Miracle-dz/UniFAR-FTUs huggingface dataset:
Process optimization for the production of polygalacturonase from citrus wastes by Saccharomyces cerevisae

The current annual world production of citrus fruits is greater than 80 million tonnes Kuivanen et al. (2014), which leads to the generation of a huge amount of citrus processing wastes. As only a small part of these wastes is used in the nutrition of livestock or in solid fuel production Li et al. (2006), a large amount is left unutilised or underutilized. Utilization and valorization of citrus peels has been a subject of various investigations Karsheva et al. (2013), as citrus wastes can be used for the production of various value added materials including enzymes. The pectin content in citrus wastes is around 25% on a dry mass basis, corresponding to about 5% on a wet mass basis Pourbafrani et al. (2010). Pectolytic enzymes are involved in the degradation of pectin, a complex colloidal acidic polysaccharides that show a backbone of galacturonic acid residues with α-1,4-glycosidic linkages Yadav et al. (2009). Pectinases have extensive applications not only in the extraction, preparation and clarification of fruit juices and wine, but also wastewater treatment, paper manufacturing, oil extraction, coffee and tea fermentation, processing and degumming of many plant fibers Hoondal et al. (2002). Among the pectinases, poly-galagturonase (EC 3.2.1.15) hydrolyses the 1,4 α-D galacturonic acid linkages of pectin Sur et al. (2014). Abstract The production of polygalacturonase (PG ase) by an yeast strain, Saccharomyces cerevisae in submerged fermentation (SmF) of various citrus wastes was optimized. The effects of the fermentation parameters namely initial pH, temperature and cultivation time on enzyme production were studied using both pure pectin and citrus wastes as the sole carbon source at a time method. It was found that although dried citrus pulps did not show sufficient inducing activity, citrus peels were proved to be competent carbon source for extra cellular polygalacturonase production. Although pure pectin at a concentration of 0.5% (w/v) was found to be most effective for enzyme production, higher concentration of lemon peel was proved to be better than pure substrate. The optimum pH for enzyme production was found to depend on the type of carbon source used as for orange peel, pure pectin and lemon peel supplemented cultures, the preferred pH s were 4, 6 and 7 respectively. Highest production was achieved at a temperature of 27°C. The enzyme production kinetics indicated that the strain took a longer time (5 days) to hydrolyse waste pectins for enzyme production than the pure substrate (3 days).
Computerized fluoroscopy with zero-dose image updates for minimally invasive femoral diaphyseal fracture reduction

In this paper, a computerized fluoroscopy with zero-dose image updates for femoral diaphyseal fracture reduction is proposed. It is achieved with a two-step procedure. Starting from a few (normally 2) calibrated fluoroscopic image, the first step, data preparation, automatically estimates the size and the pose of the diaphyseal fragments through three-dimensional morphable object fitting using a parametric cylinder model. The projection boundary of each estimated cylinder, a quadrilateral, is then fed to a region information based active contour model to extract the fragment contours from the input fluoroscopic images. After that, each point on the contour is interpolated relative to the four vertices of the corresponding quadrilateral, which resulted in four interpolation coefficients per point. The second step, image updates, repositions the fragment projection on each acquired image during bony manipulation using a computerized method. It starts with interpolation of the new position of each point on the fragment contour using the interpolation coefficients calculated in the first step and the new position of the corresponding quadrilateral. The position of the quadrilateral is updated in real time according to the positional changes of the associated bone fragments, as determined by the navigation system during fracture reduction. The newly calculated image coordinates of the fragment contour are then fed to a OpenGL® based texture warping pipeline to achieve a real-time image updates. The presented method provides a realistic augmented reality for the surgeon. Its application may result in great reduction of the X-ray radiation to the patient and to the surgical team.
Survey and Taxonomy of Transmissions Power Control Mechanisms for Wireless Body Area Networks

Wireless body area networks (WBANs) comprise several sensor nodes equipped with a short range radio-frequency transceiver, implanted and/or attached to the human body. Their low form-factor and localization imply less resources available and limited energy capabilities. Therefore, energy efficiency of WBANs is a critical issue since, in many cases, batteries cannot be replaced or recharged, requiring mechanisms to extend their life-time. The aim of transmission power control (TPC) mechanisms, which can be combined with other energy-saving mechanisms, is to reduce the energy consumption, external interferences, and specific-observation-rate in wireless communications by dynamically adjusting the transmission power output of data transmission, with the minimum effect on other performance aspects, such as reliability and latency. This paper describes and analyzes the TPCs developed as a result of a synergy created by two mechanisms, a link quality estimator and the transmission power level control. Design choices, in terms of the solutions devised to each mechanism, as well as, the strategy adopted to combine them in a TPC, are highlighted. A comparison between the newest and the most relevant research works in this area is provided as a guideline to future research. A taxonomy to classify the different TPC mechanisms developed is proposed.
Efficient Sorting: A More Powerful Test for Cross-Sectional Anomalies

Many researchers seek factors that predict the cross-section of stock returns. The standard methodology sorts stocks according to their factor scores into quantiles and forms a corresponding long-short portfolio. Such a course of action ignores any information on the covariance matrix of stock returns. Historically, it has been difficult to estimate the covariance matrix for a large universe of stocks. We demonstrate that using the recent DCC-NL estimator of Engle et al. (2017) substantially enhances the power of tests for cross-sectional anomalies: On average, 'Student' t-statistics more than double.
Do Humans Really Prefer Semi-open Natural Landscapes? A Cross-Cultural Reappraisal

There is an assumption in current landscape preference theory of universal consensus in human preferences for moderate to high openness in a natural landscape. This premise is largely based on empirical studies of urban Western populations. Here we examine for the first time landscape preference across a number of geographically, ecologically and culturally diverse indigenous populations. Included in the study were two urban Western samples of university students (from southern Sweden) and five non-Western, indigenous and primarily rural communities: Jahai (Malay Peninsula), Lokono (Suriname), Makalero (Timor), Makasae (Timor), and Wayuu (Colombia). Preference judgements were obtained using pairwise forced choice assessments of digital visualizations of a natural landscape varied systematically on three different levels of topography and vegetation density. The results show differences between the Western and non-Western samples, with interaction effects between topography and vegetation being present for the two Swedish student samples but not for the other five samples. The theoretical claim of human preferences for half-open landscapes was only significantly confirmed for the student sample comprising landscape architects. The five non Western indigenous groups all preferred the highest level of vegetation density. Results show there are internal similarities between the two Western samples on the one hand, and between the five non-Western samples on the other. To some extent this supports the idea of consensus in preference, not universally but within those categories respectively.
Activation of Dorsomedial Hypothalamic Neurons Promotes Physical Activity and Decreases Food Intake and Body Weight in Zucker Fatty Rats

Previous reports have shown that running wheel activity or voluntary exercise prevents hyperphagia and obesity in various animal models of obesity, but such effects seem only minimal in obese animals lacking leptin or leptin receptors. The mechanisms underlying this ineffectiveness remain unclear. Here, we identified the action of neuronal activation in the dorsomedial hypothalamus (DMH) in modulating physical activity, food intake and body weight using leptin receptor mutant obese Zucker (Lepr(fa), ZF) and Koletsky (Lepr(fak), SHROB) rats. Ad lib-fed SHROB rats with locked running wheels became hyperphagic and gained body weight rapidly. These alterations were not ameliorated in ad lib-fed SHROB rats with voluntary access to running wheels, but the body weight of SHROB rats with running wheel access was significantly decreased when they were pair-fed to the amounts consumed by lean controls. Determinations of hypothalamic gene expression revealed that sedentary ad lib-fed SHROB rats had increased expression of neuropeptide Y (Npy) and decreased expression of pro-opiomelanocortin (Pomc) in the arcuate nucleus (ARC). Both ARC Npy and Pomc expression were further altered under running and pair-fed conditions, indicating that both genes are appropriately regulated in response to increased energy demands or alterations caused by running activity and food restriction. Strikingly, c-Fos immunohistochemistry revealed that while voluntary running activity elevated the number of c-Fos positive cells in the DMH (particularly in the ventral and caudal subregions) of intact rats, such activation was not observed in ZF rats. Using adeno-associated virus (AAV)-mediated expression of the designer receptors hM3D(Gq) in the ventral and caudal DMH of ZF rats, we found that chemogenetic stimulation of neurons in these DMH subregions via injection of the designer drug clozapine N-oxide (CNO) significantly increased their running activity and reduced their food intake and body weight. Together, these results demonstrate that activation of ventral and caudal DMH neurons promotes physical activity and decreases food intake and body weight and suggest that intact DMH neural signaling is likely crucial for exercise-induced reductions of food intake and body weight in obese rats lacking leptin receptors.
Analysing symbolic regression benchmarks under a meta-learning approach

The definition of a concise and effective testbed for Genetic Programming (GP) is a recurrent matter in the research community. This paper takes a new step in this direction, proposing a different approach to measure the quality of the symbolic regression benchmarks quantitatively. The proposed approach is based on meta-learning and uses a set of dataset meta-features---such as the number of examples or output skewness---to describe the datasets. Our idea is to correlate these meta-features with the errors obtained by a GP method. These meta-features define a space of benchmarks that should, ideally have datasets (points) covering different regions of the space. An initial analysis of 63 datasets showed that current benchmarks are concentrated in a small region of this benchmark space. We also found out that number of instances and output skewness are the most relevant meta-features to GP output error. Both conclusions can help define which datasets should compose an effective testbed for symbolic regression methods.
A regularized deep learning approach for image de-blurring

In this paper, a novel convolutional neural network model for blind deconvolution of images is proposed. The structure of the model is based on two sub models devoted, respectively, to deblurring and denoising of an input image. The model has been designed to restore a picture affected by different kinds of noise. The main innovation is the introduction of a regularization term in the training cost function, based on a blurred/non-blurred classification tool. Results show interesting features of the model, particularly regarding the robustness of results. The comparison with other state-of-the-art models confirms the value of the model proposed in this study.
COMPARISON OF KETOROLAC VERSUS DICLOFENAC AS TREATMENT FOR ACUTE RENAL COLIC: A SYSTEMATIC REVIEW AND A NETWORK META-ANALYSIS (DIRECT AND INDIRECT COMPARISON)

Acute renal colic is one of the most frequent urologic visits in Emergency Department (ED), and early management should focus on early relief of pain. Non-steroidal anti-inflammatory drugs (NSAIDs), opiates, or combination of both are often used to treat this condition. Diclofenac is stated in European Association of Urology (EAU) guideline as first line treatment. Interestingly, it is ketorolac that currently the most common analgesics used in most EDs. A meta-analysis study was designed to investigate whether ketorolac or diclofenac is a better NSAID for early pain relief in acute renal colic patients. Relevant studies were obtained from PubMed, Science Direct, Cochrane, EBSCO, and Proquest. Based on current studies, both ketorolac and diclofenac are found superior than pethidine, while both providing a comparable pain relief with diclofenac regarded as a safer option. Further prospective data is needed in Indonesian clinical settings for its assurance in efficacy and safety
Exploring Students’ Engagement Patterns in SPOC Forums and their Association with Course Performance

With the popularity of Small Private Online Courses (SPOCs) in higher education, a plentiful of discussion data has been increasingly generated in SPOC forums. With 752 undergraduates’ discussion posts, this study aims to investigate students’ engagement patterns within SPOC forums in terms of engagement behaviors and emotions. Firstly, we designed a behavioral code rule to identify posting- and content-level behaviors, and examined their association with course performance. Secondly, we built an emotion lexicon including positivity, negativity and confusion word sets, and adopted an emotion calculation approach to visualize emotional evolutionary trends and to examine emotional differences in registration types and course performance. The results show that, (1) the high-performing group was more active in the most engagement behaviors except for interactive postings. (2) The registered group delivered more threads and wrote richer vocabulary in post content. (3) Whether students were registered for a course or not did not have a significant effect on their emotional expressions, but the registered group exhibited more confusion in forum interactions at the end of the semester. (4) Positive emotion was prevailing for the entire population. Furthermore, compared with the low-achieving group, the high-performing group had higher emotion densities in three types of emotions.
The Impact of Pathologic Upgrading of Gleason Score 7 Prostate Cancer on the Risk of the Biochemical Recurrence after Radical Prostatectomy

Objective To investigate the impact of pathologic upgrading of Gleason score (GS) 7 prostate cancer on the risk of the biochemical recurrence. Materials and Methods A total of 1678 patients with postoperative GS 7 prostate cancer without lymph node metastasis were reviewed retrospectively. The patients were categorized into four groups depending on pathologic upgrading: upgraded GS 3+4, nonupgraded GS 3+4, upgraded GS 4+3, and nonupgraded GS 4+3. Kaplan-Meier multivariate model was created. Results The mean age was significantly higher in the nonupgraded GS 4+3 group than in other groups, whereas the mean prostate-specific antigen (PSA) level was lower in the upgraded GS 3+4 group. Pathologic findings, such as extracapsular extension, seminal vesical invasion, and the surgical margin rate, were different from each other. Five-year biochemical recurrence-free survival rate was 85%, 73%, 69%, and 60% in upgraded GS 3+4, nonupgraded GS 3+4, upgraded GS 4+3, and nonupgraded GS 4+3 group, respectively. There was significant difference between the nonupgraded 4+3 and upgraded 4+3 group, as well as between upgraded 3+4 and nonupgraded 3+4 group. However, the two middle patient groups, that is, the nonupgraded GS 3+4 group and the upgraded GS 4+3 group, did not show the statistical difference (Log-rank test, p value = 0.259). Conclusion The information on pathologic upgrading in the biopsy reports of patients could help to provide more detailed analysis for the biochemical recurrence of GS 7 prostate cancer.
An association between diet quality index for Koreans (DQI-K) and total mortality in Health Examinees Gem (HEXA-G) study

BACKGROUND/OBJECTIVES Diet quality scores or indices, based on dietary guidelines, are used to summarize dietary intake into a single numeric variable. The aim of this study was to examine the association between the modified diet quality index for Koreans (DQI-K) and mortality among Health Examinees-Gem (HEXA-G) study participants. SUBJECTS/METHODS The DQI-K was modified from the original diet quality index. A total of 134,547 participants (45,207 men and 89,340 women) from the HEXA-G study (2004 and 2013) were included. The DQI-K is based on eight components: 1) daily protein intake, 2) percent of energy from fat, 3) percent of energy from saturated fat, 4) daily cholesterol intake, 5) daily whole-grain intake, 6) daily fruit intake, 7) daily vegetable intake, and 8) daily sodium intake. The association between all-cause mortality and the DQI-K was examined using Cox proportional hazard regression models. Hazard ratios and confidence intervals were estimated after adjusting for age, gender, income, smoking status, alcohol drinking, body mass index, and total energy intake. RESULTS The total DQI-K score was calculated by summing the scores of the eight components (range 0–9). In the multivariable adjusted models, with good diet quality (score 0–4) as a reference, poor diet quality (score 5–9) was associated with an increased risk of all-cause mortality (hazard ratios = 1.23, 95% confidence intervals = 1.06–1.43). Moreover, a one-unit increase in DQI-K score resulted in a 6% higher mortality risk. CONCLUSIONS A poor diet quality DQI-K score was associated with an increased risk of mortality. The DQI-K in the present study may be used to assess the diet quality of Korean adults.
Identification of candidate genes involved in atherosclerotic cardovascular disease : a systems biology appproach

Gene expression profiles and mass-spectrometry analysis of a plaque have revealed genes and proteins involved in an atherosclerotic plaque progression. Though differentially expressed genes in an atherosclerotic plaque progression have been identified previously, this is the first study that has combined gene expression data with proteins identified from different stages of plaque progression to identify pathways and candidate genes affecting state of a plaque using a network approach. We constructed an unstable plaque network with 59 genes of which 9 were transcription factors, 10 genes were over expressed and 12 genes were under expressed. Of all genes and proteins found to be associated with a plaque progression, we further identified and prioritized candidate genes which could be potential biomarker or drug targets to prevent progression of a plaque. In this study we also show that just differential expression of genes does not identify genes which are associated with the disease state but not differentially expressed.
Predicting Interactions between Virus and Host Proteins Using Repeat Patterns and Composition of Amino Acids

Previous methods for predicting protein-protein interactions (PPIs) were mainly focused on PPIs within a single species, but PPIs across different species have recently emerged as an important issue in some areas such as viral infection. The primary focus of this study is to predict PPIs between virus and its targeted host, which are involved in viral infection. We developed a general method that predicts interactions between virus and host proteins using the repeat patterns and composition of amino acids. In independent testing of the method with PPIs of new viruses and hosts, it showed a high performance comparable to the best performance of other methods for single virus-host PPIs. In comparison of our method with others using same datasets, our method outperformed the others. The repeat patterns and composition of amino acids are simple, yet powerful features for predicting virus-host PPIs. The method developed in this study will help in finding new virus-host PPIs for which little information is available.
Designing deep neural networks to automate segmentation for serial block-face electron microscopy

Today, serial block-face scanning electron microscopy (SBF-SEM) is capable of producing teravoxel-scale 3D images of biological structures at nanometer-scale resolutions. Image segmentation is fundamental to data analysis workflows in biological electron microscopy (EM), but SBF-SEM datasets can greatly exceed the manual segmentation capacity of a laboratory. Fast automated segmentation algorithms would alleviate this problem, but practical solutions remain unavailable for many biological problems of interest. Segmentation algorithms using deep neural networks have recently demonstrated significant performance gains, but designing high-performing networks that effectively solve targeted problems remains challenging. We are developing genenet, a Python package to rapidly discover, train, and deploy high-performing neural network architectures for SBF-SEM segmentation with little user intervention. Here, we demonstrate how to use genenet to train an ensemble of segmentation networks for a human platelet tissue sample. Initial results indicate this approach is viable for accelerating the segmentation process.
In vivo aerobic metabolism of the rainbow trout gut and the effects of an acute temperature increase and stress event

ABSTRACT The fish gut is responsible for numerous potentially energetically costly processes, yet little is known about its metabolism. Here, we provide the first in vivo measurements of aerobic metabolism of the gut in a teleost fish by measuring gut blood flow, as well as arterial and portal venous oxygen content. At 10°C, gut oxygen uptake rate was 4.3±0.5 ml O2 h−1 kg−1 (∼11% of whole-animal oxygen uptake). Following acute warming to 15°C, gut blood flow increased ∼3.4-fold and gut oxygen uptake rate increased ∼3.7-fold (16.0±3.3 ml O2 h−1 kg−1), now representing ∼25% of whole-animal oxygen uptake. Although gut blood flow decreased following an acute stress event at 15°C, gut oxygen uptake remained unchanged as a result of a ∼2-fold increase in oxygen extraction. The high metabolic thermal sensitivity of the gut could have important implications for the overall aerobic capacity and performance of fish in a warming world and warrants further investigation. Summary: In vivo recordings of gut oxygen uptake in a teleost fish demonstrate a high metabolic sensitivity to an acute temperature increase, as well as the metabolic responses to stress.
870 μm continuum observations of the bubble-shaped nebula Gum 31

Fil: Duronea, Nicolas Urbano. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico La Plata. Instituto Argentino de Radioastronomia (i); Argentina. Universidad Nacional de la Plata. Facultad de Ciencias Astronomicas y Geofisicas; Argentina