Miracle-dz/UniFAR-FTUs huggingface dataset:
Design and simulation of an intelligent controller for a missile avoiding airplane

This paper presents the design and simulation of an intelligent fuzzy controller to control the flight movement of an airplane being present in the midst of targeted missiles. The objective is to have the in-flight airplane, when an imminent collision danger occurs, move in a direction so as to avoid being hit by any of the targeted missiles. The airplane senses the environment around it, acquiring the coordinates of the missiles, and determines the nearest missile forward. The airplane, then, alters its movement direction in order to escape that missile within a specified time step. The fuzzy controller is designed off-line and it can then be used on-line. This design is a data-driven one and it is accomplished using a previously developed learning algorithm for the modeling of Mamdani-type fuzzy controllers. This is done, however, after addressing and tackling some challenging issues related to the 3-D to 2-D conversion, data derivation method and time step determination. The obtained FLC is then simulated and tested in a complex scenario and its reliability is emphasized.
A norm- and control-referenced comparative study of the neuropsychological profiles of shift workers and patients with obstructive sleep apnoea (OSA)

Shift work and Obstructive sleep apnoea (OSA) have been associated with excessive daytime sleepiness and increased risk of road traffic accidents. There is evidence that daytime sleepiness does not provide as satisfactory explanation for accidents, and occupational and social failures associated with sleep disorders. The possibility arises that intermittent hypoxemia and sleep deprivation due to sleep fragmentation in OSA and sleep deprivation secondary to sleep cycle disruption in shift work may underlie neuropsychological deficits, which in turn meditate these functional impairments. The current study uses a control-referenced and norm-referenced design to explore in detail the subcomponents of attention/executive functions and motor coordination of patients with OSA and shift workers with an aim to outline and compare the profiles of any cognitive impairment between these groups.
Molecular mechanisms underlying the acquisition, extinction and reinstatement of cocaine-associated memory: Relevance to addiction processes

of a dissertation at the University of Miami. An important target for combating drug addiction is to understand the neurobiological mechanisms that sub-serve relapse to drug use. Drug addiction is thought to usurp the neural mechanisms of learning and memory. The conditioned place preference (CPP) paradigm which employs the principles of Pavlovian learning is often used to investigate the incentive value of drugs of abuse and the formation of drug-associated memory. One caveat to conditioned reward studies is the use of a fixed daily dose of the addictive drug during training. However, the transition from drug use to addiction in human addicts involves an escalation in drug intake. I posit that a paradigm that can effectively simulate increases in drug intake will better model the human drug use pattern. Evidence suggests that conditioning by escalating doses of cocaine (Esc-C) confers higher magnitude and more persistent cocaine-memory than conditioning by a fixed daily dose of cocaine (Fix-C). Thus, my research objective was to investigate the contribution of different signaling molecules to the acquisition, reconsolidation, extinction and reinstatement of cocaine associated memory developed by Esc-C versus Fix-C. At the cellular level, I found that the formation of Esc-C memory was associated with markedly increased hippocampal expression of the mRNA and protein that codes for the NR2B subunit of the N-methyl-D-aspartate receptor (NMDAR) compared to formation of Fix-C memory, suggesting a positive correlation between the strength of cocaine associated memory and levels of NR2B subunit expression. Pharmacologically, the development (acquisition) of Fix-C and Esc-C memory was attenuated by antagonism of NR2B-containing NMDARs. However, inhibition of the neuronal nitric oxide synthase (nNOS) which is downstream of the NMDAR attenuated the acquisition of Fix-C but not Esc-C memory. This suggests that the acquisition of Fix-C memory is NO-dependent while Esc-C memory is NO-independent. Regarding memory reconsolidation, NR2B antagonism disrupted reconsolidation of both Fix-C and Esc-C memory. However, while reconsolidation of Fix-C memory was NO-dependent similar to acquisition, reconsolidation of Esc-C memory was NO-insensitive. Conversely, inhibition of the extracellular signal-related kinase (ERK) signaling pathway disrupted reconsolidation of Esc-C but not Fix-C memory. With respect to extinction learning, I investigated the use of phosphodiesterase (PDE) inhibitors as cognitive enhancer to facilitate elimination of extinction-resistant Esc-C CPP. I found that specific inhibition of PDE9, which increases levels of cGMP in the hippocampus and amygdala, induced extinction learning and prevented cocaine-primed reinstatement in mice conditioned by Esc-C. This suggests …
Computer simulation of furniture layout when moving from one house to another

We present a system that automatically suggests the furniture layout when one moves into a new house, taking into account the furniture layout in the previous house. In our method, the input to our system comprises the floor plans of the previous and new houses, and the furniture layout in the previous house. The furniture layout for the whole house is suggested. This method builds on a previous furniture layout method with which the furniture layout for a single room only is computed. In this paper, we propose a new method that can suggest the furniture layout for multiple rooms in the new house. To deal with this problem, we took a heuristic approach in developing a cost function by adding some new cost functions to the previous method. We show various layouts computed using our method, which demonstrates the effectiveness of it.
Entropy Production and the Pressure–Volume Curve of the Lung

We investigate analytically the production of entropy during a breathing cycle in healthy and diseased lungs. First, we calculate entropy production in healthy lungs by applying the laws of thermodynamics to the well-known transpulmonary pressure–volume (P–V) curves of the lung under the assumption that lung tissue behaves as an entropic spring similar to rubber. The bulk modulus, B, of the lung is also derived from these calculations. Second, we extend this approach to elastic recoil disorders of the lung such as occur in pulmonary fibrosis and emphysema. These diseases are characterized by particular alterations in the P–V relationship. For example, in fibrotic lungs B increases monotonically with disease progression, while in emphysema the opposite occurs. These diseases can thus be mimicked simply by making appropriate adjustments to the parameters of the P–V curve. Using Clausius's formalism, we show that entropy production, ΔS, is related to the hysteresis area, ΔA, enclosed by the P–V curve during a breathing cycle, namely, ΔS=ΔA∕T, where T is the body temperature. Although ΔA is highly dependent on the disease, such formula applies to healthy as well as diseased lungs, regardless of the disease stage. Finally, we use an ansatz to predict analytically the entropy produced by the fibrotic and emphysematous lungs.
A Multi-phase Approach for Improving Information Diffusion in Social Networks

For maximizing influence spread in a social network, given a certain budget on the number of seed nodes, we investigate the effects of selecting and activating the seed nodes in multiple phases. In particular, we formulate an appropriate objective function for two-phase influence maximization under the independent cascade model, investigate its properties, and propose algorithms for determining the seed nodes in the two phases. We also study the problem of determining an optimal budget-split and delay between the two phases.
Expanding the window for thrombolytic therapy in acute stroke. The potential role of acute MRI for patient selection.

BACKGROUND Effective therapy was not available for treatment of acute stroke until 1995, when tissue plasminogen activator (tPA) was shown to improve neurological and functional outcome in stroke patients who were treated within 3 hours of symptom onset. SUMMARY OF REVIEW Currently, many patients do not qualify for tPA therapy because they present for evaluation beyond 3 hours after stroke onset. Attempts to expand the treatment window to 6 hours, using CT to select patients, have failed. Use of early MR imaging may provide significant advantages over CT for identification of patients who are likely to benefit from thrombolytic therapy because (1) the early perfusion-weighted imaging (PWI) lesion estimates the region of acute dysfunctional brain tissue, whereas the acute diffusion-weighted imaging (DWI) lesion appears to correspond to the core of the early infarction; (2) the mismatch between the acute PWI lesion and the smaller DWI lesion represents potentially salvageable brain tissue (an estimate of the ischemic penumbra); and (3) in patients with a PWI/DWI mismatch, early reperfusion is often associated with substantial clinical improvement and reversal or reduction of DWI lesion growth. CONCLUSIONS Clinical trials that use new MRI techniques to screen patients may be able to identify a subset of acute stroke patients who are ideal candidates for thrombolytic therapy even beyond 3 hours after stroke onset.
Questionnaire design guidelines for establishment surveys

Previous literature has shown the effects of question wording or visual design on the data provided by respondents. However, few articles have been published that link the effects of question wording and visual design to the development of questionnaire design guidelines. This article proposes specific guidelines for the design of establishment surveys within statistical agencies based on theories regarding communication and visual perception, experimental research on question wording and visual design, and findings from cognitive interviews with establishment survey respondents. The guidelines are applicable to both paper and electronic instruments, and cover such topics as the phrasing of questions, the use of space, the placement and wording of instructions, the design of answer spaces, and matrices.
Energy-Economy Nexus in Indonesia: A Bivariate Cointegration Analysis

Inefficient pricing of energy products has become common feature of governments in many oil exporting developing countries. As developing countries, this can be justified only when the increased growth results from such higher energy consumption. To this end, the study examined the direction of causality between energy consumption and economic growth, and the possibility of a long run relationship between the two variables using Indonesia’s time series for the period of 1971-2010. The Granger causality test revealed a unidirectional causation running from economic growth to energy consumption, and the existence of a long run relationship. The study therefore suggests the pursuance of major reforms to ensure appropriate pricing of energy products. This can help checkmate excessive consumption with no devastating harm to economic growth
Abstract 526: Cancer immunoediting by the innate immune system in the absence of adaptive immunity

Cancer immunoediting is the process whereby the immune system protects against cancer formation and sculpts the immunogenicity of developing tumors cells. Although the full process is known to depend on innate and adaptive immunity, it remains unclear whether innate immunity alone is capable of immunoediting. By comparing the incidence and immunogenicity of 3′methylcholanthrene (MCA)-induced sarcomas in syngeneic wild-type, RAG2-/-, and RAG2-/- x γc-/- mice, we show that the innate immune system can edit the immunogenicity of primary tumors. Specifically, RAG2-/-x γc-/- mice displayed the highest incidence of MCA sarcomas, followed by RAG2-/- mice, and WT mice have the lowest incidence at four separate doses of MCA. Moreover, when cell lines were generated from MCA sarcomas, the cell lines derived from MCA sarcomas growing in RAG2-/-x γc-/- mice had the highest immunogenicity, followed by cell lines from RAG2-/- mice, and cell lines from WT mice had the lowest immunogenicity. These results show that the innate immune system can edit tumors in the absence of adaptive immunity. To examine the cellular basis of editing by the innate immune system, we analyzed the innate cells that infiltrate tumors formed from transplanting highly immunogenic MCA sarcoma cell lines into RAG2-/- or RAG2-/-x γc-/- mice. We found that M1 macrophages were detected at high levels in immunogenic tumors in RAG2-/- but not RAG2-/- x γc-/- mice. The accumulation of M1 macrophages required IFNγ and was associated with effective tumor editing. In the absence of γc and IFNγ, M2 macrophages were abundant, and editing was impaired. Notably, M1 macrophages can be elicited by administration of CD40 agonistic antibodies, thereby restoring cancer editing activity in RAG2-/-x γc-/- mice. Our results suggest that crosstalk between natural killer cells and M1 macrophages, through IFNγ, can be elicited in highly immunogenic tumors, leading to cancer immunoediting. Our highly immunogenic cell lines will provide a system to dissect the cellular and molecular basis of cancer immunoediting by the innate immune system. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 526. doi:1538-7445.AM2012-526
Fusarium Toxins in Cereals: Occurrence, Legislation, Factors Promoting the Appearance and Their Management

Fusarium diseases of small grain cereals and maize cause significant yield losses worldwide. Fusarium infections result in reduced grain yield and contamination with mycotoxins, some of which have a notable impact on human and animal health. Regulations on maximum limits have been established in various countries to protect consumers from the harmful effects of these mycotoxins. Several factors are involved in Fusarium disease and mycotoxin occurrence and among them environmental factors and the agronomic practices have been shown to deeply affect mycotoxin contamination in the field. In the present review particular emphasis will be placed on how environmental conditions and stress factors for the crops can affect Fusarium infection and mycotoxin production, with the aim to provide useful knowledge to develop strategies to prevent mycotoxin accumulation in cereals.
IFFERENT T-NORM O PERATORS IN C LASSIFICATION P ROBLEMS

Fuzzy rule based classification systems are one of the most popular fuzzy modeling systems used in pattern classification problems. This paper investigates the effect of applying nine different T-norms in fuzzy rule based classification systems. In the recent researches, fuzzy versions of confidence and support merits from the field of data mining have been widely used for both rules selecting and weighting in the construction of fuzzy rule based classification systems. For calculating these merits the product has been usually used as a T-norm. In this paper different T-norms have been used for calculating the confidence and support measures. Therefore, the calculations in rule selection and rule weighting steps (in the process of constructing the fuzzy rule based classification systems) are modified by employing these T-norms. Consequently, these changes in calculation results in altering the overall accuracy of rule based classification systems. Experimental results obtained on some well-known data sets show that the best performance is produced by employing the Aczel-Alsina operator in terms of the classification accuracy, the second best operator is Dubois-Prade and the third best operator is Dombi. In experiments, we have used 12 data sets with numerical attributes from the University of California, Irvine machine learning repository (UCI).
Measurement of Progress in Machine Translation

Machine translation (MT) systems can only be improved if their performance can be reliably measured and compared. However, measurement of the quality of MT output is not straightforward, and, as we discuss in this paper, relies on correlation with inconsistent human judgments. Even when the question is captured via “is translation A better than translation B” pairwise comparisons, empirical evidence shows that inter-annotator consistency in such experiments is not particularly high; for intra-judge consistency – computed by showing the same judge the same pair of candidate translations twice – only low levels of agreement are achieved. In this paper we review current and past methodologies for human evaluation of translation quality, and explore the ramifications of current practices for automatic MT evaluation. Our goal is to document how the methodologies used for collecting human judgments of machine translation quality have evolved; as a result, we raise key questions in connection with the low levels of judgment agreement and the lack of mechanisms for longitudinal evaluation.
Plant-Derived Flavanol (−)Epicatechin Enhances Angiogenesis and Retention of Spatial Memory in Mice

Diet and exercise have a profound impact on brain function. In particular, natural nutrients found in plants may influence neuronal survival and plasticity. Here, we tested whether consumption of a plant-derived flavanol, (−)epicatechin, enhances cognition in sedentary or wheel-running female C57BL/6 mice. Retention of spatial memory in the water maze was enhanced by ingestion of (−)epicatechin, especially in combination with exercise. Improved spatial memory was associated with increased angiogenesis and neuronal spine density, but not newborn cell survival, in the dentate gyrus of the hippocampus. Moreover, microarray analysis showed upregulation of genes associated with learning and downregulation of markers of neurodegeneration in the hippocampus. Together, our data show that ingestion of a single flavanol improves spatial memory retention in adult mammals.
Determination of Methylated CpG Sites in the Promoter Region of Catechol-O-Methyltransferase (COMT) and their Involvement in the Etiology of Tobacco Smoking

We previously reported that catechol-O-methyltransferase (COMT) is significantly associated with nicotine dependence (ND) in humans. In this study, we examined whether there exists any difference in the extent of methylation of CpG dinucleotides in the promoter region of COMT in smokers and non-smokers by analyzing the methylation status of cytosines at 33 CpG sites through direct sequencing of bisulfite-treated DNA (N = 50 per group). The cytosine was methylated at 13 of 33 CpG sites, and two of these sites showed significant differences between smokers and matched non-smoker controls. Specifically, in the −193 CpG site, the degree of methylation was 19.1% in smokers and 13.2% in non-smokers (P < 0.01). This finding was confirmed by methylation-specific PCR using an additional 100 smoker and 100 non-smoker control samples, which showed the degree of methylation to be 22.2% in smokers and 18.3% in non-smokers (P < 0.01). For the −39 CpG site, the degree of methylation was 9.2% in smokers, whereas no methylation was found in non-smoker controls. Together, our findings provide the first molecular explanation at the epigenetic level for the association of ND with methylation of the COMT promoter, implying that methylation plays a role in smoking dependence.
A hybrid approach for simulating human motion in constrained environments

We present a new algorithm to generate plausible motions for high‐DOF human‐like articulated figures in constrained environments with multiple obstacles. Our approach is general and makes no assumptions about the articulated model or the environment. The algorithm combines hierarchical model decomposition with sample‐based planning to efficiently compute a collision‐free path in tight spaces. Furthermore, we use path perturbation and replanning techniques to satisfy the kinematic and dynamic constraints on the motion. In order to generate realistic human‐like motion, we present a new motion blending algorithm that refines the path computed by the planner with motion capture data to compute a smooth and plausible trajectory. We demonstrate the results of generating motion corresponding to placing or lifting object, walking, and bending for a 38‐DOF articulated model. Copyright © 2010 John Wiley & Sons, Ltd.
Moment-sequence transforms

We classify all functions which, when applied term by term, leave invariant the sequences of moments of positive measures on the real line. Rather unexpectedly, these functions are built of absolutely monotonic components, or reflections of them, with possible discontinuities at the endpoints. Even more surprising is the fact that functions preserving moments of three point masses must preserve moments of all measures. Our proofs exploit the semidefiniteness of the associated Hankel matrices and the complete monotonicity of the Laplace transforms of the underlying measures. We also examine transformers in the multivariable setting, which reveals a new class of piecewise absolutely monotonic functions.
Optimal Multitenant Designs for Cloud Apps

Often overlooked by application architects, multitenancy is the core technology of a cloud that controls how it shares computing resources among applications. In this paper, you will first learn about two basic approaches for multitenancy, virtual and organic multitenancy, along with the benefits and disadvantages of each approach. Then you will discover why the database that supports a cloud app is a critical consideration, and learn about emerging cloud database options that promise to simplify the development and management of apps executing in the cloud. Throughout, we'll draw conclusions about which types of solutions best fit particular application scenarios.
Accelerometer-Based Gait Recognition by Sparse Representation of Signature Points With Clusters

Gait, as a promising biometric for recognizing human identities, can be nonintrusively captured as a series of acceleration signals using wearable or portable smart devices. It can be used for access control. Most existing methods on accelerometer-based gait recognition require explicit step-cycle detection, suffering from cycle detection failures and intercycle phase misalignment. We propose a novel algorithm that avoids both the above two problems. It makes use of a type of salient points termed signature points (SPs), and has three components: 1) a multiscale SP extraction method, including the localization and SP descriptors; 2) a sparse representation scheme for encoding newly emerged SPs with known ones in terms of their descriptors, where the phase propinquity of the SPs in a cluster is leveraged to ensure the physical meaningfulness of the codes; and 3) a classifier for the sparse-code collections associated with the SPs of a series. Experimental results on our publicly available dataset of 175 subjects showed that our algorithm outperformed existing methods, even if the step cycles were perfectly detected for them. When the accelerometers at five different body locations were used together, it achieved the rank-1 accuracy of 95.8% for identification, and the equal error rate of 2.2% for verification.