancer center populations, respectively. Patients with advanced cancer (compared with those with active nonadvanced cancer) had higher mortality at the VA and academic cancer center (29.2% and 17.0% 6-month mortality v 6.8% and 3.5%), respectively. This EHR phenotype can be used to measure and improve the quality of palliative care for patients with advanced cancer within and across health care settings.

Estimation of Stature from Percutaneous Upper Limb Measurements in the North Indian Population

Background: In the field of forensic anthropology, stature estimation plays an important role in the identification of unknown dismembered bodies and skeletal remains. When forensic experts find body parts during a police investigation, their first task is to determine the age, sex, and height of the person. They assist law enforcement by using scientific methods in criminal cases. Material and Methods: A cross-sectional study was carried out in the city. Measurements were taken on both the left and right sides of all males. The sample size was 563 individuals aged between 20 and 40 years. Accurate measurements of five upper extremities and stature were measured with the help of an Anthropometer and Sliding calliper. Results: The correlation observed between stature and upper limb showed varying degrees of correlation, ranging from moderate to strong 0.315 to 0.859. The precision of these equations was established by the obtained correlation value, where a greater correlation nearest to 1 indicated the highest significance. Conclusion: This research addresses a critical gap by focusing on the upper extremities in a contemporary Central Indian population. Developing stature estimation models from specific body parts not only advances anthropological research but also aids forensic investigations, especially in warm climates like Uttar Pradesh.