bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparative analysis of numerical methods for determining parameters of chemical reactions from experimental data
Authors: Prikhodko Aleksei , Shishlenin Maxim , Stadnichenko Olga
Published: December 2021

The aim of this paper is to select an optimal numerical method for determining the parameters of chemical reactions. The importance of the topic is due to the modern needs of industry, such as the improvement of chemical reactors and oil or gas processing. The paper deals with the problem of determining reaction rate constants using gradient methods and stochastic optimization algorithms. To solve an forward problem, implicit methods for solving stiff ODE systems are used. A correlation method of practical identifiability of the required parameters is used. The genetic algorithm, particle swarm method, and fast annealing method are implemented to solve an inverse problem. The gradient method for the solution of the inverse problem is implemented, and a formula for gradient of the functional is given with the corresponding adjoint problem. We apply an identifiability analysis of the unknown coefficients and arrange the coefficients in the order of their identifiability. We show that the best approach is to apply global optimization methods to find the interval of global solution and after that we refine inverse problem solution using gradient approach.
Two optimization methods for solving the inverse gravimetrical problem
Authors: Kenzhebayeva Merey
Published: December 2021

Mineral exploration, in particular, increasing the accuracy of calculations up to now is one of the urgent problems of geophysics. It is necessary to restore the density of a given inhomogeneity after considering the results of measuring the potential and its gradient on the surface of the earth. One of the measured values, the potential or the gradient of the gravity field, is chosen beyond the boundary condition, and the second corresponds to the minimized functional, i.e. one in-verse problem can be put in correspondence two different optimization problems. Both problems are solved based on the same gradient method. Based on the numerical analysis, two methods for solving the inverse problem are compared.
Identification of spacewise dependent right-hand side in two dimensional parabolic equation
Authors: Su LingDe , Vasil’ev V. I.
Published: December 2021

In this paper numerical solution of the inverse problem of determining a spacewise dependent right-hand side function in two dimensional parabolic equation is considered. Usually, the right-hand side function dependent on spatial variable is obtained from measured data of the solution at the final time point. Many mathematical modeling problems in the field of physics and engineering will encounter the inverse problems to identify the right-hand terms. When studying an inverse problem of identifying the spacewise dependent right-hand function, iterative methods are often used. We propose a new conjugate gradient method based on the constructed self-adjoint operator of the equation for numerical solution of the function and numerical examples illustrate the efficiency and accuracy.
Quantity of the inverse problem data for the system of conservation laws
Authors: Klyuchinskiy D.V. , Novikov N.S. , Shishlenin M.A.
Published: December 2021

In this paper we study properties of the model, that describes the plane acoustic waves propagation. The model is based on the hyperboliv system of PDE, which is solved numerically by using the finite-volume method, based on Godunov scheme. After studying the direct problem we turn to the inverse one, where our goal is to recover the parameters of the system of PDE by using the initial data, measured in the receivers. We obtain the formula for the gradient of the misfits functional, which allows us to apply gradient-based optimization for recovering the density of the medium. We present the results of numerical experiments for different number of receivers, thus, studying the influence of the quantity of the data of inverse problem on the accuracy of the solution.
Gelfand-Levitan-Krein method in one-dimensional elasticity inverse problem
Authors: Kabanikhin Sergey I. , Novikov Nikita S. , Shishlenin Maxim A.
Published: December 2021

In this article we propose the numerical solution of the one dimensional inverse coefficient problem for seismic equation. We use a dynamical version of Gelfand-Levitan-Krein approach for reducing a nonlinear inverse problem for recovering the shear wave’s velocity and the density of the medium to two sequences of the linear integral equations. We propose numerical algorithm for solving these equations based on a fast inversion of a Toeplitz matrix. The proposed numerical methods base on the structure of the problem and therefore improve the efficiency of the algorithms, compared with standard approaches. We present numerical results for solving considered integral equations.
Numerical Identification of the Filtration Capacitive Parameters in Two-Phase Petroleum Reservoirs
Authors: Sakabekov A. , Ahmed Zaki D. , Auzhani Y.
Published: December 2021

We study initial and boundary value problem for nonlinear three dimensional two phase nonlinear filtration problem in three dimensional bounded regions. The reservoir is a two phase and three dimensional oil-water system that is been implemented with typical parallelepiped model. The reservoir constructed with different number of grid blocks in x, y and z directions and initialized with initial pressure, water saturation, corresponding fluid and rock properties in every grid block. To find approximate solution of the above mentioned problem we use finite difference method. We form solution’s algorithm of inverse problem for numerical parameter identification of the petroleum reservoir.
Reservoir Parameters Estimation with Some Log Curves of Qiongdongnan Basin Based on LS-SVM Method
Authors: Liu Tangwei , Xu Hehua , Shi Xiaobin , Qiu Xuelin , Sun Zhen
Published: December 2021

Reservoir porosity and permeability are considered as very important parameters in characterizing oil and gas reservoirs. Traditional methods for porosity and permeability prediction are well log and core data analysis to get some regression empirical formulas. However, because of strong non-linear relationship between well log data and core data such as porosity and permeability, usual statistical regression methods are not completely able to provide meaningful estimate results. It is very difficult to measure fine scale porosity and permeability parameters of the reservoir. In this paper, the least square support vector machine (LS-SVM) method is applied to the parameters estimation with well log and core data of Qiongdongnan basin reservoirs. With the log and core exploration data of Qiongdongnan basin, the approach and prediction models of porosity and permeability are constructed and applied. There are several type of log data for the determination of porosity and permeability. These parameters are related with the selected log data. However, a precise analysis and determine of parameters require a combinatorial selection method for different type data. Some curves such as RHOB,CALI,POTA,THOR,GR are selected from all obtained logging curves of a Qiongdongnan basin well to predict porosity. At last we give some permeability prediction results based on LS-SVM method. High precision practice results illustrate the efficiency of LS-SVM method for practical reservoir parameter estimation problems.
Development and modeling of some elements of the two-wheeled mobile robot system
Authors: Karpov Alexander O , Karpov Alexey O , Yu Vasilyeva M , Belashova И E S
Published: December 2021

The article deals with the navigation system elements development process. The movement and positioning of a two-wheeled mobile robot with a high level of accuracy are realized through this system. Also, the algorithms mechanisms based on the construction of the optimal path for the autonomous device movement and based on a map building in an unknown area and avoiding obstacles are described. Using mathematical models, computer modeling of the device executive system is carried out using the engineering program MatLab.
Comparative Analysis of Efficiency of the Machine Learning Methods for Gesture Recognition Using Double-Channel Electromyography
Authors: Ponomarchuk Y V , Kuznetsov I V
Published: December 2021

The paper is devoted to the efficiency analysis of the machine learning methods for gesture recognition, which are applied to the surface double-channel electromyography data. The comparative analysis was conducted for recognition of eight types of palm movements. The results of the analysis lead to conclusion that it is necessary to consider the muscle groups’ location for better recognition accuracy and the increase of the number of considered gestures.
Deployment of Software-Controlled Distributed Laboratory Complex for a Higher Educational Institution
Authors: Kodolov S D , Klimova A S , Yu Filimonov A , Aksyonova E K
Published: December 2021

The intensive development of information systems and communication infrastructures has led to the emergence of new approaches and new tools for their management. Cloud services, virtualization technologies and software-based management tools are actively used today for building modern information systems which provides additional opportunities for managing components of these systems and for expanding such systems abilities. The use of such approaches and tools can provide a solution to the complex of problems faced by education institutions today, presenting new methods of distance learning and new forms of practical training. The balanced use of virtualization technologies and software-based control tools allows building distributed laboratory complexes of a new generation which will provide new possibilities for using the equipment that is available in educational institutions. The use of such complexes in the educational process allows not only to instill in students the skills of managing the confgura-tions of communication infrastructures that are especially relevant today, but also to organize, in addition to traditional laboratory work, new forms of contactless practical classes. When conducting such classes, students get the opportunity to fully-functional remote access to the virtual and physical components of the complex, which is especially important for organizing the educational process in modern conditions associated with the COVID-19 pandemic.The article discusses modern approaches to the construction of software-controlled communication infrastructures, tools for software-based management of their components and also, an example of the implementation of these approaches and such tools usage in the construction of a distributed laboratory complex for a higher educational institution. The main advantages of the approach based on the use of hypervisors and emulators are presented, the experience of its deployment in the modernization of the laboratory complex for a IRIT-RTF UrFU is considered.
Text-based Recommendation Systems for Software Developers: A Systematic Literature Review
Authors: Gorb Anna
Published: December 2021

Purpose: The aim of this SLR is to look at recommendation systems which receive textual information as an input. By analysing them it is possible to understand how the textual information is preprocessed and which algorithms are then used to generate recommendations. Methods: With the Search Query I frst identifed 487 papers, from which 65 were removed as duplicates. After the IC and EC application, 28 articles remained as relevant. Results: From these articles’ analysis, it was found that the most commonly used pre-processing techniques are tokenization, TF-IDF, and stopwords removal. I also determined that all algorithms for suggestions generation in such systems can be divided into 4 categories: classifcation, ranking, clustering, and heuristic-based algorithms. In the last step I found that the most frequent output of such systems are API, code, and workers suggestions. Conclusion: With this work, I looked at which pre-processing techniques are used in the text-based recommender systems for software developers and which are the most common. I have also looked at the classifcation of algorithms for such recommendation systems. Finally, I considered what kind of objects are recommended by these text-based recommendation systems.
Data-Driven Approaches to User Interface Design: A Case Study
Authors: Pimenov Denis , Solovyov Alexander , Askarbekuly Nursultan , Mazzara Manuel
Published: December 2021

The most common reason for software product failure is misunderstanding user needs. Analysing and validating user needs before developing a product can allow to prevent such failures. This paper investigates several data-driven techniques for user research and product design through prototyping, customer validation, and usability testing. The authors implemented a case study software product using the proposed techniques, and analyses how the application of UX/UI research techniques affected the development process. The case study results indicate that preliminary UX/UI research before the development reduces the cost of product changes. Moreover, the paper proposes a set of metrics for testing the effectiveness of UX/UI design.
Development of a text analysis agent for a logistics company's Q&A system
Authors: Aksyonov K. A. , Ziomkovskaya P. E. , Danwitch Dougandaga , Aksyonova O. P. , Aksyonova E. K.
Published: December 2021

The "Twin" system is an omnichannel communication platform for building voice and chatbots, capable, in particular, of receiving data in one language and transmitting in another. "Twin" can record voice and text, display detailed statistics and analytics for each call or dialog. In this article, using the Twin system, a chatbot was created for the field of cargo transportation, it describes its advantages and disadvantages and the principle of creating of such chatbots.
Spectral efficiency analysis of two-user Downlink PD-NOMA with LTE modulation and coding schemes
Authors: Kryukov Ya. V. , Pokamestov D. A. , Abenov R. R. , Mukhamadiev S. M. , Kanatbekuli I.
Published: December 2021

Non-orthogonal multiple access (NOMA) is a promising user multiplexing technique for future wireless networks that allows increasing their spectral efficiency (SE). Power-Domain NOMA (PD-NOMA) is one of the most perspective techniques in the NOMA group. It makes it possible to perform the transmission of information symbols of several users within the same time-frequency resource segment (RS) without a spreading code. Many research works show the high efficiency of PD-NOMA compared to the orthogonal multiple access (OMA). However, these results are obtained analytically using Shannon’s formula and not taking into account the real performance of existing modulation and coding schemes (MCS). The issue is that it is impossible to obtain the achievable practical performance of PD-NOMA systems in this way. We obtain the SE in RS of a PD-NOMA system with Long Term Evolution (LTE) MCS’s and compare it with OMA. As a result, we conclude that PD-NOMA gains the system SE when the multiplexed user’s signal-to-noise ratio (SNR) outreaches the threshold of the highest performing MCS provided for the transmission by a MCS table.
Hardware Phase Shift Hybrid Precoding Designs For Multi-User Massive MIMO Systems
Authors: Ayad H , Bendimerad M Y , Bendimerad F T
Published: December 2021

Hybrid precoding is a challenging design for massive MIMO systems that involves a combination of analog and digital processing, aiming to maximize the spectral efficiency (SE). Most works on hybrid precoding focus on the single phase shifter (SPS) implementation to adapt the phase from RF chains to antennas. In this paper we propose to develop the double phase shifter (DPS) and the fixed phase shifter (FPS) in both single-path and multi-path configuration. Simulation results certify a significant improvement for both proposed implementations with high hardware efficiency (HE) and high spectral efficiency especially in multi-path environment.
Radiation patterns of patch antennas on coated conducting cylinders
Authors: Chechetkin V A , Shabunin S N , Korotkov A N
Published: December 2021

The development of the Internet of Things and communication systems of the fifth generation leads to the need to place many antenna elements in a limited volume. Therefore, wearable electronics antennas are often located directly on the device body. Such surfaces can often be thought of as a conducting cylinder covered with a dielectric material. The task of analysing the radiation patterns of antennas located on such surfaces becomes urgent. This paper shows a method for analysing antenna directivity diagrams using the Green’s functions method of cylindrical layered media. This method allows to obtain in an analytical form the expressions for the analysis of such structures, which makes it possible to reduce the cost of computer time in modelling. The presented results show what kind of distortions are introduced into the radiation pattern of antennas located on a cylinder compared to an antenna located on a flat surface.
Classification Method of Rape Root Swelling Disease Based on Convolution Neural Network
Authors: Gao Yuan , Liu Changhua , Wu Xiaoming
Published: December 2021

Both the seedling stage and the adult plant stage of rape can be infected with root edema, and the damaged roots swell to form tumors of different sizes and shapes. The incidence of rape root swelling at the seedling stage reached 17%, and the average incidence at the adult plant stage was 15%, resulting in a 10.2% reduction in rape production. The average plant height, number of siliques, number of kernels per horn, 1000-seed weight and yield per plant of healthy plants were significantly higher than those of diseased plants. Grading root lesions can help trace the root causes of root lesions. However, the method of grading is often performed manually by professionals at present, which has the problems of low speed and low efficiency. In order to solve this problem, a method for grading rape root swelling based on deep convolutional neural network is proposed in this paper. Firstly, a rape root swelling model based on convolutional neural network and regional candidate network was established, and then implement it on the deep learning Tensorflow framework Model, and finally compare and analyze the results. The rape root swelling model uses the VGG16 network to extract the characteristics of the rape root swelling image. The regional candidate network generates the preliminary position candidate frame of the rape root swelling, and Fast-RCNN realizes the classification and positioning of the candidate frame. The results show that this method can achieve rapid and accurate detection of healthy, first-level tumors, second-level tumors, and third-level tumors of four-level rape root swelling, with an average accuracy rate of 84.12%. The experimental results show that the accuracy rate can reach more than 90%.
Plant root PET: visualization of photosynthate translocation to roots in rice plant
Authors: Miyoshi Y. , Nagao Y. , Yamaguchi M. , Suzui N. , Yin Y.-G. , Kawachi N. , Yoshida E. , Takyu S. , Tashima H. , Yamaya T. , Kuya N. , Teramoto S. , Uga Y.
Published: December 2021

Roots are essential to plants for uptake of water and nutrients. For the improvement of crop production, it is necessary to understand the elucidation of the root development and its function under the ground. Especially, photosynthate translocation from plant leaves to roots is an important physiological function that affects the root elongation, adaptation to the soil environment and nutrients uptake. To evaluate the translocation dynamics to roots, positron emission tomography (PET) and 11C tracer have been used. However, the spatial resolution is degraded at roots that develop around the peripheral area of field of view (FOV) due to parallax errors. In this study, to overcome this problem, we developed a small OpenPET prototype applying four-layer depth-of-interaction detectors. We demonstrated the imaging capability of 11C-photosynthate translocation to rice roots that develop throughout the entire PET field. We also tried to obtain structural information of roots by high-throughput X-ray computerized tomography (CT) system using the same test plant. As a result, we succeeded in visualizing the root structure that developed around the peripheral region of FOV and imaging the accumulation of 11C-photosynthate to the roots in those areas without degrading the spatial resolution. From obtained images, we also succeeded in evaluating the translocation dynamics varied by roots. The combined use of the high-throughput CT system and the OpenPET prototype was demonstrated to be appropriate for structural and functional analysis of roots.
Neutron energy spectrum measurement using CLYC7-based compact neutron emission spectrometer in the Large Helical Device
Authors: Sangaroon S. , Ogawa K. , Isobe M. , Kobayashi M.I. , Fujiwara Y. , Kamio S. , Yamaguchi H. , Seki R. , Nuga H. , Toyama S. , Miwa M. , Matsuyama S. , Takada E. , Murakami S. , Zhong G.Q. , Osakabe M.
Published: December 2021

Tangential compact neutron emission spectrometer (CNES) based on the Cs2LiYCl6:Ce with 7Li-enrichment (CLYC7) scintillator is newly installed in the Large Helical Device (LHD). Measurement of neutron energy spectrum was performed using CNES in tangential neutral beam (NB) heated deuterium plasma discharges. The Doppler shift of neutron energy according to the direction of tangential NB injection has been obtained. When the fast ions moving away from the CNES, lower shifted neutron energy is obtained, whereas the upper shifted neutron energy is obtained when the fast ions moving toward the CNES. The obtained neutron energy is almost consistent with the virgin deuterium-deuterium neutron energy evaluated by the simple two-body kinematic calculation.
Plasma diagnostic systems and methods used on the stellarator TJ-II
Authors: McCarthy K.J.
Published: December 2021

The TJ-II is a heliac-type stellarator device with major radius of 1.5 m and averaged minor radius ⩽0.22 m that has been operated at CIEMAT, Madrid since 1998. Its full magnetic field is created by a system of poloidal, central, toroidal and vertical field coils, thus it possesses a fully 3-dimensional plasma structure and a bean-shaped plasma cross-section. Although this results in a complicated vacuum-vessel layout, it has excellent port access for diagnostics (96 portholes). During its initial operational phase, it was equipped with a limited set of essential diagnostics. Since then, a broad variety and large number of both passive and active diagnostics have been installed. The former include Hα monitors, light spectrometers, an electron cyclotron emission radiometer, X-ray filter monitors, neutral particle analysers, magnetic diagnostics, as well as cameras, among others, while the latter include various laser, atomic and ion beam based diagnostics, microwave probe beams, Langmuir probes plus impurity injection techniques. In this paper, after describing the TJ-II stellarator, its heating and fuelling systems, the diagnostic systems employed are outlined and discussed briefly here. Finally, results obtained with selected systems are highlighted.
Large-scale forest conservation and restoration programs significantly contributed to land surface greening in China
Authors: Zhao Haiwei , Wu Chaoyang , Wang Xiaoyue
Published: December 2021

China has implemented a portfolio of large-scale forest conservation and restoration programs (FCRPs) to advance the sustainable management of forests. However, the contributions of these programs to forest recovery and land surface greening were generally evaluated on a local scale, which hindered the systematic planning of FCRPs. In this study, we analyzed the spatiotemporal patterns of tree cover (TC) change before and after the intensification of FCRPs using the Mann-Kendall test and the Theil–Sen slope estimator. With the improved phenology-based residual trend analysis (P-RESTREND) method, we derived the spatiotemporal patterns of human-induced tree cover (TCH) change on the national scale. Then, we calculated the effectiveness index of FCRPs at the provincial level, based on which the effectiveness levels for the 31 provinces of mainland China were classified. Our study showed that the area of forested lands with a significant greening trend was almost five times larger in the post-intensification phase (1999–2015) than in the pre-intensification phase of FCRPs (1982–1998). More than 29.9% of the forested lands were significantly improved in TC by human activities in the post-intensification phase. Provinces with high effectiveness levels were generally distributed in humid areas, whereas the majority of provinces with low and moderately low effectiveness levels were spread in arid and semi-arid regions. We concluded that the implementation of FCRPs had contributed greatly to the land surface greening in China. Moreover, the effectiveness of FCRPs in forest recovery was heterogeneous at the provincial level and was driven by multiple natural and socioeconomic factors.
On the attribution of the impacts of extreme weather events to anthropogenic climate change
Authors: Perkins-Kirkpatrick S E , Stone D A , Mitchell D M , Rosier S , King A D , Lo Y T E , Pastor-Paz J , Frame D , Wehner M
Published: December 2021

Investigations into the role of anthropogenic climate change in extreme weather events are now starting to extend into analysis of anthropogenic impacts on non-climate (e.g. socio-economic) systems. However, care needs to be taken when making this extension, because methodological choices regarding extreme weather attribution can become crucial when considering the events’ impacts. The fraction of attributable risk (FAR) method, useful in extreme weather attribution research, has a very specific interpretation concerning a class of events, and there is potential to misinterpret results from weather event analyses as being applicable to specific events and their impact outcomes. Using two case studies of meteorological extremes and their impacts, we argue that FAR is not generally appropriate when estimating the magnitude of the anthropogenic signal behind a specific impact. Attribution assessments on impacts should always be carried out in addition to assessment of the associated meteorological event, since it cannot be assumed that the anthropogenic signal behind the weather is equivalent to the signal behind the impact because of lags and nonlinearities in the processes through which the impact system reacts to weather. Whilst there are situations where employing FAR to understand the climate change signal behind a class of impacts is useful (e.g. ‘system breaking’ events), more useful results will generally be produced if attribution questions on specific impacts are reframed to focus on changes in the impact return value and magnitude across large samples of factual and counterfactual climate model and impact simulations. We advocate for constant interdisciplinary collaboration as essential for effective and robust impact attribution assessments.
Forest Fire Mapping using Normalized Burned Ratio and Cloud Computing to Calculate the Losses Incurred in Mount Lawu, Magetan Regency
Authors: Sukojo Bangun Muljo , Arimurti Adinda Sitaresmi Putri
Published: December 2021

Forest and land fires in Indonesia are one of the most common disasters. Over time, Indonesia’s forests have experienced a decline, one of which is the result of forest and land fires. Forest and land fires can occur due to temperatures in the dry season that continue to increase. Utilization of remote sensing technology can be used for mapping forest and fire areas, and can also be used as a reference for the government to carry out reforestation or reforestation processes in fire areas. The use of Multispectral Sensors in Sentinel 2 satellite imagery can be used to produce this research. This research takes a case study on Mount Lawu, Magetan Regency. Mount Lawu is one of the climbing tourist destinations that almost every year experiences forest and land fires. And the use of the Google Earth Engine platform that supports cloud computing to facilitate this research in accessing high data sources to process large geospatial data sets. For processing satellite images using the Normalized Burned Ratio (NBR) vegetation index processing algorithm. This research was conducted in 2018 and 2019. By using the Random Forest method, which is one of the applications of Machine Learning, it will produce several accurate results from the calculation results. The results of the calculation of the area of fire in 2018 were 284.88 hectares with a total loss of Rp 42,732,000.00 and in 2019 it was 146.03 hectares with a total loss of Rp 21,904,500. The results of this study are displayed on GEE Apps so that users can directly access the resulting data.
Tank Modeling and Its Condition Assessment using Terrestrial Laser Scanner
Authors: Gumilar Irwan , Gaol Samuel Van Livtrik Lumban , Munarda Made , Bramanto Brian , Lukmanulhakim Agus
Published: December 2021

Condition assessment of the tank must be carried out since it is related to Health, Safety, and Environment (HSE). Assessment is carried out by referring to the applicable standards. This study aims to create a 3D (Dimension) model and assess the tank using Terrestrial Laser Scanner technology. This includes planning, data acquisition, data processing, and data visualization. The data processing process starts with the registration stage with the cloud-to-cloud method, georeferencing, 3D modeling using point cloud, and tank assessment filtered point cloud data. Assessment includes analysis of volume, verticality/slope (in terms of the difference between upper and lower tank), and roundness calculations. The 3D model of the tank was generated with a registration error of less than 1 cm. The volume of tank I and tank II were calculated to 134.108 m3 and 134.067 m3, respectively. The difference between the upper and lower radius for each tank ranges from 2 to 10 mm. Considering the results and recalling the API 650 standard (American Petroleum Institute), each tank is considered reliable and in a good condition.
Identification of Land Criticality with the Application of Deep Learning in West Lahat District Using Sentinel-2A Imagery
Authors: Izzaty Atika , Sukojo Bangun Muljo
Published: December 2021

Land is an important factor in human life. In addition of land use that continue to increase every year. Land use is an element of meeting needs. This situation often makes the condition of the land around it questionable the content and level of land productivity. Land whose productivity level is lost can cause critical land to occur. Coupled with the occurrence of uncontrolled development, land productivity has decreased. By using the application of remote sensing, it is able to monitor land conditions, one of which is by using Sentinel-2A data. Sentinel-2A image data was selected to identify the condition or distribution of critical land and critical land parameters that has the most influence on criticality level of the land with Sentinel-2A imagery with a spatial resolution of 10 meters for Red, Green, Blue, and Near-Infrared canals to perform NDVI classification processing. closely related to vegetation. Based on the Regulation of the Director General of Watershed Management and Social Forestry Number: P.4/V-SET/2013 concerning the Technical Guidelines for the Preparation of Spatial Data for Critical Lands, there are 5 parameters for determining the criticality of the processed land as indicators, including the level of erosion distribution, productivity land, land management, slope, and vegetation density. Based on the results of the study, the researchers found that the distribution of critical land in Lahat Regency was 19 hectares or 0.56%, the critical class was 36,090 hectares or 10.1%, the critical potential class was 142,140 hectares or 42.1%, the class which was slightly critical is 156,860 hectares or 46.5%, and non critical class is 3 hectares or 0.074%. for very critical class. These results can be seen with the parameter that most affects the criticality of the land is vegetation density.
Analysis of outdoor thermal comfort using three-dimensional microclimate modelling in Surabaya
Authors: Firdaus Z M , Handayani H H
Published: December 2021

Surabaya is one of the metropolitan cities in Indonesia. The large population in Surabaya causes a lot of development and land conversion. This situation can affect the temperature in Surabaya to be higher than the surrounding area, thus affecting the comfort of people for outdoor activities. The level of comfort can be known when the microclimate conditions in the area have been identified. This paper aims to analyze outdoor thermal conditions using temperature, humidity, wind, and land use data which will be visualized in three dimensions to get a more comprehensive understanding. This research is located in Pakuwon Trade Center (PTC). Data acquisition was carried out on four different types of land cover, namely local residential, apartments, main parking lots, and real estate area. The results show that apartments have the lowest comfort index followed by real estate, local residential, and main parking lots. However, the four areas have comfort from warm to hot with a predicted percentage of the discomfort of around 75% - 100%. This number shows that mitigation that can reduce extreme heat and increase outdoor comfort in PTC is needed.
Analysis of Tsunami Wave Height, Run-up, and Inundation in The Coastal of Blitar and Malang Regency
Authors: Armono Haryo Dwito , Putra Adryanto Rama , Wahyudi
Published: December 2021

Indonesia is an archipelago located at the meeting point of 3 tectonic plates which constantly collide over time, the energy due to the collision will accumulate and be able to cause large earthquakes that can generate tsunamis. The island of Java is in the subduction zone of these plates, which causes the southern part of Java to have a high earthquake potential. On April 10, 2021, an earthquake measuring M 6.1 occurred in the south of Blitar and Malang. This earthquake was felt by most of the people of East Java, If the earthquake is large enough, it can cause a tsunami on the southern coast of East Java. Therefore, modeling was carried out using the FLOW module of Delft3D software while using earthquake parameters with a strength of M 9.1 which is the worst possible scenario on the southern coast of East Java. The results of this study indicate the fastest tsunami arrival time is 21 minutes, the highest maximum tsunami height is 20 meters, the highest run-up reaches 17,5 meters, and the furthest inundation reaches 765 meters along the southern coast of Blitar and Malang Regency.
OIL PATTERN IDENTIFICATION ANALYSIS USING SEMANTIC DEEP LEARNING METHOD FROM PLEIADES-1B SATELIITE IMAGERY WITH ARCGIS PRO SOFTWARE (Case Study: Village “A”)
Authors: Anita Novi , Sukojo Bangun Muljo , Meisajiwa Sondy Hardian , Romadhon Muhammad Alfian
Published: December 2021

There are many petroleum mining activities scattered in developing countries, such as Indonesia. Indonesia is one of the largest oil-producing countries in Southeast Asia with the 23rd ranking. Since the Dutch era, Indonesia has produced a very large amount of petroleum. One of the oil producing areas is “A” Village. There is an old well that produces petroleum oil which is still active with an age of more than 100 years, for now the oil well is still used by the local community as the main source of livelihood. With this activity, resulting in an oil pattern around the old oil refinery, which over time will absorb into the ground. This study aims to analyze and identify the oil pattern around the old oil refinery in the “A” area. The data used is in the form of High-Resolution Satellite Imagery (CSRT), namely Pleiades-1B with a spatial resolution of 1.5 meters. Data were identified using the Deep Learning Semantic method. For the limitation of this research is the administrative limit of XX Regency with a scale of 1: 25,000 as supporting data when cutting the image. The method used is the Deep Learning Convolutional Neural Network series. This research is based on how to wait for the method of the former oil spill which is the consideration of the consideration used. This study produced a land cover map that was classified into 3 categories, namely oil patterns area, area not affected by oil and vegetation. As a supporting value to show the accuracy of the classification results, an accuracy test method is used with the confusion matrix method. To show the accuracy of this study using thermal data taken from the field. Thermal data used in the form of numbers that show the temperature of each land cover. Based on the above reference, a research related to the analysis of very high-resolution image data (Pleiades-1B) will be conducted to examine the oil pattern. This research uses the deep learning series convolutional neural network (CNN) method. With this research, it is hoped that it can help agencies in knowing the right method to identify oil in mainland areas.
Preliminary Study of Probolinggo Active Fault in East Java Based on Gravity Method
Authors: Rochman Juan Pandu Gya Nur , Purwanto M.Singgih , Hilyah Anik , M. Haris Miftakhul F , Nuswantara Mohamad Setyo Ari , Nuriyah Syafiatun
Published: December 2021

The Gravity Method based on TOPEX satellite data is a one of geophysical method which from satellite observations. The gravity method investigate the gravitational field from one to another observation point. The principle of this method has the ability to distinguish the mass material density from its environment, so that the subsurface structure can be identified. In this research, gravity method is used to identify subsurface structures that are suspected of Probolinggo Fault and identify the rock lithology. From TOPEX we get free air anomaly and then applied the correction process to obtain Complete Bouguer Anomaly (CBA) value. The CBA value is processed interpolation to create CBA map, and then the map is filtered by butterworth to obtain regional and residual maps. The value of high gravity acceleration is 0.076 - 19.74 mGal indicating compact rocks. Meanwhile, based on the residual anomaly map, the value of smaller gravity acceleration is -0.92 - 0.9 mGal indicates lower compacting rocks with smaller mass. The gravity acceleration contrast on the residual anomaly, on the north side of fault line (0.12 mGal to 0.45 mGal) and on the south side (-0.92 mGal to -0.043 mGal), is interpreted as normal fault. Furthermore, 3D modelling shows density value less than 2 gr/cm3 we can interpret as pyroclastic fall, in between 2 gr/cm3 until 2.4 gr/cm3 is sandstone and more than 2.4 gr/cm3 is igneous rock such as andesit. 2D slicing modelling show presence the shear fault, so we can suspect this area have oblique fault with west-east direction.
The Effect of Greenness Index on Case Fatality Rate of Covid-19 Analyzed by Using Landsat-8 Image (Case Study: DKI Jakarta)
Authors: Adiba Aqiyasa , Jaelani Lalu Muhamad
Published: December 2021

COVID-19 is spreading into Indonesia and has reached tens of thousands of cases as of September 30, 2020. It was recommended by the American Public Health Association and the Centers for Disease Control and Prevention to remain physically active during COVID-19 quarantine by regularly visiting parks and green spaces as it can protect the body against the consequences of quarantine impacting physical and mental health. In this research, green space was monitored by using remotely sensed data. The green space distribution was obtained from the calculation of the Greenness Index from Landsat-8 Surface Reflectance Tier 1 satellite imagery processed through the Google Earth Engine platform. This study was conducted to determine the value of Greenness Index (GI), Case Fatality Rate (CFR) value due to COVID-19, and the relationship between them in 42 sub-districts in DKI Jakarta in the period of April to September 2020. Twenty-eight subdistricts (67%) showed negative correlation values that indicated that more green space in a region affects lower CFR growth.
HHLA2 Immune Checkpoint Is a Novel Prognostic Predictor in Hepatocellular Carcinoma
Authors: Liao Xiaoyan , Zhang Dongwei
Published: December 2021

Objectives

Immunotherapy targeting PD-1/PD-L1 had low response rates and limited overall survival benefits in patients with hepatocellular carcinoma (HCC). We characterized the expression pattern and clinical significance of B7 family immune checkpoint proteins HHLA2, PD-L1, and B7-H4 in HCC.

Methods

Immunohistochemistry for HHLA2, PD-L1, B7-H4, CD3, and CD8 was performed on tissue microarray slides from 103 surgically resected HCC specimens.

Results

Positive HHLA2 was detected in 63 (61.2%) cases, with 50 cases showing low expression and 13 cases showing high expression. Positive PD-L1 (combined positive score [CPS] ≥1) was detected in 27 (26.2%) cases, with the majority showing low expression (CPS <10) (n = 25) and only 2 cases showing high expression (CPS ≥10). The coexpression of PD-L1 and HHLA2 was observed in 17 (16.5%) cases. B7-H4 expression was detected in only one (1.0%) case. HHLA2-positive cases had significantly better survival than HHLA2-negative cases (P = .042). Positive HHLA2 correlated with higher density of CD8+ intratumoral lymphocytes (P = .015). The subgroup with both HHLA2 expression and high CD8+ cell density exhibited the most favorable prognosis (P = .036).

Conclusions

HHLA2 is frequently expressed in HCC. Positive HHLA2 correlates with higher CD8+ cell density and favorable prognosis. HHLA2 may be considered a potential therapeutic immune target in HCC.
Cortical tracking of formant modulations derived from silently presented lip movements and its decline with age
Authors: Suess Nina , Hauswald Anne , Reisinger Patrick , Rösch Sebastian , Keitel Anne , Weisz Nathan
Published: December 2021

The integration of visual and auditory cues is crucial for successful processing of speech, especially under adverse conditions. Recent reports have shown that when participants watch muted videos of speakers, the phonological information about the acoustic speech envelope, which is associated with but independent from the speakers’ lip movements, is tracked by the visual cortex. However, the speech signal also carries richer acoustic details, for example, about the fundamental frequency and the resonant frequencies, whose visuophonological transformation could aid speech processing. Here, we investigated the neural basis of the visuo-phonological transformation processes of these more fine-grained acoustic details and assessed how they change as a function of age. We recorded whole-head magnetoencephalographic (MEG) data while the participants watched silent normal (i.e., natural) and reversed videos of a speaker and paid attention to their lip movements. We found that the visual cortex is able to track the unheard natural modulations of resonant frequencies (or formants) and the pitch (or fundamental frequency) linked to lip movements. Importantly, only the processing of natural unheard formants decreases significantly with age in the visual and also in the cingulate cortex. This is not the case for the processing of the unheard speech envelope, the fundamental frequency, or the purely visual information carried by lip movements. These results show that unheard spectral fine details (along with the unheard acoustic envelope) are transformed from a mere visual to a phonological representation. Aging affects especially the ability to derive spectral dynamics at formant frequencies. As listening in noisy environments should capitalize on the ability to track spectral fine details, our results provide a novel focus on compensatory processes in such challenging situations.
Predictors of Severe Acute Respiratory Syndrome Coronavirus 2 Infection Following High-Risk Exposure
Authors: Andrejko Kristin L , Pry Jake , Myers Jennifer F , Openshaw John , Watt James , Birkett Nozomi , DeGuzman Jennifer L , Barbaduomo Camilla M , Dong Zheng N , Fang Anna T , Frost Paulina M , Ho Timothy , Javadi Mahsa H , Li Sophia S , Tran Vivian H , Wan Christine , Jain Seema , Lewnard Joseph A ,   California COVID-19 Case-Control Study Team, Samani Helia , Walas Nikolina , Xavier Erin , Poindexter Diana J , Dabbagh Najla , Spinosa Michelle M , Saretha Shrey , Cornejo Adrian F , Park Hyemin , Bermejo Miriam I , Lam Amanda , Kaur Amandeep , Dyke Ashly , Felipe Diana , Spencer Maya , Corredor Savannah , Abdulrahim Yasmine
Published: December 2021

Background

Non-pharmaceutical interventions (NPIs) are recommended for COVID-19 prevention. However, the effectiveness of NPIs in preventing SARS-CoV-2 transmission remains poorly quantified.

Methods

We conducted a test-negative design case-control study enrolling cases (testing positive for SARS-CoV-2) and controls (testing negative) with molecular SARS-CoV-2 diagnostic test results reported to California Department of Public Health between 24 February–12 November, 2021. We used conditional logistic regression to estimate adjusted odds ratios (aORs) of case status among participants who reported contact with an individual known or suspected to have been infected with SARS-CoV-2 (“high-risk exposure”) ≤14 days before testing.

Results

751 of 1448 cases (52%) and 255 of 1443 controls (18%) reported high-risk exposures ≤14 days before testing. Adjusted odds of case status were 3.02-fold (95% confidence interval: 1.75–5.22) higher when high-risk exposures occurred with household members (vs. other contacts), 2.10-fold (1.05–4.21) higher when exposures occurred indoors (vs. outdoors only), and 2.15-fold (1.27–3.67) higher when exposures lasted ≥3 hours (vs. shorter durations) among unvaccinated and partially-vaccinated individuals; excess risk associated with such exposures was mitigated among fully-vaccinated individuals. Cases were less likely than controls to report mask usage during high-risk exposures (aOR = 0.50 [0.29–0.85]). The adjusted odds of case status was lower for fully-vaccinated (aOR = 0.25 [0.15–0.43]) participants compared to unvaccinated participants. Benefits of mask usage were greatest among unvaccinated and partially-vaccinated participants, and in interactions involving non-household contacts or interactions occurring without physical contact.

Conclusions

NPIs reduced the likelihood of SARS-CoV-2 infection following high-risk exposure. Vaccine effectiveness was substantial for partially and fully vaccinated persons.