Miracle-dz/UniFAR-FTUs huggingface dataset:
Estimating temporal and spatial variation of ocean surface p CO 2 in the North Pacific using a self-organizing map neural network technique

This study uses a neural network technique to produce maps of the partial pressure of oceanic carbon dioxide ( p CO 2 sea ) in the North Pacific on a 0.25° latitude × 0.25° longitude grid from 2002 to 2008. The p CO 2 sea distribution was computed using a self-organizing map (SOM) originally utilized to map the p CO 2 sea in the North Atlantic. Four proxy parameters – sea surface temperature (SST), mixed layer depth, chlorophyll a concentration, and sea surface salinity (SSS) – are used during the training phase to enable the network to resolve the nonlinear relationships between the p CO 2 sea distribution and biogeochemistry of the basin. The observed p CO 2 sea data were obtained from an extensive dataset generated by the volunteer observation ship program operated by the National Institute for Environmental Studies (NIES). The reconstructed p CO 2 sea values agreed well with the p CO 2 sea measurements, with the root-mean-square error ranging from 17.6 μatm (for the NIES dataset used in the SOM) to 20.2 μatm (for independent dataset). We confirmed that the p CO 2 sea estimates could be improved by including SSS as one of the training parameters and by taking into account secular increases of p CO 2 sea that have tracked increases in atmospheric CO 2 . Estimated p CO 2 sea values accurately reproduced p CO 2 sea data at several time series locations in the North Pacific. The distributions of p CO 2 sea revealed by 7 yr averaged monthly p CO 2 sea maps were similar to Lamont-Doherty Earth Observatory p CO 2 sea climatology, allowing, however, for a more detailed analysis of biogeochemical conditions. The distributions of p CO 2 sea anomalies over the North Pacific during the winter clearly showed regional contrasts between El Nino and La Nina years related to changes of SST and vertical mixing.
Se p 20 05 Shock Waves and Cosmological Matrix Models

We find the shock wave solutions in a class of cosmological backgrounds with a null singularity, each of these backgrounds admits a matrix description. A shock wave solution breaks all supersymmetry meanwhile indicates that the interaction between two static D0branes cancel, thus provides basic evidence for the matrix description. The probe action of a D0-brane in the background of another suggests that the usual perturbative expansion of matrix model breaks down.
Heterocyclic amine content of cooked meat and risk of prostate cancer.

BACKGROUND Some epidemiologic studies have described positive associations between prostate cancer risk and meat consumption, but underlying mechanisms have not been identified. Heterocyclic amines are mutagens formed during the cooking of meat. Well-done meat has been associated with increased risks of colorectal and breast cancers in humans. This study examined associations between prostate cancer risk and 1) estimated daily intake of heterocyclic amines from cooked meat and 2) level of cooked-meat doneness. METHODS A population-based, case-control study involving 317 case patients with prostate cancer and 480 age-matched control subjects was carried out in Auckland, New Zealand. Levels of meat doneness and daily intake of heterocyclic amines were determined from self-reported dietary data and experimentally measured heterocyclic amine levels in locally sourced meat samples cooked under controlled conditions to varying degrees of doneness. RESULTS The heterocyclic amines found in the highest concentrations in meat samples were 2-amino-1,6-dimethylfuro[3,2-e]imidazo[4,5-b]pyridine (IFP) and 2-amino-1-methyl-6-phenylimidazo [4,5-b]pyridine (PhIP) from well-done chicken and pork and very well-done beefsteak. Meat doneness was weakly and inconsistently associated with prostate cancer risk for individual types of meat, but increased risk was observed for well-done beefsteak (relative risk = 1.68; 95% confidence interval = 1.02-2.77; two-sided P for trend =.03). A weak positive gradient of increased risk was associated with estimated daily exposure to IFP but not with the other major heterocyclic amines. CONCLUSIONS Meat doneness and estimated intake of heterocyclic amines from cooked meat were not clearly associated with prostate cancer risk.
How to overcome the feasibility problem for tariffing Internet services: the cumulus pricing scheme

The design of tariff schemes for packet-based network services, especially for differentiated Internet services, has turned out to be a non-trivial task. This is mainly due to the issue of how to account for the immense number of individual packets. This paper proposes a paradigm shift and argues that the solution of this feasibility problem is not a matter of coping with complexity, but instead a question of multidimensional mappings of time-scales. The cumulus pricing scheme (CPS) as introduced and investigated here turns out to be a good example for the resulting simple, transparent, market-managed, and feasible Internet tariff schemes.
Meteorites of northeastern New Mexico

Meteorites are naturally occurring, solid objects which reach the earth from space. Man has known about meteorites for millennia, and classical Chinese and ancient Greek and Latin literature have recorded the fall of stones from the sky. The oldest fall from which material is definitely known is the Ensisheim meteorite which fell on the 16th of November in 1492 near Ensisheim, Alsace, France. Until the early 1800's scientists remained skeptical about stones that fell from the sky. Then on April 26, 1803, a fireball was observed over France and a shower of several thousand stones fell near L'Aigle. Biot (1803) described this fall and established that meteorites do indeed fall from the sky. Brown (1961) has estimated that about 500 meteorites arrive on the earth each year of which about five are recovered (about one fall per year is recovered in the U.S.). Meteorites are named after their place of fall or find (closest village or well-known landmark). Meteorites vary in size, with the smallest weighing 0.0003 gm (Sikhote Alin, USSR) and the largest weighing about 60 metric tons (Hoba, Southwest Africa). Meteorites frequently break apart during entry into the earth's atmosphere, producing meteorite showers. The largest known meteorite shower in terms of the number of specimens occurred near Pultusk, Poland, in 1868, from which about 100,000 stones were recovered. Meteorites are divided into four broad classes: achondrites, chondrites, stony-irons and irons. Chondrites are the most abundant meteorites, making up 86% of the known meteorite falls, and stony-irons and irons the least abundant with 1.3 and 3.7%, respectively (Table 1). The irons and stony-irons, how-ever, make up over 50% of the finds, because they are easier to recognize and are more resistant to terrestrial weathering. The achondrites (Figs. 1, 2) are generally divided into eight
Resilin: Elastic MapReduce for Private and Community Clouds

The MapReduce programming model, introduced by Google, offers a simple and efficient way of performing distributed computation over large data sets. Although Google's implementation is proprietary, MapReduce can be leveraged by anyone using the free and open source Apache Hadoop framework. To simplify the usage of Hadoop in the cloud, Amazon Web Services offers Elastic MapReduce, a web service enabling users to run MapReduce jobs. Elastic MapReduce takes care of resource provisioning, Hadoop configuration and performance tuning, data staging, fault tolerance, etc. This service drastically reduces the entry barrier to perform MapReduce computations in the cloud, allowing users to concentrate on the problem to solve. However, Elastic MapReduce is restricted to Amazon EC2 resources, and is provided at an additional cost. In this paper, we present Resilin, a system implementing the Elastic MapReduce API with resources from other clouds than Amazon EC2, such as private and community clouds. Furthermore, we explore a feature going beyond the current Amazon Elastic MapReduce offering: performing MapReduce computations over multiple distributed clouds.
Employment and Taxes

This paper considers the impact of taxation policy on market work. On the basis of the evidence, we find that a 10 percentage point rise in the tax wedge will reduce overall labour input provided via the market by around 2 per cent of the population of working age. The tax wedge is the sum of the payroll, income and consumption tax rates. This only explains a minority of the market work differentials across countries. Much of the remainder is probably down to the differences in the social security systems supporting the unemployed, the sick and disabled and the early retired.
Queue-Aware Resource Allocation for Downlink OFDMA Cognitive Radio Networks

In this paper we consider resource allocation for an OFDMA-based cognitive radio point-to-multipoint network with fixed users. Specifically, we assume that secondary users are allowed to transmit on any subchannel provided that the interference that is created to any primary users is below a critical threshold. We focus on the downlink. We formulate the joint subchannel, power and rate allocation problem in the context of finite queue backlogs with a total power constraint at the base station. Thus, users with small backlogs are only allocated sufficient resources to support their backlogs while users with large backlogs share the remaining resources in a fair and efficient fashion. Specifically, we formulate the problem as a max-min problem that is queue-aware, i.e., on a frame basis. We maximize the smallest rate of any user whose backlog cannot be fully transmitted. While the problem is a large non-linear integer program, we propose an iterative method that can solve it exactly as a sequence of linear integer programs, which provides a benchmark against which to compare fast heuristics. We consider two classes of heuristics. The first is an adaptation of a class of multi-step heuristics that decouples the power and rate allocation problem from the subchannel allocation and is commonly found in the literature. To make this class of heuristics more efficient we propose an additional (final) step. The second is a novel approach, called selective greedy, that does not perform any decoupling. We find that while the multi-step heuristic does well in the non-cognitive setting, this is not always the case in the cognitive setting and the second heuristic shows significant improvement at reduced complexity compared to the multi-step approach. Finally, we also study the influence of system parameters such as number of primary users and critical interference threshold on secondary network performance and provide some valuable insights on the operation of such systems.
Acute kidney injury associated with androgenic steroids and nutritional supplements in bodybuilders

Four bodybuilders who injected anabolic steroids and ingested commercial protein (78–104 g/day) and creatine (15 g/day) products presented with serum creatinine levels between 229.84 and 335.92 µmol/L (2.6–3.8 mg/dL). Renal biopsies revealed acute tubular necrosis. Four weeks after discontinuing injections and supplements, serum creatinine was in the normal range and estimated glomerular filtration rate > 1.00 mL/s (60 mL/min), including two patients with biopsies showing >30% interstitial fibrosis and tubular atrophy. The findings highlight a risk for acute and potentially chronic kidney injury among young men abusing anabolic steroids and using excessive amounts of nutritional supplements.
The current biodiversity extinction event: Scenarios for mitigation and recovery

The current massive degradation of habitat and extinction of species is taking place on a catastrophically short timescale, and their effects will fundamentally reset the future evolution of the planet's biota. The fossil record suggests that recovery of global ecosystems has required millions or even tens of millions of years. Thus, intervention by humans, the very agents of the current environmental crisis, is required for any possibility of short-term recovery or maintenance of the biota. Many current recovery efforts have deficiencies, including insufficient information on the diversity and distribution of species, ecological processes, and magnitude and interaction of threats to biodiversity (pollution, overharvesting, climate change, disruption of biogeochemical cycles, introduced or invasive species, habitat loss and fragmentation through land use, disruption of community structure in habitats, and others). A much greater and more urgently applied investment to address these deficiencies is obviously warranted. Conservation and restoration in human-dominated ecosystems must strengthen connections between human activities, such as agricultural or harvesting practices, and relevant research generated in the biological, earth, and atmospheric sciences. Certain threats to biodiversity require intensive international cooperation and input from the scientific community to mitigate their harmful effects, including climate change and alteration of global biogeochemical cycles. In a world already transformed by human activity, the connection between humans and the ecosystems they depend on must frame any strategy for the recovery of the biota.
A Lintner Model of Payout and Managerial Rents

We develop a dynamic agency model where payout, investment and financing decisions are made by managers who attempt to maximize the rents they take from the firm, subject to a capital market constraint. Managers smooth payout in order to smooth their flow of rents. Total payout (dividends plus net repurchases) follows Lintner's (1956) target-adjustment model. Payout smooths out transitory shocks to current income and adjusts gradually to changes in permanent income. Smoothing is accomplished by borrowing or lending. Payout is not cut back to finance capital investment. Risk aversion causes managers to underinvest, but habit formation mitigates the degree of underinvestment.
Types of Microregions, Dispersion of Unemployment, and Local Employment Development in Hungary

A typical feature of the regional processes associated with Hungary's transition to a market-driven economy is the change in the nature and the dimension of regional economic differences. Experience suggests that these are both positive changes, such as private enterprises gaining ground, the quick spreading of new forms of business, and an increase in the number of small businesses; and negative processes, such as a setback in economic performance, the increase in unemployment, and an impoverishment of certain segments of society. These changes have had a varying impact in different parts of the country. Some of the regions were relatively successful in answering the challenges of the transition, while others had to face serious crises that affected the local economy and labor market. i Traditional and new measures for job creation and regional development have not proven to be successful in the management of regional employment and economic crises in the transition. While the active, as well as the passive, measures of employment policy have managed in some regions to avoid a threatening social explosion, one thing that they could not do was to stop or slow down the disintegration of a
A model of algorithmic approach to itemsets using association rules

The primary objective of data mining and expert system provides good result for using knowledge base system. From the deep study, Apriori algorithm is a representation of an improved association rule mining algorithm, which helps to avoid the replication of same items. This proposed paper is an improved version of apriori algorithm that is focused on four features namely, First data preparation and select the required data, second generate itemsets that determines the rule constraints for knowledge, third mine k-frequent itemsets using the new database and fourth generate the proposed association rule that establishes the knowledge base and provide better results compared to existing method. Finally, the knowledge database of the expert system is established and stores all the rules in the database. This system helps us to obtain a homologous decision rules as an output of given input.
Systemwide Energy Minimization in Real-Time Embedded Systems

Traditionally, dynamic voltage scaling (DVS) techniques have focused on minimizing the processor power consumption as opposed to the entire system energy. However, the slowdown resulting from DVS can increase the energy consumption of components like memory and network interfaces. Furthermore, leakage power consumption, which is increasing with the scaling device technology, must also be considered. In this paper, we present an algorithm to compute task slowdown factors based on the contribution of the processor leakage and standby energy consumption of the resources in the system. We combine slowdown with procrastination of task executions to extend sleep intervals which significantly reduces the leakage energy consumption. We show that the scheduling approach minimizes the total static and dynamic energy consumption of the systemwide resources. In this work, we consider a real-time system model using the Earliest Deadline First (EDF) policy. Our simulation experiments using randomly generated task sets show on an average 10%energy gains over traditional dynamic voltage scaling. Our procrastination scheme increases the average energy savings to 15%.
Local structure of generalized complex manifolds

We study generalized complex manifolds from the point of view of symplectic and Poisson geometry. We start by showing that every generalized complex manifold admits a canonical Poisson structure. We use this fact, together with Weinstein's classical result on the local normal form of Poisson manifolds, to prove a local structure theorem for generalized complex manifolds which extends the result Gualtieri has obtained in the "regular" case. Finally, we begin a study of the local structure of a generalized complex manifold in a neighborhood of a point where the associated Poisson tensor vanishes. In particular, we show that in such a neighborhood, a "first-order approximation" to the generalized complex structure is encoded in the data of a constant B-field and a complex Lie algebra.
Service Blueprinting: A Practical Technique for Service Innovation

With the global focus on service-led growth has come increased need for practical techniques for service innovation. Services are fluid, dynamic, experiential, and frequently -produced in real time by customers, employees, and technology, often with few static physical properties. However, most product innovation approaches focus on the design of relatively static products with physical properties. Thus, many of the invention and prototype design techniques used for physical goods and technologies do not work well for human and interactive services. This article describes one technique—service blueprinting—that has proven useful for service innovation. Service blueprinting is securely grounded in the customer's experience and it allows the clear visualization of dynamic service processes. The technique is described in detail including real case examples that illustrate the value and breadth of its applications.
Functional domains of the epithelial sodium channel.

The epithelial sodium channel (ENaC) plays an important role in ion transport of many organ systems. In kidney, colon, and sweat gland, ENaC-mediated transepithelial sodium transport helps to adjust sodium excretion in the urine, feces, and sweat to fulfill homeostatic requirements. In lung and
Machine Learning for Integer Programming

Mixed Integer Programs (MIP) are solved exactly by tree-based branch-and-bound search. However, various components of the algorithm involve making decisions that are currently addressed heuristically. Instead, I propose to use machine learning (ML) approaches such as supervised ranking and multi-armed bandits to make better-informed, input-specific decisions during MIP branch-and-bound. My thesis aims at improving the overall performance of MIP solvers. To illustrate the potential for ML in MIP, I have so far tackled branching variable selection, a crucial component of the search procedure, showing that ML approaches for variable selection can outperform traditional heuristics.
Reproductive Biology and Endocrinology Influence of Mycotoxin Zearalenone and Its Derivatives (alpha and Beta Zearalenol) on Apoptosis and Proliferation of Cultured Granulosa Cells from Equine Ovaries

Background: The mycotoxin zearalenone (ZEA) and its derivatives, alpha and beta-zearalenol (alpha and beta-ZOL), synthesized by genera Fusarium, often occur as contaminants in cereal grains and animal feeds. The importance of ZEA on reproductive disorders is well known in domestic animals species, particularly in swine and cattle. In the horse, limited data are available to date on the influence of dietary exposure to ZEA on reproductive health and on its in vitro effects on reproductive cells. The aim of this study was to evaluate the effects of ZEA and its derivatives, alpha and beta-ZOL, on granulosa cells (GCs) from the ovaries of cycling mares.
The frequency of planets in multiple systems

Context. The frequency of planets in binaries is an important issue in the field of extrasolar planet studies, because of its relevance in estimating of the global planet population of our Galaxy and the clues it can give to our understanding of planet formation and evolution. However, only preliminary estimates are available in the literature. Aims. We analyze and compare the frequency of planets in multiple systems to the frequency of planets orbiting single stars. We also try to highlight possible connections between the frequency of planets and the orbital parameters of the binaries (such as the periastron and mass ratio.) Methods. A literature search was performed for binaries and multiple systems among the stars of the sample with uniform planet detectability defined by Fischer & Valenti (2005, ApJ, 622, 1102), and 202 of the 850 stars of the sample turned out to be binaries, allowing a statistical comparison of the frequency of planets in binaries and single stars and a study of the run of the planet frequency as a function of the binary separation. Results. We found that the global frequency of planets in the binaries of the sample is not statistically different from that of planets in single stars. Even conservatively taking the probable incompleteness of binary detection in our sample into account, we estimate that the frequency of planets in binaries can be no more than a factor of three lower than that of planets in single stars. There is no significant dependence of planet frequency on the binary separation, except for a lower value of frequency for close binaries. However, this is probably not as low as required to explain the presence of planets in close binaries only as the result of modifications of the binary orbit after the planet formation.