Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluating Conservation in Zoos: a New Zealand Perspective

The research evaluates the extent to which New Zealand zoos contribute to the conservation of New Zealand indigenous species. Defined as 'an institution which houses a collection of primarily terrestrial wildlife and charges members of the public a fee in exchange for access to view the animals', zoos in New Zealand feature both exotic and indigenous species, some of which are listed as critically endangered, endangered, or vulnerable on the IUCN Red List (IUCN, 2011). The contribution that New Zealand zoos make to the conservation of New Zealand indigenous species such as tuatara (Sphenodon punctatus), North Island brown kiwi (Apteryx mantelli), and Archey's frog (Leiopelma archeyi) has rarely been examined. This research aims to address this gap by examining the New Zealand context.
Group Process in the Single-Gender Women's Recovery Group Compared With Mixed-Gender Group Drug Counseling

Enhanced affiliation among members is thought to provide increased support for women in single-gender compared with mixed-gender group therapy for substance use disorders (SUDs) and to provide a potential mechanism of action for its efficacy. In a Stage I trial of single-gender versus mixed-gender group therapy for SUDs, we examined affiliative statements made by members in 2 group treatments—the single-gender Women's Recovery Group (WRG) and mixed-gender group drug counseling (GDC). Twenty-eight WRG and 17 GDC group therapy tapes were coded and compared for 5 types of affiliative statements. Three types of affiliative statements (agreement, supportive, and completing a thought) were highly correlated and were more frequent in WRG than in GDC (d = 0.882, p = .27). In GDC, women were more likely to provide an affiliative statement to a male group member than any other combination of directionality (p < .01). Compared with mixed-gender group therapy, single-gender group therapy for SUDs may enhance support through greater frequency of affiliative statements.
[2010] Facing the Exascale Energy Wall

A recent report focused on the technical challengesin advancing from today's "petascale" systems to "exascale. "Power, or more accurately energy, was a dominant challenge. This paper briefly reviews the energy challenge for exascaled sized systems, with an emphasis on the relatively enormous energy costs of referencing operands from the memory hierarchy. Then, usinga key step from the LINPACK benchmark, we investigate twodifferent approaches to reducing such costs: one which migratescomputations up from the host to higher levels of the hierarchy,and another in moving the whole computation closer to memory. Both show significant improvements over architecture as usual.
Poly[diethylenetriammonium [aquadi-μ2-sulfato-sulfatolanthanum(III)]]

In the title compound, {(C4H16N3)[La(SO4)3(H2O)]}n, the La atom adopts an irregular LaO9 coordination geometry, including one bonded water molecule. The three sulfate groups adopt both monodentate and bidentate coordination to the metal ions. Two of the sulfate groups serve as bridges in the (100) and (010) directions, yielding infinite sheets, whereas the third is pendant to one La3+ cation. The protonated organic species interacts with the layers by way of N—H⋯O hydrogen bonds, and O–H⋯O hydrogen bonds involving aqua ligands also occur.
Modelling gross primary production of a tropical semi-deciduous forest in the southern Amazon Basin

Semi-deciduous forest in the Amazon Basin is sensitive to temporal variation in surface water availability that can limit seasonal rates of leaf and canopy gas exchange. We estimated the seasonal dynamics of gross primary production (GPP) over 3 years (2005–2008) using eddy covariance and assessed canopy spectral reflectance using MODIS imagery for a mature tropical semi-deciduous forest located near Sinop, Mato Grosso, Brazil. A light-use efficiency model, known as the Vegetation Photosynthesis Model (VPM), was used to estimate seasonal and inter-annual variations in GPP as a function of the enhanced vegetation index (EVI), the land surface water index (LSWI), and local meteorology. Our results indicate that the standard VPM was incapable of reproducing the seasonal variation in GPP, primarily because the model overestimated dry-season GPP. In the standard model, the scalar function that alters light-use efficiency (εg) as a function of water availability (Wscalar) is calculated as a linear function of the LSWI derived from MODIS; however, the LSWI is negatively correlated with several measures of water availability including precipitation, soil water content, and relative humidity (RH). Thus, during the dry season, when rainfall, soil water content, and RH are low, LSWI, and therefore, Wscalar, are at a seasonal maximum. Using previous research, we derived new functions for Wscalar based on time series of RH and photosynthetic photon flux density (PPFD) that significantly improved the performance of the VPM. Whether these new functions perform equally well in water stressed and unstressed tropical forests needs to be determined, but presumably unstressed ecosystems would have high cloud cover and humidity, which would minimize variations in Wscalar and GPP to spatial and/or temporal variation in water availability.
Left ventricular early diastolic inflow velocity and atrial ventricular plane downward velocity: useful parameters to test diastolic function in clinical practice? Diastolic parameters tested in a clinical setting.

AIMS To study the clinical value of the colour-M-mode slope of the early diastolic left ventricular filling phase (Vp) and the early diastolic downward M-mode slope of the left atrioventricular plane displacement (EDS), compared with diastolic function assessed by traditional Doppler evaluation. METHODS AND RESULTS In 65 consecutive patients EDS and Vp were compared with a four-degree traditional diastolic function classification, based on pulsed Doppler assessment of the early to atrial transmitral flow ratio (E/A), the E-wave deceleration time (Edt), and the systolic to diastolic (S/D) pulmonary venous inflow ratio. Vp (P=0.006) and EDS (P=0.045) were related to traditional diastolic function (Kruskal--Wallis analysis). EDS showed a trend brake between the moderate and severe diastolic dysfunction groups by traditional Doppler evaluation. Vp and EDS correlated weakly in simple linear regression analysis (r=0.33). Vp and EDS discriminated poorly between normal and highly abnormal diastolic function. CONCLUSIONS Vp and EDS were significantly related to diastolic function by traditional Doppler evaluation. They were, however, not useful as single parameters of left ventricular diastolic function due to a small difference between normal and highly abnormal values, allowing for little between-measurement variability. Consequently, these methods for the evaluation of left ventricular diastolic function do not add significantly to traditional Doppler evaluation.
Throughput maximization and resource optimization in NFV-enabled networks

Network function virtualization (NFV) has been emerging as a new paradigm to enable elastic and inexpensive network services in modern computer networks, through deploying flexible virtualized network functions (VNFs) running in virtual computing platforms. Different VNFs can be chained together to form different service chains, to meet various user data routing demands for different network services. In this paper we consider provisioning network services in an NFV-enabled network that consists of data centers for implementing VNF instances of service chains and switches. We study the throughput maximization problem with the aim to admit as many user requests as possible while minimizing the implementation cost of the requests, assuming that limited numbers of instances of each service chain have been stored in data centers. We first propose an optimal algorithm for the problem if all requests have identical packet rates; otherwise, we devise two approximation algorithms with probable approximation ratios, depending on whether the packet traffic of each request is splittable. We finally conduct experiments to evaluate the performance of the proposed algorithms by simulations. Experimental results show that the proposed algorithms achieve at least 15% more throughput than that of a greedy algorithm.
Impact of Grassland Radiation on the Nonmarine Silica Cycle and Miocene Diatomite

Abstract The Early Miocene rise of the grass-dominated ecosystem is a plausible trigger for a sharp Miocene increase in accumulation of nonmarine diatomaceous sediment as well as diversification of nonmarine diatoms. This grassland radiation introduced a biogeochemical mechanism for enhancing widespread and sustained mobilization of usable silica and other nutrients. Volcanism was probably responsible for episodic nonmarine diatomaceous sediments from the advent of the oldest known nonmarine diatoms in the Late Cretaceous through the Oligocene. Although prolific Miocene volcanism was undoubtedly still important in the development of many diatomites, feedback from grassland colonization of volcanic soils may explain why diatomaceous sedimentation surged in the Miocene following a more sparse pre-Miocene record. The initial rise of the grass-dominated ecosystem, increased nonmarine diatomite accumulation, and Early Miocene evolutionary radiations of nonmarine diatom taxa are at least approximately coeval. Although the earliest known grass is Paleocene, multiple lines of evidence, including mollic-epipedon paleosols, fossil occurrences of hypsodontic ungulate grazers, and fossil phytoliths, suggest that the grass-dominated ecosystem did not expand significantly until Early Miocene. The grassland radiation apparently was delayed until Middle Miocene in parts of Eurasia, Africa, and Australia. If that delay is real, the diatom/diatomite record in those regions should coincide with it. The onset of increased Miocene diatomite accumulation is as yet imprecisely dated, but coincidence with the rise of the grass-dominated ecosystem is predicted herein. Early Miocene diversifications of Actinocyclus and Thalassiosira diatoms are consistent temporally with grassland expansion where it is Early Miocene. Subsequent adjustments in the silica cycle also may be attributed to grasslands. Nonmarine diatom radiations in the Late Miocene and Pliocene coincide with sharp regressions that may have released nutrients and soluble phytolith opal stored in Miocene soils and paleosols as well as dissolved silica in soil pore waters. Regressional erosive pulses of phytoliths provide a new explanation for low Ge/ Si ratios in marine diatoms during Pleistocene glacial intervals. Nonmarine diatoms from regressive intervals should record lower Ge/Si ratios than before and after those regressions because of phytolith contributions with low Ge/Si ratios. Late Miocene radiations of C4 and moist tall-grass ecosystems may have mobilized even more silica than the short, dry-climate Early Miocene grasses. Abundance of diatomite may have fluctuated in concert with changes in degree of volcanism, even after grassland expansion, but at substantially higher levels than before this new terrestrial ecosystem arose.
The Research of Concessionaire Selection Based on an Improved Lowest Tariff Decision Model

BOT projects have been widely used in the past twenty years in the construction of infrastructure projects. Choosing a suitable concessionaire is the key of the project. Based on Particle Swarm Optimization, The study develops an improved lowest tariff decision model for choosing the best concessionaire. The model and algorithm demonstrate with a numerical example of a toll expressway BOT project. The solution derived from the concessionaire decision model can be helpful to develop infrastructure projects by BOT concession successfully.
Characterizing and improving generalized belief propagation algorithms on the 2D Edwards–Anderson model

We study the performance of different message passing algorithms in the two-dimensional Edwards–Anderson model. We show that the standard belief propagation (BP) algorithm converges only at high temperature to a paramagnetic solution. Then, we test a generalized belief propagation (GBP) algorithm, derived from a cluster variational method (CVM) at the plaquette level. We compare its performance with BP and with other algorithms derived under the same approximation: double loop (DL) and a two-way message passing algorithm (HAK). The plaquette-CVM approximation improves BP in at least three ways: the quality of the paramagnetic solution at high temperatures, a better estimate (lower) for the critical temperature, and the fact that the GBP message passing algorithm converges also to nonparamagnetic solutions. The lack of convergence of the standard GBP message passing algorithm at low temperatures seems to be related to the implementation details and not to the appearance of long range order. In fact, we prove that a gauge invariance of the constrained CVM free energy can be exploited to derive a new message passing algorithm which converges at even lower temperatures. In all its region of convergence this new algorithm is faster than HAK and DL by some orders of magnitude.
2HAPI: A Microarray Data Analysis System

SUMMARY 2HAPI (version 2 of High density Array Pattern Interpreter) is a web-based, publicly-available analytical tool designed to aid researchers in microarray data analysis. 2HAPI includes tools for searching, manipulating, visualizing, and clustering the large sets of data generated by microarray experiments. Other features include association of genes with NCBI information and linkage to external data resources. Unique to 2HAPI is the ability to retrieve upstream sequences of co-regulated genes for promoter analysis using MEME (Multiple Expectation-maximization for Motif Elicitation) AVAILABILITY 2HAPI is freely available at http://array.sdsc. edu. Users can try 2HAPI anonymously with pre-loaded data or they can register as a 2HAPI user and upload their data.
Structured Prediction Energy Networks

We introduce structured prediction energy networks (SPENs), a flexible framework for structured prediction. A deep architecture is used to define an energy function of candidate labels, and then predictions are produced by using back-propagation to iteratively optimize the energy with respect to the labels. This deep architecture captures dependencies between labels that would lead to intractable graphical models, and performs structure learning by automatically learning discriminative features of the structured output. One natural application of our technique is multi-label classification, which traditionally has required strict prior assumptions about the interactions between labels to ensure tractable learning and prediction. We are able to apply SPENs to multi-label problems with substantially larger label sets than previous applications of structured prediction, while modeling high-order interactions using minimal structural assumptions. Overall, deep learning provides remarkable tools for learning features of the inputs to a prediction problem, and this work extends these techniques to learning features of structured outputs. Our experiments provide impressive performance on a variety of benchmark multi-label classification tasks, demonstrate that our technique can be used to provide interpretable structure learning, and illuminate fundamental trade-offs between feed-forward and iterative structured prediction.
HP : High Pressure HRSG : Heat Recovery Steam Generator IGCC : Integrated Gasification Combined Cycle IP : Intermediate Pressure LHV : Lower Heating Value LP : Low Pressure NG : Natural Gas R : Regenerator

The purpose of this work is to present a thermodynamic cycle calculation software and its potential in the simulation of novel electricity generation cycles integrating CO2 sequestration. The software code ENBIPRO (ENergie-BIllanz-PROgram) is a powerful tool for heat and mass balance solving of complex thermodynamic circuits, calculation of efficiency, exergetic and exergoeconomic analysis of power plants. The software code models all pieces of equipment that usually appear in power plant installations and can accurately calculate all thermodynamic properties (temperature, pressure, enthalpy) at each node of the thermodynamic circuit, power consumption of each component, flue gas composition etc. The code has proven its validity by accurately simulating a large number of power plants and through comparison of the results with other commercial software [1]. Following a detailed presentation of the software code, ENBIPRO is used for the evaluation of a novel concept dealing with the carbonation-calcination process of lime for CO2 capture from coal fired power plants compared to integration of CO2 capture in a typical Integrated Gasification Combined Cycle power plant. In the novel concept, coal is gasified with steam and lime. Lime absorbs the CO2 released from the coal, generating limestone. The produced gas can be a low carbon or even a zero carbon (H2) gas, depending on the ratio of lime added to the process, and can be used for electricity generation in state-of-the-art combined cycles, generating almost no CO2 emissions or other harmful pollutants. The limestone is regenerated in a second reactor where pure CO2 is produced, which can be either sold to industry or sequestered in long term disposal areas. Results from thermodynamic simulations dealing with the most important features for CO2 reduction are presented concerning both technological options. The operating characteristics as well as the main figures of the plants heat balances are included.
A mid-texturing pixel rasterization pipeline architecture for 3D rendering processors

As a 3D scene becomes increasingly complex and the screen resolution increases, the design of effective memory architecture is one of the most important issues for 3D rendering processors. We propose a pixel rasterization architecture, which performs a depth test operation twice, before and after texture mapping. The proposed architecture eliminates memory bandwidth waste caused by fetching unnecessary obscured texture data, by performing the depth test before texture mapping. The proposed architecture reduces the miss penalties of the pixel cache by using a pre-fetch scheme - that is, a frame memory access, due to a cache miss at the first depth test, is done simultaneously with texture mapping. The proposed pixel rasterization architecture achieves memory bandwidth effectiveness and reduces power consumption, producing high-performance gains.
Seasonal changes in colour ratios and optically active contituents in the optical Case-2 waters of the Menai Strait, North Wales

A time series was conducted in the Menai Strait from March to December 1996 combining optical measurements by a colour sensor with measurements of light-absorbing constituents in the water. In order to improve estimations of pigment concentration in Case-2 waters, an optical model was used to synthesize the spectrum of sea-leaving radiance from the absorption properties of pure sea water, yellow substances, mineral suspended solids and phytoplankton. The original model was tested and improved by using a different set of parameters. Multiple regression was used to empirically relate colour ratios to pigments and total suspended solids.
Geometry Refinement of 3D Surfaces Using Kriging

3D imaging is a popular method for acquiring accurate models for a variety of applications. However, the size of the geometric features that can be modeled in this manner is dependant on the scanning system's resolution. This paper presents a method that attempts to accurately reconstruct regions whose features are at or below the system's scanning resolution, combining automatic region selection with a form of kriging. A curvature-based segmentation is followed by an automated geometry refinement procedure in which the model of spatial correlation between the irregularly sampled 3D data is automatically determined. Geometry refinement is done by a regularized kriging approach that is designed to preserve the sharp features typical to many 3D laser range applications. This method is validated on synthetic data, showing that the accuracy of our method is higher than that of its standard competitors. Then, the performance on real data is demonstrated through several examples.
Clustered small base stations for cache-enabled wireless networks

Caching has emerged as a vital tool in modern communication systems for reducing peak data rates by allowing strategic contents to be pre-fetched and stored locally at end users' devices. With the shift in paradigm from homogeneous cellular networks to the heterogeneous ones, the concept of data offloading to small cell base stations (SBS) has garnered significant attention. Caching at these small cell base stations has recently been proposed and is considered a promising solution for addressing the ever-increasing traffic demand of mobile devices, where strategic contents are pre-fetched and stored locally in order to avoid bottlenecks in the limited capacity backhaul connection link to the core network. Taking in the limited caching space into account, it is necessary for the SBSs to adjust their caching content based on the history of requested contents. In this work, we investigate the gains of proactive caching in terms of cache hit ratio, while tackling the large-amount of available data for cache decision matrix. In order to determine the cache decision matrix, we firstly cluster the SBSs employing k-means clustering based on the history of requested contents, then we predict the requested content by analyzing the in-cluster content popularity and with collaborative filtering. Simulation results verify the proposed cache strategy inspired by machine learning tools has more performance gain compared to conventional strategies by only caching the most popular contents.
Clinical determinants of the racial disparity in very low birth weight.

BACKGROUND Although the risk of very low birth weight (less than 1500 g) is more than twice as high among blacks as among whites in the United States, the clinical conditions associated with this disparity remain poorly explored. METHODS AND RESULTS We reviewed the medical records of over 98 percent of all infants weighing 500 to 1499 g who were born in Boston during the period 1980 through 1985 (687 infants), in St. Louis in 1985 and 1986 (397 infants), and in two health districts in Mississippi in 1984 and 1985 (215 infants). The medical records of the infants' mothers were also reviewed. These data were linked to birth-certificate files. During the study periods, there were 49,196 live births in Boston, 16,232 in St. Louis, and 16,332 in the Mississippi districts. The relative risk of very low birth weight among black infants as compared with white infants ranged from 2.3 to 3.2 in the three areas. The higher proportion of black infants with very low birth weights was related to an elevated risk in their mothers of major conditions associated with very low birth weight, primarily chorioamnionitis or premature rupture of the amniotic membrane (associated with 38.0 percent of the excess proportion of black infants with very low birth weights [95 percent confidence interval, 31.3 to 45.4 percent]); idiopathic preterm labor (20.9 percent of the excess [95 percent confidence interval, 16.0 to 26.4 percent]); hypertensive disorders (12.3 percent [95 percent confidence interval, 8.6 to 16.6]); and hemorrhage (9.8 percent [95 percent confidence interval, 5.5 to 13.5]). CONCLUSIONS The higher proportion of black infants with very low birth weights is associated with a greater frequency of all major maternal conditions precipitating delivery among black women. Reductions in the disparity in birth weight between blacks and whites are not likely to result from any single clinical intervention but, rather, from comprehensive preventive strategies.