SOC estimation of lead-carbon battery based on GA-MIUKF algorithm.

The paper proposes a SOC (State of Charge) estimation method for lead-carbon batteries based on the GA-MIUKF algorithm. The GA-MIUKF algorithm combines GA (Genetic Algorithm) for global search and optimization with the MI-UKF (Multi-innovation Unscented Kalman Filter) algorithm for estimating the SOC of lead-carbon batteries. By establishing an equivalent circuit model for the battery, the GA is employed to globally search and optimize the battery model parameters and the noise variance parameters in the MI-UKF algorithm. Comparative analyses with the UKF (Unscented Kalman Filter) algorithms and MI-UKF algorithms reveal that the SOC estimation method based on the GA-MIUKF algorithm yields more accurate results for lead-carbon battery SOC estimation, with an average estimation error of 2.0%. This highlights the efficacy of the proposed approach in enhancing SOC estimation precision.

Comparative analysis of trophic niche using stable isotopes provides insight into resource use of giant pandas.

Trophic niche is the result of the long-term evolution of species and can reflect the pressures they experience in habitats. The whole-genome sequencing of giant pandas (Ailuropoda melanoleuca) has indicated that populations distributed in Qinling (QIN) and non-QIN probably diverged 300 ky ago. Although many studies regarding foraging strategy, habitat preference, and niche partition have been conducted on these populations, there is still a lack of precise quantification of trophic niches. Here, we calculated and compared isotopic trophic niche widths of giant pandas from Sichuan (SC) and QIN populations by measuring carbon and nitrogen isotopes of their hairs; combined with data from sympatric mammals, we explored the relative trophic positions of giant pandas in the ecosystem, respectively. The Stable Isotope Bayesian Ellipses in R (SIBER) model results showed the trophic niche width of QIN pandas was 3.44‰2 , which was significantly bigger than those of the SC population (2.03‰2 ), with an overlapping about 1.45‰2 ; and they both occupied a unique position in the context, almost one trophic level lower than herbivores. Then, we determined the isotopic ratios of the main foods from the habitats of these pandas; the results suggested that the isotopic difference between bamboo shoots and other parts plus the various feeding selections of pandas on them accounted for pandas' trophic niche widths. We considered the higher nutrition availability and digestible food resources giving QIN pandas a wider trophic niche than pandas from SC. This conclusion provides a new insight into the resource use and trophic ecology of giant pandas and is important to develop refined management plans for the two populations.

Assessing the effectiveness of protected areas for panda conservation under future climate and land use change scenarios.

While the relatively stable land use and land cover (LULC) patterns is an important feature of protected areas (PAs), the influence of this feature on future species distribution and the effectiveness of the PAs has rarely been explored. Here, we assessed the role of land use patterns within PAs on the projected range of the giant panda (Ailuropoda melanoleuca) by comparing projections inside and outside of PAs for four model configurations: (1) only climate covariates, (2) climate and dynamic land use covariates, (3) climate and static land use covariates and (4) climate and hybrid dynamic-static land use covariates. Our objectives were twofold: to understand the role of protected status on projected panda habitat suitability and evaluate the relative efficacy of different climate modeling approaches. The climate and land use change scenarios used in the models include two shared socio-economic pathways (SSPs) scenarios: SSP126 [an optimistic scenario] and SSP585 [a pessimistic scenario]. We found that models including land-use covariates performed significantly better than climate-only models and that these projected more suitable habitat than climate-only models. Static land-use models projected more suitable habitat than both the dynamic and hybrid models under SSP126, while these models did not differ under SSP585. China's panda reserve system was projected to effectively maintain suitable habitat inside PAs. Panda dispersal ability also significantly impacted outcomes, with most models assuming unlimited dispersal forecasting range expansion and models assuming zero dispersal consistently forecasting range contraction. Our findings highlight that policies targeting improved land-use practices should be an effective means for offsetting some of the negative effects of climate change on pandas. As the effectiveness of PAs is projected to be maintained, we recommend the judicious management and expansion of the PA system to ensure the resilience of panda populations into the future.

Surface engineering of Al2O3 nanotubes by ureasolysis method for activating persulfate degradation of antibiotics.

Though ecofriendly, pure Al2O3 has never been used for activation of peroxodisulfate (PDS) to degrade pollutants. We report the fabrication of Al2O3 nanotubes by ureasolysis method for efficient activating PDS degradation of antibiotics. The fast ureasolysis in aqueous AlCl3 solution produces NH4Al(OH)2CO3 nanotubes, which are calcined to porous Al2O3 nanotubes, and the release of ammonia and carbon dioxide engineers the surface features of large surface area, numerous acidic-basic sites and suitable Zeta potentials. The synergy of these features facilitates the adsorption of the typical antibiotics ciprofloxacin and PDS activation, which is proved by experiment results and density functional theory simulation. The proposed Al2O3 nanotubes can catalyze 92-96% degradation of 10 ppm ciprofloxacin within 40 min, with chemical oxygen demand removal of 65-66% in aqueous, and 40-47% in whole including aqueous and catalysts. Ciprofloxacin at high concentration, other fluoroquinolones and tetracycline can also be effectively degraded. These data demonstrate the Al2O3 nanotubes prepared by the nature-inspired ureasolysis method has unique features and great potentials for antibiotics degradation.

Large variability in response to future climate and land-use changes among Chinese Theaceae species.

Theaceae is an important family in the phylogeny of angiosperm in China, which are potentially threatened by future changes in climatic and land use conditions. Therefore, understanding and predicting the isolated and combined effects of these two global change factors on Theaceae species is crucial for biodiversity conservation. Here, we assessed the isolated and combined effects of climate and land use change on the distribution shifts of 95 Theaceae species under different future scenarios by comparing projections of three model configurations: (1) dynamics climate and constant land use variables; (2) constant climate and dynamics land use variables; and (3) dynamics climate and dynamics land use variables. We find that all the three types of models predicted range contractions for most of the 95 Theaceae species under all future scenarios. Moreover, we find that climate change has rather strong effect for most species while land use change has nonsignificant or weak effect on future species distributions, although both of these two isolated effects are highly variable across individual species. Finally, the combined effect of these two factors reveals that the land use change may amplify or buffer distribution shifts expected from climate change impact depending on species. These findings emphasize the importance of taking into account the large variability in response to land use change among Theaceae species when developing land-based conservation strategies in a changing climate.

Giant pandas' staple food bamboo phyllosphere fungal community and its influencing factors.

Giant pandas have developed a series of foraging strategies to adapt to their special bamboo diets. Although bamboo is an important food resource for giant pandas in Liziping National Nature Reserve (Liziping NR), China, there are relatively few studies on their phyllosphere fungal community and its influencing factors. Herein, we used ITS1 amplification and metagenomic sequencing to analyze the phyllosphere fungi diversity and functions (KEGG, CAZyme, and antibiotic resistance gene) and explore the influencing factors for the three giant pandas foraging bamboo species (Arundinaria spanostachya, AS; Yushania lineolate, YL; and Fargesia ferax, FF) over different seasons (spring vs. autumn) in Liziping NR, China. We found that Ascomycota and Basidiomycota were the most dominant phyla in the bamboo phyllosphere. The alpha diversity (e.g., the Sobs index and Shannon index) was relatively higher in autumn samples than in spring samples, and the community structure differed significantly between the three bamboo species in spring and autumn. Some biotic and abiotic variables (e.g., the elevation and mean base diameter of bamboo) significantly influenced the abundance, diversity, and community structure of the bamboo phyllosphere fungal community. Moreover, the functional analysis showed the differences in the glycoside hydrolase community and antibiotic resistance gene (ARG) profile between spring and autumn samples. Co-occurrence network modeling suggested that AS phyllosphere fungal communities in autumn employed a much more complex network than that in spring, and the abundance of multidrug, tetracycline, and glycopeptide resistance genes was high and closely correlated with other ARGs. These results indicate that fungal community's abundance, diversity, and community structure are mainly affected by the season, host species, and elevation. The season and host species are major factors affecting the biological functions (KEGG and CAZyme), ARGs, and interactions between sympatric bacterial and fungal communities in bamboo phyllosphere. This integrated study can provide a reference basis for the seasonal management of bamboo resources foraged by wild giant pandas, and predict the risk of antibiotic resistance in bamboo phyllosphere fungal flora in Liziping NR (Xiaoxiangling mountains), China.

Predicting range shifts of the giant pandas under future climate and land use scenarios.

Understanding and predicting how species will respond to global environmental change (i.e., climate and land use change) is essential to efficiently inform conservation and management strategies for authorities and managers. Here, we assessed the combined effect of future climate and land use change on the potential range shifts of the giant pandas (Ailuropoda melanoleuca) in Sichuan Province, China. We used species distribution models (SDMs) to forecast range shifts of the giant pandas by the 2050s and 2070s under four combined climate and land use change scenarios. We also compared the differences in distributional changes of giant pandas among the five mountains in the study area. Our SDMs exhibited good model performance and were not overfitted, with a mean Boyce index of 0.960 ± 0.015 and a mean omission rate of 0.002 ± 0.003, and suggested that precipitation seasonality, annual mean temperature, the proportion of forest cover, and total annual precipitation are the most important factors in shaping the current distribution pattern of the giant pandas. Our projections of future species distribution also suggested a range expansion under an optimistic greenhouse gas emission, while suggesting a range contraction under a pessimistic greenhouse gas emission. Moreover, we found that there is considerable variation in the projected range change patterns among the five mountains in the study area. Especially, the suitable habitat of the giant panda is predicted to increase under all scenarios in the Minshan mountains, while is predicted to decrease under all scenarios in Daxiangling and Liangshan mountains, indicating the vulnerability of the giant pandas at low latitudes. Our findings highlight the importance of an integrated approach that combines climate and land use change to predict the future species distribution and the need for a spatial explicit consideration of the projected range change patterns of target species for guiding conservation and management strategies.

Forecasting the combined effects of future climate and land use change on the suitable habitat of Davidia involucrata Baill.

Accurately predicting the future distribution of species is crucial for understanding how species will response to global environmental change and for evaluating the effectiveness of current protected areas (PAs). Here, we assessed the effect of climate and land use change on the projected suitable habitats of Davidia involucrata Baill under different future scenarios using the following two types of models: (a) only climate covariates (climate SDMs) and (b) climate and land use covariates (full SDMs). We found that full SDMs perform significantly better than climate SDMs in terms of both AUC (p < .001) and TSS (p < .001) and also projected more suitable habitat than climate SDMs both in the whole study area and in its current suitable range, although D. involucrate is predicted to loss at least 26.96% of its suitable area under all future scenarios. Similarly, we found that these range contractions projected by climate SDMs would negate the effectiveness of current PAs to a greater extent relative to full SDMs. These results suggest that although D. involucrate is extremely vulnerability to future climate change, conservation intervention to manage habitat may be an effective option to offset some of the negative effects of a changing climate on D. involucrate and can improve the effectiveness of current PAs. Overall, this study highlights the necessity of integrating climate and land use change to project the future distribution of species.

Efficient Experimental Verification of Quantum Gates with Local Operations.

Verifying the correct functioning of quantum gates is a crucial step toward reliable quantum information processing, but it becomes an overwhelming challenge as the system size grows due to the dimensionality curse. Recent theoretical breakthroughs show that it is possible to verify various important quantum gates with the optimal sample complexity of O(1/ε) using local operations only, where ε is the estimation precision. In this Letter, we propose a variant of quantum gate verification (QGV) that is robust to practical gate imperfections and experimentally realize efficient QGV on a 2-qubit controlled-not gate and a 3-qubit Toffoli gate using only local state preparations and measurements. The experimental results show that, by using only 1600 and 2600 measurements on average, we can verify with 95% confidence level that the implemented controlled-not gate and Toffoli gate have fidelities of at least 99% and 97%, respectively. Demonstrating the superior low sample complexity and experimental feasibility of QGV, our work promises a solution to the dimensionality curse in verifying large quantum devices in the quantum era.

[miR-494 promotes islet ß cell proliferation, inhibits apoptosis and increases insulin secretion by activating Wnt/ß-catenin signaling pathway].

Objective To investigate the relation between the miR-494 expression with pancreatic islets ß cell function and gestational diabetes mellitus. Methods Twenty patients with gestational diabetes mellitus and healthy subjects were enrolled. The content of miR-494 in peripheral blood was measured by reverse transcription PCR. INS-1 cells were cultured and treated with low glucose (3.3 mmol/L) and high glucose (16.7 mmol/L), respectively. The insulin concentration was tested by ELISA to evaluate the insulin secretion of islet cells stimulated by high glucose. Cells were collected, after treated with miR-494 mimics control, miR-494 mimics, miR-494 inhibitor control and miR-494 inhibitor for 24 hours, 48 hours and 72 hours, respectively. The activity of INS-1 cells was detected by MTT assay; Apoptosis was detected by flow cytometry. Reverse transcription PCR and Western blot analysis were used to detect the mRNA and protein expression of Wnt3a, ß-catenin, cyclin D1 and c-Myc, respectively. Results Compared with the normal control, fasting insulin, fasting blood glucose, 1 hour-blood glucose and 2 hour-blood glucose in patients with gestational diabetes mellitus increased significantly. The content of miR-494 in peripheral blood decreased. The insulin concentration in the supernatant of INS-1 cells overexpressing miR-494 increased. When high glucose was given, the overexpression of miR-494 further promoted insulin secretion. Overexpression of miR-494 significantly promoted INS-1 cell activity and inhibited INS-1 cell apoptosis. miR-494 significantly promoted the protein expression of Wnt3a, ß-catenin, cyclin D1 and c-Myc. miR-494 inhibitor treatment showed the opposite results. Conclusion miR-494 promotes islet ß cell proliferation, inhibits apoptosis and increases insulin secretion by activating Wnt/ß-catenin signaling pathway.

Predicting range shifts of Davidia involucrata Ball. under future climate change.

Understanding and predicting how species will respond to climate change is crucial for biodiversity conservation. Here, we assessed future climate change impacts on the distribution of a rare and endangered plant species, Davidia involucrate in China, using the most recent global circulation models developed in the sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC6). We assessed the potential range shifts in this species by using an ensemble of species distribution models (SDMs). The ensemble SDMs exhibited high predictive ability and suggested that the temperature annual range, annual mean temperature, and precipitation of the driest month are the most influential predictors in shaping distribution patterns of this species. The projections of the ensemble SDMs also suggested that D. involucrate is very vulnerable to future climate change, with at least one-third of its suitable range expected to be lost in all future climate change scenarios and will shift to the northward of high-latitude regions. Similarly, at least one-fifth of the overlap area of the current nature reserve networks and projected suitable habitat is also expected to be lost. These findings suggest that it is of great importance to ensure that adaptive conservation management strategies are in place to mitigate the impacts of climate change on D. involucrate.

Cell Walls Are Remodeled to Alleviate nY2O3 Cytotoxicity by Elaborate Regulation of de Novo Synthesis and Vesicular Transport.

Yttrium oxide nanoparticles (nY2O3), one of the broadly used rare earth nanoparticles, can interact with plants and possibly cause plant health and environmental impacts, but the plant defense response particularly at the nanoparticle-cell interface is largely unknown. To elucidate this, Bright Yellow 2 (BY-2) tobacco (Nicotiana tabacum L.) suspension-cultured cells were exposed to 50 mg L-1 nY2O3 (30 nm) for 12 h. Although 42.2% of the nY2O3 remained outside of protoplasts, nY2O3 could still traverse the cell wall and was partially deposited inside the vacuole. In addition to growth inhibition, morphological and compositional changes in cell walls occurred. Together with a locally thickened (7-13-fold) cell wall, increased content (up to 58%) of pectin and reduction in (up to 29%) hemicellulose were observed. Transcriptome analysis revealed that genes involved in cell wall metabolism and remodeling were highly regulated in response to nY2O3 stress. Expression of genes for pectin synthesis and degradation was up- and down-regulated by 31-78% and 13-42%, respectively, and genes for xyloglucan and pectin modifications were up- and down-regulated by 82% and 81-92%, respectively. Interestingly, vesicle trafficking seemed to be activated, enabling the repair and defense against nY2O3 disturbance. Our findings indicate that, although nY2O3 generated toxicity on BY-2 cells, it is very likely that during the recovery process cell wall remodeling was initiated to gain resistance to nY2O3 stress, demonstrating the plant's cellular regulatory machinery regarding repair and adaptation to nanoparticles like nY2O3.

"Super-Heisenberg" and Heisenberg Scalings Achieved Simultaneously in the Estimation of a Rotating Field.

The Heisenberg scaling, which scales as N^{-1} in terms of the number of particles or T^{-1} in terms of the evolution time, serves as a fundamental limit in quantum metrology. Better scalings, dubbed as "super-Heisenberg scaling," however, can also arise when the generator of the parameter involves many-body interactions or when it is time dependent. All these different scalings can actually be seen as manifestations of the Heisenberg uncertainty relations. While there is only one best scaling in the single-parameter quantum metrology, different scalings can coexist for the estimation of multiple parameters, which can be characterized by multiple Heisenberg uncertainty relations. We demonstrate the coexistence of two different scalings via the simultaneous estimation of the magnitude and frequency of a field where the best precisions, characterized by two Heisenberg uncertainty relations, scale as T^{-1} and T^{-2}, respectively (in terms of the standard deviation). We show that the simultaneous saturation of two Heisenberg uncertainty relations can be achieved by the optimal protocol, which prepares the optimal probe state, implements the optimal control, and performs the optimal measurement. The optimal protocol is experimentally implemented on an optical platform that demonstrates the saturation of the two Heisenberg uncertainty relations simultaneously, with up to five controls. As the first demonstration of simultaneously achieving two different Heisenberg scalings, our study deepens the understanding on the connection between the precision limit and the uncertainty relations, which has wide implications in practical applications of multiparameter quantum estimation.

Zero-trade-off multiparameter quantum estimation via simultaneously saturating multiple Heisenberg uncertainty relations.

Quantum estimation of a single parameter has been studied extensively. Practical applications, however, typically involve multiple parameters, for which the ultimate precision is much less understood. Here, by relating the precision limit directly to the Heisenberg uncertainty relation, we show that to achieve the highest precisions for multiple parameters at the same time requires the saturation of multiple Heisenberg uncertainty relations simultaneously. Guided by this insight, we experimentally demonstrate an optimally controlled multipass scheme, which saturates three Heisenberg uncertainty relations simultaneously and achieves the highest precisions for the estimation of all three parameters in SU(2) operators. With eight controls, we achieve a 13.27-dB improvement in terms of the variance (6.63 dB for the SD) over the classical scheme with the same loss. As an experiment demonstrating the simultaneous achievement of the ultimate precisions for multiple parameters, our work marks an important step in multiparameter quantum metrology with wide implications.

Minimizing Backaction through Entangled Measurements.

When an observable is measured on an evolving coherent quantum system twice, the first measurement generally alters the statistics of the second one, which is known as measurement backaction. We introduce, and push to its theoretical and experimental limits, a novel method of backaction evasion, whereby entangled collective measurements are performed on several copies of the system. This method is inspired by a similar idea designed for the problem of measuring quantum work [Perarnau-Llobet et al., Phys. Rev. Lett. 118, 070601 (2017)PRLTAO0031-900710.1103/PhysRevLett.118.070601]. By using entanglement as a resource, we show that the backaction can be extremely suppressed compared to all previous schemes. Importantly, the backaction can be eliminated in highly coherent processes.

Climate change and landscape-use patterns influence recent past distribution of giant pandas.

Climate change is one of the most pervasive threats to biodiversity globally, yet the influence of climate relative to other drivers of species depletion and range contraction remain difficult to disentangle. Here, we examine climatic and non-climatic correlates of giant panda (Ailuropoda melanoleuca) distribution using a large-scale 30 year dataset to evaluate whether a changing climate has already influenced panda distribution. We document several climatic patterns, including increasing temperatures, and alterations to seasonal temperature and precipitation. We found that while climatic factors were the most influential predictors of panda distribution, their importance diminished over time, while landscape variables have become relatively more influential. We conclude that the panda's distribution has been influenced by changing climate, but conservation intervention to manage habitat is working to increasingly offset these negative consequences.

Investigation on Surface Tilting in the Failure Process of Shallow Landslides.

In recent decades, early warning systems to predict the occurrence of landslides using tilt sensors have been developed and employed in slope monitoring due to their low cost and simple installation. Although many studies have been carried out to validate the efficiency of these early warning systems, few studies have been carried out to investigate the tilting direction of tilt sensors at the slope surface, which have revealed controversial results in field monitoring. In this paper, the tilting direction and the pre-failure tilting behavior of slopes were studied by performing a series of model tests as well as two field tests. These tests were conducted under various testing conditions. Tilt sensors with different rod lengths were employed to investigate the mechanism of surface tilting. The test results show that the surface tilting measured by the tilt sensors with no rods and those with short rods located above the slip surface are consistent, while the tilting monitored by the tilt sensors with long rods implies an opposite rotational direction. These results are important references to understand the controversial surface tilting behavior in in situ landslide monitoring cases and imply the correlation between the depth of the slip surface of the slope and the surface tilting in in situ landslide monitoring cases, which can be used as the standard for tilt sensor installation in field monitoring.

Assessing the Effectiveness of China's Panda Protection System.

Protected areas form the backbone of biodiversity conservation, yet their effectiveness is often not known nor even evaluated [1-3]. China-best known for its record of ecological degradation in the face of rapidly increasing gross domestic product and resource consumption [4]-has in recent years enacted a series of policies and programs to conserve its natural resources. Chief among them is an ambitious protected area system covering 17% of its terrestrial land mass [4, 5]. An important early impetus for the establishment of this reserve system was the protection of the giant panda (Ailuropoda melanoleuca) [5-8]. Using data from two previous large-scale surveys [9, 10] separated by a decade, and including over 50,000 habitat plots, we examined the panda population and habitat trends inside and outside reserves. Despite ambitious ecocompensation programs in panda habitat outside reserves [11-13], the protection provided by reserves reduced most classes of human disturbance compared to outside reserves, and most disturbances decreased through time more strongly inside than outside reserves. Reserves also contained more and increasing suitable panda than found outside reserves [14, 15]. Comparing reserve performance, reserves with increasing older forests and bamboo correlated with increasing panda populations. Together these findings indicate that China's panda reserves have been effective and that they are functioning better over time, conserving more and better habitats and containing more pandas. While China's protected area system still has much room for improvement [4, 5], including to support pandas [16], these findings underscore the progress made in China's nascent environmental movement.

Experimental Optimal Orienteering via Parallel and Antiparallel Spins.

Antiparallel spins are superior in orienteering to parallel spins. This intriguing phenomenon is tied to entanglement associated with quantum measurements rather than quantum states. Using photonic systems, we experimentally realize the optimal orienteering protocols based on parallel spins and antiparallel spins, respectively. The optimal entangling measurements for decoding the direction information from parallel spins and antiparallel spins are realized using photonic quantum walks, which is a useful idea that is of wide interest in quantum information processing and foundational studies. Our experiments clearly demonstrate the advantage of antiparallel spins over parallel spins in orienteering. In addition, entangling measurements can extract more information than local measurements even if no entanglement is present in the quantum states.