bluuebunny/crossref_metadata_2025_split huggingface dataset:
Hydro-geochemical elucidation and its implications in the Wardha valley coalfields of central India
Authors: Ganvir P S , Guhey Rajeeva 
Published: July 2022

Abstract
The performed endeavour is to elucidate the hydro-geochemistry of the groundwater in the Wardha valley coalfield of central India. Being a coalfield of well-appreciated coal exploiting region, many studies has also disclosed the prevailing contamination issues in the same. The study is motivated to understand the groundwater chemistry and its possible implications in contamination prevalence. The measured hydro-geochemical parameters from 45 groundwater samples have manifested the rock-water interaction as a controlling mechanism with the dominance of CaMgCl facies to the extent of 67 % to 81 % in pre- and post-monsoon respectively. The hydro-geochemical facies analysis specified the ascendency of strong acid (SO4
2--Cl--NO3
-) over weak acids (HCO3
-). Such domination not only lowers the pH of the groundwater but also provide an encouraging hydro-geochemical situation for contaminations. To mitigate the contaminations like of heavy metals in and around coalfields, the pre-deliberations of such hydro-geochemical studies should be much anticipated and the present study is in agreement to it.
Developmental Strategies for a Water Quality Assessment Model with Limited Datasets – A Case Study from River Bhavani, India
Authors: Ravinashree A , Sivapragasam C , Vasudevan M 
Published: July 2022

Abstract
Understanding the significance of rational attributes for a water quality model depends largely on the availability and reliability of virgin datasets pertaining to their spatial-temporal variations and interactions. Present study aims to identify certain crucial attributes for deriving a water quality model for a selected reach of River Bhavani in Tamil Nadu, India using the results of the QUAL2K model based on a limited dataset. The spatial variations in the concentrations of inorganic suspended solids (ISS) and carbonaceous biochemical oxygen demand (cBOD) were studied in detail corresponding to the possible variations in other model parameters (pertaining to the hydraulic, environmental and climatic conditions). The results indicate that the cBOD has a significant dependency on temperature, dissolved oxygen and pH, while the ISS has shown more dependency on alkalinity, conductivity and bottom algae. It is further inferred that variations in pH and dissolved oxygen can impose triggering effects when external pollution loads (point and nonpoint sources) are introduced while generating the corresponding profiles of ISS and cBOD. Based on the results, the conceptual strategies for developing a data-limited model is presented, which can be further developed to simulate water quality profiles for similar data-limited scenario.
A study of Environmental and Ecological impacts due to Construction and Operation of Tehri-Polavaram Dam
Authors: Verma S K , Sahu R T. , Singh H , Prasad A.D. , Verma M K 
Published: July 2022

Abstract
Any water resources project has both a positive and a negative impact on the environment. Sometimes these environmental losses are unavoidable, so it is most important to minimize the environmental losses and their social-ecological and geopolitical impact. Environmental impact assessment plays an important role in identifying, predicting, and mitigating the various impacts on the environment. This paper presents the details of the construction of Tehri and Polavaram dam projects and their various impacts on the environment and ecological aspects. Any water resource expansion that fulfills minimum needs without endangering future generations’ ability to fulfils their own will be considered sustainable. There are a number of factors to consider when it comes to the long-term effects of dams on the surrounding environment, including redevelopment and relocation of people and businesses, socioeconomic influence on the surrounding area, and environmental concerns such as sedimentation, among others. Sustainable development also means that, in addition to minimizing the dam’s negative effects on the environment, making sure that the benefits of the dam outweigh the negative ones. As a result, it is recognized that water resource projects must be intended, implemented, and managed to meet future population demands while reducing disturbance to the existing eco-system and incorporating effective control measures at various phases to ameliorate any adverse effects.
Kimberlitic olivine – a proxy to kimberlite petrogenesis and ascent process
Authors: Mishra V. K. , Tiwari R. N. , Verma C. B. , Mukherjee A. , Dixit R. K. , Prabhakar G. 
Published: July 2022

Abstract
In kimberlite, olivine is an important constituent and it is found as mineral grains of different sizes, which can be of xenocrystic and magmatic origin. To know the processes, that are involved and controls the compositional variations of olivine, can provide distinct understanding into the genesis and evolution of kimberlites. In addition to this the textural features of kimberlitic olivine, which are recorded as textural events during magma assent constrains the ascent of kimberlite and the processes involved.
Unambiguous identification of kimberlitic olivine and its textural features require careful petrographic examination combined with mineral compositional analysis and use of high magnification images (BSE-SEM), all this is integrated to know the origin of olivine grain which in turn constrain the process involved in ascent of kimberlite and its petrogenesis. In this study we review the use of kimberlitic olivine in deducing the upper mantle conditions and process for kimberlite petrogenesis.
Challenges and solutions in COVID-19 related pandemic solid waste management (PSWM) - A detailed analysis with special focus on plastic waste
Authors: Upadhyay Kshitij , Bajpai Samir 
Published: July 2022

Abstract
A pandemic like novel coronavirus 2’ (SARS-CoV-2) not only poses serious public health repercussions but also affects the socio-economic and environmental conditions of the affected countries. The increased consumption of material resources in conjunction with ‘containment and preventive measures’ is generating an unprecedented amount of potentially infectious solid waste, especially that of plastic origin, which if mismanaged, is bound to affect the ecosystem and public health, as the virus can survive on fomites for longer duration. COVID-19 related pandemic waste, such as Personal protective equipment (PPEs), sanitizer and water bottles, disinfection wipes, and Single use Plastics (SUPs) products has already found its way to the aquatic and terrestrial environment. Even before the start of the COVID-19 pandemic, the management of plastic waste, an environmental stressor with trans-boundary migration capabilities, was a major environmental issue for every stake-holder.
In this paper, we propose a separate domain in the waste management framework for the effective management of pandemic related solid waste. Factors and sources contributing to increased plastic waste generation are discussed in detail. A concise picture of global plastic demand through sectors and polymer types is presented and speculations are made on how COVID-19 is going to affect the plastic demand. Current solid waste handling and management practices in developed and developing countries are critically examined from the perspective of this pandemic. We identified various challenges that waste management sectors are facing currently and offered possible solutions.
Concerns of transmission through fomites is bringing a change in public behavior and consumption pattern which affects 3R practices, while fear of secondary transmission from occupational infections is interfering with 3R practices at end-of-life plastic waste management. The legislative and restrictive frameworks on plastic use being currently put-on hold at the governmental level to ensure public safety are being used by the plastic industry to lobby for increased plastic consumption. The inability of the governments to win public confidence is further escalating unsustainable practices and slowing the shift towards sustainable economy. It is imperative to enforce sustainable practices without putting public safety at risk and to ensure that an unsustainable societal attitude wouldn’t be reinstated in the post-pandemic world. Lastly, eight research and policy points suggested here may guide future studies and governmental frameworks in the domain of COVID-19 pandemic related solid waste handling and management.
Critical analysis of hydrological mass variations of northwest India
Authors: Mira Shivani S , Srivastava S , Singh A 
Published: July 2022

Abstract
With current climate change, water availability is a huge concern. Ground-water (GW) is depleting at a steep rate globally and more specifically in Northwest India. Estimation and analysis of GW availability would be of great use for formulating a proper water management plan for the future. The study is carried out in the north-western part of India with the aim of generating a time series for total water storage (TWS) using different remote sensing and model-based data like GRACE, Landsat, MODIS. From the time series, it is clear-cut that, the TWS is showing a declining trend and this might be due to depletion of groundwater as, other variables like precipitation, evapotranspiration, soil moisture (obtained from MERRA-2 and CFSR data) are not showing any negative trend during the study period (2002 - 2021). Also, from the change detection analysis of land use land cover maps and crop yield statistics of water-intensive crops it can be concluded that croplands in the study area are increasing denoting the usage of water for irrigation at a large scale. Thus, better management of the groundwater is required for avoiding severe water scarcity in the future.
Coastal Vulnerability Assessment: A case study of the Ratnagiri coast, Maharashtra, India
Authors: Yadav A B , Mohanty P C , Singh A 
Published: July 2022

Abstract
The coastal zone is a vulnerable habitat that needs extra caution to protect ecosystems. Coastal systems are increasingly threatened by possible climate change consequences, as evidenced by the Intergovernmental Panel on Climate Change’s consecutive assessments. Increased tropical storm occurrences in recent years, in addition to the devastation caused by the tsunami in December 2004, have highlighted the necessity of analyzing the coast’s susceptibility to flooding-induced hazards to get a better knowledge of the factors that generate various hazards and, as a result, reduce the after-effects of future occurrences. The Ratnagiri coast in Maharashtra is prone to erosional hazards, periodic land rehabilitation, and sudden rises in sea level. The main objective is to calculate the CVI (Coastal Vulnerability Index) for the Ratnagiri coast. To analyze the vulnerability of the coastal region, eight risk parameters were used, viz. shoreline change rate, coastal elevation, sea level change rate, coastal slope, tide range, significant wave height, coastal geomorphology, and tsunami arrival height. The coastal vulnerability map was created by categorizing the numerous coastal portions into three vulnerability groups: high, medium, and low, which will aid coastal residents in risk mitigation in the future.
Igneous rock classification using Convolutional neural networks (CNN)
Authors: Patro Surendra , Jhariya D.C. , Sahu Mridu , Dewangan Pankaj , Dhekne P.Y. 
Published: July 2022

Abstract
This paper describes how convolutional neural networks are used to identify and classify igneous rocks (CNN). Igneous rocks are formed while still hot, hot magma crystallises and solidifies. Melt originates deep beneath the Earth’s surface, amid active plate borders or hot zones, and then rises to the surface. There are also various kinds of igneous rocks, which are addressed throughout this work, distinguishing each one is a difficult feat in and of itself. Machine learning, which is fundamentally a three-layer neural network, is a subset of deep learning. These neural networks attempt to mimic conscious brain function of humans by letting it to “learn” from massive volumes of data, but they continue to fail. A Convolutional Neural Network (ConvNet/CNN) is a Deep Learning approach for assigning priority (learnable weights and biases) to various aspects/objects in a picture while also identifying them. Classification of images, audio and video segmentation, decision support systems, speech recognition, and image analysis are just a few of the applications for CNNs.
Classifying Minerals using Deep Learning Algorithms
Authors: Singh Tajendra , Jhariya D.C. , Sahu Mridu , Dewangan Pankaj , Dhekne P.Y. 
Published: July 2022

Abstract
A mineral is an inorganic substance that occurs in nature with specific chemical content and an ordered atomic positioning. Minerals are identified by their physical properties. Minerals’ physical properties are related to their chemical composition and bonding. Quartz is extremely valuable economically. Valuable minerals and some examples of gemstones are citrine, amethyst, quartz with smoky texture and quartz of rose color can be said as rose quartz are some examples of gemstones. Sandstone, primarily composing quartz, is the most used building stone. Biotite has limited number of applications for commercial use. Deep learning is the subset of machine learning. It is based on self-learning and improvement through the examination of computer algorithms. TensorFlow library of machine learning combines a number of different algorithms and models which allows users to build deep neural networks for projects/model such as image recognition/classification and many more. Image Classification is the assignment of one label from a fixed set of categories to an input image. In this paper Convolutional neural networks (CNNs) are used primarily for image processing, classification, segmentation, and other auto-correlated data. This paper will explain the techniques and explanation for classifying minerals images using a deep learning algorithm called a convolutional neural network. Identifying minerals on a field is a tedious activity and requires a lot of information and conformation here with the help of deep learning algorithms we made a deep learning model which has all its feature already embedded in it that can be used to classify minerals with a reasonable accuracy furthermore in future it can be made more accurate and fit accordingly to the conditions.
Delineation of Groundwater Potential Zones in Koyna River Watershed, Maharashtra using Remote Sensing and GIS
Authors: Swain R C , Jhariya D C , Swain A , Mawale Y K , Rana S 
Published: July 2022

Abstract
Groundwater is considered as only source which provides water for meeting domestic, industrial and agricultural requirement. Continuous uses of water without any conservation cause lowering of Ground water level and thus living forms are facing many problems now-a-days. In current situation some existing wells getting dried up because of depletion of groundwater table as the natural groundwater recharge is not sufficient for requirements. As a result, the access to resources and their demand allows individuals to pick favorable locations for population increase. As the world’s population grows, so does urbanization and groundwater exploration. As a rising metropolitan region, it is critical to analyze the present groundwater scenario of the Koyna River watershed. This study is simple to do with the use of remote sensing and geographical information systems (GIS) by cost-effectively incorporating factors impacting groundwater potential. We will combine numerous data sets and maps in this study, including satellite imaging, drainage, groundwater level, precipitation, LULC, slope, and its existing geological map. After including the groundwater potential, it was divided into five distinct zones: extremely poor, poor, moderate, good, and very excellent [1].
Roadmap for network-based biocomputation
Authors: van Delft Falco C M J M , Månsson Alf , Kugler Hillel , Korten Till , Reuther Cordula , Zhu Jingyuan , Lyttleton Roman , Blaudeck Thomas , Meinecke Christoph Robert , Reuter Danny , Diez Stefan , Linke Heiner 
Published: July 2022

Abstract
Network-based biocomputation (NBC) is an alternative, parallel computation approach that can potentially solve technologically important, combinatorial problems with much lower energy consumption than electronic processors. In NBC, a combinatorial problem is encoded into a physical, nanofabricated network. The problem is solved by biological agents (such as cytoskeletal filaments driven by molecular motors) that explore all possible pathways through the network in a massively parallel and highly energy-efficient manner. Whereas there is currently a rapid development in the size and types of problems that can be solved by NBC in proof-of-principle experiments, significant challenges still need to be overcome before NBC can be scaled up to fill a technological niche and reach an industrial level of manufacturing. Here, we provide a roadmap that identifies key scientific and technological needs. Specifically, we identify technology benchmarks that need to be reached or overcome, as well as possible solutions for how to achieve this. These include methods for large-scale production of nanoscale physical networks, for dynamically changing pathways in these networks, for encoding information onto biological agents, for single-molecule readout technology, as well as the integration of each of these approaches in large-scale production. We also introduce figures of merit that help analyze the scalability of various types of NBC networks and we use these to evaluate scenarios for major technological impact of NBC. A major milestone for NBC will be to increase parallelization to a point where the technology is able to outperform the current run time of electronic processors. If this can be achieved, NBC would offer a drastic advantage in terms of orders of magnitude lower energy consumption. In addition, the fundamentally different architecture of NBC compared to conventional electronic computers may make it more advantageous to use NBC to solve certain types of problems and instances that are easy to parallelize. To achieve these objectives, the purpose of this roadmap is to identify pre-competitive research domains, enabling cooperation between industry, institutes, and universities for sharing research and development efforts and reducing development cost and time.
Detection Rate and Influencing Factors of Microalbuminuria in Hypertensive Patients
Authors: Xi Yang , Sun Ningling 
Published: July 2022

Abstract

Background
To investigate the detection rate and relevant influencing factors of microalbuminuria (MAU) in hypertensive patients in China.

Methods
A cross-sectional survey was conducted in 181,053 hypertensives from 600 hospitals across China. A questionnaire was used to collect information including patients’ risk factors, disease conditions, and antihypertensive drug treatment. Blood pressure was measured, and urine albumin to creatinine ratio was determined by urine strips. Patients were divided into the following subgroups: hypertension only, hypertension with and without MAU, cardiovascular risk factors, atherosclerotic cardiovascular disease (ASCVD), and single or combination drug therapy.

Results
A total of 136,483 patients with hypertension were enrolled. Patients with MAU, risk factors, and ASCVD or treated with combination drug therapy had significantly higher blood pressure compared with their corresponding counterparts (all P &lt; 0.001). The detection rate of MAU was 27.8%, 25.7%, 29.1%, and 33.4% in hypertension only, hypertension with cardiovascular risk factors, hypertension with ASCVD, and hypertension with cardiovascular risk factors and ASCVD, respectively. Multivariate logistic regression analysis showed that age &lt; 45 years, female, body mass index ≥ 28 kg/m2, living in Western China, living in Northeastern China, hypertension with risk factors and ASCVD, and combination drug therapy were positively correlated with MAU.

Conclusions
The detection rate of MAU is the highest in hypertensive patients with cardiovascular risk factors and ASCVD, and their blood pressure control is poor. Risk factor control and better blood pressure management are recommended.
Two Surgeons’ Approaches to the Upper Body Lift: A Video Discussion
Authors: Cinclair Richard , Aly Al , Kenkel Jeffrey 
Published: July 2022

Abstract

Body contouring post massive weight loss is becoming increasingly more common. In this article and accompanying video, 2 experienced surgeons, Jeffrey Kenkel, MD, and Al Aly, MD, discuss the upper body lift procedure through a moderated discussion. The goal of this article is to elucidate the similarities and differences between the surgeons’ guiding principles and specific approaches to this procedure. Topics covered in this discussion include indications, intraoperative sequencing, male chest, brachioplasty, closing technique, postoperative complications, and the typical postoperative course.

Level of Evidence: 4
Anti-skin-aging effects of human ceramides via collagen and fibrillin expression in dermal fibroblasts
Authors: Sugahara Yurika , Komorisono Masahiko , Kuwajima Mami , Yoshikawa Shuichi , Yoshida Shiori , Maeda Kazuhisa 
Published: July 2022

ABSTRACT
Intercellular lipids comprise mainly ceramides, known to enhance the barrier function of the stratum corneum. However, the activities of ceramides inside the skin have not yet been fully elucidated. Here we examined how the human ceramide mixture (HC123) functions in the dermis. We treated human skin fibroblasts with HC123-expressed fibroblast growth factor (FGF), transforming growth factor-β (TGF-β), collagen I, and fibrillin. We found that HC123 promoted the formation of collagen fibers and microfibrils (fibrillin) which affect the elasticity of the skin. We also confirmed that the gene expression of collagen and fibrillin is promoted via TGF-β and FGF2, respectively. We then investigated the permeability of HC123 for external use, in pursuit of evidence that HC123 may exert an anti-aging effect by penetrating into the dermis, activating fibroblasts, and promoting the production of collagen fibers and elastin-related microfibrils.
Online Multi-Component Cognitive Strategy Instruction for Cochlear Implant Users: Reading Comprehension
Authors: Akçakaya Hatice , Ergül Cevriye 
Published: July 2022

AbstractThe aim of this study was to examine the effect of online multi-component strategy instruction (MCCSI) on students with cochlear implants (CIs) regarding their reading comprehension. Moreover, it was to examine whether the students maintained and generalized the skills they acquired as well as the student’ and their mothers’ opinions regarding the intervention. This research was carried out with a multiple probe design across subjects. Three students with CIs who were in the fourth or fifth grade participated in this study. As a result, online MCCSI was found to be effective with a large effect size for all three students, and the students maintained their acquired skills at three and six weeks following the intervention. Additionally, two of the students were able to generalize the strategies they learned. Moreover, the opinions of the participating students and families regarding the social validity of the research were positive.