Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation Measures for Ordinal Regression

Ordinal regression (OR -- also known as ordinal classification) has received increasing attention in recent times, due to its importance in IR applications such as learning to rank and product review rating. However, research has not paid attention to the fact that typical applications of OR often involve datasets that are highly imbalanced. An imbalanced dataset has the consequence that, when testing a system with an evaluation measure conceived for balanced datasets, a trivial system assigning all items to a single class (typically, the majority class) may even outperform genuinely engineered systems. Moreover, if this evaluation measure is used for parameter optimization, a parameter choice may result that makes the system behave very much like a trivial system. In order to avoid this, evaluation measures that can handle imbalance must be used. We propose a simple way to turn standard measures for OR into ones robust to imbalance. We also show that, once used on balanced datasets, the two versions of each measure coincide, and therefore argue that our measures should become the standard choice for OR.
Evidence of Cloud Disruption in the L/T Dwarf Transition

Clouds of metal-bearing condensates play a critical role in shaping the emergent spectral energy distributions of the coolest classes of low-mass stars and brown dwarfs, L and T dwarfs. Because condensate clouds in planetary atmospheres show distinct horizontal structure, we have explored a model for partly cloudy atmospheres in brown dwarfs. Our model successfully reproduces the colors and magnitudes of both L and T dwarfs for the first time, including the unexpected brightening of the early- and mid-type T dwarfs at the J band, provided that clouds are rapidly removed from the photosphere at Teff ≈ 1200 K. The clearing of cloud layers also explains the surprising persistence and strengthening of gaseous FeH bands in early- and mid-type T dwarfs. The breakup of cloud layers is likely driven by convection in the troposphere, analogous to phenomena observed on Jupiter. Our results demonstrate that planetary-like atmospheric dynamics must be considered when examining the evolution of free-floating brown dwarfs.
Relevance feedback approach for image retrieval combining support vector machines and adapted Gaussian mixture models

A new relevance feedback (RF) approach for content-based image retrieval (CBIR) is presented, which uses Gaussian mixture (GM) models as image representations. The GM of each image is obtained as an adaptation of a universal GM which models the probability distribution of the features of the image database. In each RF round, the positive and negative examples provided by the user until the current round are used to train a support vector machine (SVM) to distinguish between the relevant and irrelevant images according to the preferences of the user. In order to quantify the similarity between two images represented as GMs, Kullback–Leibler (KL) approximations are employed, the computation of which can be further accelerated taking advantage from the fact that the GMs of the images are all refined from a common model. An appropriate kernel function, based on this distance between GMs, is used to make possible the incorporation of GMs in the SVM framework. Finally, comparative numerical experiments that demonstrate the merits of the proposed RF methodology and the advantages of using GMs for image modelling are provided.
Substrate Envelope and Drug Resistance: Crystal Structure of RO1 in Complex with Wild-Type Human Immunodeficiency Virus Type 1 Protease

ABSTRACT In our previous crystallographic studies of human immunodeficiency virus type 1 (HIV-1) protease-substrate complexes, we described a conserved “envelope” that appears to be important for substrate recognition and the selection of drug-resistant mutations. In this study, the complex of HIV-1 protease with the inhibitor RO1 was determined and comparison with the substrate envelope provides a rationale for mutational patterns.
Maximally supersymmetric string theories in D<10.

The existence of maximally supersymmetric solutions to heterotic string theory that are not toroidal compactifications of the ten-dimensional superstring is established. We construct an exact fermionic realization of an $N\phantom{\rule{0ex}{0ex}}=\phantom{\rule{0ex}{0ex}}1$ supersymmetric string theory in $D\phantom{\rule{0ex}{0ex}}=\phantom{\rule{0ex}{0ex}}8$ with non-simply-laced gauge group $\mathrm{Sp}(20)$. Toroidal compactification to six and four dimensions gives maximally extended supersymmetric theories with reduced rank $(4,12)$ and $(6,14)$, respectively.
Applications of Operator Theory to Time- Frequency Analysis and Classification

Jack McLaughlin and Les E. Atlas Interactive Systems Design Laboratory, Department of Electrical Engineering University of Washington, Box 352500, Seattle, WA 98195-2500, U.S.A. jackm| les@isdl.ee. washington.edu phone: (206) 6851315 (Atlas) EDICS # SP 2.3. 1 Abstract— An entirely new set of criteria for the design of kernels (generating functions) for time-frequency representations (TFRs) is presented. These criteria aim only to produce kernels (and thus, TFRs) which will enable more accurate classification. We refer to these kernels, which are optimized to discriminate among several classes of signals, as signal class dependent kernels , or simply class dependent kernels .
Determinants and timing of dropping out decisions: evidence from the UK FE sector

This paper investigates whether the hazard of dropping out for both male and female students changes over the duration of study. Using duration modelling techniques wend a certain degree of non-monotonic duration dependence for both males and females. However this pattern for female students aiming at high level qualifications is sensitive to attempts to control for unobserved heterogeneity. For these students the extended models show a flattened hazard function, suggesting that the hazard is basically constant over time. For males introducing controls for unobserved heterogeneity does not change the pattern of the duration dependence, suggesting that they might be at higher risk of dropping out during the first semester of their studies. In addition, we examine variations in drop out hazard patterns for students enrolled on courses which confer different qualification levels. We provide evidence of distinct hazard patterns between students pursuing 'high level' and 'low level' qualifications.
Costs of the Metabolic Syndrome in Elderly Individuals

OBJECTIVE—The cardiovascular consequences of the metabolic syndrome and its component risk factors have been documented in elderly individuals. Little is known about how the metabolic syndrome and its individual components translate into long-term medical costs. RESEARCH DESIGN AND METHODS—We used log-linear regression models to assess the independent contributions of the metabolic syndrome and its individual components to 10-year medical costs among 3,789 individuals aged ≥65 years in the Cardiovascular Health Study. RESULTS—As defined by the National Cholesterol Education Program Third Adult Treatment Panel report, the metabolic syndrome was present in 47% of the sample. Total costs to Medicare were 20% higher among participants with the metabolic syndrome ($40,873 vs. $33,010; P < 0.001). Controlling for age, sex, race/ethnicity, and other covariates, we found that abdominal obesity, low HDL cholesterol, and elevated blood pressure were associated with 15% (95% CI 4.3–26.7), 16% (1.7–31.8), and 20% (10.1–31.7) higher costs, respectively. When added to the model, the metabolic syndrome composite variable did not contribute significantly (P = 0.32). CONCLUSIONS—Abdominal obesity, low HDL cholesterol, and hypertension but not the metabolic syndrome per se are important predictors of long-term costs in the Medicare population.
Profil Kekuatan Karakter dan Kebajikan pada Mahasiswa Berprestasi

Basically each person has different character strength in achieving the goal expected. The character strength becomes a typical structure of an individual's personality that distinguishes itself from the others. Individuals with high achievement motivation will attempt to set a specific goal, using some strategic measurements, highly will-power, and always worked hard. This study aimed to explore the character strength of students who are excellence in academic. The method used mix method which are combine both quantitative and qualitative approaches. The numbers of subjects in this study were 30 students from 9 faculties in UIN Sunan Gunung Djati whom selected based on the highest GPA score. The character strength had seen from the individually measurements results of the Values in Action-Inventory strenghts (VIA-IS) which consists of 240 items in the form of scale Likert. Interviews with subjects than have been conducted to gained more information related to the character strength of them. The results has showed that a strength of character typical of the outstanding students, namely Hope, Perseverance, and Spirituality.
Newton Algorithms for Riemannian Distance Related Problems on Connected Locally Symmetric Manifolds

The squared distance function is one of the standard functions on which an optimization algorithm is commonly run, whether it is used directly or chained with other functions. Illustrative examples include center of mass computation, implementation of k-means algorithm and robot positioning. This function can have a simple expression (as in the Euclidean case), or it might not even have a closed form expression. Nonetheless, when used in an optimization problem formulated on non-Euclidean manifolds, the appropriate (intrinsic) version must be used and depending on the algorithm, its gradient and/or Hessian must be computed. For many commonly used manifolds a way to compute the intrinsic distance is available as well as its gradient, the Hessian however is usually a much more involved process, rendering Newton methods unusable on many standard manifolds. This article presents a way of computing the Hessian on connected locally-symmetric spaces on which standard Riemannian operations are known (exponential map, logarithm map and curvature). Although not a requirement for the result, describing the manifold as naturally reductive homogeneous spaces, a special class of manifolds, provides a way of computing these functions. The main example focused in this article is centroid computation of a finite constellation of points on connected locally symmetric manifolds since it is directly formulated as an intrinsic squared distance optimization problem. Simulation results shown here confirm the quadratic convergence rate of a Newton algorithm on commonly used manifolds such as the sphere, special orthogonal group, special Euclidean group, symmetric positive definite matrices, Grassmann manifold and projective space.
Augmenting RRT-planners with local trees

During the last few years, Rapidly-exploring Random Trees, RRTs, has been recognized as a very useful tool for designing efficient single-shot path planners. Another benefit is that RRTs can easily handle planning problems involving non-holonomic systems. However, it has also been noted that the narrow passage problem can become even more severe compared to other randomized methods. To reduce that problem, we suggest augmenting RRT-planners with local trees. Furthermore, using local trees, the planner is able to explore several difficult regions in parallel, something that has proved to be very effective for problems where the solution trajectory repeatedly has to pass difficult regions. We present powerful heuristics for when to create such trees and how often they should be allowed to grow, such that the RRT-planner will improve its qualities as an efficient single-shot path planner. The resulting algorithm, RRTLocTrees, is implemented in a newly developed object-oriented framework for path planning and tested on four different path planning problems, with excellent results.
A Stochastic Newton MCMC Method for Large-Scale Statistical Inverse Problems with Application to Seismic Inversion

We address the solution of large-scale statistical inverse problems in the framework of Bayesian inference. The Markov chain Monte Carlo (MCMC) method is the most popular approach for sampling the posterior probability distribution that describes the solution of the statistical inverse problem. MCMC methods face two central difficulties when applied to large-scale inverse problems: first, the forward models (typically in the form of partial differential equations) that map uncertain parameters to observable quantities make the evaluation of the probability density at any point in parameter space very expensive; and second, the high-dimensional parameter spaces that arise upon discretization of infinite-dimensional parameter fields make the exploration of the probability density function prohibitive. The challenge for MCMC methods is to construct proposal functions that simultaneously provide a good approximation of the target density while being inexpensive to manipulate. Here we present a so-called Stoch.
An Abbreviated Protocol for In Vitro Generation of Functional Human Embryonic Stem Cell-Derived Beta-Like Cells

The ability to yield glucose-responsive pancreatic beta-cells from human pluripotent stem cells in vitro will facilitate the development of the cell replacement therapies for the treatment of Type 1 Diabetes. Here, through the sequential in vitro targeting of selected signaling pathways, we have developed an abbreviated five-stage protocol (25–30 days) to generate human Embryonic Stem Cell-Derived Beta-like Cells (ES-DBCs). We showed that Geltrex, as an extracellular matrix, could support the generation of ES-DBCs more efficiently than that of the previously described culture systems. The activation of FGF and Retinoic Acid along with the inhibition of BMP, SHH and TGF-beta led to the generation of 75% NKX6.1+/NGN3+ Endocrine Progenitors. The inhibition of Notch and tyrosine kinase receptor AXL, and the treatment with Exendin-4 and T3 in the final stage resulted in 35% mono-hormonal insulin positive cells, 1% insulin and glucagon positive cells and 30% insulin and NKX6.1 co-expressing cells. Functionally, ES-DBCs were responsive to high glucose in static incubation and perifusion studies, and could secrete insulin in response to successive glucose stimulations. Mitochondrial metabolic flux analyses using Seahorse demonstrated that the ES-DBCs could efficiently metabolize glucose and generate intracellular signals to trigger insulin secretion. In conclusion, targeting selected signaling pathways for 25–30 days was sufficient to generate ES-DBCs in vitro. The ability of ES-DBCs to secrete insulin in response to glucose renders them a promising model for the in vitro screening of drugs, small molecules or genes that may have potential to influence beta-cell function.
Visualization using timelines

A timeline is a linear, graphical visualization of events over time. For example, in concurrent application, events would represent state changes for some system object (such as a task or variable). A timeline display generator creates the graphical visualization from some record of events. This paper reports on a model for timeline display generators based on a formal model of event history and the objectives of timeline visualization. In this model, any timeline display generator is completely described through the definition of a set of mathematical functions. The exact characteristics and flexibility of a particular implementation of a timeline display generator, depends on the way in which these functions have been implemented. The current prototype, xtg, (Timeline Display Generator for X-windows) serves as an example implementation of these ideas. Characteristics of xtg are presented, and its use in the analysis of a real-world client-server application is discussed. Xtg has been applied to several other applications to-date and is being applied by several telecommunications companies to areas ranging from software process analysis to call trace data analysis.
Latent Heating and Mixing due to Entrainment in Tropical Deep Convection

AbstractRecent studies have noted the role of latent heating above the freezing level in reconciling Riehl and Malkus' hot tower hypothesis (HTH) with evidence of diluted tropical deep convective cores. This study evaluates recent modifications to the HTH through Lagrangian trajectory analysis of deep convective cores in an idealized, high-resolution cloud-resolving model (CRM) simulation that uses a sophisticated two-moment microphysical scheme. A line of tropical convective cells develops within a finer nested grid whose boundary conditions are obtained from a large-domain CRM simulation approaching radiative convective equilibrium (RCE). Microphysical impacts on latent heating and equivalent potential temperature (θe) are analyzed along trajectories ascending within convective regions of the high-resolution nested grid. Changes in θe along backward trajectories are partitioned into contributions from latent heating due to ice processes and a residual term that is shown to be an approximate representati.
The Many Dimensions of Gender Equality and Their Impact on Economic Growth

Abstract This study explores the multidimensional nature of gender equality and its influence on economic growth across 64 countries from 2000–2011 using an endogenous growth model. After controlling for standard growth correlates, the empirical results show that countries that protect the economic rights of women experience higher real GDP per capita growth rates. Furthermore, after controlling for a country’s religious affiliation, the importance of religion to the lives of people living in a country had a negative influence on economic growth. Intensely held religious beliefs are strongly correlated with gender inequitable views. These attitudes might serve as an important channel through which these gender biases are institutionalized in economic practices and act to slow economic growth.
Dialectical behaviour therapy for adults with intellectual disabilities

This thesis explores the use of adapted Dialectical Behaviour Therapy (DBT) with individuals with Intellectual and Developmental Disabilities (ID/D). DBT is a multi-modal psychological intervention that aims to increase skills in interpersonal effectiveness, distress tolerance, emotional regulation and mindfulness. It was initially developed for individuals who presented with parasuicidal behaviours, and is recommended for the treatment of Borderline Personality Disorder (BPD). This thesis is presented in five papers; a systematic literature review, three empirical papers (a, b &c), and a critical review and reflection of the research process.The systematic literature review provides a narrative review of published research regarding the adaptations and outcomes of DBT for individuals with ID/D. Seven studies were reviewed using the Evaluative Method for Determining Evidence Based Practice (EBP) (Reichow, 2011). The findings detail the adaptations, results and critical appraisal of the research to date.The empirical papers consider the outcomes of adults with ID/D who received adapted DBT in a community psychological therapies service. The papers present different methodologies, and combined produce a consilience of evidence regarding the suitability of DBT for this population. Paper 2a found significant reductions on measures of depression, anxiety and anger, and increased mindfulness skills amongst 18 participants following DBT. Paper 2b uses repertory grid technique to explore the psychological changes that occur following DBT for seven participants, and found overall changes in personal construing and improvements in self-esteem. Paper 2c considers the psychological changes that occur in further depth through the presentation of two case studies. The case studies consider the complexity and idiosyncrasy of the individuals and gives consideration to the use of repertory grids to identify implicative dilemmas as part of clinical assessments.The final paper provides a critical review with personal reflections of the thesis. The author considers the research and clinical implications of the study.
Hierarchical Bayesian Analysis of Biased Beliefs and Distributional Other-Regarding Preferences

This study investigates the relationship between an actor's beliefs about others' other-regarding (social) preferences and her own other-regarding preferences, using an "avant-garde" hierarchical Bayesian method. We estimate two distributional other-regarding preference parameters, and , of actors using incentivized choice data in binary Dictator Games. Simultaneously, we estimate the distribution of actors' beliefs about others' and , conditional on actors' own and , with incentivized belief elicitation. We demonstrate the benefits of the Bayesian method compared to it's hierarchical frequentist counterparts. Results show a positive association between an actor's own (; ) and her beliefs about average (; ) in the population. The association between own preferences and the variance in beliefs about others' preferences in the population, however, is curvilinear for and insignificant for . These results are partially consistent with the cone effect (1,2) which is described in detail below. Because in the Bayesian-Nash equilibrium concept, beliefs and own preferences are assumed to be independent, these results cast doubt on the application of the Bayesian-Nash equilibrium concept to experimental data.