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Previous studies have shown that occupants' core body temperature (CBT) increases dynamically and cognitive performance declines under high indoor temperatures. On the other hand, light illuminance and correlated color temperature (CCT) have been widely studied for their physiological and cognitive impacts within thermal comfort ranges. However, light spectral power distribution (SPD) remains underexplored. This study examined the effects of two metameric white lights - identical in illuminance and CCT but differing in spectral composition (blue-enriched vs. red-enriched) - on CBT responses and cognitive performance during heat exposure. Eight college students were exposed to each lighting condition in a climate chamber maintained at 38 °C for 1h. CBT was continuously monitored using a CardioWatch, and subjects completed cognitive tasks assessing attention, executive function, memory, and emotion. Results showed that the increase rate of CBT was smaller under blue-enriched white light than under red-enriched white light, providing initial experimental evidence that metameric white light can modulate thermo-physiological responses under heat stress. No significant differences in cognitive performance were detected between lighting conditions. However, subjects exposed to red-enriched white light performed better on the learning and episodic memory task and more frequently selected 'Happy' in the emotional bias task; medium effect sizes indicated potential practical importance. These cognitive outcomes may have been influenced by a systematic order effect. Overall, the findings highlighted the importance of light SPD as a non-visual environmental factor for modulating thermo-physiological responses and potentially cognitive performance under heat stress. Future research should adopt counterbalanced designs, larger sample sizes, various high temperatures, and more diverse populations, and validate findings in real-world workspace across seasons. 

This paper focuses on the motion planning problem for the systems exhibiting both continuous and discrete behaviors, which we refer to as hybrid dynamical systems. First, the motion planning problem for hybrid systems is formulated using the hybrid equation framework, which is general to capture most hybrid systems. Second, a propagation algorithm template is proposed that describes a general framework to solve the motion planning problem for hybrid systems. Third, a rapidly-exploring random trees (RRT) implementation of the proposed algorithm template is designed to solve the motion planning problem for hybrid systems. At each iteration, the proposed algorithm, called HyRRT, randomly picks a state sample and extends the search tree by flow or jump, which is also chosen randomly when both regimes are possible. Through a definition of concatenation of functions defined on hybrid time domains, we show that HyRRT is probabilistically complete, namely, the probability of failing to find a motion plan approaches zero as the number of iterations of the algorithm increases. This property is guaranteed under mild conditions on the data defining the motion plan, which include a relaxation of the usual positive clearance assumption imposed in the literature of classical systems. The motion plan is computed through the solution of two optimization problems, one associated with the flow and the other with the jumps of the system. The proposed algorithm is applied to an actuated bouncing ball system and a walking robot system so as to highlight its generality and computational features. 

Not AvailableAs applications demand more bandwidth, the “memory wall” problem becomes increasingly severe. Therefore, the processing-in-memory (PIM) architecture has attracted significant research interest due to its ability to execute instructions offloaded by the processor. Existing works on PIM architectures are classified into two categories: regional offloading, where all instructions within a programmer-specified code region are offloaded, and selective offloading, where only instructions of interest are offloaded via hardware support. However, PIM architectures pose the amplified in-PIM traffic overhead challenge that endangers the performance of PIM and degrades the performance of the entire system. To address the challenge, we propose a PIM architecture, called fast PIM (fPIM), which integrates the PIM cache within each Channel Controller to optimize the data flow within the PIM. This design cooperates with the Processing Unit Load-balancer and Behavior-based Offloader to achieve high execution efficiency. To evaluate fPIM, we perform extensive experiments, and the results show that fPIM reduces the workload finish time by up to 88.6%, 87.5%, and 79.6% (with an average of 68.7%, 66.2%, and 59.8%), compared to three state-of-the-art PIM designs, PEI, Fafnir, and SpaceA, respectively. 

Abstract Laser ablation is a process that bears both fundamental physics interest and has wide industrial applications. For decades, the lack of probes on the relevant time and length scales has prevented access to the highly nonequilibrium phase decomposition processes triggered by laser excitation. In this study, a close integration of time-resolved probing by intense femtosecond X-ray pulses with large-scale atomistic modeling has yielded unique insights into the ablation dynamics of thin gold films irradiated by femtosecond laser pulses. The emergence and growth of nanoscale density heterogeneities in the expanding ablation plume, predicted in the simulations, are mapped to the rapid evolution of distinct small angle diffraction features. This mapping enables identification of the characteristic signatures of different phase decomposition processes occurring simultaneously in the plume, which are driven by photomechanical and thermodynamic driving forces. Beyond the specific insights into the ablation phenomenon, this study demonstrates the power of joint X-ray probing and atomistic modeling of material dynamics under extreme conditions of thermal and mechanical nonequilibrium. 

Climate change leads to frequent extreme temperature events, making cities vulnerable to severe heatwaves. Therefore, this study aims to provide a systematic and overarching review of the urban planning and design policy interventions for heatwave management. This study used a series of key terms to search for relevant studies in three databases, including Web of Science, ScienceDirect, and Wiley, and then identified 28 articles published between 2007 and 2023 after several inclusion and exclusion criteria. After a systematic review, 15 policy interventions for heatwave management were summarized from the built environment level and building level. Cooling mechanisms and the scope of application were discussed. The results of this study provide policymakers with comprehensive guidance on sustainable urban design and planning for heatwave management.