Etkinlikler

The rapid evolution of the Internet of Things (IoT) requires an evolution of computing architectures and technologies to handle increased data volumes, real-time processing requirements, and system complexity. This talk will explore how Artificial Intelligence (AI) and Fog Computing are converging to power the next generation of IoT systems, enhancing data processing capabilities at the edge while maintaining core analytics and control centrally. Integrating AI into fog computing nodes is critical to transforming traditional IoT devices into intelligent agents that can process and analyze data locally, make real-time decisions, and reduce dependence on cloud services. We will outline the basic principles of fog computing and its essential role in creating a scalable, responsive, and efficient IoT architecture. This architecture enables real-time data processing close to the source, minimizes latency, and optimizes bandwidth usage, which is critical for time-sensitive applications across multiple domains. We will explore several key applications of this integration in areas such as smart cities, industrial IoT, and autonomous vehicles. We will also present the results of our latest studies in our AIoT Lab.

The aviation industry, responsible for 915 million tons of CO2 emissions in 2019, stands at a crossroads. With its contribution to global greenhouse gas emissions currently at 3 and projected to triple or even quintuple by 2050, the need for transformative solutions is urgent. Among these, the electrification of aircraft propulsion and power systems offers a promising path forward. This shift has the potential to revolutionize propulsion architectures and fundamentally alter the relationship between propulsion systems and airframes. However, this exciting new design space also presents challenges, including technological bottlenecks, a lack of historical data, and high levels of uncertainty. Without careful navigation, the potential environmental and performance benefits of electrification can be easily undermined by suboptimal propulsion solutions. In the Integrated Design of Environmentally-friendly Aerospace Systems Laboratory (IDEAS Lab) at the University of Michigan, we strive to explore this complex design space through quantitative, system-level, and life-cycle assessments of future aircraft concepts. In this presentation, I will emphasize the critical role of systems thinking in integrating electrified propulsion technologies into the aircraft design process and will share examples of design space exploration and multi-disciplinary analysis and optimization of electrified aircraft.

The kidney consists of different segments that are essential in maintaining homeostasis throughout the body, including regulating electrolyte and water balance. The last segment of the kidney tubules is called the collecting duct (CD), where finetuning of sodium and water reabsorption occurs. A dysfunction of this process can lead to nephrogenic diabetes insipidus (NDI) that causes the inability to concentrate urine which can lead to patients excreting urine from 3 to 20 liters per day with risk of severe dehydration. It is known that NDI is caused by dysfunction of the water channel aquaporin 2 (AQP2) or the vasopressin 2 receptor (V2R) in the CD. Despite promising results of pre-clinical experiments, clinical trials often fail due to ineffectiveness or side-effects. Recent developments in organoid research promise to study kidney (patho)physiology with increased translational value compared to conventional in vitro research models. Tubuloids are kidney organoid models that are derived from adult stem cells and consist of epithelial cells from different segments of the kidney tubules. Tubuloid cells have high resemblance to their in vivo counterparts in terms of morphology and a mature expression profile of distal part of the nephron. By utilizing these tubuloid models, we show that tubuloids are capable of functional CD-specific sodium and water transport regulation under control of physiological stimuli and (inhibitory) diuretics that are commonly used in the clinic. Single cell RNAseq results show that tubuloids can be differentiated towards the thick ascending limb (TAL), distal convoluted tubule(DCT and the collecting duct (CD). Differentiated tubuloids showed significantly increased expression of these segment specific markers, including key sodium transporters NKCC2 (TAL), NCC (DCT), the sodium channel ENaC (CD) and water transport channels AQP2 (CD), AQP3 and AQP4. Radioactive tracer 22Na+ was used to study sodium reabsorption by renal ion transporters and channels, confirming that endogenous sodium channels in tubuloids reabsorb Na+ in a diuretic dependent manner. Physiological stimulation of tubuloids by desmopressin , the analog of vasopressin, resulted in upregulation of AQP2 signaling in a vasopressin 2 receptor (V2R) dependent manner. Following these findings, we performed 3D swelling assays to confirm the functional water transport capabilities. These functional assays confirmed that CD tubuloids are indeed capable of increasing water transport within the lumen of tubules and thereby respond to stimuli by swelling. By combining these functional sodium and water transport assays with the versatile tubuloid model, we propose that distal tubule differentiated tubuloids are suitable models to study kidney-specific behavior which can enable personalized medicine and studies on (rare) kidney diseases.

Information Session for Energy Technologies and Management Non-Thesis Masters Degree Program: April 18, 2024, Thursday 19:00-20:00

Information Session for Information Technology Non-Thesis Masters Degree Program: April 18th, 2024 Thursday

In todays world, many remotely operated systems are becoming ever more complex and the number of components in these systems keeps on growing. Examples include water pump systems for irrigation or mining purposes, off-shore power generation systems --the focus application area in this talk. Such systems are typically mission-critical for their users. Hence, it is of utmost importance to keep them in operating condition via well-designed maintenance policies. It makes sense for such policies to make use of whatever information is available no matter how limited. This approach is commonly labeled as condition-based maintenance (CBM) planning. In this talk, we will present a novel methodology to manage maintenance interventions as well as spare part quantity decisions for such systems. Our methodology is based on reducing the state space of the multi-component system and optimizing the resulting reduced-state Markov decision process via a linear programming approach. This methodology is highly scalable and capable of solving large problems that cannot be approached with the previously existing solution procedures due to the curse of dimensionality.

Rogers-Ramanujan identities have a central role in integer partitions. Then, they were extended combinatorially by Gordon in 1961. Andrews, found an analytic representation for Rogers-Ramanujan-Gordon identities in 1974. In this talk, a new evidently positive generating function for the difference condition side of Rogers-Ramanujan Gordon partitions when k3 is given. Also, it is combinatorially interpreted using the base partition-moves framework.

Information Session for Cyber Security Non-Thesis Masters Degree Program: April 16th, 2024 Tuesday

Information Session for Data Analytics Masters Degree Program: April16, 2024 Tuesday

CRISPRCas interference is mediated by Cas effector nucleases that are either components of multisubunit complexesin class1 CRISPRCas systemsor domains of a single proteinin class2 systems1,2,3. Here we show that the subtypeIII-E effector Cas7-11 is a single-protein effector in the class1 CRISPRCas systems originating from the fusion of a putative Cas11 domain and multiple Cas7 subunits that are derived from subtypeIII-D. Cas7-11 from Desulfonema ishimotonii (DiCas7-11), when expressed in Escherichia coli, has substantial RNA interference effectivity against mRNAs and bacteriophages. Similar to many class2 effectorsand unique among class1 systemsDiCas7-11 processes pre-CRISPR RNA into mature CRISPR RNA (crRNA) and cleaves RNA at positions defined by the target:spacer duplex, without detectable non-specific activity. We engineered Cas7-11 for RNA knockdown and editing in mammalian cells. We show that Cas7-11 has no effects on cell viability, whereas other RNA-targeting tools (such as short hairpin RNAs and Cas13) show substantial cell toxicity4,5. This study illustrates the evolution of a single-protein effector from multisubunit class1 effector complexes, expanding our understanding of the diversity of CRISPR systems. Cas7-11 provides the basis for new programmable RNA-targeting tools that are free of collateral activity and cell toxicity.

With the recent advancements in computer graphics, 3D virtual humans reached to a level of very high appearance realism. They take place in a range of applications such as games, chatbots for customer service and finance, simulations for education and healthcare, remote communication and (social) XR. Yet, their interactivity and movement is limited. We as humans are very receptive of non-verbal behaviors when we engage in social and emotional interactions. In order to interact with virtual humans naturally, 3D digital humans should also be equipped with non-verbal communication skills such as facial expressions, gestures and gaze. As they take place in more interactive applications, the demand to automatically generate their behavior on-the-fly increases. This talk will discuss the role of AI and machine learning algorithms to generate the behavior and movement of virtual humans i.e. using motion capture technology. I will present the state-of-the-art and some of our research on socially interactive virtual humans.

Fifteen years after the invention of Bitcoin, there has been a proliferation of many permissionless blockchains. Each such chain provides a public ledger that can be written to and read from by anyone. In this multi-chain world, a natural question arises: what is the optimal security an existing blockchain, a consumer chain, can extract by only reading and writing to k other existing blockchains, the provider chains In this talk, we will answer this question in three ways: (1) We will first see a protocol, Babylon, where an off-the-shelf proof-of-stake protocol (acting as a consumer chain) checkpoints onto Bitcoin (the provider chain) to reduce its stake withdrawal delay and to resolve issues such as non-slashable long-range safety attacks, low liveness resilience and difficulty to bootstrap from low token valuation. (2) Applying the checkpointing method iteratively, we will then design a protocol called interchain timestamping, which enables a consumer chain to extract the maximum economic security from the provider chains, as quantified by the slashable safety resilience.

Plasmonics and the faithfully related field of metamaterials have been among the most active and exciting areas of photonics over the last two decades. The distinctive ability of plasmonic nanostructures is to condense high amounts of optical energy into sub-wavelength volumes beyond the diffraction limit, enabling linear and nonlinear optical processes. The properties of surface plasmons are strongly related to the materials used and the geometry of the nanostructures. The meticulously designed nanostructures or metamaterials of metals, semiconductors, and 2D materials can enable the tuning of plasmonic resonances ranging from UV to mid-IR. Plasmonic nanostructures can promote a wide range of light-matter interaction processes and be a highly promising candidate for sensing, photovoltaics, nonlinear optics, and photocatalysis.

Complex systems consist of many interconnected components organized as networks. Moreover, the structure of such networks may evolve by their intrinsic rhythms. Our understanding of dynamical complex systems relies on our ability to infer appropriate models from observations. In this talk, we discuss how to learn equations of motion from observational data that underlie evolution and why the recovered dynamics contain higher-order edges, although they are not initially in the model. The results provide a necessary starting point to predict and control the network dynamics.

The adaptability of skeletal muscle mitochondria to various stressors and stimuli is well-known as these organelles are highly dynamic. However, when faced with severe and sustained mitochondrial dysfunction, these mechanisms are insufficient, leading to mitochondrial myopathies that cause significant muscular dysfunction.Mitochondrial aspartyl-tRNA synthetase (DARS2) is an essential enzyme responsible for the initial step of mitochondrial protein synthesis, attaching aspartate to its cognate tRNA. To investigate the impact of DARS2 deficiency on skeletal muscle, we generated a mouse model with muscle-specific deletion of DARS2 (mKO) using the CRE recombinase under the human skeletal muscle-specific