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ObjectivesNeighborhood disadvantage may increase the risk of adverse health outcomes among older refugees. Yet few studies rigorously estimate the effects of place-based factors on later-life health, particularly dementia and mortality. Evidence about refugees is especially sparse.MethodsThis study leveraged a natural experiment in the form of a Danish policy (1986-1998) that dispersed refugees quasi-randomly across neighborhoods upon arrival. We used longitudinal registers allowing 30 years of follow-up among refugees aged 40+ years upon arrival in Denmark (N = 9,854). Cox models assessed the association between neighborhood disadvantage and risk of dementia and mortality. We examined heterogeneous effects by sex, age, and family size. We also examined associations among non-refugee immigrants and native-born Danes.ResultsNeighborhood disadvantage was not associated with dementia in any group. One unit increase in neighborhood disadvantage index (ranges -8 to 5.7) was associated with greater mortality risk among non-refugee immigrants (HR 1.06, 95%CI: 1.02, 1.10) and native-born Danes (HR 1.11, 95%CI: 1.06, 1.17). In contrast, neighborhood disadvantage was associated with lower mortality risk among refugees (HR 0.96, 95%CI: 0.93, 0.99). Neighborhood disadvantage remained negatively associated with mortality risk in subgroups: refugees who are female (on moderate-disadvantage compared to low-disadvantage), aged 60+, and who arrived with families.DiscussionWhile neighborhood disadvantage was associated with lower mortality risk among refugees, it was associated with greater mortality risk among non-refugee immigrants and native-born Danes, perhaps due to confounding in the latter groups or different place-based experiences by immigration status. Future research is warranted to explain the reasons for contrasting findings.

Marinolides A and B, two new 24- and 26-membered bacterial macrolactones, were isolated from the marine-derived actinobacterium AJS-327 and their stereostructures initially assigned by bioinformatic data analysis. Macrolactones typically possess complex stereochemistry, the assignments of which have been one of the most difficult undertakings in natural products chemistry, and in most cases, the use of X-ray diffraction methods and total synthesis have been the major methods of assigning their absolute configurations. More recently, however, it has become apparent that the integration of bioinformatic data is growing in utility to assign absolute configurations. Genome mining and bioinformatic analysis identified the 97 kb mld biosynthetic cluster harboring seven type I polyketide synthases. A detailed bioinformatic investigation of the ketoreductase and enoylreductase domains within the multimodular polyketide synthases, coupled with NMR and X-ray diffraction data, allowed for the absolute configurations of marinolides A and B to be determined. While using bioinformatics to assign the relative and absolute configurations of natural products has high potential, this method must be coupled with full NMR-based analysis to both confirm bioinformatic assignments as well as any additional modifications that occur during biosynthesis.

The primary objective of this study was to detect vegetation disturbance resulting from visitor use by using remote sensing. A pre-classification change detection analysis based on the normalized difference vegetation index was utilized to measure the amount of vegetation cover changes at Cadillac Mountain summit, Acadia National Park, Maine. By analyzing new remote sensing data collected in 2010 and 2018, we compared the vegetation conditions at the summit (experimental site) with a nearby site with little or no visitor use (control site). Additionally, the study was designed to examine vegetation cover changes between 2001–2007 (the first time frame) and 2010–2018 (the second time frame). Similar to the results observed in the first time frame, the experimental and control sites exhibited more vegetation increase than vegetation decrease in the second time frame. The amount of vegetation increase was 1,425m2 at the experimental site and 400m2 at the control site. The amount of vegetation decrease was 150m2 at the experimental site and 75m2 at the control site. Measurable vegetation cover changes based on the remote sensing analysis could provide baseline data for monitoring further changes over an extended period of time. The advantages of using remote sensing in detecting vegetation conditions are also discussed, along with management and research implications. Keywords: remote sensing, recreation ecology, vegetation, visitor impact monitoring, parks and protected areas

BackgroundCardiovascular disease (CVD) disproportionately affects Black adults in the United States. This is increasingly acknowledged to be due to inequitable distribution of health-promoting resources. One potential contributor is inequities in educational opportunities, although it is unclear what aspects of education are most salient. School racial segregation may affect cardiovascular health by increasing stress, constraining socioeconomic opportunities, and altering health behaviors. We investigated the association between school segregation and Black adults' CVD risk.Methods and findingsWe leveraged a natural experiment created by quasi-random (i.e., arbitrary) timing of local court decisions since 1991 that released school districts from court-ordered desegregation. We used the Panel Study of Income Dynamics (PSID) (1991 to 2017), linked with district-level school segregation measures and desegregation court order status. The sample included 1,053 Black participants who ever resided in school districts that were under a court desegregation order in 1991. The exposure was mean school segregation during observed schooling years. Outcomes included several adult CVD risk factors and outcomes. We fitted standard ordinary least squares (OLS) multivariable linear regression models, then conducted instrumental variables (IV) analysis, using the proportion of schooling years spent in districts that had been released from court-ordered desegregation as an instrument. We adjusted for individual- and district-level preexposure confounders, birth year, and state fixed effects. In standard linear models, school segregation was associated with a lower probability of good self-rated health (-0.05 percentage points per SD of the segregation index; 95% CI: -0.08, -0.03; p < 0.001) and a higher probability of binge drinking (0.04 percentage points; 95% CI: 0.002, 0.07; p = 0.04) and heart disease (0.01 percentage points; 95% CI: 0.002, 0.15; p = 0.007). IV analyses also fou

From the first year of life, children represent others’ actions as goal-directed, and can reason about the causes and motivations behind others’ observable movements. While the majority of developmental literature has focused on early instrumental goals (e.g., interacting with objects), less attention has been devoted to characterizing children’s production and reasoning about non-instrumental movements and non-object-directed goals. However, these kinds of actions have the potential to play a large role in young children’s lives in the form of everyday movements such as dance and gesture. In this dissertation, I explore the extent to which children readily produce and comprehend meaningful movements with a rich spectrum of abstract goals. Specifically, I focus on dance-like movement to music, movements that produce musical sounds, and communicative movements that accompany speech (gestures). In Chapter 1, I ask whether infants readily demonstrate dance-like movement to music at home and whether early development of these behaviors has been underestimated by in-lab studies. I show that children produce dance-like behavior earlier than previously believed, and that infant dance shows developmental change with both maturation and learning. I argue that children’s dance behavior provides a window into early social, cognitive, and motor development. In Chapter 2, I explore children’s reasoning about movements that produce musical sounds. I present evidence that from childhood (6 years of age) onward, rational causal inference plays a role in linking music with agents and movements. I also find evidence of developmental change, such that preschool age children may not engage in causal reasoning about music as older children do. In Chapter 3, I shift to explore the relationship between movement and analogical reasoning. Through both correlational and experimental methods observing children’s gesture production, I suggest that children’s spontaneous gestures provide a wind

ObjectivesRepeated hospitalizations among older adults receiving Home- and Community-Based Services (HCBS) may indicate unmet medical and social needs. This study examined all-cause hospitalization trajectories and the association between area-level resource density for medical and social care and the trajectory group membership.MethodsThe study participants included 11,223 adults aged 60 years or older who were enrolled in public HCBS programs in Michigan between 2008 and 2012. Data sources included the Michigan interRAI-Home Care, Dartmouth Atlas of Health Care Data, the American Community Survey, and the County Business Patterns from the Census Bureau. The group-based trajectory modeling was used to identify trajectories of hospitalization over 15 months. Correlates of the trajectories were examined using multinomial logistic regression.ResultsFour distinct hospitalization trajectory groups emerged: "never" (43.1%)-individuals who were rarely hospitalized during the study period, "increasing" (19.9%)-individuals who experienced an increased risk of hospitalization, "decreasing" (21.6%)-individuals with a decreased risk, and "frequent" (15.8%)-individuals with frequent hospitalizations. Older adults living in areas with a higher number of social service organizations for older adults and persons with disability were less likely to be on the "frequent" trajectory relative to the "decreasing" trajectory. The density of primary care physicians was not associated with the trajectory group membership.DiscussionArea-level social care resource density contributes to changes in 15-month hospitalization risks among older adult recipients of HCBS.

The chemical examination of two undescribed marine actinobacteria has yielded three rare merosesterterpenoids, marinoterpins A-C (1-3, respectively). These compounds were isolated from the culture broth extracts of two marine-derived actinomycetes associated with the family Streptomycetaceae, (our strains were CNQ-253 and AJS-327). The structures of the new compounds were determined by extensive interpretation of 1D and 2D NMR, MS, and combined spectroscopic data. These compounds represent new chemical motifs, combining quinoline-N-oxides with a linear sesterterpenoid side chain. Additionally, consistent in all three metabolites is the rare occurrence of two five-ring ethers, which were derived from an apparent cyclization of methyl group carbons to adjacent hydroxy-bearing methylene groups in the sesterterpenoid side chain. Genome scanning of AJS-327 allowed for the identification of the marinoterpin (mrt) biosynthetic cluster, which consists of 16 open-reading frames that code for a sesterterpene pyrophosphate synthase, prenyltransferase, type II polyketide synthase, anthranilate:CoA-ligase, and several tailoring enzymes apparently responsible for installing the N-oxide and bis-tetrahydrofuran ring motifs.

The breakthroughs in multi-layer convolutional neural networks (CNNs) have caused significant progress in the applications of image classification and recognition. The size of CNNs has continuously increased to improve their prediction capabilities on various applications, and it has become increasingly costly to perform the required computations. In particular, CNNs involve a large number of multiply-accumulate (MAC) operations, and it is important to minimize the cost of multiplication as it requires most computational resources.This dissertation proposes cost-efficient approximate log multipliers, optimized for performing CNN inferences. Approximate multipliers have reduced hardware costs compared to the conventional multipliers but produce products that are not exact. The proposed multipliers are based on Mitchell's Log Multiplication that converts multiplications to additions by taking approximate logarithm. Various design techniques are applied to Mitchell Log Multiplier, including fully-parallel LOD, efficient shift amount calculation, and exact zero computation. Additionally, the truncation of the operands is studied to create the customizable log multiplier that further reduces energy consumption. This dissertation also proposes using the one's complements to handle negative numbers to significantly reduce the associated costs while having minimal impact on CNN performances. The viability of the proposed designs is supported by the detailed formal analysis as well as the experimental results on CNNs. The proposed customizable design at w=8 saves up to 88% energy compared to the exact fixed-point multiplier at 32 bits with just a performance degradation of 0.2% on AlexNet for the ImageNet ILSVRC2012 dataset.The effects of approximate multiplication are analyzed when performing inferences on deep CNNs, to provide a deeper understanding of why CNN inferences are resilient against the errors in multiplication. The analysis identifies the critical factors in the

Perovskite solar cells have drawn much attention in recent years, owing to its world-record setting photovoltaic performances. Despite its promising use in tandem applications and flexible devices, its practicality is still limited by its structural instability often arising from ion migration and defect formation. While it is generally understood that ion instability is a primary cause for degradation, there is still a lack of direct evidence of structural transformation at the atomistic scale. Such an understanding is crucial to evaluate and pin-point how such instabilities are induced relative to external perturbations such as illumination or electrical bias with time, allowing researchers to devise effective strategies to mitigate them. Here, we designed an in-situ TEM setup to enable real-time observation of amorphization in double cation mixed perovskite materials under electrical biasing at 1 V. It is found that amorphization occurs along the (001) and (002) planes, which represents the observation of in-situ facet-dependent amorphization of a perovskite crystal. To reverse the degradation, the samples were heated at 50 oC and was found to recrystallize, effectively regaining its performance losses. This work is vital toward understanding fundamental ion-migration phenomena and address instability challenges of perovskite optoelectronics.

Introduction: A critical and as-yet unmet need in Alzheimer's disease (AD) is the discovery of peripheral small molecule biomarkers. Given that brain pathology precedes clinical symptom onset, we set out to test whether metabolites in blood associated with pathology as indexed by cerebrospinal fluid (CSF) AD biomarkers.Methods: This study analyzed 593 plasma samples selected from the European Medical Information Framework for Alzheimer's Disease Multimodal Biomarker Discovery study, of individuals who were cognitively healthy (n = 242), had mild cognitive impairment (n = 236), or had AD-type dementia (n = 115). Logistic regressions were carried out between plasma metabolites (n = 883) and CSF markers, magnetic resonance imaging, cognition, and clinical diagnosis.Results: Eight metabolites were associated with amyloid b and one with t-tau in CSF, these were primary fatty acid amides (PFAMs), lipokines, and amino acids. From these, PFAMs, glutamate, and aspartate also associated with hippocampal volume and memory.Discussion: PFAMs have been found increased and associated with amyloid b burden in CSF and clinical measures. Crown Copyright (C) 2019 Published by Elsevier Inc. on behalf of the Alzheimer's Association. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-ncnd/4.0/).

To initiate V(D)J recombination for generating the adaptive immune response of vertebrates, RAG1/2 recombinase cleaves DNA at a pair of recombination signal sequences, the 12- and 23-RSS. We have determined crystal and cryo-EM structures of RAG1/2 with DNA in the pre-reaction and hairpin-forming complexes up to 2.75 Å resolution. Both protein and DNA exhibit structural plasticity and undergo dramatic conformational changes. Coding-flank DNAs extensively rotate, shift, and deform for nicking and hairpin formation. Two intertwined RAG1 subunits crisscross four times between the asymmetric pair of severely bent 12/23-RSS DNAs. Location-sensitive bending of 60° and 150° in 12- and 23-RSS spacers, respectively, must occur for RAG1/2 to capture the nonamers and pair the heptamers for symmetric double-strand breakage. DNA pairing is thus sequence-context dependent and structure specific, which partly explains the "beyond 12/23" restriction. Finally, catalysis in crystallo reveals the process of DNA hairpin formation and its stabilization by interleaved base stacking.

The microbial metabolites known as the macrolides are some of the most successful natural products used to treat infectious and immune diseases. Describing the structures of these complex metabolites, however, is often extremely difficult due to the presence of multiple stereogenic centers inherent in this class of polyketide-derived metabolites. With the availability of genome sequence data and a better understanding of the molecular genetics of natural product biosynthesis, it is now possible to use bioinformatic approaches in tandem with spectroscopic tools to assign the full stereostructures of these complex metabolites. In our quest to discover and develop new agents for the treatment of cancer, we observed the production of a highly cytotoxic macrolide, neaumycin B, by a marine-derived actinomycete bacterium of the genus Micromonospora. Neaumycin B is a complex polycyclic macrolide possessing 19 asymmetric centers, usually requiring selective degradation, crystallization, derivatization, X-ray diffraction analysis, synthesis, or other time-consuming approaches to assign the complete stereostructure. As an alternative approach, we sequenced the genome of the producing strain and identified the neaumycin gene cluster ( neu). By integrating the known stereospecificities of biosynthetic enzymes with comprehensive NMR analysis, the full stereostructure of neaumycin B was confidently assigned. This approach exemplifies how mining gene cluster information while integrating NMR-based structure data can achieve rapid, efficient, and accurate stereostructural assignments for complex macrolides.

This paper develops robust testing procedures for nonparametric kernel methods in the presence of temporal dependence of unknown forms. Based on the fixed-bandwidth asymptotic variance and the pre-asymptotic variance, we propose a heteroskedasticity and autocorrelation robust (HAR) variance estimator that achieves double robustness --- it is asymptotically valid regardless of whether the temporal dependence is present or not, and whether the kernel smoothing bandwidth is held constant or allowed to decay with the sample size. Using the HAR variance estimator, we construct the studentized test statistic and examine its asymptotic properties under both the fixed-smoothing and increasing-smoothing asymptotics. The fixed-smoothing approximation and the associated convenient t-approximation achieve extra robustness --- it is asymptotically valid regardless of whether the truncation lag parameter governing the covariance weighting grows at the same rate as or a slower rate than the sample size. Finally, we suggest a simulation-based calibration approach to choose smoothing parameters that optimize testing oriented criteria. Simulation shows that the proposed procedures work very well in finite samples.

BackgroundTo correlate parameters of Ultrasonography-guided Diffuse optical tomography (US-DOT) with pharmacokinetic features of Dynamic contrast-enhanced (DCE)-MRI and pathologic markers of breast cancer.MethodsOur institutional review board approved this retrospective study and waived the requirement for informed consent. Thirty seven breast cancer patients received US-DOT and DCE-MRI with less than two weeks in between imaging sessions. The maximal total hemoglobin concentration (THC) measured by US-DOT was correlated with DCE-MRI pharmacokinetic parameters, which included K(trans), k ep and signal enhancement ratio (SER). These imaging parameters were also correlated with the pathologic biomarkers of breast cancer.ResultsThe parameters THC and SER showed marginal positive correlation (r = 0.303, p = 0.058). Tumors with high histological grade, negative ER, and higher Ki-67 expression ≥ 20% showed statistically higher THC values compared to their counterparts (p = 0.019, 0.041, and 0.023 respectively). Triple-negative (TN) breast cancers showed statistically higher K(trans) values than non-TN cancers (p = 0.048).ConclusionTHC obtained from US-DOT and K(trans) obtained from DCE-MRI were associated with biomarkers indicative of a higher aggressiveness in breast cancer. Although US-DOT and DCE-MRI both measured the vascular properties of breast cancer, parameters from the two imaging modalities showed a weak association presumably due to their different contrast mechanisms and depth sensitivities.

According to hedonic approaches to psychological health, healthy individuals should pursue pleasant and avoid unpleasant emotions. According to instrumental approaches, however, healthy individuals should pursue useful and avoid harmful emotions, whether pleasant or unpleasant. We sought to reconcile these approaches by distinguishing between preferences for emotions that are aggregated across contexts and preferences for emotions within specific contexts. Across five days, we assessed daily confrontational and collaborative demands and daily preferences for anger and happiness. Somewhat consistent with hedonic approaches, when averaging across contexts, psychologically healthier individuals wanted to feel less anger, but not more happiness. Somewhat consistent with instrumental approaches, when examined within contexts, psychologically healthier individuals wanted to feel angrier in more confrontational contexts, and some wanted to feel happier in more collaborative contexts. Thus, although healthier individuals are motivated to avoid unpleasant emotions over time, they are more motivated to experience them when they are potentially useful.

BACKGROUND: Receipt of nephrology care prior to end-stage renal disease (ESRD) is a strong predictor of decreased mortality and morbidity, and neighborhood poverty may influence access to care. Our objective was to examine whether neighborhood poverty is associated with lack of pre-ESRD care at dialysis facilities. METHODS: In a multi-level ecological study using geospatially linked 2007-2010 Dialysis Facility Report and 2006-2010 American Community Survey data, we examined whether high neighborhood poverty (≥20% of households in census tract living below poverty) was associated with dialysis facility-level lack of pre-ESRD care (percentage of patients with no nephrology care prior to dialysis start) in mixed-effects models, adjusting for facility and neighborhood confounders and allowing for neighborhood and regional random effects. RESULTS: Among the 5,184 facilities examined, 1,778 (34.3%) were located in a high-poverty area. Lack of pre-ESRD care was similar in poverty areas (30.8%) and other neighborhoods (29.6%). With adjustment, the absolute increase in percentage of patients at a facility with no pre-ESRD care associated with facility location in a poverty area versus other neighborhood was only 0.08% (95% CI -1.32, 1.47; p = 0.9). Potential effect modification by race and income inequality was detected. CONCLUSION: Despite previously reported detrimental effects of neighborhood poverty on health, facility neighborhood poverty was not associated with receipt of pre-ESRD care, suggesting no need to target interventions to increase access to pre-ESRD care at facilities in poorer geographic areas.

PurposeTo examine the prevalence of visual field deterioration in contralateral eyes of patients with worsening open-angle glaucoma and to evaluate the spatial concordance of visual field deterioration between both eyes.MethodsOne hundred sixteen open-angle glaucoma patients who underwent 8 or more visual field examinations over ≥ 6 years of follow-up were included. The rates of the fast and slow components of visual field decay for each of 52 visual field test locations were calculated with point-wise exponential regression analysis. The spatial concordance of visual field deterioration in contralateral eyes was evaluated with a concordance ratio (calculated as the number of overlapping locations divided by the total number of deteriorating locations) and by comparing the rate of decay in corresponding modified glaucoma hemifield test clusters.ResultsThe average visual field mean deviation (± standard deviation [SD]) was -8.5 (± 6.4) dB and the mean (± SD) follow-up time was 9.0 (± 1.6) years. Sixty-three patients had mild damage, 23 had moderate damage, and 30 had severe damage. The mean concordance ratio (± SD) was 0.46 (± 0.32) for the mild group, 0.33 (± 0.27) for the moderate group, and 0.35 (± 0.21) for the severe group. Thirty-one patients (27%) had deterioration in concordant locations (p < 0.05). Visual field deterioration was greater in the superior hemifield than the inferior hemifield (p < 0.05) when evaluated with both the concordance ratio and modified glaucoma hemifield test cluster analysis methods.ConclusionsThere is only fair spatial concordance with regard to visual field deterioration between the both eyes of an individual. We conclude that testing algorithms taking advantage of inter-eye spatial concordance would not be particularly advantageous in the early detection of glaucomatous deterioration.

Standard density functional approximations often give questionable results for odd-electron radical complexes, with the error typically attributed to self-interaction. In density corrected density functional theory (DC-DFT), certain classes of density functional theory calculations are significantly improved by using densities more accurate than the self-consistent densities. We discuss how to identify such cases, and how DC-DFT applies more generally. To illustrate, we calculate potential energy surfaces of HO·Cl(-) and HO·H2O complexes using various common approximate functionals, with and without this density correction. Commonly used approximations yield wrongly shaped surfaces and/or incorrect minima when calculated self consistently, while yielding almost identical shapes and minima when density corrected. This improvement is retained even in the presence of implicit solvent.

Doctor of Ministry (DMin)

Chromatin is a mixture of DNA and DNA binding proteins that control transcription. Dynamic chromatin structure modulates gene expression and is responsible for an extraordinary spectrum of developmental processes. An intricate interplay of DNA methylation, histone modifications, histone variants, small RNA accumulation, and ATPase chromatin remodelers defines chromatin re-configuration in a precise manner, locally within a cell and globally across different cell types. The development of high-throughput screening methods such as microarray and whole-genome sequencing has led to an explosion of chromatin studies in the past decade. Moreover, genetic and molecular studies resulted in identification of a number of proteins that may influence chromatin structure. However, the exact functions of individual proteins as well as their functional relationships to each other are less understood. Also, the role of chromatin components in establishing cell- and tissue-specific chromatin structure is largely unknown. To address these open questions in chromatin biology, I focused my dissertation work on 1) studying tissue-specific DNA demethylation in seed, and 2) determining the role of a ubiquitous DNA binding protein, linker histone H1, in regulating chromatin structure.Tissue specific DNA methylation in seed. In endosperm, the nutritive tissue that nourishes the embryo, parent-of-origin specific gene expression is regulated by DNA demethylation. However, the extent to which DNA demethylation occurs in a tissue-specific manner and regulates transcription in the endosperm of crop plants like rice remains unknown. To address these questions, my colleagues and I examined the DNA methylation patterns of two rice seed tissues, embryo and endosperm. We found that endosperm genome is globally hypomethylated at non-CG sites and locally hypomethylated at CG-sites compared to embryo. We also identified that small transposons near genes (euchromatic regions) are the primary targets of D

We decompose the energy error of any variational density functional theory calculation into a contribution due to the approximate functional and that due to the approximate density. Typically, the functional error dominates, but in many interesting situations the density-driven error dominates. Examples range from calculations of electron affinities to preferred geometries of ions and radicals in solution. In these abnormal cases, the error in density functional theory can be greatly reduced by using a more accurate density. A small orbital gap often indicates a substantial density-driven error.

Chapter 1 is "Heteroskedasticity and Spatiotemporal Dependence Robust Inference for Linear Panel Models with Fixed Effects." This chapter studies robust inference for linear panel models with fixed effects in the presence of heteroskedasticity and spatiotemporal dependence of unknown forms. We propose a bivariate kernel covariance estimator, which is flexible to nest existing estimators as special cases with certain choices of bandwidths. For distributional approximations, we consider two different types of asymptotics. When the level of smoothing is assumed to increase with the sample size, the proposed estimator is consistent and the associated Wald statistic converges to a chi square distribution. We show that our covariance estimator improves upon existing estimators in terms of robustness and efficiency. When we assume the level of smoothing to be held fixed, the covariance estimator has a random limit and we show by asymptotic expansion that the limiting distribution of the test statistic depends on the bandwidth parameters, the kernel function, and the number of restrictions being tested. As this distribution is nonstandard, we establish the validity of an F-approximation to this distribution, which greatly facilitates the test. For optimal bandwidth selection, we propose a procedure based on the upper bound of asymptotic mean square error criterion. The flexibility of our estimator and proposed bandwidth selection procedure make our estimator adaptive to the dependence structure in data. This adaptiveness automates the selection of covariance estimator. That is, our estimator reduces to the existing estimators which are designed to cope with the particular dependence structures. Simulation results show that the F-approximation and the adaptiveness work reasonably well. Chapter 2 is "Spatial Heteroskedasticity and Autocorrelation Consistent Estimation of Covariance Matrix". This chapter considers spatial heteroskedasticity and autocorrelation consistent (spat