Miracle-dz/UniFAR-FTUs huggingface dataset:
Improved Stability and Stabilization Results for Stochastic Synchronization of Continuous-Time Semi-Markovian Jump Neural Networks With Time-Varying Delay

Continuous-time semi-Markovian jump neural networks (semi-MJNNs) are those MJNNs whose transition rates are not constant but depend on the random sojourn time. Addressing stochastic synchronization of semi-MJNNs with time-varying delay, an improved stochastic stability criterion is derived in this paper to guarantee stochastic synchronization of the response systems with the drive systems. This is achieved through constructing a semi-Markovian Lyapunov–Krasovskii functional together as well as making use of a novel integral inequality and the characteristics of cumulative distribution functions. Then, with a linearization procedure, controller synthesis is carried out for stochastic synchronization of the drive-response systems. The desired state-feedback controller gains can be determined by solving a linear matrix inequality-based optimization problem. Simulation studies are carried out to demonstrate the effectiveness and less conservatism of the presented approach.
Long Memory in Stock Market Volatility: Indian Evidences

Long memory in variance or volatility refers to a slow hyperbolic decay in auto-correlation functions of the squared or log-squared returns. GARCH models extensively used in empirical analysis do not account for long memory in volatility. The present paper examines the issue of long memory in volatility in the context of Indian stock market using the fractionally integrated generalized autoregressive conditional heteroscedasticity (FIGARCH) model. For the purpose, daily values of 38 indices from both National Stock Exchange (NSE) and Bombay Stock Exchange (BSE) are used. The results of the study confirm presence of long memory in volatility of all the index returns. This shows that FIGARCH model better describes the persistence in volatility than the conventional ARCH-GARCH models.
Differential Expression Profiling of Long Noncoding RNA and mRNA during Osteoblast Differentiation in Mouse

Long noncoding RNAs (lncRNAs) are emerging as an important controller affecting metabolic tissue development, signaling, and function. However, little is known about the function and profile of lncRNAs in osteoblastic differentiation in mice. Here, we analyzed the RNA-sequencing (RNA-Seq) datasets obtained for 18 days in two-day intervals from neonatal mouse calvarial pre-osteoblast-like cells. Over the course of osteoblast differentiation, 4058 mRNAs and 3948 lncRNAs were differentially expressed, and they were grouped into 12 clusters according to the expression pattern by fuzzy c-means clustering. Using weighted gene coexpression network analysis, we identified 9 modules related to the early differentiation stage (days 2–8) and 7 modules related to the late differentiation stage (days 10–18). Gene ontology and KEGG pathway enrichment analysis revealed that the mRNA and lncRNA upregulated in the late differentiation stage are highly associated with osteogenesis. We also identified 72 mRNA and 89 lncRNAs as potential markers including several novel markers for osteoblast differentiation and activation. Our findings provide a valuable resource for mouse lncRNA study and improves our understanding of the biology of osteoblastic differentiation in mice.
Tanshinone IIA Induces Autophagic Cell Death via Activation of AMPK and ERK and Inhibition of mTOR and p70 S6K in KBM‐5 Leukemia Cells

Although tanshinone IIA (Tan IIA) from Salviae miltiorrhizae was known to induce apoptosis in various cancers, its underlying mechanism of autophagic cell death was not reported yet. Thus, in the present study, the molecular mechanism of autophagic cell death by Tan IIA was investigated in KBM‐5 leukemia cells. Tan IIA significantly increased the expression of microtubule‐associated protein light chain 3 (LC3) II as a hallmark of autophagy in western blotting and immunofluorescence staining. Tan IIA augmented the phosphorylation of adenosine monophosphate‐activated protein kinase (AMPK) and attenuated the phosphorylation of mammalian target of rapamycin (mTOR) and p70 S6K in a dose‐dependent manner. Conversely, autophagy inhibitor 3‐methyladenine partly reversed the cytotoxicity and the phosphorylation of AMPK, mTOR and p70 S6K induced by Tan IIA in KBM‐5 leukemia cells. In addition, Tan IIA dramatically activated the extracellular signal regulated kinase (ERK) signaling pathway including Raf, ERK and p90 RSK in a dose‐dependent and time‐dependent manner. Consistently, ERK inhibitor PD184352 suppressed LC3‐II activation induced by Tan IIA, whereas PD184352 and PD98059 did not affect poly (ADP‐ribose) polymerase cleavage and sub‐G1 accumulation induced by Tan IIA in KBM‐5 leukemia cells. Furthermore, Tan IIA could induce autophagy via LC3‐II activation in various cancer cells such as prostate (PC‐3), multiple myeloma (U266), lung (NCI‐H460), and breast (MDA‐MB‐231) cells. Overall, these findings suggest that Tan IIA induces autophagic cell death via activation of AMPK and ERK and inhibition of mTOR and p70 S6K in KBM‐5 cells as a potent natural compound for leukemia treatment. Copyright © 2013 John Wiley & Sons, Ltd.
A Basic and Brief Scheme of an Application of a Machine Learning Process

Machine learning methods are powerful tools in modeling systems or extracting knowledge about a phenomenon from samples. This paper is written in order to make the process of machine learning clearer. Therefore, the reason behind the usage of each stage of this process was given briefly. Later, Highleyman dataset was employed in tests in ML methods.
International Journal of Hospitality Management Developing a scale of hospitableness: A tale of two worlds

Hospitableness is a socio-psychological phenomenon. Thus far, scientiﬁc attention to this concept has been mainly conceptual rather than empirical. One reason may be the difﬁculty of precisely measuring this emotionally laden concept that is felt easily but cannot be described with the same level of ease in a scientiﬁcally rigorous manner. The current study was conducted to deﬁne and measure this critical construct using a mixed-methods approach. A scale of hospitableness with structural (underlying dimen- sions) and psychometric (reliability and validity) properties was developed to measure the importance of hospitableness in different consumption contexts including, destination, hotel, and restaurant products. Several steps of scale development procedures resulted in a Hospitableness Scale with 10 stable items assembling into Heartwarming, Heart-assuring and Heart-soothing factors. © 2015 Elsevier Ltd. All rights reserved.
Hypotheses to explain high-nutrient conditions in the open sea

Ocean high-nutrient, low-chlorophyll waters are characterized principally by the persistence of major nutrients at the sea surface. This condition indicates control of autotrophic production by something other than NO{sub 3} or PO{sub 4}, but the nature of this control is at present unresolved. The range of hypotheses to explain the high-nutrient condition is illustrated by the grazing hypothesis (specific growth rates of phytoplankton are maximal and environmental stability allows development of a balanced food web that maintains low standing crops of phytoplankton) and the iron hypothesis (standing crop of plankton is constrained by availability of Fe: if more Fe were available, the standing crop of phytoplankton would increase and NO{sub 3} would be depleted, despite grazing). The iron hypothesis has been examined experimentally in the subarctic and equatorial Pacific and in Antarctic waters. In each environment, Fe enrichment enhanced the field yield of phytoplankton and that enrichment of high-nutrient waters with Fe would change the species composition of phytoplankton and food-web interactions, thereby enhancing utilization of NO{sub 3}. The magnitude of this enhancement cannot be predicted with confidence.
Slashed Moment Exponential Distribution

In this article, we introduce a new class of slash distribution, the slashed moment exponential distribution. The proposed distribution can be seen as an extension of the moment exponential distribution proposed in Dara and Ahmad (2012). This extension is more flexible than the moment exponential distribution in terms of kurtosis of distribution. It arises as the ratio of two independent random variables, a moment exponential distribution in the numerator and a power of uniform distribution in the denominator. We study some probability properties, discuss moment and maximum likelihood estimations and derive the reliability function and hazard function. Finally, we present two real data applications indicating that the new distribution can improve the moment exponential and exponentiated moment exponential distributions in fitting real data.
The role of rifting in the generation of melt: Implications for the origin and evolution of the Lada Terra‐Lavinia Planitia region of Venus

A rift zone over 6000 km in total length runs along the border of Lada Terra, a highland in the southern hemisphere of Venus, and Lavinia Planitia, a basin that has been interpreted as a site of early-stage mantle downwelling. Along the length of the rift are a number of volcanic centers of widely varying morphology and volcanic output. These include coronae, radially fractured domes, and large flow fields similar in scale to terrestrial flood basalts. We develop a model for the origin of extension related to passive rifting in response to stresses created by the adjacent downwelling. Volcanism and extension at other rifts on Venus, such as Devana Chasma, have been attributed to deep-seated mantle plume activity. In contrast, we interpret the origin of extension and volcanism along the Lada rift to be linked to upwelling and decompression melting of mantle material due to rifting and, possibly, to counterflow associated with downwelling. Extension occurred generally prior to the formation of volcanic centers and the eruption of large-scale flow fields, although most of the volcanic centers have been fractured by continued extension along the rift. Current debate over the formation of terrestrial flood basalts centers on the necessity of preexisting extension and stretched and thinned lithosphere to produce enhanced decompression melting within a large plume head or mantle thermal anomaly. Our studies of large-scale flow fields associated with the Lada rift and coronae on Venus indicate that extension is a prerequisite for the formation of the majority of large-scale flow units on Venus.
EMTC: Multilabel Corpus in Movie Domain for Emotion Analysis in Conversational Text

It is proved that in text-based communication such as sms, messengers applications, misinterpretation of partner’s emotions are pretty common. In order to tackle this problem, we propose a new multilabel corpus named Emotional Movie Transcript Corpus (EMTC). Unlike most of the existing emotion corpora that are collected from Twitters and use hashtags labels, our corpus includes conversations from movie with more than 2.1 millions utterances which are partly annotated by ourselves and independent annotators. To our intuition, conversations from movies are closer to real-life settings and emotionally richer. We believe that a corpus like EMTC will greatly beneﬁt the development and evaluation of emotion analysis systems and improve their ability to express and interpret emotions in text-based communication.
Semi-Supervised Clustering for Short Answer Scoring

This paper investigates the use of semi-supervised clustering for Short Answer Scoring (SAS). In SAS, clustering techniques are an attractive alternative to classiﬁcation because they provide structured groups of answers in addition to a score. Previous approaches use unsupervised clustering and have teachers label some items after clustering. We propose to re-allocate some of the human annotation effort to before and during the clustering process for (i) feature selection, (ii) for creating pairwise constraints and (iii) for metric learning. Our methods improve clustering performance substantially from 0.504 kappa for unsupervised clustering to 0.566
Corrosion mitigation coatings for RF sources and components

Most all high power RF sources and components require liquid cooling, usually high purity water. Copper and associated braze alloys are susceptible to corrosion if the water contains impurities or modest levels of oxygen. Unfortunately, high purity water is not readily available in many locations, including developing countries, remote sites, and naval vessels. The U.S. Navy is funding development of protective coatings to reduce or eliminate corrosion in copper coolant channels in RF sources and solenoids. This presentation will describe procedures for applying corrosion mitigation coatings in RF sources and associated components and equipment.
A Bird’s-eye View of Language Processing Projects at the Romanian Academy

This article gives a general overview of five AI language-related projects that address contemporary Romanian language, in both textual and speech form, language related applications, as well as collections of old historic documents and medical archives. Namely, these projects deal with: the creation of a contemporary Romanian language text and speech corpus, resources and technologies for developing human-machine interfaces in spoken Romanian, digitization and transcription of old Romanian language documents drafted in Cyrillic into the modern Latin alphabet, digitization of the oldest archive of diabetes medical records and dialogue systems with personal robots and autonomous vehicles. The technologies involved for attaining the objectives range from image processing (intelligent character recognition for hand-writing and old Romanian documents) to natural language and speech processing techniques (corpus compiling and documentation, multi-level processing, transliteration of different old scripts into modern Romanian, command language processing, various levels of speech-text alignments, ASR, TTS, keyword spotting, etc.). Some of these projects are approaching the end, others have just started and others are about to start. All the reported projects are national ones, less documented than the international projects we are/were engaged in, and involve large teams of experts and master/PhD students from computer science, mathematics, linguistics, philology and library sciences.
Temporal emotion-aspect modeling for discovering what students are concerned about in online course forums

ABSTRACT Textual data, as a key carrier of learning feedback, is continuously produced by many students within course forums. The temporal nature of discussion requires students’ emotions and concerned aspects (e.g. teaching styles, learning activities, etc.) to be dynamically tracked for understanding learning requirements. To characterize dynamics of emotion-aspects, this paper presents an unsupervised model, namely temporal emotion-aspect model (TEAM), modeling time jointly with emotions and aspects to capture emotion-aspect evolutions over time. Especially, the primary output of TEAM is two-fold: emotion-specific aspect probabilistic distributions and their evolutions over time. With the discussion data from two online course forums, we validated the performance of TEAM and utilized this model to discover most concerned emotion-aspects as well as their evolutionary trends for the whole learning group and different achievement levels of groups, respectively. The results indicated that, (1) content-related aspects were the main focus with higher probabilities to negative and confused emotions; (2) there were higher probabilities of emotional expressions in the initial and final stages of a semester; (3) compared with high- and medium-achieving students, low-achieving students were less active in emotional engagement on the whole, and tended to express more confusion in the final stage of a semester.
The Perception Of Network Congestion By Using Parking Fees

A lot of work has been produced in order to internalise the external effects of road transport in the user perceived cost by using trrdlic fares. In the traffic engineering practice only a few links can be charged by a toll system. The principal aim of this work has been the calculation of parking fkes able to take into account the congestion cost generatd by road users in the network and in the parking areas. The simulation of the transport system has not considered crossover traffic and it has supposed the presence of a public transport system, which could meet a higher level of demand. It has been proved that the calculated parking fees are a local maximum of the non-convex fimction estimating the social surplus generated by parking fees. The existence of the solution of the fixed-point problem has been proved by the Brewer theorem and an algorithm to solve it has been proposed. The demand elasticity for modal split has been taken into account. A simulation of the method has been carried out in a part of the real network of PaIermo (the principal town of Sicily). A comparison between the proposed method and an optimisation algorithm able to search a local maximum of social surplus function, taking into account the equilibrium between transport demand and supply, has been carried out.
Estimating Water Supply Infrastructure Cost Using Regression Techniques

AbstractThe current paper aims at the establishment and validation of reference cost functions for different types of assets of water supply systems based on known hydraulic (e.g., flow, pump head, pump power) and physical (e.g., volume, material, nominal pressure, diameter) characteristics of the assets. A five-step methodology was followed: (1) database construction and asset characterization; (2) present cost value calculation; (3) key parameters and cost function establishment; (4) model specification; and (5) model testing and validation. A sample of cost and infrastructure data from several Portuguese water utilities has been used. Multiple linear regression analysis has been carried out to obtain cost functions. Cost modeling also includes the estimation of prediction bands to describe cost uncertainty. Developed cost functions have been tested and validated using 10% of randomly selected data.
Analyzing Middle High German Syntax with RDF and SPARQL

The paper presents technological foundations for an empirical study of Middle High German (MHG) syntax. We aim to analyze the diachronic changes of MHG syntax on the example of direct and indirect object alterations in the middle ﬁeld. In the absence of syntactically annotated corpora, we provide a rule-based shallow parser and an enrichment pipeline with the purpose of quantitative evaluation of a qualitative hypothesis. We provide a publicaly available enrichment and annotation pipeline grounded. A technologically innovative aspect is the application of CoNLL-RDF and SPARQL Update for parsing.
On Hilbert

In this paper random variables that take their values from a Hilbert C -module are defined and three definitions for the mean, covariance operator, and Gaussian distribution of these random variables are given and it is shown that these definitions are equivalent. Furthermore, the concept of covariance of two real valued random variables and its properties are extended to two Hilbert C -module valued random variables. These lead us to the generalization of Rao-Blackwell theorem for this type of random variables. Finally, in a special case, it is proved that the finiteness of second moment of the norm of such a random variable is a sufficient condition for the central limit theorem to be true.
Perianth and abiotic factors regulate seed germination of Haloxylon stocksii—A cash crop candidate for degraded saline lands

Haloxylon stocksii, a common succulent halophyte of saline flats in Pakistan and adjacent countries, is utilized as forage, washing soda, and medicines by the local people. In addition, its cultivation can also prevent land degradation by erosion and salinity. Given that information about its seed ecology is limited, this study aimed to unveil the germination requirements of H. stocksii seeds. Seed morpho‐physical features and effects of perianth persistence, salinity (0–500‐mM NaCl), photoperiod (12 hr light/12 hr dark and 24 hr dark), thermoperiod (10/20°C, 15/25°C, 20/30°C, and 25/35°C), and osmotic stress (0 to −4.29 MPa) on germination and recovery were studied. Presence of perianth caused reductions both in imbibition and germination compared to seeds with perianth removed. Seeds germinated optimally under moderate (20/30°C) than lower (10/20°C and 15/25°C) and higher (25/35°C) temperatures. Under 24 hr dark seed germination was ~20% lower than that in 12‐hr photoperiod at 20/30°C and in distilled water. NaCl increment decreased germination, and only ~20% seeds germinated in the highest NaCl concentration. Ungerminated seeds, when shifted from salt solution to distilled water, showed high recovery of germination. Polyethylene glycol treatment also reduced germination, which was comparable with NaCl treatments. However, polyethylene glycol‐treated seeds showed low recovery, unlike NaCl‐treated seeds. Our data unveil that seeds of H. stocksii germinate optimally upon removal of perianth, under moderate temperature, in absence of salinity and/or osmotic stresses. This study thus provides essential baseline information for mass‐scale cultivation and conservation of H. stocksii in degraded arid‐saline areas.
Enhancing the AI2 Diagrams Dataset Using Rhetorical Structure Theory

This paper describes ongoing work on a multimodal resource based on the Allen Institute AI2 Diagrams (AI2D) dataset, which contains nearly 5000 grade-school level science diagrams that have been annotated for their elements and the semantic relations that hold between them. This emerging resource, named AI2D-RST, aims to provide a drop-in replacement for the annotation of semantic relations between diagram elements, whose description is informed by recent theories of multimodality and text-image relations. As the name of the resource suggests, the revised annotation schema is based on Rhetorical Structure Theory (RST), which has been previously used to describe the multimodal structure of diagrams and entire documents. The paper documents the proposed annotation schema, describes challenges in applying RST to diagrams, and reports on inter-annotator agreement for this task. Finally, the paper discusses the use of AI2D-RST for research on multimodality and artiﬁcial intelligence.
One event, many representations. Mapping action concepts through visual features.

This paper faces the problem of unifying the representation of actions and events in different semantic resources. The proposed solution exploits the IMAGACT visual component (video scenes that represent physical actions) as the linkage point among resources. By using visual objects, we connected resources responding to different scopes and theoretical frameworks, in which a concept-to-concept mapping appeared difﬁcult to obtain. We provide a brief description of two experiments that exploit IMAGACT videos as a linkage point: an automatic linking with BabelNet, a multilingual semantic network, and a manual linking with Praxicon, a conceptual knowledge base of action. The aim of this work is to integrate data from resources with different level of granularity in order to describe the action semantics from a linguistic, visual and motor point of view.