Miracle-dz/UniFAR-FTUs huggingface dataset:
Thermoregulatory consequences of salt loading in the lizard Pogona vitticeps

ABSTRACT Previous research has demonstrated that dehydration increases the threshold temperature for panting and decreases the thermal preference of lizards. Conversely, it is unknown whether thermoregulatory responses such as shuttling and gaping are similarly influenced. Shuttling, as an active behavioural response, is considered one of the most effective thermoregulatory behaviours, whereas gaping has been proposed to be involved in preventing brain over-heating in lizards. In this study we examined the effect of salt loading, a proxy for increased plasma osmolality, on shuttling and gaping in Pogona vitticeps. Then, we determined the upper and lower escape ambient temperatures (UETa and LETa), the percentage of time spent gaping, the metabolic rate (V̇O2), the evaporative water loss (EWL) during gaping and non-gaping intervals and the evaporative effectiveness (EWL/V̇O2) of gaping. All experiments were performed under isotonic (154 mmol l−1) and hypertonic saline injections (625, 1250 or 2500 mmol l−1). Only the highest concentration of hypertonic saline altered the UETa and LETa, but this effect appeared to be the result of diminishing the animal's propensity to move, instead of any direct reduction in thermoregulatory set-points. Nevertheless, the percentage of time spent gaping was proportionally reduced according to the saline concentration; V̇O2 was also decreased after salt loading. Thermographic images revealed lower head than body surface temperatures during gaping; however this difference was inhibited after salt loading. Our data suggest that EWL/V̇O2 is raised during gaping, possibly contributing to an increase in heat transfer away from the lizard, and playing a role in head or brain cooling. Summary: Gaping is proposed to be an important evaporative water loss response aimed at preventing overheating of the head and brain in bearded dragons.
Energy-efficient management of UMTS access networks

The increasing concern about the energy consumption of telecommunication networks is driving operators to manage their equipments so as to optimize energy utilization without sacrificing the user experience. In this paper, we focus on UMTS access networks, since access devices are the main energy consumers in UMTS networks. We propose a novel approach for the energy-aware management of UMTS access networks, consisting in a dynamic network planning, that, based on the instantaneous traffic intensity, reduces the number of active access devices when they are underutilized (typically at night). When some access devices are switched off, radio coverage and service provisioning are taken care of by the devices that remain active, possibly with some small increase in the emitted power, so as to guarantee that service is available over the whole area, with the desired quality.
Culturing, Storage, and Quantification of Rotaviruses

Group A rotaviruses (RVs) infect the young of numerous animal species and cause acute gastroenteritis. Cultivation of animal and human RVs in cells requires proteolytic activation of the viral attachment protein using trypsin. Continuous cell lines, such as rhesus monkey kidney cells, as well as primary monkey kidney cells, are routinely used for the growth and characterization of RVs. Isolation and cultivation of human RVs from clinical fecal specimens is difficult and adaptation to growth in vitro requires multiple rounds of passage in primary cells. Following growth, RV stocks can be purified by centrifugation, if required, and quantified using plaque assay or fluorescence focus assay. This unit describes easily applicable procedures for the culturing, storage, and quantification of RVs. Curr. Protoc. Microbiol. 15:15C.3. 1‐15C.3. 24. © 2009 by John Wiley & Sons, Inc.
A Diversity-Based Approach for Managing Faults in Web Services

This paper discusses the value-added of diversity to support fault tolerant Web Services operation. Web Services offering the same functionality are gathering into the same virtual space referred to as diversity group. Besides the group additional components are used including: composite manager, group manager, and Web service manager. The first component invokes the diversity groups and either resumes or aborts the overall execution in case of failures. The second component oversees Web services execution and the interactions between them. Finally, the last component monitors a Web service execution and reports either failure or success to the group manager. An architecture and a set of experiments showing the use of diversity to design and deploy fault tolerant Web services is presented in this paper.
Simulated dipeptide recognition by vancomycin

The antimicrobial activity of vancomycin and related glycopeptide antibiotics is due to stereospecific recognition of polypeptide components in bacterial cell walls. To better understand how these antibiotics recognize polypeptide determinants, we have developed dynamic models of the complexes formed by the vancomycin aglycon and two different dipeptide ligands, Ac‐D‐ala‐D‐ala and Ac‐D‐ala‐gly. Molecular dynamics simulations of the two complexes, initially conditioned with distance constraints derived from two‐dimensional nuclear magnetic resonance (NMR) studies, are conformationally stable and propagate in a manner consistent with the NMR‐derived constraints after the constraints are removed. Free energy calculations accurately predict the relative binding affinity of these two complexes and help validate the simulation models for detailed structural analysis. Although the two ligands adopt similar conformations when bound to the antibiotic, there are clear differences in the configuration of intermolecular hydrogen bonds, the overall shape of the antibiotic, and other structural features of the two complexes. This analysis illustrates how complex structural and dynamic factors interrelate and contribute to differences in binding affinity. © 1997 John Wiley & Sons, Ltd.
The coregulator exchange in transcriptional functions of nuclear receptors.

Nuclear receptors (NR) comprise a family of transcription factors that regulate gene expression in a liganddependent manner. Members of the NR superfamily include receptors for steroid hormones, such as estrogens (ER) and glucocorticoids (GR), receptors for nonsteroidal ligands, such as thyroid hormones (TR) and retinoic acid (RAR), as well as receptors that bind diverse products of lipid metabolism, such as fatty acids and prostaglandins (for review, see Beato et al. 1995; Chambon 1995; Mangelsdorf and Evans 1995). The NR superfamily also includes a large number of so-called orphan receptors for which regulatory ligands have not been identified (Mangelsdorf and Evans 1995). Although many orphan receptors are likely to be regulated by small-molecular-weight ligands, other mechanisms of regulation, such as phosphorylation (Hammer et al. 1999; Tremblay et al. 1999) have also proven to be of importance. Remarkably, the sequence of the Caenorhabditis elegans genome has revealed the presence of >200 members of the NR family, suggesting a critical role of these proteins in environmental adaptation (Sluder et al. 1999). Although mammalian genomes are unlikely to contain such a large complement of these factors, >24 distinct classes of NR have been identified in humans, and these factors exert diverse roles in the regulation of growth, development, and homeostasis. Based on their importance in biology and medicine, as well as the relatively simple mechanism of regulation, NR represent one of the most intensively studied and best-understood classes of transcription factors at the molecular level. Members of the NR family regulate transcription by several mechanisms (Fig. 1). Nuclear receptors can activate or repress target genes by binding directly to DNA response elements as homoor heterodimers or by binding to other classes of DNA-bound transcription factors. A subset of NRs, including TR and RAR, can actively repress target genes in the presence or absence of ligand binding, and many NR have been demonstrated to inhibit transcription in a ligand-dependent manner by antagonizing the transcriptional activities of other classes of transcription factors. These activities have been linked to interactions with general classes of molecules that appear to serve coactivator or corepressor function. In this review, we will discuss recent progress concerning the molecular mechanisms by which NR cofactor interactions serve to activate or repress transcription.
Minimal Maximum-Level Programming: Faster memory access via multi-level cell sharing

In multi-level-cell (MLC) memory such as Flash and Phase-change memory, shrinking cell size and the growing number of levels per cell worsen the access-rate to capacity ratio and even reduce access rate. We present Minimal Maximum-Level Programming (MMLP), a scheme for expediting cell writing by sharing physical cells among multiple data pages and exploiting the fact that making moderate changes to a cell's level is faster than making large ones. Reading is also expedited by requiring fewer reference comparisons. In a four-level cell example, we achieve a 32% reduction in write/read latency relative to prior art with negligible area overhead.
Experimental Evolution of an Oncolytic Vesicular Stomatitis Virus with Increased Selectivity for p53-Deficient Cells

Experimental evolution has been used for various biotechnological applications including protein and microbial cell engineering, but less commonly in the field of oncolytic virotherapy. Here, we sought to adapt a rapidly evolving RNA virus to cells deficient for the tumor suppressor gene p53, a hallmark of cancer cells. To achieve this goal, we established four independent evolution lines of the vesicular stomatitis virus (VSV) in p53-knockout mouse embryonic fibroblasts (p53−/− MEFs) under conditions favoring the action of natural selection. We found that some evolved viruses showed increased fitness and cytotoxicity in p53−/− cells but not in isogenic p53+/+ cells, indicating gene-specific adaptation. However, full-length sequencing revealed no obvious or previously described genetic changes associated with oncolytic activity. Half-maximal effective dose (EC50) assays in mouse p53-positive colon cancer (CT26) and p53-deficient breast cancer (4T1) cells indicated that the evolved viruses were more effective against 4T1 cells than the parental virus or a reference oncolytic VSV (MΔ51), but showed no increased efficacy against CT26 cells. In vivo assays using 4T1 syngeneic tumor models showed that one of the evolved lines significantly delayed tumor growth compared to mice treated with the parental virus or untreated controls, and was able to induce transient tumor suppression. Our results show that RNA viruses can be specifically adapted typical cancer features such as p53 inactivation, and illustrate the usefulness of experimental evolution for oncolytic virotherapy.
Serum glucose levels for predicting death in patients admitted to hospital for community acquired pneumonia: prospective cohort study

Objective To examine whether acute dysglycaemia predicts death in people admitted to hospital with community acquired pneumonia. Design Multicentre prospective cohort study. Setting Hospitals and private practices in Germany, Switzerland, and Austria. Participants 6891 patients with community acquired pneumonia included in the German community acquired pneumonia competence network (CAPNETZ) study between 2003 and 2009. Main outcome measures Univariable and multivariable hazard ratios adjusted for sex, age, current smoking status, severity of community acquired pneumonia using the CRB-65 score (confusion, respiratory rate >30/min, systolic blood pressure ≤90 mm Hg or diastolic blood pressure ≤60 mm Hg, and age ≥65 years), and various comorbidities for death at 28, 90, and 180 days according to serum glucose levels on admission. Results An increased serum glucose level at admission to hospital in participants with community acquired pneumonia and no pre-existing diabetes was a predictor of death at 28 and 90 days. Compared with participants with normal serum glucose levels on admission, those with mild acute hyperglycaemia (serum glucose concentration 6-10.99 mmol/L) had a significantly increased risk of death at 90 days (1.56, 95% confidence interval 1.22 to 2.01; P<0.001), and this risk increased to 2.37 (1.62 to 3.46; P<0.001) when serum glucose concentrations were ≥14 mmol/L. In sensitivity analyses the predictive value of serum glucose levels on admission for death was confirmed at 28 days and 90 days. Patients with pre-existing diabetes had a significantly increased overall mortality compared with those without diabetes (crude hazard ratio 2.47, 95% confidence interval 2.05 to 2.98; P<0.001). This outcome was not significantly affected by serum glucose levels on admission (P=0.18 for interaction). Conclusions Serum glucose levels on admission to hospital can predict death in patients with community acquired pneumonia without pre-existing diabetes. Acute hyperglycaemia may therefore identify patients in need of intensified care to reduce the risk of death from community acquired pneumonia.
Understanding causal conditionals: A study of individual differences

Previous studies have suggested that a minority of university students, of lower cognitive ability, are inclined to interpret abstract conditional statements, if p then q, as if they were conjunctions: p and q. In the present study we administered the conditional truth table task to a large sample of students (n = 160), but using realistic, everyday causal conditionals. We also measured their general intelligence. While individual differences were found, these were not consistent with some participants adopting a conjunctive interpretation of such statements. Rather, it appears that students of lower cognitive ability are rather likely to assume that a conditional implies its converse, so that it means also if q then p. The results are discussed with reference to the suppositional theory of conditionals and our more general account of hypothetical thinking.
A method for co-existing heterogeneous IoT environments based on compressive sensing

Compressive Sensing (CS) is a stable and robust technique that allows for the sub-sampling of data at a given data rate: `compressive sampling' or `compressive sensing' at rates smaller than the Nyquist sampling rate. It makes it possible to create standalone and net-centric applications with fewer resources required in Internet of Things (IoT). CS-based signal and information acquisition/compression paradigm combines the nonlinear reconstruction algorithm and random sampling on a sparse basis that provides a promising approach to compress signal and data in information systems. In this paper, we investigates how CS can provide new insights into coexisting heterogeneous IoT environments. First, we briefly introduce the CS theory with respect to the sampling through providing a compressed sampling process with low computation costs. Then, a CS-based framework is proposed for IoT, in which the hub nodes measure, transmit, and store the sampled data into the fusion center. Then, an efficient cluster-sparse reconstruction algorithm is proposed for in-network compression aiming at more accurate data reconstruction and lower energy efficiency. Therefore, compression should be performed locally at each Access Point (AP) and reconstruction is executed jointly to consider dependencies in the acquired data by the final fusion center.
Nuclear microscopy: A tool for imaging elemental distribution and percutaneous absorption in vivo

Nuclear microscopy is a technique based on a focused beam of accelerated particles that has the ability of imaging the morphology of the tissue in vivo and of producing the correspondent elemental maps, whether in major, minor, or trace concentrations. These characteristics constitute a strong advantage in studying the morphology of human skin, its elemental distributions and the permeation mechanisms of chemical compounds. In this study, nuclear microscopy techniques such as scanning transmission ion microscopy and particle induced X‐ray emission were applied simultaneously, to cryopreserved human skin samples with the purpose of obtaining high‐resolution images of cells and tissue morphology. In addition, quantitative elemental profiling and mapping of phosphorus, calcium, chlorine, and potassium in skin cross‐sections were obtained. This procedure accurately distinguishes the epidermal strata and dermis by overlapping in real time the elemental information with density images obtained from the transmitted beam. A validation procedure for elemental distributions in human skin based on differential density of epidermal strata and dermis was established. As demonstrated, this procedure can be used in future studies as a tool for the in vivo examination of trans‐epidermal and ‐dermal delivery of products. Microsc. Res. Tech., 2007. © 2007 Wiley‐Liss, Inc.
Hierarchical Bayesian formulations for selecting variables in regression models

The objective of finding a parsimonious representation of the observed data by a statistical model that is also capable of accurate prediction is commonplace in all domains of statistical applications. The parsimony of the solutions obtained by variable selection is usually counterbalanced by a limited prediction capacity. On the other hand, methodologies that assure high prediction accuracy usually lead to models that are neither simple nor easily interpretable. Regularization methodologies have proven to be useful in addressing both prediction and variable selection problems. The Bayesian approach to regularization constitutes a particularly attractive alternative as it is suitable for high‐dimensional modeling, offers valid standard errors, and enables simultaneous estimation of regression coefficients and complexity parameters via computationally efficient MCMC techniques. Bayesian regularization falls within the versatile framework of Bayesian hierarchical models, which encompasses a variety of other approaches suited for variable selection such as spike and slab models and the MC3 approach. In this article, we review these Bayesian developments and evaluate their variable selection performance in a simulation study for the classical small p large n setting. The majority of the existing Bayesian methodology for variable selection deals only with classical linear regression. Here, we present two applications in the contexts of binary and survival regression, where the Bayesian approach was applied to select markers prognostically relevant for the development of rheumatoid arthritis and for overall survival in acute myeloid leukemia patients. Copyright © 2012 John Wiley & Sons, Ltd.
High-cost users of medical care.

Cost characteristics of hospital patients were analyzed in 2238 medical records randomly selected from 42,880 dicharges in six contrasting hospital populations in the year 1976. Total hospital billings were concentrated on a few patients. On average, the high-cost 13% of patients consumed as many resources as the low-cost 87%. Repeated hospitalizations for the same disease were more characteristic of the expensive patients than were single cost-intensive stays, "intensive care," or prolonged single hospitalizations. Potentially harmful personal habits (e.g., drinking and smoking) were indicated in the records of high-cost patients substantially more often than in those of low-cost patients. Unexpected complications during treatment were five times more frequent in the high-cost group. Public policy programs for health insurance or cost control should include provisions based on the special characteristics of high-cost patients.
A New Radiometric Correction Method for Side-Scan Sonar Images in Consideration of Seabed Sediment Variation

Affected by the residual of time varying gain, beam patterns, angular responses, and sonar altitude variations, radiometric distortion degrades the quality of side-scan sonar images and seriously affects the application of these images. However, existing methods cannot correct distortion effectively, especially in the presence of seabed sediment variation. This study proposes a new radiometric correction method for side-scan sonar images that considers seabed sediment variation. First, the different effects on backscatter strength (BS) are analyzed, and along-track distortion is removed by establishing a linear relationship between distortion and sonar altitude. Second, because the angle-related effects on BSs with the same incident angle are the same, a novel method of unsupervised sediment classification is proposed for side-scan sonar images. Finally, the angle–BS curves of different sediments are obtained, and angle-related radiometric distortion is corrected. Experiments prove the validity of the proposed method.
Spatial patterns of the canopy stress during 2005 drought in Amazonia

In the last decades, the detection of drought occurrences and assessment of its severity using satellite data are becoming popular in disaster, desertification, crop production, phenology, land cover change and climate change studies. To detect the drought effects on different vegetation types, many methodologies have been developed, mostly relying on the use of vegetation indices. This communication reports the first attempt to assess the capability of MODIS NDVI, Enhanced Vegetation Index (EVI) and Normalized Difference Water Index (NDWI) from 2000 to 2006 time-series to detect the 2005 drought in Amazonia. To reach this objective, monthly composites of the MOD13A2 product were generated from period. Then, monthly anomalies were calculated, considering anomalous values when lower than -1 standard deviation (sd) or higher than 1 sd. Rainfall data provided by the Tropical Rainfall Measuring Mission (TRMM) was also acquired for the same time-series with the objective of supporting the understanding of vegetation response with the precipitation. Water deficit data calculated based on the TRMM data were also used to guide the sampling scheme. A land cover map for South America updated with natural land cover changes detected by the Near Real Time Deforestation Detection Project (DETER) was used as a mask to avoid false anomalies in the Brazilian Amazon. In general, NDWI and EVI showed to be sensitive and consistent for the temporal series used. NDVI presented a high variability and though a difficult interpretation. Critical months in the NDWI and EVI series coincided with the months with higher water stress calculated based on the TRMM data. EVI also showed to detect changes in the canopy structure. These preliminary results suggest that this is a strong methodology to be used in the spatial analysis of the extent of the drought effects in the vegetation. Literfall data will be incorporate in this research for validation purposes.