bluuebunny/crossref_metadata_2025_split huggingface dataset:
TracerX: Pruning Dynamic Symbolic Execution with Deletion and Weakest Precondition Interpolation (Competition Contribution)
Authors: Dutta Arpita , Maghareh Rasool , Jaffar Joxan , Godboley Sangharatna , Yu Xiao Liang 
Published: April 2024

AbstractDynamic Symbolic Execution (DSE) is an important method for the testing of programs. The major advantage of DSE is its path-by-path exploration of the program execution space. However, this often leads to the path explosion problem. To address this issue, a method of abstraction learning has been used. The key step here is the computation of an interpolant to represent the learned abstraction. In Test-Comp 2024, we use two different approaches of interpolant generation viz., Deletion Interpolation and Weakest Precondition Interpolation. The former is our more stable and mature system and briefly discussed in [8]. In this paper, we present the latter approach which is the heart of TracerX. In general, the Weakest Precondition (WP) is the ideal (most general) interpolant. However, WP is intractable to compute and is exponentially disjunctive. A major challenge is to obtain a conjunctive approximation of the WP. Therefore, we generate an approximation of the WP.
Ultimate TestGen: Test-Case Generation with Automata-based Software Model Checking (Competition Contribution)
Authors: Barth Max , Dietsch Daniel , Heizmann Matthias , Jakobs Marie-Christine 
Published: April 2024

AbstractWe introduce Ultimate TestGen, a novel tool for automatic test-case generation. Like many other test-case generators, Ultimate TestGen builds on verification technology, i.e., it checks the (un)reachability of test goals and generates test cases from counterexamples. In contrast to existing tools, it applies trace abstraction, an automata-theoretic approach to software model checking, which is implemented in the successful verifier Ultimate Automizer. To avoid that the same test goal is reached again, Ultimate TestGen extends the automata-theoretic model checking approach with error automata.
Combining Look-ahead Design-time and Run-time Control-synthesis for Graph Transformation Systems
Authors: Xu He , Schneider Sven , Giese Holger 
Published: April 2024

AbstractThe correct operation of safety-critical cyber-physical systems is crucial. However, such systems often feature a large variability of start configurations, an intractably large state space, a high degree of uncertainty, or inherently unsafe behavior. A model of the expected system behavior starting in the current state can be used by look-ahead controllers to derive control decisions to avoid paths to safety violations when possible. However, the computational effort for deriving and analyzing the future system behavior is exponential in the look-ahead.In this paper, we employ Graph Transformation Systems (GTSs) for the modeling of expected system behavior. We then combine design-time and run-time control synthesis based on Supervisory Control Theory (SCT) achieving an exponential cost-reduction for a given controller look-ahead. For a fixed required reaction time of controllers, much longer look-aheads may therefore be employed. To illustrate and evaluate our approach, we consider a system where shuttles must avoid collisions with ambulances at level crossings.
Formal Specification of Trusted Execution Environment APIs
Authors: Yu Geunyeol , Chae Seunghyun , Bae Kyungmin , Moon Sungkun 
Published: April 2024

AbstractTrusted execution environments (TEEs) have emerged as a key technology in the cybersecurity domain. A TEE provides an isolated environment in which sensitive computations can be executed securely. Trusted applications running in TEEs are developed using standardized APIs that many hardware platforms for TEE adhere to. However, formal models tailored to standard TEE APIs are not well developed. In this paper, we present a formal specification of TEE APIs using Maude. We focus on Trusted Storage API and Cryptographic Operations API, which are foundational to mobile and IoT applications. The effectiveness of our approach is demonstrated through formal analysis of MQT-TZ, an open-source TEE application for IoT. Our formal analysis has revealed security vulnerabilities in the implementation of MQT-TZ, and we patch and confirm its integrity using model checking.
Comprehending Object State via Dynamic Class Invariant Learning
Authors: Boockmann Jan H. , Lüttgen Gerald 
Published: April 2024

AbstractMaintaining software is cumbersome when method argument constraints are undocumented. To reveal them, previous work learned preconditions from exemplary valid and invalid method arguments. In practice, it would be highly beneficial to know class invariants, too, because functionality added during software maintenance must not break them. Even more so than method preconditions, class invariants are rarely documented and often cannot completely be inferred automatically, especially for objects exhibiting complex state such as dynamic data structures.This paper presents a novel dynamic approach to learning class invariants, thereby complementing related work on learning method preconditions. We automatically synthesize assertions from an adjustable assertion grammar to distinguish valid and invalid objects. While random walks generate valid objects, a combination of bounded-exhaustive testing techniques and behavioral oracles yield invalid objects. The utility of our approach for code comprehension and software maintenance is demonstrated by comparing our learned invariants to documented invariant validation methods found in real-world Java classes and to the invariants detected by the Daikon tool.
Smart Issue Detection for Large-Scale Online Service Systems Using Multi-Channel Data
Authors: Chen Liushan , Pei Yu , Wan Mingyang , Fei Zhihui , Liang Tao , Ma Guojun 
Published: April 2024

AbstractGiven the scale and complexity of large online service systems and the diversity of environments in which the services are to be invoked, it is inevitable that those service systems contain bugs that affect the users. As a result, it is essential for service providers to discover issues in their systems based on information gathered from users. iFeedback is a state-of-the-art technique for user-feedback-based issue detection. While it has been deployed to help detect issues in real-world service systems, the accuracy of iFeedback’s detection results is relatively low due to limitations in its design. In this paper, we propose theSkyNettechnique and tool that analyzes both user feedback gathered via specific channels and public posts collected from social media platforms to more accurately detect issues in service systems. We have applied the tool to detect issues for three real-world, large-scale online service systems based on their historical data gathered over a ten-month period of time.SkyNetreported in total 2790 issues, among which 93.0% were confirmed by developers as reflecting real problems that deserve their close attention. It also detected 58 out of the 62 severe issues reported during the period, achieving a recall of 93.5% for severe issues. Such results suggestSkyNetis both effective and accurate in issue detection.
Industry 5.0 and Artificial Semi-General Intelligence. Exploring Future Challenges and Opportunities Within Industries and Societies
Authors: Grybauskas Andrius 
Published: April 2024

AbstractIndustry 4.0 has been dramatically impacted by artificial intelligence technology in recent decades which has led to both positive and negative outcomes. The increased productivity and better optimization processes allowed factories to be more efficient, however, due to ever-expanding artificial intelligence capabilities certain work professions are at risk of automation. Thus, Industry 5.0 emerged as a movement that is supposed to lead to a more cohesive, resilient, and stable society. Nonetheless, a new rise of artificial semi-general intelligence is right around the corner, which delivers unprecedented digital cognitive abilities which could either be net positive or negative on society. For these reasons, this chapter attempts to discuss and unpack some of the current artificial intelligence projections, and the possible impact on industries and societies.
Gravitational production of sterile neutrinos
Authors: Koutroulis Fotis , Lebedev Oleg , Pokorski Stefan 
Published: April 2024

Abstract
We consider gravitational production of singlet fermions such as sterile neutrinos during and after inflation. The production efficiency due to classical gravity is suppressed by the fermion mass. Quantum gravitational effects, on the other hand, are expected to break conformal invariance of the fermion sector by the Planck scale-suppressed operators irrespective of the mass. We find that such operators are very efficient in fermion production immediately after inflation, generating a significant background of stable or long-lived feebly interacting particles. This applies, in particular, to sterile neutrinos which can constitute cold non-thermal dark matter for a wide range of masses, including the keV scale.
Impact of the COVID-19 pandemic on young adults’ mental health and beyond: a qualitative investigation nested within an ongoing general population cohort study
Authors: Wiedemann Anna , Jones Peter B. , Burn Anne-Marie 
Published: April 2024

Abstract
Purpose
Initial discussions about the COVID-19 pandemic often overlooked its impact on young adults. By employing a qualitative approach nested within an ongoing general population cohort study, we seek to fill a gap in the literature by providing insights into the longer-term impact on this demographic.

Methods
Data collection involved the use of in-depth semi-structured interviews. Using a pre-determined sampling frame, we purposively recruited 30 participants based on age, gender, ethnicity, and deprivation from the Neuroscience in Psychiatry Network (NSPN). The NSPN cohort, established in 2012, consists of 2403 young people aged 14–24 at baseline, recruited from Greater London and Cambridgeshire. Interviews were conducted in Autumn 2022; data were analysed using the framework method.

Results
Participants were on average 28 years old (SD = 3 years, range 24–34 years; 53.3% female). The sample comprised individuals from diverse ethnic backgrounds, with 40% from non-White ethnic groups. Many young adults reported profound personal growth and a stronger sense of resilience, a perception observed across varying levels of anxiety or depression. Nevertheless, we observed substantial disruptions to their personal and professional lives such as returning to their parents’ homes, often deferring other life plans, lacking mental health support, and encountering significant career challenges.

Conclusion
Our findings highlight the complexity of pandemic impacts, demonstrating the need for supportive policies and further research to understand the circumstances under which genuine personal growth occurs, whether it is enduring or transient, and which factors influence it.
Modelling the weld cladding process to predict weld clad position and shape error
Authors: Votruba Vojtěch , Fornůsek Tomáš , Havlan Tomáš , Kratěna Tomáš , Smolík Jan 
Published: April 2024

AbstractWire arc additive manufacturing (WAAM) is one of the most productive metal additive manufacturing methods. One of its most promising applications holds in the manufacturing of difficult-to-cut materials where production costs can be reduced with minimizing the time of machining and total tool costs. To develop a correct WAAM, technological processes for manufacturing complex-shaped components welding torch path corrections and welding power corrections have to be made especially in critical sections such as corners and sharp edges. A predictive mathematical model of the material cladding during the WAAM process has been developed for the purposes of generating an optimal toolpath of the WAAM clads. This predictive mathematical model is simplified to reflect the important physical phenomena in the weld pool but also to optimize computing time. In this paper, the principle of the mathematical model is described, and its functionality is verified by the welding experiments with five different welding power settings. For the initial calibration of the model parameters single straight-line weld clads with 5 different welding power settings (wire feeds) ranging from 5.0 to 8.6 m/min were investigated. 3D scans of these welded samples are used for the verification. With the calibrated simulation model, it was possible to predict the precise shape with a maximum deviation circa 0.20 mm. The start portions of the weld clads seem more complex having the deviation circa 0.30 mm. These are valuable results as the WAAM technology is generally considered to be reasonably rough.
Novel rat model of gaming disorder: assessment of social reward and sex differences in behavior and c-Fos brain activity
Authors: Casile Antonino , Marraudino Marilena , Bonaldo Brigitta , Micioni Di Bonaventura Maria Vittoria , Nasini Sofia , Cifani Carlo , Gotti Stefano 
Published: April 2024

Abstract
Rationale
In 2018, the International Classification of Diseases (ICD-11) classified Gaming Disorder (GD) as a mental disorder. GD mainly occurs among adolescents, who, after developing addiction, show psychopathological traits, such as social anxiety, depression, social isolation, and attention deficit. However, the different studies conducted in humans so far show several limitations, such as the lack of demographic heterogeneity and equal representation of age, differences in the type of game and in the follow-up period. Furthermore, at present, no animal models specific to GD are available.

Objectives
To address the lack of an experimental model for GD, in the present work, we proposed a new GD rat model to investigate some peculiar tracts of the disorder.

Methods
Two-month-old Wistar Kyoto rats, both males and females, were subject to a five-week training with a new innovative touch-screen platform. After five weeks of training, rats were assessed for: (a) their attachment to the play under several conditions, (b) their hyperactivity during gaming, and (c) the maintenance of these conditions after a period of game pause and reward interruption. After sacrifice, using immunohistochemistry techniques, the immunoreactivity of c-Fos (a marker of neuronal activity) was analyzed to study different neural areas.

Results
After the training, the rats subjected to GD protocol developed GD-related traits (e.g., hyperactivity, loss control), and the behavioral phenotype was maintained consistently over time. These aspects were completely absent in the control groups. Lastly, the analysis of c-Fos immunoreactivity in prelimbic cortex (PrL), orbitofrontal cortex (OFC), nucleus Accumbens, amygdala and bed nucleus of stria terminalis (BNST) highlighted significant alterations in the GD groups compared to controls, suggesting modifications in neural activity related to the development of the GD phenotype.

Conclusions
The proposal of a new GD rat model could represent an innovative tool to investigate, in both sexes, the behavioral and neurobiological features of this disorder, the possible role of external factors in the predisposition and susceptibility and the development of new pharmacological therapies.
Quality of life after immune suppressive therapy in aplastic anemia
Authors: Lommerse Iris N. , Hinnen Chris , van Vliet Liesbeth M. , Schubert Beke , Panse Jens , Halkes Constantijn J. M. , Tjon Jennifer M.-L. 
Published: April 2024

AbstractAcquired aplastic anemia (AA) is a rare form of immune-mediated bone marrow failure, which can result in life-threatening infections or bleeding if left untreated. Treatment consists of either immune suppressive therapy (IST) or allogeneic stem cell transplantation (alloHSCT). While considerable research has been published regarding survival, response rate and toxicity of both treatments, knowledge on the impact on quality of life (QoL) is scarce. We used the recently developed AA-specific QoL questionnaire (QLQ-AA/PNH-54) to evaluate QoL in a single center cohort of AA patients who were successfully treated with IST. The 54 questions represent 12 different QoL domains. Results were analyzed for all patients and grouped based on hematologic response (complete response (CR) or partial response (PR)). Thirty-six successfully treated adult patients (15 in CR, 21 in PR) completed the questionnaire (median age 54 years, range 21–71; median time since last IST 5 years, range 0–41). Fatigue was experienced by 83% of patients. Even though total QoL scores did not significantly differ between patients with PR and CR (105 vs 92, p-value 0,17) there appeared to be a trend towards higher scores in patients with PR, especially in domains concerning psychological wellbeing. This trend was most clear in the domains fear of progression (2,12 in PR patients vs 1,73 in CR patients; p-value 0,08) and role functioning (2,22 vs 1,88; p-value 0,07). In conclusion, patients with AA continue to experience psychological and physical effects despite successful IST.
Synthesis and characterization of novel azo-chitosan polymer derivatives for the antimicrobial activity
Authors: Taha Ahmed G. , Hezma A. M. 
Published: April 2024

AbstractAzo-Chitosan-dimethylaniline polymer derivatives are promising polymers for biological applications. In this paper, chitosan reacted with 4-nitrosodimethylaniline to form azo-chitosan-dimethylaniline polymer (Chs-DAN) as the novel polymer via condensation reaction. Chs-DAN modificated by doping it with zinc oxide nanoparticles (ZnO NPs) and insertion it into betacyclodextrine cycle (βCD) to give Chitosan-dimethylaniline/ZnO (Chs-DAN/ZnO NPs) and Chitosan-dimethylaniline/βCD (Chs-DAN/βCD). The generated polymers were confirmed by using XRD, FTIR and SEM analysis. Gram + ve and Gram − ve antimicrobial as well as antifungal activities have been evidenced for all samples. The antimicrobial analysis showed that the synthesized chitosan derivatives (Chs-DAN, Chs-DAN/βCD, Chs-DAN/ZnO NPs) exhibited noticeable antimicrobial and antifungal activities as compared to pure samples (Chs, DAN, ZnO NPs, βCD).
Short-term effect of liquid organic fertilisation and application methods on N2, N2O and CO2 fluxes from a silt loam arable soil
Authors: Grosz Balázs , Burkart Stefan , Well Reinhard 
Published: April 2024

AbstractThe absence of N2 flux measurements in liquid manure-amended soils has resulted in a poor understanding of the effect of manure application on gaseous N losses. The aim of this study was to quantify N2, N2O, CO2, N2O reduction to N2, depth distribution of moisture, water-extractable organic C, NO3−, NH4+, pH, and diffusivity in a laboratory incubation experiment with an arable silt-loam soil. To quantify N processes and gaseous fluxes, 15N tracing was applied. An artificial livestock slurry-mixture was added to the soil in various treatments (control, surface or injected application; slurry-application rate: 42.9 kg N ha− 1; soil water content of either 40% or 60% water-filled pore space (WFPS)). The soil was incubated for 10 days. The depth distribution of the control parameters was measured twice during the experiment on days 5 and 10. The average increase in N2 and N2O fluxes from denitrification was about 900% in slurry-amended soils. The highest N2 and N2O fluxes from denitrification were measured in the slurry injection, 60% WFPS treatment (7.83 ± 3.50 and 11.22 ± 7.60 mg N m− 2 d− 1, respectively). The hypothesis that injected slurry at a higher water content enhances denitrification was confirmed. This study provides important insights into the formation, spatial and temporal variation of the manure-soil hotspot and its impact on the denitrification process. The results will form part of a dataset to develop, improve and test manure application submodules of biogeochemical models and will help to understand in detail the effect of hotspots on N-cycling in manure-treated soils.
Does vaginal bacterial colonization contribute to preterm birth in women with asymptomatic shortened cervix?
Authors: Steetskamp J. , Zander M. , Laufs V. , Elger T. , Hasenburg A. , Skala C. 
Published: April 2024

Abstract
Purpose
The aim of this study is to describe the typical microbial spectrum and the influence of distinct vaginal infections on preterm birth in pregnancies affected by cervical incompetence.

Methods
327 patients were admitted because of asymptomatic shortening of the cervix in the second and third trimester of pregnancy. Clinical data such as age, cervical length, gestational age at admission and at delivery and vaginal microbiologic findings were collected and analyzed.

Results
The spectrum of germs in the vagina revealed seven different distinct species; the most common bacteria were Ureaplasma spp. and E. coli. In 327 included patients, 217 revealed a bacterial colonization, 110 did not. Most common bacteria in women with preterm birth before 34 weeks were Ureaplasma spp., while E. coli was most common in women undergoing preterm birth after 34 weeks. Nevertheless, the rates of occurrence of these bacterial taxa were not significantly different between who underwent preterm birth to those who did not.

Conclusions
This study gives an overview over the vaginal bacterial colonization in pregnant women with cervical incompetence. The clinical relevance of vaginal bacterial colonization remains unclear.
Sleep disturbances in late pregnancy: associations with induction of labor
Authors: Lähde Henna , Karlsson Hasse , Karlsson Linnea , Perasto Laura , Varis Viliina , Rinne Kirsi , Paavonen E. Juulia , Polo-Kantola Päivi 
Published: April 2024

Abstract
Purpose
Sleep disturbances, which are common during pregnancy, may compromise labor. Nevertheless, little is known about associations between sleep disturbances and the likelihood of ending up induction of labor (IOL). Accordingly, we aimed to evaluate the connections between sleep disturbances during pregnancy and IOL.

Methods
Altogether 1778 women from the FinnBrain Birth Cohort Study with gestation weeks over 37 + 6 were enrolled in the study. The women were divided into IOL (n = 331) and spontaneous onset of labor (SOL, n = 1447) groups. Sleep disturbances in late pregnancy were evaluated using the Basic Nordic Sleep Questionnaire. Logistic regression analyses were conducted with adjustments for age, body mass index, parity, smoking, and depressive symptoms.

Results
Sleep disturbances were frequent in both IOL and SOL groups. In the IOL group 43.0% and in the SOL group 39.0% had poor general sleep quality (P = 0.186). Nocturnal awakenings occurred most commonly, in 94.0% and 93.9%, respectively (P = 0.653). In the IOL group, more women (22.7%) were habitual snorers than in the SOL group (17.0%, P = 0.017), however, the difference lost the statistical significance in adjusted analysis (P = 0.848). Women in the IOL group were more likely to be short sleepers (< 7 h) compared to those in the SOL group (20.2% and 15.4%, respectively, P = 0.034) with no difference after adjustment (P = 0.133). The two groups showed no differences in sleep loss (P = 0.252).

Conclusions
Deterioration in sleep quality was noticeable in pregnant women, but it was unconnected with IOL. As the frequency of IOL is increasing, more research for related risk factors is needed.