Friedrich Adolph Wilhelm Diesterweg (1790-1866): Zum 200. Geburtstag

The loss of segregation of neuronal signal processing pathways is an important hypothesis for explaining the origin of functional deficits as associated with Parkinson's disease. Here we use a modeling approach which is utilized to study the influence of deep brain stimulation on the restoration of segregated activity in the target structures. Besides the spontaneous activity of the target network, the model considers a weak sensory input mimicking signal processing tasks, electrical deep brain stimulation delivered through a standard DBS electrode and synaptic plasticity. We demonstrate that the sensory input is capable of inducing a modification of the network structure which results in segregated microcircuits if the network is initialized in the healthy, desynchronized state. Depending on the strength and coverage, the sensory input is capable of restoring the functional sub-circuits even if the network is initialized in the synchronized, pathological state. Weak coordinated reset stimulation, applied to a network featuring a loss of segregation caused by global synchronization, is able to restore the segregated activity and to truncate the pathological, synchronized activity

New Method to Evaluate the Frictional Behavior within the Forming Gap during the Deep Drawing Process of Paperboard

To evaluate the influence of different normal forces and contact temperatures on the frictional behavior of paperboard during the deep drawing process, a new measurement punch was developed to measure the normal force, which induced the friction within the gap between the forming cavity and punch. The resulting dynamic coefficient of friction was calculated and reproduced via a new developed substitute test for the friction measurement device, which was first introduced in Lenske et al. (2017). The normal force within the forming gap during the deep drawing process was influenced by the blankholder force profile, the contact temperature, and the fiber direction. The friction measurements with the substitute test showed a strong dependency between the applied normal force and the dynamic coefficient of friction. Furthermore the frictional behavior was influenced by the contact temperature and the wrinkle formation

Draft genome sequence of the psychrophilic and alkaliphilic <em>Rhodonellum psychrophilum</em> strain GCM71^T

Rhodonellum psychrophilum GCM71(T), isolated from the cold and alkaline submarine ikaite columns in the Ikka Fjord in Greenland, displays optimal growth at 5 to 10°C and pH 10. Here, we report the draft genome sequence of this strain, which may provide insight into the mechanisms of adaptation to these extreme conditions

SENSOREN – AKTUELLER STAND UND HERAUSFORDERUNGEN

Sensoren sind Basiselemente, um Informationen aus der Umgebung aufzunehmen und elektronisch weiterzuverarbeiten. Sie haben wesentlich die innovativen Entwicklungen in den zurückliegenden 15 Jahren bestimmt. An ausgewählten Beispielen wird das komplexe Gebiet der Sensorik dargestellt und die Bedeutung von Sensoranwendungen in unterschiedlichsten Bereichen gezeigt. Eigene Beiträge zu resonanten Sensoren werden dargestellt. Dabei stehen Ultraschallsensoren und akustische Mikrosensoren im Mittelpunkt. Sensoren werden auch in der Zukunft eine wichtige Rolle spielen. Deshalb werden Trends abgeschätzt

Electrical Impedance Tomography: A Fair Comparative Study on Deep Learning and Analytic-based Approaches

Electrical Impedance Tomography (EIT) is a powerful imaging technique with diverse applications, e.g., medical diagnosis, industrial monitoring, and environmental studies. The EIT inverse problem is about inferring the internal conductivity distribution of an object from measurements taken on its boundary. It is severely ill-posed, necessitating advanced computational methods for accurate image reconstructions. Recent years have witnessed significant progress, driven by innovations in analytic-based approaches and deep learning. This review explores techniques for solving the EIT inverse problem, focusing on the interplay between contemporary deep learning-based strategies and classical analytic-based methods. Four state-of-the-art deep learning algorithms are rigorously examined, harnessing the representational capabilities of deep neural networks to reconstruct intricate conductivity distributions. In parallel, two analytic-based methods, rooted in mathematical formulations and regularisation techniques, are dissected for their strengths and limitations. These methodologies are evaluated through various numerical experiments, encompassing diverse scenarios that reflect real-world complexities. A suite of performance metrics is employed to assess the efficacy of these methods. These metrics collectively provide a nuanced understanding of the methods' ability to capture essential features and delineate complex conductivity patterns. One novel feature of the study is the incorporation of variable conductivity scenarios, introducing a level of heterogeneity that mimics textured inclusions. This departure from uniform conductivity assumptions mimics realistic scenarios where tissues or materials exhibit spatially varying electrical properties. Exploring how each method responds to such variable conductivity scenarios opens avenues for understanding their robustness and adaptability

Genetic dissection of apoptosis and cell cycle control in response of colorectal cancer treated with preoperative radiochemotherapy

BACKGROUND: In previous analyses we identified therapy-induced upregulation of the CDK inhibitor p21(CIP/WAF-1 )and consequently decreased tumor cell proliferation or loss of Bax as adverse factors for survival in rectal cancer treated with radiochemotherapy. Here, we address the individual role of p53 and its transcriptional targets, p21(CIP/WAF-1 )and Bax, on apoptosis induced by individual components of multimodal anticancer therapy, i.e. 5-fluorouracil (5-FU), ionising γ-radiation (IR) and heat shock/hyperthermia. METHODS: We analysed tumor samples 66 patients with rectal carcinoma treated by a neoadjuvant approach with radiochemotherapy ± heat shock/hyperthermia for the expression and mutation of p53 and the expression of p21(CIP/WAF-1 )and Bax. These data were correlated with the tumor response. The functional relevance of p53, p21(CIP/WAF-1 )and Bax was investigated in isogeneic HCT116 cell mutants treated with 5-FU, IR and heat shock. RESULTS: Rectal carcinoma patients who received an optimal heat shock treatment showed a response that correlated well with Bax expression (p = 0.018). Local tumor response in the whole cohort was linked to expression of p21(CIP/WAF-1 )(p < 0.05), but not p53 expression or mutation. This dichotomy of p53 pathway components regulating response to therapy was confirmed in vitro. In isogeneic HCT116 cell mutants, loss of Bax but not p53 or p21(CIP/WAF-1 )resulted in resistance against heat shock. In contrast, loss of p21(CIP/WAF-1 )or, to a lesser extent, p53 sensitized predominantly for 5-FU and IR. CONCLUSION: These data establish a different impact of p53 pathway components on treatment responses. While chemotherapy and IR depend primarily on cell cycle control and p21, heat shock depends primarily on Bax. In contrast, p53 status poorly correlates with response. These analyses therefore provide a rational approach for dissecting the mode of action of single treatment modalities that may be employed to circumvent clinically relevant resistance mechanisms in rectal cancer

An Educated Warm Start For Deep Image Prior-Based Micro CT Reconstruction

Deep image prior (DIP) was recently introduced as an effective unsupervised approach for image restoration tasks. DIP represents the image to be recovered as the output of a deep convolutional neural network, and learns the network's parameters such that the output matches the corrupted observation. Despite its impressive reconstructive properties, the approach is slow when compared to supervisedly learned, or traditional reconstruction techniques. To address the computational challenge, we bestow DIP with a two-stage learning paradigm: (i) perform a supervised pretraining of the network on a simulated dataset; (ii) fine-tune the network's parameters to adapt to the target reconstruction task. We provide a thorough empirical analysis to shed insights into the impacts of pretraining in the context of image reconstruction. We showcase that pretraining considerably speeds up and stabilizes the subsequent reconstruction task from real-measured 2D and 3D micro computed tomography data of biological specimens. The code and additional experimental materials are available at https://educateddip.github.io/docs.educated_deep_image_prior/

Neue Informationstechnologien und flexible Arbeitszeitsysteme : die Panelstudie zur technischen, betrieblichen, wirtschaftlichen und sozialen Entwicklung beim Einsatz flexibler Arbeitssysteme in der gewerblichen Wirtschaft des SFB 187 (NIFA-Panel)

"Der Beitrag beschreibt die inhaltlichen und methodischen Grundlagen des Betriebspanels des Bochumer Sonderforschungsbereichs 187. Übergeordnetes Ziel der Untersuchung ist es, auf der Basis repräsentativer Daten die Bestimmung zentraler technischer und arbeitsorganisatorischer Entwicklungslinien im deutschen Maschinenbau unter besonderer Berücksichtigung flexibler Fertigungsstrukturen zu analysieren. Diese Aufgabenstellung ergibt sich aus den Zielen des SFB 187 - der Entwicklung eines dezentralen technisch-arbeitsorganisatorischen Modells der rechnerintegrierten Produktion - und der Funktion des Projektes als zentraler Informationsquelle für alle Teilprojekte des Sonderforschungsbereichs. Das NIFA-Panel ist konzipiert für fünf Befragungswellen mit einem jährlichen Abstand. Befragt werden in einer schriftlichen Totalerhebung die Betriebe des bundeseutschen Maschinenbaus mit mehr als 20 Mitarbeitern. Die Befragung wird in zwei Teilen durchgeführt, wobei bei der z.T. abgeschlossenen Feldphase des ersten Teils eine Rücklaufquote von 43,8% erreicht wurde. Die vollständige erste Welle des NIFA-Panels wird Ende 1991 abgeschlossen sein." (Autorenreferat)Panel - Konzeption, flexibles Fertigungssystem, Arbeitsorganisation, Erhebungsmethode

Gastight Paperboard Package: A new Step in Food Packaging

Packages made from coated paperboard are currently used in food packaging for frosted or microwave food. These cups are usually deep drawn from flat paperboard blanks. The blanks are pre-creased to control the material overflow that appears during drawing. The resulting wrinkles in the sealing area have to be considered as capillary tubes allowing the gas exchange between the package and the environmental atmosphere. A new technological approach in 3D forming enables the prevention of capillary tubes in the sealing area. The result is a gas-tight sealable paperboard cup which is limited by its coating concerning the degree of gas tightness