Beyond the beaten paths of forecasting call center arrivals : on the use of dynamic harmonic regression with predictor variables

Modern call centers require precise forecasts of call and e-mail arrivals to optimize staffing decisions and to ensure high customer satisfaction through short waiting times and the availability of qualified agents. In the dynamic environment of multi-channel customer contact, organizational decision-makers often rely on robust but simplistic forecasting methods. Although forecasting literature indicates that incorporating additional information into time series predictions adds value by improving model performance, extant research in the call center domain barely considers the potential of sophisticated multivariate models. Hence, with an extended dynamic harmonic regression (DHR) approach, this study proposes a new reliable method for call center arrivals' forecasting that is able to capture the dynamics of a time series and to include contextual information in form of predictor variables. The study evaluates the predictive potential of the approach on the call and e-mail arrival series of a leading German online retailer comprising 174 weeks of data. The analysis involves time series cross-validation with an expanding rolling window over 52 weeks and comprises established time series as well as machine learning models as benchmarks. The multivariate DHR model outperforms the compared models with regard to forecast accuracy for a broad spectrum of lead times. This study further gives contextual insights into the selection and optimal implementation of marketing-relevant predictor variables such as catalog releases, mail as well as postal reminders, or billing cycles

Lehrerurteile über Schülerleistungen. Untersuchungen zur diagnostischen Kompetenz von Lehrkräften

Die kumulative Dissertationsschrift setzt sich mit verschiedenen Facetten diagnostischer Urteile von Lehrkräften auseinander. Dabei wird ein heuristisches Modell der diagnostischen Urteilsbildung herausgearbeitet, welches bestehende Stränge zur Erklärung der Güte diagnostischer Urteile systematisiert. Anhand von drei separaten Forschungsbeiträgen werden Aspekte des Modells beleuchtet und anschließend diskutiert

VISOR: a versatile haplotype-aware structural variant simulator for short- and long-read sequencing.

Abstract Summary VISOR is a tool for haplotype-specific simulations of simple and complex structural variants (SVs). The method is applicable to haploid, diploid or higher ploidy simulations for bulk or single-cell sequencing data. SVs are implanted into FASTA haplotypes at single-basepair resolution, optionally with nearby single-nucleotide variants. Short or long reads are drawn at random from these haplotypes using standard error profiles. Double- or single-stranded data can be simulated and VISOR supports the generation of haplotype-tagged BAM files. The tool further includes methods to interactively visualize simulated variants in single-stranded data. The versatility of VISOR is unmet by comparable tools and it lays the foundation to simulate haplotype-resolved cancer heterogeneity data in bulk or at single-cell resolution. Availability and implementation VISOR is implemented in python 3.6, open-source and freely available at https://github.com/davidebolo1993/VISOR. Documentation is available at https://davidebolo1993.github.io/visordoc/. Supplementary information Supplementary data are available at Bioinformatics online

Idiopathic sclerosing orbital inflammation mimicking a malignant spindle cell tumor in a dog

A dog presented with a retrobulbar mass, diagnosed histopathologically as malignant spindle cell neoplasia. Emergence of analogous findings in the contralateral orbit prompted extended immunohistochemistry of the original mass and reassignment to idiopathic sclerosing orbital inflammation. Early incisional biopsy with extended immunohistochemical analysis should be considered for canine orbital tumors

Functional analysis of structural variants in single cells using Strand-seq

Somatic structural variants (SVs) are widespread in cancer, but their impact on disease evolution is understudied due to a lack of methods to directly characterize their functional consequences. We present a computational method, scNOVA, which uses Strand-seq to perform haplotype-aware integration of SV discovery and molecular phenotyping in single cells by using nucleosome occupancy to infer gene expression as a readout. Application to leukemias and cell lines identifies local effects of copy-balanced rearrangements on gene deregulation, and consequences of SVs on aberrant signaling pathways in subclones. We discovered distinct SV subclones with dysregulated Wnt signaling in a chronic lymphocytic leukemia patient. We further uncovered the consequences of subclonal chromothripsis in T cell acute lymphoblastic leukemia, which revealed c-Myb activation, enrichment of a primitive cell state and informed successful targeting of the subclone in cell culture, using a Notch inhibitor. By directly linking SVs to their functional effects, scNOVA enables systematic single-cell multiomic studies of structural variation in heterogeneous cell populations

Rpv3–1 mediated resistance to grapevine downy mildew is associated with specific host transcriptional responses and the accumulation of stilbenes

Background: European grapevine cultivars (Vitis vinifera spp.) are highly susceptible to the downy mildew pathogen Plasmopara viticola. Breeding of resistant V. vinifera cultivars is a promising strategy to reduce the impact of disease management. Most cultivars that have been bred for resistance to downy mildew, rely on resistance mediated by the Rpv3 (Resistance to P. viticola) locus. However, despite the extensive use of this locus, little is known about the mechanism of Rpv3-mediated resistance. Results: In this study, Rpv3-mediated defense responses were investigated in Rpv3+ and Rpv3ˉ grapevine cultivars following inoculation with two distinct P. viticola isolates avrRpv3+ and avrRpv3ˉ, with the latter being able to overcome Rpv3 resistance. Based on comparative microscopic, metabolomic and transcriptomic analyses, our results show that the Rpv3–1-mediated resistance is associated with a defense mechanism that triggers synthesis of fungi-toxic stilbenes and programmed cell death (PCD), resulting in reduced but not suppressed pathogen growth and development. Functional annotation of the encoded protein sequence of genes significantly upregulated during the Rpv3–1-mediated defense response revealed putative roles in pathogen recognition, signal transduction and defense responses. Conclusion: This study used histochemical, transcriptomic and metabolomic analyses of Rpv3+ and susceptible cultivars inoculated with avirulent and virulent P. viticola isolates to investigate mechanism underlying the Rpv3–1-mediated resistance response. We demonstrated a strong correlation between the expressions of stilbene biosynthesis related genes, the accumulation of fungi-toxic stilbenes, pathogen growth inhibition and PCD

Identification of novel follicular dendritic cell sarcoma markers, FDCSP and SRGN, by whole transcriptome sequencing

Follicular dendritic cell (FDC)-sarcoma is a rare neoplasm with morphologic and phenotypic features of FDCs. It shows an extremely heterogeneous morphology, therefore, its diagnosis relys on the phenotype of tumor cells. Aim of the present study was the identification of new specific markers for FDC-sarcoma by whole transcriptome sequencing (WTS). Candidate markers were selected based on gene expression level and biological function. Immunohistochemistry was performed on reactive tonsils, on 22 cases of FDC-sarcomas and 214 control cases including 114 carcinomas, 87 soft tissue tumors, 5 melanomas, 5 thymomas and 3 interdigitating dendritic cell sarcomas. FDC secreted protein (FDCSP) and Serglycin (SRGN) proved to be specific markers of FDC and related tumor. They showed better specificity and sensitivity values than some well known markers used in FDC sarcoma diagnosis (specificity: 98.6%, and 100%, respectively; sensitivity: 72.73% and 68.18%, respectively). In our cohorts CXCL13, CD21, CD35, FDCSP and SRGN were the best markers for FDC-sarcoma diagnosis and could discriminate 21/22 FDC sarcomas from other mesenchymal tumors by linear discriminant analysis. In summary, by WTS we identified two novel FDC markers and by the analysis of a wide cohort of cases and controls we propose an efficient marker panel for the diagnosis of this rare and enigmatic tumor