Escape Analysis Research Articles

MEA2: A Lightweight Field-Sensitive Escape Analysis with Points-to Calculation for Golang

Escape analysis plays a crucial role in garbage-collected languages as it enables the allocation of non-escaping variables on the stack by identifying the dynamic lifetimes of objects and pointers. This helps in reducing heap allocations and alleviating garbage collection pressure. However, Go, as a garbage-collected language, employs a fast yet conservative escape analysis, which is field-insensitive and omits point-to-set calculation to expedite compilation. This results in more variables being allocated on the heap. Empirical statistics reveal that field access and indirect memory access are prevalent in real-world Go programs, suggesting potential opportunities for escape analysis to enhance program performance. In this paper, we propose MEA 2 , an escape analysis framework atop GoLLVM (an LLVM-based Go compiler), which combines field sensitivity and points-to analysis. Moreover, a novel generic function summary representation is designed to facilitate fast inter-procedural analysis. We evaluated it by using MEA 2 to perform stack allocation in 12 wildly-use open-source projects. The results show that, compared to Go’s escape analysis, MEA 2 can reduce heap allocation sites by 7.9

Hybrid immunity to SARS-CoV-2 arises from serological recall of IgG antibodies distinctly imprinted by infection or vaccination

We describe the molecular-level composition of polyclonal immunoglobulin G (IgG) anti-spike antibodies from ancestral severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, vaccination, or their combination ("hybrid immunity") at monoclonal resolution. Infection primarily triggers S2/N-terminal domain (NTD)-reactive antibodies, whereas vaccination mainly induces anti-receptor-binding domain (RBD) antibodies. This imprint persists after secondary exposures wherein >60% of ensuing hybrid immunity derives from the original IgG pool. Monoclonal constituents of the original IgG pool can increase breadth, affinity, and prevalence upon secondary exposures, as exemplified by the plasma antibody SC27. Following a breakthrough infection, vaccine-induced SC27 gained neutralization breadth and potency against SARS-CoV-2 variants and zoonotic viruses (half-maximal inhibitory concentration [IC50] ∼0.1-1.75nM) and increased its binding affinity to the protective RBD class 1/4 epitope (dissociation constant [KD]<5 pM). According to polyclonal escape analysis, SC27-like binding patterns are common in SARS-CoV-2 hybrid immunity. Our findings provide a detailed molecular definition of immunological imprinting and show that vaccination can produce class 1/4 (SC27-like) IgG antibodies circulating in the blood.

A disulfidptosis-related lncRNA index predicting prognosis and the tumor microenvironment in colorectal cancer

Colorectal cancer (CRC) is a common and deadly cancer worldwide with a high lethality rate. Disulfidptosis has been found to be an emerging mode of death in cancer, and the purpose of this study was to explore the relationship between disulfidptosis-related lncRNAs (DRLs) and CRC and to develop a prognostic model for CRC and DRLs. The gene expression data and clinicopathologic information of colorectal cancer patients were obtained from The Cancer Genome Atlas (TCGA) and screened for DRLs based on correlation analysis. The least absolute shrinkage and selection operator (LASSO) and Cox regression were used to construct the prognostic model, and its validation was carried out by PCA and receiver operating characteristic (ROC) curves. We constructed nomograms combined with the model. Finally, the possible mechanisms by which lncRNAs affect CRC were explored by functional enrichment analysis, immune infiltration and immune escape analysis. In summary, we developed a prognostic marker consisting of lncRNAs associated with disulfidptosis to help clinicians predict the survival of different CRC patients and use different targeted therapies and immunotherapies depending on the condition.

Correlation between chromatin epigenetic-related lncRNA signature (CELncSig) and prognosis, immune microenvironment, and immunotherapy in non-small cell lung cancer.

Chromatin regulators drive cancer epigenetic changes, and lncRNA can play an important role in epigenetic changes as chromatin regulators. We used univariate Cox, LASSO, and multivariate Cox regression analysis to select epigenetic-associated lncRNA signatures. Twenty-five epigenetic-associated lncRNA signatures (CELncSig) were identified to establish the immune prognostic model. According to Kaplan-Meier analysis, the overall survival of the high-risk group was significantly lower than the low-risk group. Receiver operating characteristic (ROC) curves, C-index, survival curve, nomogram, and principal component analysis (PCA) were performed to validate the risk model. In GO/KEGG analysis, differentially expressed lncRNAs were correlated with the PI3K-Akt pathway, suggesting that they were highly associated with the metastasis of LUAD. Interestingly, in the immune escape analysis, the TIDE score was lower, and the possibility of immune dysfunction is also slighter in the high-risk group, which means they still have the potential to receive immunotherapy. And CELncsig is highly correlated with immune pathways T_cell_co-inhibition and Check-point. Also, the IMvigor210 cohort analysis indicated that our risk-scoring model has significant potential clinical application value in lung cancer immunotherapy. And we also screened out ten potential chemotherapy agents using the 'pRRophetic' package.

Construction of lncRNA prognostic model related to cuproptosis in esophageal carcinoma.

Background: Esophageal carcinoma (ESCA) is one of the most prevalent malignant tumors in the world. The prognosis of patients has significantly improved with the development of surgery, targeted therapy and immunotherapy. But the 5-year survival rate of ESCA patients is still incredibly low. Cuproptosis is a type of mitochondrial cell death induced by copper. It is unclear how cuproptosis-related lncRNAs (CRLs) affect ESCA prognosis. Methods: In this study, we obtained the clinical data of ESCA patients, the transcriptome data from TCGA and identified CRLs by co-expression analysis, lasso regression, and cox regression analysis, to build a prognostic model. Then we validated the prognostic model using the Kaplan-Meier curve, cox regression analysis, and ROC, to create a nomogram based on risk score to forecast the prognosis of ESCA. Next, the immune escape of the CRLs was examined using the TIDE algorithm to assess its sensitivity to possible ESCA medications. Results: To predict the prognosis of ESCA patients, we created a predictive model using 6 CRLs (AC034199.1, AC125437.1, AC107032.2, CTBP1-DT, AL024508.1, and AC008610.1), validated by the Kaplan-Meier and ROC curves. The model has a higher diagnostic value compared to other clinical features. The 6 CRLs expressed high in TCGA and ESCA specimens. Enrichment analysis revealed CRLs largely contributed to the interaction between cytokines and their receptors as well as complement coagulation cascades. The immunity escape analysis demonstrated that immunotherapy had a worse effect in the low-risk group than in the high-risk group. Additionally, we screened out potential antineoplastic drugs according to the results of the immunoassay and obtained 5 drugs, including CP-466722, crizotinib, MS-275, KIN001-135, and CP-466722. Conclusion: The prognosis of patients with ESCA can be correctly predicted by the 6 CRLs chosen from this investigation. It lays the groundwork for more investigation into the ESCA mechanism and the identification of novel therapeutic targets.

Effects, capabilities, and boxes: from scope-based reasoning to type-based reasoning and back

Reasoning about the use of external resources is an important aspect of many practical applications. Effect systems enable tracking such information in types, but at the cost of complicating signatures of common functions. Capabilities coupled with escape analysis offer safety and natural signatures, but are often overly coarse grained and restrictive. We present System C, which builds on and generalizes ideas from type-based escape analysis and demonstrates that capabilities and effects can be reconciled harmoniously. By assuming that all functions are second class, we can admit natural signatures for many common programs. By introducing a notion of boxed values, we can lift the restrictions of second-class values at the cost of needing to track degree-of-impurity information in types. The system we present is expressive enough to support effect handlers in full capacity. We practically evaluate System C in an implementation and prove its soundness.

Evaluation of the sustainability of technologies to recycle spent lithium-ion batteries, based on embodied energy and carbon footprint

Battery demand is estimated to growth at a 25% annual rate, to reach a volume of 2600 GWh in 2030. Recovering critical raw materials from end-of-life batteries is now mandatory to limit the need of primary raw materials in the long-term.However, recycling of lithium-ion batteries (LIBs) is still in its early stage. Many technologies have been proposed, that consist of a combination of mechanical processing, often after thermal pre-treatment, ended up to hydrometallurgical or pyrometallurgical processing. All these methods have several pros and cons in terms of applicability, safety, environmental impact, eventual recovery efficiency of the components, and economic factors.In this frame, the evaluation of the sustainability of the proposed technologies plays a fundamental role in selecting the most suitable approaches able to support material supply for batteries, identifying the major solutions to optimize the end-of-life management strategies for LIBs, in the perspective of a circular economy context. However, LCA was developed to evaluate commercially mature technologies.This paper aims to propose and discuss, for the first time, the sustainability of 33 different technologies available in literature for LIBs recovery, even if developed only at laboratory level, by a screening approach, preliminary to LCA analysis. For this purpose, ESCAPE (standing for Evaluation of Sustainability of material substitution using CArbon footPrint by a simplified approach) tool based on the calculation of embodied energy and carbon footprint is used.Based on ESCAPE analysis results, this work shows and discusses the parameters that affect the technologies sustainability (thermal and mechanical treatments and chemicals and water use). The results, in accord with preliminary available LCA data, indicate that chemicals and ultrapure water consumption are the most energy-intensive processes drivers, showing that pyrometallurgy can limit carbon footprint and energy consumption in comparison to hydrometallurgy. Finally, by using the ESCAPE index, it is shown that some technologies may be improved for example by using industrial water instead of ultrapure water and/or by recycling the chemicals used for leaching steps.In summary it is shown that ESCAPE tool can be used in supporting eco-design strategies with the aim to facilitate the understanding of environmental implications of proposed LIBs recovery technologies and to focalize the research toward the more promising ones.

Capture and escape analyses on planar retrograde periodic orbit around the Earth

The present study investigates capture and escape dynamics associated with a planar, high–energy, retrograde periodic orbit around the Earth for applications to spacecraft trajectories. A lunar gravity assist plays the central role in both capture and escape scenarios. In the capture analysis, the trade–off among time–of–flights, launch energies, and insertion delta–v are revealed. A variety of solutions exists including fast, multi–revolutional, and Sun–perturbed transfers. The escape analysis, on the other hand, focuses on transfers with short time–of–flights. The search finds that a double lunar gravity assist, occurring after a departure delta–v on the periodic orbit, enables efficient escape from the Earth with substantial hyperbolic excess velocities. The overall result leads to a concept “Comet Interception from eArth retrOgrade orbIT viA Lunar gravIty Assist” using the retrograde periodic orbit as a staging post and enabling fast lunar encounters to travel toward the interplanetary region.

Potent and protective IGHV3-53/3-66 public antibodies and their shared escape mutant on the spike of SARS-CoV-2

Neutralizing antibodies (nAbs) to SARS-CoV-2 hold powerful potentials for clinical interventions against COVID-19 disease. However, their common genetic and biologic features remain elusive. Here we interrogate a total of 165 antibodies from eight COVID-19 patients, and find that potent nAbs from different patients have disproportionally high representation of IGHV3-53/3-66 usage, and therefore termed as public antibodies. Crystal structural comparison of these antibodies reveals they share similar angle of approach to RBD, overlap in buried surface and binding residues on RBD, and have substantial spatial clash with receptor angiotensin-converting enzyme-2 (ACE2) in binding to RBD. Site-directed mutagenesis confirms these common binding features although some minor differences are found. One representative antibody, P5A-3C8, demonstrates extraordinarily protective efficacy in a golden Syrian hamster model against SARS-CoV-2 infection. However, virus escape analysis identifies a single natural mutation in RBD, namely K417N found in B.1.351 variant from South Africa, abolished the neutralizing activity of these public antibodies. The discovery of public antibodies and shared escape mutation highlight the intricate relationship between antibody response and SARS-CoV-2, and provide critical reference for the development of antibody and vaccine strategies to overcome the antigenic variation of SARS-CoV-2.

Adaptive RISE control for asymptotic rigid-body attitude tracking with additive disturbances

This paper presents a novel adaptive RISE (robust integral of the sign of the error) control method for the asymptotic rigid-body attitude tracking with inertia uncertainties and bounded unstructured external C2 disturbances. By virtue of a specially constructed synthesis of modified dynamic scaling mechanism, integration by parts, and finite escape analysis, the new design provides a simple but intuitive solution to the long-standing open problem in almost all RISE-based control schemes, that is, establishing global asymptotic tracking results without information about exact bounds of the external disturbances and its derivatives. Besides significant improvement on robustness, the proposed adaptation mechanism itself can also be regarded as a new kind of non-CE (non-certainty-equivalent) adaptive formulation, where very few extra dynamic extensions are required to largely recover ideal parameter estimation performance in commonly seen non-CE designs. The structure of the proposed controller is also equivalent to an adaptive feedforward compensator plus a stable low-pass filter whose input contains high gain feedback components, which allows flexible adjustments to establish ideal transient response and avoid chattering. Numerical simulations demonstrate that the above unique features of the proposed method lead to notable advantages over the composite adaptive RISE method.

Context-Sensitive Data Race Detection for Concurrent Programs

Data races have become one of the severe issues affecting the correctness of concurrent programs. Existing detection tools for data races have many false positives and false negatives. To improve the correctness, this paper proposes a context-sensitive approach to detect data races in concurrent programs. Several program analysis techniques are conducted to reduce false positives and false negatives. First, control-flow analysis is used to construct call graphs, in which escape analysis is employed to find escaped objects among threads. Second, context-sensitive alias analysis is employed to find alias objects. Finally, happens-before analysis is conducted to reduce false positives and false negatives. We develop a prototype tool ConRacer based on WALA and evaluate it on several benchmarks. We also compare ConRacer with existing static and dynamic tools. The experimental results show that ConRacer can effectively detect data races and reduce false positives and false negatives.

Design and Implementation of an Escape Analysis in the Context of Safety-Critical Embedded Systems

The use of a managed, type-safe language such as Standard ML, Ada Ravenscar, or Java in hard real-time and embedded systems offers productivity, safety, and dependability benefits at a reasonable cost. Static software systems, that is systems in which all relevant resource entities such as threads and their priorities, for instance, and the entire source code are known ahead of time, are particularly interesting for the deployment in safety-critical embedded systems: Code verification is rather maintainable in contrast to dynamic systems. Additionally, static analyses can incorporate information from all software and system layers to assist compilers in emitting code that is well suited to an application on a particular hardware device. It was shown in the past that a program composed in type-safe Java in combination with a static system setup can be as efficient as one that is written in C [30], which is still the most widely used language in the embedded domain. Escape analysis (EA) is one of several static-analysis techniques. It supports, for instance, runtime efficiency by enabling automated stack allocation of objects. In addition, Stilkerich et al. [27, 28] have argued that EA enables further applications in safety-critical embedded systems such as the computation of memory classes stated in the Real-Time Specification for Java (RTSJ) [6]. EA can be applied to any programming language but the quality of its results greatly benefits from the properties of a type-safe language. Notably, embedded multicore devices can positively be affected by the use of EA. Thus, we explore an ahead-of-time (AOT) escape analysis in the context of the KESO JVM featuring a Java AOT compiler targeting (deeply) embedded (hard) real-time systems.

Sustainable Urban Planning Technique of Fire Disaster Prevention for Subway

Subway infrastructure is a representative urban infrastructure for sustainable urban development as part of its policy to harmonize with economic growth. As the transportation infrastructure of large cities develops with high speed and intelligence, more attention will be paid to its safety. The main cause of death in subway fires is asphyxiation, due to the closed specificity of the underground space. Therefore, smoke exhaust facilities should be capable of minimizing the effects of smoke to ensure the safe evacuation of passengers in the event of fire. In this study, three kinds of fire locations are adopted to analyze the distribution of platform temperature, CO, and visibility in connection with the smoke exhaust system operation method. We evaluate the performance of the applicable smoke exhaust system from ASET-based untenable area analysis. Fatality evaluation by escape analysis according to the smoke exhaust system estimates the fatality based on the tenability performance evaluation. Moreover, the FED method was used to evaluate tenability performance. Therefore, the result of this study suggests a solution for sustainable subway Disaster response from the performance evaluation of the subway platform smoke exhaust system for safe evacuation of passengers, which is essential for subway construction or remodeling.

Разработка внутреннего представления компилятора Kotlin / Native и оптимизаций на его основе

Kotlin is a statically typed programming language that supports object-oriented and functional programming. It supports JVM, JS and native platforms via LLVM (Kotlin / Native). The first two targets are backed with well-developed virtual machines that can perform advanced program optimizations at runtime. However, for native platforms, all optimizations must be performed at compile time. Currently Kotlin / Native lacks many optimizations, which is why the performance of the generated code is poor in many cases. This paper describes a way to solve this problem by introducing an additional SSA-based intermediate representation and implementing escape analysis using it. Experimental results have shown that this approach can significantly improve performance.

PYE

Languages like Java and C# follow a two-step process of compilation: static compilation and just-in-time (JIT) compilation. As the time spent in JIT compilation gets added to the execution-time of the application, JIT compilers typically sacrifice the precision of program analyses for efficiency. The alternative of performing the analysis for the whole program statically ignores the analysis of libraries (available only at runtime), and thereby generates imprecise results. To address these issues, in this article, we propose a two-step (static+JIT) analysis framework called precise-yet-efficient (PYE) that helps generate precise analysis-results at runtime at a very low cost. PYE achieves the twin objectives of precision and performance during JIT compilation by using a two-pronged approach: (i) It performs expensive analyses during static compilation, while accounting for the unavailability of the runtime libraries by generating partial results, in terms of conditional values , for the input application. (ii) During JIT compilation, PYE resolves the conditions associated with these values, using the pre-computed conditional values for the libraries, to generate the final results. We have implemented the static and the runtime components of PYE in the Soot optimization framework and the OpenJDK HotSpot Server Compiler (C2), respectively. We demonstrate the usability of PYE by instantiating it to perform two context-, flow-, and field-sensitive heap-based analyses: (i) points-to analysis for null-dereference-check elimination; and (ii) escape analysis for synchronization elimination. We evaluate these instantiations against their corresponding state-of-the-art implementations in C2 over a wide range of benchmarks. The extensive evaluation results show that our strategy works quite well and fulfills both the promises it makes: enhanced precision while maintaining efficiency during JIT compilation.

Restructuring AMS to reduce synchronization overheads on android system

In this paper, we present an optimization method which can be used to improve the performance of android system by reducing the synchronization overheads in the activity manager service (AMS) component. The optimization decreases the waiting time of synchronizations by dividing the original single object lock in AMS into different ones. We use an alias analysis method, i.e. escape analysis, to divide all the synchronized code blocks into different equivalence classes so that there is no intersection of objects accessed for two blocks from different equivalence classes. Then, we can use different object locks to guard these code blocks. We implemented our optimization on android 6.0, and decreased the waiting time of synchronization locks in AMS by 30.9 and 27.7% when the system starts up and runs normally. We find that the distribution of the waiting time for the synchronized lock is in accordance with the characteristics of power-law distribution.

YY1 Positively Regulates Transcription by Targeting Promoters and Super-Enhancers through the BAF Complex in Embryonic Stem Cells.

SummaryYin Yang 1 (YY1) regulates early embryogenesis and adult tissue formation. However, the role of YY1 in stem cell regulation remains unclear. YY1 has a Polycomb group (PcG) protein-dependent role in mammalian cells. The PcG-independent functions of YY1 are also reported, although their underlying mechanism is still undefined. This paper reports the role of YY1 and BAF complex in the OCT4-mediated pluripotency network in mouse embryonic stem cells (mESCs). The interaction between YY1 and BAF complex promotes mESC proliferation and pluripotency. Knockdown of Yy1 or Smarca4, the core component of the BAF complex, downregulates pluripotency markers and upregulates several differentiation markers. Moreover, YY1 enriches at both promoter and super-enhancer regions to stimulate transcription. Thus, this study elucidates the role of YY1 in regulating pluripotency through its interaction with OCT4 and the BAF complex and the role of BAF complex in integrating YY1 into the core pluripotency network.

Eliminating object reference checks by escape analysis on real-time Java virtual machine

The real-time specification for Java (RTSJ) makes Java to be a real-time programming language. However, the RTSJ’s memory management system is more complicated than J2SE’s. The assignment rules of RTSJ, which prevent the creation of dangling references, must be checked by real-time Java virtual machines (JVMs) at run-time. These frequent run-time object reference checks introduce significant time overheads and unpredictable execution time, which has great impact on real-time systems. This paper presents an equivalence class based, context sensitive and flow insensitive escape analysis algorithm that effectively eliminates unnecessary run-time reference checkpoints of RTSJ programs. The optimization framework has been implemented in an open-source real-time JVM namely jRate and evaluated by CD$$_x$$, a relative authority real-time Java benchmark suite. The results show that this optimization algorithm eliminates more than 90% static reference checkpoints, removes about 50% run-time reference checkpoints on average , and improves the run-time performance of average 3.13%, max 8.93%.

The Perfect Getaway

The use of a managed, type-safe language such as Java in real-time and embedded systems offers productivity and, in particular, safety and dependability benefits at a reasonable cost. It has been shown for commodity systems that Escape Analysis (EA) enables a set of useful optimizations, and benefits from the properties of a type-safe language. In this article, we explore the application of escape analysis in KESO [Stilkerich et al. 2012], a Java ahead-of-time compiler targeting embedded real-time systems. We present specific applications of EA for embedded programs that go beyond the widely known stack-allocation and synchronization optimizations such as extended remote-procedure-call (RPC) support for software-isolated applications, automated inference of immutable data, or improved upper space and time bounds for worst-case estimations.

Characterization of glycol chitosan grafted with low molecular weight polyethylenimine as a gene carrier for human adipose-derived mesenchymal stem cells

Mesenchymal stem cells (MSCs) have a great capacity for self-renewal while still maintaining their multipotency, and can differentiate into a variety of cell types. The delivery of genes to a site of injury is a current and interesting field of gene therapy. In the present study, we describe a nonviral gene delivery carrier, glycol chitosan-methyl acrylate-polyethylenimine (GMP) polymer targeted towards human adipose-derived mesenchymal stem cells (AD-MSCs). Transfection efficiency, using luciferase (Luc) and a pDNA encoding enhanced green fluorescent protein (EGFP), along with cytotoxicity assays, were performed in human AD-MSCs. The results show that the transfection efficiency of the GMP polymer was similar to that of PEI25kD, and the cytotoxicity was lower. Moreover, human AD-MSCs were treated with the GMP polymer/pDNA polyplex and its cellular uptake and distribution were analyzed by flow cytometry and confocal microscopy. Furthermore, we performed endosomal escape analysis using LysoTracker Red, and found that the conjugated GMP polymer could escape from the endosome to the cytosol. Human AD-MSCs treated with the GMP polymer maintained their potential for osteogenic differentiation and phenotypic expression of human AD-MSCs based on flow cytometry analysis. The present study demonstrates that the GMP polymer can be used as a potential targeted–delivery carrier for effective gene delivery.