Miracle-dz/UniFAR-FTUs huggingface dataset:
No Provable Limits to `Scientific Knowledge

SFI WORKING PAPER: 1995-04-038 SFI Working Papers contain accounts of scientific work of the author(s) and do not necessarily represent the views of the Santa Fe Institute. We accept papers intended for publication in peer-reviewed journals or proceedings volumes, but not papers that have already appeared in print. Except for papers by our external faculty, papers must be based on work done at SFI, inspired by an invited visit to or collaboration at SFI, or funded by an SFI grant. ©NOTICE: This working paper is included by permission of the contributing author(s) as a means to ensure timely distribution of the scholarly and technical work on a non-commercial basis. Copyright and all rights therein are maintained by the author(s). It is understood that all persons copying this information will adhere to the terms and constraints invoked by each author's copyright. These works may be reposted only with the explicit permission of the copyright holder. www.santafe. edu
Speech production, perception, and input of simultaneous bilingual preschoolers: Evidence from voice onset time

This study assesses the effects of age and language exposure on VOT production in 29 simultaneous bilingual children aged 3;7 to 5;11 who speak German as a heritage language in the Netherlands. Dutch and German have a binary voicing contrast, but the contrast is implemented with different VOT values in the two languages. The results suggest that bilingual children produce ‘voiced’ plosives similarly in their two languages, and these productions are not monolingual-like in either language. Bidirectional cross-linguistic influence between Dutch and German can explain these results. Yet, the bilinguals seemingly have two autonomous categories for Dutch and German ‘voiceless’ plosives. In German, the bilinguals’ aspiration is not monolingual-like, but bilinguals with more heritage language exposure produce more target-like aspiration. Importantly, the amount of exposure to German has no effect on the majority language’s ‘voiceless’ category. This implies that more heritage language exposure is associated with more language-specific voicing systems.
Calculated activity of Mn2+ at the outer surface of the root cell plasma membrane governs Mn nutrition of cowpea seedlings

Manganese (Mn) is an essential micronutrient for plant growth but is often toxic in acid or waterlogged soils. Using cowpea (Vigna unguiculata L. Walp.) grown with 0.05–1500 μM Mn in solution, two short-term (48 h) solution culture experiments examined if the effects of cations (Ca, Mg, Na, Al, or H) on Mn nutrition are related to the root cells’ plasma membrane (PM) surface potential, ψ00. When grown in solutions containing levels of Mn that were toxic, both relative root elongation rate (RRER) and root tissue Mn concentration were more closely related to the activity of Mn2+ at the outer surface of the PM, {Mn2+}00 (R2=0.812 and 0.871) than to its activity in the bulk solution, {Mn2+}b (R2=0.673 and 0.769). This was also evident at lower levels of Mn (0.05–10 μM) relevant to studies investigating Mn as an essential micronutrient (R2=0.791 versus 0.590). In addition, changes in the electrical driving force for ion transport across the PM influenced both RRER and the Mn concentration in roots. The {Mn2+}b causing a 50% reduction in root growth was found to be c. 500 to >1000 μM (depending upon solution composition), whilst the corresponding value was 3300 μM when related to {Mn2+}00. Although specific effects such as competition are not precluded, the data emphasize the importance of non-specific electrostatic effects in the Mn nutrition of cowpea seedlings over a 1×105-fold range of Mn concentration in solution.
Changes in Cerebral CB1 Receptor Availability after Acute and Chronic Alcohol Abuse and Monitored Abstinence

Involvement of the type 1 cannabinoid receptor (CB1R) in the effects of alcohol on the brain is supported by animal experiments, but how in vivo CB1R levels are altered in alcoholic patients is still unclear. To assess the short-time effects of a binge drinking episode on CB1R availability, 20 healthy social drinkers underwent [18F]MK-9470-positron emission tomography (PET) at baseline and after intravenous ethanol administration (ALC ACU). Moreover, 26 alcoholic patients underwent sequential CB1R PET after chronic heavy drinking (ALC CHR) and after 1 month of abstinence (ALC ABST). Seventeen healthy subjects served as controls. Compared with baseline, ALC ACU resulted in a global increase of CB1R availability (+15.8%). In contrast, a global decreased CB1R availability was found in ALC CHR patients (−16.1%) compared with controls, which remained unaltered after abstinence (−17.0%). Voxel-based analysis showed that ALC CHR patients had reduced CB1R availability, especially in the cerebellum and parieto-occipital cortex. After abstinence, reduced CB1R availability extended also to other areas such as the ventral striatum and mesotemporal lobe. In conclusion, whereas the acute alcohol effect is an increase in CB1R availability, chronic heavy drinking leads to reduced CB1R availability that is not reversible after 1 month of abstinence. Longer follow-up is required to differentiate whether this is a compensatory effect of repeated endocannabinoid overstimulation or an enduring trait-like feature. An enhanced CB1R signaling may offer a new therapeutic direction for treatment of the negative affective state produced by alcohol withdrawal and abstinence, which is critical for the maintenance of alcohol addiction.
A Fast Simulation Method Using Overlapping Grids for Interactions between Smoke and Rigid Objects

Recently, many techniques using computational fluid dynamics have been proposed for the simulation of natural phenomena such as smoke and fire. Traditionally, a single grid is used for computing the motion of fluids. When an object interacts with a fluid, the resolution of the grid must be sufficiently high because the shape of the object is represented by a shape sampled at the grid points. This increases the number of grid points that are required, and hence the computational cost is increased. To address this problem, we propose a method using multiple grids that overlap with each other. In addition to a large single grid (a global grid) that covers the whole of the simulation space, separate grids (local grids) are generated that surround each object. The resolution of a local grid is higher than that of the global grid. The local grids move according to the motion of the objects. Therefore, the process of resampling the shape of the object is unnecessary when the object moves. To accelerate the computation, appropriate resolutions are adaptively‐determined for the local grids according to their distance from the viewpoint. Furthermore, since we use regular (orthogonal) lattices for the grids, the method is suitable for GPU implementation. This realizes the real‐time simulation of interactions between objects and smoke.
Objective Reduction in Many-Objective Optimization: Linear and Nonlinear Algorithms

The difficulties faced by existing multiobjective evolutionary algorithms (MOEAs) in handling many-objective problems relate to the inefficiency of selection operators, high computational cost, and difficulty in visualization of objective space. While many approaches aim to counter these difficulties by increasing the fidelity of the standard selection operators, the objective reduction approach attempts to eliminate objectives that are not essential to describe the Pareto-optimal front (POF). If the number of essential objectives is found to be two or three, the problem could be solved by the existing MOEAs. It implies that objective reduction could make an otherwise unsolvable (many-objective) problem solvable. Even when the essential objectives are four or more, the reduced representation of the problem will have favorable impact on the search efficiency, computational cost, and decision-making. Hence, development of generic and robust objective reduction approaches becomes important. This paper presents a principal component analysis and maximum variance unfolding based framework for linear and nonlinear objective reduction algorithms, respectively. The major contribution of this paper includes: 1) the enhancements in the core components of the framework for higher robustness in terms of applicability to a range of problems with disparate degree of redundancy; mechanisms to handle input data that poorly approximates the true POF; and dependence on fewer parameters to minimize the variability in performance; 2) proposition of an error measure to assess the quality of results; 3) sensitivity analysis of the proposed algorithms for the critical parameter involved, and the characteristics of the input data; and 4) study of the performance of the proposed algorithms vis-à-vis dominance relation preservation based algorithms, on a wide range of test problems (scaled up to 50 objectives) and two real-world problems.
Rethinking the Policy Objectives of Development Aid: From Economic Growth to Conflict Prevention

The current consensus objective of development aid in the international community is to reduce poverty in general and to achieve the Millennium Development Goals (MDGs) in particular. In addition, the dominant view identifies economic growth as the principal means to this end. But the policy objective of aid can be defined in many ways, and has in fact varied over time with shifting priorities within the international community about the ultimate ends of development and the means for advancing those ends. This paper argues that more attention should be given to conflict prevention as a policy objective of development aid and explores the implications of doing so for aid programme priorities and the international aid architecture in general. The paper shows that violent conflict is a major obstacle to achieving the MDGs; it identifies 64 worst performing countries and finds that the majority have experienced violent internal conflict, and/or are vulnerable because of the socioeconomic correlates of internal war. The paper then argues that development policy priorities and their support with aid can be deployed to reduce these risks. Conflict prevention is thus an important policy objective as a means to achieving MDGs as well as an end itself since security from violence is an essential aspect of human wellbeing and human security. Integrating this policy objective would imply adjustments that would need to be made in aid architecture.
Cholesterol-Lowering Probiotics as Potential Biotherapeutics for Metabolic Diseases

Cardiovascular diseases are one of the major causes of deaths in adults in the western world. Elevated levels of certain blood lipids have been reported to be the principal cause of cardiovascular disease and other disabilities in developed countries. Several animal and clinical trials have shown a positive association between cholesterol levels and the risks of coronary heart disease. Current dietary strategies for the prevention of cardiovascular disease advocate adherence to low-fat/low-saturated-fat diets. Although there is no doubt that, in experimental conditions, low-fat diets offer an effective means of reducing blood cholesterol concentrations on a population basis, these appear to be less effective, largely due to poor compliance, attributed to low palatability and acceptability of these diets to the consumers. Due to the low consumer compliance, attempts have been made to identify other dietary components that can reduce blood cholesterol levels. Supplementation of diet with fermented dairy products or lactic acid bacteria containing dairy products has shown the potential to reduce serum cholesterol levels. Various approaches have been used to alleviate this issue, including the use of probiotics, especially Bifidobacterium spp. and Lactobacillus spp. Probiotics, the living microorganisms that confer health benefits on the host when administered in adequate amounts, have received much attention on their proclaimed health benefits which include improvement in lactose intolerance, increase in natural resistance to infectious disease in gastrointestinal tract, suppression of cancer, antidiabetic, reduction in serum cholesterol level, and improved digestion. In addition, there are numerous reports on cholesterol removal ability of probiotics and their hypocholesterolemic effects. Several possible mechanisms for cholesterol removal by probiotics are assimilation of cholesterol by growing cells, binding of cholesterol to cellular surface, incorporation of cholesterol into the cellular membrane, deconjugation of bile via bile salt hydrolase, coprecipitation of cholesterol with deconjugated bile, binding action of bile by fibre, and production of short-chain fatty acids by oligosaccharides. The present paper reviews the mechanisms of action of anti-cholesterolemic potential of probiotic microorganisms and probiotic food products, with the aim of lowering the risks of cardiovascular and coronary heart diseases.
Image Sequence Segmentation Using a Single Evolutionary Graph Pyramid

In the presented method, an irregular pyramid is used to segment the successive frames of an image sequence: A pyramid is built with the rst image of the sequence, and then it is updated from image to image, using a split-and-merge process that takes into account the changes occurred between two successive frames. Thus, the same pyramid structure is used along the sequence, speeding up the process. Homogeneity criteria allow to have the required compromise between speed and quality, i.e. to look for image evolution at a particular resolution. Thanks to the graph representation , objects obtained in a given image can be tracked in the rest of the sequence.
The Innovation Network as a Complex Adaptive System: Flexible Multi-agent Based Modeling, Simulation, and Evolutionary Decision Making

The literature rarely considers an innovation network as a complex adaptive system. In this paper, theories of complex adaptive systems research are employed to model and analyze intra-organization networks, inter-organization networks as well as their interaction mechanisms in the whole innovation context, with a conceptual framework proposed and presented. Flexible multi-agent based modeling, smart simulation, self-survival and adaptive intelligent software agents, expert systems, analytic hierarchy process, hybrid decision support approach, and statistical methods are integrated to deal with the innovation network problem and support evolutionary decision making in the open and dynamic environments.
Fourier decomposition and frequency analysis of the pulsating stars with $P < $ 1 d in the OGLE database - II. Multiperiodic RR Lyrae variables in the Galactic Bulge

We present the results of a systematic search for multiperiodic pulsators among the Galactic Bulge RR Lyrae stars of the OGLE-1 sample. We identify one "canonical" double-mode variable (RRd star) pulsating in two radial modes. In 38 stars we detect secondary periodicities very close to the primary pulsation frequency. This type of multiperiodic variables constitute ∼23% of RRab and ∼5% of RRc population of the Bulge. With the observed period ratios of 0.95−1.02 the secondary periods must correspond to nonradial modes of oscillation. Their beating with the primary (radial) pulsation leads to a long-term amplitude and phase modulation, known as the Blazhko effect. The Blazhko RRab variables occur more frequently in the Galactic Bulge than in the LMC. The opposite tendency is seen in case of the RRd stars. The differences of incidence rates are most likely caused by different metallicity of the two populations. We discuss pulsation properties of the OGLE-1 Blazhko stars and compare them with predictions of theoretical models. We argue, that the oblique magnetic pulsator model of Shibahashi (2000) cannot account for the observations and should be ruled out.
Clinicopathologic findings in polypoidal choroidal vasculopathy.

PURPOSE To elucidate the pathogenic mechanism of polypoidal choroidal vasculopathy (PCV) based on histopathologic findings. METHODS Specimens obtained by surgical excision of PCV from five eyes of five patients (mean age, 75.6 +/- 3.1 years) were studied histopathologically. Immunohistochemical studies were also performed to identify CD34, vascular endothelial growth factor (VEGF), CD68, alpha-smooth muscle actin (alpha-SMA) and hypoxia-inducible factor (HIF)-1alpha. RESULTS Hyalinization of choroidal vessels and massive exudation of fibrin and blood plasma were observed in all the specimens of PCV lesions. Some blood vessels were located above the RPE in two of the five eyes. Immunohistochemically, CD68-positive cells were detected around the hyalinized vessels. There were no alpha-SMA-positive cells in the vessels of PCV. CD34 staining showed endothelial discontinuity. Vascular endothelial cells within the PCV specimens were negative for VEGF. HIF-1alpha positive inflammatory cells were located in the stroma of specimens. CONCLUSIONS Hyalinization of choroidal vessels, like arteriosclerosis, is characteristic of PCV.
Plasma levobupivacaine concentrations following scalp block in patients undergoing awake craniotomy.

BACKGROUND Levobupivacaine is an effective local anaesthetic agent for nerve blockade with less systemic toxicity than racemic bupivacaine. The safety and efficacy of levobupivacaine for scalp blockade during awake craniotomy have not been addressed previously. METHODS Serial arterial plasma levobupivacaine concentrations following scalp blockade were measured to 2 h in 10 patients booked for awake craniotomy for epilepsy or tumour surgery. Bilateral scalp blockade providing surgical anaesthesia was achieved with a mean dose of 177 mg (2.5 mg kg(-1), range 1.6-3.2 mg kg(-1)) of levobupivacaine (0.5%, 5 mg ml(-1)) with epinephrine (5 microg ml(-1)) added immediately before the block insertion. RESULTS The maximum measured plasma levobupivacaine concentration was 1.58 (0.44) microg ml(-1) [mean (SD)] with a mean time to peak plasma concentration of 12 (4) min. There were no episodes in any of the 10 patients of symptoms or signs suggestive of either CNS or CVS toxicity. CONCLUSIONS This study demonstrated a relatively rapid rise of plasma levobupivacaine concentration without evidence of cardiovascular or central nervous system sequelae in a sample population of patients who may be particularly prone to perioperative seizures.
Softmax GAN

Softmax GAN is a novel variant of Generative Adversarial Network (GAN). The key idea of Softmax GAN is to replace the classification loss in the original GAN with a softmax cross-entropy loss in the sample space of one single batch. In the adversarial learning of $N$ real training samples and $M$ generated samples, the target of discriminator training is to distribute all the probability mass to the real samples, each with probability $\frac{1}{M}$, and distribute zero probability to generated data. In the generator training phase, the target is to assign equal probability to all data points in the batch, each with probability $\frac{1}{M+N}$. While the original GAN is closely related to Noise Contrastive Estimation (NCE), we show that Softmax GAN is the Importance Sampling version of GAN. We futher demonstrate with experiments that this simple change stabilizes GAN training.
AN AUTOMATIC LEAF RECOGNITION SYSTEM FOR PLANT IDENTIFICATION USING MACHINE VISION TECHNOLOGY

Plants are the backbone of all life on Earth and an essential resource for human well-being. Plant recognition is very important in agriculture for the management of plant species whereas botanists can use this application for medicinal purposes. Leaf of different plants have different characteristics which can be used to classify them. This paper presents a simple and computationally efficient method for plant identification using digital image processing and machine vision technology. The proposed approach consists of three phases: pre-processing, feature extraction and classification. Preprocessing is the technique of enhancing data images prior to computational processing. The feature extraction phase derives features based on color and shape of the leaf image. These features are used as inputs to the classifier for efficient classification and the results were tested and compared using Artificial Neural Network (ANN) and Euclidean (KNN) classifier. The network was trained with 1907 sample leaves of 33 different plant species taken form Flavia dataset. The proposed approach is 93.3 percent accurate using ANN classifier and the comparison of classifiers shows that ANN takes less average time for execution than Euclidean distance method.
Are inflationary predictions sensitive to very high energy physics

It has been proposed that the successful inflationary description of density perturbations on cosmological scales is sensitive to the details of physics at extremely high (trans-Planckian) energies. We test this proposal by examining how inflationary predictions depend on higher-energy scales within a simple model where the higher-energy physics is well understood. We find the best of all possible worlds: inflationary predictions are robust against the vast majority of high-energy effects, but can be sensitive to some effects in certain circumstances, in a way which does not violate ordinary notions of decoupling. This implies both that the comparison of inflationary predictions with CMB data is meaningful, and that it is also worth searching for small deviations from the standard results in the hopes of learning about very high energies.
Levels of Communication Act: Functional Communicative Features of Social Work Institutional Discourse

The article studies basic functional communicative features of social work discourse. Assuming the actualization of triple communication bonds “a social worker – a client – a social service” in social work interaction, the authors study the key levels of communicative actions, which verbalize both institutional and personal elements in this communication domain. The approach provides an opportunity to specify social work discourse as a contaminated phenomenon combining the features of a social-ritual kind within the institutional type of discourse and an existential kind within personality-oriented type of discourse. The linguistic means of actualizing conventional components of this type of discourse are determined.
BO-ARED: A new AQM algorithm with adaptive adjustment of parameters

To address the problems of network congestion, Active queue management (AQM) is advocated to improve the quality of services (QoS) for Internet. Random early detective (RED) algorithm is one of notably AQM mechanism, because it could reduce the high drop rate of bursty flows, avoid global synchronization among flows and reduces network latency (“ping time”). However, RED requires careful tuning of its parameters in order to provide good performance. For solving this problem, this paper proposes a new mechanism to improve RED algorithm, which is named BO-ARED (An Adaptive RED Algorithm Combined With Buffer Occupation). By matching router's buffer occupation with wq, minth, maxth and Pmax parameter settings, to make BO-ARED adapt to network environment variation automatically. The simulations take comparisons of the BO-ARED with RED, ARED and BORED. It is shown in the simulation results that BO-ARED algorithm maintains the great performance while network environment varies. It has low drop rate, low average delay time and high throughput with it adaptive parameters.