Miracle-dz/UniFAR-FTUs huggingface dataset:
Reasoning about Dynamic Networks of Inﬁnite-State Processes with Global Synchronization

We propose a generic framework for reasoning about dynamic networks of inﬁnite state processes such as counter processes, timed processes, or pushdown processes, with complex synchronization mechanisms, including global synchronization (i.e., broadcast communication). We deﬁne models for such networks, called CTN, based on Petri nets with transfer operations. To-kens (representing occurrences of processes) have attached colors over inﬁnite domains (representing data values, clocks, stacks, etc.). We also deﬁne a (second-order) logic called CTSL allowing to express constraints on locations of tokens in the nets and on their colors. We prove that the ∃ ∗ ∀ ∗ fragment of CTSL is decidable whenever the underlying logic for expressing constraints on colors is decidable. Moreover, we show that the same fragment is closed under post and pre image computations. These results can be used in veriﬁcation such as in invariance checking. We show that our framework can be applied for reasoning about multithreaded programs with procedure calls and dynamic creation of process with global synchronization, and on dynamic programs with real-time constraints.
Gera¸c˜ao de Trajet´oria para VANT com Resultados Experimentais

: This paper proposes a new approach for generating smooth trajectories for unmanned aerial vehicles (UAVs or drones) that can be executed in real time with limited processing embedded hardware. The objective is to perform autonomous aerial image acquisition, ensuring repeatability. In addition, a state feedback control law based on previously identified commercial hexacopter nominal parameters, with integral and feedforward actions was implemented and validated for trajectory tracking in the presence of wind disturbances, in a real and simulated environment.
Artiﬁcial thinking and doomsday projections: a discourse on trust, ethics and safety

The article reﬂects on where AI is headed and the world along with it, considering trust, ethics and safety. Implicit in artiﬁ-cial thinking and doomsday appraisals is the engineered divorce from reality of sublime human embodiment. Je ﬀ rey White, Dietrich Brandt, Jan Soe ﬀ ner, and Larry Stapleton, four scholars associated with AI & Society, address these issues, and more, in the following exchange.
Scholarly Commons @ Baptist Health South Florida Scholarly Commons @ Baptist Health South Florida

Coronavirus disease 2019 (COVID-19) is a pandemic. Neurological complications of COVID-19 have not been reported. Encephalopathy has not been described as a presenting symptom or complication of COVID-19. We report a case of a 74-year-old patient who traveled from Europe to the United States and presented with encephalopathy and COVID-19.
Biomonitoring of wild fish to assess chemical pollution in English rivers : an application of a fish tissue archive

Since 2007 CEH and the Environment Agency are building a Fish Tissue Archive by annually collecting roach (and in 2007/08 also some eels and bleak) from a number of English river sites and storing them long-term at -80°C. This provides a resource for retrospective monitoring of bioaccumulative pollutants in the fish tissue - allowing future scientists to answer questions that cannot yet be answered or are not yet asked. By the end of 2014, 1684 fish had been collected of which 179 have so far been analysed for one or more groups of chemicals: metals, organochlorine pesticides, PCBs and PBDEs. The results from the individual fish were compared to each other as well as to regulatory standards and previously published UK and European data. Some of the results are: With the exception of lead in 3% of analysed individuals, no food standards were exceeded, but the environmental quality standard (EQS) for mercury was exceeded in the majority of samples (111/144) and the very low EQS for PBDEs was greatly exceeded in all samples. Some patterns found were: • Mercury and selenium increased with size of the fish and to some extent with the distance of the sampling site from the river source. • PBDE concentration correlated well with the modelled concentration of treated sewage at the sampling site • A hotspot was found for DDTs (banned in 1981) and to a lesser extent lindane, chlordane and copper. Further investigations revealed that a pesticide factory had been located close to the sampling site for much of the 20th century. This shows how unexpected results can point to previously unknown issues, which warrant further investigation. • Compared to previous European data, eels were generally less contaminated with organic pollutants and roach were low in mercury and cadmium, but relatively high in lead.
A Case Study of Developer Bots: Motivations, Perceptions, and Challenges

Continuous integration and deployment (CI/CD) is now a widely adopted development model in practice as it reduces the time from ideas to customers. This adoption has also revived the idea of "shifting left" during software development -- a practice intended to find and prevent defects early in the software delivery process. To assist with that, engineering systems integrate developer bots in the development workflow to improve developer productivity and help them identify issues early in the software delivery process. In this paper, we present a case study of developer bots in Microsoft. We identify and analyze 23 developer bots that are deployed across 13,000 repositories and assist about 6,000 developers daily in their CI/CD software development workflows. We classify these bots across five major categories: Config Violation, Security, Data-privacy, Developer Productivity, and Code Quality. By conducting interviews and surveys with bot developers and bot users and by analyzing about half a million historical bot actions spanning over one and a half years, we present software workflows that motivate bot instrumentation, factors impacting their usefulness as perceived by bot users, and challenges associated with their use. Our findings echo existing issues with bots, such as noise, and illustrate new benefits (e.g., cross-team communication) and challenges (e.g., too many bots) for large software teams.
Detection of Optimizations Missed by the Compiler

With the increasing significance of compilers in software development, identifying optimization bugs and enhancing their performance has become a significant challenge. In recent years, many studies have targeted only specific analyses to identify missed optimizations (e.g., in data flow analyses). While there have been some general approaches, most rely on differential testing between different compilers, which makes it difficult to identify optimization bugs that are common to multiple compilers. This paper tackles these challenges by introducing an effective and general approach called MOD. MOD works by using a manually-curated mapping between optimizations, ensuring that code should be consistently optimized: if one optimization triggers but the other does not, that indicates a bug in either of the two optimizations. We implemented MOD as a tool to detect missed optimizations in the available expressions of the LLVM. Experimental results show that MOD can report 20 correct alerts in one hour of detection of random test programs.
Improving Web Performance by Client Characterization Driven Server Adaptation

We categorize the set of clients communicating with a server on the Web based on information that can be determined by the server. The Web server uses the information to direct tailored actions. Users with poor connectivity may choose not to stay at a Web site if it takes a long time to receive a page, even if the Web server at the site is not the bottleneck. Retaining such clients may be of interest to a Web site. Better connected clients can receive enhanced representations of Web pages, such as with higher quality images. We explore a variety of considerations that could be used by a Web server in characterizing a client. Once a client is characterized as poor or rich, the server can deliver altered content, alter how content is delivered, alter policy and caching decisions, or decide when to redirect the client to a mirror site. We also use network-aware client clustering techniques to provide a coarser level of client categorization and use it to categorize subsequent clients from that cluster for which a client-speci c categorization is not available. Our results for client characterization and applicable server actions are derived from real, recent, and diverse set of Web server logs. Our experiments demonstrate that a relatively simple characterization policy can classify poor clients such that these clients subsequently make the majority of badly performing requests to a Web server. This policy is also stable in terms of clients staying in the same class for a large portion of the analysis period. Client clustering can significantly help in initially classifying clients for which no previous information about the client is known. We also show that di erent server actions can be applied to a signi cant number of request sequences with poor performance.
TRACE ELEMENT COMBINATIONS IN UPPER CRETACEOUS DINOSAUR EGG FOSSILS FROM XIXIA BASIN AND DISCUSSION ON PALEOCLIMATE

Neutron activation analysis of respectively samplings of dinosaur egg fossils and wall rocks from the Upper Cretaceous in Xixia, Henan Province demonstrates that elementary combinations in the dinosaur egg fossils are featured by obvious abnormal high contents of both iridium and strontium,which are inferred to have caused fabric and pathological changes of those eggs. Thereby the dinosaur eggs couldn't be hatched, and probably resulted in the high concentration of their fossils. Moreover,the analysis of elementary combinations as well as geological data indicates that the climate during the Late Cretaceous in this area might have been semiarid to arid.
Ancient Philosophical Resources For Understanding and Dealing With Anger

Ancient philosophical schools developed and discussed perspectives and practices on the emotion of anger useful in contemporary philosophical practice with clients, groups, and organizations. This paper argues the case for incorporating these insights from four main philosophical schools (Platonist, Aristotelian, Epicurean, and Stoic) sets out eight practices drawn from these schools, and discusses how these insights can be used by philosophical practitioners with clients.
Green Technology Adoption and Skill Reallocation

The green transition towards a carbon neutral economy constitutes a technological transformation, in which firms need to invest in new, clean technologies. In order to be operated, these new technologies often require a set of technology-specific skills that differ from those that were relevant for dirtier predecessors. We model the green technology investment decision of firms in a labour market with search frictions and two-sided heterogeneity. We find that the presence of skill mismatch negatively affects the expected productivity of the new, green technologies, delaying their adoption and resulting in higher emission intensity in production compared to a counterfactual with no labour market frictions. The induced effect is of first-order, making it policy-relevant. This slower diffusion of green technologies in the presence of skill heterogeneity results in workers with green skills being locked in brown jobs. We also find that an accelerated greening of the economy leads to larger labour market transitions. More specialised new technologies further reinforce these effects, and so does a slower pace of technological progress. Finally, our model results suggests that retraining policies are a useful policy tool both in the absence as well as the presence of a carbon tax or investment subsidies.
Prognostication and Risk factors of Status Epilepticus in patients Prognostication and Risk factors of Status Epilepticus in patients treated in Neurointensive Care Units treated in Neurointensive Care Units

Background: Status epilepticus (SE) can lead to sequelae or even death. Identifying characteristics associated with poor outcome is crucial in guiding patient treatment, to our information, there is no data illustrating the prevalence and outcome of cases with critical tumor illness with AMS accompanied to non-convulsive seizures (NCS) or NCSE Aim of the study: The aim of the study was to evaluate risk factors and prognosing in cases with Status epilepticus (SE) treated in neurointensive care units. Patients and Methods: This was a retrospective cohort investigation, in which 50 cases had SE-episodes were included, we in retrospect analyzed all SE-episodes managed over an interval of 2-yrs (April 2019 to April 2021) in the NICU at the hospital. Results: the commonest cause was idiopathic (40%), the commonest trigger factor was poor compliance (38%). 88% of the patients were recurrent SE. Conclusion: Many conditions have complicated the image in daily practice so real-life data are vital so as to recognize real cases in the ward. No severe seasonality of SE patients has been found. In our study, the commonest cause of SE was idiopathic, the commonest trigger factor was poor compliance and most of the patients were recurrent SE
Appaction: Automatic GUI Interaction for Mobile Apps via Holistic Widget Perception

In industrial practice, GUI (Graphic User Interface) testing of mobile apps still inevitably relies on huge manual efforts. The major efforts are those on understanding the GUIs, so that testing scripts can be written accordingly. Quality assurance could therefore be very labor-intensive, especially for modern commercial mobile apps, where one may include tremendous, diverse, and complex GUIs, e.g., those for placing orders of different commercial items. To reduce such human efforts, we propose Appaction, a learning-based automatic GUI interaction approach we developed for Meituan, one of the largest E-commerce providers with over 600 million users. Appaction can automatically analyze the target GUI and understand what each input of the GUI is about, so that corresponding valid inputs can be entered accordingly. To this end, Appaction adopts a multi-modal model to learn from human experiences in perceiving a GUI. This allows it to infer corresponding valid input events that can properly interact with the GUI. In this way, the target app can be effectively exercised. We present our experiences in Meituan on applying Appaction to popular commercial apps. We demonstrate the effectiveness of Appaction in GUI analysis, and it can perform correct interactions for numerous form pages.
EchoTube: Modular and Robust Press Sensing along Flexible Tubes using Waveguided Ultrasound

While pressing can enable a wide variety of interesting applications, most press sensing techniques operate only at close distances and rely on fragile electronics. We present EchoTube, a robust, modular, simple, and inexpensive system for sensing low-resolution press events at a distance. EchoTube works by emitting ultrasonic pulses inside a flexible tube which acts as a waveguide and detecting reflections caused by deformations in the tube. EchoTube is deployable in a wide variety of situations: the flexibility of the tubes allows them to be wrapped around and affixed to irregular objects. Because the electronic elements are located at one end of the tube, EchoTube is robust, able to withstand crushing, impacts, water, and other adverse conditions. In this paper, we detail the design, implementation, and theory behind EchoTube; characterize its performance unPermission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from permissions@acm.org. ISS ’19, November 10–13, 2019, Daejeon, Republic of Korea. Copyright © 2019 Association of Computing Machinery. ACM ISBN 978-1-4503-6891-9/19/11 . $15.00. http://dx.doi. org/10.1145/3343055.3359712 der different configurations; and present a variety of exemplar applications that illustrate its potential.
LightF3: A Lightweight Fully-Process Formal Framework for Automated Verifying Railway Interlocking Systems

Interlocking has long played a crucial role in railway systems. Its functional correctness, particularly concerning safety, forms the foundation of the entire signaling system. To date, numerous efforts have been made to formally model and verify interlocking systems. However, two main problems persist in most prior work: (1) The formal description of the interlocking system heavily depends on reusing existing models, which often results in overgeneralization and failing to fully utilize the intrinsic characteristics of interlocking systems. (2) The verification techniques of current approaches may quickly become outdated, and there is no adaptable method to integrate state-of-the-art verification algorithms or tools. To address the above issues, we present LightF3, a lightweight and fully-process formal framework for modeling and verifying railway interlocking systems. LightF3 provides RIS-FL, a formal language based on FQLTL (a variant of LTL) to model the system and its specifications. LightF3 transforms the RIS-FL model automatically to the aiger model, which is the mainstream input of state-of-the-art model checkers, and then invokes the most advanced checkers to complete the verification task. We evaluated LightF3 by testing five real station instances from our industrial partner, demonstrating its effectiveness as a new framework. Additionally, we analyzed the statistics of the verification results from different model-checking techniques, providing useful conclusions for both the railway interlocking and formal methods communities.
outputs Removing the HUD : The Impact of Non-Diegetic Game Elements and Expertise on Player Involvement Conference Item

Previous research has shown that player involvement can be influenced by a range of factors, from the controllers used to the perceived level of challenge provided by the game. However, little attention has been paid to the influence of the game interface. Game interfaces consist of both diegetic (that can be viewed by the player-character, e.g. the game world) and non-diegetic components (that are only viewed by the player, e.g. the heads-up display). In this paper we examine two versions of a first-person shooter game to investigate how immersion is influenced through interacting with a diegetic and non-diegetic interface. Our findings suggest that the removal of non-diegetic elements, such as the heads-up display, is able to influence immersion in expert players through increasing their cognitive involvement and sense of control. We argue that these results illustrate the importance of considering the role of expertise in relation to how particular design choices will influence the player experience.
Human Bodies as Interaction Materials for Somatic, Social, and Multisensory Virtual Reality Experiences

Recently, the field of Human-Computer Interaction has begun to embrace the crucial role of our bodies across our cognitive and social processes. The movement of embodied interaction has been followed by a somatic and material turn that strives to design technology for richer multi-sensory somatic experiences. Despite the booming developments in tangible and wearable technologies, there is strikingly limited research exploring the potential of our own physical and virtual bodies to become the material for the design of interaction, in the same ways that tangible materials are. In this position paper, we propose a series of approaches for designing technology for social interaction, that integrate human bodies as interaction materials to elicit a multisensory embodied experience. We illustrate this approach with examples of several virtual reality experiences that we have designed for supporting social connection.
Journal Pre-proofs Towards the purification of IgY from egg yolk by centrifugal partition chromatography

Although their high potential as alternative biopharmaceuticals, less than 2% of the total polyclonal antibodies produced worldwide correspond to immunoglobulin Y (IgY) due to the difficulties in isolating them from egg yolk that is a complex biological matrix. In this work, the proteins water soluble fraction (WSPF) of egg yolk was first obtained and the proteins present identified by one-dimensional gel electrophoresis (SDS-PAGE) and label-free quantitative nano-liquid chromatography-tandem mass spectrometry (nano-LC-MS/MS). The egg yolk WSPF was then applied to create aqueous biphasic systems (ABS) composed of polyethylene glycol 1000 g·mol -1 (PEG 1000) and phosphate buffer, followed by centrifugal partition chromatography (CPC) to purify IgY. The characterization of the WSPF showed the presence of six major proteins: the target antibody IgY, serum albumin (α-livetin), ovalbumin, ovotransferrin, vitellogenin 1 and vitellogenin 2. The results obtained by ABS revealed a high affinity of all proteins to the polymer-rich phase. However, by changing the PEG and salt concentration, a higher selectivity was observed for IgY, with the remaining proteins partitioning between the two phases. The best ABS were applied in CPC, finally allowing a multi-stage partition and to the technology scale-up. The CPC operating conditions were optimized, allowing to obtain IgY with 50.6% of purity.
Real time face detection and recognition

In this demo session, a real-time automatic face detection and recognition system will be demonstrated. The system, which is implemented as a desktop application with a user interface, detects the faces in the images that are grabbed from a web camera using a cascaded classifier consisting of Modified Census Transform features. Then, using the same method, it locates the eyes and the mouth on each face and uses this information to align the faces. Finally, it recognizes these aligned faces using a novel method called local Zernike moments. In order to improve the detection performance, the system also includes face tracking. The result of the recognition process can be observed by the names that are written by the system near the faces. The system makes it possible to add a previously unseen person to the database easily via its user interface.
P4b: A Translator from P4 Programs to Boogie

P4 is a mainstream language for Software Defined Network (SDN) data planes. P4 is designed to achieve target-independent, protocol-independent, and configurable SDN data planes. However, logic errors may occur in P4 programs, resulting in improper packet processing, which may cause serious network errors and information disclosure. In addition, P4 programs contain many branches and thus are more challenging to ensure correctness. Formal verification is a powerful technique to verify the correctness of P4 programs. Unfortunately, current P4 verification studies lack basic toolchains, and their intermediate languages are not expressive enough. We present P4b, an efficient translator from P4 programs to Boogie, a verification-oriented intermediate representation. We provide formal translation rules to ensure the correctness of the translation process. The translated results can be verified by the toolchain of Boogie. We conducted experiments on 170 P4 programs collected from GitHub, and the experimental results demonstrate that our translator is useful and practical. The screencast is available at https://youtu.be/8_rEj3QFQeM. The tool is available at https://github.com/Invincibleyc/P4B-Translator.