Subsequent Process Research Articles

Pedestrian trajectory prediction method based on automatic driving

Pedestrian trajectory prediction plays a crucial role in autonomous driving, as its accuracy directly affects the autonomous driving system’s comprehension of the environment and subsequent decision-making processes. Current trajectory prediction methods tend to oversimplify pedestrians to mere point coordinates, utilizing positional information to infer interactions among individuals while overlooking the temporal correlations between them, thereby excessively simplifying pedestrian characteristics. To address the aforementioned issues, this paper proposes a trajectory prediction model for autonomous driving applications, that takes into account both pedestrian motion characteristics and scene interaction. The model optimizes the LSTM unit structure twice, serving to learn correlations among long trajectories of pedestrians and to integrate multiple forms of information into the neighborhood interaction module. Furthermore, our model introduces dual attention mechanisms for individuals and scenes, focusing on the key motion points of individual pedestrians and their interactive behavior with others in busy scenarios. The efficacy of the model was validated on the MOT16 pedestrian dataset and the Daimler pedestrian path prediction dataset, outperforming mainstream methods with 8% and 10% reductions in Average Displacement Error and Final Displacement Error respectively.

Programs of study and earnings dynamics

University programs differ in the subsequent earnings processes of their enrollees, including many features that students might care about to differing degrees such as the level of average earnings, earnings growth, and volatility. Do the earnings features of a university program’s enrollees reflect the causal effect of enrolling in that program or the self-selection of students into that program? Would students experience a different earnings process if they enrolled in a different program of study? To estimate the causal impact of enrolling in a program of study on the enrollees’ future earnings process, we exploit a discontinuity built into the Danish national university admissions system, which provides quasi-random assignment of similar applicants to different programs. We leverage the rich cross-program variation in the enrollees’ future earnings processes to measure the impact of entering a program whose enrollees experience high earnings levels, growth, and volatility on their own subsequent earnings level, growth, and volatility. We find that a student’s subsequent earnings levels and volatility – but not their earnings growth – are caused by entering programs of study whose enrollees have those features.

High-Throughput Single-Cell, Single-Mitochondrial DNA Assay Using Hydrogel Droplet Microfluidics.

There is growing interest in understanding the biological implications of single cell heterogeneity and heteroplasmy of mitochondrial DNA (mtDNA), but current methodologies for single-cell mtDNA analysis limit the scale of analysis to small cell populations. Although droplet microfluidics have increased the throughput of single-cell genomic, RNA, and protein analysis, their application to sub-cellular organelle analysis has remained a largely unsolved challenge. Here, we introduce an agarose-based droplet microfluidic approach for single-cell, single-mtDNA analysis, which allows simultaneous processing of hundreds of individual mtDNA molecules within >10,000 individual cells. Our microfluidic chip encapsulates individual cells in agarose beads, designed to have a sufficiently dense hydrogel network to retain mtDNA after lysis and provide a robust scaffold for subsequent multi-step processing and analysis. To mitigate the impact of the high viscosity of agarose required for mtDNA retention on the throughput of microfluidics, we developed a parallelized device, successfully achieving ~95 % mtDNA retention from single cells within our microbeads at >700,000 drops/minute. To demonstrate utility, we analyzed specific regions of the single-mtDNA using a multiplexed rolling circle amplification (RCA) assay. We demonstrated compatibility with both microscopy, for digital counting of individual RCA products, and flow cytometry for higher throughput analysis.

Physico-Mechanical Properties of Pumpkin Seeds in the Context of Drying Processes

The paper highlights the significance of the drying process in post-harvest cucurbit seed treatment technology. To improve the effectiveness of drying high-moisture seeds, a plant construction design was introduced, incorporating the concept of providing varied heat distribution to a vigorously agitated seed layer. The paper validates the necessity of refining the dimensional, frictional, and aerodynamic properties of pumpkin seeds to determine the optimal operating modes for the proposed dryer. (Research purpose) To identify the physical and mechanical properties of pumpkin seeds by defining their dimensional, frictional and aerodynamic characteristics. (Materials and methods) The study employs one-factor experimental research methods with subsequent statistical data processing. An experimental study was conducted on the physical and mechanical properties of Volzhskaya Grey pumpkin seeds possessing a standard moisture content ranging between 9.3 and 9.7 percent. Well-known laboratory apparatuses, namely the «conical tank» and the «inclined plane», were used to determine the natural repose angle and to enhance the accuracy of friction coefficients determination. For analyzing the aerodynamic properties of the seeds, the K-293 Petkus air separator was employed. (Results and discussion) Research methods were developed and experimental plants were described. It was established that with a probability confidence level of 0.95, the static friction coefficients of pumpkin seeds on a solid steel sheet, a perforated steel sieve and on rubber are 0.473, 0.418, 0.481, respectively, and the dynamic friction coefficients under the identical conditions are measured as 0.331, 0.293, 0.337. The average angle of natural repose is found to be 22 degrees, the midsection area is 97.94 square millimeters, the soaring velocity is 7.083 meters per second, the windage coefficient stands at 0.196 and the aerodynamic drag coefficient is 0.136. (Conclusions). The assumption that enhancing the drying efficiency of vegetable seeds can be achieved by implementing a diverse thermal energy supply to continuously moving mass inside the apparatus is confirmed, provided that the seeds do not stick together in layers resulting in blockage of the coolant flow. An improved design of the dryer configurations has been developed and, to validate its optimum design and technological specifications, an in-depth analysis of the seeds' dimensional, frictional, and aerodynamic attributes has been conducted.

Tacheometric Survey and 3D-Model Building of Fortification Objects in the South of Western Siberia

Purpose. The most objective planigraphy of the earthen fortifications is one of the initial conditions for the reliability of the description of these objects and the subsequent analysis of their defensive capabilities. One of the most common devices for the instrumental surveys in modern archaeological research is a total station. The purpose of the tacheometric survey was to build 3D-models of the earthern fortifications of various types (cape settlements – Chultukov Log-9, ostrogs and redoubts (Umrevinsky, Salt Turn). The work at these objects included two stages – an instrumental survey of the monument and subsequent processing of the survey results with the 3D-models buildings and objects indication.Results. The tacheometric survey was carried out in various landscape zones (the Altai mountains, the northern forest-steppe of the Upper Ob, the steppe zone of the Middle Irtysh) within the river valleys of the Katun, Ob and Irtysh. The wide chronological framework of the sites (the Chultukov Log-9 settlement, the Umrevinsky ostrog, the Salt Turn redoubt) corresponds to the period from the beginning of the 1st millennium AD up to the first quarter of the 18th century and provide an opportunity for the most objective assessment of the tacheometric survey results.Conclusions. The result of the work was the building of the 3D-models of various earthen fortification objects (hillforts, ostrogs, redoubts). Both previously untraceable defensive structures (ditch), and the characteristics of the fenced areas of these structures, previously recorded in written sources, have been identified.

Quantifying predictive uncertainty in damage classification for nondestructive evaluation using Bayesian approximation and deep learning

Magnetic flux leakage (MFL), a widely used nondestructive evaluation (NDE) method, for inspecting pipelines to prevent potential long-term failures. However, during field testing, uncertainties can affect the accuracy of the inspection and the decision-making process regarding damage conditions. Therefore, it is essential to identify and quantify these uncertainties to ensure the reliability of the inspection. This study focuses on the uncertainties that arise during the inverse NDE process due to the dynamic magnetization process, which is affected by the relative motion of the MFL sensor and the material being tested. Specifically, the study investigates the uncertainties caused by sensing liftoff, which can affect the output signal of the sensing system. Due to the complexity of describing the forward uncertainty propagation process, this study compared two typical machine learning (ML)-based approximate Bayesian inference methods, convolutional neural network and deep ensemble, to address the input uncertainty from the MFL response data. Besides, an autoencoder method is applied to tackle the lack of experimental data for the training model by augmenting the dataset, which is constructed with the pre-trained model based on transfer learning. Prior knowledge learned from large simulated MFL signals can fine-tune the autoencoder model which enhances the subsequent learning process on experimental MFL data with faster generalization. The augmented data from the fine-tuned autoencoder is further applied for ML-based defect size classification. This study conducted prediction accuracy and uncertainty analysis with calibration, which can evaluate the prediction performance and reveal the relation between the liftoff uncertainty and prediction accuracy. Further, to strengthen the trustworthiness of the prediction results, the decision-making process guided by uncertainty is applied to provide valuable insights into the reliability of the final prediction results. Overall, the proposed framework for uncertainty quantification offers valuable insights into the assessment of reliability in MFL-based decision-making and inverse problems.

Simulation study on effect of flame cutting speed on temperature field and residual stress distribution

Due to the advantages of flame cutting in thick plate cutting and cutting cost, it is widely used in the metal cutting process of shipbuilding and machinery manufacturing. But at the same time, the local heating of flame cutting will cause residual stress inside the steel plate. Residual stress is an important reason for deformation and cracking of components. The change of temperature field is the premise of affecting the distribution of residual stress. Cutting speed has an important effect on the distribution of temperature field and residual stress field. In this paper, ABAQUS is used to create a finite element model for flat flame cutting of Q345D low-alloy steel. Based on the working principle of flame cutting, the model of flame cutting composite heat source is established and the subprogram of composite heat source is written. The thermal-mechanical direct coupling method is used to simulate and analyze the effect of different cutting speeds on the temperature and residual stress field distribution of the flat flame cutting process, to provide a reference for the subsequent processing.

Light-Driven Three-Component Carbonylation of Aryl Halides Using Abundant Metal Carbonyl.

Carbonyl compounds are widely found in various pharmaceutical intermediates and synthetic precursors. Herein we report a simple light-driven three-component aryl halide process for synthesizing a variety of carbonylation products, utilizing Co2(CO)8 as an abundant solid carbonyl source, in good to excellent yields. The products can easily be subjected to further functionalization in synthesis. Mechanism studies indicated that this reaction is enabled by aryl radical generation and the subsequent CO insertion, alkene insertion, and protonation process.

Space-time dependent non-local thermal transport effects on laser ablation dynamics in inertial confinement fusion

In inertial confinement fusion (ICF), electron thermal transport plays a key role in laser ablation and the subsequent implosion processes, which always exhibits intractable non-local effects. Simple modifications of the local Spitzer–Härm model with either an artificially-assumed constant flux limiter or a purely time-dependent one are applied to explain some experimental data, but fail to simultaneously reproduce the space-time evolution of the whole laser ablation process. Here, by carrying out a series of one-dimensional and two-dimensional radiation hydrodynamic simulations where the space-time-dependent non-local thermal transport model proposed by Schurt, Nicolaï and Busquet (the SNB model) are self-consistently included, we systematically study the non-local effects on the whole laser ablation dynamics including those occurring at the critical surface, the conduction zone and the ablation front. Different from those obtained previously, our results show that due to the non-local heat flow redistribution and redirection, at the critical surface the thermal flux is more inhibited, in the conduction zone the lateral thermal transport is suppressed, and ahead of the ablation front the plasma is preheated. When combined together they eventually result in significant improvement of the laser absorption efficiency, extension of the conduction zone, increase of both the mass ablation rate and shock velocity. Furthermore, the dependence of these laser ablation dynamics on different drive laser intensities is investigated, which provides beneficial enlightenments on potential laser pulse shaping and/or ignition scheme optimization in ICF.

Cascade Electrochemical Aerobic Oxygenation of 2-Substituted Indoles and Electrochemical [5 + 3] Annulation with Amidines: Access to Eight-Membered Benzo[1,3,5]triazocin-6(5H)-ones.

The cascade electrochemical C3-selective aerobic oxygenation of 2-substituted indoles and electrochemical [5 + 3] annulation with amidines through an undivided cell galvanostatic method employing molecular oxygen and "electricity" as green oxidants was developed. This protocol provides an efficient and direct approach to eight-membered benzo[1,3,5]triazocin-6(5H)-ones. Mechanistic studies suggested that two subsequent electrochemical processes both proceeded through radical pathways.

Tuning Surface Potential Polarization to Enhance N2 Affinity for Ammonia Electrosynthesis.

Electrocatalytic N2 reduction reaction (NRR) to synthesize ammonia is a sustainable reaction that is expected to replace Haber Bosch process. Laminated Bi2WO6 has great potential as an NRR electrocatalyst, however, the effective activity requires that the inert substrate is fully activated. Here, for the first time, success is achieved in activating the Bi2WO6 basal planes with NRR activity through Ti doping. The introduction of Ti successfully tunes the surface potential distribution and enhances the N2 adsorption. The subsequently strong hybrid coupling of d(Ti)-p(N) orbitals fills the electronic state of N2 antibonding molecular orbital, which greatly weakens the bonding strength of N≡N bonds. Further, in situ synchrotron radiation-based Fourier transform infrared(SR-FTIR) spectrum and theoretical calculations show that surface potential polarization enhances the adsorption of HNN* by Bi-Ti dual-metal sites, which is beneficial for the subsequent activation hydrogenation process. The Ti-Bi2WO6 nanosheets achieve 11.44% Faradaic efficiency (-0.2V vs. RHE), a NH3 yield rate of 23.14µgmg-1h-1 (15N calibration), and satisfactory stability in 0.1M HCl environment. The mutual assistance of theory and experiment can help understand and develop of excellent two-dimensional (2D) materials for the NRR.

Automated Monitoring System for Suspended Photocatalytic Batch Reactions Based on Online Circulatory Spectrophotometry.

Employing an automated monitoring system (AMS) for data acquisition offers benefits, such as reducing the workload, in the kinetic study of suspended photocatalytic batch reactions. However, the current methods in this field tend to narrowly focus on the substrate and often overlook the optical characteristics of both the mixture and solid particles. To address this limitation, in this study, we propose a novel AMS based on online circulatory spectrophotometry (OCS) and incorporate debubbling, aeration, and segmented flow (DAS), named DAS-OCS-AMS. Initially, a debubbler is introduced to mitigate the issue of signal noise caused by bubbles (SNB). Subsequently, an aerated and segmented device is developed to address the issue of particle deposition on the inner wall of the pipeline (PDP) and on the windows of the flow cell (PDW). The proposed DAS-OCS-AMS is applied to monitor the kinetics of the photocatalytic degradation of Acid Orange Ⅱ by TiO2 (P25), and its results are compared with those obtained using the traditional OCS-AMS. The comparative analysis indicates that the proposed DAS-OCS-AMS effectively mitigates the influence of SNB, PDP, and PDW, yielding precise results both for the mixture and solid particles. The DAS-OCS-AMS provides a highly flexible universal framework for online circulatory automated monitoring and a robust hardware foundation for subsequent data processing research.

In Situ-Generated Hollow CoFe-LDH/Co-MOF Heterostructure Nanorod Arrays for Oxygen Evolution Reaction.

Assembling a heterostructure is an effective strategy for enhancing the electrocatalytic activity of hybrid materials. Herein, CoFe-layered double hydroxide and Co-metal-organic framework (CoFe-LDH/Co-MOF) hollow heterostructure nanorod arrays are synthesized. First, [Co(DIPL)(H3BTC)(H2O)2]n [named as Co-MOF, DIPL = 2,6-di(pyrid-4-yl)-4-phenylpyridine, H3BTC = 1,3,5-benzenetricarboxylic acid] crystalline materials with a uniform hollow structure were prepared on the nickel foam. The CoFe-LDH/Co-MOF composite perfectly inherits the original hollow nanorod array morphology after the subsequent electrodeposition process. Optimized CoFe-LDH/Co-MOF hollow heterostructure nanorod arrays display excellent performance in oxygen evolution reaction (OER) with ultralow overpotentials of 215 mV to deliver current densities of 10 mA cm-2 and maintain the electrocatalytic activity for a duration as long as 220 h, ranking it one of the non-noble metal-based electrocatalysts for OER. Density functional theory calculations validate the reduction in free energy for the rate-determining step by the synergistic effect of Co-MOF and CoFe-LDH, with the increased charge density and noticeable electron transfer at the Co-O site, which highlights the capability of Co-MOF to finely adjust the electronic structure and facilitate the creation of active sites. This work establishes an experimental and theoretical basis for promoting efficient water splitting through the design of heterostructures in catalysts.

Fixation-related potentials during mobile map assisted navigation in the real world: The effect of landmark visualization style.

An often-proposed enhancement for mobile maps to aid assisted navigation is the presentation of landmark information, yet understanding of the manner in which they should be displayed is limited. In this study, we investigated whether the visualization of landmarks as 3D map symbols with either an abstract or realistic style influenced the subsequent processing of those landmarks during route navigation. We utilized a real-world mobile electroencephalography approach to this question by combining several tools developed to overcome the challenges typically encountered in real-world neuroscience research. We coregistered eye-movement and EEG recordings from 45 participants as they navigated through a real-world environment using a mobile map. Analyses of fixation event-related potentials revealed that the amplitude of the parietal P200 component was enhanced when participants fixated landmarks in the real world that were visualized on the mobile map in a realistic style, and that frontal P200 latencies were prolonged for landmarks depicted in either a realistic or abstract style compared with features of the environment that were not presented on the map, but only for the male participants. In contrast, we did not observe any significant effects of landmark visualization style on visual P1-N1 peaks or the parietal late positive component. Overall, the findings indicate that the cognitive matching process between landmarks seen in the environment and those previously seen on a map is facilitated by more realistic map display, while low-level perceptual processing of landmarks and recall of associated information are unaffected by map visualization style.

Influence of initial electric arc root position on electric arc behavior with spark plugs in large lean burn spark ignited gas engines

Increasing efficiency while reducing emissions leads to high mean effective pressures, high compression ratios and increasingly lean operation for spark ignited large gas engines. Despite these boundary conditions, gas engines must be operated between knocking and misfiring at low cycle-to-cycle fluctuations. The excess air ratio and the ignition process of the lean mixture greatly influence the stability of the combustion process. To enable sufficiently low cycle-to-cycle fluctuation of the combustion process despite the ever increasing excess air ratio levels, it is necessary to understand and investigate the sub-areas of the engine process, for example, ignition, flow condition and mixture formation. This paper focuses on one sub-area of conventional spark ignition, the influence of the electric arc root position on the origin and stretching of the electric arc, because electric arc behavior is considered important in the subsequent combustion process. The results show that electric arc roots on the downstream end of the electrodes tend to enable a longer electric arc length at the first electric arc short circuit (i.e. the first abrupt shortening of the electric arc during its spark duration) than electric arcs with electric arc roots on the upstream ends of the electrodes.

Three-dimensional spiral model of the wicking effect for continuous polyester filaments

The wicking effect constitutes a pivotal determinant in facilitating the ingress and transference of liquid water within yarns and fabrics. Its significance looms prominently in the context of subsequent product processing, particularly concerning the immersion and interface bonding of textile matrix composites. The twist exerts profound influence over the fiber disposition and density within yarns, as well as the yarn and the wicking pathways for liquid water. We use a mathematical model grounded in the three-dimensional helical capillary permeation mechanism, inherently linked to the twist factor. This model operates under the assumption that the yarn's fibers exhibit uniform diameters and arrangements. Leveraging the macroscopic force equilibrium method, a function of liquid capillary rise with wicking time was deduced. and the dynamic progression of liquid water ascent within the yarn was simulated using the COMSOL platform. Subsequently, a series of wicking experiments were executed on polyester filament yarns, each characterized by varying twist levels. The results revealed that the experimental data coincided well with the theoretical prediction, thus affirming the model's accuracy.

Engineering Phase Separation in Niobate Glass through Ab Initio Molecular Dynamics for Enhanced Energy Storage Performance and Unprecedented Thermal Stability in Niobate-Based Glass Ceramics.

The advancement of lead-free glass ceramics (GCs) possessing appropriate energy storage characteristics is crucial for the renewable energy and electronics industry. In this study, we synthesized lead-free GCs predominantly composed of the tungsten bronze phase, Ba3.3Nb10O28.3. Ab initio molecular dynamics initially reveal nonuniform distribution within the Ba/Nb-O regions in niobite glassy melts, offering valuable insights for the subsequent crystallization process. The proposal of a B-site engineering strategy is suggested, which entails the concurrent reduction of grain size and augmentation of the band gap in tungsten bronze GCs doped with Ta. This approach results in a substantial enhancement of the dielectric breakdown strength (BDS). Phase-field simulations have indicated that the refinement of grain sizes plays a pivotal role in augmenting the local electric field distribution and breakdown path, thereby contributing to the enhancement of BDS. As a consequence of these modifications, a notably high recoverable energy density (Wrec) of 5.23 J/cm3 can be achieved, accompanied by an ultrahigh efficiency (η) of 94%, and superior thermal stability in energy storage. These outcomes are particularly evident in the case of 2 mol % Ta2O5-doped P2O5-K2O-BaO-Bi2O3-TeO2-Nb2O5 (PKBBTN-T) GCs, where the Wrec and η can be determined to be 2.87 ± 3% J/cm3 and 95.46 ± 4%, respectively, over a temperature range spanning from 20 to 150 °C. Additionally, this specimen exhibits an exceptionally high discharge energy density (Wdis) of 4.01 J/cm3. This comprehensive investigation, comprising experimental and theoretical analyses, establishes an effective pathway and paradigm for the development of dielectric materials with ultrahigh energy storage properties.

The effect of carbohydrate intake on sleep quality and exercise performance

Carbohydrates are essential nutrients within the context of our daily dietary intake, serving a crucial function in the provision of energy for human metabolism, as well as exerting a significant influence on athletic performance and the subsequent process of recuperation. Carbohydrates, being a primary source of energy for the human body, hold significant significance in our daily existence. Carbohydrates serve multiple functions, including the reduction of body protein consumption, possession of detoxifying qualities, and potential contribution to an extended lifespan through acceptable ingestion. The appropriate consumption of carbohydrates significantly influences the overall health and quality of life of those without any specific health conditions. The dietary intake of an athlete plays a pivotal role in determining their performance on the field. Carbohydrates provide a primary energy source within the dietary regimen of athletes, playing a pivotal role in fueling explosive power, endurance, and other critical determinants of athletic success. The significance of carbs in relation to sleep should not be overlooked. The objective of this paper is to investigate the influence of carbohydrate consumption on both exercise performance and sleep quality. Additionally, this study will undertake a more extensive examination and analysis by include both athletes and individuals from the general population.

A Clutter Removal Method Based on the F-K Domain for Ground-Penetrating Radar in Complex Scenarios

Ground-penetrating radar (GPR) is a classic geophysical exploration method that utilizes the emission and reception of electromagnetic waves to non-destructively detect target objects in the target medium. It has been widely applied in various fields such as pipeline detection, cavity detection, and rebar detection. However, GPR systems are susceptible to environmental clutter interference, which poses challenges for data interpretation and subsequent processing. In this paper, the separability of clutter and target signal in the frequency-wavenumber (F-K) domain is validated through modeling, leading to the proposal of a comprehensive clutter removal method based on the F-K domain for complex scenarios. The direct coupling wave is initially eliminated by applying a peak matching mean subtraction filter, which avoids the artifacts. Subsequently, the F-K domain transformation is performed and surface clutter undulations are effectively removed using a method based on singular value decomposition and k-means clustering. Finally, an angle filter with Gaussian tapering at the edges is designed based on physical models to efficiently eliminate linear interference without undesired ringing interference. The commonly used clutter removal algorithms, including mean subtraction (MS), singular value decomposition (SVD), robust principal component analysis (RPCA), and traditional F-K filtering methods, are compared with the proposed algorithm on both the numerical simulated data and actual GPR data. The results from visual and quantitative analysis confirm that our proposed method is more effective than current commonly used clutter suppression algorithms. We have successfully enhanced the Signal-to-Clutter Ratio (SCR) of the GPR data, resulting in an Improvement Factor (IF) of 30.63 dB, 23.59 dB, and 30.60 dB for simulated data, experimental data, and TU1208 public data, respectively. The detection capability of buried targets is enhanced, thereby establishing a solid foundation for subsequent data interpretation and target identification.

Development of Cellulose Air Filters for Capturing Fine and Ultrafine Particles through the Valorization of Banana Cultivation Biomass Waste

Outdoor and indoor atmospheric pollution is one of the major problems that humanity continues to face. As a mitigation pathway, numerous technologies have been developed for air purification, including the use of fibrous filters. In this study, the particle capture efficiencies and pressure drops of air filters manufactured with cellulose pulp extracted from banana pseudostems were studied across three particle size ranges (PM10, PM2.5, and PM1). Two pretreatments were applied, alkaline with soda-antraquinone (alkali-treated pulp) and a subsequent bleaching process (bleached pulp), and four manufacturing processes were tested: crushing, freeze-drying, vacuum filtration, and pressing. In addition, a study varying filter grammage (70, 100, and 160 g·m−2) and pressing pressures (2, 4, 6, and 8 t) was also performed. After conducting these particle tests, the filter manufactured with bleached pulp, having a grammage of 160 g·m−2 and pressed at 4 t, was deemed the optimal individual solution. It demonstrated high particle retention efficiencies across all particle size ranges (with values exceeding 80%), a moderate pressure drop below 1000 Pa, and high thermal stability (degradation above 220 °C). However, combining freeze-drying and two-ton pressing processes yielded improved results (83% for the smallest particles and 89% for others) with approximately half the pressure drop. Based on these results, this study stands as a noteworthy contribution to waste valorization and the advancement of environmentally friendly materials for particle air filters. This is achieved through the adoption of simple and cost-effective technology, coupled with the utilization of 100% natural agricultural waste as the primary manufacturing material.