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         "url": "http://dx.doi.org/10.1016/j.ijmultiphaseflow.2026.105725", 
         
         "author": [ 
            "Jonathan Wurst","Maximilian Dreisbach","Alexander Stroh","Jochen Kriegseis","Kathrin Schulte"
         ],
         "authors": [
         	
            	{"first" : "Jonathan",	"last" : "Wurst"},
            	{"first" : "Maximilian",	"last" : "Dreisbach"},
            	{"first" : "Alexander",	"last" : "Stroh"},
            	{"first" : "Jochen",	"last" : "Kriegseis"},
            	{"first" : "Kathrin",	"last" : "Schulte"}
         ],
         "volume": "200","pages": "105725",
         "issn" : "0301-9322",
         
         "doi" : "10.1016/j.ijmultiphaseflow.2026.105725",
         
         "bibtexKey": "Wurst_2026"

      }
,
      {
         "type" : "Publication",
         "id"   : "https://puma.ub.uni-stuttgart.de/bibtex/2b6194830899aa2dc2b245baf30890a37/pumaibtb_tb",         
         "tags" : [
            "imported","myown"
         ],
         
         "intraHash" : "b6194830899aa2dc2b245baf30890a37",
         "interHash" : "4a3852eda73552c662d58342d5127a98",
         "label" : "Bioreactive separation technology: A retrospective and perspective",
         "user" : "pumaibtb_tb",
         "description" : "",
         "date" : "2026-04-08 09:16:41",
         "changeDate" : "2026-04-08 09:17:53",
         "count" : 1,
         "pub-type": "article",
         "journal": "Chemical Engineering and Processing - Process Intensification",
         "year": "2026", 
         "url": "https://www.sciencedirect.com/science/article/pii/S0255270126000929", 
         
         "author": [ 
            "Thomas Waluga","Daniel Ohde","Marion Ansorge-Schumacher","Regina Benfer","Wilfried Bluemke","Heiko Briesen","Jakob Burger","Anja Drews","Johannes Gescher","Christiane Glasmacher-Remberg","Marcus Grünewald","Niels Hansen","Christoph Held","Dirk Holtmann","Selin Kara","Jan von Langermann","Andreas Liese","Jørgen Magnus","Alexander Pelzer","Jürgen Pleiss","Tina Radespiel","Jens-Uwe Repke","Katrin Rosenthal","Anett Schallmey","Irina Smirnova","John M. Woodley","Thomas Wucherpfennig","Michael Zavrel","Tim Zeiner","Mirko Skiborowski"
         ],
         "authors": [
         	
            	{"first" : "Thomas",	"last" : "Waluga"},
            	{"first" : "Daniel",	"last" : "Ohde"},
            	{"first" : "Marion",	"last" : "Ansorge-Schumacher"},
            	{"first" : "Regina",	"last" : "Benfer"},
            	{"first" : "Wilfried",	"last" : "Bluemke"},
            	{"first" : "Heiko",	"last" : "Briesen"},
            	{"first" : "Jakob",	"last" : "Burger"},
            	{"first" : "Anja",	"last" : "Drews"},
            	{"first" : "Johannes",	"last" : "Gescher"},
            	{"first" : "Christiane",	"last" : "Glasmacher-Remberg"},
            	{"first" : "Marcus",	"last" : "Grünewald"},
            	{"first" : "Niels",	"last" : "Hansen"},
            	{"first" : "Christoph",	"last" : "Held"},
            	{"first" : "Dirk",	"last" : "Holtmann"},
            	{"first" : "Selin",	"last" : "Kara"},
            	{"first" : "Jan",	"last" : "von Langermann"},
            	{"first" : "Andreas",	"last" : "Liese"},
            	{"first" : "Jørgen",	"last" : "Magnus"},
            	{"first" : "Alexander",	"last" : "Pelzer"},
            	{"first" : "Jürgen",	"last" : "Pleiss"},
            	{"first" : "Tina",	"last" : "Radespiel"},
            	{"first" : "Jens-Uwe",	"last" : "Repke"},
            	{"first" : "Katrin",	"last" : "Rosenthal"},
            	{"first" : "Anett",	"last" : "Schallmey"},
            	{"first" : "Irina",	"last" : "Smirnova"},
            	{"first" : "John M.",	"last" : "Woodley"},
            	{"first" : "Thomas",	"last" : "Wucherpfennig"},
            	{"first" : "Michael",	"last" : "Zavrel"},
            	{"first" : "Tim",	"last" : "Zeiner"},
            	{"first" : "Mirko",	"last" : "Skiborowski"}
         ],
         "volume": "224","pages": "110787","abstract": "Biocatalysis, using enzymes or whole cells, offers high selectivity under mild conditions, but its broader application is often hindered by slow kinetics, equilibrium limitations, product inhibition and the processing of dilute streams in the presence of enzymes and cells. Bioreactive separation, defined as the simultaneous process of biocatalysis and separation, provides a powerful concept to overcome these barriers and therefore offers the potential of superiority over conventional processes. The current retro- and perspective paper, which is the result of an interdisciplinary workshop with academic and industry experts from the areas of biotechnology, fluid separations and process systems engineering, provides a focussed review, paired with a distinct novel definition of bioreactive separations that links to multifunctional reactors in chemical engineering and in situ product removal in biocatalysis. By establishing a common framework, this definition connects different research areas and enables systematic development. The current status of bioreactive separation processes is evaluated using SWOT analyses to identify key potentials and challenges. Based on this, a vision for 2040 is outlined, highlighting the need for advances in integration strategies, biocatalyst design, modelling and simulation, and applied research. Overall, a coordinated progress in these areas can significantly enhance the scalability and sustainability of bioprocessing.",
         "issn" : "0255-2701",
         
         "orcid" : "0000-0003-1045-8202",
         
         "doi" : "https://doi.org/10.1016/j.cep.2026.110787",
         
         "bibtexKey": "WALUGA2026110787"

      }
,
      {
         "type" : "Publication",
         "id"   : "https://puma.ub.uni-stuttgart.de/bibtex/28cf570ab77f8fafbce720774da22d9b0/rstraesser",         
         "tags" : [
            "myown","istbib","peerreviewed"
         ],
         
         "intraHash" : "8cf570ab77f8fafbce720774da22d9b0",
         "interHash" : "72bcabb273b65b759f0c0254d20b152a",
         "label" : "Bilinear Data-Driven Min-Max MPC: Designing Rational Controllers via Sum-of-squares Optimization",
         "user" : "rstraesser",
         "description" : "",
         "date" : "2026-03-30 15:52:03",
         "changeDate" : "2026-03-30 15:52:03",
         "count" : 3,
         "pub-type": "inproceedings",
         "booktitle": "64th IEEE Conference on Decision and Control (CDC)","publisher":"IEEE",
         "year": "2025", 
         "url": "", 
         
         "author": [ 
            "Yifan Xie","Julian Berberich","Robin Strässer","Frank Allgöwer"
         ],
         "authors": [
         	
            	{"first" : "Yifan",	"last" : "Xie"},
            	{"first" : "Julian",	"last" : "Berberich"},
            	{"first" : "Robin",	"last" : "Strässer"},
            	{"first" : "Frank",	"last" : "Allgöwer"}
         ],
         "pages": "1042-1047",
         "doi" : "10.1109/CDC57313.2025.11312878",
         
         "bibtexKey": "ist:xie25b"

      }
,
      {
         "type" : "Publication",
         "id"   : "https://puma.ub.uni-stuttgart.de/bibtex/2341fc1f6ecb0ce0f8b98320fd54f09f0/rstraesser",         
         "tags" : [
            "myown","amicus"
         ],
         
         "intraHash" : "341fc1f6ecb0ce0f8b98320fd54f09f0",
         "interHash" : "a0a03a19ca366f5e4de5c056800fe621",
         "label" : "Path-following model predictive control for autonomous e-scooters",
         "user" : "rstraesser",
         "description" : "",
         "date" : "2026-03-30 15:47:10",
         "changeDate" : "2026-03-30 15:47:10",
         "count" : 3,
         "pub-type": "inproceedings",
         "booktitle": "Proc. IEEE Intelligent Transportation Systems Conference (ITSC)","publisher":"IEEE",
         "year": "2025", 
         "url": "", 
         
         "author": [ 
            "David Meister","Robin Strässer","Felix Brändle","Marc Seidel","Benno Bassler","Nathan Gerber","Jan Kautz","Elena Rommel","Frank Allgöwer"
         ],
         "authors": [
         	
            	{"first" : "David",	"last" : "Meister"},
            	{"first" : "Robin",	"last" : "Strässer"},
            	{"first" : "Felix",	"last" : "Brändle"},
            	{"first" : "Marc",	"last" : "Seidel"},
            	{"first" : "Benno",	"last" : "Bassler"},
            	{"first" : "Nathan",	"last" : "Gerber"},
            	{"first" : "Jan",	"last" : "Kautz"},
            	{"first" : "Elena",	"last" : "Rommel"},
            	{"first" : "Frank",	"last" : "Allgöwer"}
         ],
         "pages": "1906-1911",
         "doi" : "10.1109/ITSC60802.2025.11423123",
         
         "bibtexKey": "ist:meister25b"

      }
,
      {
         "type" : "Publication",
         "id"   : "https://puma.ub.uni-stuttgart.de/bibtex/24388409c34817782daa3824d0bdd2ffb/dremy",         
         "tags" : [
            "myown"
         ],
         
         "intraHash" : "4388409c34817782daa3824d0bdd2ffb",
         "interHash" : "9e3436b51b0ae16ad31a2b283d5b8ef7",
         "label" : "Steering the Path with a Semi-Passive Robot to Break Post-Stroke Synergies",
         "user" : "dremy",
         "description" : "",
         "date" : "2026-03-23 16:53:38",
         "changeDate" : "2026-03-23 16:53:38",
         "count" : 2,
         "pub-type": "article",
         "journal": "IEEE Transactions on Biomedical Engineering",
         "year": "2026", 
         "url": "", 
         
         "author": [ 
            "Thomas E. Augenstein","C. David Remy","Shreeya Buddaraju","Edward S. Claflin","Chandramouli Krishnan"
         ],
         "authors": [
         	
            	{"first" : "Thomas E.",	"last" : "Augenstein"},
            	{"first" : "C. David",	"last" : "Remy"},
            	{"first" : "Shreeya",	"last" : "Buddaraju"},
            	{"first" : "Edward S.",	"last" : "Claflin"},
            	{"first" : "Chandramouli",	"last" : "Krishnan"}
         ],
         "pages": "1-11","abstract": "Objective: Abnormal coupling of elbow flexors with shoulder abductors\u2014the \u201Cflexor synergy\u201D\u2014is a common post stroke motor impairment that interferes with upper extremity function. Previous studies have shown that practicing elbow extension while loading shoulder abductors can improve independent joint control. However, these approaches often involve expensive and bulky equipment, limiting their use in clinic. SepaRRo is a semi-passive rehabilitation robot that uses brakes to generate training forces, reducing its cost relative to existing systems. SepaRRo can also load the shoulder abductors during horizontal planar reaching, suggesting that it could target the flexor synergy. However, it is unclear if training with a semi-passive robot can produce out-of-flexor synergy kinematic adaptations. Methods: Chronic stroke survivors (n = 15) with upper extremity impairment participated in a randomized, crossover-design experiment where they reached for a functional target with their more-impaired limb in two conditions: SepaRRo resisting their motion to the target (Resistance), and SepaRRo generating an additional lateromedial force to load their shoulder abductors (Steering). For each condition, we measured changes in reaching kinematics with motion capture equipment. Results: Following the Steering condition, participants demonstrated significantly greater shoulder abduction than the Pre-test and the Resistance condition (p0.112). Participants reduced their el bow extension following the Resistance condition (p = 0.018). Conclusion: Steering facilitated out-of-synergy adaptations that were not present following simple resistance. Significance: Conventional training methods may facilitate post-stroke synergies and impede recovery, while SepaRRo's steering forces may lead to improvements in independent joint control in stroke survivors.",
         "issn" : "1558-2531",
         
         "doi" : "10.1109/TBME.2026.3674710",
         
         "bibtexKey": "11435379"

      }
,
      {
         "type" : "Publication",
         "id"   : "https://puma.ub.uni-stuttgart.de/bibtex/25ea14734b9c7a1705878fd840a491442/marcseidel",         
         "tags" : [
            "myown","exc2075"
         ],
         
         "intraHash" : "5ea14734b9c7a1705878fd840a491442",
         "interHash" : "1ed92d7b7e991abaa535a84e439df3c2",
         "label" : "A Controller Synthesis Framework for Weakly-Hard Control Systems",
         "user" : "marcseidel",
         "description" : "",
         "date" : "2026-03-20 18:40:26",
         "changeDate" : "2026-03-23 12:58:20",
         "count" : 1,
         "pub-type": "inproceedings",
         "booktitle": "2026 IEEE 32nd Real-Time and Embedded Technology and Applications Symposium (RTAS)","publisher":"IEEE",
         "year": "2026", 
         "url": "https://arxiv.org/abs/2603.20146", 
         
         "author": [ 
            "Marc Seidel","Martina Maggio","Frank Allgöwer"
         ],
         "authors": [
         	
            	{"first" : "Marc",	"last" : "Seidel"},
            	{"first" : "Martina",	"last" : "Maggio"},
            	{"first" : "Frank",	"last" : "Allgöwer"}
         ],
         
         "preprinturl" : "https://arxiv.org/abs/2603.20146",
         
         "bibtexKey": "ist:seidel26b"

      }
,
      {
         "type" : "Publication",
         "id"   : "https://puma.ub.uni-stuttgart.de/bibtex/24864ccb34c23f7f35e3e6456d91df837/lmandl",         
         "tags" : [
            "rg-ml","myown","simliva","PN2-2","isd","EXC2075","updated"
         ],
         
         "intraHash" : "4864ccb34c23f7f35e3e6456d91df837",
         "interHash" : "02b47cd2b93c5cabeb39c9d2239071f5",
         "label" : "Physics-informed time-integrated DeepONet: Temporal tangent space operator learning for high-accuracy inference",
         "user" : "lmandl",
         "description" : "",
         "date" : "2026-03-18 08:57:48",
         "changeDate" : "2026-03-18 08:57:48",
         "count" : 3,
         "pub-type": "article",
         "journal": "Computer Methods in Applied Mechanics and Engineering",
         "year": "2026", 
         "url": "https://www.sciencedirect.com/science/article/pii/S0045782526001908", 
         
         "author": [ 
            "Luis Mandl","Dibyajyoti Nayak","Tim Ricken","Somdatta Goswami"
         ],
         "authors": [
         	
            	{"first" : "Luis",	"last" : "Mandl"},
            	{"first" : "Dibyajyoti",	"last" : "Nayak"},
            	{"first" : "Tim",	"last" : "Ricken"},
            	{"first" : "Somdatta",	"last" : "Goswami"}
         ],
         "volume": "455","pages": "118917","abstract": "Accurately modeling and inferring solutions to time-dependent partial differential equations (PDEs) over extended temporal horizons remains a core challenge in scientific machine learning. Traditional full rollout (FR) methods, predicting entire trajectories in a single pass, often fail to capture the causal dependencies inherent to dynamical systems and exhibit poor generalization outside the training time horizon. In contrast, autoregressive (AR) approaches, which evolve the system step by step, are prone to error accumulation, as predictions at each time step depend on potentially erroneous prior outputs. These shortcomings limit the long-term accuracy and reliability of both strategies. To overcome these issues, we introduce Physics-Informed Time-Integrated Deep Operator Network (PITI-DeepONet), an operator learning framework designed for stable and accurate long-term time evolution, well beyond the training time horizon. PITI-DeepONet employs a dual-output DeepONet architecture trained via either fully physics-informed or hybrid physics- and data-driven objectives. The training enforces consistency between the learned temporal derivative and its counterpart obtained via automatic differentiation. Rather than directly forecasting future states, the network learns the time-derivative operator from the current state, which is then integrated using classical time-stepping schemes - such as explicit Euler, fourth-order Runge-Kutta, second-order Adams-Bashforth-Moulton, or implicit Euler - to advance the solution sequentially in time. Additionally, the framework supports residual monitoring during inference to estimate prediction quality and flags when the learned temporal tangent becomes unreliable, e.g., outside the training domain. Applied to benchmark problems, PITI-DeepONet demonstrates enhanced accuracy and stability over extended inference time horizons when compared to traditional methods. Mean relative L2 errors reduced by 84% (versus FR) and 79% (versus AR) for the one-dimensional heat equation; by 87% (versus FR) and 98% (versus AR) for the one-dimensional Burgers equation; by 42% (versus FR) and 89% (versus AR) for the two-dimensional Allen-Cahn equation; and by 58% (vs. FR) and 61% (vs. AR) for the one-dimensional Kuramoto-Sivashinsky equation. By moving beyond classic FR and AR schemes, PITI-DeepONet paves the way for more reliable, long-term integration of complex, time-dependent PDEs.",
         "issn" : "0045-7825",
         
         "doi" : "https://doi.org/10.1016/j.cma.2026.118917",
         
         "bibtexKey": "MANDL2026118917"

      }
	  
   ]
}
