722 research outputs found
Ternary Organic Solar Cells Based on Two Highly Efficient Polymer Donors with Enhanced Power Conversion Efficiency
No full textTernary structures are demonstrated as a promising approach to increase the efficiency and light harvesting of solar cells. A high power conversion efficiency of 10.2% is achieved for ternary organic solar cells with two efficient polymer donors. The improved performance is attributed to the synergistic effects of enhanced light absorption and charge transport, efficient energy transfer, improved charge generation and morphology.clos
Engineered hydrogels as functional components in controllable neuromodulation for translational therapeutics
No full textControllable neuromodulation leveraging multimodal triggers synergized with hydrogels represents a transformative therapeutic strategy for pro-regenerative neural repair. Strategic incorporation of programmable neuromodulatory interventions and engineered hydrogels within localized neural niches is critical for clinical translation, characterized by lower invasiveness and greater therapeutic efficacy. This review elucidates the physiochemical features of hydrogels, systematically classifying hydrogel-based neuromodulation into five distinct modes (electrical, ionic, biomechanical, optical, and biochemical) and highlighting the intrinsic multidimensional structural and chemical engineering employed to enhance neuromodulatory performance. Key principles of hydrogel design and fabrication are provided from the perspective of tissue–implant interactions, such as mechanical compatibility, electrointegration, adhesion, and wireless activation. Hydrogels embedded with low-impedance organic and inorganic components, such as conductive polymers and noble metals, are investigated to provide high-level evidence to enable precise cellular stimulation for intrinsic nerve repair, neural prosthesis, and brain–machine interface. Crucially, this review highlights the synergistic integration of these principles into multimodal, closed-loop systems, which combine functions like electrophysiological sensing with on-demand biochemical release for intelligent, autonomous therapies. Finally, this review confronts the critical challenges for clinical translation and discusses future directions, including the potential of artificial intelligence-driven materials design to accelerate the development of next-generation neural interfaces
A Satellite Selection Algorithm for Achieving High Reliability of Ambiguity Resolution with GPS and Beidou Constellations
No full textReliability of carrier phase ambiguity resolution (AR) of an integer least-squares (ILS) problem depends on ambiguity success rate (ASR), which in practice can be well approximated by the success probability of integer bootstrapping solutions. With the current GPS constellation, sufficiently high ASR of geometry-based model can only be achievable at certain percentage of time. As a result, high reliability of AR cannot be assured by the single constellation. In the event of dual constellations system (DCS), for example, GPS and Beidou, which provide more satellites in view, users can expect significant performance benefits such as AR reliability and high precision positioning solutions. Simply using all the satellites in view for AR and positioning is a straightforward solution, but does not necessarily lead to high reliability as it is hoped. The paper presents an alternative approach that selects a subset of the visible satellites to achieve a higher reliability performance of the AR solutions in a multi-GNSS environment, instead of using all the satellites. Traditionally, satellite selection algorithms are mostly based on the position dilution of precision (PDOP) in order to meet accuracy requirements. In this contribution, some reliability criteria are introduced for GNSS satellite selection, and a novel satellite selection algorithm for reliable ambiguity resolution (SARA) is developed. The SARA algorithm allows receivers to select a subset of satellites for achieving high ASR such as above 0.99. Numerical results from a simulated dual constellation cases show that with the SARA procedure, the percentages of ASR values in excess of 0.99 and the percentages of ratio-test values passing the threshold 3 are both higher than those directly using all satellites in view, particularly in the case of dual-constellation, the percentages of ASRs (>0.99) and ratio-test values (>3) could be as high as 98.0 and 98.5 % respectively, compared to 18.1 and 25.0 % without satellite selection process. It is also worth noting that the implementation of SARA is simple and the computation time is low, which can be applied in most real-time data processing applications
Ambiguity Acceptance Testing : A Comparison of the Ratio Test and Difference Test
No full textInteger ambiguity resolution is an indispensable procedure for all high precision GNSS applications. The correctness of the estimated integer ambiguities is the key to achieving highly reliable positioning, but the solution cannot be validated with classical hypothesis testing methods. The integer aperture estimation theory unifies all existing ambiguity validation tests and provides a new prospective to review existing methods, which enables us to have a better understanding on the ambiguity validation problem. This contribution analyses two simple but efficient ambiguity validation test methods, ratio test and difference test, from three aspects: acceptance region, probability basis and numerical results. The major contribution of this paper can be summarized as: (1) The ratio test acceptance region is overlap of ellipsoids while the difference test acceptance region is overlap of half-spaces. (2) The probability basis of these two popular tests is firstly analyzed. The difference test is an approximation to optimal integer aperture, while the ratio test follows an exponential relationship in probability. (3) The limitations of the two tests are firstly identified. The two tests may under-evaluate the failure risk if the model is not strong enough or the float ambiguities fall in particular region. (4) Extensive numerical results are used to compare the performance of these two tests. The simulation results show the ratio test outperforms the difference test in some models while difference test performs better in other models. Particularly in the medium baseline kinematic model, the difference tests outperforms the ratio test, the superiority is independent on frequency number, observation noise, satellite geometry, while it depends on success rate and failure rate tolerance. Smaller failure rate leads to larger performance discrepancy
Generalized-positioning for mixed-frequency of mixed-GNSS and its preliminary applications
No full textModernized GPS and GLONASS, together with new GNSS systems, BeiDou and Galileo, offer code and phase ranging signals in three or more carriers. Traditionally, dual-frequency code and/or phase GPS measurements are linearly combined to eliminate effects of ionosphere delays in various positioning and analysis. This typical treatment method has imitations in processing signals at three or more frequencies from more than one system and can be hardly adapted itself to cope with the booming of various receivers with a broad variety of singles. In this contribution, a generalized-positioning model that the navigation system independent and the carrier number unrelated is promoted, which is suitable for both single- and multi-sites data processing. For the synchronization of different signals, uncalibrated signal delays (USD) are more generally defined to compensate the signal specific offsets in code and phase signals respectively. In addition, the ionospheric delays are included in the parameterization with an elaborate consideration. Based on the analysis of the algebraic structures, this generalized-positioning model is further refined with a set of proper constrains to regularize the datum deficiency of the observation equation system. With this new model, uncalibrated signal delays (USD) and ionospheric delays are derived for both GPS and BeiDou with a large dada set. Numerical results demonstrate that, with a limited number of stations, the uncalibrated code delays (UCD) are determinate to a precision of about 0.1 ns for GPS and 0.4 ns for BeiDou signals, while the uncalibrated phase delays (UPD) for L1 and L2 are generated with 37 stations evenly distributed in China for GPS with a consistency of about 0.3 cycle. Extra experiments concerning the performance of this novel model in point positioning with mixed-frequencies of mixed-constellations is analyzed, in which the USD parameters are fixed with our generated values. The results are evaluated in terms of both positioning accuracy and convergence time.\u
Fixed failure rate ambiguity validation methods for GPS\ud and compass
No full textAmbiguity resolution plays a crucial role in real time kinematic GNSS positioning which gives centimetre precision positioning results if all the ambiguities in each epoch are correctly fixed to integers. However, the incorrectly fixed ambiguities can result in large positioning offset up to several meters without notice. Hence, ambiguity validation is essential to control the ambiguity resolution quality. Currently, the most popular ambiguity validation is ratio test. The criterion of ratio test is often empirically determined. Empirically determined criterion can be dangerous, because a fixed criterion cannot fit all scenarios and does not directly control the ambiguity resolution risk. In practice, depending on the underlying model strength, the ratio test criterion can be too conservative for some model and becomes too risky for others.\ud
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A more rational test method is to determine the criterion according to the underlying model and user requirement. Miss-detected incorrect integers will lead to a hazardous result, which should be strictly controlled. In ambiguity resolution miss-detected rate is often known as failure rate. In this paper, a fixed failure rate ratio test method is presented and applied in analysis of GPS and Compass positioning scenarios. A fixed failure rate approach is derived from the integer aperture estimation theory, which is theoretically rigorous. The criteria table for ratio test is computed based on extensive data simulations in the approach. The real-time users can determine the ratio test criterion by looking up the criteria table. This method has been applied in medium distance GPS ambiguity resolution but multi-constellation and high dimensional scenarios haven't been discussed so far. \ud
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In this paper, a general ambiguity validation model is derived based on hypothesis test theory, and fixed failure rate approach is introduced, especially the relationship between ratio test threshold and failure rate is examined. In the last, Factors that influence fixed failure rate approach ratio test threshold is discussed according to extensive data simulation. The result shows that fixed failure rate approach is a more reasonable ambiguity validation method with proper stochastic model
Impact of donor halogenation on reorganization energies and voltage losses in bulk-heterojunction solar cells
No full textDonor halogenation is a common molecular design strategy used to reduce voltage losses (ΔVloss) and improve the power conversion efficiency (PCE) of bulk-heterojunction (BHJ) organic solar cells. Here, the impact of donor halogenation on the performance of organic donor–acceptor (DA) solar cells based on over 30 different materials systems is investigated, and the main reason for the improved performance of solar cells after donor halogenation is ascribed to the increased energy of the charge transfer (CT) state, and the reduced reorganization energy of the CT states (λCT). Also, the impact of donor halogenation on λCT is found to be stronger for the solar cells using the Y-series acceptors (Y5, Y6, etc.) than those using the non-Y-series acceptors (fullerene, ITIC, etc.), which is conducive to achieving lower ΔVloss in organic solar cells. Finally, the impact of donor halogenation on the solar cell performance is demonstrated to be dependent on the halogen substitution position, as well as the number of halogen atoms added to the donor molecule: Halogen substitution on the side groups of the donor molecule is found to be more effective than substitution at the backbone in reducing ΔVloss. These results suggest that future molecular design strategies focusing on the reduction of materials reorganization energy will be of great importance for further improving the performance of organic solar cells
Orbit determination of FedSat based on GPS receiver position solutions – first results
No full textOn 14th December 2002, the Australian small satellite FedSat was launched with a Japanese HII-A rocket into an 800 km sun-synchronous orbit with an inclination of 98.6 degrees. One of the payloads is a dual frequency GPS BlackJack receiver from NASA Jet Propulsion Laboratory (JPL). This receiver provides a Position, Velocity and Time (PVT) solution and also raw measurements (code and carrier), which will be used in different ways for\ud
Precise Orbit Determination (POD), Orbit Determination (OD) based on GPS position solutions, 2-axis Attitude Determination (AD) and atmospheric experiments
Influenza Epidemic Trend Surveillance and Prediction Based on Search Engine Data: Deep Learning Model Study
No full textBackground: influenza outbreaks pose a significant threat to global public health. Traditional surveillance systems and simple algorithms often struggle to predict influenza outbreaks in an accurate and timely manner. Big data and modern technology have offered new modalities for disease surveillance and prediction. Influenza-like illness can serve as a valuable surveillance tool for emerging respiratory infectious diseases like influenza and COVID-19, especially when reported case data may not fully reflect the actual epidemic curve.Objective: this study aimed to develop a predictive model for influenza outbreaks by combining Baidu search query data with traditional virological surveillance data. The goal was to improve early detection and preparedness for influenza outbreaks in both northern and southern China, providing evidence for supplementing modern intelligence epidemic surveillance methods.Methods: we collected virological data from the National Influenza Surveillance Network and Baidu search query data from January 2011 to July 2018, totaling 3,691,865 and 1,563,361 respective samples. Relevant search terms related to influenza were identified and analyzed for their correlation with influenza-positive rates using Pearson correlation analysis. A distributed lag nonlinear model was used to assess the lag correlation of the search terms with influenza activity. Subsequently, a predictive model based on the gated recurrent unit and multiple attention mechanisms was developed to forecast the influenza-positive trend.Results: this study revealed a high correlation between specific Baidu search terms and influenza-positive rates in both northern and southern China, except for 1 term. The search terms were categorized into 4 groups: essential facts on influenza, influenza symptoms, influenza treatment and medicine, and influenza prevention, all of which showed correlation with the influenza-positive rate. The influenza prevention and influenza symptom groups had a lag correlation of 1.4-3.2 and 5.0-8.0 days, respectively. The Baidu search terms could help predict the influenza-positive rate 14-22 days in advance in southern China but interfered with influenza surveillance in northern China.Conclusions: complementing traditional disease surveillance systems with information from web-based data sources can aid in detecting warning signs of influenza outbreaks earlier. However, supplementation of modern surveillance with search engine information should be approached cautiously. This approach provides valuable insights for digital epidemiology and has the potential for broader application in respiratory infectious disease surveillance. Further research should explore the optimization and customization of search terms for different regions and languages to improve the accuracy of influenza prediction models.</p
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