bluuebunny/crossref_metadata_2025 huggingface dataset:
Fear facilitates utilitarian moral judgments: Evidence from a moral judgment task
Authors: Tao Yanqiang , Dong Jia , Niu Haiqun , Lv Yichao , He Xiaoyan , Zhang Shuang , Liu Xiangping
Published: July 2023

Previous research on moral judgment (MJ) has focused on understanding the cognitive processes and emotional factors that influence different types of moral judgment tasks, such as personal and impersonal dilemmas. However, few studies have distinguished between the emotions related to cognition and the complex emotions specifically caused by MJ tasks. This gap in knowledge is important to address to have a better understanding of how emotions influence moral judgment. The aim of this study was to investigate the influence of fear and the role of moral emotions on MJ. Data were collected from 145 participants through jsPsych and analyzed using mixed‐model analysis of variance (ANOVA) and correlation analysis. The study found that individuals who were triggered by the fear increased the number of utilitarian moral judgments in personal moral scenarios and lengthened the cognitive process, but not in impersonal moral dilemmas. Hence, we speculate that fear may play a cognitive role in personal moral dilemmas and an emotional role in impersonal moral dilemmas. Another finding is that the complex moral emotions arising from the moral decision‐making process may affect the effectiveness of fear and potentially influence moral judgments. However, this study adopts a cautious attitude toward these discoveries, and further verification of this hypothesis should be conducted in the future.
Clinical and genetic findings in 13 Chinese children with keratinopathic ichthyosis
Authors: Yang Zhou , Xu Zhe , He Rui , Xiang Xin , Zhang Bin , Ma Lin
Published: July 2023

Importance

Keratinopathic ichthyosis (KPI) represents a group of predominantly autosomal dominant genodermatoses resulting from mutations in the KRT1, KRT2, or KRT10 genes. In KPI, the relationship between genotype and phenotype is complex.

Objective

To analyze the clinical manifestations and gene mutations in Chinese patients with KPI.

Methods

Clinical data were collected from 13 children diagnosed with KPI, and peripheral blood DNA samples were extracted from both the patients and their parents Next‐generation sequencing was performed using a congenital ichthyosis multi‐gene panel, and the selected variants in the patients and their parents were further validated using the Sanger sequencing method.

Results

Genetic analysis identified missense mutations in either KRT1 or KRT10 in ten patients exhibiting varying degrees of severity and distinct features of epidermolytic ichthyosis. A missense hotspot mutation in KRT2 was identified in one patient with superficial epidermolytic ichthyosis. Additionally, two truncation mutations in KRT10 were detected, leading to the development of generalized ichthyosiform erythroderma. Ear malformation and ectropion at birth, scalp involvement, and palmoplantar hyperkeratosis were observed as early signs of ichthyosis with confetti.

Interpretation

We analyzed the genotype‐phenotype correlations in KPI, revealing that the types and locations of different mutations are associated with distinct phenotypic characteristics. Oral acitretin could be considered a treatment option for severe patients at an appropriate dosage and timing.
Comparative effectiveness of sodium‐glucose cotransporter‐2 inhibitors among patients with heart failure with preserved ejection fraction
Authors: Riaz Munaza , Smith Steven M. , Dietrich Eric A. , Winchester David E. , Guo Jingchuan , Park Haesuk
Published: July 2023

Background

Sodium‐glucose cotransporter‐2 inhibitors (SGLT2i) are recommended by the American Heart Association for management of heart failure with preserved ejection fraction (HFpEF), but little is known about their in‐class comparative effectiveness in real‐world settings.

Objectives

To assess the in‐class comparative effectiveness of SGLT2i for preventing HF‐related and all‐cause hospitalizations among patients with HFpEF.

Methods

Using MarketScan® Commercial and Medicare Supplemental research databases (2012–2020), this cohort study included adults with HFpEF treated with SGLT2i. Stabilized inverse probability treatment weighted Cox proportional hazards regression was used to compare HF‐related and all‐cause hospitalizations in three pairwise comparisons: dapagliflozin versus canagliflozin, empagliflozin versus canagliflozin, and dapagliflozin versus empagliflozin. Subgroup and sensitivity analyses were conducted to assess robustness of the main analysis.

Results

In total, 3629 SGLT2i users (881 dapagliflozin, 1120 canagliflozin, and 1628 empagliflozin) were included. Compared with canagliflozin, dapagliflozin was associated with decreased risk of HF‐related hospitalization (adjusted hazard ratio [aHR], 0.75; 95% confidence interval [CI], 0.56–1.01) and all‐cause hospitalization (aHR, 0.84; 95% CI 0.73–0.97). Compared with canagliflozin, empagliflozin was associated with 55% decreased risk of HF‐related hospitalization (aHR, 0.45; 95% CI 0.34–0.59) and 18% decreased risk of all‐cause hospitalization (aHR, 0.82; 95% CI 0.73–0.93). Compared with empagliflozin, dapagliflozin was associated with 50% increased risk of HF‐related hospitalization (aHR, 1.50; 95% CI 1.09–2.07) and a statistically nonsignificant increase in the risk of all‐cause hospitalization (aHR, 1.05; 95% CI 0.92–1.20).

Conclusions

Compared with canagliflozin or dapagliflozin use, empagliflozin use was associated with decreased risk of HF‐related and all‐cause hospitalizations. Compared with canagliflozin, dapagliflozin was associated with a reduced risk of HF‐related and all‐cause hospitalizations.
Protein–protein association properties of human βB2‐crystallins
Authors: Velasco‐Bolom José‐Luis , Domínguez Laura
Published: July 2023

Protein–protein association events are involved in many physiological and pathological processes. Cataract disease is a pathology that manifests protein aggregation of crystallins. β‐Crystallins are present in a high proportion in the eye lens. Therefore, the structural study of the dimerization properties of crystallins can shed light on the first stages of protein aggregation. In the present work, we examine the protein–protein association profiles of the human βB2‐crystallin by employing extensive coarse‐grained molecular dynamics (CG‐MD) and the Markov state analysis. Interestingly, our results clearly show important changes in the protein dimerization kinetics between wt‐HβB2C and the deamidated systems. The two systems show dimeric conformations. However, the association and dissociation rates are very different. Our results show that the deamidated system can associate faster and dissociate slower than the wt‐ HβB2C. The deamidated system is in a slightly opened conformation with the Greek‐key motifs well folded, suggesting that a complete unfolding of the protein is not required for aggregation. Our results describe the first stages of crystallin aggregation due to post‐translational modifications.
Inclusion of binary proxy variables in logistic regression improves treatment effect estimation in observational studies in the presence of binary unmeasured confounding variables
Authors: Rosenbaum Cornelius , Yu Qingzhao , Buzhardt Sarah , Sutton Elizabeth , Chapple Andrew G.
Published: July 2023

We present a simulation study and application that shows inclusion of binary proxy variables related to binary unmeasured confounders improves the estimate of a related treatment effect in binary logistic regression. The simulation study included 60,000 randomly generated parameter scenarios of sample size 10,000 across six different simulation structures. We assessed bias by comparing the probability of finding the expected treatment effect relative to the modeled treatment effect with and without the proxy variable. Inclusion of a proxy variable in the logistic regression model significantly reduced the bias of the treatment or exposure effect when compared to logistic regression without the proxy variable. Including proxy variables in the logistic regression model improves the estimation of the treatment effect at weak, moderate, and strong association with unmeasured confounders and the outcome, treatment, or proxy variables. Comparative advantages held for weakly and strongly collapsible situations, as the number of unmeasured confounders increased, and as the number of proxy variables adjusted for increased.
How does global trade in environmental goods contribute to theSDGsin developing countries?
Authors: Wang Peiyu , Mao Xiyan , Huang Xianjin
Published: July 2023

Global trade in environmental goods (EGs) has provided a new vision for international cooperation in response to sustainable development goals (SDGs). However, there are ongoing debates over whether developing countries can achieve sustainability during their trade participation. This study proposes a conceptual framework to observe countries' current trade status and potential for benefit from global EG trade. By tracing the changing status of 142 countries in the conceptual framework during 2001–2019, this study finds that global EG trade reduces inequality among developed countries while it increases inequality among developing countries. Some emerging market countries may enhance their status in the global trade network, but their upgrading within the global value chain remains slow. The current poor EG trade state and limited benefit potential of most developing countries will have a non‐significant impact in terms of achieving the SDGs. The study suggests that regional trade will give developing countries a better chance to integrate into trade markets and support them toward achieving the SDGs.
Atomic Force Microscopy Analysis of Aluminum Layer Properties and Correlation to Masking Functionality in Copper Plating Metallization for Solar Cells
Authors: Hatt Thibaud , Morawietz Tobias , Bartsch Jonas , Tutsch Leonard , Glatthaar Markus
Published: July 2023

The native AlOxgrown on a thin sputtered aluminum layer can be used as mask for electroplating copper, e.g., for metallizing silicon heterojunction (SHJ) solar cells. Effects that influence the masking quality for selective electroplating are studied herein. Atomic force microscopy characterization in PeakForce mode highlights the presence of some insulation defects in the native AlOxdue to local contamination, pinholes, or tunneling currents. A focused ion beam/scanning electron microscopy analysis is further conducted to understand some defects in detail. The AlOxinsulation can be improved by adsorbing a self‐assembled monolayer, which is mainly required along the process sequence to adjust the surface wetting of the Al for optimal NaOHaqprinting. The mask quality and complete metallization sequence for solar cells are demonstrated on industrial SHJ precursors. Inkjet‐ and FlexTrail‐printing of NaOHaqare shown to be suitable to pattern the Al layer. Promising conversion efficiency comparable to screen‐printing reference is reached on large area.
What plant breeding may (and may not) look like in 2050?
Authors: Bassi Filippo M. , Sanchez‐Garcia Miguel , Ortiz Rodomiro
Published: July 2023

At the turn of 2000 many authors envisioned future plant breeding. Twenty years after, which of those authors’ visions became reality or not, and which ones may become so in the years to come. After two decades of debates, climate change is a “certainty,” food systems shifted from maximizing farm production to reducing environmental impact, and hopes placed into GMOs are mitigated by their low appreciation by consumers. We revise herein how plant breeding may raise or reduce genetic gains based on the breeder's equation. “Accuracy of Selection” has significantly improved by many experimental‐scale field and laboratory implements, but also by vulgarizing statistical models, and integrating DNA markers into selection. Pre‐breeding has really promoted the increase of useful “Genetic Variance.” Shortening “Recycling Time” has seen great progression, to the point that achieving a denominator equal to “1” is becoming a possibility. Maintaining high “Selection Intensity” remains the biggest challenge, since adding any technology results in a higher cost per progeny, despite the steady reduction in cost per datapoint. Furthermore, the concepts of variety and seed enterprise might change with the advent of cheaper genomic tools to monitor their use and the promotion of participatory or citizen science. The technological and societal changes influence the new generation of plant breeders, moving them further away from field work, emphasizing instead the use of genomic‐based selection methods relying on big data. We envisage what skills plant breeders of tomorrow might need to address challenges, and whether their time in the field may dwindle.
Histological characteristics of a uterine hemangiosarcoma in a Brazilian Girolando cow
Authors: de Souza Giovanna Gati , Dinau Fernando Carmona , Ximenes Pedro Pol , de Moura Fernanda Barthelson Carvalho , Contel Isabeli Joaquim , Braga Iolanda Simões , Pelaquim Isadora Fernanda , Rocha Noeme Sousa
Published: July 2023

A 7‐year‐old, pregnant dairy cow of the Girolando breed, weighing 450 kg, was referred to a veterinary hospital, presenting with lateral recumbency for 2 days. No health or reproductive alterations had ever been reported on the property of origin. A fetotomy was conducted at the hospital's reproductive care unit after purulent vaginal discharges, and no signals of fetal viability were observed, indicating an abortive process. The patient died within 24 hours following the reproductive intervention. A postmortem examination was performed, which revealed uterine alteration, comprising a bluish‐black, nondelimited, focally extensive mass in the region of the serous wall, involving the uterine corpus and horns and presenting diffuse haemorrhage without mucosal involvement. Histopathological examination confirmed the diagnosis of hemangiosarcoma. Uterine endothelial cells were Ki67‐positive, revealing proliferative activity of the neoplasm.
Megaoesophagus in a pet rabbit
Authors: Muffat‐es‐Jacques Patricia , Raymond Paul , Renard Jade , Combes Anais , Pignon Charly
Published: July 2023

A 1‐year‐old, male, lop‐eared rabbit presented for anorexia and weakness. A dental trim and medical treatment for gastrointestinal stasis were implemented. Owners reclaimed the animal after 2 days. Two‐weeks later, its condition had worsened, and regurgitation was observed. Thoracic radiographs followed by barium contrast oesophagram revealed bronchopneumonia and megaoesophagus. A computed tomographic examination ruled out any structural compression (tumours, vascular ring anomalies). Treatment with assisted feeding, antibiotics and sildenafil was started. Increased regurgitations and worsening respiratory distress were observed. The rabbit died 16 days later. At postmortem examination, the oesophagus was dilated and filled with food, and the lungs showed patchy pneumonia and lobular consolidation. Generalised muscular atrophy and pericardial effusion were observed. Histopathological examination revealed severe broncho‐ and aspiration pneumonia, and moderate multifocal muscle degeneration affecting skeletal, lingual and oesophageal muscle and myocardium. The final diagnosis was acquired megaoesophagus. This is the first report of megaoesophagus in a rabbit.
Evaluation of replicate sampling using hierarchical spatial modeling of population surveys accounting for imperfect detectability
Authors: Camp Richard J. , Asing Chauncey K. , Banko Paul C. , Berry Lainie , Brinck Kevin W. , Farmer Chris , Genz Ayesha S.
Published: July 2023

Effective species management and conservation benefit from knowledge of species distribution and status. Surveys to obtain that information often involve replicate sampling, which increases survey effort and costs. We simultaneously modeled species distribution, abundance and spatial correlation, and compared the uncertainty in replicate abundance estimates of the endangered palila (Loxioides bailleui) using hierarchical generalized additive models with a soap film smoother that incorporated random effects for visit. Based on survey coverage and detections, we selected the 2017 point‐transect distance sampling survey on Mauna Kea, Hawai‘i Island, for our modeling. Our modeling approach allowed us to account for imperfect detections, control the effects of boundary features, and generate visit‐specific density surface maps. We found that visit‐specific smooths were nearly identical, indicating that little information was gained from a subsequent visit, and that most of the estimator uncertainty was derived from within‐visit variability. Scaling back the palila survey to a single visit would halve the survey effort and logistical costs and increase efficiencies in data management and processing. Changing the sampling protocol warrants careful consideration and our findings may help management and regulatory agencies by maximizing efficiency and minimizing costs of surveying protocols, while providing guidelines on how to best collect information critical to species' conservation.
Onboarding and Preliminary Functionality Training
Authors: Witczak Marcin , Seybold Lothar , Bulach Eric , Maucher Niko
Published: July 2023

The objective of this chapter is to introduce the reader into the KIS.ME IoT platform, which is divided into the hardware and cloud-based software layers. In particular, we start with the registration and onboarding of the IoT hardware. Subsequently, a hierarchical system overview is provided pertaining to users as well as assets and their digital twins. The chapter discusses also an intuitive concept of Datapoints, which constitute the main source of knowledge about the current status of an asset. The rest of the chapter is devoted to placing assets inside workspaces and associating them with a set of functional rules. After a comprehensive introduction to Rule engine, the reader is guided towards topics related to analysing the efficiency of the system associated with KIS.ME. The chapter is summarized with a set of exercises motivating the reader to obtain further skills pertaining to practical applications of the modern IoT.
Incremental Dead State Detection in Logarithmic Time
Authors: Stanford Caleb , Veanes Margus
Published: July 2023

Identifying live and dead states in an abstract transition system is a recurring problem in formal verification; for example, it arises in our recent work on efficiently deciding regex constraints in SMT. However, state-of-the-art graph algorithms for maintaining reachability informationincrementally(that is, as states are visited and before the entire state space is explored) assume that new edges can be added from any state at any time, whereas in many applications, outgoing edges are added from each state as it is explored. To formalize the latter situation, we proposeguided incremental digraphs(GIDs), incremental graphs which support labelingclosedstates (states which will not receive further outgoing edges). Our main result is that dead state detection in GIDs is solvable in$$O(\log m)$$amortized time per edge formedges, improving upon$$O(\sqrt{m})$$per edge due to Bender, Fineman, Gilbert, and Tarjan (BFGT) for general incremental directed graphs.

We introduce two algorithms for GIDs: one establishing the logarithmic time bound, and a second algorithm to explore a lazy heuristics-based approach. To enable an apples-to-apples experimental comparison, we implemented both algorithms, two simpler baselines, and the state-of-the-art BFGT baseline using a common directed graph interface in Rust. Our evaluation shows 110-530x speedups over BFGT for the largest input graphs over a range of graph classes, random graphs, and graphs arising from regex benchmarks.
Certifying the Fairness of KNN in the Presence of Dataset Bias
Authors: Li Yannan , Wang Jingbo , Wang Chao
Published: July 2023

We propose a method for certifying the fairness of the classification result of a widely used supervised learning algorithm, thek-nearest neighbors (KNN), under the assumption that the training data may have historical bias caused by systematic mislabeling of samples from a protected minority group. To the best of our knowledge, this is the first certification method for KNN based on three variants of the fairness definition: individual fairness,$$\epsilon $$-fairness, and label-flipping fairness. We first define the fairness certification problem for KNN and then propose sound approximations of the complex arithmetic computations used in the state-of-the-art KNN algorithm. This is meant to lift the computation results from the concrete domain to an abstract domain, to reduce the computational cost. We show effectiveness of thisabstract interpretationbased technique through experimental evaluation on six datasets widely used in the fairness research literature. We also show that the method is accurate enough to obtain fairness certifications for a large number of test inputs, despite the presence of historical bias in the datasets.
NNV 2.0: The Neural Network Verification Tool
Authors: Lopez Diego Manzanas , Choi Sung Woo , Tran Hoang-Dung , Johnson Taylor T.
Published: July 2023

This manuscript presents the updated version of the Neural Network Verification (NNV) tool. NNV is a formal verification software tool for deep learning models and cyber-physical systems with neural network components. NNV was first introduced as a verification framework for feedforward and convolutional neural networks, as well as for neural network control systems. Since then, numerous works have made significant improvements in the verification of new deep learning models, as well as tackling some of the scalability issues that may arise when verifying complex models. In this new version of NNV, we introduce verification support for multiple deep learning models, including neural ordinary differential equations, semantic segmentation networks and recurrent neural networks, as well as a collection of reachability methods that aim to reduce the computation cost of reachability analysis of complex neural networks. We have also added direct support for standard input verification formats in the community such as VNNLIB (verification properties), and ONNX (neural networks) formats. We present a collection of experiments in which NNV verifies safety and robustness properties of feedforward, convolutional, semantic segmentation and recurrent neural networks, as well as neural ordinary differential equations and neural network control systems. Furthermore, we demonstrate the capabilities of NNV against a commercially available product in a collection of benchmarks from control systems, semantic segmentation, image classification, and time-series data.
Rounding Meets Approximate Model Counting
Authors: Yang Jiong , Meel Kuldeep S.
Published: July 2023

The problem of model counting, also known as $$\#\textsf{SAT}$$, is to compute the number of models or satisfying assignments of a given Boolean formula F. Model counting is a fundamental problem in computer science with a wide range of applications. In recent years, there has been a growing interest in using hashing-based techniques for approximate model counting that provide $$(\varepsilon , \delta )$$-guarantees: i.e., the count returned is within a $$(1+\varepsilon )$$-factor of the exact count with confidence at least $$1-\delta $$. While hashing-based techniques attain reasonable scalability for large enough values of $$\delta $$, their scalability is severely impacted for smaller values of $$\delta $$, thereby preventing their adoption in application domains that require estimates with high confidence.

The primary contribution of this paper is to address the Achilles heel of hashing-based techniques: we propose a novel approach based on rounding that allows us to achieve a significant reduction in runtime for smaller values of $$\delta $$. The resulting counter, called $$\textsf{ApproxMC6}$$ (The resulting tool $$\textsf{ApproxMC6}$$ is available open-source at https://github.com/meelgroup/approxmc), achieves a substantial runtime performance improvement over the current state-of-the-art counter, $$\textsf{ApproxMC}$$. In particular, our extensive evaluation over a benchmark suite consisting of 1890 instances shows $$\textsf{ApproxMC6}$$ solves 204 more instances than $$\textsf{ApproxMC}$$, and achieves a $$4\times $$ speedup over $$\textsf{ApproxMC}$$.
Rely-Guarantee Reasoning for Causally Consistent Shared Memory
Authors: Lahav Ori , Dongol Brijesh , Wehrheim Heike
Published: July 2023

Rely-guarantee (RG) is a highly influential compositional proof technique for concurrent programs, which was originally developed assuming a sequentially consistent shared memory. In this paper, we first generalize RG to make it parametric with respect to the underlying memory model by introducing an RG framework that is applicable to any model axiomatically characterized by Hoare triples. Second, we instantiate this framework for reasoning about concurrent programs under causally consistent memory, which is formulated using a recently proposed potential-based operational semantics, thereby providing the first reasoning technique for such semantics. The proposed program logic, which we call $${\textsf{Piccolo}}$$
Piccolo
, employs a novel assertion language allowing one to specify ordered sequences of states that each thread may reach. We employ $${\textsf{Piccolo}}$$
Piccolo
for multiple litmus tests, as well as for an adaptation of Peterson’s algorithm for mutual exclusion to causally consistent memory.
Closed-Loop Analysis of Vision-Based Autonomous Systems: A Case Study
Authors: Păsăreanu Corina S. , Mangal Ravi , Gopinath Divya , Getir Yaman Sinem , Imrie Calum , Calinescu Radu , Yu Huafeng
Published: July 2023

Deep neural networks (DNNs) are increasingly used in safety-critical autonomous systems as perception components processing high-dimensional image data. Formal analysis of these systems is particularly challenging due to the complexity of the perception DNNs, the sensors (cameras), and the environment conditions. We present a case study applying formal probabilistic analysis techniques to an experimental autonomous system that guides airplanes on taxiways using a perception DNN. We address the above challenges by replacing the camera and the network with a compact abstraction whose transition probabilities are computed from the confusion matrices measuring the performance of the DNN on a representative image data set. As the probabilities are estimated based on empirical data, and thus are subject to error, we also compute confidence intervals in addition to point estimates for these probabilities and thereby strengthen the soundness of the analysis. We also show how to leverage local, DNN-specific analyses as run-time guards to filter out mis-behaving inputs and increase the safety of the overall system. Our findings are applicable to other autonomous systems that use complex DNNs for perception.
Verse: A Python Library for Reasoning About Multi-agent Hybrid System Scenarios
Authors: Li Yangge , Zhu Haoqing , Braught Katherine , Shen Keyi , Mitra Sayan
Published: July 2023

We present the Verse library with the aim of making hybrid system verification more usable for multi-agent scenarios. In Verse, decision making agents move in a map and interact with each other through sensors. The decision logic for each agent is written in a subset of Python and the continuous dynamics is given by a black-box simulator. Multiple agents can be instantiated, and they can be ported to different maps for creating scenarios. Verse provides functions for simulating and verifying such scenarios using existing reachability analysis algorithms. We illustrate capabilities and use cases of the library with heterogeneous agents, incremental verification, different sensor models, and plug-n-play subroutines for post computations.
Automated Analyses of IOT Event Monitoring Systems
Authors: Apicelli Andrew , Bayless Sam , Das Ankush , Gacek Andrew , Jaganathan Dhiva , Padhi Saswat , Sharma Vaibhav , Whalen Michael W. , Yadav Raveesh
Published: July 2023

AWS IoT Events is an AWS service that makes it easy to respond to events from IoT sensors and applications.Detector modelsin AWS IoT Events enable customers to monitor their equipment or device fleets for failures or changes in operation and trigger actions when such events occur. If these models are incorrect, they may become out-of-sync with the actual state of the equipment causing customers to be unable to respond to events occurring on it.

Working backwards from common mistakes made when creating detector models, we have created a set of automated analyzers that allow customers to prove their models are free from six common mistakes. Our analyzers have been running in the AWS IoT Events production service since December 2021. Our analyzers check six correctness properties in the production service in real time. 93% of customers of AWS IoT Events have run our analyzers without needing to have any knowledge of them. Our analyzers have reported property violations in 22% of submitted detector models in the production service.
Synthesizing Permissive Winning Strategy Templates for Parity Games
Authors: Anand Ashwani , Nayak Satya Prakash , Schmuck Anne-Kathrin
Published: July 2023

We present a novel method to compute permissive winning strategies in two-player games over finite graphs with $$ \omega $$
ω
-regular winning conditions. Given a game graph G and a parity winning condition $$\varPhi $$
Φ
, we compute a winning strategy template$$\varPsi $$
Ψ
that collects an infinite number of winning strategies for objective $$\varPhi $$
Φ
in a concise data structure. We use this new representation of sets of winning strategies to tackle two problems arising from applications of two-player games in the context of cyber-physical system design – (i) incremental synthesis, i.e., adapting strategies to newly arriving, additional$$\omega $$
ω
-regular objectives $$\varPhi '$$

Φ
′

, and (ii) fault-tolerant control, i.e., adapting strategies to the occasional or persistent unavailability of actuators. The main features of our strategy templates – which we utilize for solving these challenges – are their easy computability, adaptability, and compositionality. For incremental synthesis, we empirically show on a large set of benchmarks that our technique vastly outperforms existing approaches if the number of added specifications increases. While our method is not complete, our prototype implementation returns the full winning region in all 1400 benchmark instances, i.e. handling a large problem class efficiently in practice.
Online Causation Monitoring of Signal Temporal Logic
Authors: Zhang Zhenya , An Jie , Arcaini Paolo , Hasuo Ichiro
Published: July 2023

Online monitoring is an effective validation approach for hybrid systems, that, at runtime, checks whether the (partial) signals of a system satisfy a specification in, e.g., Signal Temporal Logic (STL). The classic STL monitoring is performed by computing a robustness interval that specifies, at each instant, how far the monitored signals are from violating and satisfying the specification. However, since a robustness interval monotonically shrinks during monitoring, classic online monitors may fail in reporting new violations or in precisely describing the system evolution at the current instant. In this paper, we tackle these issues by considering the causation of violation or satisfaction, instead of directly using the robustness. We first introduce a Boolean causation monitor that decides whether each instant is relevant to the violation or satisfaction of the specification. We then extend this monitor to a quantitative causation monitor that tells how far an instant is from being relevant to the violation or satisfaction. We further show that classic monitors can be derived from our proposed ones. Experimental results show that the two proposed monitors are able to provide more detailed information about system evolution, without requiring a significantly higher monitoring cost.
Automated Verification of Correctness for Masked Arithmetic Programs
Authors: Liu Mingyang , Song Fu , Chen Taolue
Published: July 2023

Masking is a widely-used effective countermeasure against power side-channel attacks for implementing cryptographic algorithms. Surprisingly, few formal verification techniques have addressed a fundamental question, i.e., whether the masked program and the original (unmasked) cryptographic algorithm are functional equivalent. In this paper, we study this problem for masked arithmetic programs over Galois fields of characteristic 2. We propose an automated approach based on term rewriting, aided by random testing and SMT solving. The overall approach is sound, and complete under certain conditions which do meet in practice. We implement the approach as a new tool and carry out extensive experiments on various benchmarks. The results confirm the effectiveness, efficiency and scalability of our approach. Almost all the benchmarks can be proved for the first time by the term rewriting system solely. In particular, detects a new flaw in a masked implementation published in EUROCRYPT 2017.
Automatic Program Instrumentation for Automatic Verification
Authors: Amilon Jesper , Esen Zafer , Gurov Dilian , Lidström Christian , Rümmer Philipp
Published: July 2023

In deductive verification and software model checking, dealing with certain specification language constructs can be problematic when the back-end solver is not sufficiently powerful or lacks the required theories. One way to deal with this is to transform, for verification purposes, the program to an equivalent one not using the problematic constructs, and to reason about its correctness instead. In this paper, we propose instrumentation as a unifying verification paradigm that subsumes various existing ad-hoc approaches, has a clear formal correctness criterion, can be applied automatically, and can transfer back witnesses and counterexamples. We illustrate our approach on the automated verification of programs that involve quantification and aggregation operations over arrays, such as the maximum value or sum of the elements in a given segment of the array, which are known to be difficult to reason about automatically. We implement our approach in the MonoCera tool, which is tailored to the verification of programs with aggregation, and evaluate it on example programs, including SV-COMP programs.
Certified Verification for Algebraic Abstraction
Authors: Tsai Ming-Hsien , Fu Yu-Fu , Liu Jiaxiang , Shi Xiaomu , Wang Bow-Yaw , Yang Bo-Yin
Published: July 2023

We present a certified algebraic abstraction technique for verifying bit-accurate non-linear integer computations. In algebraic abstraction, programs are lifted to polynomial equations in the abstract domain. Algebraic techniques are employed to analyze abstract polynomial programs; SMT QF_BV solvers are adopted for bit-accurate analysis of soundness conditions. We explain how to verify our abstraction algorithm and certify verification results. Our hybrid technique has verified non-linear computations in various security libraries such as Bitcoin and OpenSSL. We also report the certified verification of Number-Theoretic Transform programs from the post-quantum cryptosystem Kyber.
Complete Multiparty Session Type Projection with Automata
Authors: Li Elaine , Stutz Felix , Wies Thomas , Zufferey Damien
Published: July 2023

Multiparty session types (MSTs) are a type-based approach to verifying communication protocols. Central to MSTs is a projection operator: a partial function that maps protocols represented as global types to correct-by-construction implementations for each participant, represented as a communicating state machine. Existing projection operators are syntactic in nature, and trade efficiency for completeness. We present the first projection operator that is sound, complete, and efficient. Our projection separates synthesis from checking implementability. For synthesis, we use a simple automata-theoretic construction; for checking implementability, we present succinct conditions that summarize insights into the property of implementability. We use these conditions to show that MST implementability is PSPACE-complete. This improves upon a previous decision procedure that is in EXPSPACE and applies to a smaller class of MSTs. We demonstrate the effectiveness of our approach using a prototype implementation, which handles global types not supported by previous work without sacrificing performance.
Ownership Guided C to Rust Translation
Authors: Zhang Hanliang , David Cristina , Yu Yijun , Wang Meng
Published: July 2023

Dubbed a safer C, Rust is a modern programming language that combines memory safety and low-level control. This interesting combination has made Rust very popular among developers and there is a growing trend of migrating legacy codebases (very often in C) to Rust. In this paper, we present a C to Rust translation approach centred around static ownership analysis. We design a suite of analyses that infer ownership models of C pointers and automatically translate the pointers into safe Rust equivalents. The resulting tool, Crown, scales to real-world codebases (half a million lines of code in less than 10 s) and achieves a high conversion rate.
Compositional Probabilistic Model Checking with String Diagrams of MDPs
Authors: Watanabe Kazuki , Eberhart Clovis , Asada Kazuyuki , Hasuo Ichiro
Published: July 2023

We present a compositional model checking algorithm for Markov decision processes, in which they are composed in the categorical graphical language ofstring diagrams. The algorithm computes optimal expected rewards. Our theoretical development of the algorithm is supported by category theory, while what we call decomposition equalities for expected rewards act as a key enabler. Experimental evaluation demonstrates its performance advantages.
Formally Verified EVM Block-Optimizations
Authors: Albert Elvira , Genaim Samir , Kirchner Daniel , Martin-Martin Enrique
Published: July 2023

The efficiency and the security of smart contracts are their two fundamental properties, but might come at odds: the use of optimizers to enhance efficiency may introduce bugs and compromise security. Our focus is on (Ethereum Virtual Machine) block-optimizations, which enhance the efficiency of jump-free blocks of opcodes by eliminating, reordering and even changing the original opcodes. We reconcile efficiency and security by providing the verification technology to formally prove the correctness of block-optimizations on smart contracts using the Coq proof assistant. This amounts to the challenging problem of proving semantic equivalence of two blocks of instructions, which is realized by means of three novel Coq components: a symbolic execution engine which can execute an block and produce a symbolic state; a number of simplification lemmas which transform a symbolic state into an equivalent one; and a checker of symbolic states to compare the symbolic states produced for the two blocks under comparison.

Artifact:https://doi.org/10.5281/zenodo.7863483
Geschlechtsspezifische Unterschiede spezieller Tumorerkrankungen
Authors: Lehnen Nathalie , Hallek Michael
Published: July 2023

Hintergrund

Zahlreiche Daten zeigen, dass Geschlecht und Gender als relevante Modulatoren bestimmter onkologischer und hämatologischer Erkrankungen einen zunehmenden Stellenwert in der Präzisionsmedizin verdient haben. Dieser Beitrag soll eine Zusammenfassung des aktuellen Wissensstands über Geschlechtsunterschiede in Inzidenz und Outcome spezieller Tumorerkrankungen bieten und mögliche zugrunde liegende Ursachen näher beleuchten.

Material und Methoden

Auswertung und Diskussion von Grundlagenarbeiten, Metaanalysen und klinischen Studien

Ergebnisse

Es bestehen für eine Vielzahl der onkologischen Erkrankungen signifikante geschlechtsspezifische Unterschiede in Inzidenz, Ansprechraten und Mortalität. Zumeist haben Männer ein schlechteres Outcome, während Frauen höhere therapieassoziierte Toxizität und distinkte Präsentationen in jungem Alter aufweisen. Hormonelle, immunologische und pharmakologische Ursachen liegen nahe.

Schlussfolgerung

Eine fortschrittliche in Bezug auf die einzelnen Patient*innen individualisierte Therapie in Onkologie und Hämatologie wird sich zukünftig daran messen, die bestehenden relevanten Unterschiede zwischen den Geschlechtern im klinischen Alltag zu berücksichtigen und in Studien zugrunde liegende Mechanismen weiter zu beleuchten, um eine bestmögliche Behandlung für onkologische Patient*innen zu garantieren und zukünftig zu optimieren.
Soil Micro-eukaryotic Diversity Patterns Along Elevation Gradient Are Best Estimated by Increasing the Number of Elevation Steps Rather than Within Elevation Band Replication
Authors: Huang Shuyin , Lentendu Guillaume , Fujinuma Junichi , Shiono Takayuki , Kubota Yasuhiro , Mitchell Edward A. D.
Published: July 2023

The development of high-throughput sequencing (HTS) of environmental DNA (eDNA) has stimulated the study of soil microbial diversity patterns and drivers at all scales. However, given the heterogeneity of soils, a challenge is to define effective and efficient sampling protocols that allow sound comparison with other records, especially vegetation. In studies of elevational diversity pattern, a trade-off is choosing between replication within elevation bands vs. sampling more elevation bands. We addressed this question for soil protists along an elevation gradient on Mt. Asahi, Hokkaido, Japan. We compared two sampling approaches: (1) the replicate strategy (five replicates at six elevational bands, total = 30) and (2) the transect strategy (one sample in each of 16 different elevational bands). Despite a nearly twofold lower sampling effort, the transect strategy yielded congruent results compared to the replicate strategy for the estimation of elevational alpha diversity pattern: the regression coefficients between diversity indices and elevation did not differ between the two options. Furthermore, for a given total number of samples, gamma diversity estimated across the entire transect was higher when sampling more elevational bands as compared to replication from fewer elevational bands. Beta diversity (community composition turnover) was lower within a given elevational band than between adjacent bands and increased with elevation distance. In redundancy analyses, soil organic matter-related variable (the first principal component of soil organic matter, water content, total organic carbon, and nitrogen by whom were highly correlated) and elevation best explained elevational beta diversity pattern for both sampling approaches. Taken together, our results suggest that sampling a single plot per elevation band will be sufficient to obtain a good estimate of soil micro-eukaryotic diversity patterns along elevation gradients. This study demonstrated the effectiveness of the transect strategy in estimating diversity patterns along elevation gradients which is instructive for future environmental or even experimental studies. While not advocating for completely replacing replication-based sampling practices, it is important to note that both replicate and transect strategies have their merits and can be employed based on specific research goals and resource limitations.
Management of Central Venous Stenoses and Occlusions
Authors: Kitrou Panagiotis , Katsanos Konstantinos , Karnabatidis Dimitrios
Published: July 2023

Symptomatic central venous stenosis and occlusion remains the gordian knot of vascular access. Advances in techniques, like sharp recanalization, allowed for improved success rates in crossing these difficult lesions. There is also increasing evidence of new devices in treating central venous stenosis and, at the same time, improving the time needed between interventions. High-pressure balloons, paclitaxel-coated balloons, bare metal stents and covered stents have been tested with an aim to offer additional treatment options, although obstacles still exist. In the current review, authors describe relevant techniques and options, provide the evidence and evaluate the actual implementation of these devices in this demanding field.
AgAnimalGenomes: browsers for viewing and manually annotating farm animal genomes
Authors: Triant Deborah A. , Walsh Amy T. , Hartley Gabrielle A. , Petry Bruna , Stegemiller Morgan R. , Nelson Benjamin M. , McKendrick Makenna M. , Fuller Emily P. , Cockett Noelle E. , Koltes James E. , McKay Stephanie D. , Green Jonathan A. , Murdoch Brenda M. , Hagen Darren E. , Elsik Christine G.
Published: July 2023

Current genome sequencing technologies have made it possible to generate highly contiguous genome assemblies for non-model animal species. Despite advances in genome assembly methods, there is still room for improvement in the delineation of specific gene features in the genomes. Here we present genome visualization and annotation tools to support seven livestock species (bovine, chicken, goat, horse, pig, sheep, and water buffalo), available in a new resource called AgAnimalGenomes. In addition to supporting the manual refinement of gene models, these browsers provide visualization tracks for hundreds of RNAseq experiments, as well as data generated by the Functional Annotation of Animal Genomes (FAANG) Consortium. For species with predicted gene sets from both Ensembl and RefSeq, the browsers provide special tracks showing the thousands of protein-coding genes that disagree across the two gene sources, serving as a valuable resource to alert researchers to gene model issues that may affect data interpretation. We describe the data and search methods available in the new genome browsers and how to use the provided tools to edit and create new gene models.
Controlled prospective study on ultrasound simulation training in fetal echocardiography: FESIM II
Authors: Janzing Paul , Nourkami-Tutdibi Nasenien , Tutdibi Erol , Freundt Paula , von Ostrowski Thomas , Langer Martin , Zemlin Michael , Steinhard Johannes
Published: July 2023

Purpose

To analyze the learning curves of ultrasound novices in fetal echocardiography during structured simulation-based ultrasound training (SIM-UT) including a virtual, randomly moving fetus.

Methods

11 medical students with minimal (< 10 h) prior obstetric ultrasound experience underwent 12 h of structured fetal echocardiography SIM-UT in individual hands-on sessions during a 6-week training program. Their learning progress was assessed with standardized tests after 2, 4, and 6 weeks of SIM-UT. Participants were asked to obtain 11 fetal echocardiography standard planes (in accordance with ISUOG and AHA guidelines) as quickly as possible. All tests were carried out under real life, examination-like conditions on a healthy, randomly moving fetus. Subsequently, we analyzed the rate of correctly obtained images and the total time to completion (TTC). As reference groups, 10 Ob/Gyn physicians (median of 750 previously performed Ob/Gyn scans) and 10 fetal echocardiography experts (median of 15,000 previously performed Ob/Gyn scans) were examined with the same standardized tests.

Results

The students showed a consistent and steady improvement of their ultrasound performance during the training program. After 2 weeks, they were able to obtain > 95% of the standard planes correctly. After 6 weeks, they were significantly faster than the physician group (p < 0.001) and no longer significantly slower than the expert group (p = 0.944).

Conclusion

SIM-UT is highly effective to learn fetal echocardiography. Regarding the acquisition of the AHA/ISUOG fetal echocardiography standard planes, the students were able to reach the same skill level as the expert group within 6 weeks.