Accelerated generation of holograms with ultra-low memory symmetrically high-compressed look-up table

Computer-generated holography technology has been widely applied,and as research in this field deepens,the demand for memory and computational power in small AR and VR devices continues to increase.This paper presents a hologram generation method,i.e.,a symmetrically high-compressed look-up table method,which can reduce memory usage by50%.In offline computing,half of the basic horizontal and vertical modulation factors are stored,halving the memory requirements without affecting inline speed.Currently,its potential extends to various holographic applications,including the production of optical diffraction elements.

Discrete multi-step phase hologram for high frequency acoustic modulation

Acoustic holograms can recover wavefront stored acoustic field information and produce high-fidelity complex acoustic fields. Benefiting from the huge spatial information that traditional acoustic elements cannot match, acoustic holograms pursue the realization of high-resolution complex acoustic fields and gradually tend to high-frequency ultrasound applications. However, conventional continuous phase holograms are limited by three-dimensional(3D) printing size, and the presence of unavoidable small printing errors makes it difficult to achieve acoustic field reconstruction at high frequency accuracy. Here, we present an optimized discrete multi-step phase hologram. It can ensure the reconstruction quality of image with high robustness, and properly lower the requirement for the 3D printing accuracy. Meanwhile, the concept of reconstruction similarity is proposed to refine a measure of acoustic field quality. In addition, the realized complex acoustic field at 20 MHz promotes the application of acoustic holograms at high frequencies and provides a new way to generate high-fidelity acoustic fields.

Multi-dimensional multiplexing optical secret sharing framework with cascaded liquid crystal holograms

Secret sharing is a promising technology for information encryption by splitting the secret information into different shares.However,the traditional scheme suffers from information leakage in decryption process since the amount of available information channels is limited.Herein,we propose and demonstrate an optical secret sharing framework based on the multi-dimensional multiplexing liquid crystal(LC)holograms.The LC holograms are used as spatially separated shares to carry secret images.The polarization of the incident light and the distance between different shares are served as secret keys,which can significantly improve the information security and capacity.Besides,the decryption condition is also restricted by the applied external voltage due to the variant diffraction efficiency,which further increases the information security.In implementation,an artificial neural network(ANN)model is developed to carefully design the phase distribution of each LC hologram.With the advantage of high security,high capacity and simple configuration,our optical secret sharing framework has great potentials in optical encryption and dynamic holographic display.

Synthetic Aperture Positioning: A Review

Obtaining precise position of interested emitters passively has wide applications in both civilian and military fields.Different from traditional parameter measurement and direct position determination(DPD)method,recently a new passive localization method based on synthetic aper-ture technique,named synthetic aperture positioning(SAP),has been proposed.The method com-pensates for the nonlinear phase produced by relative motion between the moving platform and the emitter,achieving coherent summation of intercepted signals.The SAP can obtain high-resolution and high-precision localization results at a low signal-to-noise ratio.This paper summarizes the research progress of SAP,including localization principles,spaceborne applications,and application scope analysis.Besides,the possible future outlook of SAP is considered.

Synthetic polymers:A review of applications in drilling fluids

With the growth of deep drilling and the complexity of the well profile,the requirements for a more complete and efficient exploitation of productive formations increase,which increases the risk of various complications.Currently,reagents based on modified natural polymers(which are naturally occurring compounds)and synthetic polymers(SPs)which are polymeric compounds created industrially,are widely used to prevent emerging complications in the drilling process.However,compared to modified natural polymers,SPs form a family of high-molecular-weight compounds that are fully synthesized by undergoing chemical polymerization reactions.SPs provide substantial flexibility in their design.Moreover,their size and chemical composition can be adjusted to provide properties for nearly all the functional objectives of drilling fluids.They can be classified based on chemical ingredients,type of reaction,and their responses to heating.However,some of SPs,due to their structural characteristics,have a high cost,a poor temperature and salt resistance in drilling fluids,and degradation begins when the temperature reaches 130℃.These drawbacks prevent SP use in some medium and deep wells.Thus,this review addresses the historical development,the characteristics,manufacturing methods,classification,and the applications of SPs in drilling fluids.The contributions of SPs as additives to drilling fluids to enhance rheology,filtrate generation,carrying of cuttings,fluid lubricity,and clay/shale stability are explained in detail.The mechanisms,impacts,and advances achieved when SPs are added to drilling fluids are also described.The typical challenges encountered by SPs when deployed in drilling fluids and their advantages and drawbacks are also discussed.Economic issues also impact the applications of SPs in drilling fluids.Consequently,the cost of the most relevant SPs,and the monomers used in their synthesis,are assessed.Environmental impacts of SPs when deployed in drilling fluids,and their manufacturing processes are identified,together with advances in SP-treatment methods aimed at reducing those impacts.Recommendations for required future research addressing SP property and performance gaps are provided.

The occurrence,inheritance,and segregation of complex genomic structural variation in synthetic Brassica napus

"Synthetic"allopolyploids recreated by interspecific hybridization play an important role in providing novel genomic variation for crop improvement.Such synthetic allopolyploids often undergo rapid genomic structural variation(SV).However,how such SV arises,is inherited and fixed,and how it affects important traits,has rarely been comprehensively and quantitively studied in advanced generation synthetic lines.A better understanding of these processes will aid breeders in knowing how to best utilize synthetic allopolyploids in breeding programs.Here,we analyzed three genetic mapping populations(735 DH lines)derived from crosses between advanced synthetic and conventional Brassica napus(rapeseed)lines,using whole-genome sequencing to determine genome composition.We observed high tolerance of large structural variants,particularly toward the telomeres,and preferential selection for balanced homoeologous exchanges(duplication/deletion events between the A and C genomes resulting in retention of gene/chromosome dosage between homoeologous chromosome pairs),including stable events involving whole chromosomes("pseudoeuploidy").Given the experimental design(all three populations shared a common parent),we were able to observe that parental SV was regularly inherited,showed genetic hitchhiking effects on segregation,and was one of the major factors inducing adjacent novel and larger SV.Surprisingly,novel SV occurred at low frequencies with no significant impacts on observed fertility and yield-related traits in the advanced generation synthetic lines.However,incorporating genome-wide SV in linkage mapping explained significantly more genetic variance for traits.Our results provide a framework for detecting and understanding the occurrence and inheritance of genomic SV in breeding programs,and support the use of synthetic parents as an important source of novel trait variation.

High-Precision DOA Estimation Method Based on Synthetic Aperture Technique

The existing direction-of-arrival(DOA)estimation methods only utilize the current received signals,which are susceptible to noise.In this paper,a method for DOA estimation based on a motion platform is proposed to achieve high-precision DOA estimation by utilizing past and present signals.The concept of synthetic aperture is introduced to construct a linear DOA estima-tion model.A DOA fine-tuning method based on the linear model is proposed to eliminate the lin-ear DOA variation,achieving a non-coherent accumulation of DOA estimations.Moreover,the baseband modulation and the phase modulation caused by the range history are compensated to achieve the coherent accumulation of all the DOA estimations.Simulation results show that the proposed method can significantly improve the DOA estimated accuracy at low signal-to-noise ratios(SNR).

A synthetic diagnostics platform for microwave imaging diagnostics in tokamaks

Interpreting experimental diagnostics data in tokamaks,while considering non-ideal effects,is challenging due to the complexity of plasmas.To address this challenge,a general synthetic diagnostics(GSD)platform has been established that facilitates microwave imaging reflectometry and electron cyclotron emission imaging.This platform utilizes plasma profiles as input and incorporates the finite-difference time domain,ray tracing and the radiative transfer equation to calculate the propagation of plasma spontaneous radiation and the external electromagnetic field in plasmas.Benchmark tests for classical cases have been conducted to verify the accuracy of every core module in the GSD platform.Finally,2D imaging of a typical electron temperature distribution is reproduced by this platform and the results are consistent with the given real experimental data.This platform also has the potential to be extended to 3D electromagnetic field simulations and other microwave diagnostics such as cross-polarization scattering.

Predictive modeling for postoperative delirium in elderly patients with abdominal malignancies using synthetic minority oversampling technique

BACKGROUND Postoperative delirium,particularly prevalent in elderly patients after abdominal cancer surgery,presents significant challenges in clinical management.AIM To develop a synthetic minority oversampling technique(SMOTE)-based model for predicting postoperative delirium in elderly abdominal cancer patients.METHODS In this retrospective cohort study,we analyzed data from 611 elderly patients who underwent abdominal malignant tumor surgery at our hospital between September 2020 and October 2022.The incidence of postoperative delirium was recorded for 7 d post-surgery.Patients were divided into delirium and non-delirium groups based on the occurrence of postoperative delirium or not.A multivariate logistic regression model was used to identify risk factors and develop a predictive model for postoperative delirium.The SMOTE technique was applied to enhance the model by oversampling the delirium cases.The model’s predictive accuracy was then validated.RESULTS In our study involving 611 elderly patients with abdominal malignant tumors,multivariate logistic regression analysis identified significant risk factors for postoperative delirium.These included the Charlson comorbidity index,American Society of Anesthesiologists classification,history of cerebrovascular disease,surgical duration,perioperative blood transfusion,and postoperative pain score.The incidence rate of postoperative delirium in our study was 22.91%.The original predictive model(P1)exhibited an area under the receiver operating characteristic curve of 0.862.In comparison,the SMOTE-based logistic early warning model(P2),which utilized the SMOTE oversampling algorithm,showed a slightly lower but comparable area under the curve of 0.856,suggesting no significant difference in performance between the two predictive approaches.CONCLUSION This study confirms that the SMOTE-enhanced predictive model for postoperative delirium in elderly abdominal tumor patients shows performance equivalent to that of traditional methods,effectively addressing data imbalance.

Exploration on Teaching Reform of Synthetic Biology Course Based on the New Engineering Concept

Synthetic biology is a new frontier of life science,which aims to design,transform and even synthesize organisms with engineering design concept.Doing a good job in the teaching of"synthetic biology"is of great significance to the cultivation and reserve of biotechnology professionals in China,and also has an important impact on students' employment competitiveness.Under the background of"new engineering",the course reform of"synthetic biology"was carried out in terms of the construction of teaching staff,teaching methods,students' participation and the innovation of course content,and specific reform suggestions were put forward,hoping to effectively promote the sustainable development of"synthetic biology"and effectively improve the quality of education.

Modulated-ISRJ rejection using online dictionary learning for synthetic aperture radar imagery

In electromagnetic countermeasures circumstances,synthetic aperture radar(SAR)imagery usually suffers from severe quality degradation from modulated interrupt sampling repeater jamming(MISRJ),which usually owes considerable coherence with the SAR transmission waveform together with periodical modulation patterns.This paper develops an MISRJ suppression algorithm for SAR imagery with online dictionary learning.In the algorithm,the jamming modulation temporal properties are exploited with extracting and sorting MISRJ slices using fast-time autocorrelation.Online dictionary learning is followed to separate real signals from jamming slices.Under the learned representation,time-varying MISRJs are suppressed effectively.Both simulated and real-measured SAR data are also used to confirm advantages in suppressing time-varying MISRJs over traditional methods.

CO_(2)capture costs of chemical looping combustion of biomass:A comparison of natural and synthetic oxygen carrier

Chemical looping combustion has the potential to be an efficient and low-cost technology capable of contributing to the reduction of the atmospheric concentration of CO_(2) in order to reach the 1.5/2°C goal and mitigate climate change.In this process,a metal oxide is used as oxygen carrier in a dual fluidized bed to generate clean CO_(2) via combustion of biomass.Most commonly,natural ores or synthetic materials are used as oxygen carrier whereas both must meet special requirements for the conversion of solid fuels.Synthetic oxygen carriers are characterized by higher reactivity at the expense of higher costs versus the lower-cost natural ores.To determine the viability of both possibilities,a techno-economic comparison of a synthetic material based on manganese,iron,and copper to the natural ore ilmenite was conducted.The synthetic oxygen carrier was characterized and tested in a pilot plant,where high combustion efficiencies up to 98.4%and carbon capture rates up to 98.5%were reached.The techno-economic assessment resulted in CO_(2) capture costs of 75 and 40€/tCO_(2) for the synthetic and natural ore route respectively,whereas a sensitivity analysis showed the high impact of production costs and attrition rates of the synthetic material.The synthetic oxygen carrier could break even with the natural ore in case of lower production costs and attrition rates,which could be reached by adapting the production process and recycling material.By comparison to state-of-the-art technologies,it is demonstrated that both routes are viable and the capture cost of CO_(2) could be reduced by implementing the chemical looping combustion technology.

A Study of EM Algorithm as an Imputation Method: A Model-Based Simulation Study with Application to a Synthetic Compositional Data

Compositional data, such as relative information, is a crucial aspect of machine learning and other related fields. It is typically recorded as closed data or sums to a constant, like 100%. The statistical linear model is the most used technique for identifying hidden relationships between underlying random variables of interest. However, data quality is a significant challenge in machine learning, especially when missing data is present. The linear regression model is a commonly used statistical modeling technique used in various applications to find relationships between variables of interest. When estimating linear regression parameters which are useful for things like future prediction and partial effects analysis of independent variables, maximum likelihood estimation (MLE) is the method of choice. However, many datasets contain missing observations, which can lead to costly and time-consuming data recovery. To address this issue, the expectation-maximization (EM) algorithm has been suggested as a solution for situations including missing data. The EM algorithm repeatedly finds the best estimates of parameters in statistical models that depend on variables or data that have not been observed. This is called maximum likelihood or maximum a posteriori (MAP). Using the present estimate as input, the expectation (E) step constructs a log-likelihood function. Finding the parameters that maximize the anticipated log-likelihood, as determined in the E step, is the job of the maximization (M) phase. This study looked at how well the EM algorithm worked on a made-up compositional dataset with missing observations. It used both the robust least square version and ordinary least square regression techniques. The efficacy of the EM algorithm was compared with two alternative imputation techniques, k-Nearest Neighbor (k-NN) and mean imputation (), in terms of Aitchison distances and covariance.

Development of a building information model-guided post-earthquake building inspection framework using 3D synthetic environments

Computer vision-based inspection methods show promise for automating post-earthquake building inspections.These methods survey a building with unmanned aerial vehicles and automatically detect damage in the collected images.Nevertheless,assessing the damage′s impact on structural safety requires localizing damage to specific building components with known design and function.This paper proposes a BIM-based automated inspection framework to provide context for visual surveys.A deep learning-based semantic segmentation algorithm is trained to automatically identify damage in images.The BIM automatically associates any identified damage with specific building components.Then,components are classified into damage states consistent with component fragility models for integration with a structural analysis.To demonstrate the framework,methods are developed to photorealistically simulate severe structural damage in a synthetic computer graphics environment.A graphics model of a real building in Urbana,Illinois,is generated to test the framework;the model is integrated with a structural analysis to apply earthquake damage in a physically realistic manner.A simulated UAV survey is flown of the graphics model and the framework is applied.The method achieves high accuracy in assigning damage states to visible structural components.This assignment enables integration with a performance-based earthquake assessment to classify building safety.

Are Ni/and Ni5Fe1/biochar catalysts suitable for synthetic natural gas production?A comparison with g-Al2O3 supported catalysts

Among challenges implicit in the transition to the post-fossil fuel energetic model,the finite amount of resources available for the technological implementation of CO_(2) revalorizing processes arises as a central issue.The development of fully renewable catalytic systems with easier metal recovery strategies would promote the viability and sustainability of synthetic natural gas production circular routes.Taking Ni and NiFe catalysts supported over g-Al_(2)O_(3) oxide as reference materials,this work evaluates the potentiality of Ni and NiFe supported biochar catalysts for CO_(2) methanation.The development of competitive biochar catalysts was found dependent on the creation of basic sites on the catalyst surface.Displaying lower Turn Over Frequencies than Ni/Al catalyst,the absence of basic sites achieved over Ni/C catalyst was related to the depleted catalyst performances.For NiFe catalysts,analogous Ni_(5)Fe_(1) alloys were constituted over both alumina and biochar supports.The highest specific activity of the catalyst series,exhibited by the NiFe/C catalyst,was related to the development of surface basic sites along with weaker NiFe-C interactions,which resulted in increased Ni0:NiO surface populations under reaction conditions.In summary,the present work establishes biochar supports as a competitive material to consider within the future low-carbon energetic panorama.

Skyrmion-based logic gates controlled by electric currents in synthetic antiferromagnet

Skyrmions in synthetic antiferromagnetic(SAF) systems have attracted much attention in recent years due to their superior stability, high-speed mobility, and completely compensated skyrmion Hall effect. They are promising building blocks for the next generation of magnetic storage and computing devices with ultra-low energy and ultra-high density.Here, we theoretically investigate the motion of a skyrmion in an SAF bilayer racetrack and find the velocity of a skyrmion can be controlled jointly by the edge effect and the driving force induced by the spin current. Furthermore, we propose a logic gate that can realize different logic functions of logic AND, OR, NOT, NAND, NOR, and XOR gates. Several effects including the spin–orbit torque, the skyrmion Hall effect, skyrmion–skyrmion repulsion, and skyrmion–edge interaction are considered in this design. Our work may provide a way to utilize the SAF skyrmion as a versatile information carrier for future energy-efficient logic gates.

In Vitro Synthetic Seed Production of Potato under Different Fungicide Levels and Storage Intervals

Potato propagation through tubers and seed is an inefficient way of propagation thus we propose an alternative method in this study which is in vitro propagation.Plantlets were raised from True Potato Seeds(TPS)in test tubes containing 10 mL of Murashige Skoog(MS)medium.Subculturing was done after every 21 days and after four subsequent subculturing,when there was an adequate quantity of stock material,uninodal cuttings of about 3-4 mm in length were prepared from in vitro proliferated potato plants by excising leaves of 1-2 mm on each side of the node.Prepared uninodal cuttings were cultured on 1/2 strength MS medium for root primordia development.The selected uninodal cuttings with root primordia were encapsulated with sodium alginate solution(3.5%(w/v)),mixed with 1.25%charcoal and different concentration of fungicide(thiophanate methyl,sigma)to enhance the viability percentage of synthetic seed.Furthermore,these encapsulated uninodal cuttings were subjected to different storage intervals to check maximum storage.Results showed that optimum dose for fungicide is 150 mg/L as it resulted in good viability percentage,shoot number,shoot length,rooting percentage,root number,root length and ideal for bead formation with sodium alginate.Similarly,results revealed that encapsulated uninodal cuttings can be stored at a temperature of 4℃ up to 45 days with a survival rate of 63.33%.Encapsulated uninodal cutting stored for 60 days showed a poor viability percentage of about 43.03%.It can be concluded that optimum dose of 150 mg/L with storage time of 45 days should be used to get a better outcome for synthetic potato seed production.

Wide-spectrum optical synthetic aperture imaging via spatial intensity interferometry

High resolution imaging is achieved using increasingly larger apertures and successively shorter wavelengths.Optical aperture synthesis is an important high-resolution imaging technology used in astronomy.Conventional long baseline amplitude interferometry is susceptible to uncontrollable phase fluctuations,and the technical difficulty increases rapidly as the wavelength decreases.The intensity interferometry inspired by HBT experiment is essentially insensitive to phase fluctuations,but suffers from a narrow spectral bandwidth which results in a lack of effective photons.In this study,we propose optical synthetic aperture imaging based on spatial intensity interferometry.This not only realizes diffraction-limited optical aperture synthesis in a single shot,but also enables imaging with a wide spectral bandwidth,which greatly improves the optical energy efficiency of intensity interferometry.And this method is insensitive to the optical path difference between the sub-apertures.Simulations and experiments present optical aperture synthesis diffraction-limited imaging through spatial intensity interferometry in a 100 nm spectral width of visible light,whose maximum optical path difference between the sub-apertures reaches 69λ.This technique is expected to provide a solution for optical aperture synthesis over kilometer-long baselines at optical wavelengths.

Implementation of natural hand gestures in holograms for 3D object manipulation

Holograms provide a characteristic manner to display and convey information, and have been improved to provide better user interactions Holographic interactions are important as they improve user interactions with virtual objects. Gesture interaction is a recent research topic, as it allows users to use their bare hands to directly interact with the hologram. However, it remains unclear whether real hand gestures are well suited for hologram applications. Therefore, we discuss the development process and implementation of three-dimensional object manipulation using natural hand gestures in a hologram. We describe the design and development process for hologram applications and its integration with real hand gesture interactions as initial findings. Experimental results from Nasa TLX form are discussed. Based on the findings, we actualize the user interactions in the hologram.

Current advances of biocontainment strategy in synthetic biology

Synthetic biotechnology has led to the widespread application of genetically modified organisms(GMOs)in biochemistry, bioenergy, and therapy. However, the uncontrolled spread of GMOs may lead to genetic contamination by horizontal gene transfer, resulting in unpredictable biosafety risks. To deal with these challenges, many effective methods have been developed for biocontainment. In this article, we summarize and discuss recent advances in biocontainment strategies from three aspects: DNA replication, transcriptional regulation, and protein translation. We also briefly introduce the efforts in the biocontainment convention, such as the recent publication of the Tianjin Biosecurity Guidelines for the Code of Conduct for Scientists.