Dual auxotrophy coupled red labeling strategy for efficient genome editing in Saccharomyces cerevisiae.

The homologous recombination strategy has a long history of editing Saccharomyces cerevisiae target genes. The application of CRISPR/Cas9 strategy to editing target genes in S. cerevisiae has also received a lot of attention in recent years. All findings seem to indicate that editing relevant target genes in S. cerevisiae is an extremely easy event. In this study, we systematically analyzed the advantages and disadvantages of homologous recombination (HR) strategy, CRISPR/Cas9 strategy, and CRISPR/Cas9 combined homology-mediated repair (CRISPR/Case9-HDR) strategy in knocking out BY4742 ade2. Our data showed that when the ade2 was knocked out by HR strategy, a large number of clones appeared to be off-target, and 10 %-80 % of the so-called knockout clones obtained were heteroclones. When the CRISPR/Cas9 strategy was applied, 60% of clones were off-target and the rest were all heteroclones. Interestingly, most of the cells were edited successfully, but at least 60 % of the clones were heteroclones, when the CRISPR/Cas9-HDR strategy was employed. Our results clearly showed that the emergence of heteroclone seems inevitable regardless of the strategies used for editing BY4742 ade2. Given the characteristics of BY4742 defective in ade2 showing red on the YPD plate, we attempted to build an efficient yeast gene editing strategy, in which the CRISPR/Cas9 combines homology-mediated repair template carrying an ade2 expression cassette, BY4742(ade2Δ0) as the start strain. We used this strategy to successfully achieve 100 % knockout efficiency of trp1, indicating that technical challenges of how to easily screen out pure knockout clones without color phenotype have been solved. Our data showed in this study not only establishes an efficient yeast gene knockout strategy with dual auxotrophy coupled red labeling but also provides new ideas and references for the knockout of target genes in the monokaryotic mycelium of macrofungi.

Pred-SF: A Precipitation Prediction Model Based on Deep Neural Networks.

How to predict precipitation accurately and efficiently is the key and difficult problem in the field of weather forecasting. At present, we can obtain accurate meteorological data through many high-precision weather sensors and use them to forecast precipitation. However, the common numerical weather forecasting methods and radar echo extrapolation methods have insurmountable defects. Based on some common characteristics of meteorological data, this paper proposes a Pred-SF model for precipitation prediction in target areas. The model focuses on the combination of multiple meteorological modal data to carry out self-cyclic prediction and a step-by-step prediction structure. The model divides the precipitation prediction into two steps. In the first step, the spatial encoding structure and PredRNN-V2 network are used to construct the autoregressive spatio-temporal prediction network for the multi-modal data, and the preliminary predicted value of the multi-modal data is generated frame by frame. In the second step, the spatial information fusion network is used to further extract and fuse the spatial characteristics of the preliminary predicted value and, finally, output the predicted precipitation value of the target region. In this paper, ERA5 multi-meteorological mode data and GPM precipitation measurement data are used for testing to predict the continuous precipitation of a specific area for 4 h. The experimental results show that Pred-SF has strong precipitation prediction ability. Some comparative experiments were also set up for comparison to demonstrate the advantages of the combined prediction method of multi-modal data and the stepwise prediction method of Pred-SF.

Numerical Forecast Correction of Temperature and Wind Using a Single-Station Single-Time Spatial LightGBM Method.

Achieving high-performance numerical weather prediction (NWP) is important for people's livelihoods and for socioeconomic development. However, NWP is obtained by solving differential equations with globally observed data without capturing enough local and spatial information at the observed station. To improve the forecasting performance, we propose a novel spatial lightGBM (Light Gradient Boosting Machine) model to correct the numerical forecast results at each observation station. By capturing the local spatial information of stations and using a single-station single-time strategy, the proposed method can incorporate the observed data and model data to achieve high-performance correction of medium-range predictions. Experimental results for temperature and wind prediction in Hainan Province show that the proposed correction method performs well compared with the ECWMF model and outperforms other competing methods.

Strain-Guided Oxidative Nanoperforation on Graphene.

Increased applications of nanoporous graphene in nanoelectronics and membrane separations require ordered and precise perforation of graphene, whose scalablility and time/cost effectiveness represent a significant challenge in existing nanoperforation methods, such as catalytical etching and lithography. A strain-guided perforation of graphene through oxidative etching is reported, where nanopores nucleate selectively at the bulges induced by the prepatterned nanoprotrusions underneath. Using reactive molecular dynamics and theoretical models, the perforation mechanisms are uncovered through the relationship between bulge-induced strain and enhanced etching reactivity. Parallel experiments of chemical vapor deposition (CVD) of graphene on SiO2 NPs/SiO2 substrates verify the feasibility of such strain-guided perforation and evolution of pore size by exposure of varied durations to oxygen plasma. This scalable method can be feasibly applied to a broad variety of 2D materials (e.g., graphene and h-boron nitride) and nanoprotrusions (e.g., SiO2 and C60 nanoparticles), allowing rational fabrication of 2D material-based devices.

Rapid Programmable Nanodroplet Motion on a Strain-Gradient Surface.

When a nanodroplet is placed on a lattice surface, an inhomogeneous surface strain field perturbs the balance of van der Waals force between the nanodroplet and surface, thus providing a net driving force for nanodroplet motion. Using molecular dynamics and theoretical analysis, we study the effect of strain gradient on modulating the movement of a nanodroplet. Both modeling and simulation show that the driving force is opposite to the direction of strain gradient, with a magnitude that is proportional to the strain gradient as well as nanodroplet size. Two representative surfaces, graphene and copper (111) plane, are exemplified to demonstrate the controllable motion of the nanodroplet. When the substrate undergoes various types of reversible deformations, multiple motion modes of nanodroplets can be feasibly achieved, including acceleration, deceleration, and turning, becoming a facile strategy to manipulate nanodroplets along a designed two-dimensional pathway.

Closed-edged bilayer phosphorene nanoribbons producing from collapsing armchair phosphorene nanotubes.

A new phosphorous allotrope, closed-edged bilayer phosphorene nanoribbon, is proposed via radially deforming armchair phosphorene nanotubes. Using molecular dynamics simulations, the transformation pathway from round PNTs falls into two types of collapsed structures: arc-like and sigmoidal bilayer nanoribbons, dependent on the number of phosphorene unit cells. The fabricated nanoribbions are energetically more stable than their parent nanotubes. It is also found via ab initio calculations that the band structure along tube axis substantially changes with the structural transformation. The direct-to-indirect transition of band gap is highlighted when collapsing into the arc-like nanoribbons but not the sigmoidal ones. Furthermore, the band gaps of these two types of nanoribbons show significant size-dependence of the nanoribbon width, indicative of wider tunability of their electrical properties.

Trends of the sunshine duration and diffuse radiation percentage on sunny days in urban agglomerations of China during 1960-2005.

The long-term observational data of sunshine duration (SD) and diffuse radiation percentage (defined as diffuse solar radiation/total solar radiation, DRP) on sunny days during 1960-2005 were analyzed in 7 urban agglomerations and the whole of China. The results show that the sunny sunshine duration (SSD) has decreased significantly except at a few stations over northwestern China in the past 46 years. An obvious decrease of the SSD is found in eastern China, with the trend coefficients lower than -0.8. Accompanied by the SSD decline, the sunny diffuse radiation percentage (SDRP) in most stations shows obvious increasing trends during the 46 years. The averaged SDRP over China has increased 2.33% per decade, while the averaged SSD shows a decrease of -0.13 hr/day per decade. The correlation coefficient between SDRP and SSD is -0.88. SSD decreased over urban agglomerations (small to large city clusters) in the past 46 years, especially in large cities and medium cities, due to the strong anthropogenic activities and air pollution represented by aerosol option depth (AOD) and tropospheric column NO2 (TroNO2). On the regional scale, SSD has an opposite trend from SDRP during 1960 to 2005, and the variation trends of regional mean values of SSD and SDRP in southeastern China are more pronounced than those in northwestern China.

Rock pressure evaluation in coal face based on multi-factor decision-making theory.

The behavior of rock pressure is a natural and inevitable phenomenon during coal seam mining, resulting in numerous casualties and equipment damage annually. The ability to predict and assess the strength of rock pressure in the coal face beforehand has become crucial in preventing rock pressure accidents. This paper took the prediction of rock pressure strength in coal face as the research object, and based on the multi-factor decision-making theory, proposed a new method for the evaluation of rock pressure strength in coal face-"dual-dimension rock pressure strength evaluation method". Initially, the rock pressure strength index IA was obtained through the application of the law of sedimentary pressure control and microseismic monitoring data. The drilling data at the exploration scale served as references. Then, based on the rock pressure control mechanism, the rock pressure strength index IB was obtained by utilizing a type of Euclidean distance formula at the coal face scale. Finally, in order to mutually correct the two rock pressure strength indices, the rock pressure strength grade matrix was employed to acquire the rock pressure strength grade of the coal face. Applying this evaluation method to the coal face, the prediction outcomes aligned with the actual situation. Therefore, this method can provide a theoretical reference for the prediction of rock pressure strength and the prevention of rock pressure accidents in alternative areas.

A LIBS spectrum baseline correction method based on the non-parametric prior penalized least squares algorithm.

Laser-induced breakdown spectroscopy (LIBS) has become a popular element analysis technique because of its real-time multi-element detection and non-damage advantages. However, due to factors such as laser-substance interaction and the experimental environment, the measured LIBS spectrum signal contains a continuous background, severely influencing spectrum analysis. In this paper, we propose a LIBS spectrum baseline correction method based on the non-parametric prior penalized least squares (NPPPLS) algorithm. Compared with the traditional Penalized Least Squares (PLS) method, improvements have been made in two aspects. On the one hand, a new weight method with faster convergence is proposed. On the other hand, we combine the Adam algorithm and introduce the RMSE of the baseline correction result at the previous time to constrain the update of the balance parameter, which enables the balance parameter to be adjusted adaptively and no parameter prior is required. The simulation results show that the proposed NPPPLS algorithm can achieve excellent correction results, even with no parametric priors. In addition, the performance of the NPPPLS algorithm is not affected by the initial value of the balance parameter, and the stability and robustness are significantly improved. Finally, we conducted baseline correction of the experimental LIBS spectrum and performed univariate and multivariate analyses. The results show that the quantitative analysis accuracy is improved after baseline correction, and the correlation coefficient R2 of different elements obtained by the extreme learning machine method of multivariate analysis can reach 0.99, demonstrating a better quantitative analysis result. The simulation and experimental results verify the excellent performance of the proposed NPPPLS algorithm, which can be effectively used to improve the accuracy of quantitative analysis. In addition, this method is also expected to be used for baseline correction of the Raman spectrum, near-infrared spectrum and so on.

Self-assembled CsPbBr3 quantum dots with wavelength-tunable photoluminescence for efficient active jamming.

CsPbBr3 perovskite quantum dots (QDs) show great potential in various applications due to their size-dependent and excellent optoelectronic properties. However, it is still challenging to synthesize size-tunable CsPbBr3 QDs with purple emission. Herein, CsPbBr3 nanospheres (NS) with purple emission (432 nm) and wavelength-tunable photoluminescence were synthesized using a two-step recrystallization method for the first time. A nanocube (NC) strategy resulting from CsPbBr3 nanosphere self-assembly via polar solvent-induced surface ligand mismatch was proposed. The self-assembly process endows the QDs with wavelength-tunable photoluminescence ranging from 432 to 518 nm. The significant reduction in defects during self-assembly was confirmed by transient optical spectroscopy measurements, photoluminescence quantum yields (PLQY), and the disappearance of tail bands in the long-wavelength region of the photoluminescence (PL) spectrum. This theory demonstrated that the decrease in high defect surfaces and increase in specific surface area were the reasons for the decline in defects. Most importantly, these QDs could be used for the active jamming of optical imaging systems based on charged-coupled devices (CCDs), including laser imaging radar and low light level (LLL) night vision systems. QDs significantly increase the mean square error (MSE) of the image, while the detection rate of the target by the artificial intelligence algorithm decreased by 95.17%. The wide wavelength tunable emission caused by structural changes makes it arduous for silicon-based detectors to avoid the interference of QDs by adding filters or by other means.

Dual Plasmon Resonances and Tunable Electric Field in Structure-Adjustable Au Nanoflowers for Improved SERS and Photocatalysis.

Flower-like metallic nanocrystals have shown great potential in the fields of nanophononics and energy conversion owing to their unique optical properties and particular structures. Herein, colloid Au nanoflowers with different numbers of petals were prepared by a steerable template process. The structure-adjustable Au nanoflowers possessed double plasmon resonances, tunable electric fields, and greatly enhanced SERS and photocatalytic activity. In the extinction spectra, Au nanoflowers had a strong electric dipole resonance located around 530 to 550 nm. Meanwhile, a longitudinal plasmon resonance (730~760 nm) was obtained when the number of petals of Au nanoflowers increased to two or more. Numerical simulations verified that the strong electric fields of Au nanoflowers were located at the interface between the Au nanosphere and Au nanopetals, caused by the strong plasmon coupling. They could be further tuned by adding more Au nanopetals. Meanwhile, much stronger electric fields of Au nanoflowers with two or more petals were identified under longitudinal plasmon excitation. With these characteristics, Au nanoflowers showed excellent SERS and photocatalytic performances, which were highly dependent on the number of petals. Four-petal Au nanoflowers possessed the highest SERS activity on detecting Rhodamine B (excited both at 532 and 785 nm) and the strongest photocatalytic activity toward photodegrading methylene blue under visible light irradiation, caused by the strong multi-interfacial plasmon coupling and longitudinal plasmon resonance.

Strong Visible Light Absorption and Abundant Hotspots in Au-Decorated WO3 Nanobricks for Efficient SERS and Photocatalysis.

Metal/semiconductor hybrids show potential application in fields of surface-enhanced Raman spectroscopy (SERS) and photocatalysis due to their excellent light absorption, electric field, and charge-transfer properties. Herein, a WO3-Au metal/semiconductor hybrid, which was a WO3 nanobrick decorated with Au nanoparticles, was prepared via a facile hydrothermal method. The WO3-Au hybrids show excellent visible light absorption, strong plasmon coupling, high-performance SERS, and good photocatalytic activity. In particular, on sensing rhodamine B (RhB) under 532 nm excitation, bare WO3 nanobricks have a Raman enhancement factor of 2.0 × 106 and a limit of detection of 10-8 M due to the charger-transfer property and abundant oxygen vacancies. WO3-Au metal/semiconductor hybrids display a largely improved Raman enhancement factor compared to pure Au and WO3 components owing to the synergistic effect of electromagnetic enhancement and charge transfer. The Raman enhancement factor and limit of detection are further improved, reaching 5.3 × 108 and 10-12 M, respectively, on increasing the content of Au to 2.1 wt %, owing to the strong plasmon coupling between the Au nanoparticles. Additionally, the WO3-Au hybrids also exhibit excellent photocatalytic activity toward degradation of RhB under visible light irradiation. WO3-Au (2.1 wt %) possesses the fastest photocatalytic rate, which is 6.1 and 2.0 times that of pure WO3 nanobricks and commercial P25, respectively. The enhanced photocatalytic activity is attributed to the strong plasmon coupling and the efficient charge transfer between Au and WO3 nanobricks. The as-prepared materials show great potential in detecting and degrading pollutants in environmental treatment.

Multi-interfacial plasmon coupling in multigap (Au/AgAu)@CdS core-shell hybrids for efficient photocatalytic hydrogen generation.

Plasmon coupling induced intense light absorption and near-field enhancement have vast potential for high-efficiency photocatalytic applications. Herein, (Au/AgAu)@CdS core-shell hybrids with strong multi-interfacial plasmon coupling were prepared through a convenient strategy for efficient photocatalytic hydrogen generation. Bimetallic Au/AgAu cores with an adjustable number of nanogaps (from one to four) were primarily synthesized by well-controlled multi-cycle galvanic replacement and overgrowth processes. Extinction tests and numerical simulations synergistically revealed that the multigap Au/AgAu hybrids possess a gap-dependent light absorption region and a local electric field owing to the multigap-induced multi-interfacial plasmon coupling. With these characteristics, hetero-photocatalysts prepared by further coating of CdS shells on multigap Au/AgAu cores exhibited a prominent gap-dependent photocatalytic hydrogen production activity from water splitting under light irradiation (λ > 420 nm). It is found that the hydrogen generation rates of multigap (Au/AgAu)@CdS have an exponential improvement compared with that of pure CdS as the number of nanogaps increases. In particular, four-gap (Au/AgAu)@CdS core-shell catalysts displayed the highest hydrogen generation rate, that is 96.1 and 47.2 times those of pure CdS and gapless Au@CdS core-shell hybrids. These improvements can be ascribed to the strong plasmon absorption and near-field enhancement induced by the multi-interfacial plasmon coupling, which can greatly improve the light-harvesting efficiency, offer more plasmonic energy, and boost the generation and separation of electron-hole pairs in the multigap catalysts.

Structure-Adjustable Gold Nanoingots with Strong Plasmon Coupling and Magnetic Resonance for Improved Photocatalytic Activity and SERS.

Au nanoingots, on which an Au nanosphere is accurately placed in an open Au shell, are synthesized through a controllable hydrothermal method. The prepared Au nanoingots exhibit an adjustable cavity structure, strong plasmon coupling, tunable magnetic plasmon resonance, and prominent photocatalytic and SERS performances. Au nanoingots exhibit two resonance peaks in the extinction spectrum, one (around 550 nm) is ascribed to electric dipole resonance coming from the central Au, and the other one (650-800 nm) is ascribed to the magnetic dipole resonance originating from the open Au shell. Numerical simulations verify that the intense electric and magnetic fields locate in the bowl-shaped nanogap between the Au nanosphere and shell, and they can be further optimized by changing the size of the outer Au shell. Au nanoingots with the largest shell have the strongest electric field because of large-area plasmon coupling, while Au nanoingots with the largest shell opening size have the strongest magnetic field. As a result, the structure-adjustable Au nanoingots show a high tunability and enhancement of catalytic reduction of p-nitrophenol and SERS detection of Rhodamine B. Specially, Au nanoingots with the largest shell size exhibit the highest catalytic activity and Raman signals at 532 nm excitation. However, Au nanoingots with the largest shell opening size have the highest photocatalytic activity with light irradiation (λ > 420 nm) and exhibit the best SERS performance at 785 nm excitation.

[Temporal and spatial characteristics of atmospheric NO2 over Hainan Island and the pollutant sources in recent 10 years].

The temporal-spatial characteristics of the tropospheric column NO2 (TroNO2) and total column NO2 (TotNO2) over Hainan Island are analyzed using remote sensing data derived from OMI sensor, and also combining surface wind, SO2, HYSPLIT model to research the source of atmospheric pollutants over Hainan Island. The results show that: The value of NO2 in northern area is higher than that in southern area, and the value of NO, in central mountainous area is lower than those other places. In addition, the seasonal variation of NO2 indicates that NO2 is higher in winter and lower in summer, which can be attributed to precipitation in summer and external transport of atmospheric pollutants in winter. Long-term changes of NO2 in Hainan Island appear opposite trends during winter and summer, which is declining in winter and has a weak increase in summer. The reasonable explanation is that local emissions of pollutants play an important role in summer, but external transport is the main resource of pollutants over Hainan Island. The TroNO2 in Haikou City has a good relationship with favorable delivered days in PRD, the correlation coefficient is 0.84 with 99% confidence level. Moreover, there are 3 transport paths in Dec. 2013 which can impact Haikou City from backward trajectory analysis, but all of them pass through the PRD, which can further prove that atmospheric pollutants of Hainan Island in winter are mainly delivery from PRD region.