Large Layer Research Articles

Stratifikasi Sosial dalam Novel La Hami Karya Marah Rusli

This study aims to describe the social stratification in Sumbawa Island before the eruption of Mount Tambora in 1815 in the novel La Hami by Marah Rusli, which includes; (1) the form of social stratification in the novel La Hami by Marah Rusli (2) the cause of social stratification in the novel La Hami by Marah Rusli, (3) the impact of social stratification in the novel La Hami by Marah Rusli. This research is a literary research using a qualitative approach using a descriptive method whose data are in the form of words, phrases, and sentences, and the data source is taken in the novel La Hami by Marah Rusli. The data collection technique is done by reading and understanding the novel, marking data related to the research problem to gain a deeper understanding of the problem, and inventorizing (searching) the data. The results of this study are that there are three forms of social stratification (layers of society) consisting of a layer of nobles, a layer of people, and a layer of slaves. The noble layer is the highest layer in the life of the people on Sumbawa Island, this noble layer has a high position in the royal government system. The people's layer is the largest layer or called the mass of the people, they are independent but still under the sultanate government. The slave layer is a layer that must work for the royal mangkubumi, they are not free like the masses of the people. Factors causing social stratification in the novel La Hami by Marah Rusli are measures of wealth, measures of power, measures of honor and measures of knowledge. The impacts are social conflict and class endogamy.

A polynomial-correction Navier-Stokes characteristic boundary condition

In an effort to assess the efficacy of different non-reflecting boundary conditions (NRBCs) in high-order solvers, several NRBCs have been implemented in the context of the discontinuous Galerkin (DG) discretization. The methods considered are based on buffer zone techniques and boundary-imposed conditions. The former mainly utilizes the sponge layer (SL), the perfectly matched layer (PML) and the supersonic layer (SSL), while the latter uses a Riemann extrapolation (RE) technique and a novel polynomial-correction Navier-Stokes characteristic boundary condition (PC-NSCBC). The developed PC-NSCBC method reconstructs an explicit boundary state, instead of modifying the equations on the boundary or specifying ad hoc compatibility conditions on corners and edges. This property pairs well with a Riemann solver, as is typical in a DG method. Moreover, the boundary state can be assembled either from a one-dimensional perspective (NSCBC1D) or using partial knowledge of multi-dimensional effects (NSCBC3D).Four different benchmark problems are considered: a 1D linear acoustic pulse in a quiescent flow, a 2D non-linear pressure pulse in a quiescent flow, an isentropic vortex and a shear-flow vortex shedding instability. Results imply that mainly the PML performs better than most other approaches. This is especially true for acoustically-dominated flows. Alternatively, for flow conditions predominantly less acoustic in nature and strongly non-linear, instabilities in the PML may arise. The SL and SSL both suggest that a larger layer is required to deliver comparable results to the PML. The proposed (PC-)NSCBC methods demonstrate reasonable success with no instabilities reported, which is impressive given the comparatively less computational effort required. Partial inclusion of the transverse terms in the NSCBC3D noticeably enhances the output of the NSCBC1D, albeit further investigation is required to determine an optimal, universal expression for its transverse tuning coefficient.

Re-configurable parallel Feed-Forward Neural Network implementation using FPGA

This paper proposes a novel hardware architecture for a Feed-Forward Neural Network (FFNN) with the objective of minimizing the number of execution clock cycles needed for the network’s computation. The proposed architecture depends mainly on using two physical layers that are multiplexed and reused during the computation of the FFNN to achieve an efficient parallel design. Two physical layers are designed to handle the computation of different sizes of Neural Networks (NN). The proposed FFNN architecture hardware resources are independent of the NN’s number of layers, instead, they depend only on the number of neurons in the largest layer. This versatile architecture serves as an accelerator in Deep Neural Network (DNN) computations as it exploits parallelism by making the two physical layers work in parallel through the computations. The proposed implementation was implemented with 18-bit fixed point representation reaching 200 MHz clock speed on a Spartan7 FPGA. Furthermore, the proposed architecture achieves a lower neuron computation factor compared to previous works in the literature.

Disruption of Arctic Staircases by Shear

AbstractThough thermohaline staircases exist in a large fraction of the Arctic halocline, the interactions of such staircases with shear and turbulence are still largely unexplored. We perform a series of three‐dimensional Direct Numerical Simulations with and without shear and demonstrate the capacity of shear to disrupt Arctic staircases. We force an oscillating shear throughout the domain in order to represent the effects of passing internal waves of wavelengths much larger than the simulated domain. Shear is shown to disrupt staircases when the Richardson number falls below 1/4 for small layer heights (0.5 m thick), but larger layers (1 m thick) are more resistant. We determine the presence and strength of the layers using measures of steppiness from the literature, finding that a metric based on the rms temperature gradient proves most accurate. This work demonstrates that double‐diffusive interfaces can be surprisingly robust, sometimes even maintaining their structure in strong, dynamically unstable shears.

Accelerating heat transfer modeling in material extrusion additive manufacturing: From desktop to big area

Thermal modeling informs the understanding of cooling phenomena and structural evolution during material extrusion (MatEx) additive manufacturing to help predict and tune final part properties. For fused filament fabrication (FFF) and big area additive manufacturing (BAAM), in particular, thermal models are well-suited to augment parameter optimization and closed-loop control for high throughput manufacturing of custom parts and products. However, limitations in computational time, speed, and cost pose a challenge to modeling large structures with sufficient multi-dimensional granularity over extended timescales, with many models confined either to high-resolution studies on short length and timescales or low-resolution, lumped approximations for larger timescale simulations. Thus, the goal of this work is to develop a high-fidelity thermal model applicable from desktop to BAAM systems with minimal computational constraint. Here we present a scalable, 2D finite volume “proof-of-concept” model and algorithm to rapidly simulate thermal histories across both FFF and BAAM length and time scales. Our approach implements a two-dimensional implicit numerical strategy that confers reduced computational complexity while offering fine scale granularity in capturing critical inter- and intralayer cooling dynamics and radiative heat transfer. Further, analysis of the effective Biot number (Bi) reveals that, on the BAAM scale, layer width and radiative heat transfer both drive the formation of intralayer temperature gradients, exceeding 51 °C between the layer center and edge. We further simulate the fabrication of single road-width acrylonitrile-butadiene-styrene (ABS) walls at the BAAM scale (50 layers) to demonstrate both the relative speed of the computational approach and its ability to capture the complex dynamics of a multilayer build. The model agrees with published experimental measurements, and results gauge the influence of layer thickness and proximity to print bed on cooling behavior, with larger layers and separation from the print bed lending to longer periods for interlayer welds to form above the ABS glass transition temperature (Tg). Finally, a BAAM case study highlights the model’s utility in design for additive manufacturing (DfAM) and print optimization, demonstrating how changes in bed temperature and layer time can impact interlayer bonding.

Anatomical characteristics of macroalgal species from Bombuyanoi Island, East Bolaang Mongondow Regency, North Sulawesi

This research aims to study the anatomical structure of macroalgae. Sample of macroalga was collected by using Line Intercept Transect (LIT) method with sampling quadrat. Macroalgae samples were dried and separated from the roots, stems, leaves and receptacles (if present). Samples were cut transversely and longitudinally at each section and observed under binoculared microscope of Olympus CX with monitor. Based on the histology, anatomical structure of macroalgae species can be divided into two tissues from outside to inside, namely cortex and medullary cells. The cortex is composed of one layer or more. The cortex is the area between the epidermis and the central column. The medulla cells only have one layer which is the largest layer. Based on the observation result of cells type from observed spesies Eucheuma denticilatum, Gracilaria arcuata, Hydropuntia edulis, G. salicornia, Hypnea valentiae, Turbinaria deccurens, and T. ornata, it shows that cells of medulla become small toward cortex.Indonesian title: Karakteristik anatomi jenis makroalga dari Pulau Bombuyanoi, Kabupaten Bolaang Mongondow Timur, Sulawesi Utara

Large-scale and green production of multi-layer graphene in deep eutectic solvents

To promote the industrial applications of graphene, it is crucial to develop a low-cost, green, and efficient production method. A practical and eco-friendly deep eutectic solvent-assisted ball milling technique was developed to prepare multi-layer graphene in this study. The expanded graphite was used as raw material, and the deep eutectic solvent was prepared by mixing urea and choline chloride. The obtained graphene was characterized by Fourier-transform infrared spectroscopy, X-ray diffraction, X-ray photoelectron spectroscopy, scanning electron microscopy, transmission electron microscopy, atomic force microscopy, thermogravimetric analysis, and Raman spectroscopy. After ball milling for 48 h, most of the graphite particles could be exfoliated into graphene sheets, and no new covalent bond or interaction was formed. Multi-layer graphene in N-methylpyrrolidone had better dispersibility and larger layers than that in N,N-dimethylformamide. The obtained multi-layer graphene exhibited few defects, high crystal integrity, 11–12 layers, 2–5 μm size at the lateral dimension, and superior thermal stability. This technique of low-energy ball milling in the nontoxic deep eutectic solvents provides a new idea for the efficient exfoliation of multi-layer graphene and also a certain reference value for the exfoliation of other two-dimensional nanosheets.

Energies and E1, M1, E2, and M2 line strengths for Nb XXXIV

The multiconfiguration Dirac-Hartree-Fock (MCDHF) method is used to calculate energies, lifetimes, wavelengths, transition probabilities, weighted oscillator strengths, and line strengths for electric dipole (E1), magnetic dipole (M1), electric quadrupole (E2), and magnetic quadrupole (M2) transitions among the lowest 226 fine-structure levels arising from the 2s22p4, 2s2p5, 2p6, 2s22p33l, 2s2p43l, and 2p53l (l = s, p, d) configurations in O-like Nb XXXIV. The valence and core-valence correlation effects are included in the calculations. The Breit-interaction and the leading quantum electrodynamics contributions are taken into account in the relativistic configuration interaction calculations. The present energies, wavelengths, line strengths, and oscillator strengths are compared with the available experimental and other theoretical results. The accuracy of the present results is estimated using the comparison between the results from the two largest layers in the present MCDHF calculations.

Independent sets in the middle two layers of Boolean lattice

For an odd integer n=2d−1, let B(n,d) be the subgraph of the hypercube Qn induced by the two largest layers. In this paper, we describe the typical structure of independent sets in B(n,d) and give precise asymptotics on the number of them. The proofs use Sapozhenko's graph container method and a recently developed method of Jenssen and Perkins, which combines Sapozhenko's graph container lemma with the cluster expansion for polymer models from statistical physics.

Café latte: spontaneous layer formation in laterally cooled double diffusive convection

Abstract

Investigation of Polymer/OMMT Nanocomposites-Influence Factor and Mechanism of Substructure Morphology

By mechanical blending method or melt extrusion method, several kinds of poymers and OMMT were selected with different mixing progress and conditions, and several polymer/OMMT nanocomposites with different substructure morphology were prepared. The properties of polymer/OMMT nanocomposites were investigated. Firstly, several types of OMMT were prepared with different layer spacing, the results of XRD and TEM showed that the OMMT with larger layer spacing would form exfoliation nanocomposites, and then the schemes explained the mechanism. The polyethylene (such as LDPE, HDPE, LLDPE) composited with the same OMMT indicated the influence of different molecular chain structure. Different morphology of PP/OMMT and EPDM/OMMT nano-composites were discussed to find the relationship of shear force effecting structure.

Profit Comparison of Fertilized Egg Production and Consumption in Laying Hens in Gondangrejo District, Karanganyar

This study aims to compare the profit of fertilized egg production and consumption in layer breeders in Gondangrejo District, Karanganyar Regency. Data was collected at layer chicken farmers in Gondangrejo District, Karanganyar Regency. The study was conducted from October to December 2019. Data were collected using a questionnaire. The method of data collection is done by purposive sampling. Purposive sampling is the taking of data by giving certain considerations or giving conditions to the samples taken. The parameters observed were chicken population, average egg production, percentage of fertilized eggs, percentage of damaged eggs, and percentage of empty eggs. The selling price of Rp. 20,000.00 / kg of consumption eggs, the selling price of fertilized eggs Rp. 2,200.00 / item and the price of empty eggs (after candling 4 days of hatching) Rp. 10,000.00 / kg or half of the price of normal consumption eggs. Respondent B had the largest difference in sales price among all respondents, namely Rp.49,754,585.00 because it had the largest layer of livestock population and the average egg production. Multiple regression analysis obtained Y = 18,479,449-30,251 X1 + 46,389 X2. Production of fertilized eggs and eggs together has a positive influence on the profitability of selling fertile eggs. The conclusion of this study is fertile egg production provides optimal profit when egg production and egg fertility are high. Keywords: Prices of fertilized eggs, egg production, fertilized egg production, coefficient of determination

Reduction of Energy Hole in WSN

Energy hole problem in the wireless sensor network (WSN) is a critical issue due to the energy discharge of the sensor nodes in a rapid manner which lies closer to the sink. This is because of the fact that nearer sensor nodes send their own information as well as the information received from other regions to the sink. After sometime these sensor nodes start losing their power levels and become incapable to transfer data to sink and perform other activities despite the fact the energy of nodes in other regions are still unused which further disturbs the network performance. In this article, we have proposed a Concentric Layered Hexagonal Network Division Approach (CLHND) for solving energy hole issue. Initially, the network is divided into concentric hexagons and each hexagon act as a different layer. After that, each hexagon is divided into six equal portions. In the subsequent stage, the larger layer will be selected from all other layers. Now to decrease additional energy discharging from this layer, numerous sensor nodes positioned. In the final phase to prevent the energy hole issue, a suitable directing and ordering have been done which further improves network lifetime. The simulation results showed that the proposed CLHND approach has resolved the energy hole issue as compared to the existing techniques such as HRTBR and SEHP

A Novel Systolic Parallel Hardware Architecture for the FPGA Acceleration of Feedforward Neural Networks

New chips for machine learning applications appear, they are tuned for a specific topology, being efficient by using highly parallel designs at the cost of high power or large complex devices. However, the computational demands of deep neural networks require flexible and efficient hardware architectures able to fit different applications, neural network types, number of inputs, outputs, layers, and units in each layer, making the migration from software to hardware easy. This paper describes novel hardware implementing any feedforward neural network (FFNN): multilayer perceptron, autoencoder, and logistic regression. The architecture admits an arbitrary input and output number, units in layers, and a number of layers. The hardware combines matrix algebra concepts with serial-parallel computation. It is based on a systolic ring of neural processing elements (NPE), only requiring as many NPEs as neuron units in the largest layer, no matter the number of layers. The use of resources grows linearly with the number of NPEs. This versatile architecture serves as an accelerator in real-time applications and its size does not affect the system clock frequency. Unlike most approaches, a single activation function block (AFB) for the whole FFNN is required. Performance, resource usage, and accuracy for several network topologies and activation functions are evaluated. The architecture reaches 550 MHz clock speed in a Virtex7 FPGA. The proposed implementation uses 18-bit fixed point achieving similar classification performance to a floating point approach. A reduced weight bit size does not affect the accuracy, allowing more weights in the same memory. Different FFNN for Iris and MNIST datasets were evaluated and, for a real-time application of abnormal cardiac detection, a ${\hspace{-0.112em}\times \hspace{-0.112em}}256$ acceleration was achieved. The proposed architecture can perform up to 1980 Giga operations per second (GOPS), implementing the multilayer FFNN of up to 3600 neurons per layer in a single chip. The architecture can be extended to bigger capacity devices or multi-chip by the simple NPE ring extension.

Improvement of a discharge nozzle damping attachment to suppress fires of class D

The software package COSMOSFloWorks has been used to study a discharge nozzle damping attachment. A procedure has been proposed to estimate the covering of surface with dimensions of 0.4×0.4 m by a fire-extinguishing powder. It was established that existing discharge nozzle damping attachments are not efficient because at extinguishing light metals they do not effectively reduce the speed of powder supply onto a flammable surface and fan the fire, not being able to cover the burning surface by a fire-extinguishing powder. After putting out the fire the surface that was covered with powder reveals the burnouts. We have modeled the optimal structural parameters for a discharge nozzle damping attachment in order to extinguish fires of class D in the form of a discharge nozzle damping attachment with an elliptical top and a parabolic reflector. It has been proven that a damping attachment with two working surfaces outperforms the previous damping attachment with a single working surface by 30 %. Given this, the fire-extinguishing powder covers the burning surface by a larger layer, preventing the fanning of chips from the surface of a burning metal, thereby shortening the duration of burning and improving the efficiency of a fire-extinguishing powder supply. Experimental study has confirmed that the use of a damping attachment that supplies a fire-extinguishing powder with two working surfaces in order to extinguish fires of class D increases the powder feed to a fire site, reaching above 90 %. The diameter and the shape of the attachment have been determined. The attachment must acquire the form of a diffuser with a diameter of 16 mm. Our development could be used when designing the stationary and portable fire extinguishing systems for light metals and alloys, including incendiary grenades under condition of proper selection of the powder. We have achieved positive results during field tests of the discharge nozzle damping attachment using a make-up fire to burn the shavings of magnesium alloys

The adaptive slicing algorithm and its impact on the mechanical property and surface roughness of freeform extrusion parts

ABSTRACTIn the process of fused deposition modelling, the layer thickness plays a vital role in determining the surface quality and forming time. If a larger layer thickness is adopted, the molding time will be shorter, as a result, the surface accuracy of the product will be worse at the same time. If a smaller thickness is used, the surface quality of the product can be guaranteed, but the molding time will be very long accordingly. Therefore, there exists conflict between guaranteeing the surface quality and shortening the forming time of the part. This paper adopts adaptive slicing algorithm to solve this conflict. According to the curvature of the model, an appropriate thickness value is adopted automatically where the model curvature is large, a smaller thickness value is necessary, on the contrary, a larger thickness value is used. The tensile strength experiment was made through the specimens of ASTM D638 to study the influence of layer thickness. The temperature of the first six layers in the processing of building was collected. The ultra-depth picture of the cross-sectional area showed that the temperature would affect the neck length between adjacent filaments. Moreover, the surface roughness of the cylinder with different layer thicknesses was measured and the Ra curve figures showed the surface roughness was also influenced by layer thickness. The experiment results suggested the layer thickness was a critical factor in determining mechanical property and surface roughness by changing the layer counts and the neck length between adjacent filaments. It can be noted from the experiments that the adaptive slicing algorithm was not only good at enhancing the surface accuracy and tensile strength, it could also improve the building efficiency.

Prediction of osteonecrosis collapse of the femoral head based on the proportion of the proximal sclerotic rim

The purpose of this study was to predict ONFH-induced collapse based on the percentage of the proximal sclerotic rim. In total, 101 patients satisfying the inclusion criteria who received treatment at Guang'anmen Hospital were enrolled. Bilateral hip-joint computed tomography (CT) of the necrotic tissue was performed, and the largest layer within the coronal CT images was selected together with its anterior and posterior layers to calculate the proportion of the proximal sclerotic rim. The patients were divided into collapse and non-collapse groups, and the difference in the proportions of their proximal sclerotic rims was analysed. Specifically, a receiver operating characteristic (ROC) curve was created. The proportion of the proximal sclerotic rim represented by the maximal Youden's index was used as the reference value for collapse prediction, and its predictive value was assessed. The proportion in the collapse group was 13.11 ± 10.65 %, whereas the proportion in the non-collapse group was 51.91 ± 21.29 % (P < 0.01). Additionally, the proportion corresponding to the maximal Youden's index (0.902) was 29.24 %. For clinical convenience, 30 % was selected as the reference value for collapse prediction, with 97.30 % sensitivity, 87.5 % specificity, 94.01 % accuracy, a positive likelihood ratio (LR) of 7.78, and a negative LR of 0.03. Therefore, the proportion of the proximal sclerotic rim is of great significance in predicting ONFH-induced collapse, and 30 % could be used as the critical value in clinical practice. When the proportion is >30 %, the collapse risk is low, whereas at <30 %, the risk is high, and effective mechanical support should be provided.

Role of lunar atmospheric tides in thermosphere density

Half a million objects, including debris, satellites, and the International Space Station, orbit Earth in the thermosphere, the largest layer of the planet's atmosphere. To predict the orbits—and potential collisions—of all this stuff, scientists must forecast the weather in the thermosphere. To help develop a more comprehensive and nuanced model of this weather, Zhang et al. explored the role that lunar atmospheric tides play in the density of thermosphere air.

Elastic bending analysis of bilayered beams containing a gradient layer by an alternative two-variable method

Aifantis’s strain gradient elasticity theories and Zhang’s two-variable method are used to study elastic bending problems of bilayered micro-cantilever beams, containing a gradient layer, subjected to a transverse concentrated load. The differential element method is used to obtain differential governing equations. The variational method is employed to overcome the difficulty in deriving nonlocal natural boundary conditions, which could not be automatically fulfilled in gradient theories, not like that in classical theories. Then the differential governing equations subjected to the related boundary conditions are solved analytically to obtain the deformation field, which could be degenerated to that in classical elasticity theories. The gradient parameters of epoxy polymeric resin and copper single crystals in the present model are provided by fitting Lam’s and Demir’s experiments. The influences of length and layer thickness on normalized deflection and effective rigidity are discussed in a representative case of a Cu/epoxy polymeric resin beam. Results show that size effect makes the effective rigidity vary more prominently with shorter beam length or larger layer thickness. For given materials, although size effect exists, classical elasticity theories are still valid in some particular combination of three geometric parameters: beam length, upper and lower layer thicknesses.

Hypothesis on the Dual Origin of the Mammalian Subplate

The development of the mammalian neocortex relies heavily on subplate. The proportion of this cell population varies considerably in different mammalian species. Subplate is almost undetectable in marsupials, forms a thin, but distinct layer in mouse and rat, a larger layer in carnivores and big-brained mammals as pig, and a highly developed embryonic structure in human and non-human primates. The evolutionary origin of subplate neurons is the subject of current debate. Some hypothesize that subplate represents the ancestral cortex of sauropsids, while others consider it to be an increasingly complex phylogenetic novelty of the mammalian neocortex. Here we review recent work on expression of several genes that were originally identified in rodent as highly and differentially expressed in subplate. We relate these observations to cellular morphology, birthdating, and hodology in the dorsal cortex/dorsal pallium of several amniote species. Based on this reviewed evidence we argue for a third hypothesis according to which subplate contains both ancestral and newly derived cell populations. We propose that the mammalian subplate originally derived from a phylogenetically ancient structure in the dorsal pallium of stem amniotes, but subsequently expanded with additional cell populations in the synapsid lineage to support an increasingly complex cortical plate development. Further understanding of the detailed molecular taxonomy, somatodendritic morphology, and connectivity of subplate in a comparative context should contribute to the identification of the ancestral and newly evolved populations of subplate neurons.