Miracle-dz/UniFAR-FTUs huggingface dataset:
ClusterNet: Routing Congestion Prediction and Optimization Using Netlist Clustering and Graph Neural Networks

Accurately predicting routing congestion caused by netlist topology is essential as circuit designs become increasingly complex. To correctly predict routing congestion, the use of graph neural networks (GNNs) has gained great attention. However, existing GNN-based methods have limitations in capturing crucial netlist information and effectively representing complex topologies. In this work, we propose a novel approach, ClusterNet, to predict routing congestion caused by netlist topology. Our approach leverages netlist clustering to overcome these limitations. We first divide the netlist into highly connected clusters using the Leiden algorithm, enabling an analysis of the local netlist topology. We then predict routing congestion by exploiting GNNs to generate cluster embeddings that capture the detailed netlist topology. In addition, we introduce a cluster padding method that utilizes the trained model to mitigate routing congestion. By applying the proposed ClusterNet, we can accurately predict and optimize routing congestion from specific cluster topologies. Our experimental results demonstrated improved prediction performance, with a mean absolute error of 0.056 and an R2 score of 0.669. Furthermore, routing congestion optimization significantly improved the total negative slack and reduced the number of failing endpoints by 14.5% and 9.9%, respectively.
Communication Solutions for LVDC Island Networks

Production and generation of electrical power is evolving to more environmental friendly technologies and schemes. Pushed by the increasing cost of fossil fuels, the operational costs of producing electrical power with fossil fuels and the effect in the environment, like pollution and global warming, renewable energy sources gain constant impulse into the global energy economy. In consequence, the introduction of distributed energy sources has brought a new complexity to the electrical networks. In the new concept of smart grids and decentralized power generation; control, protection and measurement are also distributed and requiring, among other things, a new scheme of communication to operate with each other in balance and improve performance. In this research, an analysis of different communication technologies (power line communication, Ethernet over unshielded twisted pair (UTP), optic fiber, Wi-Fi, WiMAX, and Long Term Evolution) and their respective characteristics will be carried out. With the objective of pointing out strengths and weaknesses from different points of view (technical, economical, deployment, etc.) to establish a richer context on which a decision for communication approach can be done depending on the specific application scenario of a new smart grid deployment. As a result, a description of possible optimal deployment solutions for communication will be shown considering different options for technologies, and a mention of different important considerations to be taken into account will be made for some of the possible network implementation scenarios.
Non Parametric Estimation of Inhibition for Point Process Data

For a single geyser one eruption may inhibit another eruption. The objective is to estimate the inhibition function of geyser eruptions using a non parametric algorithm by extending the non parametric estimation method of Marsan and Lenglin? (2008) for clustered Hawkes processes to the case where there may be inhibition. The proposed method is tested using simulated geyser eruption data from known densities: Exponential, Pareto, Normal, and Uniform. The method is then applied ot the actual data from the Lone Pine Geyser in Yellowstone National Park. The data consists of 163 eruptions from 2011. The results indicate that geyser eruptions do inhibit other eruptions to some degree.
Household affiliation of young adults in Italy and Norway. The significance of gender, sociocultural background, work and money

Italy and Norway are characterized by different household patterns of young adults, with young Italians being more likely to live in their parents' house and young Norwegians more likely to live independently, alone or in multi-occupant households. This paper asks why, and how these differences can be understood. We focus on three types of household affiliation in young adulthood: Living with parents, living alone (including in multi-occupant households) and living in a couple, and conduct multivariate analyses on the interaction of gender, sociocultural background, and economic activity indicators at the individual level. We use EU SILC micro data on 2007, a time when the economic prospects and the labour market situation were relatively stable in both countries. The results show that young adults' living arrangements are differently affected by the included subset of factors in the two countries. Generally, the propensity of young adults to live with parents and not in a couple appears more sensitive to individual characteristics in Italy than in Norway. This applies both to sociocultural and economic characteristics. Whereas an important prerequisite of leaving the parental home among young (native born) Italians, and particularly among Italian men, is to have finished education and attained a permanent job, young Norwegians establish households on their own more or less in any case.
Vertically propagating waves in a numerical stratospheric model

Vertically propagating planetary scale waves are an important feature of the wintertime stratospheric and mesospheric dynamics. The waves, particularly zonal wavenumbers 1 and 2, are analyzed in the quasi-geostrophic chemical-dynamical numerical stratospheric model developed at M. I. T. It appears that zonal wavenumbers 1 and 2 in the model propagate energy more rapidly through the winter stratosphere than those which are observed. Above the stratopause there is little or no propagation of energy by the model waves in disagreement with observed wintertime quasi-geostrophic waves. The latter may be due to wave reflection at the rigid lid upper boundary of the model. It is likely that the former is due to the inability of the model to precisely simulate the wintertime mean circulation. It is shown that vertical propagation of planetary scale mid latitude eddies is quite sensitive to the zonal wind -configuration. In the final section, wave-zonal interactions are qualitatively discussed by examining spatial derivatives of two eddy fluxes. It is found that most conversions between quasi-geostrophic eddies and the zonal flow occur in the vicinity of the jets. Thesis Supervisor: Ronald Prinn, Associate Professor -3CONTENTS Page
Natural history traits of the terrestrial breeding frog Batrachyla taeniata (Anura: Batrachylidae) in wet meadows of Patagonia

ABSTRACT Anurans have diverse reproductive modes, and some species of the austral forests of Patagonia have become specialized in terrestrial reproduction. Batrachyla taeniata is one of these species: it inhabits wetlands, lays its eggs during late summer and fall in terrestrial conditions, and has overwintering tadpoles. We studied a population of B. taeniata that breeds in wet meadows surrounded by native Patagonian forest and described its life cycle parameters (breeding phenology, egg development, and coexistence with other anurans) over two different years with contrasting hydroperiods. We also analyzed the effect of predatory insects on tadpole survival. Embryo development occurred in wet soil, which may be exposed to the sun or not, and took from 48 to 63 days to hatch. Free-swimming larvae overwintered in the wetland and coexisted in spring with pond-breeding anurans that varied in composition and abundance according to the wetland hydroperiod. The survivorship of B. taeniata tadpoles was significantly greater than that of P. thaul tadpoles when both were exposed to a free belostomatid predator. We consider that the terrestrial reproductive mode and life cycle of B. taeniata enable this species to survive in the variable biotic conditions determined by hydroperiod length.
Generative design for gene therapy: An in vivo validated method

Machine learning-assisted biological sequence design is a topic of intense interest due to its potential impact on healthcare and biotechnology. In recent years many new approaches have been proposed for sequence design through learning from data alone (rather than mechanistic or structural approaches). These black-box approaches roughly fall into two camps: (i) optimization against a learned oracle (ii) sampling designs from a generative model. While both approaches have demonstrated promise, real-world evidence of their effectiveness is limited, whether used alone or in combination. Here we develop a robust generative model named VAEProp and use it to optimize Adeno-associated virus (AAV) capsids, a fundamental gene therapy vector. We show that our method outperforms algorithmic baselines on this design task in the real world. Critically, we demonstrate that our approach is capable of generating vector designs with field-leading therapeutics potential through in-vitro and non-human primate validation experiments.
Adaptive Deadbeat Predictive Control for PMSM-based solar-powered electric vehicles with enhanced stator resistance compensation

This article introduces an innovative approach called Adaptive Deadbeat Predictive Control (ADPC), specifically designed to regulate the operation of a Permanent Magnet Synchronous Motor (PMSM) within a solar-powered electric vehicle (SEV). Considering the influence of factors such as magnetic saturation, material aging, and temperature fluctuations, discrepancies may arise between actual and nominal parameter values. Notably, the stator inductance, permanent magnet flux linkage, and stator resistance are crucial variables in this context. The article conducts an in-depth theoretical examination of the consequences of these parameter mismatches on the overall stability of the system. To mitigate the effects of stator resistance variability, an adaptive control methodology is proposed. This strategy hinges on real-time control adaptation, achieved by continuously estimating the resistance value through diligent consideration of the actual winding temperature. The proposed Adaptive Deadbeat Predictive Control framework is seamlessly implemented and simulated within the MATLAB Simulink environment. The simulation results eloquently validate the efficacy of the proposed control approach, showcasing its adeptness in mitigating the system’s sensitivity to stator resistance deviations, thereby fortifying the overall control resilience.
Nitrogen oxides from high-altitude aircraft: An update of potential effects on ozone

A sensitivity study is carried out using the Lawrence Livermore National Laboratory one-dimensional and two-dimensional chemical-radiative-transport models of the global atmosphere to examine possible effects of future aircraft NOx emissions to stratospheric ozone. A broad range in magnitude, altitude, and latitude of the assumed NOx emissions is examined. Major findings of this initial study are as follows: (1) Nitrogen oxides from the exhaust gases of stratospheric aircraft can reduce stratospheric ozone on a global basis. These calculated ozone reductions depend strongly on NOx injection altitude and magnitude. (2) The altitude at which NOx emissions cause the largest reduction in the ozone column is about 25 km according to one-dimensional model calculations and about 28 km according to the two-dimensional model. (3) For a given altitude and magnitude Of NOx emissions, the two-dimensional model finds that the reduction of global ozone depends on latitude of the injections, with maximum ozone reduction for tropical injection. For a given injection, the largest ozone column reductions occur in the polar regions. (4) For very large Clx mixing ratios, NOx emissions can increase the ozone column, partially counteracting the ozone reduction caused by Clx. This effect is found only in a highly Clx perturbed stratosphere where ozone is already greatly depleted. (5) Water vapor (without nitric oxide) in the exhaust gives a small ozone reduction; water vapor and nitric oxide together give an ozone reduction less than that calculated for NO alone by factors between 0.85 and 0.97. (6) Calculated global reductions of ozone due to NOx emissions are smaller in the two-dimensional model than in the one-dimensional model, by factors that range from 0.66 to 0.86 for injection altitudes between 20 to 34 km. (7) On the basis of an uncertain estimate of fuel consumption by future stratospheric aircraft, calculations for a fleet of 500 aircraft operating at 22 km with NOx emission properties of 1988 subsonic commercial aircraft engines give global ozone reductions of about 20%. There is reason to believe that such nitric oxide emissions may be lowered, perhaps by a factor of 10, by advanced emission reduction technology.
Creative and Critical Entanglements With AI in Art Education

Since the advent of the postdigital era, technologies have been dramatically transforming human lives, shifting the ways humans communicate, learn, and create. This article aims to envision how entanglements with nonhuman intelligences can unsettle and reshape pedagogical approaches in the field of art education. I argue for the need to reconceptualize relations between humans and artificial intelligence (AI) as collaborative and symbiotic relationships beyond instrumental understandings, which are informed by posthuman perspectives. Reframing human–AI relations will help art educators and researchers not only explore the potential of AI for new inquiry and creativity in art curricula, but also critically examine possible ethical issues for its implementation in art classrooms. By looking at how AI has been explored in new media art projects that intersect emergent intelligences and art pedagogy, I investigate their implications for future art education.
Enhancing ASP(Q) evaluation

is an extension of Answer Set Programming (ASP) that enables the declarative and modular modeling of problems within the entire polynomial hierarchy. The first implementation of ASP(Q), known as qasp, utilized a translation to Quantified Boolean Formulae (QBF) to take advantage of the advanced and mature QBF-solving technology. However, the QBF encoding implemented by qasp is highly general, potentially leading to complex formulas that existing QBF solvers struggle to evaluate due to the large number of symbols and sub-clauses. In the paper titled “An efficient solver for ASP(Q) ", that has been presented during the 39th International Conference on Logic Programming (ICLP23), we introduced a novel implementation that builds upon the concepts of qasp and incorporates a more efficient encoding procedure, optimized encodings of ASP(Q) programs in QBF, and a machine learning model for the automatic selection of QBF-solving back-ends. Inthispaper, we give an overview of the results we have obtained in the above-mentioned paper and discuss possible future directions.
Purdue e-Pubs Purdue e-Pubs

Failure studies are important in revealing the root causes, behaviors, and life cycle of defects in software systems. These studies either focus on understanding the characteristics of defects in specifc classes of systems or the characteristics of a specifc type of defect in the systems it manifests in. Failure studies have infuenced various software engineering research directions, especially in the area of software evolution, defect detection, and program repair. In this paper, we refect on the conduct of failure studies in software engineering. We reviewed a sample of 52 failure study papers. We identifed several recurring problems in these studies, some of which hinder the ability of the engineering community to trust or replicate the results. Based on our fndings, we suggest future research directions, including identifying and analyzing failure causal chains, standardizing the conduct of failure studies, and tool support for faster defect analysis.
THE POTENTIAL OF HEIGHT TEXTURE MEASURES FOR THE SEGMENTATION OF AIRBORNE LASERSCANNER DATA

Airborne laserscanning is being used for an increasing number of mapping and GIS data acquisition tasks. Besides the original purpose of digital t errain model generation, new applications arise in the a utomatic detection and modeling of objects s uch as buildings or vegetation for the generation of 3-D city models. A crucial prerequisite for the automatic extraction of objects on the Earth's surface from laserscanner height data is the segmentation o f datasets. Besides the height it self, h eight texture defined by local variations of the height is a significant feature of objects to be recognized. The paper shows the potential of the a nalysis of height t exture for the a utomatic segmentation o f dense laserscanner datasets and the detection o f objects in the segmented data. Based on the definition and computation o f a number of texture measures used as bands in a classification approach, objects like buildings, single trees, ground vegetation and roads can be recognized. The technique was applied to a FLI-MAP laserscanner dataset with an average point density of more than five points per squaremeter, acquired over a village in The Netherlands. In a maximum likelihood classification based on the absolute height and several t exture measures derived from it, a c lassification accuracy of 98% could b e achieved. Based on the result of the segmentation, all buildings of the scene and most single trees could be automatically detected.
Matching of treatment-resistant heroin-dependent patients to medical prescription of heroin or oral methadone treatment: results from two randomized controlled trials.

AIMS To investigate which baseline patient characteristics of treatment-resistant heroin addicts differentially predicted treatment response to medical heroin prescription compared to standard methadone maintenance treatment. DESIGN Two open-label randomized controlled trials; pooled data. SETTING Methadone maintenance programmes and heroin treatment centres in six cities in the Netherlands. PARTICIPANTS Four hundred and thirty heroin addicts. INTERVENTION Methadone plus injectable heroin or methadone plus inhalable heroin compared to methadone alone prescribed over 12 months: heroin maximum 1000 mg per day, methadone maximum 150 mg per day. MAIN OUTCOME MEASURE Dichotomous, multi-domain response index, including validated indicators of physical health, mental status and social functioning. FINDINGS Data of the inhalable and injectable heroin trials were pooled. Intention-to-treat analysis showed that treatment with medically prescribed heroin plus methadone was significantly more effective (51.8% response) than standard methadone maintenance treatment (28.7%) (95% CI of response difference: 14.1-32.2%). Multivariate logistic regression analyses showed that only one of all baseline characteristics was predictive of a differential treatment effect: patients who had previously participated in abstinence-orientated treatment responded significantly better to heroin-assisted treatment than to methadone treatment (61% versus 24%), while patients without experience in abstinence-orientated treatment did equally well in heroin-assisted or methadone maintenance treatment (39% and 38%, respectively). CONCLUSIONS The effect of heroin-assisted treatment is not dependent on clinical characteristics, with the exception of previous abstinence-orientated treatment: medical prescription of heroin is most effective for those patients who have previously participated in abstinence-orientated treatment.
Study on the properties of sodium bismuth titanate coating prepared by supersonic plasma spraying

Abstract In order to realize the preparation of environmentally friendly piezoelectric ceramic coatings on the surface of metallic materials, sodium bismuth titanate (Bi0.5Na0.5TiO3, BNT) ceramic coatings were prepared by supersonic plasma spraying. The surface morphology, cross-sectional morphology, phase structure, and elemental valence variations of the BNT coating were examined, as well as the dielectric and ferroelectric properties of the BNT coating. The results show that the coating has a good quality and a single perovskite structure. The dielectric constant was stable at about 425 and the dielectric loss was stable at about 0.06 when the test frequency reached 200 kHz. The coating exhibits good hysteresis lines under different applied electric fields. When the applied electric field was 40 kV/cm, the remnant polarization value of the prepared coating was 11.47 µC/cm2. It can be seen that the BNT piezoelectric coating prepared by supersonic plasma spraying has good ferroelectric and dielectric properties, which lays a solid foundation for in-situ monitoring of environmentally friendly lead-free BNT piezoelectric coating.
The Urban Heat Island Of San Antonio, Texas (USA)

A study of the urban heat island effect was carried out comparing 45-year daily temperature records (1946-1990) of San Antonio, Texas (USA), with three small surrounding towns; New Braunfels, Poteet, and Boerne. These towns are all within 40 kilometers of San Antonio and were chosen because they form a nearly equilateral triangle around the city from northeast to south to northwest, respectively. The study shows that, on average, the minimum temperatures at the San Antonio International Airport (the location of the weather station) are increasing at an average rate of about 0.3°C per decade relative to surrounding small towns with similar elevation. The difference in minimum temperatures is most pronounced during the summer months. The summer temperature minimum differences relative to New Braunfels indicated the largest increase at 0.4 ± 0.1°C per decade and an increase of 0.2 ± 0.1°C per decade relative to Poteet. In 1947, the minimum temperatures in New Braunfels were on average about 0.2°C warmer than San Antonio and they were about equal between San Antonio and Poteet. In 1990, summer minimum temperatures were more than 1.7°C cooler in New Braunfels and more than 1.0°C cooler in Poteet. A similar trend in the minimum summer temperatures is seen in comparisons with Boerne but the magnitudes are smaller and there are larger temperature fluctuations in the data. This may be due to the higher elevation of Boerne (about 700 meters above see level) whereas San Antonio, New Braunfels, and Poteet all have similar elevations (about 200 meters above see level). The same effects are found in the maximum temperatures in the winter months for New Braunfels and Poteet. They are increasing at average rates of about 0.8°C per decade compared to New Braunfels and 0.5°C per decade compared to Poteet in the winter months. No statistical change in the winter maximum temperatures between San Antonio and Boerne was found. Despite many mitigating influences (e.g., much vegetation, little polluting industry), it has been shown that San Antonio has an increasing urban heat island effect.