bluuebunny/crossref_metadata_2025_split huggingface dataset:
Hydrothermal synthesis of hierarchical boehmite (γ-AlOOH) hollow microspheres with highly active surface
Authors: Wang Fang , Yuan Xue , Wang Dengwu 
Published: June 2021

In this study, hierarchical boehmite (γ-AlOOH) hollow microspheres with highly active surface were prepared by hydrothermal synthesis. Scanning electron microscopy images showed that the hierarchical structure of the product was composed of hexagonal nanoflake units. Transmission electron microscopy images confirmed that the (010) plane was the main exposed surface of the crystal, and the ratio of the (010) plane to the total surface area of the crystal units was about 91.5%. The (010) plane of γ-AlOOH is occupied by hydroxyl groups with adsorption activity, which has a great influence on the adsorption performance of the materials. The possible mechanism of the product was proposed. Cetyltrimethylammonium bromide, which was used as the structure inducer, broke the interlayer hydrogen bonds of γ-AlOOH. As a result, the separated layers of the crystal formed thin flake-like structure units. The (010) crystal surface, which was usually caught between the lattice layers, could be exposed on the surface with this unique morphology. The N2 adsorption–desorption experiment showed that the specific surface area of the as-synthesized product was 43.5 m2 g−1. The adsorption capacity test revealed that γ-AlOOH hollow microspheres had an excellent adsorption performance, namely, the maximum adsorption capacity of the product for Congo red is 110 mg g−1.
Theoretical study of a high-efficiency GaP–Si heterojunction betavoltaic cell compared with metal–Si Schottky barrier betavoltaic cell
Authors: Wang Yu , Lu Jingbin , Zheng Renzhou , Li Xiaoyi , Liu Yumin , Zhang Xue , Zhang Yuehui , Chen Ziyi 
Published: June 2021

In this work, energy converters, which contain a GaP–Si heterojunction and Si-based Schottky barrier diodes with Al, Ti, Ag, and W, are used to convert 2 μm-thick 63Ni radioactive source energy into electrical energy. First, energy deposition distributions of the 63Ni radioactive source in these converters are simulated by using the Monte Carlo method. Then, the electrical output properties of the 63Ni/GaP–Si cell and 63Ni/metal–Si cell are determined through the numerical calculation. For the 63Ni/GaP–Si cell, with the optimized thickness of the GaP layer and doping concentration of Si, the maximum output power density and the conversion efficiency are 0.189 µW cm−2 and 1.83%, respectively. For the Si-based Schottky barrier cells with Al, Ti, Ag, and W, the 63Ni/Al–Si cell has the best electrical output properties with the same thickness of the metal layer and doping concentration of Si. When the thickness of metal Al is 0.1 µm and the doping concentration Na is 1 × 1013 cm−3, the maximum output power density and the conversion efficiency are 0.121 µW cm−2 and 1.18%, respectively. The calculation results indicate that the 63Ni/GaP–Si battery has better electrical output properties than the 63Ni/Al–Si Schottky battery. These results are valuable for fabricating practical batteries.
Deep learning virtual Zernike phase contrast imaging for singlet microscopy
Authors: Bian Yinxu , Jiang Yannan , Deng Weijie , Shen Renbing , Shen Hua , Kuang Cuifang 
Published: June 2021

Singlet microscopy is very attractive for the development of cost-effective and portable microscopes. In contrast to conventional microscope objectives, which consist of multiple lenses, the manufacturing process for singlet lenses is done without extensive assembling and aligning. In this manuscript, we report a novel singlet virtual Zernike phase contrast microscopy setup for unstained pathological tumor tissue slides. In this setup, the objective consists of only one lens. There is no need for the inset Zernike phase plate, which is even more expensive than a whole brightfield microscopy setup. The Zernike phase contrast is virtually achieved by the deep learning computational imaging method. For the practical virtual Zernike phase contrast microscopy setup, the computational time is less than 100 ms, which is far less than that of other computational quantitative phase imaging algorithms. With a conceptual demo experimental setup, we proved our proposed method to be competitive with a research-level conventional Zernike phase contrast microscope and effective for the unstained transparent pathological tumor tissue slides. It is believed that our deep learning singlet virtual phase contrast microscopy is potential for the development of low-cost and portable microscopes and benefits resource-limited areas.
Inhibition of apical domain formation does not block blastocyst development in bovine embryos
Authors: dos Anjos S. A. A. , da Costa C. P. , Assumpção M. E. O. A. , Visintin J. A. , Goissis M. D. 
Published: June 2021

The first event of cellular differentiation consists of the segregation of the trophectoderm and the inner cell mass. Studies in mice suggest that cell contractility and the formation of an apical domain play important roles in this event; however, this remains unknown in the bovine. We tested the hypothesis that blocking apical domain formation would halt subsequent trophectoderm differentiation in bovine embryos. We first assessed the formation of an apical domain by the presence of Par-6 Family Cell Polarity Regulator Beta (PARD6B) and Ezrin (EZR), which appeared after the 8-cell stage. We inhibited apical domain formation by blocking cell contractility with 25 μM (–)-blebbistatin. Treatment from 90 to 186 h after insemination did not reduce blastocyst development compared with the untreated control group or the group treated with inactive (+)-blebbistatin. Immunofluorescence staining after blebbistatin treatment revealed the absence of EZR and the trophectoderm marker Caudal Type Homeobox 2 (CDX2). Following blebbistatin treatment, Yes1 Associated Transcriptional Regulator (YAP), which is involved in the Hippo signalling pathway, exhibited cytoplasmic staining instead of nuclear localisation. Despite changes in protein expression and localisation, no difference in trophectoderm or total cell numbers was observed. In conclusion, inhibition of cell contractility inhibited apical domain formation without impairing blastocyst formation, suggesting that a different biological mechanism is involved in trophectoderm and inner cell mass differentiation in bovine embryos.
Drivers of fatal bird collisions in an urban center
Authors: Van Doren Benjamin M. , Willard David E. , Hennen Mary , Horton Kyle G. , Stuber Erica F. , Sheldon Daniel , Sivakumar Ashwin H. , Wang Julia , Farnsworth Andrew , Winger Benjamin M. 
Published: June 2021

Significance
Collisions with built structures are an important source of bird mortality, killing hundreds of millions of birds annually in North America alone. Nocturnally migrating birds are attracted to and disoriented by artificial lighting, making light pollution an important factor in collision mortality, and there is growing interest in mitigating the impacts of light to protect migrating birds. We use two decades of data to show that migration magnitude, light output, and wind conditions are important predictors of collisions at a large building in Chicago and that decreasing lighted window area could reduce bird mortality by ∼60%. Our finding that extinguishing lights can reduce bird death has global implications for conservation action campaigns aimed at eliminating an important cause of bird mortality.
Overcoming COVID-19 vaccination resistance when alternative policies affect the dynamics of conformism, social norms, and crowding out
Authors: Schmelz Katrin , Bowles Samuel 
Published: June 2021

Significance
We provide a model of policy effectiveness to explore the dynamics of vaccine resistance, drawing on our panel data set. The key ideas motivating the model are that voluntary citizen compliance is essential to policy success even under enforcement and that compliance preferences are endogenous, possibly crowded out by enforcement or enhanced due to conformism as more other citizens comply. Our panel data tracks intraindividual changes in trust in public institutions and vaccine acceptance, allowing inferences about causal effects. Our contribution is the integration of three features: 1) a model of interaction of public policy and citizen preferences, 2) using appropriate data, and 3) allowing insights on how to address the COVID-19 pandemic and other important societal challenges.
Accessibility measure for eternal inflation: dynamical criticality and higgs metastability
Authors: Khoury Justin 
Published: June 2021

Abstract
We propose a new measure for eternal inflation, based on search optimization and first-passage statistics. This work builds on the dynamical selection mechanism for vacua based on search optimization proposed recently by the author and Parrikar. The approach is motivated by the possibility that eternal inflation has unfolded for a finite time much shorter than the exponentially long mixing time for the landscape. The proposed accessibility measure assigns greater weight to vacua that are accessed efficiently under time evolution. It is the analogue of the closeness centrality index widely used in network science. The proposed measure enjoys a number of desirable properties. It is independent of initial conditions and oblivious to physical vs comoving weighing of pocket universes. Importantly, the proposed measure makes concrete and testable predictions that are largely independent of anthropic reasoning. Firstly, it favors vacua residing in regions of the landscape with funnel-like topography, akin to the energy landscape of naturally-occurring proteins. Secondly, it favors regions of the landscape that are tuned at dynamical criticality, with vacua having an average lifetime of order the de Sitter Page time. Thus the predicted lifetime of our universe is of order its Page time, ∼ 10130 years, which is compatible with Standard Model estimates for electroweak metastability. Relatedly, the supersymmetry breaking scale should be high, at least 1010 GeV. The discovery of beyond-the-Standard Model particles at the Large Hadron Collider or future accelerators, including low-scale supersymmetry, would rule out the possibility that our vacuum lies in an optimal region of the landscape. The present framework suggests a correspondence between the near-criticality of our universe and dynamical critical phenomena on the string landscape.
Sourced fluctuations in generic slow contraction
Authors: Artymowski Michał , Ben-Dayan Ido , Thattarampilly Udaykrishna 
Published: June 2021

Abstract
We introduce a set of generic conditions for the slow contracting Universe and for a narrowed-down category of models called fast-roll models. We present general conditions for superhorizon freeze-out of scalar and tensor perturbations and show that any fast-roll model satisfies them, as in the case of inflation. We are interested in the “Sourced Bounce” scenario, where perturbations are sourced by a U(1) gauge field coupled to a bouncer scalar field. The requirement of a slightly red tilted scalar spectrum greatly restricts the allowed couplings between the scalar and the gauge field. We show that a viable slightly red scalar spectrum is achievable. However, within the fast-roll approximation the tensor-to-scalar ratio is in general r ≃ 1/9, inconsistent with current observations. We demonstrate the general result with an explicit example we dub "Intermediate contraction". We prove that small modifications in fast-roll that do not alter the Green's functions, do not result in r < 0.06 consistent with the data for more than an e-fold. Hence, a successful “Sourced Bounce” requires a different source or a significant deviation from fast-roll.
Greenhouse automation: smart watering system for plants in greenhouse using programmable logic control (PLC)
Authors: Dwinugroho T B , Hapsari Y T , Kurniawanti  
Published: June 2021

Abstract
Automation is a technology used to carry out work processes or procedures without human assistance. Greenhouse automation is carried out related to the many operational activities in the greenhouse that involve many human repetitive activities. Some of them are related to fertilizing, watering, spraying pesticides and others. In the current era of the industrial revolution 4.0, manual activities that use human labor began to diminish and were replaced with automated systems and devices in order to streamline the operation of a work field,. PLCs can be defined as a micro-computer based controllers that use instructions stored in memory that can be programmed to implement logic, sequencing, timing, counting and arithmetic functions through digital or analog input / output (I / O) modules, to control machines and processes. This PLC is commonly used in the industrial world as an automation tool for production machines. PLC can be implemented as an automation tool in a greenhouse in this case as an automatic watering system for plants. This research resulted in a prototype of an automatic watering system on a clock based and combined clock-sensor based greenhouse that can run simultaneously on the same PLC.
DEEPORCD: Detection of Oral Cancer using Deep Learning
Authors: Dharani R. , Revathy S. 
Published: June 2021

Abstract
Oral cancer is a widespread and complex cancer with a high severity. Oral cancer is the eighth most common cancer in the world in India, with 130,000 deaths in each year. The tumor occurs in the salivary glands, tonsils, as well as in the neck, face and mouth. There are various diagnostic methods for oral cancer, such as a biopsy, in which a small tissue sample is taken from a part of the body and tested under a microscope also some screening methods. But the downside is that cannot clearly identify cancer cells and cannot classify the number of cells affected by cancer, so in this work cancer cells will find and classify that affected in the oral area through digital processing technology. The use of advanced technologies and an in-depth learning algorithm are possible for early detection and classification. This work uses three characteristics-extracting techniques such as the bag histogram of oriented gradients, wavelet features and the Zernike Moment. Once retrieving the texture characteristics, the fuzzy particle swarm optimization algorithm (FPSO) is applied to choose the best characteristic. Finally, these characteristics were classified using the Convolution Neural Network (CNN) classifier. For comparison of the efficiency of the proposed method, Recall Rate, Classification Accuracy, Precision Rate, and Error Rate. Evaluation outcomes demonstrated that the combination of ABC, FPSO and CNN performs better in the detection of oral cancer.
Football Player Performance Analysis using Particle Swarm Optimization and Player Value Calculation using Regression
Authors: Jana Ayanabha , Hemalatha Sweetlin 
Published: June 2021

Abstract
This paper aims at analysing the statistical data of various football players to establish a correlation between their play style and individual scores with their quantifiable attributes. Having established a correlation, the next step involves using the Particle Swarm Optimization(PSO) to simulate a match and draw a comparison between two random players, constraining their attribute scores within the boundaries of the top-recommended player for each attribute, as suggested by the k-nearest neighbors algorithm. This aids in setting up a benchmark score for the particular player position for a random selection from this subset based on z-score inference. Having optimized the player position score, stepwise regression and smoothing splines are used to model a prediction to compute the overall score of the player. Lastly, a regression equation is modelled using stepwise regression to estimate the net worth of the player based on their skill set, and predictions are performed using the optimal score obtained from PSO, by extracting the individual attribute scores from the inverse regression relation. From the experiment, the optimized score for the left striker(LS) comes out to be 86.32766. Running the PSO on all left strikers gives a 98% probability of obtaining a player whose score is greater than the benchmark score. For the two left strikers whose scores were optimized, the predicted worth from the stepwise model comes out to be 8.933734 and 8.191562, the former being greater than the historical worth.
Development of a Navigation and Position Tracking System for a Remotely Operated Vehicle (ROV) – ORCA
Authors: Tejaswini P , Deepika I Sai , Santhanam Sakthivel Murugan 
Published: June 2021

Abstract
Remotely Operated Vehicles (ROVs) are a class of manually operated underwater vehicles that are designed for specific applications in maritime environments. For an underwater vehicle, vigilant precautions must be ensured in designing the navigation module because of the inconsistent nature of underwater channels. This paper aims to focus on the same, by developing an apt navigation system for the Remotely Operated Vehicle, ORCA which has been equipped with sensors such as temperature, pressure, and leak detector, for monitoring the ambient conditions during deployment and an Inertial Measurement Unit for tracking and positioning of an ROV. Mission Oriented Operating Suite-Interval Programming runs as the platform for navigation. Emergency Float-Up Mechanism that allows the system to be easily retrieved during emergency failures has been built in. The authors have made a successful attempt at building a navigation module that achieves stability and accurate positioning of an ROV after certain post-processing of data.
Extraction of High-level and Low-level feature for classification of Image using Ridgelet and CNN based Image Classification
Authors: Nisia T Gladima , Rajesh S 
Published: June 2021

Abstract
Remote Sensing image classification is an important research area for the recent time, because of its various application areas. Among the many available feature extraction methods, this paper uses the ridgelet based feature extraction method and those obtained features are combined with deep features obtained from the Convolutional Neural Network (CNN). Here, the Ridgelet’s are used to obtain the low-level features and CNN is used to obtain high-level feature. The system tries to construct the ridgelet filter for obtaining the low-level feature. The multi-resolution CNN is introduced using the concept of fusing high-level and low-level features via ridgelet and CNNs. Then, fused features are then classified and the output classified image is obtained. Experimental verifications are conducted on NWPU-RESISC45 dataset and the output results are provided to prove the best classification accuracies compared with the other proposed systems.
Synthesis and microstructure evaluation of ODS steel 316L with zirconia dispersion
Authors: Bandriyana B , Sugeng B , Salam R , Hairani D , Sujatno A , Shabrina N , Silalahi M 
Published: June 2021

Abstract
An Austenitic ODS steel was developed for reactor structural material by dispersed 0.5 wt % of nano powder zirconia (ZrO2) to the AISI 316L steel. The synthesis was carried out by the powder metallurgy process with high energy milling and cooled compacting process. A new apparatus of APS (Arc Plasma Sintering) was used for consolidation the sample in the sintering process. Characterizations of the microstructure and elemental composition distribution were performed using the Scanning Electron Microscope (SEM) with X-ray Diffraction Spectroscopy (EDX) and area mapping. Identification for the change of phasesand hardness were analyzed using the XRD-test and Vickers Hardness measurement. Austenitic phase with relatively equiaxed grain and homogeny distribution of the ZrO2 dispersoid were identified after the sintering process followed by the improvement of hardness due to the pinning effect of the grain boundaries.
Modified screen-printed electrode using graphene ink for electrochemical sensor application
Authors: Anshori I , Harimurti S , Rizalputri L N , Hartono M S , Althof R R , Handayani M , Mengko Tati L E R , Yuliarto B 
Published: June 2021

Abstract
In lab-on-chip development, screen printed electrode (SPE) method is usually utilized as an electrochemical sensor. As a basic conductive material, carbon has several advantages compared to other conductive materials. SPE performance can be enhanced by using a nanomaterial due to its unique properties, such as its small size particle and large surface area that can accelerate the electron transfer on the surface of the electrode. Graphene as a carbon-based nanomaterial is an extraordinary material to work with because of its good electrical conductivity and large specific surface area. In this work, we developed a graphene paste from the water-based graphene ink with the addition of polyurethane binder material to realize a nanocarbon conductive paste, which insoluble in water and other electrolytes. Our graphene paste was deposited on the working electrode area of SPE and the performance was tested using cyclic voltammetry method. The result showed that the optimal ratio for the graphene carbon paste, polyurethane to graphene ink, was 1:15 %vol. With this ratio, the performance of the modified SPE could successfully be increased and it also showed a stable sensing performance by having a low error value, below 3%, for 7 times of repeated measurements.
The differences of physicochemical characteristics of graphene-like nanomaterials directly grown on copper foil and quartz substrate in chemical vapor deposition (CVD)
Authors: Priyanti A D , Saraswati T E 
Published: June 2021

Abstract
The preparation of graphene material is possibly conducted using chemical vapor deposition (CVD) method using hydrogen, argon, and acetylene gases using a copper substrate. The use of different substrates, especially glass-based substrates, has not been widely studied. Therefore, in the present study, we analyzed the chemical and physical characteristics of the carbon materials grown in CVD on a different substrate, i.e., copper foil and quartz substrate. The XRD analysis of the carbon materials produced shows a definitive peak for carbon which is in broad feature and left-shifted to 2θ around 23°. Raman spectroscopy’s characterization shows that the material grown on copper foil revealed a 2D band, appearing around 2600 cm−1, which was absent for the carbon material deposited on the quartz substrate. Physically, the carbon powder produced is hydrophobic, light, and black. The structural character of the graphene material observed by using the electron microscope consists of overlapped layers. The FTIR analysis shows that the material growth on copper foil and quartz substrate has C=C bond, concluded that the material produced as graphene-like nanomaterials.
Synthesis and Structure Characterization of Copper(II) Complex with Phenylhydrazine
Authors: Rasyda Y A , Rahardjo S B , Marliyana S D 
Published: June 2021

Abstract
The Cu(II)-phenylhydrazine complex was synthesized and characterized by ultraviolet-visible spectroscopy, atomic absorption spectroscopy, thermogravimetry/differential scanning calorimetry, molar conductivity, infrared spectroscopy and magnetic susceptibility measurements. The metal complex was prepared through reaction of 1:4 mole ratio of CuSO45H2O to phenylhydrazine ligand in methanol at room temperature for 15 minutes. The peak shifting in the electronic spectra to the smaller maximum wavelength than copper salt from 815 nm to 518 nm indicated the formation of the complex. The copper content in the complex was 13.93% which was according to the empirical formula of Cu(phenylhydrazine)2(SO4)(H2O)n (n= 4,5, or 6). Thermal analysis showed the release of five water molecules as hydrate and the electrical conductivity showed that the complex was nonelectrolyte. The complex was paramagnetic with an effective magnetic moment of 1.93 BM. The broadness band peak of the electronic spectra at 19531 cm−1 showed the d-d transition. The studies confirmed that the ligand is monodentate and the proposed formula of the complex was [Cu(phenylhydrazine)2(SO4)]·5H2O with square planar geometry.