pwc-archive/papers-with-abstracts huggingface dataset:
TuneS: Patient-specific model-based optimization of contact configuration in deep brain stimulation
Authors: Anna Franziska Frigge, Lina Uggla, Elena Jiltsova, Markus Fahlström, Dag Nyholm, Alexander Medvedev
Date: 2024-12-19 00:00:00

Objective: The objective of this study is to develop and evaluate a systematic approach to optimize Deep Brain Stimulation (DBS) parameters, addressing the challenge of identifying patient-specific settings and optimal stimulation targets for various neurological and mental disorders. Methods: TuneS, a novel pipeline to predict clinically optimal DBS contact configurations based on predefined targets and constraints, is introduced. The method relies upon patient-specific models of stimulation spread and extends optimization beyond traditional neural structures to include automated, model-based targeting of streamlines. Results: Initial findings demonstrate that STN motor streamlines consistently receive a significant portion of the allocated stimulation volume, suggesting that a consistent portion of the stimulation should ideally focus on the STN motor streamlines. At the example of a small cohort of Parkinson's disease patients, the value of model-based contact predictions for assessing stimulation targets while observing constraints is demonstrated. Conclusion: TuneS shows promise as a research tool, enabling systematic assessment of DBS target effectiveness and facilitating constraint-aware optimization of stimulation parameters. Significance: The presented pipeline offers a pathway to improve patient-specific DBS therapies and contributes to the broader understanding of effective DBS targeting strategies.
A Model-free Biomimetics Algorithm for Deterministic Partially Observable Markov Decision Process
Authors: Yide Yu, Yue Liu, Xiaochen Yuan, Dennis Wong, Huijie Li, Yan Ma
Date: 2024-12-19 00:00:00
Tasks: Decision Making Under Uncertainty

Partially Observable Markov Decision Process (POMDP) is a mathematical framework for modeling decision-making under uncertainty, where the agent's observations are incomplete and the underlying system dynamics are probabilistic. Solving the POMDP problem within the model-free paradigm is challenging for agents due to the inherent difficulty in accurately identifying and distinguishing between states and observations. We define such a difficult problem as a DETerministic Partially Observable Markov Decision Process (DET-POMDP) problem, which is a specific setting of POMDP. In this problem, states and observations are in a many-to-one relationship. The state is obscured, and its relationship is less apparent to the agent. This creates obstacles for the agent to infer the state through observations. To effectively address this problem, we convert DET-POMDP into a fully observable MDP using a model-free biomimetics algorithm called BIOMAP. BIOMAP is based on the MDP Graph Automaton framework to distinguish authentic environmental information from fraudulent data. Thus, it enhances the agent's ability to develop stable policies against DET-POMDP. The experimental results highlight the superior capabilities of BIOMAP in maintaining operational effectiveness and environmental reparability in the presence of environmental deceptions when compared with existing POMDP solvers. This research opens up new avenues for the deployment of reliable POMDP-based systems in fields that are particularly susceptible to DET-POMDP problems.
High-Accuracy Model Predictive Control with Inverse Hysteresis for High-Speed Trajectory Tracking of Piezoelectric Fast Steering Mirror
Authors: Sen yang, Xiaofeng Li
Date: 2024-12-19 00:00:00
Tasks: Model Predictive Control

Piezoelectric fast steering mirrors (PFSM) are widely utilized in beam precision-pointing systems but encounter considerable challenges in achieving high-precision tracking of fast trajectories due to nonlinear hysteresis and mechanical dual-axis cross-coupling. This paper proposes a model predictive control (MPC) approach integrated with a hysteresis inverse based on the Hammerstein modeling structure of the PFSM. The MPC is designed to decouple the rate-dependent dual-axis linear components, with an augmented error integral variable introduced in the state space to eliminate steady-state errors. Moreover, proofs of zero steady-state error and disturbance rejection are provided. The hysteresis inverse model is then cascaded to compensate for the rate-independent nonlinear components. Finally, PFSM tracking experiments are conducted on step, sinusoidal, triangular, and composite trajectories. Compared to traditional model-free and existing model-based controllers, the proposed method significantly enhances tracking accuracy, demonstrating superior tracking performance and robustness to frequency variations. These results offer valuable insights for engineering applications.
Milestones at the Origin of Life
Authors: Søren Toxvaerd
Date: 2024-12-19 00:00:00

Living organisms have some common structures, chemical reactions and molecular structures. The organisms consist of cells with cell division, they have homochirality of protein and carbohydrate units, and metabolism, and genetics, and they are mortal. The molecular structures and chemical reactions underlying these features are common from the simplest bacteria to human beings. The origin of life is evolutionary with the emergence of a network of spontaneous biochemical reactions, and the evolution has taken place over a very long time. The evolution contains, however some "landmarks" and bottlenecks, which in a revolutionary manner directed the evolution, and the article tries to establish the order of these events. The article advocates that a possible order in the emergence of life is that the first milestone in prebiotic evolution is at the emergence of homochirality in proteins. The homochirality of peptides is, however, with instability and racemization which causes aging of the peptides and mortality. The metabolism and genetics are established through homochiral enzymes in the Earth's crust for $\approx$ 4 Gyr ago. Finally, the cells with cell division are established in the Hot Springs environment at the interface between the crust and the Hadean Ocean.
Towards a mathematical framework for modelling cell fate dynamics
Authors: Sean T. Vittadello, Léo Diaz, Yujing Liu, Adriana Zanca, Michael P. H. Stumpf
Date: 2024-12-19 00:00:00

An adult human body is made up of some 30 to 40 trillion cells, all of which stem from a single fertilized egg cell. The process by which the right cells appear to arrive in their right numbers at the right time at the right place -- development -- is only understood in the roughest of outlines. This process does not happen in isolation: the egg, the embryo, the developing foetus, and the adult organism all interact intricately with their changing environments. Conceptual and, increasingly, mathematical approaches to modelling development have centred around Waddington's concept of an epigenetic landscape. This perspective enables us to talk about the molecular and cellular factors that contribute to cells reaching their terminally differentiated state: their fate. The landscape metaphor is however only a simplification of the complex process of development; it for instance does not consider environmental influences, a context which we argue needs to be explicitly taken into account and from the outset. When delving into the literature, it also quickly becomes clear that there is a lack of consistency and agreement on even fundamental concepts; for example, the precise meaning of what we refer to when talking about a `cell type' or `cell state.' Here we engage with previous theoretical and mathematical approaches to modelling cell fate -- focused on trees, networks, and landscape descriptions -- and argue that they require a level of simplification that can be problematic. We introduce random dynamical systems as one natural alternative. These provide a flexible conceptual and mathematical framework that is free of extraneous assumptions. We develop some of the basic concepts and discuss them in relation to now `classical' depictions of cell fate dynamics, in particular Waddington's landscape.
Reservoir Computing Generalized
Authors: Tomoyuki Kubota, Yusuke Imai, Sumito Tsunegi, Kohei Nakajima
Date: 2024-11-23 00:00:00

A physical neural network (PNN) has both the strong potential to solve machine learning tasks and intrinsic physical properties, such as high-speed computation and energy efficiency. Reservoir computing (RC) is an excellent framework for implementing an information processing system with a dynamical system by attaching a trained readout, thus accelerating the wide use of unconventional materials for a PNN. However, RC requires the dynamics to reproducibly respond to input sequence, which limits the type of substance available for building information processors. Here we propose a novel framework called generalized reservoir computing (GRC) by turning this requirement on its head, making conventional RC a special case. Using substances that do not respond the same to identical inputs (e.g., a real spin-torque oscillator), we propose mechanisms aimed at obtaining a reliable output and show that processed inputs in the unconventional substance are retrievable. Finally, we demonstrate that, based on our framework, spatiotemporal chaos, which is thought to be unusable as a computational resource, can be used to emulate complex nonlinear dynamics, including large scale spatiotemporal chaos. Overall, our framework removes the limitation to building an information processing device and opens a path to constructing a computational system using a wider variety of physical dynamics.
Modularity, Hierarchical Flows and Symmetry of the Drosophila Connectome
Authors: Peter Grindrod, Renaud Lambiotte, Rohit Sahasrabuddhe
Date: 2024-12-02 00:00:00

This report investigates the modular organisation of the Central region in the Drosophila connectome. We identify groups of neurones amongst which information circulates rapidly before spreading to the rest of the network using Infomap. We find that information flows along pathways linking distant neurones, forming modules that span across the brain. Remarkably, these modules, derived solely from neuronal connectivity patterns, exhibit a striking left-right symmetry in their spatial distribution as well as in their connections. We also identify a hierarchical structure at the coarse-grained scale of these modules, demonstrating the directional nature of information flow in the system.
Testing linearity of spatial interaction functions à la Ramsey
Authors: Abhimanyu Gupta, Jungyoon Lee, Francesca Rossi
Date: 2024-12-19 00:00:00

We propose a computationally straightforward test for the linearity of a spatial interaction function. Such functions arise commonly, either as practitioner imposed specifications or due to optimizing behaviour by agents. Our conditional heteroskedasticity robust test is nonparametric, but based on the Lagrange Multiplier principle and reminiscent of the Ramsey RESET approach. This entails estimation only under the null hypothesis, which yields an easy to estimate linear spatial autoregressive model. Monte Carlo simulations show excellent size control and power. An empirical study with Finnish data illustrates the test's practical usefulness, shedding light on debates on the presence of tax competition among neighbouring municipalities.
Good Controls Gone Bad: Difference-in-Differences with Covariates
Authors: Sunny Karim, Matthew D. Webb
Date: 2024-12-19 00:00:00

This paper introduces the two-way common causal covariates (CCC) assumption, which is necessary to get an unbiased estimate of the ATT when using time-varying covariates in existing Difference-in-Differences methods. The two-way CCC assumption implies that the effect of the covariates remain the same between groups and across time periods. This assumption has been implied in previous literature, but has not been explicitly addressed. Through theoretical proofs and a Monte Carlo simulation study, we show that the standard TWFE and the CS-DID estimators are biased when the two-way CCC assumption is violated. We propose a new estimator called the Intersection Difference-in-differences (DID-INT) which can provide an unbiased estimate of the ATT under two-way CCC violations. DID-INT can also identify the ATT under heterogeneous treatment effects and with staggered treatment rollout. The estimator relies on parallel trends of the residuals of the outcome variable, after appropriately adjusting for covariates. This covariate residualization can recover parallel trends that are hidden with conventional estimators.
An Analysis of the Relationship Between the Characteristics of Innovative Consumers and the Degree of Serious Leisure in User Innovation
Authors: Taichi Abe, Yasunobu Morita
Date: 2024-12-18 00:00:00
Tasks: Marketing

This study examines the relationship between the concept of serious leisure and user innovation. We adopted the characteristics of innovative consumers identified by Luthje (2004)-product use experience, information exchange, and new product adoption speed-to analyze their correlation with serious leisure engagement. The analysis utilized consumer behavior survey data from the "Marketing Analysis Contest 2023" sponsored by Nomura Research Institute, examining the relationship between innovative consumer characteristics and the degree of serious leisure (Serious Leisure Inventory and Measure: SLIM). Since the contest data did not directly measure innovative consumer characteristics or serious leisure engagement, we established alternative variables for quantitative analysis. The results showed that the SLIM alternative variable had positive correlations with diverse product experiences and early adoption of new products. However, no clear relationship was found with information exchange among consumers. These findings suggest that serious leisure practice may serve as a potential antecedent to user innovation. The leisure career perspective of the serious leisure concept may capture the motivations of user innovators that Okada and Nishikawa (2019) identified.
Assessing the viability of non-light water reactor concepts for electricity and heat generation in decarbonized energy systems
Authors: Alexander Wimmers, Fanny Böse, Leonard Göke
Date: 2024-12-19 00:00:00

Recent pledges to triple global nuclear capacity by 2050 suggest a "nuclear renaissance," bolstered by reactor concepts such as sodium-cooled fast reactors, high-temperature reactors, and molten salt reactors. These technologies claim to address the challenges of today's high-capacity light-water reactors, i.e., cost overruns, delays, and social acceptance, while also offering additional non-electrical applications. However, this analysis reveals that none of these concepts currently meet the prerequisites of affordability, competitiveness, or commercial availability. We omit social acceptability. The cost analysis reveals optimistic FOAK cost assumptions of 5,623 to 9,511 USD per kW, and NOAK cost projections as low as 1,476 USD per kW. At FOAK cost, the applied energy system model includes no nuclear power capacity, and thus indicates that significant cost reductions would be required for these technologies to contribute to energy system decarbonization. In low-cost scenarios, reactors capable of producing high temperature heat become competitive with other low-carbon technologies. We conclude that, for reactor capacties to increase significantly, a focus on certain technology lines ist necessary. However, until a concept becomes viable and commercially available, policymakers should prioritize existing technologies to decarbonize energy systems.
Provincial allocation of China's commercial building operational carbon towards carbon neutrality
Authors: Yanqiao Deng, Minda Ma, Nan Zhou, Chenchen Zou, Zhili Ma, Ran Yan, Xin Ma
Date: 2024-12-19 00:00:00

National carbon peak track and optimized provincial carbon allocations are crucial for mitigating regional inequality within the commercial building sector during China's transition to carbon neutrality. This study proposes a top-down model to evaluate carbon trajectories in operational commercial buildings up to 2060. Through Monte Carlo simulation, scenario analysis is conducted to assess carbon peak values and the corresponding peaking year, thereby optimizing carbon allocation schemes both nationwide and provincially. The results reveal that (1) the nationwide carbon peak for commercial building operations is projected to reach 890 (+- 50) megatons of carbon dioxide (MtCO2) by 2028 (+- 3.7 years) in the case of the business-as-usual scenario, with a 7.87% probability of achieving the carbon peak under the decarbonization scenario. (2) Significant disparities will exist among provinces, with Shandong's carbon peak projected at 69.6 (+- 4.0) MtCO2 by 2029, approximately 11 times higher than Ningxia's peak of 6.0 (+- 0.3) MtCO2 by 2027. (3) Guided by the principle of maximizing the emission reduction potential, the optimal provincial allocation scheme reveals the top three provinces requiring the most significant reductions in the commercial sector: Xinjiang (5.6 MtCO2), Shandong (4.8 MtCO2), and Henan (4.7 MtCO2). Overall, this study offers optimized provincial carbon allocation strategies within the commercial building sector in China via dynamic scenario simulations, with the goal of hitting the carbon peak target and progressing toward a low-carbon future for the building sector.
The Role of Patents: Incentivizing Innovation or Hindering Progress?
Authors: Gaetan de Rassenfosse
Date: 2024-12-18 00:00:00
Tasks: International Law

This article examines the complex trade-offs inherent in the patent system, exploring whether patents truly incentivize innovation or inadvertently hinder progress. It traces the historical evolution of patent rights from their origins in Renaissance Venice to the modern framework enshrined in constitutional and international law. By balancing the exclusivity granted to inventors with the need for public access to knowledge, the article highlights how patents stimulate R&D investments while sometimes limiting follow-on innovation due to prolonged monopolies. It discusses the economic rationales for patent protection, such as increasing private returns to encourage invention, against criticisms that patents restrict the free flow of ideas essential for collective progress. Ultimately, the review argues that although patents are designed to reward creativity and secure economic benefits, they remain a contentious instrument whose benefits and limitations must be carefully weighed in policy debates.
A bibliometric analysis and scoping study to identify English-language perspectives on slums
Authors: Katharina Henn, Michaela Lestakova, Kevin Logan, Jakob Hartig, Stefanos Georganos, John Friesen
Date: 2024-12-18 00:00:00

Slums, informal settlements, and deprived areas are urban regions characterized by poverty. According to the United Nations, over one billion people reside in these areas, and this number is projected to increase. Additionally, these settlements are integral components of urban systems. We conducted a bibliometrical analysis and scoping study using the Web of Science Database to explore various perspectives on urban poverty, searching for scientific publications on the topic and providing details on the countries where the studies were conducted. Based on 3947 publications, we identify the extent to which domestic research organizations participate in studying urban poverty and which categories of science they investigate, including life sciences \& biomedicine, social sciences, technology, physical sciences, and arts & humanities. Thereby, we find that research on slums is often limited to specific countries, e.g. India, South Africa, Kenya, or Brazil. This focus is not necessarily correlated with the number of people living in slums. The scientific discourse is up to now predominantly shaped by medical and social sciences with few studies addressing technological questions. Finally, our analysis identifies several possible future directions for research on slums.
System and sub-system energy resilience during public safety power shutoffs (PSPS) in California -- An evidence-based argument
Authors: Daniel Thompson, Gianluca Pescaroli, Maham Furqan
Date: 2024-12-18 00:00:00

This study examines historical relationships between Public Safety Power Shutoffs (PSPS) events enacted by California's investor-owned utilities (IOUs), at the system and sub-system levels, along with other disruptions to macro electricity systems. This study contributes to understanding the balance between system-wide resilience goals, such as wildfire hazard mitigation, and sub-system-level priorities, such as minimizing the frequency and duration of localized disruptions. Focusing on circuit-level data from 2018 to 2023 as a proxy for sub-systems, we evaluate differences in outage frequency, duration, and customer impact across three major IOUs in California. Results highlight a differentiation between 'higher impact' de-energization events, which have occurred less frequently, and circuits impacted frequently but with lower customer or duration impacts. Study outcomes suggest that resilience, from the perspective of PSPS events, may be more temporal, which in this case is driven by infrastructure and planning investments by IOUs. Future work aims to incorporate socio-demographic factors, including urban-rural divide, to identify further opportunities to enhance resilience at the circuit and sub-circuit levels.
The Emergence of Strategic Reasoning of Large Language Models
Authors: Dongwoo Lee, Gavin Kader
Date: 2024-12-17 00:00:00

Although large language models (LLMs) have demonstrated strong reasoning abilities in structured tasks (e.g., coding and mathematics), it remains unexplored whether these abilities extend to strategic multi-agent environments. We investigate strategic reasoning capabilities -- the process of choosing an optimal course of action by predicting and adapting to others' actions -- of LLMs by analyzing their performance in three classical games from behavioral economics. We evaluate three standard LLMs (ChatGPT-4, Claude-2.1, Gemini 1.5) and three specialized reasoning LLMs (GPT-o1, Claude-3.5-Sonnet, Gemini Flash Thinking 2.0) using hierarchical models of bounded rationality. Our results show that reasoning LLMs exhibit superior strategic reasoning compared to standard LLMs (which do not demonstrate substantial capabilities), and often match or exceed human performance. Since strategic reasoning is fundamental to future AI systems (including Agentic AI and Artificial General Intelligence), our findings demonstrate the importance of dedicated reasoning capabilities in achieving effective strategic reasoning.
Digital Transformation in Switzerland: The Current State and Expectations
Authors: Johannes Lehmann, Michael Beckmann
Date: 2024-12-17 00:00:00
Tasks: Descriptive, Self-Learning

This paper provides a comprehensive, descriptive overview of the current state of digital transformation in the Swiss economy and delineates areas that businesses should keep an eye on. Key findings illustrate that even established technologies are not universally adopted, that companies tend to overestimate their technological status compared to their competitors, and that it is important to have the appropriate technological know-how when introducing new technologies. In addition, companies expect changes in their work processes and employment conditions in connection with the digital transformation. Specifically, work tasks are expected to become more complex, diverse and varied. Employees' knowledge acquisition will gain in importance, especially in the form of formal further training and self-learning. Employees will also be more autonomous in making decisions about their jobs and working hours.