Miracle-dz/UniFAR-FTUs huggingface dataset:
Emotional Reactions and the Pulse of Public Opinion: Measuring the Impact of Political Events on the Sentiment of Online Discussions

This paper analyses changes in public opinion by tracking political discussions in which people voluntarily engage online. Unlike polls or surveys, our approach does not elicit opinions but approximates what the public thinks by analysing the discussions in which they decide to take part. We measure the emotional content of online discussions in three dimensions (valence, arousal and dominance), paying special attention to deviation around average values, which we use as a proxy for disagreement and polarisation. We show that this measurement of public opinion helps predict presidential approval rates, suggesting that there is a point of connection between online discussions (often deemed not representative of the overall population) and offline polls. We also show that this measurement provides a deeper understanding of the individual mechanisms that drive aggregated shifts in public opinion. Our data spans a period that includes two US presidential elections, the attacks of September 11, and the start of military action in Afghanistan and Iraq.
Biomarkers in pulmonary hypertension

There have been significant recent advances in the understanding of the pathophysiology of pulmonary hypertension, and a growing number of therapeutic agents have become available to the treating physician. Traditional methods of diagnosing and monitoring this condition have comprised echocardiography and right heart catheterisation, in addition to functional measures, such as estimation of functional class and the 6-min walk test. An increasing number of biomarkers have been described that are elevated in pulmonary hypertension and which may assist the clinician in diagnosis and in the assessment of disease severity and response to treatment. The present article details the more important biomarkers, their potential applications and the evidence supporting their use.
Distinct effects of semantic plausibility and semantic composition in MEG

To date, research on the neurobiology of semantic processing has focused almost entirely on the processing of semantic anomaly, inspired by Kutas & Hillyard’s (1980) discovery of an electrophysiological anomaly detector, the N400 ERP. As a consequence, little progress has been made in understanding how the brain computes the meanings of well-formed plausible expressions. In this study we contrasted semantically implausible and semantically plausible but difficult sentences with control sentences in MEG, in order to elucidate the neural bases of “normal” semantic processing outside the classic semantic violation paradigm. Plausibility, but not semantic composition effort, affected the amplitudes of a left temporal source at 300-400ms (M350), consistent with previous MEG results. In contrast, semantic composition effort, but not plausibility, affected the amplitudes of an anterior midline field (AMF) at 350-500ms. The N400 is commonly hypothesized to reflect semantic “integration. ” But these results show that when semantic composition/integration is manipulated in well-formed plausible expressions, effects occur in the frontal lobe and not in the generator of the N400 effect.
The geometric-VaR backtesting method

This article develops a new test to evaluate value-at-risk (VaR) forecasts. VaR is a standard risk measure widely utilized by financial institutions and regulators, yet estimating VaR is a challenging problem, and popular VaR forecast relies on unrealistic assumptions. Hence, assessing the performance of VaR is of great importance. We propose the geometric-VaR test which utilizes the duration between the violations of VaR as well as the value of VaR. We conduct a Monte Carlo study based on desk-level data and we find that our test has high power against various alternatives.
Title: Ionic Basis of " on " and " off " Persistent Activity in Layer Iii Lateral Entorhinal Cortical Principal Neurons Mechanisms of " on " and " off " Firing in Lec Neurons

Running head: Mechanisms of " On " and " Off " firing in LEC neurons Abstract Principal neurons in layer III of the rat lateral entorhinal cortex (LEC) generate a self-sustained plateau potential and persistent spiking following the application of a brief supra-threshold excitatory stimulus delivered in the presence of the muscarinic receptor agonist carbachol. This persistent activity can be terminated by application of a second excitatory stimulus, and these cells can be repeatedly toggled between "On" and "Off" states by consecutive excitatory stimuli. However, the ionic mechanisms that underlie the production of "On" and "Off" states in layer III LEC neurons are unknown, but appear to involve activity-dependent conductances, since they can be initiated by trains of action potentials evoked by either depolarizing current pulses applied to the cell, or by repetitive spiking induced by activation of excitatory synaptic inputs. In this study, we obtained intracellular recordings from rat layer III LEC neurons in-vitro, and a series of pharmacological and ionic substitution experiments were performed to identify mechanisms involved in the induction and termination of persistent spiking. Our data indicate that initiation of the "On" state depends on spike-evoked calcium influx and subsequent activation of calcium-activated non-selective cationic current. Moreover, we show that termination of persistent firing in response to an excitatory stimulus can be blocked by tetraethylammonium or iberiotoxin, suggesting that the activation of calcium activated potassium current mediated by BK channels is required to induce the "Off" state.
Scaling of InP HEMT Cascode Integrated Circuits to THz Frequencies

In this paper, we demonstrate that the cascode amplifier topology can be extended to operating frequencies > 500 GHz. Two packaged cascode amplifiers are reported, including a broadband 3 stage amplifier with ~17 dB gain and 8.3 dB packaged noise figure at 300 GHz and a narrowband amplifier with 10 dB gain at 0.55 THz measured in package. Both of these amplifiers use 30 nm InP HEMT transistors, are realized in coplanar waveguide on a 1-Mil thick InP substrate and use a monolithically integrated electromagnetic transition for coupling energy from the chip to the waveguide package.
Respiratory dynamics of discontinuous gas exchange in the tracheal system of the desert locust, Schistocerca gregaria

SUMMARY Gas exchange dynamics in insects is of fundamental importance to understanding evolved variation in breathing patterns, such as discontinuous gas exchange cycles (DGCs). Most insects do not rely solely on diffusion for the exchange of respiratory gases but may also make use of respiratory movements (active ventilation) to supplement gas exchange at rest. However, their temporal dynamics have not been widely investigated. Here, intratracheal pressure, VCO2 and body movements of the desert locust Schistocerca gregaria were measured simultaneously during the DGC and revealed several important aspects of gas exchange dynamics. First, S. gregaria employs two different ventilatory strategies, one involving dorso-ventral contractions and the other longitudinal telescoping movements. Second, although a true spiracular closed (C)-phase of the DGC could be identified by means of subatmospheric intratracheal pressure recordings, some CO2 continued to be released. Third, strong pumping actions do not necessarily lead to CO2 release and could be used to ensure mixing of gases in the closed tracheal system, or enhance water vapour reabsorption into the haemolymph from fluid-filled tracheole tips by increasing the hydrostatic pressure or forcing fluid into the haemocoel. Finally, this work showed that the C-phase of the DGC can occur at any pressure. These results provide further insights into the mechanistic basis of insect gas exchange.
Partitioned Fair Round Robin: A Fast and Accurate QoS Aware Scheduler for Embedded Systems

A large class of embedded systems today which concurrently execute numerous independent QoS sensitive applications like streaming audio and video, web browsing, email, interactive gaming etc. Have proportional share schedulers at their heart as the principal resource multiplexing strategy. However, producing schedulers that have both low scheduling overheads as well as good proportional share allocation accuracy have proved to be a daunting task. On one hand, we have schemes that provide optimal task allocation fairness accuracy, but generally suffer scheduling overheads that are at least logarithmic to the number of tasks. On the other hand there are O (1) complexity round-robin based algorithms, but they generally fail to provide good fairness properties. This paper presents Partitioned Proportional Round-Robin (PPRR), a two level hierarchical O (1) proportional share scheduler that achieves near optimal fairness accuracy while executing a mix of jobs with varying priorities in most practical scenarios. Simulation based experimental results reveal that even on systems containing up to 50 tasks with skewed execution rate requirements, a PPRR scheduler with just eight groups is able to provide less than about one percent deviation per task with respect to their ideal execution rates.
Design Constraints on a Synthetic Metabolism

A metabolism is a complex network of chemical reactions that converts sources of energy and chemical elements into biomass and other molecules. To design a metabolism from scratch and to implement it in a synthetic genome is almost within technological reach. Ideally, a synthetic metabolism should be able to synthesize a desired spectrum of molecules at a high rate, from multiple different nutrients, while using few chemical reactions, and producing little or no waste. Not all of these properties are achievable simultaneously. We here use a recently developed technique to create random metabolic networks with pre-specified properties to quantify trade-offs between these and other properties. We find that for every additional molecule to be synthesized a network needs on average three additional reactions. For every additional carbon source to be utilized, it needs on average two additional reactions. Networks able to synthesize 20 biomass molecules from each of 20 alternative sole carbon sources need to have at least 260 reactions. This number increases to 518 reactions for networks that can synthesize more than 60 molecules from each of 80 carbon sources. The maximally achievable rate of biosynthesis decreases by approximately 5 percent for every additional molecule to be synthesized. Biochemically related molecules can be synthesized at higher rates, because their synthesis produces less waste. Overall, the variables we study can explain 87 percent of variation in network size and 84 percent of the variation in synthesis rate. The constraints we identify prescribe broad boundary conditions that can help to guide synthetic metabolism design.
Impacts of mobile technologies, systems and resources on language learning: A systematic review of selected journal publications from 2007-2016

This study examined the mobile-assisted language learning studies published from 2007 to 2016 in selected journals from the aspects of adopted mobile devices, mobile learning systems/resources, and the benefits and challenges of utilizing mobile devices or learning systems/resources. The results revealed that the traditional mobile devices (e.g., Personal Digital Assistants, PDAs) and the current popular mobile devices (e.g., smartphones and tablet PCs) were frequently adopted for language learning in different time periods, while wearable devices have not been adopted by any language learning research so far. In addition, most of the studies used researcher-developed learning systems/resources, while the use of educational affordances of free applications or resources needs to be promoted. Furthermore, the abundant benefits of using mobile devices or mobile learning systems/resources for language acquisition were found in many studies, such as providing substantial chances for learning, and providing or building authentic environments for learners’ meaningful knowledge construction; on the other hand, the studies also reported several challenges (e.g., insufficient practice time and the lack of effective learning strategies) to be overcome in the future. Finally, several suggestions are provided for researchers or practitioners to conduct their future work.
The Metabolic Syndrome and Mind-Body Therapies: A Systematic Review

The metabolic syndrome, affecting a substantial and increasing percentage of the worldwide population, is comprised of a cluster of symptoms associated with increased risk of type 2 diabetes, cardiovascular disease, and other chronic conditions. Mind-body modalities based on Eastern philosophy, such as yoga, tai chi, qigong, and meditation, have become increasingly popular worldwide. These complementary therapies have many reported benefits for improving symptoms and physiological measures associated with the metabolic syndrome. However, clinical trial data concerning the effectiveness of these practices on the syndrome as a whole have not been evaluated using a systematic and synthesizing approach. A systematic review was conducted to critically evaluate the data from clinical trials examining the efficacy of mind-body therapies as supportive care modalities for management of the metabolic syndrome. Three clinical trials addressing the use of mind-body therapies for management of the metabolic syndrome were identified. Findings from the studies reviewed support the potential clinical effectiveness of mind-body practices in improving indices of the metabolic syndrome.
Detection of Type 2 Diabetes Mellitus Disease with Data Mining Approach Using Support Vector Machine

Diabetes is a chronic disease and a major problem of morbidity and mortality in developing countries. The International Diabetes Federation (IDF) estimates that 285 million people around the world have diabetes. This total is expected to rise to 438 million within 20 years. Type 2 diabetes (TTD) is the most common type of diabetes and accounts for 90-95% of all diabetes. Detection of TTD from various factors or symptoms became an issue which was not free from false presumptions accompanied by unpredictable effects. According to this context,data mining could be used as an alternative way,help us in knowledge discovery from data. This paper utilize support vector machine (SVM) in the data mining process to acquire information from historical data of patient medical records. It offers a decision-making support through early detection of TTD for physicians and others.
Retrieving of Remembrances via a Computational Cognitive Model of Knowledge Representation

To understand oneself is one of the greatest challenges for man. Subsequently, a multitude of theories was proposed by the past to model the mind and the behaviour that it dictates. Nowadays, computational technology has progressed to the point that partial implementations of mental models can be rigorously constructed. ACT-R (Anderson et al., 2004) is a computational cognitive theory that allows modellers to develop simulations of human behaviour that cover a wild variety of cognitive phenomena. This implies that the popular ACT-R architecture can offers a fair approximation of human cognitive ability. However, some exceptions do not support this conventional wisdom.
Delays in Motor Development in Children with Down Syndrome

Background Children with Down syndrome (DS) present with delays in motor development. The reduced size of the cerebrum, brain maturation disorders, and pathophysiological processes lead to motor development delay. The aim of this study was to examine the gross motor function and estimate what motor abilities are significantly delayed in children with Down syndrome even if they attend physical therapy sessions. Another purpose of the study was to assess the functional balance. Material/Methods The study group consisted of 79 children with DS (42 boys, 37 girls), average age 6 years and 3 months ±4 years and 6 months. Participants were divided into 3 groups according to (i) age: <3 years old, 3–6 years old, and >6 years old; and (ii) motor impairment scale: mild (SNR 1), moderate (SNR 2), and severe (SNR 3). Children were assessed using the Gross Motor Function Measure-88 (GMFM-88) and Pediatric Balance Scale (PBS). Results None of the assessed children developed all the functions included in GMFM-88. The standing position was achieved at the specified age by 10% of children in the first age group (<3 years old) and 95% of children aged 3–6 years. Similarly, the walking ability was performed by 10% of children under 3 years old and by 95% of children aged 3–6 years. The median score of PBS was 50 points (min. 34 p. – max. 56 p.). There was a statistically significant correlation between PBS scores and GMFM-88 scores, r=0.7; p<0.0001, and between balance scores and GMFM – 88 E (walking, running, jumping) (r=0.64; p<0.0001). Conclusions Motor development, especially standing position and walking ability, is delayed in children with Down syndrome. Balance and motor functions are correlated with each other, so both aspects of development should be consider together in physical therapy of children with Down syndrome.
Fuzzy toric geometries

We describe a construction of fuzzy spaces which approximate projective toric varieties. The construction uses the canonical embedding of such varieties into a complex projective space: The algebra of fuzzy functions on a toric variety is obtained by a restriction of the fuzzy algebra of functions on the complex projective space appearing in the embedding. We give several explicit examples for this construction; in particular, we present fuzzy weighted projective spaces as well as fuzzy Hirzebruch and del Pezzo surfaces. As our construction is actually suited for arbitrary subvarieties of complex projective spaces, one can easily obtain large classes of fuzzy Calabi-Yau manifolds and we comment on fuzzy K3 surfaces and fuzzy quintic three-folds. Besides enlarging the number of available fuzzy spaces significantly, we show that the fuzzification of a projective toric variety amounts to a quantization of its toric base.
A Model Checker for Hybrid Logic

The current technological trend depicts a scenario in which space, and more generally the environment in which the computation takes place, represents a key aspect that must be considered in order to improve systems context awareness. Reasoning about such context can be interpreted as spatial reasoning, which means not only to be able to carry out inferences about the space itself, but also inferences about spatially related information according a given background knowledge. Past works have shown that hybrid modal logics are a powerful and rich formalism to model qualitative spatial reasoning and reasoning on information spread into graph-like structures. In this paper we present the preliminary results we obtained in designing and implementing HyLMoC, a model checking system for hybrid modal logics. The functionalities of the model checker are based on backend module that accepts as inputs a list of hybrid modal formulas and the specification of a labeled graph structure that is compliant with the characteristics of a Kripke model. The current implementation of the backend allows to perform different reasoning tasks with respect to those inputs: Local and Global model checking, and All-worlds model checking.
Non-Parametric Early Warning Signals from Volumetric DDoS Attacks

Distributed Denial of Service (DDoS) is a classic type of Cybercrime and can still strongly damage company reputat ion and increase costs. Attackers have continuously improved t heir strategies, and the amount of unleashed communication requ ests has doubled in volume, size and frequency. This has occurred through different isolated hosts, leading them to resourceexhaustion. Previous studies have concentrated efforts in de t cting or mitigating ongoing DDoS attacks. However, addressing DD oS when it is already in place may be too late. In this article, we attract the attention for the crucial role and importance of the early prediction of attack trends in order to support network resilience. We suggest the use of statistical and non-param etric leading indicators for identifying trends of volumetric DDoS attacks and we report promising results over real dataset fr om CAIDA.
Weak Reflection Principle for Levy Processes

In this paper, we develop a new mathematical technique which allows us to express the joint distribution of a Markov process and its running maximum (or minimum) through the marginal distribution of the process itself. This technique is an extension of the classical reflection principle for Brownian motion, and it is obtained by weakening the assumptions of symmetry required for the classical reflection principle to work. We call this method a weak reflection principle and show that it provides solutions to many problems for which the classical reflection principle is typically used. In addition, unlike the classical reflection principle, the new method works for a much larger class of stochastic processes which, in particular, do not possess any strong symmetries. Here, we review the existing results which establish the weak reflection principle for a large class of time-homogeneous diffusions on a real line and then proceed to extend this method to the L\'{e}vy processes with one-sided jumps (subject to some admissibility conditions). Finally, we demonstrate the applications of the weak reflection principle in financial mathematics, computational methods and inverse problems.
Genistein inhibits estradiol- and environmental endocrine disruptor-induced growth effects on neuroblastoma cells in vitro

The aim of this study was to examine the effect of genistein on human neuroblastoma cell proliferation induced by two common environmental endocrine disruptors, bisphenol A (BPA) and Di-2-ethylhexyl phthalate (DEHP), and to investigate its underlying mechanism. SK-N-SH human neuroblastoma cells were treated with E2 (1 ng/ml), BPA (2 μg/ml) or DEHP (100 μM), with or without genistein (12.5 μM) in vitro. The number of viable cells was detected with an absorbance reader after 0, 24, 48 or 72 h treatment. The percentage of cells in different phases, and expression of Akt and its phosphorylation levels were also assessed by flow cytometry and western blot analysis at 72 h, respectively. The BPA and DEHP groups had a 30% higher number of viable cells compared to the non-treated group at 48 h (P<0.001). However, the cell numbers did not increase significantly in the groups with additional treatment with genistein (P>0.05 vs. control) and the same trend was observed at 72 h. The expression of phospho-Akt protein was increased in the groups treated with BPA or DEHP compared to the control group at 72 h (P<0.05), while no significant elevation in the expression of phospho-Akt was observed (P>0.05) in genistein-treated groups. Cells were arrested at the G2/M phase by genistein. Similar effects were observed in the E2 group with or without genistein treatment. Akt protein expression had no significant change among all the groups (P>0.05). In conclusion, estradiol- or environmental endocrine disruptor-induced proliferation of human neuroblastoma cells is effectively abolished by genistein, likely in a cell cycle- and Akt pathway-dependent manner.
On diffeomorphisms over surfaces trivially embedded in the 4–sphere

A surface in the 4-sphere is trivially embedded, if it bounds a 3- dimensional handle body in the 4-sphere. For a surface trivially embedded in the 4-sphere, a dieomorphism over this surface is extensible if and only if this preserves the Rokhlin quadratic form of this embedded surface. AMS Classication 57N10; 57N05, 20F38