Miracle-dz/UniFAR-FTUs huggingface dataset:
In situ transmission electron microscopy of resistive switching in thin silicon oxide layers

Silicon oxide-based resistive switching devices show great potential for applications in nonvolatile random access memories. We expose a device to voltages above hard breakdown and show that hard oxide breakdown results in mixing of the SiOx layer and the TiN lower contact layers. We switch a similar device at sub-breakdown fields in situ in the transmission electron microscope (TEM) using a movable probe and study the diffusion mechanism that leads to resistance switching. By recording bright-field (BF) TEM movies while switching the device, we observe the creation of a filament that is correlated with a change in conductivity of the SiOx layer. We also examine a device prepared on a microfabricated chip and show that variations in electrostatic potential in the SiOx layer can be recorded using off-axis electron holography as the sample is switched in situ in the TEM. Taken together, the visualization of compositional changes in ex situ stressed samples and the simultaneous observation of BF TEM contrast.
Effects of Eating Attitudes, Mood States and Competitive Behaviour Among Sports Women

The purpose of this study was to find out the effects of Eating Attitudes, Mood states and Competitive Behaviour among sports women. This study deals with the analysis of data, findings and discussion of findings. To achieve the objectives of the study, the scholar will adopt the entire process of the research work, the sample and its selection, proper tools and adequate statistical techniques for organizing, analyzing of the data. A Standardized questionnaire arranged for taking information regarding the Effects of Eating Attitudes, Mood states and Competitive Behaviour among sports women. The data that was collected through various 300 subjects (150 + 150 females) were selected randomly belonging to the age of 18 to 22 years from different colleges of Haryana State University.
The SIM neural module : self-organized learning of 2 Dinvariant representationsDanny

Developing spatial invariant 2D representations in a self-organizing way is realised by the Self-organizing Invariant representation Map (SIM) module which we introduce in this contribution. The model consists of a bi-layer structure of abstract neurons with adaptive forward connections and integrates weight-sharing with existing competitive learning rules. Adopting an unsupervised learning strategy, learning is fast and local in nature and implies that the model can be used as a modular building block at diierent levels of processing in larger vision systems. We discuss the behavior of the model on a toy problem and we demonstrate the integration of several SIM modules into larger application systems by reporting on a SIM-based handwritten numeral recognition system and a SIM-based natural object recognition system.
Localization with a Mobile Beacon in Underwater Acoustic Sensor Networks

Localization is one of the most important issues associated with underwater acoustic sensor networks, especially when sensor nodes are randomly deployed. Given that it is difficult to deploy beacon nodes at predetermined locations, localization schemes with a mobile beacon on the sea surface or along the planned path are inherently convenient, accurate, and energy-efficient. In this paper, we propose a new range-free Localization with a Mobile Beacon (LoMoB). The mobile beacon periodically broadcasts a beacon message containing its location. Sensor nodes are individually localized by passively receiving the beacon messages without inter-node communications. For location estimation, a set of potential locations are obtained as candidates for a node's location and then the node's location is determined through the weighted mean of all the potential locations with the weights computed based on residuals.
An Evaluation of Rescheduling Techniques and Architectures in Holonic Manufacturing Systems

Holonic Manufacturing Systems (HMS) have been proposed as a way to meet the ever increasing needs f or robustness to disturbances, adaptability and flexibility t o rapid change, and efficient use of available resources on the factory floors of 21st Century manufacturing enterpri ses. We analyse a particular type of HMS called a holonic assembly system which focuses on flexible control, ansportation, transformation and storage of parts for assembling value-added products. Assembly tasks need to be rescheduled within this system due to extraneous circumstances, including the occurrence of unp redictable machine faults or the introduction of ' rush' orders. To facilitate the widespread adoption and deployme nt of HMS technology, a comprehensive conceptual model is required. This paper outlines such a model by provid ing: (i) an architecture for the unambiguous specification of the structure and relationships among func tio al entities ( holons) within the system, and (ii) an operational model with well-defined semantics for applying techniques such as rescheduling. The paper identifies a repertoire of techniques for reschedu ling tasks and discusses their suitability to different architectures. The paper argues, from a pragmatic pe rspective, that an integration of agent-basedand function blockoriented approaches to support holonic capability need to b e pursued. Then it compares temperatureandpreferencerescheduling techniques. The focus of this evaluation is th e influence of different strategies on performance and identification of opportunities for opti misation.
Massive Genomic Decay in Serratia symbiotica, a Recently Evolved Symbiont of Aphids

All vertically transmitted bacterial symbionts undergo a process of genome reduction over time, resulting in tiny, gene-dense genomes. Comparison of genomes of ancient bacterial symbionts gives only limited information about the early stages in the transition from a free-living to symbiotic lifestyle because many changes become obscured over time. Here, we present the genome sequence for the recently evolved aphid symbiont Serratia symbiotica. The S. symbiotica genome exhibits several of the hallmarks of genome evolution observed in more ancient symbionts, including elevated rates of evolution and reduction in genome size. The genome also shows evidence for massive genomic decay compared with free-living relatives in the same genus of bacteria, including large deletions, many pseudogenes, and a slew of rearrangements, perhaps promoted by mobile DNA. Annotation of pseudogenes allowed examination of the past and current metabolic capabilities of S. symbiotica and revealed a somewhat random process of gene inactivation with respect to function. Analysis of mutational patterns showed that deletions are more common in neutral DNA. The S. symbiotica genome provides a rare opportunity to study genome evolution in a recently derived heritable symbiont.
Interactivity in a VLE for children

Virtual Learning Environments are a relatively new concept and little research is done to positive effects of a VL E on the learning process of children. Due to its success in conventional learning methods interactivity is often taken for g ranted in a successful VLE. A close study of some literature on experiments with observations of VLE’s, make clear that interactivity in a VLE can have its drawbacks and a ctu l obstruct gaining knowledge. Supporting the construc tivism theory, other observations do hint at positive effe cts of interactivity in VLE’s. In the end most experiments are just not thorough enough to make any real conclusions about the positive effects. Implications of possibilities are there, but actual proof is still needed to be gained via large r more thorough experiments.
School Choice, Stratification, and Information on School Performance: Lessons from Chile

In the early 1980s, Chile implemented a nationwide school choice system, under which the government finances education via a flat per-student sub- sidy (or voucher) to the public or private school chosen by a family. At present, about 94 percent of all schools (public, religious, and secular private) are voucher funded. More than half of urban schools are private, and most of these operate as for-profit institutions.1 Since the early 1990s, Chile has also publicized information on school performance and increased per pupil expen- diture substantially. Despite these and other reforms, Chile has found it challenging to improve students’ learning outcomes.2 Hsieh and Urquiola find that the country’s rel- ative performance in international tests did not change much between 1970 and 1999.3 Its performance on the 2000 Programme for International Student Assessment (PISA) is not only much lower than the OECD average but is similar to that of other Latin American countries and low relative to countries with similar income per capita.
The effect of chemotherapy on programmed cell death 1/programmed cell death 1 ligand axis: some chemotherapeutical drugs may finally work through immune response

Most tumors are immunogenic which would trigger some immune response. Chemotherapy also has immune potentiating mechanisms of action. But it is unknown whether the immune response is associated with the efficacy of chemotherapy and the development of chemoresistance. Recently, there is a growing interest in immunotherapy, among which the co-inhibitory molecules, programmed cell death 1/programmed cell death 1 ligand (PD-1/PD-L1) leads to immune evasion. Since some reports showed that conventional chemotherapeutics can induce the expression of PD-L1, we try to summarize the effect of chemotherapy on PD-1/PD-L1 axis and some potential molecules relevant to PD-1/PD-L1 in chemoresistance in this review.
The VLT-FLAMES survey of massive stars: stellar parameters and rotational velocities in NGC 3293, NGC 4755 and NGC 6611

An analysis is presented of VLT-FLAMES spectroscopy for three Galactic clusters, NGC 3293, NGC 4755 and NGC 6611. Non-LTE model atmosphere calculations have been used to estimate effective temperatures (from either the helium spectrum or the silicon ionization equilibrium) and gravities (from the hydrogen spectrum). Projected rotational velocities have been deduced from the helium spectrum (for fast and moderate rotators) or the metal line spectrum (for slow rotators). The origin of the low gravity estimates for apparently near main sequence objects is discussed and is related to the stellar rotational velocity. The atmospheric parameters have been used to estimate cluster distances (which are generally in good agreement with previous determinations) and these have been used to estimate stellar luminosities and evolutionary masses. The observed Hertzsprung-Russell diagrams are compared with theoretical predictions and some discrepancies including differences in the main sequence luminosities are discussed. Cluster ages have been deduced and evidence for non-coeval star formation is found for all three of the clusters. Projected rotational velocities for targets in the older clusters, NGC 3293 and NGC 4755, have been found to be systematically larger than those for the field, confirming recent results in other similar age clusters. The distribution of projected rotational velocities are consistent with a Gaussian distribution of intrinsic rotational velocities. For the relatively unevolved targets in the older clusters, NGC 3293 and NGC 4755, the peak of the velocity distribution would be 250 km s −1 with a full-width-half-maximum of approximately 180 km s −1 . For NGC 6611, the sample size is relatively small but implies a lower mean rotational velocity. This may be evidence for the spin-down effect due to angular momentum loss through stellar winds, although our results are consistent with those found for very young high mass stars. For all three clusters we deduce present day mass functions with Γ-values in the range of −1.5 to −1.8, which are similar to other young stellar clusters in the Milky Way.
Key Role of Nf-κ B in the Cellular Pharmacokinetics of Adriamycin in MCF-7/Adr Cells: The Potential Mechanism for Synergy with 20(S)-Ginsenoside Rh2

We have previously demonstrated that ginsenoside 20(S)-Rh2 is a potent ABCB1 inhibitor and explored the cellular pharmacokinetic mechanisms for its synergistic effect on the cytotoxicity of adriamycin. The present studies were conducted to elucidate the key factors that influenced ABCB1 expression which could further alter adriamycin cellular pharmacokinetics. Meanwhile, the influence of 20(S)-Rh2 on the above factors was revealed for explaining its synergistic effect from the view of ABCB1 expression. The results indicated that 20(S)-Rh2 inhibited adriamycin-induced ABCB1 expression in MCF-7/Adr cells. Subsequent analyses indicated that 20(S)-Rh2 markedly inhibited adriamycin-induced activation of the MAPK/Nf-κ translocation to the nucleus and Nf-κ binding activity. Furthermore, 20(S)-Rh2 repressed the adriamycin-enhanced ability of Nf-κ to bind to the human MDR1 promoter, and MAPK/Nf-κ reversed the adriamycin-induced expression of ABCB1. Moreover, the cellular pharmacokinetics of adriamycin was also significantly altered by inhibiting Nf-κ B. In conclusion, the MAPK/Nf-κ B pathway mediates adriamycin-induced ABCB1 expression and subsequently alters the cellular pharmacokinetics of adriamycin. It was speculated that 20(S)-Rh2 acted on this pathway to lower adriamycin-induced ABCB1 expression in MCF-7/Adr cells, which provided mechanism-based support to the development of 20(S)-Rh2 as a multi-drug resistance (MDR) reversal agent.
Modeling of Speech Parameter Sequence Considering Global Variance for HMM-Based Speech Synthesis

Speech technologies such as speech recognition and speech synthesis have many potential applications since speech is the main way in which most people communicate. Various linguistic sounds are produced by controlling the configuration of oral cavities to convey a message in speech communication. The produced speech sounds temporally vary and are significantly affected by coarticulation effects. Thus, it is not straightforward to segment speech signals into corresponding linguistic symbols. Moreover, the acoustics of speech vary even if the same words are uttered by the same speaker due to differences in the manner of speaking and articulatory organs. Therefore, it is essential to stochastically model them in speech processing. The hidden Markov model (HMM) is an effective framework for modeling the acoustics of speech. Its introduction has enabled significant progress in speech and language technologies. In particular, there have been numerous efforts to develop HMM-based acoustic modeling techniques in speech recognition, and continuous density HMMs have been widely used in modern continuous speech recognition systems (Gales & Young (2008)). Moreover, several approaches have been proposed for applying the HMM-based acoustic modeling techniques to speech synthesis technologies (Donovan & Woodland (1995); Huang et al. (1996)) such as Text-to-Speech (TTS), which is . from a given text. Recently, HMM-based speech synthesis has been proposed (Yoshimura et al. (1999)) and has generated interest owing to its various attractive features such as completely data-driven voice building, flexible voice quality control, speaker adaptation, small footprint, and so forth (Zen et al. (2009)). A basic framework of HMM-based speech synthesis consists of training and synthesis processes. In the training process, speech parameters such as spectral envelope and fundamental frequency (F0) are extracted from speech waveforms and then their time sequences are modeled by context-dependent phoneme HMMs. To model the dynamic characteristics of speech acoustics with HMMs, which assume piecewise constant statistics within an HMM state and conditional independence, a joint vector of static and dynamic features is usually used as an observation vector. In the synthesis process, a smoothly varying speech parameter trajectory is generated by maximizing the likelihood of a composite sentence HMM subject to a constraint between static and dynamic features with respect to not the observation vector sequence including both static and dynamic features but the static feature vector sequence (Tokuda et al. (2000)). Finally, a vocoding technique is employed Modeling of Speech Parameter Sequence Considering Global Variance for HMM-Based Speech Synthesis 6
Spiking neural network connectivity and its potential for temporal sensory processing and variable binding

The most biologically-inspired artificial neurons are those of the third generation, and are termed spiking neurons, as individual pulses or spikes are the means by which stimuli are communicated. In essence, a spike is a short-term change in electrical potential and is the basis of communication between biological neurons. Unlike previous generations of artificial neurons, spiking neurons operate in the temporal domain, and exploit time as a resource in their computation. In 1952, Alan Lloyd Hodgkin and Andrew Huxley produced the first model of a spiking neuron; their model describes the complex electro-chemical process that enables spikes to propagate through, and hence be communicated by, spiking neurons. Since this time, improvements in experimental procedures in neurobiology, particularly with in vivo experiments, have provided an increasingly more complex understanding of biological neurons. For example, it is now well-understood that the propagation of spikes between neurons requires neurotransmitter, which is typically of limited supply. When the supply is exhausted neurons become unresponsive. The morphology of neurons, number of receptor sites, amongst many other factors, means that neurons consume the supply of neurotransmitter at different rates. This in turn produces variations over time in the responsiveness of neurons, yielding various computational capabilities. Such improvements in the understanding of the biological neuron have culminated in a wide range of different neuron models, ranging from the computationally efficient to the biologically realistic. These models enable the modeling of neural circuits found in the brain.
Oscillometric blood pressure pulse morphology

This paper presents a new analysis of oscillometric blood pressure signals using pulse morphology under different pressure points. As the pulse morphology contains potentially critical clinical information, quantitative signal metrics are used to characterize the blood pressure pulse using pulse morphology. Signals metrics at three different pressure points namely systolic, mean arterial and diastolic pressure points are obtained and are compared across three different age groups (&#60;30, 30–55, >55). It is observed that the pulses change their characteristics at different pressure points and also with age. This preliminary analysis indicates the usefulness of pulse morphology of oscillometric blood pressure signals for diagnostic purposes through comparison of the proposed signal metrics over age and at different pressure points.
Reasoning by model: The case of multiple quantification.

A theory of deductive reasoning is presented fora major class of inferences that has not been investigated by psychologists: inferences that depend on multiply-quantified premises (e.g., "None of the Princeton letters is in the same place as any of the Dublin letters"). It is argued that reasoneis construct mental models based on their knowledge of the meanings of quantifiers (and other terms, including relational expressions). Three experiments corroborate the model theory's prediction that inferences that require the construction of only 1 model will be easier than those that require more than 1 model. The model theory assumes that the logical properties of quantifiers emerge from their meanings and are not mentally represented in rules of inference. How such a semantic process can occur compositionally (i.e., guided by the syntactic analysis of sentences) is described. Deductive reasoning is a process of thought that yields new information from old and aims to establish valid conclusions, that is, conclusions that are necessarily true given the truth of the initial premises or observations. The study of its underlying mental mechanisms is almost as old as experimental psychology, but remains a matter of controversy. There are three main views that have been proposed in both cognitive psychology and artificial intelligence. First, the reasoning mechanism depends on formal rules of inference; second, it depends on content-specific rules of inference; and, third, it depends on semantic procedures that search for interpretations (or models) of the premises that are counterexamples to conclusions. The principal goal of this article is to establish a theory of deductive reasoning for a major class of inferences that has not been investigated before by psychologists: those that depend on multiply-quantified premises. There are theories of relational reasoning and of syllogistic reasoning (i.e., from singly quantified premises), but multiple quantification is more powerful, and its logical analysis calls for the full resources of that branch of logic known as the first-order predicate calculus. In this article we develop a theory based on the manipulation of models and report experimental evidence that confirms this theory. An example of a multiply-quantified assertion is as follows: None of the artists is taller than any of the beekeepers. Such assertions contain a relational expression—here, a two-place relation, "taller than"; its arguments are quantified by such expressions as "all," "some," "none," and "any. " These quantifiers behave in ways that are similar to the quantifiers of the firstorder predicate calculus, but there are other "nonstandard"
Sensitivity Analysis for the Assessment of Causal Vaccine Effects on Viral Load in HIV Vaccine Trials

Summary. Vaccines with limited ability to prevent HIV infection may positively impact the HIV/AIDS pandemic by preventing secondary transmission and disease in vaccine recipients who become infected. To evaluate the impact of vaccination on secondary transmission and disease, efficacy trials assess vaccine effects on HIV viral load and other surrogate endpoints measured after infection. A standard test that compares the distribution of viral load between the infected subgroups of vaccine and placebo recipients does not assess a causal effect of vaccine, because the comparison groups are selected after randomization. To address this problem, we formulate clinically relevant causal estimands using the principal stratification framework developed by Frangakis and Rubin (2002, Biometrics58, 21–29), and propose a class of logistic selection bias models whose members identify the estimands. Given a selection model in the class, procedures are developed for testing and estimation of the causal effect of vaccination on viral load in the principal stratum of subjects who would be infected regardless of randomization assignment. We show how the procedures can be used for a sensitivity analysis that quantifies how the causal effect of vaccination varies with the presumed magnitude of selection bias.