Context-based Normalization of Histological Stains using Deep Convolutional Features

While human observers are able to cope with variations in color and appearance of histological stains, digital pathology algorithms commonly require a well-normalized setting to achieve peak performance, especially when a limited amount of labeled data is available. This work provides a fully automated, end-to-end learning-based setup for normalizing histological stains, which considers the texture context of the tissue. We introduce Feature Aware Normalization, which extends the framework of batch normalization in combination with gating elements from Long Short-Term Memory units for normalization among different spatial regions of interest. By incorporating a pretrained deep neural network as a feature extractor steering a pixelwise processing pipeline, we achieve excellent normalization results and ensure a consistent representation of color and texture. The evaluation comprises a comparison of color histogram deviations, structural similarity and measures the color volume obtained by the different methods.Comment: In: 3rd Workshop on Deep Learning in Medical Image Analysis (DLMIA 2017

Benchmarking in cluster analysis: A white paper

To achieve scientific progress in terms of building a cumulative body of knowledge, careful attention to benchmarking is of the utmost importance. This means that proposals of new methods of data pre-processing, new data-analytic techniques, and new methods of output post-processing, should be extensively and carefully compared with existing alternatives, and that existing methods should be subjected to neutral comparison studies. To date, benchmarking and recommendations for benchmarking have been frequently seen in the context of supervised learning. Unfortunately, there has been a dearth of guidelines for benchmarking in an unsupervised setting, with the area of clustering as an important subdomain. To address this problem, discussion is given to the theoretical conceptual underpinnings of benchmarking in the field of cluster analysis by means of simulated as well as empirical data. Subsequently, the practicalities of how to address benchmarking questions in clustering are dealt with, and foundational recommendations are made

Transarticular screw fixation for osteoarthritis of the atlanto axial segment

Atlantoaxial (C1-C2) facet joint osteoarthitis is a distinct clinical syndrome that often goes unrecognized. Severe pain resistant to conservative treatment that is corroborated by the radiographic findings represents the indication for surgery. The aim of this study was to retrospectively examine the long-term outcome [after an average 6.5years (SD 4.0)] of C1-2 fusion for osteoarthritis of the atlantoaxial segment in 35 consecutive patients [25 male, 10 female; aged 62 (SD 15)years]. At follow-up, clinical outcome and radiological status was examined in 27/35 (77%) patients, and self-rated pain and disability (Neck Pain and Disability Scale; NPDS) in 29/35 (83%) patients. In 27/35 patients (77%), 2 screws were inserted; in 7 patients (20%), only 1 screw; and in 1 patient (3%), no screws. 11% of the patients had late complications requiring revision surgery. All patients showed solid fusion at the long-term follow-up. 26% patients showed an improvement in sensory disturbances, 63% no change, and 11% a worsening. 89% were pain-free or had markedly reduced pain. The average score on the NPDS (0-100) was 34 (SD 27), representing ‘mild' neck problems, and the average pain intensity (0-5 VAS) was 1.5 (SD 1.5). Eighty-five percent of the patients declared that they would make the same decision again to undergo surgery. In conclusion, in a group of patients with a painful and debilitating degenerative disorder of C1-2, posterior transarticular atlantoaxial fusion proved to be an effective treatment with a low rate of serious complication

Ribosome specificity of archaebacterial elongation factor 2 Studies with hybrid polyphenylalanine synthesis systems

AbstractPolyphenylalanine synthesis with ribosomes and two separated, partially purified elongation factors (EF) was measured in cell-free systems from the archaebacteria Thermoplasma acidophilum and Methanococcus vannielii, in an eukaryotic system from rat liver and an eubacterial one with Escherichia coli ribosomes and factors from Thermus thermophilus. By substitution of heterologous EF-2 or EF-G, respectively, for the homologous factors, ribosome specificity was shown to be restricted to factors from the same kingdom. In contrast EF-1 from T. thermophilus significantly cooperated with ribosomes from T. acidophilum

The Impact of Additive Manufacturing on Supply Chains and Business Models: Qualitative Analyses of Supply Chain Design, Governance Structure, and Business Model Change

Recent global crises like the COVID-19 pandemic challenge traditional global supply chains (SCs). Their disaggregated, “fine-sliced” character comes with a high risk of disruption, and current supply bottlenecks (e.g., the chip shortage in the automotive industry) demonstrate that there is often no quick fix. Firms are increasingly under pressure to react and (re-)design their SCs to increase their resilience. Additive manufacturing (AM) technologies are acclaimed for their potential to foster the shift from global SCs to shorter, decentralized, and more resilient SCs. The key feature of AM technologies lies in their inherently digital and flexible nature. Their specific characteristics are envisioned to enable location-independent manufacturing close to or even at the point of demand and lead to a commoditization of manufacturing infrastructure for flexible outsourcing to local partners. Moreover, AM technologies are expected to revolutionize the way firms do business and put traditional business models at stake. This doctoral thesis is motivated by the outlined potential of AM and the resulting impact on firms’ supply chain design (SCD) and business model choices. The extant literature raises high expectations for AM. However, concrete and real-world insights from specific application domains are still scarce. This thesis seeks to fill the gap between high-level literature-based visions and currently emerging realistic business models and SCDs for AM. Thereby, AM is understood as a potential intervention emanating from outside firms and requiring them to react by realigning their business models and SC structures to maintain a fit. This thesis aims to build an in-depth understanding of these mechanisms and, hence, of the inner causal processes involved in the AM SCD and business model choices. This concentration on the rationales and underlying behavioral patterns is formalized with primarily exploratory (how and why) research questions that are addressed with qualitative research methodologies, mainly case study research and grounded theory. These methodological practices are applied in the industrial AM context, entailing an embedding of this thesis in challenging industries where AM applications have already started to create value (i.e., in the aerospace, rail, automotive, and machinery and equipment industries). The selected research approaches are mostly inductive and, hence, strongly driven by the data collected from this context (e.g., in interviews, by reviewing documents, and by analyzing websites). Additionally, this thesis relies on grand theories, namely transaction cost economics, the resource-based view, and configuration theory, to discuss the findings in their light and to interpret and distill nuances of these theories for their application in the industrial AM context. This thesis is cumulative, consisting of four studies that form its main body. These studies are organized in two parts, part A and part B, since two domains of strategic decisions are targeted jointly, the business model development (part A) and AM SCD choice (part B) for industrial AM. Different perspectives are associated with the two parts. Logistics service providers (LSPs) are in a critical position to develop AM business models. Based on the expected shift to decentralized, shorter SCs, the traditional business models of LSPs are at risk, and their inherent customer orientation puts them under pressure to adjust to their customers’ needs in AM. In part A, study A.1 applies a process-based perspective to build a broad understanding of how LSPs currently respond to AM and consumer-oriented polymer 3D printing with specific AM activities. It proposes six profiles of how LSPs leverage AM, both as users for their in-house operations and as developers of AM-specific services for external customers. A key finding is that the initiated AM activities are oftentimes strongly based on LSPs’ traditional resources. Only a few LSPs are found whose AM activities are detached from their traditional business models to focus on digital platform-based services for AM. In contrast to the process-based perspective and focus on business model dynamics in study A.1, study A.2 takes an output perspective to propose six generic business model configurations for industrial AM. Each configuration emerges from the perspective of LSPs and is reflected by their potential partners/competitors and industrial customers. Study A.2 explores how the six generic configurations fit specific types of LSPs and how they are embedded in a literature-based service SC for industrial AM. In combination, studies A.1 and A.2 provide a comprehensive understanding of how LSPs are currently reacting to AM and an empirically grounded perspective on “finished” AM business models to evaluate and refine literature-based visions. Part B of this thesis is devoted to the mechanism of (re-)designing SCs for AM, which is investigated from the perspective of focal manufacturing firms based on their dominant position in SCs. Two dimensions are used to characterize AM SCDs, their horizontal scope (geographic dispersion) and vertical scope (governance structure). The combination of both dimensions is ideally suited to capture the literature-based vision of shorter, decentralized AM SCs (horizontal scope) with eased outsourcing to local partners (vertical scope). Study B.1 takes a firm-centric perspective to develop an in-depth understanding for AM make-or-buy decisions of manufacturing firms, the outcomes of which determine the SC governance structure. This study elaborates how the specific (digital and emerging) traits of industrial AM technologies modify arguments of grand theories that explain make-or-buy decisions in the “analog” age. In comparison, study B.2 shifts from a firm-centric to a network perspective to rely on both dimensions for investigating cohesive AM SCD configurations. More specifically, study B.2 explores four polar AM SCD configurations and reveals manufacturing firms’ rationales for selecting them. Thereby, it builds an understanding for why manufacturing firms currently have valid reasons to implement industrial AM in-house or distributed in a secure, firm-owned network. As a result, combining both studies provides an understanding of why manufacturing firms currently select specific governance structures for industrial AM and opt for SCDs that differ from the literature-based vision of decentralized, outsourced AM. Overall, this thesis positions itself as theory-oriented research that also aims at supporting managers of manufacturing firms and LSPs in making informed decisions when implementing AM in their SCs and developing AM-based business models. The three studies A.1, A.2, and B.2 contribute to initial theory building on how and why specific AM business models and SCDs emerge. With their focus on developing an understanding for the causal processes (how and why) and by assuming a process-based and output perspective, they can draw a line from firms’ current reactions to sound reflections on future-oriented, high-level expectations for AM. As a result, the studies significantly enrich and refine the current body of knowledge in the AM business model literature on LSPs and the operations and supply chain management literature on AM SCDs, focusing on their geographic dispersion and governance structure. This thesis further contributes with its context-specificity to building domain knowledge for industrial AM, which can serve as one “puzzle piece” for theorizing on how AM and other digitally dominated (manufacturing) technologies will shape the era of digital business models and SCs. In particular, study B.1 stands out by its focus on theory elaboration and the objective of developing contextual middle-range theory. It reveals that emerging digital AM is a setting where the argumentation of grand theories provides contradicting guidance on whether to develop AM in-house or outsource the manufacturing process. Such findings for industrial AM raise multiple opportunities for future research, among them are the comparison with other industry contexts with similar characteristics and the operationalization of the propositions developed in this thesis in follow-up quantitative decision-support models

Make‐or‐buy decisions for industrial additive manufacturing

Much of the potential of industrial additive manufacturing (AM) is said to lie in the digital specification of components that can be transmitted seamlessly and unambiguously to partners fostering flexible outsourcing. In industry, we observe nuanced AM supply chain governance structures that result from make‐or‐buy decisions, with a tendency to implement AM in‐house. Thus, there is a discrepancy between what is discussed in the literature and implemented in practice. We apply a multiple‐case study approach to investigate why and how AM impacts the make‐or‐buy decision of manufacturing firms. We identify four decision profiles demonstrating the spectrum of specific governance structures and develop a framework to explain the underlying rationales. We find strong arguments for in‐house AM including firms’ perceived need to protect their digitally encapsulated intellectual property, reevaluation of their core competencies, commitment to internal learning, and senior management's enthusiasm for AM. By using transaction cost economics and the resource‐based view, we contribute to the understanding of how arguments of these general theories are modified by the digital and emerging traits of AM. We reveal contradicting guidance in the theories’ argumentation for the case of AM and provide managers a clear perspective on alternative strategies for their AM implementation process

Rapid testing leads to the underestimation of the scrapie prevalence in an affected sheep and goat flock

To obtain a more detailed understanding of the prevalence of classical scrapie infections in a heavily affected German sheep flock (composed of 603 sheep and 6 goats), we analysed 169 sheep and 6 goats that carried the genotypes susceptible to the disease and that were therefore culled following discovery of the index case. The initial tests were performed using the Biorad TeSeE ELISA and reactive results were verified by official confirmatory methods (OIE-immunoblot and/or immunohistochemistry (IHC)) to demonstrate the deposition of scrapie-associated PrPSc in the brain stem (obex). This approach led to the discovery of 40 additional subclinically scrapie-infected sheep. Furthermore, peripheral lymphatic and nervous tissue samples of the 129 sheep and 6 goats with a negative CNS result were examined by IHC in order to identify any preclinical infections which had not already spread to the central nervous system (CNS). Using this approach we found 13 additional sheep with PrPSc depositions in the gut-associated lymph nodes (GALT) as well as in the enteric nervous system. Moreover, in most of these cases PrPSc was also deposited in the spleen and in the retropharyngeal and superficial cervical lymph nodes. Taken together, these results show a 30.3% infection prevalence in this scrapie-affected flock. Almost 7.4% of the infected animals harboured PrPSc exclusively in the peripheral lymphatic and nervous tissue and were therefore missed by the currently used testing strategy

Growth cone response to ephrin gradients produced by microfluidic networks

A microfluidic network (μFN) etched into a silicon wafer was used to deliver protein solutions containing different concentrations of the axonal guidance molecule ephrinA5 onto a silicone stamp. In a subsequent microcontact printing (μCP) step, the protein was transferred onto a polystyrene culture dish. In this way, stepwise substrate-bound concentration gradients of ephrinA5 were fabricated spanning a total distance of 320 μm. We tested the response of chick retinal ganglion cell (RGC) axons, which are guided in vivo by ephrin gradients, to these in vitro gradients. Temporal, but not nasal axons stop at a distinct zone in the gradient, which is covered with a certain surface density of substrate-bound ephrinA5. Within the temporal RGC population, all axons respond uniformly to the gradients tested. The position of the stop zone depends on the slope of the gradient with axons growing further into the gradient in shallow gradients than in steep gradients. However, axons stop at lower ephrinA5 concentrations in shallow gradients than in steep gradients, indicating that the growth cone can adjust its sensitivity during the detection of a concentration gradient of ephrinA5