Miracle-dz/UniFAR-FTUs huggingface dataset:
Empirical Predictions for the Period Distribution of Planets to Be Discovered by the Transiting Exoplanet Survey Satellite

Launched in 2018 April, NASA’s Transiting Exoplanet Survey Satellite (TESS) has been performing a wide-field survey for exoplanets orbiting bright stars with a goal of producing a rich database for follow-on studies. Here we present estimates of the detected exoplanet orbital periods in the 2 minute cadence mode during the TESS mission. For a two-transit detection criterion, the expected mean value of the most frequently detected orbital period is 5.01 days, with the most frequently detected range of 2.12–11.82 days in the region with observation of 27 days. Near the poles where the observational duration is 351 days, the expected mean orbital period is 10.93 days, with the most frequently detected range being from 3.35 to 35.65 days. For one transit, the most frequently detected orbital period is 8.17 days in the region with observation of 27 days and 11.25 days in the region near the poles. For the entire TESS mission containing several sectors, we estimate that the mean value of orbital period is 8.47 days for two-transit detection criterion and 10.09 days for one-transit detection criterion. If TESS yields a planet population substantially different from what is predicted here, the underlying planet occurrence rates are likely different between the stellar sample probed by TESS and that by Kepler.
SinReQ: Generalized Sinusoidal Regularization for Low-Bitwidth Deep Quantized Training

Deep quantization of neural networks (below eight bits) offers significant promise in reducing their compute and storage cost. Albeit alluring, without special techniques for training and optimization, deep quantization results in significant accuracy loss. To further mitigate this loss, we propose a novel sinusoidal regularization, called SinReQ1, for deep quantized training. SinReQ adds a periodic term to the original objective function of the underlying training algorithm. SinReQ exploits the periodicity, differentiability, and the desired convexity profile in sinusoidal functions to automatically propel weights towards values that are inherently closer to quantization levels. Since, this technique does not require invasive changes to the training procedure, SinReQ can harmoniously enhance quantized training algorithms. SinReQ offers generality and flexibility as it is not limited to a certain bitwidth or a uniform assignment of bitwidths across layers. We carry out experimentation using the AlexNet, CIFAR-10, ResNet-18, ResNet-20, SVHN, and VGG-11 DNNs with three to five bits for quantization and show the versatility of SinReQ in enhancing multiple quantized training algorithms, DoReFa [32] and WRPN [24]. Averaging across all the bit configurations shows that SinReQ closes the accuracy gap between these two techniques and the full-precision runs by 32.4% and 27.5%, respectively. That is improving the absolute accuracy of DoReFa and WRPN by 2.8% and 2.1%, respectively.
Self-Stabilizing Snapshot Objects for Asynchronous Fail-Prone Network Systems

A snapshot object simulates the behavior of an array of single-writer/multi-reader shared registers that can be read atomically. Delporte-Gallet et al. proposed two fault-tolerant algorithms for snapshot objects in asynchronous crash-prone message-passing systems. Their first algorithm is non-blocking; it allows snapshot operations to terminate once all write operations had ceased. It uses O(n) messages of O(n v) bits, where $n$ is the number of nodes and v is the number of bits it takes to represent the object. Their second algorithm allows snapshot operations to always terminate independently of write operations. It incurs O(n**2) messages. The fault model of Delporte-Gallet et al. considers both node failures (crashes). We aim at the design of even more robust snapshot objects. We do so through the lenses of self-stabilization---a very strong notion of fault-tolerance. In addition to Delporte-Gallet et al.'s fault model, a self-stabilizing algorithm can recover after the occurrence of transient faults; these faults represent arbitrary violations of the assumptions according to which the system was designed to operate (as long as the code stays intact). In particular, in this work, we propose self-stabilizing variations of Delporte-Gallet et al.'s non-blocking algorithm and always-terminating algorithm. Our algorithms have similar communication costs to the ones by Delporte-Gallet et al. and O(1) recovery time (in terms of asynchronous cycles) from transient faults. The main differences are that our proposal considers repeated gossiping of O(v) bits messages and deals with bounded space (which is a prerequisite for self-stabilization). Lastly, we explain how to extend the proposed solutions to reconfigurable ones.
Effect of Container Color on Substrate Temperatures and Growth of Red Maple and Redbud

Heat stress is problematic to root growth in the production of containerized nursery plants. Container color may moderate effects of solar radiation on substrate temperatures. Studies were conducted near Manhattan, KS, to evaluate effects of con- tainer color on growth of roots and shoots in bush beans (Phaseolus vulgaris L.), red maple (Acer rubrum L.), and eastern redbud (Cercis canadensis L.). Four treatments among studies included containers colored flat and gloss white, silver, and black; a green container color treatment was added to the tree studies. Plants were grown in bark-based soil-less substrate and temperatures were measured at 5-cm depths in the south sides and centers. After 4 months, plant variables were measured. Roots were separated into three sections: core, north, and south. In the bean study, substrate temperatures at the south sideofthecontaineraveraged lowestinflatandglosswhite('36 8C)andgreatest inblack containers (50.3 8C). Root density at the south side was reduced in beans by 63% to 71% in black compared with flat and gloss white. In heat-sensitive maples, substrate tem- peratures at the south side of containers averaged up to 7.7 8C greater in black and green than in other treatments. Substrate temperatures in the center averaged 3.5 to 3.8 8C greater in black than in flat and gloss white, resulting in up to 2.5 times greater root density in flat and gloss white than in black containers. In heat-tolerant redbuds, the effectsofcontainercoloronwhole-plantgrowthwere lessevident. Datasuggestthatheat- sensitiveplantsbenefitfrombeinggrowninwhitecontainersorpaintingoutersurfacesof green and black containers white.
A weakly supervised sequence tagging and grammar induction approach to semantic frame slot filling

This paper describes continuing work on semantic frame slot filling for a command and control task using a weakly-supervised approach. We investigate the advantages of using retraining techniques that take the output of a hierarchical hidden markov model as input to two inductive approaches: (1) discriminative sequence labelers based on conditional random fields and memory-based learning and (2) probabilistic context-free grammar induction. Experimental results show that this setup can significantly improve F-scores without the need for additional information sources. Furthermore, qualitative analysis shows that the weakly supervised technique is able to automatically induce an easily interpretable and syntactically appropriate grammar for the domain and task at hand.
Functional income distribution and aggregate demand in the Euro area

An increase in the wage share has contradictory effects on the subaggregates of aggregate demand. Private consumption expenditures ought to increase because wage incomes typically are associated with higher consumption propensities than capital incomes. Investment expenditures ought to be negatively affected because investment will positively depend on profits. Net exports will be negatively affected because an increase in the wage share corresponds to an increase in unit labour costs and thus a loss in competitiveness. Therefore, theoretically, aggregate demand can be either wage-led or profit-led depending on how these effects add up. The results will crucially depend on how open the economy is internationally. The paper estimates a post-Kaleckian macro model incorporating these effects for the Euro area and finds that the Euro area is presently in a wage-led demand regime. Implications for wage policies are discussed.
Representation of strongly independent preorders by sets of scalar-valued functions

We provide conditions under which an incomplete strongly independent preorder on a convex set X can be represented by a set of mixture preserving real-valued functions. We allow X to be infinite dimensional. The main continuity condition we focus on is mixture continuity. This is sufficient for such a representation provided X has countable dimension or satisfies a condition that we call Polarization.
Search for Intra-day Optical Variability in γ-Ray-loud Blazars S5 0716+714 and 3C 273

We present the photometric observations of blazars S5 0716+714 and 3C 273 with high temporal resolution (30–60 s) in the I or R bands. The observations were performed with a 1.02 m optical telescope from 2007 March 7 to 2012 May 16. The F-test, one-way analysis of variance (ANOVA) test, and z-transformed discrete correlation function (ZDCF) cross-correlation zero lag test are used to search for intra-day variability (IDV). Four and five reliable IDVs survive three tests for S5 0716+714 and 3C 273, respectively. IDVs are found for S5 0716+714 and 3C 273. A flare on 2008 May 8 has ΔI ≈ 0.06 ± 0.01 mag in a duration of 0.54 hr for S5 0716+714. A flare on 2011 May 10 shows ΔR ≈ 0.05 ± 0.01 mag in a duration of 0.40 hr for 3C 273. Sharp dips appear on 2011 May 9 for 3C 273 and show ΔR ≈ 0.05 ± 0.01 mag. Under the assumptions that the IDV is tightly connected to black hole mass, M•, and that the flare durations are representative of the minimum characteristic timescales, we can estimate upper bounds to M•. In the case of the Kerr black holes, M• ≲ 108.91 M⊙ and M• ≲ 109.02 M⊙ are given for S5 0716+714 and 3C 273, respectively. These mass measurements are consistent with those measurements reported in the literature. Also, we discuss the origins of optical variations found in this work.
Intelligent fuzzy multi-objective optimization: analysis and new research directions

Multi-objectives decision making (MODM) represents an interest area of research since most real life problems have a set of conflict objectives. MODM has its roots in late-nineteenth-century welfare economics, in the works of Edgeworth and Pareto. Because of the shortcomings that faces the FMODM, it attracts the attentions of researchers to enhance the field of FMODM by developing more powerful links (bridges) between it and other sciences such as artificial intelligence. This paper presents a review of the connections between artificial intelligence and FMODM to deal with its shortcomings. Also, It indicated the new direction for more research work.
Near Optimal Coflow Scheduling in Networks

The coflow scheduling problem has emerged as a popular abstraction in the last few years to study data communication problems within a data center[6]. In this basic framework, each coflow has a set of communication demands and the goal is to schedule many coflows in a manner that minimizes the total weighted completion time. A coflow is said to complete when all its communication needs are met. This problem has been extremely well studied for the case of complete bipartite graphs that model a data center with full bisection bandwidth and several approximation algorithms and effective heuristics have been proposed recently[1,2,29]. In this work, we study a slightly different model of coflow scheduling in general graphs (to capture traffic between data centers [15,29]) and develop practical and efficient approximation algorithms for it. Our main result is a randomized 2 approximation algorithm for the single path and free path model, significantly improving prior work. In addition, we demonstrate via extensive experiments that the algorithm is practical, easy to implement and performs well in practice.
On the Lower Bound of the Divisibility of Exponential Sums in Binomial Case

Francis Castro, et al [2] computed the exact divisibility of families of exponential sums associated to binomials $F(X) = aX^{d_1} + bX^{d_2}$ over $\mathbb{F}_p$, and a conjecture is presented for related work. Here we study this question.
The True Sample Complexity of Identifying Good Arms

We consider two multi-armed bandit problems with $n$ arms: (i) given an $\epsilon > 0$, identify an arm with mean that is within $\epsilon$ of the largest mean and (ii) given a threshold $\mu_0$ and integer $k$, identify $k$ arms with means larger than $\mu_0$. Existing lower bounds and algorithms for the PAC framework suggest that both of these problems require $\Omega(n)$ samples. However, we argue that these definitions not only conflict with how these algorithms are used in practice, but also that these results disagree with intuition that says (i) requires only $\Theta(\frac{n}{m})$ samples where $m = |\{ i : \mu_i > \max_{i \in [n]} \mu_i - \epsilon\}|$ and (ii) requires $\Theta(\frac{n}{m}k)$ samples where $m = |\{ i : \mu_i > \mu_0 \}|$. We provide definitions that formalize these intuitions, obtain lower bounds that match the above sample complexities, and develop explicit, practical algorithms that achieve nearly matching upper bounds.
PREStO: A Systematic Framework for Blockchain Consensus Protocols

The rapid evolution of blockchain technology has brought together stakeholders from fundamentally different backgrounds. The result is a diverse ecosystem, as exemplified by the development of a wide range of different blockchain protocols. This raises questions for decision and policy makers: How do different protocols compare? What are their tradeoffs? Existing efforts to survey the area reveal a fragmented terminology and the lack of a unified framework to reason about the properties of blockchain protocols. In this article, we work toward bridging this gap. We present a five-dimensional design space with a modular structure in which protocols can be compared and understood. Based on these five axes—optimality, stability, efficiency, robustness, and persistence—we organize the properties of existing protocols in subcategories of increasing granularity. The result is a dynamic scheme—termed the PREStO framework—which aids the interaction between stakeholders of different backgrounds, including managers and investors, and which enables systematic reasoning about blockchain protocols. We illustrate its value by comparing existing protocols and identifying research challenges, hence making a first step toward understanding the blockchain ecosystem through a more comprehensive lens.
Constraints on past plate and mantle motion from new ages for the Hawaiian‐Emperor Seamount Chain

Estimates of the relative motion between the Hawaiian and Louisville hot spots have consequences for understanding the role and character of deep Pacific‐mantle return flow. The relative motion between these primary hot spots can be inferred by comparing the age records for their seamount trails. We report 40Ar/39Ar ages for 18 lavas from 10 seamounts along the Hawaiian‐Emperor Seamount Chain (HESC), showing that volcanism started in the sharp portion of the Hawaiian‐Emperor Bend (HEB) at ≥47.5 Ma and continued for ≥5 Myr. The slope of the along‐track distance from the currently active Hawaiian hot spot plotted versus age is constant (57 ± 2 km/Myr) between ∼57 and 25 Ma in the central ∼1900 km of the seamount chain, including the HEB. This model predicts an age for the oldest Emperor Seamounts that matches published ages, implying that a linear age‐distance relationship might extend back to at least 82 Ma. In contrast, Hawaiian age progression was much faster since at least ∼15 Ma and possibly as early as ∼27 Ma. Linear age‐distance relations for the Hawaii‐Emperor and Louisville seamount chains predict ∼300 km overall hot spot relative motion between 80 and 47.5 Ma, in broad agreement with numerical models of plumes in a convecting mantle, and paleomagnetic data. We show that a change in hot spot relative motion may also have occurred between ∼55 Ma and ∼50 Ma. We interpret this change in hot spot motion as evidence that the HEB reflects a combination of hot spot and plate motion changes driven by the same plate/mantle reorganization.
The near and mid-infrared photometric properties of known redshift z ≥ 5 quasars

We assemble a catalogue of 488 spectroscopically confirmed very high (z ≥ 5.00) redshift quasars (VHzQ) and report their near- (ZYJHKs/K) and mid- (WISE W1234) infrared properties. 97 per cent of the VHzQ sample is detected in one or more near-infrared (NIR) band, with lack of coverage rather than lack of depth being the reason for the non-detections. 389 (80 per cent) of the very high redshift quasars are detected at 3.4 μm in the W1 band from the unWISE catalogue and all of the z ≥ 7 quasars are detected in both unWISE W1 and W2. Using archival Wide Field Camera (WFCAM)/United Kingdom Infrared Telescope (UKIRT) and VISTA Infrared Camera (VIRCAM)/Visible and Infrared Survey Telescope for Astronomy (VISTA) data we check for photometric variability that might be expected from super-Eddington accretion. We find 28 of the quasars have sufficient NIR measurements and signal-to-noise ratio to look for variability. Weak variability was detected in multiple bands of Sloan Digital Sky Survey (SDSS) J0959+0227, and very marginally in the Y-band of MMT J0215-0529. Only one quasar, SDSS J0349+0034, shows significant differences between WFCAM and VISTA magnitudes in one band. With supermassive black hole accretion likely to be redshift invariant up to very high redshift, further monitoring of these sources is warranted. All the data, analysis codes and plots used and generated here can be found at: github.com/d80b2t/VHzQ.
Factors Influencing Choice of Sources for Domestic Energy Used in Households in Thuti Sub-Location, Othaya

Energy is one of the key drivers of economic, social and political development of the world hence its increase in demand. Countries are faced with problems of sustainable energy sources for home use, which will accelerate countries economic growth. During the 2000s several programmes aiming at testing and disseminating energy saving technologies were implemented in Kenya (Smith et al., 2000). One of these technologies was improved cook stoves, which was intended to increase the efficiency of using energy from Biomass and other sources. The purpose of this study is to examine factors influencing choice of sources for domestic energy used in Thuti sub-location in Othaya sub-county, which included among others socio-cultural and economic factors, stakeholders influence, and the switching factors from traditional to more efficient and cleaner fuels and technologies.Descriptive survey research was design was used to collect required data.The target population of 275 households where systematic random sampling was used to select 27 households. For qualitative data collection, 12 key informants were selected using purposive sampling from Thuti Sub-location were used. The result showed that the source of fuel wood used in Thuti Sub-location from their own farms and Karima forest, representing 73.1% and 26.9% of the total population respectively. This concurs with the objectives of the Green Belt Movement (GBM), which is to encourage sustainable fuel wood usage for the household through planting of trees in their farms while at the same time rehabilitating Karima Forest.On the adoption of alternative sources of energy, the result showed that the households learned of these sources from friends represented at 40.7% followed by Neighbours, 25.9 % and parents at 14.8%. Indicating that there is a close association among the households in their day-to-day activities and choice and sources of domestic energy used. The overall findings underlined the importance in social groups, stakeholders and government advocacy in the choice and sources of domestic energy to be adopted for efficient cooking and sustainability in Thuti Sub-location. This study therefore will be of significant to; policy makers, researchers, residents of rural households to build a case for intervention on the most efficient and clean choice for domestic energy among the rural households in Thuti Sub-location and the environs. Key w ords: Domestic energy, choice, households, adoption, sustainability
Personalized Apprenticeship Learning from Heterogeneous Decision-Makers

Human domain experts solve difficult planning problems by drawing on years of experience. In many cases, computing a solution to such problems is computationally intractable or requires encoding heuristics from human domain experts. As codifying this knowledge leaves much to be desired, we aim to infer their strategies through observation. The challenge lies in that humans exhibit heterogeneity in their latent decision-making criteria. To overcome this, we propose a personalized apprenticeship learning framework that automatically infers a representation of all human task demonstrators by extracting a human-specific embedding. Our framework is built on a propositional architecture that allows for distilling an interpretable representation of each human demonstrator's decision-making.
Alternative Performance Metrics And Optimal Strategies For Peer-To-Peer File Dissemination Networks

Peer-to-peer (P2P) file distribution is a scalable way to disseminate content to a wide audience. For a P2P network, one fundamental performance metric is the average time needed to deliver a certain file to all peers, which in general depends on the topology of the network and the scheduling of transmissions. Despite its apparent importance, how to minimize average finish time remains an open question even for a fully-connected network. This is mainly due to the analytical challenges that come with the combinatorial structures of the problem. In this thesis, by using the water-filling technique, we determine how each peer should use its capacity to sequentially minimize the file download times in an upload-constrained P2P network. Furthermore, it is shown that this scheduling also minimizes average finish time for the network. This optimality result not only provides fundamental insight to scheduling in such P2P systems, but also can serve as a benchmark to evaluate practical algorithms and illustrate the scalability of P2P networks. An overview of existing P2P systems is given, analytical challenges posed by the inclusion of download constraints are considered, and further areas for research in P2P optimality are discussed.
Spin and valley waves in Dirac semimetals with population imbalance

We find inter-valley wave collective mode in graphene and three-dimensional Weyl-Dirac semimetals in the presence of valley population imbalance. The dispersion relation of this mode is gapless, proportional to the square of the wavevector at small frequencies, and inversely proportional to the electron-electron exchange interaction energy. The valley wave serves as an energy gain source for the external field, that generates the inter-valley transitions. The spin wave analog is discussed for the case of semimetal with the non-equilibrium spin orientation.