Miracle-dz/UniFAR-FTUs huggingface dataset:
Bactericidal Activity of Curcumin I Is Associated with Damaging of Bacterial Membrane

Curcumin, an important constituent of turmeric, is known for various biological activities, primarily due to its antioxidant mechanism. The present study focused on the antibacterial activity of curcumin I, a significant component of commercial curcumin, against four genera of bacteria, including those that are Gram-positive (Staphylococcus aureus and Enterococcus faecalis) and Gram-negative (Escherichia coli and Pseudomonas aeruginosa). These represent prominent human pathogens, particularly in hospital settings. Our study shows the strong antibacterial potential of curcumin I against all the tested bacteria from Gram-positive as well as Gram-negative groups. The integrity of the bacterial membrane was checked using two differential permeabilization indicating fluorescent probes, namely, propidium iodide and calcein. Both the membrane permeabilization assays confirmed membrane leakage in Gram-negative and Gram-positive bacteria on exposure to curcumin I. In addition, scanning electron microscopy and fluorescence microscopy were employed to confirm the membrane damages in bacterial cells on exposure to curcumin I. The present study confirms the broad-spectrum antibacterial nature of curcumin I, and its membrane damaging property. Findings from this study could provide impetus for further research on curcumin I regarding its antibiotic potential against rapidly emerging bacterial pathogens.
Cyclic AMP-dependent plasticity underlies rapid changes in odor coding associated with reward learning

Significance Cyclic AMP signaling is involved in learning across taxa, but how cAMP modulation drives coherent plasticity across circuits is unclear. Results of this study demonstrate that cAMP-dependent plasticity in the Drosophila brain drives olfactory learning-induced plasticity, which is biased toward appetitive conditioning and modulates motivated behavior. Learning and memory rely on dopamine and downstream cAMP-dependent plasticity across diverse organisms. Despite the central role of cAMP signaling, it is not known how cAMP-dependent plasticity drives coherent changes in neuronal physiology that encode the memory trace, or engram. In Drosophila, the mushroom body (MB) is critically involved in olfactory classical conditioning, and cAMP signaling molecules are necessary and sufficient for normal memory in intrinsic MB neurons. To evaluate the role of cAMP-dependent plasticity in learning, we examined how cAMP manipulations and olfactory classical conditioning modulate olfactory responses in the MB with in vivo imaging. Elevating cAMP pharmacologically or optogenetically produced plasticity in MB neurons, altering their responses to odorants. Odor-evoked Ca2+ responses showed net facilitation across anatomical regions. At the single-cell level, neurons exhibited heterogeneous responses to cAMP elevation, suggesting that cAMP drives plasticity to discrete subsets of MB neurons. Olfactory appetitive conditioning enhanced MB odor responses, mimicking the cAMP-dependent plasticity in directionality and magnitude. Elevating cAMP to equivalent levels as appetitive conditioning also produced plasticity, suggesting that the cAMP generated during conditioning affects odor-evoked responses in the MB. Finally, we found that this plasticity was dependent on the Rutabaga type I adenylyl cyclase, linking cAMP-dependent plasticity to behavioral modification. Overall, these data demonstrate that learning produces robust cAMP-dependent plasticity in intrinsic MB neurons, which is biased toward naturalistic reward learning. This suggests that cAMP signaling may serve to modulate intrinsic MB responses toward salient stimuli.
Anxiety, Depression, and Emotion

Preface 1. Depression seen through an animal model: an expanded hypothesis of pathophysiology and improved models 2. Depression in rodents and humans: Commentary on Jay Weiss 3. The regulation of defensive behaviors in rhesus monkeys: Implications for understanding anxiety disorders 4. Adaptive and maladaptive fear-related behaviors: Implications for psychopathology from Kalin's promate model 5. Affective style, mood, and anxiety disorders: An affective neuroscience approach 6. Anterior cerebral symmetry, affect, and psychopathology: COmmentary on the withdrawal-approach model 7. Cognitive functioning in depression: Nature and origins 8. Cognitive functioning in anxiety and depression 9. Mood, personality, and personality disorder 10. Mood, personality, and personality disorders: Commentary 11. The early develoment of empathy, guilt, and internalization of responsibility: Implications for gender differences in internalizing and externalizing problems 12. The role of emotion in the development of child psychopathology: A commentary on Zahn-Waxler
Hybridisation of evolutionary programming and machine learning with k-nearest neighbor estimation

Evolutionary programming (EP) focus on the search step size which decides the ability of escaping local minima, however does not touch the issue of search in promising region. Estimation of distribution algorithms (EDAs) focus on where the promising region is, however have less consideration about behavior of each individual in solution search algorithms. Since the basic ideas of EP and EDAs are quite different, it is possible to make them reinforce each other. In this paper, we present a hybrid evolutionary framework to make use of both the ideas of EP and EDAs through introducing a mini estimation operator into EP's search cycle. Unlike previous EDAs that use probability density function (PDF), the estimation mechanism used in the proposed framework is the k-nearest neighbor estimation which can perform better with relative small amount of training samples. Our experimental results have shown that the incorporation of machine learning techniques, such as k-nearest neighbor estimation, can improve the performance of evolutionary optimisation algorithms for a large number of benchmark functions.
Challenges to Our Understanding of the General Circulation:

About 14,700 years ago (14.7 kyr BP), towards the end of the last ice age, the climate warmed dramatically and abruptly around the North Atlantic—by as much as the difference between full glacial and interglacial conditions—in no more than a decade or two. This is all the more remarkable because it occurred in the presence of massive ice sheets and continuation of the albedo forcing that presumably had been helping maintain glacial conditions up to that point. But it was not to last. Sometime just after 13 kyr BP this Bølling-Allerød warm period ended as climate first cooled, and then abruptly cooled, into the so-called Younger Dryas. As near-glacial conditions returned, glaciers advanced in Europe, and the forests that had established themselves in the preceding warm epoch died. The Younger Dryas ended with a second abrupt warming that occurred over only a decade or so and that shifted temperatures back to those of the Holocene and of today. The idea that the climate system goes through such abrupt shifts did not take the climate research community by storm but dribbled into acceptance in the 1980s and the early 1990s. Only when duplicate ice cores said the same thing and the evidence was found in multiple indicators within the ice—oxygen isotopes, dust concentrations, snow accumulation, and so on—and could be correlated with terrestrial and marine records did acceptance that abrupt climate change was a reality sink in. This gradual acceptance is telling. When Hays et al. (1976) showed just how well climate records from deep-sea cores could be matched to orbital cycles, it was deeply satisfying: the gradual waxing and waning of the great ice sheets could be explained by equally gradual changes in the distribution of delivery of solar radiation to the Earth's surface. Insolation over high northern latitudes was deemed to be particularly important, with reduction in summer leading to retention of winter snow and ice sheet growth. All that remained was to show exactly how the climate system accomplished the necessary links.
Formation of Isobutene from 3-Hydroxy-3-Methylbutyrate by Diphosphomevalonate Decarboxylase

ABSTRACT Isobutene is an important commercial chemical used for the synthesis of butyl rubber, terephthalic acid, specialty chemicals, and a gasoline performance additive known as alkylate. Currently, isobutene is produced from petroleum and hence is nonrenewable. Here, we report that the Saccharomyces cerevisiae mevalonate diphosphate decarboxylase (ScMDD) can convert 3-hydroxy-3-methylbutyrate (3-HMB) to isobutene. Whole cells of Escherichia coli producing ScMDD with an N-terminal 6×His tag (His6-ScMDD) formed isobutene from 3-HMB at a rate of 154 pmol h−1 g cells−1. In contrast, no isobutene was detected from control cells lacking ScMDD. His6-ScMDD was purified by nickel affinity chromatography and shown to produce isobutene from 3-HMB at a rate of 1.33 pmol min−1 mg−1 protein. Controls showed that both His6-ScMDD and 3-HMB were required for detectable isobutene formation. Isobutene was identified by gas chromatography (GC) with flame ionization detection as well as by GC-mass spectrometry (MS). ScMDD was subjected to error-prone PCR, and two improved variants were characterized, ScMDD1 (I145F) and ScMDD2 (R74H). Whole cells of E. coli producing ScMDD1 and ScMDD2 produced isobutene from 3-HMB at rates of 3,000 and 5,888 pmol h−1 g cells−1, which are 19- and 38-fold increases compared to rates for cells producing His6-ScMDD. This showed that genetic modifications can be used to increase the rate at which ScMDD converts 3-HMB to isobutene. Because 3-HMB can be produced from l-leucine, ScMDD has a potential application for the production of renewable isobutene. Moreover, isobutene is a gas, which might simplify its purification from a fermentation medium, substantially reducing production costs.
Soundscapes and the rural: a conceptual review from a British perspective

This paper explores how British rural space is variously constructed through the sonic-aural realm. Through a review of literature from the social scientific and artistic domains, the article proposes a typology of approaches and conceptual frameworks to illustrate the processes and actors involved in a sonic geography / rural aurality. Tranquillity / pastoralism, acoustic ecology, quotidian lives / local speech, artist creativity and consumer technology, in their different ways, drive or are driven by discourses and aesthetics within society. The article is offered as a foundation stone on which an integrative analytical framework might be built.
Achieving network optima using Stackelberg routing strategies

In noncooperative networks users make control decisions that optimize their individual performance objectives. Nash equilibria characterize the operating points of such networks. Nash equilibria are generically inefficient and exhibit suboptimal network performance. Focusing on routing, a methodology is devised for overcoming this deficiency, through the intervention of the network manager. The manager controls part of the network flow, is aware of the noncooperative behavior of the users and performs its routing aiming at improving the overall system performance. The existence of maximally efficient strategies for the manager, i.e., strategies that drive the system into the global network optimum, is investigated. A maximally efficient strategy of the manager not only optimizes the overall performance of the network, but also induces an operating point that is efficient with respect to the performance of the individual users (Pareto efficiency). Necessary and sufficient conditions for the existence of a maximally efficient strategy are derived, and it is shown that they are met in many cases of practical interest. The maximally efficient strategy is shown to be unique and it is specified explicitly.
Learning and recognizing complex multi-agent activities with applications to american football plays

We are interested in modeling and recognizing complex behaviors in video, where multiple agents are interacting in a time-varying manner and in a spatially-localized domain such as American football. Our approach pushes the model complexity onto the observations by using a multi-variate kernel density while maintaining a simple HMM model. The temporal interactions of objects are captured by coupling the kernel observation distributions with a time-varying state-transition matrix, producing a Non-Stationary Kernel HMM (NSK-HMM). This modeling philosophy specifically addresses several issues that plague the more complex stationary models with simple observations, i.e. Dynamic Multi-Linked HMM (DML-HMM) and the Time-Delayed Probabilistic Graphical Model (TDPGM). These include: smaller training datasets, sensitivity to intra class variability and/or dense uninformative clutter tracks. Experiments are performed in the American football video domain, where the offensive plays are the activities. Comparisons are made to the DML-HMM and an extension of the TDPGM to DBNs (TDDBN). The NSK-HMM achieves a 57.7% classification accuracy across seven activities, while the DML-HMM is 26.7% and the TDDBN is 21.3%. When tested on four activities the NSK-HMM achieves a 76.0% accuracy.
Survival in Patients with Primary Pulmonary Hypertension: Results from a National Prospective Registry

OBJECTIVE To characterize mortality in persons diagnosed with primary pulmonary hypertension and to investigate factors associated with survival. DESIGN Registry with prospective follow-up. SETTING Thirty-two clinical centers in the United States participating in the Patient Registry for the Characterization of Primary Pulmonary Hypertension supported by the National Heart, Lung, and Blood Institute. PATIENTS Patients (194) diagnosed at clinical centers between 1 July 1981 and 31 December 1985 and followed through 8 August 1988. MEASUREMENTS At diagnosis, measurements of hemodynamic variables, pulmonary function, and gas exchange variables were taken in addition to information on demographic variables, medical history, and life-style. Patients were followed for survival at 6-month intervals. MAIN RESULTS The estimated median survival of these patients was 2.8 years (95% Cl, 1.9 to 3.7 years). Estimated single-year survival rates were as follows: at 1 year, 68% (Cl, 61% to 75%); at 3 years, 48% (Cl, 41% to 55%); and at 5 years, 34% (Cl, 24% to 44%). Variables associated with poor survival included a New York Heart Association (NYHA) functional class of III or IV, presence of Raynaud phenomenon, elevated mean right atrial pressure, elevated mean pulmonary artery pressure, decreased cardiac index, and decreased diffusing capacity for carbon monoxide (DLCO). Drug therapy at entry or discharge was not associated with survival duration. CONCLUSIONS Mortality was most closely associated with right ventricular hemodynamic function and can be characterized by means of an equation using three variables: mean pulmonary artery pressure, mean right atrial pressure, and cardiac index. Such an equation, once validated prospectively, could be used as an adjunct in planning treatment strategies and allocating medical resources.
Monte Carlo simulation studies of EEG and MEG localization accuracy

Both electroencephalography (EEG) and magnetoencephalography (MEG) are currently used to localize brain activity. The accuracy of source localization depends on numerous factors, including the specific inverse approach and source model, fundamental differences in EEG and MEG data, and the accuracy of the volume conductor model of the head (i.e., the forward model). Using Monte Carlo simulations, this study removes the effect of forward model errors and theoretically compares the use of EEG alone, MEG alone, and combined EEG/MEG data sets for source localization. Here, we use a linear estimation inverse approach with a distributed source model and a realistic forward head model. We evaluated its accuracy using the crosstalk and point spread metrics. The crosstalk metric for a specified location on the cortex describes the amount of activity incorrectly localized onto that location from other locations. The point spread metric provides the complementary measure: for that same location, the point spread describes the mis‐localization of activity from that specified location to other locations in the brain. We also propose and examine the utility of a “noise sensitivity normalized” inverse operator. Given our particular forward and inverse models, our results show that 1) surprisingly, EEG localization is more accurate than MEG localization for the same number of sensors averaged over many source locations and orientations; 2) as expected, combining EEG with MEG produces the best accuracy for the same total number of sensors; 3) the noise sensitivity normalized inverse operator improves the spatial resolution relative to the standard linear estimation operator; and 4) use of an a priori fMRI constraint universally reduces both crosstalk and point spread. Hum. Brain Mapping 16:47–62, 2002. © 2002 Wiley‐Liss, Inc.
The Structure of Spot Rates and Immunization

Empirical studies of the modern theories of bond pricing typically choose proxies for the state variables in a rather arbitrary fashion. This paper empirically analyzes the question of the optimal spot rates to use as state variables. The authors' findings indicate that the four-year spot rate serves as the best proxy in the one-state-variable model. In the case of the two-state-variables model, the six-year rate and eight-month rate are identified as best. Tests of the out-of-sample prediction ability indicate that their model is superior to F. R. Macaulay's duration model and alternative proxies for state variables. Copyright 1990 by American Finance Association.
Reflexes from the Lungs and Airways CO 2 relaxes parenchyma in the liquid-filled rat lung

Emery MJ, Eveland RL, Kim SS, Hildebrandt J, Swenson ER. CO2 relaxes parenchyma in the liquid-filled rat lung. J Appl Physiol 103: 710–716, 2007. First published May 10, 2007; doi:10.1152/japplphysiol.00128. 2006. —CO2 regulation of lung compliance is currently explained by pHand CO2-dependent changes in alveolar surface forces and bronchomotor tone. We hypothesized that in addition to, but independently of, those mechanisms, the parenchyma tissue responds to hypercapnia and hypocapnia by relaxing and contracting, respectively, thereby improving local matching of ventilation (V̇A) to perfusion (Q̇). Twenty adult rats were slowly ventilated with modified Krebs solution (rate 3 min , 37°C, open chest) to produce unperfused living lung preparations free of intra-airway surface forces. The solution was gassed with 21% O2, balance N2, and CO2 varied to produce alveolar hypocapnia (PCO2 26.1 2.4 mmHg, pH 7.56 0.04) or hypercapnia (PCO2 55.0 2.3 mmHg, pH 7.23 0.02). The results show that lung recoil, as indicated from airway pressure measured during a breathhold following a large volume inspiration, is reduced 30% when exposed to hypercapnia vs. hypocapnia (P 0.0001, paired t-test), but stress relaxation and flow-dependent airway resistance were unaltered. Increasing CO2 from hypoto hypercapnic levels caused a substantial, significant decrease in the quasi-static pressure-volume relationship, as measured after inspiration and expiration of several tidal volumes, but hysteresis was unaltered. Furthermore, addition of the glycolytic inhibitor NaF abolished CO2 effects on lung recoil. The results suggest that lung parenchyma tissue relaxation, arising from active elements in response to increasing alveolar CO2, is independent of (and apparently in parallel with) passive tissue elements and may actively contribute to V̇A/Q̇ matching.
The VITA Financial Services Sales Support Environment

Knowledge-based recommender technologies support customers and sales representatives in the identification of appropriate products and services. These technologies are especially useful for complex and high involvement products such as cars, computers, or financial services. In this paper we present the VITA (Virtualis Tanacsado) financial services recommendation environment which has been deployed for the Fundamenta building and loan association in Hungary. On the basis of knowledge-based recommender technologies, VITA supports sales dialogs between Fundamenta sales representatives and customers interested in financial services (e.g., loans). VITA has been developed and is maintained on the basis of an environment which supports automated testing and debugging of knowledge bases and recommender process definitions. Besides presenting the VITA environment we focus on reporting empirical results which clearly show the payoffs of the deployed application in terms of time savings in the conduction of sales dialogs.
Saliency Based on Multi-scale Ratio of Dissimilarity

Recently, many vision applications tend to utilize saliency maps derived from input images to guide them to focus on processing salient regions in images. In this paper, we propose a simple and effective method to quantify the saliency for each pixel in images. Specially, we define the saliency for a pixel in a ratio form, where the numerator measures the number of dissimilar pixels in its center-surround and the denominator measures the total number of pixels in its center-surround. The final saliency is obtained by combining these ratios of dissimilarity over multiple scales. For images, the saliency map generated by our method not only has a high quality in resolution also looks more reasonable. Finally, we apply our saliency map to extract the salient regions in images, and compare the performance with some state-of-the-art methods over an established ground-truth which contains 1000 images.
FIREBALL: the Faint Intergalactic medium Redshifted Emission Balloon: overview and first science flight results

FIREBALL (the Faint Intergalactic Redshifted Emission Balloon) is a balloon-borne 1m telescope coupled to an ultraviolet fiber-fed spectrograph. FIREBALL is designed to study the faint and diffuse emission of the intergalactic medium, until now detected primarily in absorption. FIREBALL is a path finding mission to test new technology and make new constraints on the temperature and density of this gas. We report on the first successful science flight of FIREBALL, in June 2009, which proved every aspect of the complex instrument performance, and provided the strongest measurements and constraints on IGM emission available from any instrument.
Rumor Mills: The Social Impact of Rumor and Legend

The goal of this volume is to explore the social and political dynamics of rumour and the related concept of urban or contemporary legend. These forms of communication often appear in tandem with social problems, including riots, racial or political violence, and social and economic upheavals. The volume emphasizes the connection of rumour to a set of social concerns from government corruption and corporate scandal, to racial, religious, and other prejudices. Central to the dialogue are issues of truth, belief, history, public policy, and evidence.
Semantic World Models for Ubiquitous Augmented Reality

Augmented reality (AR) applications use geometric models as a central component of their operation. Both rendering and interaction require a detailed knowledge of the environment and the objects to be visualized. Usually such models are created especially for a single application and provide exactly the required information. With the combination of AR and ubiquitous computing more complex requirements for such models are appearing. In this paper we describe our experimental prototypes of semantic data models for ubiquitous augmented reality applications and discuss some further research directions and approaches to such world models.