The ground delay program (GDP) is a commonly used tool in air traffic management. Developing a departure flight delay prediction model based on GDP can aid airlines and control authorities in better flight planning and adjusting air traffic control strategies. A model that combines the improved sparrow search algorithm (ISSA) and Multilayer Perceptron (MLP) has been proposed to minimise prediction errors. The ISSA uses tent chaotic mapping, dynamic adaptive weights, and Levy flight strategy to enhance the algorithm’s accuracy for the sparrow search algorithm (SSA). The MLP model’s hyperparameters are optimised using the ISSA to improve the model’s prediction accuracy and generalisation performance. Experiments were performed using actual GDP-generated departure flight delay data and compared with other machine learning techniques and optimisation algorithms. The results of the experiments show that the mean absolute error (MAE) and root mean square error (RMSE) of the ISSA-MLP model are 16.8 and 24.2, respectively. These values are 5.61%, 6.3% and 1.8% higher in MAE and 4.4%, 5.1% and 2.5% higher in RMSE compared to SSA, particle swarm optimisation (PSO) and grey wolf optimisation (GWO). The ISSA-MLP model has been verified to have good predictive and practical value.

The target backsheath field acceleration mechanism is one of the main mechanisms of laser-driven proton acceleration (LDPA) and strongly depends on the comprehensive performance of the ultrashort ultra-intense lasers used as the driving sources. The successful use of the SG-II Peta-watt (SG-II PW) laser facility for LDPA and its applications in radiographic diagnoses have been manifested by the good performance of the SG-II PW facility. Recently, the SG-II PW laser facility has undergone extensive maintenance and a comprehensive technical upgrade in terms of the seed source, laser contrast and terminal focus. LDPA experiments were performed using the maintained SG-II PW laser beam, and the highest cutoff energy of the proton beam was obviously increased. Accordingly, a double-film target structure was used, and the maximum cutoff energy of the proton beam was up to 70 MeV. These results demonstrate that the comprehensive performance of the SG-II PW laser facility was improved significantly.

Collaborative planning for multiple hypersonic vehicles can effectively improve operational effectiveness. Time coordination is one of the main forms of cooperation among multi-hypersonic glide vehicles, and time cooperation trajectory optimisation is a key technology that can significantly increase the success rate of flight missions. However, it is difficult to obtain satisfactory time as a constraint condition during trajectory optimisation. To solve this problem, a multilayer Perceptrona is trained and adopted in a time-decision module, whose input is a four-dimensional vector selected according to the trajectory characteristics. Additionally, the MLP will be capable of determining the optimal initial heading angle of each aircraft to reduce unnecessary manoeuvering performance consumption in the flight mission. Subsequently, to improve the cooperative flight performance of hypersonic glide vehicles, the speed-dependent angle-of-attack and bank command were designed and optimised using the Artificial Bee Colony algorithm. The final simulation results show that the novel strategy proposed in this study can satisfy terminal space constraints and collaborative time constraints simultaneously. Meanwhile, each aircraft saves an average of 13.08% flight range, and the terminal speed is increased by 315.6m/s compared to the optimisation results of general purpose optimal control software (GPOPS) tools.

OBJECTIVES/GOALS: NSF often requires cross-disciplinary team composition to be competitive for funding. To what extent do research teams have multidisciplinary authorships after they win an award, given that awards are not contracts? We examined the quantity and quality of multidisciplinary collaboration of NSF-funded teams before and after receiving their award. METHODS/STUDY POPULATION: Our sample was 150 PIs and Co-PIs (67% male) from 58 NSF-funded EAGER (EArly-concept Grants for Exploratory Research) grants between 2013 and 2019. Using publicly available information, we collected the number of conference papers, publications, and grants PIs/co-PIs produced with each other (all PIs and co-PIs in a team or a partial subset). Based on Ph.D. fields, we also cataloged whether the combination of PIs/co-PI authors on outputs represented unidisciplinary or multidisciplinary collaboration after their NSF award. Multidisciplinary collaboration consisted of multidivisional (Ph.D. disciplines across NSF divisions, e.g., political science and cognitive psychology) or multidirectorate (Ph.D. disciplines across NSF directorates, e.g., psychology and engineering) authorship. RESULTS/ANTICIPATED RESULTS: Of the 74% of PI and co-PI teams who collaborated after their EAGER award, almost 9 out of 10 chose to work with a collaborator from a different discipline, and almost 8 out of 10 chose to work with a researcher from an extremely diverse discipline from their own (e.g., computer science and psychology). Research on interdisciplinary teams largely emphasizes the challenges and problems they face but the current research demonstrated that 90% of the sample chose to continue working together across disciplines after EAGER awards. Therefore, future research should dedicate more attention to the nontangible benefits members receive in interdisciplinary teams. Moreover, quality measures revealed higher H-indices for multidisciplinary than unidisciplinary journals and conferences. DISCUSSION/SIGNIFICANCE: Our archival results revealed that NSF EAGER grants are having their intended effect of being a catalyst for 1) continued multidisciplinary (and especially multidirectorate) collaboration) and 2) high-quality multidisciplinary publication and conference output. These results have contributed to NSF policy changes to reinstate the EAGER grant.

Shape memory polymers (SMPs) are a type of programmable materials capable of transforming their shapes in a pre-programmed way upon the application of an external stimulus. These materials have been tested for various potential applications particularly in the biomedical field for polymers with general and specific requirements. This review focuses on the recent advances in biomedical applications, including self-tightening sutures, pressure bandages, self-expansion stents, tissue engineering scaffolds, artificial muscles, drug delivery, and orthodontic archwires, after a brief description of the concepts, classifications, programming procedures, and material requirements of SMPs.

As a typical plasma-based optical element that can sustain ultra-high light intensity, plasma density gratings driven by intense laser pulses have been extensively studied for wide applications. Here, we show that the plasma density grating driven by two intersecting driver laser pulses is not only nonuniform in space but also varies over time. Consequently, the probe laser pulse that passes through such a dynamic plasma density grating will be depolarized, that is, its polarization becomes spatially and temporally variable. More importantly, the laser depolarization may spontaneously take place for crossed laser beams if their polarization angles are arranged properly. The laser depolarization by a dynamic plasma density grating may find application in mitigating parametric instabilities in laser-driven inertial confinement fusion.

In the present study, we investigated the influence of different mid-stage N compensation timings on agronomic and physiological traits associated with grain yield and quality in field experiments. Two japonica rice cultivars with a good tasting quality (Nangeng 9108 and Nangeng 5055) were examined under eight N compensation timings (N1–N6: one-time N compensation at 7-2 weeks before heading; N7: split N compensation at 5 and 3 weeks before heading; N8: split N compensation at 4 and 2 weeks before heading) and a control with no N compensation. The highest yield was obtained with N7, followed by N3. The yield advantage is mainly attributable to the improved population structure (higher productive tiller rate with a stable number of effective panicles), higher total number of spikelets per unit area (large panicles with more grains per panicle), larger leaf area index in the late period and higher photosynthetic production capacity (more dry matter accumulation and transportation in the middle and late periods). Delaying N compensation timing improved the processing and nutritional quality of rice, but decreased the quality of appearance and cooking/eating traits. Our results suggest that, from the perspective of achieving relative coordination between high yield and high quality of japonica rice, the optimal N compensation should be divided equally at 5 and 3 weeks before heading. However, if simplifying the number of operations and the pursuit of eating quality were considered, one-time N compensation should be conducted at 5 weeks before heading.

This paper studied the use of eye movement data to form criteria for judging whether pilots perceive emergency information such as cockpit warnings. In the experiment, 12 subjects randomly encountered different warning information while flying a simulated helicopter, and their eye movement data were collected synchronously. Firstly, the importance of the eye movement features was calculated by ANOVA (analysis of variance). According to the sorting of the importance and the Euclidean distance of each eye movement feature, the warning information samples with different eye movement features were obtained. Secondly, the residual shrinkage network modules were added to CNN (convolutional neural network) to construct a DRSN (deep residual shrinkage networks) model. Finally, the processed warning information samples were used to train and test the DRSN model. In order to verify the superiority of this method, the DRSN model was compared with three machine learning models, namely SVM (support vector machine), RF (radom forest) and BPNN (backpropagation neural network). Among the four models, the DRSN model performed the best. When all eye movement features were selected, this model detected pilot perception of warning information with an average accuracy of 90.4%, of which the highest detection accuracy reached 96.4%. Experiments showed that the DRSN model had advantages in detecting pilot perception of warning information.

China plays a critical role in global biodiversity conservation, as both a biodiversity hotspot and for its role in international and domestic animal trade. Efforts to promote wildlife conservation have sparked interest in the attitudes held by Chinese citizens towards animals. Using a questionnaire, we sought to investigate the attitudes of 317 Chinese nationals across 22 provincial-level administrative units regarding their uses of animals, their perceived emotional capacities and views on exotic pets. We reduced the variables related to perceived uses of animals via Principal Component Analysis and ran Generalised Linear Models and Structural Equation Modelling to test relationships between questionnaire-derived variables. Perceptions of animals were divided into two Kellert categories — Utilitarian and Humanistic uses — and 97% of participants believed in animals’ capacities to have and express emotions. We found few interactions, with exotic pets, ie playing with or taking photographs, but the acceptability of owning an exotic pet influenced the likelihood of purchasing one. A belief that animals express emotions encouraged people to look for them as pets but thinking that pets make people happy made exotic pet ownership less acceptable. The shift in attitudes to include humanistic perceptions of animals, a belief in animals as emotive beings and understanding of terminology changed from the previous utilitarian views of pre-reform China, suggesting a readiness to embrace further conservation efforts in China. This deeper understanding of Chinese attitudes toward animals and drivers of the exotic pet trade within China may enable conservation efforts to better target future campaigns.

This study aimed to investigate the relationship between bone quality in terms of metabolism, homeostasis of elements, bone mineral density (BMD), and microstructure and keel-bone fractures in laying hens (Gallus gallus domesticus). One hundred and twenty 17 week old Lohmann White laying hens with normal keel bones were individually housed in furnished cages for 25 weeks. Birds were then euthanased and dissected to assess keel-bone status at 42 weeks. Serum and keel-bone samples from normal keel (NK) and fractured keel (FK) hens were collected to determine the previously mentioned bone quality parameters. The results showed FK hens to have higher levels of the components of osteocalcin, greater alkaline phosphatase activity in serum and keel bones, and greater tartrate-resistant acid phosphatase (TRAP) activity in keel bones, compared to NK hens. Additionally, FK hens also had higher concentrations of Li, B, K, Cu, As, Se, Sn, Hg, and Pb, but lower concentrations of Na, P, and Ca. Moreover, FK hens showed decreased bone microstructural parameters including bone volume/tissue volume, trabecular number, degree of anisotropy, connectivity density, and BMD, but increased trabecular separation. Meanwhile, no differences were detected in serum TRAP activity, trabecular thickness, bone surface, or bone surface/bone volume. Results showed laying hens with keel-bone fractures to have differences in bone metabolism, elements of home-ostasis, bone microstructure parameters, and BMD. These results suggest that keel-bone fractures may be associated with bone quality.

We describe a new low-frequency wideband radio survey of the southern sky. Observations covering 72–231 MHz and Declinations south of $+30^\circ$ have been performed with the Murchison Widefield Array “extended” Phase II configuration over 2018–2020 and will be processed to form data products including continuum and polarisation images and mosaics, multi-frequency catalogues, transient search data, and ionospheric measurements. From a pilot field described in this work, we publish an initial data release covering 1,447 $\mathrm{deg}^2$ over $4\,\mathrm{h}\leq \mathrm{RA}\leq 13\,\mathrm{h}$ , $-32.7^\circ \leq \mathrm{Dec} \leq -20.7^\circ$ . We process twenty frequency bands sampling 72–231 MHz, with a resolution of 2′–45′′, and produce a wideband source-finding image across 170–231 MHz with a root mean square noise of $1.27\pm0.15\,\mathrm{mJy\,beam}^{-1}$ . Source-finding yields 78,967 components, of which 71,320 are fitted spectrally. The catalogue has a completeness of 98% at ${{\sim}}50\,\mathrm{mJy}$ , and a reliability of 98.2% at $5\sigma$ rising to 99.7% at $7\sigma$ . A catalogue is available from Vizier; images are made available via the PASA datastore, AAO Data Central, and SkyView. This is the first in a series of data releases from the GLEAM-X survey.

The great demographic pressure brings tremendous volume of beef demand. The key to solve this problem is the growth and development of Chinese cattle. In order to find molecular markers conducive to the growth and development of Chinese cattle, sequencing was used to determine the position of copy number variations (CNVs), bioinformatics analysis was used to predict the function of ZNF146 gene, real-time fluorescent quantitative polymerase chain reaction (qPCR) was used for CNV genotyping and one-way analysis of variance was used for association analysis. The results showed that there exists CNV in Chr 18: 47225201-47229600 (5.0.1 version) of ZNF146 gene through the early sequencing results in the laboratory and predicted ZNF146 gene was expressed in liver, skeletal muscle and breast cells, and was amplified or overexpressed in pancreatic cancer, which promoted the development of tumour through bioinformatics. Therefore, it is predicted that ZNF146 gene affects the proliferation of muscle cells, and then affects the growth and development of cattle. Furthermore, CNV genotyping of ZNF146 gene was three types (deletion type, normal type and duplication type) by Real-time fluorescent quantitative PCR (qPCR). The association analysis results showed that ZNF146-CNV was significantly correlated with rump length of Qinchuan cattle, hucklebone width of Jiaxian red cattle and heart girth of Yunling cattle. From the above results, ZNF146-CNV had a significant effect on growth traits, which provided an important candidate molecular marker for growth and development of Chinese cattle.

We report the experimental results of the commissioning phase in the 10 PW laser beamline of the Shanghai Superintense Ultrafast Laser Facility (SULF). The peak power reaches 2.4 PW on target without the last amplifying during the experiment. The laser energy of 72 ± 9 J is directed to a focal spot of approximately 6 μm diameter (full width at half maximum) in 30 fs pulse duration, yielding a focused peak intensity around 2.0 × 1021 W/cm2. The first laser-proton acceleration experiment is performed using plain copper and plastic targets. High-energy proton beams with maximum cut-off energy up to 62.5 MeV are achieved using copper foils at the optimum target thickness of 4 μm via target normal sheath acceleration. For plastic targets of tens of nanometers thick, the proton cut-off energy is approximately 20 MeV, showing ring-like or filamented density distributions. These experimental results reflect the capabilities of the SULF-10 PW beamline, for example, both ultrahigh intensity and relatively good beam contrast. Further optimization for these key parameters is underway, where peak laser intensities of 1022–1023 W/cm2 are anticipated to support various experiments on extreme field physics.

The performance of hypersonic vehicles in the take-off stage considerably influences their capability of accomplishing the flight tasks. This study is aimed at enhancing the take-off performance of a cruise aircraft using the improved chimp optimisation algorithm. The proposed algorithm, which uses the Sobol sequence for initial population generation and a function of the weight factors, can effectively overcome the problems of premature convergence and low accuracy of the original algorithm. In particular, the Sobol sequence aims to obtain a better fitness value in the first iteration, and the weight factor aims to accelerate the convergence speed and avoid the local optimal solution. The take-off mass model of the hypersonic vehicle is constructed considering the flight data obtained using the pseudo-spectral method in the climb phase. Simulations are performed to evaluate the algorithm performance, and the results show that the algorithm can rapidly and stably optimise the benchmark function. Compared to the original algorithm, the proposed algorithm requires 28.89% less optimisation time and yields an optimised take-off mass that is 1.72kg smaller.

Previous literature finds anomalies are at least as prevalent in developed markets as in emerging markets; namely, the global anomaly puzzle. We show that while market development and information diffusion are linearly related, information diffusion has a nonlinear impact on anomalies. This is consistent with theoretical developments concerning the process of information diffusion. In extremely low-efficiency regimes, without newswatchers sowing the seeds of price discovery and ensuring the long-run convergence of price to fundamentals, initial mispricing and subsequent correction will not occur. The concentration of emerging countries in low-efficiency regimes provides an explanation to the puzzle.