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This paper has provided an objection to Nagels bat theory as the defense for physicalism. Thomas Nagel has used a bat theory to point out the contradiction feature between a scientific theory and phenomenal consciousness. In this work, I argued that what we know as phenomenal consciousness may just be our memory system, which can be explained by science.

Purpose The disinfection robot developed by the authors and team focuses on achieving fast and precise disinfection under a given or specific disinfection zone. This looks to solve problems with traditional robots that pay less attention to the level, efficiency and zones of disinfection. To effectively support and guarantee normal running for the whole system, a digital twin system is applied to the disinfection robot. This study aims to achieve fast, precise and thorough disinfection via the developed mobile robot. Design/methodology/approach The designed robot is composed primarily of the following three parts: a mobile platform, a six-axis robotic arm and a ultraviolet-C (UVC) LED array. The UVC LED array is installed on the end-effector to achieve large-scale, precise manipulation. The adoption of all types of advanced sensors and the development of an intuitive and user-friendly client interface are helpful in achieving remote control, path planning, data monitoring and custom disinfection functions. Findings Disinfection of three different locations in the laboratory was performed; the dosage distribution of the surface as radiated by the UVC robot was detected; and feasibility of development was validated. Originality/value The developed disinfection robot achieved fast, precise and thorough disinfection for a given or specific disinfection zone.

Lake surface water temperature (LSWT) monitoring is significant as it provides valuable information on climate changes and resultant changes in lakes. Here, monthly moderate resolution imaging spectroradiometer LSWT data of 364 lakes during 2001–2015 were analysed to determine spatiotemporal patterns of daytime (LSWTd), nighttime (LSWTn), daily LSWT (LSWTm) and their drivers in the Qinghai-Tibet Plateau at monthly, seasonal and annual timescales. We focused on spatiotemporal heterogeneity of LSWT trends. Results showed climatological LSWT presented a saddle-shaped distribution along the northeast-southwest direction except for LSWTd in March, while highly heterogeneous LSWT trends without spatial dependence were observed at all timescales. Diurnal asymmetry of LSWT trends was evident with 56.04–88.19% lakes showing smaller LSWTd trends than LSWTn trends except for August and September. Further, we found lake surface albedo trend could effectively explain spatial patterns of LSWT trends at different timescales, and its interactions with other variable trends generally were the largest or second-largest.

Understanding the spatiotemporal patterns of carbon footprints (CFs) of grains production is important to formulate regional heterogeneous greenhouse gas (GHG) mitigation strategies. This study evaluates the CFs, farm CFs (FCFs: CFs of per unit area), and production CFs (PCFs: CFs of per unit yield) of main grains production in China based on a new scale data set: agricultural statistics data of over 300 prefecture-level regions. A comparison of CFs of main grains production between main producing area (MPA) and non-main producing area (NMPA) are firstly discussed on a totally new scale. Results show that the CFs of main grains production of MPA accounts for 54–57% of country’s total although the area of farmland of MPA only accounts for 42%. The PCF and FCF of rice production are higher in MPA, while those of wheat and maize production are lower in MPA. It implies that there are less GHG emission of rice (main paddy grain) productions in NMPA and less GHG emission of wheat and maize (main dryland grains) production in MPA. In additional, the PCF of rice shows growth, while that of wheat and maize shows decline from 2008 to 2017. The growth of PCF of rice is mainly driven by the rise of PCF in MPA. Findings are expected to improve the understanding patterns of China’s CF of main grains production and subsequently contribute to GHG mitigation.

Atomic force microscopy (AFM) based nanorobotic technology provides a unique manner for delicate operations at the nanoscale in various ambient, thanks to its ultrahigh spatial resolution, outstanding environmental adaptability, and numerous measurement approaches. However, one vital challenge behind nanoscale operations is the task space positioning problem, known for its difficulty to realize desirable relative position between the AFM sharp tip and the target. It is noted that although one AFM possesses nanometer imaging resolution, it is hard to achieve nanometer positioning accuracy due to system uncertainties, such as the uncompensated nonlinearity and the thermal drift generated internally/externally. In order to tackle the vital positioning problem in the space, this letter proposes a specific visual servoing control framework using a local ambient image as feedback to overcome positioning uncertainty at the nanoscale. In this letter, we employ the optimal Archimedean spiral scanning strategy and try to exceed the speed criterion to pursue faster and uniform local scan for generating feedback images. To fulfill reliable precise tip locating with the possible non-ideal feedback images, a type of visual servoing control approach i.e., extended non-vector space (ENVS) controller based on the subset projection method, was developed for tackling environmental noise and disturbances. Experimental studies were conducted to verify the effectiveness of the proposed task space tip locating methodology. Testing results demonstrated that the positioning uncertainty was attenuated dramatically, and $\text{1 nm}$ level positioning precision has been achieved for the $\text{500 nm}\times \text{500 nm}$ task space.

In the past decades, bubbles have been gaining extensive attentions for their wide range of applications, especially those at the micro-scale. Research on the bubbles’ mechanical properties is necessary for better implementations. Precise measurement of the microbubbles’ mechanical properties (e.g. stiffness and adhesion) relies largely on delicate manipulation technologies in aqueous environment. As a consequence, atomic force microscopy (AFM) has been widely adopted in this field. Bubble stiffness is an important indicator to reflect the stability. Existing studies mainly focused on statistic property of the microbubbles’ stiffness, which may omit delicate specific characteristics of a single microbubble. In this letter, as an instance, AFM-based stiffness measurement of a single hydrogen microbubble has been carried out. The electrochemistry method was adopted to generate stable hydrogen microbubbles. By using force volume mode of a commercial AFM, the temperature-dependent stiffness property of the microbubble was studied. Furthermore, stiffness map of a single microbubble was captured, which shows location-dependent anisotropic characteristic, contradicting the preassumption that stiffness of bubbles should be isotropic. To explain this phenomenon, the contact condition between the AFM tip and the bubble surface is considered as the key reason that induces the anisotropic observation, and a corresponding model is established to verify this hypothesis.

Ecological engineering is an important measure to promote ecosystem adaptation and restoration to deal with environmental change and human disturbance. To assess the effectiveness of ecological construction and analyze the influencing factors of ecosystem changes in the Qinghai-Tibet Plateau (QTP), this study detected the spatial changes and dynamic hotspots of vegetation ecosystems in the ecological construction regions of the QTP (QTPE) and regions without ecological construction (QTPWE) using hot spot analysis and comprehensive dynamic degree model. Then the random forest (RF) model and geographical weighted regression model were used to study the degree and spatial heterogeneity of impacts of climate and human activities on normalized difference vegetation index (NDVI). Results showed that the vegetation restoration of the QTPE was obvious during 2001-2018 as the area of the increasing NDVI accounted for 74.15%. In addition, the effects of climate and human activities on NDVI of vegetation ecosystem showed significant spatial heterogeneity. The RF model showed that population density was the most significant factor affecting ecosystem vegetation in the QTPE, and its relative importance was between 26.1-32.6%, followed by downward shortwave radiation (7.9-16.8%). However, climate factors still had the greatest impact in the QTPWE, with the relative importance of precipitation and temperature being 45% and 15%, respectively. These findings provide a scientific basis for the restoration and management of vegetation on the QTP, and are of great significance for the deployment of future ecological engineering projects.

Emerging and disappearing climate zones are frequently used to diagnose and project climate change. However, little attempt has been made to quantify shifts of climate zones in Qinghai-Tibet Plateau (QTP) based on the high-resolution data sets. Our results show that highland climate was decreased substantially during 1961–2011 and were mainly replaced by boreal climate. We also found that the mean elevation of boreal and highland climate continues to rise, with obvious longitudinal geographical characteristics over the study period. Furthermore, we found that the climate spaces (a climate space defined as the volume of 10°C × 500 mm here) of both boreal and highland climate types tend to be warm and humid ones, which may provide more suitable climate conditions for species to maintain and promote diversity. Characterization of changes in QTP climate types deepens our understanding of regional climate and its biological impacts. Emerging and disappearing climate zones are frequently used to diagnose and project climate change. However, little attempt has been made to quantify shifts of climate zones in Qinghai-Tibet Plateau (QTP) based on the high-resolution data sets. Our results show that highland climate was decreased substantially during 1961-2011 and were mainly replaced by boreal climate. We also found that the mean elevation of boreal and highland climate continues to rise, with obvious longitudinal geographical characteristics over the study period. Furthermore, we found that the climate spaces (a climate space defined as the volume of 10 degrees C x 500 mm here) of both boreal and highland climate types tend to be warm and humid ones, which may provide more suitable climate conditions for species to maintain and promote diversity. Characterization of changes in QTP climate types deepens our understanding of regional climate and its biological impacts. Plain Language Summary Climate classification is the key to simplifying complex climate and helps to deepen the understanding of regional climate change. Based on the high-resolution data set (LZ0025), the sharp climatic gradient features and their potential biological impact on Qinghai-Tibet Plateau (QTP) was quantified. With the temperature increase, the spatial distribution of highland tundra climate was gradually replaced by boreal climate. More importantly, the contraction of highland climate and the expansion of boreal climate has obvious elevation characteristics. In addition, climate spaces of highland and boreal climate types tend to warm and humid ones, which may provide more climatic niches for different species and contribute to regional biodiversity.

Agricultural runoff is the main source of water pollution in Central Asia. Excessive nitrogen (N) inputs from overuse of chemical fertilizers are threatening regional water resources. However, the scarcity of quantitative data and simplified empirical models limit the reliability of grey water footprint (GWF), particularly in undeveloped regions. In this study, we developed an Integrated Excess Nitrogen Load Model (IENLM) to calculate excess N load and evaluate its potential water environmental pressure in Central Asia. The model optimized the biological N fixation and atmospheric N deposition modules by involving more environmental variables and human activities. Results showed that N fertilizer application contributed over 60% to total N input and was mainly responsible for 42.9% increase of total GWF from 101.5 to 145.0 billion m3 during 1992 - 2018. Water pollution level (WPL) increased from 0.55 in 1992 to 2.41 in 2018 and the pollution assimilation capacity of water systems has been fully consumed just by N load from agriculture since 2005. GWF intensity and grey water pollution – efficiency types in all Central Asian countries have improved in recent years except for Turkmenistan. N fertilizer application and agricultural economy development were the main driving factors induced N pollution. Results were validated by riverine nitrate concentrations and the estimates from prior studies. In future, combining the N fertilizer reduction with other farm management practices were projected to effectively improve the WPL. The modeling framework is favorable for N pollution research in data-scarce regions and provides a scientific basis for decision-making for agriculture and water resource managements.

Understanding the spatiotemporal patterns of carbon footprints (CFs) of grains production is important to formulate regional heterogeneous greenhouse gas (GHG) mitigation strategies. This study evaluates the CFs, farm CFs (FCFs: CFs of per unit area), and production CFs (PCFs: CFs of per unit yield) of main grains production in China based on a new scale data set: agricultural statistics data of over 300 prefecture-level regions. A comparison of CFs of main grains production between main producing area (MPA) and non-main producing area (NMPA) are firstly discussed on a totally new scale. Results show that the CFs of main grains production of MPA accounts for 54-57% of country's total although the area of farmland of MPA only accounts for 42%. The PCF and FCF of rice production are higher in MPA, while those of wheat and maize production are lower in MPA. It implies that there are less GHG emission of rice (main paddy grain) productions in NMPA and less GHG emission of wheat and maize (main dryland grains) production in MPA. In additional, the PCF of rice shows growth, while that of wheat and maize shows decline from 2008 to 2017. The growth of PCF of rice is mainly driven by the rise of PCF in MPA. Findings are expected to improve the understanding patterns of China's CF of main grains production and subsequently contribute to GHG mitigation.

Microplastics (MPs) have been widely detected in the environments, yet the sources of MPs in freshwater of remote areas at high altitude were not well understood. This study investigated the abundance and distribution of MPs in water bodies and sediments at the Qinghai-Tibet Plateau (QTP). MPs were detected in all samples (47 water and 33 sediment samples) with the mean abundance of 624.70 ± 411.39 items/m3 in water and 41.52 ± 22.31 items/kg in sediment. In descending order, the highest MP oncentrations were found in turbid rivers＞agricultural channel water＞lakes＞ordinary rivers. The results showed that MP abundance was associated with the water quality (especially COD) on the QTP, and it was negatively correlated with altitude due to less human activities (especially agricultural activities) at high altitude areas. In addition, more abundant MPs with small sized was found in the higher altitudes than low ones. Determining the effects of different environments on the distribution and degradation of MPs in the high altitude area of the QTP, this study emphasized the attention to be given to this emerging pollutant in the high altitude remote areas.

The welding and other hot or cold processing region behavior in important structures is the key characteristics for the structural integrity assessment, it is necessary to accurately derive the material mechanical properties in the failure driving force (such as stress and strain) analysis in the local area. The hot or cold processing would induce the change and the inhomogeneous of the material mechanical properties in the local processing region of the structure, and it is difficult to obtain the precise mechanical properties in these regions by the traditional material tensile test. To accurately obtain actual material mechanical properties in the local region of structures, a micro-indentation test system has been established, which incorporated by a CMT6103 Material Test Device, an indenter displacement sensor and a group of special micro-indenter assemblies are established, and a numerical testing inversion analysis method by using ABAQUS software is also proposed in this paper. Based on above test system and analysis platform, an approach to obtain material mechanical properties in local region of structure is proposed and established. The verification experiment and analysis is performed by using a group of various changed mechanical property of 316L austenitic stainless steel through different cold-work hardening. The investigated results indicate the material mechanical properties and the micro-indentation morphological change have evidently relevance, and the material mechanical parameters, such as the yield stress σ y , the strain hardening exponent n and others could be conveniently and effectively obtained by the proposed approach in this paper.

Mining activities that shape geographical patterns of biodiversity in individual regions are increasingly understood, but the complex interactions on broad scales and in changing environments are still unclear. In this study, we developed a series of empirical models that simulate the changes in biodiversity and ecosystem functions in mine-affected regions along elevation gradients (1500-3600 m a.s.l) in the metal-rich Qilian Mountains (~800 km) on the northeastern Tibetan Plateau (China). Our results confirmed the crucial role of potentially toxic elements (PTEs) dispersal, topography, and climatic heterogeneity in the diversification of plant community composition. On average, 54% of the changes in ecosystem functions were explained by the interactions among topography, climate, and PTEs. However, merely 30% of the changes were correlated with a single driver. Plant species composition (explained variables = 94.8%) changed more in lowland than in highland areas. The changes in species composition (explained variables = 94.8%) in the PTE-polluted habitats located in the warm low-elevation deserts and grasslands were greater than those occurring in the alpine deserts and grasslands. The ecosystem functions (soil characteristics, nutrient migration, and plant biomass) experienced greater changes in the humid low-elevation grasslands and alpine deserts. The effect of topography (i.e., slope and aspect) was less important than that of climatic heterogeneity (MAT, win10, and ET0) in predicting ecosystem functions of PTE-polluted habitats. Our results suggest that the processes driven by climate or other factors can result in high-altitude PTE-affected habitat expansions or contractions.

Environmental issues have become some of the greatest challenges encountered across the life cycle Shale gas operations, and mostly involve the management, disposal, and spill of flowback and produced (FP) waters during the process of hydraulic fracturing. This study evaluates Shale gas resources, addresses water resource management problems, and identifies the corresponding environmental implications of FP waters under uncertainty. Multiple tools, including structural optimization, process design, cost analysis, environmental assessment, and stochastic technology, are integrated into a general modeling framework based on game theory. This mathematic framework corresponds to a dominant-subordinate-interactive problem, where two major participants are identified as the downstream decision maker at the dominant level (e.g., power generation sector) and the upstream decision maker at the subordinate level (e.g., Shale gas producer). The Monte Carlo technique is used for simulating the estimated ultimate recovery (EUR) of a single well. Thereafter, the developed model is applied to a special case study of the Marcellus Shale play in Beaver County, Pennsylvania. Multiple decisions regarding gas production, processing, water management, as well as electricity generation would been examined under different probability levels. Results indicate that the changes in violation levels would lead to distinct environmental and economic performances of the supply chain. A lower probability level of the EUR value would correspond to an increased reliability on fulfilling the system demands, and then to higher economic benefits and freshwater supply; conversely, a higher probability level of the EUR value would result in lower economic benefits and lower freshwater supply, and the risk of violating the EUR value would also increase.

In China, an unambiguous greening trend was observed over the last three decades. The feedback induced by vegetation growth can affect regional climate. Here, we investigated how vegetation feeds back to land surface temperature (LST) in temperature zones and land-use types in China using 18-years (2001-2018) of Moderate Resolution Imaging Spectroradiometer (MODIS) LST and Normalized Difference Vegetation Index (NDVI) data. We first showed that vegetation feedback was significantly negative (p0.1, t-test) in most parts of China. Specifically, we discovered a downtrend of vegetation feedback from the coldest temperature zone to the hottest temperature zone. Moreover, vegetation feedback and thermal condition showed an inverse relationship among temperature zones. The inverse relationship clarified that vegetation growth can cool most parts of China during climate change. In the end, we showed the pattern of vegetation feedback among land-use types. Due to the expansion of grassland, vegetation feedback may temporarily positive. Suitable vegetation coverage in urban land, banning deforestation, and cultivating land reasonably can decrease the local temperature by inducing negative vegetation feedback.

Potentially toxic elements (PTEs) generated from mining activities have affected ecological diversity and ecosystem functions around the world. Accurately assessing the long-term effects of PTEs is critical to classifying recoverable areas and proposing management strategies. Mining activities that shape geographical patterns of biodiversity in individual regions are increasingly understood, but the complex interactions on broad scales and in changing environments are still unclear. In this study, we developed a series of empirical models that simulate the changes in biodiversity and ecosystem functions in mine-affected regions along elevation gradients (1500–3600 m a.s.l) in the metal-rich Qilian Mountains (∼800 km) on the northeastern Tibetan Plateau (China). Our results confirmed the crucial role of PTEs dispersal, topography, and climatic heterogeneity in the diversification of plant community composition. On average, 54% of the changes in ecosystem functions were explained by the interactions among topography, climate, and PTEs. However, merely 30% of the changes were correlated with a single driver. The changes in species composition (explained variables = 94.8%) in the PTE-polluted habitats located in the warm and humid low-elevation deserts and grasslands were greater than those occurring in the dry alpine deserts and grasslands. The ecosystem functions (soil characteristics, nutrient migration, and plant biomass) experienced greater changes in the humid low-elevation grasslands and alpine deserts. Our results suggest that the processes driven by climate or other factors can result in high-altitude PTE-affected habitat facing greater threats.

The Qinghai-Tibet Plateau (QTP) is a typical ecologically fragile area. Once the surface vegetation degenerates, it may not be restored. This requires the development of soil organic matter (SOM) monitoring method without destroying the surface, so as to ensure the sustainable development of plateau agriculture. This work investigated the environmental factors that are significantly related to SOM content in the river valley of the southern QTP. These environmental factors include soil hydrothermal factors (soil moisture content and soil temperature), topographic factors (elevation and slope) and vegetation factor (NDVI). The original band reflectivity (OR) of Landsat 8 OLI images and the band reflectivity after the first-order derivative (FDR) and the second-order derivative (SDR) processing were combined with the above environmental factors to estimate SOM content. The results showed that the accuracy of the model was improved obviously by adding environmental factors. The estimation effect of back propagation neural network (BPNN) model was better than that of geographically weighted regression (GWR) model, partial least squares regression (PLSR) model and multivariable linear regression (MLR) model. GWR model can also meet the estimation requirements, while PLSR and MLR models cannot achieve effectively the estimation of SOM content. FDR-BPNN model considering environmental factors was the best model for estimating SOM content, with R2 being 0.947, RMSEC being 4.701 g·kg−1 and MAEV being 5.485 g·kg−1. Moreover, the model had the lowest uncertainty and the highest stability. This study will provide a good insight for the monitoring of SOM content in the future, and provide basic data support for the implementation of precision agriculture in the QTP.

Atomic force microscopy (AFM) based manipulation technologies have been attractive for decades due to the overwhelming advantages of nanometer spatial resolution, universal working environment, and various mechanical measurement methods. It is noted that though the AFM possesses nanometer imaging resolution, it is hard to achieve nanometer locating precision due to uncertainties, especially the thermal drift which distorts AFM images through relatively long capturing time. Since an AFM image is typically utilized as a reference map for nanomanipulation, the uncertainty induced distorted image will definitely introduce location deviation between the real nano-world and the captured, which usually leads to low efficiency or even failure of tasks. Therefore, to achieve high accuracy for AFM-based manipulation, the positioning uncertainty should be detected and then overcome. In this study, we present a universal approach to quantitatively measure and overcome nanorobot tip locating uncertainty by developing a featureless spiral local scan strategy together with the non-vector space (NVS) navigation approach. Experimental study reveals that variation of the tip locating uncertainty of AFM fast axis is more significant than that of the slow axis with different scan angles.

In the past 50–60 years, the bubble has gained attention for its wide range of applications, especially in micro-scale. Research on the bubble’s mechanical properties is necessary so that we can manipulate the bubble better (for better implementation). Precise measurement of the microbubble’s mechanical properties (e.g., stiffness and surface tension) relies largely on delicate manipulation technology, as a result, atomic force microscopy (AFM) has been widely implemented. However, in previous AFM-scanned figures, microbubbles were usually captured with a relatively large distortion and the bubble topology was not clear enough to locate precisely the AFM probe so that further nanomanipulation or measurements could not occur. In this paper, AFM-based properties measurement of a single micro-bubble has been studied. An electrochemistry method was applied to generate stable bubbles. By using force volume mode, a single bubble was captured. The bubble, which should be isotropic, showed instead location-dependent anisotropic characteristics. In this case, the shape of the bubble (which influences the angle between the bubble’s surface and the AFM tip) was proposed as the key reason to explain the anisotropic phenomenon, and a corresponding model was established to verify the hypothesis.