Simple Structure Research Articles

Predicting Small Molecule Binding Nucleotides in RNA Structures Using RNA Surface Topography.

RNA small molecule interactions play a crucial role in drug discovery and inhibitor design. Identifying RNA small molecule binding nucleotides is essential and requires methods that exhibit a high predictive ability to facilitate drug discovery and inhibitor design. Existing methods can predict the binding nucleotides of simple RNA structures, but it is hard to predict binding nucleotides in complex RNA structures with junctions. To address this limitation, we developed a new deep learning model based on spatial correlation, ZHmolReSTasite, which can accurately predict binding nucleotides of small and large RNA with junctions. We utilize RNA surface topography to consider the spatial correlation, characterizing nucleotides from sequence and tertiary structures to learn a high-level representation. Our method outperforms existing methods for benchmark test sets composed of simple RNA structures, achieving precision values of 72.9% on TE18 and 76.7% on RB9 test sets. For a challenging test set composed of RNA structures with junctions, our method outperforms the second best method by 11.6% in precision. Moreover, ZHmolReSTasite demonstrates robustness regarding the predicted RNA structures. In summary, ZHmolReSTasite successfully incorporates spatial correlation, outperforms previous methods on small and large RNA structures using RNA surface topography, and can provide valuable insights into RNA small molecule prediction and accelerate RNA inhibitor design.

Relationship between the induced voltage of a rotor bar and the rotation characteristics of a high-temperature superconducting induction motor

Although high-temperature superconducting induction motors have a simple structure, they are distinguished by their high efficiency and high power density. However, an accurate theoretical model that defines the primary electrical characteristics controlling the motor has not been established because of the nonlinear characteristics of high-temperature superconducting squirrel-cage rotor winding. As part of establishing such a model, an experiment was conducted to analyze the relationship between the induced voltage of the rotor bar in a high-temperature superconducting squirrel-cage rotor winding and stator-side quantities (voltage and transport current), as well as its rotation characteristics. A subject was a 1.5 kW class induction motor using Bi–Sr–Ca–Cu–O high-temperature superconducting rotor bars and the experiment was performed at a temperature and a frequency of 77 K and 60 Hz, respectively. The induced voltages of the rotor bars were measured by applying a rotating magnetic field and exhibited a distorted waveform characterized by a third-order harmonic in a magnetic flux flow state. Despite the distorted voltage waveform of the rotor bar, the stator transport current responsible for driving the induction motor remained unaffected and the motor initiated rotation in a slip rotation mode. From the above results, it was experimentally clarified that a stator voltage exceeding the critical current of the rotor bar must be applied when starting the induction motor. It was also shown that the rotor bar can be regarded as a constant resistance for a constant effective value of the stator current when transitioning the motor into a slip rotation state.

Adaptations in Vocational Guidance: Experience from the Colombian Amazon

As we move into late postmodernity, the instruments and processes proposed require research and development processes that allow them to remain in force within current technological mediations and trends. In this context, the instruments that facilitate vocational guidance processes are included. Therefore, this innovation experience arises as a response to the needs present in the Colombian context, based on two objectives: To reduce the number of items in the CHASIDE vocational orientation test, 2) To validate the resulting test. A longitudinal study with a quantitative approach was carried out, with a convenience sampling in three Colombian municipalities during 2019-2023. Quantitative statistical analysis techniques, data were analyzed including statistics of mean, variance, Pearson's correlation coefficient, hypothetical difference of means, degrees of freedom, t-statistic, P(t) and critical value of t (one tail and two tails), and others. Additionally, internal consistency was checked using Cronbach's Alpha. Managing to reduce the test from 98 items to 35 items, preserving its two dimensions (Aptitudes and Interests), with a simpler structure, which responds to a Multifactorial Profile (PM), its validation confirmed the new structure, that established 7 factors for the dimension of aptitudes, constituted by 27 items and 3 factors for the Interests dimension with 8 items. In conclusion, social changes are reflected in factor structures and their groupings within professions, leaving the unifactorial proposed by Holland in the RIASEC, to give way to interactions within aptitudes and interests. Aptitudes being more stable than interests over time.

Two-dimensional distribution experiment of “lattice diffraction” using ultrasound in an educational laboratory

Abstract A device that can study the two-dimensional distribution of ultrasonic diffraction on lattice structures has been developed for educational laboratory, enabling students to design the size, shape and dimension of diffraction obstacles independently. In the experiment, metal balls were used to simulate atomic lattice structures, and the two-dimensional diffraction distribution data of simple cubic, body-centered cubic, and hexagonal close-packed structure were collected. The results were compared with the sound field simulation of COMSOL, and good consistency was found. By observing the diffraction results of complex structures, students can gain a better understanding of the concept of diffraction.

An enhanced electromagnetic energy harvester based on dual ratchet structure with secondary energy recovery

Abstract With the continuous advancement of ultra-low-power electronic devices, capturing energy from the surrounding environment to power these smart devices has emerged as a new direction. However, most of the mechanical energy available for harvesting in the environment exhibits ultra-low frequencies. Therefore, the feasibility of self-powering low-power devices largely depends on the effective utilization of this ultra-low-frequency mechanical energy. Consequently, this work proposes an enhanced electromagnetic energy harvester based on a dual ratchet structure with secondary energy recovery. It converts ultra-low frequency vibrations into fast rotational movements by means of a rack and pinion mechanism, thus achieving high power output while maintaining a simple structure. Experimental tests demonstrate that the proposed harvester exhibits excellent power output under ultra-low-frequency external excitation. Under external excitation with a frequency of 1.5 Hz and an amplitude of 22 mm, with the optimal load matched at 20 Ω, the maximum power output reaches 598 mW, with a power density of 1572.65 μW/cm³. The secondary energy recovery power accounts for 34.4 %, resulting in a 52.56 % enhancement in the energy harvester's output performance. Additionally, hand-cranking tests indicate that the fabricated prototype of the electromagnetic energy harvester can power some common electronic devices, including smartphones, showcasing significant application potential.

Novel Design and Performance Analysis of 1R1T Remote Center-of-Motion Mechanisms With Partially Decoupled T- and R-Motions

Abstract Remote center-of-motion (RCM) mechanisms provide a way for surgical instruments to pass through a remote center (e.g., skin incision) under geometrical constraints, facilitating safer operations in minimally invasive surgery (MIS). One rotation and one translation (1R1T, pitch and insertion) are the basic requirements for RCM mechanisms. To make the structure simpler and control easier, a novel concept of 1R1T RCM mechanisms with partially decoupled motions, inspired by the double-parallelogram 1R RCM mechanisms, is proposed in this article, by investigating and proving its motion combination principle based on the screw theory. New evolution procedures based on the configuration evolution method have been derived to design 1R1T RCM mechanisms based on two approaches of inserting the T-motion in an original 1R RCM mechanism, resulting in two types of 1R1T RCM mechanisms with partially decoupled motions and base-locating actuators. The kinematic models of one typical proposed mechanism (including the forward and inverse kinematics) and its Jacobian matrix are derived. The performance analysis is presented, including RCM validation, velocity, singularity, and workspace analysis. Then, the dimensional optimization based on the discrete solution method is derived. Finally, a prototype of the proposed mechanism is presented with preliminary experiments performed to verify the feasibility of the synthesized RCM mechanisms. The results show that the RCM mechanism performs the 1R1T partially decoupled motion, and it can be used as the basic element of an active manipulator of an MIS robot.

Silicon Clathrate-Supported Catalysts with Low Work Functions for Ammonia Synthesis.

Diamond-type silicon has a work function of ≈4.8eV, and conventional n- or p-type doping modifies the value only between 4.6 and 5.05eV. Here, it is shown that the alkali clathrates AxSi46 have substantially lower work functions approaching 2.6eV, with clear trends between alkali electropositivity and clathrate cage size. The low work function enables alkali clathrates such as K8Si46 to be effective Haber-Bosch catalyst supports for NH3 synthesis. The catalytic properties of Si, Ge, and Sn-based clathrates are investigated while supporting Fe and Ru on the surface. The activity largely scales with the work function, and low activation energies below 60kJ mol-1 are observed due to strong electron donation effects from the support. Ru metal and Sn clathrates seem to be unsuitable for stability issues. Compared to other similar hydride/electride catalysts, the simple structure and composition combined with stability in air/water make a systematic study of these clathrates possible and open the door to other electron-rich Zintl phases and related intermetallics as low-work function materials suitable for catalysis. The observed low work function may also have implications for other existing electronic applications.

Polycyclic aromatic hydrocarbon derivatives onto polar microplastics of polyurethane: equilibrium, thermodynamics, and kinetics of monolayer-multilayer adsorption.

The study of the adsorption of polycyclic aromatic hydrocarbons on microplastics (MPs) has attracted much attention as to how microplastics can act as carriers of these pollutants. Polyurethane (PU) is one of the MPs found in aquatic environments, containing different functional groups it can interact with polar and nonpolar molecules. PAH derivatives (dPAHs) present different properties and thus can be adsorbed by different interactions; thus, this study investigated the adsorption of fluorene (FLN), dibenzothiophene (DBT), dibenzofuran (DBF), and carbazole (CBZ) onto PU MP. The Langmuir, Freundlich, and BET isotherm models were examined, and the BET model best fitted. The adsorption was a nonspontaneous process, exothermic for mono- and multilayer formation for FLN, DBT, and CBZ, and endothermic for DBF monolayer formation. The adsorption monolayer was formed by van der Waals forces, H─bonding, and π─π interactions, while the formation of the multilayer can be explained by π─π and hydrophobic interactions. The pseudo-second-order model proved to be more consistent for the adsorption of dPAHs. The adsorption in artificial seawater shows no significant differences for the monolayer but favored the adsorption multilayer due to the salting-out effect. Due to the existence of several adsorption mechanisms, PU MP interacts with dPAHs in greater quantities when compared to a MP with a simpler structure.

Thermotunable mid-infrared metamaterial absorption material based on combined hollow cylindrical VO2 structure

We have designed a metamaterial absorption material based on the VO2 phase transition effect. The aim is to realize thermally tunable broadband absorption in the mid-infrared band. The metamaterial absorption material is a three-layer structure. From top to bottom, the combined hollow cylindrical VO2 resonant layer, the SiO2 dielectric layer and the Ti substrate. In this work, we perform numerical simulations using the three-dimensional time-domain finite element difference method. The simulation shows that the absorption material's average absorption intensity is adjustable by temperature between 0.09 and 0.95. At a temperature of 342 K, the absorption material has an absorption bandwidth of 17.3 μm (6.43 μm to 23.73 μm) with an absorption rate above 90%. And the average absorption in this band range is 94.95%. And this band covers the wavelength of the atmospheric transparency window (8 μm∼14 μm), which suggests that our absorption material has great application prospects. In this work, we first analyze the electromagnetic field at the absorption material's resonant wavelength and explain the absorption material's absorption mechanism. Then, we investigated the absorption effect of the absorption material under the VO2 structure with different temperatures. And we explain temperature's effect on the absorption material's absorption effect by analyzing the electric field's change on the absorption material's surface at different temperatures for the same wavelength. The effect of the absorption material structural parameters on the absorption material absorption performance to determine the optimal structural parameters was then investigated. Finally, we investigate the absorption curves of the absorption material under different columnar VO2 layers and demonstrate the innovative and unique nature of the designed absorption material. The absorption material we designed has a simple structure and is easy to configure. And the absorption material has high average absorption rate and a wide absorption bandwidth. We therefore believe that the metamaterial absorption material has great application prospects in optoelectronic detection, infrared imaging and infrared stealth.

Band gap generation in cantilever beams through periodic material removal

Traditional methods for generating band gaps in beams usually involve adding periodic elements like tuned mass dampers or masses, or applying complex geometrical changes. This research suggests a subtraction-based method achieved by removing material in the thickness direction through straightforward machining operations, thus forming periodic cells. The numerical studies start with band gap analysis, using periodic theory to assess different periodic cell configurations. This is followed by numerical and experimental studies on cantilever beams, each containing a set number of these periodic cells. Non-contact vibration measurements are conducted on one plain and six machined aluminum beams using a multipoint laser vibrometer and an automated impact hammer. The experimental findings corroborate the band gaps predicted by the numerical model, confirming the effectiveness of this approach. The study notes that the optimal periodicity of the cells and the contrast in thickness vary with the beam’s dimensions, and that the thickness contrast markedly affects the quantity, width, and intensity of the resulting band gaps. These results indicate that (1) periodic material removal in beam-like structures allows improved vibration reduction while mass is reduced, and (2) manufacturing can play a key role in vibration control in simple structures.

A single-sided all-at-once preconditioning for linear system from a non-local evolutionary equation with weakly singular kernels

In Lin et al. (2021) [21] and Zhao et al. (2023) [37], two-sided preconditioning techniques are proposed for non-local evolutionary equations, which possesses (i) mesh-size independent theoretical bound of condition number of the two-sided preconditioned matrix; (ii) small and stable iteration numbers in numerical tests. In this paper, we modify the two-sided preconditioning by multiplying the left-sided and the right-sided preconditioners together as a single-sided preconditioner. Such a single-sided preconditioner essentially derives from approximating the spatial matrix with a fast diagonalizable matrix and keeping the temporal matrix unchanged. Clearly, the matrix-vector multiplication of the single-sided preconditioning is faster to compute than that of the two-sided one, since the single-sided preconditioned matrix has a simpler structure. More importantly, we show theoretically that the single-sided preconditioned generalized minimal residual (GMRES) method has a convergence rate no worse than the two-sided preconditioned one. As a result, the one-sided preconditioned GMRES solver requires less computational time than the two-sided preconditioned GMRES solver in total. Numerical results are reported to show the efficiency of the proposed single-sided preconditioning technique.

New disturbance observer-based speed estimator for induction motor

<p>This paper discusses a novel disturbance observer designed as an estimator to determine the rotor speed of an induction motor. This observer is a solution to obtain a simple structure with a small number of compact observer gains. Furthermore, the adaptation law is no longer required to estimate induction motor speed values. This is a machine model-based computation method that uses a stationary reference frame. The nonlinearity problem is solved using an additional state vector in the observer model, which is known as an extended state observer. This approach easily and systematically determines the observer gain by applying the linear quadratic regulator (LQR) method, thereby avoiding time-consuming trial errors. The proposed observer, which was presented in both continuous and discrete forms, was tested using a sensorless V/f- controlled induction motor. The simulation results show that the proposed observer can accurately estimate all states, namely, the rotor flux and stator current; therefore, the proposed estimator provides the speed and electromagnetic torque for a wide operational range of speeds and load torques. It was also shown that the proposed observer was robust to noise and uncertainty in induction motor parameters.</p>

Crystal field optimization, luminescence enhancement and thermal stability of novel K2NaAl0.4Ga0.6F6:Mn4+ solid solution red phosphor for high-performance warm WLED

Mn4+-doped fluoride phosphors have important application value in the background light and WLED lighting fields. Therefore, the synthesis of efficient and stable Mn4+-doped red phosphor is of great application value. In this study, a series of red-emitting K2NaAl1-yGayF6:xMn4+ (y = 0, 0.2, 0.4, 0.6, 0.8 and 1) (x = 0.01, 0.03, 0.05, 0.07 and 0.09) solid solution phosphors are successfully synthesized by simple coprecipitation method. The synthesis strategy of simple crystal structure optimization is proposed to realize simultaneously the crystal field optimization, luminescence enhancement and thermal stability of red phosphor. The calculation and theoretical analysis of crystal field strength are used to prove that solid solution matrix K2NaAl0.4Ga0.6F6 is the most ideal matrix material. X-ray powder diffraction, energy-dispersive X-ray spectrometer and scanning electron microscope are employed to determine the crystal structure, composition and morphology of all samples. Optical properties are characterized using excitation spectra, emission spectra and fluorescence lifetime curves. Moreover, the CIE coordinates of red-light show that the phosphor has low correlated color temperature and excellent color purity. Intriguingly, the as-prepared K2NaAl0.4Ga0.6F6:Mn4+ phosphor possesses admirable thermal quenching behavior and color stability at high temperature. At a temperature of 423 K, the photoluminescence intensity can be maintained at 52 % of the original intensity (298 K). The activation energy, the chromaticity shift and chromaticity coordinate variation are also systematically calculated. More importantly, A high-performance warm WLED with low correlated color temperature (CCT = 3982 K) and high color rendering index (Ra = 93.7) is achieved by using K2NaAl0.4Ga0.6F6:Mn4+ as a red-emitting material. These results demonstrate that K2NaAl0.4Ga0.6F6:Mn4+ red phosphor provides a novel choice for the warm WLED required for indoor lighting.

Image reconstruction through a nonlinear scattering medium via deep learning

Image reconstruction through the opaque medium has great significance in fields of biophotonics, optical imaging, mesoscopic physics, and optical communications. Previous researches are limited in the simple linear scattering process. Here, we develop a nonlinear speckle decoder network, which can reconstruct the phase information of the fundamental frequency wave via the nonlinear scattering signal. Further, we validate the ability of our model to recover simple and complex structures by using MNIST and CIFAR data sets, respectively. We then show that the model is able to restore the image information through different sets of nonlinear diffusers and reconstruct the image of a kind of completely unseen object category. The proposed method paves the way to nonlinear scattering imaging and information encryption.

Design and research on the posture-adjustable mannequin for chest-up and hunchbacked posture

The development of garment personalization has put forward diverse requirements for mannequins. In this paper, we present a garment mannequin that can continuously alter the body posture in response to changes in human body posture in the chest and back regions. This research is founded on an analysis of the patterns and ranges of movement in the mannequin's chest and hunchbacked motions. We segmented the mannequin into six modules: neck, front chest, back, left and right shoulders, and waist and abdomen. By employing stepper motors, we independently drive the front chest, back, and left and right shoulders to achieve the simulation and continuous adjustment of the mannequin's body posture for chest and hunchbacked positions. The comparison of the 3D scans shows that the mannequin fits well in several cross-sections with the corresponding body variations of real people, and the results of the real shirt also show that the shirt made based on the simulated hunchbacked body mannequin is significantly better than the standard shirt in terms of comfort and aesthetics for a person with a hunchbacked body posture. The body posture adjustable mannequin can replace multiple static mannequins, which can provide strong support for the business model of personalized clothing customization. Compared with the existing dynamic mannequin, it has the advantages of high relevance, simple structure and low production cost.

Computer vision in the food industry: Accurate, real-time, and automatic food recognition with pretrained MobileNetV2

In contemporary society, the application of artificial intelligence for automatic food recognition offers substantial potential for nutrition tracking, reducing food waste, and enhancing productivity in food production and consumption scenarios. Cutting-edge technologies such as Computer Vision and Deep Learning are highly beneficial, enabling machines to learn automatically, thereby facilitating automatic visual recognition. Despite some research in this field, the challenge of achieving accurate automatic food recognition quickly remains a significant research gap. Some models have been developed and implemented, but maintaining high performance swiftly, with low computational cost and low access to expensive hardware accelerators, is still an area that needs further exploration and improvement. This study employs the pre-trained MobileNetV2 model, which is cost-efficient and fast, for automatic food recognition on the public Food11 dataset, comprising 16643 images. It also utilizes various tools and techniques such as dataset understanding, transfer learning, data augmentation, regularization, dynamic learning rate, hyperparameter tuning, and consideration of images in different sizes to cut time and enhance the model’s performance and robustness. These techniques aid in choosing appropriate metrics, achieving better performance, avoiding overfitting and accuracy fluctuations, speeding up the model, and increasing the generalization of findings, making the study and its results applicable to real-world applications. Despite MobileNetV2′s simpler structure and fewer trainable parameters compared to some deep-dense models in the deep learning area, it quickly achieved approximately 92.97 % accuracy. This underscores the model’s potential for implementation in real-world applications, which is the main intention of this study.

Direct Arylation Polycondensation‐Derived Polythiophene Achieves Over 16% Efficiency in Binary Organic Solar Cells via Tuning Aggregation and Miscibility

AbstractPolythiophenes are the most appealing donor materials in organic solar cells (OSCs) due to their simple chemical structures. However, the top‐performance polythiophenes are typically synthesized via Stille polycondensation, which is problematic due to significant toxicity and poor atom economy. By contrast, direct arylation polycondensation (DArP) is an eco‐friendly, and atom‐efficient alternative for synthesizing conjugated polymers, while the best efficiency for DArP‐derived polythiophenes is below 12%. This study reports a series of polythiophene‐based donors synthesized via DArP. Among these, PT4F‐Th reaches a power conversion efficiency (PCE) of 16.4%, which not only matches the current record for polythiophene‐based donor materials, but also marks the highest PCE achieved by DArP‐derived donors to date. The superior performance of PT4F‐Th is largely attributed to its optimal temperature‐dependent aggregation behavior and moderate miscibility with acceptors, along with the highest crystallinity among the candidates, resulting in the most favorable blend film morphology. This study underscores the significant potential of DArP‐derived polythiophenes in developing high‐performance and eco‐friendly OSCs.

Effects of delay and error in the feedback structure of ecological management

Ecosystems face various emergent uncertainties owing to factors such as climate change and accelerating anthropogenic impacts. Uncertainty is a major challenge and a barrier that ecosystem management faces, because it is difficult to precisely predict a priori risks that can have significant impacts on ecosystems. Hence, management with adaptive capacity is recommended to deal with such uncertainties, and feedback structures are central mechanisms for such flexible management. This study used mathematical models to clarify the specific impacts of feedback structures on ecosystem management, such as resource and wildlife management. In particular, the impact of errors in estimating ecosystem status when providing feedback and the impact of the time lag before feedback effects were implemented into management were examined. Overestimation of ecosystem status or a large time lag led to undesirable temporal oscillations in ecosystem status. However, these scenarios can be avoided when combined with management practices that limit the impact of management on the ecosystem, such as input control. Ecosystem management tends to have a large spatiotemporal scale, and implementing highly accurate monitoring and sophisticated feedback structures is difficult. However, the results suggest that effective ecosystem management with a simple feedback structure can be achieved through such complementary institutional design.

Design of the Elastic Modulus of porous lattice structures composed of cells with continuously variable cross section carrying structures

BackgroundPorous bone implants have a wide range of applications for their low elastic modulus and good connectivity. It is necessary to explore an elastic modulus control method that can significantly regulate the elastic modulus under the condition of maintaining a constant porosity. MethodsFor achieving continuously changing elastic modulus of porous lattice structure, the simple cubic lattice structures were selected as research object, and the distribution of cross-sectional sizes of its carrying structures were set as variable continuous curves. The prediction model for the elastic modulus was established based on the elasticity mechanics and the equal mass assumption. Then, the prediction model is enhanced through compression simulation of the unit cell structure. Finally, the accuracy of prediction model is validated by compression experiments. FindingsThe results indicate that the distribution of cross-sectional size of the carrying structures has a significant impact on the elastic modulus of unit cell structures under the constraint of equal mass. By adjusting the characteristic parameters of distribution curves, the elastic modulus can be changed within a large range. InterpretationVariable cross-section can effectively change the elastic modulus of porous structures while ensuring constant porosity. This method has important value in decoupling the influence of geometric parameters on the elastic modulus of porous structures.

Triple band self-decoupled MIMO antenna pair for 5G communication

A two port multiple input multiple output (MIMO) antenna with self-isolation is proposed for the application of fifth generation (5G) mobile phones. In this antenna, feeding ports that are inherently isolated across a bandwidth without the need for extra decoupling components directly excite the MIMO antenna. An approach involving the creation of common and differential modes utilizes a mode-cancellation technique to comprehensively understand the self-decoupling mechanism on a physical level. The proposed self-decoupled antenna pair exhibits about 22 dB isolation across the triple band 2.58 GHz to 2.84 GHz, 3.4 GHz to 3.9 GHz and 4.3 GHz to 4.6 GHz, respectively. According to the experimental findings, the proposed MIMO system may offer better than 22 dB isolation across all ports and a respectable level of overall gain 1.9 dBi, 3.77 dBi and 2.9 dBi across 2.58 GHz to 2.84 GHz, 3.4 GHz to 3.9 GHz and 4.3 GHz to 4.6 GHz. A suggested design method, with its advantages of self-decoupling, simple structure, high efficiency and triple band demonstrates amazing upcoming 5G highly integrated MIMO antennas for 5G devices.