Miracle-dz/UniFAR-FTUs huggingface dataset:
Brier Curves: a New Cost-Based Visualisation of Classifier Performance

It is often necessary to evaluate classifier performance over a range of operating conditions, rather than as a point estimate. This is typically assessed through the construction of 'curves' over a 'space', visualising how one or two performance metrics vary with the operating condition. For binary classifiers in particular, cost space is a natural way of showing this range of performance, visualising loss against operating condition. However, the curves which have been traditionally drawn in cost space, known as cost curves, show the optimal loss, and hence assume knowledge of the optimal decision threshold for a given operating condition. Clearly, this leads to an optimistic assessment of classifier performance. In this paper we propose a more natural way of visualising classifier performance in cost space, which is to plot probabilistic loss on the y-axis, i.e., the loss arising from the probability estimates. This new curve provides new ways of understanding classifier performance and new tools to compare classifiers. In addition, we show that the area under this curve is exactly the Brier score, one of the most popular performance metrics for probabilistic classifiers.
Resource allocation for non-orthogonal multiple access in heterogeneous networks

In this paper, novel resource allocation design is investigated for NOMA-enhanced heterogeneous networks (Het-Nets), where small cell base stations (SBSs) are enabled to communicate with multiple small cell users (SCUs) via the NOMA protocol. The resource allocation problem with the aim of maximizing the sum rate of SCUs is formulated as a many-to-one matching game. Due to the existence of co-channel interference, this game is shown to belong to a class of matching games with peer effects. To solve this game, we propose a novel distributed algorithm where the SBSs and resource blocks (RBs) can interact to decide their desired allocation. The proposed algorithm is proved to converge to a two-sided exchange-stable matching with much lower complexity compared to the centralized method. Simulation results unveil that: 1) The proposed algorithm closely approaches the global optimal solution by around 92.5% within a limited number of iterations; and 2) The developed NOMA-enhanced HetNets scheme achieves a higher sum rate of SCUs compared to the traditional OMA-based HetNets scheme.
On the impact of cryptography on complexity theory

We trace three major directions of research in complexity theory to their origins in the foundations of cryptography. Specifically, we refer to the theory of pseudorandomness (including the various incarnations of this concept), to the study of various forms of probabilistic proof system (including interactive proofs, zero-knowledge proofs, and probabilistically checkable proofs), and to the finer study of reductions (including random self-reducibility, worst-case to average-case reductions, average-case preserving reductions, and black-box reductions).
Mathematical modeling of pathways to improve the safety of the saphenous veins radiofrequency ablation

A widely used radiofrequency ablation (RFA) technology for insufficient saphenous veins treatment is accompanied by a high incidence of paresthesia. Thanks to mathematical modeling of standard RFA procedure the thermal damage zone that extends beyond the vein wall has been defined and the practical recommendations for reducing the incidence of side effects during the procedure have been given.
Smart Robust Resources Control in LV Network to Deal With Voltage Rise Issue

Often voltage rise along low voltage (LV) networks limits their capacity to accommodate more renewable energy (RE) sources. This paper proposes a robust and effective approach to coordinate customers' resources and control voltage rise in LV networks, where photovoltaics (PVs) are considered as the RE sources. The proposed coordination algorithm includes both localized and distributed control strategies. The localized strategy determines the value of PV inverter active and reactive power, while the distributed strategy coordinates customers' energy storage units (ESUs). To verify the effectiveness of proposed approach, a typical residential LV network is used and simulated in the PSCAD-EMTC platform.
Outlier-robust moment-estimation via sum-of-squares

We develop efficient algorithms for estimating low-degree moments of unknown distributions in the presence of adversarial outliers. The guarantees of our algorithms improve in many cases significantly over the best previous ones, obtained in recent works of Diakonikolas et al, Lai et al, and Charikar et al. We also show that the guarantees of our algorithms match information-theoretic lower-bounds for the class of distributions we consider. These improved guarantees allow us to give improved algorithms for independent component analysis and learning mixtures of Gaussians in the presence of outliers. Our algorithms are based on a standard sum-of-squares relaxation of the following conceptually-simple optimization problem: Among all distributions whose moments are bounded in the same way as for the unknown distribution, find the one that is closest in statistical distance to the empirical distribution of the adversarially-corrupted sample.
Do ghosts exist ? Clientelistic networks and corruption in public education ∗

We study the effect that political alignment between local (municipal) and regional (department) politicians plays in explaining false or “ghost” students, fabricated by local politicians and bureaucrats to obtain (and then divert) more transfers from the national government. Using a Regression Discontinuity Design, we show that the proportion of ghost students is larger in municipalities where the candidate from the governor’s party is elected, suggesting that resource extraction in this highly clientelistic environment is particularly valuable to politicians whose political network is connected to higher echelons of power. Also, we find larger effects in “autonomous municipalities” that have more discretion over resource spending. Additional findings reveal that the quality and quantity of education are not higher in aligned areas, where instead there is a higher likelihood of future electoral fraud and incumbent parties have better future electoral prospects. These results are consistent with the idea that places with more valuable rents and discretionary scope for diversion of resources for the reproduction of the clientelistic network engage more in this form of corruption, in which a substantial part of the money is being diverted for political and economic gain rather than to improve the quantity or quality of the service. Finally, the higher likelihood of future electoral vote fraud and party performance is consistent with a resulting entrenchment of the clientelistic machine.
Expert Witness Testimony in the Criminal Trial of Eugene de Kock: A Critique of the Posttraumatic Stress Disorder (PTSD) Defence

The Diagnosis of Posttraumatic Stress Disorder (PTSD) was presented as the core testimony in mitigation of sentence in the Eugene de Kock criminal trial. Several hundred pages of expert witness testimony were assessed and the difficulties of diagnosing PTSD for forensic determination, especially when the client is familiar with the usually well-publicised symptoms, are presented. The obligation of expert witnesses to remain objective, testify within their areas of expertise, not assume the role of lie detectors and write accurate reports were emphasised.
BMP-4 inhibits neural differentiation of murine embryonic stem cells.

Members of the transforming growth factor-beta superfamily, including bone morphogenetic protein 4 (BMP-4), have been implicated as regulators of neuronal and glial differentiation. To test for a possible role of BMP-4 in early mammalian neural specification, we examined its effect on neurogenesis in aggregate cultures of mouse embryonic stem (ES) cells. Compared to control aggregates, in which up to 20% of the cells acquired immunoreactivity for the neuron-specific antibody TuJ1, aggregates maintained for 8 days in serum-free medium containing BMP-4 generated 5- to 10-fold fewer neurons. The action of BMP-4 was dose dependent and restricted to the fifth through eighth day in suspension. In addition to the reduction in neurons, we observed that ES cell cultures exposed to BMP-4 contained fewer cells that were immunoreactive for glial fibrillary acidic protein or the HNK-1 neural antigen. Furthermore, under phase contrast, cultures prepared from BMP-4-treated aggregates contained a significant proportion of nonneuronal cells with a characteristic flat, elongated morphology. These cells were immunoreactive for antibodies to the intermediate filament protein vimentin; they were rare or absent in control cultures. Treatment with BMP-4 enhanced the expression of the early mesodermal genes brachyury and tbx6 but had relatively little effect on total cell number or cell death. Coapplication of the BMP-4 antagonist noggin counteracted the effect of exogenous BMP-4, but noggin alone had no effect on neuralization in either the absence or presence of retinoids. Collectively, our results suggest that BMP-4 can overcome the neuralizing action of retinoic acid to enhance mesodermal differentiation of murine ES cells.
Unexpected Plasma Plume Shapes Produced by a Microsecond Plasma Gun Discharge

The plasma plume shapes produced at the outlet of a 1 mm inner diameter plasma gun capillary are investigated over an extended range of both neon flow rates and pulse repetition rate (prr). Various complex, but stable, plume shapes are observed. It appears first that for a given flow rate, the plume shape can be modulated with prr sweeping, revealing fascinating multidart shape when discharge is triggered at a fundamental frequency and up to the sixth harmonic. Second, reproducible similar plume patterns, either multidarts or conical shaped, can be obtained for given appropriate flow rate/prr parameter couples. These phenomena tend to show the effect of the force exchange between the neutral gas flow and the discharge species resulting in plume patterning.
A Construction Grammar Approach to Prepositional Phrase Attachment: Semantic Feature Analysis of V NP1 into NP2 Construction

This paper provides a construction grammar perspective to identifying the ambiguity of prepositional phrase (PP) attachments (i.e., whether a PP is attached to the closest VP or NP1). Despite the wide discussion of these two structures (VP-attached and NP1-attached), we raise the possibility for a third parsing structure (about 11.3% from all 1845 instances analyzed), a co-attachment to both verb and noun. A co-attachment structure denotes the lack of [movement] feature in both the verb and noun surrounding a PP. This proposal is arrived when we annotate the semantic feature [-movement] to both VP and NP1, respectively, in a caused-motion construction of V NP1 into NP2 (e.g., vote an individual into the presidency; shamed us into pity; define ourselves into a box).
Process Migration in the Sprite Operating System

This paper describes a process migration facility for the Sprite operating system. In order to provide location-transparent remote execution, Sprite associates with each process a distinguished home node, which provides kernel services to the process throughout the process''s lifetime. System calls that depend on the location of a process are forwarded to the process''s home node. Performance measurements based on a few simple benchmarks show that remote execution using the home node model is efficient as long as the number of system calls that must be forwarded home is small; this appears to be the case as long as file-system-related calls can be handled without involving the home node. The benchmarks also show that the cost of migrating a process can vary from a fraction of a second to many seconds; it is determined primarily by the number of dirty virtual memory pages and file blocks associated with the process.
Transferability of thermostabilizing mutations between β-adrenergic receptors

Abstract In previous work we described six point mutations that thermostabilised the turkey β1-adrenergic receptor (tβ1AR). The thermostable mutant, tβ1AR-m23, had an apparent Tm 21°C higher than the native protein when solubilized in dodecylmaltoside (DDM) and, in addition, was significantly more stable in short chain detergents, which allowed its crystallization and structure determination. Identification of thermostabilizing mutations in tβ1AR was performed by systematic mutagenesis followed by expressing and assaying each of the 318 mutants for their thermostability. This is time-consuming, so to facilitate studies on related receptors, we have studied the transferability of these mutations to the human adrenergic receptors, hβ1AR and hβ2AR, which have, respectively, 76% and 59% sequence identity to tβ2AR, excluding the N- and C-termini. Thermostability assays revealed that hβ1AR was much more unstable than tβ2AR, whereas hβ2AR was more stable than tβ1AR. Addition of the 6 thermostabilizing mutations in tβ2AR-m23 into both hβ2AR and hβ2AR increased their apparent Tms by 17°C and 11°C, respectively. In addition, the mutations affected the global conformation of the human receptors so that they were predominantly in the antagonist bound form, as was originally observed for tβ2AR-m23. Thus, once thermostabilizing mutations have been identified in one G protein-coupled receptor, stabilization of close members within the subfamily is rapidly obtainable.
Numerical quadratures and orthogonal polynomials

Orthogonal polynomials of dierent kinds as the basic tools play very important role in construction and analysis of quadrature formulas of maximal and nearly maximal algebraic degree of exactness. In this survey paper we give an account on some important connections between orthogonal polynomials and Gaussian quadratures, as well as several types of generalized orthogonal polynomials and corresponding types of quadratures with simple and multiple nodes. Also, we give some new results on a direct connection of generalized Birkho-Young quadratures for analytic functions in the complex plane with multiple orthogonal polynomials.
WatCA: The Waterloo consistency analyzer

Today's online applications depend on fast storage and retrieval of up-to-date data at web scale. To meet this growing demand, the designers of distributed storage systems have devised a rich variety of data replication protocols, offering different trade-offs between consistency, latency, and availability. Understanding the sweet spot, and testing whether a system delivers a particular level of consistency, are challenging problems as consistency itself is difficult to reason about. This demo paper describes an interactive software tool for measuring and visualizing the consistency actually observed by client applications accessing a key-value storage system in real time. The tool can be used to evaluate performance trade-offs in a system with tunable consistency, or to verify the correctness of a storage system that guarantees certain forms of so-called “strong consistency”.
Joint Bi-Affine Parsing and Semantic Role Labeling

We propose a simple encoder-decoder model for joint learning of dependency parsing and semantic role labeling (SRL). Experiments on CoNLL-2009 datasets show that our model is competitive with the state-of-the-art ensemble model on SRL task and significantly outperforms state-ofthe-art joint models on joint evaluation metrics. Results show that with the implicit encoding, the syntax information can further improve a state-of-the-art semantic role labeler. Keywords-Parsing, SRL, Joint Learning
A Uni ... ed Model of Investment Distortions : Theory and Evidence ¤

This paper develops and tests a structural investment model nesting the Q theory and . ve distortions: contract-induced CEO myopia, empire building, shirking, debt overhang, and ‡otation costs. Supporting the empire building hypothesis, founders’ (non-founders’) investment is consistent with their deriving an annual bene.t of $3.30 ($0.40) per $1000 of capital. Evidence of contract-induced myopia is also found. Coe¢cients on marginal q are consistent with regions of inertia due to ‡otation costs. However, cash-‡ow coe¢cients suggest the existence of other non-linear costs of external funds. Signi.cant overhang e¤ects are only found for low Q . rms. The Q and shirking theories are rejected. JEL Classi.cation: G31, G32
An Improved Weighted HITS Algorithm Based on Similarity andPopularity

The HITS algorithm is a very popular and effective algorithm to rank documents based on the link information among a set of documents. However, it assigns every link with the same weight which results in topic drift. In this paper, we generalize the similarity of web pages and propose a query-induced similarity describing how a webpage is similar to another on a query topic. Then, we provide a new improved weighted hits-based (I-HITS) algorithm by assigning appropriate weights to links with the similarity and popularity of web pages. Experiment results indicate that the improved HITS algorithm can find more relevant pages than HITS, ARC, SALSA and improve the relevance by 30%-50%. Furthermore, it can avoid the problem of topic drift and enhance the quality of web search effectively.
Myopic exoplanet detection algorithm based on an analytica l model of AO-corrected coronagraphic multi-spectral imagi ng

High contrast imaging for the detection and characterisati on of exoplanets rests upon the instrument’s capability to cancel the light of the host star. Unfortunate ly he combination of adaptive optics and coronagraphy is not sufficient: the residual starlight, or speckle noise, may be rela tiv ly bright compared to the signal of the planet and limits the detection sensitivity. These speckles find th eir origin in wavefront errors created by imperfections in the optical components. As they evolve on various time sca le , calibrating these speckles out is very tricky and the suppression of the unavoidable residual speckle noise m u t be done by post-processing methods. The current empirical post-processing methods for calibrating out the residual speckles and detecting the potential exoplanets are not sufficient with respect to the specifications to be reached by the n ew and future generations of instruments. In this communication, we develop, in a bayesian framework, an inversion method that is based on an analytical imaging model. The model links the instrumental aberration s to the speckle pattern on the image focal plane, distinguishing between aberrations upstream and downstre am of the coronagraph. This approach allows us to estimate both the speckles and the object map using the fact t h t he object does not scale with the wavelength as the speckle pattern does. We validate this method on reali stic images with simulation conditions typical of a SPHERE-like instrument. We assess the performance of the me thod for different contrasts between the star and the planet flux.
Testing the Applicability of the Official Croatian DTM for Normalization of UAV-based DSMs and Plot-level Tree Height Estimations in Lowland Forests

The Airborne Laser Scanning (ALS) technology has been implemented in operational forest inventories in a number of countries. At the same time, as a cost-effective alternative to ALS, Digital Aerial Photogrammetry (PHM), based on aerial images, has been widely used for the past 10 years. Recently, PHM based on Unmanned Aerial Vehicle (UAV) has attracted great attention as well. Compared to ALS, PHM is unable to penetrate the forest canopy and, ultimately, to derive an accurate Digital Terrain Model (DTM), which is necessary to normalize point clouds or Digital Surface Models (DSMs). Many countries worldwide, including Croatia, still rely on PHM, as they do not have complete DTM coverage by ALS (DTMALS). The aim of this study is to investigate if the official Croatian DTM generated from PHM (DTMPHM) can be used for data normalization of UAV-based Digital Surface Model (DSMUAV) and estimating plot-level mean tree height (HL) in lowland pedunculate oak forests. For that purpose, HL estimated from DSMUAV normalized with DTMPHM and with DTMALS were generated and compared as well as validated against field measurements. Additionally, elevation errors in DTMPHM were detected and eliminated, and the improvement by using corrected DTMPHM (DTMPHMc) was evaluated. Small, almost negligible variations in the results of the leave-oneout cross-validation were observed between HL estimated using proposed methods. Compared to field data, the relative root mean square error (RMSE%) values of HL estimated from DSMUAV normalized with DTMALS, DTMPHM, and DTMPHMc were 5.10%, 5.14%, and 5.16%, respectively. The results revealed that in the absence of DTMALS, the existing official Croatian DTM could be readily used in remote sensing based forest inventory of lowland forest areas. It can be noted that DTMPHMc did not improve the accuracy of HL estimates because the gross errors mainly occurred outside of the study plots. However, since the existence of the gross errors in Croatian DTMPHM has been confirmed by several studies, it is recommended to detect and eliminate them prior to using the DTMPHM in forest inventory.
MINIMUM VARIANCE IMPORTANCE SAMPLING VIA POPULATION MONTE

Variance reduction has always been a central issue in Monte Carlo experiments. Population Monte Carlo can be used to this effect, in that a mixture of importance functions, called a D-kernel, can be iteratively optimized to achieve the minimum asymptotic variance for a function of interest among all possible mixtures. The implementation of this iterative scheme is illustrated for the computation of the price of a European option in the Cox-Ingersoll-Ross model. A Central Limit theorem as well as moderate deviations are established for the D-kernel Population Monte Carlo methodology. Mathematics Subject Classification. 60F05, 62L12, 65-04, 65C05, 65C40, 65C60. Received January 19, 2007.
Face Recognition between Two Person using Kernel Principal Component Analysis and Support Vector Machines

Face recognition is gaining enormous interest nowadays. However, the technical challenges to "teach" a computer to recognize faces have been very difficult. Many methods and approaches have been proposed in the literature. This paper presents a face recognition method based on the combined kernel principal component analysis (KPCA) and support vector machine (SVM) methods. First, the KPCA method is utilized to extract features from the input images. The SVM method is then applied to these extracted features to classify the input images. We compare the performance of this face recognition method to other commonly-used methods. Our experiments show that the combination of KPCA and SVM achieves a higher performance compared to the nearest neighbor classifier, support vector machine, and the combination of kernel principal component analysis and nearest neighbor classifier.
Rapid assessment of postural instability in Parkinson’s disease (RAPID): a pilot study

Background: The Fahn’s pull (or retropulsion) test is an item in the motor section of the Unified Parkinson’s Disease Rating Scale, which is used almost exclusively to classify postural instability in Parkinson’s disease (PD). However, the test is hard to standardize and is often performed incorrectly, making it hard to interpret. Moreover, it may not be safe to administer in patients who experience pain in the shoulders, neck, trunk and/or lower extremities. Identifying and grading postural instability in PD without requiring a physical challenge would not only be useful for the clinician but would assist patients and caregivers in its recognition. We propose the use of the rapid assessment of postural instability in Parkinson’s disease (RAPID) questionnaire as a non‐physical assessment tool.