Leibniz University Hannover
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The Future of Circular Cities?! Planning for sustainable and inclusive communities
Get PDFEuropean cities such as Thessaloniki and Hanover are facing major transformations and continue to experience increasing challenges today, such as the Covid-19 pandemic or the financial crisis. While there are many common denominators in the challenges faced by European cities, there are also differences and local specificities. Various threats have intensified structural upheavals and impacted various sectors, such as health, retail, labour and mobility. Meanwhile, the challenges themselves grow ever more acute.
This publication comprises the results of the Thessaloniki Summer School 2024 that focused on ‘Thessaloniki as Circular City?!’ and the discussions held there on planning for sustainable and inclusive communities. The Summer School is a central cornerstone of the university partnership for joint educational and research activities between the Leibniz University of Hanover (The Faculty of Architecture and Landscape and The Institute of Environmental Planning) and the Aristotle University of Thessaloniki – AUTh (The Faculty of Engineering and The School of Architecture). It is funded by the German Academic Exchange Service (DAAD) as part of the ‘Centres of the Future’ (FutureCentres) project
Developing a Business Model for Platform-Based Applications in SME Sawmills: a Systematic Approach
Get PDFThis paper presents a methodical approach to developing a business model for a platform-based application for sawmill companies within small and medium-sized enterprises (SMEs). The product development process was executed by a consortium comprising organizations specializing in artificial intelligence, platform technologies, sensor technologies, automated connectivity, a research department in business model innovation, and multiple application partners from the relevant customer segment. The methodological framework followed a structured guideline that began with an in-depth requirements analysis, including stakeholder interviews across the value chain. Insights gained from this process led to identifying market requirements and potential solutions for smart services, which subsequently informed the technical design specifications. Based on these insights, the business model was developed through collaborative workshops within the consortium. The business model development was divided into four components: value capture, value delivery, value proposition, and value creation. Each workshop facilitated the elaboration and prioritization of these components and additional smart service specifics, ensuring continuous alignment with the findings from the requirements analysis. To support a successful market introduction, a comprehensive ecosystem was conceptualized and established. As a result, this study outlines an operator model that encompasses the relevant information and financial flows, as well as the value delivery among the involved stakeholders. Additionally, it outlines a clear product definition, cost structure, suitable revenue models tailored to the selected customer segments, and customer and data context. This research provides valuable insights into the design and implementation of business models tailored platform solutions, enhancing operational efficiency and service delivery in the sawmill industry while supporting SMEs in their digital transformation efforts
Solutions for challenges in autonomous robotic surgical instrument handling
No full textThe global healthcare sector faces a critical shortage of healthcare workers, posing a substantial threat to the sustainability of modern healthcare systems. Despite various socioeconomic measures, these efforts have seen limited success, prompting increased interest in automation to alleviate medical staff workloads. One promising approach is the development of robotic scrub nurses (RSNs), autonomous surgical assistants in charge of surgical instrument handling. Despite commendable efforts, significant challenges continue to hinder RSN implementation, including the need for large datasets of annotated images to train AI-based detectors, unreliable tool localization performance, and the absence of a versatile gripper that can securely handle various surgical instruments.
This dissertation proposes solutions that address these key challenges to help enable RSNs to effectively perform instrument detection, localization, and grasping. The primary contributions of this work include: 1) a novel data augmentation method based on a limited number of manually annotated images to improve detection performance and generalization with minimal annotation effort, 2) a multi-view voting approach for improved tool localization by filtering out detection errors, and 3) the design of a hybrid gripper based on granular jamming technology, capable of securely grasping a wide range of instruments while promoting compatibility with human collaboration.
Experimental results demonstrated the efficacy of the proposed solutions, showing high detection performance achieved through data augmentation, a significant reduction in localization errors with multi-view aggregation, and reliable performance of the hybrid gripper in handling diverse surgical instruments. These advancements represent a significant step forward in RSN development, offering the potential to enhance surgical efficiency and help mitigate the impact of the healthcare workforce shortage
Entwicklung einer Leitstruktur für das Cochlea-Implantat zur Wirkstofffreisetzung und Neuritenlenkung von Spiralganglienneuronen
No full textDie Behandlung eines sensorineuralen Hörverlust ist eine Herausforderung, bei der das
Einsetzen eines Cochlea-Implantats (CI) eine wichtige therapeutische Rolle spielt. Ein
Hauptproblem ist dabei der unzureichende Kontakt zwischen der CI-Elektrode und den
Spiralganglienneuronen (SGN), was die Signalübertragung und damit das Hörverständnis
der Nutzer beeinträchtigt. Vor diesem Hintergrund werden innovative Konzepte zur
Verbesserung der Schnittstelle zwischen CI und SGN entwickelt.
Ein möglicher Ansatz besteht in der Nutzung von biokompatiblen Polymerfasern als
neuronales Leitsystem. Diese Fasern werden mit den Wachstumsfaktoren Brain-derived
neurotrophic factor (BDNF) und Neurotrophin-3 (NT-3) dekoriert, die langsam freigesetzt
werden, um das Überleben der SGN zu fördern und das Wachstum von Neuriten zu
stimulieren. Um ein Entlangwachsen der ausgewachsenen Neuriten an den Fasern zu
begünstigen werden diese zuvor mit Laminin und Heparansulfat (HS), Komponenten der
extrazellulären Matrix, beschichtet. Zusätzlich wurde ein System entwickelt, das
entzündungshemmende Wirkstoffe wie Dexamethasonphosphat (DexP) über kovalent an
die Fasern gebundene nanoporöse Silica-Nanopartikel (NPSNP) freisetzen kann.
Bei den experimentellen Untersuchungen wurde zunächst die erfolgreiche Modifizierung
der Fasern mit Aminogruppen auf der Oberfläche durchgeführt. Dabei wiesen die
aminomodifizierten Fasern eine raue Oberfläche auf. Danach wurde HS kovalent an die
Fasern angebunden, gefolgt von der Inkubation in einer Lösung mit NT-3 und/oder BDNF.
Die Freisetzungsexperimente zeigten Unterschiede im Freisetzungsverhalten, wobei die
aminomodifizierten und mit HS-beschichteten Fasern, aufgrund der Oberflächenrauheit,
die größten Mengen der Wachstumsfaktoren freisetzen konnten. In vitro-Studien bestätigen
die neuroprotektive Wirkung der Wachstumsfaktoren und deren Einfluss auf die
Verlängerung der Neuriten. Wurden die Fasern mit Laminin beschichtet, wuchsen die
Neuriten entlang der Fasern, was vielversprechende Möglichkeiten zur Verbesserung des
Elektroden-Nerven-Kontakt bietet. Bei den Arbeiten mit NPSNP wurden Partikel mit einer
Größe von 40 nm erstellt, welche erfolgreich modifiziert und kovalent an die Fasern
gebunden wurden. Die Freisetzung von DexP zeigte eine kontinuierliche Abgabe des
Wirkstoffs, um mögliche Entzündungen zu bekämpfen
Das Startup-Ökosystem der LUH : Eine Übersicht
Get PDFDie Leibniz Universität Hannover verfügt über eine starke, vielfältige und leistungsfähige Förderumgebung für ihre Startups. Dieses Startup-Ökosystem wird getragen von vielfältigen Aktivitäten verschiedener Fakultäten, Forschungszentren und zentraler Einrichtungen. Wichtig dabei ist, dass diese Maßnahmen zentral koordiniert und wohl aufeinander abgestimmt sind. Die vorliegende Ausgabe des Unimagazins gibt einen Überblick über die Vielfalt dieser Angebote
Combination of Optical Imaging and Spectroscopy for the Detection of Melanoma Skin Cancer
Get PDFCutaneous melanoma is the most lethal form of skin cancer, responsible for over half of skin cancer-related deaths in recent decades. Current screening methods of skin cancer rely on invasive surgical excisions and histopathology, which cause discomfort for patients and are time-consuming. To address overcome this challenge, a multimodal optical biopsy system was developed, capable of simultaneously acquiring Raman spectroscopy (RS), optical coherence tomography (OCT), ultrasound imaging (US), and photoacoustic tomography (PAT) data within a short timeframe, aimed at enabling non-invasive, in vivo skin cancer diagnosis.
A model using synthetic melanin dissolved in dimethyl sulfoxide was applied to fresh porcine skin samples to simulate melanoma and study melanin's effects. Raman spectra and OCT images from 65 suspected melanocytic lesions and surrounding healthy skin of 47 patients were analyzed to differentiate melanoma, nevi, and healthy skin. Key OCT parameters (attenuation coefficient, R², RMSE) were extracted for machine learning. The system’s expansion to spatially offset Raman spectroscopy (SORS) showed promise, with initial porcine skin tests revealing deeper structural insights. Ultrasound and photoacoustic tomography imaging were validated on agar phantoms and ex vivo melanoma samples, with in vivo results confirming its clinical potential.
The system demonstrated reliable performance in terms of resolution, in vivo and ex vivo measurements, as well as the classification and identification performance of skin melanoma. Ultimately, the developed system, integrated with artificial intelligence, offers the potential for non-invasive diagnosis of melanoma and other skin cancers. This approach minimizes the discomfort associated with traditional biopsies while enhancing patient care and clinical outcomes
Scenario Analysis Of The Hospital Environment To Identify The Target Transformability Potential Of A German Hospital System
Get PDFHospitals operate in a highly volatile environment in which constantly changing demands arise, for example, from politics, from the population or from technical progress. In order to compete in this environment in the long term, hospitals must react in a targeted manner to these changes. The need for hospitals to be transformable is thus high. Measures to make a system transformable are associated with structural changes that often involve a high organisational and financial effort. It is therefore essential for hospital planners to know the exact need for transformability in order to design the transformability in line with requirements but without excessive effort. With this aim in mind, the most important change drivers for hospital systems in Germany are identified in this paper by means of a systematic survey among groups of people working in hospitals. Based on this, the probable development directions of the most relevant change drivers are described and by using a scenario analysis, their impact on the hospital system could be quantified. From this, the target transformability potentials of each hospital object could be derived, which can serve as a basis for hospital planners to take appropriate measures to achieve goal-oriented design of transformability
Developing a Strategy to Align Multiple Governance Practices into a Single Global Supply Chain Management Policy? Methodology and Insights from the Primever Case Study
Get PDFOne of the most important issues in the logistics of perishable products is the problem of efficient handling of goods in the supply chain due to transportation problems and tracking requirements. Since 1963, Primever has developed its expertise in its core business: the transportation of fruits and vegetables. In 2020, Primever became the Primever Group through successive international acquisitions by expanding its branches and connections with international companies and customers. The organisational transformation between a network of independent companies and a single group increases the complexity of management and governance. In fact, each company integrates the group with a different supply chain governance methodology and its own Transport Management System and tools. In parallel the evolution of technologies represents an opportunity to improve the management of the group and the reliability of the operations, thanks to a more efficient collection of data, among other things; and a source of risks, if not well managed, affecting perishable goods and supply chains in terms of food spoilage and transportation issues. In such a context one of the major issues is how to continuously integrate new companies with a strategy of alignment and ensure the efficiency of the global supply chain for perishable goods, taking into account the requirements of stakeholders? To fill this gap and help define a global strategy for group management over different time horizons, we propose an original methodology based on a digital maturity assessment model. The different levels of maturity detailed in the model take into account technologies such as blockchain, AI (Artificial Intelligence), IoT (Internet of things), and management processes (human resources, transport, information system, quality, finance, etc.). The proposed strategies help the group to develop its global supply chain
Quantum logic spectroscopy of titanium ions
Get PDFPrecision spectroscopy of complex atomic and molecular ions is a valuable tool for
fundamental physics and astrophysical applications. It can improve measurements
of magnetic fields of stars and the search for variations of fundamental constants
using quasar spectra. Molecular ions in particular are promising candidates for
measuring an electron electric dipole moment or to search for a possible variation
in the electron to proton mass ratio.
A complex level structure often results in the absence of closed cycling transitions,
used for direct laser cooling and detection. State preparation also becomes more
involved, compared to typically used atomic ions. Cooling and detection can be
provided by a quantum logic approach, where a well controllable ion is co-trapped
in addition to the complex ion. Both ions interact strongly due to the Coulomb
interaction. This enables sympathetic cooling. Moreover, the shared motional
mode can be used as a bus to transfer information on the internal state of the
complex ion to the well controllable ion, where it can be read out.
In this work quantum logic was used for spectroscopy of Zeeman levels in 48Ti+
and for initialization of its ground state in one Zeeman level. For this a trapped
ion experiment based on 40Ca+ was set up an characterized.
A novel method for preparation of dual-species two-ion ion crystals has been
developed and evaluated to simplify and improve current preparation strategies.
It starts from a multi-ion dual-species ion chain, where one species is directly
coolable and the other one is sympathetically cooled. Reduction of the number
of ions is based on an iterative process, where the ion chain in split is half,
each sub-chains’ constituents are detected and the chain closest to a dual-species
two-ion crystal is kept, while the other one is discarded from the trap. Splitting
and discarding is done by tailoring the potential landscape close to the ions
using DC potentials. The ion chains’ constituents are detected using fluorescence
imaging on the directly cooled ionic species and inferring the other species’
position from that measurement.
This method was applied to prepare 48Ti+- 40Ca+ two-ion crystals. Utilizing quantum
logic, the Zeeman level splitting of 48Ti+ is measured and state preparation
is demonstrated, using a far detuned Raman laser at 532 nm. Building on these
capabilities, a pathway for high precision spectroscopy, using a direct microwave
interaction is presented.
A far detuned Raman laser can be applied to many different ions because it
is not very dependent on the ion’s level structure. As an example it can be
used to investigate molecular ions, as already reported in [Chin-wen Chou et al., Nature,
545(7653):203–207, May 2017]. The
experiment presented here, aims to investigate 24MgH+ ions in the future. For
that preliminary results for a convenient molecular ion preparation are showcased