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The increasing frequency of global drought events poses a significant threat to the stability of grassland ecosystems' functionality. The Inner Mongolian grasslands stand out as one of the world's most drought-prone regions, facing elevated drought risks compared to other biomes. An in-depth comprehension of the impact of drought on grassland ecosystems is paramount for their long-term sustainability. Using the Standardized Precipitation Evapotranspiration Index (SPEI) from 1982 to 2018, this study identified various drought events within the Inner Mongolian grasslands, encompassing moderate drought, severe drought, and extreme drought. The resistance of the vegetation to the different drought conditions, assessed through net primary productivity (NPP) as a metric (reflecting its capacity to maintain its original level during drought periods), was examined. The research findings indicated that the period from 2001 to 2018 witnessed a substantial increase in both the frequency and the extent of drought events compared to the period from 1982 to 2000, particularly concerning severe and extreme droughts. The areas most severely impacted by extreme drought were the Xilingol League and the Alxa League. From 1982–2000 to 2001–2018, under moderate drought conditions, vegetation resistance exhibited a minor decrease in the central and eastern regions but experienced a slight increase in the western region. In contrast, under severe drought conditions, the western region saw a significant decrease in vegetation resistance. Remarkably, under extreme drought conditions, the western region showed a substantial increase in vegetation resistance, while the central and eastern regions experienced a slight decrease. Across all three drought conditions, as precipitation levels declined, the resistance of the meadow–steppe–desert ecosystems demonstrated a high–low–high distribution pattern. The temperate desert steppe exhibited a minimal vulnerability to drought, boasting resistance levels exceeding 0.9. Notably, extreme drought had the most pronounced impact on the temperate meadow steppe, temperate steppe, and temperate desert steppe, particularly within the temperate meadow steppe category. Given these findings, the authorities responsible for grassland management should prioritize regions characterized by frequent drought occurrences and low drought resistance, such as Ulanqab City, the Xilingol League, and the western part of Hulun Buir City. Safeguarding steppe ecosystems is of paramount importance for stabilizing vegetation productivity and land carbon sinks, especially under the anticipated exacerbation of climate conditions in the future. [ABSTRACT FROM AUTHOR]

Background. Coronary artery ectasia (CAE) is an easily recognized abnormality of coronary artery anatomy and morphology. However, its pathogenesis remains unclear. Objectives. This study aimed to identify abnormal methylation-modified genes in patients with CAE, which could provide a research basis for CAE. Methods. Peripheral venous blood samples from patients with CAE were collected for RNA sequencing to identify differentially expressed genes (DEGs), followed by functional enrichment. Then, the DNA methylation profile of CAE was downloaded from GSE87016 (HumanMethylation450 BeadChip data, involving 11 cases and 12 normal controls) to identify differentially methylated genes (DMGs). Finally, after taking interaction genes between DEGs and DMGs, abnormal methylation-modified genes were identified, followed by protein–protein interaction analysis and expression validation using reverse transcriptase polymerase chain reaction. Results. A total of 152 DEGs and 4318 DMGs were obtained from RNA sequencing and the GSE87016 dataset, respectively. After taking interaction genes, 9 down-regulated DEGs due to hypermethylation and 11 up-regulated DEGs due to hypomethylation were identified in CAE. A total of 10 core abnormal methylation-modified genes were identified, including six down-regulated DEGs due to hypermethylation (netrin G1, ADAM metallopeptidase domain 12, immunoglobulin superfamily member 10, sarcoglycan dela, Dickkopf WNT signaling pathway inhibitor 3, and GATA binding protein 6), and four up-regulated DEGs due to hypomethylation (adrenomedullin, ubiquitin specific peptidase 18, lymphocyte antigen 6 family member E, and MX dynamin-like GTPase 1). Some signaling pathways were identified in patients with CAE, including cell adhesion molecule, O-glycan biosynthesis, and the renin–angiotensin system. Conclusions. Abnormal methylation-modified DEGs involved in signaling pathways may be involved in CAE development. [ABSTRACT FROM AUTHOR]

Grassland aboveground biomass (AGB) is an important indicator for studying the change in grassland ecological quality and carbon cycle. The rapid development of high-resolution remote sensing and unmanned aerial vehicles (UAV) provides a new opportunity for accurate estimation of grassland AGB on the plot scale. In this study, the mountain grassland was taken as the research object. Using UAV Light Detection and Ranging (LiDAR) data and multispectral satellite images, the influence of topographic correction methods on AGB estimation was compared and a series of LiDAR metrics and vegetation indices were extracted. On this basis, a comprehensive indicator, the vegetation index-height-intensity model (VHI), was proposed to estimate AGB quickly. The results show that: (1) Among the four topographic correction methods, the Teillet regression has the best effect, and can effectively improve the accuracy of AGB estimation in mountain grassland. The correlation between corrected ratio vegetation index and AGB was the highest (correlation coefficient: 0.682). (2) Among the height and intensity metrics, median height and max intensity yielded the higher accuracy in estimating AGB, with Root Mean Square Error (RMSE) of 322 g/m2 and 333 g/m2, respectively. (3) The VHI integrated spectrum and LiDAR information, and its accuracy for AGB estimation for mountain grassland, was obviously better than other indicators, with an RMSE of 272 g/m2. We also found that the accuracy of VHI in univariate models was comparable to that of complex multivariate models such as stepwise regression, support vector machine, and random forest. This study provides a new approach for estimating grassland AGB with multi-source data. As a simple and effective indicator, VHI has shown strong application potential for grassland AGB estimating in mountainous areas, and can be further applied to grassland carbon cycle research and fine management. [ABSTRACT FROM AUTHOR]

Estimating the Start of Growing Season (SOS) of grassland on the global scale is an important scientific issue since it can reflect the response of the terrestrial ecosystem to environmental changes and determine the start time of grazing. However, most remote sensing data has coarse- temporal and spatial resolution, resulting in low accuracy of SOS retrieval based on remote sensing methods. In recent years, much research has focused on multi-source data fusion technology to improve the spatio-temporal resolution of remote sensing information, and to provide a feasible path for high-accuracy remote sensing inversion of SOS. Nevertheless, there is still a lack of quantitative evaluation for the accuracy of these data fusion methods in SOS estimation. Therefore, in this study, the SOS estimation accuracy is quantitatively evaluated based on the spatio-temporal fusion daily datasets through the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) and other models in Xilinhot City, Inner Mongolia, China. The results show that: (1) the accuracy of SOS estimation based on spatio-temporal fusion daily datasets has been slightly improved, the average Root Mean Square Error (RMSE) of SOS based on 8d composite datasets is 11.1d, and the best is 9.7d ( f s t a r f m 8 ); (2) the estimation accuracy based on 8d composite datasets ( R M S E ¯ = 11.1d) is better than daily fusion datasets ( R M S E ¯ = 18.2d); (3) the lack of the Landsat data during the SOS would decrease the quality of the fusion datasets, which ultimately reduces the accuracy of the SOS estimation. The R M S E ¯ of SOS based on all three models increases by 11.1d, and the STARFM is least affected, just increases 2.7d. The results highlight the potential of the spatio-temporal data fusion method in high-accuracy grassland SOS estimation. It also shows that the dataset fused by the STARFM algorithm and composed for 8 days is better for SOS estimation. [ABSTRACT FROM AUTHOR]

The capacitance of MnO2 supercapacitors (SCs) is not high as expected due to its low conductivity of MnO2. The synergistic effects of MnO2 with high theoretical specific capacitance and TiN with high theoretical conductivity can extremely enhance the electrochemical performance of the MnO2-TiN electrode material. In this work, we synthesized different nanostructured and crystalline-structured MnO2 modified TiN nanotube arrays electrode materials by hydrothermal method and explained the formation mechanism of different nanostructured and crystalline-structured MnO2. The influences of MnO2 nanostructures and crystalline-structures on the electrochemical performance has been contrasted and discussed. The specific capacitance of δ-MnO2 nanosheets-TiN nanotube arrays can reach 689.88 F g−1, the highest value among these samples TN-MO-SS, TN-MO-S, TN-MO-SR, TN-MO-RS, and TN-MO-R. The reason is explained based on MnO2 nanostructure and crystalline-structure and electron/ion transport properties. The specific capacitance retention rates are 97.2% and 82.4% of initial capacitance after 100 and 500 cycles, respectively, indicating an excellent charging-discharging cycle stability. [ABSTRACT FROM AUTHOR]

In flexible electronics, appropriate inlaid structures for stress dispersion to avoid excessive deformation that can break chemical bonds are lacking, which greatly hinders the fabrication of super‐foldable composite materials capable of sustaining numerous times of true‐folding. Here, mimicking the microstructures of both cuit cocoon possessing super‐flexible property and Mimosa leaf featuring reversible scatheless folding, super‐foldable C‐web/FeOOH‐nanocone (SFCFe) conductive nanocomposites are prepared, which display cone‐arrays on fiber structures similar to Mimosa leaf, as well as non‐crosslinked junctions, slidable nanofibers, separable layers, and compressible network like cuit cocoon. Remarkably, the SFCFe can undergo over 100 000 times of repeated true‐folding without structural damage or electrical conductivity degradation. The mechanism underlying this super‐foldable performance is further investigated by real‐time scanning electron microscopy folding characterization and finite‐element simulations. The results indicate its self‐adaptive stress‐dispersion mechanism originating from multilevel biomimetic structures. Notably, the SFCFe demonstrates its prospect as a super‐foldable anode electrode for aqueous batteries, which shows not only high capacities and satisfactory cycling stability, but also completely coincident cyclic voltammetry and galvanostatic charge–discharge curves throughout the 100 000 times of true‐folding. This work reports a mechanical design considering the self‐adaptive stress dispersion mechanism, which can realize a scatheless super‐foldable electrode for soft‐matter electronics. [ABSTRACT FROM AUTHOR]

• Remote sensing was used to monitor plateau wetland ecological degradation. • A composite wetland degradation index was constructed to assess wetland degradation quantitatively. • We analyzed ecological degradation process with three administrative levels. The Zoige Plateau Wetland is the largest high-altitude swamp wetland in China. It plays a key role in ecological balance and the global change. Climate change and improper utilization have consequently resulted in decreased wetland area, disrupted ecosystem structure, and wetland function degradation and function loss. The Zoige Plateau Wetland thus faces severe ecological degradation problems. In this study, selecting the Zoige Plateau Wetland as the study area, remote sensing was used to track the ecological degradation process during 2000–2015 from three aspects (area degradation, structure degradation and function degradation) and at three administrative levels (study area, county and key township). To assess the wetland degradation quantitatively, an analytic hierarchy process (AHP) was used to construct a composite wetland degradation index based on five indicators: wetland area change rate, landscape fractal dimension, landscape fragmentation, vegetation biomass and vegetation coverage. The results showed the following. (1) In terms of area change rate, the total wetland area had continuously decreased during 2000–2015 compared to that in the 1990s, and 2010 was the most significant. The frequency of negative change in the wetland area reached 87.5% in all four counties and across four time periods (2000, 2005, 2010 and 2015), and 85% at the township level. At the spatial scale, Hongyuan County had the smallest wetland area change rate. (2) In terms of structure change, the variations in landscape fractal dimension and landscape fragmentation generally exhibited similar trends at different levels. Specifically, the ecosystem structure was seriously affected in 2000, then gradually recovered in 2005 and 2010, and was again under aggravated interference in 2015. (3) In terms of function change, the above-ground biomass yield in the northeastern region was higher than that in the southern region. A low value was detected in 2000, and then the value increased and remained essentially the same in 2005 and 2010. However, the value decreased in 2015, indicating deteriorated vegetation condition. The vegetation coverage in the study area remained steady, without deterioration in a particular year. (4) In terms of the whole study area, the wetland degradation grades in the four periods were mild (2000), moderate (2005), mild (2010) and mild (2015). In brief, the wetland degradation was the most severe in 2005. Over the 2000–2015 period, the spatial degradation pattern of the Zoige Plateau Wetland progressed from the northeast to the southwest. The model built in this study could be widely applicable. And this study has also some reference value for monitoring and management of wetland degradation by remote sensing. [ABSTRACT FROM AUTHOR]

Background: MMPs/TIMPs system is well known to play important roles in pressure overloadinduced cardiac remodeling, and Amlodipine and Atorvastatin have been showed to exert favourable protective effects on cardiovascular disease, however, it is not clear whether Amlodipine and Atorvastatin can improve hypertensive cardiac remodeling and whether the MMPs/TIMPs system is involved. The present study aims to answer these questions. Methods: 36 weeks old male spontaneous hypertension (SHR) rats were randomly divided into four groups: 1). SHR control group, 2). Amlodipine alone (10 mg/kg/d) group, 3). Atorvastatin alone (10 mg/kg/d) group, 4).Combination of Amlodipine and Atorvastatin (10 mg/kg/d for each) group. Same gender, weight and age of Wistar-Kyoto (WKY) rats with normal blood pressure were used as normal control. Drugs were administered by oral gavage over 12 weeks. The blood pressure and left ventricle mass index were measured. Enzyme activity of MMP-2 and MMP-9 was assessed with Gelatin zymography. MMP-2, MMP-9, TIMP-1 and TIMP-2 mRNA and protein expression was studied by RT-PCR and Western blot. Single factor ANOVA and LSD-t test were used in statistical analysis. Results: Treatment with Amlodipine alone or combination with atorvastatin significantly decreased blood pressure, left ventricle mass index in SHR rats (P < 0.05 for both). Compared with WKY rats, the myocardial levels of MMP-2, MMP-9 mRNA, protein and enzyme activity were significantly increased (P<0.05). Amlodipine alone, Atorvastatin alone, and combination of the two all reduced MMP-2 and MMP-9 mRNA, protein and enzyme activity, with the best effects seen in the combination. Compared with WKY rats, the myocardial levels of TIMP-1 mRNA and protein were significantly increased (P<0.05), however, there was no difference in levels of TIMP-2. Neither Amlodipine alone, Atorvastatin alone, nor combination of the two drugs significantly affect the expression of TIMP-1 or TIMP- 2. Conclusion: Amlodipine and Atorvastatin could improve ventricular remodeling in SHR rats through intervention with the imbalance of MMP-2/TIMP-2 and MMP-9/TIMP-1 system. [ABSTRACT FROM AUTHOR]

Grassland is not only an important landscape of the Beijing–Tianjin sandstorm source control project area, but also a significant object of the Beijing–Tianjin sandstorm source control project. By taking the situation in 2000 as the base of comparison and using the established grassland vegetation growth model, the monitoring and evaluation of grassland vegetation dynamic variation in the project area from 2000 to 2010 was conducted based on MODIS 16 days NDVI data. The conclusions are as follows: (1) The comparative result of average growth between each year from 2001 to 2010 and the base year was on the good side in general; the grassland growth was good both in the early and later periods of grassland growth peak season than in the first years of the project implementation, indicating that the implementation of the Beijing–Tianjin sandstorm source project has significantly improved the growth conditions of grassland vegetation; (2) With regard to the annual dynamic variation of grassland growth, the area proportions of the grasslands, of which the average grassland growth was on the good side, fluctuated and increased slightly with the time changes in general. The area proportions of the grasslands, of which the average grassland growth was on the bad side, fluctuated and decreased in general. The area proportions of the grasslands with normal growth showed an increasing overall trend; (3) From the regional perceptive on four zones, including the northern arid grassland desertification control zone, Hunshandake sandy land control zone, the farming-pastoral area of desertified land control zone, and the water conservation zone of Yanshan hills and mountains, except that the grassland growth in the farming-pastoral area of desertified land control zone was bad, the average growth of other three zones was good each year from 2001 to 2010 compared with the base year. (4) In respect of space, the regions with big grassland growth variation in the project area were concentrated in the western and eastern sections of the northern arid grassland desertification control zone and the western section of Hunshandake sandy land control zone. The grassland growth variation in the water conservation zone of Yanshan hills and mountains and the farming-pastoral area of desertified land control zone were relatively stable. On one hand, the conclusions of this paper can evaluate the effectiveness of the project control, on the other hand, it can also provide scientific basics to grassland management departments, facilitate the rational utilization of grassland, and preserve the regional ecological balance. [ABSTRACT FROM AUTHOR]

Facing the worsening degradation of grasslands, state and local governments in China have implemented a series of ecological protection projects. Ningxia Hui Autonomous Region was the first province in China to implement a region-wide grazing ban, the effect of which has become contentious at all levels of government and a topic of public concern. The change of grassland desertification is the most direct indicator of the grazing ban’s effect. This paper chooses Yanchi County in Ningxia as the study area to analyze the grassland desertification situation. Based on a series of Landsat TM/ETM+ images, field observations and expert review, a Ningxia grassland desertification classification and grading system was constructed. Then, spectral mixture analysis (SMA) and a decision-tree method were used to interpret images of the study area from 4 years: 1993, 2000, 2006, and 2011. The following results were obtained: the area of desertified grassland decreased gradually from 4142\;\km^2 in 1993 to 3695\;\km^2 in 2011, a decrease of 10.80%. The severity of desertification also declined as the area of severely desertified grassland gradually decreased to 324\;\km^2 in 2011 from 1093\;\km^2 in 1993, a decrease of 70.34%. The annual reduction rate of the desertified grassland area reached its peak during the period 2000–2006. In particular, the areas of severely desertified grassland declined by 8.86% annually. In a situation of declining rainfall, human factors (such as ecological protection policy) have become a major cause of ongoing grassland desertification reversal and restoration of grassland vegetation. [ABSTRACT FROM PUBLISHER]

Temperature and precipitation are considered to be the most important indicators affecting the green-up date. Sensitivity of the green-up date to temperature and precipitation is considered to be one of the key indicators to characterize the response of terrestrial ecosystems to climate change. We selected the main grassland types for analysis, including temperate steppe, temperate meadow steppe, upland meadow, and lowland meadow. This study investigates the variation in key meteorological indicators (daily maximum temperature (Tmax), daily minimum temperature (Tmin), and precipitation) between 2001 and 2018. We then examined the partial correlation and sensitivity of green-up date (GUD) to Tmax, Tmin, and precipitation. Our analysis indicated that the average GUD across the whole area was DOY 113. The mean GUD trend was −3.1 days/decade and the 25% region advanced significantly. Tmax and Tmin mainly showed a decreasing trend in winter (p > 0.05). In spring, Tmax mainly showed an increasing trend (p > 0.05) and Tmin a decreasing trend (p > 0.05). Precipitation showed no significant (p > 0.05) change trend and the trend range was ±10 mm/decade. For temperate steppe, the increase in Tmin in March promotes green-up (27.3%, the proportion of significant pixels), with a sensitivity of −0.17 days/°C. In addition, precipitation in April also promotes green-up (21.7%), with a sensitivity of −0.32 days/mm. The GUDs of temperate meadow steppe (73.9%), lowland meadow (65.9%), and upland meadow (22.1%) were mainly affected by Tmin in March, with sensitivities of −0.15 days/°C, −0.13 days/°C, and −0.14 days/°C, respectively. The results of this study reveal the response of vegetation to climate warming and contribute to improving the prediction of ecological changes as temperatures increase in the future. [ABSTRACT FROM AUTHOR]

• The RSDI is suitable for monitoring aeolian desertification. • The areas with significant restoration (34.1%) exceeded those with significant deterioration (6%) in the NSPB. • In the areas with significant restoration, 57.4% of the land was mainly affected by human activities. The northern sand-prevention belt (NSPB) is the key area for sand control in China, and the various ecological projects conducted there are important to the Chinese strategy for ecological security. In this paper, a new remote sensing-based desertification index (RSDI) based on principal component analysis was constructed from four aspects of vegetation greenness, surface moisture, soil grain size, and surface radiation. The overall evaluation accuracy of the index was 89.2%, and the kappa coefficient was 0.80, indicating high sensitivity to different degrees of aeolian desertification and suitability for multiscale research. The coefficient of variation, Mann–Kendall test, Theil–Sen median trend analysis, and residual analysis were used to analyze the spatiotemporal changes and driving forces of the RSDI in the NSPB from 2000 to 2020. The RSDI was used to compare aeolian desertification in different subregions, land use types, and ecological project areas. The important results are as follows: (1) the trend of the average RSDI was downward, but it increased significantly in 2008–2009 and 2013–2014; (2) the RSDI was characterized by relatively high volatility in 28.9% and moderate volatility in 27.1% of the area; (3) the areas with significant restoration (34.1%) greatly exceeded those with significant deterioration (6%), whereas 59.9% of the total area was stable; and (4) within the area with significant restoration, 57.4% was primarily affected by human activities, and 42.4% was primarily affected by climate change; however, most of the area with significant deterioration (71.1%) was affected by human activities. In general, the degree of aeolian desertification in the NSPB has decreased in the past 20 years and its ecological quality has continued to recover. However, unreasonable human activities still need to be reduced, and the ecological management of areas under serious threat of desertification needs to be strengthened. [ABSTRACT FROM AUTHOR]

Northern China has been long threatened by aeolian desertification. In recent years, all levels of the Chinese government have performed a series of ecological protection and sand control projects. To grasp the implementation effects of these projects and adjust policies in time, it is necessary to understand the process of aeolian desertification quickly and accurately. Remote sensing technologies play an irreplaceable role in aeolian desertification monitoring. In this study, the Zhenglan Banner, which is in the hinterland of the Hunshandake Sandy Land, was considered as the research area. Based on unmanned aerial vehicle (UAV) images, ground survey data, and Landsat images called in Google Earth Engine (GEE), the aeolian desertified land (ADL) in 2000, 2004, 2010, 2015, and 2019 was extracted using spectral mixture analysis. A desertification index (DI) was constructed to evaluate the spatial and temporal dynamics of the ADL in the Zhenglan Banner. Finally, a residual analysis explored the driving forces of aeolian desertification. The results showed that (1) the ADL area in the Zhenglan Banner has been trending downwards over the past 20 years but rebounded from 2004 to 2010; (2) over the past 20 years, the area of slightly, moderately, and severely desertified land has decreased at annual rates of 0.4%, 2.7%, and 3.4%, respectively; (3) human activities had significantly positive and negative impacts on the aeolian desertification trend for 20.0% and 21.0% of the study area, respectively, but not for the rest. This paper explored new techniques for rapid aeolian desertification monitoring and is of great significance for controlling and managing aeolian desertification in this region. [ABSTRACT FROM AUTHOR]

The accumulation of heat and moderate precipitation are the primary factors that are used by grasslands to trigger a green-up date. The accumulated growing degree-days (AGDD) requirement over the preseason is an important indicator of the response of grassland spring phenology to climate change. This study adopted the Normalized Difference Phenology Index (NDPI), which derived from the Moderate Resolution Imaging Spectroradiometer (MODIS), to extract annual green-up dates in the Hulun Buir grassland in China between 2001–2015. Our analysis indicated that the range (standard deviation) and trend for the green-up date were DOY (day of year) 104 to DOY 144 (10.6 days) and −2.0 days per decade. Nine point two percent of the study area had significant (p < 0.05) changes in AGDD requirements. The partial correlations between the AGDD requirements and chilling days (67.04%, pixels proportion) were negative and significant (p < 0.05). The partial correlations between the AGDD requirement and precipitation (28.87%) were positive and significant (p < 0.05). Finally, the partial correlation between the AGDD requirement and insolation (97.65%) were positive and significant (p < 0.05). The results of this study could reveal the response of vegetation to climate warming and contribute to improving the phenological mechanism model of different grassland types in future research. [ABSTRACT FROM AUTHOR]

Land use/land cover change (LUCC) is the most direct driving force of landscape pattern change. The Zoige Plateau is a natural ecosystem with the largest high-altitude swamp wetland in China and its land use pattern has undergone great changes in recent years, but how the changes of each land use type affect the landscape pattern is uncertain. Here, we used the object-oriented method to extract land use information in 2015. Then, combined with land use data, the land use change characteristics from 2000 to 2015 were analyzed. We used the correlation analysis method to analyze the effects of land use changes on landscape pattern systematically. Three key conclusions were reached. (1) Land use information for the Zoige Plateau could be extracted with high accuracy by combining the object-oriented method and support vector machine (SVM). The overall accuracy was 93.2% and the Kappa coefficient was 0.889. (2) The comprehensive dynamic degree of land use was the highest from 2010 to 2015. From 2000 to 2015, the wetland area decreased the fastest because 57.05% of the wetlands were transferred out. Construction land increased the fastest, and the transferred in area from grassland and farmland were the main reason. (3) The effects of unused land, farmland, and construction land on the overall landscape pattern were stronger than that of the other types, among which farmland had the most significant impact (with a correlation coefficient of 0.959, p < 0.001). The change of unused land was the most highly significant factor associated with the landscape area pattern, and both the water body and unused land showed strong correlations with landscape shape pattern change. This suggested that the effects of land use types occupying a relatively small area on the landscape pattern were intensified. This study will provide guidance for the environmental management of local land resources and other natural ecosystem areas. [ABSTRACT FROM AUTHOR]