Resource amendments commonly promote plant invasions, raising concerns over the potential consequences of nitrogen (N) deposition; however, it is unclear whether invaders will benefit from N ...deposition more than natives. Growth is among the most fundamental inherent traits of plants and thus good invaders may have superior growth advantages in response to resource amendments. We compared the growth and allocation between invasive and native plants in different N regimes including controls (ambient N concentrations). We found that invasive plants always grew much larger than native plants in varying N conditions, regardless of growth- or phylogeny-based analyses, and that the former allocated more biomass to shoots than the latter. Although N addition enhanced the growth of invasive plants, this enhancement did not increase with increasing N addition. Across invasive and native species, changes in shoot biomass allocation were positively correlated with changes in whole-plant biomass; and the slope of this relationship was greater in invasive plants than native plants. These findings suggest that enhanced shoot investment makes invasive plants retain a growth advantage in high N conditions relative to natives, and also highlight that future N deposition may increase the risks of plant invasions.
Recent studies have identified genes and core pathways that are altered in human glioblastoma. However, the mechanisms by which alterations of these glioblastoma genes singly and cooperatively ...transform brain cells remain poorly understood. Further, the cell of origin of glioblastoma is largely elusive. By targeting a
p53 in-frame deletion mutation to the brain, we show that p53 deficiency provides no significant growth advantage to adult brain cells, but appears to induce pleiotropic accumulation of cooperative oncogenic alterations driving gliomagenesis. Our data show that accumulation of a detectable level of mutant p53 proteins occurs first in neural stem cells in the subventricular zone (SVZ) and that subsequent expansion of mutant p53-expressing Olig2
+ transit-amplifying progenitor-like cells in the SVZ-associated areas initiates glioma formation.
Background
Cancer pain management is still unsatisfactory, although some effective guidelines exist. Educational interventions are reported to be useful in pain relief for oncology outpatients.
Aim
...The aims of this systematic review were to evaluate the effects of nurse‐led educational interventions on improving cancer pain outcomes for oncology patients, and to establish an effective cancer pain protocol for clinical nursing practice in China.
Methods
A three‐step search strategy was utilized. Eight databases were searched using the standards provided by the Joanna Briggs Institute that guided article selection, critical appraisal, data collection and data synthesis.
Results
A total of 1093 studies were identified through a literature search. Only six studies complied with the inclusion criteria and were found to be methodologically sound. In general, the included studies indicated positive results pertaining to patient's knowledge and attitudes towards analgesics and cancer pain management and decreased pain intensity. Studies reported minimal effects of intervention on anxiety, depression, satisfaction regarding cancer pain management and patient's quality of life.
Conclusions
Educational interventions were reported as effective methods to improve cancer pain outcomes. Analysis of the six included studies demonstrated the overall positive effects of nurse‐led educational interventions for improving cancer pain management.
Implications for nursing and health policy
The results suggest that an effective cancer pain protocol for improving cancer pain management can be established in China.
Two proton-receptor sensors for detecting pH change based on 1,8-naphthalimide, N-allyl-4-(4'-N,N-dioctylpropionamide-acetamido-piperazinyl)-1,8-naphthalimide (
1
), and ...N-(N,N-dioctylpropionamide-acetamido)-4-allyl-1-piperazinyl-1,8-naphthalimide (
2
), were designed, synthesized, and characterized. Photophysical characteristics of the sensors were investigated in different organic solvents and Britton–Robinson buffer/EtOH (1:1, v/v) solution. Sensor
2
displayed a good sensor activity towards protons within the pH range from 3.29 to 6.59, while sensor
1
demonstrated sensitivity to lower pH values from 2.21 to 4.35. The selectivity of the pH sensors toward protons in commonly used buffer solutions and in the presence of metal cations (Na
+
, K
+
, Ca
2+
, Mg
2+
, Al
3+
, Pb
2+
, Fe
3+
, Ni
2+
, Zn
2+
, Cu
2+
, Hg
2+
, Ag
+
, Co
2+
, Cr
3+
, Mn
2+
, and Cd
2+
) was studied by monitoring the changes in their fluorescence intensity. The results obtained indicate that the synthesized derivatives hold potential for monitoring pH variations between 2.21 and 6.59 in strong acid environments and bio-samples.
This phase 3, randomized trial in China compared the efficacy and safety of roxadustat, an oral hypoxia-inducible factor prolyl hydroxylase inhibitor, with placebo for anemia in patients with CKD who ...were not undergoing dialysis. Roxadustat was superior to placebo in increasing and maintaining hemoglobin levels.
Standalone renewable energy system holds the most promising solution to the electrification of remote areas without utility grid access as well as to reduce fossil fuel consumption and environmental ...pollution. However, the random volatility and unpredictability of renewable energy are key factors to restrict its large-scale accommodation. In the present study, a multi-objective mean-semi-entropy model is proposed for a standalone micro-grid with photovoltaic-wind-battery-diesel generator hybrid system, with the aim of providing a trade-off solution between maximum profits and minimum risk in consideration of photovoltaic and wind uncertainties. Then, the preference-inspired co-evolutionary algorithm, along with Pareto optimality concept, is used for the system techno-economic optimization, i.e., to maximize the profits defined as the mean value of the return and to minimize the risk defined as the semi-entropy simultaneously. Subsequently, the preference ranking organization method is used for decision making to determine the optimal trade-off dispatch solution. Simulation results show that the multi-objective mean-semi-entropy model is well applicable to deal with standalone micro-grid operation, considering the integration of uncertain renewable energy resources.
•A planning method for standalone micro-grid with uncertain wind and photovoltaic power is investigated.•A multi-objective mean-semi-entropy model for optimal standalone micro-grid operation is proposed.•An optimal dispatch solution from the perspective of risk aversion and profit maximization is studied.•Different models are employed for comparison to fully evaluate the effectiveness of the proposed model.
Steering micromotors is important for using them in practical applications and as model systems for active matter. This functionality often requires magnetic materials in the micromotor, taxis ...behavior of the micromotor, or the use of specifically designed physical boundaries. Here, we develop an optoelectronic strategy that steers micromotors with programmable light patterns. In this strategy, light illumination turns hydrogenated amorphous silicon conductive, generating local electric field maxima at the edge of the light pattern that attracts micromotors via positive dielectrophoresis. As an example, metallo-dielectric Janus microspheres that self-propelled under alternating current electric fields were steered by static light patterns along customized paths and through complex microstructures. Their long-term directionality was also rectified by ratchet-shaped light patterns. Furthermore, dynamic light patterns that varied in space and time enabled more advanced motion controls such as multiple motion modes, parallel control of multiple micromotors, and the collection and transport of motor swarms. This optoelectronic steering strategy is highly versatile and compatible with a variety of micromotors, and thus it possesses the potential for their programmable control in complex environments.
Deep learning based spectral CT imaging Wu, Weiwen; Hu, Dianlin; Niu, Chuang ...
Neural networks,
December 2021, 2021-12-00, 20211201, Letnik:
144
Journal Article
Recenzirano
Odprti dostop
Spectral computed tomography (CT) has attracted much attention in radiation dose reduction, metal artifacts removal, tissue quantification and material discrimination. The x-ray energy spectrum is ...divided into several bins, each energy-bin-specific projection has a low signal-noise-ratio (SNR) than the current-integrating counterpart, which makes image reconstruction a unique challenge. Traditional wisdom is to use prior knowledge based iterative methods. However, this kind of methods demands a great computational cost. Inspired by deep learning, here we first develop a deep learning based reconstruction method; i.e., U-net with Lpp-norm, Total variation, Residual learning, and Anisotropic adaption (ULTRA). Specifically, we emphasize the various multi-scale feature fusion and multichannel filtering enhancement with a denser connection encoding architecture for residual learning and feature fusion. To address the image deblurring problem associated with the L22- loss, we propose a general Lpp-loss, p>0. Furthermore, the images from different energy bins share similar structures of the same object, the regularization characterizing correlations of different energy bins is incorporated into the Lpp- loss function, which helps unify the deep learning based methods with traditional compressed sensing based methods. Finally, the anisotropically weighted total variation is employed to characterize the sparsity in the spatial–spectral domain to regularize the proposed network In particular, we validate our ULTRA networks on three large-scale spectral CT datasets, and obtain excellent results relative to the competing algorithms. In conclusion, our quantitative and qualitative results in numerical simulation and preclinical experiments demonstrate that our proposed approach is accurate, efficient and robust for high-quality spectral CT image reconstruction.
This paper seeks to shed light on how ports spread their influence through propagatory activation of other ports in the global oil traffic network from 2009 to 2016. Using a modified linear threshold ...model, the paper does not attempt to identify a few fixed ports that served as “seeds” for propagation and influence maximization. Instead it identifies active seed port hubs via their diffusion patterns and the number of ports in the networks that become influenced as a result. The computations show that diffusion is highly uneven but Rotterdam, Antwerp and Singapore emerged as the three most influential seed ports particularly in 2013 and 2016. Whereas over half of the ports in the networks were able to influence just one other port, Rotterdam and Antwerp influenced ports in the entire network. Singapore's spread of influence is smaller but its activation rate is more rapid because the port-city's influence tends to be much more regionally confined. Rotterdam's propagation occurs in fewer stages than Antwerp's suggesting that information and innovation spread more readily from the former city-port. Taken together, the analysis points to the above three city-ports as the most effective hubs for dissemination of information in the oil, including tanker, industry.
•A modified LT model are proposed to measure the diffusion of influence among ports.•The diffusion of influence among ports is highly uneven.•Half of the ports in the networks were able to influence just one other port.•Rotterdam, Antwerp and Singapore emerged as the three most influential ports.
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