Multiple Orders Research Articles

Controlled generation of mode-switchable nanosecond pulsed vector vortex beams from a Q-switched fiber laser.

We reported and demonstrated a ring Q-switched Ytterbium-doped fiber laser that can generate mode-switchable nanosecond pulsed vector vortex beams between two different orders. In the spatial optical path of the fiber laser, several cascaded Q-plates, divided into two Q-plate groups, are applied for intracavity mode conversion between LP01 mode and vector vortex beams. In one Q-plate group, two quarter-wave plates are inserted to achieve the addition and subtraction of the order of Q-plates. By tuning the polarization state in the cavity, mode-switchable vector vortex beams (VVBs), including cylindrical vector beams (CVBs), elliptically polarized cylindrical vector beams (EPCVBs), and vortex beams, of two different orders can be generated on demand. The experimental results show that by using the group of 1st and 3rd orders Q-plates, the 2nd and 4th orders mode-switchable VVBs (vortex beams with topological charges of ±2, ±4, CVBs and EPCVBs of 2nd- and 4th-order) can be obtained from the fiber laser. The slope efficiency, pulse width, and repetition rate are 33.4%, 360 ns, and 241kHz respectively. To the best of our knowledge, this is the first time to realize the direct generation of mode-switchable VVBs on the arbitrary position of the higher-order Poincaré sphere between two different orders from a fiber laser. This work lays the foundation for the flexible generation of arbitrary modes of VVBs with multiple different orders in the laser cavity.

A Resource Scheduling Method for Enterprise Management Based on Artificial Intelligence Deep Learning

Under the current trend of economic globalization and international competition, more and more production enterprises are introducing the project management model, that is, customer or order projection, and using the concept of project management to manage operations. In an enterprise, there are multiple customers at the same time, and the production line can also generate multiple orders from different customers at the same time. That is to say, multiple projects are running at the same time, resulting in continuous changes in management processes, heavy project coordination tasks, and a serious waste of corporate resources. The resources that can be used are limited. In the production business using project management, how to rationally utilize the limited business scheduling resources has become the focus of research. Aiming at the method of business management resource scheduling, this paper investigates the application of enhanced particle swarm algorithm on the cloud deep learning platform, and the mapping problem between virtual machines and physical machines. As a heuristic algorithm, particle swarm optimization is suitable for solving combinatorial optimization problems. By improving the diversity of particle hosts and setting parameters, it improves the integration speed and accuracy of the algorithm. Through the analysis of the current situation of multi-project business management, it examines the allocation of resources. In terms of business management, it has established a resource allocation model for multiple projects. The results show that the method improves the efficiency of the enterprise by 35% compared to the traditional method with a 20% reduction in personnel. A better configuration scheme is simulated by MATLAB, which verifies the scientificity and effectiveness of the method studied in this paper.

Enhanced magnetic and magnetodielectric behavior in morphologically distinct BTFO and LSMO composites

In this work, sol–gel modified technique is used to synthesize the (1-x)BTFO-(x)LSMO composites (x = 0, 0.1, 0.2, 0.3, and 0.4). The composite's dual (BTFO and LSMO) phases are verified using X-ray diffraction analysis. A scanning and transmission electron microscope is used to analyze the distinct morphology of the two phases that demonstrated the plate-like grains and quasi-spherical particles of BTFO and LSMO phases in the composites, respectively. The magnetic studies reveal that the saturation magnetization (Ms ∼ 7.0 emu/g) and coercive field (Hc ∼ 1660 Oe) increased by nearly-three and 66 times for 40 % LSMO contained composite. The enhanced magnetic behavior is due to the interaction between the multiple magnetic ordering (AFM/FM) present in the prepared composites. The estimated values of squareness ratio (Mr/Ms) are lower than 0.5, illustrating the multi-domain nature of the composites. The switching field distribution (SFD) plot indicates that strong exchange coupling exists in the x = 0.4 composite compared to others. The change in dielectric permittivity at different magnetic fields is due to the magnetodielectric (MD) coupling in the composites. The field-dependent MD studies reveal that maximum MD strength (∼0.34 %) and minimum magnetoloss (ML) (∼0.02 %) are observed in x = 0.2 and 0.1 composites at 100 kHz, respectively. It is due to the non-collinear alignment of magnetic Mn ions at RT, which leads to the inverse Dzyalonskii-Moriya interaction. Additionally, the maximum MD coupling strength γ (-16.87 (emu/g)2) is observed in the x = 0.2 composite. The observed MD response in the composites is due to the dominating grain capacitive effect rather than the resistive effect, which is ascertained by the frequency-dependent magnetoresistance measurement. Hence, the composite's enhanced magnetic and magnetodielectric behavior makes it a suitable candidate for multifunctional device applications.

Four-dimensional emittance measurements of ultrafast electron diffraction optics corrected up to sextupole order

Ultrafast electron diffraction (UED) is a technique in which short-pulse electron beams can probe the femtosecond-scale evolution of atomic structure in matter driven far from equilibrium. As an accelerator physics challenge, UED imposes stringent constraints on the brightness of the probe electron beam. The low normalized emittance employed in UED, often at the 10-nm scale and below, is particularly sensitive to both applied field aberrations and space-charge effects. The role of aberrations is increasingly important in small probe systems that often feature multiple orders of magnitude variations in beam size during transport. In this work, we report the correction of normal quadrupole, skew quadrupole, and sextupole aberrations via dedicated corrector elements in an ultrafast electron microdiffraction beamline. To do this, we generate precise four-dimensional phase space maps of rf-compressed electron beams and find excellent agreement with aberration-free space-charge simulations. Finally, we discuss the role a probe-forming aperture can play in improving the brightness of bunches with appreciable space-charge effects.

A Geo‐Structurally Based Correction Factor for Apparent Dissolution Rates in Fractured Media

AbstractField measurements of apparent geochemical weathering reaction rates in subsurface fractured porous media are known to deviate from laboratory measurements by multiple orders of magnitude. To date, there is no geologically based explanation for this discrepancy that can be used to predict reaction rates in field systems. Proposed correction factors are typically based on ad hoc characterizations related to geochemical kinetic models. Through a series of high‐fidelity reactive transport simulations of mineral dissolution within explicit 3D discrete fracture networks, we are able to link the geo‐structural attributes with reactive transport observations. We develop a correction factor to linear transition state theory for the prediction of the apparent dissolution rate based on measurable geological properties. The modified rate law shows excellent agreement with numerical simulations, indicating that geological structure could be a primary reason for the discrepancy between laboratory and field observations of apparent dissolution rates in fractured media.

Heterogeneous Multiagent Systems With Different Fractional Order: An Experience-Based Fusion Controller

Cooperation control of heterogeneous multi-agent systems (MASs) with different fractional order subject to intermittent sampled-data transmission is investigated in this brief. Existing works considering MASs with multiple fractional order mainly focus on continuous input with frequency domain analysis and their results are thus based on sophisticated characteristic equations. Instead, inspired by the memory retention property of Caputo fractional derivative, heterogeneous experience-based fusion controllers are devised to handle the hereditary effect based on time domain analysis. The devised fusion controllers are composed of intermittent sampled data, which not only incorporate current available samplings but also include earlier experience of agents. In addition, the fusion controllers can successfully transform MASs with different fractional order into general discrete-time plants at sampling instants, and at the same time, ensure the asymptotical stability of sampling errors as well as controllers besides those sampling instants. Thereby, the achievement of consensus only relates to the connectivity of communication graph. Effectiveness of theoretical results is substantiated finally by numerical examples.

Streamline of the gene line: Implementation of reflex homologous recombination deficiency (HRD) tumor testing in newly diagnosed ovarian cancer patients (593)

Streamline of the gene line: Implementation of reflex homologous recombination deficiency (HRD) tumor testing in newly diagnosed ovarian cancer patients (593)

Elucidating the large variation in ion diffusivity of microelectronic packaging materials

The risk of corrosion poses a challenge to meet the stringent reliability requirements of microelectronic devices that are used in harsh environments. Microelectronic devices are often encapsulated in polymer packaging materials, which protect them from corrosion. These polymers are, however, not completely hermetic and thus allow small amounts of ions and moisture to reach the device, which might cause corrosion of the microelectronic circuitry. To improve and predict the reliability of the device, it is important to quantify the ion diffusivity in these materials. Previously reported values for the ion diffusivity vary by multiple orders of magnitude for a single class of material. Here, we investigate the causes for this discrepancy using three experimental methods: (i) saltwater immersion, (ii) diffusion cell measurements, and (iii) transient electric current measurements. Several materials, such as silicone, epoxy, and polyamide, were tested to cover the broad spectrum of polymers used by the microelectronics industry. We found that the discrepancies are likely due to the strong dependence of the ion diffusivity on both the moisture content within the polymers, as well as on the salt concentration and pH of the solutes. Furthermore, we found that the very low ion diffusivity causes long measuring times, and thus a large risk for errors from contamination, leakage, or minor defects in the samples.

Legal pluralism and environmental governance: the regulatory design potential of Bhutan’s gross national happiness and Canada’s reconciliation approaches

As humans exceed global ecological limits nation state-based environmental governance attracts persistent criticism. Historically, the focus of regulatory design for environmental law has been to provide access to natural resources or the environment but without ecosystem-based standards at any scale or cumulative effects assessment by which state governments evaluate whether they are achieving ecosystem health. Illuminated within these nation state regimes are two examples where legal pluralism has or is mandating environmental regulatory design that more explicitly elevates ecological function as a key outcome. Bhutan’s relatively recent state environmental laws are part of its broader development approach of Gross National Happiness (GNH), an expression of state, Buddhist, and other customary laws. This ‘internal legal pluralism’ in state policy is expressed through multiple layers of plans and project review by administrative agencies and a GNH screening tool. By contrast, Canada is reforming its environmental laws to account for cumulative impacts and Indigenous rights. In particular, state governments have committed to aligning their laws with the United Nations Declaration on the Rights of Indigenous Peoples, and plural legal agreements establish unique collaborative governance bodies. The purpose of this article is to examine how legal pluralism is influencing the evolution of regulatory design for environmental governance in Bhutan and Canada. While the plural legal aspects of their regimes have resulted in the prioritization of ecological health, that focus in both regimes is vulnerable without further regulatory scaffolding to establish ecological limits that engage with multiple legal orders at various temporal and spatial scales.

Fast anisotropic Mg and H diffusion in wet forsterite

Adding hydrogen to forsterite strongly increases the diffusion rate of Mg, but the reason for this is unclear. As Mg diffusion in forsterite can influence its electrical conductivity, understanding this process is important. In this study we use density functional theory to predict the diffusivity of H-bearing Mg vacancies and we find that they are around 1000 times slower than H-free Mg vacancies. H-bearing Mg vacancies are many orders of magnitude more concentrated than H-free Mg vacancies, however, and diffusion is a combination of diffusivity and defect concentration. Overall, the presence of hydrated Mg vacancies is predicted to cause a large (multiple orders of magnitude) increase in both diffusion rate and diffusional anisotropy with a strong preference for diffusion in the [001] direction predicted. In models of experimental data, the effect of water concentration on diffusion is often described by a constant best-fitting exponent. Our results suggest that this exponent will vary between 0.5 and 1.6 across common experimental conditions with pressure decreasing and temperature increasing this exponent. These results suggest that Mg diffusion in forsterite could vary considerably throughout upper mantle conditions in ways that cannot be captured with a simple single-exponent model. Comparisons to measures of hydrogen diffusivity suggest that the diffusion of hydrated Mg vacancies also controls the diffusion of hydrogen in (iron-free) forsterite and that our conclusions above also apply to hydrogen diffusion rates and anisotropy. We also find that cation diffusivity likely cannot explain experimental measurements of the effect of water on electrical conductivity in olivine.

Optimization of integrated production scheduling and vehicle routing problem with batch delivery to multiple customers in supply chain

In supply chain literature, production coordination and vehicle routing have received a lot of attention. Even though all functions in the supply chain are interrelated, they are normally handled independently. This disconnected approach might lead to less-than-ideal outcomes. Increasing total efficiency by integrating manufacturing and delivery scheduling processes is popular. This study focuses on synchronic production–distribution scheduling difficulties, particularly permutation flow shop scheduling in production and sequence-dependent setup time (SDST) and vehicle routing alternatives in distribution. To create a cost-effective distribution among the placement of geographically separated clients and hence to minimize delivery costs, batch delivery to customers employing a succession of homogenized capacity limitation vehicles is examined here. However, this might result in the failure to complete multiple client orders before their deadlines, raising the cost of lateness. As a result, the goal of this study is to lower the overall cost of tardiness and batch distribution in the supply chain. To accomplish so, a mixed-integer nonlinear programming model is developed, and the model is solved using a suggested genetic algorithm (GA). Because there is no established benchmark for this issue, a set of genuine problem scenarios is created in order to assess the proposed GA in a viable and difficult environment. Ruiz's benchmark data, which is derived from Taillard's benchmark cases of permutation flow shops, was supplemented with SDSTs in the production of test examples. In comparison to an exact method, the results show that the proposed GA can rapidly seek solutions to optimality for most small-sized instances. Furthermore, for medium and large-scale cases, the proposed GA continues to work well and produces solutions in a fair amount of time in comparison to GA without the local search.

Stochastic Analysis of the Marginal and Dependence Structure of Streamflows: From Fine-Scale Records to Multi-Centennial Paleoclimatic Reconstructions

The identification of the second-order dependence structure of streamflow has been one of the oldest challenges in hydrological sciences, dating back to the pioneering work of H.E Hurst on the Nile River. Since then, several large-scale studies have investigated the temporal structure of streamflow spanning from the hourly to the climatic scale, covering multiple orders of magni-tude. In this study, we expanded this range to almost eight orders of magnitude by analysing small-scale streamflow time series (in the order of minutes) from ground stations and large-scale streamflow time series (in the order of hundreds of years) acquired from paleocli-matic reconstructions. We aimed to determine the fractal behaviour and the long-range de-pendence behaviour of the streamflow. Additionally, we assessed the behaviour of the first four marginal moments of each time series to test whether they follow similar behaviours as sug-gested in other studies in the literature. The results provide evidence in identifying a common stochastic structure for the streamflow process, based on the Pareto–Burr–Feller marginal dis-tribution and a generalized Hurst–Kolmogorov (HK) dependence structure.

Battery control with lookahead constraints in distribution grids using reinforcement learning

In this paper, a computationally efficient real-time control of a battery with lookahead state-of-energy constraints in active distribution grids with distributed energy sources is presented. The goal is to follow a previously computed dispatch plan or to optimize a monetary cost from buying and selling power at the point of common coupling. However, the lookahead constraints render the battery decisions non-trivial. The current practice in literature to solve this problem is Model Predictive Control (MPC), which does not scale for large grids. Instead, here, we propose a reinforcement learning approach based on the Deep Deterministic Policy Gradient (DDPG) algorithm. To satisfy the lookahead battery constraints we adapt the experience replay technique used in DDPG. To guarantee the satisfaction of the hard grid constraints, we introduce a safety layer that performs constrained optimization. Our approach does not need forecasts contrary to MPC. We perform evaluations on a realistic grid and comparisons with Lyapunov optimization and MPC. We show that we can achieve costs close to MPC and Lyapunov, while reducing the computational time by multiple orders of magnitude.

무극도 관련 문헌 연구*

Documentation related to Mugeuk-do (Limitless Dao) is rare in comparison to other Korean new religions given that it has been open to the public and translated since the 1970s. Due to its rarity, the documentation has been used uncritically, without there being any comparative study or historical research. It is undeniable that distortions and fallacies are embedded in these documents, and this has resulted in quite a few problems in precisely understanding Mugeuk-do and Daesoon Jinrihoe (The Fellowship of Daesoon Truth), an order that has inherited the legacy of Mugeuk-do. In this regard, this study aims to critically define the characteristics and limitations of the major documents related to Mugeuk-do that were published by the colonial government in the 1920s~1930s and recorded by multiple orders in the 1970s-1980s through comparisons. An attempt to conduct this research allows for the discovery of a solution to the problem of uncritical usage of those materials. The documents produced by the colonial government that can be used as basic texts to study Mugeuk-do are The General Conditions of the Religion Mugeuk-do (無極大道敎槪況) and Unofficial Religions of the Korea (朝鮮の類似宗敎). These can be found through bibliography, comparison, and historical research. Chapters 6, 7, and 8 of The General Conditions of the Religion Mugeuk-do are a possible source on the order that reflects the circumstances of Mugeuk-do until 1925. In the case of Unofficial Religions of the Korea, if the descriptive perspective on unofficial religions is excluded, the articles written about the circumstances post 1925 have credibility. Another document that describes multiple orders and can be used as a basic text is chapter 2 of ‘Progress of the Order’ in Daesoon Jinrihoe’s The Canonical Scripture. This is because its record precisely reflects the conditions of the era, with regard to the fact that it is the freest from distortions caused by changes in the belief system and it is less biased towards certain sects or denominations. Furthermore, the collection period of the articles is the earliest. Accordingly, as basic texts, Chapters 6, 7, and 8 of The General Conditions of the Religion Mugeuk-do and the articles from Unofficial Religions of the Korea after 1925, as well as chapter 2 of ‘Progress of the Order’ in The Canonical Scripture are appropriate for studying Mugeuk-do. In addition, Overview of Bocheonism, History of Jeungsan-gyo, and The True Scripture of the Great Ultimate can be utilized as references after removing distortions and fallacies through comparative study. Henceforth, relevant documents should be utilized to establish comprehensive data on Mugeuk-do through comparative and historical research.

Elements of high order in finite fields specified by binomials

Let $F_q$ be a field with $q$ elements, where $q$ is a power of a prime number $p\geq 5$. For any integer $m\geq 2$ and $a\in F_q^*$ such that the polynomial $x^m-a$ is irreducible in $F_q[x]$, we combine two different methods to explicitly construct elements of high order in the field $F_q[x]/\langle x^m-a\rangle$. Namely, we find elements with multiplicative order of at least $5^{\sqrt[3]{m/2}}$, which is better than previously obtained bound for such family of extension fields.

Fast Sparse Decision Tree Optimization via Reference Ensembles.

Sparse decision tree optimization has been one of the most fundamental problems in AI since its inception and is a challenge at the core of interpretable machine learning. Sparse decision tree optimization is computationally hard, and despite steady effort since the 1960's, breakthroughs have been made on the problem only within the past few years, primarily on the problem of finding optimal sparse decision trees. However, current state-of-the-art algorithms often require impractical amounts of computation time and memory to find optimal or near-optimal trees for some real-world datasets, particularly those having several continuous-valued features. Given that the search spaces of these decision tree optimization problems are massive, can we practically hope to find a sparse decision tree that competes in accuracy with a black box machine learning model? We address this problem via smart guessing strategies that can be applied to any optimal branch-and-bound-based decision tree algorithm. The guesses come from knowledge gleaned from black box models. We show that by using these guesses, we can reduce the run time by multiple orders of magnitude while providing bounds on how far the resulting trees can deviate from the black box's accuracy and expressive power. Our approach enables guesses about how to bin continuous features, the size of the tree, and lower bounds on the error for the optimal decision tree. Our experiments show that in many cases we can rapidly construct sparse decision trees that match the accuracy of black box models. To summarize: when you are having trouble optimizing, just guess.

Quantitative Diagnosis of TCM Syndrome Types Based on Adaptive Resonant Neural Network.

Artificial intelligence has become one of the most rapidly developing disciplines in the application field of pattern recognition. In target recognition, sometimes, there are multiple identical or similar copies of the target to be recognized in the image, and it is difficult to classify and estimate by traditional methods. In this case, it is necessary to use the SOM network to separate multiple targets and use the multiple order parameters in the improved SNN to pair the target. The change of its thickness can intuitively reflect the abnormality of its tissue. Therefore, the choroidal thickness of the central fovea can be measured to study the relationship between the choroidal structure and BRVO and arteriosclerosis. The purpose of this study is to further study the correlation between branch retinal vein occlusion and arteriosclerosis by quantitatively measuring retinal vessel diameter and choroidal thickness, to analyze the correlation between different TCM syndrome types of nonischemic BRVO and retinal arteriosclerosis, and to provide theoretical basis for clinical nonischemic BRVO TCM syndrome types and traditional Chinese medicine treatment, so as to reflect its clinical application value. In order to solve the single fixed structure of traditional SNN and poor scalability, combined with the Kohonen layer structure in the self-organizing mapping network, an improved collaborative neural network model is proposed. This paper studies the network training method and operation convergence and analyzes the converged network and the pattern classification results obtained by the network. In order to solve the single fixed structure of traditional SNN and poor scalability, combined with the Kohonen layer structure in the self-organizing mapping network, an improved collaborative neural network model is proposed. The results of our proposed improved model on the MNIST dataset can achieve the same level of current state-of-the-art machine learning classifiers in recognition accuracy with a smaller network size and network complexity.

Polycyclic Aromatic Compounds in Rivers Dominated by Petrogenic Sources after a Boreal Megafire.

Polycyclic aromatic compounds (PACs) threaten the health of aquatic ecosystems. In northeastern Alberta, Canada, decades of oil sands mining and upgrading activities have increased PAC delivery into freshwaters. This PAC pollution adds to natural inputs from river erosion of bitumen-bearing McMurray Formation outcrops and wildfire inputs. Quantifying these petrogenic and pyrogenic PAC inputs, which is key for understanding industrial impacts, remains a challenge. To distinguish petrogenic from pyrogenic inputs, we characterized river water PACs before and after the 2016 Fort McMurray wildfire, one of the largest natural disasters in Canadian history. Samples of wildfire ash and outcropping bitumen allow us to distinguish between these important PAC sources. River PAC concentrations ranged over multiple orders of magnitude (10s-10 000s ng/L). Petrogenic PACs dominated most of the postfire period with only short-term episodes of pyrogenic signatures in burned watersheds due to the wash-in of ash from the watershed. Wildfire PAC inputs during these events resulted in exceptional increases in concentrations that met or exceeded high (petrogenic) background concentrations, driven by the natural erosion of outcropping bitumen. Our dataset offers the first quantification of these two important PAC sources in this industrialized region and provides new insight into the impacts of increasing wildfire frequency and severity across the Boreal Forest.

Fast and scalable quantum Monte Carlo simulations of electron-phonon models.

We introduce methodologies for highly scalable quantum Monte Carlo simulations of electron-phonon models, and we report benchmark results for the Holstein model on the square lattice. The determinant quantum Monte Carlo (DQMC) method is a widely used tool for simulating simple electron-phonon models at finite temperatures, but it incurs a computational cost that scales cubically with system size. Alternatively, near-linear scaling with system size can be achieved with the hybrid Monte Carlo (HMC) method and an integral representation of the Fermion determinant. Here, we introduce a collection of methodologies that make such simulations even faster. To combat "stiffness" arising from the bosonic action, we review how Fourier acceleration can be combined with time-step splitting. To overcome phonon sampling barriers associated with strongly bound bipolaron formation, we design global Monte Carlo updates that approximately respect particle-hole symmetry. To accelerate the iterative linear solver, we introduce a preconditioner that becomes exact in the adiabatic limit of infinite atomic mass. Finally, we demonstrate how stochastic measurements can be accelerated using fast Fourier transforms. These methods are all complementary and, combined, may produce multiple orders of magnitude speedup, depending on model details.

Three-dimensional simulation of impinging jet atomization of soft mist inhalers using the hybrid VOF-DPM model

Impinging jet atomization is a new approach in inhalation therapy for drug delivery. Numerical simulation is a powerful tool for pursuing better understandings of the impinging jet dynamics. However, it is an extremely challenging task to simulate atomization of soft mist inhalers due to their complex nozzle geometry and spatial-temporal evolution of jets and droplets whose sizes span multiple orders of magnitude. In this work, the atomization process was simulated by a Computational Fluid Dynamics (CFD) model that couples the Volume of Fluid method (VOF), Discrete Phase Model (DPM), and Adaptive Mesh Refinement (AMR). A mapping approach was used to efficiently couple the liquid flow inside the small-scale nozzle with the large-scale multiphase jet flow outside the nozzle. The influence of flow field inside the nozzle on the atomization characteristics was explored. The numerical and experimental jet dynamics are consistent with regard to the plume geometry and particle size distribution. It was revealed that with the increase of the impingement angle and nozzle inlet pressure, the fluctuation of liquid sheet becomes more violent, which directly affects the breakup pattern and leads to much finer droplets. This method can be used to optimize the inhalers for better atomization performance.