A Modified AVI Model for Groundwater Vulnerability Mapping: Case Studies in Southern Italy

Many methods for evaluating the aquifer’s vulnerability to pollution have been developed in the past four decades by using geographic information system (GIS) tools. However, even if the aquifer vulnerability concept is well defined and the methods have been constantly tested and compared, the problem of the choice of the best “standard” method remains. To meet these objectives, aquifer vulnerability maps are of crucial importance. The choice of method depends on several factors, including the scale of the project, the hydrogeological characteristics of the area, and data availability. Among the many methods, the AVI (Aquifer Vulnerability Index) method has been widely used as it considers only two physical parameters. The AVI Index represents the hydraulic resistance of an aquifer to vertical flow, as a ratio between the thickness of each sedimentary unit above the uppermost aquifer (D, length), and the estimated hydraulic conductivity (K, length/time) of each of these layers. The AVI Index has a time dimension and is divided into five classes. In order to avoid a widespread presence of the higher vulnerability classes, especially in shallow aquifers, the AVI classification has been modified using statistical methods. The study reports the application of the modified AVI method for groundwater pollution vulnerability, in three different areas of southern Italy, highlighting the limitations of the method in alluvial aquifers and the differences with other methods.

ECCsplorer: a pipeline to detect extrachromosomal circular DNA (eccDNA) from next-generation sequencing data

Background Extrachromosomal circular DNAs (eccDNAs) are ring-like DNA structures physically separated from the chromosomes with 100 bp to several megabasepairs in size. Apart from carrying tandemly repeated DNA, eccDNAs may also harbor extra copies of genes or recently activated transposable elements. As eccDNAs occur in all eukaryotes investigated so far and likely play roles in stress, cancer, and aging, they have been prime targets in recent research—with their investigation limited by the scarcity of computational tools. Results Here, we present the ECCsplorer, a bioinformatics pipeline to detect eccDNAs in any kind of organism or tissue using next-generation sequencing techniques. Following Illumina-sequencing of amplified circular DNA (circSeq), the ECCsplorer enables an easy and automated discovery of eccDNA candidates. The data analysis encompasses two major procedures: first, read mapping to the reference genome allows the detection of informative read distributions including high coverage, discordant mapping, and split reads. Second, reference-free comparison of read clusters from amplified eccDNA against control sample data reveals specifically enriched DNA circles. Both software parts can be run separately or jointly, depending on the individual aim or data availability. To illustrate the wide applicability of our approach, we analyzed semi-artificial and published circSeq data from the model organisms Homo sapiens and Arabidopsis thaliana, and generated circSeq reads from the non-model crop plant Beta vulgaris. We clearly identified eccDNA candidates from all datasets, with and without reference genomes. The ECCsplorer pipeline specifically detected mitochondrial mini-circles and retrotransposon activation, showcasing the ECCsplorer’s sensitivity and specificity. Conclusion The ECCsplorer (available online at https://github.com/crimBubble/ECCsplorer) is a bioinformatics pipeline to detect eccDNAs in any kind of organism or tissue using next-generation sequencing data. The derived eccDNA targets are valuable for a wide range of downstream investigations—from analysis of cancer-related eccDNAs over organelle genomics to identification of active transposable elements.

Modeling and Profiling of Aggregated Industrial Network Traffic

The industrial network infrastructures are transforming to a horizontal architecture to enable data availability for advanced applications and enhance flexibility for integrating new technologies. The uninterrupted operation of the legacy systems needs to be ensured by safeguarding their requirements in network configuration and resource management. Network traffic modeling is essential in understanding the ongoing communication for resource estimation and configuration management. The presented work proposes a two-step approach for modeling aggregated traffic classes of brownfield installation. It first detects the repeated work-cycles and then aims to identify the operational states to profile their characteristics. The performance and influence of the approach are evaluated and validated in two experimental setups with data collected from an industrial plant in operation. The comparative results show that the proposed method successfully captures the temporal and spatial dynamics of the network traffic for characterization of various communication states in the operational work-cycles.

What impact have Covid-19 pandemic on number of death occurring at the Emergency Department: A Retrospective Analysis of Mortality in India from January 2019 to May 2021

BackgroundAcute treatment in emergency case management is required for survival and stabilization of critical patients, followed by a shifting to the relevant medical department for further care. However, for the seriously ill critical patients, i.e., when the care provided by the Emergency Department (ED) of the hospital is not enough to enable transfer, death may occur while treatment in the emergency department. This aspect of emergency management is often overlooked, and very few researcher and government is really serious regarding who dies in the ED. Aim and ObjectiveThe aim of my study was to determine the total Mortality occurring in India from 1st January 2019 to 31st May 2021(limitation here due to data availability is limited from accredited source) of emergency department admissions of public and private health facilities. The objective is to find out if there is increase or decrease in mortality of emergency department admissions during the covid-19 pandemic era by comparing average mortality of ED per month of public, private, rural, urban health facilities before the pandemic from 1st and 2nd year of pandemic i.e. 2020 and 2021 respectively MethodsThis research study is a cross sectional retrospective analysis of the mortality occurring at the emergency department of public and private, rural, urban hospitals from 1st January 2019 to May31st 2021 with aim to find out impact of covid-19. Electronic patient records from HMIS (health management information system) of MoHFW (ministry of health and family welfare) , Government of India is collected, observed, analyzed, compared for all patients deaths occurring at Emergency Department (ED) of public and private, rural, urban health facilities (n = 452102) during the period January 2019 to May 2021. ResultsThe study results found that largest total number of death occurred in the ED during may 2021 whereas the least number of deaths occurred in February 2019 (limitation is data availability up to May 2021 from accredited sources). During the first year of the pandemic, average mortality per month (Jan2020-Dec2020) in the emergency department (ED) of rural, urban, public and private hospitals in India was 16067per month whereas before the pandemic it was 12542 per month while during second year of pandemic i.e. 2021 the average mortality increased to 21758 per month (up to May 2021).DiscussionRecently a new strain omicron has again disrupted the normal life and lockdown and other measures are being implemented by different countries to save lives. The mortality at ED are having various etiologies, clinical severity at time of admission has a direct correlation with mortality, which requires the necessity of advanced triage system. There exists a lack of proper knowledge and advanced directives in the beginning i.e. December 2019 of the covid-19 pandemic era.Conclusions Due to novel disease majority of clinicians have challenging situation as well as Emergency Medicine (EM) teams faced a sudden increase in the number of cases with limited resources. Furthermore, a lack of proper knowledge and directives may have hindered access to proper care, as witnessed in many part of the world and available in various literatures. The authors hope that this study will help global researchers as well as policy makers to promote further research and discussion into preparation methods for such pandemics to reduce patient’s risk of death in the ED. KeywordsEmergency department, Death, Covid-19, Pandemic, Health facilities,

EUREC⁴A's <i>Maria S. Merian</i> ship-based cloud and micro rain radar observations of clouds and precipitation

As part of the EUREC4A field campaign, the research vessel Maria S. Merian probed an oceanic region between 6 to 13.8∘ N and 51 to 60∘ W for approximately 32 d. Trade wind cumulus clouds were sampled in the trade wind alley region east of Barbados as well as in the transition region between the trades and the intertropical convergence zone, where the ship crossed some mesoscale oceanic eddies. We collected continuous observations of cloud and precipitation profiles at unprecedented vertical resolution (7–10 m in the first 3000 m) and high temporal resolution (1–3 s) using a W-band radar and micro rain radar (MRR), installed on an active stabilization platform to reduce the impact of ship motions on the observations. The paper describes the ship motion correction algorithm applied to the Doppler observations to extract corrected hydrometeor vertical velocities and the algorithm created to filter interference patterns in the MRR observations. Radar reflectivity, mean Doppler velocity, spectral width and skewness for W-band and reflectivity, mean Doppler velocity, and rain rate for MRR are shown for a case study to demonstrate the potential of the high resolution adopted. As non-standard analysis, we also retrieved and provided liquid water path (LWP) from the 89 GHz passive channel available on the W-band radar system. All datasets and hourly and daily quicklooks are publically available, and DOIs can be found in the data availability section of this publication. Data can be accessed and basic variables can be plotted online via the intake catalog of the online book “How to EUREC4A”.

Extreme precipitating events in satellite and rain-gauge products over the Sahel

Over the recent decades, Extreme Precipitation Events (EPE) have become more frequent over the Sahel. Their properties, however, have so far received little attention. In this study the spatial distribution, intensity, seasonality and interannual variability of EPEs are examined, using both a reference dataset, based on a high-density rain-gauge network over Burkina Faso and 24 precipitation gridded datasets. The gridded datasets are evaluated in depth over Burkina Faso while their commonalities are used to document the EPE properties over the Sahel. EPEs are defined as the occurrence of daily-accumulated precipitation exceeding the all-day 99th percentile over a 1°x1° pixel. Over Burkina Faso, this percentile ranges between 21 and 33 mm day-1. The reference dataset show that EPEs occur in phase with the West African monsoon annual cycle, more frequently during the monsoon core season and during wet years. These results are consistent among the gridded datasets over Burkina Faso but also over the wider Sahel. The gridded datasets exhibit a wide diversity of skills when compared to the Burkinabe reference. The Global Precipitation Climatology Centre Full Data Daily version 1 (GPCC-FDDv1) and the Global Satellite Mapping of Precipitation gauge Reanalysis version 6.0 (GSMaP-gauge-RNL v6.0) are the only products that properly reproduce all of the EPE features examined in this work. The datasets using a combination of microwave and infrared measurements are prone to overestimate the EPE intensity, while infrared-only products generally underestimate it. Their calibrated versions perform than their uncalibrated (near-real-time) versions. This study finally emphasizes that the lack of rain-gauge data availability over the whole Sahel strongly impedes our ability to gain insights in EPE properties.

Continuous Monitoring of Vital Signs With Wearable Sensors During Daily Life Activities: Validation Study

Background Continuous telemonitoring of vital signs in a clinical or home setting may lead to improved knowledge of patients’ baseline vital signs and earlier detection of patient deterioration, and it may also facilitate the migration of care toward home. Little is known about the performance of available wearable sensors, especially during daily life activities, although accurate technology is critical for clinical decision-making. Objective The aim of this study is to assess the data availability, accuracy, and concurrent validity of vital sign data measured with wearable sensors in volunteers during various daily life activities in a simulated free-living environment. Methods Volunteers were equipped with 4 wearable sensors (Everion placed on the left and right arms, VitalPatch, and Fitbit Charge 3) and 2 reference devices (Oxycon Mobile and iButton) to obtain continuous measurements of heart rate (HR), respiratory rate (RR), oxygen saturation (SpO2), and temperature. Participants performed standardized activities, including resting, walking, metronome breathing, chores, stationary cycling, and recovery afterward. Data availability was measured as the percentage of missing data. Accuracy was evaluated by the median absolute percentage error (MAPE) and concurrent validity using the Bland-Altman plot with mean difference and 95% limits of agreement (LoA). Results A total of 20 volunteers (median age 64 years, range 20-74 years) were included. Data availability was high for all vital signs measured by VitalPatch and for HR and temperature measured by Everion. Data availability for HR was the lowest for Fitbit (4807/13,680, 35.14% missing data points). For SpO2 measured by Everion, median percentages of missing data of up to 100% were noted. The overall accuracy of HR was high for all wearable sensors, except during walking. For RR, an overall MAPE of 8.6% was noted for VitalPatch and that of 18.9% for Everion, with a higher MAPE noted during physical activity (up to 27.1%) for both sensors. The accuracy of temperature was high for VitalPatch (MAPE up to 1.7%), and it decreased for Everion (MAPE from 6.3% to 9%). Bland-Altman analyses showed small mean differences of VitalPatch for HR (0.1 beats/min [bpm]), RR (−0.1 breaths/min), and temperature (0.5 °C). Everion and Fitbit underestimated HR up to 5.3 (LoA of −39.0 to 28.3) bpm and 11.4 (LoA of −53.8 to 30.9) bpm, respectively. Everion had a small mean difference with large LoA (−10.8 to 10.4 breaths/min) for RR, underestimated SpO2 (>1%), and overestimated temperature up to 2.9 °C. Conclusions Data availability, accuracy, and concurrent validity of the studied wearable sensors varied and differed according to activity. In this study, the accuracy of all sensors decreased with physical activity. Of the tested sensors, VitalPatch was found to be the most accurate and valid for vital signs monitoring.

Identifying potential sites for artificial groundwater recharge using GIS and AHP techniques: A case study of Erbil basin, Iraq

Excessive extraction, uncontrolled withdrawal of groundwater, and unregulated practices have caused severe depletion of groundwater resources in the Erbil basin, Iraq. This situation has had a number of negative consequences on human settlement, agricultural activities, clean water supply, and the environment. Runoff harvesting and artificial groundwater recharge play a significant role in the sustainable management of water resources, particularly in arid and semi-arid regions. This study aims to: (1) delineate groundwater recharge zones using multiple thematic layers that control the groundwater recharge process, and (2) identify prospective sites and structures to perform artificial groundwater recharge. In order to generate a potential map for groundwater recharge zones, seven thematic layers are considered in this study, namely, topographic position index, geomorphology, lithology, land cover, slope, drainage-length density, and lineament-length density. After that, the analytic hierarchy process was applied to weight, rank, and reclassify these seven thematic layers. All maps are then integrated within the ArcGIS environment for delineating groundwater recharge zones. Accordingly, the resulting map categorizes the study area into five zones: extremely high, high, moderate, low, and extremely low potential for groundwater recharge. As expected, areas along the Greater Zab river show the highest possibility for groundwater recharge. Likewise, rugged eastern hills demonstrate an encouraging capacity for artificial aquifer recharge, whereas the least effective area is represented by built-up land. Based on the generated map, two dams are proposed as promising artificial recharge structures for harvesting runoff water east of Erbil city. Lastly, the resulting map of the potential groundwater recharge zones is verified using static water level data, where the coefficient of determination (R2) achieved a satisfactory result (0.73). These findings provide crucial evidence for implementing a sustainable management plan of surface and groundwater resources. The applied method is eventually valid for regions where appropriate and adequate field data availability is a serious issue.

Escherichia coli concentration, multiscale monitoring over the decade 2011–2021 in the Mekong basin, Lao PDR

Bacterial pathogens in surface waters may threaten human health, especially in developing countries, where untreated surface water is often used for domestic needs. The objective of the long-term multiscale monitoring of Escherichia coli concentration in stream water, and that of associated variables (temperature, electrical conductance, dissolved oxygen concentration and saturation, pH, oxidation-reduction potential, turbidity, and total suspended sediment concentration), was to identify the drivers of bacterial dissemination across tropical catchments. This data description paper presents three datasets (see section Data availability) collected at 31 sampling stations located within the Mekong river and its tributaries in Lao PDR (0.6–25,946 km2) from 2011 to 2021. The 1,602 records have been used to describe the hydrological processes driving in-stream Escherichia coli concentration during flood events, to understand land-use impact on bacterial dissemination on small and large catchment scales, to relate stream water quality and diarrhea outbreaks, and to build numerical models. The database may be further used e.g. to interpret new variables measured in the monitored catchments, or to map the health risk posed by fecal pathogens.

Detecting Population Regulation of Winter Flounder from Noisy Data

Year-class size of marine fish is thought to be determined during the first year of life, with density-dependent mortality during the larval or juvenile stages. However, investigations of such dynamics are often limited by data availability. To test this paradigm for winter flounder (Pseudopleuronectes americanus) in Narragansett Bay, Rhode Island, the abundances of 29 year classes moving through seven life stages were analyzed with a novel extension of key-factor analysis. Evidence of density dependence was identified between the egg and July young-of-the-year stages and high process-error variance was detected throughout the life cycle, suggesting year-class size is not fully determined until age-2. However, the first summer appeared to be a critical life stage for winter flounder, during which high temperatures, hypoxia, and predator abundance contributed to increased mortality rates behind a long-term population decline. Due to its general data requirements, the key-factor analysis method developed here may be applied to other marine populations to identify the impacts of external stressors at particular life stages and the degree to which they are compensated by density-dependent processes.