The fate of humankind and all other life forms on earth is threatened by a foe, known as climate change. All parts of the world are affected directly or indirectly by this phenomenon. The rivers are drying up in some places and in other places, it is flooding. The global temperature is rising every year and the heat waves are taking many souls. The cloud of "extinction" is upon the majority of flora and fauna; even humans are prone to various fatal and life-shortening diseases from pollution. This is all caused by us. The so-called "development" by deforestation, releasing toxic chemicals into air and water, burning of fossil fuels in the name of industrialisation, and many others have made an irreversible cut in the heart of the environment. However, it is not too late; all of this could be healed back with the help of technology and our efforts together. As per the international climate reports, the average global temperature has increased by a little more than 1 °C since 1880s. The research is primarily focused on the use of machine learning and its algorithm to train a model that predicts the ice meltdown of a glacier, given the features using the Multivariate Linear Regression. The research strongly encourages the use of features by manipulating them to determine the feature with a major impact on the cause. The burning of coal and fossil fuels is the main source of pollution as per the study. The research focuses on the challenges to gather data that would be faced by the researchers and the requirement of the system for the development of the model. The study is aimed to spread awareness in society about the destruction we have caused and urges everyone to come forward and save the planet.
This report assesses the effects of stratospheric ozone depletion and anticipated ozone recovery on the intensity of ultraviolet (UV) radiation at the Earth's surface. Interactions between changes in ozone and changes in climate, as well as their effects on UV radiation, are also considered. These evaluations focus mainly on new knowledge gained from research conducted during the last four years. Furthermore, drivers of changes in UV radiation other than ozone are discussed and their relative importance is assessed. The most important of these factors, namely clouds, aerosols and surface reflectivity, are related to changes in climate, and some of their effects on short- and long-term variations of UV radiation have already been identified from measurements. Finally, projected future developments in stratospheric ozone, climate, and other factors affecting UV radiation have been used to estimate changes in solar UV radiation from the present to the end of the 21st century. New instruments and methods have been assessed with respect to their ability to provide useful and accurate information for monitoring solar UV radiation at the Earth's surface and for determining relevant exposures of humans. Evidence since the last assessment reconfirms that systematic and accurate long-term measurements of UV radiation and stratospheric ozone are essential for assessing the effectiveness of the Montreal Protocol and its Amendments and adjustments. Finally, we have assessed aspects of UV radiation related to biological effects and human health, as well as implications for UV radiation from possible solar radiation management (geoengineering) methods to mitigate climate change.
Evidence on rising global temperature, melting of ice caps, and withdrawal of glaciers
brings attentions to the enhancement of energy efficiency in energy intensive industries. Having a
realistic comparison between one plant and the best practice technology (BPT) in operation in the field
helps significantly to distinguish and diagnose the potentials where measures towards energy efficiency
improvement would be applicable. In this regard, for manufacturing industries, one of the most widely
used energy benchmarking tools is the Energy Benchmark Curve. An energy benchmark curve plots the
efficiency of plants as a function of the total production volume from all similar plants or as a function
of the total number of plants that operate at that level of efficiency or worse. This paper reviews the
methodology through which the benchmark curve is obtained for a specific industry followed by a
comparison of energy intensity for the iron and steel industry among China and the US. According to
the international energy benchmark curve for the iron and steel industry, the savings potentials per ton
of crude steel for the US. and China have been respectively 4.1 and 7.1 gigajoule comparing with the
BPT in the field. Finally, an overview over certain measures to enhance efficiency of such plants is
presented.
Three techniques to retrieve information on sea ice thickness from both active and passive radar backscatter data are presented. The first inversion model is a combination of the radiative transfer theory with dense medium phase and amplitude correction theory (DMPACT), and the Levenberg-Marquardt optimization algorithm. The radiative transfer theory was applied as the forward model to generate radar backscatter data, while the DMPACT was included to account for the close spacing effect among the scatterers within the medium. The Levenberg-Marquardt optimization algorithm was then applied to reduce the error between the model generated radar backscatter data and the measured radar backscatter data from satellite images so that the sea ice thickness could be estimated. The second method presented was the neural network inversion method which utilizes a chain of neurons with variable weights. Once the network was fully operational it would be possible to predict the sea ice thickness, provided sufficient training data are given. The last method was the genetic algorithm which is a search technique used in order to predict the approximate sea ice thickness from the measured data. Data from ground truth measurements carried out in Ross Island, Antarctica, together with radar backscatter data extracted from purchased satellite images were used as input to verify the models. All three models were tested and successfully predicted sea ice thickness from actual terrain using the ground truth measurement data, with several constraints and assumptions placed to avoid problems during the retrieval process. While the models still have their own limitations, the potential use of the models for actual sea ice thickness retrieval was confirmed.
Glaciozyma antarctica PI12, is a psychrophilic yeast isolated from Antarctic sea. In this work, Expressed Sequence Tags (EST) from cells exposed to three different temperatures; 15 °C, 0 °C and -12 °C were generated to identify genes associated with cold adaptation. A total of 5376 clones from each library were randomly picked and sequenced. Comparative analyses from the resulting ESTs in each condition identified several groups of genes required for cold adaptation. Additionally, 319 unique transcripts that encoded uncharacterised functions were identified in the -12 °C library and are currently unique to G. antarctica. Gene expression analysis using RT-qPCR revealed two of the unknown genes to be up-regulated at -12 °C compared to 0 °C and 15 °C. These findings further contribute to the collective knowledge into G. antarctica cold adaptation and as a resource for understanding the ecological and physiological tolerance of psychrophilic microbes in general.
Mood profiling has a long history in the field of sport and exercise. Several novel mood profile clusters were identified and described in the literature recently (Parsons-Smith et al., 2017). In the present study, we investigated whether the same clusters were evident in an Italian-language, sport and exercise context. The Italian Mood Scale (ITAMS; Quartiroli et al., 2017) was administered to 950 Italian-speaking sport participants (659 females, 284 males, 7 unspecified; age range = 16-63 year, M = 25.03, SD = 7.62) and seeded k-means clustering methodology applied to the responses. Six distinct mood profiles were identified, termed the iceberg, inverse iceberg, inverse Everest, shark fin, surface, and submerged profiles, which closely resembled those reported among English-speaking participants (Parsons-Smith et al., 2017). Significant differences were found in the distribution of specific mood profiles across gender and age groups. Findings supported the cross-cultural generalizability of the six mood profiles and offer new research avenues into their antecedents, correlates and behavioral consequences in Italian-language contexts.
Satellite imagery reveals flowstripes on Foundation Ice Stream parallel to ice flow, and meandering features on the ice-shelf that cross-cut ice flow and are thought to be formed by water exiting a well-organised subglacial system. Here, ice-penetrating radar data show flow-parallel hard-bed landforms beneath the grounded ice, and channels incised upwards into the ice shelf beneath meandering surface channels. As the ice transitions to flotation, the ice shelf incorporates a corrugation resulting from the landforms. Radar reveals the presence of subglacial water alongside the landforms, indicating a well-organised drainage system in which water exits the ice sheet as a point source, mixes with cavity water and incises upwards into a corrugation peak, accentuating the corrugation downstream. Hard-bedded landforms influence both subglacial hydrology and ice-shelf structure and, as they are known to be widespread on formerly glaciated terrain, their influence on the ice-sheet-shelf transition could be more widespread than thought previously.
Metal ions are one of the essential elements which are extensively involved in many cellular activities. With rapid advancements in genome sequencing techniques, bioinformatics approaches have provided a promising way to extract functional information of a protein directly from its primary structure. Recent findings have suggested that the metal content of an organism can be predicted from its complete genome sequences. Characterizing the biological metal usage of cold-adapted organisms may help to outline a comprehensive understanding of the metal-partnerships between the psychrophile and its adjacent environment. The focus of this study is targeted towards the analysis of the metal composition of a psychrophilic yeast Glaciozyma antarctica PI12 isolated from sea ice of Antarctica. Since the cellular metal content of an organism is usually reflected in the expressed metal-binding proteins, the putative metal-binding sequences from G. antarctica PI12 were identified with respect to their sequence homologies, domain compositions, protein families and cellular distribution. Most of the analyses revealed that the proteome was enriched with zinc, and the content of metal decreased in the order of Zn > Fe > Mg > Mn, Ca > Cu. Upon comparison, it was found that the metal compositions among yeasts were almost identical. These observations suggested that G. antarctica PI12 could have inherited a conserved trend of metal usage similar to modern eukaryotes, despite its geographically isolated habitat.
Global warming is reducing the Arctic sea-ice and causing energetic stress to marine key predatory species such as polar bears and narwhals contributing to the ongoing pollution already threatening the biodiversity and indigenous people of the vulnerable region. Now, the opening of the Arctic gateway and in particular the increase in shipping activities causes further stress to marine mammals in the region. These shipping activities are foreseen to happen in the Northwest and Northeast Passage, Northern Sea Route and Transpolar Sea Route in the Arctic Ocean, which could be yet another step towards a crucial tipping point destabilizing global climate, including weathering systems and sea-level rise. This calls for international governance through the establishment of Arctic International National Parks and more Marine Protected Areas through the Arctic Council and UN's Law of the Sea to ensure sustainable use of the Arctic Ocean and adjacent waters.
Genome data mining of the Antarctic yeast, Glaciozyma antarctica PI12 revealed an expansin-like protein encoding sequence (GaEXLX1). The GaEXLX1 protein is 24.8 kDa with a high alkaline pI of 9.81. Homology modeling of GaEXLX1 showed complete D1 and D2 domains of a conventional expansin. The protein exhibited 36% sequence similarity to Clavibacter michiganensis EXLX1 (PDB: 4JCW). Subsequently, a recombinant GaEXLX1 protein was produced using Escherichia coli expression system. Incubation with Avicel, filter paper and cotton fiber showed that the protein can disrupt the surface of crystalline and pure cellulose, suggesting a cell wall modification activity usually exhibited by expansin-like proteins. Binding assays displayed that GaEXLX1 can bind to polymeric substrates, including those postulated to be present in the sea ice ecosystem such as crab chitin and moss lichenan. GaEXLX1 may assist in the recognition and loosening of these substrates in the sea ice prior to hydrolysis by other extracellular enzymes. Similar loosening mechanism to classical expansin-like protein has been postulated for this psychrophilic protein based on several conserved residues of GaEXLX1 involved in binding interaction identified by docking analyses.
Today, insular Southeast Asia is important for both its remarkably rich biodiversity and globally significant roles in atmospheric and oceanic circulation. Despite the fundamental importance of environmental history for diversity and conservation, there is little primary evidence concerning the nature of vegetation in north equatorial Southeast Asia during the Last Glacial Period (LGP). As a result, even the general distribution of vegetation during the Last Glacial Maximum is debated. Here we show, using the stable carbon isotope composition of ancient cave guano profiles, that there was a substantial forest contraction during the LGP on both peninsular Malaysia and Palawan, while rainforest was maintained in northern Borneo. These results directly support rainforest "refugia" hypotheses and provide evidence that environmental barriers likely reduced genetic mixing between Borneo and Sumatra flora and fauna. Moreover, it sheds light on possible early human dispersal events.