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Abstract Chlorophyll a (Chl-a) is a key indicator of marine ecosystems, and certain hydro-meteorological parameters (HMPs) are highly correlated with its fluctuations. Here, relevant and accessible HMPs were used as inputs, combined with machine learning (ML) algorithms for estimating 3D Chl-a in the South China Sea (SCS). With the inputs of temperature, salinity, depth, wind speed, wind direction, sea surface pressure, and relative humidity, the LightGBM-based model performed well, achieving high R2 values of 0.985 and 0.789 in validation and testing sets, respectively. Based on a large number of in situ measurements, this model enables the estimation of the 3D distribution of summer Chl-a in the SCS over the past fifteen years using a 3D hydrographic dataset combined with surface meteorological parameters. The results show that the 3D distribution of the model estimated Chl-a is characterized similarly to the previous studies and can capture the effect of hydro-meteorological conditions on Chl-a distribution. The environmental variables affecting Chl-a were considered more comprehensively in this study, and the methodological framework has the potential to be applied to the low-cost monitoring of the remaining water quality parameters.

With urbanisation and population growth, understanding spatial interactions in cities is increasingly vital for urban management. In recent decades, spatial interactions could be predicted accurately with the support of large GPS data, but anonymous trajectory data lacks semantic details, limiting predictions and behaviour understanding. To address this, we proposed a Semantic-Integrated Mobility Trajectory Model (SMTM), integrating social media check-in data, remote sensing imagery, and taxi trajectory data capable of accurately predict travel flow. Specifically, Convolutional Neural Networks (CNN) and Long Short Term Memory (LSTM) extract demographic insights, Graph Convolutional Networks (GCN) and Gate Recurrent Units (GRU) are incorporated to predict spatial interaction intensity. We conducted two case studies in New York City, U.S., and Ningbo, China, using taxi trips (over three million trips in New York and nearly one million trips in Ningbo) and social media check-in data (around 60,000 records for each city). Results demonstrate excellent performance over baselines. Furthermore, the integration of travel trajectories and census data revealed diverse travel preferences at various scales, including intra-region, inter-region, and inter-urban. The SMTM model contributes to optimising the design of public spaces and personalised recommendations.

With the acceleration of urbanization and continuous population growth in China, transportation issues in central cities, especially large and mega-cities, have become increasingly prominent. A series of problems such as economic efficiency decline and reduced residents' well-being caused by traffic congestion have become significant factors constraining the sustainable development of cities. As a core component of the urban transportation system, the prioritized development of urban public transportation is crucial for alleviating traffic congestion, improving environmental quality, and enhancing residents' quality of life. However, from the beginning of 2023, the share of public transportation in residents' travel has gradually decreased, with the total passenger volume still lower than the same period in 2019. In response to the challenges faced by the public transportation system under the new circumstances, this paper reviews the necessity of prioritized development of urban public transportation, analyzes the reasons for the decline in the share of public transportation in residents' overall travel modes, and proposes targeted suggestions. On this basis, the paper explores the intrinsic connection between the strategy of prioritizing public transportation development and sustainable urban development.

Biomimetic neuromorphic sensing systems, inspired by the structure and function of biological neural networks, represent a major advancement in the field of sensing technology and artificial intelligence. This review paper focuses on the development and application of electrolyte gated transistors (EGTs) as the core components (synapses and neuros) of these neuromorphic systems. EGTs offer unique advantages, including low operating voltage, high transconductance, and biocompatibility, making them ideal for integrating with sensors, interfacing with biological tissues, and mimicking neural processes. Major advances in the use of EGTs for neuromorphic sensory applications such as tactile sensors, visual neuromorphic systems, chemical neuromorphic systems, and multimode neuromorphic systems are carefully discussed. Furthermore, the challenges and future directions of the field are explored, highlighting the potential of EGT-based biomimetic systems to revolutionize neuromorphic prosthetics, robotics, and human–machine interfaces. Through a comprehensive analysis of the latest research, this review is intended to provide a detailed understanding of the current status and future prospects of biomimetic neuromorphic sensory systems via EGT sensing and integrated technologies.

Mangrove forests are crucial in absorbing, storing, and purifying pollutants while maintaining ecological balance. A study was conducted in 2020 to investigate the biogeochemical processes of seawater and sedimentary environmental factors in the Qi'ao Island mangrove wetland. The study comprised two survey sections and ten survey stations within the mangrove forest and 16 large-scale survey stations in the adjacent sea area. During ebb tides, the mean concentrations of inorganic nitrogen and phosphate in Section D1 of the mangrove forest were 0.63 mg/L and 0.003 mg/L, respectively. These levels were significantly lower than the results observed in the adjacent sea area and Section D2 of the mangrove forest during flood tides. The mangrove forest efficiently absorbed and consumed nutrients, with the nitrogen-to-phosphorus ratio of consumed nutrients being notably higher than that typically utilized by plants during growth. We identified various biogeochemical processes, including nitrogen fixation, mineralization, nitrification, and denitrification, occurring within the mangrove forest. Seawater measurements in Section D1 during ebb tides showed the mean pH of 7.58 and dissolved oxygen levels of 4.52 mg/L, resulting in a dissolved oxygen saturation level of only 57.0 %. The low dissolved oxygen levels were attributed to organic matter degradation in the forest. Consequently, the longer the water retention time, the more obvious the trend of hypoxia and acidification was observed. In the adjacent sea area, the sedimentary environment was deemed healthy, with pollutants primarily originating from runoff and ship discharge from waterways and ports. However, within the mangrove forest, the sediments exhibited higher enrichment factors for organic carbon and sulfide, indicating significant pollution compared to the adjacent sea area. The sediments were conducive to the accumulation and burial of total Hg, Zn, and Cu, while other heavy metals did not show prominent deposition and enrichment. Notably, the enrichment factor of oils was as high as 4.37, leading to the formation of an oil pollution zone at the forest edge, and the enrichment of pollutants in sediment may inhibit the growth and expansion of mangroves. Overall, this study shed light on the occurrence of seawater acidification, hypoxia, and the behavior of sediment pollutants within the mangrove forest. The findings provide valuable insights to support efforts aimed at promoting and maintaining the ecosystem health of mangrove forests.

Abstract Porous films offer a general and simple strategy for balancing the electron/hole transport, and ion doping/dedoping process in organic electrochemical transistor (OECT) channel. Here a universal 3D integrated approach that simultaneously achieves both enhanced transconductance (gm) and mechanical stretchability via constructing a multilayer breath‐figured porous polymer channel by poly(3‐hexylthiophene) (P3HT)/ polystyrene‐block‐poly(ethylene‐ran‐butylene)‐block‐polystyrene (SEBS) and poly(2,5‐bis(3‐triethyleneglycoloxythiophen‐2‐yl)‐co‐thiophene) (Pg2T‐T)/SEBS mixture is demonstrated. The formed multilayer elastic porous structure provides efficient and tunable ionic‐electronic coupling and transport pathways, while also introducing immunity toward mechanical tensile deformation. Remarkably, an obvious increase in gm [from 10.05 mS (2.13 mS) to 29.23 mS (7.38 mS) for Pg2T‐T (P3HT)] is acquired by assembling the OECT porous channel from a single layer to a 3D trilayer. Moreover, mechanical stretchability as high as 40% for Pg2T‐T and 60% for P3HT, is obtained with >21% gm retained. Furthermore, high gms (9.34 mS and 0.92 mS for Pg2T‐T and P3HT, respectively) are maintained after 600 stretching cycles (20% and 30% tensile strains for Pg2T‐T and P3HT, respectively). Overall, the 3D porous structure provides an effective strategy to enhance stretchability and electrical performance for OECTs, as well as opens possibilities for other electronics where both stretchability and a large surface‐to‐volume ratio are needed.

Dynamic glucose monitoring is important to reduce the risk of metabolic diseases such as diabetes. Wearable biosensors based on organic electrochemical transistors (OECTs) have been developed due to their excellent signal amplification capabilities and biocompatibility. However, traditional wearable biosensors are fabricated on flat substrates with limited gas permeability, resulting in the inefficient evaporation of sweat, reduced wear comfort, and increased risk of inflammation. Here, we proposed breathable OECT-based glucose sensors by designing a porous structure to realize optimal breathable and stretchable properties. The gas permeability of the device and the relationship between electrical properties under different tensile strains were carefully investigated. The OECTs exhibit exceptional electrical properties (gm ~1.51 mS and Ion ~0.37 mA) and can retain up to about 44% of their initial performance even at 30% stretching. Furthermore, obvious responses to glucose have been demonstrated in a wide range of concentrations (10−7–10−4 M) even under 30% strain, where the normalized response to 10−4 M is 26% and 21% for the pristine sensor and under 30% strain, respectively. This work offers a new strategy for developing advanced breathable and wearable bioelectronics.

Purpose: To compare biomechanical and clinical properties of the novel internal fixation Interlocking Hip Screw (IHS) and conventional inverted triangle cannulated screws (ITCS) for treatment of Pauwels Ⅲ femoral neck fractures.Methods: Twenty synthetic femurs were osteotomized to simulate 70° Pauwels Ⅲ femoral neck fractures and randomly divided into two groups: Group IHS and Group ITCS. Specimens were loaded in quasi-static ramped and cyclical compression testing in 25° adduction to analyze for axial stiffness, failure load, and interfragmentary displacement. 21 matched patients with Pauwels Ⅲ femoral neck fracture who received closed reduction and internal fixation from January 2020 to January 2021 in both Group IHS and Group ITCS. Demographic data, time to surgery, operating duration, intraoperative blood loss, number of fluoroscopies, length of hospital stay, fracture healing time, Harris Hip Score (HHS), the score of Visual Analogue Scale (VAS) and complications such as nonunion, avascular necrosis, and femoral neck shortening were compared.Results: All specimens in the two groups survived in the axial and cyclical compression test. The axial stiffness was significantly higher for Group IHS (277.80 ± 26.58 N/mm) versus Group ITCS (205.33 ± 10.46 N/mm), p < 0.05. The maximum failure loading in Group IHS performed significantly higher than in Group ITCS (1,400.48 ± 71.60 N versus 996.76 ± 49.73 N, p < 0.05). The interfragmentary displacement of the cyclic loading test for Groups IHS and Group ITCS was 1.15 ± 0.11 mm and 1.89 ± 0.14 mm, respectively, p < 0.05. No significant difference was found in terms of demographic data, time to surgery, intraoperative blood loss, length of hospital stay and the occurrence of nonunion and avascular necrosis between groups. Shorter operating duration and fewer intraoperative fluoroscopic views were noticed using IHS compare to ITCS, p < 0.05. The HHS was 72.14 ± 5.76 and 86.62 ± 5.01 in Group IHS, and was 67.29 ± 5.27 and 81.76 ± 5.13 in Group ITCS at 3-month and 6-month follow-up, respectively, p < 0.05. The magnitude of femoral neck shortening was significantly lower in Group IHS compared to Group ITCS (4.80 ± 1.03 mm versus 5.56 ± 1.21 mm, p < 0.05).Conclusion: Our study demonstrated that IHS provided better biomechanical and clinical performance due to its unique biological and biomechanical mechanisms, compared with ITCS. Thus, IHS is a feasible alternative to ITCS for the fixation of Pauwels Ⅲ femoral neck fractures.

Residual current analysis of multiple stations’ periodic observational data for sea currents, and multiple voyages, multiple seasons from 2018 to 2022, revealed the existence of a strong southwest current zone, 20–30 m underwater and within the coastal current area of Yangjiang, western Guangdong, in the northwest region of the South China Sea. The velocity of the residual currents in the strong–current zone was 38.2–100.3 cm/s. Observational data for wind, sea currents, salinity and tide from multiple coastal stations in the spring (from March 2019 to May 2019) and summer (from June 2019 to August 2019) of 2019 demonstrated the existence of abrupt strong currents in the coastal current sea area of Yangjiang, western Guangdong. Analyses of continuous sequence hydro meteorological data for the Yangjiang area indicated that wind stress was the main factor determining the direction of sea currents; increases in the near-shore water level produce a westward geostrophic current and a wind current in the shallow sea area; their joint effect was the key factor determining the velocity of the coastal current in this sea area. In spring and summer, when Pearl River runoff into the sea reaches a peak, and under the action of the northeast wind, the water level on the west coast of Guangdong rose. This created a barotropic pressure–gradient force from the shore to the outer sea, generating a southwestward geostrophic current in the same direction as the wind-driven current. The joint action of the wind-driven and geostrophic currents then generated a sudden southwestward coastal current.

In population-oriented ergonomics product design and musculoskeletal kinetics analysis, digital spine models of different shape, pose and material property are in great demand. The purpose of this study was to construct a parameterized finite element spine model with adjustable spine shape and material property. We used statistical shape model approach to learn inter-subject shape distribution from 65 CT images of training subjects. Second order polynomial regression was used to model the age-dependent changes in vertebral material property derived from spatially aligned CT images. Finally, a parametric spine generator was developed to create finite element instances of different shapes and material properties. For quantitative analysis, the generalization ability to emulate spine shapes of different people was evaluated by fitting into 17 test CT images. The median fitting accuracy was 0.8 for Dice coefficient and 0.43 mm for average surface distance. The age-dependent bone density regression curve was also proved to well agree with large population statistics data. Finite element simulation was performed to compare how shape parameters influenced the biomechanics distribution of spine. The proposed parametric finite element whole spine model will assist the design process of new devices and biomechanical simulation towards a wide range of population.

Abstract Background To demonstrate the correlation between guide pin-shaft angle (PSA) at the anteroposterior film and anteversion angle of guide pin at the lateral film and investigate whether excellent tip–apex distance (TAD) can be obtained by changing the entry point via axial rotation of the main intramedullary nail. Methods Fifty patients with intertrochanteric femoral fractures (IFFs) undergoing internal fixation with intramedullary nails under 2D fluoroscopy were retrospectively enrolled. Both of the PSA at the anteroposterior film and anteversion angle at the lateral film before and after adjustment of the guide pin were collected. Pearson correlation analysis was performed to investigate their correlation. Intraoperative and postoperative outcomes were recorded. Furthermore, the software of Mimics 10.0 and Pro/E were used to establish the 3D models of the proximal femur and main intramedullary nail/guide pin, respectively. Surgery was simulated on the Pro/E software platform and solid geometry analysis was conducted to calculate the correlation between the PSA and the anteversion angle. Results Pearson correlation analysis indicated there was a positive correlation between PSA and anteversion angle, with the correlation coefficient of 0.902 (p

Filter-bank multicarrier with offset quadrature amplitude modulation (FBMC-OQAM) has been considered as an alternative scheme to orthogonal frequency division multiplexing (OFDM). However, the traditional channel estimation techniques of the OFDM cannot be directly applied to the FBMC-OQAM system because of the real-field orthogonality of the FBMC-OQAM signals. Although traditional channel estimation techniques, such as least square (LS) and minimum mean square error (MMSE), are widely applied to the FBMC-OQAM system via canceling the intrinsic imaginary interference from adjacent data symbols, the LS algorithm is subject to noise enhancement and it results in large mean square error (MSE), while the mmse algorithm needs to know the statistical information of channel in advance. Due to sparsity of the wireless channel, channel estimation is investigated as a compressive sensing (CS) problem. In this paper, we first introduce the coding method to cancel intrinsic imaginary interference for the FBMC-OQAM system. Then, a novel sparse adaptive subspace pursuit (SASP) method is proposed to improve the accuracy of LS channel estimation. Finally, we develop two distinctive algorithms, namely, auxiliary pilot (AP) SASP and coding-SASP, to estimate channel frequency respond (CFR) in the FBMC-OQAM system. The simulation results show that the AP-SASP and coding-SASP algorithms can offer a low complexity and fewer measurements compared with conventional orthogonal matching pursuit (OMP) and regularized OMP (ROMP) methods. Moreover, the proposed AP-SASP and coding-SASP algorithms have a better bit error ratio (BER) performance than the conventional OMP and ROMP methods for FBMC system in the doubly selective channels.

Objective: The aim of this study was to compare clinical outcomes of patients with femoral neck fractures treated with the dynamic hip system blade (DHS-BLADE) or cannulated compression screws. Methods: Eighty-six patients with femoral neck fractures were treated by closed reduction internal fixation with a DHS-BLADE (n = 42; 18 males and 24 females; mean age: 56.3 years (37–87)) or cannulated compression screws (n = 44; 20 males and 24 females; mean age: 53.8 years (26–83)) between March 2011 and August 2013. The groups were compared with Harris hip score, operation time, surgical blood loss, incision size, hospital stay, and related complications. Results: The average follow-up time was 27 months (range, 24–36 months). There was no significant difference for the operation time, incision size, hospital stay, and Harris hip score between the groups. Also, no statistically significant differences in the rates of nonunion (4.5% vs. 0) and avascular necrosis of the femoral head (9.1% vs. 7.1%) were observed. However, the screw group experienced significantly less surgical blood loss (32.4 ± 24.7 ml) than the blade group (87.2 ± 46.6 ml; P = 0.041). The incidence of femoral neck shortening above 10 mm in the screw group was significantly higher than that in the blade group (15.9% vs. 2.4%, P = 0.031). The blade group had a significantly lower incidence of screw migration than the screw group (4.8% vs. 22.7%, P = 0.016). Conclusion: The DHS-BLADE and cannulated compression screws might be equally effective in terms of postoperative fracture union. However, the DHS-BLADE has advantages over cannulated compression screws for preventing femoral neck shortening, screw migration, and cut-out. Level of evidence: Level III, Therapeutic study. Keywords: Femoral neck fracture, Cannulated screw, Dynamic hip system blade, Internal fixation

Quantum-inspired language models have been introduced to Information Retrieval due to their transparency and interpretability. While exciting progresses have been made, current studies mainly investigate the relationship between density matrices of difference sentence subspaces of a semantic Hilbert space. The Hilbert space as a whole which has a unique density matrix is lack of exploration. In this paper, we propose a novel Quantum Expectation Value based Language Model (QEV-LM). A unique shared density matrix is constructed for the Semantic Hilbert Space. Words and sentences are viewed as different observables in this quantum model. Under this background, a matching score describing the similarity between a question-answer pair is naturally explained as the quantum expectation value of a joint question-answer observable. In addition to the theoretical soundness, experiment results on the TREC-QA and WIKIQA datasets demonstrate the computational efficiency of our proposed model with excellent performance and low time consumption.

With the development of precise positioning with multi-GNSS, the inter-system bias (ISB) has become an issue that cannot be ignored. ISB is introduced from the differences among satellite reference clocks and different receiver hardware delay biases. To analyze the characteristics of multi-GNSS ISB, the precise point positioning (PPP) with full-rank uncombined model was derived for GLONASS, BDS, GALILEO, while the GPS receiver clock was selected as the reference. In addition, a recommended ISB parameter processing model was adopted. Data of 28-days from the Multi-GNSS Experiment (MGEX) station was used to estimate and analyze the ISB parameters. Based on a statistical analysis of the acquired data, results demonstrate that: (a) The rms of multi-GNSS PPP positional bias can reach 4.6 mm, 3.4 mm and 8.5 mm for E, N and U directions, respectively, which guarantees the reliability and accuracy of the ISB parameter solution. (b) The intra-day ISB time series of the three groups is relatively stable with standard deviations less than 0.6 ns. The ISB parameters between the GALILEO and GPS system are the most stable and the standard deviation was the smallest, at about 0.37 ns, which may be related to the good signal quality of the GALILEO system. (c) The mean of the single-day solution of the ISB parameter is not stable and the amplitude of the jump can be up to 60 ns. However, each station shows a similar variation for the same ISB parameter on the same day. The situation is independent of the type of receiver and antenna; however, it may be affected by the satellite reference clock of different systems. (d) There is a clear relationship between the ISB parameters and receiver types.

Spectrum sensing is an important task in cognitive radio. However, currently available Analog-to-Digital Converters (ADC) can hardly satisfy the sampling rate requirement for wideband signals. Even with such an ADC, the cost is extremely high in terms of price and power consumption. In this paper, we propose a spectrum-sensing method based on single-channel sub-Nyquist sampling. Firstly, a serial Multi-Coset Sampling (MCS) structure is designed to avoid mismatches among sub-ADCs in the traditional parallel MCS. Clocks of the sample/hold and ADC are provided by two non-uniform sampling clocks. The cooperation between these two non-uniform sampling clocks shifts the high sampling rate burden from the ADC to the sample/hold. Secondly, a power spectrum estimation method using sub-Nyquist samples is introduced, and an efficient spectrum-sensing algorithm is proposed. By exploiting the frequency-smoothing property, the proposed efficient spectrum-sensing algorithm only needs to estimate power spectrum at partial frequency bins to conduct spectrum sensing, which will save a large amount of computational cost. Finally, the sampling pattern design of the proposed serial MCS is given, and it is proved to be a minimal circular sparse ruler with an additional constraint. Simulations show that mismatches in traditional parallel MCS have a serious impact on spectrum-sensing performance, while the proposed serial MCS combined with the efficient spectrum-sensing algorithm exhibits outstanding spectrum-sensing performance at much lower computational cost.