Search for: All records

We give two characterizations of Pareto optimality via “near” weighted utilitarian welfare maximization. One characterization sequentially maximizes utilitarian welfare functions using a finite sequence of nonnegative and eventually positive welfare weights. The other maximizes a utilitarian welfare function with a certain class of positive hyperreal weights. The social welfare ordering represented by these “near” weighted utilitarian welfare criteria is characterized by the standard axioms for weighted utilitarianism under a suitable weakening of the continuity axiom.

 

We consider the problem of establishing that a program-synthesis problem is unrealizable (i.e., has no solution in a given search space of programs). Prior work on unrealizability has developed some automatic techniques to establish that a problem is unrealizable; however, these techniques are all black-box , meaning that they conceal the reasoning behind why a synthesis problem is unrealizable. In this paper, we present a Hoare-style reasoning system, called unrealizability logic for establishing that a program-synthesis problem is unrealizable. To the best of our knowledge, unrealizability logic is the first proof system for overapproximating the execution of an infinite set of imperative programs. The logic provides a general, logical system for building checkable proofs about unrealizability. Similar to how Hoare logic distills the fundamental concepts behind algorithms and tools to prove the correctness of programs, unrealizability logic distills into a single logical system the fundamental concepts that were hidden within prior tools capable of establishing that a program-synthesis problem is unrealizable. 

Biosignals from wearable sensors have shown great potential for capturing environmental distress that pedestrians experience from negative stimuli (e.g., abandoned houses, poorly maintained sidewalks, graffiti, and so forth). This physiological monitoring approach in an ambulatory setting can mitigate the subjectivity and reliability concerns of traditional self-reported surveys and field audits. However, to date, most prior work has been conducted in a controlled setting and there has been little investigation into utilizing biosignals captured in real-life settings. This research examines the usability of biosignals (electrodermal activity, gait patterns, and heart rate) acquired from real-life settings to capture the environmental distress experienced by pedestrians. We collected and analyzed geocoded biosignals and self-reported stimuli information in real-life settings. Data was analyzed using spatial methods with statistical and machine learning models. Results show that the machine learning algorithm predicted location-based collective distress of pedestrians with 80% accuracy, showing statistical associations between biosignals and the self-reported stimuli. This method is expected to advance our ability to sense and react to not only built environmental issues but also urban dynamics and emergent events, which together will open valuable new opportunities to integrate human biological and physiological data streams into future built environments and/or walkability assessment applications.

 

Proteins from Sulfolobus solfataricus (S. solfataricus), an extremophile, are active even at high temperatures. The single-stranded DNA (ssDNA) binding protein of S. solfataricus (SsoSSB) is overexpressed to protect ssDNA during DNA metabolism. Although SsoSSB has the potential to be applied in various areas, its structural and ssDNA binding properties at high temperatures have not been studied. We present the solution structure, backbone dynamics, and ssDNA binding properties of SsoSSB at 50 °C. The overall structure is consistent with the structures previously studied at room temperature. However, the loop between the first two β sheets, which is flexible and is expected to undergo conformational change upon ssDNA binding, shows a difference from the ssDNA bound structure. The ssDNA binding ability was maintained at high temperature, but different interactions were observed depending on the temperature. Backbone dynamics at high temperature showed that the rigidity of the structured region was well maintained. The investigation of an N-terminal deletion mutant revealed that it is important for maintaining thermostability, structure, and ssDNA binding ability. The structural and dynamic properties of SsoSSB observed at high temperature can provide information on the behavior of proteins in thermophiles at the molecular level and guide the development of new experimental techniques. 

Monolithic 3D (M3D) integration provides massive vertical integration through the use of nanoscale inter-layer vias (ILVs). However, high integration density and aggressive scaling of the inter-layer dielectric make ILVs especially prone to defects. We present a low-cost built-in self-test (BIST) method that requires only two test patterns to detect opens, stuck-at faults, and bridging faults (shorts) in ILVs. We also propose an extended BIST architecture for fault detection, called Dual-BIST, to guarantee zero ILV fault masking due to single BIST faults and negligible ILV fault masking due to multiple BIST faults. We analyze the impact of coupling between adjacent ILVs arranged in a 1D array in block-level partitioned designs. Based on this analysis, we present a novel test architecture called Shared-BIST with the added functionality of localizing single and multiple faults, including coupling-induced faults. We introduce a systematic clustering-based method for designing and integrating a delay bank with the Shared-BIST architecture for testing small-delay defects in ILVs with minimal yield loss. Simulation results for four two-tier M3D benchmark designs highlight the effectiveness of the proposed BIST framework.