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.

We consider a two-dimensional (2-D) model of an autophoretic particle. Beyond a certain emission/absorption rate (characterized by a dimensionless Péclet number, $Pe$) the particle is known to undergo a bifurcation from a non-motile to a motile state, with different trajectories, going from a straight to a chaotic motion by increasing $Pe$. From the full model, we derive a reduced closed model which involves only two time-dependent complex amplitudes $C_1(t)$ and $C_2(t)$ corresponding to the first two Fourier modes of the solute concentration field. It consists of two coupled nonlinear ordinary differential equations for $C_1$ and $C_2$ and presents several advantages: (i) the straight and circular motions can be handled fully analytically; (ii) complex motions such as chaos can be analysed numerically very efficiently in comparison with the numerically expensive full model involving partial differential equations; (iii) the reduced model has a universal form dictated only by symmetries (meaning that the form of the equations does not depend on a given phoretic model); (iv) the model can be extended to higher Fourier modes. The derivation method is exemplified for a 2-D model, for simplicity, but can easily be extended to three dimensions, not only for the presently selected phoretic model, but also for any model in which chemical activity triggers locomotion. A typical example can be found, for example, in the field of cell motility involving acto-myosin kinetics. This strategy offers an interesting way to cope with swimmers on the basis of ordinary differential equations, allowing for analytical tractability and efficient numerical treatment.

Planting patterns have significant effects on rice growth. Nonetheless, little is known about differences in annual crop yield and resource utilization among mechanized rice planting patterns in a rice–wheat cropping system. Field experiments were conducted from 2014 to 2017 using three treatments: pot seedling transplanting for rice and row sowing for wheat (PST-RS), carpet seedling transplanting for rice and row sowing for wheat (CST-RS) and row sowing for both crops (RS-RS). The results showed that, compared with RS-RS, PST-RS and CST-RS prolonged annual crop growth duration by 25–26 and 13–15 days, increased effective accumulated temperature by 399 and 212°C days and increased cumulative solar radiation by 454 and 228 MJ/m2 because of the earlier sowing of rice by 28 and 16 days in PST-RS and CST-RS, respectively. Compared with RS-RS, the annual crop yield of PST-RS and CST-RS increased by 3.1–3.8 and 2.0–2.6 t/ha, respectively, because of the increase in the number of spikelets/kernels per hectare, aboveground biomass, mean leaf area index and grain–leaf ratio. In addition, temperature production efficiency, solar radiation production efficiency and solar radiation use efficiency were higher in PST-RS, followed by CST-RS and RS-RS. These results suggest that mechanized rice planting patterns such as PST-RS increase annual crop production in rice–wheat cropping systems by increasing yield and solar energy utilization.

Adjacent dyadic systems are pivotal in analysis and related fields to study continuous objects via collections of dyadic ones. In our prior work (joint with Jiang, Olson, and Wei), we describe precise necessary and sufficient conditions for two dyadic systems on the real line to be adjacent. Here, we extend this work to all dimensions, which turns out to have many surprising difficulties due to the fact that $d+1$ , not $2^d$ , grids is the optimal number in an adjacent dyadic system in $\mathbb {R}^d$ . As a byproduct, we show that a collection of $d+1$ dyadic systems in $\mathbb {R}^d$ is adjacent if and only if the projection of any two of them onto any coordinate axis are adjacent on $\mathbb {R}$ . The underlying geometric structures that arise in this higher-dimensional generalization are interesting objects themselves, ripe for future study; these lead us to a compact, geometric description of our main result. We describe these structures, along with what adjacent dyadic (and n-adic, for any n) systems look like, from a variety of contexts, relating them to previous work, as well as illustrating a specific exa.

In centrifugal compressors, the identification of flow instability signals from experiments is a difficult problem owing to the nonlinear and non-stationary characteristics. Otherwise, the complicated asymmetric structure of the volute brings a huge challenge to the evolution and circumferential nonuniformity characteristics of the flow instabilities. This paper presents experimental and numerical investigations on internal flow field to understand the flow instability characteristics in a centrifugal compressor. Considering nonlinear and non-stationary signals, a method based on Fourier-transform and variational mode decomposition was introduced to analyse the flow instability characteristics. The Fourier spectrum results show that at 0.21kg/s of 80krpm, the pressure signal has a noticeable high-frequency fluctuation, which indicates that the compressor enters the flow instability state. The variational mode decomposition results show that before a surge, the compressor experiences different flow instability stages: the RI stage, the coexistence stage of RI and stall, and the stall stage. Moreover, obvious circumferential nonuniformity characteristics of flow instabilities were observed during the throttling process. RI first occurred at the 180° circumferential position and then the stall first appeared in the circumferential range of 60° to 240°. The simulation results that it is because that the asymmetric volute causes the adverse pressure gradient inside the impeller passage and a high-pressure region (120°–240°) at the upstream of the impeller inlet. Under this combined action of the two, the effect region of tip leakage vortex expands the upstream of the impeller inlet. Meanwhile, the tip leakage vortex core migrates to a lower span of blades. This study demonstrates the ability to analyse nonlinear and non-stationary signals from a centrifugal compressor via variational mode decomposition, and provides a useful guidance for the identification of flow instability signals.

To persist (without immigration) in habitats with unpredictable environmental conditions, annuals must produce seeds each year or have a seed bank. Thus, we predicted that compared to perennials, annuals have a wider germination temperature range (GTR, the difference in temperature between the week with the highest and the week with the lowest germination during the natural germination season). We determined the GTR via germination phenology data for 350 herbaceous species in 59 families from the eastern USA: summer annuals (SA), 63; winter annuals (WA), 83; monocarpic perennials (MP), 28; and polycarpic perennials (PP), 176. There was no significant phylogenetic signal for the GTR. The width of the GTR during the first spring germination season was 9.6, 8.7 and 8.8°C for MP, PP and SA, respectively, and during the first autumn germination season 12.8, 11.8 and 12.4°C for MP, PP and WA, respectively. Annuals did not have a wider GTR than perennials in either the spring or the autumn germination season. Our data suggest that selection for early germination in either spring or autumn has resulted in only small differences in the GTR. We predict that global warming will have little or no effect on reshaping the germination phenology of herbaceous species of temperate eastern North America.

The early identification and prediction of hand-foot-and-mouth disease (HFMD) play an important role in the disease prevention and control. However, suitable models are different in regions due to the differences in geography, social economy factors. We collected data associated with daily reported HFMD cases and weather factors of Zibo city in 2010~2019 and used the generalised additive model (GAM) to evaluate the effects of weather factors on HFMD cases. Then, GAM, support vectors regression (SVR) and random forest regression (RFR) models are used to compare predictive results. The annual average incidence was 129.72/100 000 from 2010 to 2019. Its distribution showed a unimodal trend, with incidence increasing from March, peaking from May to September. Our study revealed the nonlinear relationship between temperature, rainfall and relative humidity and HFMD cases and based on the predictive result, the performances of three models constructed ranked in descending order are: SVR > GAM> RFR, and SVR has the smallest prediction errors. These findings provide quantitative evidence for the prediction of HFMD for special high-risk regions and can help public health agencies implement prevention and control measures in advance.

Mars exploration motivates the search for extraterrestrial life, the development of space technologies, and the design of human missions and habitations. Here, we seek new insights and pose unresolved questions relating to the natural history of Mars, habitability, robotic and human exploration, planetary protection, and the impacts on human society. Key observations and findings include:

1. – high escape rates of early Mars' atmosphere, including loss of water, impact present-day habitability;

2. – putative fossils on Mars will likely be ambiguous biomarkers for life;

3. – microbial contamination resulting from human habitation is unavoidable; and

4. – based on Mars' current planetary protection category, robotic payload(s) should characterize the local martian environment for any life-forms prior to human habitation.

Some of the outstanding questions are:

1. – which interpretation of the hemispheric dichotomy of the planet is correct;

2. – to what degree did deep-penetrating faults transport subsurface liquids to Mars' surface;

3. – in what abundance are carbonates formed by atmospheric processes;

4. – what properties of martian meteorites could be used to constrain their source locations;

5. – the origin(s) of organic macromolecules;

6. – was/is Mars inhabited;

7. – how can missions designed to uncover microbial activity in the subsurface eliminate potential false positives caused by microbial contaminants from Earth;

8. – how can we ensure that humans and microbes form a stable and benign biosphere; and

9. – should humans relate to putative extraterrestrial life from a biocentric viewpoint (preservation of all biology), or anthropocentric viewpoint of expanding habitation of space?

Studies of Mars' evolution can shed light on the habitability of extrasolar planets. In addition, Mars exploration can drive future policy developments and confirm (or put into question) the feasibility and/or extent of human habitability of space.

Schistosomiasis has been subjected to extensive control efforts in the People's Republic of China (China) which aims to eliminate the disease by 2030. We describe baseline results of a longitudinal cohort study undertaken in the Dongting and Poyang lakes areas of central China designed to determine the prevalence of Schistosoma japonicum in humans, animals (goats and bovines) and Oncomelania snails utilizing molecular diagnostics procedures. Data from the Chinese National Schistosomiasis Control Programme (CNSCP) were compared with the molecular results obtained.

Sixteen villages from Hunan and Jiangxi provinces were surveyed; animals were only found in Hunan. The prevalence of schistosomiasis in humans was 1.8% in Jiangxi and 8.0% in Hunan determined by real-time polymerase chain reaction (PCR), while 18.3% of animals were positive by digital droplet PCR. The CNSCP data indicated that all villages harboured S. japonicum-infected individuals, detected serologically by indirect haemagglutination assay (IHA), but very few, if any, of these were subsequently positive by Kato-Katz (KK).

Based on the outcome of the IHA and KK results, the CNSCP incorporates targeted human praziquantel chemotherapy but this approach can miss some infections as evidenced by the results reported here. Sensitive molecular diagnostics can play a key role in the elimination of schistosomiasis in China and inform control measures allowing for a more systematic approach to treatment.

Before coronavirus disease 2019 (COVID-19), few hospitals had fully tested emergency surge plans. Uncertainty in the timing and degree of surge complicates planning efforts, putting hospitals at risk of being overwhelmed. Many lack access to hospital-specific, data-driven projections of future patient demand to guide operational planning. Our hospital experienced one of the largest surges in New England. We developed statistical models to project hospitalizations during the first wave of the pandemic. We describe how we used these models to meet key planning objectives. To build the models successfully, we emphasize the criticality of having a team that combines data scientists with frontline operational and clinical leadership. While modeling was a cornerstone of our response, models currently available to most hospitals are built outside of their institution and are difficult to translate to their environment for operational planning. Creating data-driven, hospital-specific, and operationally relevant surge targets and activation triggers should be a major objective of all health systems.