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Abstract Motivation We are witnessing an enormous growth in the amount of molecular profiling (-omics) data. The integration of multi-omics data is challenging. Moreover, human multi-omics data may be privacy-sensitive and can be misused to de-anonymize and (re-)identify individuals. Hence, most biomedical data is kept in secure and protected silos. Therefore, it remains a challenge to re-use these data without infringing the privacy of the individuals from which the data were derived. Federated analysis of Findable, Accessible, Interoperable, and Reusable (FAIR) data is a privacy-preserving solution to make optimal use of these multi-omics data and transform them into actionable knowledge. Results The Netherlands X-omics Initiative is a National Roadmap Large-Scale Research Infrastructure aiming for efficient integration of data generated within X-omics and external datasets. To facilitate this, we developed the FAIR Data Cube (FDCube), which adopts and applies the FAIR principles and helps researchers to create FAIR data and metadata, to facilitate re-use of their data, and to make their data analysis workflows transparent, and in the meantime ensure data security and privacy.

[Introduction] With the continuous and rapid growth of the number of tree barrier inspections, visible light aerial photogrammetry has become the most important inspection method for hidden dangers of tree barriers in transmission lines of power supply bureaus in various cities. Since airborne laser radar cannot perform rapid iteration on a large number of point clouds, it is difficult to obtain high-precision point cloud power lines with visible light aerial photogrammetry. In the case of flourishing trees, it is difficult to comprehensively judge and analyze the relationship between tree tops, tree crowns and power lines, which results in problems such as misjudgment and omission of hidden dangers of tree barriers in the process of power line inspection. In order to solve this kind of problem, a solution of acquiring vectorized power line by laser radar is proposed. Through the intelligent analysis of vegetation information collected by multi-period visible light aerial photogrammetry, the solution of tree barrier is obtained. [Method] In view of the comprehensive situation that the image data collected by visible light aerial photogrammetry couldn't obtain high-precision point cloud power lines, it was difficult to simultaneously and comprehensively analyze the relationship between tree tops, tree crowns and power lines, and laser point cloud data couldn't be quickly iterated in large quantities, an overhead line tree barrier rapid analysis and processing system for multi-source spatio-temporal data of vectorized power lines was developed, which was suitable for the current conventional tree barrier inspection means, had comprehensive functions, saved resources, and was suitable for transmission and distribution networks. [Result] Through the three-dimensional real scene display of laser point cloud and visible light image data, the function of identifying and analyzing hidden dangers of tree barriers in power lines is realized. The vectorized power lines are complete and accurate. At the same time, combined with oblique photography technology, the data analysis of the hidden dangers of tree barriers results can identify 100% of the number of tree barrier hidden dangers. [Conclusion] The technical solution is accurate and effective, improves the efficiency and accuracy of the inspection of hidden dangers of tree barriers, and can provide guidance for practical application.

Mapping cultural ecosystem services (CES) in river basins is crucial for spatially identifying areas that merit conservation due to their significant CES contributions. However, precise quantification of the appropriate area of mapping units, which is the basis for CES assessment, is rare in existing studies. In this study, the optimal area threshold of mapping units (OATMU) identification, consisting of a multi-dimensional indicator framework and a methodology for validation, was established to clarify the boundary and the appropriate area of the mapping units for CES. The multi-dimensional indicator framework included geo-hydrological indicator (GI), economic indicator (EI) and social management indicator (SMI). The OATMU for each indicator was determined by seeking the inflection point in the second-order derivative of the power function. The minimum value of the OATMU for each indicator was obtained as the OATMU for CES. Finally, the OATMU for CES was validated by comparing it with the area of administrative villages in the river basin. The results showed the OATMU for CES was 3.60 km2. This study adopted OATMU identification, with easy access to basic data and simplified calculation methods, to provide clear and generic technical support for optimizing CES mapping.

Lithium metal batteries suffer from short lifespans and low Coulombic efficiency (CE) due to the high reactivity of Li and the poor stability of the solid electrolyte interphase (SEI). Herein, we propose the concept of a pseudo-concentrated electrolyte (PCE) induced by an electron-deficient additive (4-pyridylboronic acid; 4-PBA) to form a robust, LiF-rich SEI, thus addressing the above issues. Molecular dynamics simulations confirm that 4-PBA can increase the coordination number of PF6- anions in the Li+ solvation sheath to achieve pseudo-concentrated LiPF6 in the electrolyte. Moreover, the 4-PBA can scavenge harmful PF5 decomposed from LiPF6 to stabilize the LiF-rich SEI. The resulting robust LiF-rich SEI promotes Li growth along the SEI/Li interface and represses the growth of Li dendrites. Thus, excellent performance is achieved, with a high CE of 97.1% for a Li||Cu cell at 1.0 ​mA ​cm−2, and over 950 cycles at 0.5 ​mA ​cm−2 for Li||Li symmetric cells with 1.0 ​wt% 4-PBA electrolyte. Meanwhile, the resulting stable boron-containing cathode electrolyte interphase enables Li||LiNi0·6Co0·2Mn0·2O2 (NCM622) cells to achieve excellent stability, with a capacity retention of 86.9% after 200 cycles.

Abstract The construction of stable cathode electrolyte interphase (CEI) is the key to improve the NCM811 particle structure and interfacial stability via electrolyte engineering. In He’s work, lithium hexamethyldisilazide (LiHMDS) as the electrolyte additive is proposed to facilitate the generation of stable CEI on NCM811 cathode surface and eliminate H2O and HF in the electrolyte at the same time, which boosts the cycling performance of Li||NCM811 battery up to 1000 or 500 cycles with 4.5 V cut-off voltage at 25 or 60 °C.

The cooling effect of green infrastructure (GI) is becoming a hot topic on mitigating the urban heat island (UHI) effect. Alterations to the green space are a viable solution for reducing land surface temperature (LST), yet few studies provide specific guidance for landscape planning adapted to the different regions. This paper proposed and defined the landscape complexity and the threshold value of cooling effect (TVoE). Results find that: (1) GI provides a better cooling effect in the densely built-up area than the green belt; (2) GI with a simple form, aggregated configuration, and low patch density had a better cooling intensity; (3) In the densely built-up area, TVoE of the forest area is 4.5 ha, while in the green belt, TVoE of the forest and grassland area is 9 ha and 2.25 ha. These conclusions will help the planners to reduce LST effectively, and employ environmentally sustainable planning.

Bio‐inspired soft robots provide a promising solution for robots working in human‐centered scenarios and interacting with unstructured environments. However, the functional versatility and multimodal sensing of soft robots still need improvements. On one hand, the configuration of a soft robot is predefined during manufacturing; on the other hand, the multimodal perception of the deformable soft actuator is challenging. In this work, a reconfigurable and proprioceptive soft origami module is presented, where two kinds of basic actuation modes (i.e., extension and bending) are realized, and multimodal perception is enabled using a novel foldable self‐inductance sensor. As a result, the origami module can be reconfigured to assemble multifunctional robots that can measure interaction force, body configuration, and other environmental information. Dedicated experiments are performed to validate the performance of the proposed origami module. An intelligent gripper assembled using three origami modules is designed with the capabilities of grasping mode adjustment, grasping force measurement, and the grasping target's size measurement. An intelligent jellyfish is assembled using five origami modules, and equipped with buoyancy adjustment and underwater grasping capabilities. The proposed proprioceptive modular soft origami provides an effective solution for versatile and intelligent soft robot design.

BackgroundEmerging evidence suggests that exercise is a simple and effective method for maintaining brain function.AimsThis review evaluates the effects of five physical exercises, including aerobic training (AT), high-intensity interval training (HIIT), combined training (CT), resistance training (RT), and AT+RT, on the serum level of brain-derived neurotrophic factor (BDNF) in healthy and non-healthy populations.MethodsWe searched CNKI, PubMed, Embase, Scopus, Medline, Web of Science, and Cochrane Library databases to review randomized controlled studies on exercise interventions for BDNF. Quantitative merging analysis of the resulting data using Bayesian network meta-analysis.ResultsThe screening and exclusion of the searched literature resulted in the inclusion of 39 randomized controlled trials containing 5 exercise interventions with a total of 2031 subjects. The AT, RT, AT+RT, HIIT, and CT groups (intervention groups) and the CG group (conventional control group) were assigned to 451, 236, 102, 84, 293, and 865 subjects, respectively. The Bayesian network meta-analysis ranked the effect of exercise on BDNF level improvement in healthy and non-healthy subjects as follows: RT > HIIT > CT > AT+RT > AT > CG. Better outcomes were observed in all five intervention groups than in the CG group, with RT having the most significant effect [MD = 3.11 (0.33, 5.76), p < 0.05].ConclusionsRT at moderate intensity is recommended for children and older adults in the case of exercise tolerance and is effective in maintaining or modulating BDNF levels for promoting brain health.Systematic Review Registrationhttps://inplasy.com, INPLASY202250164.

Abstract The performance of lithium metal batteries (LMBs) is determined by many factors from the bulk electrolyte to the electrode‐electrolyte interphases, which are crucially affected by electrolyte additives. Herein, the authors develop the heptafluorobutyrylimidazole (HFBMZ) as a hexa‐functional additive to inhibit the dendrite growth on the surface of lithium (Li) anode, and then improve the cycling performance and rate capabilities of Li||LiNi0.6Co0.2Mn0.2O2 (NCM622). The HFBMZ can remove the trace H2O and HF from the electrolyte, reducing the by‐products on the surface of solid electrolyte interphase (SEI) and inhibiting the dissolution of metal ions from NCM622. Also, the HFBMZ can enhance the wettability of the separator to promote uniform Li deposition. HFBMZ can make Li+ easy to be desolvated, resulting in the increase of Li+ flux on Li anode surface. Moreover, the HFBMZ can optimize the composition and structure of SEI. Therefore, the Li||Li symmetrical cells with 1 wt% HFBMZ‐contained electrolyte can achieve stable cycling for more than 1200 h at 0.5 mA cm–2. In addition, the capacity retention rate of the Li||NCM622 can reach 92% after 150 cycles at 100 mA g–1.

Abstract The performance of Li batteries is influenced by the Li+ solvation structure, which can be precisely adjusted by the components of the electrolytes. In this review, we overview the strategies for optimizing electrolyte solvation structures from three different perspectives, including anion regulation, binding energy regulation, and additive regulation. These strategies can optimize the composition of the electrode‐electrolyte interface, enhance the anti‐oxidative stability of electrolytes as well as regulate the behaviors of anions, solvents, and Li+ during the cycling process. Moreover, we also provide our insights into these aspects as well as present perspectives on high‐performance Li batteries.

Lithium batteries are currently the most popular and promising energy storage system, but the current lithium battery technology can no longer meet people's demand for high energy density devices. Increasing the charge cutoff voltage of a lithium battery can greatly increase its energy density. However, as the voltage increases, a series of unfavorable factors emerges in the system, causing the rapid failure of lithium batteries. To overcome these problems and extend the life of high‐voltage lithium batteries, electrolyte modification strategies have been widely adopted. Under this content, this review first introduces the degradation mechanism of lithium batteries under high cutoff voltage, and then presents an overview of the recent progress in the modification of high‐voltage lithium batteries using electrolyte modification strategies. Finally, the future direction of high‐voltage lithium battery electrolytes is also proposed.

The urban landscape is being affected by rapid urbanization, leading to a complexity of land features and a fragmentation of patches. However, many studies have focused on the prediction of land-use change with a lack of research on the landscape character types which have more integrated descriptions of land features. Hence, this study predicts and identifies landscape character types (LCTs) in different periods based on the PLUS model and the K-Medoids algorithm, taking the central city of Chongqing as an example, to reveal the differences in the influence of driving factors on LCTs. The results show that (1) the urban landscape characteristic types present a gradient change from the built-up area to the outward expansion. (2) The SHDI and LPI of landscape character types decreased significantly with the expansion of construction land. (3) Nighttime light, distance from water bodies, and distance from the motorways are the main factors affecting the change of landscape character types. This study predicts and identifies urban landscape character types and quantifies the impact of urban expansion on landscape character. It can be used to guide urban planning and help governments to make more informed decisions on sustainable urban development and ecological conservation.

Ecological restoration has become an important tool for mitigating and adapting to environmental degradation caused by global urbanization. However, current research has focused on single indicators and qualitative analysis, meaning that ecological restoration has not been effectively and comprehensively addressed. This study constructed a spatial priority identification system for ecological restoration, with landscape area, landscape structure and landscape function as the core indicators. The system has wide adaptability. In this work, the spatial classification of ecological degradation was performed by overlay analysis. The results showed the following: (1) In the Shanghai metropolitan area, the landscape quality showed a trend of degradation, with built-up areas encroaching on forests and cropland. (2) Ecological degradation in the suburbs was more severe than that in the urban center. Forests had the highest landscape area indicator (LAI) stability. Significant degradation of landscape structure indicators (LSIs) occurred when built-up area and cropland were transformed into forests. (3) Different types of ecological restoration had significant spatial distribution patterns. Through this identification system, this study aimed to help planners/managers of ecological restoration to recognize the changing patterns of regional landscape quality and its relationship with land cover. It ultimately provides a basis for the formulation of regional ecological objectives and spatial strategies.

This paper proposes an improved impedance function for roads with mixed traffic. It is known that only limited studies consider the impact of nonmotorized traffic on travel impedance of a road segment, and a comparison of the impedance considering nonmotorized traffic with the classic BPR function, which does not consider the former, is scarce. Most of the previous studies targeted road conditions in developed countries, where the presence of nonmotorized traffic is negligible, and therefore limited efforts have been invested to develop improved impedance function considering mixed traffic. To overcome this limitation, this paper develops an improved impedance function and carries out a case study for a road in the city of Wuhan, China. The improved impedance function explicitly considers the interaction between motorized and nonmotorized traffic. Taxi GPS data from the case study road is used to extract and analyze the travel time of the “probe vehicles” running through the sampled segment at any time during a sampling day. The capacity of the road segment is measured, and the traffic flow of motorized vehicles and nonmotorized vehicles on the segment is counted. Based on the above data, the classic BPR function and the improved one proposed in this paper are calibrated. After comparing and analyzing the observed road impedance based on both analytical and simulation results, the classic BPR function and the proposed impedance function, the proposed impedance function is found to be more accurate to simulate the observed road impedance, with the error reducing from 14.83 s with the classic BPR impedance function to 6.50 s with the improved function. The proposed impedance function possesses a simple structure and high flexibility, and the parameters calibrated in this paper can be applied to similar roads to provide more realistic impedance than the previous ones based on the classic BPR function. The calibrated improved impedance function’s transferability to other similar roads is validated by applying it to another road and the results show that the percentage error between the predicted travel times and the observed ones is only 3.8%.