Experimental Information Research Articles

Smooth trends in fermium charge radii and the impact of shell effects.

The quantum-mechanical nuclear-shell structure determines the stability and limits of the existence of the heaviest nuclides with large proton numbers Z ≳ 100 (refs. 1-3). Shell effects also affect the sizes and shapes of atomic nuclei, as shown by laser spectroscopy studies in lighter nuclides4. However, experimental information on the charge radii and the nuclear moments of the heavy actinide elements, which link the heaviest naturally abundant nuclides with artificially produced superheavy elements, is sparse5. Here we present laser spectroscopy measurements along the fermium (Z = 100) isotopic chain and an extension of data in the nobelium isotopic chain (Z = 102) across a key region. Multiple production schemes and different advanced techniques were applied to determine the isotope shifts in atomic transitions, from which changes in the nuclear mean-square charge radii were extracted. A range of nuclear models based on energy density functionals reproduce well the observed smooth evolution of the nuclear size. Both the remarkable consistency of model prediction and the similarity of predictions for different isotopes suggest a transition to a regime in which shell effects have a diminished effect on the size compared with lighter nuclei.

Natural Products with Potential for the Treatment of Pain: Global Evidence from the NAPRALERT Database.

Natural products (NPs) continue to inform the discovery and development of a diversity of drugs, both marketed and investigational. Pain, one of the most common of human experiences and profound challenges in medicine and biology, has emerged at the core of an urgent societal problem, in the United States and globally. The present study employs a retrospective analysis of an extensive set of published literature curated in the NAPRALERT database to identify NPs with experimental evidence of bioactivity supporting the selection and prioritization of NP leads with promise in pain management. The NAPRALERT pain data set currently documents >38,000 pain-relevant experiments reported in >1,750 distinct journals. The evidence presented here was annotated from >10,000 distinct scientific publications identifying NP extracts and isolates with experimental biological data indicating positive mitigation of pain, inflammation, and/or modulation of nociceptive signaling targets. Correlation of ethnomedical uses with experimental data represents a value-added approach to the selection and prioritization of leads. Dissemination of this unique NP/pain data set, with experimental data and information applicable to basic, translational, and clinical science stakeholders alike, furnishes practical evidence in support of a rational selection of NPs for directed pain research. A large portion of the NAPRALERT pain-relevant data set, along with a set of query tools designed to assist user-directed selection and prioritization of leads, are presented as Supporting Information in order to mitigate the limitations inherent in presenting such a large data set in (print) format. To support user efforts, this report involves explication of NAPRALERT data organization and the articulation of rational approaches to user-guided selection of evidence-based NP leads.

Investigating immersion and migration decisions for agent-based modelling: Acautionary tale.

Agent-based modelling provides an appealing methodological choice for simulating human behaviour and decisions. The currently dominant approaches based on static transition rates or unverified assumptions are restrictive, and could be enhanced with insights from cognitive experiments on actual decision making. Here, one common concern is that standard surveys or experiments may lack ecological validity, limiting the extent to which research findings can be generalised to real-life settings. For complex, highly emotive decision-making scenarios, such as those related to irregular migration, the typically used short, methodical survey questions may not appropriately map onto complex real-world decisions of interest. Immersive contexts may offer more accurate representations of reality, potentially enhancing the usefulness of experimental information in multi-disciplinary modelling endeavours. This preregistered study, aimed directly at examining the effect of immersion on risk-taking in the context of migration decisions, and indirectly at informing a multi-disciplinary construction of an agent-based model of migration, presents a choice-based interactive fiction game in which players make migration decisions to advance through a story. (N = 1000 Prolific users) took part in one of four experimental conditions, three involving different renditions of the game attempting to create immersion, with the last condition presenting the decisions in standard survey format. Although addressing the lack of ecological validity in survey data is important for improving agent-based modelling methodology, the experimental design used to tackle this issue, while responding directly to modelling needs, proved too complex. The created experimental conditions ended up too distinct from each other, involving stimuli that differed in quantity and content. This introduced several unintended and uncontrolled confounds, making it impossible to meaningfully interpret the results of this experiment on its own. Our results act as a cautionary tale for agent-based modellers, highlighting that the modelling needs should not override the principles of experimental design, and provide motivation for more rigorous research on this topic.

Minimal Information for Studies of Extracellular Vesicles (MISEV): Ten-Year Evolution (2014–2023)

In the tenth year since the first edition of MISEV was released in 2014, MISEV2023 has been reported in 2024 with the aim of refining the standard and improving the rigor, reproducibility, and transparency of extracellular vesicle (EV) research to clarify the requirements for experimental design of EVs, emphasize the importance of reproducible experimental results as well as encouraging openness of experimental information. The release of MISEV has significantly contributed to the quality of research in the field of EVs, which creates a more reliable research environment. However, despite the important role of MISEV, there is still a need for the EV researchers to continue to push for the widespread implementation of the guidelines to meet the evolving nature and challenges of EV research. The evolution of EV research and the attention it receives have grown exponentially over time, as has the number of people involved in the writing of MISEV. Here, this review briefly summarizes the evolution of the three editions of MISEV, aiming to recall MISEV2014 and MISEV2018 while learning about the latest release, MISEV2023, to gain a deeper understanding of the content, and to provide a quick note for beginners who want to learn about MISEV and explore the EV world.

Study on the polymerization shrinkage and mechanical-physical properties of dental resin composite modified by polyurethane dimechacrylate and glass flake fillers: Short title: Aging resistance for dental resin composites with low shrinkage

ObjectivesWe intend to explore the polymerization shrinkage and mechanical-physical properties of the dental resin composite modified by polyurethane oligomer PU-MA and glass flakes fillers, and provide some experimental information for developing new dental materials. MethodsBased on Bis-GMA/TEGDMA, the new dental resin composite was hand fabricated by combining PU-MA with different content (65 wt% ∼ 75 wt%) of glass flakes/Si-Al-borosilicate glass mixed fillers. The kinetics of polymerization shrinkage was investigated by using an experimental set-up based on laser triangulation. The mechanical-physical properties of specimens after 60 days water immersion and 5000 times thermo-cycles were measured by three-point bending test and micro vickers hardness tester. Data were submitted to one-way ANOVA/LSD-test (α = 0.05). Independent sample T test was used to analyze the data before and after aging. Two-way ANOVA was adopted to analyze the effect of composition and aging condition on the mechanical-physical properties (α = 0.05). ResultsPU-PG-75% performs lower volume shrinkage (1.35 %). As the increase of filler content, the water sorption and solubility increased and the depth of cure decreased significantly (P < 0.05). After aging, the flexural strength, elasticity modulus and vickers hardness of commercial products dropped obviously and PU-PG-75wt% was relatively stable. Conclusions20 wt% PU-MA could decrease the volume shrinkage of dental resin composite effectively. 60 days water immersion and 5000 times thermal cycles simultaneously resulted in a significant reduction in the flexural properties for experimental materials. PU-PG-75% may have the potential to be taken as a low shrinkage dental resin composite with good mechanical properties. Clinical SignificanceThis new synthesized composite could perform low polymerization shrinkage and better mechanical resistance, which may provide a new idea for improving the lifespan of direct restoration.

Mapping lineage-traced cells across time points with moslin

Simultaneous profiling of single-cell gene expression and lineage history holds enormous potential for studying cellular decision-making. Recent computational approaches combine both modalities into cellular trajectories; however, they cannot make use of all available lineage information in destructive time-series experiments. Here, we present moslin, a Gromov-Wasserstein-based model to couple cellular profiles across time points based on lineage and gene expression information. We validate our approach in simulations and demonstrate on Caenorhabditis elegans embryonic development how moslin predicts fate probabilities and putative decision driver genes. Finally, we use moslin to delineate lineage relationships among transiently activated fibroblast states during zebrafish heart regeneration.

SMCVdb: a database of experimental cellular toxicity information for drug candidate molecules.

Many drug discovery exercises fail because small molecules that are effective inhibitors of target proteins exhibit high cellular toxicity. Early and effective assessment of toxicity and pharmacokinetics is essential to accelerate the drug discovery process. Conventional methods for toxicity profiling, including in vitro and in vivo assays, are laborious and resource-intensive. In response, we introduce the Small Molecule Cell Viability Database (SMCVdb), a comprehensive resource containing toxicity data for over 24 000 compounds obtained through high-content imaging (HCI). SMCVdb seamlessly integrates chemical descriptions and molecular weight data, offering researchers a holistic platform for toxicity data aiding compound prioritization and selection based on biological and economic considerations. Data collection for SMCVdb involved a systematic approach combining HCI toxicity profiling with chemical information and quality control measures ensured data accuracy and consistency. The user-friendly web interface of SMCVdb provides multiple search and filter options, allowing users to query the database based on compound name, molecular weight range, or viability percentage. SMCVdb empowers users to access toxicity profiles, molecular weights, compound names, and chemical descriptions, facilitating the exploration of relationships between compound properties and their effects on cell viability. In summary, the database provides experimentally derived cellular toxicity information for over 24 000 drug candidate molecules to academic researchers, and pharmaceutical companies. The SMCVdb will keep growing and will prove to be a pivotal resource to expedite research in drug discovery and compound evaluation. Database URL: http://smcvdb.rcb.ac.in:4321/.

Translational Dynamics of Cations and Anions in Ionic Liquids from NMR Field Cycling Relaxometry: Highlighting the Importance of Heteronuclear Contributions.

NMR field cycling relaxometry is a powerful method for determining the rotational and translational dynamics of ions, molecules, and dissolved particles. This is in particular true for ionic liquids (ILs) in which both ions carry NMR sensitive nuclei. In the IL triethylammonium bis(trifluoromethanesulfonyl)imide ([TEA][NTf2]), there are 1H nuclei at the [TEA]+ cations and 19F nuclei at the [NTf2]- anions. Moreover, the high viscosity of this IL leads to frequency-dependent relaxation rates, leaving the so-called extreme narrowing regime. Both the rotational and the translational dynamics of the constituents of ILs can be obtained by separating the contributions of intra- and intermolecular relaxation rates. In particular, the translational dynamics can be obtained separately by applying the so-called "low-frequency approach" (LFA), utilizing the fact that the change in the total relaxation rates at low frequencies results solely from translational motions. However, for systems containing multiple NMR active nuclei, heteronuclear interactions can also affect their relaxation rates. For [TEA][NTf2], the intermolecular relaxation rate is either the sum of 1H-1H cation-cation and 1H-19F cation-anion interactions or the sum of 19F-19F anion-anion and 19F-1H anion-cation interactions. Due to the lack of available experimental information, the 1H-19F heteronuclear intermolecular contribution has often been neglected in the past, assuming it to be negligible. Employing a suitable set of ILs and by making use of isotopic H/D substitution, we show that the 1H-19F heteronuclear intermolecular contribution in fact cannot be neglected and that the LFA cannot be applied to the total 1H and total 19F relaxation rates.

Graphene Coating and its Effect on Performance of Box Type Solar Cooker: An Experimental Investigation

Background: Solar cookers have been the subject of several theoretical and empirical investigations, with numerous modifications attempted to increase efficiency and security. Solar cookers need much sophisticated research and enhancement work to function better. A thorough grasp of the application of graphene in box-type solar cooking systems is crucial for both solar energy and graphene. Objective: To improve the performance of box-type solar cookers, this patent research aims to offer an experimental investigation and insightful information on of applying graphene coating to the absorber plate and its derivative. Materials and Methods: To ensure equal dispersion of graphene into the black paint, three samples containing (1, 3, and 5wt%) of graphene embedded with the paint were produced with 1mm, 3mm, and 5mm thickness of the coating and stirred at 400 rpm for two hours using a magnetic stirrer. Xray diffraction and scanning electron microscopy have been studied to comprehend the influence of graphene nanoparticles on the surface morphology of the coated absorber panel. Performance evaluations of the box-type solar cookers were conducted with and without a graphene coating on the absorber plate, and data has been recorded for each case. Results: The results of patent research show that the absorber plate with (1, 3, and 5wt.%) of graphene embedded with black paint 1mm, 3mm, and 5mm thickness coating has a maximum thermal efficiency of 41.48% with 97.08 W cooking power, 46% with 109.35 W cooking power, and 49% with 114.77 W cooking power for the average solar irradiation is 978 W/m2. Discussion: It was determined that the cooking power (P), the first figure of merit (F1), and the second figure of merit (F2) were all satisfactorily achieved. Embedding black paint into graphene coating has been shown to significantly influence the heat transmission and thermal performance enhancement of box-type solar cookers, as demonstrated by the findings of X-ray diffraction and Scanning Electron Microscopy analysis. Conclusion: The current research makes it abundantly evident that the incorporation of graphene into the absorber plate of a box-type solar cooker, together with the application of a black paint coating, leads to increased heat transfer rates, which in turn provides an increase in cooking power. Because of this, graphene is an attractive nanomaterial that has the potential to improve the performance of box-type solar cookers, which is the novelty of this research work.

Unmasking AlphaFold to integrate experiments and predictions in multimeric complexes.

Since the release of AlphaFold, researchers have actively refined its predictions and attempted to integrate it into existing pipelines for determining protein structures. These efforts have introduced a number of functionalities and optimisations at the latest Critical Assessment of protein Structure Prediction edition (CASP15), resulting in a marked improvement in the prediction of multimeric protein structures. However, AlphaFold's capability of predicting large protein complexes is still limited and integrating experimental data in the prediction pipeline is not straightforward. In this study, we introduce AF_unmasked to overcome these limitations. Our results demonstrate that AF_unmasked can integrate experimental information to build larger or hard to predict protein assemblies with high confidence. The resulting predictions can help interpret and augment experimental data. This approach generates high quality (DockQ score > 0.8) structures even when little to no evolutionary information is available and imperfect experimental structures are used as a starting point. AF_unmasked is developed and optimised to fill incomplete experimental structures (structural inpainting), which may provide insights into protein dynamics. In summary, AF_unmasked provides an easy-to-use method that efficiently integrates experiments to predict large protein complexes more confidently.

Combined LC-MS/MS feature grouping, statistical prioritization, and interactive networking in msFeaST.

Computational metabolomics workflows have revolutionized the untargeted metabolomics field. However, the organization and prioritization of metabolite features remains a laborious process. Organizing metabolomics data is often done through mass fragmentation-based spectral similarity grouping, resulting in feature sets that also represent an intuitive and scientifically meaningful first stage of analysis in untargeted metabolomics. Exploiting such feature sets, feature-set testing has emerged as an approach that is widely used in genomics and targeted metabolomics pathway enrichment analyses. It allows for formally combining groupings with statistical testing into more meaningful pathway enrichment conclusions. Here, we present msFeaST (mass spectral Feature Set Testing), a feature-set testing and visualization workflow for LC-MS/MS untargeted metabolomics data. Feature-set testing involves statistically assessing differential abundance patterns for groups of features across experimental conditions. We developed msFeaST to make use of spectral similarity-based feature groupings generated using k-medoids clustering, where the resulting clusters serve as a proxy for grouping structurally similar features with potential biosynthesis pathway relationships. Spectral clustering done in this way allows for feature group-wise statistical testing using the globaltest package, which provides high power to detect small concordant effects via joint modeling and reduced multiplicity adjustment penalties. Hence, msFeaST provides interactive integration of the semi-quantitative experimental information with mass-spectral structural similarity information, enhancing the prioritization of features and feature sets during exploratory data analysis. The msFeaST workflow is freely available through https://github.com/kevinmildau/msFeaST and built to work on MacOS and Linux systems.

Enhanced path tracking control of hydraulic support pushing mechanism via adaptive sliding mode technique in coal mine backfill operations

The hydraulic support pushing mechanism is the primary equipment utilized in coal mine backfill operations, playing a crucial role in enhancing filling efficiency, ensuring a stable filling body, and managing gob safety. This paper focuses on analyzing the dynamic model and the interrelationship of the hydraulic cylinder, which serves as the power source for the pushing mechanism. To address the intricate coupling effects arising from the hydraulic cylinders and the displacement-force induced by the shared pump, this study employs feedforward compensation for decoupling analysis. Additionally, this article introduces an adaptive sliding mode approach law and an adaptive synovial controller to combat issues such as buffeting and interference. The simulation results demonstrate that the sliding mode reaching law proposed in this paper can achieve a stable state in approximately 3 seconds, which is significantly better than other methods. Combining the experimental equipment information from a mining area in Hebei Province with Amesim-Simulink simulation results, it is evident that the adaptive sliding mode controller exhibits an error range between approximately 1.33E-4 and 1.5E-4 during the stable phase. This performance surpasses traditional PI and fuzzy PID controllers in terms of path tracking ability, effectively enabling precise control of the filling support pushing mechanism.

Mechanism of Nucleic Acid Phosphodiester Bond Cleavage by Human Endonuclease V: MD and QM/MM Calculations Reveal a Versatile Metal Dependence.

Human endonuclease V (EndoV) catalytically removes deaminated nucleobases by cleaving the phosphodiester bond as part of RNA metabolism. Despite being implicated in several diseases (cancers, cardiovascular diseases, and neurological disorders) and potentially being a useful tool in biotechnology, details of the human EndoV catalytic pathway remain unclear due to limited experimental information beyond a crystal structure of the apoenzyme and select mutational data. Since a mechanistic understanding is critical for further deciphering the central roles and expanding applications of human EndoV in medicine and biotechnology, molecular dynamics (MD) simulations and quantum mechanics/molecular mechanics (QM/MM) calculations were used to unveil the atomistic details of the catalytic pathway. Due to controversies surrounding the number of metals required for nuclease activity, enzyme-substrate models with different numbers of active site metals and various metal-substrate binding configurations were built based on structural data for other nucleases. Subsequent MD simulations revealed the structure and stability of the human EndoV-substrate complex for a range of active site metal binding architectures. Four unique pathways were then characterized using QM/MM that vary in metal number (one versus two) and modes of substrate coordination [direct versus indirect (water-mediated)], with several mechanisms being fully consistent with experimental structural, kinetic, and mutational data for related nucleases, including members of the EndoV family. Beyond uncovering key roles for several active site amino acids (D240 and K155), our calculations highlight that while one metal is essential for human EndoV activity, the enzyme can benefit from using two metals due to the presence of two suitable metal binding sites. By directly comparing one- versus two-metal-mediated P-O bond cleavage reactions within the confines of the same active site, our work brings a fresh perspective to the "number of metals" controversy.

ChatMol: interactive molecular discovery with natural language.

Natural language is poised to become a key medium for human-machine interactions in the era of large language models. In the field of biochemistry, tasks such as property prediction and molecule mining are critically important yet technically challenging. Bridging molecular expressions in natural language and chemical language can significantly enhance the interpretability and ease of these tasks. Moreover, it can integrate chemical knowledge from various sources, leading to a deeper understanding of molecules. Recognizing these advantages, we introduce the concept of conversational molecular design, a novel task that utilizes natural language to describe and edit target molecules. To better accomplish this task, we develop ChatMol, a knowledgeable and versatile generative pretrained model. This model is enhanced by incorporating experimental property information, molecular spatial knowledge, and the associations between natural and chemical languages. Several typical solutions including large language models (e.g. ChatGPT) are evaluated, proving the challenge of conversational molecular design and the effectiveness of our knowledge enhancement approach. Case observations and analysis offer insights and directions for further exploration of natural-language interaction in molecular discovery. Codes and data are provided in https://github.com/Ellenzzn/ChatMol/tree/main.

Structural and biochemical characterization of the C-terminal region of the human RTEL1 helicase.

RTEL1 is an essential DNA helicase which plays an important role in various aspects of genome stability, from telomere metabolism to DNA replication, repair and recombination. RTEL1 has been implicated in a number of genetic diseases and cancer development, including glioma, breast, lung and gastrointestinal tumors. RTEL1 is a FeS helicase but, in addition to the helicase core, it comprises a long C-terminal region which includes a number of folded domains connected by intrinsically disordered loops and mediates RTEL1 interaction with factors involved in pivotal cellular pathways. However, information on the architecture and the function of this region is still limited. We expressed and purified a variety of fragments encompassing the folded domains and the unstructured regions. We determined the crystal structure of the second repeat, confirming that it has a fold similar to the harmonin homology domains. SAXS data provide low-resolution information on all the fragments and suggest that the presence of the RING domain affects the overall architecture of the C-terminal region, making the structure significantly more compact. NMR data provide experimental information on the interaction between PCNA and the RTEL1 C-terminal region, revealing a putative low-affinity additional site of interaction. A biochemical analysis shows that the C-terminal region, in addition to a preference for telomeric RNA and DNA G-quadruplexes, has a high affinity for R-loops and D-loops, consistent with the role played by the RTEL1 helicase in homologous recombination, telomere maintenance and preventing replication-transcription conflicts. We further dissected the contribution of each domain in binding different substrates.

Investigation on the failure of the space HgCdTe detector with long-term storage tests

The HgCdTe detector is the core device of the infrared imaging system, its reliability directly restricts the performance of the whole imaging system. For some special applications, it maintains in a non-operating storage state for a long time, it is significant to study its storage reliability. Due to the long lifetime of detectors, most studies have been conducted with accelerated life tests, there is a lack of experimental information concerning the failure of these detectors after longtime storage. In this article, the performance degradation of Hg1-xCdxTe detector with the 127 months long-term storage test is studied. The failure mode and failure mechanism of detectors are investigated through the statistics analysis and optical photomicrography. The results indicate that there are three failure modes, such as low-temperature opening circuit, chip circuit opening, and signal reduction accompanied by increased noise. The main type of failure is in the mode of signal reduction accompanied by increased noise, which is a typical failure mode for long-term storage of HgCdTe detectors. In this typical failure mode, corrosion products are observed near the photosensitive surface in the failure detector, which prove to be a metal product of indium. The long-term storage results can provide data support for accelerating storage test and improve the HgCdTe detectors design.

Secondary structure propensities of the Ebola delta peptide E40 in solution and model membrane environments

The Ebola delta peptide is an amphipathic, 40-residue peptide encoded by the Ebola virus, referred to as E40. The membrane-permeabilising activity of the E40 delta peptide has been demonstrated in cells and lipid vesicles suggesting the E40 delta peptide likely acts as a viroporin. The lytic activity of the peptide increases in the presence of anionic lipids and a disulphide bond in the C-terminal part of the peptide. Previous in silico work predicts the peptide to show a partially helical structure, but there is no experimental information on the structure of E40. Here, we use circular dichroism spectroscopy to report the secondary structure propensities of the reduced and oxidised forms of the E40 peptide in water, detergent micelles, and lipid vesicles composed of neutral and anionic lipids (POPC and POPG, respectively). Results indicate that the peptide is predominately a random coil in solution, and the disulphide bond has a small but measurable effect on peptide conformation. Secondary structure analysis shows large uncertainties and dependence on the reference data set and, in our system, cannot be used to accurately determine the secondary structure motifs of the peptide in membrane environments. Nevertheless, the spectra can be used to assess the relative changes in secondary structure propensities of the peptide depending on the solvent environment and disulphide bond. In POPC-POPG vesicles, the peptide transitions from a random coil towards a more structured conformation, which is even more pronounced in negatively charged SDS micelles. In vesicles, the effect depends on the peptide-lipid ratio, likely resulting from vesicle surface saturation. Further experiments with zwitterionic POPC vesicles and DPC micelles show that both curvature and negatively charged lipids can induce a change in conformation, with the two effects being cumulative. Electrostatic screening from Na+ ions reduced this effect. The oxidised form of the peptide shows a slightly lower propensity for secondary structure and retains a more random coil conformation even in the presence of PG-PC vesicles.

Thermochemical and kinetic study of the recombination and dissociation reactions R + Br (+M) ⇄ RBr (+M) (R = CH3, CH2Cl, CHCl2, CHClBr, CH2Br and CHBr2)

The kinetics of the recombination and thermal dissociation reactions R + Br (+M) ⇄ RBr (+M) with R = CH3, CH2Cl, CHCl2, CHClBr, CH2Br and CHBr2 were theoretically studied over wide temperature and pressure ranges employing unimolecular reaction rate theory combined with potential energy surfaces derived at the ab initio G4//B3LYP/6-311++G(3df,3pd) level. The resulting rate constants are in good agreement with the available experimental information. Rate constant values for the reactions of CH2Cl, CHCl2, CHClBr, CH2Br and CHBr2 radicals with Br atoms are for a first time reported. Standard enthalpies of formation for the above and related molecules have been calculated.

Relevant information in TDD experiment reporting

Relevant information in TDD experiment reporting

Construction of a Digital Twin of a Grain Dryer Using Statistical Identification Methods

The authors present the results of constructing the digital twin of a grain dryer by statistical identification methods using experimental information and simulation of the functioning processes of a roundabout dryer. The accuracy of the results of the simulation was determined based on the convergence of the correlation functions of the experimental and simulated processes. The statistical characteristics of the simulated process of drying grain crops are very close to the estimates of the drying process obtained in the course of experimental studies, their normalized correlation functions are identical and can serve as a basis for developing a digital twin of the dryer.