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Highlights Excellent impedance matching through component modulation engineering. Rich heterogeneous interfaces are constructed to realize excellent electromagnetic wave (EMW) absorption performance. Long-term corrosion protection and excellent EMW absorption properties.

The examination of the spatiotemporal characteristics and developmental trends of drought is crucial for enhancing water resource management, bolstering drought resistance, and improving disaster prevention capabilities. This study employs the Standardized Precipitation Evapotranspiration Index (SPEI) and grain yield data across various time scales, in conjunction with methodologies such as Run Theory, Mann-Kendall, and Standardized Yield Residual Series, to conduct an in-depth investigation into the spatiotemporal variation characteristics of meteorological drought in Hunan Province and its impact on grain yield. The findings suggest that: (1) Since 1960, the likelihood of seasonal drought occurrence in Hunan Province has been ranked as autumn > winter > spring > summer, with mild drought occurring most frequently, followed by moderate drought, while the frequency of severe and extreme drought remains low. (2) Meteorological drought in Hunan Province exhibits spatial differences at the seasonal scale, with the overall drought changes in spring and summer displaying a non-significant upward trend; the western and southern regions exhibit a trend of aridification in autumn; and in winter, the Zhangjiajie and Xiangxi regions show an insignificant downward trend. (3) From 1960 to 2022, grain production in Hunan Province has demonstrated a pattern of fluctuation and increase. The meteorological yield of grain crops displays a high-low-high spatial distribution from south to north. Concurrently, there is a positive correlation between short-term climate change and meteorological output, while long-term climate change is not evident. (4) El Niño Southern Oscillation (ENSO) is a significant circulation factor affecting meteorological drought in Hunan Province, and the meteorological drought in autumn and winter in Hunan Province is significantly influenced by ENSO. The research findings can provide reference significance and a scientific basis for drought research and comprehensive management in Hunan Province, and offer data and theoretical support for promoting economic development.

Abstract Alloying is regarded as one of the most promising strategies for boosting performance of catalysts for hydrogen evolution reaction (HER) due to the adjustable electronic structure and intermediate adsorption. However, there is no theory (including d‐band center theory) can accurately guide the preparation and design of alloy catalysts, and thus resulting all the reported alloy catalysts are obtained by time‐consuming and laborious experimental exploration. Herein, we proposed a mean d‐band center (εas) as a new accurate descriptor for alloy activity prediction. Theoretical simulation and experiment results revealed that this descriptor exhibits a strong scaling relation with H adsorption energy. Besides, the obtained Cu–Ag alloy displays an optimal overpotential of 223 mV at 10 mA/cm2 in 0.5 mol/L H2SO4, which is more than 300 mV lower than those of pristine Cu (530 mV) and Ag (569 mV) powder. Our work provides a new idea toward designing highly efficient HER catalysts and broadens the applicability of d‐band theory to activity prediction of alloys.

Highlights The hierarchical porous structure is regulated by various species of PVP to achieve impedance matching. Interfacial engineering boosts conductivity and constructs a multiband (C, X, Ku) tunable electromagnetic wave absorber. Hierarchical porous molybdenum selenide/epoxy coating exhibits marine anticorrosion capability.

The introduction of the pilot flame can stabilize the lean premixed flame and promote its industrial application. However, the interaction mechanism between the pilot and main flames is complicated. To reveal the effect of the pilot flame on the main flame, a laminar lean premixed flame adjacent to a rich premixed pilot flame on one side and a similar lean premixed flame on the other side was considered. A two-dimensional numerical model was adopted with detailed chemistry and species transport, also with no artificial flame anchoring boundary conditions. The results show that the pilot flame could promote the main flame stabilized in different locations with various shapes, by adjusting the stretch, heat transfer, and preferential diffusion in a complicated manner. The pilot flame improves the local equivalence ratio and transfer more heat to the main flame. The growth of the pilot flame equivalence ratio and inlet velocity enhances the combustion on the rich side of the main flame and helps it anchor closer to the flame wall. Both the curvature and strain rate show a significant effect on the flame root, which contributes to the main flame bending towards the pilot flame.

A robust wood material crack detection algorithm, sensitive to small targets, is indispensable for production and building protection. However, the precise identification and localization of cracks in wooden materials present challenges owing to significant scale variations among cracks and the irregular quality of existing data. In response, we propose a crack detection algorithm tailored to wooden materials, leveraging advancements in the YOLOv8 model, named ICDW-YOLO (improved crack detection for wooden material-YOLO). The ICDW-YOLO model introduces novel designs for the neck network and layer structure, along with an anchor algorithm, which features a dual-layer attention mechanism and dynamic gradient gain characteristics to optimize and enhance the original model. Initially, a new layer structure was crafted using GSConv and GS bottleneck, improving the model’s recognition accuracy by maximizing the preservation of hidden channel connections. Subsequently, enhancements to the network are achieved through the gather–distribute mechanism, aimed at augmenting the fusion capability of multi-scale features and introducing a higher-resolution input layer to enhance small target recognition. Empirical results obtained from a customized wooden material crack detection dataset demonstrate the efficacy of the proposed ICDW-YOLO algorithm in effectively detecting targets. Without significant augmentation in model complexity, the mAP50–95 metric attains 79.018%, marking a 1.869% improvement over YOLOv8. Further validation of our algorithm’s effectiveness is conducted through experiments on fire and smoke detection datasets, aerial remote sensing image datasets, and the coco128 dataset. The results showcase that ICDW-YOLO achieves a mAP50 of 69.226% and a mAP50–95 of 44.210%, indicating robust generalization and competitiveness vis-à-vis state-of-the-art detectors.

Abstract Background and Aims Massive hepatocellular carcinoma (MHCC, a maximum tumor size of at least 10 cm) tends to have a poor prognosis. Therefore, this study aims to construct and validate prognostic nomograms for MHCC. Methods Clinic data of 1292 MHCC patients between 2010 and 2015 were got from the surveillance, epidemiology, and end results (SEER) cancer registration database. The whole set was separated into the training and validation sets at a ratio of 2:1 randomly. Variables, significantly associated with cancer‐specific (CSS) and overall survival (OS) of MHCC were figured out by multivariate Cox regression analysis and were taken to develop nomograms. The concordance index (C‐index), calibration curve, and decision curve analysis (DCA) were taken to validate the predictive abilities and accuracy of the nomograms. Results Race, alpha‐fetoprotein (AFP), grade, combined summary stage, and surgery were identified as independent factors of CSS, and fibrosis score, AFP, grade, combined summary stage, and surgery significantly correlated with OS in the training cohort. They then were taken to construct prognostic nomograms. The constructed model for predicting CSS exhibited satisfactory performance with a C‐index of 0.727 (95% CI: 0.746–0.708) in the training group and 0. 672 (95% CI: 0.703–0.641) in the validation group. Besides, the model for predicting OS of MHCC also showed strong performance both in the training group (C‐index: 0.722, 95% CI: 0.741–0.704) and the validation (C‐index: 0.667, 95% CI: 0.696–0.638) group. All calibration curves and decision curves performed satisfactory predictive accuracy and clinic application values of the nomograms. Conclusion The web‐based nomograms for CSS and OS of MHCC were developed and validated in this study, which prospectively could be tested and may serve as additional tools to assess patient's individualized prognosis and make precise therapeutic selection to improve the poor outcome of MHCC.

To overcome the serious situation of electromagnetic pollution at present stage, herein the hierarchical carbon/CoFe2O4/Co3Fe7 composites were prepared via an innovative ball milling assistant chemical precipitation and subsequent annealing technique. By changing the solvent ratio of DW/DMF and the additive amount of milling balls, the micro-nano structures, electromagnetic parameters and response behavior of hybrids can be adjusted, in which the N-6 composite obtains a maximal RL of −42.70 dB at 16.42 GHz with the broadest EAB of 8.68 GHz for only 2.38 mm. Based on the well matched impedance within wide frequency region, the excellent attenuation properties of this composite generated from the strong dielectric polarizations, magnetic resonances, eddy current and structure-scattering effect could play roles to absorb incident electromagnetic wave. In short, this investigation offers an innovative route to synthesize the hierarchical carbon decorated with CoFe2O4 and Co3Fe7 nanoparticles for super electromagnetic absorption.

Abstract The Early Jurassic angiosperm Nanjinganthus has triggered a heated debate among botanists, partially due to the fact that the enclosed ovules were visible to naked eyes only when the ovary is broken but not visible when the closed ovary is intact. Although traditional technologies cannot confirm the existence of ovules in a closed ovary, newly available Micro-CT can non-destructively reveal internal features of fossil plants. Here, we performed Micro-CT observations on three dimensionally preserved coalified compressions of Nanjinganthus. Our outcomes corroborate the conclusion given by Fu et al., namely, that Nanjinganthus is an Early Jurassic angiosperm.

Chromatin structural domains, or topologically associated domains (TADs), are a general organizing principle in chromatin biology. RNA polymerase II (RNAPII) mediates multiple chromatin interactive loops, tethering together as RNAPII-associated chromatin interaction domains (RAIDs) to offer a framework for gene regulation. RAID and TAD alterations have been found to be associated with diseases. They can be further dissected as micro-domains (micro-TADs and micro-RAIDs) by clustering single-molecule chromatin-interactive complexes from next-generation three-dimensional (3D) genome techniques, such as ChIA-Drop. Currently, there are few tools available for micro-domain boundary identification. In this work, we developed the MCI-frcnn deep learning method to train a Faster Region-based Convolutional Neural Network (Faster R-CNN) for micro-domain boundary detection. At the training phase in MCI-frcnn, 50 images of RAIDs from Drosophila RNAPII ChIA-Drop data, containing 261 micro-RAIDs with ground truth boundaries, were trained for 7 days. Using this well-trained MCI-frcnn, we detected micro-RAID boundaries for the input new images, with a fast speed (5.26 fps), high recognition accuracy (AUROC = 0.85, mAP = 0.69), and high boundary region quantification (genomic IoU = 76%). We further applied MCI-frcnn to detect human micro-TADs boundaries using human GM12878 SPRITE data and obtained a high region quantification score (mean gIoU = 85%). In all, the MCI-frcnn deep learning method which we developed in this work is a general tool for micro-domain boundary detection.

Drilling vertical and horizontal wellbores in the shale reservoir may trigger the in-situ stress release around the wellbore walls and change the original stress equilibrium state, leading the wellbores to instability. This stress change in the wellbore corresponds to the stress paths of confining pressure unloading and axial stress loading under laboratory conditions. In this paper, according to the conventional triaxial compression test results, laboratory experiments and DEM simulations by PFC2D were conducted to deeply study the strength, failure, strain energy evolution, and micro-crack damage mechanism of shale specimens under confining pressure unloading conditions. The shale specimens at different bedding inclinations were tested under different initial axial stress levels and confining pressure unloading rates, with fixed initial unloading confining pressure. This research revealed that confining pressure unloading induces greater plastic deformation, more micro-crack damage and strain energy dissipation, and a more complex failure pattern. The strain energy dissipation and dilatation under confining pressure unloading conditions are mainly induced by the generation and accumulation of tensile cracks. Moreover, the unloading rate has a significant effect on the mechanical properties, and the high unloading rate enhances the failure strength and induces more strain energy dissipation and micro tensile cracks. For the wellbore drilling in shale formations, when the buried depth and vertical stress are fixed, the lower the lateral stress is, the easier it is to form tensile failure around the wellbore wall in the drilling process, and the more induced fractures will be generated in the formation around the wellbore.

ESG investment strategy has attracted increasing attention from the financial market, and the inconsistency of enterprise ESG rating results of different rating agencies has gradually become the focus of attention of regulators and investors. In this article, the listed companies with ESG ratings in Shanghai and Shenzhen A-shares from 2016 to 2020 were selected as the research samples. Combined with difference-in-differences model and ordinary least squares methods, the rationality of these ESG ratings was evaluated by examining the difference in the impact of three international ESG rating agencies, such as Bloomberg, and three Chinese ESG rating agencies, such as Sino-securities, on the stock price crash risk. The research findings are as follows: First, after incorporating the ESG ratings of FTSE Russell, MSCI, and China Alliance of Social Value Investment, the stock price crash risk of enterprises is significantly reduced. Second, the company's share price crash risk will be lower when the ESG evaluation results of Bloomberg or MSCI is better. Third, compared with social indicators, investors pay more attention to the environmental performance of enterprises in decision making. Enterprises with high environmental scores have lower stock price crash risk. The findings of this article play an enlightening role for China to improve its ESG system, construct an ESG disclosure policy, and improve the market role of ESG rating.

Due to the rapid development of wireless electrommunication and electronic techniques in current age, electromagnetic radiation and electromagnetic interference (EMI) have brought serious threat to the normal operation of precision electronic instruments and human health. Herein, the reclaimed straw of sorghum derived biochar/(Fe,Ni) hybrid has been prepared via a facile calcination process. The as-prepared hybrid possesses an outstanding low-frequency electromagnetic absorbing performance i.e. the maximum RL of T-600 can achieve −44.18 dB with effective absorption bandwidth (EAB) of 0.17~0.99 GHz for 2 mm and a board EAB of 0.53~2.49 GHz for only 1 mm. Meanwhile, the maximum RL of T-700 can attain −46.36 dB with EAB of 0.49~1.43 GHz and the board EAB of 0.89~2.81 GHz for the same thickness, which are owing to the cooperative effect of interface polarization, dipole polarization, natural resonance, eddy current and conduction loss, multi-reflection and scatter, better impedance matching and so on. This environmentally-friendly biochar/(Fe,Ni) hybrid can be employed as a novel low-frequency microwave absorbent for its good performance and reclamation of waste straw in sorghum.

PurposeTo study the topographical relationship between acute macular neuroretinopathy (AMN) lesions and the choroidal watershed zone (CWZ) or patchy choroidal filling (PCF) using multimodal imaging.MethodsLesions in patients diagnosed with AMN were clinically examined using multimodal imaging, including fundus photography, near-infrared reflectance imaging, spectral-domain optical coherence tomography (OCT), fluorescein angiography, indocyanine green angiography, OCT angiography, and microperimetry. The topographical relationship between AMN and the CWZ or PCF was evaluated.ResultsSeven eyes of six patients were included in the study. The mean age of the patients was 35.8 ± 11.7 years. The AMN lesions were collocated with the CWZ in five eyes and the PCF in one eye. Among these eyes, three had complete patterns, and three had partial patterns. Only one eye showed no topographical relationship between AMN and the CWZ or PCF.ConclusionThe colocation of AMN and CWZ/PCF suggests that the AMN lesions were within an area with a dual-watershed zone: the watershed zone between the retinal deep capillary plexus and choriocapillaris, and the choroidal watershed zone or patchy choroidal filling. This retinal area was highly vulnerable to hypoperfusion. Our results suggest a novel pathophysiological mechanism for AMN.

This paper discusses a hybrid grey wolf optimizer utilizing a clone selection algorithm (pGWO-CSA) to overcome the disadvantages of a standard grey wolf optimizer (GWO), such as slow convergence speed, low accuracy in the single-peak function, and easily falling into local optimum in the multi-peak function and complex problems. The modifications of the proposed pGWO-CSA could be classified into the following three aspects. Firstly, a nonlinear function is used instead of a linear function for adjusting the iterative attenuation of the convergence factor to balance exploitation and exploration automatically. Then, an optimal α wolf is designed which will not be affected by the wolves β and δ with poor fitness in the position updating strategy; the second-best β wolf is designed, which will be affected by the low fitness value of the δ wolf. Finally, the cloning and super-mutation of the clonal selection algorithm (CSA) are introduced into GWO to enhance the ability to jump out of the local optimum. In the experimental part, 15 benchmark functions are selected to perform the function optimization tasks to reveal the performance of pGWO-CSA further. Due to the statistical analysis of the obtained experimental data, the pGWO-CSA is superior to these classical swarm intelligence algorithms, GWO, and related variants. Furthermore, in order to verify the applicability of the algorithm, it was applied to the robot path-planning problem and obtained excellent results.

Discovering valuable and diverse resources in an educational digital library can be difficult with the existing large number of content collections. Researchers in information retrieval and related domains have moved from considering only keyword-based matching to modeling the underlying behavior pattern of users. To achieve the purpose of both precision and diversity while providing online educational resource services, in this paper, we propose a weighted network-based information filtering framework that models user usage as a bipartite user-resource network; users and resources are treated as nodes in this network, each edge from a user to a resource means usage, and the weight represents the accumulation of multiple usage scenarios. Under this framework, we propose two individual algorithms, the unbalanced heat conduction algorithm and the unbalanced mass diffusion algorithm, and one hybrid multistage heat conduction and mass diffusion algorithm. There are two stages in these algorithms. In stage 1, an initial energy is assigned to each resource that has been visited by the target and passes to users according to a specific strategy. In stage 2, the energy is similarly transferred from users to resources, and a sorted resource list ranked by energy is presented to the target user. Experiments on a real-world dataset of one year of academic search logs showed improved performance from multiple indicators compared to existing algorithms.

Background: Amlodipine (AML) is the initial therapy most commonly prescribed for patients with hypertension in China. However, AML monotherapy is often less effective in achieving blood pressure (BP) control than other agents. Objective: We performed a clinical study to evaluate efficacy and safety of a combination therapy with AML, olmesartan (OLM), or an OLM/hydrochlorothiazide (HCTZ) compound for Chinese patients with mild-to-moderate hypertension. Methods: In the clinical trial, patients were initially treated with OLM 20 mg/d combined with AML 5 mg/d. Then OLM was uptitrated to 40 mg/d or changed to an OLM/HCTZ (20/12.5 mg/d) compound if the patients did not reach the target of seated diastolic BP

The intelligent design method based on generative adversarial networks (GANs) represents an emerging structural design paradigm where design rules are not artificially defined but are directly learned from existing design data. GAN-based methods have exhibited promising potential compared to conventional methods in the schematic design phase of reinforced concrete (RC) shear wall structures. However, for the following reasons, it is challenging to apply GAN-based approaches in the industry and to integrate them into the structural design process. (1) The data form of GAN-based methods is heterogeneous from that of the widely used computer-aided design (CAD) methods, and (2) GAN-based methods have high requirements on the hardware and software environment of the user’s computer. As a result, this study proposes an integrated schematic design method for RC shear wall structures, providing a workable GAN application strategy. Specifically, (1) a preprocessing method of architectural CAD drawings is proposed to connect the GAN with the upstream architectural design; (2) a user-friendly cloud design platform is built to reduce the requirements of the user’s local computer environment; and (3) a heterogeneous data transformation method and a parametric modeling procedure are proposed to automatically establish a structural analysis model based on GAN’s design, facilitating downstream detailed design tasks. The proposed method makes it possible for the entire schematic design phase of RC shear wall structures to be intelligent and automated. A case study reveals that the proposed method has a heterogeneous data transformation accuracy of 97.3% and is capable of generating shear wall layout designs similar to the designs of a competent engineer, with 225 times higher efficiency.

Crop traits such as aboveground biomass (AGB), total leaf area (TLA), leaf chlorophyll content (LCC), and thousand kernel weight (TWK) are important indices in maize breeding. How to extract multiple crop traits at the same time is helpful to improve the efficiency of breeding. Compared with digital and multispectral images, the advantages of high spatial and spectral resolution of hyperspectral images derived from unmanned aerial vehicle (UAV) are expected to accurately estimate the similar traits among breeding materials. This study is aimed at exploring the feasibility of estimating AGB, TLA, SPAD value, and TWK using UAV hyperspectral images and at determining the optimal models for facilitating the process of selecting advanced varieties. The successive projection algorithm (SPA) and competitive adaptive reweighted sampling (CARS) were used to screen sensitive bands for the maize traits. Partial least squares (PLS) and random forest (RF) algorithms were used to estimate the maize traits. The results can be summarized as follows: The sensitive bands for various traits were mainly concentrated in the near-red and red-edge regions. The sensitive bands screened by CARS were more abundant than those screened by SPA. For AGB, TLA, and SPAD value, the optimal combination was the CARS-PLS method. Regarding the TWK, the optimal combination was the CARS-RF method. Compared with the model built by RF, the model built by PLS was more stable. This study provides guiding significance and practical value for main trait estimation of maize inbred lines by UAV hyperspectral images at the plot level.

Herein, A4 typing paper was used as a novel source to manufacture FeNi3 and NiCx coated carbon skeleton via facile routes. The product was examined for its ability to absorb electromagnetic emission which can be a health hazard. The impact of precursor concentration on the final electromagnetic wave absorption of samples was evaluated; the composite prepared under suitable concentration possesses outstanding multiband absorption ability of −34.64 dB and −26.7 dB at 2.32 GHz and 17.2 GHz, respectively, together with an ultra-wide effective absorption bandwidth of 9.58 GHz at only 3.9 mm. The strong dipole polarization and broad frequency range of preferable impedance matching, along with the coupling of other auxiliary mechanisms, are responsible for this excellent property. The as-prepared absorber has great potency for multiband absorption of electromagnetic waves.

Conducting polymer-based composites have recently becoming popular in both academic research and industrial practices due to their high conductivity, ease of process, and tunable electrical properties. The multifunctional conducting polymer-based composites demonstrated great application potential for in vivo therapeutics and implantable electronics, including drug delivery, neural interfacing, and minimally invasive electronics. In this review article, the state-of-the-art conducting polymer-based composites in the mentioned biological fields are discussed and summarized. The recent progress on the synthesis, structure, properties, and application of the conducting polymer-based composites is presented, aimed at revealing the structure-property relationship and the corresponding functional applications of the conducting polymer-based composites. Furthermore, key issues and challenges regarding the implantation performance of these composites are highlighted in this paper.

The origin of angiosperms has been a long-standing botanical debate. The great diversity of angiosperms in the Early Cretaceous makes the Jurassic a promising period in which to anticipate the origins of the angiosperms. Here, based on observations of 264 specimens of 198 individual flowers preserved on 34 slabs in various states and orientations, from the South Xiangshan Formation (Early Jurassic) of China, we describe a fossil flower, Nanjinganthus dendrostyla gen. et sp. nov.. The large number of specimens and various preservations allow for an evidence-based reconstruction of the flower. From the evidence of the combination of an invaginated receptacle and ovarian roof, we infer that the seeds of Nanjinganthus were completely enclosed. Evidence of an actinomorphic flower with a dendroid style, cup-form receptacle, and angiospermy, is consistent with Nanjinganthus being a bona fide angiosperm from the Jurassic, an inference that we hope will re-invigorate research into angiosperm origins.

In this study, the quaternary hybrid of (Zn0.5Co0.5Fe2O4/Mn0.5Ni0.5Fe2O4)@C-MWCNTs with high-performance in low frequency electromagnetic absorption was synthesized via a facile two-step solvothermal synthesis method. The physicochemical properties as well as electromagnetic parameters and microwave absorption performance were characterized by XRD, SEM, TEM, RS, TGA, and VNA, respectively. The results indicate a nuclear-shell morphology of this hybrid for amorphous carbon coated on the surface of Zn0.5Co0.5Fe2O4 and Mn0.5Ni0.5Fe2O4 mixed polycrystalline ferrites. In addition, the MWCNTs synchronously enwind in the nuclear-shell NPs to form a special cross-linking structure. The outstanding low frequency microwave absorption property is attributed to the synergistic effect of dielectric and magnetic loss, better impedance matching condition, and excellent attenuation characteristics of the as-prepared paramagnetic quaternary hybrid. Maximum RL of −35.14 dB at 0.56 GHz with an effective absorption bandwidth in the range of 0.27−1.01 GHz can be obtained with thickness of 5 mm. This hybrid exhibits superior low frequency microwave absorption properties compared with other ferrite-carbon nanocomposites. This investigation provides a new route to prepare suitable candidates for the absorption of electromagnetic waves in a low frequency band on account of its good performance and simple preparation process.

MnFe2O4 NPs are successfully decorated on the surface of SiO2 sheets to form the SiO2-MnFe2O4 composite via one-pot hydrothermal synthesis method. The phase identification, morphology, crystal structure, distribution of elements, and microwave absorbing properties in S-band (1.55~3.4 GHz) of the as-prepared composite were investigated by XRD, SEM, TEM, and Vector Network Analyzer (VNA) respectively. Compared with the pure MnFe2O4 NPs, the as-prepared SiO2-MnFe2O4 composite exhibits enhanced microwave absorption performance in this frequency band due to the strong eddy current loss, better impedance matching, excellent attenuation characteristic, and multiple Debye relaxation processes. The maximum reflection loss of −14.87 dB at 2.25 GHz with a broader −10 dB bandwidth over the frequency range of 1.67~2.9 GHz (1.23 GHz) can be obtained at the thickness of 4 mm. Most importantly, the preparation method used here is relatively simple, hence such composite can be served as a potential candidate for effective microwave absorption in S-band.

Experiments on transient directional solidification were carried out to study the columnar to equiaxed transition (CET) in Al-7Si alloy without and with an alternating electric current pulse (AECP). Without AECP, the macrostructure consists of typical columnar and equiaxed zones, separated by a near horizontal plane. As the AECP is applied during solidification, an additional fine equiaxed zone (FEZ) occurs in the as-cast macrostructure. From measured temperature profiles, cooling rate and temperature gradient are determined. It is found that CET occurs for a critical value of the cooling rate, which is observed to be about 0.14 K·s−1 in the present investigation. Furthermore, the macrostructural observation with mold for embedding the mesh plate demonstrates that the major factor responsible for the formation of fine equiaxed grains is the detachment of crystal nuclei from the upper contact surface and the lateral wall. The detachment is in turn ascribed to electric current-associated free energy change (ΔGe)-induced the driving force F.

Many rock engineering accidents have proven that the coalescence of discontinuities in surrounding rock can have a major impact on the security and stable operation of energy infrastructure. To give an insight into the understanding of the crack propagation and coalescence in fissured rock masses, a series of uniaxial compression experiments were conducted on rock-like specimens containing nonpersistent fissures. The digital speckle correlation method (DSCM) and the acoustic emission (AE) monitoring system were adopted to capture the real-time strain field on the specimens’ surfaces and microfracturing events within specimens, respectively. The experimental results indicated that the strength and deformation modulus of specimens were significantly affected by fissure inclination. The damage process showed obvious progressive stain localization failure characteristics. The clear and intuitive full-field strain field development was successfully monitored by the DSCM technique. The real-time strain accumulation, crack initiation, propagation, and coalescence were also analyzed. Each time, the saltation of the strain field was usually accompanied by the fluctuation of the stress curve and obvious AE events. Crack coalescence modes between fissures changed from tension coalescence mode to mixed tension-shear coalescence mode, then to shear coalescence mode with an increase in fissure inclination. Five basic failure modes were identified from the experimental results: Tensile failure across the fissure planes, rotation failure of newly generated blocks, mixed failure mode, shear failure, and splitting failure. An investigation of the fracture processes of rock-like specimens containing nonpersistent fissures using these methods can enhance understanding of the fracture behavior of jointed rocks.

The synthesis and application of biomass-derived carbon in energy storage have drawn increasing research attention due to the ease of fabrication, cost-effectiveness, and sustainability of the meso/microporous carbon produced from various biological precursors, including plants, fruits, microorganisms, and animals. Compared to the artificial nanostructured carbons, such as fullerene, carbon nanotube and graphene, the biomass-derived carbons may obtain superior capacitance, rate performance and stability in supercapacitor applications ascribing to their intrinsic nanoporous and hierarchical structures. However, challenges remain in processing techniques to obtain biomass-derived carbons with high carbon yield, high energy density, and controllable graphitic microstructures, which may require a clear understanding over the chemical and elemental compositions, and the intrinsic microstructural characteristics of the biological precursors. Herein we present comprehensive analyses over the impacts of the chemical and elemental compositions of the precursors on the carbon yield of the biomass, as well as the mechanism of chemical activation on the nanoporous structure development of the biomass-derived carbons. The structure–property relationship and functional performance of various biomass-derived carbons for supercapacitor applications are also discussed in detail and compared. Finally, useful insights are also provided for the improvements of biomass-derived carbons in supercapacitor applications.

In recent years, energy-efficient data collection has evolved into the core problem in the resource-constrained Wireless Sensor Networks (WSNs). Different from existing data collection models in WSNs, we propose a collaborative data collection scheme based on optimal clustering to collect the sensed data in an energy-efficient and load-balanced manner. After dividing the data collection process into the intra-cluster data collection step and the inter-cluster data collection step, we model the optimal clustering problem as a separable convex optimization problem and solve it to obtain the analytical solutions of the optimal clustering size and the optimal data transmission radius. Then, we design a Cluster Heads (CHs)-linking algorithm based on the pseudo Hilbert curve to build a CH chain with the goal of collecting the compressed sensed data among CHs in an accumulative way. Furthermore, we also design a distributed cluster-constructing algorithm to construct the clusters around the virtual CHs in a distributed manner. The experimental results show that the proposed method not only reduces the total energy consumption and prolongs the network lifetime, but also effectively balances the distribution of energy consumption among CHs. By comparing it o the existing compression-based and non-compression-based data collection schemes, the average reductions of energy consumption are 17.9% and 67.9%, respectively. Furthermore, the average network lifetime extends no less than 20-times under the same comparison.