Miracle-dz/UniFAR-FTUs huggingface dataset:
2Planning for Contingencies: A Decision-based Approach

A fundamental assumption made by classical AI planners is that there is no uncertainty in the world: the planner has full knowledge of the conditions under which the plan will be executed and the outcome of every action is fully predictable. These planners cannot therefore construct contingency plans, i.e., plans in which diffierent actions are performed in diffierent circumstances. In this paper we discuss some issues that arise in the representation and construction of contingency plans and describe Cassandra, a partial-order contingency planner. Cassandra uses explicit decision-steps that enable the agent executing the plan to decide which plan branch to follow. The decision-steps in a plan result in subgoals to acquire knowledge, which are planned for in the same way as any other subgoals. Cassandra thus distinguishes the process of gathering information from the process of making decisions. The explicit representation of decisions in Cassandra allows a coherent approach to the problems of contingent planning, and provides a solid base for extensions such as the use of diffierent decision-making procedures.
Representations of National Identity in Fictionalized History: Children’s Picture Books and World War I

ABSTRACT With the centenary of World War I (WWI) commemorative events taking place, Australia’s involvement in this conflict is popularly seen as inextricably linked to a definitive national identity. Numerous children’s books have been published that represent events from WWI. Eight such picture books, aimed at primary school students and published post-2010, are selected for analysis. This analysis comes at a time when there is significant attention being paid by governments, community organisations, media outlets and the general public to the anniversary of WWI. Therefore, it is timely to analyse representations of this conflict, particularly to understand contemporary representations aimed at children.
The 4+1 View Model of Industri–Academia Collaboration

Industry–academia projects exist in complex contexts of various stakeholders, time perspec-tives, and goals. In order to analyze projects and communicate about them, we have deﬁned an “architectural” model for industry– academia collaboration, inspired by Kruchten’s software architecture model. The model has four views of i) time, ii) space, iii) activity and iv) domain, corresponding to the ques-tions: when, where, how and what. The +1 view is the scenario, binding the other four to-gether. We illustrate the model by applying it to the Industrial Excellence Center EASE and the Sigrun Software Innovation and Engineering Institute. The model helps analyzing industry–academia collaboration projects, to ﬁnd gaps and reduce redundant work.
A Formal Model for Channel Allocation in Distributed Mobile Computing Systems

The wireless channels are the most important resources in a mobile comuting system. Each communiction session that involes a mobile host requires a channel to be allocated. The possibility of reuse of wireless channels in different cells subject to satisfying the reuse constraint is the main concern for optimizing the channel usage. The channel allocation problem deals with optimization of the channel usage in the mobile computing system. We present a formal model for channel allocation problem in a distributed mobile computing system using Duration Calculus. We propose a new distributed dynamic channel allocation algorithm based on the formal model. The proposed algorithm attempts to bring in the best features of the permission-based and token-based principles. Siba K. Udgata is a senior lecture in the P.G. Dept. of Computer Science, Berhampur University India. He has been a UNU/IIST fellow from 1 March to 31 August, 2001. His research interests include mobile computing, distributed systems. Dang Van Hung is a Resaerch Fellow at UNU/IIST. His research interests include Formal Techniques of Programming, Concurrent and Distributed Systems, Real-Time Systems. E-mail: dvh@iist.unu. Copyright c © 2003 by UNU/IIST, Siba K. Udgata and Dang Van Hung
Using Existing Data to Address Important Clinical Questions in Critical Care

Objective:With important technological advances in healthcare delivery and the Internet, clinicians and scientists now have access to overwhelming number of available databases capturing patients with critical illness. Yet, investigators seeking to answer important clinical or research questions with existing data have few resources that adequately describe the available sources and the strengths and limitations of each. This article reviews an approach to selecting a database to address health services and outcomes research questions in critical care, examines several databases that are commonly used for this purpose, and briefly describes some strengths and limitations of each. Data Sources:Narrative review of the medical literature. Summary:The available databases that collect information on critically ill patients are numerous and vary in the types of questions they can optimally answer. Selection of a data source must consider not only accessibility but also the quality of the data contained within the database, and the extent to which it captures the necessary variables for the research question. Questions seeking causal associations (e.g., effect of treatment on mortality) usually either require secondary data that contain detailed information about demographics, laboratories, and physiology to best address nonrandom selection or sophisticated study design. Purely descriptive questions (e.g., incidence of respiratory failure) can often be addressed using secondary data with less detail such as administrative claims. Although each database has its own inherent limitations, all secondary analyses will be subject to the same challenges of appropriate study design and good observational research. Conclusion:The literature demonstrates that secondary analyses can have significant impact on critical care practice. While selection of the optimal database for a particular question is a necessary part of high-quality analyses, it is not sufficient to guarantee an unbiased study. Thoughtful and well-constructed study design and analysis approaches remain equally important pillars of robust science. Only through responsible use of existing data will investigators ensure that their study has the greatest impact on critical care practice and outcomes.
Music Retrieval by Rhythmic Similarity Applied on Greek and African Traditional Music

This paper presents a method for retrieving music recordings by means of rhythmic similarity in the context of traditional Greek and African music. To this end, Self Similarity Analysis is applied either on the whole recording or on instances of a music thumbnail that can be extracted from the recording with an optional thumbnailing scheme. This type of analysis permits the extraction of a rhythmic signature per music recording. Similarity between signatures is measured with a standard Dynamic Time Warping technique. The proposed method was evaluated on corpora of Greek and African traditional music where human improvisation plays a key role and music recordings exhibit a variety of music meters, tempi and instrumentation.
Feature co-occurrence representation based on boosting for object detection

This paper proposes a method of feature co-occurrence representation based on boosting for object detection. A previously proposed method that combines multiple binary-classified codes by AdaBoost to represent the co-occurrence of features has been shown to be effective in face detection. However, if an input feature is difficult to be assigned to a correct binary code due to occlusion or other factors, a problem arises here since the process of binary classification and co-occurrence representation may combine features that include an erroneous code. In response to this problem, this paper proposes a Co-occurrence Probability Feature (CPF) that combines multiple weak classifiers by addition and multiplication arithmetic operators using Real AdaBoost in which the outputs of weak classifiers are real values. Since CPF combines classifiers using two types of operators, diverse types of co-occurrence can be represented and improved detection performance can be expected. To represent even more diversified co-occurrence, this paper also proposes co-occurrence representation that applies a subtraction arithmetic operator. Although co-occurrence representation using addition and multiplication operators can represent co-occurrence between features, use of the subtraction operator enables the representation of co-occurrence between local features and features having other properties. This should have the effect of revising the probability of the detection-target class obtained from local features. Evaluation experiments have shown co-occurrence representation by the proposed methods to be effective.
Korean Red Ginseng Improves Blood Pressure Stability in Patients with Intradialytic Hypotension

Introduction. Intradialytic hypotension (IDH) is a common complication during hemodialysis which may increase mortality risks. Low dose of Korean red ginseng (KRG) has been reported to increase blood pressure. Whether KRG can improve hemodynamic stability during hemodialysis has not been examined. Methods. The 8-week study consisted of two phases: observation phase and active treatment phase. According to prehemodialysis blood pressure (BP), 38 patients with IDH were divided into group A (BP ≥ 140/90 mmHg, n = 18) and group B (BP < 140/90 mmHg, n = 20). Patients were instructed to chew 3.5 gm KRG slices at each hemodialysis session during the 4-week treatment phase. Blood pressure changes, number of sessions disturbed by symptomatic IDH, plasma levels of vasoconstrictors, blood biochemistry, and adverse effects were recorded. Results. KRG significantly reduced the degree of blood pressure drop during hemodialysis (P < 0.05) and the frequency of symptomatic IDH (P < 0.05). More activation of vasoconstrictors (endothelin-1 and angiotensin II) during hemodialysis was found. The postdialytic levels of endothelin-1 and angiotensin II increased significantly (P < 0.01). Conclusion. Chewing KRG renders IDH patients better resistance to acute BP reduction during hemodialysis via activation of vasoconstrictors. Our results suggest that KRG could be an adjuvant treatment for IDH.
Identifying computer generated graphics VIA histogram features

Discriminating computer generated graphics from photographic images is a challenging problem of digital forensics. An important approach to this issue is to explore usual image statistics. In this way, when the statistical distributions (i.e., histograms) of some types of residual images are established, previous works usually apply operations on these histograms or compute statistical quantities to extract features. However, as the histograms are fundamental resources and can present most image information, the histograms themselves can be directly used as features and we do not need further manipulations on them. Based on this consideration, we simply take several highest histogram bins of the difference images as features to carry out classification, and these simple histogram features work well in terms of both detection accuracy and computational complexity. Actually, experimental results demonstrate that, with only 112 features, the proposed method outperforms some state-of-the-art works.
Variation-Based Image Segmentation and its Multiscale Realizations

s: A variational approach for image segmentation is discussed in this paper. The approach is based on the interpolation of surface. This interpolation is computed using edge points as interpolating points and minimizing an energy functional which interpolate a smooth threshold surface. An efficient Sequential Relaxation Algorithm (SRA) with the property of global convergence, for solving the optimization problem, is proposed. Moreover, our algorithm is also formulated in a multiscale framework. The performance of our method is demonstrated on a variety of real and synthetic images and compared with traditional techniques. Examples show that our segmentation method gives very promising results.
Chaotic Time Series Prediction Based on Radial Basis Function Network

A prediction method for chaotic time series, based on radial basis function (RBF) network, is proposed. First, two important parameters for reconstructing phase space, the time delay and the embedding dimension, are estimated by correlation integral method, and the embedding dimension is the number of input units. Second, RBF centers are optimized by means of the cross iterative fuzzy clustering algorithm (CIFCA) and the regularized orthogonal least squares algorithm (ROISA), and the selected RBF centers construct hidden units. The proposed method centralizes advantages of CIFCA and ROISA, and it can decrease network scale, improve generalization performance, accelerate network training speed and avoid ill-conditioning of learning problems. A case of known chaotic system, Rollser system, verifies validity of the proposed method.
A SOURCE / FILTER APPROACH TO AUDIO MELODY EXTRACTION

We propose the extension of a previously submitted system to address the Audio Melody Extraction task. The original system is based on the decomposition of the signal into a leading voice and an accompaniment. For this submission, the model for the accompaniment is as in the previous one : it relies on a Non-negative Matrix Factorization (NMF) of the spectrogram. The model for the leading voice is based on the original source/filter model, and includes some refinements such as an explicit smoothing parameterization of the filter parts, in order for the model to be closer to a natural sound production model. Preliminary tests show that our systems obtain results comparable to the systems provided last year. The GSMM extension proposed in this paper may also benefit from some bug removal from last year’s code. Although the proposed models do not lead to great improvements in the results, we believe the underlying semantics of the estimated parameters are easier to interprete and open this model for future indexing applications.
Generation, Characterization and Epitope Mapping of Two Neutralizing and Protective Human Recombinant Antibodies against Influenza A H5N1 Viruses

Background The development of new therapeutic targets and strategies to control highly pathogenic avian influenza (HPAI) H5N1 virus infection in humans is urgently needed. Broadly cross-neutralizing recombinant human antibodies obtained from the survivors of H5N1 avian influenza provide an important role in immunotherapy for human H5N1 virus infection and definition of the critical epitopes for vaccine development. Methodology/Principal Findings We have characterized two recombinant baculovirus-expressed human antibodies (rhAbs), AVFluIgG01 and AVFluIgG03, generated by screening a Fab antibody phage library derived from a patient recovered from infection with a highly pathogenic avian influenza A H5N1 clade 2.3 virus. AVFluIgG01 cross-neutralized the most of clade 0, clade 1, and clade 2 viruses tested, in contrast, AVFluIgG03 only neutralized clade 2 viruses. Passive immunization of mice with either AVFluIgG01 or AVFluIgG03 antibody resulted in protection from a lethal H5N1 clade 2.3 virus infection. Furthermore, through epitope mapping, we identify two distinct epitopes on H5 HA molecule recognized by these rhAbs and demonstrate their potential to protect against a lethal H5N1 virus infection in a mouse model. Conclusions/Significance Importantly, localization of the epitopes recognized by these two neutralizing and protective antibodies has provided, for the first time, insight into the human antibody responses to H5N1 viruses which contribute to the H5 immunity in the recovered patient. These results highlight the potential of a rhAbs treatment strategy for human H5N1 virus infection and provide new insight for the development of effective H5N1 pandemic vaccines.
Neurobiological Mechanisms Linking Stress and Nicotine to Increased Alcohol Consumption

Alcohol use is a leading cause of preventable disease, disability and death worldwide. Among other factors, exposure to stress or nicotine promotes drinking in humans, yet the neurobiological mechanisms mediating these interactions are unknown. Decades of research indicate that alcohol, stress hormones and nicotine act within the mesolimbic dopamine system to promote behavioral reinforcement. Based on this literature, the central hypothesis guiding my dissertation was that exposure to stress or nicotine promoted drinking via adaptations within ventral tegmental area (VTA). The findings presented in the second chapter of my thesis describe a novel adaptation within the mesolimbic dopamine system contributing to increased alcohol self-administration. Exposure to stress blunted subsequent dopamine responses to alcohol and increased alcohol consumption via VTA stress hormone receptors. These adaptations arose from excitatory GABA transmission onto VTA GABA neurons. Further investigation revealed that excitatory shifts in GABA transmission were associated with the downregulation of the chloride transporter KCC2. Pharmacological enhancement of KCC2 function within the VTA prevented stress-induced drinking, identifying a novel mechanism of stress-induced alcohol consumption. The results in the third and fourth chapters reveal that similar adaptations within the VTA may also contribute to the co-use of nicotine and alcohol. As was observed after stress, exposure to acute nicotine blunted dopamine responses to alcohol and increased alcohol self-administration. Blocking glucocorticoid receptors during nicotine normalized the dopamine signaling and drinking to control levels, indicating that nicotine recruits stress hormone receptors to influence subsequent responses to alcohol. The fourth chapter examines the effects of adolescent nicotine exposure on adult responses to alcohol, since early-life tobacco use confers a major risk for subsequent alcohol abuse. Animals treated with nicotine during adolescence show attenuated dopamine signaling and increased self-administration throughout adulthood. Pharmacological enhancement of KCC2 in adulthood prevented the elevated alcohol intake, highlighting a potential therapeutic role of this drug to reduce alcohol consumption long after the initial nicotine exposure. Taken together, this body of work suggests that exposure to stress or nicotine boosts drinking via anionic plasticity mechanisms within the VTA and implicates KCC2 activation as a potential therapeutic target in the treatment of excessive alcohol consumption. Degree Type Dissertation Degree Name Doctor of Philosophy (PhD) Graduate Group Neuroscience This dissertation is available at ScholarlyCommons: https://repository.upenn. edu/edissertations/2606 First Advisor John Dani Second Advisor Christopher Pierce
Novel millimeter-wave slow-wave phase shifter using MEMS technology

A novel mm-wave MEMS phase shifter based on a slow wave structure is introduced. The phase shifter uses co-planer wave guide that has the signal line loaded with inductors through capacitive coupling. The inductor and the capacitive coupling capacitor are designed to work for the mm-wave frequency range. Integrated metal to metal RF MEMS switches are designed such that inductors can be shortened to ground to obtain a normal CPW when the switches are closed. When the switches are open, the signal is traveling in the slow wave structures and a phase shift is obtained. Unlike other phase shifters, the proposed design can handle higher power and does not have neither MEMS capacitive nor metal to metal switches on the signal line. The measured pull-in voltage is 45 volt. The phase shifter is designed, modeled, fabricated and tested. The phase shift per length is 355 °/cm. The phase shifter exhibits high resolution of phase shift while maintaining a return loss of 20 dB and a worst insertion loss of 3.21 dB at 60 GHz.
Problematização da proposta “Escola sem Partido” na perspectiva do letramento ideológico

Analisamos alguns impactos que a Escola sem Partido pode ocasionar ao trabalho pedagogico orientado pelo letramento ideologico. Analisamos documentos escritos publicados, artigos jornalisticos e entrevistas que versam sobre o proposito e atuacao do movimento. A investigacao toma como objeto de analise a proposta impositiva de que o professor deve ser neutro mediante discussoes que envolvem politica, ideologia e agremiacao partidaria, tendo como foco analitico o efeito dessa implicacao ao letramento ideologico. A movimento investigado desautoriza a pratica do letramento ideologico mediada pelo professor na escola.
Systematic Review of Pears and Health

Fruit consumption is universally promoted, yet consumption of fruit remains low in the United States. We conducted a systematic review on pear consumption and health outcomes searching both PubMed and Agricola from 1970 to present. The genus Pyrus L. consists of species of pears cultivated in Europe, parts of Asia, South America, and North America. Like most fruit, pears are concentrated in water and sugar. Pears are high in dietary fiber, containing 6 g per serving. Pears, similar to apples, are concentrated in fructose, and the high fiber and fructose in pears probably explain the laxative properties. Pears contain antioxidants and provide between 27 and 41 mg of phenolics per 100 g. Animal studies with pears suggest that pears may regulate alcohol metabolism, protect against ulcers, and lower plasma lipids. Human feeding studies with pears have not been conducted. In epidemiological studies, pears are combined with all fresh fruits or with apples, because they are most similar in composition. The high content of dietary fiber in pears and their effects on gut health set pears apart from other fruit and deserves study.
Review of teriflunomide and its potential in the treatment of multiple sclerosis

In the light of new cases of progressive multifocal leukoencephalopathy and induced autoimmunity in multiple sclerosis (MS) patients who received treatment with upcoming disease-modifying immunosuppressant drugs with a highly specific mode of action such as natalizumab, rituximab, or alemtuzumab, alternative oral treatment options for a subgroup of less severely affected MS patients are a major focus of drug development. These agents are currently investigated in phase III clinical trials and some of them are characterized by a favorable safety profile. With an emphasis on teriflunomide, the active metabolite of an immunosuppressant approved for the treatment of rheumatoid arthritis since 1998, a number of oral treatment options for patients with MS are discussed.