Research on the firm's heterogeneity is a well-developed concept in the export context; literature can found in the export context. Previous research can found on firm heterogeneity and firm performance, but they are in export context. On the other hand, importing firms' heterogeneity is less sought in the literature, which we believe as a clear gap in the export-import research stream. Limited research has done in the context of importing firms. The purpose of our thesis is to explore the different forms of heterogeneities that Pakistani importing firms' practices are gaining a competitive advantage. Furthermore, our goal is to examine the extent of heterogeneity dimensions to what contributes to their performances. There is a significant gap in the research field of import. As there is less research in the import context, this will be a fundamental goal of research towards firms' heterogeneity and the importance of a country.

abstract: In recent years, the rise in social media usage both vertically in terms of the number of users by platform and horizontally in terms of the number of platforms per user has led to data explosion. User-generated social media content provides an excellent opportunity to mine data of interest and to build resourceful applications. The rise in the number of healthcare-related social media platforms and the volume of healthcare knowledge available online in the last decade has resulted in increased social media usage for personal healthcare. In the United States, nearly ninety percent of adults, in the age group 50-75, have used social media to seek and share health information. Motivated by the growth of social media usage, this thesis focuses on healthcare-related applications, study various challenges posed by social media data, and address them through novel and effective machine learning algorithms. The major challenges for effectively and efficiently mining social media data to build functional applications include: (1) Data reliability and acceptance: most social media data (especially in the context of healthcare-related social media) is not regulated and little has been studied on the benefits of healthcare-specific social media; (2) Data heterogeneity: social media data is generated by users with both demographic and geographic diversity; (3) Model transparency and trustworthiness: most existing machine learning models for addressing heterogeneity are considered as black box models, not many providing explanations for why they do what they do to trust them. In response to these challenges, three main research directions have been investigated in this thesis: (1) Analyzing social media influence on healthcare: to study the real world impact of social media as a source to offer or seek support for patients with chronic health conditions; (2) Learning from task heterogeneity: to propose various models and algorithms that are adaptable to new social media platforms and robust to dynamic social media data, specifically on modeling user behaviors, identifying similar actors across platforms, and adapting black box models to a specific learning scenario; (3) Explaining heterogeneous models: to interpret predictive models in the presence of task heterogeneity. In this thesis, novel algorithms with theoretical analysis from various aspects (e.g., time complexity, convergence properties) have been proposed. The effectiveness and efficiency of the proposed algorithms is demonstrated by comparison with state-of-the-art methods and relevant case studies. / Dissertation/Thesis / Doctoral Dissertation Computer Science 2019

Doctor of Philosophy / Department of Biology / Brett K. Sandercock / Habitat heterogeneity is a key driver of biodiversity in many ecosystems. In native ecosystems, habitat heterogeneity can arise from multiple drivers including nutrients, topoedaphic conditions, and ecological disturbance. Historically, the prairies of North America existed as a heterogeneous mosaic of habitat conditions created by the interaction of fire and grazing by native ungulates. The focus of many grazing systems has been to minimize disturbance caused by grazing by promoting uniform distributions of grazing animals across management units. Patch-burn grazing is an alternative rangeland management practice that has been proposed to restore historical patch dynamics and biodiversity to rangelands by simulating historical disturbance processes. In my dissertation research, I tested the hypothesis that patch- burn grazing restores habitat heterogeneity to rangelands, and that the resulting habitat heterogeneity can promote biodiversity of native wildlife. I focus on responses of small mammals and coyotes to patch-burn grazing to gain a better understanding of wildlife responses to rangeland management, and because grassland mammals are an ecologically important group. My 3.5-year field study of habitat and small mammal responses to rangeland management showed that: 1) patch-burn grazing created greater heterogeneity in vegetative structure and composition of plant functional groups than in positive and negative controls; 2) habitat heterogeneity created by the interaction of fire and grazing increased small mammal richness and diversity compared to a negative control managed for uniform grazing distributions; 3) the interaction of fire and grazing structured small mammal communities in tallgrass prairie; and 4) population dynamic responses of small mammals to fire and grazing disturbance were species- specific. My 3-year study of coyote survival and resource selection revealed that: 1) rangeland management influences resource selection by coyotes in seasons when they depend on small mammal prey, but not during other seasons; and 2) anthropogenic sources of mortality are important for coyotes at a protected area, even in the absence of harvest. My field results show that restoring the drivers of historical patch dynamics to managed rangelands and publicly held grasslands that are not currently grazed could have profound effects on biodiversity conservation in North America, while continuing to provide ecosystem services to society.

The increasing involvement of individuals in social media over the past decade has enabled firms to pursue new avenues in communication and sponsoring activities. Besides general research on either social media or sponsoring, questions regarding the consequences of a joint activity (sponsoring activities in social media) remain unexplored. Hence, the present study analyses whether the perceived image of the brand and the celebrity endorser credibility of a top sports team influence the perceived brand value of the sponsoring firm in a social media setting. Moreover, these effects are compared between existing customers and non-customers of the sponsoring firm. Interestingly, perceived celebrity endorser credibility plays no role in forming brand value perceptions in the case of the existing customers. Implications for marketing theory and practice are derived. (authors' abstract)

Cell-to-cell variation in expression of pluripotency- and lineage-determining factors has been proposed to be integral to the process of cell fate commitment in pluripotent cells both in vitro and in vivo. Understanding the sources of this heterogeneity in pluripotent stem cells promises greater insight into the mechanisms underlying cell fate choice. I identify mitochondrial membrane potential as an axis of heterogeneity in mouse embryonic stem cell populations, and show that high mitochondrial membrane potential marks cells that are in a stable self-renewing state. Partial overlap with previously described metastable subpopulations is demonstrated through gene expression analysis. I present evidence that similarly to previous findings in HeLa, heterogeneity in mitochondrial membrane potential is associated with variation in global transcription rate in mESCs. The direct impact of global transcription rate on differentiation propensity is demonstrated through manipulation of RNA Pol II transcription elongation rate. Mitochondrial variability is therefore likely a functionally relevant source of extrinsic gene expression variability in mouse embryonic stem cells.

Characterization of heterogeneous soil hydraulic parameters of deep vadose zones is often difficult and expensive, making it necessary to rely on other sources of information. Pedotransfer functions (PTFs) based on soil texture data constitute a simple alternative to inverse hydraulic parameter estimation, but their accuracy is often modest. Inverse modeling entails a compromise between detailed description of subsurface heterogeneity and the need to restrict the number of parameters. We propose two methods of parameterizing vadose zone hydraulic properties using a combination of k-means clustering of kriged soil texture data, PTFs, and model inversion. One approach entails homogeneous and the other heterogeneous clusters. Clusters may include subdomains of the computational grid that need not be contiguous in space. The first approach homogenizes within-cluster variability into initial hydraulic parameter estimates that are subsequently optimized by inversion. The second approach maintains heterogeneity through multiplication of each spatially varying initial hydraulic parameter by a scale factor, estimated a posteriori through inversion. This allows preserving heterogeneity without introducing a large number of adjustable parameters. We use each approach to simulate a 95 day infiltration experiment in unsaturated layered sediments at a semiarid site near Phoenix, Arizona, over an area of 50 x 50 m(2) down to a depth of 14.5 m. Results show that both clustering approaches improve simulated moisture contents considerably in comparison to those based solely on PTF estimates. Our calibrated models are validated against data from a subsequent 295 day infiltration experiment at the site.

Numerical experiments assuming land-use distributions of different heterogeneity of wet and dry surfaces were performed on a cloudy day in spring with a calm wind to examine their influences on the domain-averaged fluxes as well as on the distribution of the fluxes within the domain. The results substantiate that, for ]arge heterogeneity, i.e., small patches, the distribution of the patches plays no role in the magnitude of the atmospheric fluxes. For !arger patches, however, the domain-averaged latent heat-fluxes depend appreciably on both the heterogeneity as well as on the fractional coverage by the land-use types. On the average, for heterogeneous conditions, the prevailing land-use type governs the fluxes. Nevertheless, no exact linearity between the fractionally coverage of the two land-use types and the resulting fluxes exists. Discontinuities in the fluxes which lead to the non-linear behaviour of the domain-averaged fluxes occur at the border between two !arger areas of extremely different characteristics, namely, grass (wet, cool) and sand (dry, warm). Three different patterns of behaviour are found for the temporal development of the differences in the domain-averaged fluxes which depend on both the heterogeneity and the pattern of the land use. / Numerische Experimente, bei denen unterschiedlich heterogene Landnutzungsverteilungen trockener und feuchte Flächen angenommen werden, wurden für einen wolkigen Schwachwindtag im Frühjahr durchgeführt. Die Ergebnisse belegen, daß bei großer Heterogenität, d.h. kleinen Flächen, deren Anordnung keine Rolle spielt. Bei großen Flächen jedoch hängen die Gebietsmittelwerte der latenten Wärmeflüsse merklich sowohl von der Heterogenität als auch von dem Flächenanteil der Landnutzung ab. Im Mittel beherrscht der vorherrschende Landnutzungstyp die Flüsse. Dennoch ist kein exaktes lineares Verhalten zwischen dem Flächenanteil der Landnutzung und den resultierenden Flüssen vorhanden. Diskontinuitäten in der Verteilung der Flüsse, die letztendlich zu der Nichtlinearität der Gebietsmittelwerte der Flüsse führen, treten an den Grenzen der größeren Flächen unterschiedlicher Oberflächencharakteristika auf, in dieser Studie Gras (feucht, kühl) und Sand (trocken, warm). Drei unterschiedliche Verhaltensweisen im zeitlichen Verlauf der Differenzen der Gebietsmittelwerte der Flüsse wurden gefunden, die vom Muster und der Heterogenität der Landnutzung abhängen.

Single enzymes of E. coli sourced B-galactosidase were analysed in effort to expand the wealth of knowledge in the area of heterogeneity. Static and dynamic heterogeneity was studied with respect to catalytic rate, electrophoretic mobility, and heat shock protein chaperone systems. Temperature was found to be a contributing factor to the observed range of dynamic heterogeneity, with the range increasing with temperature. The inhibitor dissociation constant was determined to be a heterogeneous property of B-galactosidase. A novel assay was developed in which a single enzyme molecule was subjected to three separate solutions while the enzyme itself remained free in solution. / October 2016

Using a sample of 51 banking organizations, I examine the effect of the Statement of Financial Accounting Standard 133 on the belief heterogeneity of market participants and how this heterogeneity affects abnormal trading volume surrounding earnings announcements. SFAS 133 is the first standard to require that all derivatives be recognized at fair-value and that the fluctuations in derivative fair-values be reported in either net income or other comprehensive income. The behavior of derivative instruments and the fair-valuation and treatment prescribed by SFAS 133 are complex. Due to the underlying complexity of both derivatives and the accounting treatment prescribed by the SFAS 133 standard, I expect that investors may have differing interpretations of the newly provided information. My hypothesis is that the income effects arising from the fair-value accounting for derivatives (SFAS 133) are associated with an increase in differing beliefs among individuals. I find that the income effects of SFAS 133 are significantly and positively related to belief heterogeneity among investors. The net income and other comprehensive income effects of SFAS 133 are significantly and positively related to increasing levels of abnormal trading volume surrounding earnings announcements. Additionally, levels of SFAS 133 net income is positively and significantly associated with three measures of belief heterogeneity derived from analysts’ forecasts. In an extended analysis I model the SFAS 133 income effects on abnormal volume using the three belief heterogeneity measures as the conduit. I find support for two of the three heterogeneity measures acting as a conduit for the effect of the SFAS 133 related income measures on abnormal volume. The results of this study indicate that, while the recognized fair-value of derivatives is value relevant to equity prices (Ahmed, Kilic, & Lobo, 2006), the income effects of the same financial standard causes heterogeneity in beliefs about the firm. This suggests that, at least in the case of derivative fair-values, there exists a trade-off between value relevance and the strength of consensus surrounding beliefs in the market.

It is not known whether pancreatic cancers evolve from a single or multiple cells, or from a particular pancreatic lineage. However, in the Pdx1-Cre; LSL-KrasG12D; LSLTp53R172H mouse model of pancreatic cancer, all pancreatic lineages are susceptible to express mutant KRas and p53. Hence, such mouse model implies a scenario of maximal heterogeneity of cancer cell origins. On this basis, I isolated seven subclones of heterogeneous mouse pancreatic cancer cells from a single tumour; each of them had a distinct morphology and gene expression profile. Notably, they possessed different intrinsic phospho-SMADs downstream of the TGFβ receptor (phospho-SMAD2/3) or the BMP receptor (Phospho-SMAD1/5/8). I discovered that SMAD4, a co-SMAD which is frequently found to be lost in pancreatic caner tissues, upregulated HNF4α via the classical BMP-SMAD1 pathway, when cells were experiencing metabolic stress upon deprivation of serum, or in the presence of excess thymidine. Under serum starvation at a hypoglycemic-like glucose concentration, the HNF4α-expressing sub-clones appeared to be more able to sustain an unstressed morphology than other non-HNF4α-expressing sub-clones. Immunohistochemical staining on pancreatic cancer sections revealed nuclear co-localization of SMAD4 and HNF4α in human (half of the cases) and in mouse samples. As a secondary project conducted during characterization of cells, I also found that three of the subclones more robustly proliferated under anchorage independent conditions, and they relied on the MEK-ERK pathway and the canonical Wnt pathway, to a different degree. Both studies demonstrate for the first time in primary cell culture that pancreatic cancer cells within a tumour could be highly heterogeneous in terms of both morphology and signaling pathways.