Pseudomonas aeruginosa, a main cause of human infection, can gain resistance to the antibiotic aztreonam through a mutation in NalD, a transcriptional repressor of cellular efflux. Here we combine computational analysis of clinical isolates, transcriptomics, metabolic modeling and experimental validation to find a strong association between NalD mutations and resistance to aztreonam-as well as resistance to other antibiotics-across P. aeruginosa isolated from different patients. A detailed analysis of one patient's timeline shows how this mutation can emerge in vivo and drive rapid evolution of resistance while the patient received cancer treatment, a bone marrow transplantation, and antibiotics up to the point of causing the patient's death. Transcriptomics analysis confirmed the primary mechanism of NalD action-a loss-of-function mutation that caused constitutive overexpression of the MexAB-OprM efflux system-which lead to aztreonam resistance but, surprisingly, had no fitness cost in the absence of the antibiotic. We constrained a genome-scale metabolic model using the transcriptomics data to investigate changes beyond the primary mechanism of resistance, including adaptations in major metabolic pathways and membrane transport concurrent with aztreonam resistance, which may explain the lack of a fitness cost. We propose that metabolic adaptations may allow resistance mutations to endure in the absence of antibiotics and could be targeted by future therapies against antibiotic resistant pathogens.

As the semiconductor process technology continuously scales down, circuit delay variations due to manufacturing and environmental variations become more and more serious. These delay variations are hardly predictable and thus require an additional design margin, which impedes the chance to reduce the area and power consumption of a chip. One of the best solutions to alleviate this problem is to measure circuit delays at run time and control the supply voltage accordingly through a closed-loop dynamic voltage and frequency scaling (DVFS) scheme. The key issue of this scheme is the delay mismatch between the monitoring circuit and the target block. A large delay mismatch might lose the advantage of the closed-loop DVFS. It becomes much worse as a circuit block operates in wider voltage range, from near-threshold voltage to super-overdrive voltage. This paper proposes novel delay monitoring systems with multiple generic monitors for wide voltage range operation, which provide a better delay correlation between the monitoring circuit and the target block compared to conventional monitoring approaches. The proposed approaches reduce the maximum error by up to 91% for a popular processor core in a 14-nm FinFET process technology, thereby bring a decrease of design margin, lower-power, and/or lower-cost design.

Abstract We propose a physics‐inspired simulation framework that expresses visual effects of flowing water frozen in glaze or directional icicles. The proposed ice model considers the direction of the water flow, which affects the growth of icicles. Water dynamics are computed using a conventional particle‐based simulation. Ice glaze and directional icicles are generated by incorporating our freezing solver. To determine whether a water particle is converted into ice or remains liquid, we compute the nucleation energy based on the humidity and water flow. The humidity is approximated as a virtual water film on object surfaces. The water flow is incorporated by introducing a growth direction vector to guide the direction of icicle growth. Ice‐generating regions can be controlled using 3‐D modeling tools such as Autodesk Maya or 3DS Max. Experiments showed that a realistic ice glaze was created on the surfaces of objects and that icicles grew in the direction of the water flow.

Abstract Simulating the clumping and stiffness of wet hair or fur is a challenging problem. The dynamics of wet hair or fur are characterized by clumping and stiffness at the tip, which can be seen clearly in running animals or headbanging scenes. Existing animation methods address these phenomena within preset scenarios. However, there is no consensus on a method for depicting the details of wet hair. This paper therefore proposes a new method for modeling the clumping and stiffness of wet hair or fur. Previous studies have focused on modeling the absorption of water into hair or fur, whereas this paper considers a realistic simulation of wet hair. Unlike dry hair strands, wet hair strands adjacent to one another are subject to a clumping force, gathering together and becoming more stiff as the saturation level of water increases. The proposed method builds on a surface‐tension model based on smoothed particle hydrodynamics to simulate the clumping force and to adjust the hair elasticity via stiffness constraints. The method gives realistic simulations of wet hair by maintaining the clumping force of the wet hair during movement and by simulating the stiffness of the hair in line with its water‐saturation level.

This brief presents an efficient approach to statistical static timing analysis (STA), which estimates the system delay of statistical STA through deterministic STA. In statistical STA, the system delay is modeled as a function of random variables, so it is commonly expressed as a probability density function (pdf). Therefore, to estimate the system delay of statistical STA through deterministic STA, we must find the relationship between an arbitrary percentile point on the pdf of the system delay and the gate delays used in deterministic STA. However, there is no closed-form equation for an arbitrary percentile point on the pdf of the system delay, we derive an analytic expression for the upper bound of an arbitrary percentile point on the pdf of the system delay. This allows us to obtain the corresponding gate delays that are used to estimate the upper bound of the percentile point on the pdf of the system delay through deterministic STA. Experimental results indicate that the percentile point on the pdf of the system delay obtained with statistical STA is strictly bounded by the upper bound of the percentile point obtained with the proposed method within an average 6% difference range.

In LTE, random access has a large impact on the overall system performance such as call setup delays and handover delays. Therefore, optimal configuration of RACH factors such as a resource configuration index, a transmission power control parameter, a backoff parameter, and the preamble split is critical from the system performance point of view. In this paper, we focus on the preamble split out of all above things to improve RACH performance. Three history-based preamble split schemes are proposed and their performance is evaluated in terms of random access success rate. Our proposed schemes have little overhead and can be easily combined with other RACH optimization schemes.

This paper focuses on statistical optimization and, more specifically, timing yield (TY)-constrained optimization. For cell replacement in timing-constrained optimization, we need an indicator that examines whether or not a timing violation occurs and gives the available timing for a gate. In deterministic optimization, the timing slack is used for this indicator. Although there is an analogous concept of TY slack in statistical optimization, it has not been well utilized. This paper proposes an effective way to use the TY slack for successful statistical optimization. To achieve this, we present an efficient method to calculate the TY slacks of gates and a strategy that uses timing resources for effective statistical optimization. Based on this work, we propose a novel statistical leakage minimization method that uses the TY slack for a gate change metric. The use of TY-based metrics that are appropriate for statistical design ensures that our method has a better optimization performance at a higher speed. Experimental results on ISCAS-85 benchmark circuits show that the leakage minimization method reduces leakage by 25.2% compared to the statistical benchmark method. In addition, our method has a better runtime when the number of gates is high.

DIGITAL IDEA specializes in creating state-of-the-art visual effects for feature films, both domestic and international. Our slate of films include commercial successes such as Marineboy, Scam, Castaway on the Moon, Take Off, Best Seller, Influence, and Moss. The services we provided for these feature films span over a wide range from digital matte painting, digital environments, to FX simulation, face replacement, and pre-visualization. Digital matte painters created photo-realistic backdrops, virtual environments, and set extensions, our R&D team simulated natural phenomenon such as liquid, fire, smoke, cloth, and fur, and our pre-viz team created animated storyboards to predict and examine characters' movements, angles, camera moves, timing, and focal lengths. The video clip presented at SIGGRAPH ASIA 2010's Computer Animation Festival highlights DIGITAL IDEA's VFX work on feature films released since 2009. Here we show before and after shots that illustrate how a director's imagination becomes a reality with the right tools and right talent: how a previsualization shapes the final shot, and how impossible stunts and camera moves are made possible with the aid of computer graphics.

This paper presents a novel method for full-chip statistical leakage estimation that considers the impact of process variation. The proposed method considers the correlations among leakage currents in a chip and the state dependence of the leakage current of a cell for an accurate analysis. For an efficient addition of the cell leakage currents, we propose the virtual-cell approximation (VCA), which sums cell leakage currents sequentially by approximating their sum as the leakage current of a single virtual cell while preserving the correlations among leakage currents. By the use of the VCA, the proposed method efficiently calculates a full-chip leakage current. Experimental results using ISCAS benchmarks at various process variation levels showed that the proposed method provides an accurate result by demonstrating average leakage mean and standard deviation errors of 3.12% and 2.22%, respectively, when compared with the results of a Monte Carlo (MC) simulation-based leakage estimation. In efficiency, the proposed method also demonstrated to be 5000 times faster than MC simulation-based leakage estimations and 9000 times faster than the Wilkinson's method-based leakage estimation.