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The origami principle of folding planar sheets into functional three-dimensional devices promises a future with increased compactness and reconfigurability of biomedical robots. To inspire new origami-based biomedical robots, we highlight two categories of origami patterns that are applicable to build compact actuators, deployable stents, and minimally invasive surgery devices. Due to the requirements in system integration, biocompatibility, and payload capability, the conventional paper-based origamis are converted to physical robots by replacing the zero-thickness facets and zero-width folds with thick panels and flexible hinges, respectively. Therefore, the physical origami-based robots become inhomogeneous, making it more complex and challenging to analyze their mechanics. So far, no such model can analyze the mechanics of any physical origami robot. Herein, we propose a computational model that discretizes the continuous structures into truss and spring elements to fulfill this goal. Based on the model, we simulate the identified origami structures under various boundary conditions to investigate their application in biomedical scenarios. This article is expected to accelerate the design iteration of new functional biomedical origami robots.

Periodic Nonuniform Samplings of order N (PNSN) are interleavings of periodic samplings. For a base period T, simple algorithms can be used to reconstruct functions of spectrum included in an union of N intervals δk of length 1/T. In this paper we study the behavior of these algorithms when applied to any function. We prove that they result in N (or less) foldings on , each of δk holding at most one folding.

Folding a thin sheet material such as paper along curves creates a developable surface composed of ruled surface patches. When using such surfaces in design, designers often repeat a process of folding along curves drawn on a sheet and checking the folded shape. Although several methods for constructing such shapes on a computer have been proposed, it is still difficult to check the folded shapes instantly from the crease patterns. In this paper, we propose a simple method that approximately realizes a simulation of curved folds with a triangular mesh from its crease pattern. The proposed method first approximates curves in a crease pattern with polylines and then generates a triangular mesh. In order to construct the discretized developable surface, the edges in the mesh are rearranged so that they align with the estimated rulings. The proposed method is characterized by its simplicity and is implemented on an existing origami simulator that runs in a web browser.

Knowledge-based statistical potentials have been shown to be rather effective in protein 3-dimensional (3D) structure evaluation and prediction. Recently, several statistical potentials have been developed for RNA 3D structure evaluation, while their performances are either still at low level for the test datasets from structure prediction models or dependent on the “black-box” process through neural networks. In this work, we have developed an all-atom distance-dependent statistical potential based on residue separation for RNA 3D structure evaluation, namely rsRNASP, which is composed of short- and long-ranged potentials distinguished by residue separation. The extensive examinations against available RNA test datasets show that, rsRNASP has apparently higher performance than the existing statistical potentials for the realistic test datasets with large RNAs from structure prediction models including the newly released RNA-Puzzles dataset, and is comparable to the existing top statistical potentials for the test datasets with small RNAs or near-native decoys. Additionally, rsRNASP is also superior to RNA3DCNN, a recently developed scoring function through 3D convolutional neural networks. rsRNASP and the relevant databases are available at website https://github.com/Tan-group/rsRNASP.SIGNIFICANCERNAs play crucial roles in catalyzing biochemical reactions and regulating gene expression, and the biological functions of RNAs are generally coupled to their structures. Complementary to experiments, developing computational models to predict RNA 3D structures can be very helpful for understanding RNA biology functions. For a computational model, a reliable energy function is essentially important either for guiding conformational folding or for structure evaluation. For this purpose, we developed a residue-separation-based distance-dependent statistical potential, named rsRNASP which distinguishes the short- and long-ranged interactions, for RNA 3D structure evaluation. Our rsRNASP were examined against extensive test sets and shows overall superior performance over existing top traditional statistical potentials and a recently developed scoring function through 3D convolutional neural networks, especially for realistic test set from various computational structure prediction models.

Aim: The method of utilization of IoT and other evolving techniques in medical equipment design field is discussed in the present paper. A remotely managed interface equipped in a wheelchair cum bed is embedded for elderly or physically challenged people. With the help of a camera embedded in the proposed solution, a real-time remote monitoring of the patient is achieved using an android application on the concerned person. For achieving the above mentioned purpose, the use of linear actuators has been done. This paper further aims to explore the hidden potentials of the merger of all these fields to benefit the end users. Objectives: Remote monitoring of health of the patient through a cloud-based android application. Automatic adjustment of the wheelchair into bed and vice-versa. Automatic stool passing chamber facility is available under the proposed model. Injuries during transportation of the patient from one chair to another (or chair to bed) have been limited in our designed model. Methods: The basic mechanism of proposed wheelchair has been designed using the computer-aided design software. The basic methodology adopted for development of prototype & subsequent “user review analysis” is displayed. The CAD Model of the wheelchair cum stretcher was designed using the “Solid works solid modelling techniques”. The basic structure has been designed with several modifications when compared to the conventional wheelchair design. The computer made design was then utilized for final fabrication of the prototype. The prototype was tested for endurance, load bearing capacity and customer comfort during various phases of development. The feedbacks of several subjects were recorded for future utilization in improved design & fabrication. Results: The proposed model is of utmost importance as the number of critical patients like accident cases, critical pre and post-surgery cases is increasing day by day. Sometimes these patients need intime medication during transition in ambulance while they are picked up from houses and referred to nearby big hospitals. During transition or in hospital, critical patients can be handled efficiently by a specialist doctor through his/her smart phone applications. It also optimizes the services of specialist doctors as we can find the shortage of specialists in Indian hospitals. In a nutshell, this WheelChair system can be moved anywhere due to its portability. Following are the most highlighted features: 1. Authorized relatives and Doctors can see and interact with the patient remotely at any time on his/her smart phone. 2. Authorized relatives and Doctors can see the Vital Sign of patient like BP, ECG, and Pulse etc. at any time through Smart Phone. 3. Doctor can instruct the caretaker to release the emergency drugs through Infusion Pump. 4. Doctor can plan the exceptions, drug infusion, alarm, etc. 5. System is portable and can easily be shifted to ambulance. All transmissions are wireless, so there is no hassle of wires and connectivity. Conclusion: The presented work is limited to the design and fabrication of a new model of wheelchair, which works as a stretcher and has locomotive capabilities. The key feature of the design is its versatility and adaptability to various working conditions. The feedback obtained from various subjects during the testing of wheelchair shows their confidence and a fair degree of comfort which they felt while using the wheelchair. The easy and user-friendly use of the android application helps to monitor the health of the patient. The smartphone camera helped to achieve this data. The analysis of the data can be done in the cloud-based station. The linear actuator has proved to be the low cost and highly reliable equipment to propel the wheelchair.

The design of hybrid nucleic acid nanomaterials capitalizes on the partitioning of architectural and functional roles between structurally diverse RNA modules and chemically robust DNA components. Selecting optimal combinations of RNA and DNA building blocks is the key to preparing stable polygonal RNA-DNA hybrid nanoshapes. Here, we outline a simple screening strategy by gel electrophoresis under native folding conditions to identify combinations of RNA and DNA modules that self-assemble to robust polygonal hybrid nanoshapes. As a proof of concept, we outline the preparation of RNA-DNA hybrid nanoshapes containing a set of different RNA architectural joints, including internal loop motifs and three-way junction (3WJ) folds. For each hybrid nanoshape, we demonstrate the selection process used to identify optimal DNA modules from a library of DNA connectors. The simple screening strategy outlined here provides a general robust method to identify and prepare RNA-DNA hybrid nanoshapes from diverse libraries of discrete nucleic acid building blocks.

We present new algorithms to classify structural ensembles of macromolecules, based on the recently proposed extended similarity measures. Molecular Dynamics provides a wealth of structural information on systems of biologically interest. As computer power increases we capture larger ensembles and larger conformational transitions between states. Typically, structural clustering provides the statistical mechanics treatment of the system to identify relevant biological states. The key advantage of our approach is that the newly introduced extended similiarity indices reduce the computational complexity of assessing the similarity of a set of structures from O(N2) to O(N). Here we take advantage of this favorable cost to develop several highly efficient techniques, including a linear-scaling algorithm to determine the medoid of a set (which we effectively use to select the most representative structure of a cluster). Moreover, we use our extended similarity indices as a linkage criterion in a novel hierarchical agglomerative clustering algorithm. We apply these new metrics to analyze the ensembles of several systems of biological interest such as folding and binding of macromolecules (peptide,protein,DNA -protein). In particular, we design a new workflow that is capable of identifying the most important conformations contributing to the protein folding process. We show excellent performance in the resulting clusters (surpassing traditional linkage criteria), along with faster performance and an efficient cost-function to identify when to merge clusters.

Curved displays have recently become very popular, with wide applications for both industry and consumers. However, built upon initially flat films, most flexible displays are often incompatible with general nondevelopable surfaces. In this paper, we report a method for producing curved displays of nondevelopable shapes by using a structure-mechanics-inspired functional optimization method to design tessellation patterns that fold into the desired shapes. Representative displays in spherical and saddle shapes are demonstrated. The microfabrication process is employed for manufacturing 2D flexible foldable circuit boards, pick-and-place technology is used for placing illuminant elements onto the boards, and mold guidance is used for folding 2-D sheets into curved 3D display prototypes. The proposed technology is feasible for mass production and advances the application of next-generation curved displays.

The aeroelastic model of a folding wing varies with different configurations, so it actually represents a parameter-varying system. Firstly, a new approach based on interpolation of local models is proposed to generate the linear parameter-varying model of a folding wing. This model is capable of predicting the aeroelastic responses during the slow morphing process and is suitable for subsequent control synthesis. The underlying inconsistencies among local linear time-invariant (LTI) models are solved through the modal matching of structural modes and the special treatment of the rational functions in aerodynamic models. Once the local LTI models are represented in a coherent state-space form, the aeroservoelastic (ASE) model at any operating point can be immediately generated by the matrix interpolation technique. Next, based on the present ASE model, the design of a parameterized controller for suppressing the gust-induced vibration is studied. The receptance method is applied to derive fixed point controllers, and the effective independence method is adopted and modified for optimal sensor placement in variable configurations, which can avoid solving ill-conditioned feedback gains. Numerical simulation demonstrates the effectiveness of the proposed interpolation-based modeling approach, and the parameterized controller exhibits a good gust mitigation effect within a wide parameter-varying range. This paper provides an effective and practical solution for modeling and control of the parameterized aeroelastic system.

Motivation In the last decade, de novo protein structure prediction accuracy for individual proteins has improved significantly by utilising deep learning (DL) methods for harvesting the co-evolution information from large multiple sequence alignments (MSAs). The same approach can, in principle, also be used to extract information about evolutionary-based contacts across protein–protein interfaces. However, most earlier studies have not used the latest DL methods for inter-chain contact distance prediction. This article introduces a fold-and-dock method based on predicted residue-residue distances with trRosetta. Results The method can simultaneously predict the tertiary and quaternary structure of a protein pair, even when the structures of the monomers are not known. The straightforward application of this method to a standard dataset for protein–protein docking yielded limited success. However, using alternative methods for generating MSAs allowed us to dock accurately significantly more proteins. We also introduced a novel scoring function, PconsDock, that accurately separates 98% of correctly and incorrectly folded and docked proteins. The average performance of the method is comparable to the use of traditional, template-based or ab initio shape-complementarity-only docking methods. Moreover, the results of conventional and fold-and-dock approaches are complementary, and thus a combined docking pipeline could increase overall docking success significantly. This methodology contributed to the best model for one of the CASP14 oligomeric targets, H1065. Availability and implementation All scripts for predictions and analysis are available from https://github.com/ElofssonLab/bioinfo-toolbox/ and https://gitlab.com/ElofssonLab/benchmark5/. All models joined alignments, and evaluation results are available from the following figshare repository https://doi.org/10.6084/m9.figshare.14654886.v2. Supplementary information Supplementary data are available at Bioinformatics online.

Most shipyard companies maintain efficiency in all aspects of their business to survive. One of these aspects is ship production costs and their reduction. This study proposes a solution to this problem using an optimization method. A hatch cover composed of plates and stiffeners was selected as a case study. In this study, the mass and material cost of the hatch cover was optimized as an objective function using the Pareto approach with developed optimization methods. Plate thickness t, stiffener shape s, and plate material type m were selected as the design variables in this study along with some constraints. To estimate the optimal plate thickness, an expression of stress equations was developed using an optimization technique. Furthermore, stiffener shape and plate material type selection were optimized using a genetic algorithm (GA). The results show that the optimization method is effective to decrease the mass and material cost of a hatch cover.

Origami, the ancient art of paper folding, has shown its potential as a versatile platform to design various reconfigurable structures. The designs of most origami-inspired architected materials rely on a periodic arrangement of identical unit cells repeated throughout the whole system. It is challenging to alter the arrangement once the design is fixed, which may limit the reconfigurable nature of origami-based structures. Inspired by phase transformations in natural materials, here we study origami tessellations that can transform between homogeneous configurations and highly heterogeneous configurations composed of different phases of origami unit cells. We find that extremely localized and reprogrammable heterogeneity can be achieved in our origami tessellation, which enables the control of mechanical stiffness and in-situ tunable locking behavior. To analyze this high reconfigurability and variable stiffness systematically, we employ Shannon information entropy. Our design and analysis strategy can pave the way for designing new types of transformable mechanical devices. Origami-inspired metamaterials are attractive for their programmable shape-shifting properties but are typically characterized by low structural rigidity. Here, 3D heterogeneous origami structures display highly reconfigurable mechanical properties, including finely controllable and reversible stiffness variation.

In recent years, as a result of advancing VLSI technology, Orthogonal Frequency Division Multiplexing (OFDM) has received a great deal of attention and has been adopted in many new generation wideband data communication systems such as IEEE 802.11a, IEEE 802.16e, HiPerLAN/2, Digital Audio/Video Broadcasting (DAB/DVB), and for 4G Radio mobile communications. This is because of its high bandwidth efficiency as the use of orthogonal waveforms with overlapping spectra. The immunity to multipath fading channel and the capability for parallel signal processing make it a promising candidate for the next generation mobile communication systems. The modulation and demodulation of OFDM based communication systems can be efficiently implemented with an FFT and IFFT, which has made the FFT valuable for those communication systems. The complexity of an OFDM system highly depends upon the computation of Fast Fourier Transform (FFT) algorithm. With the advent of new technology in the fields of VLSI and communication, there is also an ever growing demand for high speed processing and low area design. It is also a well-known fact that the multiplier unit forms an integral part of processor design. Due to this regard, high speed multiplier architectures become the need of the day.

Deacon speculates on the origin of interpretation of signs using autocatalytic origin of life models and Peircean terminology. I explain why interpretation evolved only later as a triadic intervention between symbols and actions. In all organisms the passive one-dimensional genetic informational symbol sequences are converted to active functional proteins or nucleic acids by three-dimensional folding. This symbol grounding is a direct symbol-to-action conversion. It is universal throughout all evolution. Folding is entirely a lawful physical process, leaving neither freedom nor necessity for interpretation. Similarly, the initial converse action-to-symbol conversion of sensory inputs also leaves no freedom for interpretation until after the action-to-symbol conversion.

3D shape completion from single-view scan is an important task for follow-up applications such as recognition and segmentation, but it is challenging due to the critical sparsity and structural incompleteness of single-view point clouds. In this paper, a three-stage generative network (TSGN) is proposed for single-view point cloud completion, which generates fine-grained dense point clouds step by step and effectively overcomes the ubiquitous problem—the imbalance between general and individual characteristics. In the first stage, an encoder–decoder network consumes a partial point cloud and generates a rough sparse point cloud inferring the complete geometric shape. Then, a bi-channel residual network is designed to refine the preliminary result with assistance of the original partial input. A local-based folding network is introduced in the last stage to extract local context information from the revised result and build a dense point cloud with finer-grained details. Experiments on ShapeNet dataset and KITTI dataset validate the effectiveness of TSGN. The results on ShapeNet demonstrate the competitive performance on both CD and EMD.

Strategies for investigating and optimizing the expression and folding of proteins for biotechnological and pharmaceutical purposes are in high demand. Here, we describe a dual-reporter biosensor system that simultaneously assesses in vivo protein translation and protein folding, thereby enabling rapid screening of mutant libraries. We have validated the dual-reporter system on five different proteins and find an excellent correlation between reporter signals and the levels of protein expression and solubility of the proteins. We further demonstrate the applicability of the dual-reporter system as a screening assay for deep mutational scanning experiments. The system enables high throughput selection of protein variants with high expression levels and altered protein stability. Next generation sequencing analysis of the resulting libraries of protein variants show a good correlation between computationally predicted and experimentally determined protein stabilities. We furthermore show that the mutational experimental data obtained using this system may be useful for protein structure calculations., Heterologous expression of recombinant proteins often results in misfolding, aggregation and degradation. Here, we show an in vivo dual-biosensor system that simultaneously assesses protein translation and protein folding, thereby enabling rapid screening of expression strains as well as mutant libraries.

Origami that can form various shapes by setting simple creases on the paper and folding along these creases has a lot of applications from the fields of art to engineering. The inverse problem of origami that determines the distribution of creases based on the desired shape is very complicated. In this paper, we use theoretical kinematics to systematically analyse an inverse folding problem of a toy about how to fold a piece of paper into a disc through a smaller hole without breaking it. The results show that some four-crease and six-crease patterns can achieve the expected function, and they can be easily folded with 1 degree of freedom (DOF). It not only opens up a new way to solve the inverse folding problem but also helps students to understand mechanisms and machine theory.

International audience; The development of ultrafast kinetic methods is one of the factors that allowed the research on protein folding to flourish over the last twenty years. The introduction of new optical triggering techniques enabled to experimentally investigate the protein dynamics at the nanosecond to millisecond timescale, allowing researchers to test theoretical predictions and providing experimental benchmarks for computer simulations. In this work the details of how to perform kinetic experiments by the laserinduced temperature jump technique, using the two most commonly used probing techniques (namely infrared absorption and fluorescence spectroscopy) are given, with a strong emphasis on the practical details.

Flexible light-emitting devices that can transform from two-dimensional to three-dimensional (3D) forms could be of use in the development of next-generation displays. Various approaches for converting two-dimensional structures into 3D architectures have been explored, including origami methods that rely on folding along lines in which a structure has been thinned. But the fabrication of foldable 3D light-emitting devices remains challenging due, in particular, to the lack of a practical method for patterning the folding lines. Here we show that 3D foldable quantum dot light-emitting diodes (QLEDs) can be created using laser patterning and metal etch-stop layers with customized ablation thresholds. The approach allows etching to be limited to selected layers of the multilayered QLEDs, and it can be precisely tuned by using alloy-type etch-stop layers. The approach can be used to create QLED architectures with extremely small bending radii (0.047 mm), and we illustrate its capabilities by fabricating a 3D foldable passive matrix array of QLEDs that can display letters and numbers. Two-dimensional arrays of quantum dot light-emitting diodes can be folded into three-dimensional architectures—including a passive matrix array that can display letters and numbers—by using laser patterning and metal etch-stop layers to create folding lines.

Students’ previous knowledge at a superficial level is reviewed when they solve mathematical problems. This action is imperative to strengthen their knowledge and provide the right information needed to solve the problems. Furthermore, Pirie and Kieren's theory stated that the act of returning to a previous level of understanding is called folding back. Therefore, this descriptive-explorative study examines high school students' levels of knowledge in solving mathematics problems using the folding back method. The sample consists of 33 students classified into male and female groups, each interviewed to determine the results of solving arithmetic problems based on gender. The results showed differences in the level of students' understanding in solving problems. Male students carried out the folding back process at the level of image having, formalizing, and structuring. Their female counterparts conducted it at image-making, property noticing, formalizing, and observing. Subsequently, both participants were able to carry out understanding activities, including explaining information from a mathematical problem, defining the concept, having an overview of a particular topic, identifying similarities and differences, abstracting mathematical concepts, and understanding its ideas in accordance with a given problem. This study suggested that Pirie and Kieren's theory can help teachers detect the features of students’ understanding in solving mathematical problems.

We take an institutional perspective to examine how innovation thrives under conditions of resistance. Specifically, we conceive illicit innovation as a process of successive institutionalization of a new practice in the face of contrary law. In the German federal state of Bavaria, the global movement of craft-beer brewing collides with a regional jurisdiction that prohibits precisely these brewing practices and instead protects the traditional institution of purity-brewing (Reinheitsgebot). Grounded on an embedded qualitative case study of brewers and industry representatives, we build a theory of institutional folding of new norms and practices over established ones. This way, creative brewers have succeeded in legitimizing new practices of naturalness-brewing (Natürlichkeitsgebot). Whereas the legal resistance has stimulated brewers to create an original counter-institution, the illicit innovation has also begun to change the institutional context of the beer industry in Bavaria.

Origami enables the folding of objects into a variety of shapes. This paper presents a swimming robot using the folding and unfolding motion of a tabular origami. A squid‐inspired jet propulsion mechanism is used to design an origami swimming robot. The swimming robot utilizes a pulsed‐jet mechanism through the folding motion of the tubular origami structure, which could deform and undulate to provide propulsion for the swimming robot. The robot is incorporated in a stable body, while both swimming forward and steering are generated by the folding motion of the origami structure and undulating fins. An analytical model to investigate the jet propulsion mechanism to capture the relationship between the motor's speed and the generated thrust is developed. The prototype of the swimming robot is fabricated by 3D printing, and experiments verify the robot's components and assembly system. The results show that the swimming robot could achieve swimming forward by folding origami, which could provide unique advantages over other existing underwater propulsion technologies, including scalability and water treatment capabilities. The origami structure provides a novel and simple propulsion mechanism for the swimming robot here, and the mechanism promotes the development of a new class of independent swimming robots.

Motivation The development of an open-source platform to predict protein 1D features and 3D structure is an important task. In this paper, we report an open-source toolkit for protein 3D structure modeling, named OPUS-X. It contains three modules: OPUS-TASS2, which predicts protein torsion angles, secondary structure and solvent accessibility; OPUS-Contact, which measures the distance and orientation information between different residue pairs; and OPUS-Fold2, which uses the constraints derived from the first two modules to guide folding. Results OPUS-TASS2 is an upgraded version of our previous method OPUS-TASS. OPUS-TASS2 integrates protein global structure information and significantly outperforms OPUS-TASS. OPUS-Contact combines multiple raw co-evolutionary features with protein 1D features predicted by OPUS-TASS2, and delivers better results than the open-source state-of-the-art method trRosetta. OPUS-Fold2 is a complementary version of our previous method OPUS-Fold. OPUS-Fold2 is a gradient-based protein folding framework based on the differentiable energy terms in opposed to OPUS-Fold that is a sampling-based method used to deal with the non-differentiable terms. OPUS-Fold2 exhibits comparable performance to the Rosetta folding protocol in trRosetta when using identical inputs. OPUS-Fold2 is written in Python and TensorFlow2.4, which is user-friendly to any source-code-level modification. Availabilityand implementation The code and pre-trained models of OPUS-X can be downloaded from https://github.com/OPUS-MaLab/opus_x. Supplementary information Supplementary data are available at Bioinformatics online.

In a seminal paper, Stallings introduced folding of morphisms of graphs. One consequence of folding is the representation of finitely-generated subgroups of a finite-rank free group as immersions of finite graphs. Stallings's methods allow one to construct this representation algorithmically, giving effective, algorithmic answers and proofs to classical questions about subgroups of free groups. Recently Dani--Levcovitz used Stallings-like methods to study subgroups of right-angled Coxeter groups, which act geometrically on CAT(0) cube complexes. In this paper we extend their techniques to fundamental groups of non-positively curved cube complexes., 12 pages

A methodology that integrates a folding step into the conventional poly(amic acid)/polyimide film fabrication scheme is developed. It enables fabricating cross-linked polyimide (XCP2) films into a host of complex-shaped objects. Particularly unprecedented is that these origami (3D) objects can be unfolded into a 2D temporary shape under externally applied stress at

The Bighorn uplift, Wyoming, developed in the Rocky Mountain foreland during the 75–55 Ma Laramide orogeny. It is one of many crystalline-cored uplifts that resulted from low-amplitude, large-wavelength folding of Phanerozoic strata and the basement nonconformity (Great Unconformity) across Wyoming and eastward into the High Plains region, where arch-like structures exist in the subsurface. Results of broadband and passive-active seismic studies by the Bighorn EarthScope project illuminated the deeper crustal structure. The seismic data show that there is substantial Moho relief beneath the surface exposure of the basement arch, with a greater Moho depth west of the Bighorn uplift and shallower Moho depth east of the uplift. A comparable amount of Moho relief is observed for the Wind River uplift, west of the Bighorn range, from a Consortium for Continental Reflection Profiling (COCORP) profile and teleseismic receiver function analysis of EarthScope Transportable Array seismic data. The amplitude and spacing of crystalline-cored uplifts, together with geological and geophysical data, are here examined within the framework of a lithospheric folding model. Lithospheric folding is the concept of low-amplitude, large-wavelength (150–600 km) folds affecting the entire lithosphere; these folds develop in response to an end load that induces a buckling instability. The buckling instability focuses initial fold development, with faults developing subsequently as shortening progresses. Scaled physical models and numerical models that undergo layer-parallel shortening induced by end loads determine that the wavelength of major uplifts in the upper crust occurs at approximately one third the wavelength of folds in the upper mantle for strong lithospheres. This distinction arises because surface uplifts occur where there is distinct curvature upon the Moho, and the vergence of surface uplifts can be synthetic or antithetic to the Moho curvature. In the case of the Bighorn uplift, the surface uplift is antithetic to the Moho curvature, which is likely a consequence of structural inheritance and the influence of a preexisting Proterozoic suture upon the surface uplift. The lithospheric folding model accommodates most of the geological observations and geophysical data for the Bighorn uplift. An alternative model, involving a crustal detachment at the orogen scale, is inconsistent with the absence of subhorizontal seismic reflectors that would arise from a throughgoing, low-angle detachment fault and other regional constraints. We conclude that the Bighorn uplift—and possibly other Laramide arch-like structures—is best understood as a product of lithospheric folding associated with a horizontal end load imposed upon the continental margin to the west.

Preview., How the patterns of cortex folding are implemented during embryonic development is poorly understood. In this issue of Neuron, Han et al. (2021) establish that a population of neural progenitor cells co-expressing Neurog2 and Ascl1 are key in this process.

Atomistic molecular dynamics (MD) simulations represent established technique for investigation of RNA structural dynamics. Despite continuous development, contemporary RNA simulations still suffer from suboptimal accuracy of empirical potentials (force fields, ffs) and sampling limitations. Development of efficient enhanced sampling techniques is important for two reasons. First, they allow to overcome the sampling limitations and, second, they can be used to quantify ff imbalances provided they reach a sufficient convergence. Here, we study two RNA tetraloops (TLs), namely the GAGA and UUCG motifs. We perform extensive folding simulations and calculate folding free energies (ΔGfold) with the aim to compare different enhanced sampling techniques and to test several modifications of the nonbonded terms extending the AMBER OL3 RNA ff. We demonstrate that replica exchange solute tempering (REST2) simulations with 12-16 replicas do not show any sign of convergence even when extended to time scale of 120 μs per replica. However, combination of REST2 with well-tempered metadynamics (ST-MetaD) achieves good convergence on a time-scale of 5-10 μs per replica, improving the sampling efficiency by at least two orders of magnitude. Effects of ff modifications on ΔGfold energies were initially explored by the reweighting approach and then validated by new simulations. We tested several manually-prepared variants of gHBfix potential which improve stability of the native state of both TLs by up to ~2 kcal/mol. This is sufficient to conveniently stabilize the folded GAGA TL while the UUCG TL still remains under-stabilized. Appropriate adjustment of van der Waals parameters for C-H…O5’ base-phosphate interaction are also shown to be capable of further stabilizing the native states of both TLs by ~0.6 kcal/mol.

The analysis of protein folding reactions by monitoring the kinetic effects of specifically designed single-point mutations, the so-termed phi-value analysis, has been a favorite technique to experimentally probe the mechanisms of protein folding. The idea behind phi-value analysis is that the effects that mutations have on the folding and unfolding rate constants report on the energetic/structural features of the folding transition state ensemble (TSE), which is the highest point in the free energy surface connecting the native and unfolded states, and thus the rate limiting step that ultimately defines the folding mechanism. For single-domain, two-state folding proteins, the general procedure to perform the phi-value analysis of protein folding is relatively simple to implement in the lab. Once the mutations have been produced and purified, the researcher needs to follow a few specific guidelines to perform the experiments and to analyze the data so produced. In this chapter, a step-by-step description of how to measure and interpret the effects induced by site-directed mutations on the folding and unfolding rate constants of a protein of interest is provided. Some possible solutions to the most typical problems that arise when performing phi-value analysis in the lab are also provided.

Computational coarse-grained models play a fundamental role as a research tool in protein folding, and they are important in bridging theory and experiments. Folding mechanisms are generally discussed using the energy landscape framework, which is well mapped within a class of simplified structure-based models. In this chapter, simplified computer models are discussed with special focus on structure-based ones.

Origami-inspired robots are of particular interest given their potential for rapid and accessible design and fabrication of elegant designs and complex functionalities through cutting and folding of flexible 2D sheets or even strings, i.e.printable manufacturing. Yet, origami robots still require bulky, rigid components or electronics for actuation and control to accomplish tasks with reliability, programmability, ability to output substantial force, and durability, restricting their full potential. Here, we present a printable self-sustained compliant oscillator that generates periodic actuation using only constant electrical power, without discrete components or electronic control hardware. This oscillator is robust (9 out of 10 prototypes worked successfully on the first try), configurable (with tunable periods from 3 s to 12 s), powerful (can overcome hydrodynamic resistance to consistently propel a swimmer at ~1.6 body lengths/min), and long-lasting (~10^3 cycles); it enables driving macroscale devices with prescribed autonomous behaviors, e.g. locomotion and sequencing. This oscillator is also fully functional underwater and in high magnetic fields. Our analytical model characterizes essential parameters of the oscillation period, enabling programmable design of the oscillator. The printable oscillator can be integrated into origami-inspired systems seamlessly and monolithically, allowing rapid design and prototyping; the resulting integrated devices are lightweight, low-cost, compliant, electronic-free, and nonmagnetic, enabling practical applications in extreme areas. We demonstrate the functionalities of the oscillator with: (i) autonomous gliding of a printable swimmer, (ii) LED flashing, and (iii) fluid stirring. This work paves the way for realizing fully printable autonomous robots with a high integration of actuation and control., 23 pages, 5 figures. This manuscript has been accepted for publication in Soft Robotics. Supplementary texts, movies, and figures are not uploaded

Datasets representing the conformational landscapes of protein structures are high dimensional and hence present computational challenges. Efficient and effective dimensionality reduction of these datasets is therefore paramount to our ability to analyze the conformational landscapes of proteins and extract important information regarding protein folding, conformational changes and binding. Representing the structures with fewer attributes that capture the most variance of the data, makes for quicker and precise analysis of these structures. In this work we make use of dimensionality reduction methods for reducing the number of instances and for feature reduction. The reduced dataset that is obtained is then subjected to topological and quantitative analysis. In this step we perform hierarchical clustering to obtain different sets of conformation clusters that may correspond to intermediate structures. The structures represented by these conformations are then analyzed by studying their high dimension topological properties to identify truly distinct conformations and holes in the conformational space that may represent high energy barriers. Our results show that the clusters closely follow known experimental results about intermediate structures, as well as binding and folding events.

Optical tweezers is a single-molecule technique that allows probing of intra- and intermolecular interactions that govern complex biological processes involving molecular motors, protein–nucleic acid interactions and protein/RNA folding. Recent developments in instrumentation eased and accelerated optical tweezers data acquisition, but analysis of the data remains challenging. Here, to enable high-throughput data analysis, we developed an automated python-based analysis pipeline called POTATO (Practical Optical Tweezers Analysis TOol). POTATO automatically processes the high-frequency raw data generated by force-ramp experiments and identifies (un)folding events using predefined parameters. After segmentation of the force-distance trajectories at the identified (un)folding events, sections of the curve can be fitted independently to worm-like chain and freely-jointed chain models, and the work applied on the molecule can be calculated by numerical integration. Furthermore, the tool allows plotting of constant force data and fitting of the Gaussian distance distribution over time. All these features are wrapped in a user-friendly graphical interface (https://github.com/REMI-HIRI/POTATO), which allows researchers without programming knowledge to perform sophisticated data analysis.SIGNIFICANCEStudying (un)folding of biopolymer structures with optical tweezers under different conditions generates very large datasets for statistical data analysis. Recent technical improvements accelerated data acquisition by coupling modern instruments with microfluidic systems, at the same time creating the need for a high-throughput, and unbiased data analysis. We developed Practical Optical Tweezers Analysis TOol (POTATO); an open-source python-based tool that can process data gathered by any OT force-ramp experiment in an automated fashion. POTATO is principally designed for data preprocessing, identification of (un)folding events and the fitting of the force-distance curves. In addition, all parameters for preprocessing, statistical analysis and fitting of the curves can be adapted to suit the dataset under analysis in an easy-to-use graphical user interface.

High-throughput methods in science have created a trend to generate massive amount of data that challenge our ability to mine and search through massive information spaces. Thus more efficient and effective solutions for data analysis and optimization are required continuously. The best solutions for many problems-solving approaches in science could have many sources of inspiration coming from diverse natural phenomena. In this context, most Artificial Intelligence (AI) approaches benefit from emulation natural processes for their information processing strategy. Among the AI protocols, meta-heuristic algorithms for learning model and optimization have exploited a number of biological phenomena leading to highly effective search and learning engines. Examples of these processes are the ant colony organization, brain function and genetics among others. The evolution has turned all these biological events in highly efficient procedures, whose basics principles have then provided an excellent ground of new computational algorithms The aim of this report is pave the way to a new class of nature-based meta-heuristic methods which shall be based on diverse chemical and biomolecular systems. We present five examples from different subjects of Chemistry like Organic Chemistry, Chemical Physics and Biomolecules; and introduce how computational models could be inferred from them. Besides, we develop one of these models, in detail, which is based on protein evolution and folding principles. We consider that the wealth of systems and processes related to Chemistry, as those described in the present communication, might boost the development of relevant meta-heuristic and classification algorithms in upcoming years.

The total number of amino acid sequences that can fold to a target protein structure, known as “designability”, is a fundamental property of proteins that contributes to their structure and function robustness. The highly designable structures always have higher thermodynamic stability, mutational stability, fast folding, regular secondary structures, and tertiary symmetries. Although it has been studied on lattice models for very short chains by exhaustive enumeration, it remains a challenge to estimate the designable quantitatively for real proteins. In this study, we designed a new deep neural network model that samples protein sequences given a backbone structure using sequential Monte Carlo method. The sampled sequences with proper weights were used to estimate the designability of several real proteins. The designed sequences were also tested using the latest AlphaFold2 and RoseTTAFold to confirm their foldabilities. We report this as the first study to estimate the designability of real proteins.

Nowadays, origami folding in combination with actuation mechanisms can offer deployable structure design, yield compliance, and have several properties of soft material. An easy complex folding pattern can yield an array of functionalities in actuated hinges or active spring elements. This paper presents various cylinder origami robot designs that can be untethered magnetically actuated. The different designs are analyzed and compared to achieve the following three types of motion: Peristaltic, rolling, and turning in different environments, namely, board, sandpaper, and sand. The proposed origami robot is able translate 53 mm in peristaltic motion within 20 s and is able to roll one complete cycle in 1 s and can turn ≈ 180∘ in 1.5 s. The robot also demonstrated a peristaltic locomotion at a speed of ≈2.5 mm s−1, ≈1.9 mm s−1, and ≈1.3 mm s−1 in board, sandpaper, and sand respectively, rolling motion at a speed of 1 cycle s−1, ≈0.66 cycles s−1, and ≈0.33 cycles s−1 in board, sandpaper, and sand respectively, and turning motion of ≈180∘, ≈83∘, and ≈58∘ in board, sandpaper, and sand respectively. The evaluation of the robotic motion and actuation is discussed in detail in this paper.

Folding fans are complex artifacts that include a variety of materials that have been processed and assembled to produce very small supports and decorations. Unfortunately, due to their fragility, as well as the lack of suitable non-invasive and non-destructive analytical techniques, the constituent materials and stratigraphies of historic folding fans have been rarely studied so far. This work aimed to develop and demonstrate a suitable analytical methodology for characterizing a French fan and to establish manufacturing techniques employed in its production. To this goal, advanced non-destructive and micro-destructive photonic techniques were employed to gather compositional and processing information with a non-invasive approach. This artifact provided the opportunity to evaluate the potential of different techniques: Portable Raman spectroscopy (with excitation at 785 nm) was used for identifying the pigments of the painted leaves and the gemstones; particle-induced X-ray emission (PIXE) and Rutherford backscattering spectrometry (RBS) were employed to quantify metal alloy compositions and stratigraphy of the decorations; portable laser-induced breakdown spectroscopy (LIBS) allowed the measurement of elemental depth profiles of metal decorations which were congruent with those provided by PIXE. Finally, additional stratigraphic information on metal decorations, in terms of gold distribution and state of conservation, was achieved through selective laser ablation.

Trapped ion mobility mass spectrometry is proving to be a disruptive technology in LCMS based proteomics. One primary drawback of this hardware is the lack of compatibility with the hundreds of data processing pipelines historically in use. This study describes a simple data conversion tool that “folds” the TIMSTOF ion mobility data into the MS2 fragmentation spectra allowing simple downstream processing. Little to no detriment in the assignment of peptide spectral matches is observed when “folding” the 1/k0 value into the low mass region. To demonstrate one utility of TIMS Folding, spectral libraries are provided in multiple common formats that were constructed from the same files both with and without folded ion mobility data. When new data is acquired and folded using the same parameters prior to data processing the folded ion mobility data can be used as an additional metric for peptide match confidence against folded spectral libraries.

The growing need for wearable devices, fitness accessories and biomedical equipment has led to the upsurge in research and development of thin flexible battery research and development. The current state of art wearable electronics products being developed in several fields require installation of power sources in different configurations and at times require the battery to undergo mechanical folding during product operation. This requires the product batteries to robustly withstand the imposed mechanical stresses during use along with the other desirable characteristics attributed to the power source such as high C-rate capability, high capacity and low capacity degradation rate. Works that explore the effects of static and dynamic folding on li-ion power sources is limited and oftentimes doesn’t adhere to definite test protocols resulting in non-standardized experimental data that can’t be applied to real-life product scenarios. Specifically, the effect of fold diameter on the battery state of health degradation when subjected to both static and dynamic folding is not yet completely explored. Present study aims to address this gap in the literature by investigating the effect of varying the fold diameter is both static (U-flex-to-install) and dynamic (dynamic U-fold) tests. Four different values of fold diameters have been chosen for experimentation and to study its effect during the aforementioned tests. Multiple samples have been tested for a given test condition so as to generate high fidelity data. Ultimately, a regression model developed previously has been augmented with the results generated in the current study.

The growing interest in the flexible field of electronics has provided impetus to incorporation of electronic components such as resistors, capacitors, LEDs, sensors, etc. into flexible circuits. Power sources are another significant component of a majority of electronic circuits which need to be integrated in flexible circuits so as to push the bounds of the wearable technology. One way to do this is by using a laminated film to laminate ultra-thin pouch batteries and then bind them to a flexible substrate. During the lamination process, these batteries are exposed to higher temperatures (above 100 °C), albeit for a short period of time, which can result in damage to the battery’s internals. In this study, a Li-ion pouch cell has been laminated using a hot roller lamination process with different conditions of lamination speed and temperature. The laminated batteries have then been subjected to accelerated life testing in presence and absence of static and dynamic mechanical folding so as to investigate the effect of folding on the laminated batteries. Further, the SOH degradation of the tested batteries is computed and has been incorporated in a regression model so as to study the effect of lamination parameters.

In recent years, fluorogenic RNA aptamers, such as Spinach, Broccoli, Corn, Mango, Coral, and Pepper have gathered traction as an efficient alternative labeling strategy for background-free imaging of cellular RNAs. However, their application has been somewhat limited by relatively inefficient folding and fluorescent stability. With the recent advent of novel RNA-Mango variants which are improved in both fluorescence intensity and folding stability in tandem arrays, it is now possible to image RNAs with single-molecule sensitivity. Here we discuss the protocol for imaging Mango II tagged RNAs in both fixed and live cells.