Anthropogenic and natural fragmentations shape the spatial distribution and genetic diversity of roe deer in the marginal area of its geographic range

Habitat destruction and fragmentation are major factors in the destruction of genetic diversity and affect the movement behavior of the Roe deer population in the remaining habitats. Here, we study the population and landscape genetics of Capreolus capreolus (roe deer) in northern and northwestern Iran using twelve polymorphism microsatellite markers. From 111 total specimens, 63 had successful extraction (6 feces, 35 tissues, 9 bones, and 13 antlers). We considered 30 microsatellite polymorphic loci, of which only 12 were amplified for our further analysis. For genetic diversity analysis, the Weir-Cockerham method was applied to measure the inbreeding coefficient (FIS) and fixation index (FST) for each locus as well as for each population. For landscape genetics, the susceptibility patterns of genetic variations were assessed using three hypotheses including isolation by distance (IBD), isolation by environment (IBE), isolation by resistance (IBR), and individual landscape genetic analysis. A habitat suitability map as an indicator of landscape resistance was constructed from several species distribution models (SDMs) algorithms including Generalized Boosting Models (GBM), Maximum Entropy (Maxent), Random Forest (RF), Generalized Linear Model (GLM), Multivariate Adaptive Regression Splines (MARS) and artificial neural networks (ANN) and an ensemble model. Our estimated FIs index showed that the Golestan, Arasbaran, and Guilan populations had the highest and lowest genetic diversity among roe deer populations. According to the Fst criterion, our results showed that Golestan and East Azarbaijan (Arasbaran) had the highest and Mazandaran had the lowest genetic distance patterns. Our results do not suggest that there is high genetic differentiation for roe deer in the region, with high levels of gene flow between study areas. We found that geographic distance has no significant relationship with genetic distance and that there is no significant relationship between the ecological niche non-similarity matrix and the genetic distance matrix. The most influential factors affecting gene flow in roe deer were aspect and elevation variables. The analysis suggests that the landscape has no significant influence on the structuring of the studied population and shows little genetic differentiation

Landslide susceptibility mapping: machine and ensemble learning based on remote sensing big data

Predicting landslide occurrences can be difficult. However, failure to do so can be catastrophic, causing unwanted tragedies such as property damage, community displacement, and human casualties. Research into landslide susceptibility mapping (LSM) attempts to alleviate such catastrophes through the identification of landslide prone areas. Computational modelling techniques have been successful in related disaster scenarios, which motivate this work to explore such modelling for LSM. In this research, the potential of supervised machine learning and ensemble learning is investigated. Firstly, the Flexible Discriminant Analysis (FDA) supervised learning algorithm is trained for LSM and compared against other algorithms that have been widely used for the same purpose, namely Generalized Logistic Models (GLM), Boosted Regression Trees (BRT or GBM), and Random Forest (RF). Next, an ensemble model consisting of all four algorithms is implemented to examine possible performance improvements. The dataset used to train and test all the algorithms consists of a landslide inventory map of 227 landslide locations. From these sources, 13 conditioning factors are extracted to be used in the models. Experimental evaluations are made based on True Skill Statistic (TSS), the Receiver Operation characteristic (ROC) curve and kappa index. The results show that the best TSS (0.6986), ROC (0.904) and kappa (0.6915) were obtained by the ensemble model. FDA on its own seems effective at modelling landslide susceptibility from multiple data sources, with performance comparable to GLM. However, it slightly underperforms when compared to GBM (BRT) and RF. RF seems most capable compared to GBM, GLM, and FDA, when dealing with all conditioning factors

Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background Disorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021. Methods We estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous system combined. Findings Globally, the 37 conditions affecting the nervous system were collectively ranked as the leading group cause of DALYs in 2021 (443 million, 95% UI 378–521), affecting 3·40 billion (3·20–3·62) individuals (43·1%, 40·5–45·9 of the global population); global DALY counts attributed to these conditions increased by 18·2% (8·7–26·7) between 1990 and 2021. Age-standardised rates of deaths per 100 000 people attributed to these conditions decreased from 1990 to 2021 by 33·6% (27·6–38·8), and age-standardised rates of DALYs attributed to these conditions decreased by 27·0% (21·5–32·4). Age-standardised prevalence was almost stable, with a change of 1·5% (0·7–2·4). The ten conditions with the highest age-standardised DALYs in 2021 were stroke, neonatal encephalopathy, migraine, Alzheimer's disease and other dementias, diabetic neuropathy, meningitis, epilepsy, neurological complications due to preterm birth, autism spectrum disorder, and nervous system cancer. Interpretation As the leading cause of overall disease burden in the world, with increasing global DALY counts, effective prevention, treatment, and rehabilitation strategies for disorders affecting the nervous system are needed. Funding Bill & Melinda Gates Foundation

Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BackgroundDisorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021.MethodsWe estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous system combined.FindingsGlobally, the 37 conditions affecting the nervous system were collectively ranked as the leading group cause of DALYs in 2021 (443 million, 95% UI 378–521), affecting 3·40 billion (3·20–3·62) individuals (43·1%, 40·5–45·9 of the global population); global DALY counts attributed to these conditions increased by 18·2% (8·7–26·7) between 1990 and 2021. Age-standardised rates of deaths per 100 000 people attributed to these conditions decreased from 1990 to 2021 by 33·6% (27·6–38·8), and age-standardised rates of DALYs attributed to these conditions decreased by 27·0% (21·5–32·4). Age-standardised prevalence was almost stable, with a change of 1·5% (0·7–2·4). The ten conditions with the highest age-standardised DALYs in 2021 were stroke, neonatal encephalopathy, migraine, Alzheimer's disease and other dementias, diabetic neuropathy, meningitis, epilepsy, neurological complications due to preterm birth, autism spectrum disorder, and nervous system cancer.InterpretationAs the leading cause of overall disease burden in the world, with increasing global DALY counts, effective prevention, treatment, and rehabilitation strategies for disorders affecting the nervous system are needed

Geology, geochemistry and mineralogy of the tareek darreh gold deposit, north of torbat-e jaam, northeast iran

The Tareek Darreh gold deposit is located 40km north of Torbat-e Jaam in the Khorasan-Razavi province, NE-Iran. The study area is mainly comprised of slightly metamorphosed, sedimentary rocks of Jurassic age including alternation of shale, siltstone, and sandstone. These rocks have been intruded by plutonic rocks such as gabbronorite, diorite, quartz-diorite, and rhyodacite. The ore bodies were exposed after trenching and pitting. In this study, all trenches and pits were systematically sampled and analysed by XRF, XRD, and ICP methods as well as petrological mineralogical studies. The alteration minerals of quartz, chlorite, albite, and sericite are mostly observed on the top or margin of the stocks. Alteration is more intensive at the contacts of the stocks where vein type mineralization has occurred. The veins are mainly composed of quartz and calcite  with arsenopyrite, chalcopyrite, and pyrite main ore minerals. Four promising mineralization zones were selected for further studies. The analytical results for the zones No. 2 and No. 4 confirm high gold, copper, bismuth, tellurium, and silver. In the zone No. 2 (50 x 80 m2) an average of 3.5ppm gold was recorded for one of the trenches, while in zone No. 4 (50 x 250m2). The average gold content is 1.35ppm. According to our studies, The Tareek Darreh gold deposit is considered to be similar to the "intrusion-related gold systems".The Tareek Darreh gold deposit is located 40km north of Torbat-e Jaam in the Khorasan-Razavi province, NE-Iran. The study area is mainly comprised of slightly metamorphosed, sedimentary rocks of Jurassic age including alternation of shale, siltstone, and sandstone. These rocks have been intruded by plutonic rocks such as gabbronorite, diorite, quartz-diorite, and rhyodacite. The ore bodes are exposed by trenching and pitting .In this study, all trenches and pits were systematically sampled and analysed by XRF, XRD, and ICP methods as well as petrological mineralogical studies. The alteration minerals of quartz, chlorite, albite, and sericite are mostly observed on the top or margin of the stocks. Alteration is more intensive at the contacts of the stocks where vein type mineralization has occurred. The veins are mainly composed of silica type and calcite type, arsenopyrite, chalcopyrite, and pyrite main ore minerals. Four promising mineralization zones were selected for further studies. The analytical results for the zones No. 2 and No. 4 confirm high gold, copper, bismuth, tellurium, and silver. In the zone No. 2 (50 x 80 m2) an average of 3.5ppm gold was recorded for one of the trenches, while in zone No. 4 (50 x 250m2). The average gold content is 1.35ppm.  According to our studies, The Tareek Darreh gold deposit is considered to be similar to the "intrusion-related gold systems"

Deep Neural Network Utilizing Remote Sensing Datasets for Flood Hazard Susceptibility Mapping in Brisbane, Australia

Large damages and losses resulting from floods are widely reported across the globe. Thus, the identification of the flood-prone zones on a flood susceptibility map is very essential. To do so, 13 conditioning factors influencing the flood occurrence in Brisbane river catchment in Australia (i.e., topographic, water-related, geological, and land use factors) were acquired for further processing and modeling. In this study, artificial neural networks (ANN), deep learning neural networks (DLNN), and optimized DLNN using particle swarm optimization (PSO) were exploited to predict and estimate the susceptible areas to the future floods. The significance of the conditioning factors analysis for the region highlighted that altitude, distance from river, sediment transport index (STI), and slope played the most important roles, whereas stream power index (SPI) did not contribute to the hazardous situation. The performance of the models was evaluated against the statistical tests such as sensitivity, specificity, the area under curve (AUC), and true skill statistic (TSS). DLNN and PSO-DLNN models obtained the highest values of sensitivity (0.99) for the training stage to compare with ANN. Moreover, the validations of specificity and TSS for PSO-DLNN recorded the highest values of 0.98 and 0.90, respectively, compared with those obtained by ANN and DLNN. The best accuracies by AUC were evaluated in PSO-DLNN (0.99 in training and 0.98 in testing datasets), followed by DLNN and ANN. Therefore, the optimized PSO-DLNN proved its robustness to compare with other methods

Ancient Gold-Mercury Mining in the Takht-e Soleyman Area, Northwest Iran

The world heritage ancient site of Takht-e Soleyman and its assemblage of metal objects, together with the geological wealth and the  vast ancient mining relics of the Takab area motivated the authors to conduct the investigation that led to this article. The ancient  mining and ore processing sites of the Takht-e Soleyman area were surveyed and investigated in an area of 5000 km2. This contribution introduces briefly the geology and mineral resources together with the traces of ancient mining and ore processing in the area of Takht-e Soleyman. Some archaeological sites were found and documented for the first time during this investigation

Anthropogenic and natural fragmentations shape the spatial distribution and genetic diversity of roe deer in the marginal area of its geographic range

Habitat destruction and fragmentation are major factors in the destruction of genetic diversity and affect the movement behavior of the Roe deer population in the remaining habitats. Here, we study the population and landscape genetics of Capreolus capreolus (roe deer) in northern and northwestern Iran using twelve polymorphism microsatellite markers. From 111 total specimens, 63 had successful extraction (6 feces, 35 tissues, 9 bones, and 13 antlers). We considered 30 microsatellite polymorphic loci, of which only 12 were amplified for our further analysis. For genetic diversity analysis, the Weir-Cockerham method was applied to measure the inbreeding coefficient (FIS) and fixation index (FST) for each locus as well as for each population. For landscape genetics, the susceptibility patterns of genetic variations were assessed using three hypotheses including isolation by distance (IBD), isolation by environment (IBE), isolation by resistance (IBR), and individual landscape genetic analysis. A habitat suitability map as an indicator of landscape resistance was constructed from several species distribution models (SDMs) algorithms including Generalized Boosting Models (GBM), Maximum Entropy (Maxent), Random Forest (RF), Generalized Linear Model (GLM), Multivariate Adaptive Regression Splines (MARS) and artificial neural networks (ANN) and an ensemble model. Our estimated FIs index showed that the Golestan, Arasbaran, and Guilan populations had the highest and lowest genetic diversity among roe deer populations. According to the Fst criterion, our results showed that Golestan and East Azarbaijan (Arasbaran) had the highest and Mazandaran had the lowest genetic distance patterns. Our results do not suggest that there is high genetic differentiation for roe deer in the region, with high levels of gene flow between study areas. We found that geographic distance has no significant relationship with genetic distance and that there is no significant relationship between the ecological niche non-similarity matrix and the genetic distance matrix. The most influential factors affecting gene flow in roe deer were aspect and elevation variables. The analysis suggests that the landscape has no significant influence on the structuring of the studied population and shows little genetic differentiation