Miracle-dz/UniFAR-FTUs huggingface dataset:
The effect of dietary phosphatidylcholine and its constituent fatty acids on microdiet ingestion and fatty acid absorption rate in gilthead sea bream, Sparus auratus, larvae

This study tested the effect of the level of dietary phosphatidylcholine (PC) and its constituent medium-chain fatty acids on microdiet ingestion (μg diet larva−1 h−1) and the absorption rate of the free fatty acid [14C]16:0 (pmole larva−1 h−1) in 15, 20, 21, 25, 26, 30 and 31-day-old gilthead sea bream, Sparus auratus L. , larvae. Fish were fed four microdiets (A, B, C and D): microdiet A contained no phospholipid (PL), while microdiet B included 10 g kg−1Artemia nauplii PL (3.7 g kg−1 PC). Microdiets C and D contained 10 g kg−1 purified saturated PC dimyristoyl (C14:0) and polyunsaturated PC dilinoleoyl (C18:2[cis]−9,12), respectively. Larvae from one or both of the PC microdiets demonstrated significantly higher (P < 0.05) ingestion rates (μg diet larva−1 h−1) than the non-PL microdiet control in 15, 21, 22, 25 and 26-day-old larvae and the Artemia PL microdiet in 15, 22 and 26-day-old larvae. However, microdiet ingestion and fatty acid absorption rate appeared to be independent of the associated medium carbon chain saturated or polyunsaturated fatty acid moiety of the PC diets. Apparent absorption, as measured by the retention of radio-labelled [14C]16:0 following 8 h of non-labelled microdiet feeding, was possibly related to feeding.
Assessing the market niche of Eurasian rail freight in the belt and road era

PurposeThis paper presents an overview of the recent development of Eurasian rail freight in the Belt and Road era and further evaluates its service quality in terms of transit times and transport costs compared to other transport modes in containerised supply chains between Europe and China.Design/methodology/approachA trade-off model of transit time and transport costs based on quantitative data from primary and secondary sources is developed to demonstrate the market niche for Eurasian rail freight vis-a-vis the more established modes of transport of sea, air and sea/air. In a scenario analysis, further cargo attributes influencing modal choice are employed to show for which cargo type Eurasian rail freight service is favourable from a shipper's point of view.FindingsAt present, Eurasian rail freight is about 80% less expensive than air freight with only half of the transit time of conventional sea freight. Our scenario analysis further suggests that for shipping time-sensitive goods with lower cargo value ranging from $US1.23/kg to $US10.89/kg as well as goods with lower time sensitivity and higher value in a range of $US2.46/kg to $US21.78/kg, total logistics costs of Eurasian rail freight service rail is cheaper than all other modes of transport.Practical implicationsAs an emerging competitive solution, Eurasian rail freight demonstrates to be an option beneficial in terms of transport cost, transit time, reliability and service availability, which offers a cost-efficient option enabling shippers to build up agile and more sustainable supply chains between China and Europe.Originality/valueOur study firstly provides a comprehensive assessment of present Eurasian rail freight including a thorough comparison with alternative modes of transport from a shipper's point of view.
Effects of light intensity on activity and pelagic dispersion of fish: studies with a seabed-mounted echosounder

Didrikas, T. , and Hansson, S. 2009. Effects of light intensity on activity and pelagic dispersion of fish: studies with a seabed-mounted echosounder. - ICES Journal of Marine Science, 66: 388-395.A seabed-mounted, upwards-pinging echosounder was used to study fish activity and pelagic dispersion in relation to fish size, light, and temperature. Four phases (day, dusk, night, dawn) in fish dispersion were distinguished over the diel cycle, and the swimming speed of fish varied among these phases. Notably, average swimming speed by day was twice as high as by night. For all phases combined, fish size, light intensity, and temperature explained 52% of the variability in swimming speed. When different phases were analysed separately, fish size was the most important variable by day, whereas light had the strongest effects on swimming speed in the evening. During the mornings, variability in swimming speed was best correlated with temperature, but by night all factors (fish size, light intensity, temperature) had similar effects on activity. These results have implications for fish bioenergetics models. Such models should account for seasonal, light-driven cycles in activity-induced respiration estimates, in particular when modelling populations at high latitudes.
Cougar Prey Use In A Wildland–Urban Environment In Western Washington

Abstract The Cougar (Puma concolor) is an apex predator whose occurrence and space- use patterns are closely tied to the abundance and vulnerability of ungulate prey. Deer (Odocoileus spp.) and Elk (Cervus elaphus) readily use residential portions of the landscape, but little is known of Cougar prey use within these environments. We used Global Positioning System and VHF relocation data from 20 Cougars to examine prey use in a wildland-urban landscape in western Washington. We tested for differences (α = 0.10) between wildland and residential prey compositions using the Chi-square test of homogeneity and used an ANOVA fixed-effects model to determine the potential influence of residential development on the duration of Cougar presence on kills. We located 304 kills throughout the study area with Black-tailed Deer (Odocoileus hemionus columbianus, 55.3%), Beaver (Castor canadensis, 22.0%), and Elk (8.8%) constituting the bulk of Cougar diet. Wildland and residential prey compositions were significantly different, with Cougars killing a higher proportion of Deer, Beavers, and Mountain Beavers (Aplodontia rufa) in wildland areas and more Coyotes (Canis latrans), Raccoons (Procyon lotor), Opossums (Didelphis virginiana), and domestic species close to residential development. Kill location did not have a significant effect on the duration of stay regardless of species killed, nor was the effect of location significant when comparing kills of the same species. Cougar diet in wildland-urban forests of western Washington is diverse, but Cougars do not appear to shift their space-use patterns to take advantage of non-ungulate prey close to residential development. However, long-term management of Cougars in wildland-urban environments may require an examination of ungulate presence in residential environments to ensure that these populations do not encourage Cougar presence in habitats close to people.
Green coffee beans feature extractor using image processing

This study offers a novel solution to deal with the low signal-to-noise ratio and slow execution rate of the first derivative edge detection algorithms namely, Roberts, Prewitt and Sobel algorithms. Since the two problems are brought about by the complex mathematical operations being used by the algorithms, these were replaced by a discriminant. The developed discriminant, equivalent to the product of total difference and intensity divided by the normalization values, is based on the “pixel pair formation” that produces optimal peak signal to noise ratio. Results of the study applying the discriminant for the edge detection of green coffee beans shows improvement in terms of peak signal to noise ratio (PSNR), mean square error (MSE), and execution time. It was determined that accuracy level varied according to the total difference of pixel values, intensity, and normalization values. Using the developed edge detection technique led to improvements in the PSNR of 2.091%, 1.16 %, and 2.47% over Sobel, Prewitt, and Roberts respectively. Meanwhile, improvement in the MSE was measured to be 13.06%, 7.48 %, and 15.31% over the three algorithms. Likewise, improvement in execution time was also achieved at values of 69.02%, 67.40 %, and 65.46% over Sobel, Prewitt, and Roberts respectively.
Object-oriented multiscale deep features for hyperspectral image classification

ABSTRACT The classification of hyperspectral images (HSIs) is one of the most popular topics in the remote sensing community. Numerous feature extraction methods have been proposed to improve the classification accuracy of HSIs. Recently, deep features extracted by convolution neural network (CNN) have been introduced into the classification process of HSIs. Due to the nonlinear and invariant advantages of the features, CNN methods provide a powerful tool for representing geographic objects and classifying HSIs. However, traditional deep features only extracted at pixel-level and often neglect multiscale characteristics of geographic objects. In this study, a new deep feature extraction method is proposed, which takes advantage of multi-scale object analysis and the CNN model. Firstly, multiscale image objects are obtained by the multiscale segmentation algorithm and multiscale low-level features of objects are extracted. Secondly, the CNN is devoted to obtain deep features from low-level object features at each scale, respectively. Thirdly, the obtained deep features at all scales are stacked and fed to one fully connected layer to extract the multiscale deep learning features for classification. Finally, the logistic regression classifier is applied to hyperspectral image (HSI) classification based on object-oriented multiscale deep features. The proposed method was carried out on three widely used hyperspectral data sets: University of Pavia, Salinas, and Washington DC. The results reveal that the proposed method provides better results than other state-of-the-art methods.
Deep Learning-Based Maximum Temperature Forecasting Assisted with Meta-Learning for Hyperparameter Optimization

Time series forecasting of meteorological variables such as daily temperature has recently drawn considerable attention from researchers to address the limitations of traditional forecasting models. However, a middle-range (e.g., 5–20 days) forecasting is an extremely challenging task to get reliable forecasting results from a dynamical weather model. Nevertheless, it is challenging to develop and select an accurate time-series prediction model because it involves training various distinct models to find the best among them. In addition, selecting an optimum topology for the selected models is important too. The accurate forecasting of maximum temperature plays a vital role in human life as well as many sectors such as agriculture and industry. The increase in temperature will deteriorate the highland urban heat, especially in summer, and have a significant influence on people’s health. We applied meta-learning principles to optimize the deep learning network structure for hyperparameter optimization. In particular, the genetic algorithm (GA) for meta-learning was used to select the optimum architecture for the network used. The dataset was used to train and test three different models, namely the artificial neural network (ANN), recurrent neural network (RNN), and long short-term memory (LSTM). Our results demonstrate that the hybrid model of an LSTM network and GA outperforms other models for the long lead time forecasting. Specifically, LSTM forecasts have superiority over RNN and ANN for 15-day-ahead in summer with the root mean square error (RMSE) value of 2.719 (°C).
Evolution of NO3 reactivity during the oxidation of isoprene

Abstract. In a series of experiments in an atmospheric simulation chamber (SAPHIR,1 Forschungszentrum Jülich, Germany), NO3 reactivity (kNO3) resulting from the reaction of NO3 with isoprene and stable trace gases formed as products was measured directly using a flow tube reactor coupled to a cavity ring-down spectrometer (FT-CRDS). The experiments were carried out in both dry and humid air with variation of the initial mixing ratios of ozone (50–100 ppbv), isoprene (3–22 ppbv) and NO2 (5–30 ppbv). kNO3 was in excellent agreement with values calculated from the isoprene mixing ratio and the rate coefficient for the reaction of NO3 with isoprene. This result serves to confirm that the FT-CRDS returns accurate values of kNO3 even at elevated NO2 concentrations and to show that reactions of NO3 with stable reaction products like non-radical organic nitrates do not contribute significantly to NO3 reactivity during the oxidation of isoprene. A comparison of kNO3 with NO3 reactivities calculated from NO3 mixing ratios and NO3 production rates suggests that organic peroxy radicals and HO2 account for ∼50 % of NO3 losses. This contradicts predictions based on numerical simulations using the Master Chemical Mechanism (MCM version 3.3.1) unless the rate coefficient for reaction between NO3 and isoprene-derived RO2 is roughly doubled to ∼5×10-12 cm3 molecule−1 s−1.
mlgsim: a program for detecting clones using a simulation approach

Asexual reproduction and polyploidy are relatively rare in animals with chromosomal sex determination and always represent a derived condition. To accomplish asexual reproduction several changes in gene expression are required in the mechanism of oogenesis. Polyploidy increases the cell volume and also gives rise to alterations in general physiology. Nevertheless, there are asexual animals that not only survive but seem to be doing better than their sexual progenitors. This is expressed in the distribution pattern called geographical parthenogenesis. Using molecular phylogeny, I here examine the evolution of Otiorynchid weevils, mainly Otiorhynchus scaber and sulcatus in an attempt to trace the evolutionary history and find out what causes the variation in success of different parthenogens. I also evaluate the contribution of asexuality, hybridity and polyploidy as explanations behind geographical parthenogenesis in insects. I conclude that what is called O. scaber is, in fact, a set of geographical polyploids as polyploidy and not asexuality explains the difference in clonal success. I also argue that O. sulcatus is a recently formed clonal species of non-hybrid origin that may well be a good example of a true general purpose genotype. I find little support for asexuality or a hybrid origin as explanations behind geographical parthenogenesis in insects. Finally, I argue that polyploidy in all eukaryotes should be seen as an opportunity for the species evolution, not as a limitation that ensures the demise of the taxa.
AN EARLY PREDICTION AND DIAGNOSIS OF SEPSIS IN INTENSIVE CARE UNITS: AN UNSUPERVİSED MACHINE LEARNING MODEL

Sepsis infection, which is one of the most important causes of death in intensive care units, is seen as a severe global health crisis. If an early diagnosis of sepsis infection cannot be made, and treatment is not started rapidly, septic shock may result in multiple organ failure and death is almost inevitable. Therefore, it is vital to establish an early diagnosis and start the treatment at once. This study aims to accomplish a new model of unsupervised machine learning using lactate and Ph laboratory test values, which are considered to be important parameters to diagnose sepsis infection. The data used in the study have been obtained from MIMIC-III international clinical database. Unsupervised machine learning has been performed via the Fuzzy-C algorithm along with validity indexes like Xie Beni on patients’ data diagnosed sepsis and non-sepsis. The machine-generated ten labels at the end of the training session considering-designed validity indexes. The labelled cluster representatives have been reduced to two dimensions by Principal Component Analysis method in order to monitor the learning in a two-dimensional space. The study contributes to the literature by conducting unsupervised learning through two parameters (Lactate and Ph) and leading to multi-parameter studies. In addition, the study reports that there are five types of sepsis patterns in terms of Lactate and PH laboratory tests.
An Efficient Algorithm for Power Prediction in PV Generation System

Aiming at the existing photovoltaic power generation prediction methods, the modeling is complicated, the prediction accuracy is low, and it is difficult to meet the actual needs. Based on the improvement of the traditional wavelet neural network, a dual-mode cuckoo search wavelet neural network algorithm combined prediction method is proposed, which takes into account the extraction of chaotic features of surface solar radiation and photovoltaic output power. The proposed algorithm first reconstructs the chaotic phase space of the hidden information of each influencing factor in the data history of PV generation and according to the correlation analysis, the solar radiation is utilized as additional input. Next, the proposed algorithm overcomes the limitations of the cuckoo search algorithm such as the sensitivity to the initial value and searchability and convergence speed by dual-mode cuckoo search wavelet neural network algorithm. Lastly, a prediction model of the proposed algorithm is proposed and the prediction analysis is performed under different weather conditions. Simulation results show that the proposed algorithm shows better performance than the existing algorithms under different weather conditions. Under various weather conditions, the mean values of TIC, EMAE and ENRMSE error indicators of the proposed forecasting algorithm were reduced by 43.70%, 45.75%, and 45.41%, respectively. Compared with the Chaos-WNN prediction method, the prediction performance has been further improved under various weather conditions and the mean values of TIC, EMAE and ENRMSE error indicators have been reduced by 25.55%, 27.26%, and 36.83%, respectively. ©2020. CBIORE-IJRED. All rights reserved
Body Size and Consumer-Resource Dynamics

"Plausible" consumer-resource models, based on energetic reasoning and allometric empiricism, are formulated and their dynamics investigated. Most of the parameters in these models are determined by the body sizes and metabolic categories (endotherm, vertebrate ectotherm, invertebrate ectotherm, or plant) of the populations in question. The remaining parameters have clear biological meanings. The intent of these models is to provide maximum realism from minimum data when needed because of constraints of time or of resources for empirical research. The models also demonstrate the influence of physiological power and body size on consumer-resource dynamics. For a given metabolic type, we define ecological scope as the ratio of maximal ingestion rate to respiration rate. Invertebrate ectotherms have greater ecological scope than do vertebrate ectotherms, which have greater scope than do endotherms. Greater ecological scope implies ability to subsist on scarcer resources and a tendency to more stable dynamics. Changes in dynamics associated with increased resource carrying capacity K (the "paradox of enrichment") are investigated. Robust limit cycles (sustained oscillations) require a Type III functional response, but even in this case the cycles quickly "implode" (with respect to changes in K) to extremely small densities if the resource-consumer body mass ratio is too high. Estimates are given for resource-consumer body mass ratios that permit robust limit cycles, and some pertinent data are discussed. An analytic expression for the periods of limit cycles is derived. In terms of body mass, the periods scale as (consumer body mass)1/8 (resource body mass)1/8.
Immortalized Human Pituitary Cells Express Glycoproteinα -Subunit and Thyrotropin β (TSHβ)

A major problem in the study of human pituitary cells is their lack of proliferative capacity in vitro. To address this issue, we have infected normal human, postmortem pituitary cells in monolayer culture with a temperature-sensitive (tsA58) mutant of SV40 large T antigen. Several epithelial-like colonies were isolated; and one, designated CHP2, has been studied in detail to identify its functional characteristics. CHP2 cells have undergone more than 150 culture passages and retain an epithelial morphology. They exhibit tight temperature-dependent growth, in the presence and absence of serum, with cell division at 33 C and growth inhibition at 39 C. CHP2 cells, at both temperatures, showed diffuse immunostaining for humanα -subunit and focal staining for TSHβ. Gene expression was confirmed by RT-PCR and sequencing. TRH and GnRH receptors were not detectable, and their absence was confirmed by their lack of effects on intracellular calcium and inositol phospholipids. Cytogenetic analysis showed that the c.
Discontinuity Preserving Scheme

Non-linear schemes are widely used in high-speed flows to capture the discontinuities present in the solution. Limiters and weighted essentially non-oscillatory schemes (WENO) are the most common non-linear numerical schemes. Most of the high-resolution schemes use the piecewise parabolic reconstruction (PPR) technique for their robustness. However, it may be impossible to achieve non-oscillatory and dissipation-free solutions with the PPR technique without non-linear switches. Most of the shock-capturing schemes use excessive dissipation to suppress the oscillations present in the discontinuities. To eliminate these issues, an algorithm is proposed that uses the shock-capturing scheme (SCS) in the first step, and then the result is refined using a novel scheme called the Discontinuity Preserving Scheme (DPS). The present scheme is a hybrid shock capture-fitting scheme. The present scheme has outperformed other schemes considered in this work, in terms of shock resolution in linear and non-linear test cases. The most significant advantage of the present scheme is that it can resolve shocks with three grid points. KeywordsShock capturing scheme, WENO, High-resolution schemes, Conservative schemes, Finite volume method.
The moderating role of spiritual intelligence in the relationship between hexaco personality dimensions and students' academic stress

The moderating role of spiritual intelligence in the relationship between hexaco personality dimensions and students' academic stress Zohreh Hashemi, Sanaz Eyni, Ramin Tagavi هديكچ :هنيمز یگدینت صحت ی ل ی لوادتم رت ی ن فطاع تلاح ی ی ا نهذ ی شناد هک تسا صحت لوط رد نازومآ ی ل م هبرجت ار نآ دوخ ی دننک ،هنیمز نیا رد . یم یشقن هچ یونعم يوه و یتیصخش داعبا شناد یلیصحت یگدینت نازیم رد دناوت آ ؟دشاب هتشاد نازوم :فده ش تیمها هب هجوت اب تخان نییعت یاهریغتم ریث ت و هدننک شناد یلیصحت یگدینت رب راذگ لیدعت شقن یسررب فده اب رضاح شهوژپ ،نازومآ هدننک رد یونعم يوه ی شناد یلیصحت یگدینت و وکازگه یتیصخش داعبا نیب ةطبار تفرگ ماجنا نازومآ . :شور وژپ کی شهوژپ نیا ا یفاشتکا شه حرط عون ز یاه . دوب یگتسبمه شناد هیلک ار شهوژپ نیا یرامآ هعماج یلیصحت لاس رد لیبدرا ناتسرهش مود هطسوتم عطقم موس لاس نازومآ 18 11 لیکشت هعماج نیا زا . دنداد 241 هنومن هویش هب رفن هشوخ یفداصت یریگ دنچ یا هلحرم یا لماش شهوژپ یاهرازبا . دندش باختنا یس هها گدینت یلیصحت ی ( نآوه و گنآ ، 2116 ،نرتشا و یل( وکازگه یتیصخش ههایس ،) 2114 سایقم و ) یونعم يوه ( گنیک ، 2118 ندوب ) . د هداد هدافتسا اب اه زا نومزآ یگتسبمه نوسریپ و لیلحت هریغتمدنچ نویسرگر لیلحت و هیزجت یلیدعت ی . دش هتفاي :اه داد ناشن یلیدعت نویسرگر لیلحت جیاتن ک ه تقادص زج هب ،وکازگه یتیصخش داعبا همه نیب هطبار رد یونعم يوه نورب و عضاوت شناد یلیصحت یگدینت اب ،ییارگ آ شقن نازوم لیدعت ( دراد هدننک 110 / 1 > p شناد یلیصحت یگدینت و وکازگه یتیصخش داعبا نیب هطبار ،یونعم يوه شیازفا اب یترابع هب .) فیعض نازومآ رت یم . دوش هجيتن :یريگ شناد یلیصحت یگدینت و وکازگه یتیصخش داعبا نیب هطبار لیدعت اب یونعم يوه شهوژپ نیا جیاتن ساسارب نازومآ یم یگدینت عون نیا زورب زا دناوت . دهاکب یتیصخش داعبا دوجو رثا رب اه :اهديلك هژاو یصحت یگدینت ،وکازگه یتیصخش داعبا یونعم يوه ،یل