Miracle-dz/UniFAR-FTUs huggingface dataset:
Demand for Electricity in a Poor Economy∗

Over a billion people do not have electricity in their homes and whether electricity spreads across the developing world hinges on household willingness to pay for it. Our surveys, conducted in 100 villages in India’s poorest state, uncover innovations in off-grid solar technologies and government-led grid expansions which imply that households face a growing choice set on where to source electricity from. The main contribution of this paper is to create a demand system founded upon experimental variation in solar prices that allows us to assess household willingness to pay for different sources of electricity. This reveals two key insights. The first is that though off-grid solar is valuable to unelectrified households it is largely a stop-gap with households preferring the grid when that becomes available. The second is that extending the grid to all consumers necessitates rationing and disadvantages off-grid solar whereas raising prices or removing theft limits grid access and advantages off-grid solar. Our paper demonstrates that these trade-offs will be central to electricity policy in poor economies. ∗We thank Manoj Sinha and Col. Baljit Singh of Husk Power Systems for their partnership in implementing the project. We are grateful to Liran Einav and seminar participants at Berkeley, Harvard, LSE, MIT, Stanford and the Western Economic Association for comments. We thank Shruti Bhimsaria, Menna Bishop, Catherine Che, Ananya Kotia, Rakesh Pandey, Aditya Petwal, Vı́ctor Quintas-Mart́ınez and Rashi Sabherwal for excellent research assistance. We thank the Shakti Sustainable Energy Foundation, the LGT Venture Philanthropy Foundation, USAID and the International Growth Center (IGC) for financial support. All views and errors are solely ours. †Burgess [Dept of Economics, LSE: r.burgess@lse.ac. uk]; Greenstone [Dept of Economics, University of Chicago: mgreenst@uchicago.edu]; Ryan [Corresponding author, Dept of Economics, Yale University: nicholas.ryan@yale.edu. ]; Sudarshan [University of Chicago, Energy Policy Institute at Chicago (India): anants@uchicago.edu]
มหาวิทยาลัย มณฑลยูนนาน ประเทศสาธารณรัฐประชาชนจีน Organizational Climate and Self-efficacy among Nurses in University Hospitals , Yunnan Province , The People ’ s Republic of China

บทคัดย่อ การศกึษาเชิงพรรณาหาความสมัพันธ์นี ม้วีตัถปุระสงค์เพื อ่ศกึษาระดบับรรยากาศองค์การในภาพรวม และในแต่ละด้าน และสมรรถนะแห่งตน และเพื่อศึกษาความสัมพันธ์ระหว่างบรรยากาศองค์การในภาพรวม และในแต่ละด้านของพยาบาลโรงพยาบาลมหาวทิยาลยั มณฑลยนูนาน สาธารณรฐัประชาชนจนี เกบ็รวบรวม ข้อมลูจากพยาบาลจ� านวน 426 คนที ถู่กสุ ม่แบบหลายข้ันตอนจากประชากรพยาบาลทั ง้หมด 6,359 คน จาก 2 โรงพยาบาลมหาวทิยาลยัที ผ่่านการสุ ม่ในเบื อ้งต้นมาก่อน เครื อ่งมอืวจิยัประกอบด้วยแบบสอบถามส่วนบคุคล แบบสอบถามบรรยากาศองค์การ (OCQ) และแบบวดัสมรรถนะแห่งตนฉบบัภาษาจนี (GSES) ค่าความเช่ือมั น่ ของแบบวัด OCQ และ GSES เท่ากับ 0.89 และ 0.93 ตามล�าดับ วิเคราะห์ข้อมูลด้วยสถิติเชิงพรรณาและค่า สมัประสทิธิ ส์หสมัพนัธ์แบบล� าดบัที ข่องสเปียร์แมน ผลการศกึษาพบว่า: 1) บรรยากาศองค์การในภาพรวมซึ ง่ รับรู้โดยพยาบาลอยู่ในระดับดี และบรรยากาศองค์การด้านความยืดหยุ่น ด้านความรับผิดชอบในหน้าที่ ด้าน มาตรฐานการปฏิบัติงาน ด้านความชัดเจน และด้านความยึดมั่นผูกพันในทีมอยู่ในระดับดี แต่ด้านการได้รับ รางวัลอยู่ในระดับต�่า 2) พยาบาลรับรู้สมรรถนะแห่งตนในระดับปานกลาง 3) มีความสัมพันธ์เชิงบวกอย่างมี นัยส�าคัญระหว่างบรรยากาศองค์การในภาพรวมและแต่ละด้าน กับสมรรถนแห่งตนของพยาบาล (p<0.01) ผลการศกึษาเหล่านี ใ้ห้ข้อมลูที ม่คีณุค่ากับผู อ้� านวยการโรงพยาบาลและผู บ้รหิารทางการพยาบาล เพ่ือปรับปรุง บรรยากาศองค์การและเพื่อเพิ่มสมรรถนะแห่งตนของพยาบาล
Flow based anomaly detection system using Reputation and Evolutionary computation

Discovery, on computer networks, of entities nefarious and profane is the responsibility of an Intrusion Detection System IDS. Techniques for malicious intrusion detection are as diverse as their targets, with associated architectures often Characterized in two ways: 1) networkbased or host-based; and 2) signature-based or behaviour-based. A signature-based IDS reacts to strings or traffic flowing across its aperture that match a signature in a repository of undesirable bit-patterns. As the signature repository grows over time, it is increasingly very difficult to compare every International Research Journal in Advanced Engineering and Technology (IRJAET)
The Acquisition of Aspect in English and Russian

The aim of this paper is to test the validity of Hoekstra and Hyams’s (1998) Eventivity Constraint hypothesis vs. Gavruseva’s (2003) Underspecification of Aspect Hypothesis with respect to the interaction between the acquisition of finiteness and aspect on the basis of data from child English and child Russian. A more general aim is to to determine to what extent aspect influences the acquisition of finiteness. The paper is divided into three sections as follows: the first section consists of a theoretical framework, providing information on the main differences between the English and the Russian aspectual systems, the second section presents the hypotheses to be tested with respect to the acquisition of aspect and finiteness and the third section presents the case study and the results confirming or contradicting the hypotheses tested.
Diffusive hydrodynamics from integrability breaking

We describe the crossover from generalized hydrodynamics to conventional hydrodynamics in nearly integrable systems. Integrable systems have infinitely many conserved quantities, which spread ballistically in general. When integrability is broken, only a few of these conserved quantities survive. The remaining conserved quantities are generically transported diffusively; we derive a compact and general diffusion equation for these. The diffusion constant depends on the matrix elements of the integrability-breaking perturbation; for a certain class of integrability-breaking perturbations, including long-range interactions, the diffusion constant can be expressed entirely in terms of generalized hydrodynamic data.
TransMatch: A Transfer-Learning Scheme for Semi-Supervised Few-Shot Learning

The successful application of deep learning to many visual recognition tasks relies heavily on the availability of a large amount of labeled data which is usually expensive to obtain. The few-shot learning problem has attracted increasing attention from researchers for building a robust model upon only a few labeled samples. Most existing works tackle this problem under the meta-learning framework by mimicking the few-shot learning task with an episodic training strategy. In this paper, we propose a new transfer-learning framework for semi-supervised few-shot learning to fully utilize the auxiliary information from labeled base-class data and unlabeled novel-class data. The framework consists of three components: 1) pre-training a feature extractor on base-class data; 2) using the feature extractor to initialize the classifier weights for the novel classes; and 3) further updating the model with a semi-supervised learning method. Under the proposed framework, we develop a novel method for semi-supervised few-shot learning called TransMatch by instantiating the three components with imprinting and MixMatch. Extensive experiments on two popular benchmark datasets for few-shot learning, CUB-200-2011 and miniImageNet, demonstrate that our proposed method can effectively utilize the auxiliary information from labeled base-class data and unlabeled novel-class data to significantly improve the accuracy of few-shot learning task, and achieve new state-of-the-art results.
Vainshtein screening in bimetric cosmology

We demonstrate that the instabilities in linear cosmological perturbations in bimetric theory are the manifestation of the non-linear Vainshtein mechanism on an FRW background. The spin-2 mass serves as the cosmological Vainshtein scale in this case. This allows us to quantitatively address early universe cosmology. In particular, in a global analysis, we study data from the cosmic microwave background radiation and local measurements of the Hubble flow. We show that bimetric cosmology resolves the discrepancy in the local and early-time measurements of the Hubble scale via an effective phantom dark energy component.
An Adaptive and Fast Convergent Approach to Differentially Private Deep Learning

With the advent of the era of big data, deep learning has become a prevalent building block in a variety of machine learning or data mining tasks, such as signal processing, network modeling and traffic analysis, to name a few. The massive user data crowdsourced plays a crucial role in the success of deep learning models. However, it has been shown that user data may be inferred from trained neural models and thereby exposed to potential adversaries, which raises information security and privacy concerns. To address this issue, recent studies leverage the technique of differential privacy to design private-preserving deep learning algorithms. Albeit successful at privacy protection, differential privacy degrades the performance of neural models. In this paper, we develop ADADP, an adaptive and fast convergent learning algorithm with a provable privacy guarantee. ADADP significantly reduces the privacy cost by improving the convergence speed with an adaptive learning rate and mitigates the negative effect of differential privacy upon the model accuracy by introducing adaptive noise. The performance of ADADP is evaluated on real-world datasets. Experiment results show that it outperforms state-of-the-art differentially private approaches in terms of both privacy cost and model accuracy.
Temporal Normalizing Flows

Analyzing and interpreting time-dependent stochastic data requires accurate and robust density estimation. In this paper we extend the concept of normalizing flows to so-called temporal Normalizing Flows (tNFs) to estimate time dependent distributions, leveraging the full spatio-temporal information present in the dataset. Our approach is unsupervised, does not require an a-priori characteristic scale and can accurately estimate multi-scale distributions of vastly different length scales. We illustrate tNFs on sparse datasets of Brownian and chemotactic walkers, showing that the inclusion of temporal information enhances density estimation. Finally, we speculate how tNFs can be applied to fit and discover the continuous PDE underlying a stochastic process.
X-Ray Observations of a z ∼ 6.2 Quasar/Galaxy Merger

Quasars at early redshifts (z > 6) with companion galaxies offer unique insights into the growth and evolution of the first supermassive black holes. Here, we report on a 150 ks Chandra observation of PSO J308.0416−21.2339, a z = 6.23 quasar with a merging companion galaxy identified in [C ii] and rest-frame UV emission. With net counts, we find that PSO J308.0416−21.2339 is powerful ( in rest-frame 2.0–10.0 keV) yet soft (spectral power-law index and optical-to-X-ray slope αOX = −1.41 ± 0.11). In addition, we detect three hard-energy photons 2. ″0 to the west of the main quasar, cospatial with the brightest UV emission of the merging companion. As no soft-energy photons are detected in the same area, this is potentially indicative of a highly obscured source. With conservative assumptions, and accounting for both background fluctuations and the extended wings of the quasar’s emission, these photons only have a probability P = 0.021 of happening by chance. If confirmed by deeper observations, this system is the first high-redshift quasar and companion individually detected in X-rays and is likely a dual active galactic nucleus.
An Adaptive Similarity Measure to Tune Trust Influence in Memory-Based Collaborative Filtering

The aim of the recommender systems is to provide relevant and potentially interesting information to each user. This is fulfilled by utilizing the already recorded tendencies of similar users or detecting items similar to interested items of the user. Challenges such as data sparsity and cold start problem are addressed in recent studies. Utilizing social information not only enhances the prediction accuracy but also tackles the data sparseness challenges. In this paper, we investigate the impact of using direct and indirect trust information in a memory-based collaborative filtering recommender system. An adaptive similarity measure is proposed and the contribution of social information is tuned using two learning schemes, greedy and gradient-based optimization. The results of the proposed method are compared with state-of-the-art memory-based and model-based CF approaches on two real-world datasets, Epinions and FilmTrust. The experiments show that our method is quite effective in designing an accurate and comprehensive recommender system.
Complete reduction of integrals in two-loop five-light-parton scattering amplitudes

We reduce all the most complicated Feynman integrals in two-loop five-light-parton scattering amplitudes to master integrals, while other integrals can be reduced even more easily. Our results are expressed as a system of linear relations in block-triangle form, which are very efficient for numerical calculation. Based on this, complete next-to-next-to-leading order QCD calculation for three jets, photons, or hadrons production at hadron colliders becomes possible. In order to find out the block-triangle relations, we develop a new method which is efficient and general. The method may provide a practical solution for the bottleneck problem of reducing multiloop multiscale integrals.
Research Frontiers in Transfer Learning - a systematic and bibliometric review

Humans can learn from very few samples, demonstrating an outstanding generalization ability that learning algorithms are still far from reaching. Currently, the most successful models demand enormous amounts of well-labeled data, which are expensive and difficult to obtain, becoming one of the biggest obstacles to the use of machine learning in practice. This scenario shows the massive potential for Transfer Learning, which aims to harness previously acquired knowledge to the learning of new tasks more effectively and efficiently. In this systematic review, we apply a quantitative method to select the main contributions to the field and make use of bibliographic coupling metrics to identify research frontiers. We further analyze the linguistic variation between the classics of the field and the frontier and map promising research directions.
Quasi-powerful $p$-groups.

In this paper we introduce the notion of a quasi-powerful $p$-group for odd primes $p$. These are the finite $p$-groups $G$ such that $G/Z(G)$ is powerful in the sense of Lubotzky and Mann. We show that this large family of groups shares many of the same properties as powerful $p$-groups. For example, we show that they have a regular power structure, and we generalise a result of Fern\'andez-Alcober on the order of commutators in powerful $p$-groups to this larger family of groups. We also obtain a bound on the number of generators of a subgroup of a quasi-powerful $p$-group, expressed in terms of the number of generators of the group. We give an infinite family of examples which demonstrates this bound is close to best possible.
Formation of S0s in extreme environments I: clues from kinematics and stellar populations

Despite numerous efforts, it is still unclear whether lenticular galaxies (S0s) evolve from spirals whose star formation was suppressed, or formed trough mergers or disc instabilities. In this paper we present a pilot study of 21 S0 galaxies in extreme environments (field and cluster), and compare their spatially resolved kinematics and global stellar populations. Our aim is to identify whether there are different mechanisms that form S0s in different environments. Our results show that the kinematics of S0 galaxies in field and cluster are, indeed, different. Lenticulars in the cluster are more rotationally supported, suggesting that they are formed through processes that involve the rapid consumption or removal of gas (e.g. starvation, ram pressure stripping). In contrast, S0s in the field are more pressure supported, suggesting that minor mergers served mostly to shape their kinematic properties. These results are independent of total mass, luminosity, or disc-to-bulge ratio. On the other hand, the mass-weighted age, metallicity, and star formation time-scale of the galaxies correlate more with mass than with environment, in agreement with known relations from previous work, such as the one between mass and metallicity. Overall, our results re-enforce the idea that there are multiple mechanisms that produce S0s, and that both mass and environment play key roles. A larger sample is highly desirable to confirm or refute the results and the interpretation of this pilot study.
Model Weight Theft With Just Noise Inputs: The Curious Case of the Petulant Attacker

This paper explores the scenarios under which an attacker can claim that 'Noise and access to the softmax layer of the model is all you need' to steal the weights of a convolutional neural network whose architecture is already known. We were able to achieve 96% test accuracy using the stolen MNIST model and 82% accuracy using the stolen KMNIST model learned using only i.i. d. Bernoulli noise inputs. We posit that this theft-susceptibility of the weights is indicative of the complexity of the dataset and propose a new metric that captures the same. The goal of this dissemination is to not just showcase how far knowing the architecture can take you in terms of model stealing, but to also draw attention to this rather idiosyncratic weight learnability aspects of CNNs spurred by i.i. d. noise input. We also disseminate some initial results obtained with using the Ising probability distribution in lieu of the i.i. d. Bernoulli distribution.
Ultracompact H ii regions with extended emission: the complete view

In this paper we present the results of a morphological study performed on a sample of 28 ultracompact \hiirs~located near extended free-free emission, using radio continuum observations at 3.6~cm with the C and D VLA~configurations, with the aim of determining a direct connection between them. By using previously published observations in B and D VLA~configurations, we compiled a final catalogue of 21 ultracompact \hiirs ~directly connected with the surrounding extended emission. The observed morphology of most of the ultracompact \hiirs~in radio continuum emission is irregular (single or multi-peaked sources) and resembles a classical bubble structure in the Galactic plane with well-defined cometary arcs. Radio continuum images superimposed on colour composite \textit{Spitzer} images reinforce the assignations of direct connection by the spatial coincidence between the ultracompact components and regions of saturated 24~\micron~emission. We also find that the presence of extended emission may be crucial to understand the observed infrared-excess because an underestimation of ionizing Lyman photons was considered in previous works.
How to GAN event subtraction

Subtracting event samples is a common task in LHC simulation and analysis, and standard solutions tend to be inefficient. We employ generative adversarial networks to produce new event samples with a phase space distribution corresponding to added or subtracted input samples. We first illustrate for a toy example how such a network beats the statistical limitations of the training data. We then show how such a network can be used to subtract background events or to include non-local collinear subtraction events at the level of unweighted 4-vector events.
Didactic Lectures and Interactive Sessions in Small Groups: A Comparative Study among Undergraduate Students in Hawler College of Medicine

Aims: To study and compare didactic lectures with interactive sessions in small groups among undergraduate medical students. Study Design: A quasi-experimental research design. Place and Duration of Study: Hawler College of Medicine, between October 2011 and May 2012. Methodology: Two administrative groups of students were selected out of four groups of medical students in their final year at Hawler College of Medicine. A pretest and post test evaluation of both experimental and comparison groups was conducted using the same criteria. A questionnaire was used to address students' perception of the new teaching method. For comparing the results of both groups in the examination, we computed the mean mark achieved by each group (pre and post test). Student’s t -test was used to compare means of both groups. Research Article British Journal of Education, Society & Behavioural Science, 3(2): 144-153, 2013 145 Results: Out of 72 students who were originally included in the study, 64 students (88.8%) of both groups performed both pre and post test examinations. The age range of the students was 21-26 (mean age+ S.D 23.25+ 1.01). There was no statistically significant difference between the two means (pre and post) of the lecture format (P = 0.15), while the difference between the two means of problem-solving interactive class was statistically significant. Students in the study group showed higher marks than students in the lecture format (P = 0.059). Twenty eight (90%) students found interactive sessions more active way of learning than lectures, 29 (93%) students agreed that interactive sessions provide more group interactive skills. There were some negative attitudes like heavy workload on students (55%), and uncertainty about the accuracy of information from colleagues (52%). Conclusion: Effectiveness of small group teaching may depend on the teaching style in small groups.
Metamagnetism and magnetoresistance in CeBi single crystals

We report the synthesis of CeBi single crystals grown out of Bi self flux and a systematic study of the magnetic and transport properties with varying temperature and applied magnetic fields. From these $R(T,B)$ and $M(T,B)$ data we could assemble the temperature-field ($T-B$) phase diagram for CeBi and visualize the three dimensional $M-T-B$ surface. The magnetoresistance (MR) in the low temperature regime shows a power-law, non-saturated behavior with large MR ($\sim 3\times10^5 \%$ at $2~$K and $14~$T), along with Shubnikov-de Haas oscillations. With increasing temperatures, MR decreases, and then becomes negative for $T\gtrsim 12~$K. This crossover in MR seems to be unrelated to any specific metamagnetic transitions, but rather associated with changing from a low-temperature normal metal with an anomalously large MR to increased scattering off of local Ce moments as temperature increases.
A ternary Cahn–Hilliard–Navier–Stokes model for two-phase flow with precipitation and dissolution

We consider the incompressible flow of two immiscible fluids in the presence of a solid phase that undergoes changes in time due to precipitation and dissolution effects. Based on a seminal sharp interface model a phase-field approach is suggested that couples the Navier–Stokes equations and the solid’s ion concentration transport equation with the Cahn–Hilliard evolution for the phase fields. The model is shown to preserve the fundamental conservation constraints and to obey the second law of thermodynamics for a novel free energy formulation. An extended analysis for vanishing interfacial width reveals that in this limit the sharp interface model is recovered, including all relevant transmission conditions. Notably, the new phase-field model is able to realize Navier-slip conditions for solid–fluid interfaces in the limit.