24 research outputs found
A hyperbolic two -step model based finite difference method for studying thermal deformation in a micro thin film heated by ultrashort -pulsed lasers
Heat transport through micro thin films plays a very important role in microtechnology applications. Many microelectronic devices have metal thin films as their key components. Microscale heat transfer is also important for the thermal processing of materials, including laser micromachining, laser patterning, laser synthesis and laser surface hardening. Hence, studying the thermal behavior of thin films is essential for predicting the performance of a microelectronic device or for obtaining the desired microstructure. Recently, it has become very popular to use ultrashort-pulsed lasers in thermal processing, which lasers have pulse durations of the order of subpicoseconds to femtoseconds, and these kinds of lasers can limit the undesirable spread of the thermal process zone in the heated sample. However, ultrashort-pulsed lasers can induce ultrafast damage, which occurs after the heating pulse is over. Therefore, in order to apply ultrashort-pulsed lasers successfully, one must study the thermal deformation to prevent the thermal damage.
In the previous research, the parabolic two-step micro heat transport equations have been widely applied in microscale heat transfer. However, when the laser pulse duration is much shorter than the electron-lattice thermal relaxation time for the activation of ballistic behavior in the electron gas, the parabolic two-step model may lose accuracy, as pointed out the in the literature.
It has not been seen in the literature employing the hyperbolic two-step model for studying thermal deformation in a micro thin film exposed to ultrashort-pulsed lasers, which is important for enhancing our understanding of micro heat transfer in a micro thin film exposed to ultrashort-pulsed lasers. Hence, the purpose of this dissertation is to employ the hyperbolic two-step model with temperature-dependent thermal properties for obtaining temperature distribution in a thin film induced by ultrashort-pulsed lasers and to couple with the dynamic equations of motions in order to study thermal deformation in the thin film. To this end, we first develop an implicit finite difference scheme for solving the hyperbolic two-step model with temperature-dependent thermal properties. The scheme is shown to satisfy a discrete analogus of an energy estimate. We then apply it to studying thermal deformations in two-dimensional (2D) thin films exposed to ultrashort-pulsed lasers. In this method, staggered grids are designed, and the coupling effect between lattice temperature and strain rate, as well as the hot electron blast effect in momentum transfer, are considered. As such, this obtained method allows us to avoid non-physical oscillations in the solution.
To demonstrate the applicability of the method, we test three physical cases, (1) 1D double-layered thin film with perfectly contacted interface irradiated by ultrashort-pulsed lasers, (2) 2D single-layered thin film irradiated by ultrashort-pulsed lasers, and (3) 2D double-layered thin film with perfectly contacted interface irradiated by ultrashort-pulsed lasers. Results show that the method is promising and there are some differences between the hyperbolic two-step model and the parabolic model. Particularly, one may see the differences regarding the change in electron temperature (Δ Te/(ΔTe)max) and the displacement (u) in x direction
Effects of Temperature on Emergence and Seasonality of West Nile Virus in California
Temperature has played a critical role in the spatiotemporal dynamics of West Nile virus transmission throughout California from its introduction in 2003 through establishment by 2009. We compared two novel mechanistic measures of transmission risk, the temperature-dependent ratio of virus extrinsic incubation period to the mosquito gonotrophic period (BT), and the fundamental reproductive ratio (R0) based on a mathematical model, to analyze spatiotemporal patterns of receptivity to viral amplification. Maps of BT and R0 were created at 20-km scale and compared throughout California to seroconversions in sentinel chicken flocks at half-month intervals. Overall, estimates of BT and R0 agreed with intensity of transmission measured by the frequency of sentinel chicken seroconversions. Mechanistic measures such as these are important for understanding how temperature affects the spatiotemporal dynamics of West Nile virus transmission and for delineating risk estimates useful to inform vector control agency intervention decisions and communicate outbreak potential
Use of media and public-domain Internet sources for detection and assessment of plant health threats
Event-based biosurveillance is a recognized approach to early warning and situational awareness of emerging health threats. In this study, we build upon previous human and animal health work to develop a new approach to plant pest and pathogen surveillance. We show that monitoring public domain electronic media for indications and warning of epidemics and associated social disruption can provide information about the emergence and progression of plant pest infestation or disease outbreak. The approach is illustrated using a case study, which describes a plant pest and pathogen epidemic in China and Vietnam from February 2006 to December 2007, and the role of ducks in contributing to zoonotic virus spread in birds and humans. This approach could be used as a complementary method to traditional plant pest and pathogen surveillance to aid global and national plant protection officials and political leaders in early detection and timely response to significant biological threats to plant health, economic vitality, and social stability. This study documents the inter-relatedness of health in human, animal, and plant populations and emphasizes the importance of plant health surveillance
Recasting the theory of mosquito-borne pathogen transmission dynamics and control
Mosquito-borne diseases pose some of the greatest challenges in public health, especially in tropical and sub-tropical regions of theworld. Efforts to control these diseases have been underpinned by a theoretical framework developed for malaria by Ross and Macdonald, including models, metrics for measuring transmission, and theory of control that identifies key vulnerabilities in the transmission cycle. That framework, especially Macdonald\u27s formula for R0 and its entomological derivative, vectorial capacity, are nowused to study dynamics and design interventions for many mosquito-borne diseases. A systematic review of 388 models published between 1970 and 2010 found that the vast majority adopted the Ross-Macdonald assumption of homogeneous transmission in a well-mixed population. Studies comparing models and data question these assumptions and point to the capacity to model heterogeneous, focal transmission as the most important but relatively unexplored component in current theory. Fine-scale heterogeneity causes transmission dynamics to be nonlinear, and poses problems for modeling, epidemiology and measurement. Novel mathematical approaches show how heterogeneity arises from the biology and the landscape on which the processes of mosquito biting and pathogen transmission unfold. Emerging theory focuses attention on the ecological and social context formosquito blood feeding, themovement of both hosts and mosquitoes, and the relevant spatial scales for measuring transmission and for modeling dynamics and control
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Data-driven modeling to assess receptivity for Rift Valley Fever virus.
Rift Valley Fever virus (RVFV) is an enzootic virus that causes extensive morbidity and mortality in domestic ruminants in Africa, and it has shown the potential to invade other areas such as the Arabian Peninsula. Here, we develop methods for linking mathematical models to real-world data that could be used for continent-scale risk assessment given adequate data on local host and vector populations. We have applied the methods to a well-studied agricultural region of California with [Formula: see text]1 million dairy cattle, abundant and competent mosquito vectors, and a permissive climate that has enabled consistent transmission of West Nile virus and historically other arboviruses. Our results suggest that RVFV outbreaks could occur from February-November, but would progress slowly during winter-early spring or early fall and be limited spatially to areas with early increases in vector abundance. Risk was greatest in summer, when the areas at risk broadened to include most of the dairy farms in the study region, indicating the potential for considerable economic losses if an introduction were to occur. To assess the threat that RVFV poses to North America, including what-if scenarios for introduction and control strategies, models such as this one should be an integral part of the process; however, modeling must be paralleled by efforts to address the numerous remaining gaps in data and knowledge for this system
An Epidemiological Model of Rift Valley Fever with Spatial Dynamics
As a category A agent in the Center for Disease Control bioterrorism list, Rift Valley fever (RVF) is considered a major threat to the United States (USA). Should the pathogen be intentionally or unintentionally introduced to the continental USA, there is tremendous potential for economic damages due to loss of livestock, trade restrictions, and subsequent food supply chain disruptions. We have incorporated the effects of space into a mathematical model of RVF in order to study the dynamics of the pathogen spread as affected by the movement of humans, livestock, and mosquitoes. The model accounts for the horizontal transmission of Rift Valley fever virus (RVFV) between two mosquito and one livestock species, and mother-to-offspring transmission of virus in one of the mosquito species. Space effects are introduced by dividing geographic space into smaller patches and considering the patch-to-patch movement of species. For each patch, a system of ordinary differential equations models fractions of populations susceptible to, incubating, infectious with, or immune to RVFV. The main contribution of this work is a methodology for analyzing the likelihood of pathogen establishment should an introduction occur into an area devoid of RVF. Examples are provided for general and specific cases to illustrate the methodology
Accelerating CPU-based Sparse General Matrix Multiplication with Binary Row Merging
Sparse general matrix multiplication (SpGEMM) is a fundamental building block
for many real-world applications. Since SpGEMM is a well-known memory-bounded
application with vast and irregular memory accesses, considering the memory
access efficiency is of critical importance for optimizing SpGEMM. Yet, the
existing methods put less consideration into the memory subsystem and achieved
suboptimal performance. In this paper, we thoroughly analyze the memory access
patterns of SpGEMM and their influences on the memory subsystem. Based on the
analysis, we propose a novel and more efficient accumulation method named
BRMerge for the multi-core CPU architectures.
The BRMerge accumulation method follows the row-wise dataflow. It first
accesses the matrix, generates the intermediate lists for one output row,
and stores these intermediate lists in a consecutive memory space, which is
implemented by a ping-pong buffer. It then immediately merges these
intermediate lists generated in the previous phase two by two in a tree-like
hierarchy between two ping-pong buffers. The architectural benefits of BRMerge
are 1) streaming access patterns, 2) minimized TLB cache misses, and 3)
reasonably high L1/L2 cache hit rates, which result in both low access latency
and high bandwidth utilization when performing SpGEMM. Based on the BRMerge
accumulation method, we propose two SpGEMM libraries named BRMerge-Upper and
BRMerge-Precise, which use different allocation methods. Performance
evaluations with 26 commonly used benchmarks on two CPU servers show that the
proposed SpGEMM libraries significantly outperform the state-of-the-art SpGEMM
libraries.Comment: This work has been submitted to the IEEE Access since May 31, 2022,
and is currently under review by the IEEE Access. 15 pages, 6 fgures, 2
table
OpSparse: a Highly Optimized Framework for Sparse General Matrix Multiplication on GPUs
Sparse general matrix multiplication (SpGEMM) is an important and expensive
computation primitive in many real-world applications. Due to SpGEMM's inherent
irregularity and the vast diversity of its input matrices, developing
high-performance SpGEMM implementation on modern processors such as GPUs is
challenging. The state-of-the-art SpGEMM libraries (i.e., and
) adopt several algorithms to tackle the challenges of global load
balance, local load balance, and allocation of the result matrix. While these
libraries focus on the high-level algorithm design for SpGEMM, they neglect
several low-level architecture-specific optimizations, which causes inefficient
implementations in their libraries. In this paper, we classify their
inefficient implementations into seven categories. Based on our observations,
we propose a highly optimized SpGEMM library called . The
optimizations in include 1) optimizing the binning method by
improving the utilization of the shared memory, 2) optimizing the hashing
method by reducing the access to the hash table, 3) improving the trade-off
between hash collision rate and hardware utilization in the hashing method by
setting appropriate binning ranges, 4) reducing the overheads of global memory
utilization by minimizing the global memory usage of the metadata, and 5)
improving the execution parallelism by overlapping global memory allocation
with kernel execution. Performance evaluations with 26 commonly used matrices
on an Nvidia Tesla V100 GPU show that achieves up to ,
, and performance speedup over three state-of-the-art
libraries: , , and , respectively.Comment: This paper has been submitted to the IEEE Access since May 7, 2022,
and is currently under review by IEEE Access. 20 pages, 11 fgures, 5 table
Seasonal mosquito abundance patterns.
<p>Realistic annual patterns for <i>Cx. tarsalis</i> and <i>Ae. melanimon</i> defined using trap data for each of the dominant land use categories within the study area. Traps collected <i>Ae. melanimon</i> only in 2 land uses, with the largest numbers occurring in seasonally flooded wetlands.</p
Seasonal temperature pattern within the study area.
<p>Graph showing daily mean temperatures (dark line) and – percentiles (shaded area) for the study area.</p