When do ventures break path dependence? Evidence from financial and technological success of serial entrepreneurs

This study examines ventures' path dependence and path breaking in the context of serial entrepreneurship. While prior entrepreneurial experience is known to cause ventures' path dependence, little is known about how different types of experience, especially financial versus technological, shape it. Specifically, we investigate how the financial and technological success of serial entrepreneurs' prior ventures influences their subsequent ventures' path-breaking behavior singly and jointly. We find that while the financial success of prior ventures facilitates subsequent ventures' path-dependent propensity, technological success leads subsequent ventures to break the path by entering new technology domains different from those of prior ventures. The relationship between prior ventures' financial success and subsequent ventures' path breaking is contingent on prior ventures' technological success. Under the condition of prior ventures' technological success, the negative effect of financial success on path breaking weakens. We corroborate our hypotheses using Crunchbase for entrepreneur and venture data worldwide from 1967 to 2018 and patent data from USPTO. Our findings have important implications for the source of ventures' path-breaking behaviors, highlighting the role of the entrepreneurs' technological success in prior ventures in disentangling their subsequent ventures from path dependence.

Interfacial spin-state engineering through lattice-distorted transition metal oxides heterostructure enables low-voltage and durable anion-exchange-membrane water electrolysis

Transition metal oxides (TMOs) exhibit electrocatalytic activity intrinsically tied to their electron spin states, yet precise spin-state regulation without sacrificing structural integrity presents a persistent challenge. Here we introduce a hetero-lattice engineering approach to achieve spin-state modulation in TMOs through lattice distortion. We demonstrate a lattice-distorted Co3O4/MoO3 heterostructure (Co-O-Mo|H) that effectively converts low-spin Co3 + [e(g)(0)t(2)(g)(6)] to high-spin Co3+ [e(g)(2)t(2)(g)(4)]. This electronic reconfiguration enables strengthened *OH adsorption while promoting efficient *OOH desorption, resulting in exceptional oxygen evolution reaction performance with a low overpotential of 211 mV at 10 mA cm(-2), outperforming benchmark RuO2 (321 mV). Simultaneously, the engineered Co-O-Mo interface creates highly active hydrogen evolution sites, delivering ultralow overpotentials of 40/151 mV at current densities of 10/100 mA cm(-2), respectively, surpassing commercial Pt/C (52/170 mV). Integrated into an anion-exchange membrane electrolyzer, the Co-O-Mo|H-based system demonstrates exceptional durability (>200 h at 10 mA cm(-2)) and superior performance, achieving low cell voltages of 1.48/1.57 V at 10/100 mA cm(-2), significantly lower than the 1.58 V and 1.68 V required by RuO2 & Vert;20 % Pt/C. These findings establish a new paradigm for spin-state engineering through lattice distortion in transition metal oxides, offering a strategic pathway toward developing economically viable and robust hydrogen production technologies.

In-vivo monitoring of macrophage mitochondrial pH dynamics in zebrafish using an ultrasensitive and water-soluble targeted fluorescent sensor

Mitochondrial pH has a key role in cellular metabolism and also may be a sign of pathology. Thus, closely monitoring of minor changes in this value is critical in biological research. However, it proves difficult due to a lack of availability of appropriate probes. A water-soluble fluorescent mitochondrial targeting probe TPP-MpH is reported. The probe has a hemicyanin-based fluorophore, a triphenylphosphonium (TPP) group for mitochondrial targeting and a PEG group for increased water solubility and biocompatibility. The experimental results show that TPP-MpH reflects ultrasensitive responses to different pH values. The experimental results with cell and zebrafish models indicate that TPP-MpH is highly responsive and specific to pH levels, showing excellent stability and minimal toxicity. Confocal fluorescence imaging confirms that TPP-MpH effectively targets mitochondria and accurately monitors their pH fluctuations. To our astonishment, at pH 8.0 and 9.0, TPP-MpH showed expression in specific cells in the gallbladder and liver region of the zebrafish model, these cells are predominantly mitochondria-rich cells that are involved in the uptake of Na+ ions. Hence, these findings open the door to use this probe for further and deep biological studies.

Creating text-based AI clones of myself: Exploring perceptions, development strategies, and challenges

AI clones are evolving to include digital representations of real world individuals as chatbots. While often used to replicate famous figures, as the technology becomes more accessible, it is crucial to understand whether everyday users would create their own clones and how they interact with them. In this study, within the scope of AIgenerated personas and their role in representing users’ needs and identities, we focus on personas that directly reflect the qualities of real humans. We define this as AI self clones—conversational AI representations that reflect their human creators—and examine how creators construct and engage with them. We conducted a 7-day study in which participants (N=12) created and interacted with their text based AI self clones using CloneBuilder, a web-based authoring interface for configuring and tuning AI self clones. The system enables individuals to create AI representations that encapsulate their unique personality, values, and interaction style. Our findings reveal that each participant developed a clone tailored to their personal circumstances. As the participants iteratively refined and tested their clone, their direction and expectations of AI clones evolved from performing specific roles to becoming entities that facilitated self exploration and relationship formation. Unexpected responses from the clone prompted self reflection and identity questioning. Overall, this paper explores the motivations for creating these clones, the strategies participants use to build and refine them, and the moments of emotional connection and break out experiences that emerge during the crafting process, along with key design implications, challenges, and ethical considerations in developing AI self clones.

AIPO: Automatic Instruction Prompt Optimization by model itself with "Gradient Ascent

Large language models (LLMs) can perform a variety of tasks such as summarization, translation, and question answering by generating answers with user input prompt. The text that is used as input to the model, including instruction, is called input prompt. There are two types of input prompt: zero-shot prompting provides a question with no examples, on the other hand, few-shot prompting provides a question with multiple examples. The way the input prompt is set can have a big impact on the accuracy of the model generation. The relevant research is called prompt engineering. Prompt engineering, especially prompt optimization is used to find the optimal prompts optimized for each model and task. Manually written prompts could be optimal prompts, but it is time-consuming and expensive. Therefore, research is being conducted on automatically generating prompts that are as effective as human-crafted ones for each task. We propose Automatic Instruction Prompt Optimization (AIPO), which allows the model to generate an initial prompt directly through instruction induction when given a task in a zero-shot setting and then improve the initial prompt to optimal prompt for model based on the "gradient ascent" algorithm. With the final prompt generated by AIPO, we achieve more accurate generation than manual prompt on benchmark datasets regardless of the output format.

A Kronecker congruence relation for modular functions of higher level and genus

Let j be the elliptic modular function, a weakly holomorphic modular function for SL2(Z). Weber showed that for each prime p the modular polynomial 'T'p(x, y) of j satisfies what is known as the Kronecker congruence relation 'T'p(x, y) equivalent to (xp-y)(x-yp) (mod pZ[x, y]). We give a generalization of this congruence applicable to certain weakly holomorphic modular functions of higher level in terms of integrality over Z[j]. (c) 2025 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

Advancing indigenous peoples' sovereignty in international environmental treaties: a call for exception clauses in international trade and investment law

Indigenous peoples face persistent threats from extractive industries and state-led development, often without sufficient legal safeguards. International environmental treaties, while referencing Indigenous rights, typically use non-binding language that enables weak or selective implementation. This paper aims to identify how treaty design can more effectively protect existing domestic Indigenous protections. Drawing on trade and investment law examples-such as New Zealand's Treaty of Waitangi clauses and Colombia's reservation lists-it argues for systematically incorporating explicit carve-out mechanisms into environmental and human rights treaties. Naming Indigenous groups and domestic laws within treaty texts can strengthen legal certainty and shield protections from erosion. The paper concludes with recommendations for negotiators, including legal audits, inter-ministerial coordination, and capacity-building to help states, particularly in the Global South, design carve-outs that reinforce Indigenous sovereignty.

Evaluation of combustion models and reaction mechanisms to predict NOx and CO emissions from densely distributed lean-premixed multinozzle CH4/H2/air flames

This work explores the importance of reaction mechanisms and combustion models on the flame length and emission characteristic prediction by computational fluid dynamics (CFD) simulations of a complex multinozzle combustor configuration, operating under CH4/H2 blend variations. For the study, both RANS and LES turbulence models are explored. Test data used for the analysis is taken from work published by KAIST University, on the investigation of combustion dynamics and NOx/CO emissions from lean-premixed multinozzle CH4/H2 blended flames. The combustion domain consists of densely distributed small-scale multitube injectors called Micromixer nozzles. This setup provides insights into the collective behavior of small-scale multinozzle flames and resultant emission rates. Test data for different inlet compositions, keeping a thermal power condition of 78 kW, are considered for evaluation. Results from simulations for OH*chemiluminescence, OH concentrations, NOx, and CO emissions are compared against the test data. Reduce model fuel library (MFL) mechanism with relevant NOx pathways along with flamelet generated manifold (FGM) model found to predict the trend of flame length and emissions concentration with change in fuel composition reasonably well, compared to detailed chemistry combustion model, as well as test data. However, for capturing the impact of local nonunity Lewis number effects, the detailed chemistry model is found to be better for the low turbulent flow conditions, as considered in the referred experimental data.

A Multi-View Attention-Based Encoder-Decoder Framework for Clustered Traveling Salesman Problem

Many autonomous mobile robot path planning scenarios require servicing grouped delivery points. Such clustered routing problems are naturally formulated as the clustered traveling salesman problem (CluTSP), which comprises two interdependent subproblems: global inter-cluster routing to determine the order of cluster visits and local intra-cluster routing to optimize paths within each cluster. Existing approaches often solve these subproblems separately, which leads to suboptimal solutions due to limited information sharing between global and local decisions and requires long computation times. To address these limitations, we propose a unified deep reinforcement learning framework to obtain a powerful and flexible CluTSP routing agent based on a novel multi-view attention-based encoder-decoder framework. Our graph neural network-based dual encoder structure effectively captures both global and local routing contexts, and the collaborative decoder generates the overall robot trajectory from a global perspective. Our novel and efficient architecture enables solving both subproblems via unified one-shot construction without addressing each problem separately. Extensive experiments demonstrate that our approach significantly outperforms existing decomposition-based and learning-based methods.

Experimental realization of acoustic logic gates based on valley-locked interface states in two-dimensional metamaterials

Acoustic logic gates have recently garnered extensive attention for their potential in low-energy and high-efficiency information processing. However, their development still faces several critical challenges, including limited robustness, insufficient experimental validation, and restricted functional diversity. To address these issues, we design and demonstrate, both numerically and experimentally, an acoustic metamaterial platform based on valley-locked waveguides that supports a series of logic functions. The proposed metamaterial enables reliable realization of basic logic operations, including AND, OR, and XOR, within a certain frequency bandwidth, using a single configuration. For more complex logic functions, including NOR, XNOR, and NAND, flexible operation at any selected frequency within a specific bandwidth is achieved by introducing a bias input and combining two trident-shaped waveguides. Furthermore, the robustness of the proposed metamaterial systems is experimentally verified under the presence of structural defects, confirming the feasibility of valley-locked waveguides for logic implementation. These findings open new avenues for the development of reconfigurable and scalable acoustic computing architectures.