Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparison of International Panel on Climate Change Fourth Assessment Report climate model simulations of surface albedo with satellite products over northern latitudes

[1] The surface albedos simulated by seventeen climate models over the northern latitudes of the Western Hemisphere were compared with satellite-derived albedo products provided by the International Satellite Cloud Climatology Project (ISCCP). Model simulations were conducted in support of the International Panel on Climate Change (IPCC) Fourth Assessment Report (AR4). Results show the following: (1) Annual albedo of the region averaged for all models is fairly close to that provided by the ISCCP (0.351 versus 0.334). The difference between model average and ISCCP albedos is well below the standard deviation in albedo among models. (2) Most models simulated seasonal variations in regional albedo reasonably well. In summer, the models systematically overestimated albedo relative to the ISCCP data by as much as 0.05. In winter, large differences were detected among the climate models. (3) The spatial correlations among models, and between models and ISCCP, depend on geographic location, season and surface type. In general, the spatial correlation coefficients between individual models and the ISCCP data were highest for the land surface in midsummer and for the ocean surface in spring. Model bias was smaller for the ocean surface than for the land surface, and smaller in summer than in winter. (4) Unlike the modeling results, the satellite data showed large interannual variations in albedo and a systematic decreasing trend over the 16 year period of 1984–1999. Depending on season, the standard deviation of albedo interannual variation ranged from 0.036 to 0.074, and the linear regression slope of the decreasing trend ranged from −0.02 to −0.05 per decade according to ISCCP results. The large interannual variation and decreasing trend are not reflected in model simulations. Additional efforts are still required to improve surface albedo simulations in GCMs and its mapping from satellite.
Influence of the RelA Activity on E. coli Metabolism by Metabolite Profiling of Glucose-Limited Chemostat Cultures

Metabolite profiling of E. coli W3110 and the isogenic ΔrelA mutant cells was used to characterize the RelA-dependent stringent control of metabolism under different growth conditions. Metabolic profiles were obtained by gas chromatography–mass spectrometry (GC-MS) analysis and revealed significant differences between E. coli strains grown at different conditions. Major differences between the two strains were assessed in the levels of amino acids and fatty acids and their precursor metabolites, especially when growing at the lower dilution rates, demonstrating differences in their metabolic behavior. Despite the fatty acid biosynthesis being the most affected due to the lack of the RelA activity, other metabolic pathways involving succinate, lactate and threonine were also affected. Overall, metabolite profiles indicate that under nutrient-limiting conditions the RelA-dependent stringent response may be elicited and promotes key changes in the E. coli metabolism.
Dissolution of Evaporites in and Around the Delaware Basin

Permian evaporites in the Ochoan Castile, Salado, and Rustler Formations in the Delaware Basin of southeast New Mexico and west Texas have been subjected to various degrees of dissolution (notably of halite and gypsum) through geologic time. Eastward tilting of the Delaware Basin has resulted in the exhumation and erosion of Ochoan rocks in the western part of the basin. Waters in the Capitan, Rustler, Castile, and Bell Canyon Formations have previously been proposed as agents or consequences of evaporite dissolution according to four principal models: solution-and-fill, phreatic dissolution, brine density flow, and stratabound dissolution (along bedding planes). Several geomorphological features of positive and negative relief have previously been cited as indicators of evaporite dissolution. Brine density flow has been used to explain the selective dissolution of certain evaporite horizons during the late Cenozoic. A review of available geological data has revealed that Halite deposition was probably not so extensive as formerly believed Waters with potential to dissolve evaporites are in the Rustler and Capitan, but not in the Bell Canyon, Salado mine seeps, or the'castile brine reservoirs Brine density flow has not been active in removing most of the "missing" halite, nor are "point-source" dissolution features likely to have their roots a t the Bell Canyon Major evaporite dissolution has not been confined to the late Cenozoic, but much of it took place during the Permian, Triassic, Jurassic, and Tertiary periods The Bell Canyon Formation has not been a sink for dissolution-derived brine
Segmentation of neuroanatomy in magnetic resonance images

Segmentation in neurological magnetic resonance imaging (MRI) is necessary for feature extraction, volume measurement and for the three-dimensional display of neuroanatomy. Automated and semi-automated methods offer considerable advantages over manual methods because of their lack of subjectivity, their data reduction capabilities, and the time savings they give. We have used dual echo multi-slice spin-echo data sets which take advantage of the intrinsically multispectral nature of MRI. As a pre-processing step, a rf non-uniformity correction is applied and if the data is noisy the images are smoothed using a non-isotropic blurring method. Edge-based processing is used to identify the skin (the major outer contour) and the eyes. Edge-focusing has been used to significantly simplify edge images and thus allow simple postprocessing to pick out the brain contour in each slice of the data set. Edge- focusing is a technique which locates significant edges using a high degree of smoothing at a coarse level and tracks these edges to a fine level where the edges can be determined with high positional accuracy. Both 2-D and 3-D edge-detection methods have been compared. Once isolated, the brain is further processed to identify CSF, and, depending upon the MR pulse sequence used, the brain itself may be sub-divided into gray matter and white matter using semi-automatic contrast enhancement and clustering methods.
3-D Localization and Mapping Using a Single Camera Based on Structure-from-Motion with Automatic Baseline Selection

This paper presents a system of 3-D simultaneous localization and mapping (SLAM) using monocular vision-based on the structure-from-motion scheme. An crucial issue in applying structure-from-motion to SLAM is that accuracy depends heavily on the baseline distance. We address this problem by selecting an appropriate baseline based on criteria for the tradeoff between the baseline distance and the number of feature points visible in the images. Experimental results show that full 3-D sparse maps with camera trajectory were built from images captured with a handy camera.
A Survey of Cloud Storage Facilities

There are many applications such as software for processing customer records in telecom, patient records in hospitals, email processing software accessing a single email in a mailbox etc. which require to access a single record in a database consisting of millions of records. A basic feature of these applications is that they need to access data sets which are very large but simple. Cloud computing provides computing requirements for these kinds of new generation of applications involving very large data sets which cannot possibly be handled efficiently using traditional computing infrastructure. In this paper, we describe storage services provided by three well-known cloud service providers and give a comparison of their features with a view to characterize storage requirements of very large data sets as examples and we hope that it would act as a catalyst for the design of storage services for very large data set requirements in future. We also give a brief overview of other kinds of storage that have come up in the recent past for cloud computing.
Sound collection and visualization system enabled participatory and opportunistic sensing approaches

This paper presents a sound collection system to visualize environmental sounds that are collected using a crowd-sourcing approach. An analysis of physical features is generally used to analyze sound properties; however, human beings not only analyze but also emotionally connect to sounds. If we want to visualize the sounds according to the characteristics of the listener, we need to collect not only the raw sound, but also the subjective feelings associated with them. For this purpose, we developed a sound collection system using a crowdsourcing approach to collect physical sounds, their statistics, and subjective evaluations simultaneously. We then conducted a sound collection experiment using the developed system on ten participants. We collected 6,257 samples of equivalent loudness levels and their locations, and 516 samples of sounds and their locations. Subjective evaluations by the participants are also included in the data. Next, we tried to visualize the sound on a map. The loudness levels are visualized as a color map and the sounds are visualized as icons which indicate the sound type. Finally, we conducted a discrimination experiment on the sound to implement a function of automatic conversion from sounds to appropriate icons. The classifier is trained on the basis of the GMM-UBM (Gaussian Mixture Model and Universal Background Model) method. Experimental results show that the F-measure is 0.52 and the AUC is 0.79.
Identifying Risk Factors for Metabolic Syndrome in Biomedical Text

Identifying risk factors and biomarkers for diseases is an important aspect of biomedical research. However, much of the underlying information resides in the research literature and is not available in executable form. We propose a methodology based on automatic semantic interpretation (using SemRep) to capture risk factors and biomarkers for diseases asserted in MEDLINE citations. In this initial study, we focus on metabolic syndrome. The performance of SemRep in identifying risk factors and biomarkers for this disorder was 53% recall (CI, 44% to 62%) and 67% precision (CI, 62% to 72%). We discuss how the information captured could assist clinicians in finding current and new risk factors for metabolic syndrome as well as diseases predisposed by this disorder. The availability of this information in executable form can support guideline development and the timely translation of biomedical research into improvements in quality of patient care.
Extensions to Standard ML to Support Transactions

A transaction is a control abstraction that lets programmers treat a sequence of operations as an atomic ("all-or-nothing") unit. This paper describes our progress on on-going work to extend SML with transactions. What is novel about our work on transactions is support for multi-threaded concurrent transactions. We use SML''s modules facility to reflect explicitly orthogonal concepts heretofore inseparable in other transaction-based programming languages.
Effects of Age and Hypertension on Autonomic Nervous Regulation During Passive Head‐Up Tilt

To study the effects of age and hypertension on autonomic nervous function with passive postural change, we examined 31 normotensive subjects (25 to 85 years old) and 31 hypertensive patients (21 to 71 years old) without any cardiac disease, diabetes mellitus, or neurological disorders. Subjects were passively placed in a 60° head-up tilting position after 15 minutes in the supine position. Autonomic nervous function was evaluated by frequency domain analysis of heart rate with the autoregressive method. Using low-frequency (0.1 Hz) and high-frequency (0.25 Hz) peaks, the ratio of low- to highfrequency power (L/H) was calculated as an index of sympathetic activity and the ratio of high to total power (%HF) as that of parasympathetic activity. With the patient in the supine position, total power spectral density declined logarithmically with age in normotensive subjects and hypertensive patients, but %HF and L/H showed no changes. In response to passive tilting, L/H was increased and %HF was decreased in the normotensive subjects, and these responses declined with age logarithmically. In contrast, hypertensive patients exhibited less autonomic response to postural change regardless of age. These results suggest that autonomic neural response to tilt is decreased with age; however, attenuation of the response by hypertension is not associated with an increase in age.
Cytotoxic and antitumor activity of a recombinant immunotoxin composed of disulfide‐stabilized anti‐TAC Fv fragment and truncated pseudomonas exotoxin

Disulfide‐stabilized Fv (dsFv)‐immunotoxins are recombinant immunotoxins in which the inherently unstable Fv moiety, composed of the VH‐VL heterodimer, is stabilized by a disulfide bond engineered between structurally conserved framework positions of VH and VL. Anti‐Tac(dsFv)‐PE38KDEL is composed of such a dsFv, directed to the α subunit of the IL2 receptor (IL2R), and containing a truncated form of Pseudomonas exotoxin (PE38KDEL). We have found this new type of immunotoxin to be indistinguishable in its in vitro activity and specificity from its single‐chain immunotoxin counterpart, anti‐Tac(Fv)‐PE38KDEL. We have now examined the therapeutically relevant factors, including stability, pharmacokinetics, and antitumor activity of this new disulfide‐stabilized Fv‐immunotoxin. We found that anti‐Tac(dsFv)‐PE38KDEL was specifically cytotoxic to human activated T‐lymphocytes in addition to IL2R bearing cell lines. Anti‐Tac(dsFv)‐PE38KDEL was considerably more stable at 37° C in human serum and in buffered saline than the single‐chain immunotoxin, anti‐Tac(Fv)‐PE38KDEL. The half‐life in blood was similar for both immunotoxins (approx. 20 min). The therapeutic potential of the disu Hide‐stabilized immunotoxin was evaluated using an animal model of immunodeficient mice bearing subcutaneous tumor xenografts of human IL2R‐bearing cells. Anti‐Tac(dsFv)‐PE38KDEL caused complete regression of tumors with no toxic effects in mice. Because dsFv‐immunotoxins are more stable and can be produced with significantly improved yields compared to scFv‐immunotoxins, dsFv‐immunotoxin may be more useful for therapeutic applications. © 1994 Wiley‐Liss, Inc.
Local Convergence Properties of Douglas--Rachford and ADMM

The Douglas--Rachford (DR) and alternating direction method of multipliers (ADMM) are two proximal splitting algorithms designed to minimize the sum of two proper lower semi-continuous convex functions whose proximity operators are easy to compute. The goal of this work is to understand the local linear convergence behaviour of DR/ADMM when the involved functions are moreover partly smooth. More precisely, when the two functions are partly smooth relative to their respective smooth submanifolds, we show that DR/ADMM (i) identifies these manifolds in finite time; (ii) enters a local linear convergence regime. When both functions are locally polyhedral, we show that the optimal convergence radius is given in terms of the cosine of the Friedrichs angle between the tangent spaces of the identified submanifolds. Under polyhedrality of both functions, we also provide condition sufficient for finite convergence of DR. The obtained results are illustrated by several concrete examples and supported by numerical experiments.
A novel mathematical model of the electrical action potential in a canine Purkinje fiber cell

Purkinje fiber (PF) cells exhibit action potential (AP) morphology and duration markedly different to those of ventricle myocytes. In order to study heterogeneity at the Purkinje-ventricular junction (PVJ), we construct a new AP model for the canine PF cell based on detailed experimental data of ion channel characteristics obtained by voltage clamp techniques. Single-cell PF model is incorporated into a 1D transmural strand model, which is used to simulate the AP conduction through the PVJ under physiological and short QT syndrome (SQTS) conditions. Simulations produced the APD dispersion patterns and pseudo-ECGs consistent with experimental data under physiological conditions. Incorporating changes to the activation kinetics and time constants of the IKs channel associated with the KCNQ1 gene mutation resulted in the shortened QT interval characteristic of SQTS.
Subduction of the North Pacific Mode Waters in a Global High-Resolution GCM*

Abstract The annual subduction rate in the North Pacific is estimated using five-day outputs from a high-resolution general circulation model (GCM). Two maxima (>200 m yr−1) are found in the western North Pacific: one is responsible for the formation of the subtropical mode water (STMW) and the other for the formation of the central mode water (CMW). A local maximum (>75 m yr−1) is also found in the formation region of the eastern subtropical mode water (ESMW). These results are compared with a calculation using the winter mixed layer depth and annual mean velocity fields to examine the effect of mesoscale eddies. Although the mesoscale eddies do not markedly affect the general subduction pattern, they enhance the annual subduction rate by up to 100 m yr−1 in the formation region of the STMW/CMW, a 34% increase in a regional average (30°–44°N, 140°E–170°W). Further analysis shows that the effects of the mean seasonal cycle and smaller-scale (<30 days) eddies are generally small. The authors suggest that t.
Flexible Independent Component Analysis

This paper addresses an independent component analysis (ICA) learning algorithm with flexible nonlinearity, so named as flexible ICA, that is able to separate instantaneous mixtures of sub- and super-Gaussian source signals. In the framework of natural Riemannian gradient, we employ the parameterized generalized Gaussian density model for hypothesized source distributions. The nonlinear function in the flexible ICA algorithm is controlled by the Gaussian exponent according to the estimated kurtosis of demixing filter output. Computer simulation results and performance comparison with existing methods are presented.
In-Band Full-Duplex Wireless: Challenges and Opportunities

In-band full-duplex (IBFD) operation has emerged as an attractive solution for increasing the throughput of wireless communication systems and networks. With IBFD, a wireless terminal is allowed to transmit and receive simultaneously in the same frequency band. This tutorial paper reviews the main concepts of IBFD wireless. One of the biggest practical impediments to IBFD operation is the presence of self-interference, i.e., the interference that the modem's transmitter causes to its own receiver. This tutorial surveys a wide range of IBFD self-interference mitigation techniques. Also discussed are numerous other research challenges and opportunities in the design and analysis of IBFD wireless systems.
A novel approach to statistical downscaling considering nonstationarities: application to daily precipitation in the Mediterranean area

In the present study, nonstationarities in predictor–predictand relationships within the framework of statistical downscaling are investigated. In this context, a novel validation approach is introduced in which nonstationarities are explicitly taken into account. The method is based on results from running calibration periods. The (non)overlaps of the bootstrap confidence interval of the mean model performance (derived by averaging the performances of all calibration/verification periods) and the bootstrap confidence intervals of the individual model errors are used to identify (non)stationary model performance. The specified procedure is demonstrated for mean daily precipitation in the Mediterranean area using the bias to assess model skill. A combined circulation‐based and transfer function–based approach is employed as a downscaling technique. In this context, large‐scale seasonal atmospheric regimes, synoptic‐scale daily circulation patterns, and their within‐type characteristics, are related to daily station‐based precipitation. Results show that nonstationarities are due to varying predictors–precipitation relationships of specific circulation configurations. In this regard, frequency changes of circulation patterns can damp or increase the effects of nonstationary relationships. Within the scope of assessing future precipitation changes under increased greenhouse warming conditions, the identification and analysis of nonstationarities in the predictors–precipitation relationships leads to a substantiated selection of specific statistical downscaling models for the future assessments. Using RCP4.5 scenario assumptions, strong increases of daily precipitation become apparent over large parts of the western and northern Mediterranean regions in winter. In spring, summer, and autumn, decreases of precipitation until the end of the 21st century clearly dominate over the entire Mediterranean area.
Economic Growth Across Chinese Provinces: In Search of Innovation-Driven Gains

In this paper we analyse the impact of R&D on total factor productivity across Chinese provinces. We introduce innovations explicitly into a production function and evaluate their contribution to economic growth in 1993 - 2006. The empirical results highlight the importance and the interaction between local and external research. The evidence indicates that growth in China is not explained simply by factor input accumulation.
Participación laboral y discapacidad: el caso de la Comunidad Andaluza

The main objective of this work is to analyse the effects of having a disability on the probability of being active in the Andalusian Community. Taken the data from the “Encuesta sobre Discapacidades, Deficiencias y Estado de Salud” of 1999, we estimate different specifications of a logit model of labour participation, which includes variables related to person’s socio-economics characteristics and several variant of the disability and deficiency variables (number, type and level). The results show that being disabled jointly with receiving subsidies or benefits has an negative generic influence on the probability of being active. Moreover, the interaction between disability and perception of public transfers potentially related to the disability status have a very negative effect on such a probability.
Asymptotic waveform evaluation for timing analysis

Asymptotic waveform evaluation (AWE) provides a generalized approach to linear RLC circuit response approximations. The RLC interconnect model may contain floating capacitors, grounded resistors, inductors, and even linear controlled sources. The transient portion of the response is approximated by matching the initial boundary conditions and the first 2q-1 moments of the exact response to a lower-order q-pole model. For the case of an RC tree model, a first-order AWE approximation reduces to the RC tree methods. >
Efficient incremental phrase-based document clustering

Document clustering has become inevitable for applications that aim to extract information from huge corpuses. Such applications face two main challenges; one is the efficient representation of the documents, along with using an efficient similarity measure, and the second is dealing with the dynamic nature of the corpus. In this paper, an efficient document clustering model is introduced for incrementally storing and updating clusters of a dataset. A new phrase-based similarity method is developed along with the model to calculate the similarity between documents and clusters. Experimental results show that the new clustering model can achieve more accurate results than the traditional algorithms.