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Crystalline materials have shaken their traditionally inflexible reputation and show the ability in response to external stimuli by macroscopic dynamic effects such as mechanical deformations or motions. Recently, the hybrid strategy has been proposed in Zhang’s group to design and prepare multifunctional flexible crystalline materials by integrating flexible crystals with functional materials (responsive polymers and/or other components with special functions), which expands the range of available stimuli and opens up a broad prospect for the practical application of flexible crystals in the fields of flexible optoelectronics, bionics, and intelligence.

This letter devises a physics-informed neural hierarchical control for uncertain networked microgrids (NMs) to provide certificated safe and stable control of NMs undergoing disturbances and uncertain perturbations. The main contributions include 1) a learning-based hierarchical control framework for inverter-based resources (IBRs) in NMs under unprecedented uncertainties of renewable energies; 2) a robust control Lyapunov barrier function (rCLBF) to provide provable safety and stability guarantees under uncertain scenarios; 3) an rCLBF-based, physics-informed learning scheme to simultaneously discover the certificates and control policy with explicit safety, stability, and robustness guarantees, enabling certified generalization beyond nominal operating scenarios. The efficacy of the rCLBF-based neural hierarchical control is thoroughly validated in different NMs cases.

Deep-learning (DL)-based methods have been shown to be effective on the hyperspectral image (HSI) anomaly detection task because of their feature extraction ability. However, current DL-based methods lack an effective means of regularizing the background information. In this article, the hyperbolic space-based autoencoder (HSAE) is proposed for the hyperspectral anomaly detection task. We assume that an effective hierarchical structural representation can better model the HSI in the spatial domain, and this enables the background information to be effectively regularized. Motivated by this idea, the HSAE embeds the HSI into hyperbolic space, which is a non-Euclidean geometry with a constant negative curvature and an exponential growth distance between points. Using a wrapped normal prior distribution, the training of the hidden representation is supervised to preserve more hierarchical features. After the training process, a hyperbolic distance-based anomaly detector (HDB) is introduced to discover anomalies in a more robust way. Experimental results on several popular HSI benchmarks fully demonstrate the superiority of our HSAE.

Low-light raw image denoising is an essential task in computational photography, to which the learning-based method has become the mainstream solution. The standard paradigm of the learning-based method is to learn the mapping between the paired real data, i.e., the low-light noisy image and its clean counterpart. However, the limited data volume, complicated noise model, and underdeveloped data quality have constituted the learnability bottleneck of the data mapping between paired real data, which limits the performance of the learning-based method. To break through the bottleneck, we introduce a learnability enhancement strategy for low-light raw image denoising by reforming paired real data according to noise modeling. Our learnability enhancement strategy integrates three efficient methods: shot noise augmentation (SNA), dark shading correction (DSC) and a developed image acquisition protocol. Specifically, SNA promotes the precision of data mapping by increasing the data volume of paired real data, DSC promotes the accuracy of data mapping by reducing the noise complexity, and the developed image acquisition protocol promotes the reliability of data mapping by improving the data quality of paired real data. Meanwhile, based on the developed image acquisition protocol, we build a new dataset for low-light raw image denoising. Experiments on public datasets and our dataset demonstrate the superiority of the learnability enhancement strategy.

New energy is considered to be an indispensable means to significantly reduce carbon emissions and to achieve the temperature-control goals defined by the Paris Climate Accord. Despite the bright future, the inherent characteristics, including volatility, intermittency and uneven seasonal and geographical distributions, and the rapid growth of installations make it increasingly difficult to connect green electricity to grids. This becomes a dominating bottleneck for the low-carbon transition of China Energy Group (CE). This paper aims to help with the implementation of the new-energy development plan and to define the low-carbon energy-transition path for CE. Based on the current industry structure of CE, Shenhua Engineering Technology Co., Ltd proposes the concept of an ‘integrated energy corridor’. The integrated energy corridor represents a comprehensive energy-transmission channel with coal, green electricity, green hydrogen, green oxygen and other green energy products such as transmission media, railways, pipelines and power grids as transmission means and thermal power, coal chemical plants, cities, etc. along the route as new-energy consumers and regulators. The integrated energy corridor can support the rapid development of new-energy assets and the low-carbon transition of CE.An ‘integrated energy corridor’ is proposed in China as a comprehensive energy-transmission channel with coal, green electricity, green hydrogen, green oxygen and other green energy products. The integrated energy corridor can support the rapid development of new-energy assets and the low-carbon transition.Graphical Abstract

An integrative power flow approach is established for networked microgrids. Our new contributions include: 1) A distributed augmented power flow (APF) algorithm for networked microgrids is devised to incorporate hierarchical control effects in/among microgrids; 2) Based upon APF, an enhanced distributed continuation power flow (CPF$^+$) algorithm is established to explore operating regions of droop coefficients and power interchanges for static voltage stability assessment; and 3) A programmable distributed platform is designed to coordinate power interchanges and support plug-and-play while protecting local customers’ privacy. RTDS experiments validate the high fidelity of APF, while its scalability and convergence performance are verified on medium and large networked microgrids. Extensive tests demonstrate the effectiveness of CPF$^+$ in quantifying secure operation regions of networked microgrids.

Quantum networks are considered to be the future of secure communication in the coming quantum era. However, significant efforts are lacking on developing practical quantum networks for power grids. This paper establishes a quantum network-based power grid (QNetGrid) framework and develops a real-time, reliable, flexible, programmable, and cost-effective QNetGrid software testbed containing repeater-based quantum communication, quantum routing, real software-defined networking (SDN) switches, and real-time networked microgrids (NMs) operations. It makes the following contributions: 1) a repeater and routing based quantum network simulator (QNSim) is developed, 2) repeaters with and without quantum memories are respectively simulated in QNSim, 3) different routing scenarios in QNetGrid are investigated, 4) a real-time QNetGrid software testbed is built in RTDS incorporating QNSim and real SDN switches, and 5) various test cases are designed, and experimental results produced with the QNetGrid testbed provide valuable insights for building quantum networks in power grids.

To analyze and summarize the experience of single-port robotic-assisted laparoscopic ambulatory surgery (AS) for intraligamental myomectomy.

With the rapid development of the Internet of Things, a large number of mobile devices participate in the perception and aggregation of data, outsourcing and storing massive data on various cloud platforms. Thus, a new data perception and privacy protection model based on mobile group intelligence perception and cloud computing is required. The existing work on data security and privacy protection mainly focuses on the independent link of data collection, aggregation, and services, which lacks holistic consideration for the different service requirements. To end this issue, this article comprehensively integrates the security and privacy protection requirements of various stages in the mobile group intelligence perception for data collection, aggregation, and service from a global perspective. Aiming at data privacy and security issues in the existing mobile group intelligence perception system, and the difficulty in guaranteeing the quantity and quality of data at the same time, a mobile group intelligence perception mechanism oriented to user privacy and data security is proposed. This mechanism uses deep learning as its core algorithm to handle big data cases. It can provide authenticity and reliability guarantees for the subsequent data application on the premise of protecting user privacy. Experimental results prove that the mechanism proposed in this article meets the security requirements, and its user-end computing overhead is small.

This perspective lays out a framework to enable the breeding of crops that can meet worldwide demand under the challenges of global climate change. Past work in various fields has produced multiple prediction methods to contribute to different plant breeding objectives. Our proposed framework focuses on the integration of these methods into decision-support tools that quantify the effects on multiple objectives of decisions made throughout the plant breeding pipeline. We discuss the complementarities among these methods with an emphasis on integration into tools that utilize operations research and systems approaches to help plant breeders rapidly and optimally design new cultivars under extant time, cost, and environmental constraints. In illustrating this potential, we demonstrate the interconnectedness and probabilistic nature of plant breeding objectives and highlight research opportunities to refine and combine knowledge across multiple disciplines. Such a framework can help plant breeders more efficiently breed for future environments, including so-called minor crops, leading to an overall increase in the resiliency of global food production systems.

With the development of Unmanned Aerial Vehicle (UAV) system autonomy, network communication technology and group intelligence theory, mission execution in the form of a UAV swarm will be an important realization of future applications. Traditional single-UAV mission reliability modeling methods have been unable to meet the requirements of UAV swarm mission reliability modeling. Therefore, the UAV swarm mission reliability modeling and evaluation method is proposed. First, aimed at the interdependence among the multiple layers, a multi-layer network model of a UAV swarm is established. At the same time, based on the system having the following characteristics—using a mission chain to complete the mission and applying the connectivity of the mission network—the mission network model of a UAV swarm is established. Second, vulnerability and connectivity are selected as two indicators to reflect the reliability of the mission, and aimed at random attack and deliberate attack, vulnerability and connectivity evaluation methods are proposed. Finally, the validity and accuracy of the constructed model are verified through simulations, and the model and selected indicators can meet the reliability requirements of the UAV swarm mission. In this way, this study provides quantitative reference for UAV-swarm-related decision-making work and supports the development of UAV-swarm-related work.

Multifunctional porous organic polymers (POPs) are excellent porous materials for CO2capture and Hg2+adsorption. Especially, plentiful ultramicropores (d< 0.7 nm) and a high nitrogen (N) content are beneficial for CO2capture, and the micropores and the specific functional groups are helpful for Hg2+adsorption, while the facile construction of the multifunctional POPs still remains a challenge. Herein, a series of bifunctional POPs was simply fabricated from the ketone-based polymers on the basis of the postfunctionalization. Because of their low Brunauer–Emmett–Teller (BET) surface area (SBET) and pore volume (Vtotal), the polymers were further carried out the Schiff-based reaction using melamine (MA) as the postmodifier. As the rigid external cross-linker, MA embedded in the pores of the polymers and supported the skeleton of the polymers. The resulting polymers showed a sharp increase of the SBET(up to 703 m2/g) and Vtotal(up to 0.657 cm3/g), high N content (up to 36.95 wt %), and three-dimensional hierarchical porosity. In particular, the high ultramicropore volume (up to 0.199 cm3/g) of the resulting polymers made them effective for CO2capture (193 mg/g; 273 K and 1 bar). The high micropore volume (up to 0.272 cm3/g) and abundant N (up to 36.95 wt %) offered them high Hg2+capacity (425 mg/g at 298 K). This facile postfunctionalization strategy is potentially useful for the fabrication of some other multifunctional POPs.

Melamine-based porous organic polymers (POPs) are promising for gas uptake and water treatment because of their unique and tunable porosity, high nitrogen (N) content, and high Brunauer–Emmett–Teller (BET) surface area (SBET). However, it is difficult to construct ketone-based POPs by the Friedel–Crafts acylation reaction. Herein, the ketone-based POPs were postfunctionalized with melamine (MA) by the Schiff-based reaction and the rigid triazine rings of MA were embedded in the polymer chains as rigid cross-linkers, resulting in the polymers with high SBET(555 m2·g–1) and total pore volume (0.72 cm3·g–1). Moreover, plentiful imine, amino, and triazine functionalities were inserted in the polymers, providing the polymers with high N content of 41.83 wt %. The resulting polymers were promising for CO2capture (145 mg·g–1; 273 K, 1.0 bar) and Hg2+removal (372 mg·g–1). This study offers a universal strategy to construct melamine-based POPs from various ketone-functionalized HCPs via a simple postfunctionalization.

Butanol is an attractive second-generation biofuel as well as an important chemical. Production of butanol from lignocellulosic feedstock via consolidated bioprocessing has attracted increasing interest in recent years. However, this has been limited by the inefficient degradation of extracellular polysaccharides in butanol-producing strains. In this study, production of butanol directly from hemicellulose was achieved simply through overexpression of an indigenous xylanase in Clostridium acetobutylicum. The xylanase (XynB) encoded by CA_P0053 was highly soluble and fully secreted from C. acetobutylicum. The extracellular xylanase activity was increased 88-fold, and 4.03 g/L biobutanol was obtained from hemicellulose, which has been the highest yield yet reported from either hemicellulose or xylan. This study proved that the solventogenic C. acetobutylicumhad great potential for consolidated production of biofuels. Understanding and applying its secretion mechanism will be of great significance in the future.

N-containing porous organic polymers and derived porous carbons are promising for CO2capture, while their simple fabrication still remains a challenge. Herein, the porphyrin-based triazine polymers were simply constructed from tetraphenylporphyrin and cyanuric chloride according to one-pot Scholl coupling reaction and Friedel–Crafts reaction. The as-fabricated polymers had the maximum CO2uptake of 173 mg/g and high CO2/N2selectivity (IAST: 59.35) at 273 K and 1.0 bar. After KOH-activated carbonization, the Brunauer–Emmett–Teller surface area (1004–3238 m2/g), micropore area (798–1434 m2/g), pore volume (0.54–1.76 cm3/g), micropore volume (0.41–1.02 cm3/g), and ultra-micropore volume (up to 0.29 cm3/g) were significantly improved, indicative of their outstanding CO2uptakes (171–282 mg/g). The ultramicropore volume with a pore size of less than 1.2 nm and N content were proven to be the vital factors for CO2capture. The synthetic strategy provides a simple and effective approach for the synthesis of the porphyrin-based triazine polymers, and the derived porous carbons were efficient for CO2capture.

Genomic selection is a technique that breeders use to select plant or animal individuals to mate and produce new generations of species. The conventional selection method is to select individuals that are either observed or predicted to be the best based on the assumption that parents with better phenotypes will produce better offspring. A major limitation of this method is its focus on the short‐term genetic gains at the cost of genetic diversity and long‐term growth potential. Recently, several new genomic selection methods were proposed to maximize the long‐term potential. Along this research direction, we propose a new method, the complementarity‐based selection strategy (CBS), to improve the tradeoff between short‐term genetic gain and long‐term potential. This approach is inspired by the genetic compatibility mate‐choice mechanism in animals. Our selection method selects the individual with the highest genomic estimated breeding value to emphasize short‐term achievement and then pairs it with the individual that is the most complementary to the one with highest genomic estimated breeding value to emphasize the long‐term growth potential. The CBS method allows favorable alleles to be accounted for within the selection and more of them to be included. We present simulation results that compare the performance of the new method against the state‐of‐the‐art methods in the literature and show that the CBS approach has a great potential to further improve long‐term response in genomic selection.

Unmanned Aerial Vehicle (UAV) swarms have been foreseen to play an important role in military applications in the future, wherein they will be frequently subjected to different disturbances and destructions such as attacks and equipment faults. Therefore, a sophisticated robustness evaluation mechanism is of considerable importance for the reliable functioning of the UAV swarms. However, their complex characteristics and irregular dynamic evolution make them extremely challenging and uncertain to evaluate the robustness of such a system. In this paper, a complex network theory-based robustness evaluation method for a UAV swarming system is proposed. This method takes into account the dynamic evolution of UAV swarms, including dynamic reconfiguration and information correlation. The paper analyzes and models the aforementioned dynamic evolution and establishes a comprehensive robustness metric and two evaluation strategies. The robustness evaluation method and algorithms considering dynamic reconfiguration and information correlation are developed. Finally, the validity of the proposed method is verified by conducting a case study analysis. The results can further provide some guidance and reference for the robust design, mission planning and decision-making of UAV swarms.

The ground‐source heat pump heating and cooling system is currently the most important development and utilization method of shallow geothermal resources, but its key component is the ground heat exchanger system. Herein, a new type of ground heat exchanger, the soil‐cement energy pile, is proposed. The similarity model comparison experiments of the soil‐cement energy piles and the soil energy pile in summer and winter were conducted respectively, and the 3D numerical models of heat transfer of the two kinds of energy piles are established, their related thermal properties are verified. Then the heat transfer calculation methods of the soil‐cement energy pile are presented and validated. The research has shown that the soil‐cement energy pile has good thermodynamic performance, which effectively reduces the largest thermal resistance in the heat transfer system of the energy pile, the thermal resistance of pile body material, and the heat transfer per linear meter of the soil‐cement energy pile is 21.20%–55.60% higher than that of the soil energy pile. The soil‐cement energy pile is of great significance to improve the thermal efficiency of the ground‐source heat pump system and can reduces the overall project cost. The soil‐cement energy pile is a new type of ground heat exchanger, which has good thermodynamic performance and effectively reduces the largest thermal resistance in the heat transfer system of the ground‐source heat pump heating or cooling. The heat transfer per linear meter of the soil‐cement energy pile is 21.20–55.60% higher than that of the soil energy pile.

This study was to determine differences in the global metabolic profiles of serum and urine of Xuanhan yellow cattle, Simmental crossbred cattle (Simmental × Xuanhan yellow cattle), and cattle-yaks (Jersey × Maiwa yak) under heat stress (temperature–humidity index remained above 80 for 1 week). A total of 55 different metabolites associated with the three breeds were identified in the serum and urine samples by gas chromatography–mass spectrometry. The metabolic adaptations to heat stress are heterogeneous. Cattle-yaks mobilize a greater amount of body protein to release glucogenic amino acids to supply energy, whereas the tricarboxylic acid cycle is inhibited. Simmental crossbred cattle mobilize a greater amount of body fat to use free fatty acids as an energy source. In comparison with Simmental crossbred cattle and cattle-yaks, Xuanhan yellow cattle have higher glycolytic activity and possess a stronger antioxidant defense system and are, in conclusion, more adapted to hot and humid environments.

Specific imaging of cancer cells has been well-accepted in cancer diagnosis although it cannot precisely mark the boundary between the normal and cancerous cells and report their mutual influence. We report a nanorod fluorescent probe of copper perylenetetracarbonate (PTC-Cu) that can specifically light up normal cells. In combination with cancer cell imaging, the cocultured normal and cancer cells can be lit up with different colors, offering a clear contrast between the normal and cancer cells when they coexist. Because cancerous cells are only 20–30% in cancer area, this provides a possibility to visibly detect the mutual influence between the cancer and normal cells during therapy. We expect this method is beneficial to better cancer diagnosis and therapy.

Printable hydrogels desired in bioengineering have extremely high demands on biocompatibility and mechanic strength, which can hardly be achieved in conventional hydrogels made with biopolymers. Here, we show that on employment of the strategy of coordination-triggered hierarchical self-assembly of naturally occurring small-molecule folic acid, supramolecular hydrogels with robust mechanical elastic modulus comparable to synthetic double-network polymer gels can be made at concentrations below 1%. A sequence of hierarchical steps are involved in the formation of this extraordinary hydrogel: petrin rings on folate form tetramers through hydrogen bonding, tetramers stack into nanofibers by π–π stacking, and zinc ions cross-link the nanofibers into larger-scale fibrils and further cross-link the fibril network to gel water. These supramolecular qualities endow the hydrogel with shear-thinning and instant healing ability, which makes the robust gel injectable and printable into various three-dimensional structures. Owing to the excellent biocompatibility, the gel can support cells three-dimensionally and can be used as an ideal carrier for imaging agent (Gd3+), as well as chemodrugs. In combination with its easy formation and abundant sources, this newly discovered metallo-folate supramolecular hydrogel is promising in various bioengineering technological applications.

Three submerged macrophytes, Hydrilla verticillata, Vallisneria natans,and Potamogeton crispus, were planted in winter and spring to investigate the environmental mechanism of phosphorus transformation during submerged macrophyte growth periods. The experimental buckets each contained 4,832.80 g of dry sediment (depth: 10 cm) and 100 L water. The phosphorus (P) fractions in the water and sediment were investigated along with the environmental factors, including pH, dissolved oxygen (DO), and redox potential (ORP). The concentrations of the different forms of P in the water and sediment were lower in the submerged macrophyte groups. Submerged macrophyte uptake was the primary reason for the decrease in P in the water and sediment. At the end of the experiment, the total amounts of phosphorus accumulated by H. verticillata, V. natans, and P. crispuswere 156.05 g, 282.24 g, and 115.84 g, respectively, and the three submerged macrophytes enriched P by 4.18%, 7.56%, and 3.10%. The levels of the environmental factors pH, DO, and ORP were higher in the submerged macrophyte groups than the control groups. The environmental factors had different effects on the different forms of P during growth of the submerged macrophytes. H. verticillataprimarily acted on the soluble reactive phosphorus (SRP) through environmental factors, while P. crispusacted on the dissolved total phosphorous, SRP, dissolved organic phosphorus, and particulate phosphorous through these factors. V. natanshad a weak impact on P content in the water through the environmental factors. Hence, the transformation of P between the sediment and water was affected by environmental factors. Overall, the results of this study reveal the effects of environmental factors under submerged macrophyte growth on water purification as well as the migration and transformation of P in the sediment and on the surface and provide a theoretical basis for the ecological restoration of eutrophicated shallow lakes.

•A bionic spider web microchannel structure design method was proposed.•Structural parameters and flow parameters was investigated.•Parameter coupling characteristics were analyzed and fitting equation was obtained.

A failure criterion fully considering the anisotropy and hydration of shale is essential for shale formation stability evaluation. Thus, a novel failure criterion for hydration shale is developed by using Jaeger’s shear failure criterion to describe the anisotropy and using the shear strength reduction caused by clay minerals hydration to evaluate the hydration. This failure criterion is defined with four parameters in Jaeger’s shear failure criterion (S1, S2, αand φ), three hydration parameters (k, ωshand σs) and two material size parameters (dand l0). The physical meanings and determining procedures of these parameters are described. The accuracy and applicability of this failure criterion are examined using the published experimental data, showing a cohesive agreement between the predicted values and the testing results, R2 = 0.916 and AAREP (average absolute relative error percentage) of 9.260%. The error (|Dp|) is then discussed considering the effects of β(angle between bedding plane versus axial loading), moisture content and confining pressure, presenting that |Dp| increases when βis closer to 30°, and |Dp| decreases with decreasing moisture content and with increasing confining pressure. Moreover, |Dp| is demonstrated as being sensitive to S1and being steady with decrease in the data set when βis 0°, 30°, 45° and 90°.

Lignosulfonate, as the large-scale by-products from the sulfite pulping, converting them to porous carbon is an alternative potential path. However, most sodium lignosulfonate (LS-Na) derived porous carbon all belonged to the dominated microporous carbon materials, and had poor graphitization degree and low heteroatoms content. Here, a series of hierarchically porous carbon with rich and controllable mesopores were firstly prepared from LS-Na by two dual template strategies. These carbon materials showed high Brunauer-Emmett-Teller (BET) surface areas (SBET) of 230.6–1483.3 m2/g, hierarchical porous structure (mesopore content up to 84.5%), rich heteroatoms (N, O, S) doping (9.22–22.53%), and good graphitization structure. The incorporation of SBA-15 and Ni species as the nano-templates not only brought the unique micro-structure, but also enhanced mesoporous properties. SLS-C had the largest CO2uptake (206.2 mg/g) due to the largest micropore volume (Vmicro) and ultramicropore volume (Vultra) by micropore filling mechanism. SLS-S-Ni-C possessed effective iodine capacity (∼2.2 g/g) and good recycling (∼90.9%), the adsorption process was based on the dominated physical adsorption, meanwhile, also along with the weak chemical interaction for some iodine molecules by little strong binding sites. SLS-Ni-C had the largest equilibrium capacity of RhB (350.6 mg/g) and the fast adsorption kinetic (about 50 min) due to the large SBET, suitable micro-mesopores size and proportion. This work provided a kind of hierarchical porous carbon from LS-Na by dual template routes, and matched adsorbents for the removal of targeted contaminants.

In this study, we compared the impacts of Bacillus subtilisPB6 (BS) and bacitracin methylene disalicylate (BMD) on the growth performance, intestinal morphology, expression of tight connection protein, and cecal microbiota community of male ducks through a 42-d trial. Three-hundred and sixty male Cherry Valley meat-type ducklings (1-day-old) were distributed into 3 groups of 6 replicates: CON group (control, basal diet), BMD group (basal diet + 45 mg/kg BMD, active ingredient dose in the feed), and BS group (basal diet + 2 × 107CFU/kg BS in the feed). Results showed that supplementing the diet with BS reduced the average daily feed intake (ADFI) during d 15 to 42 and d 1 to 42 compared with the CON group (P = 0.032). It also reduced feed conversion ratio (FCR) during d 15 to 42 and d 1 to 42 (P< 0.05) relative to the other groups. The ileal villus height (VH) and villus height /crypt depth ratio (V/C) were increased (P< 0.05) in both the BS and BMD groups, and the jejunal VH and V/C ratio were increased in the BS group (P< 0.05). Relative to the CON, BS supplementation was associated with numerical augmentation of goblet cells in the jejunal mucosa and upregulation of jejunal zonula occludens (ZO-1) and ileal mucin2(P< 0.05) mRNA levels. Analysis showed a negative correlation between FCR (d 0–42) and VH, V/C, and the number of goblet cells in the jejunum (P< 0.05). Additionally, BMD or BS supplementation altered the alpha diversity of colonic microbiota (P< 0.05). Correlation analysis revealed that Butyricimonas, Enterobacteriaceae, Clostridiaceae, and Tannerellaceaewere positively associated with the acetic acid and butyrate concentrations (P< 0.05). Taken together, the supplementation of BS in the diet of male ducks was conducive to reducing FCR by meliorating intestinal morphology, upregulating ZO-1and mucin2mRNA levels, regulating the abundance of microbiota, and metabolites, and having a greater effect than BMD supplementation.

Selecting for multiple traits as opposed to a single trait has become increasingly important in genomic selection. As one of the most popular approaches to multitrait genomic selection, index selection uses a weighted average of all traits as a single breeding objective. Although intuitive and effective, index selection is not only numerically sensitive but also structurally incapable of finding certain optimal breeding parents. This paper proposes a new selection method for multitrait genomic selection, the L-shaped selection, which addresses the limitations of index selection by normalizing the trait values and using an L-shaped objective function to find optimal breeding parents. This algorithm has been proven to be able to find any Pareto optimal solution with appropriate weights. Two performance metrics have also been defined to quantify multitrait genomic selection algorithms with respect to their ability to accelerate genetic gain and preserve genetic diversity. Computational experiments were conducted to demonstrate the improved performance of L-shaped selection over-index selection.

The household energy mix has significant impacts on human health and climate, as it contributes greatly to many health- and climate-relevant air pollutants. Compared to the well-established urban energy statistical system, the rural household energy statistical system is incomplete and is often associated with high biases. Via a nationwide investigation, this study revealed high contributions to energy supply from coal and biomass fuels in the rural household energy sector, while electricity comprised ∼20%. Stacking (the use of multiple sources of energy) is significant, and the average number of energy types was 2.8 per household. Compared to 2012, the consumption of biomass and coals in 2017 decreased by 45% and 12%, respectively, while the gas consumption amount increased by 204%. Increased gas and decreased coal consumptions were mainly in cooking, while decreased biomass was in both cooking (41%) and heating (59%). The time-sharing fraction of electricity and gases (E&G) for daily cooking grew, reaching 69% in 2017, but for space heating, traditional solid fuels were still dominant, with the national average shared fraction of E&G being only 20%. The non-uniform spatial distribution and the non-linear increase in the fraction of E&G indicated challenges to achieving universal access to modern cooking energy by 2030, particularly in less-developed rural and mountainous areas. In some non-typical heating zones, the increased share of E&G for heating was significant and largely driven by income growth, but in typical heating zones, the time-sharing fraction was <5% and was not significantly increased, except in areas with policy intervention. The intervention policy not only led to dramatic increases in the clean energy fraction for heating but also accelerated the clean cooking transition. Higher income, higher education, younger age, less energy/stove stacking and smaller family size positively impacted the clean energy transition.In rural China, affordable modern energy was increasingly adopted for cooking, and clean energy carriers were also used more for space heating.

Spatial diffusion and time delay are two main important factors in biological systems. In this paper, a predator-prey model with Holling III functional response, which includes time delay and diffusion processes is presented. It was found that time delay can induce transition from wave pattern to stationary pattern. Furthermore, for different values of time delay, different types of stationary patterns are obtained in the predator-prey model. These results may be useful for us to understand the pattern transition arising from intrinsic elements in the real ecosystems. [ABSTRACT FROM AUTHOR]

Coded aperture snapshot spectral imaging (CASSI) provides an efficient mechanism for recovering 3D spectral data from a single 2D measurement. However, since the reconstruction problem is severely underdetermined, the quality of recovered spectral data is usually limited. In this paper we propose a novel dual-camera design to improve the performance of CASSI while maintaining its snapshot advantage. Specifically, a beam splitter is placed in front of the objective lens of CASSI, which allows the same scene to be simultaneously captured by a grayscale camera. This uncoded grayscale measurement, in conjunction with the coded CASSI measurement, greatly eases the reconstruction problem and yields high-quality 3D spectral data. Both simulation and experimental results demonstrate the effectiveness of the proposed method.

As the global awareness and concerns about the environment issues increase, many governments, regulatory organisations and business leaders have begun to call on the manufacturing and business communities to play leading roles in the process of moving the global economy towards sustainability. Fierce market competition and price sensitivity have been big obstacles in the development and growth of sustainable/green production industry. In this study, analyses are conducted between two groups of ordinary and green production sectors which produce a similar type of product with different materials and techniques. We categorise them as green and ordinary companies. A game theoretical model is formulated to analyse the market competition, and obtain the dynamic equilibrium under the free entry assumption. Sensitivity analyses and numerical examples can provide suggestions to assist policy makers, governments, company executives and consumers to make better and rational decisions.

In this paper, the authors present and analyze a new hybrid inexact Logarithmic-Quadratic Proximal method for solving nonlinear complementarity problems. Each iteration of the new method consists of a prediction and a correction step. The predictor is produced using an inexact Logarithmic-Quadratic Proximal method, which is then corrected by the Proximal Point Algorithm. The new iterate is obtained by combining predictor and correction point at each iteration. In this paper, the authors prove the convergence of the new method under the mild assumptions that the function involved is continuous and monotone. Comparison to another existing method with numerical experiments on classical NCP instances demonstrates its superiority.

The main objective of electric power dispatch is to provide electricity to the customers at low cost and high reliability. Transmission line failures constitute a great threat to the electric power system security. We use a Markov decision process (MDP) approach to model the sequential dispatch decision making process where demand level and transmission line availability change from hour to hour. The action space is defined by the electricity network constraints. Risk of the power system is the loss of transmission lines, which could cause involuntary load shedding or cascading failures. The objective of the model is to minimize the expected long-term discounted cost (including generation, load shedding, and cascading failure costs). Policy iteration can be used to solve this model. At the policy improvement step, a stochastic mixed integer linear program is solved to obtain the optimal action. We use a PJM network example to demonstrate the effectiveness of our approach.

In this paper, we investigate the existence of periodic solutions for a class of second order nonlinear random impulse differential equations. By extending the definitions of continuous function bound set, curvature bound set and Nagumo set in topological degree to PC space, and defining the appropriate operators and conditions, using the theory of topological degree and coincidence degree, we prove that the solution must be bounded if it exists and find the boundary value. Finally, we define appropriate Nagumo set and autonomous curvature bound set, and obtain the existence of periodic solutions of equations and simultaneous equations by using Mawhin’s continuity theorem.

We present an energy matrix representation for multiband images that captures spatial and spectral properties. Using a physical model for spectral reflectance, we derive a pseudoinverse method for the comparison of energy matrices that is invariant to the spectral properties of the scene illumination. At the same time, this method determines the illumination change matrix, allowing direct comparison of images obtained under different illumination conditions. We demonstrate the performance of the method for both illumination-invariant recognition and illumination correction on a large set of multiband images. The energy matrices are generated using a small set of oriented steerable filters. We also demonstrate that a related set of rotationally symmetric filters can be used for recognition invariant to both illumination and rotation and that subsequent processing can be used to recover the rotation angle of a recognized object. © 1998 Society of Photo-Optical Instrumentation Engineers.

We represent texture in a color image by using spatial correlation functions defined within and between sensor bands. This representation has been shown to be useful for surface recognition, but the structure of spatial correlation functions depends on the spectral properties of the scene illumination. Using a linear model for surface spectral reflectance with the same number of parameters as the number of classes of photoreceptors, we show that illumination changes correspond to linear transformations of a surface correlation matrix. From this relationship we derive a distance function for comparing sets of spatial correlation functions that can be used for illumination-invariant recognition. This distance function can be computed efficiently from estimated correlation functions. We demonstrate, using a large body of experiments, that this distance function can be used for accurate surface recognition in the presence of large changes in illumination spectral distribution.

In this paper, certain problems concerning nonessential singularities of the second kind (NSSKs), especially continuous NSSKs for 3-D digital filters, are discussed. It is shown that continuous NSSKs, both inT2U and onT3, may exist in stable systems. Based on the Weierstrass theorem of multidimensional complex analysis, the existence criteria of continuous NSSKs inT2U and onT3 are obtained. Certain basic properties of this type of singularities are given. A stability condition for a transfer functionH(Z) with continuous NSSKs and the inverse ofH(Z) is derived. Furthermore, for isolated NSSKs, a new necessary and sufficient condition for stability is developed for a class of systems.

We introduce a method for segmenting surfaces of three-dimensional objects using two images of the object obtained from the same viewpoint under different illumination conditions. The method allows the surface spectral reflectance to vary from point to point and requires only weak conditions on the uncalibrated illumination configuration. The algorithm is based on the local recovery of an illumination change matrix that depends on surface geometry but not on the spectral reflectance of the surface. We show that for typical sensor noise levels, this technique can be used for the reliable detection of surface orientation changes of a few degrees. This approach can be generalized using a calibrated setup to recover a dense set of surface orientation estimates from two images. We present a set of experiments demonstrating the capability of the algorithm for the segmentation of planar surfaces in the presence of spatially varying spectral reflectance. © 1998 Society of Photo-Optical Instrumentation Engineers.

Physalis alkekengi L. var. franchetii (PALF) is a traditional Chinese medicine, which is well known for its antimicrobial, anti-inflammatory, antipyretic, and expectorant properties. Its fruits and fruiting calyxes are used as dietary supplements and traditional herbs in China. However, the quality of calyxes is uneven, and it is prone to getting moldy or moth-eaten during storage. High-performance liquid chromatography (HPLC) fingerprints and multivariate chemometric methods were combined to evaluate quality, and three representative compounds were chosen as the quality markers (Q-markers). Hierarchical cluster analysis (HCA) and principal component analysis (PCA) provided a clear discrimination of PALF samples. Through further verification by partial least squares discriminant analysis (PLS-DA), backpropagation artificial neural network (BP-ANN), machine learning, and combination with the determination of the content, biology, and pharmacology effect judgment, galuteolin, rutin, and physalin O could be used as Q-markers that their contents affect the quality of PALF grade evaluation. A simple method was established to rapidly assess the quality of PALF that is important for its clinical application and storage and provide a reference for evaluating the quality of materials used in Chinese medicine.

The objective of this experiment was to investigate the potential benefits of active dry yeast (ADY) on the growth performance, rumen fermentation, nutrient digestibility, and serum parameters of weaned beef calves. Thirty Simmental crossbred male calves (body weight = 86.47 ± 4.41 kg and 70 ± 4 d of age) were randomly divided into 2 groups: control (CON) (fed basal ration) and ADY (fed basal ration and 5 g/d ADY per calf). The dietary concentrate-to-roughage ratio was 35:65. All the calves were regularly provided rations three times a day at 07:00, 13:00, and 19:00 and had free access to water. The experiment lasted for 60 d. The average daily gain of ADY group was higher (P= 0.007) than that of the CON group, and the ratio of feed intake to average daily gain in the ADY group was reduced (P= 0.022) as compared to the CON group. The concentration of ruminal ammonia-N was higher (P= 0.023) in the CON group than that in the ADY group, but an opposite trend of microbial protein was found between the 2 groups. Also, the ruminal concentrations of propionate and butyrate were higher (P< 0.05) in the ADY group than those in the CON group. Calves fed ADY exhibited higher (P< 0.05) crude protein and neutral detergent fiber digestibility. Supplementation of ADY increased (P< 0.05) the contents of glucose, glutathione peroxidase, superoxide dismutase, immunoglobulin A, immunoglobulin M, and interleukin 10 in the serum of calves, but an opposite trend was observed in malondialdehyde, interleukin 1 beta, and tumor necrosis factor alpha contents between the 2 groups. In conclusion, dietary supplementation with ADY could improve the growth performance, rumen fermentation, nutrient digestibility, antioxidant ability, and immune response of weaned beef calves.

Carbon capture, storage, and utilization (CCSU) is recognized as an effective method to reduce the excessive emission of CO2. Absorption by amine aqueous solutions is considered highly efficient for CO2capture from the flue gas because of the large CO2capture capacity and high selectivity. However, it is often limited by the equipment corrosion and the high desorption energy consumption, and adsorption of CO2using solid adsorbents has been receiving more attention in recent years due to its simplicity and high efficiency. More recently, a great number of porous organic polymers (POPs) have been designed and constructed for CO2capture, and they are proven promising solid adsorbents for CO2capture due to their high Brunauer-Emmett-Teller (BET) surface area (SBET), adjustable pore size and easy functionalization. In particular, they usually have rigid skeleton, permanent porosity, and good physiochemical stability. In this review, we have a detailed review for the different POPs developed in recent years, not only the design strategy, but also the special structure for CO2capture. The outlook of the opportunities and challenges of the POPs is also proposed.

Accelerated degradation testing (ADT) is frequently conducted in the laboratory to predict the products' reliability under normal operating conditions. Two kinds of methods, degradation path models and stochastic process models, are utilized to analyze degradation data and the latter one is the most popular method. However, some limitations like imprecise solution process and estimation result of degradation ratio still exist, which may affect the accuracy of the acceleration model and the extrapolation value. Moreover, the conducted solution of this problem, Bayesian method, lose key information when unifying the degradation data. In this paper, a new data processing and parameter inference method based on Bayesian method is proposed to handle degradation data and solve the problems above. First, Wiener process and acceleration model is chosen; Second, the initial values of degradation model and parameters of prior and posterior distribution under each level is calculated with updating and iteration of estimation values; Third, the lifetime and reliability values are estimated on the basis of the estimation parameters; Finally, a case study is provided to demonstrate the validity of the proposed method. The results illustrate that the proposed method is quite effective and accuracy in estimating the lifetime and reliability of a product.

Multi-reference configuration interaction is used to produce potential energy curves (PECs) for the excited B^1Π state of KH molecule. To investigate the correlation effect of core-valence electrons, five schemes are employed which include the different correlated electrons and different active spaces. The PECs are fitted into analytical potential energy functions (APEFs). The spectroscopic parameters, ro-vibrational levels, and transition frequencies are determined based on the APEFs and compared with available experimental and theoretical data. The molecular properties for B^1Π obtained in this letter, which are better than those available in literature, can be reproduced with calculations using the suitable correlated electrons and active space of orbitals.

A new real-time infrared image enhancement algorithm which applies to FPGA is proposed in this paper. In real-time infrared image processing, image's contrast is very low, the noise of the regular graph is effects of real-time infrared image system precision primary factors, Seems particularly important how about to reduce infrared image noise and improve the precision at the infrared image. In order to reduce infrared image noise, we use adaptive piecewise linear transformation algorithm for infrared image enhancement, and objective evaluation of the enhanced images, at the same time also to discuss real-time of the algorithm, and verify the feasibility of applying this algorithm.