Area Trade-offs Research Articles

Urban growth simulation guided by ecosystem service trade-offs in Wuhan metropolitan area: Methods and implications for spatial planning

The effective integration of ecosystem services (ESs) and urban growth simulation is crucial for spatial planning decisions that support sustainable and high-quality development. Interactions (i.e., trade-offs, synergies, and irrelevance) generally exist among ESs, however, few studies have been done on the methodology for simulating urban growth that optimizes the synergistic effect of ESs. In this study, the Wuhan metropolitan area was taken as the research area. Four key ESs in 2000, 2010, and 2020: water yield (WY), carbon storage (CS), habitat quality (HQ), and soil retention (SR) were evaluated by using the InVEST model. Then the ordered weighted averaging (OWA) method was applied to optimally allocate ESs trade-offs and identify ecological priority protection areas (EPPAs). Finally, the PLUS model was used to simulate urban growth scenarios under different levels of ESs protection constraints and propose spatial planning strategies. The results revealed the following. (1) From 2000 to 2020, the three ESs (i.e., WY, CS, and HQ) exhibited the spatial distribution pattern with high in the east and low in the west, and higher in the woodland than in built-up areas, except SR, which remained at a weak level throughout the region. (2) During the 20 years, SR and the other three ESs, HQ and CS showed a synergistic relationship; WY exhibited a very weak trade-off with HQ; and WY and CS changed from a very weak trade-off to a weak synergy. (3) Seven ecosystem service patterns (ESPs) were generated, and ESP 5 was compared as the ideal option. The weights of SR, WY, CS, and HQ in this pattern were 0.063, 0.187, 0.313, and 0.437, respectively. (4) By 2030, the built-up areas will exhibit edge expansion and interconnection development trends, with the high-constraint ecological protection scenario as the most compact mode, and the spatial structure of “two districts, one axis, four cities as one” is consistent with the development tendency. Our findings can help to enrich the method of urban growth management oriented by ecological protection, and provide a scientific basis for ecological environment restoration and land use spatial planning practices.

CSAIL2019 Crypto-Puzzle Solver Architecture

tThe CSAIL2019 time-lock puzzle is an unsolved cryptographic challenge introduced by Ron Rivest in 2019, replacing the solved LCS35 puzzle. Solving these types of puzzles requires large amounts of intrinsically sequential computations, with each iteration performing a very large (3,072-bit for CSAIL2019) modular multiplication operation. The complexity of each iteration is several times greater than known field-programmable gate array (FPGA) implementations, and the number of iterations has been increased by about 1,000x compared with LCS35. Because of the high complexity of this new puzzle, a number of intermediate, or milestone, versions of the puzzle have been specified. In this article, we present several FPGA architectures for the CSAIL2019 solver, which we implement on a medium-sized Intel Agilex device. We develop a new multi-cycle modular multiplication method, which is flexible and can fit on a wide variety of sizes of current FPGAs. We introduce a class of multi-cycle squarer-based architectures that allow for better resource and area trade-offs. We also demonstrate a new approach for improving the fitting and timing closure of large, chip-filling arithmetic designs. We used the solver to compute the first 23 out of 28 milestone solutions of the puzzle, which are the first reported results for this problem.

Internal-states beat-frequency ADC using a subcircuit sharing architecture for SNDR improvement with decreased area tradeoff

Internal-states beat-frequency ADC using a subcircuit sharing architecture for SNDR improvement with decreased area tradeoff

Socio-economic and environmental trade-offs in Amazonian protected areas and Indigenous territories revealed by assessing competing land uses.

Protected area (PA) assessments rarely evaluate socio-economic and environmental impacts relative to competing land uses, limiting understanding of socio-environmental trade-offs from efforts to protect 30% of the globe by 2030. Here we assess deforestation and poverty outcomes (fiscal income, income inequality, sanitation and literacy) between 2000 and 2010 of strict PAs (SPAs), sustainable-use PAs (SUPAs) and Indigenous territories (ITs) compared with different land uses (agriculture and mining concessions) across ~5,500 census tracts in the Brazilian Legal Amazon. ITs reduced deforestation relative to all alternative land uses (48-83%) but had smaller socio-economic benefits compared with other protection types and land uses (18-36% depending on outcome), indicating that Indigenous communities experience socio-economic trade-offs. By contrast, SUPAs, and potentially SPAs, did not reduce deforestation relative to small-scale agriculture (landholdings <10 ha) but did so relative to larger agricultural landholdings (70-82%). Critically, these reductions in deforestation frequently occurred without negative socio-economic outcomes. By contrast, ITs and SUPAs protected against deforestation from mining, but at the cost of smaller improvements in income and inequality. Our results suggest that although PAs in the Brazilian Legal Amazon substantially reduced deforestation without compromising local socio-economic development, efforts to secure Indigenous rights need additional interventions to ensure these communities are not further disadvantaged.

Coupling management ecosystem service supply-supply trade-offs and supply–demand trade-offs: Framework and practice

Ecosystem services (ESs) are the bridge between ecosystem and social system, and how to effectively manage different types of ES trade-offs is the key barrier to ensure that ecosystems provide sustainable benefits for human beings. The objective of this study is to propose a theoretical and methodological framework for the coupled management of ES supply-supply trade-offs and demand-demand trade-offs and to propose an ES trade-offs management scheme for the study area (Jiangxi Province) according to this framework. In this study, we evaluated the provision of ES and the intensity of two types of ES trade-offs in the study area through InVest model, and explored the driving mechanism of the two types of ES trade-offs through redundancy analysis. Finally, we proposed a land use structure in the study area that alleviates the intensity of both types of ES trade-offs through multi-objective nonlinear programming. The results showed that: (1) the water yield service supply in Jiangxi Province showed a pattern of high in the north and low in the south, and the carbon sequestration service supply showed a pattern of high in the south and low in the north. (2) The supply-supply trade-off intensity of two ES is generally low in the north and high in the south, and the supply–demand trade-off intensity of water yield service and carbon sequestration service is basically high in the densely populated area in the north of Jiangxi. (3) Forestland area, farmland area and water area are the supply–demand trade-off driving forces of water yield service and carbon sequestration service, grassland area is an independent driving force of carbon sequestration service, and farmland area and cultivated land area are the supply-supply trade-off driving forces. The study shows that in order to achieve the lowest supply-supply trade-off intensity and supply–demand trade-off intensity in Jiangxi Province at the same time, the forestland should reach at least 104470 km2, the water area should reach 12,900.7 km2, the farmland area should reach 281333.3 km2, and the grassland area should increase to 15,457.9 km2. The results are expected to provide a new perspective for ecosystem management research.

A social-ecological approach for identifying and mapping ecosystem service trade-offs and conservation priorities in peri-urban areas.

Considering both ecological and social dimensions in the assessment of ecosystem services (ESs) can facilitate acceptable and inclusive management strategies, especially in peri-urban areas characterized by intricate human-ecosystem interactions. A limited body of research, however, has mapped the plural values of ESs and their different types of trade-offs in such areas. This research aimed to execute an interdisciplinary analysis of the biophysical and social values of ESs in peri-urban Shanghai, China, through a social-ecological approach that integrates spatial biophysical assessment with participatory mapping. Trade-off analysis in both ES types and ES valuations were then conducted, and multicriteria decision-making was applied for conservation. Our results reveal that trade-off intensities were lower within the social values compared to the biophysical values. Within both value dimensions, relatively stronger trade-offs were found between food production and other ESs. Areas with both high biophysical and social values were infrequently observed across ESs. Based on the characteristics of diverse values, our study identified priority conservation areas and provided management implications. We argue that adopting the integrated social-ecological perspective in sustainable environmental management contributes to the realization of harmonious coexistence between people and nature in peri-urban areas.

Towards Automated RISC-V Microarchitecture Design with Reinforcement Learning

Microarchitecture determines the implementation of a microprocessor. Designing a microarchitecture to achieve better performance, power, and area (PPA) trade-off has been increasingly difficult. Previous data-driven methodologies hold inappropriate assumptions and lack more tightly coupling with expert knowledge. This paper proposes a novel reinforcement learning-based (RL) solution that addresses these limitations. With the integration of microarchitecture scaling graph, PPA preference space embedding, and proposed lightweight environment in RL, experiments using commercial electronic design automation (EDA) tools show that our method achieves an average PPA trade-off improvement of 16.03% than previous state-of-the-art approaches with 4.07× higher efficiency. The solution qualities outperform human implementations by at most 2.03× in the PPA trade-off.

Competing digital capacities: between state-led digital governance and local data center tradeoffs

ABSTRACT Governments worldwide are embracing digital transformation, envisioning limitless data capacities for public policy. However, this paper uncovers a crucial oversight: the neglect of material resources sustaining digital ecosystems. This paper introduces contested ‘digital capacities’ in public policy, to show how the aspiration for unlimited data processing strains local resources. Through a comparative analysis of national digitization strategies in the United States and the United Kingdom, this paper reveals a disconnect between the sociotechnical imaginaries and infrastructural demands underpinning these strategies. The infrastructural demands are leading to social and environmental tradeoffs in regional areas strained by digital infrastructure development. I argue that these competing digital capacities – the capacity to govern through digitization and related resource capacities – provide productive data friction for governments to pause and assess the broader social and ecological costs of their national digitization policies. As such, this article emphasizes the need for policymakers to align national digital governance strategies with regional planning for equitable outcomes. By reevaluating competing digital capacities encompassed in national sociotechnical imaginaries, this paper highlights the urgent need for a balanced approach to digitization.

Accuracy Analysis on Design of Stochastic Computing in Arithmetic Components and Combinational Circuit

Stochastic circuits are used in applications that require low area and power consumption. The computing performed using these circuits is referred to as Stochastic computing (SC). The arithmetic operations in this computing can be realized using minimum logic circuits. The SC system allows a tradeoff of computational accuracy and area; thereby, the challenge in SC is improving the accuracy. The accuracy depends on the SC system’s stochastic number generator (SNG) part. SNGs provide the appropriate stochastic input required for stochastic computation. Hence we explore the accuracy in SC for various arithmetic operations performed using stochastic computing with the help of logic circuits. The contributions in this paper are; first, we have performed stochastic computing for arithmetic components using two different SNGs. The SNGs considered are Linear Feed-back Shift Register (LFSR) -based traditional stochastic number generators and S-box-based stochastic number generators. Second, the arithmetic components are implemented in a combinational circuit for algebraic expression in the stochastic domain using two different SNGs. Third, computational analysis for stochastic arithmetic components and the stochastic algebraic equation has been conducted. Finally, accuracy analysis and measurement are performed between LFSR-based computation and S-box-based computation. The novel aspect of this work is the use of S-box-based SNG in the development of stochastic computing in arithmetic components. Also, the implementation of stochastic computing in the combinational circuit using the developed basic arithmetic components, and exploration of accuracy with respect to stochastic number generators used is presented.

Trade-off and driving factors of water-energy-food nexus in Mu Us sandy land, China

Water, energy, and food are essential resources for human survival. The trade-off among these resources can limit regional economic development and pose challenges to livelihood security. In this study, we constructed a root-mean-square deviation (RMSD) index to measure the water-energy-food nexus (WEFN) trade-off. Multi-source data and analysis methods, including ordinary least square (OLS), geographically weighted regression (GWR), and geographic detectors (GD) are employed to explore the trade-offs of water, energy, and food resources and their dominant influencing factors in the Mu Us Sandy Land. The results indicate that the trade-off between regional water-food sub-nexus exhibited the highest magnitude, and trade-offs among all sub-nexus types demonstrated significant fluctuations in spatial distribution. Both OLS and GWR results identified temperature, precipitation, normalized differential vegetation index, slope, digital elevation model, and nighttime light as significant factors influencing the spatial differentiation of WEFN trade-offs. Moreover, geographic detector analysis indicated that precipitation is the dominant factor, and its interaction with other influencing factors further impacts the regional WEFN trade-off. The discussion section examines the RMSD method's effectiveness, the dominant factors shaping WEFN trade-offs, as well as scale effect in WEFN trade-offs in the Mu Us area and underscores that mitigation of water shortages can yield a leverage effect, leading to a marked reduction in the trade-offs. This research contributes new ideas and tools to WEFN research from a geographic perspective, aiming to provide guidance for collaborative resource management and regional sustainable development.

TF-Predictor: Transformer-Based Prerouting Path Delay Prediction Framework

Timing mismatch between different stages of physical design poses great challenges for circuit optimization to achieve the desired performance, power and area (PPA) tradeoff. The inaccurate timing estimation prior to routing may lead to over-design with unwanted power and area consumption or iterating back to cell placement at the cost of design turn-around time. Existing learning models could not predict post-routing circuit timing with satisfying accuracy and efficiency due to the limitations of the ignorance of delay correlation along the timing path and the empirical feature selection solutions. In this work, an accurate and efficient pre-routing path delay prediction framework is proposed by utilizing transformer network and residual model with an ensemble feature selection mechanism. Owing to the combined filter and wrapper methods, an ensemble feature selection mechanism is implemented to determine the optimal feature subset based on the timing and physical information at the placement stage for path delay prediction, which is extracted as feature sequences for each cell along the timing path to be trained by transformer network. With the residual model, the predicted timing mismatch between the placement and routing stages by transformer network is further calibrated to estimate the post-routing path delay. The proposed framework has been validated with ISCAS’85 and OpenCores benchmark circuits for the prediction of post-routing path delay, where the perdition error in terms of rRMSE is limited within 1.3% and 3.0% and the correlation coefficient R is higher than 0.999 and 0.995 for seen and unseen circuits respectively, indicating an error reduction by 2.3 10.6 times compared by prior learning-based models. In addition, the framework achieves average three orders of magnitude speedup compared with the commercial tools and is accelerated by a factor of 14 128 as against the competitive learning models, which is promising to be applied to guide design optimization prior to time-consuming routing stage.

Automatic Generation of Spatial Accelerator for Tensor Algebra

Tensor algebra finds applications in various domains including machine learning applications, data analytics and others. Spatial hardware accelerators are widely used to boost the performance of tensor algebra applications. It has a complex hardware architecture and rich design space. Prior approaches based on manual implementation lead to low programming productivity, making it hard to explore the large design space. In this paper, we propose Tensorlib, a framework for generating spatial hardware accelerators for tensor algebra applications. Tensorlib is motivated by the observation that, tensor dataflows can be expressed with linear transformations, and they share common hardware modules which can be reused across different designs. Tensorlib first uses Space-Time Transformation to explore different dataflows, which can compactly represent the hardware dataflow using a transformation matrix. Next, we identify the common structures of different dataflows and build parameterized hardware module templates. Our generation framework can select the needed hardware modules for each dataflow, connect the modules using a specified interconnection pattern, and automatically generate the complete hardware accelerator design. Tensorlib remarkably improves the productivity for the development and optimization of spatial hardware architecture, providing a rich design space with trade-offs in performance, area, and power. Experiments show that Tensorlib can automatically generate hardware designs with different dataflows for a variety of tensor algebra programs. Tensorlib can achieve 318 MHz frequency and 786 GFLOP/s throughput for matrix multiplication kernel on Xilinx VU9P FPGA, which outperforms the state-of-the-art generators.

A Horizon Scan to Support Chemical Pollution-Related Policymaking for Sustainable and Climate-Resilient Economies.

While chemicals are vital to modern society through materials, agriculture, textiles, new technology, medicines, and consumer goods, their use is not without risks. Unfortunately, our resources seem inadequate to address the breadth of chemical challenges to the environment and human health. Therefore, it is important we use our intelligence and knowledge wisely to prepare for what lies ahead. The present study used a Delphi-style approach to horizon-scan future chemical threats that need to be considered in the setting of chemicals and environmental policy, which involved a multidisciplinary, multisectoral, and multinational panel of 25 scientists and practitioners (mainly from the United Kingdom, Europe, and other industrialized nations) in a three-stage process. Fifteen issues were shortlisted (from a nominated list of 48), considered by the panel to hold global relevance. The issues span from the need for new chemical manufacturing (including transitioning to non-fossil-fuel feedstocks); challenges from novel materials, food imports, landfills, and tire wear; and opportunities from artificial intelligence, greater data transparency, and the weight-of-evidence approach. The 15 issues can be divided into three classes: new perspectives on historic but insufficiently appreciated chemicals/issues, new or relatively new products and their associated industries, and thinking through approaches we can use to meet these challenges. Chemicals are one threat among many that influence the environment and human health, and interlinkages with wider issues such as climate change and how we mitigate these were clear in this exercise. The horizon scan highlights the value of thinking broadly and consulting widely, considering systems approaches to ensure that interventions appreciate synergies and avoid harmful trade-offs in other areas. We recommend further collaboration between researchers, industry, regulators, and policymakers to perform horizon scanning to inform policymaking, to develop our ability to meet these challenges, and especially to extend the approach to consider also concerns from countries with developing economies. Environ Toxicol Chem 2023;42:1212-1228. © 2023 Crown copyright and The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC. This article is published with the permission of the Controller of HMSO and the King's Printer for Scotland.

Ecosystem Service Synergies Promote Ecological Tea Gardens: A Case Study in Fuzhou, China

Exploring the trade-off/synergy among ecosystem services (ESs) of agroecosystems could provide effective support for improving agricultural resilience for sustainable development. The construction of ecological tea gardens is emerging, aims to achieve a win-win situation for the tea industry and ecological environment protection. However, the effect of ES trade-offs/synergies on tea production is still not clear. In this study, we selected Fuzhou city, China, as a case study and explored the relationship among tea production and ESs in 2010 and 2020. Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) and Intelligent Urban Ecosystem Management System (IUEMS) models were used to assess the ecosystem (dis)services, which were tea production, water yield, soil retention, net primary productivity (NPP), climate regulation, soil erosion and carbon emissions. Then, the sum of trade-off/synergy coefficients of ESs (Cts) were defined to reveal the trade-off/synergy in tea gardens and areas except tea gardens (ETG areas). K-means clustering was used to assess the spatiotemporal change of traditional tea garden and ecological tea garden, reflecting the effect of ecological tea garden construction. The results showed that: (1) the high-value areas of tea production were mainly distributed in Lianjiang County, with yields up to 3.6 t/ha, and the low-value areas in Yongtai County, with yields from 0.1–1.0 t/ha. Other ESs showed spatial heterogeneity. (2) The trade-offs in ETG areas intensified from 2010 to 2020, with Cts decreasing from −0.28 to −0.73, and the synergy in tea garden was at risk of decline, with Cts decreasing from 4.46 to 1.02. (3) From 2010 to 2020, 96.72% of traditional tea gardens (Area I) were transformed into ecological tea gardens (Areas IV and V). (4) Further, we classified the tea garden into five zones based on tea yield, with Zone I as the low tea yield areas and Zone V as the highest. From Zone I to Zone V, the Cts increased from 2.6 to 7.5 in 2010, and from 1.9 to 6.5 in 2020, respectively. These results demonstrate the effectiveness of the construction of ecological tea gardens in Fuzhou and provide a reference for subsequent studies on the ESs of tea gardens and governance of ecological tea gardens.

Going big by going small: Trade-offs in microbiome explanations of cancer

Microbial factors have been implicated in cancer risk, disease progression, treatment and prevention. The key word, however, is “implicated.” Our aim in this paper is to map out some of the tensions between competing methods, goals, and standards of evidence in cancer research with respect to the causal role of microbial factors. We discuss an array of pragmatic and epistemic trade-offs in this research area: prioritizing coarse-grained versus fine-grained explanations of the roles of microbiota in cancer; explaining general versus specific cancer targets; studying model organisms versus human patients; and understanding and explaining cancer versus developing diagnostic tools and treatments. In light of these trade-offs and the distinctive complexity and heterogeneity on both sides of the microbiome-cancer relationship, we suggest that it would be more productive and intellectually honest to frame much of this work, at least currently, in terms of generating causal hypotheses to investigate further. Claims of established causal connections between the microbiome and cancer are in many cases overstated. We also discuss the value of “black boxing” microbial causal variables in this research context and draw some general cautionary lessons for ongoing discussions of microbiomes and cancer.

Nitrogen and oxygen codoped porous carbon based on a synthetic polymer for high-performance solid-state supercapacitors

Most commercial supercapacitors are fabricated using porous carbon; however, their energy densities are relatively low. To further improve the energy storage performance of supercapacitors assembled using carbon materials, a novel synthetic polymer-derived carbon (SPMA-BQ-x-T) material was prepared by a facile and low-cost strategy. The SPMA-BQ-x-T materials exhibit coexistent structure of micropores and mesopores, homogeneous N, O codoping, and connected spherical morphology. In addition, although SPMA-BQ-x-T materials have low N-doping content (<2 %), they show large specific surface area of approximately 2000 m2 g−1, which maybe partly attribute to the abundance CN single bonds existed in the precursor of SPMA-BQ. They are further used as the electrode materials in supercapacitors. The electrodes (SPMA-BQ-5-800) prepared under the optimal conditions show a high specific capacitance of 414.6 F g−1 at 0.5 A g−1 in a three-electrode system and 254 F g−1 at 0.5 A g−1 in solid-state supercapacitors (SSCs). The SSCs also display high energy density, long-term cycling stability, and good rate capability, suggesting their application potential in energy storage fields. This work achieves good electrochemical effect without pursuing high N-doping content by using a facile and low-cost preparation strategy, which has certain significance for the trade-off of specific surface area and N-doping content.

Evaluating Trade-Off and Synergies of Ecosystem Services Values of a Representative Resources-Based Urban Ecosystem: A Coupled Modeling Framework Applied to Panzhihua City, China

Following significant urban expansion, the ecological problems of resource-based cities are gradually exposed. It is of great significance to study the ecosystem services of resource-based cities to achieve their sustainable development goals and to alleviate the conflicts between environmental protection and the utilization of the surrounding resources. However, in the current research on resource-based cities, few scholars have combined multiple minerals and multiple ecosystem services to explore the impact of mineral resources on the ecosystem. In this study, based on the historical data spanning from 2002 to 2018, we used the CA–Markov model to project the land use of Panzhihua City to 2030. Based on future land use projection, we quantified four ecosystem services (ESs) variables, including water yield, carbon storage, habitat quality, and soil conservation, using the InVEST model from the perspective of land use evolution in Panzhihua City. In addition, we explored the trade-offs and synergies of different ecosystem services and the correlations between different mineral species and ecosystem services using Spearman’s correlation coefficient. Results showed the following: (1) During 2002–2018, water yield service, habitat quality service, and carbon storage service of Panzhihua City decreased year by year, and soil conservation service showed significant fluctuations; most of the low ESs areas were distributed in the central region of Panzhihua. On the contrary, most high ESs areas were located in the forest region. (2) The trade-offs and synergistic relationships among different ecosystem services showed significant spatial variations. There were synergistic relationships among ESs and weak trade-offs between water yield services, soil conservation, and habitat quality services. There was also significant spatial variability in the trade-offs and synergies among ecosystem services, with water production services showing “east trade-offs and west synergies” with soil conservation and habitat quality services, and most of the rest showing trade-offs in urban areas. (3) ESs in mining areas showed trade-offs in general, mainly between water production services and carbon storage services, with clay as the major negative factor of mineral species, and iron ore mines that have undergone ecological protection construction showed the lowest negative impact on ecology.

Ecosystem service trade-offs and spatial non-stationary responses to influencing factors in the Loess hilly-gully region: Lanzhou City, China

The identification of trade-offs and synergies relationships among ecosystem services is one of the important contents of evaluating the regional ecological environment, and is of great significance to regional ecological governance and sustainable development. In this study, Lanzhou was selected as the research area. Four key ecosystem services, such as habitat quality, soil retention, food production, and ecological leisure were evaluated by using the InVEST model and related formulas. The difference comparison method was used to measure trade-offs and synergies relationships among ecosystem services. Then the spatial non-stationarity response of the trade-offs to influencing factors was explored through GWLR model. Finally, the trade-offs intensity among the ecosystem services of each township was calculated by using the PPF and the trade-offs intensity index, and township development strategies to enhance synergies had been formulated. The results showed: (1) The high-value areas of habitat quality, soil retention, and ecological leisure were all distributed in the areas with high vegetation coverage such as nature reserves, national forest parks, and forest farms, while the high-value areas of food production services were distributed in the Qinwangchuan Basin, Zhuanglang River and Wanchuan Basin and other areas with abundant water resources. (2) The spatial distribution pattern of trade-offs and synergies relatiionships among ecosystem services had heterogeneity. Among them, the habitat quality-food production, soil rentention-food production and habitat quality-ecological leisure services were mainly trade-offs in the whole study area, and the remaining services were mainly synergistic. (3) The relationships between ecosystem services trade-offs and influencing factors, including ≥0 °C accumulated temperature, DEM and construction land area proportion, were robust, and the response of trade-offs to ≥0 °C accumulated temperature and DEM was highly similar. (4) Based on the principle of superposition analysis method, the whole study area was divided into four types of areas: I (4 types of services coexistence), II (3 types of services coexistence), III (2 types of services coexistence) and IV (to develop at most one service). This study can provide certain scientific guidance for the optimization and governance of regional ecosystems and the synergic development of townships.

Hybrid Accumulator Factored Systolic Array for Machine Learning Acceleration

Deep learning applications have become ubiquitous in today’s era and it has led to vast development in machine learning (ML) accelerators. Systolic arrays have been a primary part of ML accelerator architecture. To fully leverage the systolic arrays, it is required to explore the computer arithmetic data-path components and their tradeoffs in accelerators. We present a novel factored systolic array (FSA) architecture, in which the carry propagation adder (CPA) and carry-save adder (CSA) perform hybrid accumulation on least significant bit (LSB) bits and most significant bits (MSB) bits, respectively, inside each processing element. In addition, a small CPA to complete accumulation for MSB bits along with rounding logic for each column of the array is placed, which not only reduces the area, delay, and power but also balances the combinational and sequential area tradeoffs. We demonstrate the hybrid accumulator with partial CPA factoring in “Gemmini,” an open-source practical systolic array accelerator and factoring technique does not change the functionality of the base design. We implemented three baselines, original Gemmini and two variants of it, and show that the proposed approach leads to overall significant reduction in area within the range 12.8% – 50.2% and in power within the range 18.6% – 41% with improved or similar delay in comparison to the baselines.

Land use trade-offs in China's protected areas from the perspective of accounting values of ecosystem services

“Accounting values” (quantity * unit value), assessed with an assumption of a constant unit value, are often used in creating macroeconomic aggregates like Gross Domestic Product (GDP). This approach has also been used to estimate the total value of ecosystem services (ES) - the benefits humans receive from functioning ecosystems. In China, this has been referred to as Gross Ecosystem Product (GEP). While the concepts of value and ES may be understood from multiple perspectives, ESs' accounting values contribute important information to the discussion of land use trade-offs in China's protected areas (PAs). These trade-offs include (1) whether additional conserved lands should be opened to tourism development, since tourism brings both positive and negative impacts; (2) whether PAs should be reduced, maintained, or expanded, since PAs safeguard sustainable wellbeing but also require maintenance; and (3) how to undertake conservation on lands traditionally used for human livelihood development, since conservation and livelihood may conflict. Previous studies have suggested (1) joint evaluation based on both GDP and ESs' values may lead to more sustainable decision-making than solely GDP-oriented evaluation; (2) the benefits of maintaining terrestrial PAs in China is $2.64 trillion/yr, over 14 times greater than the costs; (3) integrating ES valuation into environmental impact assessment helps link environmental impacts with human wellbeing and financial costs (e.g., land encroachment of a tourism highway in the Wulingyaun Scenic Area was estimated to cause permanent loss of ES values at $0.5 million/yr); and (4) integrating non-marketable cultural ESs into payment for ESs schemes can further balance conservation with livelihood development. Future research should consider (1) option and non-use values to present a more comprehensive picture of PAs' contributions to sustainable wellbeing and human interdependence with the rest of nature (2) both PAs' quantity (e.g., optimal coverage of PAs); and quality (e.g., management effectiveness, connectivity); (3) more sophisticated and feasible valuation methods (e.g., more cost-effective and engaged deliberation) to improve the credibility of aggregate values over large spatial scales; and (4) interaction between environmental components and ESs.