bluuebunny/crossref_metadata_2025_split huggingface dataset:
A solution to a sex ratio puzzle inMelittobiawasps
Authors: Abe Jun , Iritani Ryosuke , Tsuchida Koji , Kamimura Yoshitaka , West Stuart A. 
Published: May 2021

SignificanceMany social interactions generate "a tragedy of the commons," where individuals would do better if everyone cooperated, but selfish interests can select against cooperation. Examples range from the production of extracellular enzymes by bacteria, to cooperative breeding in animals, to female-biased sex ratios in structured populations, where brothers compete for mates. We examined the offspring sex ratios produced byMelittobiawasps in natural populations and found that females adjust their offspring sex ratio in response to both the presence of other females and whether they had dispersed. Dispersal matters because it determines the genetic relatedness between interacting individuals, and so an analogous influence of dispersal would be predicted for a range of cooperative traits, including parasite virulence.
Equatorial auroral records reveal dynamics of the paleo-West Pacific geomagnetic anomaly
Authors: He Fei , Wei Yong , Maffei Stefano , Livermore Philip W. , Davies Christopher J. , Mound Jon , Xu Kaihua , Cai Shuhui , Zhu Rixiang 
Published: May 2021

SignificanceThe structure of Earth’s ancient magnetic field is constrained by paleomagnetic measurements. However, owing to data sparsity, models need to be smoothed; such smoothing can obscure rapid but crucial fluctuations in the field. We have shown that historical observations of equatorial aurorae can provide added constraints on the dynamics of Earth’s deep interior, suggesting possible fluctuating behavior of a low-intensity geomagnetic anomaly during the seventeenth and eighteenth centuries in the West Pacific. This anomaly is an ancient analogue to the present-day South Atlantic Anomaly, whose existence impacts the functioning of low-Earth orbit satellites. Our study sheds light on the origin, time dependence, and possible future evolution of similar geomagnetic features.
E-H mode transitions and high-energy electron characteristics of helical antenna coupled plasma
Authors: Wang Chuansheng , Lin Xin , Li Fei , Yu Xilong 
Published: May 2021

Abstract
Metastable and high-energy electron characteristics obtained from optical emission spectroscopy are used to analyze the dependence of the H mode on the magnetic field strength and discharge pressure. The results show that the H-mode characteristics gradually appears as the magnetic field strength is increased, the reason being that electrons undergo multiple acceleration-collision cycles at high magnetic field strength, thereby the metastable ionization will be increased. This improves energy utilization and making the H mode appearing. The variation in the density of metastable states and the Langmuir probe data shows that the electron energy distribution function evolves from non-Maxwellian to Maxwellian. The radial constraint of the magnetic field to the electrons and thus reduces the electron heating efficiency. Moreover, the increase in electric field strength with magnetic field leads to an increase in energy obtained by the electrons per unit distance. The competition between the two makes the number of high-energy electrons decrease rapidly first, and then increase slowly with magnetic field strength increasing. The turning point increases with the increase of discharge pressure and radio-frequency (RF) power. And the higher the pressure the lower the high-energy electron. For fields between 105.5 G and 212.7 G. In the H-mode regime, and with increasing RF power, the number of high-energy electrons will be sudden rise after experiencing a steady increase. The sudden rise RF power increase with magnetic field and decrease with discharge pressure increase. However, at high magnetic fields (>265 G) and high power (>450 W), the high-energy electron density decreases with power increasing.
First-principles identification of deep energy levels of sulfur impurities in silicon and their carrier capture cross sections
Authors: Cai Lele , Wang Shanshan , Huang Menglin , Wu Yu-Ning , Chen Shiyou 
Published: May 2021

Abstract
Studies of the deep energy levels and nonradiative carrier capture induced by sulfur doping in silicon were initiated 60 years ago; however, the defect configurations, their deep energy levels, and the carrier capture cross sections are still not well understood. In this study, we focus on SSi substitution, and perform a first-principles study of its defect configurations and the deep energy levels using hybrid exchange-correlation functional. We discover a new distortive configuration for SSi
+ besides the previously obtained structure with higher symmetry. For both SSi
+ configurations, the deep transition levels

ε

(0/+) and

ε

(+/2+) are determined as 0.35 eV and 0.68 eV below the conduction band minimum, respectively. As a benchmark calculation, the hole-capture cross sections for neutral and +1 charged states are obtained based on the distortive structure. The cross section for SSi
+ agrees with the experiment, demonstrating the multi-phonon process for SSi
+ capturing a hole, whereas the cross section of SSi
0 is significantly lower than the experimental data because hole capture by SSi
0 is an Auger-type process. Our calculations provide a benchmark for the evaluation of the cross section of carrier capture in semiconductors using multi-phonon nonradiative recombination theory.
Semiconductor nanowire arrays for optical sensing: a numerical insight on the impact of array periodicity and density
Authors: Zagaglia Luca , Demontis Valeria , Rossella Francesco , Floris Francesco 
Published: May 2021

Abstract
Recent advances in the nanofabrication and modeling of metasurfaces have shown the potential of these systems in providing unprecedented control over light–matter interactions at the nanoscale, enabling immediate and tangible improvement of features and specifications of photonic devices that are becoming always more crucial in enhancing everyday life quality. In this work, we theoretically demonstrate that metasurfaces made of periodic and non-periodic deterministic assemblies of vertically aligned semiconductor nanowires can be engineered to display a tailored effective optical response and provide a suitable route to realize advanced systems with controlled photonic properties particularly interesting for sensing applications. The metasurfaces investigated in this paper correspond to nanowire arrays that can be experimentally realized exploiting nanolithography and bottom-up nanowire growth methods: the combination of these techniques allow to finely control the position and the physical properties of each individual nanowire in complex arrays. By resorting to numerical simulations, we address the near- and far-field behavior of a nanowire ensemble and we show that the controlled design and arrangement of the nanowires on the substrate may introduce unprecedented oscillations of light reflectance, yielding a metasurface which displays an electromagnetic behavior with great potential for sensing. Finite-difference time-domain numerical simulations are carried out to tailor the nanostructure parameters and systematically engineer the optical response in the VIS-NIR spectral range. By exploiting our computational-methods we set-up a complete procedure to design and test metasurfaces able to behave as functional sensors. These results are especially encouraging in the perspective of developing arrays of epitaxially grown semiconductor nanowires, where the suggested design can be easily implemented during the nanostructure growth, opening the way to fully engineered nanowire-based optical metamaterials.
Balanced charge transport and enhanced performance of blue quantum dot light-emitting diodes via electron transport layer doping
Authors: Yang Yue , Su Liang , Feng Nannan , Liu Anqi , Xing Xiaoxue , Lu Min , Yu William W 
Published: May 2021

Abstract
The unbalanced charge transport is always a key influencing factor on the device performance of quantum dot light-emitting diodes (QLEDs), particularly for the blue QLEDs due to their large optical band gap. Here, a method of electron transport layer (ETL) doping was developed to regulate the energy levels and the carrier mobility of the ETL, which resulted in more balanced charge injection, transport and recombination in the blue emitting CdZnS/ZnS core/shell QLEDs. Consequently, an enhanced performance of blue QLEDs was achieved by modulating the charge balance through ETL doping. The maximum external quantum efficiency and luminance was dramatically increased from 2.2% to 7.3% and from 3786 cd m−2 to 9108 cd m−2, respectively. The results illustrate that charge transport layer doping is a simple and effective strategy to regulate the charge injection barrier and carrier mobility of QLEDs.
Efficient inverse design and spectrum prediction for nanophotonic devices based on deep recurrent neural networks
Authors: Yan Ruoqin , Wang Tao , Jiang Xiaoyun , Huang Xing , Wang Lu , Yue Xinzhao , Wang Huimin , Wang Yuandong 
Published: May 2021

Abstract
The development of nanophotonic devices has presented a revolutionary means to manipulate light at nanoscale. How to efficiently design these devices is an active area of research. Recently, artificial neural networks (ANNs) have displayed powerful ability in the inverse design of nanophotonic devices. However, there is limited research on the inverse design for modeling and learning the sequence characteristics of a spectrum. In this work, we propose a deep learning method based on an improved recurrent neural network to extract the sequence characteristics of a spectrum and achieve inverse design and spectrum prediction. A key feature of the network is that the memory or feedback loops it comprises allow it to effectively recognize time series data. In the context of nanorods hyperbolic metamaterials, we demonstrated the high consistency between the target spectrum and the predicted spectrum, and the network learned the deep physical relationship concerning the structural parameter changes reflected on the spectrum. The effectiveness of our approach is also tested by user-drawn spectra. Moreover, the proposed model is capable of predicting an unknown spectrum based on a known spectrum with only 0.32% mean relative error. The prediction model may be helpful to predict data beyond the detection limit. We propose this versatile method as an effective and accurate alternative to the application of ANNs in nanophotonics, paving way for fast and accurate design of desired devices.
Research on Guidance and Control Law Design of Decelerating Transition and Vertical Landing for a STOVL UAV
Authors: Dong Zixu , Ren Yang , Chen Kun , Chen Yaohui 
Published: May 2021

Abstract
In this paper, an integrated design method for guidance and control laws for a short takeoff and vertical landing (STOVL) unmanned aerial vehicle (UAV) during decelerating transition and vertical landing phases under thrust vector control is studied. Based on the principle of time-scale separation, the outer-loop guidance law adopts an implicit dynamic inverse method to provide attainable overload vector control instructions for decelerating transition and vertical landing phases. Meanwhile, the inner-loop control law adopts an improved eigen-structure assignment method, which tracks guidance instructions and maintains a stable attitude. The attitude nozzles are joined to the attitude control with the dropping of dynamic pressure, thereby assisting aerodynamic surfaces to stabilize attitudes. Subsequently, the feasibility and effect of the control methods for a STOVL UAV during decelerating transition and vertical landing phases are verified by a 6-DOF flight simulation platform. The simulation results demonstrate that the integrated design method is beneficial for a quick evaluation of the overall scheme.
Performance of backpropagation artificial neural network to predict el nino southern oscillation using several indexes as onset indicators
Authors: Aprilia B , Marzuki  , Taufiq I 
Published: May 2021

AbstractEl Nino Southern Oscillation (ENSO) is a world’s climate anomaly that occurs repeatedly, unavoidable, has significant natural disaster impact for countries around the Pacific Ocean include Indonesia. ENSO has a time series of predictors, so it can be predicted the Artificial Neural Network (ANN). ANN has several important advantages over the more statistical models traditionally used. ANNs can accommodate non-linear relationship and the flexibility in testing multiple inputs. This research aims to predict the onset of ENSO using the ANN-backpropagation method of learning rate and momentum variation. The prediction is based on several indexes during 1979-2018, i.e., Sea Surface Temperature (Nino 1.2, Nino 3, Nino 3.4, and Nino 4), Southern Oscillation Index (SOI), Multivariate ENSO and then verified with prediction data from the International Research Institute (IRI). The results of this prediction stated that in the period JAS (July-August-September) and DJF (December-January-February) 2020/2021 world climate conditions are in normal ENSO in which there are no El Nino and La Nina phenomena. Thus, the ANN-backpropagation method is an appropriate method to predict ENSO.
Effect of ansatz on soliton propagation pattern in photorefractive crystals
Authors: Ripai A , Sutantyo Trengginas E P , Abdullah Z , Syafwan M , Hidayat W 
Published: May 2021

Abstract
Soliton propagation and some related parameter in a photorefractive crystal are considered. This study analyzes the soliton propagation on a photorefractive crystal having both linear and quadratic electro-optical effects through a time-dependent model of nonlinear dynamics equation using the numerical split-step Fourier method. In conducting analysis, we apply various models of ansatz as initial conditions of the optical beam envelope. Based on the studies conducted, ansatz influences the soliton propagation pattern in the photorefractive crystals. Besides, we found ansatz in secant-hyperbolic and Gaussian functions as the most appropriate model for realizing solitons in crystals. Finally, the photorefractive effect supports the evolution of soliton before it achieved a level of stability.
Relationship between cloud vertical structures inferred from radiosonde humidity profiles and precipitation over Indonesia
Authors: Lismalini  , Marzuki  , Ali Shafii M , Yusnaini H 
Published: May 2021

Abstract
Knowledge of cloud vertical structure, including the presence of multiple cloud layers, is important for several climate-related applications such as for understanding the impact of clouds on Earth’s radiation budget. Moreover, the vertical distribution of latent heat release that affects global circulation and precipitation. The characteristics of cloud vertical structure may change as a consequence of climate change. However, study on cloud vertical structure in Indonesia is limited to case study based on short period observation. This study aims to analyse the vertical structure of clouds, such as cloud base height (CBH), the height of the cloud top (CT) and the number of cloud layers due to climate change in Indonesia, based on ∼ 30 years radiosonde observation. The relation between cloud vertical structures and precipitation was investigated. We used the radiosonde data from nine observation stations in Indonesia. On an average, it is observed that over Indonesia one-layer clouds is most frequently observed cloud, more than 60% of the time. This number is much larger than the fraction of single layer clouds over the globe which is about 58 % of the time. The cloud vertical structures in Indonesia vary from month to month. The cloud vertical structure during wet and dry season is different which indicate a strong relationship between cloud vertical structure and precipitation.
Detection of buried human bodies using ground-penetrating radar method
Authors: Bagaskara Adika , Wafi Abdurrahman , Setiawan Nugroho Syarif , Mariyanto Mariyanto 
Published: May 2021

Abstract
Indonesia is a country that often experiences natural disasters as it is a meeting point of several tectonic plates. When a natural disaster occurs, most of the time the evacuation team having some trouble finding the buried victims underground. The Ground-Penetrating Radar (GPR) method is one of the solutions for this problem. GPR or also called georadar is a geophysical method that is used to investigate conditions under the earth’s surface using electromagnetic waves. This study aims to detect buried human bodies underground using the GPR method to increase the effectiveness and efficiency of natural disaster victims by doing a simulation measurement. It took place in one of the public cemeteries in Jakarta, Indonesia passing two graves with corpses buried around three years before the survey. GPR measurements were conducted using Geoscanners AKULA A9000+ Antenna GCB3070 to detect the buried human bodies underground. The GPR data then processed using MATLAB based program called matGPR. A series of adjustments and filters such as signal position adjustment, remove DC, mean filter, inverse amplitude decay, remove global background, and Karhunen-Loeve (KL) filter have been applied to the data. The result of data processing shows amplitude contrasts which are suspected to be the buried corpses. Further research can be conducted to investigate the buried victims from landslides, earthquakes, and other natural disasters.
Application of complementary split ring resonator to focus microwave for cancer treatment using the hyperthermia method
Authors: Yusri R , Muldarisnur  
Published: May 2021

Abstract
The hyperthermia method for cancer treatment aims to select and eliminate cancer and normal cells by raising the temperature of the cancer cells in the 36-48 using radiation from electromagnetic waves, while normal cells are kept at ambient temperature. This research is conducted by simulating an applicator as a complementary Split Ring Resonator (cSRR) in the radio frequency range of 434-915 MHz using Finite Element Method. The average temperature distribution of cancer cells in the shape of a ball 1 mm in diameter with a position of 5 mm from the port reaches 55.5 . Cell size variations show a different temperature distribution, larger cell sizes (5 mm in diameter) have decreased in temperature distribution which only reached around 46.1 . This temperature distribution is also caused by the position of the cell against the port, the cell is shifted away from the port which results in a temperature distribution of 43.3 . So that the optimal size and position of cancer cell for this treatment is as small as and as close as the cell with port. This data shows that the cSRR applicator can be used for the hyperthermia method.
Deterministic seismic hazard analysis for assessing earthquake hazard in Sungai Penuh and Kerinci Regency
Authors: Resta Ichy Lucya , Apriliyani Devi Putri , Nasri MZ , Juventa  , Dewi Ira Kusuma 
Published: May 2021

AbstractAssessment of seismic hazard is necessary in land use planning and hazard mitigation. It leading to subdivided a region into sub-region which different safeguards to prevent damage in case an earthquake is occurred. The quantitative assessment of seismic hazard is carried out in Sungai Penuh and Kerinci Regency using deterministic seismic hazard analysis (DSHA) method. Earthquake scenario of Mw7 at depth of 10 km by Siulak fault source were used for analysis to estimate the ground motion over the investigated areas. The resulting DSHA map reveals high seismic hazard level in terms of PGA 49.8 – 71.9 gal alongside the active Siulak fault zones. The intensity of the region are dominated by VII-VII of MMI scale which puts in the high hazard zone.
Reservoir fluid production optimization to sustain net-present value (NPV) using gradient-based Quasi-Newton method
Authors: Salim C , Wahjudhi S M , Mariyanto  
Published: May 2021

Abstract
After several years of production, the strong water drive reservoir can have high water cut. Unlike hydrocarbon, water has no commercial value, and tends to be disposed or separated. This leads to the decline in net present value (NPV) of reservoir. To sustain reservoir’s NPV for as long as possible, a gradient-based Quasi-Newton optimization in reservoir simulation is proposed. This mathematical method uses BFGS algorithm to find the minimum of the objective function of reservoir production. This method also assumes constant production and injection rate. Initially, the algorithm produces the base NPV (before optimized using Quasi-Newton method). After that, BFGS generates optimized NPV by iterating line search in the objective function until it meets the stopping criterion. This algorithm also shows the optimized oil and water production curve. These comparisons show how oil and water should be produced to sustain the NPV. The results show that the water cut value is decreased and NPV decline happens later than the non-optimized NPV. As a conclusion, to answer the sustainable energy needs, Quasi-Newton method using BFGS algorithm and its improvements are suitable to sustain the reservoir production in the long run.
Influence of topography on lightning density in Sumatra
Authors: Yusnaini H , Marzuki  , Muharsyah R , Vonnisa M , Tangang F 
Published: May 2021

Abstract
Lightning is one phenomenon that plays an essential role in weather modeling and forecasts. Moreover, lightning also has an impact on humans and facilities. Lightning shows variations both temporally and spatially. In this study, the spatial distribution of lightning in Sumatra was examined to see topography’s effect on lightning density in this region. We analyzed lightning data from the World Wide Lightning Location Network (WWLLN) observation. Topographic data, particularly the altitude and terrain slope data, were obtained from the digital elevation model (DEM) Shuttle Radar Topography Mission (SRTM). It was found that the lightning density is slightly correlated with the terrain slope and the altitude. High concentrations of lightning are observed in the land, consistent with some previous studies. Lower concentrations are seen on Sumatra’s western side, particularly in the hillside of the Barisan Mountains. Although Sumatra’s eastern side has a low elevation and a small topography slope, a high lightning concentration is observed in this region. The distribution of lightning shows seasonal variation in which the largest density is found during the dry season (MAM), which is different from the previous studies.
Effect of gamma ray normalization on net pay calculation, a case study of “PE” field, central Sumatra basin
Authors: Cahyaningati W P , Mariyanto M , Lestari W , Amelia R , Yusroni S A , Sapdawati S 
Published: May 2021

Abstract
Reservoir’s quality is very important in exploration of oil and gas. This quality can be used to determine the productive field including the reserve itself. To analyse the reservoir quality, net pay thickness needs to be determined. However, different quality of logging tools will affect the log reading and thickness interval. Therefore, it needs to be normalized in order to equalize the reading of minimum and maximum log values in interest zone. This study is intended to interpret the impact of gamma ray normalization on net calculation. The net pay calculation is carried out with and without normalization. To do normalization, cumulative percentile used are 3% and 93%. For instance, before normalization, the highest net pay in PE_35 is 12ft. After P93 and P3 normalization, the highest net pay value become 13.5ft and 51.5ft respectively. If the net pay value of PE_35 using P3 normalization is compared to the net pay value before normalized, then the normalized value is optimized more than 5%, which is a good amount of optimization. Thus, to obtain an optimistic net pay value, normalization must be done. To conclude this study, 3% cumulative percentile normalization method has shown the most optimistic net pay value increase.