Miracle-dz/UniFAR-FTUs huggingface dataset:
Context Matters for Size: Why External Validity Claims and Development Practice do not Mix

Abstract In this paper we examine how policymakers and practitioners should interpret the impact evaluation literature when presented with conflicting experimental and non-experimental estimates of the same intervention across varying contexts. As is well known, non-experimental estimates of a treatment effect comprise a causal treatment effect and a bias term due to endogenous selection into treatment. When non-experimental estimates vary across contexts any claim for external validity of an experimental result must make the assumption that (a) treatment effects are constant across contexts, while (b) selection processes vary across contexts. This assumption is rarely stated or defended in systematic reviews of evidence. As an illustration of these issues, we examine two thoroughly researched literatures in the economics of education – class size effects and gains from private schooling – which provide experimental and non-experimental estimates of causal effects from the same context and across multiple contexts. We show that the range of “true” causal effects in these literatures implies non-experimental estimates from the right context are, at present, a better guide to policy than experimental estimates from a different context. We conclude with recommendations for research and policy, including the need to evaluate programs in context, and avoid simple analogies to clinical medicine in which “systematic reviews” attempt to identify best-practices by putting most (or all) weight on the most “rigorous” evidence with no allowance for context.
Die Wahrnehmung des Klimawandels in Destinationen: Eine explorative Analyse

Zusammenfassung Der Klimawandel und seine möglichen Auswirkungen auf Tourismusnachfrage und -angebot werden vielfältig in den Medien diskutiert. Als Reaktion auf den Klimawandel werden meist Anpassungs- oder Vermeidungsstrategien diskutiert. Die Interessensgruppen in den Destinationen gehen unterschiedlich mit dieser Diskussion um und nehmen den Klimawandel und dessen Auswirkungen auf verschiedenste Weise wahr. Im Zuge der Alpine Space Forschungsinitiative ClimAlpTour wurde in drei verschiedenen Destinationen in Tirol und Vorarlberg, mit insgesamt 65 Destinationsstakeholdern in Gruppeninterviews erstens über deren Wahrnehmung der Klimawandelauswirkungen und zweitens über deren Reaktionsstrategien auf diese Auswirkungen, diskutiert. Es zeigt sich dabei dass die Anpassungsstrategien Vermeidungsstrategien in allen Destinationen vorgezogen werden. Abstract Climate change and its possible impacts upon the tourism industry are discussed in various different contexts. Reactions of industry stakeholders are divided into adaptation and mitigation strategies. Different stakeholder groups contribute in manifold ways to this ongoing discussion due to varying perceptions of climate change and climate change induced impacts upon tourism. In the course of the Alpine Space research initiative ClimAlpTour, 65 tourism stakeholders from three destinations in Tyrol and Vorarlberg in Austria were invited to participate in group discussions regarding perceived climate change impacts and possible strategies and measures corresponding to these influences. Stakeholders in all three destinations prefer to apply adaptation measures instead of mitigation measure as a reaction to climate change.
Mitigating Judgment Proofness: Information Acquisition vs. Extended Liability

We present a simple lending model of judgment proof borrowers with private information and heterogeneous wealth, where large and small lenders coexist. Lenders subject would-be borrowers to pre-lending screening, which is not observable and cannot therefore be committed to ex ante. We document market segmentation and credit rationing : borrowers with limited wealth, who face a less severe moral hazard, are funded by large lenders ; wealthy borrowers turn to small lenders who face a higher cost of capital ; borrowers with abundant wealth do not get any financing. With advances in the screening technology, large lenders (small lenders) contract (expand) their loan portfolio. In contrast, as a result of an increase in the liability of lenders, large lenders (small lenders) increase (decrease) the number of loans that they make. The qualitative impact on social welfare of an increase in lender liability or advances in information technology is ambiguously tied to the quality of the borrower pool.
Sorting red blood cells in deep deterministic lateral displacement devices

We study deformability-based sorting of red blood cells via deep deterministic lateral displacement (DLD) using an in-house integral equation solver. Our goal is to quantitatively characterize the physical mechanisms enabling the cell separation. To this end, we systematically investigate the effects of the interior fluid viscosity and the membrane elasticity of a cell on its behavior. In particular, we consider deep devices in which a cell can show rich dynamics such as taking a particular angular orientation depending on its mechanical property. We have found out that cells moving with a sufficiently high positive inclination angle with respect to the flow direction displace laterally while those with smaller angles travel with the flow streamlines. Thereby, deformability-based cell sorting is possible. The underlying mechanism here is cell migration due to the cell's positive inclination and the shear gradient. The higher the inclination is, the farther the cell can travel laterally. We also assess the efficiency of the technique for dense suspensions. It turns out that most of the cells in dense suspensions does not displace in the lateral direction no matter what their deformability is. As a result, separating cells using a DLD device becomes harder.
PENINGKATAN KECERDASAN COMPUTER PLAYER PADA GAME PERTARUNGAN BERBASIS K-NEAREST NEIGHBOR BERBOBOT

Salah satu teknologi komputer yang berkembang dan perubahannya cukup pesat adalah game. Tujuan dibuatnya game adalah sebagai sarana hiburan dan memberikan kesenangan bagi penggunanya. Contoh elemen dalam pembuatan game yang penting adalah adanya tantangan yang seimbang sesuai level. Dalam hal ini, adanya kecerdasan buatan atau AI merupakan salah satu unsur yang diperlukan dalam pembentukan game. Penggunaan AI yang tidak beradaptasi ke strategi lawan akan mudah diprediksi dan repetitif. Jika AI terlalu pintar maka player akan kesulitan dalam memainkan game tersebut. Dengan keadaan seperti itu akan menurunkan tingkat enjoyment dari pemain. Oleh karena itu, dibutuhkan suatu metode AI yang dapat beradaptasi dengan kemampuan dari player yang bermain. Sehingga tingkat kesulitan yang dihadapi dapat mengikuti kemampuan pemainnya dan pengalaman enjoyment ketika bermain game terus terjaga. Pada penelitian sebelumnya, metode AI yang sering digunakan pada game berjenis pertarungan adalah K-NN. Namun metode tersebut menganggap semua atribut dalam game adalah sama sehingga hal ini mempengaruhi hasil learning AI menjadi kurang optimal. Penelitian ini mengusulkan metode untuk AI dengan menggunakan metode K-NN berbobot pada game berjenis pertarungan. Dimana, pembobotan tersebut dilakukan untuk memberikan pengaruh setiap atribut dengan bobot disesuaikan dengan aksi player. Dari hasil evaluasi yang dilakukan terhadap 50 kali pertandingan pada 3 skenario uji coba, metode yang diusulkan yaitu K-NN berbobot mampu menghasilkan tingkat kecerdasan AI dengan akurasi sebesar 51%. Sedangkan, metode sebelumnya yaitu K-NN tanpa bobot hanya menghasilkan tingkat kecerdasan AI sebesar 38% dan metode random menghasilkan tingkat kecerdasan AI sebesar 25%.
FastPose: Towards Real-time Pose Estimation and Tracking via Scale-normalized Multi-task Networks

Both accuracy and efficiency are significant for pose estimation and tracking in videos. State-of-the-art performance is dominated by two-stages top-down methods. Despite the leading results, these methods are impractical for real-world applications due to their separated architectures and complicated calculation. This paper addresses the task of articulated multi-person pose estimation and tracking towards real-time speed. An end-to-end multi-task network (MTN) is designed to perform human detection, pose estimation, and person re-identification (Re-ID) tasks simultaneously. To alleviate the performance bottleneck caused by scale variation problem, a paradigm which exploits scale-normalized image and feature pyramids (SIFP) is proposed to boost both performance and speed. Given the results of MTN, we adopt an occlusion-aware Re-ID feature strategy in the pose tracking module, where pose information is utilized to infer the occlusion state to make better use of Re-ID feature. In experiments, we demonstrate that the pose estimation and tracking performance improves steadily utilizing SIFP through different backbones. Using ResNet-18 and ResNet-50 as backbones, the overall pose tracking framework achieves competitive performance with 29.4 FPS and 12.2 FPS, respectively. Additionally, occlusion-aware Re-ID feature decreases the identification switches by 37% in the pose tracking process.
Asymptotic solutions of stratified shear flow with horizontal eddy coefficient of turbulent viscosity

We consider linearized equations of perturbed mean flow under the Boussinesq approximation with the presence of eddy coefficients of turbulent viscosity but with the absence of turbulent diffusivity. By including both the horizontal and vertical eddy viscosity, an equation for the vertical velocity perturbation leads to a fourth-order Taylor-Goldstein equation. In the absence of vertical eddy viscosity, a modified Taylor-Goldstein equation is obtained, an extended version of the inviscid case but at the same order. Under an assumption of slowly varying background horizontal velocity and Brunt-V\"ais\"al\"a frequency, we present asymptotic solutions using the WKB method for the latter, where both geometrical and physical optics approximations can be obtained. Furthermore, using the method of Frobenius and again by means of asymptotic approximations, we also investigate the behavior of a gravity wave near a critical level, a height where the background velocity is equal to the horizontal phase speed. The vertical velocity perturbation, which now consists of upward-moving and downward-moving waves, takes a different form depending whether it locates above or below the critical level, as well as whether the wind shear near the critical level takes a positive or negative value.
Exponential Two-Armed Bandit Problem

We consider exponential two-armed bandit problem in which losses are described by exponential probability distribution densities. The results may be applied to queueing systems in which two alternative modes of server operation are available. One has to determine the mode corresponding to the smaller service time and provide its predominant application. We develop Bayesian approach and present recursive equation for determining Bayesian strategy and Bayesian risk. In minimax setting of the problem, we use the main theorem of the game theory to determine minimax risk and minimax strategy as Bayesian ones corresponding to the worst-case prior distribution. Numerical results are presented for some moderate control horizons.
Magnetic proximity in a van der Waals heterostructure of magnetic insulator and graphene

Engineering 2D material heterostructures by combining the best of different materials in one ultimate unit can offer a plethora of opportunities in condensed matter physics. Here, in the van der Waals heterostructures of the ferromagnetic insulator Cr2Ge2Te6 and graphene, our observations indicate an out-of-plane proximity-induced ferromagnetic exchange interaction in graphene. The perpendicular magnetic anisotropy of Cr2Ge2Te6 results in significant modification of the spin transport and precession in graphene, which can be ascribed to the proximity-induced exchange interaction. Furthermore, the observation of a larger lifetime for perpendicular spins in comparison to the in-plane counterpart suggests the creation of a proximity-induced anisotropic spin texture in graphene. Our experimental results and density functional theory calculations open up opportunities for the realization of proximity-induced magnetic interactions and spin filters in 2D material heterostructures and can form the basic building blocks for future spintronic and topological quantum devices.
Quantum preprocessing for security enhancement in classical two-party computation

In classical two-party computation, a trusted initializer who prepares certain initial correlations can help make the bipartite computation secure. We propose two bipartite quantum protocols with possible aborts for approximately generating such bipartite classical correlations with varying degrees of privacy, without introducing a third party. The two parties are assumed to be weakly cooperating and one of them needs to be modestly honest so that the quantum precomputed correlations can be established successfully. Then the main two-party classical computation has nontrivial information-theoretic security for generic circuits.
CCD UBVRI photometry of the open cluster Berkeley 8

The poorly studied Berkeley 8 (Be8) open cluster is analysed from CCD UBVRI photometric data taken with the 0.90 m telescope at the Sierra Nevada Observatory. The Z = +0.008 PARSEC isochrone gave us a reddening of E(B-V) = 0.69 +- 0.03, a distance of 3410 +- 300 pc and an age of 2.8 +- 0.2 Gyr. Its median Gaia DR2 distance, d = 3676 +- 810 pc is in good agreement with our photometric distances, 3410 - 3620 pc within the uncertainties. The kinematic parameters of five likely members of Be 8 with the circular orbits, ecc = [0.23, 0.30] reflect the properties of the Galactic thin disc, which is also consistent with what is expected of its metal content ([M/H] = -0.27). Be8 with R > 9 kpc (co-rotation gap at 9 kpc) may have been originating from different galactic radius or different star formation region.
Nearly Optimal Measurement Scheduling for Partial Tomography of Quantum States

Many applications of quantum simulation require to prepare and then characterize quantum states by performing an efficient partial tomography to estimate observables corresponding to $k$-body reduced density matrices ($k$-RDMs). For instance, variational algorithms for the quantum simulation of chemistry usually require that one measure the fermionic 2-RDM. While such marginals provide a tractable description of quantum states from which many important properties can be computed, their determination often requires a prohibitively large number of circuit repetitions. Here we describe a method by which all elements of $k$-body qubit RDMs acting on $N$ qubits can be directly measured with a number of circuits scaling as ${\cal O}(3^{k} \log^{k-1}\! N)$, an exponential improvement in $N$ over prior art. Next, we show that if one is able to implement a linear depth circuit on a linear array prior to measurement, then one can directly measure all elements of the fermionic 2-RDM using only ${\cal O}(N^2)$ circuits. We prove that this result is asymptotically optimal, thus establishing an exponential separation between the number of circuits required to directly measure all elements of qubit versus fermion RDMs. We further demonstrate a technique to estimate the expectation value of any linear combination of fermionic 2-RDM elements using ${\cal O}(N^4 / \omega)$ circuits, each with only ${\cal O}(\omega)$ gates on a linear array where $\omega \leq N$ is a free parameter. We expect these results will improve the viability of many proposals for near-term quantum simulation.
Modeling Price Dynamics, Optimal Portfolios, and Option Valuation for Cryptoassets

The authors demonstrate the construction of an optimal dynamic portfolio of cryptoassets that minimizes either return variance or conditional value at risk. One can view such a portfolio as a minimum-risk index for this asset class. They carefully backtested the dynamic portfolio model and developed a fair valuation model for options based on a dynamic pricing model for the underlying cryptoasset index. They obtain the valuation by passing from the natural world to the equivalent martingale measure via the Esscher transform. The work underscores the need for a cryptoasset index–based exchange-traded fund, the development of derivatives, particularly for cryptoportfolio insurance purposes, and the development of (nearly) riskless rates for this asset class. TOPICS: Currency, options, statistical methods, VAR and use of alternative risk measures of trading risk Key Findings ▪ This article provides a methodology for constructing an optimal dynamic portfolio of major cryptoassets that minimizes either return variance or conditional value at risk. ▪ The authors develop a fair valuation model for options based on a dynamic pricing model for the underlying cryptoindex. ▪ The work emphasizes the need for a cryptoasset index–based exchange-traded fund and the development of derivatives, in particular for cryptoportfolio insurance purposes.
Cultural background influences electrical stimulation effects on the social brain

Cultural background influences social cognition, however no study has examined brain stimulation differences attributable to cultural background. 104 young adults [52 South-East Asian Singaporeans (SEA); 52 Caucasian Australians (CA)] received anodal high-definition transcranial direct current stimulation (HD-tDCS) to the dorsomedial prefrontal cortex (dmPFC) or the right temporoparietal junction (rTPJ). Participants completed tasks with varying demands on self-other processing. At baseline, SEA showed greater self-other integration than CA. Anodal HD-tDCS to the dmPFC resulted in the CA performing closer to the SEA. Baseline performance on a mental rotation task and the self-reference effect in memory (SRE) was comparable between groups. In the combined sample, rTPJ HD-tDCS decreased interference from the egocentric perspective during mental rotation and dmPFC HD-tDCS removed the SRE. Stimulation effects were comparable when baseline performance was comparable. When baseline performance differed, stimulation differences were identified. Therefore, cultural background is an important consideration in social brain stimulation studies.
A Kernel Regression Procedure in the 3D Shape Space with an Application to Online Sales of Children’s Wear

This paper is focused on kernel regression when the response variable is the shape of a 3D object represented by a configuration matrix of landmarks. Regression methods on this shape space are not trivial because this space has a complex finite-dimensional Riemannian manifold structure (non-Euclidean). Papers about it are scarce in the literature, the majority of them are restricted to the case of a single explanatory variable, and many of them are based on the approximated tangent space. In this paper, there are several methodological innovations. The first one is the adaptation of the general method for kernel regression analysis in manifold-valued data to the three-dimensional case of Kendall’s shape space. The second one is its generalization to the multivariate case and the addressing of the curse-ofdimensionality problem. Finally, we propose bootstrap confidence intervals for prediction. A simulation study is carried out to check the goodness of the procedure, and a comparison with a current approach is performed. Then, it is applied to a 3D database obtained from an anthropometric survey of the Spanish child population with a potential application to online sales of children’s wear.
Label Propagation Ensemble for Hyperspectral Image Classification

The imbalance between limited labeled pixels and high dimensionality of hyperspectral data can easily give rise to Hughes phenomenon. Semisupervised learning (SSL) methods provide promising solutions to address the aforementioned issue. Graph-based SSL algorithms, also called label propagation methods, have obtained increasing attention in hyperspectral image (HSI) classification. However, the graphs constructed by utilizing the geometrical structure similarity of samples are unreliable due to the high dimensionality and complexity of the HSIs, especially for the case of very limited labeled pixels. Our motivation is to construct label propagation ensemble (LPE) model, then use the decision fusion of multiple label propagations to obtain pseudolabeled pixels with high classification confidence. In LPE, random subspace method is introduced to partition the feature space into multiple subspaces, then several label propagation models are constructed on corresponding subspaces, finally the results of different label propagation models are fused at decision level, and only the unlabeled pixels whose label propagation results are the same will be assigned with pseudolabels. Meanwhile extreme learning machine classifiers are trained on the labeled and pseudolabeled samples during the iteration. Compared with traditional label propagation methods, our proposed method can deal with the situation of very limited labeled samples by providing pseudolabeled pixels with high classification confidence, consequently, the accurate base classifiers are obtained. To demonstrate the effectiveness of the proposed method, LPE is compared with several state-of-the-art methods on four hyperspectral datasets. In addition, the method that only use label propagation is investigated to show the importance of ensemble technique in LPE. The experimental results demonstrate that the proposed method can provide competitive solution for HSI classification.
A circularly polarized horn antenna with elliptical waveguide polarizer

In this article, a circularly polarized horn antenna with elliptical waveguide polarizer is proposed. By converting linear polarization into circular polarization in the elliptical waveguide polarizer, circularly polarized radiation can be realized by the proposed antenna in D‐band. The observation shows that the proposed antenna achieves the impedance bandwidth of 16.7% for S11 < −10 dB from 110 to 130 GHz and the axial‐ratio bandwidth of 11.7% from 114 to 128 GHz. The measured gain of the proposed antenna can reach the range 13.6‐17.82 dBic from 110 to 130 GHz. Besides, the measured normalized beam of the proposed antenna at the far field is able to realize a sidelobe below −25 dB, as well as good axial symmetry. With the elliptical waveguide polarizer, it is obtained that the proposed antenna has the potential application of circularly polarized radiation in millimeter and sub‐millimeter wave band.
A high-accuracy indoor positioning system based on UWB

In this paper, a high-accuracy indoor positioning system based on the ultra-wideband (UWB) technique is proposed. The proposed system uses a simple ranging process to obtain the distance between the mobile node and the fixed base stations. Besides, an improved time of arrival (ToA) algorithm with Kalman filtering is proposed to improve the positioning accuracy. Measurements have been performed in the real indoor 13m*7.6m environment with many obstacles and the root-mean-square error (RMSE) is less than 0.3m. The proposed system offers a wide range of application in robotics, industrial automation, postsorting system and so on.
Revisiting B ! D'

We re-examine the determination ofjVcbj from B! Dl in view of recent experimental and theoretical progress, discussing the parameterization of the form factors and studying the role played by the unitarity constraints. Our t to experimental and lattice results for B! D‘ givesjVcbj = 40:49(97) 10 3 and to R(D) = 0:299(3).