Motivation.To assist efforts in determining and exploring the functional properties of proteins, it is desirable to characterize and predict protein flexibilities.Results.In this study, the conformational entropy is used as an indicator of the protein flexibility. We first explore whether the conformational change can capture the protein flexibility. The well-defined decoy structures are converted into one-dimensional series of letters from a structural alphabet. Four different structure alphabets, including the secondary structure in 3-class and 8-class, the PB structure alphabet (16-letter), and the DW structure alphabet (28-letter), are investigated. The conformational entropy is then calculated from the structure alphabet letters. Some of the proteins show high correlation between the conformation entropy and the protein flexibility. We then predict the protein flexibility from basic amino acid sequence. The local structures are predicted by the dual-layer model and the conformational entropy of the predicted class distribution is then calculated. The results show that the conformational entropy is a good indicator of the protein flexibility, but false positives remain a problem. The DW structure alphabet performs the best, which means that more subtle local structures can be captured by large number of structure alphabet letters. Overall this study provides a simple and efficient method for the characterization and prediction of the protein flexibility.

In the current highly industrialized living environment, air quality has become an increasing public health concern. Natural environments like forests have excellent air quality due to high concentrations of negative oxygen ions originating from low-voltage ionization, without harmful ozone. Traditional negative oxygen ion generators require high voltage for corona discharge to produce ions. However, high voltage can increase electron collisions and excitations, leading to more dissociation and recombination of oxygen molecules and consequently higher ozone production. To address the challenge of generating negative oxygen ions without accompanying ozone production, this study designed and constructed a low-voltage negative oxygen ion generator based on nanometer-tip carbon fiber electrodes. The advantage of this device lies in the high curvature radius of carbon fibers, which provides high local electric field strength. This allows for efficient production of negative oxygen ions at low operating voltages without generating ozone. Experiments demonstrated that the device can efficiently generate negative oxygen ions at a working voltage as low as 2.16 kV, 28% lower than the lowest voltage reported in similar studies. The purification device manufactured in this study had a total decay constant for PM_2.5 purification of 0.8967 min⁻¹ within five minutes, compared to a natural decay constant of only 0.0438 min⁻¹, resulting in a calculated Clean Air Delivery Rate (CADR) of 0.1535 m³/min. Within half an hour, concentrations of PM_2.5, PM₁, PM₁₀, formaldehyde, and TVOC were reduced by 99.09%, 99.40%, 99.37%, 94.39%, and 99.35%, respectively, demonstrating good decay constants and CADR. These findings confirm its effectiveness in improving indoor air quality, highlighting its significant application value in air purification.

With the rapid development of high-throughput sequencing technology, the proteomics research becomes a trendy field in the post genomics era. It is necessary to identify all the native-encoding protein sequences for further function and pathway analysis. Toward that end, the Human Proteome Organization lunched the Human Protein Project in 2011. However many proteins are hard to be detected by experiment methods, which becomes one of the bottleneck in Human Proteome Project. In consideration of the complicatedness of detecting these missing proteins by using wet-experiment approach, here we use bioinformatics method to pre-filter the missing proteins. Since there are analogy between the biological sequences and natural language, the n-gram models from Natural Language Processing field has been used to filter the missing proteins. The dataset used in this study contains 616 missing proteins from the “uncertain” category of the neXtProt database. There are 102 proteins deduced by the n-gram model, which have high probability to be native human proteins. We perform a detail analysis on the predicted structure and function of these missing proteins and also compare the high probability proteins with other mass spectrum datasets. The evaluation shows that the results reported here are in good agreement with those obtained by other well-established databases. The analysis shows that 102 proteins may be native gene-coding proteins and some of the missing proteins are membrane or natively disordered proteins which are hard to be detected by experiment methods.

Free-standing polymer films that are ultra-thin, lightweight, and robust hold significant promise for applications in flexible electronics. However, their performance has been constrained by the challenge of simultaneously enhancing mechanical strength and reducing density. Herein, an ultra-thin and robust polyimide (PI)-based covalent organic framework-modified multi-walled carbon nanotube (MWCNT-COF) film is demonstrated for high-specific-power flexible GaAs solar cells. The film exhibits a high Young’s modulus of 1.53 GPa, a tensile strength exceeding 97.53 MPa, and a low density of 0.73 g cm ⁻³ , representing a 45.1% reduction in density. The incorporation of 3D interconnected layered and porous MWCNT-COF significantly enhances the film’s mechanical properties while reducing its density. The synergistic effects of robust MWCNTs and covalently bonded COF layers, combined with the thermally stable PI molecular structure, impart exceptional strength and lightness to the film. Computational studies further confirm that COF-grafted MWCNTs effectively modify the polyamide acid matrix, substantially improving the mechanical properties of the PI films. Moreover, flexible dual-junction and triple-junction GaAs solar cells were successfully fabricated using 6 µm-thick MWCNT-COF/PI composite films, delivering outstanding specific powers of 8998 and 7749 W kg ⁻¹ , along with efficiencies of 26.6% and 31.5% (AM0), respectively. These results underscore the potential for high-performance applications in space and energy systems. This work offers valuable insights into the development of high-performance flexible GaAs solar cells based on ultra-thin and robust PI films for a wide range of applications.

The crystal structure evolution and phase transformation of single-crystal germanium during temperature-assisted nanomachining were investigated using the molecular dynamics method. The differences in surface atomic distribution, material removal volume, subsurface damage depth, surface roughness, and normal cutting force of single-crystal germanium under two different cutting depths at preheating temperatures of 300 K, 450 K, 600 K, 750 K, and 900 K were compared. The results show that with the increase in cutting depth, the material removal amount and subsurface damage depth increase. In addition, as the temperature increases, the thermal softening effect mitigates brittle fracture at low temperatures can reduce the brittle fracture at low temperatures, and the material removal mode also transitions from brittle fracture to plastic shear, which makes the internal stress of the workpiece balanced and thus conducive to forming a better machined surface. However, constrained by the size effect, it is difficult to explain the machining mechanism of single-crystal germanium cutting at the macroscopic level. Therefore, this study innovatively simulated the heating input via temperature control, revealing the machining mechanism of single-crystal germanium cutting at different temperatures from a microscopic perspective. The results show that increasing cutting depth enlarges material removal volume and subsurface damage. More importantly, preheating induces a non-monotonic transition in material removal behavior: from brittle fracture at 300 K to stable plastic shear between 450 K and 750 K, and eventually to thermally induced tearing above 750 K. An optimal processing window is identified—450 K minimizes subsurface damage, while 750 K maximizes removal efficiency. These findings provide quantitative guidance for selecting preheating temperatures in ultra-precision machining of brittle semiconductors.