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"Hauke, Jan"
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Local firm upgrading in global value chains : a business model perspective
This book analyzes how a company can innovate and change its business model to the degree that it can climb up the value chain. The research synthesizes a combination of the global value chain and the business model literature to create a new framework of local firm upgrading. The findings of an empirical test of the model indicate that local firms are more than just a link within a global value chain. Each firm has a choice and inter-firm differences indicate that there is a strong firm level factor. Next to other factors, the founder is the key driver of local firm upgrading. He is possibly the most important element within a firm.
Book
Comparison of Values of Pearson's and Spearman's Correlation Coefficients on the Same Sets of Data
Spearman's rank correlation coefficient is a nonparametric (distribution-free) rank statistic proposed by Charles Spearman as a measure of the strength of an association between two variables. It is a measure of a monotone association that is used when the distribution of data makes Pearson's correlation coefficient undesirable or misleading. Spearman's coefficient is not a measure of the linear relationship between two variables, as some \"statisticians\" declare. It assesses how well an arbitrary monotonic function can describe a relationship between two variables, without making any assumptions about the frequency distribution of the variables. Unlike Pearson's product-moment correlation coefficient, it does not require the assumption that the relationship between the variables is linear, nor does it require the variables to be measured on interval scales; it can be used for variables measured at the ordinal level. The idea of the paper is to compare the values of Pearson's product-moment correlation coefficient and Spearman's rank correlation coefficient as well as their statistical significance for different sets of data (original - for Pearson's coefficient, and ranked data for Spearman's coefficient) describing regional indices of socio-economic development.
Journal Article
Conceptual Design of Offshore Jacket Substructures Using Machine Learning
The offshore wind sector is mature and has led to standardized design methods for offshore substructures. The conceptual design phase is critical for efficiency and cost-effectiveness and forms the basis for further design iterations. As turbine capacity increases, so does the complexity of offshore substructures, making design more challenging. However, the design process still relies on the expertise of the design engineers. These engineers rely heavily on their experience and intuition when designing, which can lead to biases due to limited information. To address this problem, Machine Learning (ML) techniques offer a promising way to improve the accuracy and efficiency of the conceptual design of offshore substructures. The current study is limited to the conceptual design of jacket substructures and was conducted on a self-developed global dataset of real jackets. The ML-based approach proposed in this study is capable of learning from existing data, recognizing intricate relationships between design variables, and potentially providing more accurate estimates for the initial conceptual design of offshore jacket substructures.
Journal Article
Coxa valga and antetorta configuration leads to underestimation of the femoral component size: a matched case-control study of patients undergoing cementless total hip arthroplasty
Background
Total hip arthroplasty (THA) is the gold standard procedure for patients with end-stage osteoarthritis after failed conservative therapy. Digital templating is commonly employed in preoperative preparation for THA and contributes positively to its outcome. However, the impact of coxa valga and antetorta (CVA) configurations on stem size prediction accuracy remains not reported. Previous studies demonstrated that the size of the lesser trochanter (LT) can be used to determine femoral anteversion on pelvis radiographs. This study investigates the accuracy of preoperative digital templating in predicting stem size in patients with CVA undergoing cementless THA.
Methods
Preoperative radiographs of 620 patients undergoing cementless THA were retrospectively investigated. Radiographs were standardized with patients standing and the leg internally rotated by 15°. A CVA group was established including patients with a CCD angle greater than 140° and a lesser trochanter (LT) size of at least 10 mm for men and 8 mm for women. For the control group, radiographs with a CCD angle ranging from 125–135° and LT size 3–10 mm for men and 3–8 mm for women were selected. Preoperative templating was performed using mediCAD. To reduce confounding factors, case-control matching was carried out for BMI and body height.
Results
After case-control matching, a total of thirty-one matches were analyzed. Stem size was underestimated in 74% (23/31) in the CVA and 13% (4/31) in the control group (
p
< 0.001). Moreover, patients with CVA were more likely to be underestimated by two sizes compared to controls (
p
< 0.004). In contrast, the exact stem size was predicted more frequently in the control group (
p
< 0.001).
Conclusion
Stem size in patients with a CVA configuration are at high risk of being underestimated when using digital templating. These findings can be valuable for guiding in intraoperative decisions and lowering the risk of complications associated with an undersized femoral component.
Journal Article
Turbulence Modeling for Physics-Informed Neural Networks: Comparison of Different RANS Models for the Backward-Facing Step Flow
Physics-informed neural networks (PINN) can be used to predict flow fields with a minimum of simulated or measured training data. As most technical flows are turbulent, PINNs based on the Reynolds-averaged Navier–Stokes (RANS) equations incorporating a turbulence model are needed. Several studies demonstrated the capability of PINNs to solve the Naver–Stokes equations for laminar flows. However, little work has been published concerning the application of PINNs to solve the RANS equations for turbulent flows. This study applied a RANS-based PINN approach to a backward-facing step flow at a Reynolds number of 5100. The standard k-ω model, the mixing length model, an equation-free νt and an equation-free pseudo-Reynolds stress model were applied. The results compared favorably to DNS data when provided with three vertical lines of labeled training data. For five lines of training data, all models predicted the separated shear layer and the associated vortex more accurately.
Journal Article
Performance of in silico prediction tools for the classification of rare BRCA1/2 missense variants in clinical diagnostics
Background
The use of next-generation sequencing approaches in clinical diagnostics has led to a tremendous increase in data and a vast number of variants of uncertain significance that require interpretation. Therefore, prediction of the effects of missense mutations using
in silico
tools has become a frequently used approach. Aim of this study was to assess the reliability of
in silico
prediction as a basis for clinical decision making in the context of hereditary breast and/or ovarian cancer.
Methods
We tested the performance of four prediction tools (Align-GVGD, SIFT, PolyPhen-2, MutationTaster2) using a set of 236
BRCA1/2
missense variants that had previously been classified by expert committees. However, a major pitfall in the creation of a reliable evaluation set for our purpose is the generally accepted classification of
BRCA1/2
missense variants using the multifactorial likelihood model, which is partially based on Align-GVGD results. To overcome this drawback we identified 161 variants whose classification is independent of any previous
in silico
prediction. In addition to the performance as stand-alone tools we examined the sensitivity, specificity, accuracy and Matthews correlation coefficient (MCC) of combined approaches.
Results
PolyPhen-2 achieved the lowest sensitivity (0.67), specificity (0.67), accuracy (0.67) and MCC (0.39). Align-GVGD achieved the highest values of specificity (0.92), accuracy (0.92) and MCC (0.73), but was outperformed regarding its sensitivity (0.90) by SIFT (1.00) and MutationTaster2 (1.00). All tools suffered from poor specificities, resulting in an unacceptable proportion of false positive results in a clinical setting. This shortcoming could not be bypassed by combination of these tools. In the best case scenario, 138 families would be affected by the misclassification of neutral variants within the cohort of patients of the German Consortium for Hereditary Breast and Ovarian Cancer.
Conclusion
We show that due to low specificities state-of-the-art
in silico
prediction tools are not suitable to predict pathogenicity of variants of uncertain significance in
BRCA1/2
. Thus, clinical consequences should never be based solely on
in silico
forecasts. However, our data suggests that SIFT and MutationTaster2 could be suitable to predict benignity, as both tools did not result in false negative predictions in our analysis.
Journal Article
HerediVar and HerediClassify: tools for streamlining genetic variant classification in hereditary breast and ovarian cancer
Background
Multiple different evidence types as well as gene-specific variant classification guidelines need to be considered during the classification of variants, making the process complex. Therefore, tools that support variant classification by experts are urgently needed.
Methods
We present HerediVar a web application and HerediClassify a variant classification algorithm. The performance of HerediClassify was validated and compared to other variant classification tools. HerediClassify implements 19/28 variant classification criteria by the American College of Medical Genetics and gene-specific recommendations for
ATM
,
BRCA1
,
BRCA2
,
CDH1
,
PALB2
,
PTEN
, and
TP53
.
Results
HerediVar offers modular annotation services and allows for collaboration in the classification of variants. On the validation dataset, HerediClassify shows an average F1-Score of 93% across all criteria. HerediClassify outperforms other automated variant classification tools like vaRHC and Cancer SIGVAR.
Conclusion
In HerediVar and HerediClassify we present a powerful solution to support variant classification in HBOC. Through their modular design, HerediVar and HerediClassify are easily extendable to other use cases and human genetic diagnostics as a whole.
Journal Article
The urban heat island in the city of Poznań as derived from Landsat 5 TM
To study urban heat island (UHI), Landsat 5 TM data and in situ measurements of air temperature from nine points in Poznań (Poland) for the period June 2008–May 2013 were used. Based on data from measurement points located in different types of land use, the surface urban heat island (SUHI) maps were created. All available and quality-controlled Landsat 5 TM images from 15 unique days were used to obtain the characteristics of land surface temperature (LST) and UHI intensity. In addition, spatial analysis of UHI was conducted on the basis of Corine Land Cover 2006 dataset. In situ measurements at a height of 2 m above ground level show that the UHI is a common occurrence in Poznań with a mean annual intensity of 1.0 °C. The UHI intensity is greater during the warm half of the year. Moreover, results based on the remote sensing data and the Corine Land Cover 2006 indicate that the highest value of the mean LST anomalies (3.4 °C) is attained by the continuous urban fabric, while the lowest value occurs within the broad-leaved forests (−3.1 °C). To re-count from LST to the air temperature at a height of 2 m above ground level (
T
agl
), linear and non-linear regression models were created. For both models, coefficients of determination equal about 0.80, with slightly higher value for the non-linear approach, which was applied to estimate the
T
agl
spatial variability over the city of Poznań.
Journal Article
Prevalence of pathogenic BRCA1/2 germline mutations among 802 women with unilateral triple-negative breast cancer without family cancer history
Background
There is no international consensus up to which age women with a diagnosis of triple-negative breast cancer (TNBC) and no family history of breast or ovarian cancer should be offered genetic testing for germline
BRCA1
and
BRCA2
(gBRCA) mutations. Here, we explored the association of age at TNBC diagnosis with the prevalence of pathogenic gBRCA mutations in this patient group.
Methods
The study comprised 802 women (median age 40 years, range 19–76) with oestrogen receptor, progesterone receptor, and human epidermal growth factor receptor type 2 negative breast cancers, who had no relatives with breast or ovarian cancer. All women were tested for pathogenic gBRCA mutations. Logistic regression analysis was used to explore the association between age at TNBC diagnosis and the presence of a pathogenic gBRCA mutation.
Results
A total of 127 women with TNBC (15.8%) were gBRCA mutation carriers (
BRCA1
:
n
= 118, 14.7%;
BRCA2
:
n
= 9, 1.1%). The mutation prevalence was 32.9% in the age group 20–29 years compared to 6.9% in the age group 60–69 years. Logistic regression analysis revealed a significant increase of mutation frequency with decreasing age at diagnosis (odds ratio 1.87 per 10 year decrease, 95%CI 1.50–2.32,
p
< 0.001). gBRCA mutation risk was predicted to be > 10% for women diagnosed below approximately 50 years.
Conclusions
Based on the general understanding that a heterozygous mutation probability of 10% or greater justifies gBRCA mutation screening, women with TNBC diagnosed before the age of 50 years and no familial history of breast and ovarian cancer should be tested for gBRCA mutations. In Germany, this would concern approximately 880 women with newly diagnosed TNBC per year, of whom approximately 150 are expected to be identified as carriers of a pathogenic gBRCA mutation.
Journal Article
Germline loss-of-function variants in the BARD1 gene are associated with early-onset familial breast cancer but not ovarian cancer
Background
The role of the
BARD1
gene in breast cancer (BC) and ovarian cancer (OC) predisposition remains elusive, as published case-control investigations have revealed controversial results. We aimed to assess the role of deleterious
BARD1
germline variants in BC/OC predisposition in a sample of 4920
BRCA1/2
-negative female BC/OC index patients of the German Consortium for Hereditary Breast and Ovarian Cancer (GC-HBOC).
Methods
A total of 4469 female index patients with BC, 451 index patients with OC, and 2767 geographically matched female control individuals were screened for loss-of-function (LoF) mutations and potentially damaging rare missense variants in
BARD1
. All patients met the inclusion criteria of the GC-HBOC for germline testing and reported at least one relative with BC or OC. Additional control datasets (Exome Aggregation Consortium, ExAC; Fabulous Ladies Over Seventy, FLOSSIES) were included for the calculation of odds ratios (ORs).
Results
We identified LoF variants in 23 of 4469 BC index patients (0.51%) and in 36 of 37,265 control individuals (0.10%), resulting in an OR of 5.35 (95% confidence interval [CI] = 3.17–9.04;
P
< 0.00001).
BARD1-
mutated BC index patients showed a significantly younger mean age at first diagnosis (AAD; 42.3 years, range 24–60 years) compared with the overall study sample (48.6 years, range 17–92 years;
P
= 0.00347). In the subgroup of BC index patients with an AAD < 40 years, an OR of 12.04 (95% CI = 5.78–25.08;
P
< 0.00001) was observed. An OR of 7.43 (95% CI = 4.26–12.98;
P
< 0.00001) was observed when stratified for an AAD < 50 years. LoF variants in
BARD1
were not significantly associated with BC in the subgroup of index patients with an AAD ≥ 50 years (OR = 2.29; 95% CI = 0.82–6.45;
P
= 0.11217). Overall, rare and predicted damaging
BARD1
missense variants were significantly more prevalent in BC index patients compared with control individuals (OR = 2.15; 95% CI = 1.26–3.67;
P
= 0.00723). Neither LoF variants nor predicted damaging rare missense variants in
BARD1
were identified in 451 familial index patients with OC.
Conclusions
Due to the significant association of germline LoF variants in
BARD1
with early-onset BC, we suggest that intensified BC surveillance programs should be offered to women carrying pathogenic
BARD1
gene variants.
Journal Article