Influence of the Honed Cutting Edge on Tool Wear and Surface Integrity in Slot Milling of 42CrMo4 Steel

The cutting edge microgeometry has a significant influence on the wear behavior of cutting tools and therefore on the machining performance. To investigate the effect of tailored cutting edge microgeometries, a detailed geometrical description of different cutting edge designs is necessary. The cutting edge profile is analyzed with respect to the machining conditions as well as the cutting edge segments S? and S?. Furthermore, this paper presents the influence of tailored cutting edges on tool wear, burr formation and residual stresses in slot milling of 42CrMo4 steel regarding the normalized ploughing zone in front of the cutting edge. © 2012 The Authors

Computer-based methods for a socially sustainable urban and regional planning

Due to global restructuring and urbanization, urban and regional planning is presented with the great challenge of offering sustainable planning strategies. Through particular consideration of the interaction between spatial and social structures, this research project aims to provide a methodical instrument that helps to factor the social dimension of sustainability into planning. The project comprises three modules. In the first one, a method will be developed, which makes it possible to generate spatial structures with very different characteristics. In the framework of the second module, we first elaborate on graph-based methods for analyzing spatial structures, and secondly we develop an agent-based simulation model for residential segregation. The third module contains an empirical study of the interactions between built structures and socio-spatial organization in the partner city of Dresden. Through the comparison of simulation models and small-scale empirical data, one should be able to derive theoretical concepts which can in turn be used to evaluate specific built structures.Peer Reviewe

Cell Cycle Regulating Kinase Cdk4 as a Potential Target for Tumor Cell Treatment and Tumor Imaging

The cyclin-dependent kinase (Cdk)-cyclin D/retinoblastoma (pRb)/E2F cascade, which controls the G1/S transition of cell cycle, has been found to be altered in many neoplasias. Inhibition of this pathway by using, for example, selective Cdk4 inhibitors has been suggested to be a promising approach for cancer therapy. We hypothesized that appropriately radiolabeled Cdk4 inhibitors are suitable probes for tumor imaging and may be helpful studying cell proliferation processes in vivo by positron emission tomography. Herein, we report the synthesis and biological, biochemical, and radiopharmacological characterizations of two 124I-labeled small molecule Cdk4 inhibitors (8-cyclopentyl-6-iodo-5-methyl-2-(4-piperazin-1-yl-phenylamino)-8H-pyrido[2,3-d]-pyrimidin-7-one (CKIA) and 8-cyclopentyl-6-iodo-5-methyl-2-(5-(piperazin-1-yl)-pyridin-2-yl-amino)-8H-pyrido[2,3-d]pyrimidin-7-one (CKIB)). Our data demonstrate a defined and specific inhibition of tumor cell proliferation through CKIA and CKIB by inhibition of the Cdk4/pRb/E2F pathway emphasizing potential therapeutic benefit of CKIA and CKIB. Furthermore, radiopharmacological properties of [124I]CKIA and [124I]CKIB observed in human tumor cells are promising prerequisites for in vivo biodistribution and imaging studies

Transformer Utilization in Medical Image Segmentation Networks

Owing to success in the data-rich domain of natural images, Transformers have recently become popular in medical image segmentation. However, the pairing of Transformers with convolutional blocks in varying architectural permutations leaves their relative effectiveness to open interpretation. We introduce Transformer Ablations that replace the Transformer blocks with plain linear operators to quantify this effectiveness. With experiments on 8 models on 2 medical image segmentation tasks, we explore -- 1) the replaceable nature of Transformer-learnt representations, 2) Transformer capacity alone cannot prevent representational replaceability and works in tandem with effective design, 3) The mere existence of explicit feature hierarchies in transformer blocks is more beneficial than accompanying self-attention modules, 4) Major spatial downsampling before Transformer modules should be used with caution.Comment: Accepted in NeurIPS 2022 workshop, Medical Imaging Meets NeurIPS (MedNeurIPS

Computer-based methods for a socially sustainable urban and regional planning

Due to global restructuring and urbanization, urban and regional planning is presented with the great challenge of offering sustainable planning strategies. Through particular consideration of the interaction between spatial and social structures, this research project aims to provide a methodical instrument that helps to factor the social dimension of sustainability into planning. The project comprises three modules. In the first one, a method will be developed, which makes it possible to generate spatial structures with very different characteristics. In the framework of the second module, we first elaborate on graph-based methods for analyzing spatial structures, and secondly we develop an agent-based simulation model for residential segregation. The third module contains an empirical study of the interactions between built structures and socio-spatial organization in the partner city of Dresden. Through the comparison of simulation models and small-scale empirical data, one should be able to derive theoretical concepts which can in turn be used to evaluate specific built structures

MedNeXt: Transformer-driven Scaling of ConvNets for Medical Image Segmentation

There has been exploding interest in embracing Transformer-based architectures for medical image segmentation. However, the lack of large-scale annotated medical datasets make achieving performances equivalent to those in natural images challenging. Convolutional networks, in contrast, have higher inductive biases and consequently, are easily trainable to high performance. Recently, the ConvNeXt architecture attempted to modernize the standard ConvNet by mirroring Transformer blocks. In this work, we improve upon this to design a modernized and scalable convolutional architecture customized to challenges of data-scarce medical settings. We introduce MedNeXt, a Transformer-inspired large kernel segmentation network which introduces - 1) A fully ConvNeXt 3D Encoder-Decoder Network for medical image segmentation, 2) Residual ConvNeXt up and downsampling blocks to preserve semantic richness across scales, 3) A novel technique to iteratively increase kernel sizes by upsampling small kernel networks, to prevent performance saturation on limited medical data, 4) Compound scaling at multiple levels (depth, width, kernel size) of MedNeXt. This leads to state-of-the-art performance on 4 tasks on CT and MRI modalities and varying dataset sizes, representing a modernized deep architecture for medical image segmentation. Our code is made publicly available at: https://github.com/MIC-DKFZ/MedNeXt.Comment: Accepted at MICCAI 202

Zurich Consensus: German Expert Opinion on the St. Gallen Votes on 15 March 2009 (11th International Conference at St. Gallen: Primary Therapy of Early Breast Cancer)

A German working group of 23 breast cancer experts discussed the results from the vote at this year's St. Gallen Consensus Conference on Primary Therapy for Early Breast Cancer ( March 11-14, 2009) and came up with some concrete recommendations for day-to-day therapeutic decisions in Germany. Due the fact that the concept of the St. Gallen Consensus Conference merely allows for a minimal consensus, the objective of the working group was to provide practice-related recommendations for day-to-day clinical decisions in Germany. One area of emphasis at St. Gallen was tumor biology as a starting point for reaching individual therapeutic decisions. Intensive discussion was necessary with respect to the clinical relevance of predictive and prognostic factors. A new addition to the area of systemic therapy was a first-ever discussion of the adjuvant administration of bisphosponates and the fact that therapy with trastuzumab in HER2 overexpressing breast cancer has been defined as the standard for neoadjuvant therapy. The value of taxanes as a component of (neo) adjuvant chemotherapy as well as the value of aromatase inhibitors for the endocrine adjuvant treatment of postmenopausal patients were affirmed

"Song of Life (SOL)" study protocol: a multicenter, randomized trial on the emotional, spiritual, and psychobiological effects of music therapy in palliative care

Background: Although patients in palliative care commonly report high emotional and spiritual needs, effective psychosocial treatments based on high quality studies are rare. First research provides evidence for benefits of psychosocial interventions in advanced cancer care. To specifically address end-of-life care requirements, life review techniques and creative-arts based therapies offer a promising potential. Therefore, the present study protocol presents a randomized controlled trial on the effectiveness of a newly developed music therapy technique that is based on a biographically meaningful song (“Song of Life”; SOL). Methods: In a design with two parallel arms, 104 patients at two palliative care units will be randomly assigned to three sessions of either SOL (experimental group) or relaxation exercises (control group). Improvements in the psychological domain of quality of life will be the primary endpoint, while secondary outcomes encompass spiritual well-being, ego-integrity, overall quality of life, and distress. Additionally, caregivers will be asked to provide feedback about the treatment. Assessment of biopsychological stress markers and qualitative analysis of perceived strengths and weaknesses will complement data collection. Discussion: Based on the results of a previous pilot study, we dedicated considerable efforts to optimizing the intervention and selecting appropriate outcomes for the present trial. We are confident to have designed a methodologically rigorous study that will contribute to the evidence-base and help to develop the potential of psychosocial interventions in palliative care. Trial registration: German Clinical Trials Register (DRKS) – DRKS00015308 (date of registration: September 07th 2018)

Role of Intraparotid and Neck Lymph Node Metastasis in Primary Parotid Cancer Surgery: A Population-Based Analysis

Simple Summary The prognostic role of intraparotid (PAR) and cervical lymph node (LN) metastasis on overall survival (OS) of primary parotid cancer is unclear. All 345 Thuringian patients with parotid cancer from 1996 to 2016 were included in a population-based study. OS was assessed in relation to the total number of removed PAR and cervical LN, number of positive intraparotid (PAR+), positive cervical LN, LN ratio, log odds of positive LN (LODDS), as well as including the PAR as LODDS-PAR. PAR was assessed in 42% of the patients (22% of these PAR+). T and N classification were not independent predictors of OS. When combining T with LODDS instead of N, higher T became a strong prognosticator, but not LODDS. When combining T classification with LODDS-PAR, both higher T classification and the classification with LODDS-PAR became independent predictors of worse OS. LODDS-PAR seems to be an optimal prognosticator for OS in primary parotid cancer. Abstract This population-based study investigated the prognostic role of intraparotid (PAR) and cervical lymph node (LN) metastasis on overall survival (OS) of primary parotid cancer. All 345 patients (median age: 66 years; 43% female, 49% N+, 31% stage IV) of the Thuringian cancer registries with parotid cancer from 1996 to 2016 were included. OS was assessed in relation to the total number of removed PAR and cervical LN, number of positive intraparotid (PAR+), positive cervical LN, LN ratio, log odds of positive LN (LODDS), as well as including the PAR as LODDS-PAR. PAR was assessed in 42% of the patients (22% of these PAR+). T and N classification were not independent predictors of OS. When combining T with LODDS instead of N, higher T (T3/T4) became a prognosticator (hazard ratio (HR) = 2.588; CI = 1.329–5.040; p = 0.005) but not LODDS ( p > 0.05). When combining T classification with LODDS-PAR, both higher T classification (HR = 2.256; CI = 1.288–3.950; p = 0.004) and the alternative classification with LODDS-PAR (≥median −1.11; HR 2.078; CI = 1.155–3.739; p = 0.015) became independent predictors of worse OS. LODDS-PAR was the only independent prognosticator out of the LN assessment for primary parotid cancer