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Predicting the failure time of unstable slopes is one of the most pivotal issues. In this paper, the inverse square root acceleration (INSRA) method was proposed to estimate the time-of-failure (TOF) of landslides. Four collapsed slopes were presented in the three open-pit mines, two of them were probed by ground-based radar, and two of them were obtained from previous scientific papers. The inverse velocity (INV) method and INSRA method were adopted to analyze these four landslides and one slope which had great deformation but did not reach failure. Compared with the traditional INV method, the INSRA method can promote the forecasting effectiveness and has the advantage of higher accuracy.

A novel coupled hydro-mechanical non-ordinary state-based peridynamics is proposed to investigate hydro-mechanical problems in fissured porous rocks. The hydraulic bond is introduced to the coupled numerical model to transfer the water flow stored in material points. The flow equations for fissured porous rocks are obtained in the framework of peridynamics. Then, the relationship between peridynamic hydraulic conductivity and classic hydraulic conductivity for one-dimensional and two-dimensional flow cases is established. Moreover, Biot's porous media theory is employed to determine the deformation caused by water pressure, which is introduced to the non-ordinary state-based peridynamic government equation. In addition, the effects of mechanical deformation and fracture on hydraulic conductivity are considered in the coupled hydro-mechanical non-ordinary state-based peridynamic model. Finally, three different numerical experiments are carried out to verify the correctness of the coupled hydro-mechanical peridynamic model proposed in this paper, and it is found that the present numerical results are in good agreement with the analytical solutions.

In large-array millimeter-wave (mmWave) systems, hybrid multi-user precoding is one of the most attractive research topics. This paper first presents a low-dimensional manifolds architecture for the analog precoder. An objective function is formulated to maximize the Energy Efficiency (EE) in consideration of the insertion loss for hybrid multi-user precoder. The optimal scheme is intractable to achieve, so that we present a user clustering hybrid precoding scheme. By modeling each user set as a manifold, we formulate the problem as clustering-oriented multi-manifolds learning. We discuss the effect of non-ideal factors on the EE performance. Through proper user clustering, the hybrid multi-user precoding is investigated for the sum-rate maximization problem by manifold quasi conjugate gradient methods. The high signal to interference plus noise ratio (SINR) is achieved and the computational complexity is reduced by avoiding the conventional schemes to deal with high-dimensional channel parameters. Performance evaluations show that the proposed scheme can obtain near-optimal sum-rate and considerably higher spectral efficiency than some existing solutions.

This study describes the synthesis and vacuole-inducing activity of 5-((4-(pyridin-3-yl)pyrimidin-2-yl)amino)-1H-indole-2-carbohydrazide derivatives, including five potent derivatives 12c, 12 g, 12i, 12n, and 12A that exhibit excellent vacuole-inducing activity. Remarkably, 12A effectively induces methuosis in tested cancer cells but not human normal cells. In addition, 12A exhibits high pan-cytotoxicity against different cancer cell lines but is hardly toxic to normal cells. It is found that the 12A-induced vacuoles are derived from macropinosomes but not autophagosomes. The 12A-induced cytoplasmic vacuoles may originate from the endoplasmic reticulum (ER) and be accompanied by ER stress. The MAPK/JNK signalling pathway is involved in the 12A-induced methuotic cell death. Moreover, 12A exhibits significant inhibition of tumour growth in the MDA-MB-231 xenograft mouse model. The excellent potency and selectivity of 12A prompt us to select it as a good lead compound for further development of methuosis inducers and investigation of the molecular and cellular mechanisms underlying methuosis. Novel methuosis-inducing anticancer agents are designed and synthesised. Vacuole inducers 12i and 12A display high anticancer activity and little-toxic to normal cells. Compound 12A is a selective methuosis inducer involving the activation of MAPK/JNK signalling pathway. Compound 12A effectively inhibits tumour growth in the MDA-MB-231 xenografted mouse model.

Massive high-resolution spaceborne synthetic aperture radar (SAR) data are available nowadays, effecting rapid development in the urban remote sensing technology. In this study, we use a set of 27 scenes from TerraSAR-X to reconstruct the three-dimensional (3D) point clouds of a skyscraper—North Star Times Tower in Beijing, China. We study in detail the derivation process of a 3D model of tomographic SAR (TomoSAR) from the two-dimensional (2D) imaging mathematical model of SAR. We observe the presence of a spatial shift in the elevation direction of TomoSAR, which yields poor and even incorrect results when greedy algorithms such as orthogonal matching pursuit (OMP) or regularized orthogonal matching pursuit (ROMP) algorithms are applied. Then, we propose a phase compensation method to eliminate the spatial shift. Both OMP and ROMP algorithms are used for TomoSAR imaging on high-resolution TerraSAR-X data. The experimental results with North Star Times Tower demonstrate the accuracy of the theoretical analysis and the effectiveness of the algorithms. Finally, we compare the ROMP and OMP algorithms and conclude that both algorithms can yield similar reconstruction results in TomoSAR imaging. The ROMP algorithm does not depend on sparsity and can suppress noise through regularization selection at the cost of time. The OMP algorithm introduces noise when the sparsity is inaccurate.

Ecological risks (ERs) are external threats to ecosystem structure and function, and the evaluation of ER is valuable for understanding the extent of the disturbance of ecosystems by human activities. An objective investigation of the spatio-temporal characteristics of ER and its affecting elements can contribute to the improvement of the ecological environment and the sustainable development of regional resources. The Funiu Mountains were chosen as the study area, the ecological risk index was built using landscape interference and landscape separation, and the spatial–temporal properties and scale effect of the ER were assessed. The findings of ER may be separated into four distinct zones to study the variations in ER levels from 2000 to 2015: modest, mild, moderate, and high. Furthermore, geographically weighted regression (GWR) was used to ascertain the degree to which environmental factors impact ER and regional disparities. The results show: (1) Ecological risk assessment was sensitive to scale transformation, and there are variations in the spatial pattern of ER on diverse scale units. With the scale following a 1 km grid to the watershed, Global Moran’s I values dropped from 0.53 to 0.04, and 1 km × 1 km was the most suitable unit. (2) The ecological and environmental quality of the Funiu Mountains improved from 2000 to 2015. The extent of the high ecological risk zone dropped by 398.07 km2, but other types of ecological risk regions rose, owing to the execution of policies aimed at restoring cropland to forests. The ER presented a transitional distribution from a high risk in the surrounding area to low risk in the central area. (3) From the perspective of correlations among the influencing factors, altitude and slope had a negative correlation with other influencing factors, while others were positively correlated. The correlation coefficient between land-use degree and human activities intensity and ER was the highest. Each environmental factor had significant effects on the ERs and spatial variation existed, where the land-use degree and human activities intensity were the main obstacle factors limiting ER improvement. Population density, altitude, slope, and maximum temperature all displayed effects on ER with different directions and intensities.

A 3D cross-network Co3O4–xNx nanostructure is obtained from the cobalt–alanine complex (Co(C3H5O2N)2) by amino acid self-assembly and subsequent pyrolysis. In this process, Co(C3H5O2N)2 forms a 2D ...

Pathfinding is a fundamental problem for many areas, e.g., robotics, automation, computer-aided design, and computer graphics. Although outdoor pathfinding is fledged, indoor pathfinding remains a challenge due to the lack of indoor maps. Currently, some efforts have utilized building information modeling (BIM) to generate either the grid-based map or the topological map. However, either the grid-based map or the topological map is not sufficient to provide accurate and efficient pathfinding service. This article proposes a novel grid-topological map and develops an accurate and efficient indoor pathfinding scheme based on BIM. The grid-topological map is modeled jointly adopting the advantages of both the grid-based map and the topological map. First, the grid-based map is generated using the BIM data by extracting and mapping geometric and semantic data into planar grids. Second, a grid thinning algorithm is proposed to produce the topological map directly using the grid-based map. Third, a grid-topological map is presented by combining both the grid-based map and topological map. On top of the grid-topological map, an accurate and efficient pathfinding algorithm is developed. Empirical studies proved the effectiveness of the grid-topological map, as well as the accuracy and efficiency of the proposed indoor pathfinding algorithm.

In complex network, the links among the nodes fabricate thousands of polygons, where triangles are the most foundamental ones. As more links are added to the network, more polygons are split to be triangles. Discovering the triangles can help understand the current status of the network. Due to the limitations of internal memory, discovering all the triangles in a large-scale real-world network, e.g., online social network (OSN), is challenging and has intrigued researchers for years. Currently, parallel computation frameworks, e.g., MapReduce, have been employed to address this issue. The last reducer is required to load all the neighbors of each node into internal memory, which causes “the curse of the last reducer.” The scale-free characteristic in real-world networks furthur exacerbate the applicability of the parallel triangle discovery algorithms. The current efforts on this issue mainly focus on dividing a large network into several small subnetworks and later employ internal memory algorithms. In this paper, we address this issue from a different perspective by employing the power-law degree distribution in scale-free networks. We theoretically and empirically prove that one node in scale-free network has a limited number of neighbors with a higher degree. Employing this finding, an novel parallel triangle discovery algorithm called degree partition (DePart) is designed. Since only the portion of neighbors with higher degrees are loaded into internal memory in the reducers, DePart solves “the curse of the last reducer” problem and works efficiently in clusters with limited internal memory. We develop DePart using MapReduce framework and examine the performance of DePart on five large real-world networks. The empirical testing results demonstrate that DePart has a favorable tradeoff between internal memory and total disk space and outperforms the current state-of-the-art MapReduce-based triangle discovery algorithms.

Toll-like receptor (TLR) genes have recently been used to assess the adaptive genetic diversity under natural selection. Here, we newly developed a set of primer pairs for amplifying TLR genes (TLR1LB, TLR2A, TLR3, TLR4, TLR5, TLR7 and TLR15) in the vulnerable Chinese egret (Egretta eulophotes). The PCR products, ranged between 407 and 988 bp (an average of 762 bp), were successfully amplified by using this primer set. Sequence analyses of all these TLR genes indicated that there were 22–75 variable sites and 20–77 single nucleotide polymorphisms. This primer set was also confirmed useful for nine other ardeid species, including four members in ardeinae and five in botaurinae. The versatility of this primer set will provide a useful groundwork for the further studies on the TLR conservation genetics of this vulnerable egret and other ardeid birds.

The least angle sensitivity (LARS) algorithm is used to realize the global sensitivity analysis of slope stability, while simultaneously considering the effects of several geotechnical parameters on slope stability. In addition, the Sobol sequence is applied in the sample simulation to generate the geotechnical parameters, thereby increasing the accuracy of the results. Two cases are considered to investigate the effects of the geotechnical parameters on slope stability, and the accuracy and efficiency of the LARS algorithm are examined. The importance measure indexes obtained using the LARS algorithm are in good agreement with those obtained using the Monte Carlo (MC) method. To determine the importance measure indexes, the performance functions of the slope stability analysis are required to be run N times when using the LARS algorithm, which is $$1/(n \cdot N + 1)$$ the required number for the MC method, where n and N represent the number of random variables and sample size, respectively. In this scenario, the computational efficiency is considerably increased.

Ring Brazilian disc specimens are favored for determining the tensile strength and mixed mode fracture toughness. To further understand the fracture mechanism of ring Brazilian disc specimens, the phase field method is used to investigate the cracking process and peak load of ring Brazilian disc specimens. First, the numerical validity and accuracy of the phase field method is verified by a benchmark example. Then, the effect of aperture ratio and crack inclination angle on the failure process and peak load of ring Brazilian disc specimens is studied. Finally, by combining the phase field method and J-integral method, the influence of prefabricated crack inclination angle and aperture ratios on mode I and II fracture toughness of cracked ring Brazilian disc specimens is discussed.

Single-atom Ag-decorated MnO2 hollow microspheres (Ag-MnO2 HMSs) with oxygen vacancies are successfully fabricated via a self-template strategy and redox etching method. The transmission electron m...

Natural gas-hydrates are valuable energy resource with rich deposits, and their thermal transport and thermal dynamic mechanical behaviors significantly affect the long-term production process and phase change-based thermal energy storage characteristics of these energy resources. This paper aims to propose novel relations to predict the thermophysical properties, to investigate the hydrate phase evolution in microstructures, and to study the thermal transport and thermal dynamic mechanical properties. Hydrates formation experiments in sandpack samples and ultrasonic wave tests are conducted with the aid of X-ray CT imaging. Digitalization microstructures models and variables are defined to describe the hydrate phase evolution, and novel relations are proposed to accurately predict the thermophysical properties based on the microporosity and ultrasonic wave velocities. The thermal transport and thermal dynamic mechanical properties in microstructures with hydrate, water, residuary pore and grain phases are studied. Results show that the average errors of porosity, P-wave and S-wave velocities between the experimental data and computed results by the proposed relations are less than 5%, indicating the accuracy and reliability of the proposed method. The temperature fraction decreases with increasing underground temperature and decreasing hydrate saturation. The thermal stress and thermal displacement increase as temperature and hydrate saturation increase. There are strong anisotropy for the temperature fraction, thermal stress and thermal displacement during the thermal transport of hydrates.

A sodium polyacrylate-mediated strategy was employed to prepare well-defined MoS2 ball-flower-like nanomaterials. It was found that the polyacrylate acted as a morphology-directing agent to promote MoS2 nanosheets to self-assemble into ball-flowers with 3D hierarchical structures. Moreover, as an electrode applied in a supercapacitor, the ball-flower-like MoS2 exhibited a remarkable pseudocapacitive performance such as a high specific capacitance and superior cycling durability.

The excessive expansion of road transportation often has an impact on the quality of regional habitats. This paper attempts to assess the impact of road transportation on regional habitat quality in economically developed areas. A kernel density analysis was used to characterise the road transportation development in Jiangsu Province from 2000 to 2015. An Integrated Valuation of Ecosystem Services and Trade‐offs (InVEST) habitat quality model was applied to assess changes in habitat quality. Furthermore, a fixed‐effect regression model was utilised to examine the impact of road transportation development in Jiangsu Province on habitat quality. The analysis indicates that the average kernel density of road transportation in the province increased from 0.109 to 0.551 km/km2 while the habitat quality decreased from 0.51 to 0.48. The development of road transportation in Jiangsu Province has had a serious negative impact on the quality of the habitat. For every 1‐ha increase in land area for road use, the habitat quality index will decrease by 0.066; for every 1 km/km2 increase in road transportation kernel density, the habitat quality index will decline by 0.121.

Treatments for cognitive deficits associated with central nervous system (CNS) disorders such as Alzheimer disease and schizophrenia remain significant unmet medical needs that incur substantial pressure on the health care system. The α7 nicotinic acetylcholine receptor (nAChR) has garnered substantial attention as a target for cognitive deficits based on receptor localization, robust preclinical effects, genetics implicating its involvement in cognitive disorders, and encouraging, albeit mixed, clinical data with α7 nAChR orthosteric agonists. Importantly, previous orthosteric agonists at this receptor suffered from off-target activity, receptor desensitization, and an inverted U-shaped dose-effect curve in preclinical assays that limit their clinical utility. To overcome the challenges with orthosteric agonists, we have identified a novel selective α7 positive allosteric modulator (PAM), BNC375. This compound is selective over related receptors and potentiates acetylcholine-evoked α7 currents with only marginal effect on the receptor desensitization kinetics. In addition, BNC375 enhances long-term potentiation of electrically evoked synaptic responses in rat hippocampal slices and in vivo. Systemic administration of BNC375 reverses scopolamine-induced cognitive deficits in rat novel object recognition and rhesus monkey object retrieval detour (ORD) task over a wide range of exposures, showing no evidence of an inverted U-shaped dose-effect curve. The compound also improves performance in the ORD task in aged African green monkeys. Moreover, ex vivo 13C-NMR analysis indicates that BNC375 treatment can enhance neurotransmitter release in rat medial prefrontal cortex. These findings suggest that α7 nAChR PAMs have multiple advantages over orthosteric α7 nAChR agonists for the treatment of cognitive dysfunction associated with CNS diseases. SIGNIFICANCE STATEMENT: BNC375 is a novel and selective α7 nicotinic acetylcholine receptor (nAChR) positive allosteric modulator (PAM) that potentiates acetylcholine-evoked α7 currents in in vitro assays with little to no effect on the desensitization kinetics. In vivo, BNC375 demonstrated robust procognitive effects in multiple preclinical models across a wide exposure range. These results suggest that α7 nAChR PAMs have therapeutic potential in central nervous system diseases with cognitive impairments.

Convex edges are located on convex surfaces of hidden geometry spaces, resulting in shorter geometrical distance than observed. Convex edges reveal the close relationships between two connected nodes and have a key role in many research fields and applications, including social, trust, and protein–protein interaction networks. We first quantitatively define convex edges using hidden geometry space defined by Ricci curvature and show these to be capable of predicting highly interacted edges in social networks. From empirical studies of social networks, we find that convex edges often occur on two connected nodes with similar popularity and allow for frenemy (or versatile node) identification, and that almost all nodes maintain an upper bound of convex edges. These findings present further evidence of the limited attention in an attention economy from a different perspective. Using three well-known synthetic networks, we show that convex edges can reflect the formation of a network from scatter (concave) to aggregation (convex). Taken together, our results show that convex edges are a novel mechanism to investigate social networks from different disciplines and offer insights into many network phenomena.

A binder-free electrode has been fabricated by directly growing MoSe2 nanosheets on the macroporous Ti mesh skeleton (MoSe2 NS-Ti) via a facile hydrothermal deposition method. The as-prepared MoSe2 NS-Ti electrode is characteristic of robust porous hierarchical nanostructures with large surface area, enriched exposed active edges and improved electroconductivity. As a result, in comparison to the bare MoSe2 electrode, the MoSe2 NS-Ti electrode shows dramatically enhanced electrocatalytic activity and pseudocapacitive performance due to its desirable structural features.

With the aim of developing lanthanide fluoride-based nanoparticles (NPs) with enhanced upconversion (UC) luminescence properties, Ca2+-doped water-soluble β-NaErF4:Yb nanocrystals are prepared by a facile solvothermal reaction using ethylene glycol and water as the solvents and comb-like superplasticizer (SP), polyacrylic-co-methyl allyl polyoxyethylene ether copolymer as the capping agent. The SP-capped upconversion nanoparticles (UCNPs) are characterized by X-ray diffraction, scanning electron microscopy, and Fourier transform infrared spectroscopy. The results show that the capping agent has great influence on the morphology and colloidal solubility of the nanocrystals. The morphological and phase evolution of the nanocrystals is studied. Furthermore, bright red UC luminescence is observed when the sol is irradiated by a 980 nm laser, and the red UC photoluminescence (UCPL) emission is enhanced by eight times upon doping with 50 mol% Ca2+. The decay time and stability of the UCPL are also discussed. With the efficient stable red UC, the Ca2+ doped water-soluble NaErF4:Yb nanocrystals may find use in various optical applications.

Pore scale variables (e.g., porosity, grain size) are important indexes to predict the hydraulic properties of porous geomaterials. X-ray images from ten types of intact sandstones and another type of sandstone samples subjected to triaxial compression are used to investigate the permeability and fracture characteristics. A novel double threshold segmentation algorithm is proposed to segment cracks, pores and grains, and pore scale variables are defined and extracted from these X-ray CT images to study the geometric characteristics of microstructures of porous geomaterials. Moreover, novel relations among these pore scale variables for permeability prediction are established, and the evolution process of cracks is investigated. The results indicate that the pore-scale permeability is prominently improved by cracks. In addition, excellent agreements are found between the measured and the estimated pore scale variables and permeability. The established correlations can be employed to effectively identify the hydraulic properties of porous geomaterials.

A successive interference cancellation (SIC)-based weighted least-squares (WLS) estimation for the carrier frequency offset (CFO) and the sampling frequency offset (SFO) is presented for wireless local area networks (WLANs) based on orthogonal frequency division multiplexing (OFDM). The proposed SIC-based WLS performs the estimation by exploiting the phase rotation in the frequency domain caused by the CFO and the SFO. SIC-based WLS estimates the CFO and the SFO successively instead of by traditional simultaneous estimation. The estimation of CFO based on the Taylor series is performed first, and then the WLS estimation of SFO based on successive cancellation of the CFO is carried out. The simulation results show that the SIC-based WLS can estimate the CFO and the SFO effectively. Compared to the WLS scheme, a performance improvement of more than 0.6 dB is achieved by SIC-based WLS, and nearly 10 percent of the complexity is reduced.

In this paper, a criterion of crack branching based on the energy release rate is proposed. Theory of multidimensional space method for crack branching is established in the framework of the extended finite element method (XFEM), in which the formula of the boundary shift energy is deduced. The boundary cracking energy is obtained because the boundary shift model is abstracted into the boundary cracking model. The energy release rates of the crack branching in four quadrants are determined based on boundary cracking energy. Further, the energy release rate of the crack branching is introduced into multidimensional space method to determine the crack branching. If the crack tip branching, the criteria of crack branching are applied to determine the direction of the branching cracks, otherwise the criteria of maximum circumferential stress are applied to determine the direction of the cracks. Moreover, a classical numerical example is investigated to verify the correctness of the criterion of crack branching in the framework of the multidimensional space method.

Chinese authors indirectly portray real social relationships in society by incorporating their own experiences and feelings about politics, economic life, and cultural habits. Social and natural knowledge are mixed and hidden in natural literary language. Therefore, by well defining the type of original text, the pipeline for processing the text and the rules to build the graph, we can extract enough valid and useful information. Based on higher-level information, we can build a literary character graph to promote computers’ comprehension of literature. The identification of opposite characters is a challenging topic because the character relationships are intricate and complex. The cryptic expression in literary works can enhance the readability of the plot, but it is obvious that it increases the cost of understanding. Even for human readers different types of characters are difficult to classify and identify, and it usually needs careful reading for several times to get the subtle differences among the characters. Though extracting knowledge from Chinese literature is a complicated and difficult topic, this paper models the graph of polar literary characters and divides polar communities by extracting polar vertices and polar edges based on the concept of literary sentiment polarity. The results show that using a long-sentence window is a good trade-off. The experiments of modern Chinese polar literature show that the accuracy of the community division method for the integrated graph polarity is obviously better than the method based on the co-occurrence network, and it can automatically match the positive and negative communities as well as build the complete graph structure. It clearly reflects the meaning of literary works from the perspective of polarity. This systematic model describes general standard operation steps for the machine to understand complex Chinese literature. The experiments conducted on seven benchmark Chinese novel datasets demonstrate that the method based on emotional polarity shows a significant improvement compared to baseline performance. Though we use Chinese datasets in this paper, the model and methods are important references for literature analysis and graph extraction in other languages.

This paper proposes an intelligent approach (fuzzy logic) for the design of external-cavity semiconductor lasers (ECLs) for better disturbance rejection. As a kind of nonlinear optical system, ECL output frequency is difficult to be stabilized by conventional methods. The fuzzy logic algorithm is preferred for ECLs stabilization, which could update parameters automatically. Suddenability to reject nonlinear disturbances arch occur in the fuzzy logic systemduring operation, speed of operation and PID gains are alteredonline in accordance with the disturbances to reject. To showthe efficacy of the proposed method, a fuzzy logic ECL stabilization system is designed. The results prove that our method is effective and robust.

Feld’s friendship paradox is a widely accepted observation that states that the friends of any particular individual tend to have more friends on average than the individual has. Due to its implications for information transmission, the friendship paradox has become a generalized paradigm in many disciplines. However, how many of an individual’s friends have more friends than the individual does is still unknown, yet interesting. In this paper, we revisited the Feld’s friendship paradox and we found that only a limited number of a person’s friends have more friends than the person herself has. This conclusion was reached from empirical studies using real-world networks and is true regardless of the number of one’s neighbours, which contradicts the intuitive deduction from the friendship paradox. For one thing, if a person is unpopular, the number of her friends that have more friends than she does grows with the number of friends that she makes. This observation crystallizes the tenable margin of the friendship paradox. In another case, if a person is popular, as she acquires more friends, fewer of her friends have more friends than she does. This finding suggests an observation bias in the friendship paradox, which makes individuals feel less popular than their friends. Besides enriching our knowledge of the friendship paradox in psychological science, the findings reported here are also beneficial for technical areas such as large-scale triangle discovery. Although the friendship paradox was proposed from the perspective of the number of neighbours, the findings reported here can shed light on theories and applications from different disciplines like information, happiness, obesity, and extroversion, to name a few.

Two-tier massive multiple-input multiple-output (MIMO) systems achieve high sum spectral efficiency by simultaneously serving large numbers of users. However, as the number of service antennas and users tend to infinity, the performance is limited by directed inter-cell and intra-cell interferences. Handling these interferences are challenging due to the large channel dimensionality and the high complexity associated with implementing large precoding/combining matrices. Moreover, two-tier massive MIMO is computationally demanding, as the high antenna count results in high-dimensional matrix operations when conventional MIMO hybrid precoding is applied. In this paper, a manifold learning two-tier beamforming (MLTB) scheme is proposed to enable efficient and low-complexity operation in large scale dimensional MIMO systems. Users of multi-cell are clustered into several regions of user groups by manifold learning. Most of the high-dimensional channels are embedded in the low-dimensional subspace by manifold learning, while retaining the potential spatial correlation of the high-dimensional channels. The nonlinearity of high-dimensional channel is transformed into local linearity to achieve dimensionality reduction. Through proper user clustering, the beamformers are split into outer beamformers and inner beamformers. The outer beamformers can minimize inter-cell interference and the inner beamformers can minimize multi-user interference of intra-groups. The high signal to interference plus noise ratio (SINR) is achieved and the computational complexity is reduced by avoiding the conventional schemes to deal with high-dimensional channel parameters. Performance evaluations show that the proposed MLTB scheme can obtain near-optimal sum-rate and considerably higher energy efficiency than the conventional schemes.

Objective. To improve the diagnostic capacity of serum biomarkers for colorectal cancer (CRC), we introduced three novel indicators, namely, the C-X-C motif chemokine ligand 5 (CXCL5), stanniocalcin 2 (STC2), and chitinase 3 like 1 (CHI3L1) and assessed their performances in the detection of CRC. Methods. A total of 887 serum samples (153 health, 342 polyps, and 392 CRCs) were collected. Concentrations of CXCL5, STC2, and CHI3L1 were measured by the ELISA. CEA and CA199 were determined by electrochemiluminescence. Binary logistic regression was used to build the combination model. ROC analysis was used to evaluate the performance of biomarkers alone or in combination. Results. Model_2 that based on CXCL5, STC2, and CHI3L1 was the best approach in discriminating CRC from non-CRC controls (AUC, 0.943 (0.922–0.960); sensitivity, 0.848; specificity, 0.917; and accuracy, 0.887 in the training cohort and 0.959 (95% CI 0.927–0.980), 0.878, 0.917, and 0.900 in the testing cohort, respectively). In the detection of early CRC, Model_2 revealed AUC, sensitivity, specificity, and accuracy of 0.925 (0.897–0.947), 0.793, 0.917, and 0.886 in the training cohort and those of 0.926 (0.979–0.959), 0.786, 0.931, and 0.898 in the testing cohort. Furthermore, Model_2 exhibited an excellent diagnostic performance in CEA-negative cases (0.938 (0.913–0.957), 0.826, 0.917, and 0.888 in the training cohort and 0.961 (0.925–0.983), 0.887, 0.931, and 0.918 in the testing cohort). As used alone, STC2 achieved the capacities that is second only to that of Model_2 (0.866 (0.837–0.892), 0.859, 0.842, and 0.853 in the training cohort and 0.887 (0.842–0.923), 0.922, 0.799, and 0.853 in the testing cohort). STC2 alone also yielded acceptable results for early CRC detection (0.815 (0.776–0.849), 0.767, 0.849, and 0.829 in the training cohort and 0.870 (0.812–0.914), 0.952, 0.799, and 0.833 in the testing cohort). Moreover, STC2 maintained diagnostic accuracy for CRC patients with negative CEA (0.874 (0.842–0.901), 0.862, 0.849, and 0.853 in the training cohort and 0.898 (0.848–0.936), 0.930, 0.801, and 0.842 in the testing cohort). In comparison, the performances of the CEA and CA199 based Model_1 were far from satisfactory, especially in early cases (0.767 (0.726–0.805), 0.491, 0.863, and 0.771 in the training cohort and 0.817 (0.754–0.870), 0.476, 0.889, and 0.796 in the testing cohort). Conclusions. STC2 was a promising serum biomarker for CRC diagnosis either used alone or in combination with CXCL5 and CHI3L1.

The QC-LDPC code, with its excellent error correction performance and hardware friendliness, has been identified as one of the channel encoding schemes by Wi-Fi 6. Shorting, puncturing, or repeating operations are needed to ensure that user data can be sent with integer symbols and complete rate matching. Due to the uncertainty of the user data size, the modulation’s selectivity, and the difference in the number of spatial streams, the receiver must deal with more than 106 situations. At the same time, other computationally intensive tasks occupy the time slot budget of the receiver. Typical are demodulation and decoding. Hence, the receiver needs to quickly reverse the demodulated data process. This paper first proposes a co-processing method and VLSI architecture compatible with all code lengths, code rates, and processing parameters. The co-processor separates field and block splicing, simplifying the control logic. There is no throughput rate bottleneck, and the maximum delay is less than 1 us.

Background Trauma patients are often in a state of psychological stress, experiencing helplessness, sadness, frustration, irritation, avoidance, irritability and other adverse emotions. Doctors and nurses are at the forefront of caring trauma patients and they play a crucial role in psychological supports and mental health care. However, few qualitative studies had based on the framework of the Theory of Planned Behavior (TPB) to explore the experiences in providing psychological care for trauma patients. We examined attitudinal, normative, and control beliefs underpinning medical staffs’ decisions to perform psychological care. Method A qualitative study of in-depth semi-structured interviews was conducted among 14 doctors and nurses engaging in trauma care. The participants came from six tertiary hospitals in Chongqing, China. Data analysis was performed using the approach of Colaizzi. According to the framework of TPB, the researchers identified and summarized the themes. Results Important advantages (mutual trust, patients' adherence and recovery), disadvantages (workload, short-term ineffective, practice unconfidently), referents (supportive: managers, patients, kinsfolk, nursing culture; unsupportive: some colleagues and patients), barriers (insufficient time or energy, resources situations), and facilitators (access to psychologist, training/education, reminders) were identified. Some demands, such as training diversity, multidisciplinary cooperation and families' support, reflected by doctors and nurses were important for them to carry out psychological care. Conclusion According to the TPB, this article explored the internal and external promotion and hindrance factors that affecting the intentions and behaviors of doctors and nurses in implementing psychological care for trauma patients. We also focused on the experience and demands of health professionals in conducting psychological care, which could provide references for managers to formulate corresponding psychological care procedures and norms.

Background The vulnerable Chinese Egret (Egretta eulophotes) is a long-distance migratory waterbird whose migration and wintering information is poorly understood. This study aims to identify the autumn migration routes and wintering areas of juvenile Chinese Egrets and determine the migration movement traits of this species. Methods Thirty-nine juvenile Chinese Egrets from the Fantuozi Island, an uninhabited offshore island with a large breeding colony of Chinese Egrets in Dalian, China, were tracked using GPS/GSM transmitters. Some feathers from each tracked juvenile were collected for molecular identification of sex in the laboratory. The GPS locations, recorded at 2-h intervals from August 2018 to May 2020, were used for the analyses. Results Of the 39 tracked juveniles, 30 individuals began their migration between September and November, and 13 successfully completed their autumn migration between October and November. The juveniles migrated southward via three migration routes, coastal, oceanic and inland, mainly during the night. The migration duration, migration distance, flight speed, and stopover duration of the 13 juvenile egrets that completed migration averaged 5.08 ± 1.04 days, 3928.18 ± 414.27 km, 57.27 ± 5.73 km/h, and 23.08 ± 19.28 h, respectively. These juveniles wintered in the coastal wetlands of Southeast Asia including those in the Philippines, Vietnam, and Malaysia, and only one successfully began its spring migration in June 2020. Conclusions This study newly finds that the oceanic route taken by juvenile Chinese Egrets, suggesting that the juveniles are able to fly over the Pacific Ocean without a stopover. Moreover, our novel data indicate that coastal wetlands along the East Asian–Australasian Flyway are important areas for both autumn migration stopover and the wintering of these juveniles, suggesting that international cooperation is important to conserve the vulnerable Chinese Egret and the wetland habitats on which it depends.

Millimeter-wave (mmWave) massive MIMO (multiple-input multiple-output) is a promising technology as it provides significant beamforming gains and interference reduction capabilities due to the large number of antennas. However, mmWave massive MIMO is computationally demanding, as the high antenna count results in high-dimensional matrix operations when conventional MIMO processing is applied. Hybrid precoding is an effective solution for the mmWave massive MIMO systems to significantly decrease the number of radio frequency (RF) chains without an apparent sum-rate loss. In this paper, we propose user clustering hybrid precoding to enable efficient and low-complexity operation in high-dimensional mmWave massive MIMO, where a large number of antennas are used in low-dimensional manifolds.By modeling each user set as a manifold, we formulate the problem as clustering-oriented multi-manifolds learning. The manifold discriminative learning seek to learn the embedding low-dimensional manifolds, where manifolds with different user cluster labels are better separated, and the local spatial correlation of the high-dimensional channels within each manifold is enhanced. Most of the high-dimensional channels are embedded in the low-dimensional manifolds by manifold discriminative learning, while retaining the potential spatial correlation of the high-dimensional channels. The nonlinearity of high-dimensional channel is transformed into global and local nonlinearity to achieve dimensionality reduction. Through proper user clustering, the hybrid precoding is investigated for the sum-rate maximization problem by manifold quasi conjugate gradient methods. The high signaltointerferenceplusnoise ratio (SINR) is achieved and the computational complexity is reduced by avoiding the conventional schemes to deal with high-dimensional channel parameters. Performance evaluations show that the proposed scheme can obtain near-optimal sum-rate and considerably higher spectral efficiency than some existing solutions

Millimeter-wave massive multiple-input multiple-output is a key technology in 5G communication system. In particular, the hybrid precoding method has the advantages of being power efficient and less expensive than the full-digital precoding method, so it has attracted more and more attention. The effectiveness of this method in simple systems has been well verified, but its performance is still unknown due to many problems in real communication such as interference from other users and base stations, and users are constantly on the move. In this article, we propose a dynamic user clustering hybrid precoding method in the high-dimensional millimeter-wave multiple-input multiple-output system, which uses low-dimensional manifolds to avoid complicated calculations when there are many antennas. We model each user set as a novel Convolutional Restricted Boltzmann Machine manifold, and the problem is transformed into cluster-oriented multi-manifold learning. The novel Convolutional Restricted Boltzmann Machine manifold learning seeks to learn embedded low-dimensional manifolds through manifold learning in the face of user mobility in clusters. Through proper user clustering, the hybrid precoding is investigated for the sum-rate maximization problem by manifold quasi-conjugate gradient methods. This algorithm avoids the traditional method of processing high-dimensional channel parameters, achieves a high signal-to-noise ratio, and reduces computational complexity. The simulation result table shows that this method can get almost the best summation rate and higher spectral efficiency compared with the traditional method.