Educating Reflective Practitioners: The Design of an IT Management Masters Program

The IT Management Group at Umeå University, Sweden, has developed a master program in IT management with emphasison incorporating practice in the learning process. The basic premise lies in the use of reflection-in-action as an approach topresenting students with practical problems throughout the program. We discuss the ways in which practice is at the heart ofthe program, both as a tool for exemplifying codified knowledge such as technical skills and methods but also as arenas forsituated knowledge creation and transfer where reflection and action are intertwined. The paper ends with a discussion of theprogram design, challenges in implementing the reflective practice approach and competencies the students need in theirfuture professional roles

Orchestrating Digital Innovation: The Case of the Swedish Center for Digital Innovation

In recent years, researchers have paid increasing attention to how firms facilitate and enact digital innovation in networks with diverse actors (i.e., heterogeneous networks). However, while considerable evidence shows that firms can build key capabilities via engaging with external partners, we found few studies on how they orchestrate digital innovation in situations where an academic unit plays a facilitating role in the heterogeneous network. We address this question by focusing on experiences from a national academic initiative, the Swedish Center for Digital Innovation (SCDI). Formed in 2013, the SCDI has adopted an engaged scholarship approach and a combination of activities designed to increase digital innovation capabilities among partner organizations. We argue that acquiring new knowledge through external and internal sources stimulates firms and public sector organizations engaged in digital innovation to integrate such new knowledge with their existing knowledge base. Specifically, we demonstrate how SCDI’s core activities have created increased capabilities for the involved stakeholders, and we offer lessons learned and recommendations for academic units that wish to orchestrate digital innovation

Precision thinning - a comparison of optimal stand-level and pixel-level thinning

Precision forestry allows decision-making on tree level or pixel level, as compared to stand-level data. However, little is known about the importance of precision in thinning decisions and its long-term effects on within-stand variation, stand economy and growth. In this study, silviculture was optimized for Net Present Value (NPV) in 20 conifer-dominated forest stands in hemi-boreal southern Sweden. The precision-thinning approach, Precision Thinning (PT), is compared with a stand-level approach, Stand Level Thinning (SLT) that is optimized for the same criteria but based on stand-level data. The results suggest no substantial long-term benefit or drawback in implementing thinning decisions based on pixel-level data as compared to stand-level data when optimizing stand economy. The result variables NPV and Mean annual increment of living stem volume (MAI(net)) were not higher for PT than for SLT. The within-stand variation in basal area (m(2)/ha(-1)) was lower at the end of the rotation compared to the start of the simulation for both SLT and PT. At the end of the rotation, SLT had higher variation in basal area compared to PT. However, pixel-level information enables adapting the silviculture to the within-stand variation which may favour other forest management goals than strictly financial goals

PDE-Foam - a probability-density estimation method using self-adapting phase-space binning

Probability Density Estimation (PDE) is a multivariate discrimination technique based on sampling signal and background densities defined by event samples from data or Monte-Carlo (MC) simulations in a multi-dimensional phase space. In this paper, we present a modification of the PDE method that uses a self-adapting binning method to divide the multi-dimensional phase space in a finite number of hyper-rectangles (cells). The binning algorithm adjusts the size and position of a predefined number of cells inside the multi-dimensional phase space, minimising the variance of the signal and background densities inside the cells. The implementation of the binning algorithm PDE-Foam is based on the MC event-generation package Foam. We present performance results for representative examples (toy models) and discuss the dependence of the obtained results on the choice of parameters. The new PDE-Foam shows improved classification capability for small training samples and reduced classification time compared to the original PDE method based on range searching.Comment: 19 pages, 11 figures; replaced with revised version accepted for publication in NIM A and corrected typos in description of Fig. 7 and

Broadleaf retention benefits to bird diversity in mid-rotation conifer production stands

Retention forestry involves saving important forest structures for flora and fauna during the final felling of a stand, including dead wood and variable amounts of living trees, i.e. green tree retention (GTR). Here we evaluate the long-term effects on avian diversity from GTR by surveying forest birds in 32 mid-rotation stands in southern Sweden, in which broadleaf GTR was present or absent. Complementing the many studies that have assessed GTR in clear-cuts, our results indicated that bird assemblages can also benefit from broadleaf GTR several decades after final felling in conifer dominated production stands. The GTR stands harboured a higher bird abundance and species richness than the control stands without GTR, and also appears to have benefited several important guilds, such as broadleaf-associated birds and cavity nesters. However, variation in the number trees retained, the species composition of retained trees, and their environmental context within the stand (e.g. density and proximity of surrounding production trees), limited our capacity to detect threshold requirements for GTR. In summary, our study provides a "glimpse into the future" as mid-rotation production stands with such old and large retained trees are unusual in today's landscape, but are expected to become more common in the decades to come, in Sweden and many other nations. Our study thereby provides provisional support for the continued and future use of this practice, and indicates that the biodiversity contribution of retention trees continues to occur several decades into the stand's rotation

Costs and benefits of seven alternatives for riparian forest buffer management

Stand development in riparian forest buffers was simulated for three forest landscapes in Sweden, using data taken from a sample plot inventory along 38 streams. The objectives were: to quantify the effects on wood production and the economy of management alternatives for buffers; and to evaluate the development of important stand structures for buffer functionality. Buffer widths from 0 to 30 m were analyzed with unmanaged or selective logging as alternatives. Leaving unmanaged buffers resulted in the cost being generally proportional to the area of productive forest land covered by buffers in the landscape. The cost for the widest buffer alternative, 30 m, when left unmanaged, was between 4 and 10% of the total net present value of the entire forest landscape. Allowing selective logging to promote broadleaved trees in the buffer reduced the costs to 1-3% of the net present value. Selective logging increased the volume share of broadleaved trees in the buffer, thus enhancing some of its ecological functions. Unmanaged buffers increased the amount of dead wood more than the alternatives with selective logging. Decisions about buffer zone management must consider the trade-off between economic and environmental benefits, as well as the trade-offs between contrasting environmental goals

Detection of breast cancer lymph node metastases in frozen sections with a point-of care low-cost microscope scanner

Background Detection of lymph node metastases is essential in breast cancer diagnostics and staging, affecting treatment and prognosis. lntraoperative microscopy analysis of sentinel lymph node frozen sections is standard for detection of axillary metastases but requires access to a pathologist for sample analysis. Remote analysis of digitized samples is an alternative solution but is limited by the requirement for high-end slide scanning equipment. Objective To determine whether the image quality achievable with a low-cost, miniature digital microscope scanner is sufficient for detection of metastases in breast cancer lymph node frozen sections. Methods Lymph node frozen sections from 79 breast cancer patients were digitized using a prototype miniature microscope scanner and a high-end slide scanner. Images were independently reviewed by two pathologists and results compared between devices with conventional light microscopy analysis as ground truth. Results Detection of metastases in the images acquired with the miniature scanner yielded an overall sensitivity of 91% and specificity of 99% and showed strong agreement when compared to light microscopy (k = 0.91). Strong agreement was also observed when results were compared to results from the high-end slide scanner (k = 0.94). A majority of discrepant cases were micrometastases and sections of which no anticytokeratin staining was available. Conclusion Accuracy of detection of metastatic cells in breast cancer sentinel lymph node frozen sections by visual analysis of samples digitized using low-cost, point-of-care microscopy is comparable to analysis of digital samples scanned using a high-end, whole slide scanner. This technique could potentially provide a workflow for digital diagnostics in resource-limited settings, facilitate sample analysis at the point-of-care and reduce the need for trained experts on-site during surgical procedures.Peer reviewe

Quantification of Estrogen Receptor-Alpha Expression in Human Breast Carcinomas With a Miniaturized, Low-Cost Digital Microscope : A Comparison with a High-End Whole Slide- Scanner

Introduction: A significant barrier to medical diagnostics in low-resource environments is the lack of medical care and equipment. Here we present a low-cost, cloud-connected digital microscope for applications at the point-of-care. We evaluate the performance of the device in the digital assessment of estrogen receptor-alpha (ER) expression in breast cancer samples. Studies suggest computer-assisted analysis of tumor samples digitized with whole slide-scanners may be comparable to manual scoring, here we study whether similar results can be obtained with the device presented. Materials and methods: A total of 170 samples of human breast carcinoma, immunostained for ER expression, were digitized with a high-end slide-scanner and the point-of-care microscope. Corresponding regions from the samples were extracted, and ER status was determined visually and digitally. Samples were classified as ER negative (<1% ER positivity) or positive, and further into weakly (1-10% positivity) and strongly positive. Interobserver agreement (Cohen's kappa) was measured and correlation coefficients (Pearson's product-momentum) were calculated for comparison of the methods. Results: Correlation and interobserver agreement (r = 0.98, p < 0.001, kappa = 0.84, CI95% = 0.75-0.94) were strong in the results from both devices. Concordance of the point-of-care microscope and the manual scoring was good (r = 0.94, p < 0.001, kappa = 0.71, CI95% = 0.61-0.80), and comparable to the concordance between the slide scanner and manual scoring (r = 0.93, p < 0.001, kappa = 0.69, CI95% = 0.60-0.78). Fourteen (8%) discrepant cases between manual and device-based scoring were present with the slide scanner, and 16 (9%) with the point-of-care microscope, all representing samples of low ER expression. Conclusions: Tumor ER status can be accurately quantified with a low-cost imaging device and digital image-analysis, with results comparable to conventional computer-assisted or manual scoring. This technology could potentially be expanded for other histopathological applications at the point-of-care

A novel deep learning-based point-of-care diagnostic method for detecting Plasmodium falciparum with fluorescence digital microscopy

Background Malaria remains a major global health problem with a need for improved field-usable diagnostic tests. We have developed a portable, low-cost digital microscope scanner, capable of both brightfield and fluorescence imaging. Here, we used the instrument to digitize blood smears, and applied deep learning (DL) algorithms to detect Plasmodium falciparum parasites. Methods Thin blood smears (n = 125) were collected from patients with microscopy-confirmed P. falciparum infections in rural Tanzania, prior to and after initiation of artemisinin-based combination therapy. The samples were stained using the 4′,6-diamidino-2-phenylindole fluorogen and digitized using the prototype microscope scanner. Two DL algorithms were trained to detect malaria parasites in the samples, and results compared to the visual assessment of both the digitized samples, and the Giemsa-stained thick smears. Results Detection of P. falciparum parasites in the digitized thin blood smears was possible both by visual assessment and by DL-based analysis with a strong correlation in results (r = 0.99, p <0.01). A moderately strong correlation was observed between the DL-based thin smear analysis and the visual thick smear-analysis (r = 0.74, p <0.01). Low levels of parasites were detected by DL-based analysis on day three following treatment initiation, but a small number of fluorescent signals were detected also in microscopy-negative samples. Conclusion Quantification of P. falciparum parasites in DAPI-stained thin smears is feasible using DL-supported, point-of-care digital microscopy, with a high correlation to visual assessment of samples. Fluorescent signals from artefacts in samples with low infection levels represented the main challenge for the digital analysis, thus highlighting the importance of minimizing sample contaminations. The proposed method could support malaria diagnostics and monitoring of treatment response through automated quantification of parasitaemia and is likely to be applicable also for diagnostics of other Plasmodium species and other infectious diseases.Peer reviewe