Miracle-dz/UniFAR-FTUs huggingface dataset:
On the satisfiability problem for fragments of the two-variable logic with one transitive relation

We study the satisfiability problem for two-variable first-order logic over structures with one transitive relation. We show that the problem is decidable in 2-NExpTime for the fragment consisting of formulas where existential quantifiers are guarded by transitive atoms. As this fragment enjoys neither the finite model property nor the tree model property, to show decidability we introduce a novel model construction technique based on the infinite Ramsey theorem. We also point out why the technique is not sufficient to obtain decidability for the full two-variable logic with one transitive relation; hence, contrary to our previous claim, [FO$^2$ with one transitive relation is decidable, STACS 2013: 317-328], the status of the latter problem remains open.
Global Cancer Statistics, 2002

Estimates of the worldwide incidence, mortality and prevalence of 26 cancers in the year 2002 are now available in the GLOBOCAN series of the International Agency for Research on Cancer. The results are presented here in summary form, including the geographic variation between 20 large “areas” of the world. Overall, there were 10.9 million new cases, 6.7 million deaths, and 24.6 million persons alive with cancer (within three years of diagnosis). The most commonly diagnosed cancers are lung (1.35 million), breast (1.15 million), and colorectal (1 million); the most common causes of cancer death are lung cancer (1.18 million deaths), stomach cancer (700,000 deaths), and liver cancer (598,000 deaths). The most prevalent cancer in the world is breast cancer (4.4 million survivors up to 5 years following diagnosis). There are striking variations in the risk of different cancers by geographic area. Most of the international variation is due to exposure to known or suspected risk factors related to lifestyle or environment, and provides a clear challenge to prevention.
"It was Colonel Mustard in the Study with the Candlestick": Using Artifacts to Create An Alternate Reality Game-The Unworkshop

Workshops are used for academic social networking, but connections can be superficial and result in few enduring collaborations. This unworkshop offers a novel interactive format to create deep connections, peer- learning, and produces a technology-enhanced experience. Participants will generate interactive technological artifacts before the unworkshop, which will be used together and orchestrated at the unworkshop to engage all participants in an alternate reality game set in local places at the conference.
Pyrrolizidine Alkaloids—Genotoxicity, Metabolism Enzymes, Metabolic Activation, and Mechanisms

Pyrrolizidine alkaloid‐containing plants are widely distributed in the world and are probably the most common poisonous plants affecting livestock, wildlife, and humans. Because of their abundance and potent toxicities, the mechanisms by which pyrrolizidine alkaloids induce genotoxicities, particularly carcinogenicity, were extensively studied for several decades but not exclusively elucidated until recently. To date, the pyrrolizidine alkaloid‐induced genotoxicities were revealed to be elicited by the hepatic metabolism of these naturally occurring toxins. In this review, we present updated information on the metabolism, metabolizing enzymes, and the mechanisms by which pyrrolizidine alkaloids exert genotoxicity and tumorigenicity.
Estimation With Low-Rank Time–Frequency Synthesis Models

Many state-of-the-art signal decomposition techniques rely on a low-rank factorization of a time–frequency (t–f) transform. In particular, nonnegative matrix factorization (NMF) of the spectrogram has been considered in many audio applications. This is an analysis approach in the sense that the factorization is applied to the squared magnitude of the analysis coefficients returned by the t–f transform. In this paper, we instead propose a synthesis approach, where low-rankness is imposed to the synthesis coefficients of the data signal over a given t–f dictionary (such as a Gabor frame). As such, we offer a novel modeling paradigm that bridges t–f synthesis modeling and traditional analysis based NMF approaches. The proposed generative model allows us in turn to design more sophisticated multilayer representations that can efficiently capture diverse forms of structure. Additionally, the generative modeling allows us to exploit t–f low-rankness for compressive sensing. We present efficient iterative shrinkage algorithms to perform estimation in the proposed models and illustrate the capabilities of the new modeling paradigm over audio signal processing examples.
Quantitative susceptibility map reconstruction using annihilating filter‐based low‐rank Hankel matrix approach

Quantitative susceptibility mapping (QSM) inevitably suffers from streaking artifacts caused by zeros on the conical surface of the dipole kernel in k‐space. This work proposes a novel and accurate QSM reconstruction method based on k‐space low‐rank Hankel matrix constraint, avoiding the over‐smoothing problem and streaking artifacts.
Association Between Posttraumatic Stress Disorder and Lack of Exercise, Poor Diet, Obesity, and Co-Occuring Smoking: A Systematic Review and Meta-Analysis

Objectives: Research has shown that posttraumatic stress disorder (PTSD) increases the risk of development of cardiometabolic disease (CMD) including cardiovascular disease and diabetes. Whether PTSD is also associated with behavioral risk factors (e.g., diet, exercise, smoking and obesity) for CMD, is less clear. Methods: PubMed, Web of Science, and Scopus databases were searched to obtain papers published between 1980–2016. Studies were reviewed for quality using the Quality of Cohort screen. Significance values, odds ratios (OR), 95% confidence intervals (CI), and tests of homogeneity of variance were calculated. Principal Findings: A total of 1,349 studies were identified from our search and 29 studies met all eligibility criteria. Individuals with PTSD were 5% less likely to have healthy diets (pooled adjusted OR = 0.95; 95% CI: 0.92, 0.98), 9% less likely to engage in physical activity (pooled adjusted OR = 0.91; 95% CI: 0.88, 0.93), 31% more likely to be obese (pooled adjusted OR = 1.31; 95% CI:1.25, 1.38), and about 22% more likely to be current smokers (pooled adjusted OR = 1.22; 95% CI: 1.19, 1.26), than individuals without PTSD. Conclusions: Evidence shows PTSD is associated with reduced healthy eating and physical activity, and increased obesity and smoking. The well-established association between PTSD and metabolic and cardiovascular disease may be partly due to poor diet, sedentary lifestyle, high prevalence of obesity, and co-occurring smoking in this population. The well-established association of PTSD with CMD is likely due in part to poor health behaviors in this patient population.
Smoking Cessation Ameliorates Microalbuminuria With Reduction of Blood Pressure and Pulse Rate in Patients With Already Diagnosed Diabetes Mellitus

Background Smoking cessation in newly diagnosed type 2 diabetes patients is reported to be associated with amelioration of metabolic parameters and blood pressure (BP), and the reduction of microalbuminuria. The aim of this study is to demonstrate changes in BP, pulse rate (PR), and microalbuminuria in already diagnosed diabetes patients who quit smoking. Methods We retrospectively evaluated diabetes outpatients who were habitual smokers, and who visited to our smoking cessation clinic. Patients were divided into two groups based on their smoking status at the termination of a 3-month smoking cessation program (smoking cessation group and smoking group), and analyzed systolic and diastolic BPs, PR, HbA1c, and body weight at the start date, and at 1, 3, 6, and 12 months thereafter. The urinary albumin-to-creatinine ratio was also measured at the start date and at 12 months. Results Thirty-five patients met our criteria. Mean diabetes duration was 12 years. Eighteen patients (52%) quit smoking. Success or failure of smoking cessation depended on nicotine dependence rather than good or bad glycemic control. Both BP and PR decreased significantly after 1 month or later in the smoking cessation group without worsening HbA1c, while both parameters did not show any changes in the smoking group. Microalbuminuria was also ameliorated significantly at 12 months compared with that at the start date in the smoking cessation group (95.8 ± 92.9 mg/gCr vs. 75.5 ± 96.3 mg/gCr, P = 0.0059), while it did not show a significant change in the smoking group. (61.9 ± 43.5 mg/gCr vs. 97.7 ± 90.4 mg/gCr, P = 0.1039). Conclusions Smoking cessation might cause a reduction in chronic kidney disease progression through ameliorating microalbuminuria without metabolic adverse effects in patients already diagnosed with diabetes mellitus.
Profile-guided memory optimization for deep neural networks

Recent years have seen deep neural networks (DNNs) becoming wider and deeper to achieve better performance in many applications of AI. Such DNNs however require huge amounts of memory to store weights and intermediate results (e.g., activations, feature maps, etc.) in propagation. This requirement makes it difficult to run the DNNs on devices with limited, hard-to-extend memory, degrades the running time performance, and restricts the design of network models. We address this challenge by developing a novel profile-guided memory optimization to efficiently and quickly allocate memory blocks during the propagation in DNNs. The optimization utilizes a simple and fast heuristic algorithm based on the two-dimensional rectangle packing problem. Experimenting with well-known neural network models, we confirm that our method not only reduces the memory consumption by up to $49.5\%$ but also accelerates training and inference by up to a factor of four thanks to the rapidity of the memory allocation and the ability to use larger mini-batch sizes.
CNPY2 inhibits MYLIP-mediated AR protein degradation in prostate cancer cells

The androgen receptor (AR) is a ligand-dependent transcription factor that promotes prostate cancer (PC) cell growth through control of target gene expression. This report suggests that Canopy FGF signaling regulator 2 (CNPY2) controls AR protein levels in PC cells. We found that AR was ubiquitinated by an E3 ubiquitin ligase, myosin regulatory light chain interacting protein (MYLIP) and then degraded through the ubiquitin-proteasome pathway. CNPY2 decreased the ubiquitination activity of MYLIP by inhibition of interaction between MYLIP and UBE2D1, an E2 ubiquitin ligase. CNPY2 up-regulated gene expression of AR target genes such as KLK3 gene which encodes the prostate specific antigen (PSA) and promoted cell growth of PC cells. The cell growth inhibition by CNPY2 knockdown was rescued by AR overexpression. Furthermore, positive correlation of expression levels between CNPY2 and AR/AR target genes was observed in tissue samples from human prostate cancer patients. Together, these results suggested that CNPY2 promoted cell growth of PC cells by inhibition of AR protein degradation through MYLIP-mediated AR ubiquitination.
Formal Process Virtual Machine for Smart Contracts Verification

This paper reports on the development and verification of a novel formal symbolic process virtual machine (FSPVM) for verifying the reliability and security of Ethereum smart contracts, denoted as FSPVM-E, completely in Coq proof assistant. It adopts execution-verification isomorphism (EVI), an extension of Curry-Howard isomorphism (CHI), as its fundamental theoretical framework. The current version of FSPVM-E is constructed on a general, extensible, and reusable formal memory (GERM) framework, an extensible and universal formal intermediate programming language Lolisa, which is a large subset of the Solidity programming language using generalized algebraic datatypes, and the corresponding formally verified interpreter of Lolisa, denoted as FEther. It supports the ERC20 standard and can automatically simultaneously symbolically execute the smart contract programs of Ethereum and verify their reliability and security properties using Hoare logic in Coq. In addition, this work, contributes to solving the problems of automation, inconsistency and reusability in higher-order logic theorem proving.
Pancreaticopleural fistula: a rare cause of pleural empyema

Abstract Aim: Pancreaticopleural fistula (PPF) is a rare complication of acute or chronic pancreatitis. When the pancreatic duct disrupts, pancreatic fluid may leak into the retroperitoneum and fistulate into the pleural cavity. Patients usually present with thoracic complaints, making it hard to suspect an abdominal etiology. Although PPF is uncommon, one must consider this diagnosis in patients with thoracic complaints and a history of alcohol abuse or pancreatitis. Methods: We present an illustrative case and review of the literature on PPF. Results: A 47-year old man was presented with recurrent PPF due to pancreas divisum, pancreatic stones and chronic exudative pancreatitis, resulting in unilateral empyema. After initial conservative treatment, operative measures were needed. We report omentoplasty against the diaphragmatic hiatus in combination with VATS (video-assisted thoracoscopic surgery) thoracotomy with decortication and debridement as a feasible operative option for resolving PPF. Conclusion: PPF is a rare complication of pancreatitis. The diagnosis is difficult to make and can be confirmed by thoracocentesis and proper imaging, preferably MRCP. Treatment options include conservative, endoscopic (ERCP) or surgical measures. Omentoplasty positioned against the diaphragmatic hiatus is a feasible technique for closure of PPF.
Evolution of Visual Odometry Techniques

With rapid advancements in the area of mobile robotics and industrial automation, a growing need has arisen towards accurate navigation and localization of moving objects. Camera based motion estimation is one such technique which is gaining huge popularity owing to its simplicity and use of limited resources in generating motion path. In this paper, an attempt is made to introduce this topic for beginners covering different aspects of vision based motion estimation task. The evolution of VO schemes over last few decades is discussed under two broad categories, that is, geometric and non-geometric approaches. The geometric approaches are further detailed under three different classes, that is, feature-based, appearance-based, and a hybrid of feature and appearance based schemes. The non-geometric approach is one of the recent paradigm shift from conventional pose estimation technique and is thus discussed in a separate section. Towards the end, a list of different datasets for visual odometry and allied research areas are provided for a ready reference.
Another(’s) perspective on subjectivity in causal connectives: a usage-based analysis of volitional causal relations

Dans une hypothese de categorisation linguistique, les connecteurs de cause sont pris comme des outils de categorisation. En effet, des etudes sur corpus suggerent que les connecteurs sont fortement specialises dans une seule categorie de causalite specifique, mais aussi que leur usage n'est pas limite aux categories de causalite auxquelles ils sont prototypiquement associes. Si nous supposons que le sens des connecteurs causaux peut etre adequatement decrit en reference a des categories conceptuelles bien definies, comment pouvons-nous expliquer qu’il y ait une variation dans leur usage reel? Nous mettons l'accent sur les relations de coherence causale volitionnelle, qui constituent le contexte d'usage prototypique du connecteur neerlandais daarom ‘c'est pourquoi’. Un autre moyen d’expression des relations causales volitionnelles est le recours au connecteur dus ‘alors/donc’ qui est prototypiquement utilise dans les relations de causalite epistemique. Notre hypothese est que les relations de causalite volitionnelle exprimees par daarom vs dus different systematiquement en termes de subjectivite. Nous proposons un modele d'analyse qui contient de multiples operationnalisation de la notion de subjectivite et une distinction entre differents niveaux de complexite (sous-clause, clause, et discours). Nous constatons que les relations causales volitionnelles en dus contiennent plus souvent des elements subjectifs que les relations causales volitionnelles en daarom. Nous interpretons cette distribution au sein d'un cadre theorique fonde sur l'usage (usage-based framework), et nous proposons d'analyser les cas volitionnels de dus comme des instanciations non-prototypiques du sens de dus, qui est donc intrinsequement subjectif et prototypiquement epistemique.
A Scalable Linearizable Multi-Index Table

Concurrent data structures typically index data using a single primary key and provide fast atomic access to data associated with a given key value. However, it is often required to atomically access information via multiple primary and secondary keys, and even through additional properties that do not naturally represent keys for the given data. We present lock-free and lock-based algorithms of a table with multiple indexing, supporting linearizable inserts, deletes, and retrieve operations. We have implemented Java versions of our algorithms and evaluated their performance on a multi-core machine. The results show that the proposed table implementations are scalable and more efficient than any existing available alternative for in-memory realizations of a multi-index table.
Relationship between EFL Learners’ Perceived Social Self-Efficacy and their Foreign Language Classroom Anxiety

The present study was conducted to investigate the relationship between the perceived social self-efficacy of the students of English and their foreign language classroom anxiety. The required data were gathered through the application of the original versions of two standard questionnaires: Smith and Betz’s (2000) 25-item Scale of Perceived Social Self-Efficacy (SPSSE) and Horwitz, Horwitz and Cope’s (1986) 33-item Foreign Language Classroom Anxiety Scale (FLCAS). A total of 151 participants (including 127 students of English Language and Literature in B.A. level and 24 students of Teaching English as a Foreign Language at M.A. level) took part in the study. Correlational analysis was employed to determine the relationship between perceived social self-efficacy and foreign language classroom anxiety. Pearson Product-Moment correlation analysis results (r = -.164, p < .05) showed that the participants’ perceived social self-efficacy had a reverse relationship with their foreign language classroom anxiety. Further calculations were done for the type and rate of the influence of demographic variables (namely age, gender, academic seniority, and educational level) on students’ PSSE and FLCA. According to the One-Way ANOVA results, no meaningful relationship was observed between age, gender, academic seniority, and educational level of the participants, and their perceived social self-efficacy or foreign language classroom anxiety. Based on the findings of this study, the rate of perceived social self-efficacy (i.e. trust in self in social situations) seems to play a key role in the intensity of foreign language learners’ anxiety and a vital parameter in their full-functioning and efficient learning.
Budget-Aware Scheduling Algorithms for Scientific Workflows with Stochastic Task Weights on Heterogeneous IaaS Cloud Platforms

This paper introduces several budget-aware algorithms to deploy scientific workflows on IaaS cloud platforms, where users can request Virtual Machines (VMs) of different types, each with specific cost and speed parameters. We use a realistic application/platform model with stochastic task weights, and VMs communicating through a datacenter. We extend two well-known algorithms, MinMin and HEFT, and make scheduling decisions based upon machine availability and available budget. During the mapping process, the budget-aware algorithms make conservative assumptions to avoid exceeding the initial budget; we further improve our results with refined versions that aim at re-scheduling some tasks onto faster VMs, thereby spending any budget fraction leftover by the first allocation. These refined variants are much more time-consuming than the former algorithms, so there is a trade-off to find in terms of scalability. We report an extensive set of simulations with workflows from the Pegasus benchmark suite. Most of the time our budget-aware algorithms succeed in achieving efficient makespans while enforcing the given budget, despite (i) the uncertainty in task weights and (ii) the heterogeneity of VMs in both cost and speed values.
Long‐term ecological data for conservation: Range change in the black‐billed capercaillie (Tetrao urogalloides) in northeast China (1970s–2070s)

Abstract Long‐term ecological data can be an effective tool to help ecologists integrate future projections with historical contexts and provide unique insights into the long‐term dynamics of endangered species. However, hampered by data limitations, including incomplete and spatially biased data, relatively few studies have used multidecadal datasets or have examined changes in biogeography from a historical perspective. The black‐billed capercaillie (Tetrao urogalloides) is a large capercaillie (classified as Least Concern [LC] on the IUCN red list) that has undergone a dramatic decline in population during the late 20th century and is considered endangered. Its conservation status is pessimistic, and the species requires immediate protection. Therefore, we supplemented a historical dataset to identify changes in this bird's range and population in northeast China over the long term. The study area spanned Heilongjiang Province, Jilin Province, and the northeast corner of Inner Mongolia in northeast China. We integrated an ecological niche model (BIOMOD2) with long‐term ecological data on this species to estimate the magnitude of change in distribution over time. Our results revealed a 35.25% reduction in the current distribution of this species compared to their potential distribution in the 1970s. This decline is expected to continue under climate change. For example, the future range loss was estimated to be 38.79 ± 0.22% (8.64–90.19%), and the actual state could be worse, because the baseline range of the model was greater than the real range in the 2000s, showing a 12.39% overestimation. To overcome this poor outlook, a conservation strategy should be established in sensitive areas, including the southwestern Greater Khingan Mountains and northern Lesser Khingan Mountains. Actions that should be considered include field investigations, establishing a monitor network, designing ecological corridors, and cooperating with local inhabitants, governments, and conservation biologists to improve the conservation of the black‐billed capercaillie.
Resource control system stability of mobile data centers

The mobile data center is the basis for building systems with a network-centric architecture. The system for managing the resources of a mobile cloud data center redistributes the computing resources of the data center in accordance with the needs of applications to meet real-time requirements. Resource management is carried out by moving virtual machines from one server to another, which can be located in another data center of the network-centric system. In this paper, we consider the architecture of the cloud data center resource management system using live migration of virtual machines. It is shown that reverse migrations violate the stability of resource management system. In order to reduce the number of reverse migrations, better forecasting is required while determining server overload/underload and when selecting a destination host. The proposed method of determining the stability criterion will minimize the reverse migration flow, which, with a probability of at least 0.9, will make it possible to consider a sustainable system for managing virtual resources of the data center.