bluuebunny/crossref_metadata_2025_split huggingface dataset:
Early-winter North Atlantic low-level jet latitude biases in climate models: implications for simulated regional atmosphere-ocean linkages
Authors: Bracegirdle Thomas J , Lu Hua , Robson Jon 
Published: December 2021

Abstract
Climate model biases in the North Atlantic (NA) low-level tropospheric westerly jet are a major impediment to reliably representing variability of the NA climate system and its wider influence, in particular over western Europe. A major aspect of the biases is the occurrence of a prominent early-winter equatorward jet bias in Coupled Model Inter-comparison Project Phase 5 (CMIP5) models that has implications for NA atmosphere-ocean coupling. Here we assess whether this bias is reduced in the new CMIP6 models and assess implications for model representation of NA atmosphere-ocean linkages, in particular over the sub-polar gyre (SPG) region. Historical simulations from the CMIP5 and CMIP6 model datasets were compared against reanalysis data over the period 1861–2005. The results show that the early-winter equatorward bias remains present in CMIP6 models, although with an approximately one-fifth reduction compared to CMIP5. The equatorward bias is mainly associated with a weaker-than-observed frequency of poleward excursions of the jet to its northern position. A potential explanation is provided through the identification of a strong link between NA jet latitude bias and systematically too-weak model-simulated low-level baroclinicity over eastern North America in early-winter. CMIP models with larger equatorward jet biases exhibit weaker correlations between temporal variability in speed of the jet and sea surface conditions (sea surface temperatures and turbulent heat fluxes) over the SPG. The results imply that the early-winter equatorward bias in jet latitude in CMIP models could partially explain other known biases, such as the weaker-than-observed seasonal-decadal predictability of the NA climate system.
Modeling of colloidal systems in technological processes
Authors: Belenko E V , Sakharov P A , Khvatov A V , Lukanina Yu K 
Published: December 2021

Abstract
The article describes the main methods of mathematical modeling of industrial free-dispersed systems. The method of constructing the regression equation by the method of linear and nonlinear installation of coefficients is proposed. The fundamentals of tensor and harmonic approaches to the analysis of disperse systems are considered, which allow optimizing the equations of material and energy balance in the conditions of industrial operation of dispersions.
The application of basin modeling of oil and gas systems for seismogeological projects for assessment of hydrocarbon potential and risks of exploration work
Authors: Trigub A V , Chereneva K R 
Published: December 2021

Abstract
In this article, the methodology of basin modeling was systematized and the sequence of solutions to the applied problems related to the forecast of deposits of oil and gas was updated, and the applicability of basin modeling to traditional regional projects was evaluated.
Soil cryogenesis as a natural risk factor for gas pipelines in the permafrost zone during modern warming
Authors: Khudyakov I , Reshotkin O V , Demin D V 
Published: December 2021

Abstract
The paper summarizes the experience of studying the effect of modern warming on the thawing depth of sandy and loamy soils in the permafrost zone. The definition of soil cryogenesis as a natural process and facies as the end result of soil cryogenesis as a process is given. The effect of soil cryogenesis facies on stress corrosion cracking of gas pipes of the Gazprom system in cold and warm seasons has been studied. It was found that the facies of soil cryogenesis are interconnected by the process of energy and mass exchange. It is shown that in the annual cycle, each facies formed by soil cryogenesis is the basis for the development of stress corrosion cracking of gas pipelines.
Development of polymer emulsions stabilized with anionic polyelectrolytes
Authors: Khvatov A V , Sakharov P A , Lukanina Yu K , Belenko E V 
Published: December 2021

Abstract
The colloidal-chemical principles of the formation of reversibly reversible microemulsions based on compositions of anionic polysaccharides, higher fatty acids, and nonionic polyoxyethylated surfactants have been investigated. The structural formula of the interpolymer complex in the “polyelectrolyte - surfactant” system was proposed, and the molar ratios of the components were determined. The effectiveness of the developed polymer emulsions as drilling fluids for the construction of oil wells is shown.
Application of Machine Learning Algorithms in Predicting Pyrolytic Analysis Result
Authors: Suong Le Thi Nhut , Bondarev A V , Kozlova E V 
Published: December 2021

Abstract
Geochemical studies of organic matter in source rocks play an important role in predicting the oil and gas accumulation of any territory, especially in oil and gas shale. For deep understanding, pyrolytic analyses are often carried out on samples before and after extraction of hydrocarbon with chloroform. However, extraction is a laborious and time-consuming process and the workload of laboratory equipment and time doubles. In this work, machine learning regression algorithms is applied for forecasting S2ex based on the pyrolytic analytic result of non-extracted samples. This study is carried out using more than 300 samples from 3 different wells in Bazhenov formation, Western Siberia. For developing a prediction model, 5 different machine learning regression algorithms including Multiple Linear Regression, Polynomial Regression, Support vector regression, Decision tree and Random forest have been tested and compared. The performance of these algorithms is examined by R-squared coefficient. The data of the X2 well was used for building a model. Simultaneously, this data is divided into 2 parts – 80% for training and 20% for checking. The model also was used for prediction of wells X1 and X3. Then, these predictive results were compared with the real results, which had been obtained from standard experiments. Despite limited amount of data, the result exceeded all expectations. The result of prediction also showcases that the relationship between before and after extraction parameters are complex and non-linear. The proof is R2 value of Multiple Linear Regression and Polynomial Regression is negative, which means the model is broken. However, Random forest and Decision tree give us a good performance. With the same algorithms, we can apply for prediction all geochemical parameters by depth or utilize them for well-logging data.
Distributions of environmental parameters and fish at Humbold Bay, Jayapura
Authors: Pujiyati S , Hamuna B , Hisyam M , Rohilah  , Azzah A H , Sunarwati E , Pasaribu R 
Published: December 2021

Abstract
Research on the distribution of fish and plankton in waters that are equipped with environmental parameters is needed to obtain maximum results and increase accuracy also it provides comprehensive information. The research, which was conducted in Humbold Bay, aimed to map the fish and plankton distribution data both vertically and horizontally and combine it with environmental parameters in the bay. Fish and plankton’s data was the volume backscattering strength (Sv) value obtained using the SIMRAD EK-15 device while environmental parameter data, such as temperature, salinity, and chlorophyll obtained from marine.copernicus.eu which processed in the 5-80 m depth range. The results showed that Humbold Bay had the highest average surface temperature distribution was 30 °C, with the highest average salinity from 35.89 ppt and the highest average chlorophyll value from 0.3859 mg/m3. The horizontal distribution of plankton had an average SV value of -76.63 dB, while the fish was -56.00 dB that evenly distributed. Vertically, the Sv of plankton decreased with increasing depth as well as the Sv of fish which its’ also did not have a distribution pattern in certain environmental parameters.
Unmanned Surface Vehicle (USV) performance test in Bintan Island Waters
Authors: Fauzi R , Jaya I , Iqbal M 
Published: December 2021

Abstract
An unmanned surface vehicle (USV) is an unmanned vehicle that is operated on the surface of the water for certain purposes, for example, bathymetry measurement, underwater imaging, etc. These unmanned surface vehicles can be used in impassable waters for crewed vessels in dangerous waters. This research measures the movement of the vehicle acceleration and then calculates it as the USV roll and pitch values. The direction of movement and wind speed and the height of the water surface at low tide are also aspects measured in this research. An accelerometer is a sensor that can measure the acceleration of an object, both dynamic and static. Based on the observations, the highest roll value is 6.0° deep while the highest pitch value is 6.5°. The standard deviation value at roll conditions of 2.92 and the standard deviation value at pitch conditions of 1.25. The average frequency of roll conditions is 2.18 and pitch conditions of 1.13. The dominant wind moves from the south to the southwest with a dominant speed ranging from 3.0 to 4.0 m/s. The results of this research indicate that the USV has a good performance so that it is possible to collect data in the water.
Segmentation of seagrass (Enhalus acoroides) using deep learning mask R-CNN algorithm
Authors: Lestari N A , Jaya I , Iqbal M 
Published: December 2021

Abstract
Seagrass is an Angiosperms that live in shallow marine waters and estuaries. The method commonly used to identify seagrass is Seagrass-Watch which is done by sampling seagrass or by carrying a seagrass identification book. Technological developments in the era of the industrial revolution 4.0 made it possible to identify seagrass automatically. This research aims to apply the deep learning algorithm to detect seagrass recorded by underwater cameras. Enhalus acoroides seagrass species identification was carried out using a deep learning method with the mask region convolutional neural networks (Mask R-CNN) algorithm. The steps in the research procedure include collecting, labeling, training, testing models, and calculating the seagrass area. This study used 6000 epochs and got a measure of value generated by the model of ± 1.2. The Precision value, namely the model’s ability to correctly classify objects, reached 98.19% and the model’s ability to find all positive objects, based on system testing was able to perform recall is 95.04% and the F1 Score value of 96.58%. The results showed that the MASK R-CNN algorithm could detect and segment seagrass Enhalus acoroides.
Spatial and temporal analysis for mangrove community healthiness in Liki Island, Papua-Indonesia
Authors: Nurdiansah D , Dharmawan I W E 
Published: December 2021

Abstract
Indonesian mangrove declined significantly in the last two decades which has been considered to deliver a negative impact for adjacent communities in small islands. Mangrove quality monitoring was conducted during Nusa Manggala Expedition in 2018, which was aimed to analyze forest structure and healthiness using spatial-temporal investigation in Liki island, Papua. Field data were collected from 10m-×-10m quadratic plots which were distributed following stratified purposive sampling method. Spatial and temporal was implemented using Sentinel 2 imagery on this area from 2016 to 2021. The result of this field study had considered that mangrove in Liki island was in moderate healthiness since the MHI value was between 33.33%-66.67%. It was supported by remote sensing analysis in 2018 which showed that the moderate MHI area was dominant by approximately 42% compared to the excellent area in about 33%. Liki’s mangrove had experienced a declining trend of excellent category from 2016 and reached the lowest area of its category in 2018. In the last four-year observation, excellent areas gradually increased which was covering 57.68% of forest MHI. The dynamic of mangrove healthiness on this island tended to be delivered by natural events.
Distribution and diversity of gelatinous zooplankton in the southern South China Sea
Authors: Kamaruddin N A , Ishak N H A 
Published: December 2021

Abstract
Although gelatinous zooplankton are widely distributed in many ocean ecosystems, they have been understudied due to their fragility nature, difficulties to sample or handle and a lack of expertise. This study gives an insight into the distribution and diversity of gelatinous species in the Southern South China Sea. Species composition, distribution and abundance of gelatinous zooplankton were investigated along the East Coast of Peninsular Malaysia. A total of 37 species were recorded from 10 locations along 4 transects at 5.10° N and 6.80° N extending from 103.2° E to 105.3° E in August 2016. Seven medusae, six siphonophores, four appendicularians, six chaetognaths, six salps, four doliolids and four pteropods were identified from the study area. Appendicularia with 201 ind/m3 was found to be the most dominant taxa recorded, followed by chaetognaths with 197 ind/m3. Scyphomedusae were the least represented group in the study, with an abundance of 8 ind/m3. Stations near the inshore region show higher abundance and diversity of gelatinous zooplankton compared to offshore regions. The evenness index between stations revealed that the gelatinous zooplankton were evenly distributed. According to Principal Component Analysis (PCA), the diversity and distribution of gelatinous zooplankton are driven by depth and temperature.
The application of Landsat imageries and mangrove vegetation index for monitoring mangrove community in Segara Anakan Lagoon, Cilacap, Central Java
Authors: Prayudha B , Siregar V , Ulumuddin Y I , Suyadi  , Prasetyo L B , Agus S B , Suyarso  , Anggraini K 
Published: December 2021

Abstract
The only place for estuarine-mangroves in Java Island, Segara Anakan Lagoon, experiences the vast decline of mangrove cover. Satellite remote sensing has a critical role in monitoring that change as it allows to record vast areas over time. However, most studies tend to utilize satellite data to investigate the change of mangrove areas into other land-use types rather than identify the mangrove community’s shifting. This study utilized the mangrove vegetation index (MVI) for monitoring the changes of mangrove communities at the life-form level using satellite data. The study used multi-temporal Landsat images as it has historical systematic archive data. The threshold value of the index for each class is defined by referring to the field data. The class referred to the life-form classification consisting of mangrove trees, Nypa, and understorey. The image analysis was conducted using Google Earth Engine (GEE), while R software was used for determining threshold values through statistical analysis. The result shows that the MVI can differentiate between some life forms of mangroves, with the overall accuracy reaching 78.79% and a kappa coefficient of 0.729. Further, the multi-temporal maps showed the decline of mangrove tree areas, which the understorey and Nypa community have replaced.
Suitability analysis of mangrove conversation areas in Mundu District, Cirebon Regency using Geographic Information Systems (GIS)
Authors: Akbar M R , Abimanyu A , Faid G M , Izza M Y N , As-syahiraand Z N , Febriani C 
Published: December 2021

AbstractThis study aims to analyze the suitability of mangrove conservation areas in the Mundu District, Cirebon Regency. In this study, we used Sentinel-2A satellite data obtained from ESA Copernicus’s web to analyze the normalized difference vegetation index (NDVI) of mangrove that will be used as a mangrove health indicator and several oceanographic characteristics to assess the suitability of mangrove conservation areas based on weighing-scores systems. All data were then analyzed using image processing combined with geographic information systems (GIS) tools available in the open-access QGIS software. Results show that the health of the mangrove based on vegetation index was in the range of 0.3–0.6. Mangroves in Mundu Region have consisted of two species,Avicennia marina, andRhizophora apiculata. The substrate in this area is dominated by muddy sand with a pH value of 8 and an average salinity of 32 PSU. The tidal type in Mundu region has mixed semi-diurnal characteristics with an average tidal height of 1.22 m. Based on those parameters and NDVI analysis, the suitability rank for mangrove conservation areas can be classified as suitable with a total score in the ranges of 101-200.
Spatial and temporal variability of satellite sea surface temperature in the Makassar Strait and the Java Sea
Authors: Syahdan M , Atmadipoera A S , Susilo S B , Lumban-Gaol J 
Published: December 2021

Abstract
Sea surface temperature (SST) data obtained from the Aqua-MODIS satellite from 2002 to 2012 were analyzed to determine the spatial and temporal variability in the key region of small pelagic fisheries between Makassar Strait and the Java Sea. Results of the Empirical Orthogonal Function (EOF) analysis show that the characteristics of this region are described by 60% based on the greatest contribution value respectively. The largest contribution of 52% shows that the SSTs in this region is warm. A strong indicator of these conditions appears in the east through the southern part of Kalimantan Island while the weak indicator is in the south to western part of Sulawesi Island. The temporal variation shows that the annual oscillation is dominant in this area where maximum SSTs occurs in the first transitional monsoon (April), while the minimum occurs in the southeast monsoon period (August). The influence of southeast monsoon formats the minimum SSTs area in the south of South Sulawesi that is generated by parallel wind-driven induces to the coast and the divergent current close to the coast. Due to inter-annual variability, minimum SSTs occurs before the El Nino episode whereas the maximum occurs before the La Nina event.
Internal solitary waves in the Northwest Sumatra Sea-Indonesia: from observation and modeling
Authors: Prasetya I A , Atmadipoera A S , Budhiman S , Nugroho U C 
Published: December 2021

Abstract
>The southern Andaman waters has been well known as one of the strongest generating and propagating area of internal solitary waves (ISWs), generated by semidiurnal barotropic tidal currents that impinge submarine ridge offshore western Weh. This study aims to investigate sea surface features of internal tides and tidal current around the submarine ridge and adjacent Weh-Aceh waters, derived from satellite imagery datasets (January-May 2018) and CROCO model-output datasets. The results show that sea surface signatures of ISWs are characterized by a strong radar signal backscattering of a dense ripple package in the generating area and two groups of ISWs arch in the propagating area, where the distance of the package groups and wavelengths vary 60-80 km and 9-163 km, respectively. Observed ISWs in March 2018 was 31. The satellite and model datasets suggest that generating area of internal waves is confined over the Breuh ridge. Here, the very strong semidiurnal (M2) barotropic tidal currents of 0.5-5.0 m/s are observed. During high-tide, amplified barotropic tidal currents acrossing the ridge flow partly southeastward into the Weh-Breuh passage. The model suggests that generating internal tidal waves over the ridge are manifested by strong vertical perturbation of isopycnal and current stratifications in the Lee-waves area.
Analysis of the relationship between chlorophyll-a and sea surface temperature on marine capture fisheries production in Indonesia: 2018
Authors: Ningsih W A L , Lestariningsih W A , Heltria S , Khaldun M H I 
Published: December 2021

Abstract
Fishery production in Indonesia is still relatively high, dominated by the marine capture fisheries. Oceanographic dynamics can affect the high and low levels of marine fishery production. Sea surface temperature and chlorophyll-a are oceanographic parameters that are often used as indicators for determining fishing areas, especially pelagic fish which are associated with ocean fertility. This study aims to identify the effect of chlorophyll-a and sea surface temperature (SST) on the production of fish catches in Indonesia: 2018. Data on marine capture fisheries production (skipjack, mackerel tuna, tuna and shrimp) in 2018 were obtained from the Ministry of Marine Affairs and Fisheries (KKP). Data of Chlorophyll-a and sea surface temperature (SST) are satellite observations from Marine Copernicus. The relationship between chlorophyll-a and sea surface temperature (SST) with marine capture fisheries production was analyzed using logistic regression analysis. The results showed that chlorophyll-a significantly affected the yield of skipjack and tuna in Indonesia with coefficients of -5.7066 and -4.3760, respectively. A higher concentration of chlorophyll-a had the possibility to produce high fish production of 0.0033 times than an area with a lower concentration of chlorophyll-a.
Turbulent mixing process in the Lombok Strait
Authors: Naulita Y , Natih N M N , Nabil  
Published: December 2021

AbstractTurbulent mixing process in the Lombok Strait was evaluated from density inversions in CTD (Conductivity Temperature Depth) profiles obtained from the INSTANT (International Nusantara Stratification and Transport) recovery cruise, June 14-19th2005. The quality of the detected-overturn regions has been improved by applying wavelet denoising to CTD signals. The Thorpe analysis shows that many overturn regions less than 7 m were detected in throughout the water column of the Lombok Strait. Based on linear relationship between Thorpe Scale and Ozmidov Scale, the turbulent kinetic energy dissipation rate ε was estimated about 10−12−10−6W kg−1and density of eddy diffusivityKρ(10−6−10−2m2s−1). A relatively high ofKρØ (10−2m2s−1) was found at the southern part of the strait, near the sill which obstruct the Indonesian Thoughflow into the Indian Ocean. The dipped and rebounded isopycnal surfaces of σθ= 25.5–26.5 near the sill and the presence of strong shear at the same depth of the interval solitary wave (150 to 250 m) indicate that strong turbulence in this layer was driven by shear instability associated with breaking internal waves.
Broadband absorption of monolayer MoS2 in visible region using a tetramerized nanorod metasurface
Authors: Pei Yao , Sang Tian , Mi Qing , Wang Jicheng , Wang Yueke 
Published: December 2021

Abstract
High-efficient broadband absorption of the monolayer MoS2 is achieved by using a tetramerized nanorod metasurface (TNM), and the average absorption of 64.5% for the monolayer MoS2 can be obtained in the visible range of 400–750 nm. The unit cell of the TNM consists four Ag nanorods with different diameters, the incident light can be selectively absorbed by the monolayer MoS2 due to the magnetic resonance associated with the individual Ag nanorod, and broadband absorption of the monolayer MoS2 is realizable due to the cooperative magnetic resonances related to the tetramerized Ag nanorods. In addition, the absorption of the monolayer MoS2 is robust to the variation of the structural parameters, and it exhibits wide-angle and polarization-independent features.