Propagation Method Research Articles

Distribution, importance and constraints in gum and resin bearing species in Ethiopia

Dry forest is the largest forest type in Ethiopia that currently covers 55 M ha. These forests are predominantly rich in Acacia, Boswellia and Commiphora species that gives the important export commodities such as gum arabic, frankincense and myrrh. However, these forests are suffering by huge degradation due to anthropogenic pressures also they are shrinking continuously by the expansion of agricultural lands, human settlement, overgrazing, and lack of policy and inappropriate tapping method. The aim of this paper was to review distribution, importance and constraints in gum and resin bearing species in Ethiopia. In Ethiopia expected areas covered by natural gum and resin bearing species in the different regions, the leading one Tigray have 940000 ha coverage, the other Amhara, Oromía, Gam-bela, Somalia, Beneshangul-Gumuz, Nationalities and Peoples of the South (SNNP) and Afar followed Tigray region respectively. The majority of the households in rural Ethiopia make use of non-timber forest products (NTFPs) for different purposes, extending from food, feed, energy, and medicine to income generation and cultural practices. Among the range of NTFPs, gums and resins are advanta-geous trade commodities with a potential for helping social and economic developments both at rural and urban areas in Ethiopia. Commercial gums and resins are produced in rural areas, traded in urban and utilized by western countries and, hence, touch varied ranges of human lives and cross-sections. Therefore, adequate research and clear action oriented plans, improve tapping methods, clear policy about utilization and conservation gum and resin bearing species and identify method of propagation is recommended.

Reverse design of the ideal pulse for hollow capillary fiber post-compression schemes

The countless applications of ultrashort laser pulses in very different scientific areas explain the ongoing efforts to develop new strategies for the generation of light pulses with increasingly better characteristics. In this work, we theoretically study the application of the nonlinear reverse propagation method to produce few-cycle pulses with clean temporal profiles from standard post-compression setups based in hollow capillary fibers. By numerically solving the propagation of a desired goal pulse in the backward direction, we are able to predict the structure of the ideal input pulse that could be perfectly compressed in a given setup. Although the goal pulse cannot be chosen in a simple manner due to the fundamental symmetries of the nonlinear propagation equation, our analysis shows that the ideal pulse presents a recurring form and that, in general, both its intensity profile and phase must be shaped to recover the optimized goal output. Published by the American Physical Society 2024

An efficient uncertainty propagation method for nonlinear dynamics with distribution-free P-box processes

The distribution-free P-box process serves as an effective quantification model for time-varying uncertainties in dynamical systems when only imprecise probabilistic information is available. However, its application to nonlinear systems remains limited due to excessive computation. This work develops an efficient method for propagating distribution-free P-box processes in nonlinear dynamics. First, using the Covariance Analysis Describing Equation Technique (CADET), the dynamic problems with P-box processes are transformed into interval Ordinary Differential Equations (ODEs). These equations provide the Mean-and-Covariance (MAC) bounds of the system responses in relation to the MAC bounds of P-box-process excitations. They also separate the previously coupled P-box analysis and nonlinear-dynamic simulations into two sequential steps, including the MAC bound analysis of excitations and the MAC bounds calculation of responses by solving the interval ODEs. Afterward, a Gaussian assumption of the CADET is extended to the P-box form, i.e., the responses are approximate parametric Gaussian P-box processes. As a result, the probability bounds of the responses are approximated by using the solutions of the interval ODEs. Moreover, the Chebyshev method is introduced and modified to efficiently solve the interval ODEs. The proposed method is validated based on test cases, including a duffing oscillator, a vehicle ride, and an engineering black-box problem of launch vehicle trajectory. Compared to the reference solutions based on the Monte Carlo method, with relative errors of less than 3%, the proposed method requires less than 0.2% calculation time. The proposed method also possesses the ability to handle complex black-box problems.

Binary Graph Convolutional Network With Capacity Exploration.

The current success of Graph Neural Networks (GNNs) usually relies on loading the entire attributed graph for processing, which may not be satisfied with limited memory resources, especially when the attributed graph is large. This paper pioneers to propose a Binary Graph Convolutional Network (Bi-GCN), which binarizes both the network parameters and input node attributes and exploits binary operations instead of floating-point matrix multiplications for network compression and acceleration. Meanwhile, we also propose a new gradient approximation based back-propagation method to properly train our Bi-GCN. According to the theoretical analysis, our Bi-GCN can reduce the memory consumption by an average of ∼31x for both the network parameters and input data, and accelerate the inference speed by an average of ∼51x, on three citation networks, i.e., Cora, PubMed, and CiteSeer. Besides, we introduce a general approach to generalize our binarization method to other variants of GNNs, and achieve similar efficiencies. Although the proposed Bi-GCN and Bi-GNNs are simple yet efficient, these compressed networks may also possess a potential capacity problem, i.e., they may not have enough storage capacity to learn adequate representations for specific tasks. To tackle this capacity problem, an Entropy Cover Hypothesis is proposed to predict the lower bound of the width of Bi-GNN hidden layers. Extensive experiments have demonstrated that our Bi-GCN and Bi-GNNs can give comparable performances to the corresponding full-precision baselines on seven node classification datasets and verified the effectiveness of our Entropy Cover Hypothesis for solving the capacity problem.

WALISONGO DAN VOICE OF BACEPROT: SYIAR ISLAM INKULTURATIF DI INDONESIA

Voice of Baceprot (VoB) is a heavy metal band consisting of three young Muslim sisters from Garut, Indonesia. The emergence of VoB is a catalyst in the Islamic world. In the context of the propagation of Islamic values, the presence of VoB with its heavy metal music can be compared to the propagation method applied by the Wali Songo to the Javanese community. Clifford Geertz gave the title to the Wali Songo as cultural brokers because of their role in synthesizing Javanese traditions with Islamic teachings. If Wali Songo used the macapat & gamelan art traditions to spread Islam to the Javanese people, VoB chose the heavy metal music genre to spread Islamic values to the world today. VoB's choice of music with the heavy metal genre itself has certainly raised many questions, how Islam views music, especially heavy metal. The composition of VoB band personnel consisting of 3 young women with complete hijab clothing and singing heavy metal music as their stage identity not only makes VoB a cultural broker but also a political actor for Islamic women in the world arena. When analyzed with the framework of Christian theological reflection from theologian Kosuke Koyama, what VoB has done is part of the concept of contextual participatory theology. Koyama expresses the importance of respecting local culture and context in the appreciation and meaning of faith. Thus, VoB emerges as a unique and innovative representation in preaching, providing a new understanding of the role of women, and heavy metal music in today's Islamic world.

Saffron In Vitro Propagation: An Innovative Method by Temporary Immersion System (TIS), Integrated with Machine Learning Analysis

The propagation of Crocus sativus L. relies exclusively on corm multiplication. As underground storage organs, corms are susceptible to a wide range of pathogens, environmental stresses, and diseases, making traditional propagation methods often ineffective with the loss of valuable material. In vitro propagation offers an alternative for the saffron culture under controlled conditions. In particular, the innovative application of the Temporary Immersion System (TIS) represents a technological advancement for enhancing biomass production with a reduction in operational costs. The current study utilized the Plantform™ bioreactor to propagate in vitro saffron corms from the ‘Abruzzo’ region (Italy), integrating machine learning models to assess its performance. The evaluation of saffron explants after 30, 60, and 90 days of culture showed a marked improvement in growth and microcorm production compared to conventional in vitro culture on semisolid medium, supported by the machine learning analysis. Indeed, the Random Forest algorithm revealed a predictive accuracy with an R2 value of 0.81 for microcorm number, showcasing the capability of machine learning models to forecast propagation outcomes effectively. These results confirm that applying TIS in saffron culture could lead to economically viable, large biomass production within a controlled environment, irrespective of seasonality. This study represents the first endeavor to use TIS technology to enhance the in vitro propagation of saffron in conjunction with machine learning, suggesting an innovative approach for cultivating high-value crops like saffron.

Evaluating Propagation Techniques for Cannabis sativa L. Cultivation: A Comparative Analysis of Soilless Methods and Aeroponic Parameters.

Given the rapid growth of the Cannabis industry, developing practices for producing young plants with limited genetic variation and efficient growth is crucial to achieving reliable and successful cultivation results. This study presents a multi-faceted experiment series analyzing propagation techniques for evaluating proficiency in the growth and development of Cannabis vegetative cuttings. This research encompasses various (1) soilless propagation methods including aeroponics, horticultural (phenolic) foam, and rockwool; (2) transplant timings; (3) aeroponic spray intervals; and (4) aeroponic reservoir nutrient concentrations, to elucidate their impact on rooting and growth parameters amongst two Cannabis cultivars. Aeroponics was as effective as, and in some cases more effective than, soilless propagation media for root development and plant growth. In aeroponic systems, continuous spray intervals, compared to intermittent, result in a better promotion of root initiation and plant growth. Moreover, raised nutrient concentrations in aeroponic propagation demonstrated greater rooting and growth. The effects of experimental treatment were dependent on the cultivar and sampling day. These findings offer valuable insights into how various propagation techniques and growth parameters can be tailored to enhance the production of vegetative cuttings. These results hold critical implications for cultivators intending to achieve premium harvests through efficient propagule methods and optimization strategies in the competitive Cannabis industry. Ultimately, our findings suggest that aeroponic propagation, compared to alternative soilless methods, is a rapid and efficient process for cultivating vegetative cuttings of Cannabis and offers sustainable advantages in resource conservation and preservation.

A Method for the Rapid Propagation of Emergency Event Notifications in a Long Vehicle Convoy

Convoys composed of autonomous vehicles could improve the transportation and freight industries in several ways. One of the avenues of improvement is in fuel efficiency, where the vehicles maintain a close following distance to each other in order to reduce air resistance by way of the draft effect. While close following distances improve fuel efficiency, they also reduce both the margin of safety and the system’s tolerance to disturbances in relative position. The system’s tolerance to disturbances is known as string stability, where the error magnitude either grows or decays as it propagates rearward through the convoy. One of the major factors in a system’s string stability is its delay in sending state updates to other vehicles, the most pertinent being a hard braking maneuver. Both external sensors and vehicle-to-vehicle communication standards have relatively long delays between peer vehicle state changes and the information being actionable by the ego vehicle. The system presented here, called the Convoy Vehicular Ad Hoc Network (Convoy VANET), was designed to reliably propagate emergency event messages with low delay while maintaining reasonable channel efficiency. It accomplishes this using a combination of several techniques, notably relative position-based retransmission delays. Our results using Network Simulator 3 (ns3) show the system propagating messages down a 20-vehicle convoy in less than 100 ms even with more than a 35% message loss between vehicles that are not immediately adjacent. These simulation results show the potential for this kind of system in situations where emergency information must be disseminated quickly in low-reliability wireless environments.

Successful shoot tip grafting of cacao (Theobroma cacao L.) due to the application of plant growth regulators on various concentrations

Cacao plays an important role in the Indonesia economy. Therefore, its production and area expansion have to increase to achieve maximum cacao productivity by the quality and superior cacao clones. Shoot tip grafting is one of the propagation methods to obtain superior cacao plants by applying Plant Growth Regulators (PGRs). Research on the effect of several PGRs with various concentrations on cacao (Theobroma cacao L.) shoot tip grafting was conducted at the Integrated Innovation Farmer Group, Belubus, Sungai Talang Village, Guguak District, Lima Puluh Kota Regency, West Sumatra from February until June 2022. This study aimed to determine the interaction between PGR type and concentration on the grafting success and growth of cacao shoot tip grafted seedling. The research was designed by a Factorial Completely Randomized Design with three replications. The first factor was the type of PGR, i.e., synthetic PGR (BAP), young corn seed extract, shallot extract, and young coconut water. The second factor was the concentration of PGR, i.e., 0%, 25%, 50%, 75% and 100%. The results showed an interaction between PGRs with some concentrations on the number of shoots, shoot length, and leaf length on the grafted cacao seedling. The natural PGR from young coconut water at a concentration of 75% gave the best effect on the number of shoots (3.33 shoots) and shoot length (24.50 cm) of cacao seedling.

A nodal discontinuous Galerkin method for wave propagation in coupled acoustic–elastic media

AbstractThe accurate numerical solution at an acoustic–elastic interface is important for offshore exploration. The solution requires careful implementation for the acoustic–elastic boundary conditions. In this work, we leverage a nodal discontinuous Galerkin method, in which the unstructured uniform triangular meshes are used for the model meshing and an explicit upwind numerical flux derived from the Riemann problem is adopted to handle the boundary conditions at the acoustic–elastic interface. Several numerical results are provided to assess the accuracy and convergence properties of this method. The convergence analysis is carried out in the coupled model with a flat interface, and the accuracy of the proposed method is verified in the curved interface coupled model. Finally, a more complex model with a salt dome, inspired by real geophysical applications, is carried out in this study. The numerical results demonstrate that the proposed nodal discontinuous Galerkin method is effective and accurate for dealing with the coupled acoustic–elastic media with complex geometries.

A novel uncertainty propagation and probability assessment method for the frequency response function involving correlated uncertainties

A novel uncertainty propagation and probability assessment method for the frequency response function involving correlated uncertainties

Implications of the Propagation Method for the Phytochemistry of Nepeta cataria L. throughout a Growing Season.

Catnip (Nepeta cataria L.) plants produce a wide array of specialized metabolites with multiple applications for human health. The productivity of such metabolites, including nepetalactones, and natural insect repellents is influenced by the conditions under which the plants are cultivated. In this study, we assessed how field-grown catnip plants, transplanted after being propagated via either single-node stem cuttings or seeds, varied regarding their phytochemical composition throughout a growing season in two distinct environmental conditions (Pittstown and Upper Deerfield) in the state of New Jersey, United States. Iridoid terpenes were quantified in plant tissues via ultra-high-performance liquid chromatography with triple quadrupole mass spectrometry (UHPLC-QqQ-MS), and phenolic compounds (phenolic acids and flavonoids) were analyzed via UHPLC with diode-array detection (UHPLC-DAD). The highest contents of total nepetalactones in Pittstown were found at 6 weeks after transplanting (WAT) for both seedlings and cuttings (1305.4 and 1223.3 mg/100 g, respectively), while in Upper Deerfield, the highest contents for both propagules were at 11 WAT (1247.7 and 997.1 mg/100 g, respectively) for seed-propagated and stem cuttings). The highest concentration of nepetalactones was associated with floral-bud to partial-flowering stages. Because plants in Pittstown accumulated considerably more biomass than plants grown in Upper Deerfield, the difference in nepetalactone production per plant was striking, with peak productivity reaching only 598.9 mg per plant in Upper Deerfield and 1833.1 mg per plant in Pittstown. Phenolic acids accumulated in higher contents towards the end of the season in both locations, after a period of low precipitation, and flavone glycosides had similar accumulation patterns to nepetalactones. In both locations, rooted stem cuttings reached their maximum nepetalactone productivity, on average, four weeks later than seed-propagated plants, suggesting that seedlings have, overall, better agronomic performance.

The Influence of Maturity, Storage, and Embryo Size on Coconut Callus Induction Success

Coconut palms (Cocos nucifera L.) are globally significant palms with both economic and cultural value. Despite the increasing demand for coconut products, production is decreasing globally due to palm senility, pests, and diseases. It has been estimated that over half of the world’s coconut palms need to be replaced immediately. The coconut industry has acknowledged that conventional propagation methods are unlikely to yield sufficient high-quality planting material. Therefore, coconut tissue culture is considered a potential solution to this problem. By using coconut tissue culture, a large number of plantlets can be obtained in a short period of time. In this study, the quality of explants and the development stage (visible shoot/non-visible shoot) of coconut used for micropropagation were examined. To our knowledge, little research has been undertaken on this aspect of coconut micropropagation. Our results indicated that tender coconut fruit exhibited an advantage over mature fruits. In addition, coconut plumule explants subjected to an extended storage of 15 days demonstrated enhanced development compared to those without storage. Notably, smaller embryos utilized as explants displayed superior callus formation compared to their larger counterparts. Finally, embryos possessing shoots exhibited improved callus initiation, albeit accompanied by a more pronounced browning effect. Further investigations are required to obtain more knowledge about the most suitable conditions for plumule explants that lead to optimal callus initiation.

Approximate propagation of normal distributions for stochastic optimal control of nonsmooth systems

We present a method for the approximate propagation of mean and covariance of a probability distribution through ordinary differential equations (ODE) with discontinuous right-hand side. For piecewise affine systems, a normalization of the propagated probability distribution at every time step allows us to analytically compute the expectation integrals of the mean and covariance dynamics while explicitly taking into account the discontinuity. This leads to a natural smoothing of the discontinuity such that for relevant levels of uncertainty the resulting ODE can be integrated directly with standard schemes and it is neither necessary to prespecify the switching sequence nor to use a switch detection method. We then show how this result can be employed in the more general case of piecewise smooth functions based on a structure preserving linearization scheme. The resulting dynamics can be straightforwardly used within standard formulations of stochastic optimal control problems with chance constraints.

Wave optical propagation in realistic lens systems through multi-slice decomposition with phase compensation

A fast and accurate optical simulation is essential in the design and analysis of optical systems. We propose a wave propagation method through multi-slice decomposition with phase compensation (MSDP) to calculate the wave propagation in realistic lens systems. An estimation of the phase compensation term for the refraction effect and diffraction effect is given, and a modified phase compensation term is presented for calculation through optical systems with a high numerical aperture or an incident optical field featuring a broad spectrum. The proposed method yields accurate and fast results for micro-optical lens systems with the radius of curvature comparable to an illumination wavelength. In a macroscopic optical system with a high numerical aperture, an object with abundant spatial frequencies is reconstructed from the diffraction patterns produced by a single aspherical lens, further demonstrating the effectiveness and applicability of the method in realistic lens systems.

Localised wavenumber estimation and its application to waveguide discontinuities

Wave propagation methods have been widely investigated for the potential application to the detection and localisation of discontinuities in structural waveguides. In the low-mid frequency ranges, previous preliminary works that used the analytic signal theory have considered local wavenumber estimations based on the time domain for the purpose of localisation in mechanical structures. However, these have not fully exploited the potential of this approach. This is accomplished herein for a one-dimensional infinite-like waveguide by means of two methods applied in the spatial domain; namely the Hilbert transform via the wavenumber domain estimator and the Direct Quadrature method. Modifications are proposed to make these methods more suitable to the space-wavenumber application and for the purpose of localisation. A three-dimensional plot is proposed, where local divergences of the wavenumbers indicate the positions of the discontinuities for otherwise uniform waveguides. Numerical simulations and experiments show an accurate estimation of the local wavenumbers and validate the methods with the proposed modifications for the localisation of different types of discontinuities.

A compressed 2D-DOA and polarization estimation algorithm for mmWave polarized massive MIMO systems

Due to providing greater degrees-of-freedom (DOFs) and securer communication guarantees than traditional scalar array, polarized massive multiple-input multiple-output (MIMO) technique offers a prospective insight into millimeter-wave (mmWave) communication. In this paper, a compressed two-dimensional (2D) direction-of-arrival (DOA) and polarization estimation algorithm combining the compressive sampling propagator method with reduced-dimension multiple signal classification (CSPM-RDMUSIC) is developed for mmWave polarized massive MIMO systems. First, a synchronous compressive network is constructed to compress the high-dimensional output into a low-dimensional one. Thereafter, a propagator is structured to acquire the signal subspace. Subsequently, accurate 2D-DOA and polarization estimation are achieved using a coarse-refined strategy, where the vector cross-product technology is investigated for coarse 2D-DOA estimation and then RDMUSIC is exploited to perform 2D local search for accurate parameter estimation. Owing to integrating the CSPM framework with the RDMUSIC strategy, the developed approach provides high-precision parameter estimation with relative computational economy, supporting mmWave communication demands. What's more, it's suitable for arbitrary array geometry with high flexibility. Several experimental results validate the superiorities of the developed framework.

Design and Optimization of Air Inlet in Cuttings Incubator

The microclimate environment can be conveniently controlled with accuracy by plant incubators, in which the cuttings propagation method can efficiently enhance seedling production. To ensure air flow evenly throughout the incubator, the scientific design of the air inlet is crucial. This study utilized a computational fluid dynamics (CFD) model to simulate the airflow patterns in a culture layer under different air inlet conditions. Furthermore, the optimal design parameters were determined by way of response surface methodology (RSM) and the Non-dominated Sorting Genetic Algorithm-II (NSGA-II). Adopting the optimal parameters, a prototype was manufactured, and a cuttings experiment was carried out with apple cuttings in the incubator. The results showed that the optimal air inlet radius is 90 mm, the optimal air inlet height is 188 mm, and the optimal uniform flow plate hole diameter is 13 mm. Meanwhile, the apple cuttings were able to root. Therefore, this incubator with optimal parameters can be used for cuttings. The study provides a methodological and theoretical basis for the future optimizing of air inlet parameters and promoting cuttings rooting.

Broadband silicon nitride integrated polarization rotators at 780 nm

Polarization management, and in particular polarization rotation, is becoming increasingly important for photonic integrated circuits (PICs). While fiber-optic networks are generally polarization insensitive, the large aspect ratio of high-index-contrast PIC waveguides leads to a large polarization-dependent response of integrated components such as waveguides, optical cavities, couplers, etc. Although foundry-processed polarization rotators operating at telecom and datacom wavelengths (C- and O-band) have been demonstrated, to date, there have been few reports of devices operating at shorter wavelengths. This work demonstrates silicon nitride (SiN) polarization rotators operating from λ=700-1000 nm (the I/Z-band) that take advantage of optical coupling between two waveguiding layers in a standard foundry process. We demonstrate a broadband white-light polarization measurement setup that enables precise characterization of the polarization-dependent transmission of photonic waveguide devices. Measurements on foundry-processed devices confirm full TE-to-TM rotation exhibiting a maximum polarization extinction ratio (PER) approaching 20 dB (limited by our measurement setup), and an exceptionally large bandwidth of up to 160 nm with an insertion loss less than 0.2 dB. Beam propagation method (3D-BPM) simulations show good agreement with experimental data and enable the device parameters to be adjusted to accommodate different operating wavelengths and geometries with no changes to the existing foundry process. This work opens up opportunities for applications in quantum information and bio-sensing where operation at λ<1000nm is needed.

Morphological Reconstruction for Variable Wing Leading Edge Based on the Node Curvature Vectors.

Precise morphology acquisition for the variable wing leading edge is essential for its bio-inspired adaptive control. Therefore, this study proposes a morphological reconstruction method for the variable wing leading edge, utilizing the node curvature vectors-based curvature propagation method (NCV-CPM). By establishing a strain-arc curvature function, the method fundamentally mitigates the impact of surface curvature angle on curvature computation accuracy at sensing points. We introduce a technique that uses high-order curvature fitting functions to determine the curvature vectors of arc segment nodes. This method reduces cumulative errors in curvature computation linked to the linear interpolation-based curvature propagation method (LI-CPM) at unattached sensor positions. Integrating curvature-strain functions aids in wing leading-edge strain field reconstruction, supporting structural health monitoring. Additionally, a particle swarm algorithm optimizes the sensing point distribution, reducing network complexity. This study demonstrates significantly enhanced morphological reconstruction accuracy compared to those obtained with conventional LI-CPM.