1,117 research outputs found
Integrated Techno-Economic and Life Cycle Analyses of Biomass Utilization for Value-Added Bioproducts in the Northeastern United States
A multi-stage spatial analysis was first conducted to select locations for lignocellulosic biomass-based bioproduct facility, using Geographical Information System (GIS) spatial analysis, multi-criteria analysis ranking algorithm, and social-economic assessment. A case study was developed to determine locations for lignocellulosic biorefineries using feedstocks including forest residue biomass and three energy crops for 13 states in the northeastern United States. In the entire study area, 11.1% of the counties are high-suitable, 48.8% are medium-suitable for biorefinery siting locations. A non-parametric analysis of cross-group surveys showed that preferences on biorefinery siting are homogeneous for experts in academia and industry groups, but people in government agencies presented different opinions. With the Maximum Likelihood test, parameters of distributions and mean values were estimated for nine weighted criteria. Social asset evaluation focusing on degree of rurality and social capital index further sorted counties with higher community acceptance and economic viability. A total of 15 counties were selected with the highest potential for biorefinery sites in the region.
A mixed-integer linear programming model was then developed to optimize the multiple biomass feedstock supply chains, including feedstock establishment, harvest, storage, transportation, and preprocessing. The model was applied for analyses of multiple biomass feedstocks at county level for 13 states in the northeastern United States. In the base case with a demand of 180,000 dry Mg/year of biomass, the delivered costs ranged from 86.97 per dry Mg with an average of 67.90 to 150.81 per dry Mg across the northeastern U.S. Considered the entire study area, the delivered cost averaged 84.47 /dry Mg for hybrid willow, 97.87 per dry Mg for Miscanthus. Seventy seven out of 387 counties could be able to deliver biomass at 1.20 million for pellet, and 6.66 million, and annual operation cost was 16.79 per kg, with the discounted payback period (DPB) of 9.98 years. Alternative cases of KOH-reuse and steam processes had GHG emission of 15.4 kg CO2 eq, and 10.2 kg CO2 eq for every 1 kg activated carbon, respectively. Monte Carlo simulation showed 49.96% of the probability for an investment to be profitable in activated carbon production for supercapacitor electrodes
Essays on Health-related Disparities
As the most critical conditions of human life and a significant contributor to human capability, health is the fundamental unit for a functioning society. As a construct, health is also inherently multi-dimensional, and to understand and to evaluate whether the infrastructure of a society endows fair "health opportunities" to its people can be an enduring task for both researchers and policy-makers. In this dissertation, I explore this complex and ever more relevant issue of health disparity from different angles using administrative data and extensive exploration of the literature. In particular, I analyse the geographic disparity in quality of care and the potential drivers - differential provider behaviour. Looking at health status, I investigate the disparity of health outcomes due to external economic shocks and found that individuals from economically disadvantaged areas exhibit significantly worse mental health conditions. Given the geographic disparity, I further examine how different sources of information on provider quality affect patient choice and decision to travel for care. Moreover, I survey on how the internet has facilitated the disparity in information and diverging opinions on health. Finally, from a systems perspective, I scrutinise structural characteristics in health care system design that create disparities in benefits and access. My inquiry into the complex phenomenon of health disparity presents a humble contribution to the exiting literature at the intersection of health economics, medical sociology and social epidemiology
ON THE CULTIVATION AND PROMOTION PATH OF COLLEGE STUDENTSâ CULTURAL SELF-CONFIDENCE FROM THE PERSPECTIVE OF POSITIVE PSYCHOLOGY
Mozi: Universal Love and Human Agency
Mozi (c. 480-390 B.C.E.) was a Chinese philosopher from the Warring States period in early Chinese history whose utilitarianism contrasted with Confucian and Daoist thought. Through reading the Mohist text in translation, I examined the relationship between two central principles in Moziâs philosophy: Heavenâs standard universal love and human action. Mozi builds his arguments in the framework of a sociopolitical hierarchy that incorporates utilitarian analyses of customs, morality, and beliefs in ghosts and spirits. By comparing secondary sources in English and Chinese, reading different translations, and learning from graphical analysis of the textâs key termsâ original Chinese ideographs, I concluded that in Moziâs philosophy, human action is the necessary agent to carry out Heavenâs will of universal love for the ultimate goal of benefitting all people
Robust heavy-tailed versions of generalized linear models with applications in actuarial science
Generalized linear models (GLMs) form one of the most popular classes of
models in statistics. The gamma variant is used, for instance, in actuarial
science for the modelling of claim amount in insurance. A flaw of GLMs is that
they are not robust against outliers (i.e., against erroneous or extreme data
points). A difference in trends in the bulk of the data and the outliers thus
yields skewed inference and prediction. Cantoni and Ronchetti (2001) proposed a
robust frequentist approach which is now the most commonly applied. It consists
in an estimator which is derived from a modification of the derivative of the
log-likelihood. We propose an approach which is modelling-based and thus
fundamentally different. It allows for an understanding and interpretation of
the modelling, and it can be applied for both frequentist and Bayesian
statistical analyses. We show that the approach possesses appealing theoretical
and empirical properties. In particular, we show through a simulation study
that it offers an advantage in terms of estimation performance
How Chinese social media sentiment about COVID changed during 2020
Chinese social media sentiment about the pandemic fluctuated during 2020. Yan Wang and Yuxi Zhang (LSE-Fudan Global Public Policy Hub) use platform data to analyse how these waves of sentiment emerged and shifted, and look at the case of Chengdu Girl, a woman who caught COVID in December of that year
Asymptotic stability of rarefaction waves for compressible Navier-Stokes equations with relaxation
The asymptotic stability of rarefaction wave for 1-d relaxed compressible
isentropic Navier-Stokes equations is established. For initial data with
different far-field values, we show that there exists a unique global in time
solution. Moreover, as time goes to infinity, the obtained solutions are shown
to converge uniformly to rarefaction wave solution of -system with
corresponding Riemann initial data. The proof is based on energy methods
Get Out of the Valley: Power-Efficient Address Mapping for GPUs
GPU memory systems adopt a multi-dimensional hardware structure to provide the bandwidth necessary to support 100s to 1000s of concurrent threads. On the software side, GPU-compute workloads also use multi-dimensional structures to organize the threads. We observe that these structures can combine unfavorably and create significant resource imbalance in the memory subsystem causing low performance and poor power-efficiency. The key issue is that it is highly application-dependent which memory address bits exhibit high variability.
To solve this problem, we first provide an entropy analysis approach tailored for the highly concurrent memory request behavior in GPU-compute workloads. Our window-based entropy metric captures the information content of each address bit of the memory requests that are likely to co-exist in the memory system at runtime. Using this metric, we find that GPU-compute workloads exhibit entropy valleys distributed throughout the lower order address bits. This indicates that efficient GPU-address mapping schemes need to harvest entropy from broad address-bit ranges and concentrate the entropy into the bits used for channel and bank selection in the memory subsystem. This insight leads us to propose the Page Address Entropy (PAE) mapping scheme which concentrates the entropy of the row, channel and bank bits of the input address into the bank and channel bits of the output address. PAE maps straightforwardly to hardware and can be implemented with a tree of XOR-gates. PAE improves performance by 1.31 x and power-efficiency by 1.25 x compared to state-of-the-art permutation-based address mapping
- âŠ