Fleet management in free-floating bike sharing systems using predictive modelling and explorative tools

For redistribution and operating bikes in a free-floating systems, two measures are of highest priority. First, the information about the expected number of rentals on a day is an important measure for service providers for management and service of their fleet. The estimation of the expected number of bookings is carried out with a simple model and a more complex model based on meterological information, as the number of loans depends strongly on the current and forecasted weather. Secondly, the knowledge of a service level violation in future on a fine spatial resolution is important for redistribution of bikes. With this information, the service provider can set reward zones where service level violations will occur in the near future. To forecast a service level violation on a fine geographical resolution the current distribution of bikes as well as the time and space information of past rentals has to be taken into account. A Markov Chain Model is formulated to integrate this information. We develop a management tool that describes in an explorative way important information about past, present and predicted future counts on rentals in time and space. It integrates all estimation procedures. The management tool is running in the browser and continuously updates the information and predictions since the bike distribution over the observed area is in continous flow as well as new data are generated continuously

User-based redistribution in free-floating bike sharing systems

We investigate the problem of user-based redistribution for free-floating bike sharing systems (BSS). We present a stochastic model of the bike dynamics and we show that the spatial distribution of bikes is correlated. This is specific to free-floating systems and it results in a substantially reduced service level. Offering incentives to users may stimulate them to change their behavior and usage pattern. We analyze drop-off incentives, derive an incentive methodology and study its potential. We show that by implementing a smart incentive system, the number of bikes for establishing a specific service level can be reduced significantly, even if only a minority of users participates. Under realistic behavioral assumptions, 30–50% reduction of bikes is achievable, which converts into substantial costs savings for the operator. Our research was carried out in the context of the development of the new e-bike sharing system “smide” in Zurich, launched in 2017. The incentive approach has been implemented and tested in a field test

Banks' risk culture and management control systems: a systematic literature review

Over ten years of a debate about the best ways to make banks safer have led to the conclusion that improving their risk culture is one venue to achieve this goal. Consequently, different disciplines discuss topics related to risk culture from varying methodological angles. This effort of many scholars provides a rich basis of theoretical and empirical evidence to guide business practice and improve regulation. However, the application of many approaches and methods can result in fragmentation and loss of a comprehensive perspective. This paper strives to counteract this fragmentation by providing a comprehensive perspective focusing particularly on the embeddedness of risk culture into banks’ management control systems. In order to achieve this goal, we apply a systematic literature review and interpret the identified findings through the theoretical lens of management control research. This review identifies 103 articles, which can be structured along three categories: Assessment of risk culture, relation between risk culture and management controls (with the subcategories embeddedness of risk culture in overall management control packages, risk culture and cultural controls, risk culture and action controls, risk culture and results controls, as well as risk culture and personnel controls) and development of banks’ risk culture over time. Along these categories the identified findings are interpreted and synthesized to a comprehensive model and consequences for theory, business practice and regulation are derived

On stochastic imitation dynamics in large-scale networks

We consider a broad class of stochastic imitation dynamics over networks, encompassing several well known learning models such as the replicator dynamics. In the considered models, players have no global information about the game structure: they only know their own current utility and the one of neighbor players contacted through pairwise interactions in a network. In response to this information, players update their state according to some stochastic rules. For potential population games and complete interaction networks, we prove convergence and long-lasting permanence close to the evolutionary stable strategies of the game. These results refine and extend the ones known for deterministic imitation dynamics as they account for new emerging behaviors including meta-stability of the equilibria. Finally, we discuss extensions of our results beyond the fully mixed case, studying imitation dynamics where agents interact on complex communication networks.Comment: Extended version of conference paper accepted at ECC 201

ABCB1 (MDR1) polymorphisms and ovarian cancer progression and survival: A comprehensive analysis from the Ovarian Cancer Association Consortium and The Cancer Genome Atlas

<b>Objective</b> <i>ABCB1</i> encodes the multi-drug efflux pump P-glycoprotein (P-gp) and has been implicated in multi-drug resistance. We comprehensively evaluated this gene and flanking regions for an association with clinical outcome in epithelial ovarian cancer (EOC).<p></p> <b>Methods</b> The best candidates from fine-mapping analysis of 21 <i>ABCB1</i> SNPs tagging C1236T (rs1128503), G2677T/A (rs2032582), and C3435T (rs1045642) were analysed in 4616 European invasive EOC patients from thirteen Ovarian Cancer Association Consortium (OCAC) studies and The Cancer Genome Atlas (TCGA). Additionally we analysed 1,562 imputed SNPs around ABCB1 in patients receiving cytoreductive surgery and either ‘standard’ first-line paclitaxel–carboplatin chemotherapy (n = 1158) or any first-line chemotherapy regimen (n = 2867). We also evaluated ABCB1 expression in primary tumours from 143 EOC patients.<p></p> <b>Result</b> Fine-mapping revealed that rs1128503, rs2032582, and rs1045642 were the best candidates in optimally debulked patients. However, we observed no significant association between any SNP and either progression-free survival or overall survival in analysis of data from 14 studies. There was a marginal association between rs1128503 and overall survival in patients with nil residual disease (HR 0.88, 95% CI 0.77–1.01; p = 0.07). In contrast, <i>ABCB1</i> expression in the primary tumour may confer worse prognosis in patients with sub-optimally debulked tumours.<p></p> <b>Conclusion</b> Our study represents the largest analysis of <i>ABCB1</i> SNPs and EOC progression and survival to date, but has not identified additional signals, or validated reported associations with progression-free survival for rs1128503, rs2032582, and rs1045642. However, we cannot rule out the possibility of a subtle effect of rs1128503, or other SNPs linked to it, on overall survival.<p></p&gt

Common genetic variation in cellular transport genes and epithelial ovarian cancer (EOC) risk

Background Defective cellular transport processes can lead to aberrant accumulation of trace elements, iron, small molecules and hormones in the cell, which in turn may promote the formation of reactive oxygen species, promoting DNA damage and aberrant expression of key regulatory cancer genes. As DNA damage and uncontrolled proliferation are hallmarks of cancer, including epithelial ovarian cancer (EOC), we hypothesized that inherited variation in the cellular transport genes contributes to EOC risk. Methods In total, DNA samples were obtained from 14,525 case subjects with invasive EOC and from 23,447 controls from 43 sites in the Ovarian Cancer Association Consortium (OCAC). Two hundred seventy nine SNPs, representing 131 genes, were genotyped using an Illumina Infinium iSelect BeadChip as part of the Collaborative Oncological Gene-environment Study (COGS). SNP analyses were conducted using unconditional logistic regression under a log-additive model, and the FDR q<0.2 was applied to adjust for multiple comparisons. Results The most significant evidence of an association for all invasive cancers combined and for the serous subtype was observed for SNP rs17216603 in the iron transporter gene HEPH (invasive: OR = 0.85, P = 0.00026; serous: OR = 0.81, P = 0.00020); this SNP was also associated with the borderline/low malignant potential (LMP) tumors (P = 0.021). Other genes significantly associated with EOC histological subtypes (p<0.05) included the UGT1A (endometrioid), SLC25A45 (mucinous), SLC39A11 (low malignant potential), and SERPINA7 (clear cell carcinoma). In addition, 1785 SNPs in six genes (HEPH, MGST1, SERPINA, SLC25A45, SLC39A11 and UGT1A) were imputed from the 1000 Genomes Project and examined for association with INV EOC in white-European subjects. The most significant imputed SNP was rs117729793 in SLC39A11 (per allele, OR = 2.55, 95% CI = 1.5-4.35, p = 5.66x10-4). Conclusion These results, generated on a large cohort of women, revealed associations between inherited cellular transport gene variants and risk of EOC histologic subtypes

BRCA2 polymorphic stop codon K3326X and the risk of breast, prostate, and ovarian cancers

Background: The K3326X variant in BRCA2 (BRCA2*c.9976A>T; p.Lys3326*; rs11571833) has been found to be associated with small increased risks of breast cancer. However, it is not clear to what extent linkage disequilibrium with fully pathogenic mutations might account for this association. There is scant information about the effect of K3326X in other hormone-related cancers. Methods: Using weighted logistic regression, we analyzed data from the large iCOGS study including 76 637 cancer case patients and 83 796 control patients to estimate odds ratios (ORw) and 95% confidence intervals (CIs) for K3326X variant carriers in relation to breast, ovarian, and prostate cancer risks, with weights defined as probability of not having a pathogenic BRCA2 variant. Using Cox proportional hazards modeling, we also examined the associations of K3326X with breast and ovarian cancer risks among 7183 BRCA1 variant carriers. All statistical tests were two-sided. Results: The K3326X variant was associated with breast (ORw = 1.28, 95% CI = 1.17 to 1.40, P = 5.9x10- 6) and invasive ovarian cancer (ORw = 1.26, 95% CI = 1.10 to 1.43, P = 3.8x10-3). These associations were stronger for serous ovarian cancer and for estrogen receptor–negative breast cancer (ORw = 1.46, 95% CI = 1.2 to 1.70, P = 3.4x10-5 and ORw = 1.50, 95% CI = 1.28 to 1.76, P = 4.1x10-5, respectively). For BRCA1 mutation carriers, there was a statistically significant inverse association of the K3326X variant with risk of ovarian cancer (HR = 0.43, 95% CI = 0.22 to 0.84, P = .013) but no association with breast cancer. No association with prostate cancer was observed. Conclusions: Our study provides evidence that the K3326X variant is associated with risk of developing breast and ovarian cancers independent of other pathogenic variants in BRCA2. Further studies are needed to determine the biological mechanism of action responsible for these associations

Germline polymorphisms in an enhancer of PSIP1 are associated with progression-free survival in epithelial ovarian cancer.

Women with epithelial ovarian cancer (EOC) are usually treated with platinum/taxane therapy after cytoreductive surgery but there is considerable inter-individual variation in response. To identify germline single-nucleotide polymorphisms (SNPs) that contribute to variations in individual responses to chemotherapy, we carried out a multi-phase genome-wide association study (GWAS) in 1,244 women diagnosed with serous EOC who were treated with the same first-line chemotherapy, carboplatin and paclitaxel. We identified two SNPs (rs7874043 and rs72700653) in TTC39B (best P=7x10-5, HR=1.90, for rs7874043) associated with progression-free survival (PFS). Functional analyses show that both SNPs lie in a putative regulatory element (PRE) that physically interacts with the promoters of PSIP1, CCDC171 and an alternative promoter of TTC39B. The C allele of rs7874043 is associated with poor PFS and showed increased binding of the Sp1 transcription factor, which is critical for chromatin interactions with PSIP1. Silencing of PSIP1 significantly impaired DNA damage-induced Rad51 nuclear foci and reduced cell viability in ovarian cancer lines. PSIP1 (PC4 and SFRS1 Interacting Protein 1) is known to protect cells from stress-induced apoptosis, and high expression is associated with poor PFS in EOC patients. We therefore suggest that the minor allele of rs7874043 confers poor PFS by increasing PSIP1 expression.This project has been supported by a grant from Cancer Australia. The Mayo Clinic GWAS was supported by R01CA114343 (Haplotype-based genome screen for ovarian cancer loci). The Ovarian Cancer Association Consortium is supported by a grant from the Ovarian Cancer Research Fund thanks to donations by the family and friends of Kathryn Sladek Smith. The AOCS was supported by the U.S. Army Medical Research and Materiel Command under DAMD17-01-1-0729, the National Health and Medical Research Council (NHMRC) of Australia (grants 400281, 400413), Cancer Council Victoria, Cancer Council Queensland, Cancer Council New South Wales, Cancer Council South Australia, The Cancer Foundation of Western Australia, and Cancer Council Tasmania. G. Chenevix-Trench is a Senior Principal Research fellow of the NHMRC. Y. Lu is funded by NHMRC grant 496675, S. MacGregor is supported by an NHMRC career development award, S. Edwards and J. French are supported by Fellowships from the National Breast Cancer Foundation (NBCF) Australia. The QIMR Berghofer groups were supported by NHMRC project grants (1051698 to SM and 1058415 to SLE and JDF) and a Weekend to End Women’s Cancer Research Grant (to SLE). A deFazio is funded by the University of Sydney Cancer Research Fund and A deFazio and PR Harnett are funded by the Cancer Institute NSW through the Sydney-West Translational Cancer Research Centre. B. Gao is supported by NHMRC and Cancer Institute NSW scholarship. KBM and MO’R are funded by CR-UK. The Bavarian study (BAV) was supported by ELAN Funds of the University of Erlangen-Nuremberg. HSK would like to thank Ira Schwaab for her tireless work on sample preparation. The Belgian study (BEL) was funded by Nationaal Kankerplan and we would like to thank Gilian Peuteman, Thomas Van Brussel and Dominiek Smeets for technical assistance. The Japanese study (JPN) was funded by a Grant-in-Aid for the Third Term Comprehensive 10-Year Strategy for Cancer Control from the Ministry of Health, Labour and Welfare. The International Collaborative Ovarian Neoplasm study (ICON)7 trial team would like to thank the Medical Research Council (MRC) Clinical Trial Unit (CTU) at the University of London (UCL), the ICON7 Translational Research Sub-group, and the University of Leeds for their work on the coordination of samples and data from the ICON7 trial. The LAX study (Women’s Cancer Program) was supported by the American Cancer Society Early Detection Professorship (120950-SIOP-06-258-06-COUN) and Entertainment Industry Foundation. Funding for MALOVA (MAL) was provided by research grant RO1 CA 61107 from the National Cancer Institute, Bethesda, MD; research grant 94 222 52 from the Danish Cancer Society, Copenhagen, Denmark; and the Mermaid I project. The Mayo Clinic study (MAYO) was supported by R01 CA122443, P50 CA136393. The Oregon study (ORE) was funded by the Sherie Hildreth Ovarian Cancer Research Fund and the OHSU Foundation. We would like to thank all members of Scottish Gynaecological Clinical Trials group and the SCOTROC1 investigators. SCOTROC1 (SRO) was funded by Cancer Research UK, and the SCOTROC biological studies were supported by Cancer Research UK (grant C536/A6689). RSH receives support from NIH/NIGMS grant K08GM089941, NIH/NCI grant R21 CA139278, NIH/NIGMS grant UO1GM61393, University of Chicago Cancer Center Support Grant (#P30 CA14599) and Breast Cancer SPORE Career Development Award.This is the final version of the article. It first appeared from Impact Journals via http://dx.doi.org/10.18632/oncotarget.704

Common variants at theCHEK2gene locus and risk of epithelial ovarian cancer

Genome-wide association studies have identified 20 genomic regions associated with risk of epithelial ovarian cancer (EOC), but many additional risk variants may exist. Here, we evaluated associations between common genetic variants [single nucleotide polymorphisms (SNPs) and indels] in DNA repair genes and EOC risk. We genotyped 2896 common variants at 143 gene loci in DNA samples from 15 397 patients with invasive EOC and controls. We found evidence of associations with EOC risk for variants at FANCA, EXO1, E2F4, E2F2, CREB5 and CHEK2 genes (P ≤ 0.001). The strongest risk association was for CHEK2 SNP rs17507066 with serous EOC (P = 4.74 x 10(-7)). Additional genotyping and imputation of genotypes from the 1000 genomes project identified a slightly more significant association for CHEK2 SNP rs6005807 (r (2) with rs17507066 = 0.84, odds ratio (OR) 1.17, 95% CI 1.11-1.24, P = 1.1×10(-7)). We identified 293 variants in the region with likelihood ratios of less than 1:100 for representing the causal variant. Functional annotation identified 25 candidate SNPs that alter transcription factor binding sites within regulatory elements active in EOC precursor tissues. In The Cancer Genome Atlas dataset, CHEK2 gene expression was significantly higher in primary EOCs compared to normal fallopian tube tissues (P = 3.72×10(-8)). We also identified an association between genotypes of the candidate causal SNP rs12166475 (r (2) = 0.99 with rs6005807) and CHEK2 expression (P = 2.70×10(-8)). These data suggest that common variants at 22q12.1 are associated with risk of serous EOC and CHEK2 as a plausible target susceptibility gene.Other Research Uni