Miracle-dz/UniFAR-FTUs huggingface dataset:
Artificial Intelligence-Based Modeling and Control of Fluidized Bed Combustion

1 Introduction AI-inspired techniques have a lot to offer when developing methods for advanced identification , monitoring, control and optimization of industrial processes, such as power plants. Advanced control methods have been extensively examined in the research of the Power Plant Automation group at the Systems Engineering Laboratory (for an overview, see Ikonen & Kovacs 2007), e.g., in fuel inventory modelling, combustion power control, modelling and control of flue gas oxygen, drum control, modelling and control of superheaters, or in optimization of flue-gas emissions (Ikonen et al. 2000; Benyo et al. 2006; Najim et al 2006). Most engineering approaches to artificial intelligence (AI) are characterized by two fundamental properties: the ability to learn from various sources and the ability to deal with plant complexity. Learning systems that are able to operate in uncertain environments based on incomplete information are commonly referred to as being intelligent. A number of other approaches exist, characterized by these properties, but not easily categorized as AI-systems. Advanced control methods (adaptive, predictive, multivariable, robust, etc.) are based on the availability of a model of the process to be controlled. Hence identification of processes becomes a key issue, leading to the use of adaptation and learning techniques. A typical learning control system concerns a selection of learning techniques applied for updating a process model, which in turn is used for the controller design. When design of learning control systems is complemented with concerns for dealing with uncertainties or vagueness's in models, measurements, or even objectives, particularly close connections exist between advanced process control and methods of artificial intelligence and machine learning. 2 Objectives of the research Needs for advanced techniques are typically characterized by the desire to properly handle plant non-linearities, the multivariable nature of the dynamic problems, and the necessity to adapt to changing plant conditions. In the field of fluidized bed combustion (FBC) control, the many promising applications arise from the uncertainties and complexity of the combustion process, and the difficulties in obtaining reliable measurements from the changing furnace conditions. In our works, research on the application of AI techniques on the FBC have been conducted on fields such as modelling of FBC flue gas emissions from data using distributed logic processors, on-line identification of multi-fuel FBC NOx emissions using adaptive prototypes, modelling combustion in FBC using Wiener and Hammerstein models, or multivariable FBC trajectory control using genea-logical decision trees. Currently work focuses on applications …
Structural studies of conotoxins

Conotoxins are small disulfide‐rich peptides from the venoms of marine cone snails. They target a variety of ion channels, transporters, and receptors besides the interest in their natural functions in venoms and they are of much interest as drug leads. This short article gives an overview of the structural diversity of conotoxins, and illustrates this diversity with recent selected examples of conotoxin structures. © 2009 IUBMB IUBMB Life, 61(2): 144–150, 2009
The effects of e-learning characteristics on e-learner's scholastic performance

RThe main object of this study is to stipulate the relation between e-learning characteristics and e-learner's scholastic performance through the integrated study model of perspective of educational technology and information technology. Using e-learning system quality, e-learning contents characteristics and interaction as independent variable, e-learner's scholastic performance as dependent variable and learning motivation as mediator, this study has examined the relationship among these variables. Two hundreds and twelve undergraduates in cyber university participated in the survey and filled out questionnaires related to this study. The main results are as followed. First, content's quality, technical quality and the support of school affairs have a significant effect on the e-learner's scholastic performance. Second, Learning motivation plays a partial mediating role in the relationship between e-learning characteristics and e-learner's scholastic performance. The meaningful implication of this study is that to improve e-learner's scholastic performance, we have to offer e-learners more customized various learning plans, learning contents and interaction between e-learners and e-learning systems.
Subjective understanding, computer models of belief systems

Abstract : Modeling human understanding of natural language requires a model of the processes underlying human thought. No two people think exactly alike; different people subscribe to different beliefs and are motivated by different goals in their activities. A theory of subjective understanding has been proposed to account for subjectively-motivated human thinking ranging from ideological belief to human discourse and personality traits. A process-model embodying this theory has been implemented in a computer system, POLITICS. POLITICS models human ideological reasoning in understanding the natural language text of international political events. POLITICS can model either liberal or conservative ideologies. Each ideology produces a different interpretation of the input event. POLITICS demonstrates its understanding by answering questions in natural language question-answer dialogs.
Intrusion Detection: Supervised Machine Learning

Due to the expansion of high-speed Internet access, the need for secure and reliable networks has become more critical. The sophistication of network attacks, as well as their severity, has also increased recently. As such, more and more organizations are becoming vulnerable to attack. The aim of this research is to classify network attacks using neural networks (NN), which leads to a higher detection rate and a lower false alarm rate in a shorter time. This paper focuses on two classification types: a single class (normal, or attack), and a multi class (normal, DoS, PRB, R2L, U2R), where the category of attack is also detected by the NN. Extensive analysis is conducted in order to assess the translation of symbolic data, partitioning of the training data and the complexity of the architecture. This paper investigates two engines; the first engine is the back-propagation neural network intrusion detection system (BPNNIDS) and the second engine is the radial basis function neural network intrusion detection system (BPNNIDS). The two engines proposed in this paper are tested against traditional and other machine learning algorithms using a common dataset: the DARPA 98 KDD99 benchmark dataset from International Knowledge Discovery and Data Mining Tools. BPNNIDS shows a superior response compared to the other techniques reported in literature especially in terms of response time, detection rate and false positive rate. Categroy: Ubiquitous computing
An On-Board Remaining Useful Life Estimation Algorithm for Lithium-Ion Batteries of Electric Vehicles

Battery remaining useful life (RUL) estimation is critical to battery management and performance optimization of electric vehicles (EVs). In this paper, we present an effective way to estimate RUL online by using the support vector machine (SVM) algorithm. By studying the characteristics of the battery degradation process, the rising of the terminal voltage and changing characteristics of the voltage derivative (DV) during the charging process are introduced as the training variables of the SVM algorithm to determine the battery RUL. The SVM is then applied to build the battery degradation model and predict the battery real cycle numbers. Experimental results prove that the built battery degradation model shows higher accuracy and less computation time compared with those of the neural network (NN) method, thereby making it a potential candidate for realizing online RUL estimation in a battery management system (BMS).
Differential regulation of human fibroblast growth factor 1 transcripts provides a distinct mechanism of cell-specific growth factor expression.

Four variants of fibroblast growth factor 1 (FGF-1) mRNA, FGF-1.A, -1.B, -1.C, and -1.D, originate from four discrete promoters of the gene. Each promoter is coupled with its 5'-untranslated exon. These four promoters are separated by as much as 70 kbp in the FGF-1 locus. The present study indicates that expression of these transcripts in different cell types is regulated by distinct mechanisms. FGF-1.C mRNA requires de novo protein synthesis and de novo transcription for expression and processing, and this mRNA increases acutely in response to TGF-beta and serum stimulation. The serum-induced FGF-1.C correlates with a marked increase in protein level. In addition, FGF-1.C mRNA also increases significantly (more than 100-fold) in response to phorbol 12-myristate 13-acetate. FGF-1.D mRNA is uniquely superinduced by serum in the presence of cycloheximide and displays delayed early kinetics, suggesting that this mRNA does not require de novo protein synthesis for expression. In sharp contrast to the FGF-1.C and -1.D mRNAs, FGF-1.B mRNA levels do not increase in response to serum or phorbol 12-myristate 13-acetate and are in fact slightly down-regulated. Furthermore, FGF-1.B mRNA is stable and appears to have a long half-life (> 12 h). Thus, the unique cell-specific regulation of these FGF-1 transcripts and subsequent protein synthesis indicate that each transcript may have a distinct role in development, normal cellular processes, and, upon aberrant regulation, disease. In support of these conclusions, multiple FGF-1 transcripts in normal, fetal, and diseased tissues, containing mixed cell types, were detected. Our results suggest that FGF-1 transcripts FGF-1.C and -1.D arising from promoters 1C and 1D are specific and are potential markers for proliferation of certain cells, whereas transcripts FGF-1.A and -1.B arising from promoters 1A and 1B are specific for maintenance and survival of cells, particularly cardiac and neuronal cells. Together, these data provide evidence for a biological function for multiple promoter usage of a single gene. The discrete mechanisms for expression of the FGF-1 gene further underscore the biological significance of this growth factor.
Transkranielle Magnet- und Gleichstromstimulation bei Kopfschmerzen

Zusammenfassung Seit einigen Jahren erlaubt die repetitive transkranielle Magnetstimulation (rTMS) und die transkranielle Gleichstromstimulation (tDCS) über eine Veränderung der neuronalen Aktivität oder des Ruhemembranpotenzials die Induktion und Modulation von neuroplastischen Veränderungen im Großhirn. tDCS erzielt prolongierte neuronale Erreg-barkeits- und Aktivitätsänderungen im menschlichen Gehirn über Veränderungen des neuronalen Membranpotenzials. rTMS ruft durch repetitiv induzierte elektrische Felder an den Zellmembranen über die Stimulationsdauer hinaus anhaltende Erregbarkeitsveränderungen hervor. Die Mehrzahl der neurophysiologischen Studien zur Pathophysiologie der Migräne stimmen darin überein, dass die Erregbarkeit des Gehirns der Patienten zwischen den Anfällen erhöht ist, besonders ausgeprägt in den visuellen Anteilen der Gehirnrinde. rTMS und tDCS eröffnen damit einen neuen Zugang sowohl zum Studium der pathophysiologischen Grundlagen als auch zu deren möglicher therapeutischer Beeinflussung.
Pricing and Hedging Volatility Derivatives

Volatility is the key variable in option pricing models and for risk management in general. Not surprisingly, this has led to the recognition that volatility uncertainty is an important risk factor. This realization, in turn, has given rise to derivative instruments tied to volatility, such as variance swaps, volatility swaps, and options on both variance and volatility, which are specifically designed to help manage this risk. To price these contracts, a model is needed for the volatility process. This article develops full pricing and risk management models for these instruments in the context of a Heston square root stochastic volatility model, including expressions for all of the standard Greek letters and a couple of new ones for the parameters of the volatility process. In addition, the authors provide a procedure for setting up optimal hedges of variance and volatility contracts using a finite set of options as an operational approximation to the full solution requiring a continuum of options
Physiologic compensation is supranormal in compensated aortic stenosis: does it return to normal after aortic valve replacement or is it blunted by coexistent coronary artery disease? An intramyocardial magnetic resonance imaging study.

BACKGROUND In compensated aortic stenosis (AS), cardiac performance measured at the ventricular chamber is typically supranormal, whereas measurements at the myocardium are often impaired. We investigated intramyocardial mechanics after aortic valve replacement (AVR) and the effects relative to the presence or absence of coronary artery disease (CAD+ or CAD-), respectively. METHODS AND RESULTS Twenty-nine patients (46 to 91 years, 10 female) with late but not decompensated AS underwent cardiovascular MRI before AVR (PRE), with follow-up at 6+/-1 (EARLY) and 13+/-2 months (LATE) to determine radiofrequency tissue-tagged left ventricle (LV) transmural circumferential strain, torsion, structure, and function. At the myocardial level, concentric LV hypertrophy regressed 18% LATE (93+/-22 versus 77+/-17 g/m2; P<0.0001), whereas at the LV chamber level, ejection fraction was supranormal PRE, 67+/-6% (ranging as high as 83%) decreasing to 59+/-6% LATE (P<0.05), representing not dysfunction but a return to more normal LV physiology. Between the CAD+ and CAD- groups, intramyocardial strain was similar PRE (19+/-10 versus 20+/-10) but different LATE, with dichotomization specifically related to the CAD state. In the CAD- patients, strain increased to 23+/-10% (+20%), whereas in CAD+ patients it fell to 16+/-11% (-26%), representing a nearly 50% decline after AVR (P<0.05). This was particularly evident at the apex, where CAD- strain LATE improved 17%, whereas for CAD+ it decreased 2.5-fold. Transmural strain and myocardial torsion followed a similar pattern, critically dependent on CAD. AVR impacted LV geometry and mitral apparatus, resulting in decreased mitral regurgitation, negating the double valve consideration. CONCLUSIONS In AS patients after AVR, reverse remodeling of the supranormal systolic function parallels improvement in cardiovascular MRI-derived regression of LV hypertrophy and LV intramyocardial strain. However, discordant effects are evident after AVR, driven by CAD status, suggesting that the typical AVR benefits are experienced disproportionately by those without CAD and not by those obliged to undergo concomitant coronary artery bypass grafting/AVR.
Genetic Diversity and Temporal Variation in the Cyanophage Community Infecting Marine Synechococcus Species in Rhode Island's Coastal Waters

ABSTRACT The cyanophage community in Rhode Island's coastal waters is genetically diverse and dynamic. Cyanophage abundance ranged from over 104 phage ml−1 in the summer months to less then 102 phage ml−1 during the winter months. Thirty-six distinct cyanomyovirus g20 genotypes were identified over a 3-year sampling period; however, only one to nine g20 genotypes were detected at any one sampling date. Phylogenetic analyses of g20 sequences revealed that the Rhode Island cyanomyoviral isolates fall into three main clades and are closely related to other known viral isolates of Synechococcus spp. Extinction dilution enrichment followed by host range tests and PCR restriction fragment length polymorphism analysis was used to detect changes in the relative abundance of cyanophage types in June, July, and August 2002. Temporal changes in both the overall composition of the cyanophage community and the relative abundance of specific cyanophage g20 genotypes were observed. In some seawater samples, the g20 gene from over 50% of isolated cyanophages could not be amplified by using the PCR primer pairs specific for cyanomyoviruses, which suggested that cyanophages in other viral families (e.g., Podoviridae or Siphoviridae) may be important components of the Rhode Island cyanophage community.
Responsabilidade social interna: entre a diferença e o discurso no cenário organizacional

The aim of this essay is to discuss that the Internal Social Responsibility discourse as a management model intends to homogenize the treatment of the internal actors of the organization, once it is used in an instrumental perspective focused exclusively in legal themes on the work relation, in opposition to a meaningful perspective focused on the humanization of the work environment. Consequently, organizations hide, under this discourse, practices truly dehumanizing in social life, and encourage, even more, intolerance to differences. This discussion takes place in Latin America, where it demands strength from intercultural discourses and the defense of the human rights in political and business agendas, what highlights the contradictions inherent to these discourses. From a bibliographic review oversocial responsibility, discourse, social identity theory and self-concept theory, the individual, social and organizational mechanisms of elaboration and overcome of stereotypes were discussed, as they help the person to establish references for the perceptions and interpretations of reality. It is discussed that the discourse of social internal responsibility could propose a change in the way that the persons are treated in the organization. In this context, difference would not as a way of social exclusion, but it would be a way to promote equity, giving value to characteristics of individual action in the organization and not in the sense of reinforce the difference between “us” and “them”, in function of the role that each one has in the organizational dynamic.
Interaction of Nanomaterials with Plants: What Do We Need for Real Applications in Agriculture?

The number of published researching works related with applications of nanomaterials in agriculture is increasing every year. Most of such works focus on the synthesis of nanodevices, their characteristics as nanocarriers for controlled release of active substances, and their interaction (either positive or negative) with plants or microorganisms under controlled conditions. Important knowledge has been gained about the uptake and distribution of nanomaterials in plants, although there are still gaps regarding internalization inside plant cells. Nanoparticle traits and plant species greatly affect the interaction, and nanodevices can enter and move through different pathways (apoplast vs. symplast), what influences their effectiveness and their final fate. Depending on the effect we are expecting for a nanocarrier, the application method might be critical. However, in order to get that research used in the field, some problems must be addressed. First, the cost for escalating the production of nanodevices must be affordable with the current production cost of agricultural goods. Second, we need to be sure that a technology is safe before spreading it into the environment. Third, consumers will distrust a technology unfamiliar for them in the same way that happened with transgenic crops. We need to broaden our horizons and start looking for real practical approaches, filling the main gaps that hamper our jump from laboratory research into field applications.
Reasoning in description logics with variables: preliminary results regarding the EL logic

This paper studies the extension of description logics with variables ranging over infinite domains of concept names and role names. As a preliminary work, we consider more specifically the extension of the logic EL with variables and we investigate in this context two reasoning mechanisms, namely compliance (a kind of matching) and pattern containment. The main technical results are derived by establishing a correspondance between the EL logic and finite variable automata.
Bringing Theory to Life: Strategies that Make Culturally Responsive Pedagogy a Reality in Diverse Secondary Classrooms

Normal.dotm 0 0 1 111 635 COE-ESL 5 1 779 12.0 0 false 18 pt 18 pt 0 0 false false false /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:. 0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:"Times New Roman"; mso-ascii-font-family:Cambria; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Cambria; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} Preparing U.S. teachers for effectiveness with culturally and linguistically diverse (CLD) secondary students remains a challenge, given the relative homogeneity of educators and their enculturation to an educational system based on European American norms and values. Although culturally responsive pedagogy has emerged as a promising avenue for promoting student achievement, instructional tools are needed to support application of theory in multicultural classrooms. In this paper the authors provide a framework for linguistic and academic development, contextualized within a larger model of biography-driven instruction. Instructional strategies implemented throughout the lesson are described, and their usefulness for improving teacher performance is explored.
Child development in developing countries 1 Developmental potential in the fi rst 5 years for children in developing countries

Centre for International Child Health, Institute of Child Health, University College London, UK (Prof S Grantham-McGregor FRCP), London School of Tropical Medicine and Hygiene, UK (Y B Cheung PhD), Group for the Analyses of Development, Lima, Peru (S Cueto PhD), Department of Applied Economics, University of Minnesota, USA (Prof P Glewwe PhD), Human Sciences Research Council, South Africa (Prof L Richter PhD), and Division of Nutritional Sciences and Department of Psychology, Cornell University, USA (B Strupp PhD)
Episodic and Semantic Memory Contribute to Familiar and Novel Episodic Future Thinking

Increasing evidence indicates that episodic future thinking (EFT) relies on both episodic and semantic memory; however, event familiarity may importantly affect the extent to which episodic and semantic memory contribute to EFT. To test this possibility, two behavioral experiments were conducted. In Experiment 1, we directly compared the proportion of episodic and semantic memory used in an EFT task. The results indicated that more episodic memory was used when imagining familiar future events compared with novel future events. Conversely, significantly more semantic memory was used when imagining novel events compared with familiar events. Experiment 2 aimed to verify the results of Experiment 1. In Experiment 2, we found that familiarity moderated the effect of priming the episodic memory system on EFT; particularly, it increased the time required to construct a standard familiar episodic future event, but did not significantly affect novel episodic event reaction time. Collectively, these findings support the hypothesis that event familiarity importantly moderates episodic and semantic memory's contribution to EFT.