Miracle-dz/UniFAR-FTUs huggingface dataset:
Metal-Insulator Transition in Disordered Two-Dimensional Electron Systems

We present a theory of the metal-insulator transition in a disordered two-dimensional electron gas. A quantum critical point, separating the metallic phase, which is stabilized by electronic interactions, from the insulating phase, where disorder prevails over the electronic interactions, has been identified. The existence of the quantum critical point leads to a divergence in the density of states of the underlying collective modes at the transition, causing the thermodynamic properties to behave critically as the transition is approached. We show that the interplay of electron-electron interactions and disorder can explain the observed transport properties and the anomalous enhancement of the spin susceptibility near the metal-insulator transition.
Sveriges Riksbank Working Paper Series Populism

In their pursuit of being elected, politicians might not provide their constituents with independent viewpoints, but just try to outguess popular opinion. Although rational voters see through such populism, candidates can not resist resorting to it when the spoils of office are too large. For an intermediate parameter range, both populism and its opposite, “candor”, can be sustained as equilibria. This means that the public’s trust or distrust in politicians may be self-fulfilling prophecies. Importantly, the more informed politicians are about public opinion, the more likely it is that populist behavior can be avoided.
WHY WORRY? IMPACTS ON THE QUANTITIES AND QUALITIES OF WORRY: AN EXAMINATION OF FAITH, MEANING, AND NEED SATISFACTION

x Chapter 1: Problem Statement . 1 Chapter 2: Literature Review . 3 The Construct of Worry . 3 Worry and its Role in Development . 12 The Measurement of Worry . 15 Faith and Worry . 17 The Construct of Faith . 21 Fowler’s (1981) Stages of Faith . 26 Faith Development Measurement Issues . 32 Meaning in Life . 34 Self-Determination Theory (SDT) . 38 Integration of the constructs relationship to worry: Faith stage development, Self Determination, and Meaning in Life . 44 Purpose . 52 Hypotheses and research questions . 54 Chapter 3: Methods . 60 Participants and Procedure. 60 Participants . 60
ML approach to radial acceleration estimation and CRLB computation

The paper analyzes a method to estimate radial acceleration jointly to other target parameters (i.e.: ρ̇ and A). The estimator performance has been analyzed in case of one burst and M burst, in both analytical and simulated ways. To have an exploitable estimate of ρ̈ an accuracy of at least 10 m/s2 is needed. To achieve this level of accuracy very high SNR is needed.
Random Indexing Re-Hashed

This paper introduces a modified version of Random Indexing, a technique for dimensionality reduction based on random projections. We here describe how RI can be efficiently implemented using the notion of universal hashing. This eliminates the need to store any random vectors, replacing them instead with a small number of hash-functions, thereby dramatically reducing the memory footprint. We dub this reformulated version of the method Hashed Random Indexing (HRI).
Effects of Thermal Mass, Window Size, and Night-Time Ventilation on Peak Indoor Air Temperature in the Warm-Humid Climate of Ghana

Most office buildings in the warm-humid sub-Saharan countries experience high cooling load because of the predominant use of sandcrete blocks which are of low thermal mass in construction and extensive use of glazing. Relatively, low night-time temperatures are not harnessed in cooling buildings because office openings remain closed after work hours. An optimization was performed through a sensitivity analysis-based simulation, using the Energy Plus (E+) simulation software to assess the effects of thermal mass, window size, and night ventilation on peak indoor air temperature (PIAT). An experimental system was designed based on the features of the most promising simulation model, constructed and monitored, and the experimental data used to validate the simulation model. The results show that an optimization of thermal mass and window size coupled with activation of night-time ventilation provides a synergistic effect to obtain reduced peak indoor air temperature. An expression that predicts, indoor maximum temperature has been derived for models of various thermal masses.
Pedagogical transitions among science teachers: how does context intersect with teacher beliefs?

Abstract This paper examines attitudes to pedagogical change, among teachers within a second level science department in Ireland. It explores the beliefs and contextual constraints that mediate diversification from a primarily didactic pedagogical approach towards more student-led pedagogies. Using a multi-method approach incorporating observations of teaching, focus group interviews, one to one interviews and open-ended questionnaires, findings were analysed inductively to generate a number of themes. The findings suggest that a teacher’s sense of identity and beliefs are significant influences on their predisposition towards pedagogical change. Interestingly, the middle class, academic context of the school and the terminal Leaving Certificate state examination, were both identified as latent contextual barriers to pedagogical change. The implementation of curricular reform at Junior Cycle level in Ireland is ongoing, with a new science specification in place since September 2016. This specification has a significant student-led and skill-based emphasis and varied pedagogical approaches are necessary to effectively deliver this new curriculum. Professional development is available to assist teachers with the curricular reform. However, findings in this paper suggest that intrinsic beliefs and contextual constraints may limit access to, or meaningful engagement with such training, negating pedagogical change for some teachers and their students.
The Theory of Incentives Applied to the Transport Sector

Building upon Iossa and Martimort (2008), we study the main incentive issues and the form of optimal contracts for Public Private Partnerships (PPPs) in transports. We present a basic model of procurement in a multitask environment in which a risk-averse firm chooses unobservable efforts in infrastructure and service quality. We begin by analyzing the effect on incentives and risk transfer of bundling building and operation into a single contract. We consider the factors that affect the optimal allocation of demand risk and their implications for the choice of contract length. We discuss the dynamics of PPP contracts and how the risk of regulatory opportunism affects contract design and incentives.
Gravitational lensing effects on high-redshift Type II supernova studies with the Next Generation Space Telescope

We derive the expected Type II supernova (SN) differential number counts, N(m), and Hubble diagram for SCDM and LCDM cosmological models, taking into account the effects of gravitational lensing (GL) produced by the intervening cosmological mass. The mass distribution of dark matter haloes (i.e. the lenses) is obtained by means of a Monte Carlo method applied to the Press–Schechter mass function. The haloes are assumed to have a Navarro, Frenk & White (NFW) density profile, in agreement with recent simulations of hierarchical cosmological models. Up to z=15, the (SCDM, LCDM) models predict a total number of (857, 3656) SNII yr−1 in 100 surveyed 4×4 arcmin2 fields of the Next Generation Space Telescope (NGST). NGST will be able to reach the peak of the N(m) curve, located at AB≈30(31) for SCDM (LCDM) in J and K wavelength bands, and detect (75 per cent, 51 per cent) of the above SN events. This will allow a detailed study of the early cosmic star formation history, as traced by SNIIe. N(m) is only very mildly affected by the inclusion of lensing effects. In addition, GL introduces a moderate uncertainty in the determination of cosmological parameters from Hubble diagrams, when these are pushed to higher z. For example, for a ‘true’ LCDM with (ΩM=0.4, ΩΛ=0.6), without proper account of GL, one would instead derive We briefly compare our results with previous similar work and discuss the limitations of the model.
Prediction of Bond Between Steel and Concrete by Numerical Analysis

This paper presents the results of subtask dealing with the bond behavior study of the reinforcement systems under monotonic loading pull-out tests. This numerical method is based on the slip and the bond stress distributions through the anchored length of the bar in the concrete block. The work refers, especially to the implementation of rein- forcing bars and bond-slip models between steel and concrete in the developed finite element program. For the application of the proposed method, three analytical expressions of bond-slip relationship are selected. The obtained results are pre- sented and commented with the fundamental characteristics of plain concrete and reinforced concrete members. The bond models in contribution with concrete and reinforcing steel provide a relativity good representation of bond-zone system responses.
A species‐level model for metabolic scaling of trees II. Testing in a ring‐ and diffuse‐porous species

Summary 1. A 17-parameter ‘species model’ that predicts metabolic scaling from vascular architecture was tested in a diffuse-porous maple (Acer grandidentatum) and a ring-porous oak (Quercus gambelii). Predictions of midday water transport (Q) and its scaling with above-ground mass (M) were compared with empirical measurements. We also tested the assumption that Q was proportional to the biomass growth rate of the shoot (G). 2. Water transport and biomass growth rate were measured on 18 trees per species that spanned a broad range in trunk diameter (4–26 cm). Where possible, the same trees were used for obtaining the 17 model parameters that concern external branching, internal xylem conduit anatomy, and soil-to-canopy sap pressure drop. 3. The model succeeded in predicting the Q by M b scaling exponent, b, being within 8% (maple) and 6% (oak) of measured exponents from sap flow data. In terms of absolute Q, the model was better in maple (16% Q overestimate) than oak (128% overestimate). The overestimation of Q was consistent with the model not accounting for cavitation, which is reportedly more prevalent in oak than in maple at the study site. 4. The modelled and measured Q by M b exponents averaged within 3·6% of the measured G by M b exponents, supporting the assumption that G / Q 1 . The average b exponent was 0·62 ± 0·016 (mean ± SE) across species, rejecting b =0 ·75 for intraspecific scaling. 5. The performance of this species model, both for scaling purposes as well as for predicting rates of water consumption within and between species, argues for its further refinement and wider application in ecology and ecosystem biology.
TopicViz: Semantic Navigation of Document Collections

When people explore and manage information, they think in terms of topics and themes. However, the software that supports information exploration sees text at only the surface level. In this paper we show how topic modeling -- a technique for identifying latent themes across large collections of documents -- can support semantic exploration. We present TopicViz, an interactive environment for information exploration. TopicViz combines traditional search and citation-graph functionality with a range of novel interactive visualizations, centered around a force-directed layout that links documents to the latent themes discovered by the topic model. We describe several use scenarios in which TopicViz supports rapid sensemaking on large document collections.
For Personal Use. Only Reproduce with Permission from Elsevier Ltd. Brain Function after Severe Brain Damage Brain Function in Coma, Vegetative State, and Related Disorders

We review the nosological criteria and functional neuroanatomical basis for brain death, coma, vegetative state, minimally conscious state, and the locked-in state. Functional neuro-imaging is providing new insights into cerebral activity in patients with severe brain damage. Measurements of cer-ebral metabolism and brain activations in response to sensory stimuli with PET, fMRI, and electrophysiological methods can provide information on the presence, degree, and location of any residual brain function. However, use of these techniques in people with severe brain damage is methodologically complex and needs careful quantitative analysis and interpretation. In addition, ethical frameworks to guide research in these patients must be further developed. At present, clinical examinations identify nosological distinctions needed for accurate diagnosis and prognosis. Neuroimaging techniques remain important tools for clinical research that will extend our understanding of the underlying mechanisms of these disorders. An accurate and reliable assessment of the arousal and awareness of consciousness in patients with severe brain damage is of greatest importance for their management. Progress in intensive care has led to an increase in the number of patients who survive severe acute brain damage. Although most of these patients recover from coma within the first days after the injury, some permanently lose all brainstem function (brain death), whereas others progress to " wakeful unawareness " (vegetative state). Those who recover typically progress through different stages before fully or partly recovering consciousness (minimally conscious state; figure 1). Clinical practice has shown the challenges of identifying signs of these patients' conscious perception of the environment and of themselves. Misdiagnoses of vegetative state, minimally conscious state, and locked-in syndrome are common. 1–6 Bedside assessment of residual brain function in patients who are severely brain-damaged is difficult because motor responses may be very limited or inconsistent. In addition, consciousness is not an all-or-nothing phenomenon 7 and its clinical assessment relies on inferences made from responses to external stimuli that are observed at the time of the examination. 8 In this review we will first define bedside assessment of consciousness. We review the main clinical notions of altered states of consciousness after severe brain damage. Finally, we discuss recent functional neuroimaging findings in patients with these disorders, with a special emphasis on patients in a vegetative state. Acute brain injury Coma Locked-in syndrome Vegetative state Chronic coma (very rare) Brain death Death Minimally conscious state Permanent vegetative state (>3 months if non-traumatic, >1 year if traumatic) Confusional …
Serum Levels of the Inflammatory Cytokines in Patients with Lumbar Radicular Pain Due to Disc Herniation

Study Design Cohort study. Purpose This study primarily aimed to evaluate the serum levels of tumor necrosis factor-alpha (TNF-α) and interleukin (IL)-4 in patients with lumbar radiculopathy 1 and 12 months after microdiscectomy. Overview of Literature Lumbar radiculopathy is possibly caused by inflammatory changes in the nerve root. The intraneural application of pro-inflammatory cytokines induces behavioral signs associated with pain. Anti-inflammatory cytokine treatment effectively reduces hyperalgesia. Methods The role of TNF-α and IL-4 in long-lasting lumbar radiculopathy was addressed. A total of 262 patients were recruited from Anqing Hospital, Anhui Medical University. During inclusion at 1 and 12 months, serum concentrations of TNF-α and IL-4 were analyzed by enzyme-linked immunosorbent assay, and pain intensity was reported on a 0–10 cm visual analog scale (VAS). Results Sixty six patients had VAS <3 and 196 patients had VAS ≥3. Serum concentrations of pro-inflammatory TNF-α and anti-inflammatory IL-4 in patients with lumbar radiculopathy related to disc herniation were measured at 1- and 12-month follow-up. TNF-α decreased in both VAS groups with time. In contrast, IL-4 increased in both groups at 1 month and then decreased gradually until month 12. The changes in serum levels of TNF-α and IL-4 over time between the VAS ≥3 and VAS <3 groups were significantly different. Conclusions Chronic lumbar radiculopathy may be associated with high level of pro-inflammatory substances, such as TNF-α, in serum after disc herniation, and elevated anti-inflammatory cytokine in patients with lumbar radiculopathy may indicate a favorable outcome.
Junior High School Students’ Understanding and Problem Solving Skills on the Topics of Line and Angles

Line and angles is important topics to learn to develop the geometry skills and also mathematics skills such as understanding and problem solving skills. But, the fact was given by Indonesian researcher show that Indonesian students’ understanding and problem solving skills still low in this topics. This fact be a background to investigate students’ understanding and problem solving skills in line and angles topics. To investigate these skills, this study used descriptive-qualitative approach. Individual written test (essay) and interview was used in this study. 72 students grade 8th from one of Junior High School in Lembang, worked the written test and 18 of them were interviewed. Based on result, almost of student were have a good instrumental understanding in line and angles topic in same area, but almost all student have a low instrumental understanding in line and angles topic in different area. Almost all student have a low relational understanding. Also, almost all student have a low problem solving skills especially in make and use strategy to solve the problem and looking back their answer. Based on result there is need a meaningfulness learning strategy, which can make students build their understanding and develop their problem solving skill independently.
Enhanced Security using Hybrid Encryption Algorithm

Information Security plays a major role in today’s scenario. Cloud computing is a technology that provides access to information and computing resources from anywhere that a network is available. There is a need to secure the data stored on cloud. The main goal behind the design of encryption algorithm must be security against unauthorized attacks. However, for all cloud computing applications, performance and cost of implementation are also major concerns. Encryption algorithm would not be of much use if it is very much secure but slow in performance. The security and performance of encryption algorithms must be balanced. In this paper, encryption algorithms (AES, Blowfish, Twofish) has been discussed to analyze the performance level of each algorithm.
Collective Learning and Optimal Consensus Decisions in Social Animal Groups

Learning has been studied extensively in the context of isolated individuals. However, many organisms are social and consequently make decisions both individually and as part of a collective. Reaching consensus necessarily means that a single option is chosen by the group, even when there are dissenting opinions. This decision-making process decouples the otherwise direct relationship between animals' preferences and their experiences (the outcomes of decisions). Instead, because an individual's learned preferences influence what others experience, and therefore learn about, collective decisions couple the learning processes between social organisms. This introduces a new, and previously unexplored, dynamical relationship between preference, action, experience and learning. Here we model collective learning within animal groups that make consensus decisions. We reveal how learning as part of a collective results in behavior that is fundamentally different from that learned in isolation, allowing grouping organisms to spontaneously (and indirectly) detect correlations between group members' observations of environmental cues, adjust strategy as a function of changing group size (even if that group size is not known to the individual), and achieve a decision accuracy that is very close to that which is provably optimal, regardless of environmental contingencies. Because these properties make minimal cognitive demands on individuals, collective learning, and the capabilities it affords, may be widespread among group-living organisms. Our work emphasizes the importance and need for theoretical and experimental work that considers the mechanism and consequences of learning in a social context.
Efficient SKIP Mode Detection for Coarse Grain Quality Scalable Video Coding

Scalable video coding (SVC) was recently standardized by the Joint Video Team as an extension of H.264. In SVC, a computationally expensive exhaustive mode decision is employed to select the best coding mode for each macroblock (MB), which achieves a high coding efficiency. In order to reduce computational complexity, we propose an efficient SKIP mode detection approach for coarse grain quality SVC. It makes use of the coding information of spatial neighboring MBs and the co-located MB in base layer to predict the SKIP mode MB and early terminate its mode decision procedure. Experimental results show that the proposed early SKIP mode decision approach can achieve the average computational saving about 54% with almost no loss of rate distortion (RD) performance in the enhancement layer.
Non-Linear Merging Strategies for Merge-and-Shrink Based on Variable Interactions

Merge-and-shrink is a general method for deriving accurate abstraction heuristics.We present two novel nonlinear merging strategies, UMC and MIASM, based on variable interaction. The principle underlying our methods is to merge strongly interacting variables early on. UMC measures variable interaction by weighted causal graph edges, and MIASM measures variable interaction in terms of the number of necessary states in the abstract space defined by the variables. The methods partition variables into clusters in which the variable interactions are strong, and merge variables within each cluster before merging the clusters. Experiment results show that our merging strategies outperform existing merging strategies in general and can produce heuristics that give perfect guidance for solving tasks that previous methods cannot even solve.
A method for semi-automatic grading of human blastocyst microscope images.

BACKGROUND The precise assessment of embryo viability is an extremely important factor for the optimization of IVF treatments. In order to assess embryo viability, several embryo scoring systems have been developed. However, they rely mostly on a subjective visual analysis of embryo morphological features and thus are subject to inter- and intra-observer variation. In this paper, we propose a method for image segmentation (the dividing of an image into its meaningful constituent regions) and classification of human blastocyst images with the aim of automating embryo grading. METHODS The delineation of the boundaries (segmentation) of the zona pellucida, trophectoderm (TE) and inner cell mass (ICM) were performed using advanced image analysis techniques (level set, phase congruency and fitting of ellipse methods). The fractal dimension and mean thickness of TE and ICM image texture descriptors (texture spectrum and grey-level run lengths) were calculated to characterize the main morphological features of the blastocyst with the aim of automatic grading using Support Vector Machine classifiers. RESULTS The fractal dimension calculated from the delineated TE boundary provided a good indication of cell number (presented a 0.81 Pearson correlation coefficient with the number of cells), a feature closely associated with blastocyst quality. The classifiers showed different accuracy levels for each grade. They presented accuracy ranges from 0.67 to 0.92 for the embryo development classification, 0.67-0.82 for the ICM classification and 0.53-0.92 for the TE classification. The value 0.92 was the highest accuracy achieved in the tests with 73 blastocysts. CONCLUSIONS Semi-automatic grading of human blastocysts by a computer is feasible and may offer a more precise comparison of embryos, reducing subjectivity and allowing embryos with apparently identical morphological scores to be distinguished.