Miracle-dz/UniFAR-FTUs huggingface dataset:
Epidemiology of and factors associated with end-of-life decisions in a surgical intensive care unit

Objective:To investigate the epidemiology of and possible factors associated with end-of-life decisions in a surgical intensive care unit. Design:Analysis of prospectively collected data. Setting:University hospital surgical intensive care unit. Patients:All patients admitted to the surgical intensive care unit between September 2002 and July 2006. Measurements and Main Results:During the study period, 14,720 patients were admitted to the surgical intensive care unit (61.8 male; mean age, 62 yrs). The prevalence of end-of-life decisions was 2.7% (n = 398); 230 patients (1.6%) had a do-not-resuscitate order, 90 (0.6%) had a decision to withhold therapy, and 78 (0.5%) had a decision to withdraw life-supportive therapy. Patients with end-of-life decisions had higher severity scores on the day of intensive care unit admission, were mostly unplanned admissions, were older, and were more commonly referred from the emergency room or other hospitals compared to those who did not have an end-of-life decision. The prevalence of end-of-life decisions increased significantly with the severity of sepsis. An end-of-life decision was made for 29% of the patients who died in the intensive care unit. Intensive care unit and hospital mortality rates were 6.1% and 10.3%, respectively, overall, and 65.1% and 82.2%, respectively, in patients with an end-of-life decision. In multivariate analysis, older age, admission from another hospital, cirrhosis, sepsis syndromes, simplified acute physiology score II, and sequential organ failure assessment scores were independently associated with end-of-life decisions. Conclusions:Twenty-nine percent of patients who die in the surgical intensive care unit have an end-of-life decision. Severe sepsis/septic shock was associated with a 16-fold increased likelihood of having an end-of-life decision.
Segmentation and Feature Extraction of Lymphocytes WBC using Microscopic Images

This paper presents a proposition for an algorithmic procedure to isolate and count the lymphocytes White Blood Cell (WBC) form microscopic Images. The process involves segmentation of cells, scanning algorithm ,feature extraction, and recognition of lymphocyte cells. The scanning algorithm returns the number and location of candidate area in WBC images. For feature extraction, a combination of the shape feature moment invariants and the roundness are found to have an excellent recognition accuracy for identifying the lymphocyte cells from other WBC types. The whole work has been developed using MATLAB environment, in particular the Image Processing Toolbox. Keywords—Segmentation, White Blood Cells(WBC), Feature Extraction
Searching for non‐transposable targets of planarian nuclear PIWI in pluripotent stem cells and differentiated cells

Nuclear PIWIs together with their guide RNAs (piRNAs) epigenetically silence various genes including transposons in many organisms. In planarians, the nuclear piwi family gene, DjpiwiB is specifically transcribed in adult pluripotent stem cells (adult PSC, neoblast), but not in differentiated cells. However, the protein accumulates in the nuclei of both neoblasts and their descendant differentiated cells. Interestingly, PIWI(DjPiwiB)‐piRNA complexes are indispensable for the repression of transposable genes at the onset of differentiation from neoblasts. Here, we conducted a comparative transcriptome analysis between control and DjpiwiB(RNAi) animals to identify non‐transposable target genes of the DjPiwiB‐piRNA complexes. Using bioinformatic analyses and RNAi we demonstrate that DjPiwiB‐piRNA complexes are required for the proper expression of Djmcm2 and Djhistone h4 in neoblasts and that DjPiwiB‐piRNA complexes regulate the transient expression of Djcalu during neoblast differentiation. Thus, DjPiwiB‐piRNA complexes regulate the correct expression patterns during neoblast self‐renewal and differentiation.
Spatial and temporal variability of sources of ambient fine particulate matter (PM 2.5 ) in California

To identify major sources of ambient fine partic- ulate matter (PM2.5, dp < 2.5 µm) and quantify their con- tributions in the state of California, a positive matrix fac- torization (PMF) receptor model was applied on Speciation Trends Network (STN) data, collected between 2002 and 2007 at eight distinct sampling locations, including El Cajon, Rubidoux, Los Angeles, Simi Valley, Bakersfield, Fresno, San Jose, and Sacramento. Between five to nine sources of fine PM were identified at each sampling site, several of which were common among multiple locations. Secondary aerosols, including secondary ammonium nitrate and ammo- nium sulfate, were the most abundant contributor to ambient PM2.5 mass at all sampling sites, except for San Jose, with an annual average cumulative contribution of 26 to 63 %, across the state. On an annual average basis, vehicular emissions (including both diesel and gasoline vehicles) were the largest primary source of fine PM at all sampling sites in southern California (17-18 % of total mass), whereas in Fresno and San Jose, biomass burning was the most dominant primary contributor to ambient PM2.5 (27 and 35 % of total mass, respectively), in general agreement with the results of pre- vious source apportionment studies in California. In Bakers- field and Sacramento, vehicular emissions and biomass burn- ing displayed relatively equal annual contributions to ambi- ent PM2.5 mass (12 and 25 %, respectively). Other commonly identified sources at all sites included aged and fresh sea salt and soil, which contributed to 0.5-13 %, 2-27 %, and 1-19 % of the total mass, respectively, across all sites and seasons. In addition, a few minor sources were identified exclusively at some of the sites (e.g., chlorine sources, sulfate-bearing road dust, and different types of industrial emissions). These sources overall accounted for a small fraction of the total PM mass across the sampling locations (1 to 15 %, on an annual average basis).
Economic Analysis of Fuelwood Marketing in Enugu State, Nigeria

The study examined the marketing margin and the profitability of fuel wood business in Enugu State, Nigeria. Cluster random sampling technique was employed in carrying out the study in the three urban areas of the State. A total of 90 traders (middle men) were selected namely 45 fuel wood wholesalers and 45 retailers for the study. Data were obtained through primary sources by use of questionnaires. Information sourced from them included sources of fuelwood, purchasing and selling prices, transfer costs and means of transportation. The data were analyzed by employing marketing and gross margins. The findings of the study revealed that the marketing margin for the traders was 45.9% while the harvesters share was 54.1%. The result of the profitability analysis showed that variable costs were high at both wholesale and retail levels consisting of 84.47% and 91.27% of sales revenue at wholesale and retail levels respectively. The findings showed that the gross margins for wholesalers were N77, 998.17and retailers N59, 162.88 respectively. The overall result revealed that fuelwood marketing in the study area was inefficient because of high marketing margins and variable costs. The study concludes that to improve on the level of performance on fuelwood business in the study area feeder roads should be improved upon. This will facilitate easy conveyance of fuel wood from the rural areas to urban centres and also credit advancement to the fuelwood sellers is advocated.
Um estudo sobre alfabetização científica com jovens catarinenses

Resumo: A alfabetizacao cientifica e tecnologica da populacao e importante para preparar os cidadaos para a vida cotidiana e participacao politica. Visando avaliar a educacao cientifica oferecida aos estudantes secundaristas do estado de Santa Catarina, a presente investigacao teve por objetivo mensurar o nivel de alfabetizacao cientifica dos alunos da terceira serie do ensino medio de escolas de Florianopolis e Criciuma. Participaram da pesquisa 754 estudantes, sendo que 618 eram de escolas publicas e 136 de escolas particulares. Os participantes responderam ao Teste de Alfabetizacao Cientifica Basica, uma traducao para o portugues de um instrumento de mensuracao de alfabetizacao cientifica sul-africano. Os resultados apontam que o nivel de alfabetizacao cientifica encontrado foi de 36,5%, semelhante ao da Africa do Sul. Os alunos de escolas particulares obtiveram indices superiores aos da rede publica. Conclui-se que e necessario aprimorar o ensino de ciencia em Santa Catarina para promover a inclusao social dos cidadaos. Palavras-chave: alfabetizacao cientifica, ensino medio, ciencia e tecnologia, redes de ensino, ensino de ciencias.
The Spreading of Alternatives: Is it the Perceived Choice or Actual Choice that Changes our Preference?

After making a difficult choice, the preference rating of a chosen alternative tends to increase, and the rating of the rejected one tends to decrease. Such a change of preference is called spreading of alternatives. It is unclear whether it is the choice itself, or the choice one believes one has made that leads to preference change. Using a facial attractiveness task, we addressed this question by setting up an experiment to measure how the actual choice and perceived choice changed the preference. In the current study, participants first rated the attractiveness of female faces, and then made a choice between two faces that they had rated the same, after which, they re-rated the female faces. Notably, in the re-rating session, participants were given either veridical, false, or no feedback about their prior choice. This way, we were able to measure the functions of actual choice and perceived choice in rating changes. Results showed that both actual action and perceived action exert significant influence in shaping preference. The veridical feedback enhanced the spreading of alternatives effect whereas the false feedback weakened this effect, indicating that preference can be modulated by explicit manipulation. Copyright © 2016 John Wiley & Sons, Ltd.
You Only Look Twice: Rapid Multi-Scale Object Detection In Satellite Imagery

Detection of small objects in large swaths of imagery is one of the primary problems in satellite imagery analytics. While object detection in ground-based imagery has benefited from research into new deep learning approaches, transitioning such technology to overhead imagery is nontrivial. Among the challenges is the sheer number of pixels and geographic extent per image: a single DigitalGlobe satellite image encompasses >64 km2 and over 250 million pixels. Another challenge is that objects of interest are minuscule (often only ~10 pixels in extent), which complicates traditional computer vision techniques. To address these issues, we propose a pipeline (You Only Look Twice, or YOLT) that evaluates satellite images of arbitrary size at a rate of >0.5 km2/s. The proposed approach can rapidly detect objects of vastly different scales with relatively little training data over multiple sensors. We evaluate large test images at native resolution, and yield scores of F1 > 0.8 for vehicle localization. We further explore resolution and object size requirements by systematically testing the pipeline at decreasing resolution, and conclude that objects only ~5 pixels in size can still be localized with high confidence. Code is available at this https URL.
Technical Note: Feasibility of CO 2 profile retrieval from limb viewing solar occultation made by the ACE-FTS instrument

Abstract. Major limitations of our present knowledge of the global distribution of CO2 in the atmosphere are the uncertainty in atmospheric transport mixing and the sparseness of in situ concentration measurements. Limb viewing space-borne sounders, observing the atmosphere along tangential optical paths, offer a vertical resolution of a few kilometers for profiles, which is much better than currently flying or planned nadir sounding instruments can achieve. In this paper, we analyse the feasibility of obtaining CO2 vertical profiles in the 5–25 km altitude range from the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS, launched in August 2003), high spectral resolution solar occultation measurements. Two main difficulties must be overcome: (i) the accurate determination of the instrument pointing parameters (tangent heights) and pressure/temperature profiles independently from an a priori CO2 profile, and (ii) the potential impact of uncertainties in the temperature knowledge on the retrieved CO2 profile. The first difficulty has been solved using the N2 collision-induced continuum absorption near 4 μm to determine tangent heights, pressure and temperature from the ACE-FTS spectra. The second difficulty has been solved by a careful selection of CO2 spectral micro-windows. Retrievals using synthetic spectra made under realistic simulation conditions show a vertical resolution close to 2.5 km and accuracy of the order of 2 ppm after averaging over 25 profiles. These results open the way to promising studies of transport mechanisms and carbon fluxes from the ACE-FTS measurements. First CO2 vertical profiles retrieved from real ACE-FTS occultations shown in this paper confirm the robustness of the method and applicability to real measurements.
SALMONELLA SPP. ISOLATION FROM CHICKEN SAMPLES AND IDENTIFICATION BY POLYMERASE CHAIN REACTION

Summary Ozbey, G. & H. B. Ertas, 2005. Salmonella spp. isolation from chicken samples and identification by polymerase chain reaction. Bulg. J. Vet. Med., 9, No 1, 67�73. In this study, carcass, intestine, liver, gall bladder and spleen samples of chickens slaughtered at an abattoir in the Elazig province were tested for the presence of Salmonella spp. The identity of Salmonella spp. was further proved by culture and by polymerase chain reaction (PCR). A total of 1250 samples were tested. All samples were collected from different commercially reared chicken flocks. Chicken carcasses, intestines, livers, gall bladders and spleen were found positive with proportions of 12%, 7.2%, 4%, 2% and 1.6% respectively, by both culture and PCR. The Salmonella detection rate was the highest (12%) in chicken carcasses and the lowest (1.6%) in spleen. This study showed that Salmonella spp. was widespread among the chicken population in Elazig.
Parameter Estimation for Time Varying Dynamical Systems using Least Squares Support Vector Machines

Abstract This paper develops a new approach based on Least Squares Support Vector Machines (LS-SVMs) for parameter estimation of time invariant as well as time varying dynamical SISO systems. Closed-form approximate models for the state and its derivative are first derived from the observed data by means of LS-SVMs. The time-derivative information is then substituted into the system of ODEs, converting the parameter estimation problem into an algebraic optimization problem. In the case of time invariant systems one can use least-squares to solve the obtained system of algebraic equations. The estimation of time-varying coefficients in SISO models, is obtained by assuming an LS-SVM model for it.
Monetary and Fiscal Responses during the Financial Crisis in the Developing and Emerging Economies

The study provides empirical analyses of the role of monetary and fiscal policy on economic growth during the financial crisis in developing and emerging economies. I investigate 72 episodes of financial crisis in developing and emerging countries, in order to assess the effect of monetary and fiscal policy on output cost over the financial crisis. I find out that effect of monetary and fiscal tightening will increase output cost during the financial crisis. The results show that fiscal policy has been more effective tools in dealing with financial crisis, than the effect of monetary policy. In addition, the result suggests that the coordination with an expansionary fiscal policy and a neutral monetary policy will reduce output cost during the financial crisis in developing and emerging countries. Normal 0 false false false EN-US X-NONE X-NONE
Sequencing of the Cheese Microbiome and Its Relevance to Industry

The microbiota of cheese plays a key role in determining its organoleptic and other physico-chemical properties. It is essential to understand the various contributions, positive or negative, of these microbial components in order to promote the growth of desirable taxa and, thus, characteristics. The recent application of high throughput DNA sequencing (HTS) facilitates an even more accurate identification of these microbes, and their functional properties, and has the potential to reveal those microbes, and associated pathways, responsible for favorable or unfavorable characteristics. This technology also facilitates a detailed analysis of the composition and functional potential of the microbiota of milk, curd, whey, mixed starters, processing environments, and how these contribute to the final cheese microbiota, and associated characteristics. Ultimately, this information can be harnessed by producers to optimize the quality, safety, and commercial value of their products. In this review we highlight a number of key studies in which HTS was employed to study the cheese microbiota, and pay particular attention to those of greatest relevance to industry.
Trade Flows and Volatility of Their Fundamentals: Some Evidence from Mexico

In this paper we investigate the effects of volatility of the fundamental determinants of trade on trade flows in Mexico during the period 1991-2008. Our import and export functions are based on the well known imperfect substitute goods model of trade. We focus on the effects on imports and exports of real exchange rate as well as measures of relative prices and real income and their associated conditional volatility. We consider a vector error-correction model with conditional heteroskedasticity (VEC-GARCH). Our results indicate that the imperfect substitute goods model is a reasonable empirical specification as we find evidence supporting cointegration and obtain income and price elasticities in line with those from previous empirical studies. Quantitatively, we find that income effects are the most important determinants of trade flows in the long run. Also, some preliminary results show that there might be some non-negligible volatility effects of fundamentals on the short run dynamics of Mexican imports and exports.
Do cave salamanders occur randomly in cavities? An analysis with Hydromantes strinatii

Underground environments are increasingly recognised as important habitats for the distribution of certain amphibians. However, very few analyses tested whether amphibians occur randomly in underground environments, or they select cavities with specific environmental features. We assessed the distribution of the cave salamander Hydromantes (Speleomantes) strinatii in an area of NW Italy during summer, and analysed relationships between salamander distribution and multiple cave features, considering parameters describing both the biotic and the abiotic environment. Using visual encounter surveys, species' detection probability was high, indicating that this technique provides reliable information on distribution. Salamanders were associated to caves with cold and humid microclimate, presence of wet walls, and hosting large numbers of Meta spiders. The association with less luminous caves was close to significance. Distribution data were not affected by spatial autocorrelation, suggesting that cave features are more important than the proximity to other occupied caves in determining the pattern of occupancy. Caves are heterogeneous environments: cave salamanders are strongly related to the features of underground environments. Food availability and abiotic features are major determinants of suitability for cave salamanders. Inter-correlation among biotic and abiotic cave features makes it complex identifying the role of factors determining species distribution, but quantitative analyses and PCA help to unravel the cave habitat requirements for amphibians.
Salient Object Detection Using UAVs

A salient object detection approach is proposed in this paper, tailored to the aerial images collected by Unmanned Aerial Vehicles (UAVs). In particular, the aerial images are classiﬁed. The selected image is segmented using superpixel-s, and then a weak saliency map is constructed based on image priors. Positive and negative samples are selected in accordance with the weak saliency map for training a boosted classi-ﬁer. Consequently, the classiﬁer is used to produce a strong saliency map. The weak and strong saliency maps are integrated to locate the candidate objects, and false alarms are pruned after post-processing. Experiments on aerial images collected above meadow and roof demonstrate the effectiveness of the proposed approach.
Fast photographic style transfer based on convolutional neural networks

The techniques for photographic style transfer have been researched for a long time, which explores effective ways to transfer the style features of a reference photo onto another content photograph. Recent works based on convolutional neural networks present an effective solution for style transfer, especially for paintings. The artistic style transformation results are visually appealing, however, the photorealism is lost because of content-mismatching and distortions even when both input images are photographic. To tackle this challenge, this paper introduces a similarity loss function and a refinement method into the style transfer network. The similarity loss function can solve the content-mismatching problem, however, the distortion and noise artefacts may still exist in the stylized results due to the content-style trade-off. Hence, we add a post-processing refinement step to reduce the artefacts. The robustness and effectiveness of our approach has been evaluated through extensive experiments which show that our method can obtain finer content details and less artefacts than state-of-the-art methods, and transfer style faithfully. In addition, our approach is capable of processing photographic style transfer in almost real-time, which makes it a potential solution for video style transfer.
Sensitivity enhancement of fiber optic FBG sensor for acoustic emission

A fiber optic Bragg grating based acoustic emission sensor system is developed to provide on-line monitoring of cracks or leaks in reactor vessel head penetration of nuclear power plants. Various type of fiber Bragg grating sensor including the variable length of sensing part was fabricated and prototype sensor system was tested by using PZT pulser and pencil lead break sources. In this study, we developed a cantilever type fiber sensor to enhance the sensitivity and to resonant frequency control. Two types of sensor attachment were used. First, the fiber Bragg grating sensor was fully bonded to the surface using bonding agent. Second one is that one part of fiber was partially bonded to surface and the other part of fiber will be remained freely. The resonant frequency of the fiber Bragg grating sensor will depend on the length of sensing part. Various kinds of resonant type fiber Bragg grating acoustic emission sensors were developed. Also several efforts were done to enhance the sensitivity of FBG AE sensor, which include FBG spectrum optimization and electrical and optical noise reduction. Finally, based on the self-developed acquisition system, a series of tests demonstrate the ability of the developed fiber sensor system to detect a pencil lead break event and continuous leak signal.