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Urban water management is confronted with more frequent, more extreme weather events. This paper introduces the Three-Points Approach (3PA) into Sponge City concept, to create a novel framework aimed at guiding water management interventions across local, urban, regional, and river basin scales. The 3PA integrates three domains—Day-to-day, Design, and Extreme —offering a nuanced strategy for flood and drought risk mitigation, also for extreme events. Notably, the 3PA emphasizes the fusion of blue-green infrastructure (BGI) with conventional gray approaches to enhance both multifunctionality and resilience in extreme weather conditions. The study identifies critical issues of implementing this Three-Points Sponge Policy (3PSP) approach, including spatial and temporal scales, transitioning from gray to blue-green infrastructure, asset management, data handling, and effective communication. Interventions spanning various spatial scales and addressing flood protection, drought resilience, and water quality are explored in a first and indicative application in Zhengzhou. The case study distills key design principles, highlighting the imperative of never shifting problems, embracing ecosystem-based adaptation, seeking synergy between interventions, and incorporating adaptability into designs. The 3PSP approach emerges as a holistic framework that considers both risks and benefits, contributing valuable insights to the discourse on integrating urban and river basin water management, improving our ways of dealing with extreme weather events while maximizing the day-to-day benefits of our interventions.

A critical requirement of spectroscopic large scale structure analyses is correcting for selection of which galaxies to observe from an isotropic target list. This selection is often limited by the hardware used to perform the survey which will impose angular constraints of simultaneously observable targets, requiring multiple passes to observe all of them. In SDSS this manifested solely as the collision of physical fibers and plugs placed in plates. In DESI, there is the additional constraint of the robotic positioner which controls each fiber being limited to a finite patrol radius. A number of approximate methods have previously been proposed to correct the galaxy clustering statistics for these effects, but these generally fail on small scales. To accurately correct the clustering we need to upweight pairs of galaxies based on the inverse probability that those pairs would be observed (Bianchi \& Percival 2017). This paper details an implementation of that method to correct the Dark Energy Spectroscopic Instrument (DESI) survey for incompleteness. To calculate the required probabilities, we need a set of alternate realizations of DESI where we vary the relative priority of otherwise identical targets. These realizations take the form of alternate Merged Target Ledgers (AMTL), the files that link DESI observations and targets. We present the method used to generate these alternate realizations and how they are tracked forward in time using the real observational record and hardware status, propagating the survey as though the alternate orderings had been adopted. We detail the first applications of this method to the DESI One-Percent Survey (SV3) and the DESI year 1 data. We include evaluations of the pipeline outputs, estimation of survey completeness from this and other methods, and validation of the method using mock galaxy catalogs., Comment: 30 pages, 21 figures

We present the measurement of Baryon Acoustic Oscillations (BAO) from the Lyman-$\alpha$ (Ly$\alpha$) forest of high-redshift quasars with the first-year dataset of the Dark Energy Spectroscopic Instrument (DESI). Our analysis uses over $420\,000$ Ly$\alpha$ forest spectra and their correlation with the spatial distribution of more than $700\,000$ quasars. An essential facet of this work is the development of a new analysis methodology on a blinded dataset. We conducted rigorous tests using synthetic data to ensure the reliability of our methodology and findings before unblinding. Additionally, we conducted multiple data splits to assess the consistency of the results and scrutinized various analysis approaches to confirm their robustness. For a given value of the sound horizon ($r_d$), we measure the expansion at $z_{\rm eff}=2.33$ with 2\% precision, $H(z_{\rm eff}) = (239.2 \pm 4.8) (147.09~{\rm Mpc} /r_d)$ km/s/Mpc. Similarly, we present a 2.4\% measurement of the transverse comoving distance to the same redshift, $D_M(z_{\rm eff}) = (5.84 \pm 0.14) (r_d/147.09~{\rm Mpc})$ Gpc. Together with other DESI BAO measurements at lower redshifts, these results are used in a companion paper to constrain cosmological parameters., Comment: This DESI Collaboration Key Publication is part of the 2024 publication series using the first year of observations (see https://data.desi.lbl.gov/doc/papers)

Baryon acoustic oscillations (BAO) provide a robust standard ruler to measure the expansion history of the Universe through galaxy clustering. Density-field reconstruction is now a widely adopted procedure for increasing the precision and accuracy of the BAO detection. With the goal of finding the optimal reconstruction settings to be used in the DESI 2024 galaxy BAO analysis, we assess the sensitivity of the post-reconstruction BAO constraints to different choices in our analysis configuration, performing tests on blinded data from the first year of DESI observations (DR1), as well as on mocks that mimic the expected clustering and selection properties of the DESI DR1 target samples. Overall, we find that BAO constraints remain robust against multiple aspects in the reconstruction process, including the choice of smoothing scale, treatment of redshift-space distortions, fiber assignment incompleteness, and parameterizations of the BAO model. We also present a series of tests that DESI followed in order to assess the maturity of the end-to-end galaxy BAO pipeline before the unblinding of the large-scale structure catalogs., Comment: Supporting publication of DESI 2024 III: Baryon Acoustic Oscillations from Galaxies and Quasars

We present cosmological results from the measurement of baryon acoustic oscillations (BAO) in galaxy, quasar and Lyman-$\alpha$ forest tracers from the first year of observations from the Dark Energy Spectroscopic Instrument (DESI), to be released in the DESI Data Release 1. DESI BAO provide robust measurements of the transverse comoving distance and Hubble rate, or their combination, relative to the sound horizon, in seven redshift bins from over 6 million extragalactic objects in the redshift range $0.1-1$ and $w_a<0$. This preference is 2.6$\sigma$ for the DESI+CMB combination, and persists or grows when SN~Ia are added in, giving results discrepant with the $\Lambda$CDM model at the $2.5\sigma$, $3.5\sigma$ or $3.9\sigma$ levels for the addition of Pantheon+, Union3, or DES-SN5YR datasets respectively. For the flat $\Lambda$CDM model with the sum of neutrino mass $\sum m_\nu$ free, combining the DESI and CMB data yields an upper limit $\sum m_\nu < 0.072$ $(0.113)$ eV at 95% confidence for a $\sum m_\nu>0$ $(\sum m_\nu>0.059)$ eV prior. These neutrino-mass constraints are substantially relaxed in models beyond $\Lambda$CDM. [Abridged.], Comment: This DESI Collaboration Key Publication is part of the 2024 publication series using the first year of observations (see https://data.desi.lbl.gov/doc/papers)

In this paper, we present the estimation of systematics related to the halo occupation distribution (HOD) modeling in the baryon acoustic oscillations (BAO) distance measurement of the Dark Energy Spectroscopic Instrument (DESI) 2024 analysis. This paper focuses on the study of HOD systematics for luminous red galaxies (LRG). We consider three different HOD models for LRGs, including the base 5-parameter vanilla model and two extensions to it, that we refer to as baseline and extended models. The baseline model is described by the 5 vanilla HOD parameters, an incompleteness factor and a velocity bias parameter, whereas the extended one also includes a galaxy assembly bias and a satellite profile parameter. We utilize the 25 dark matter simulations available in the AbacusSummit simulation suite at $z=$ 0.8 and generate mock catalogs for our different HOD models. To test the impact of the HOD modeling in the position of the BAO peak, we run BAO fits for all these sets of simulations and compare the best-fit BAO-scaling parameters $\alpha_{\rm iso}$ and $\alpha_{\rm AP}$ between every pair of HOD models. We do this for both Fourier and configuration spaces independently, using post-reconstruction measurements. We find a 3.3$\sigma$ detection of HOD systematic for $\alpha_{\rm AP}$ in configuration space with an amplitude of 0.19%. For the other cases, we did not find a 3$\sigma$ detection, and we decided to compute a conservative estimation of the systematic using the ensemble of shifts between all pairs of HOD models. By doing this, we quote a systematic with an amplitude of 0.07% in $\alpha_{\rm iso}$ for both Fourier and configuration spaces; and of 0.09% in $\alpha_{\rm AP}$ for Fourier space., Comment: 36 pages, 9 figures. Supporting publication of DESI 2024 III: Baryon Acoustic Oscillations from Galaxies and Quasars

We present the DESI 2024 galaxy and quasar baryon acoustic oscillations (BAO) measurements using over 5.7 million unique galaxy and quasar redshifts in the range 0.1

The Dark Energy Spectroscopic Instrument (DESI) will provide precise measurements of Baryon Acoustic Oscillations (BAO) to constrain the expansion history of the Universe and set stringent constraints on dark energy. Therefore, precise control of the global error budget due to various systematic effects is required for the DESI 2024 BAO analysis. In this work, we focus on the robustness of the BAO analysis against the Halo Occupation Distribution (HOD) modeling for the Emission Line Galaxy (ELG) tracer. Based on a common dark matter simulation, our analysis relies on HOD mocks tuned to early DESI data, namely the One-Percent survey data. To build the mocks, we use several HOD models for the ELG tracer as well as extensions to the baseline HOD models. Among these extensions, we consider distinct recipes for galactic conformity and assembly bias. We perform two independent analyses in the Fourier space and in the configuration space. We recover the BAO signal from two-point measurements after performing reconstruction on our mocks. Additionally, we also apply the control variates technique to reduce sample variance noise. Our BAO analysis can recover the isotropic BAO parameter $\alpha_\text{iso}$ within 0.1\% and the Alcock Paczynski parameter $\alpha_\text{AP}$ within 0.3\%. Overall, we find that our systematic error due to the HOD dependence is below 0.17\%, with the Fourier space analysis being more robust against the HOD systematics. We conclude that our analysis pipeline is robust enough against the HOD systematics for the ELG tracer in the DESI 2024 BAO analysis., Comment: Supporting publication of DESI 2024 III: Baryon Acoustic Oscillations from Galaxies and Quasars

Ongoing and upcoming galaxy redshift surveys, such as the Dark Energy Spectroscopic Instrument (DESI) survey, will observe vast regions of sky and a wide range of redshifts. In order to model the observations and address various systematic uncertainties, $N$-body simulations are routinely adopted, however, the number of large simulations with sufficiently high mass resolution is usually limited by available computing time. Therefore, achieving a simulation volume with the effective statistical errors significantly smaller than those of the observations becomes prohibitively expensive. In this study, we apply the Convergence Acceleration by Regression and Pooling (CARPool) method to mitigate the sample variance of the DESI-like galaxy clustering in the AbacusSummit simulations, with the assistance of the quasi-$N$-body simulations FastPM. Based on the halo occupation distribution (HOD) models, we construct different FastPM galaxy catalogs, including the luminous red galaxies (LRGs), emission line galaxies (ELGs), and quasars, with their number densities and two-point clustering statistics well matched to those of AbacusSummit. We also employ the same initial conditions between AbacusSummit and FastPM to achieve high cross-correlation, as it is useful in effectively suppressing the variance. Our method of reducing noise in clustering is equivalent to performing a simulation with volume larger by a factor of 5 and 4 for LRGs and ELGs, respectively. We also mitigate the standard deviation of the LRG bispectrum with the triangular configurations $k_2=2k_1=0.2\hMpc$ by a factor of 1.6. With smaller sample variance on galaxy clustering, we are able to constrain the BAO scale parameters to higher precision. The CARPool method will be beneficial to better constrain the theoretical systematics of BAO, redshift space distortions (RSD) and primordial non-Gaussianity., Comment: 36 pages, 15 figures, 3 tables, to be submitted to JCAP; comments welcome

We present an optimized way of producing the fast semi-analytical covariance matrices for the Legendre moments of the two-point correlation function, taking into account survey geometry and mimicking the non-Gaussian effects. We validate the approach on simulated (mock) catalogs for different galaxy types, representative of the Dark Energy Spectroscopic Instrument (DESI) Data Release 1, used in 2024 analyses. We find only a few percent differences between the mock sample covariance matrix and our results, which can be expected given the approximate nature of the mocks, although we do identify discrepancies between the shot-noise properties of the DESI fiber assignment algorithm and the faster approximation used in the mocks. Importantly, we find a close agreement (<~ 5% relative differences) in the projected errorbars for distance scale parameters for the baryon acoustic oscillation measurements. This confirms our method as an attractive alternative to simulation-based covariance matrices, especially for non-standard models or galaxy sample selections, in particular, relevant to the broad current and future analyses of DESI data., Comment: Supporting publication of DESI 2024 III: Baryon Acoustic Oscillations from Galaxies and Quasars (arXiv:2404.03000). 29 pages, 4 figures. Prepared for submission to JCAP. Code available at https://github.com/oliverphilcox/RascalC and https://github.com/misharash/RascalC-scripts/tree/DESI2024. Data points from the plots available at https://zenodo.org/doi/10.5281/zenodo.10895161

This paper provides a comprehensive overview of how fitting of Baryon Acoustic Oscillations (BAO) is carried out within the upcoming Dark Energy Spectroscopic Instrument's (DESI) 2024 results using its DR1 dataset, and the associated systematic error budget from theory and modelling of the BAO. We derive new results showing how non-linearities in the clustering of galaxies can cause potential biases in measurements of the isotropic ($\alpha_{\mathrm{iso}}$) and anisotropic ($\alpha_{\mathrm{ap}}$) BAO distance scales, and how these can be effectively removed with an appropriate choice of reconstruction algorithm. We then demonstrate how theory leads to a clear choice for how to model the BAO and develop, implement and validate a new model for the remaining smooth-broadband (i.e., without BAO) component of the galaxy clustering. Finally, we explore the impact of all remaining modelling choices on the BAO constraints from DESI using a suite of high-precision simulations, arriving at a set of best-practices for DESI BAO fits, and an associated theory and modelling systematic error. Overall, our results demonstrate the remarkable robustness of the BAO to all our modelling choices and motivate a combined theory and modelling systematic error contribution to the post-reconstruction DESI BAO measurements of no more than $0.1\%$ ($0.2\%$) for its isotropic (anisotropic) distance measurements. We expect the theory and best-practices laid out to here to be applicable to other BAO experiments in the era of DESI and beyond., Comment: 29 pages, 18 figures, 1 table, submitted to MNRAS

Thermal barrier coatings (TBCs) are applied on the surface of metallic components of modern jet engines such as combustion chambers, blades and vanes, in order to increase the engine efficiency by allowing higher operating temperatures. However, during cooling from the operating temperature (i.e. 1000 °C) to room temperature high stresses develop in the ceramic coating due to mismatch of the coefficient of thermal expansion between the metal substrate and ceramic TBC. Then, micro-cracks are generated which, ultimately, lead to the failure of the TBC system. Yttria partially stabilized zirconia (YSZ) is the state-of-art material in industrial TBCs. Since YSZ does not exhibit any self-repair, it is highly desirable to develop new TBC materials with a prolonged lifetime. This can be achieved by addition of MoSi2 intermetallic particles to the YSZ base material. Upon exposure to high-temperature and an oxidizing environment via the crack-path, these MoSi2 particles decompose into a volumetrically expanding product which fills and seals the crack..., Team Marcel Hermans

Dark Energy Spectroscopic Instrument (DESI) will construct a large and precise three-dimensional map of our Universe. The survey effective volume reaches ∼ 20 h-3, Gpc3. It is a great challenge to prepare high-resolution simulations with a much larger volume for validating the DESI analysis pipelines. AbacusSummit is a suite of high-resolution dark-matter-only simulations designed for this purpose, with 200,-3}, Gpc3 (10 times DESI volume) for the base cosmology. However, further efforts need to be done to provide a more precise analysis of the data and to cover also other cosmologies. Recently, the CARPool method was proposed to use paired accurate and approximate simulations to achieve high statistical precision with a limited number of high-resolution simulations. Relying on this technique, we propose to use fast quasi-N-body solvers combined with accurate simulations to produce accurate summary statistics. This enables us to obtain 100 times smaller variance than the expected DESI statistical variance at the scales we are interested in, e.g. k < 0.3h Mpc-1 for the halo power spectrum. In addition, it can significantly suppress the sample variance of the halo bispectrum. We further generalize the method for other cosmologies with only one realization in AbacusSummit suite to extend the effective volume ∼20 times. In summary, our proposed strategy of combining high-fidelity simulations with fast approximate gravity solvers and a series of variance suppression techniques sets the path for a robust cosmological analysis of galaxy survey data.

Dark Energy Spectroscopic Instrument (DESI) will construct a large and precise three-dimensional map of our Universe. The survey effective volume reaches ∼ 20 h-3, Gpc3. It is a great challenge to prepare high-resolution simulations with a much larger volume for validating the DESI analysis pipelines. AbacusSummit is a suite of high-resolution dark-matter-only simulations designed for this purpose, with 200,-3}, Gpc3 (10 times DESI volume) for the base cosmology. However, further efforts need to be done to provide a more precise analysis of the data and to cover also other cosmologies. Recently, the CARPool method was proposed to use paired accurate and approximate simulations to achieve high statistical precision with a limited number of high-resolution simulations. Relying on this technique, we propose to use fast quasi-N-body solvers combined with accurate simulations to produce accurate summary statistics. This enables us to obtain 100 times smaller variance than the expected DESI statistical variance at the scales we are interested in, e.g. k < 0.3h Mpc-1 for the halo power spectrum. In addition, it can significantly suppress the sample variance of the halo bispectrum. We further generalize the method for other cosmologies with only one realization in AbacusSummit suite to extend the effective volume ∼20 times. In summary, our proposed strategy of combining high-fidelity simulations with fast approximate gravity solvers and a series of variance suppression techniques sets the path for a robust cosmological analysis of galaxy survey data.

Boron containing MoSi2 is a promising material for applications at high temperature, but the oxidation mechanism is still unclear. In this work, the high temperature (1100 °C) oxidation of B doped MoSi2 in synthetic air has been investigated. A (boro)silicate layer is formed on the surface of the alloy, which features a mixture of amorphous SiO2 and cristobalite. After an initial transient period, the oxidation kinetics follows a parabolic growth rate law. The growth rate constant of the oxide layer is enhanced by the boron in the alloy by 90 % per at.% B. The increase in growth rate is associated with boron mitigating the formation of cristobalite thereby promoting the formation of amorphous SiO2., Team Marcel Hermans, Team Vera Popovich, Team Joris Dik

The Dark Energy Spectroscopic Instrument (DESI) completed its five-month Survey Validation in May 2021. Spectra of stellar and extragalactic targets from Survey Validation constitute the first major data sample from the DESI survey. This paper describes the public release of those spectra, the catalogs of derived properties, and the intermediate data products. In total, the public release includes good-quality spectral information from 466,447 objects targeted as part of the Milky Way Survey, 428,758 as part of the Bright Galaxy Survey, 227,318 as part of the Luminous Red Galaxy sample, 437,664 as part of the Emission Line Galaxy sample, and 76,079 as part of the Quasar sample. In addition, the release includes spectral information from 137,148 objects that expand the scope beyond the primary samples as part of a series of secondary programs. Here, we describe the spectral data, data quality, data products, Large-Scale Structure science catalogs, access to the data, and references that provide relevant background to using these spectra., Comment: 43 pages, 7 figures, 17 tables, submitted to AJ, DESI EDR references added

The Dark Energy Spectroscopic Instrument (DESI) was designed to conduct a survey covering 14,000 deg$^2$ over five years to constrain the cosmic expansion history through precise measurements of Baryon Acoustic Oscillations (BAO). The scientific program for DESI was evaluated during a five month Survey Validation (SV) campaign before beginning full operations. This program produced deep spectra of tens of thousands of objects from each of the stellar (MWS), bright galaxy (BGS), luminous red galaxy (LRG), emission line galaxy (ELG), and quasar target classes. These SV spectra were used to optimize redshift distributions, characterize exposure times, determine calibration procedures, and assess observational overheads for the five-year program. In this paper, we present the final target selection algorithms, redshift distributions, and projected cosmology constraints resulting from those studies. We also present a `One-Percent survey' conducted at the conclusion of Survey Validation covering 140 deg$^2$ using the final target selection algorithms with exposures of a depth typical of the main survey. The Survey Validation indicates that DESI will be able to complete the full 14,000 deg$^2$ program with spectroscopically-confirmed targets from the MWS, BGS, LRG, ELG, and quasar programs with total sample sizes of 7.2, 13.8, 7.46, 15.7, and 2.87 million, respectively. These samples will allow exploration of the Milky Way halo, clustering on all scales, and BAO measurements with a statistical precision of 0.28% over the redshift interval $z<1.1$, 0.39% over the redshift interval $1.1

The pursuit of enhancing NiTi superelasticity through laser powder bed fusion (L-PBF) and [001] texture creation poses a challenge due to increased susceptibility to hot cracking in the resulting microstructure with columnar grains. This limitation restricts NiTi's application and contributes to material waste. To overcome this, we introduce a pioneering approach: utilising spark plasma sintering (SPS) to heal directional cracks in [001] textured L-PBF NiTi shape memory alloy. Diffusion bonding and oxygen utilisation for Ti2NiOx formation was found to successfully heal the cracks. SPS enhances mechanical properties, superelasticity at higher temperatures, and two-way shape memory strain during thermomechanical cycling. This work provides an alternative solution for healing cracks in L-PBF parts, enabling the sustainable reuse of cracked materials. By implementing SPS, this approach effectively addresses hot cracking limitations, expanding the application potential of L-PBF NiTi parts while improving their functional and mechanical properties., Team Vera Popovich, Team Marcel Hermans

A novel hybrid framework of optimized deep learning models combined with multi-sensor fusion is developed for condition diagnosis of concrete arch beam. The vibration responses of structure are first processed by principal component analysis for dimensionality reduction and noise elimination. Then, the deep network based on stacked autoencoders (SAE) is established at each sensor for initial condition diagnosis, where extracted principal components and corresponding condition categories are inputs and output, respectively. To enhance diagnostic accuracy of proposed deep SAE, an enhanced whale optimization algorithm is proposed to optimize network meta-parameters. Eventually, Dempster-Shafer fusion algorithm is employed to combine initial diagnosis results from each sensor to make a final diagnosis. A miniature structural component of Sydney Harbour Bridge with artificial multiple progressive damages is tested in laboratory. The results demonstrate that the proposed method can detect structural damage accurately, even under the condition of limited sensors and high levels of uncertainties.

A novel hybrid framework of optimized deep learning models combined with multi-sensor fusion is developed for condition diagnosis of concrete arch beam. The vibration responses of structure are first processed by principal component analysis for dimensionality reduction and noise elimination. Then, the deep network based on stacked autoencoders (SAE) is established at each sensor for initial condition diagnosis, where extracted principal components and corresponding condition categories are inputs and output, respectively. To enhance diagnostic accuracy of proposed deep SAE, an enhanced whale optimization algorithm is proposed to optimize network meta-parameters. Eventually, Dempster-Shafer fusion algorithm is employed to combine initial diagnosis results from each sensor to make a final diagnosis. A miniature structural component of Sydney Harbour Bridge with artificial multiple progressive damages is tested in laboratory. The results demonstrate that the proposed method can detect structural damage accurately, even under the condition of limited sensors and high levels of uncertainties.

Hysteretic models are used to describe the nonlinear memory-based relationship between the input and output of some physical systems. A long short-term memory neural network-based method is proposed to identify nonlinear hysteretic parameters. Either force or vibration response data are used as the input of the network and the nonlinear hysteresis parameters as the output. The principal component analysis technique is applied to eliminate the redundant dimensionality of the input data. The attention mechanism is utilized to enhance the generalization ability of the standard network. Three representative hysteretic models are employed to verify the effectiveness of the present method. Both numerical and experimental results demonstrate that the proposed method could yield accurate identification results in all cases, even when uncertain and limited input data are used. Compared with the sensitivity methods and heuristic algorithms, the proposed method is more computationally efficient and can obtain more accurate identification results.

In this study, we propose a novel structural condition assessment method based on adaptive vision feature extractions and reinforced learning-assisted evolution. First, the ‘features from accelerated segment test’ (FAST) algorithm cooperating with the Kanade-Lucas-Tomasi algorithm synergistically captures the displacements from the video clips. However, the fixed threshold values in the FAST algorithm may not satisfy the pixel requirements for different images. Second, for any evolutionary algorithms (EAs), their search modes significantly affect the optimization performance but are relatively single and monotonous. Therefore, they may perform poorly for some high-dimensional and complicated multi-objective functions. To resolve these two critical problems, firstly, we propose an adaptive feature points extraction strategy during the displacements acquisition stage. Secondly, a novel local search framework subjected to the reinforced learning framework is designed for EAs as an improvement. The proposed structural condition assessment method is used to evaluate a space frame structure by optimizing the vibration data-based multi-sample objective function. The damaged locations and severities of the frame can be well identified.

One of the major challenges to improving the performance of sodium-ion batteries at low temperatures is to develop effective anode materials with novel structures and fast reaction kinetics. Currently, converting electrode materials from the crystalline to amorphous state is an effective approach to fabricate the electrode material with high sodium storage performance. Herein, a three-dimensional (3D) cross-linked heterostructure with one-dimensional (1D) amorphous potassium titanate (KTiOx) nanobelts in-situ grown on two-dimensional (2D) titanium carbide (Ti2CTx) nanosheets (a-KTiOx/Ti2CTx) was fabricated through alkalization of the multilayered Ti2CTx MXene, which exhibits remarkable sodium storage performance at both room and low temperatures. The heterostructure prepared by the combination of 1D amorphous nanobelts and 2D conductive nanosheets enables efficient strain alleviation in the electrode, a high capacitive contribution to charge storage, rapid ionic diffusion kinetics, and robust electrode integrity, thus enhancing the sodium storage performance. In particular, reversible capacities of 221.9, 144.2 and 112.6 mAh/g can be achieved at 0.1 A/g after 100 cycles at 25, 0 and -25 °C, respectively. This study provides significant insights into the construction of MXene-based electrode materials for sodium storage at low temperatures.

Given a natural language referring expression, the goal of referring video segmentation task is to predict the segmentation mask of the referred object in the video. Previous methods only adopt 3D CNNs upon the video clip as a single encoder to extract a mixed spatio-temporal feature for the target frame. Though 3D convolutions are able to recognize which object is performing the described actions, they still introduce misaligned spatial information from adjacent frames, which inevitably confuses features of the target frame and leads to inaccurate segmentation. To tackle this issue, we propose a language-aware spatial-temporal collaboration framework that contains a 3D temporal encoder upon the video clip to recognize the described actions, and a 2D spatial encoder upon the target frame to provide undisturbed spatial features of the referred object. For multimodal features extraction, we propose a Cross-Modal Adaptive Modulation (CMAM) module and its improved version CMAM+ to conduct adaptive cross-modal interaction in the encoders with spatial- or temporal-relevant language features which are also updated progressively to enrich linguistic global context. In addition, we also propose a Language-Aware Semantic Propagation (LASP) module in the decoder to propagate semantic information from deep stages to the shallow stages with language-aware sampling and assignment, which is able to highlight language-compatible foreground visual features and suppress language-incompatible background visual features for better facilitating the spatial-temporal collaboration. Extensive experiments on four popular referring video segmentation benchmarks demonstrate the superiority of our method over the previous state-of-the-art methods.

Spectrum map (SM) is an important tool to reflect the spectrum usage in the electromagnetic environment. To address the problems of low precision and poor efficiency in the SM construction, this paper develops a novel SM construction approach based on the artificial bee colony enabled sensor layout optimization and an adaptive Kriging model based on spatial autocorrelation. Considering the significant autocorrelation between sensor attributes caused by the exponentially decaying shadow fading of signal propagation, the sensor estimation groups are established, and the estimation results are obtained by the Kriging model. The simulation results show that the proposed SM construction scheme can not only effectively reduce the overhead of sensor resources but also obtain a high SM construction accuracy. Extensive simulation results show that the proposed method can reduce the RMSE of SM construction by 37.56%, 25.32% and 12.89% respectively compared with Random-OK when the standard deviation of shadow fading is 1 dB, 3 dB and 6 dB.

Aroma substances are the most crucial criteria for the sensory evaluation of tea quality, and also key attractors influencing consumers to make the decision for purchasing tea. Understanding the aromatic properties of tea infusion during different brewing time is crucial to control the tea aromatic quality. Here, headspace and direct immersion solid-phase microextraction (HS-SPME and DI-SPME), coupled with GC-MS, were employed to investigate the impact of brewing time on the changes of the volatile features of green tea infusion. Esters, aldehydes, alcohols, fatty acids, and alkaloids were the predominant volatile groups from tea infusions. Two to three minutes was identified as the best duration for the tea brewing that can maximize the abundance of aromatic chemicals in the headspace emitted from the tea infusions. The variation of the key aromatic contributors between the tea infusion and the headspace over the infusion tended to equilibrate during the tea brewing process. This study provides a theory-based reference method by analyzing the real-time aromatic characteristics in green tea. The optimal time was determined for aromatic quality control, and the complementary relationship between the volatiles in the headspace and its counterpart, tea infusion, was primarily elucidated.

Background The rhizosphere is the narrow zone of soil immediately surrounding the root, and it is a critical hotspot of microbial activity, strongly influencing the physiology and development of plants. For analyzing the relationship between the microbiome and metabolome in the rhizosphere of tea (Camellia sinensis) plants, the bacterial composition and its correlation to soil metabolites were investigated under three different fertilization treatments (unfertilized, urea, cow manure) in different growing seasons (spring, early and late summer). Results The bacterial phyla Proteobacteria, Bacteroidetes, Acidobacteria and Actinobacteria dominated the rhizosphere of tea plants regardless of the sampling time. These indicated that the compositional shift was associated with different fertilizer/manure treatments as well as the sampling time. However, the relative abundance of these enriched bacteria varied under the three different fertilizer regimes. Most of the enriched metabolic pathways stimulated by different fertilizer application were all related to sugars, amino acids fatty acids and alkaloids metabolism. Organic acids and fatty acids were potential metabolites mediating the plant-bacteria interaction in the rhizosphere. Bacteria in the genera Proteiniphilum, Fermentimonas and Pseudomonas in spring, Saccharimonadales and Gaiellales in early summer, Acidobacteriales and Gaiellales in late summer regulated relative contents of organic and fatty acids. Conclusion This study documents the profound changes to the rhizosphere microbiome and bacterially derived metabolites under different fertilizer regimes and provides a conceptual framework towards improving the performance of tea plantations.

The Dark Energy Spectroscopic Instrument (DESI) has embarked on an ambitious five-year survey to explore the nature of dark energy with spectroscopy of 40 million galaxies and quasars. DESI will determine precise redshifts and employ the Baryon Acoustic Oscillation method to measure distances from the nearby universe to z > 3.5, as well as measure the growth of structure and probe potential modifications to general relativity. In this paper we describe the significant instrumentation we developed for the DESI survey. The new instrumentation includes a wide-field, 3.2-deg diameter prime-focus corrector that focuses the light onto 5020 robotic fiber positioners on the 0.812 m diameter, aspheric focal surface. The positioners and their fibers are divided among ten wedge-shaped petals. Each petal is connected to one of ten spectrographs via a contiguous, high-efficiency, nearly 50 m fiber cable bundle. The ten spectrographs each use a pair of dichroics to split the light into three channels that together record the light from 360 - 980 nm with a resolution of 2000 to 5000. We describe the science requirements, technical requirements on the instrumentation, and management of the project. DESI was installed at the 4-m Mayall telescope at Kitt Peak, and we also describe the facility upgrades to prepare for DESI and the installation and functional verification process. DESI has achieved all of its performance goals, and the DESI survey began in May 2021. Some performance highlights include RMS positioner accuracy better than 0.1", SNR per \sqrt{\AA} > 0.5 for a z > 2 quasar with flux 0.28e-17 erg/s/cm^2/A at 380 nm in 4000s, and median SNR = 7 of the [OII] doublet at 8e-17 erg/s/cm^2 in a 1000s exposure for emission line galaxies at z = 1.4 - 1.6. We conclude with highlights from the on-sky validation and commissioning of the instrument, key successes, and lessons learned. (abridged)

The Dark Energy Spectroscopic Instrument (DESI) has embarked on an ambitious five-year survey to explore the nature of dark energy with spectroscopy of 40 million galaxies and quasars. DESI will determine precise redshifts and employ the Baryon Acoustic Oscillation method to measure distances from the nearby universe to z > 3.5, as well as measure the growth of structure and probe potential modifications to general relativity. In this paper we describe the significant instrumentation we developed for the DESI survey. The new instrumentation includes a wide-field, 3.2-deg diameter prime-focus corrector that focuses the light onto 5020 robotic fiber positioners on the 0.812 m diameter, aspheric focal surface. The positioners and their fibers are divided among ten wedge-shaped petals. Each petal is connected to one of ten spectrographs via a contiguous, high-efficiency, nearly 50 m fiber cable bundle. The ten spectrographs each use a pair of dichroics to split the light into three channels that together record the light from 360 - 980 nm with a resolution of 2000 to 5000. We describe the science requirements, technical requirements on the instrumentation, and management of the project. DESI was installed at the 4-m Mayall telescope at Kitt Peak, and we also describe the facility upgrades to prepare for DESI and the installation and functional verification process. DESI has achieved all of its performance goals, and the DESI survey began in May 2021. Some performance highlights include RMS positioner accuracy better than 0.1", SNR per \sqrt{\AA} > 0.5 for a z > 2 quasar with flux 0.28e-17 erg/s/cm^2/A at 380 nm in 4000s, and median SNR = 7 of the [OII] doublet at 8e-17 erg/s/cm^2 in a 1000s exposure for emission line galaxies at z = 1.4 - 1.6. We conclude with highlights from the on-sky validation and commissioning of the instrument, key successes, and lessons learned. (abridged)

The positive aspects of the tea plant/legume intercropping system draw attention to the Chinese tea industry for its benefit for soil fertility improvement with low fertilizer input. However, limited information exists as to the roles of intercropped legumes in the rhizosphere microbiome and tea quality. Hereby, soybean was selected as the intercropped plant to investigate its effect on bacterial communities, nutrient competition, tea plant development, and tea quality. Our data showed that intercropped soybean boosted the uptake of nitrogen in tea plants and enhanced the growth of young tea shoots. Nutrient competition for phosphorus and potassium in soil existed between soybeans and tea plants. Moreover, tea/soybean intercropping improved tea quality, manifested by a significantly increased content of non-ester type catechins (C, EGC, EC), total catechins and theanine, and decreased content of ester type catechins (EGCG). Significant differences in rhizobacterial composition were also observed under different systems. At the genus level, the relative abundance of beneficial bacteria, such as Bradyrhizobium, Saccharimonadales and Mycobacterium, was significantly increased with the intercropping system, while the relative abundance of denitrifying bacteria, Pseudogulbenkiania, was markedly decreased. Correlation analysis showed that Pseudogulbenkiania, SBR1031, and Burkholderiaceae clustered together showing a similar correlation with soil physicochemical and tea quality characteristics; however, other differential bacteria showed the opposite pattern. In conclusion, tea/soybean intercropping improves tea quality and nutrition uptake by increasing the relative abundance of beneficial rhizosphere bacteria and decreasing denitrifying bacteria. This study strengthens our understanding of how intercropping system regulate the soil bacterial community to maintain the health of soils in tea plantations and provides the basis for replacing chemical fertilizers and improvin

This paper explores a novel adaptive optimal control strategy for a class of sophisticated discrete-time nonlinear Markov jump systems (DTNMJSs) via Takagi-Sugeno (T-S) fuzzy models and reinforcement learning (RL) techniques. Firstly, the original nonlinear system model is represented by fuzzy approximation, while the relevant optimal control problem is equivalent to designing fuzzy controllers for linear fuzzy systems with Markov jumping parameters. Subsequently, we derive the fuzzy coupled algebraic Riccati equations (FCAREs) for the fuzzy-based discrete-time linear Markov jump systems by using Hamiltonian-Bellman methods. Following this, an online fuzzy optimization algorithm for DTNMJSs as well as the associated equivalence proof is given. Then, a fully model-free off-policy fuzzy RL algorithm is derived with proved convergence for the DTNMJSs without using the information of system dynamics and transition probability. Finally, two simulation examples respectively related to the single-link robotic arm and the half-car active suspension are given to verify the effectiveness and good performance of the proposed approach.

Aroma substances are the most crucial criteria for the sensory evaluation of tea quality, and also key attractors influencing consumers to make the decision for purchasing tea. Understanding the aromatic properties of tea infusion during different brewing time is crucial to control the tea aromatic quality. Here, headspace and direct immersion solid-phase microextraction (HS-SPME and DI-SPME), coupled with GC-MS, were employed to investigate the impact of brewing time on the changes of the volatile features of green tea infusion. Esters, aldehydes, alcohols, fatty acids, and alkaloids were the predominant volatile groups from tea infusions. Two to three minutes was identified as the best duration for the tea brewing that can maximize the abundance of aromatic chemicals in the headspace emitted from the tea infusions. The variation of the key aromatic contributors between the tea infusion and the headspace over the infusion tended to equilibrate during the tea brewing process. This study provides a theory-based reference method by analyzing the real-time aromatic characteristics in green tea. The optimal time was determined for aromatic quality control, and the complementary relationship between the volatiles in the headspace and its counterpart, tea infusion, was primarily elucidated.

Background The rhizosphere is the narrow zone of soil immediately surrounding the root, and it is a critical hotspot of microbial activity, strongly influencing the physiology and development of plants. For analyzing the relationship between the microbiome and metabolome in the rhizosphere of tea (Camellia sinensis) plants, the bacterial composition and its correlation to soil metabolites were investigated under three different fertilization treatments (unfertilized, urea, cow manure) in different growing seasons (spring, early and late summer). Results The bacterial phyla Proteobacteria, Bacteroidetes, Acidobacteria and Actinobacteria dominated the rhizosphere of tea plants regardless of the sampling time. These indicated that the compositional shift was associated with different fertilizer/manure treatments as well as the sampling time. However, the relative abundance of these enriched bacteria varied under the three different fertilizer regimes. Most of the enriched metabolic pathways stimulated by different fertilizer application were all related to sugars, amino acids fatty acids and alkaloids metabolism. Organic acids and fatty acids were potential metabolites mediating the plant-bacteria interaction in the rhizosphere. Bacteria in the genera Proteiniphilum, Fermentimonas and Pseudomonas in spring, Saccharimonadales and Gaiellales in early summer, Acidobacteriales and Gaiellales in late summer regulated relative contents of organic and fatty acids. Conclusion This study documents the profound changes to the rhizosphere microbiome and bacterially derived metabolites under different fertilizer regimes and provides a conceptual framework towards improving the performance of tea plantations.

The Dark Energy Spectroscopic Instrument (DESI) embarked on an ambitious 5 yr survey in 2021 May to explore the nature of dark energy with spectroscopic measurements of 40 million galaxies and quasars. DESI will determine precise redshifts and employ the baryon acoustic oscillation method to measure distances from the nearby universe to beyond redshift z > 3.5, and employ redshift space distortions to measure the growth of structure and probe potential modifications to general relativity. We describe the significant instrumentation we developed to conduct the DESI survey. This includes: a wide-field, 3.°2 diameter prime-focus corrector; a focal plane system with 5020 fiber positioners on the 0.812 m diameter, aspheric focal surface; 10 continuous, high-efficiency fiber cable bundles that connect the focal plane to the spectrographs; and 10 identical spectrographs. Each spectrograph employs a pair of dichroics to split the light into three channels that together record the light from 360-980 nm with a spectral resolution that ranges from 2000-5000. We describe the science requirements, their connection to the technical requirements, the management of the project, and interfaces between subsystems. DESI was installed at the 4 m Mayall Telescope at Kitt Peak National Observatory and has achieved all of its performance goals. Some performance highlights include an rms positioner accuracy of better than 0.″1 and a median signal-to-noise ratio of 7 of the [O ii] doublet at 8 × 10-17 erg s-1 cm-2 in 1000 s for galaxies at z = 1.4-1.6. We conclude with additional highlights from the on-sky validation and commissioning, key successes, and lessons learned.

Arid degraded soils have a coarse texture and poor organic matter content, which reduces the activity of microorganisms and soil enzymes, and thus the soil quality, plant yield and quality decrease. Potassium solubilizing bacteria (KSB) have been suggested to increase the activity of soil enzymes and increase the release of potassium from natural K-feldspar in the arid degraded soil, and thus potentially reduce the rates of the application of chemical fertilizers. Field studies were conducted for three successive growing seasons in an organic farming system to investigate the effects of K-feldspar and KSB (Bacillus cereus) on K release, soil fertility, and fruit yield of mango plants (Mangifera indica L.). The maximum growth of mango plants was found in the treatments inoculated with KSB. KSB increased soil available N, P, K, and the activity of dehydrogenase and alkaline phosphatase enzymes by 10, 7, 18, 54, and 52%, respectively. KSB increased the fruit yield of mango by 23, 27, and 23% in the first, second, and third growing seasons, respectively. The partial (up to 50%) substitution of chemical K-fertilizer with K-feldspar gave fruit yield and quality very close to that fertilized with the full chemical K-fertilizer. The release rate of K (over all the treatments) varied between 0.18 and 0.64 mg kg−1 of soil per day. KSB significantly increased the K release rate. The application of chemical K-fertilizer gave the highest K release, while substitution with K-feldspar reduced the release of K. Natural K-feldspar contains 8.2% K but is poorly soluble when applied alone. KSB increased the soil quality parameters and enhanced the growth and quality of mango fruit. The fruit yield of mango, under KSB inoculation and fertilization with different K sources, ranged between 9.14 to 17.14 t ha−1. The replacement of 50% of chemical K-fertilizer with natural K-feldspar caused a decrease in the fruit yield by 17, 8, and 2.7% in the first, second, and third years, respectively

The proliferation and differentiation of antigen-specific B cells, including the generation of germinal centers (GC), are prerequisites for long-lasting, antibody-mediated immune protection. Affinity for antigen determines B cell recruitment, proliferation, differentiation, and competitiveness in the response, largely through determining access to T cell help. However, how T cell-derived signals contribute to these outcomes is incompletely understood. Here, we report how the signature cytokine of follicular helper T cells, IL-21, acts as a key regulator of the initial B cell response by accelerating cell cycle progression and the rate of cycle entry, increasing their contribution to the ensuing GC. This effect occurs over a wide range of initial B cell receptor affinities and correlates with elevated AKT and S6 phosphorylation. Moreover, the resultant increased proliferation can explain the IL-21-mediated promotion of plasma cell differentiation. Collectively, our data establish that IL-21 acts from the outset of a T cell-dependent immune response to increase cell cycle progression and fuel cyclic re-entry of B cells, thereby regulating the initial GC size and early plasma cell output.

As promising sufficient sodium-ion reservoirs, layered O3-type binary nickel manganese oxides always suffer from terrible structural instability originating from the extraction and insertion of Na atoms. Constructing P2/O3 biphasic composites have been proved to be an effective way for enhancing the cyclability of layered sodium oxide cathodes, which are usually realized through inactive cations substitution and sodium content regulation. Herein, a novel strategy was developed to construct high concentration P2/O3 intergrowth layered cathodes via manipulating the interlayer interaction. Guided by the DFT calculations, the interval [BO4]3+ electriferous groups are beneficial to modulating the interlayer configuration, enhancing the oxygen stability and structural stability of layered oxide cathode. The high sodium-content P2/O3 composite exhibits a superior reversible capacity (159.1 mAh g−1 at 0.2 C, 1 C = 200 mA g−1), distinctive rate capability (75.3 mAh g−1 at 5 C) and excellent cycling stability with a capacity retention of 74.1% after 300 cycles at 1 C within wide potential range of 2.0–4.2 V. The results highlight that the synergetic effect of sufficient-sodium P2/O3 hybrid structure induced by manipulating the interlayer interaction is an effective strategy for achieving electrochemically stable layered cathode material for sodium-ion batteries.

Cement stabilized soil (CSS) yields wide application as a routine cementitious material due to cost-effectiveness. However, the mechanical strength of CSS impedes development. This research assesses the feasible combined enhancement of unconfined compressive strength (UCS) and flexural strength (FS) of construction and demolition (C&D) waste, polypropylene fiber, and sodium sulfate. Moreover, machine learning (ML) techniques including Back Propagation Neural Network (BPNN) and Random Forest (FR) were applied to estimate UCS and FS based on the comprehensive dataset. The laboratory tests were conducted at 7-, 14-, and 28-day curing age, indicating the positive effect of cement, C&D waste, and sodium sulfate. The improvement caused by polypropylene fiber on FS was also evaluated from the 81 experimental results. In addition, the beetle antennae search (BAS) approach and 10-fold cross-validation were employed to automatically tune the hyperparameters, avoiding tedious effort. The consequent correlation coefficients (R) ranged from 0.9295 to 0.9717 for BPNN, and 0.9262 to 0.9877 for RF, respectively, indicating the accuracy and reliability of the prediction. K-Nearest Neighbor (KNN), logistic regression (LR), and multiple linear regression (MLR) were conducted to validate the BPNN and RF algorithms. Furthermore, box and Taylor diagrams proved the BAS-BPNN and BAS-RF as the best-performed model for UCS and FS prediction, respectively. The optimal mixture design was proposed as 30% cement, 20% C&D waste, 4% fiber, and 0.8% sodium sulfate based on the importance score for each variable.

The aim of this paper is to characterize the impact of non-orthogonal multiple access (NOMA) on the age of information (AoI) of grant-free transmission. In particular, a low-complexity form of NOMA, termed NOMA-assisted random access, is applied to grant-free transmission in order to illustrate the two benefits of NOMA for AoI reduction, namely increasing channel access and reducing user collisions. Closed-form analytical expressions for the AoI achieved by NOMA assisted grant-free transmission are obtained, and asymptotic studies are carried out to demonstrate that the use of the simplest form of NOMA is already sufficient to reduce the AoI of orthogonal multiple access (OMA) by more than 40%. In addition, the developed analytical expressions are also shown to be useful for optimizing the users' transmission attempt probabilities, which are key parameters for grant-free transmission.

In group decision making (GDM), opinion dynamics is a useful tool to investigate consensus formation. Notably, consensus convergence speed is of key importance to manage the consensus formation in GDM with opinion dynamics. Recently, social network DeGroot (SNDG) model has been widely used in opinion dynamics. Based on this, this article dedicates to study how agents’ high self-confidence levels affect the consensus convergence speed in SNDG model. Interestingly, using theoretical analysis, we prove that: 1) the speed of consensus reaching is subject to the largest self-confidence level of opinion followers and 2) the speed of consensus reaching is also subject to the top two self-confidence levels of opinion leaders. Furthermore, through extensive simulation’, we find that the theoretical results are robust to the topological structure and the size of social networks.

In this paper, lag projective synchronization of nonidentical fractional delayed memristive neural networks (NFDMNN) is investigated. Due to the existence of memristor, the analysis is based on the theory of differential equations with discontinuous right-hand side proposed by Filippov. A novel controller with fractional integral sliding-mode surface is devised firstly. Successively, some sufficient criteria ensuring lag projective synchronization of NFDMNN are obtained, depending on the fractional calculus inequalities and Lyapunov direct method. Moreover, the related results improve and enrich previous synchronization works. Lastly, the validity of conclusions is verified through a simulation example.

In this paper, the problem of making a safe compliant contact between a human and an assistive robot is considered. Users with disabilities have a need to utilize their assistive robots for physical human-robot interaction (PHRI) during certain activities of daily living (ADLs). Specifically, we propose a hybrid force/velocity/attitude control for a PHRI system based on measurements from a 6-axis force/torque sensor mounted on the robot wrist. While automatically aligning the end-effector surface with the unknown environmental (human) surface, a desired commanded force is applied in the normal direction while following desired velocity commands in the tangential directions. A Lyapunov based stability analysis is provided to prove both convergence as well as passivity of the interaction to ensure both performance and safety. Simulation as well as experimental results verify the performance and robustness of the proposed hybrid controller in the presence of dynamic uncertainties as well as safe physical human-robot interactions for a kinematically redundant robotic manipulator., Comment: 14 pages, 31 figures, 1 Table, Submitted to IEEE TCST for Review

The Dark Energy Spectroscopic Instrument (DESI) has embarked on an ambitious five-year survey to explore the nature of dark energy with spectroscopy of 40 million galaxies and quasars. DESI will determine precise redshifts and employ the Baryon Acoustic Oscillation method to measure distances from the nearby universe to z > 3.5, as well as measure the growth of structure and probe potential modifications to general relativity. In this paper we describe the significant instrumentation we developed for the DESI survey. The new instrumentation includes a wide-field, 3.2-deg diameter prime-focus corrector that focuses the light onto 5020 robotic fiber positioners on the 0.812 m diameter, aspheric focal surface. The positioners and their fibers are divided among ten wedge-shaped petals. Each petal is connected to one of ten spectrographs via a contiguous, high-efficiency, nearly 50 m fiber cable bundle. The ten spectrographs each use a pair of dichroics to split the light into three channels that together record the light from 360 - 980 nm with a resolution of 2000 to 5000. We describe the science requirements, technical requirements on the instrumentation, and management of the project. DESI was installed at the 4-m Mayall telescope at Kitt Peak, and we also describe the facility upgrades to prepare for DESI and the installation and functional verification process. DESI has achieved all of its performance goals, and the DESI survey began in May 2021. Some performance highlights include RMS positioner accuracy better than 0.1", SNR per \sqrt{\AA} > 0.5 for a z > 2 quasar with flux 0.28e-17 erg/s/cm^2/A at 380 nm in 4000s, and median SNR = 7 of the [OII] doublet at 8e-17 erg/s/cm^2 in a 1000s exposure for emission line galaxies at z = 1.4 - 1.6. We conclude with highlights from the on-sky validation and commissioning of the instrument, key successes, and lessons learned. (abridged), Comment: 78 pages, 32 figures, submitted to AJ

Traditionally, the supplement of organic manure in tea plantations has been a common approach to improving soil fertility and promoting terroir compounds, as manifested by the coordinated increase in yield and quality for the resulting teas. However, information regarding the effect of organic manure in the metabolome of tea plants is still inadequate. The metabolite profiles of tea shoots applied with cow manure, urea or no fertilizer were studied using gas chromatography–mass spectrometry (GC–MS). In total, 73 metabolites were detected, and the modulated metabolites included mainly amino acids, organic acids and fatty acids. In particular, glutamine, quinic acid and proline accumulated more in tea shoots in soils treated with cow manure, but octadecanoic acid, hexadecanoic acid and eicosanoic acid were drastically reduced. Pearson correlation analysis indicated that organic acids and amino acids in tea shoots were the two major metabolite groups among the three treatments. The analysis of metabolic pathways demonstrated that the cow manure treatment significantly changed the enrichment of pathways related to amino acids, sugars and fatty acids. Sensory evaluation showed that the quality of green teas was higher when the plants used to make the tea were grown in soil treated with cow manure rather than urea during spring and late summer. The results indicated that the application of cow manure in soils changed the metabolic characteristics of tea shoots and improved the qualities of the resulting teas.

We use femtosecond extreme ultraviolet pulses derived from a free electron laser to excite and probe surface acoustic waves (SAWs) on the (001) surface of single crystal SrTiO3. SAWs are generated by a pair of 39.9 nm pulses crossed at the sample with the crossing angle defining the SAW wavelength at 84 nm. Detection of SAWs is performed via diffraction of a time-delayed 13.3 nm probe pulse by SAW-induced surface ripples. Despite the low reflectivity of the sample in the extreme ultraviolet range, the reflection mode detection is found to be efficient because of an increase in the diffraction efficiency for shorter wavelengths. We describe a methodology for extracting the SAW attenuation in the presence of a thermal grating, which is based on measuring the decay of oscillations at twice the SAW frequency. The proposed approach can be used to study ultrahigh frequency SAWs in a broad range of materials and will bridge the wave vector gap in surface phonon spectroscopy between Brillouin scattering and He atom scattering.

© 2020 Elsevier B.V. The interest on developing nickel sulfide based dual-role anode materials for both lithium-ion battery (LIBs) and sodium-ion battery (SIBs) has aroused broad attention. However, increasing their lithium and sodium storage performances necessitates smart structure design and fabrication. Herein, we demonstrate a facile strategy for the rational combination of NiS1.03 nanoparticles with sulfur doped reduced graphene oxide (NiS1.03/S-rGO), with the designed structure of ultrafine NiS1.03 nanoparticles uniformly anchored on or even wrapped in S-rGO. The systematic electrochemical studies demonstrate that the NiS1.03/S-rGO exhibits high reversible capacities of 996.1 mAh g−1 after 100 cycles at 0.1 A g−1 and 337.8 mAh g−1 up to 2000 cycles at 4 A g−1 as an anode material for LIBs. As for SIBs, the NiS1.03/S-rGO also displays high reversible capacities of 345.6 mAh g−1 at 0.1 A g−1 after 100 cycles and 242.1 mAh g−1 at 0.5 A g−1 after 200 cycles. Additionally, detailed structure analysis illustrates that the superior electrochemical performances mainly originate from the robust composite architecture where the NiS1.03 nanoparticles and S-rGO are tightly bridged via the doped sulfur atoms at the hetero-interface through a synergistic coupling effect, simultaneously guaranteeing the electrode integrity and fast diffusion kinetics. More importantly, the combination approach and mechanism understanding at the molecular level presented in this study show good promise on transition oxides/sulfides for high-performance alkali metal ion battery.

© 2020 The Authors. Journal of Orthopaedic Research® published by Wiley Periodicals LLC on behalf of Orthopaedic Research Society High functioning military transtibial amputees (TTAs) with well-fitted state of the art prosthetics have gait that is indistinguishable from healthy individuals, yet they are more likely to develop knee osteoarthritis (OA) of their intact limbs. This contrasts with the information at the knees of the amputated limbs that have been shown to be at a significantly reduced risk of pain and OA. The hypothesis of this study is that biomechanics can explain the difference in knee OA risk. Eleven military unilateral TTAs and eleven matched healthy controls underwent gait analysis. Muscle forces and joint contact forces at the knee were quantified using musculoskeletal modeling, validated using electromyography measurements. Peak knee contact forces for the intact limbs on both the medial and lateral compartments were significantly greater than the healthy controls (P ≤.006). Additionally, the intact limbs had greater peak semimembranosus (P =.001) and gastrocnemius (P ≤.001) muscle forces compared to the controls. This study has for the first time provided robust evidence of increased force on the non-affected knees of high functioning TTAs that supports the mechanically based hypothesis to explain the documented higher risk of knee OA in this patient group. The results suggest several protentional strategies to mitigate knee OA of the intact limbs, which may include the improvements of the prosthetic foot control, socket design, and strengthening of the amputated muscles.

We use femtosecond extreme ultraviolet pulses derived from a free electron laser to excite and probe surface acoustic waves (SAWs) on the (001) surface of single crystal SrTiO3. SAWs are generated by a pair of 39.9 nm pulses crossed at the sample with the crossing angle defining the SAW wavelength at 84 nm. Detection of SAWs is performed via diffraction of a time-delayed 13.3 nm probe pulse by SAW-induced surface ripples. Despite the low reflectivity of the sample in the extreme ultraviolet range, the reflection mode detection is found to be efficient because of an increase in the diffraction efficiency for shorter wavelengths. We describe a methodology for extracting the SAW attenuation in the presence of a thermal grating, which is based on measuring the decay of oscillations at twice the SAW frequency. The proposed approach can be used to study ultrahigh frequency SAWs in a broad range of materials and will bridge the wave vector gap in surface phonon spectroscopy between Brillouin scattering and He atom scattering.

Nitrogen and sulfur co-doping is emerging as a promising approach to prominently improve the sodium storage performance of carbonaceous materials. However, poisonous chemicals and rigorous conditions are normally involved in their preparation, especially in the sulfidation process. Therefore, developing novel, facile and eco-friendly approaches to construct nitrogen and sulfur co-doped carbon (NSC) is still challenging. In this work, a facile self-templating synthesis method is reported to allow the simple and green preparation of NSC. Particularly, small-molecule dithiooxamide can be directly converted to NSC through a facile thermal condensation process, serving as precursor, template, and self-doping agent simultaneously. In account of its high ionic and electronic conductivity, increased interlayer spacing, unique layers assembled structure and efficient N, S co-doping, the NSC obtained at 800 °C exhibits excellent sodium storage performances, including prominent reversible capacity (316.1 mAh g−1 at 0.1 A g−1 up to 100 cycles), remarkable rate capability (178.3 mAh g−1 at 3 A g−1), and robust stability upon long-term cycling (213.6 mAh g−1 at 1 A g−1 up to 2000 cycles), rendering itself to be a promising candidate for practical sodium-ion battery.

© 2020, The Author(s). The fifth generation (5G) wireless communication networks are being deployed worldwide from 2020 and more capabilities are in the process of being standardized, such as mass connectivity, ultra-reliability, and guaranteed low latency. However, 5G will not meet all requirements of the future in 2030 and beyond, and sixth generation (6G) wireless communication networks are expected to provide global coverage, enhanced spectral/energy/cost efficiency, better intelligence level and security, etc. To meet these requirements, 6G networks will rely on new enabling technologies, i.e., air interface and transmission technologies and novel network architecture, such as waveform design, multiple access, channel coding schemes, multi-antenna technologies, network slicing, cell-free architecture, and cloud/fog/edge computing. Our vision on 6G is that it will have four new paradigm shifts. First, to satisfy the requirement of global coverage, 6G will not be limited to terrestrial communication networks, which will need to be complemented with non-terrestrial networks such as satellite and unmanned aerial vehicle (UAV) communication networks, thus achieving a space-air-ground-sea integrated communication network. Second, all spectra will be fully explored to further increase data rates and connection density, including the sub-6 GHz, millimeter wave (mmWave), terahertz (THz), and optical frequency bands. Third, facing the big datasets generated by the use of extremely heterogeneous networks, diverse communication scenarios, large numbers of antennas, wide bandwidths, and new service requirements, 6G networks will enable a new range of smart applications with the aid of artificial intelligence (AI) and big data technologies. Fourth, network security will have to be strengthened when developing 6G networks. This article provides a comprehensive survey of recent advances and future trends in these four aspects. Clearly, 6G with additional technical requirements