Miracle-dz/UniFAR-FTUs huggingface dataset:
Transfer of Performance Models Across Analog Circuit Topologies with Graph Neural Networks

In this work, graph neural networks (GNNs) and transfer learning are leveraged to transfer device sizing knowledge learned from data of related analog circuit topologies to predict the performance of a new topology. A graph is generated from the netlist of a circuit, with nodes representing the devices and edges the connections between devices. To allow for the simultaneous training of GNNs on data of multiple topologies, graph isomorphism networks are adopted to address the limitation of graph convolutional networks in distinguishing between different graph structures. The techniques are applied to transfer predictions of performance across four op-amp topologies in a 65 nm technology, with 10000 sets of sizing and performance evaluations sampled for each circuit. Two scenarios, zero-shot learning and few-shot learning, are considered based on the availability of data in the target domain. Results from the analysis indicate that zero-shot learning with GNNs trained on all the data of the three related topologies is effective for coarse estimates of the performance of the fourth unseen circuit without requiring any data from the fourth circuit. Few-shot learning by fine-tuning the GNNs with a small dataset of 100 points from the target topology after pre-training on data from the other three topologies further boosts the model performance. The fine-tuned GNNs outperform the baseline artificial neural networks (ANNs) trained on the same dataset of 100 points from the target topology
Kua: a distributed object store over named data networking

Applications such as machine learning training systems or log collection generate and consume large amounts of data. Object storage systems provide a simple abstraction to store and access such large datasets. These datasets are typically larger than the capacities of individual storage servers, and require fault tolerance through replication. In this paper, we present Kua, a distributed object storage system built over Named Data Networking (NDN). The data-centric nature of NDN helps Kua maintain a simple design while catering to requirements of storing large objects, providing fault tolerance, low latency and strong consistency guarantees, along with data-centric security. Our prototype Kua implementation provides easy-to-use primitives to let applications store and access data securely, and our initial evaluation suggests that Kua can leverage NDN's capabilities of multicast data delivery and in-network caching to achieve higher efficiency than existing object storage systems.
A Predictable QoS-aware Memory Request Scheduler for Soft Real-time Systems

A memory controller manages the flow of data to and from attached memory devices. The order in which a set of contending memory requests from different tasks are serviced significantly influences the rate of progress and completion times of these tasks. This in turn may affect the Quality-of-Service (QoS) delivered by these tasks. In this article, we focus towards the design of a QoS-aware memory controller targeted towards soft real-time systems. The proposed memory controller tries to generate an urgency-based schedule for the contending memory requests based on the allowable response time latencies associated with each request. The objective is to improve task-level response time predictability while maximizing acquired QoS. Exhaustive experiments carried out using real memory traces and standard simulation tools exhibit the practical efficacy of the proposed memory controller design.
Bayesian Analysis of Bug-Fixing Time using Report Data

Background: Bug-fixing is the crux of software maintenance. It entails tending to heaps of bug reports using limited resources. Using historical data, we can ask questions that contribute to better-informed allocation heuristics. The caveat here is that often there is not enough data to provide a sound response. This issue is especially prominent for young projects. Also, answers may vary from project to project. Consequently, it is impossible to generalize results without assuming a notion of relatedness between projects. Aims: Evaluate the independent impact of three report features in the bug-fixing time (BFT), generalizing results from many projects: bug priority, code-churn size in bug fixing commits, and existence of links to other reports (e.g., depends on or blocks other bug reports). Method: We analyze 55 projects from the Apache ecosystem using Bayesian statistics. Similar to standard random effects methodology, we assume each project’s average BFT is a dispersed version of a global average BFT that we want to assess. We split the data based on feature values/range (e.g., with or without links). For each split, we compute a posterior distribution over its respective global BFT. Finally, we compare the posteriors to establish the feature’s effect on the BFT. We run independent analyses for each feature. Results: Our results show that the existence of links and higher code-churn values lead to BFTs that are at least twice as long. On the other hand, considering three levels of priority (low, medium, and high), we observe no difference in the BFT. Conclusion: To the best of our knowledge, this is the first study using hierarchical Bayes to extrapolate results from multiple projects and assess the global effect of different attributes on the BFT. We use this methodology to gain insight on how links, priority, and code-churn size impact the BFT. On top of that, our posteriors can be used as a prior to analyze novel projects, potentially young and scarce on data. We also believe our methodology can be reused for other generalization studies in empirical software engineering.
Mutexion: Mutually Exclusive Compression System for Mitigating Compression Side-Channel Attacks

To enhance the performance of web services, web servers often compress data to be delivered. Unfortunately, the data compression technique has also introduced a side effect called compression side-channel attacks (CSCA). CSCA allows eavesdroppers to unveil secret strings included in the encrypted traffic by observing the length of data. A promising defense technique called Debreach was recently proposed to mitigate CSCA by excluding all secret data in a web page during the compression process. Although Debreach has proven to be safe against CSCA and outperforms other approaches, the exclusion of all secret data from compression eventually resulted in a decreased compression efficiency. In this paper, we present a highly efficient CSCA mitigation system called “Mutexion” (Mutually exclusive compression) which allows us to fully take advantage of compression over an entire web page, including secret data. The key idea behind Mutexion is to fully take advantage of all the matching subsequences within a web page except only for those between secret data and user-controlled data (potentially controlled by an attacker) during the compression process. This approach of Mutexion effectively prevents side-channel leaks of secret data under CSCA misusing user-controlled data in a web page while minimizing the degradation in compression efficiency. It is required for our compressor to trace both secret data and user-controlled data in its compression process of web pages. To meet this requirement, we provide techniques to enable automated annotation of secret and user-controlled data in web pages. We implemented Mutexion as a fully working system to test live web pages and evaluated its performance with respect to security and compression efficiency. Our evaluation results demonstrated that Mutexion effectively prevents CSCA and also achieves almost the same compression ratio as the original zlib, which is vulnerable to CSCA, with a slight increase (0.032 milliseconds (7.9%) on average) in execution time.
N-DISE: NDN-based data distribution for large-scale data-intensive science

To meet unprecedented challenges faced by the world's largest data- and network-intensive science programs, we design and implement a new, highly efficient and field-tested data distribution, caching, access and analysis system for the Large Hadron Collider (LHC) high energy physics (HEP) network and other major science programs. We develop a hierarchical Named Data Networking (NDN) naming scheme for HEP data, implement new consumer and producer applications to interface with the high-performance NDN-DPDK forwarder, and build on recently developed high-throughput NDN caching and forwarding methods. We integrate NDN systems concepts and algorithms with the mainstream data distribution, processing, and management system of the Compact Muon Solenoid (CMS) experiment. We design and prototype stable, high-performance virtual LANs (VLANs) over a continental-scale wide area network testbed. In extensive experiments, our proposed integrated system, named NDN for Data-Intensive Science Experiments (N-DISE), is shown to deliver LHC data over the wide area network (WAN) testbed at throughputs exceeding 31 Gbps between Caltech and StarLight, with dramatically reduced download time.
Data enhanced iterative few-sample learning algorithm-based inverse design of 2D programmable chiral metamaterials

Abstract A data enhanced iterative few-sample (DEIFS) algorithm is proposed to achieve the accurate and efficient inverse design of multi-shaped 2D chiral metamaterials. Specifically, three categories of 2D diffractive chiral structures with different geometrical parameters, including widths, separation spaces, bridge lengths, and gold lengths are studied utilising both the conventional rigorous coupled wave analysis (RCWA) approach and DEIFS algorithm, with the former approach assisting the training process for the latter. The DEIFS algorithm can be divided into two main stages, namely data enhancement and iterations. Firstly, some “pseudo data” are generated by a forward prediction network that can efficiently predict the circular dichroism (CD) response of 2D diffractive chiral metamaterials to reinforce the dataset after necessary denoising. Then, the algorithm uses the CD spectra and the predictions of parameters with smaller errors iteratively to achieve accurate values of the remaining parameters. Meanwhile, according to the impact of geometric parameters on the chiroptical response, a new functionality is added to interpret the experimental results of DEIFS algorithm from the perspective of data, improving the interpretability of the DEIFS. In this way, the DEIFS algorithm replaces the time-consuming iterative optimization process with a faster and simpler approach that achieves accurate inverse design with dataset whose amount is at least one to two orders of magnitude less than most previous deep learning methods, reducing the dependence on simulated spectra. Furthermore, the fast inverse design of multiple shaped metamaterials allows for different light manipulation, demonstrating excellent potentials in applications of optical coding and information processing. This work belongs to one of the first attempts to thoroughly characterize the flexibility, interpretability, and generalization ability of DEIFS algorithm in studying various chiroptical effects in metamaterials and accelerating the inverse design of hypersensitive photonic devices.
Efficacy of botulinum toxin type a in the targeted treatment of sleep bruxism: a double-blind, randomised, placebo-controlled, cross-over study

Background Intramuscular injections of botulinum toxin A (BTX-A) have been used in the treatment of sleep bruxism (SB) however controlled trials are limited and the optimal injection strategy and dose is not known. Methods This double-blind, randomised, placebo-controlled, cross-over study evaluated the efficacy and safety of BTX-A in participants with SB. Average bruxism events per hour of sleep (Bruxism Index, BI) was calculated using surface electromyography. Participants with BI >5 were included and randomised by order of injection (active or placebo with the opposite 20 weeks later) and into one of three differing treatment groups: bilateral masseter (60 units(U)), bilateral masseter and temporalis (90U) and bilateral masseter, temporalis and medial pterygoid muscles (120U). Change in BI and subjective measures of headache, pain, and bruxism at 4 and 12 weeks was calculated following intervention, and differences between treatment groups analysed. Results 41 participants were recruited, 35 randomised and data from 22 participants (14 female) were analysed. BI was significantly lower at 4 weeks after active treatment when compared with placebo (mean=−1.66, p=0.003), not sustained at 12 weeks. The difference was greater with higher doses injected and among those with greater baseline BI. There was no difference in subjective measures at any time point. Five participants injected had mild, transient side effects. Discussion Targeted BTX-A injection is a safe and effective treatment for SB. A greater benefit may be achieved by administering BTX-A into more muscles and at higher total doses and among those with higher baseline BI. Trial registration number ACTRN12618001430224.
A Composite Analysis of the Stratospheric Sudden Warmings Simulated in a Perpetual January Integrati

A 7,200-day dataset from a perpetual January integration of the Berlin Troposphere-Stratosphere-Mesosphere General Circulation Model is analyzed to clarify the basic nature of the dynamical linkage between the stratosphere and the troposphere. Much attention is paid to the stratospheric sudden warming events; sixty-four events are detected in this dataset, with no clear periodicity. The 64 sudden warming events are divided into two groups according to the relative strength of planetary waves of zonal wavenumber 1 and 2 in the stratosphere, although each event has its own dynamical characteristics. Composites for each group show some general features of the stratospheric sudden warmings, including the preconditioned zonal mean states in the lower stratosphere and the upward propagation of the enhancement of planetary-scale waves from the troposphere to the stratosphere. In the preconditioned states the zonal mean temperature is lower than normal in the polar region, and the zonal mean zonal wind is stronger in the middle and high latitudes. Each group shows some different dynamical behavior, not only in the stratosphere but also in the troposphere before, during and after the sudden warming events. In the group in which the wavenumber 1 component dominates, the preconditioned states are more evident and confined to lower altitudes. Such states continue even after sudden warming events near the tropopause. In the other group of wavenumber 2 dominance, signals of sudden warming descend to the upper troposphere after the events.
Image segmentation evaluation and its application to object detection

The first parts of this Thesis are focused on the study of the supervised evaluation of image segmentation algorithms. Supervised in the sense that the segmentation results are compared to a human-made annotation, known as ground truth, by means of different measures of similarity. The evaluation depends, therefore, on three main points. First, the image segmentation techniques we evaluate. We review the state of the art in image segmentation, making an explicit difference between those techniques that provide a flat output, that is, a single clustering of the set of pixels into regions; and those that produce a hierarchical segmentation, that is, a tree-like structure that represents regions at different scales from the details to the whole image. Second, ground-truth databases are of paramount importance in the evaluation. They can be divided into those annotated only at object level, that is, with marked sets of pixels that refer to objects that do not cover the whole image; or those with annotated full partitions, which provide a full clustering of all pixels in an image. Depending on the type of database, we say that the analysis is done from an object perspective or from a partition perspective. Finally, the similarity measures used to compare the generated results to the ground truth are what will provide us with a quantitative tool to evaluate whether our results are good, and in which way they can be improved. The main contributions of the first parts of the thesis are in the field of the similarity measures. First of all, from an object perspective, we review the used basic measures to compare two object representations and show that some of them are equivalent. In order to evaluate full partitions and hierarchies against an object, one needs to select which of their regions form the object to be assessed. We review and improve these techniques by means of a mathematical model of the problem. This analysis allows us to show that hierarchies can represent objects much better with much less number of regions than flat partitions. From a partition perspective, the literature about evaluation measures is large and entangled. Our first contribution is to review, structure, and deduplicate the measures available. We provide a new measure that we show that improves previous ones in terms of a set of qualitative and quantitative meta-measures. We also extend the measures on flat partitions to cover hierarchical segmentations. The second part of this Thesis moves from the evaluation of image segmentation to its application to object detection. In particular, we build on some of the conclusions extracted in the first part to generate segmented object candidates. Given a set of hierarchies, we build the pairs and triplets of regions, we learn to combine the set from each hierarchy, and we rank them using low-level and mid-level cues. We conduct an extensive experimental validation that show that our method outperforms the state of the art in many metrics tested.
Key role of auxin cellular accumulation in totipotency and pluripotency acquisition

Genome editing and in vitro based-plant propagation require efficient plant regeneration system. Somatic embryogenesis (SE) or de novo shoot regeneration are two major systems that widely used for plant in vitro regeneration. Most SE or shoot regeneration protocols rely on the exogenous application of the synthetic auxin analog 2,4-dichlorophenoxyacetic acid (2,4-D) and naphthylene acetic acid (NAA), whereas the natural auxins indole-3-acetic acid (IAA), 4-chloroindole-3-acetic acid (4-Cl-IAA) or indole-3-butyric acid (IBA) are not or less effective for plant regeneration. Although these synthetic auxins mimics the physiological activity of the main natural auxin IAA in many aspects, there are also clear differences that have been attributed to differences in stability or to different affinities for certain TIR1/AFB-Aux/IAA auxin co-receptor pairs. Here we show that the success of 2,4-D in inducing SE from Arabidopsis is related to ineffectiveness as substrate for auxin efflux, resulting in its intracellular 2,4-D accumulation. Reducing auxin efflux by addition of the auxin transport inhibitor naphthylphthalamic acid (NPA) also allowed natural auxins and other synthetic analogs to induce SE in Arabidopsis with similar efficiencies as 2,4-D. The PIN-FORMED auxin efflux carriers PIN1, PIN2 and the ATP-binding cassette-B auxin transporters ABCB1 and ABCB19 were shown to be partially responsible for the efflux of natural auxins during SE induction. Importantly, all somatic embryos induced in Arabidopsis by IAA in the presence of NPA showed a normal embryo to seedling conversion and subsequent plant development, whereas for the 2,4-D system this was limited to 50-60% of the embryos. We showed that the auxin transport inhibition promotes de novo shoot regeneration capacity from callus induced by 4-Cl-IAA in Brassica napus. In addition, we observed a obvious acceleration in shoot bud emerging from callus induced by 4-Cl-IAA than 2,4-D. Based on our data we conclude, that the efficiency of plant propagation can be significantly improved by applying the natural auxins in the presence of the auxin transport inhibitor NPA.
Enhancers display constrained sequence flexibility and context-specific modulation of motif function

The information about when and where each gene is to be expressed is mainly encoded in the DNA sequence of enhancers, sequence elements that comprise binding sites (motifs) for different transcription factors (TFs). Most of the research on enhancer sequences has been focused on TF motif presence, whereas the enhancer syntax, that is, the flexibility of important motif positions and how the sequence context modulates the activity of TF motifs, remains poorly understood. Here, we explore the rules of enhancer syntax by a two-pronged approach in Drosophila melanogaster S2 cells: we (1) replace important TF motifs by all possible 65,536 eight-nucleotide-long sequences and (2) paste eight important TF motif types into 763 positions within 496 enhancers. These complementary strategies reveal that enhancers display constrained sequence flexibility and the context-specific modulation of motif function. Important motifs can be functionally replaced by hundreds of sequences constituting several distinct motif types, but these are only a fraction of all possible sequences and motif types. Moreover, TF motifs contribute with different intrinsic strengths that are strongly modulated by the enhancer sequence context (the flanking sequence, the presence and diversity of other motif types, and the distance between motifs), such that not all motif types can work in all positions. The context-specific modulation of motif function is also a hallmark of human enhancers, as we demonstrate experimentally. Overall, these two general principles of enhancer sequences are important to understand and predict enhancer function during development, evolution, and in disease.
Porcn is essential for growth and invagination of the mammalian optic cup

Microphthalmia, anophthalmia, and coloboma (MAC) are congenital ocular malformations causing 25% of childhood blindness. The X-linked disorder Focal Dermal Hypoplasia is frequently associated with MAC and results from mutations in Porcn, a membrane bound O-acyl transferase required for palmitoylation of Wnts to activate multiple Wnt-dependent pathways. Wnt/β-catenin signaling is suppressed in the anterior neural plate for initiation of eye formation and is subsequently required during differentiation of the retinal pigment epithelium (RPE). Non-canonical Wnts are critical for early eye formation in frog and zebrafish, however, it is unclear whether this also applies to mammals. We performed ubiquitous conditional inactivation of Porcn in mouse around the eye field stage. In PorcnCKO, optic vesicles (OV) arrest in growth and fail to form an optic cup. Ventral proliferation is significantly decreased in the mutant OV, with a concomitant increase in apoptotic cell death. While pan-ocular transcription factors such as PAX6, SIX3, LHX2, PAX2 are present, indicative of maintenance of OV identity, regional expression of VSX2, MITF, OTX2 and NR2F2 is downregulated. Failure of RPE differentiation in PorcnCKO is consistent with downregulation of the Wnt/β-catenin effector LEF1, starting around 2.5 days after inactivation. This suggests that Porcn inactivation affects signaling later than a potential requirement for Wnts to promote eye field formation. Altogether, our data shows a novel requirement for Porcn in regulating growth and morphogenesis of the OV, likely by controlling proliferation and survival. In FDH patients with ocular manifestations, growth deficiency during early ocular morphogenesis may be the underlying cause for microphthalmia.