Forward Step Research Articles

Forward steps in green medical laboratory practices for a sustainable future

Abstract This paper provides information on the significance of environmental sustainability and the potential benefits of implementing green laboratory processes. Sustainability is a broad concept that includes goals such as conservation of natural resources, energy efficiency, waste management, and reducing environmental footprints. Green laboratories strive to minimise environmental footprints by embedding sustainability principles into their everyday practices. This involves improvements in energy consumption, water usage, chemical waste reduction, and recycling, ultimately, as well as lower waste disposal costs. Implementing green laboratory approaches provides many benefits, such as a smaller environmental footprint, increased energy efficiency, water conservation, and cost savings. Moreover, a rational test ordering process can effectively contribute to reducing environmental impacts in medical laboratories. Rational test ordering provides cost-effectiveness and reduces the carbon footprint. Establishing a green and sustainable laboratory culture in medical laboratories requires a permanent organisation in where all personnel participate. Training of the hospital management teams, clinicians, and laboratory professionals is a vital point. Methodology and quality indicators should be defined by international and national laboratory associations within the framework of a green and sustainable laboratory plan, and data should be collected. In conclusion, adopting green laboratory practices reduces environmental impacts, saves costs, and accelerates innovation processes. Setting quality targets and rational test ordering practices are also essential for sustainability. Applying sustainability principles in laboratory workplaces is an important step towards protecting the environment and leaving a more liveable world for future generations.

Drag reduction using riblets downstream of a high Reynolds number inclined forward step flow

Micro-riblet is an efficient passive method for controlling turbulent boundary layers, with the potential to reduce frictional drag. In various applications within the transportation industry, flow separation is a prevalent flow phenomenon. However, the precise drag reduction performance of riblets in the presence of flow separation remains unclear. To address this, an inclined forward step model is proposed to investigate the interaction between riblet and upstream flow separation. The large eddy simulation (LES) method is applied to simulate the flow over geometries with different step angles and riblet positions. The results show riblets still reduce wall frictional resistance when subjected to the upstream flow separation. Remarkably, as the angle of the step increases from 0° to 30°, the drag reduction experiences an increment from 9.5% to 12.6%. From a turbulence statistics standpoint, riblets act to suppress the Reynold stress in the near-wall region and dampen ejection motions, thus weakening momentum exchange. Quadrant analysis reveals that with the augmentation of flow separation, the Q2 motion within the flow field intensifies, subsequently enhancing the riblet-induced drag reduction. Moreover, the position of the riblets has a significant impact on the pressure drag. Riblets close to the point of separation enhance flow separation, altering the surface pressure distribution and thus increasing the resistance. The results reveal that when the riblets are positioned approximately 160 riblet heights away from the step, their effect on the upstream flow separation becomes negligible. The precise performance of riblets under complex flow conditions is important for their practical engineering application.

The effect of cognitive tasks on reactive stepping in young and older adults

BackgroundDivided attention is commonly required in daily life, and to prevent falls, balance must be recovered when a person experiences unexpected perturbations. Previous studies have shown that additional cognitive tasks in postural responses negatively affect automatic postural responses. However, the effect of dual-tasking on reactive stepping performance is still not clearly understood. This study investigated the effect of dual-tasking on reactive stepping induced by a large perturbation in older adults and characterized the effect of dual-tasking by comparison with young adults. Research questionHow does the effect of dual-tasking on reactive stepping performance differ between young and older adults? MethodsTwenty-nine older adults and twenty-two young adults were prospectively exposed to external perturbations to induce forward reactive steps. Perturbations were delivered under simple front fixed gaze (single-task condition) and modified Stroop task (dual-task condition). Measures of the time to foot-off and reach stability, step length, velocity, and number of steps were based on force plate data for both the single- and dual-task conditions. ResultsYoung and older adults showed a delay in foot-off time during the dual-task condition compared with that during the single-task condition. The reach stability time, step length, and number of steps were worse in the dual-task condition than in the single-task condition for older adults, but not for young adults. The deficits in reactive stepping performance during dual-tasking could reflect the reactive balance capacity in real life. SignificanceThe findings of this study highlight the increased risk of falls with age.

Forward step down test - clinical rating is correlated with joint angles of the pelvis and hip: an observational study

BackgroundClinical methods for assessing quality of movement and functional tests are important to clinicians. Typical deviations from normal kinematics during the clinical test of Forward Step Down Test (FSDT) are pelvic tilt and hip adduction which are associated with the risk of knee pain.Objectives(1) to examine the correlation between clinical assessment of the FSDT and joint angle measurements of pelvis, hip, knee and ankle joints in males and females; (2) to examine the differences in joint angles between individuals rated as good, fair or poor in a FSDT performance test.MethodsNinety-two healthy individuals performing FSDT were video-taped with two-dimensional digital video cameras. The clinical assessment of the FSDT was rated by two experienced physical therapists as good, fair, or poor based on a Crossley et al. (2011) validated scale. Measurements of pelvic drop, hip adduction and knee valgus were taken using Image J software.ResultsOut of 177 lower limbs, 74 (37 in each limb) were clinically rated as “good/fair” (41.80%) while 103 (52 in the dominant leg and 51 in the non-dominant leg) were rated as “poor” (58.19%). No significant differences were observed between dominant and non-dominant legs or between males and females in clinical rating of the FSDT. Pelvic drop angle was significantly higher and hip adduction angle was significantly lower for “poor” clinical rating compared to “good/fair” in both dominant and non-dominant legs (p < 0.001) in males and females. Females demonstrated higher pelvic drop, lower hip adduction and higher knee valgus angles compared with males (p < 0.05).ConclusionsThis study showed that the clinical rating of FSDT is correlated with joint angle measurements suggesting that this assessment can be utilized in clinical practice. Individuals with poor quality performance of FSDT showed higher pelvic drop and hip adduction movement. Further studies examining different populations with diverse disorders or pathologies are essential.

High-speed AFM imaging reveals DNA capture and loop extrusion dynamics by cohesin-NIPBL

3D chromatin organization plays a critical role in regulating gene expression, DNA replication, recombination, and repair. While initially discovered for its role in sister chromatid cohesion, emerging evidence suggests that the cohesin complex (SMC1, SMC3, RAD21, and SA1/SA2), facilitated by NIPBL, mediates topologically associating domains and chromatin loops through DNA loop extrusion. However, information on how conformational changes of cohesin-NIPBL drive its loading onto DNA, initiation, and growth of DNA loops is still lacking. In this study, high-speed atomic force microscopy imaging reveals that cohesin-NIPBL captures DNA through arm extension, assisted by feet (shorter protrusions), and followed by transfer of DNA to its lower compartment (SMC heads, RAD21, SA1, and NIPBL). While binding at the lower compartment, arm extension leads to the capture of a second DNA segment and the initiation of a DNA loop that is independent of ATP hydrolysis. The feet are likely contributed by the C-terminal domains of SA1 and NIPBL and can transiently bind to DNA to facilitate the loading of the cohesin complex onto DNA. Furthermore, high-speed atomic force microscopy imaging reveals distinct forward and reverse DNA loop extrusion steps by cohesin-NIPBL. These results advance our understanding of cohesin by establishing direct experimental evidence for a multistep DNA-binding mechanism mediated by dynamic protein conformational changes.

Dynamic gradient reactivation for backward compatible person re-identification

We study the backward compatible problem for person re-identification (Re-ID), which aims to constrain the features of an updated new model to be comparable with the existing features from the old model in galleries. Most of the existing works adopt distillation-based methods, which focus on pushing new features to imitate the distribution of the old ones. However, the distillation-based methods are intrinsically sub-optimal since it forces the new feature space to imitate the inferior old feature space. To address this issue, we propose the Ranking-based Backward Compatible Learning (RBCL), which directly optimizes the ranking metric between new features and old features. Different from previous methods, RBCL only pushes the new features to find best-ranking positions in the old feature space instead of strictly alignment, and is in line with the ultimate goal of backward retrieval. However, the sharp sigmoid function used to make the ranking metric differentiable also incurs the gradient vanish issue, therefore stems the ranking refinement during the later period of training. To address this issue, we propose the Dynamic Gradient Reactivation (DGR), which can reactivate the suppressed gradients by adding dynamically computed constants during the forward step. To further help target the best-ranking positions, we include the Neighbor Context Agents (NCAs) to approximate the entire old feature space during training. Unlike previous works that mainly test on the in-domain settings, we make the early attempt to introduce the cross-domain settings (including both supervised and unsupervised) for the backward compatible person Re-ID task, which are more challenging yet meaningful. The experimental results on all five settings show that the proposed RBCL outperforms previous state-of-the-art methods by large margins.

Achieving highly reversible zinc metal anode via surface termination chemistry

An oxidation layer on a Zn surface is considered to play a negative role in hindering the practical applications of aqueous zinc ion batteries (AZBs). Herein, we demonstrate the importance of Zn-surface termination on the overall electrochemical behavior of AZBs by revisiting the well-known bottleneck issues. Experimental characterizations in conjugation with theoretical calculations reveal that the formation of a dense Zn4(OH)6SO4·xH2O (ZSH) layer from the well-designed surface-oxide termination layer improves the interface stability of the Zn anode and reduces the dehydration energy of Zn(H2O)62+, thereby accelerating the interface transport kinetics of Zn2+. Moreover, instead of directly diffusing over the ZSH layer, a new “edge dehydration-along edge transfer” mechanism of Zn2+ is discovered. Owing to the presence of a Zn anode with a ZnO-derived ZSH layer, an ultrahigh stability of over 1200 h with a high cumulative-plated capacity of 6.24mAh cm−2 is achieved with a symmetrical cell. Furthermore, high cycling stability (over 1000 cycles) and Coulombic efficiency (99.07%) are obtained in the entire AZBs with a MnO2 cathode. An understanding of the oxygen surface termination mechanism is beneficial to Zn-anode protection and is a timely forward step toward the long-pursued practical application of AZBs.

Predicting aqueous sorption of organic pollutants on microplastics with machine learning

Microplastics (MPs) are ubiquitously distributed in freshwater systems and they can determine the environmental fate of organic pollutants (OPs) via sorption interaction. However, the diverse physicochemical properties of MPs and the wide range of OP species make a deeper understanding of sorption mechanisms challenging. Traditional isotherm-based sorption models are limited in their universality since they normally only consider the nature and characteristics of either sorbents or sorbates individually. Therefore, only specific equilibrium concentrations or specific sorption isotherms can be used to predict sorption. To systematically evaluate and predict OP sorption under the influence of both MPs and OPs properties, we collected 475 sorption data from peer-reviewed publications and developed a poly-parameter-linear-free-energy-relationship-embedded machine learning method to analyze the collected sorption datasets. Models of different algorithms were compared, and the genetic algorithm and support vector machine hybrid model displayed the best prediction performance (R2 of 0.93 and root-mean-square-error of 0.07). Finally, comparison results of three feature importance analysis tools (forward step wise method, Shapley method, and global sensitivity analysis) showed that chemical properties of MPs, excess molar refraction, and hydrogen-bonding interaction of OPs contribute the most to sorption, reflecting the dominant sorption mechanisms of hydrophobic partitioning, hydrogen bond formation, and π-π interaction, respectively. This study presents a novel sorbate-sorbent-based ML model with a wide applicability to expand our capacity in understanding the complicated process and mechanism of OP sorption on MPs.

Fast GPU-based Two-way Continuous Collision Handling

Step-and-project is a popular method to simulate non-penetrating deformable bodies in physically based animation. The strategy is to first integrate the system in time without considering contacts and then resolve potential intersections, striking a good balance between plausibility and efficiency. However, existing methods can be defective and unsafe when using large time steps, taking risks of failure or demanding repetitive collision testing and resolving that severely degrade performance. In this article, we propose a novel two-way method for fast and reliable continuous collision handling. Our method launches an optimization from both ends of the intermediate time-integrated state and the previous intersection-free state. It progressively generates a piecewise linear path and eventually obtains a feasible solution for the next time step. The algorithm efficiently alternates between a forward step and a backward step until the result is conditionally converged. Thanks to a set of unified volume-based contact constraints, our method offers flexible and reliable handling of various codimensional deformable bodies, including volumetric bodies, cloth, hair, and sand. Experimental results demonstrate the safety, robustness, physical fidelity, and numerical efficiency of our method, making it particularly suitable for scenarios involving large deformations or large time steps.

CT‐value conservation based spatial transformer network for cardiac motion correction

AbstractArtifact correction is a great challenge in cardiac imaging. During the correction of coronary tissue with motion‐induced artifacts, the spatial distribution of CT value not only shifts according to the motion vector field (MVF), but also shifts according to the volume change rate of the local voxels. However, the traditional interpolation method does not conserve the CT value during motion compensation. A new sample interpolation algorithm is developed based on the constraint of conservation of CT value before and after image deformation. This algorithm is modified on the existing interpolation algorithms and can be embedded into neural networks with deterministic back propagation. Comparative experimental results illustrate that the method can not only correct motion‐induced artifacts, but also ensure the conservation of CT value in the region of interest (ROI) area, so as to obtain corrected images with clinically recognized CT value. Both effectiveness and efficiency are proved in forward motion correction process and backward training steps in deep learning. Simultaneously, using the network to learn the MVF making this method more interpretable than the existing image‐based end‐to‐end deep learning method.

Fast backward steps and detachment of single kinesin molecules measured under a wide range of loads.

To understand force generation under a wide range of loads, the stepping of single kinesin molecules was measured at loads from -20 to 42 pN by optical tweezers with high temporal resolution. The optical trap has been improved to halve positional noise and increase bandwidth by using 200-nm beads. The step size of the forward and backward steps was 8.2 nm even over a wide range of loads. Histograms of the dwell times of backward steps and detachment fit well to two independent exponential equations with fast (~0.4 ms) and slow (>3 ms) time constants, indicating the existence of a fast step in addition to the conventional slow step. The dwell times of the fast steps were almost independent of the load and ATP concentration, while those of the slow backward steps and detachment depended on those. We constructed the kinetic model to explain the fast and slow steps under a wide range of loads.

Reduced precision floating-point optimization for Deep Neural Network On-Device Learning on microcontrollers

Enabling On-Device Learning (ODL) for Ultra-Low-Power Micro-Controller Units (MCUs) is a key step for post-deployment adaptation and fine-tuning of Deep Neural Network (DNN) models in future TinyML applications. This paper tackles this challenge by introducing a novel reduced precision optimization technique for ODL primitives on MCU-class devices, leveraging the State-of-Art advancements in RISC-V RV32 architectures with support for vectorized 16-bit floating-point (FP16) Single-Instruction Multiple-Data (SIMD) operations. Our approach for the Forward and Backward steps of the Back-Propagation training algorithm is composed of specialized shape transform operators and Matrix Multiplication (MM) kernels, accelerated with parallelization and loop unrolling. When evaluated on a single training step of a 2D Convolution layer, the SIMD-optimized FP16 primitives result up to 1.72× faster than the FP32 baseline on a RISC-V-based 8+1-core MCU. An average computing efficiency of 3.11 Multiply and Accumulate operations per clock cycle (MAC/clk) and 0.81 MAC/clk is measured for the end-to-end training tasks of a ResNet8 and a DS-CNN for Image Classification and Keyword Spotting, respectively – requiring 17.1 ms and 6.4 ms on the target platform to compute a training step on a single sample. Overall, our approach results more than two orders of magnitude faster than existing ODL software frameworks for single-core MCUs and outperforms by 1.6× previous FP32 parallel implementations on a Continual Learning setup.

Lightweight and Elegant Data Reduction Strategies for Training Acceleration of Convolutional Neural Networks

Due to industrial demands to handle increasing amounts of training data, lower the cost of computing one model at a time, and lessen the ecological effects of intensive computing resource consumption, the job of speeding the training of deep neural networks becomes exceedingly challenging. Adaptive Online Importance Sampling and IDS are two brand-new methods for accelerating training that are presented in this research. On the one hand, Adaptive Online Importance Sampling accelerates neural network training by lowering the number of forward and backward steps depending on how poorly a model can identify a given data sample. On the other hand, Intellectual Data Selection accelerates training by removing semantic redundancies from the training dataset and subsequently lowering the number of training steps. The study reports average 1.9x training acceleration for ResNet50, ResNet18, MobileNet v2 and YOLO v5 on a variety of datasets: CIFAR-100, CIFAR-10, ImageNet 2012 and MS COCO 2017, where training data are reduced by up to five times. Application of Adaptive Online Importance Sampling to ResNet50 training on ImageNet 2012 results in 2.37 times quicker convergence to 71.7% top-1 accuracy, which is within 5% of the baseline. Total training time for the same number of epochs as the baseline is reduced by 1.82 times, with an accuracy drop of 2.45 p.p. The amount of time required to apply Intellectual Data Selection to ResNet50 training on ImageNet 2012 is decreased by 1.27 times with a corresponding decline in accuracy of 1.12 p.p. Applying both methods to ResNet50 training on ImageNet 2012 results in 2.31 speedup with an accuracy drop of 3.5 p.p.

Tectonics of the Western Internal Jura fold-and-thrust belt: 2D kinematic forward modelling

The balancing technique, called 2D kinematic forward modelling, is a powerful tool to understand the kinematic evolution of fold-and-thrust belts. This study presents a new 2D kinematic forward model for the westernmost Internal Jura fold-and-thrust belt (FTB), situated immediately adjacent to the Geneva Basin. The technique used not only provides a new valid balanced cross-section but also offers new insights regarding the kinematic evolution of the Western Internal Jura FTB. Our model proposes a pure thin-skinned style dominated by forward stepping deformation accompanied by minor back-stepping thrust sequences. A first deformation step is attributed to the thrusting of the Crêt de la Neige Anticline, followed by the Crêt Chalam Thrust and its imbrications. This is followed by thrusting along the Tacon and the Bienne thrusts. Imbricate fault-bend folding explains the steep southern limb of the Crêt de la Neige and the Bellecombe anticlines. 2D kinematic forward modelling yields a total amount of shortening by 23.6 km for the Western Internal Jura FTB. In addition to the primary décollement located at the base of the Keuper Group evaporites, three other décollements are found within the marly layers of the Aalenian “faciès de transition” units, the Oxfordian “Couches d’Effingen-Geissberg” members and the Berriasian Goldberg formation. The multiple thrust horizon approach is supported by new precise seismic interpretations. Our model provides a valid alternative to previous models that either propose local thickening of the Triassic evaporites or inversion of normal faults in the basement. This fully explains the elevated position of the Mesozoic cover in the Jura FTB.

Examining movement asymmetries during three single leg tasks using interlimb and single subject approaches

Purposes: To examine whether healthy individuals displayed asymmetric trunk and lower extremity kinematics in the frontal and sagittal planes using both interlimb and single subject models. MethodsTrunk, pelvis, and lower extremity kinematic waveforms were analyzed bilaterally during the single leg squat (SLS), forward step down (FSD), and lateral step down (LSD). Participants identified task specific preferred and non-preferred legs based on perceived stability for interlimb analyses. Movement patterns were also analyzed with a single subject approach that included Fisher's exact tests to assess whether asymmetries were related to the task. ResultsParticipants were found to have increased pelvic drop on the non-preferred leg during the LSD from 41 to 77% of the movement (p = 0.01). No other bilateral differences were found for interlimb analyses. Single subject analyses indicated that no task had a greater probability of finding or not finding asymmetries. Associations were found between the FSD and SLS for frontal plane hip (p < 0.01) and knee motion (p < 0.01). ConclusionsInterlimb analyses can be influenced by intraparticipant movement variability between preferred and non-preferred legs. Movement asymmetries during single leg weightbearing are likely task dependent and a battery of tests is necessary for assessing bilateral differences.

Myosin waves and a mechanical asymmetry guide the oscillatory migration of Drosophila cardiac progenitors.

Heart development begins with the formation of a tube as cardiac progenitors migrate from opposite sides of the embryo. Abnormal cardiac progenitor movements cause congenital heart defects. However, the mechanisms of cell migration during early heart development remain poorly understood. Using quantitative microscopy, we found that in Drosophila embryos, cardiac progenitors (cardioblasts) migrated through a sequence of forward and backward steps. Cardioblast steps were associated with oscillatory non-muscle myosin II waves that induced periodic shape changes and were necessary for timely heart tube formation. Mathematical modeling predicted that forward cardioblast migration required a stiff boundary at the trailing edge. Consistent with this, we found a supracellular actin cable at the trailing edge of the cardioblasts that limited the amplitude of the backward steps, thus biasing the direction of cell movement. Our results indicate that periodic shape changes coupled with a polarized actin cable produce asymmetrical forces that promote cardioblast migration.

Loads on the Knee Joint Ligaments during Stair Climbing

Background. Stair climbing is often performed by people in daily life and requires considerable energy and muscle effort. This task has been widely described in the literature, but the role of the knee joint ligaments has not been sufficiently investigated. This could be relevant for planning ligament reconstruction surgery, for providing suggestions to subjects with partial ligament injuries, and for identifying compensatory strategies for reducing ligament loads. Methods. A dynamic musculoskeletal model was used to analyse the relationship between ligament loads and muscle forces during stair climbing. Results. The most loaded ligaments were the posterior cruciate ligament and the deep fibres of the medial collateral ligament, particularly during the mid-swing phase, where the knee was maximally flexed and the hamstring muscles contracted. The anterior cruciate ligament was recruited during the stance phase to compensate for the anteriorly-directed force applied to the tibia by the vasti muscles; the collateral ligaments stabilized the knee joint during the swing phase. The tibiofemoral contact force, resulting from all external and internal forces applied to the knee, was in good agreement with data provided in the literature. Conclusions. This study represents a forward step in the knowledge of ligament loads during stair climbing, which could be useful for providing informed recommendations to subjects with ligament injuries.

A multifunctional copper single-atom electrocatalyst aerogel for smart sensing and producing ammonia from nitrate

Despite modern chemistry's success in providing affordable fertilizers for feeding the population and supporting the ammonia industry, ineffective nitrogen management has led to pollution of water resources and air, contributing to climate change. Here, we report a multifunctional copper single-atom electrocatalyst-based aerogel (Cu SAA) that integrates the multiscale structure of coordinated single-atomic sites and 3D channel frameworks. The Cu SAA demonstrates an impressive faradaic efficiency of 87% for NH3 synthesis, as well as remarkable sensing performance with detection limits of 0.15 ppm for NO3- and 1.19 ppm for NH4+. These multifunctional features enable precise control and conversion of nitrate to ammonia in the catalytic process, facilitating accurate regulation of the ammonium and nitrate ratios in fertilizers. We thus designed the Cu SAA into a smart and sustainable fertilizing system (SSFS), a prototype device for on-site automatic recycling of nutrients with precisely controlled nitrate/ammonium concentrations. The SSFS represents a forward step toward sustainable nutrient/waste recycling, thus permitting efficient nitrogen utilization of crops and mitigating pollutant emissions. This contribution exemplifies how electrocatalysis and nanotechnology can be potentially leveraged to enable sustainable agriculture.

Steinbeck’s “The Chrysanthemums”: Elisa Still Hoes the Long Row to Parity

Abstract In the short story “The Chrysanthemums,” John Steinbeck creates in the main character Elisa an everywoman. While Elisa’s desires are never clearly stated, an examination of the psychology and circumstances of American women in the 1930’s still living in the fringes of the Victorian era suggests that women want more independence and adventure than society permits. Steinbeck, always ahead of his times, intimates that the idea of a woman’s being independent and assertive is an important part of being human, yet society at large denies these attributes to too many women, including Elisa. Restoring Roe vs. Wade, long the law of the land, would be an appropriate starting point to assure a woman’s liberty and freedom to choose. Equality in the workplace would be another forward step. Steinbeck’s story opens the door for gender equality by revealing the anguish of a woman who lives her life under the confines of gender role constructs. Thus, the reader may readily see the danger in the oppression of placing a woman in a role that doesn’t fulfill her needs and desires.

A spectrally discretized wide-angle parabolic equation model for simulating acoustic propagation in laterally inhomogeneous oceans.

Sound waves can be used to carry out underwater activities. Rapidly and accurately simulating sound propagation is the basis for underwater detection. The wide-angle parabolic model has a good computational speed and accuracy and is currently the main numerical model for mid- and low-frequency sound propagation. The classical wide-angle parabolic equation model is discretized by the finite difference method and a low-order difference scheme is generally adopted. In this paper, a wide-angle parabolic equation model based on a spectral method is proposed. The depth operators of each layer are discretized via the Chebyshev spectral method and then assembled into a global matrix for the forward step. Lateral inhomogeneity is addressed by updating the global depth matrix while stepping forward. In the proposed spectral algorithm, both soft and hard seabeds can be accurately simulated by imposing boundary conditions, and the perfectly matched layer technique is used to truncate the unbounded acoustic half-space. Several representative numerical experiments prove the accuracy and efficiency of the proposed algorithm. However, the spectral method requires that the thickness of the layers does not change during the forward step. Thus, the current spectral algorithm cannot simulate waveguides with terrain undulation, which is its main limitation.