Quality of Soil in Gossaigaon Sub-Division and Its Impact on Environmental Degradation

People on Earth are under tremendous threat due to undesired changes in the physical, chemical and biological characteristics of water and soil. Due to increased human population, industrialization, use of unwanted amounts of fertilizers and man-made activities, water and soil is highly polluted with different harmful contaminants. Natural water and soil contaminates due to weathering of rocks and leaching of soils, mining processing etc. It is necessary that the quality of drinking water and soil should be checked at regular time interval, because due to use of contaminated drinking water, human population suffers from variety of water borne diseases. The study area, Gossaigaon sub-division of Kokrajhar district, Assam lies on the north bank of the Brahmaputra river and is slowly sloping towards south from the foothills of Bhutan upto an average height of 42 MSL. The tributaries of the Brahmaputra- Sankosh, Ripu, Dambra, Bura chara, Gadadhar, Gurufella, Madati, Hel, Gongea are flowing southward which have their sources in the Himalayas. In this paper an attempt has been made to assess the quality of soil of 10 different stations by considering the parameters like Colour, Temperature, pH value, Conductance, Alkalinity, Dissolved Oxygen, Hardness, TS, TDS, Chlorine, Fluorine, Sulphur, Nitrogen, Phosphorous, Iron, Calcium and Magnesium, Sodium, Potassium, Zinc, Nickel, Lead and Copper which have direct correlation with human health.

A Sensor-Based Drone for Pollutants Detection in Eco-Friendly Cities: Hardware Design and Data Analysis Application

The increase in produced waste is a symptom of inefficient resources usage, which should be better exploited as a resource for energy and materials. The air pollution generated by waste causes impacts felt by a large part of the population living in and around the main urban areas. This paper presents a mobile sensor node for monitoring air and noise pollution; indeed, the developed system is installed on an RC drone, quickly monitoring large areas. It relies on a Raspberry Pi Zero W board and a wide set of sensors (i.e., NO2, CO, NH3, CO2, VOCs, PM2.5, and PM10) to sample the environmental parameter at regular time intervals. A proper classification algorithm was developed to quantify the traffic level from the noise level (NL) acquired by the onboard microphone. Additionally, the drone is equipped with a camera and implements a visual recognition algorithm (Fast R-CNN) to detect waste fires and mark them by a GPS receiver. Furthermore, the firmware for managing the sensing unit operation was developed, as well as the power supply section. In particular, the node’s consumption was analysed in two use cases, and the battery capacity needed to power the designed device was sized. The onfield tests demonstrated the proper operation of the developed monitoring system. Finally, a cloud application was developed to remotely monitor the information acquired by the sensor-based drone and upload them on a remote database.

STR: Seasonal-Trend Decomposition Using Regression

We propose a new method for decomposing seasonal data: a seasonal-trend decomposition using regression (STR). Unlike other decomposition methods, STR allows for multiple seasonal and cyclic components, covariates, seasonal patterns that may have noninteger periods, and seasonality with complex topology. It can be used for time series with any regular time index, including hourly, daily, weekly, monthly, or quarterly data. It is competitive with existing methods when they exist and tackles many more decomposition problems than other methods allow. STR is based on a regularized optimization and so is somewhat related to ridge regression. Because it is based on a statistical model, we can easily compute confidence intervals for components, something that is not possible with most existing decomposition methods (such as seasonal-trend decomposition using Loess, X-12-ARIMA, SEATS-TRAMO, etc.). Our model is implemented in the R package stR, so it can be applied by anyone to their own data.

A Review of Burn Patients Requiring Extracorporeal Membrane Oxygenation at a Burns Facility

Respiratory compromise is a recognised sequelae of major burn injuries, and in rare instances requires extracorporeal membrane oxygenation (ECMO). Over a ten-year period, our hospital trust, an ECMO centre and burns facility, had five major burn patients requiring ECMO, whose burn injuries would normally be managed at trusts with higher levels of burn care. Three patients (60%) survived to hospital discharge, one (20%) died at our trust, and one patient died after repatriation. All patients required regular, time-intensive dressing changes from our specialist nursing team, beyond their regular duties. This review presents these patients, as well as a review of the literature on the use of ECMO in burn injury patients. A formal review of the overlap between the networks that cater to ECMO and burn patients is recommended.

A Novel, Benchmark-Centered, Eco-Impact Rating System for Sunscreens and Sunscreen Formulation Design

Ultraviolet (UV) filter compounds are the key constituents in sunscreens that protect human skin from detrimental solar radiation. Some of these products have attracted public attention due to claims of their potential negative impact on the environment, in particular marine fauna and flora. At present, consumers who want to make an eco-conscious decision cannot find suitable product details and need to rely on fragmented information or complex scientific literature. The same is true for sunscreen developers, typically formulation chemists, who at present can only work with black- and whitelists which recommend or omit compounds. The ecological impact evaluation system proposed in this publication makes it easier to choose UV filters. Selection is based intrinsically on specialized knowledge which is built on environmental safety data. By embedding this in an existing in-silico sunscreen design system, new products can be created during the project’s design phase without time and cost intensive investigations. In contrast to currently available methods, the proposed tool includes comparison with a virtual market benchmark so users can determine whether a newly developed product will be an improvement on the state of the art in terms of environmental compatibility. The level of improvement can be displayed as a logo which has been designed to be immediately understandable to consumers. The system can be re-adjusted in regular time frames, depending on market development, to motivate and drive the sunscreen industry towards more eco-compatible products.

Hospital at Home for Intrathecal Pump Refills: A Prospective Effectiveness, Safety and Feasibility Study

Continuous Intrathecal Drug Delivery through an implanted pump is a well-known therapeutic option for the management of chronic pain and severe disabling spasticity. To have a successful therapy, pump refills need to be performed at regular time intervals after implantation. In line with the increased applications of Hospital at Home, these refill procedures might be performed at the patient’s home. The aim of this pilot study is to evaluate the feasibility, safety, and effectiveness of intrathecal pump refill procedures at home. Twenty patients were included whereby pump refill procedures were conducted at the patient’s home. To enable contact with the hospital, a video connection was set-up. Tele-ultrasound was used as post-refill verification. All procedures were successfully performed with complete patient satisfaction. Ninety-five percent of the patients felt safe during the procedure, and 95% of the procedures felt safe according to the physician. All patients indicated that they preferred their next refill at home. The median time consumption for the physician/nurse at the patient’s home was 26 min and for the researcher at the hospital 15 min. In light of quality enhancement programs and personalized care, it is important to continue urgent pain management procedures in a safe way, even during a pandemic.

Controlling SARS-CoV-2 in schools using repetitive testing strategies

SARS-CoV-2 remains a worldwide emergency. While vaccines have been approved and are widely administered, these are only available to adults and adolescents in Europe. Therefore, in order to mitigate the spread of more transmissible SARS-CoV-2 variants among children, the use of non-pharmaceutical interventions is still warranted. We investigate the impact of different testing strategies on the SARS-CoV-2 infection dynamics in a primary school environment, using an individual-based modelling approach. Specifically, we consider three testing strategies: 1) symptomatic isolation, where we test symptomatic individuals and isolate them when they test positive, 2) reactive screening, where a class is screened once one symptomatic individual was identified, and 3) repetitive screening, where the school in its entirety is screened on regular time intervals. Through this analysis, we demonstrate that repetitive testing strategies can significantly reduce the attack rate in schools, contrary to a reactive screening approach. Furthermore, we investigate the impact of these testing strategies on the average number of school days lost per child.

Polymodeling of time series structures, neighborhood of residuals distribution, wavelet transformation for meso-dynamics assessment

Subject. The article provides the results of meso-dynamics analysis of main twelve industries, based on monthly data for 82 Russian regions, from January 2005 till December 2020. Objectives. The purpose of the study is to address the problem of balanced and stable spatial development of Russia’s regions and Russia, which requires modeling of adequate tools and forecasting nonlinear mesodynamics. Methods. The study follows the econophysics methodology. Results. We consider additive and multiplicative interactions of regular time series components between each other and the residuals, thus expanding the scope of tools application for the variety of considered industries and their models. Using the common and new trend models, we analyze structural changes, introduce the topological measure of proximity to the neighborhood of residuals with heavy-tailed distribution, which is estimated by median values of trends and cycles for regular components. The traditional time series decomposition (by trend, cycle, seasonality, and residual) is supplemented by our unique complex of wavelet transformations, which forms the models of cycles, using auto regression. We obtained representative and time-synchronized analytical estimates of regular components of industries’ dynamics for meso- and macro-indicators of the Russian economy that have higher accuracy than the known results for the accuracy of modeling and forecasting. Conclusions. The offered methodology and tools enable a more adequate analysis of non-linear dynamics of regions’ middle-term development. They help shift to growth point identification, create the atlas of economic industrial cycles, analyze stages of bifurcations and scenario predictive planning.

Insights from Time Series of Atmospheric Carbon Dioxide and Related Tracers

The past century has been a time of unparalleled changes in global climate and global biogeochemistry. At the forefront of the study of these changes are regular time-series observations at remote stations of atmospheric CO2, isotopes of CO2, and related species, such as O2 and carbonyl sulfide (COS). These records now span many decades and contain a wide spectrum of signals, from seasonal cycles to long-term trends. These signals are variously related to carbon sources and sinks, rates of photosynthesis and respiration of both land and oceanic ecosystems, and rates of air-sea exchange, providing unique insights into natural biogeochemical cycles and their ongoing changes. This review provides a broad overview of these records, focusing on what they have taught us about large-scale global biogeochemical change.

Impact of One Additional Substitution on Player Load and Coaching Tactics in Elite Football

Professional football players, coaches, and researchers have discussed additional substitutions in football to reduce player load for a while. However, the effects of additional substitutions on the game have not yet been investigated in detail. The aim of this paper is to determine whether an additional substitution in (1) extra time and (2) regular time would be beneficial and would lead to (a) greater tactical influence of coaches on the match, (b) load reduction during one match, and (c) load reduction during one season. The methodological approach adopted includes two studies, both of which involve data analysis of substitution times (Study 1: n = 3060; Study 2: n = 1153) as well as a survey of football coaches (Study 1: n = 37; Study 2: n = 25). For assessing the effect of an additional substitution in regular time and in extra time, the substitutions made in the Bundesliga, U19-Bundesliga West, DFB-Cup, and 2018 World Cup were evaluated. The findings of this research clearly indicate the potential of an additional substitution by enabling almost 50% of additional load reduction in regular time and 27% in extra time. However, in practice, the findings showed the limits of an additional substitution in extra time on long-term load reduction.