Miracle-dz/UniFAR-FTUs huggingface dataset:
Quantifying the vertical transport of CHBr3 and CH2Br2 over the western Pacific

Abstract. We use the GEOS-Chem global 3-D atmospheric chemistry transport model to interpret atmospheric observations of bromoform (CHBr3) and dibromomethane (CH2Br2) collected during the CAST and CONTRAST aircraft measurement campaigns over the western Pacific, January–February 2014. We use a new linearized, tagged version of CHBr3 and CH2Br2, allowing us to study the influence of emissions from specific geographical regions on observed atmospheric variations. The model describes 32 %–37 % of CHBr3 and 15 %–45 % of CH2Br2 observed variability during CAST and CONTRAST, reflecting model errors in vertical transport. The model has a mean positive bias of 30 % that is larger near the surface, reflecting errors in the poorly constrained prior emission estimates. We find using the model that observed variability of CHBr3 and CH2Br2 is driven by open ocean emissions where there is deep convection. Atmospheric variability above 6 km includes a significant contribution from coastal oceans, but it is still dominated by emissions from the open ocean and by older air masses that originate upwind. In the absence of reliable ocean emission estimates, we use a new physical age-of-air simulation to determine the relative abundance of halogens delivered by CHBr3 and CH2Br2 to the tropical transition layer (TTL). We find that 76 % (92 %) of air masses that originate from the ocean reach the TTL within two (three) atmospheric e-folding lifetimes of CHBr3 and almost all of them reach the TTL within one e-folding lifetime of CH2Br2. Over the duration of CAST and CONTRAST, and over our study region, oceans delivered a mean (range) CHBr3 and CH2Br2 mole fraction of 0.46 (0.13–0.72) and 0.88 (0.71–1.01) pptv, respectively, to the TTL, and a mean (range) Bry mole fraction of 3.14 (1.81–4.18) pptv from source gases to the upper troposphere.
Guidelines for the management of valvular heart disease The Task Force for the Management of Valvular Heart Disease of the European Society of Cardiology ( ESC ) and the European Association for CardioThoracic Surgery ( EACTS )

Authors/Task Force Members: Helmut Baumgartner* (ESC Chairperson) (Germany), Volkmar Falk* (EACTS Chairperson) (Germany), Jeroen J. Bax (The Netherlands), Michele De Bonis (Italy), Christian Hamm (Germany), Per Johan Holm (Sweden), Bernard Iung (France), Patrizio Lancellotti (Belgium), Emmanuel Lansac (France), Daniel Rodriguez Mu~ noz (Spain), Raphael Rosenhek (Austria), Johan Sjögren (Sweden), Pilar Tornos Mas (Spain), Alec Vahanian (France), Thomas Walther (Germany), Olaf Wendler (UK), Stephan Windecker (Switzerland), Jose Luis Zamorano (Spain)
KNOWLEDGE - BASED MODEL OF COMPETITION IN RESTAURANT INDUSTRY: A QUALITATIVE STUDY ABOUT CULINARY COMPETENCE, CREATIVITY, AND INNOVATION IN FIVE FULL - SERVICE RESTAURANTS IN JAKARTA

The purpose of the study is to have an in-depth description in the form of the analysis of culinary competence, creativity and innovation that develops knowledge-based model of competence in full-service restaurant business. Studies on restaurant generally focused on customers more particularly customer’s satisfaction and loyalty, and very few studies discussed internal competitive factors in restaurant business. The study aims at filling out the research gap, using knowledge-based approach that is through culinary competence, creativity and innovation. The main question is how to the restaurants develop competitive sense using thoe aspects of internal capabilities. The study is a qualitative study taking five full-service restaurants in Jakarta as case study. The data collection methods are observations and in-depth interviews with the restaurant owners, the managers or heads of restaurants, the chefs and kitchen staffs, the waiters and floor managers. The findings show that the implementation of culinary competence is carried out by the chefs designed by the restaurant owners, where the effectiveness really depends on how consistent the implementation of culinary competence is as well as how accurate the identification of customers’ segmentation is. In terms of creativity, it is found out that the simultaneous implementation of creativity between sustainable, incremental, break-through, and profitable creativities will support the success of the restaurants to win the competition. As an addition, in terms of innovation, the findings reveal that the restaurants create innovations in various aspects (product, process, function, operation, coordination) in order to attract more customers. In general, the findings of the study show should a restaurant implement culinary competition creativity and innovation by developing knowledge as source of competitive sense to win the competition in restaurant business.
AGE OF STRATOSPHERIC AIR: THEORY, OBSERVATIONS, AND MODELS

We review the relationship between tracer distributions and transport timescales in the stratosphere and discuss the use of timescales to evaluate and constrain theories and numerical models of the stratosphere. The “age spectrum,” the distribution of transit times since stratospheric air last made tropospheric contact, provides a way to understand the transport information of tracers, how sensitive different tracers are to various transport processes, and how to use tracers in combination to constrain transport rates. Trace gas observations can be used to infer aspects of the age spectrum, most commonly the “mean age,” but also the shape of the spectrum. Observational inferences of transport timescales provide stringent tests of numerical models independent of photochemistry, and comparisons of these observations with chemical transport models have highlighted certain problems with transport in the models. Age simulations and comparisons with data can now be considered standard tests of stratospheric models.
Sandpile models

This survey is an extended version of lectures given at the Cornell Probability Summer School 2013. The fundamental facts about the Abelian sandpile model on a finite graph and its connections to related models are presented. We discuss exactly computable results via Majumdar and Dhar's method. The main ideas of Priezzhev's computation of the height probabilities in 2D are also presented, including explicit error estimates involved in passing to the limit of the infinite lattice. We also discuss various questions arising on infinite graphs, such as convergence to a sandpile measure, and stabilizability of infinite configurations.
Structural Causal Bandits: Where to Intervene?

We study the problem of identifying the best action in a sequential decision-making setting when the reward distributions of the arms exhibit a non-trivial dependence structure, which is governed by the underlying causal model of the domain where the agent is deployed. In this setting, playing an arm corresponds to intervening on a set of variables and setting them to specific values. In this paper, we show that whenever the underlying causal model is not taken into account during the decision-making process, the standard strategies of simultaneously intervening on all variables or on all the subsets of the variables may, in general, lead to suboptimal policies, regardless of the number of interventions performed by the agent in the environment. We formally acknowledge this phenomenon and investigate structural properties implied by the underlying causal model, which lead to a complete characterization of the relationships between the arms' distributions. We leverage this characterization to build a new algorithm that takes as input a causal structure and finds a minimal, sound, and complete set of qualified arms that an agent should play to maximize its expected reward. We empirically demonstrate that the new strategy learns an optimal policy and leads to orders of magnitude faster convergence rates when compared with its causal-insensitive counterparts.
iPipe : A Framework for Building Datacenter Applications Using In-networking Processors

The increasing disparity of data center link bandwidth and CPU computing power motivates the use of in-networking processors to co-execute parts of datacenter applications. By offloading computations onto a NIC-side processor, we can not only save endhost server CPU cores, but also achieve lower request latency. However, building applications with an in-networking processor brings three challenges: programmability, offloading constraints, and multi-tenancy support. This work proposes iPipe, a framework for developing datacenter services that can take advantage of an innetworking processor on a programmable NIC. iPipe provides an actor programming model and exposes various APIs through the iPipe runtime. It enables efficient NIC hardware utilization and fair computational resource sharing via a lightweight actor scheduler, distributed shared objects, a cross PCIe messaging tier, a shim networking stack, and a dynamic resource manager. We build three datacenter applications (i.e., a real-time data analytics engine, a distributed transaction system, and a replicated key-value store) based on iPipe and prototype them using commodity programmable NICs (i.e., Cavium LiquidIO). Real system based evaluations show that when processing 10Gbps of application bandwidth, NIC-side offloading reduces the average number of beefy Intel cores (of three applications) from 2.2 to 0.4, along with up to 15. 8μs latency savings. We also demonstrate that iPipe is able to provide performance isolation with fair bandwidth allocation, and that it scales to multiple programmable NICs.
Is there any simple tool to enhance physical activity in patients with COPD

Background: Physical inactivity is considered as a complex behaviour that predicts poor outcomes in COPD and hastens the disease progression. Pulmonary rehabilitation has been endorsed as an effective non-pharmacological therapy to enhance exercise capacity and quality of life in patients with COPD, yet its effects on promotion of physical activity is unknown. Furthermore, the recent international guidelines on pulmonary rehabilitation emphasize on “long-term health enhancing behaviour change” and increase in physical activity is considered to enhance positive health benefits in COPD. The current study had explored the effects of ground walking prescription combined with comprehensive pulmonary rehabilitation to promote physical activity in patients with COPD. Methods: Retrospective analysis were performed on 33 COPD patients [FEV1: 59.08 % (± 22.00)] enrolled to a comprehensive 8 weeks out patients PR programme (PRP). Patients were provided with individualized ground walking prescription and feedback during PRP. Paired t-test was used to examine mean difference between outcomes at Week 0 and Week 8. A p - value < 0.05 was considered significant. Results: 29 patients completed the 8 weeks out-patient PRP. Significant improvements were observed in 6 min walk test (p ˂ 0.0001), incremental shuttle walk test (p ˂ 0.0081), CAT score (p ˂ 0.0017), Chronic Respiratory Disease Questionnaire total score (p ˂ 0.0002) and mMRC dyspnea scale (p ˂ 0.0001) at Week 8 compared to Week 0. Mean walking duration per session and days per week improved from Week 0 to Week 8 (p ˂ 0.0001 and p = 0.0054). Conclusion: This study suggests that inclusion of ground walking prescription would be pragmatic behavioral intervention during comprehensive PR to stimulate physical activity behavior in patients with COPD.
Leveraging Computer Vision and Humanoid Robots to Detect Autism in Toddlers

Autism Spectrum Disorder is a developmental disorder often characterized by limited social skills, repetitive behaviors, obsessions, and/or routines. Using the small humanoid robot NAO, we designed an interactive program to elicit common social cues from toddlers while in the presence of trained psychologists during standard toddler assessments. Our experimental design captures four different videos of the child-robot interaction, and we intend to use captured video data to create a software package that helps clinicians diagnose autism spectrum disorder earlier than the current average age of 5 years. As part of our plan for automated video analysis to flag autistic behavior, we built and tested semi-automated software that logs proxemics information, and tested it on a large group of typically developing children with the robot program.
Growth performances of female and male Holstein calves fed with milk and milk replacers.

The objective of this study was to compare growth performances of male and female Holstein calves fed milk and milk replacers. A total of 60 Holstein calves were used in the study. Calves were divided into three equal groups. In each group, there were 10 female and 10 male calves. Calves were offered colostrum for 3 days after birth and were weighed at fourth day for the trial. Initial body weights of calves in dietary treatments were statistically similar. The first, second and third groups were fed milk, milk replacer-I (CP 21% and CF 16.5%) and milk replacer-II (CP 24% and CF 18%), respectively. In addition to milk and milk replacers, calves were supplemented with ad libitum concentrate feed and alfalfa. Dietary treatment was significantly effective (P<0.05) on body weight of calves at 60 days of age. In conclusion, growth performances of calves increased with increasing protein content of milk replacer had better than those of calves fed milk replacer containing lowprotein. Therefore, during the suckling period, in feeding of Holstein calves, milk or milk replacer containing high-protein should be preferred primarily.
Economic Impacts of Climate Change on Two Mexican Coastal Fisheries: Implications for Food Security

Abstract This paper has a twofold objective: First, to estimate the changes in landings value by 2030 for two Mexican coastal fisheries, specifically shrimp and sardine fisheries, as a consequence of climate change; and second, to discuss the implications of such impacts for food security. A dynamic panel model was used for the Mexican fisheries sector, with data from 1990 through 2009. The results suggest that shrimp production will be negatively affected, while in contrast, the sardine fishery is expected to benefit from the increase in temperature. Most losses/gains would be observed in the NW Mexican Pacific, where the fishing sector has an important role in the local economy, representing a risk to food security in both direct and indirect ways.
The Possible Trinity: Optimal Interest Rate, Exchange Rate, and Taxes on Capital Flows in a DSGE Model for a Small Open Economy

Abstract A traditional way of thinking about the exchange rate (XR) regime and capital account openness has been framed in terms of the ‘impossible trinity’ or ‘trilemma’, in which policymakers can only have 2 of 3 possible outcomes: open capital markets, monetary independence and pegged XRs. This paper is an extension of Escude (A DSGE Model for a SOE with Systematic Interest and Foreign Exchange Policies in Which Policymakers Exploit the Risk Premium for Stabilization Purposes, 2013), which focused on interest rate and XR policies, since it introduces the third vertex of the ‘trinity’ in the form of taxes on private foreign debt. These affect the risk-adjusted uncovered interest parity equation and hence influence the SOE’s international financial flows. A useful way to illustrate the range of policy alternatives is to associate them with the faces of a triangle. Each of 3 possible government intervention policies taken individually (in the domestic currency bond market, in the FX market, and in the foreign currency bonds market) corresponds to one of the vertices of the triangle, each of the 3 possible pairs of intervention policies corresponds to one of its 3 edges, and the 3 simultaneous intervention policies taken jointly correspond to its interior. This paper shows that this interior, or ‘possible trinity’ is quite generally not only possible but optimal, since the CB obtains a lower loss when it implements a policy with all three interventions.
Understanding the Changes of Stratospheric Water Vapor in Coupled Chemistry-Climate Model Simulations

Abstract Past and future climate simulations from the Goddard Earth Observing System Chemistry–Climate Model (GEOS CCM), with specified boundary conditions for sea surface temperature, sea ice, and trace gas emissions, have been analyzed to assess trends and possible causes of changes in stratospheric water vapor. The simulated distribution of stratospheric water vapor in the 1990s compares well with observations. Changes in the cold point temperatures near the tropical tropopause can explain differences in entry stratospheric water vapor. The average saturation mixing ratio of a 20° latitude by 15° longitude region surrounding the minimum tropical saturation mixing ratio is shown to be a useful diagnostic for entry stratospheric water vapor and does an excellent job reconstructing the annual average entry stratospheric water vapor over the period 1950–2100. The simulated stratospheric water vapor increases over the 50 yr between 1950 and 2000, primarily because of changes in methane concentrations, offse.
Hyper-efficient model-independent Bayesian method for the analysis of pulsar timing data

A new model independent method is presented for the analysis of pulsar timing data and the estimation of the spectral properties of an isotropic gravitational wave background (GWB). We show that by rephrasing the likelihood we are able to eliminate the most costly aspects of computation normally associated with this type of data analysis. When applied to the International Pulsar Timing Array Mock Data Challenge data sets this results in speedups of approximately 2 to 3 orders of magnitude compared to established methods. We present three applications of the new likelihood. In the low signal to noise regime we sample directly from the power spectrum coefficients of the GWB signal realization. In the high signal to noise regime, where the data can support a large number of coefficients, we sample from the joint probability density of the power spectrum coefficients for the individual pulsars and the GWB signal realization. Critically in both these cases we need make no assumptions about the form of the power spectrum of the GWB, or the individual pulsars. Finally we present a method for characterizing the spatial correlation between pulsars on the sky, making no assumptions about the form of that correlation, and therefore providing the only truly general Bayesian method of confirming a GWB detection from pulsar timing data.
The Neural LASSO: Local Linear Sparsity for Interpretable Explanations

Neural networks often perform better on prediction problems than simpler classes of models, but their behavior is difﬁcult to explain. This makes it challenging to trust their predictions in safety critical domains. Recent work has focused on explaining their predictions using local linear approximations [1, 10], but these explanations can be complex when they depend on many features and it is unclear if they can be used to understand global trends in model behavior. In this work, we train neural networks to have sparse local explanations by applying L1 penalties to their input gradients. We show explanations of these networks depend on fewer inputs while their performance remains comparable across datasets and architectures. We illustrate how our approach encourages a different kind of sparsity than L1 weight decay. In a case study with ICU data, we observe that gradients vary smoothly over the input space, which suggests they can be used to gain insight into the global behavior of the model.
Geographic Variation in Germination Traits in Melia azedarach and Rhaphiolepis umbellata

Some plant species traits may not be uniform across populations distributed across a wide latitudinal range. This study examined intraspecies variation in the effects of cold stratification on the germination of seeds of two widespread trees, Rhaphiolepis umbellata (Rosaceae) and Melia azedarach (Meliaceae), collected from the subtropical Ogasawara Islands (southern seeds) and the temperate Japan mainland (northern seeds). Under the no-treatment control, the southern seeds germinated faster in R. umbellata and achieved a higher germination percentage in M. azedarach. The regional differences in germination performance were reduced by cold stratification. It was reasonable that these germination traits increase fitness under each climate region. Because the remote Ogasawara populations are sufficiently isolated to have developed some distinct characteristics, even common, widespread species may have important conservation value where they exist within insular biota.
Integrating human and machine intelligence in galaxy morphology classification tasks

Quantifying galaxy morphology is a challenging yet scientifically rewarding task. As the scale of data continues to increase with upcoming surveys, traditional classification methods will struggle to handle the load. We present a solution through an integration of visual and automated classifications, preserving the best features of both human and machine. We demonstrate the effectiveness of such a system through a re-analysis of visual galaxy morphology classifications collected during the Galaxy Zoo 2 (GZ2) project. We reprocess the top-level question of the GZ2 decision tree with a Bayesian classification aggregation algorithm dubbed SWAP, originally developed for the Space Warps gravitational lens project. Through a simple binary classification scheme, we increase the classification rate nearly 5-fold classifying 226 124 galaxies in 92 d of GZ2 project time while reproducing labels derived from GZ2 classification data with 95.7 per cent accuracy. We next combine this with a Random Forest machine learning algorithm that learns on a suite of non-parametric morphology indicators widely used for automated morphologies. We develop a decision engine that delegates tasks between human and machine and demonstrate that the combined system provides at least a factor of 8 increase in the classification rate, classifying 210 803 galaxies in just 32 d of GZ2 project time with 93.1 per cent accuracy. As the Random Forest algorithm requires a minimal amount of computational cost, this result has important implications for galaxy morphology identification tasks in the era of Euclid and other large-scale surveys.