Miracle-dz/UniFAR-FTUs huggingface dataset:
Predicting Heart Ailment in Patients with Varying number of Features using Data Mining Techniques

Data mining can be defined as a process of extracting unknown, verifiable and possibly helpful data from information. Among the various ailments, heart ailment is one of the primary reason behind death of individuals around the globe, hence in order to curb this, a detailed analysis is done using Data Mining. Many a times we limit ourselves with minimal attributes that are required to predict a patient with heart disease. By doing so we are missing on a lot of important attributes that are main causes for heart diseases. Hence, this research aims at considering almost all the important features affecting heart disease and performs the analysis step by step with minimal to maximum set of attributes using Data Mining techniques to predict heart ailments. The various classification methods used are Naïve Bayes classifier, Random Forest and Random Tree which are applied on three datasets with different number of attributes but with a common class label. From the analysis performed, it shows that there is a gradual increase in prediction accuracies with the increase in the attributes irrespective of the classifiers used and Naïve Bayes and Random Forest algorithms comparatively outperforms with these sets of data.
Democracy and Compliance in Public Goods Games

I investigate if, how, and why the effect of a contribution rule in a public goods game depends on how it is implemented: endogenously chosen or externally imposed. The rule prescribes full contributions to the public good backed by a nondeterrent sanction for those who do not comply. My experimental design allows me to disentangle to what extent the effect of the contribution rule under democracy is driven by self-selection of treatments, information transmitted via the outcome of the referendum, and democracy per se. In case treatments are endogenously chosen via a democratic decision-making process, the contribution rule significantly increases contributions to the public good. However, democratic participation does not affect participants’ contribution behavior directly, after controlling for self-selection of treatments and the information transmitted by voting.
Host plant and field density of Tetranychus phaselus Ehara (Acari: Tetranychidae)

Tetranychus phaselus (Acari: Tetranychidae) lives chiefly on the mulberry weed Fatoua villosa (Moraceae), and reaches high densities in the autumn. To test the prediction that T. phaselus is adapted to F. villosa, we investigated the suitability of six host plants available in this species’ habitat. We supplementarily investigated the association between the density of T. phaselus and the density of an important predatory mite, Neoseiulus womersleyi (Acari: Phytoseiidae) on F. villosa leaves to infer the predation pressure. To know the characteristics of host plant use in T. phaselus, these characteristics were compared with the population of the common polyphagous species T. kanzawai on ramie (Boehmeria nivea, Urticaceae) leave. With respect to host-plant suitability, T. phaselus had one of the highest egg production and the survival rate on F. villosa among all six host plants examined, which partly supports the prediction that T. phaselus is adapted to F. villosa. On the other hand, T. phaselus egg production and development time on F. villosa was similar to that of T. kanzawai reared on F. villosa. Nevertheless, T. phaselus was found only on F. villosa in the field, and the density per leaf area of T. phaselus on F. villosa was higher than that of T. kanzawai on ramie leaves. Considering that the density of N. womersleyi was not significantly associated with the density of T. phaselus, the high density of T. phaselus could be partly attributed to the scarcity of N. womersleyi on F. villosa leaves.
New forms of partnership: the role of logistics clusters in facilitating horizontal collaboration mechanisms

ABSTRACT Although the benefits of horizontal collaboration have been well documented in the literature, research has yet to offer a detailed understanding of the mechanisms that firms employ to create successful horizontal collaboration. Further, the role of logistics clusters in facilitating horizontal collaboration is crucial but not clear yet. This paper addresses these gaps. In order to address the research objectives, we employ a systematic literature review methodology. As a result of this process, one hundred thirty-three (133) papers published in leading academic journals were systematically analyzed. These studies are reviewed under the theoretical lenses of the transaction cost economics (TCE) and the derived identification of governance mechanisms (i.e. joint value propositions, informal governance, formal governance and information exchange) to achieve successful horizontal collaboration. Further, we provide a detailed description of how logistics clusters can facilitate and promote the development of such mechanisms, illustrated with companies’ best practices. As a result, several testable research propositions are put forth.
The Influence of Shape Constraints on the Thresholding Bandit Problem

We investigate the stochastic Thresholding Bandit problem (TBP) under several shape constraints. On top of (i) the vanilla, unstructured TBP, we consider the case where (ii) the sequence of arm's means $(\mu_k)_k$ is monotonically increasing MTBP, (iii) the case where $(\mu_k)_k$ is unimodal UTBP and (iv) the case where $(\mu_k)_k$ is concave CTBP. In the TBP problem the aim is to output, at the end of the sequential game, the set of arms whose means are above a given threshold. The regret is the highest gap between a misclassified arm and the threshold. In the fixed budget setting, we provide problem independent minimax rates for the expected regret in all settings, as well as associated algorithms. We prove that the minimax rates for the regret are (i) $\sqrt{\log(K)K/T}$ for TBP, (ii) $\sqrt{\log(K)/T}$ for MTBP, (iii) $\sqrt{K/T}$ for UTBP and (iv) $\sqrt{\log\log K/T}$ for CTBP, where $K$ is the number of arms and $T$ is the budget. These rates demonstrate that the dependence on $K$ of the minimax regret varies significantly depending on the shape constraint. This highlights the fact that the shape constraints modify fundamentally the nature of the TBP.
Multipole Graph Neural Operator for Parametric Partial Differential Equations

One of the main challenges in using deep learning-based methods for simulating physical systems and solving partial differential equations (PDEs) is formulating physics-based data in the desired structure for neural networks. Graph neural networks (GNNs) have gained popularity in this area since graphs offer a natural way of modeling particle interactions and provide a clear way of discretizing the continuum models. However, the graphs constructed for approximating such tasks usually ignore long-range interactions due to unfavorable scaling of the computational complexity with respect to the number of nodes. The errors due to these approximations scale with the discretization of the system, thereby not allowing for generalization under mesh-refinement. Inspired by the classical multipole methods, we propose a novel multi-level graph neural network framework that captures interaction at all ranges with only linear complexity. Our multi-level formulation is equivalent to recursively adding inducing points to the kernel matrix, unifying GNNs with multi-resolution matrix factorization of the kernel. Experiments confirm our multi-graph network learns discretization-invariant solution operators to PDEs and can be evaluated in linear time.
Robust Persistence Diagrams using Reproducing Kernels

Persistent homology has become an important tool for extracting geometric and topological features from data, whose multi-scale features are summarized in a persistence diagram. From a statistical perspective, however, persistence diagrams are very sensitive to perturbations in the input space. In this work, we develop a framework for constructing robust persistence diagrams from superlevel filtrations of robust density estimators constructed using reproducing kernels. Using an analogue of the influence function on the space of persistence diagrams, we establish the proposed framework to be less sensitive to outliers. The robust persistence diagrams are shown to be consistent estimators in bottleneck distance, with the convergence rate controlled by the smoothness of the kernel. This, in turn, allows us to construct uniform confidence bands in the space of persistence diagrams. Finally, we demonstrate the superiority of the proposed approach on benchmark datasets.
Multi-TRxPs for Industrial Automation with 5G URLLC Requirements

The Fifth Generation (5G) Ultra Reliable Low Latency Communication (URLLC) is envisioned to be one of the most promising drivers for many of the emerging use cases, including industrial automation. In this study, a factory scenario with mobile robots connected via a 5G network with two indoor cells is analyzed. The aim of this study is to analyze how URLLC requirements can be met with the aid of multi-Transmission Reception Points (TRxPs), for a scenario which is interference limited. By means of simulations, it is shown that availability and reliability can be significantly improved by using multi-TRxPs, especially when the network becomes more loaded. In fact, optimized usage of multi-TRxPs can allow the factory to support a higher capacity while still meeting URLLC requirements. The results indicate that the choice of the number of TRxPs which simultaneously transmit to a UE, and the locations of the TRxPs around the factory, is of high importance. A poor choice could worsen interference and lower reliability. The general conclusion is that it is best to deploy many TRxPs, but have the UE receive data from only one or maximum two at a time. Additionally, the TRxPs should be distributed enough in the factory to be able to properly improve the received signal, but far enough from the TRxPs of the other cell to limit the additional interference caused.
Ionospheric layer induced bymeteoric ionization in Titan ’ s atmosphere

The ablation of meteoroids and the ionization of metallic ions in the atmosphere of Titan has been investigated. The ionization rates of the most abundant metals in cometary meteoroids, Si;Mg and Fe, are calculated from the meteoroid mass loss rate and the ionization probability of each metal. We have modeled the ion-neutral chemistry of metallic ions and calculated the concentration of the most abundant metal ions and electrons. We found that long-lived metallic ions considerably change the predictions of the electron density by the models which only consider solar radiation and electrons trapped in the magnetosphere of Saturn. The inclusion of metallic ions in the upper ionospheric models leads to an increase in the electron concentration below 800 km. We conclude that an ionospheric layer should be present at around 700 km with an electron density peak similar in magnitude to the one produced by solar radiation at 1000 km or by cosmic rays at 90 km. c © 2001 Elsevier Science Ltd. All rights reserved.
Toward a Theory of Timing Effects in Self-Organized Sentence Processing

Many theories of sentence processing are based on the idea that a discrete, symbolic grammar deﬁnes all of the structures relevant for parsing, effectively supervising the parser as it selects from those structures the one that best ﬁts the input. However, local coherence effects, where people’s parsing behavior suggests they are entertaining locally viable but globally impossible structures, suggest that this may not always be the case. We introduce a self-organized sentence processing (SOSP) model of local coherence effects and use it to demonstrate how predictions about timing effects (a major source of psycholinguistic data and a shortcoming of many previous dynamical parsers) can be derived directly from a harmony (well-formedness) function covering both grammatical and ungram-matical structures. The framework we describe allows us to simulate the processing of any set of lexical features and attachment links, making it widely applicable to psycholinguistic phenomena.
A taxonomic reassessment of the genus Balsamia from China

Abstract Molecular analysis of the genus Balsamia was conducted with ITS and 28S sequences available, including newly gained sequences from Chinese specimens. Combined with the morphological examinations, a new hypogeous species, Balsamia lishanensis was described and illustrated from North China, which is morphologically characterized by reddish brown ascomata covered with fine warts, the whitish gleba with numerous small chambers, 3–5 layers peridium with reddish brown polygonal cells and the smooth and regular ellipsoid ascospores with one large oil drop. Two species previously described as Barssia were transferred to Balsamia. Balsamia platyspora was confirmed to be in existence in China based on newly collected specimen. A key to the Chinese Balsamia species was provided.
Methods in Bimodal Bilingualism Research : Experimental Studies

Introduction 251 Important Considerations When Collecting Bimodal Bilingual Data 251 Data Collection Fairs 253 General Principles of Test Development 254 The Test Battery in the Bibibi Project 255 General Language Tests 256 Vocabulary Tests 259 Morphosyntax Tests 260 Phonology Tests 263 Additional Tests 271 Adjusting the Tasks and the Details of the Applications 273 Transcribing Experimental Data 274 Conclusion 275
Transgenic Mice Expressing Cre-Recombinase Specifically in Mor SCone Photoreceptors

METHODS. Five kilobases of 5 upstream sequence of the mouse red-green (M) opsin gene or 0.5 kb of the mouse blue (S) opsin gene was cloned into a Cre-expression plasmid. Transgenic mice were generated and characterized, and appropriate lines were established. The Cre-transgenic mice were crossed with ROSA26-lacZ mice (containing floxed -galactosidase gene) and analyzed to determine Cre-recombinase activity.
Market Concentration, Risk-taking, and Efficiency of Commercial Banks in Pakistan: An Application of the Two-Stage Double Bootstrap DEA

Efficiency analysis is a vital part of prudent management practices across the banking industry, yet there is only sparse literature examining bank efficiency, especially in Asian developing countries and using a comprehensive methodology. This study aims to analyze bank efficiency in a South Asian developing country, Pakistan, for the period 2007 to 2014. Borrowing a technique from Simar and Wilson (2007), this study applies two-stage data envelopment analysis (DEA) with double bootstrapping. Our results reveal that private banks are more technically efficient than government banks; conventional commercial banks precede Islamic commercial banks in efficiency, and large banks are more technically efficient than small and medium-size banks. Moreover, the results indicate that market concentration, capital risk, credit risk, and liquidity risk have significant effects on the overall efficiency of banks. This study provides an important opportunity to advance the understanding of bank efficiency, market concentration, and risk complications in developing countries and gives insightful directions to researchers and financial institutions.
Measurement of Tire Wear Dust at the Roadside and Estimation of Emission Factor for Tire Wear

自動車タイヤの走行磨耗による粉塵の発生量を沿道で計測した。 計測は見通しのよい直線道路で 行い,距 離減衰および後背地濃度を含めておこなった。 その結果はCMB法 による解析を行うとと もに,自 動車起源の排出量を推計し,環 境省の 「浮遊粒子状物質汚染予測マニュアル」に記載され た排出係数と比較した。 その結果,今 回の観測をもとにして得られた自動車タイヤ磨耗量は,マニュ アルの排出係数を約1/10に すると自動車排気排出量と整合することがわかった。 本結果は米国EPA が公表しているタイヤ磨耗の排出係数と近い結果であった。 一方,自 動車走行による巻き上げ粉じ んについても計測を行い,同1/10と いう結果を得たが,巻 き上げ粉塵については道路環境の影響 が大きく,精 度は不十分であると考えられた。 タイヤ磨耗の排出係数は大気シミュレーションモデ ルにおけるSPM濃 度予測に与える影響が大きいことから,さ らなる追試,お よび異なる環境での 計測,等 により精度向上を図る必要がある。
The View from Above: Applications of Satellite Data in Economics

The past decade or so has seen a dramatic change in the way that economists can learn by watching our planet from above. A revolution has taken place in remote sensing and allied fields such as computer science, engineering, and geography. Petabytes of satellite imagery have become publicly accessible at increasing resolution, many algorithms for extracting meaningful social science information from these images are now routine, and modern cloud-based processing power allows these algorithms to be run at global scale. This paper seeks to introduce economists to the science of remotely sensed data, and to give a flavor of how this new source of data has been used by economists so far and what might be done in the future.
Influence οf Households’ Borrowings οn Consumer Spending During the Escalation of the Crisis

This article investigates the relationship between the borrowing activity of Russian households and their current conumer expendatures in the period of escalation of the social and economic crisis. The analysis was conducted on the basis of data provided by the Russian Longitudinal Monitoring Survey, RLMS-HSE for 2015. The paper proposes and implements an approach that makes it possible to assess the impact of borrowings on inequality in consumption and poverty among households. It was revealed that the need of repayment results in saving on food, medical treatment and other vital needs for an overwhelming number of households. This is especially acute among families being beyond the poverty threshold.
ISEE‐3 wave measurements in the distant geomagnetic tail and boundary layer

The ISEE-3 excursion into the distant tail region reveals a complex structure with several wave, particle and field characteristics that differ significantly from those measured closer to earth. The most striking results are found within the distant boundary layer where intense electrostatic turbulence levels are detected in association with bi-directional electron distributions. The wave amplitudes appear to increase with increasing downstream distance and the polarizations are those expected for ion acoustic oscillations. Near the boundary of the distant plasmas sheet the turbulence spectra are essentially identical to those measured much closer to earth on IMP-8. We also find that in the distant tail the continuum radiation spectrum has a low frequency cutoff that is much higher than the minimum value for the local plasma frequency.
RIKSBANK WORKING PAPER SERIES 297 SPEEDING UP MCMC BY EFFICIENT DATA SUBSAMPLING

The computing time for Markov Chain Monte Carlo (MCMC) algorithms can be prohibitively large for datasets with many observations, especially when the data density for each observation is costly to evaluate. We propose a framework where the likelihood function is estimated from a random subset of the data, resulting in substantially fewer density evaluations. The data subsets are selected using an e cient Probability Proportional-to-Size (PPS) sampling scheme, where the inclusion probability of an observation is proportional to an approximation of its contribution to the log-likelihood function. Three broad classes of approximations are presented. The proposed algorithm is shown to sample from a distribution that is within O(m− 1 2 ) of the true posterior, where m is the subsample size. Moreover, the constant in the O(m− 1 2 ) error bound of the likelihood is shown to be small and the approximation error is demonstrated to be negligible even for a small m in our applications. We propose a simple way to adaptively choose the sample size m during the MCMC to optimize sampling e ciency for a xed computational budget. The method is applied to a bivariate probit model on a data set with half a million observations, and on a Weibull regression model with random e ects for discrete-time survival data.
Direct Driven Hydraulic Drive: Effect of Oil on Efficiency in Sub-Zero Conditions

Direct driven hydraulic drives (DDH) have the advantages of compact high power density in hydraulic systems and flexible control of electric motors. These advantages can benefit non-road mobile machinery (NRMM) applications. However, maintaining high efficiency while working in sub-zero conditions with NRMM is challenging. Therefore, this paper investigates the effect of hydraulic oil on the efficiency of a DDH in a cold environment for an NRMM application. In the DDH setup, the speed and position control of a double-acting cylinder was implemented directly with an electric motor drive in a closed-loop system without the conventional control valves. Efficiency measurements of the DDH setup with two oils (conventional multi-grade and high-performance) were conducted under different operating conditions (speed and payload) and environmental conditions (temperature in °C). The paper provides an evaluation of the electro-hydraulic system and a discussion on the usage of hydraulic oil by non-road mobile working machines in sub-zero conditions. An experimental investigation demonstrated an improvement in efficiency of 5%-unit at 22 °C, from 2%-unit to 5%-unit at 3 °C, and of almost a 10%-unit at temperatures below zero (−10 °C) by changing oil.
Constructing an Optical Phase-Locked Loop for Partial-Transfer Imaging of Bose-Einstein Condensates

Researching the dynamics of topological features within Bose-Einstein Condensates (BECs) can provide insight into the theory of superfluids and beyond. Since these topological defects are often too small to be resolved in situ, the BEC containing them must be released from its trap in order to be imaged. As the location of these features cannot be easily controlled in the laboratory, the study of their dynamics requires alternative approaches, such as imaging only a fraction of the BEC at a time, a technique called partial-transfer imaging. One of the ways in which a fraction of a BEC can be excited out of an optical trap is through stimulated Bragg-Raman transitions, which impart kinetic energy to the atoms and change their internal state. A procedure has been established for driving Bragg-Raman transitions on Rb BECs in our lab, but it requires that two laser beams be phase-locked at difference of approximately 6.835 GHz. For this purpose, we have designed and constructed an optical phase-locked loop capable of maintaining a frequency offset of 6.912 GHz between two independent diode lasers. We discuss methods for tuning the loop, and we analyze the performance of the loop for several iterations of the system. The final system performance still needs improvement but is characterized by a square-mean phase error of x∆φ2y = 0.39, equivalent to 67.7% of the beat signal power in the carrier frequency. The loop should be optimized before using it for experiments with BECs, and we suggest some initial steps for addressing potential problems with the system. Finally, we give an overview of the future laser system to be used in BEC experiments.
Addressing initialisation uncertainty for end-to-end ecosystem models: application to the Chatham Rise Atlantis model

Ecosystem models require the specification of initial conditions, and these initial conditions have some level of uncertainty. It is important to allow for uncertainty when presenting model results, because it reduces the risk of errant or non-representative results. It is crucial that model results are presented as an envelope of what is likely, rather than presenting only one instance. We perturbed the initial conditions of the Chatham Rise Atlantis model and analysed the effect of this uncertainty on the model’s dynamics by comparing the model outputs resulting from many initial condition perturbations. At the species group level, we found some species groups were more sensitive than others, with lower trophic level species groups generally more sensitive to perturbations of the initial conditions. We recommend testing for robust system dynamics by assessing the consistency of ecosystem indicators in response to fishing pressure under perturbed initial conditions. In any set of scenarios explored using complex end-to-end ecosystem models, we recommend that associated uncertainty analysis be included with perturbations of the initial conditions.