Miracle-dz/UniFAR-FTUs huggingface dataset:
Formal proofs of two algorithms for strongly connected components in graphs

We present formal proofs for the two classical Tarjan-1972 and Kosaraju-1978 algorithms for finding strongly connected components in directed graphs. We describe the two algorithms in a functional programming style with abstract values for vertices in graphs, with functions between vertices and their successors, and with data types such that lists (for representing immutable stacks) and sets. We use the Why3 system and the Why3-logic to express these proofs and fully check them by computer. The Why3-logic is a simple multi-sorted first-order logic augmented by inductively defined predicates. Furthermore it provides useful libraries for lists and sets. The Why3 system allows description of programs in a Why3-ML programming language (a first-order programming language with ML syntax) and provides interfaces to various state-of-the-art automatic provers and to manual interactive proof-checkers (we use mainly Coq). One important point of our article is that our proofs are intuitive and human readable.
Selection in Insurance Markets: Theory and Empirics in Pictures

F rom the large-scale social insurance programs of Social Security and Medicare to the heavily regulated private markets for property and casualty insurance, government intervention in insurance markets is ubiquitous. The fundamental theoretical reason for such intervention, based on classic work from the 1970s, is the problem of adverse selection. But despite the age and infl uence of the theory, systematic empirical examination of selection in actual insurance markets is a relatively recent development. Indeed, in awarding the 2001 Nobel Prize for the pioneering theoretical work on asymmetric information to George Akerlof, Michael Spence, and Joseph Stiglitz, the Nobel committee noted this paucity of empirical work (Nobelprize.org, 2001). Over the last decade, however, empirical work on selection in insurance markets has gained considerable momentum, and a fairly extensive (and still growing) empirical literature on the topic has emerged. This research has found that adverse selection exists in some insurance markets but not in others. It has also uncovered examples of markets that exhibit “advantageous selection”—a phenomenon not considered by the original theory, and one that has different consequences for equilibrium insurance allocation and optimal public policy than the classical case of adverse selection. Researchers have also taken steps toward estimating the welfare consequences of detected selection and of potential public policy interventions. Selection in Insurance Markets: Theory and Empirics in Pictures
DESEMPENHO DAS ESCOLAS PÚBLICAS E PRIVADAS DA REGIÃO DO VALE DO PARAÍBA: UMA APLICAÇÃO DA TÉCNICA DE AGRUPAMENTOS KMEANS COM BASE NAS VARIÁVEIS DO ENEM 2015

DOI: 10.12957/cadest.2017. 30347 Este artigo avalia o desempenho dos alunos de escolas publicas e privadas da regiao sul fluminense no Exame Nacional do Ensino Medio (Enem) de 2015 por meio da tecnica nao hierarquica de agrupamentos kmeans. As escolas sao classificadas de acordo com o desempenho dos alunos em funcao das variaveis indicadoras de proficiencia media em ciencias da natureza e suas tecnologias, ciencias humanas e suas tecnologias, linguagens, codigos e suas tecnologias, matematica e suas tecnologias, redacao, formacao docente, taxas de rendimento escolar de aprovacao e participacao percentual de alunos no Enem, todas divulgadas pelo Instituto Nacional de Estudos e Pesquisas Educacionais Anisio Teixeira (INEP). Os resultados indicam a prevalencia de dois grupos que sao aqui caracterizados em funcao do porte da escola, municipio, dependencia administrativa e indicador socioeconomico. Palavras-chave : Kmeans, Analise de Agrupamento, Enem.
Focus on SQUIDs in Biomagnetism

Department of Physics, University of California, Berkeley, CA, United States of America 2 Korea Research Institute of Standards and Science, Republic of Korea MedTech West and the Institute of Neuroscience and Physiology, University of Gothenburg, Sweden Published 22 June 2018 Since the first detection of magnetic signals from the heart by Cohen et al [1] in 1970 using the superconducting quantum interference device (SQUID) developed by J Zimmermann, SQUIDs have been used to measure various magnetic fields from the human body. In the early years, biomagnetic measurements involved just a few SQUIDs. Thanks to the development of thin film technology for reproducibly fabricating SQUIDs in the 1970s and 1980s, multichannel SQUID systems for wider coverage areas followed [2, 3]. The two main applications of SQUIDs were initially magnetocardiography (MCG) [4] and magnetoencephalography (MEG) [5]. Since then, the areas of study have been diversified into, for example, lung [6], intestine [7], fetus [8], and spine [9]. Today, SQUID-based non-invasive imaging tools for functional diagnosis of the brain and heart are commercially-available with high temporal resolution and moderate spatial resolution. In addition to in vivo measurement capabilities, several diagnostic tools have been developed for in vitro diagnosis. For example, SQUID-based readout of bio-functional magnetic nanoparticles (MNPs) [10] is used for detecting cancer [11]. Traditionally, most biomagnetic measurements utilize low-temperature SQUIDs operating at liquid helium temperature. To reduce running costs, two approaches have been pursued. One is the use of high-transition temperature (high-Tc) SQUIDs, cooled with inexpensive liquid nitrogen, and the other involves helium liquefaction systems for recovering the evaporated helium gas and returning the liquid to the SQUID cryostat. Although high-Tc SQUIDs have higher intrinsic noise than their low-Tc counterparts, the reduced distance between SQUID and room temperature provides larger signal strengths. However, poor fabrication yield is currently the main barrier to high-Tc SQUID-based multichannel systems. The publications in this focus issue are selected papers presented at Biomagnetism 2016; the ‘BIOMAG’ conferences are the largest on the subject of biomagnetism.
Secure Caching Scheme by Using Blockchain for Information-Centric Network-Based Wireless Sensor Networks

This paper addresses a secure caching scheme for information-centric network (ICN)-based wireless sensor networks (WSNs). In order to achieve the above mechanism, we utilize both the public-key cryptography technique and the blockchain technique, which enable data to be safely gathered and the decentralized and cross-verified sensing data to be copied and stored. In addition, we propose a protocol design for introducing the proposed structure into an ICN-based WSN system. Furthermore, we formulate statistical models and demonstrate numerical results by performing computer simulations and hardware-based experiments
Radi(c)al Departures: Comparing Conventional Octolinear Versus Concentric Circles Schematic Maps for the Berlin U-Bahn/S-Bahn Networks Using Objective and Subjective Measures of Effectiveness

An experiment is reported in which two designs of Berlin U-/S-Bahn network maps were compared for usability. One was conventional, based on standard schematic design rules used worldwide: Straight lines with tightly radiused corners, and only horizontal, vertical, or 45o diagonal angles permitted. The other was a novel concept, based on concentric circles and spokes radiating from a central point. The former has the benefit of simple line trajectories, the latter potentially has the benefit of a coherent overall appearance. The experiment investigated both an objective performance measure (time required to plan complex journeys) and a variety of subjective measures (choice between maps, ratings of statements associated with usability, direct ratings of usability). All subjects planned journeys using both designs. Overall, performance was worse for the concentric circles map, and it received poor ratings. However, in line with previous research, objective and subjective measures were dissociated. For example, many subjects expressed a preference for the design that was not the best for them in terms of objective performance. © John Benjamins Publishing Company 2016. This article is under copyright and the publisher should be contacted for permission to re-use or reprint the material in any form.
A Novel Two-stage Framework for Extracting Opinionated Sentences from News Articles Conference Program a Novel Two-stage Framework for Extracting Opinionated Sentences from News Articles Normalized Entity Graph for Computing Local Coherence

For the past eight years, the series of TextGraphs workshops have exposed and encouraged the synergy between the field of Graph Theory and Natural Language Processing (NLP). The mix between the two started small, with graph theoretical framework providing efficient and elegant solutions for NLP applications that focused on single documents for part-of-speech tagging, word sense disambiguation and semantic role labelling, got progressively larger with ontology learning and information extraction from large text collections, and have reached web scale through the new fields of research that focus on information propagation in social networks, rumor proliferation, e-reputation, multiple entity detection, language dynamics learning and future events prediction to name but a few. The ninth edition of the TextGraphs workshop would be a new step in the series, focused on issues and solutions for large-scale graphs, such as those derived for web-scale knowledge acquisition or social networks. We encourage the description of novel NLP problems or applications that have emerged in recent years which can be addressed with graph-based solutions, as well as novel graph-based methods that can be applied to known NLP tasks. Continuing to bring together researchers interested in Graph Theory applied to Natural Language Processing provides an environment for further integration of graph-based solutions into NLP tasks. A deeper understanding of new theories of graph-based algorithms is likely to help create new approaches and widen the usage of graphs for NLP applications. This volume contains papers accepted for presentation at the workshop. We issued calls for regular papers, short papers, position papers, and demos. After careful review by the program committee, 6 regular papers and 2 short papers were accepted for presentation. The accepted papers address varied problems – from theoretical and general considerations, to NLP and real-world applications-through interesting variations to known and also novel graph-based methods. We are lucky to have two excellent invited speakers for this year's event. We thank Prof. Mohammed J. Zaki and Partha Talukdar for their enthusiastic acceptance to our invitation. Finally, we are thankful to the members of the program committee for their valuable and high quality reviews. All submissions have benefited from their expert feedback. Their timely contribution was the basis for accepting an excellent list of papers and making this edition of TextGraphs a success. Abstract Guinaudeau and Strube (2013) introduce a graph based model to compute local entity coherence. We propose a computa-tionally efficient normalization method for these graphs …
Government Bonds and the Cross-Section of Stock Returns

We study basic return comovement and predictability patterns in U.S. government bonds and the cross-section of stocks. Government bonds comove most strongly with bond-like stocks, i.e. stocks of large, mature, low-volatility, profitable, dividend-paying firms that are neither high growth nor distressed. Government bonds and bond-like stocks are also copredictable in the sense that time-series variables that predict returns on one asset class also predict returns on the other. In addition to traditional explanations for comovement and copredictability, the evidence is particularly consistent with the hypothesis that fluctuations in investor sentiment affect the demand for both bonds and bond-like stocks relative to the demand for speculative stocks.
Wage Risk and Employment Risk over the Life Cycle ∗

We define the distinction between productivity and employment risk and estimate the components of risk using wage and mobility data from the Panel Study of Income Dynamics. We then calibrate a model of intertemporal consumption and labor supply and study the effect of the two sources of risk on precautionary saving and labor supply. Finally, we measure the relative welfare costs of employment and productivity risk and the insurance contents of simple government programs. JEL Classification: D52; D91; I30.
An Improved Lane-Keeping Controller for Autonomous Vehicles Leveraging an Integrated CNN-LSTM Approach

—Representing the task of navigating a car through traffic using traditional algorithms is a complex endeavor that presents significant challenges. To overcome this, researchers have started training artificial neural networks using data from front-facing cameras, combined with corresponding steering angles. However, many current solutions focus solely on the visual information from the camera frames, overlooking the important temporal relationships between these frames. This paper introduces a novel approach to end-to-end steering control by combining a VGG16 convolutional neural network (CNN) architecture with Long Short-Term Memory (LSTM). This integrated model enables the learning of both the temporal dependencies within a sequence of images and the dynamics of the control process. Furthermore, we will present and evaluate the estimated accuracy of the proposed approach for steering angle prediction, comparing it with various CNN models including the Nvidia classic model, Nvidia model, and MobilenetV2 model when integrated with LSTM. The proposed method demonstrates superior accuracy compared to other approaches, achieving the lowest loss function. To evaluate its performance, we recorded a video and saved the corresponding steering angle results based on human perception from the robot operating system (ROS2). The videos are then split into image sequences to be smoothly fed into the processing model for training.
THERMOXIDIZED AND PHOTOXIDIZED PALM OIL-INDUCED OXIDATIVE STRESS: EFFECTS ON SOME REPRODUCTIVE PARAMETERS IN FEMALE WISTAR RATS

Thermoxidized palm oil (TPO) and photoxidized palm oil (PPO) have been shown to impact negatively on reproductive function in male Wistar rats. The current studies evaluated effects of these oils on some female reproductive parameters and oxidative status considering variations in hormonal and reproductive functions. Fifteen female Wistar rats weighing 80 - 127 g were divided into 3 groups of 5 rats each. Groups 1 (control), 2 and 3 were fed liberally on plain rat’s feeds, TPO and PPO diets respectively for thirteen weeks. Rats being 19-22 weeks old, were anaesthetized and necessary samples collected for estimation of relevant parameters. Results showed significant reduction in utero-ovarian weight in PPO-(P<0.001) and TPO-fed (P<0.001) groups compared with control. Serum malondialdehyde (MDA) concentration was significantly increased in TPO-(P<0.001) and PPO-fed (P<0.001) groups compared with control and in PPO-fed compared with TPO-fed (P<0.01) groups. Serum catalase (CAT) concentration was significantly reduced in TPO-(P<0.001) and PPO-fed (P<0.001) groups compared with control and in PPO-than TPO-fed (P<0.01) groups. Serum glutathione peroxidase (GPx) concentration was significantly lower in TPO-(P<0.001) and PPO-fed (P<0.001) groups compared with control and in PPO-compared with TPO-fed groups (P<0.01). Serum progesterone was significantly reduced in TPO-(P<0.001) and PPO-fed (P<0.001) groups compared with control. Serum estrogen was significantly higher in TPO-(P<0.001) and PPO-fed (P<0.01) rats compared with control but significantly lower in PPO-fed than TPO-fed (P<0.05) groups. We conclude that TPO and PPO induce oxidative stress and alterations in some reproductive parameters in female Wistar rats.
Spectrum Sensing with Diversity Combining Technique in Cognitive Radio

Cognitive radio (CR), which is proposed as a technology that utilizes the frequency resources effectively, has studied to relive scarcity of the frequency resources. CR provides opportunistically unused frequency to the secondary user when the primary user is not detected. Spectrum sensing is the most important technology to detect primary user. However, in the wireless channels, according to the effect of multipath fading channel, spectrum sensing performance is compromised. Therefore, in this paper, we apply diversity scheme that is a useful technique for combating multiple fading in wireless communications. There are several classes of diversity scheme, which are time diversity, antenna diversity, muitipath diversity, frequency diversity, and so on. In this paper, we adopt antenna diversity that is a kind of space diversity. By using the proposed method, we can overcome fading effect and improve spectrum sensing performance.
First report of

Paramyrothecium foliicola is reported for the first time in Brazil and worldwide causing leaf spots on hop (Humulus lupulus). The fungus was identified with a combination of morphological and molecular information. The pathogenicity of P. foliicola to hop was demonstrated through inoculations under controlled conditions.
C ENTRE FOR A PPLIED M ACROECONOMIC A NALYSIS The Australian National University W ELFARE -M AXIMIZING M ONETARY P OLICY UNDER P ARAMETER

This paper examines welfare-maximizing monetary policy in an estimated micro-founded general equilibrium model of the U.S. economy where the policymaker faces uncertainty about model parameters. Uncertainty about parameters describing preferences and technology implies uncertainty about the model’s dynamics, utility-based welfare criterion, and the “natural” rates of output and interest that would prevail absent nominal rigidities. We estimate the degree of uncertainty regarding natural rates due to parameter uncertainty. We ﬁnd that optimal Taylor rules under parameter uncertainty respond less to the output gap and more to price inﬂation than would be optimal absent parameter uncertainty. We also show that policy rules that focus solely on stabilizing wages and prices yield welfare outcomes very close to the ﬁrst-best.
Sub-percent precision Møller polarimetry in experimental Hall C

Modern experiments in Jefferson Lab Hall C require precise knowledge of the electron beam polarization. This knowledge comes from two two complementary polarimeter devices (Møller and Compton). Unlike typical Møller devices, the Hall C Møller polarimeter uses a pure iron foil that is brute-force polarized out-of-plane by a superconducting solenoid. A system of quadrupole magnets focuses the scattered and recoil electrons onto an asymmetric detector array. This design offers several improvements compared to previous devices, enabling sub-percent systematic uncertainties. This talk will introduce the Hall C Møller polarimeter and discuss the necessary work to determine < 1% precision, using the Qweak experiment as an example.
Monitoring the Heavy Element of Cr in Agricultural Soils Using a Mobile Laser-Induced Breakdown Spectroscopy System with Support Vector Machine

Due to its complicated matrix effects, rapid quantitative analysis of chromium in agricultural soils is difficult without the concentration gradient samples by laser-induced breakdown spectroscopy. To improve the analysis speed and accuracy, two calibration models are built with the support vector machine method: one considering the whole spectra and the other based on the segmental spectra input. Considering the results of the multiple linear regression analysis, three segmental spectra are chosen as the input variables of the support vector regression (SVR) model. Compared with the results of the SVR model with the whole spectra input, the relative standard error of prediction is reduced from 3.18% to 2.61% and the running time is saved due to the decrease in the number of input variables, showing the robustness in rapid soil analysis without the concentration gradient samples.
The Purchasing Power Parity Debate

Our willingness to pay a certain price for foreign money must ultimately and essentially be due to the fact that this money possesses a purchasing power as against commodities and services in that country. On the other hand, when we offer so and so much of our own money, we are actually offering a purchasing power as against commodities and services in our own country. Our valuation of a foreign currency in terms of our own, therefore, mainly depends on the relative purchasing power of the two currencies in their respective countries. Gustav Cassel, economist (1922, pp. 138–39) The fundamental things apply As time goes by. Herman Hupfeld, songwriter (1931; from the film Casablanca, 1942)
An inverse feedback fuzzy state space modeling (FFSSM) for insulin-glucose regulatory system in humans

The complexity and nonlinearity of the insulin-glucose regulatory system in humans demands for an inverse modeling technique. In this study the insulin-glucose regulatory system was modeled with the help of an inverse feedback fuzzy state space modeling (FFSSM) approach. The feedback insulin regulatory system was presented as a state space model, its input/output parameters fuzzified and the optimized values deffuzzified using the “Optimized Defuzzified Value Theorem”. In order to get a more detailed insight of the system, the properties concerning state stability of the model were studied. The model was tested and analyzed for insulin sensitive and insulin resistant subjects. The model was found state stable for an intercellular glucose level above 3.50080 mgdl-1 and 20.0080 mgdl-1 for insulin sensitive and insulin resistive subjects, respectively. At the glucose level lower than this specified level, the insulin-glucose system may stop working and the subject be encountered with some serious fatality. Decreasing the glucose intake below 103.6 and 64.5 mgdl-1, in case of insulin sensitive and insulin resistant subjects, respectively, may associate unpredictable parameter values to fuzzy parameters depicting low glucose levels. Key words: Insulin-glucose regulations, feedback systems, fuzzy state space modeling (FSSM), inverse modeling.