Miracle-dz/UniFAR-FTUs huggingface dataset:
An Analytical Model for the Forming Process of Conductive-Bridge Resistive-Switching Random-Access Memory

An analytical model for the forming process of conductive-bridge resistive-switching random-access memory is developed. The measurable forming time can be calculated using this model giving the biasing condition and is verified to be correct through comparison with the experimental data. The forming time has been shown to have multiple-slopes in exponential dependence on the applied voltage, in agreement with measurement. The model is based on the identification of three steps in the forming process: 1) metal oxidation at the anode; 2) cation migration toward the cathode; and 3) backward filament growth due to electroplating from the cathode. The accuracy of the model has also been established via numerical simulation.
The Social Sense: Susceptibility to Others’ Beliefs in Human Infants and Adults

Mind Reading One core component of social cognition, especially of the kind practiced by humans, is the capacity to formulate a representation of what someone else believes to be true, even if that belief is not anchored in reality. Holding two such beliefs in mind—one false and one true—is no simple feat, and up until a few years ago, it was generally accepted that such a capacity did not arise until children were 3 to 4 years old. Since then, a flurry of studies, using a variety of interrogation measures, has suggested that much-younger humans might, in fact, possess this capacity, commonly referred to as a theory of mind. Kovács et al. (p. 1830) devised an ingenious behavioral paradigm and applied it both to adults and to infants, which suggests that the representations of others' beliefs are indeed formed in the same way in adults and in infants. Knowledge of what others believe is present in 7-month-old infants. Human social interactions crucially depend on the ability to represent other agents’ beliefs even when these contradict our own beliefs, leading to the potentially complex problem of simultaneously holding two conflicting representations in mind. Here, we show that adults and 7-month-olds automatically encode others’ beliefs, and that, surprisingly, others’ beliefs have similar effects as the participants’ own beliefs. In a visual object detection task, participants’ beliefs and the beliefs of an agent (whose beliefs were irrelevant to performing the task) both modulated adults’ reaction times and infants’ looking times. Moreover, the agent’s beliefs influenced participants’ behavior even after the agent had left the scene, suggesting that participants computed the agent’s beliefs online and sustained them, possibly for future predictions about the agent’s behavior. Hence, the mere presence of an agent automatically triggers powerful processes of belief computation that may be part of a “social sense” crucial to human societies.
Scaling of the variance and the quantification of resource monopolization

Daniel E. Ruzzante,* David C. Hamilton, Donald L. Kramer, and James W. A. Grant* "Department of Biology, Dalhousie University, Halifax, Nova Scotia B3H 4J1, Canada, Department of Mathematics, Statistics, and Computing Science, Dalhousie University, Halifax, Nova Scotia B3H 3J5, Canada, Department of Biology, McGill University, 1205 Docteur Penfield Avenue, Montreal, Quebec H3A 1B1, Canada, and Department of Biology, Concordia University, 1455 Boulevard de Maisonneuve West, Montreal, Quebec H3G 1M8, Canada
Handling CFMU slots in busy airports

In busy airports, too many departing flights take off out of the time slot required by the Central Flow Management Unit (CFMU). During ground traffic peaks, taxi out times and runway queuing delays increase, and it seems very hard and maybe unfeasible for ground controllers to organise properly the traffic so that aircraft take off at their scheduled time. In a first part, this paper shows how a ground traffic simulator that includes a conflict resolution module can give accurate predictions of takeoff times. Then, different strategies taking into account these predictions so as to incorporate CFMU slot constraints are compared. The deviation between the required slots and the final takeoff times is measured. The efficiency of the different strategies is compared by the correlation between the number of aircraft and the generated delay.
BRCA1 Suppresses Osteopontin-mediated Breast Cancer*

BRCA1 is a well described breast cancer susceptibility gene thought to be involved primarily in DNA repair. However, mutation within the BRCA1 transcriptional domain is also implicated in neoplastic transformation of mammary epithelium, but responsible mechanisms are unclear. Here we show in a rat mammary model system that wild type (WT) BRCA1 specifically represses the expression of osteopontin (OPN), a multifunctional estrogen-responsive gene implicated in oncogenic transformation, particularly that of the breast. WT.BRCA1 selectively binds OPN-activating transcription factors estrogen receptor α, AP-1, and PEA3, inhibits OPN promoter transactivation, and suppresses OPN mRNA and protein both from an endogenous gene and a relevant model inducible gene. WT.BRCA1 also inhibits OPN-mediated neoplastic transformation characterized by morphology change, anchorage-independent growth, adhesion to fibronectin, and invasion through Matrigel. A mutant BRCA1 allele (Mut.BRCA1) associated with familial breast cancer lacks OPN suppressor effects, binds to WT.BRCA1, and impedes WT.BRCA1 suppression of OPN. Stable transfection of rat breast tumor cell lines with Mut.BRCA1 dramatically up-regulates OPN protein and induces anchorage independent growth. In human primary breast cancer, BRCA1 mutation is significantly associated with OPN overexpression. Taken together, these data suggest that BRCA1 mutation may confer increased tissue-specific cancer risk, in part by disruption of BRCA1 suppression of OPN gene transcription.
A model-driven approach for modelling and simulating new malleable learning scenarios for digital native generations

Our research proposes an innovative approach that aims at supporting pedagogical designers and teachers to reach ‘new’ learners of today or ‘digital natives’ by allowing them to model, generate and simulate new pervasive, context-aware and adaptive learning scenarios. The core element of this approach consists of an educational modelling language called context-aware adaptive activities modelling language (CAAML) and based jointly on activity theory and IMS-LD standard. To define CAAML language, firstly, we start with identifying relevant concepts that can describe the domain of ‘malleable learning’ which is a useful designation we have found for pervasive, context-aware and adaptive learning. Secondly, we describe its meta-model based on those domain concepts. After, we present the developed authoring tool called ContAct-Me which is based on the CAAML language. To test and evaluate our work, we finally present a learning scenario that values the importance of the proposed graphical language in expressing.
Magnetic Resonance–Derived 3-Dimensional Blood Flow Patterns in the Main Pulmonary Artery as a Marker of Pulmonary Hypertension and a Measure of Elevated Mean Pulmonary Arterial Pressure

Background—Pulmonary hypertension is a disease characterized by an elevation in pulmonary arterial pressure that is diagnosed invasively via right heart catheterization. Such pathological altered pressures in the pulmonary vascular system should lead to changes in blood flow patterns in the main pulmonary artery. Methods and Results—Forty-eight subjects (22 with manifest pulmonary hypertension, 13 with latent pulmonary hypertension, and 13 normal control subjects) underwent time-resolved 3D magnetic resonance phase-contrast imaging of the main pulmonary artery. Velocity fields that resulted from measurements were calculated, visualized, and analyzed with dedicated software. Main findings were as follows: (1) Manifest pulmonary hypertension coincides with the appearance of a vortex of blood flow in the main pulmonary artery (sensitivity and specificity of 1.00, 95% confidence intervals of 0.84 to 1.00 and 0.87 to 1.00, respectively), and (2) the relative period of existence of the vortex correlates significantly with mean pulmonary arterial pressure at rest (correlation coefficient of 0.94). To test the diagnostic performance of the vortex criterion, we furthermore investigated 55 patients in a blinded prospective study (22 with manifest pulmonary hypertension, 32 with latent pulmonary hypertension, and 1 healthy subject), which resulted in a sensitivity of 1.00 and specificity of 0.91 (95% confidence intervals of 0.84 to 1.00 and 0.76 to 0.98, respectively). Comparison of catheter-derived mean pulmonary artery pressure measurements and calculated mean pulmonary artery pressure values resulted in a standard deviation of differences of 3.6 mm Hg. Conclusions—Vortices of blood flow in the main pulmonary artery enable the identification of manifest pulmonary hypertension. Elevated mean pulmonary arterial pressures can be measured from the period of vortex existence.
Identification of material properties of orthotropic composite plate using hybrid non-destructive evaluation approach

Abstract Identification of material properties is one of the key issues in composite materials research. The mechanical properties of composite materials depend on diverse factors such as configuration of the laminates, constituent materials used and production method adopted. Conventional testing approach tends to be time-consuming, expensive and destructive. As an alternative, a rapid, inexpensive, hybrid and non-destructive evaluation approach which utilises experimental modal analysis and finite element analysis is proposed. Experimental modal data which consist of natural frequencies and mode shapes of an orthotropic composite plate are utilised for correlation purpose with its finite element model. This finite element model of the composite plate is continuously updated and achieves less than 5% in difference of natural frequencies and over 70% in modal assurance criterion. Material properties such as Young's moduli, in-plane shear modulus and Poisson ratio of the composite plate are then successfully determined using the well-correlated FE model.
Mobile robot navigation: implementing the GVG in the presence of sharp corners

A robot can explore an unknown environment by incrementally constructing a roadmap of that environment using line of sight sensor information. Recall that a roadmap is a one-dimensional representation of a robot's environment. This paper addresses one problem that occurs while generating a roadmap: what happens when sonar sensors cannot detect sharp objects because of the specularities? To do this, a new sensor model is combined with an already existing incremental construction procedure for a roadmap. Experiments on a mobile robot validate the results of this paper. A generalised Voronoi graph is used.
Direct Intraventricular Delivery of Drugs to the Rodent Central Nervous System

Due to an inability to cross the blood brain barrier, certain drugs need to be directly delivered into the central nervous system (CNS). Our lab focuses specifically on antisense oligonucleotides (ASOs), though the techniques shown in the video here can also be used to deliver a plethora of other drugs to the CNS. Antisense oligonucleotides (ASOs) have the capability to knockdown sequence-specific targets 1 as well as shift isoform ratios of specific genes 2. To achieve widespread gene knockdown or splicing in the CNS of mice, the ASOs can be delivered into the brain using two separate routes of administration, both of which we demonstrate in the video. The first uses Alzet osmotic pumps, connected to a catheter that is surgically implanted into the lateral ventricle. This allows the ASOs to be continuously infused into the CNS for a designated period of time. The second involves a single bolus injection of a high concentration of ASO into the right lateral ventricle. Both methods use the mouse cerebral ventricular system to deliver the ASO to the entire brain and spinal cord, though depending on the needs of the study, one method may be preferred over the other.
Preparation and Characterization of Nisoldipine Nanoparticles by Nanoprecipitation Method

The purpose of this study is to develop Nisoldipine nanoparticles with Eudragit RLPO. In this study, nanoparticles were prepared by nanoprecipitation method. The morphological structure was investigated by Transmission electron microscope (TEM) The drug loaded nanoparticles found to exhibit a spherical shape. The mean particle size of the nanoparticles found to 400-600 nm with narrow size distribution with zeta potential of about -25mV. Fourier transform infrared spectroscopy and Differential scanning colorimetry (DSC) indicated that no possible interactions between the drug and polymer. Nisoldipine was selected as a model hydrophobic, poorly water soluble drug. The in vitro release from Nisoldipine loaded Eudragit RLPO nanoparticles showed 11% at pH 1.2, 55%at pH 5.0 and 90%at pH 6.8, within 24 h.
The Each Child Study: Systematic Screening for Autism Spectrum Disorders in a Pediatric Setting

OBJECTIVE: The goal of this study was to investigate the feasibility and outcome of a systematic autism screening process for all toddlers (aged 14–30 months) in a large, community-based pediatric practice. METHODS: All toddlers who presented to the clinic during the 6-month screening period were eligible. We used 2 screening questionnaires and allowed physicians to refer directly to capture as many children as possible. Receptionists and medical assistants distributed and collected screening questionnaires; research staff did all scoring and follow-up, either by telephone or in person when indicated. RESULTS: We obtained a high rate of screening (80% of eligible children). Of the 796 children screened, 3 had already been diagnosed with an autism spectrum disorder (ASD); an additional 10 children who showed signs of early ASD that warranted further evaluation or intervention were identified. Formal screening measures identified more children with ASD than did clinical judgment or caregiver concerns; however, no single method (ie, questionnaire, caregiver concerns, provider concerns) identified all children with signs of early ASD. We had excellent participation from racially and ethnically diverse families, including Spanish-speaking families. Thirty-two percent of the children who were screened did not present for a well-child visit during the study period and were screened at a sick visit, follow-up visit, or injection appointment. CONCLUSIONS: A partnership between pediatricians and autism specialists resulted in effective, systematic autism screening. Future studies should examine how to create effective systems of care.
Blocking Conductance and Mixing in Random Walks

The notion of conductance introduced by Jerrum and Sinclair [8] has been widely used to prove rapid mixing of Markov chains. Here we introduce a bound that extends this in two directions. First, instead of measuring the conductance of the worst subset of states, we bound the mixing time by a formula that can be thought of as a weighted average of the Jerrum–Sinclair bound (where the average is taken over subsets of states with different sizes). Furthermore, instead of just the conductance, which in graph theory terms measures edge expansion, we also take into account node expansion. Our bound is related to the logarithmic Sobolev inequalities, but it appears to be more flexible and easier to compute. In the case of random walks in convex bodies, we show that this new bound is better than the known bounds for the worst case. This saves a factor of $O(n)$ in the mixing time bound, which is incurred in all proofs as a ‘penalty’ for a ‘bad start’. We show that in a convex body in $\mathbb{R}^n$, with diameter $D$, random walk with steps in a ball with radius $\delta$ mixes in $O^*(nD^2/\delta^2)$ time (if idle steps at the boundary are not counted). This gives an $O^*(n^3)$ sampling algorithm after appropriate preprocessing, improving the previous bound of $O^*(n^4)$. The application of the general conductance bound in the geometric setting depends on an improved isoperimetric inequality for convex bodies.
The phenomenon of micronutrient deficiency among children in China: a systematic review of the literature

Abstract Objective The present study aimed to review the literature on micronutrient deficiency and other factors influencing a deficiency status among children living in China. Design A systematic review was performed to analyse the literature. Setting Studies were identified through a search of PubMed and secondary references. Subjects Children living in China aged less than 18 years. Results Sixty-one articles were included. The prevalence of vitamin A deficiency decreased to approximately 10 % in 1995–2009. It increased with age but no significant difference was found between genders. The prevalence of thiamin and vitamin B12 deficiency was 10·5 % in Yunnan and 4·5 % in Chongqing provinces, respectively. Higher vitamin D deficiency rates were seen in spring and winter. The incidence of bleeding due to vitamin K deficiency was 3·3 % in 1998–2001 and more prevalent in rural areas. Both iodine deficiency and excess iodine intake were observed. Goitre rates were reported in Tibet, Jiangxi, Gansu and Hong Kong (3·5–46 %). Anaemia rates ranged from 20 % to 40 % in 2007–2011. High Se deficiency rates were found in Tibet, Shaanxi and Jiangsu. High Zn deficiency rates were also found (50–70 %) in 1995–2006. Few studies reported Ca deficiency rates (19·6–34·3 %). The degrees of deficiency for vitamin A, vitamin B12, Fe and Zn were more substantial in rural areas compared with urban areas. Conclusions The prevalence of micronutrient deficiency rates varied. Socio-economic status, environmental factors and the Chinese diet may influence micronutrient deficiency. Public health policies should consider implementing programmes of supplementation, food fortification and nutrition education to address these deficiencies among Chinese children.
Investigations of the thermal properties of human and animal tissues

The work presented in this thesis was carried as part of a project to improve the analysis of clinical data obtained by microwave thermography. For microwave thermography measurements to be usefully interpreted for detecting thermal anomalies in the human body at depths of up to several centimetres, the thermal and microwave dielectric properties of tissues must be known. This thesis is mainly concerned with the measurement and interpretation of the values of the thermal conductivity and diffusivity of human and animal tissues. The thermal properties of biological tissue are required, in conjunction with a bio-heat equation, to allow the formation of computational models to simulate the temperature distribution inside the human body. These computational models are also useful in the analysis of tomographic temperature measurements, and are essential to ensure accurate heating in hyperthermia. The Pennes conventional bio-heat equation has proven to be successful in analysing the data produced by microwave thermography. The thermal properties of biological soft tissue are dependant on the tissue water content. Water is a major constituent of most soft biological tissues, and it has a higher thermal conductivity and thermal diffusivity than any other constituent of biological tissue. The thermal properties of biological tissue can be modelled using a mixture equation, which describes the behaviour of a two phase system in terms of the thermal properties of the individual constituents and their relative volume fractions. This allows the variation of the thermal properties of biological tissue with water content to be analysed. A self-heating thermistor probe system was used in this study to measure the in-vitro thermal conductivity and thermal diffusivity of a wide variety of human and animal tissues. The system was calibrated using glycerol and agar-gelled water since the thermal behaviour of these materials and mixtures of these materials was well known. The calibration data was examined to determine the accuracy of the calibration and to determine if there was a relationship between the observed thermal conductivity and thermal diffusivity which was generated by the measurement system
Finite Element Analysis of an Adhesive Joint Using the Cohesive Zone Model and Surface Pattern Design of Bonding Surfaces

Adhesive joints have been widely used in the automotive and aerospace fields in order to reduce the weights of products. The strength of adhesive joints, accordingly, needs to be increased and their behaviour should be predicted in order to achieve accurate designs. Studies to improve the strength of adhesive joints via surface treatment methods or by using two adhesives with different mechanical properties have been conducted. Various modeling methods also have been studied to predict the behaviour of adhesive joints. Unfortunately, the relationship between the bonding surface roughness and adhesive joint strength needs to be further clarified in order to be applied in practical design. As analyzing the relationship through a conventional finite element method assuming perfect bonding is challenging, the behaviour of the adhesive joints may be analyzed using a cohesive zone model or interface modeling methods from an integrating released energy point of view. The strength of adhesive joints can be improved via micro-patterning due to the mechanical interlocking effect. Therefore, in this study, a micro-pattern was fabricated to improve the strength of adhesive joints. Various pattern-sized single leg bending joints and end notched flexure joints were manufactured and experimented upon. In this study, characteristics of each pattern surface were independently classified and modeled with a cohesive zone model. Finite element analyses were then performed and simulation results were compared with experimental results. The numerical results satisfactorily describe the experimental results, and failure loads were predicted with a maximum relative error of 8%. From these results, it may be concluded that the present findings can be applied to practical design and that the failure load can be predicted via a finite element analysis.
Taming context-sensitive languages with principled stateful parsing

Historically, true context-sensitive parsing has seldom been applied to programming languages, due to its inherent complexity. However, many mainstream programming and markup languages (C, Haskell, Python, XML, and more) possess context-sensitive features. These features are traditionally handled with ad-hoc code (e.g., custom lexers), outside of the scope of parsing theory. Current grammar formalisms struggle to express context-sensitive features. Most solutions lack context transparency: they make grammars hard to write, maintain and compose by hardwiring context through the entire grammar. Instead, we approach context-sensitive parsing through the idea that parsers may recall previously matched input (or data derived therefrom) in order to make parsing decisions. We make use of mutable parse state to enable this form of recall. We introduce principled stateful parsing as a new transactional discipline that makes state changes transparent to parsing mechanisms such as backtracking and memoization. To enforce this discipline, users specify parsers using formally specified primitive state manipulation operations. Our solution is available as a parsing library named Autumn. We illustrate our solution by implementing some practical context-sensitive grammar features such as significant whitespace handling and namespace classification.