Miracle-dz/UniFAR-FTUs huggingface dataset:
A Blueberry-Enriched Diet Attenuates Nephropathy in a Rat Model of Hypertension via Reduction in Oxidative Stress

Objective and Background To assess renoprotective effects of a blueberry-enriched diet in a rat model of hypertension. Oxidative stress (OS) appears to be involved in the development of hypertension and related renal injury. Pharmacological antioxidants can attenuate hypertension and hypertension-induced renal injury; however, attention has shifted recently to the therapeutic potential of natural products as antioxidants. Blueberries (BB) have among the highest antioxidant capacities of fruits and vegetables. Methods and Results Male spontaneously hypertensive rats received a BB-enriched diet (2% w/w) or an isocaloric control diet for 6 or 12 weeks or 2 days. Compared to controls, rats fed BB-enriched diet for 6 or 12 weeks exhibited lower blood pressure, improved glomerular filtration rate, and decreased renovascular resistance. As measured by electron paramagnetic resonance spectroscopy, significant decreases in total reactive oxygen species (ROS), peroxynitrite, and superoxide production rates were observed in kidney tissues in rats on long-term dietary treatment, consistent with reduced pathology and improved function. Additionally, measures of antioxidant status improved; specifically, renal glutathione and catalase activities increased markedly. Contrasted to these observations indicating reduced OS in the BB group after long-term feeding, similar measurements made in rats fed the same diet for only 2 days yielded evidence of increased OS; specifically, significant increases in total ROS, peroxynitrite, and superoxide production rates in all tissues (kidney, brain, and liver) assayed in BB-fed rats. These results were evidence of “hormesis” during brief exposure, which dissipated with time as indicated by enhanced levels of catalase in heart and liver of BB group. Conclusion Long-term feeding of BB-enriched diet lowered blood pressure, preserved renal hemodynamics, and improved redox status in kidneys of hypertensive rats and concomitantly demonstrated the potential to delay or attenuate development of hypertension-induced renal injury, and these effects appear to be mediated by a short-term hormetic response.
Study on Substrate Specificity at Subsites for Severe Acute Respiratory Syndrome Coronavirus 3CL Protease

Abstract Autocleavage assay and peptide‐based cleavage assay were used to study the substrate specificity of 3CL protease from the severe acute respiratory syndrome coronavirus. It was found that the recognition between the enzyme and its substrates involved many positions in the substrate, at least including residues from P4 to P2′. The deletion of either P4 or P2′ residue in the substrate would decrease its cleavage efficiency dramatically. In contrast to the previous suggestion that only small residues in substrate could be accommodated to the S1′ subsite, we have found that bulky residues such as Tyr and Trp were also acceptable. In addition, based on both peptide‐based assay and autocleavage assay, Ile at the P1′ position could not be hydrolyzed, but the mutant L27A could hydrolyze the Ile peptide fragment. It suggested that there was a stereo hindrance between the S1′ subsite and the side chain of Ile in the substrate. All 20 amino acids except Pro could be the residue at the P2′ position in the substrate, but the cleavage efficiencies were clearly different. The specificity information of the enzyme is helpful for potent anti‐virus inhibitor design and useful for other coronavirus studies. Edited by Ming‐Hua XU
Choice modelling and laboratory experiments for non-market valuation: A framework

The willingness to pay (WTP)/willingness to accept (WTA) disparity raises serious questions about preference elicitation techniques based on the Hicksian model of decision-making. In this paper we investigate the possibility of incorporating the strategies suggested by Plott and Zeiler (2005) in a Pivot Process mechanism and in a Choice Modelling experiment to eliminate the WTP/WTA disparity. The goal is to improve the reliability of the benefit estimates by comparing and contrasting these two methodologies. No methodological and analytical obstacles prevent the use the Pivot Process to calibrate the Choice Modelling estimates. By combining the two methods, a calibration procedure can be usefully developed to validate good hypothetical surveys and correct bad ones.
A domain specific language for execution profiling & regulation

Profiling consists of three stages: the collection of performance data, the processing of that data to infer performance information and the feedback of this performance information into the system. Feedback refers to using the information to change either the runtime system or the sampling parameters for subsequent profiling runs. This paper will concentrate on the latter approach for feedback. The majority of existing profiling tools focus on data collection, requiring manual intervention during processing and feedback. The developer must interpret the results presented to them to identify new profiling strategies. We introduce the concept of profiling regulation, whereby the processes of collection, processing and feedback are automated. We define a domain specific language, sampspec, that provides expressibility and control over the profiling process. The developer provides a declarative specification of the information to collect, the computations to perform and the strategies to employ based on this information. This is in contrast to the manual inspection of results and restarting the profiler. Thus, the profiling process becomes one of specification of strategies for data collection and processing, and how these strategies can adapt over time. In this paper, we describe the system model and illustrate our language through a series of worked examples.
Causes and Remedies to Low Academic Performance of Students in Public Secondary Schools: A Study of Ijero Local Government Area of Ekiti State

The purpose of this study was to find out the causes and remedies to low academic performance of students in public secondary schools in Ijero Local Government area of Ekiti State. The study adopted a survey research design. It was guided by two research questions. The population of the study consisted of 366 students of secondary schools in Ijero Local government out of which 122 were randomly selected. The instrument was validated by three experts. Findings revealed that there are various factors that contribute to low academic performance of students in secondary schools. Based on the finding recommendations were made among which are: teachers should make use of recent and relevant teaching materials to ensure better understanding and performance of students, teachers should employ different teaching methods as well as teaching must be from simple to complex and parents should give more attention and proper monitoring to their children education. Keywords : Teachers, Parents, Academic Performance, Classroom Practices.
[11C]flumazenil kinetics in the rat brain: model preference and the impact of non-specific and non-selective binding in reference region modeling

Aim: The analysis of [11C]flumazenil pre-clinical studies currently follows the quantitative models validated in the clinical setting. Since tracer kinetics can differ between species, [11C]flumazenil kinetic modeling was evaluated for the rat brain. Material and Methods: 60min [11C]flumazenil brain PET scans with arterial sampling were performed in two groups of male Wistar rats (n=10, tracer dose only; n=2, pre-saturated with 330nM of flumazenil). Time-activity curves (TACs) were generated for frontal cortex, hippocampus, cerebellum, medulla and pons (reference). Next, noiseless TACs (n=10) were simulated using an average input function and representative rate constants from animal data. A three-tissue compartment model including a compartment for non-selective binding was simulated with different levels of specific-binding (k3 ranging from 0.2 to 2.6min-1). For animal and simulated data, distribution volume (VT) and distribution volume ratios (DVR) were calculated using one and two-tissue compartment models (1TCM and 2TCM) and spectral analysis (SA). Binding potential (BPND) was determined from full and simplified reference tissue models with one or two-tissue compartments for the reference (FRTM, SRTM and SRTM-2Ref). Parameter agreement was assessed by Spearman’s correlation and Bland-Altman plots. Akaike information criterion (AIC) was used to determine model preference. Results: 1TCM and 2TCM VT of regions with high specific-binding (frontal cortex, hippocampus and cerebellum) showed similar AIC (143±7 and 148±10 respectively), strong correlation (rs=0.99) and good agreement (0.1% difference). In contrast, low specific-binding regions (pons and medulla) showed worse correlation (rs=0.77) and agreement (17.6% difference), while AIC were lower for 2TCM (134±10) than for 1TCM (161±8). The pre-saturated group displayed similar results to those of low specific-binding regions. High levels of non-specific and/or non-selective binding (2TCM VT=2.5±0.4) was observed in pons and affected BPND estimation by all tested reference tissue models. Simulations showed a similar pattern: 2TCM VT demonstrated better agreement (<8.0% bias) than 1TCM for all levels of specific-binding, while 1TCM VT demonstrated smaller bias with increasing specific-binding (from -55.1% to 3.1%). SA generated accurate VT (<0.9% bias) for all specific-binding levels. 1TCM DVRs resulted in the largest BPND overestimation (up to 58% bias), while SRTM-2Ref showed an overall smaller bias (<1.5%). Conclusion: [11C]flumazenil kinetics in rats was substantially different from that in humans, especially in low specific-binding regions. In those, the 2TCM is preferred and the standard 1TCM and SRTM can lead to major errors in parameter estimation. Instead, models which can better account for non-specific and/or non-selective binding should be used, such as 2TCM or SA.
Adaptive Reduced-Rank Estimation of Nonstationary Time-Variant Channels Using Subspace Selection

In this paper, we focus on adaptive time-variant channel estimation for vehicle-to-vehicle (V2V) communications in intelligent transportation systems (ITS) using the IEEE 802.11p physical layer. The IEEE 802.11p pilot pattern is identical to that in the well-known IEEE 802.11a/g (WiFi) standard, which was initially designed for indoor environments with little or no mobility. However, in a V2V drive-by situation, the channel impulse response rapidly changes due to the high relative velocity between transmitter and receiver, as well as the changes in the scattering environment. Hence, for such V2V channels, advanced decision directed channel estimation methods are needed to reach a frame error rate (FER) smaller than 10-1 . Even more importantly, the channels are nonstationary, which implies that the Doppler power spectral density (DSD) and the power delay profile (PDP) change on a timescale comparable with the frame length, which complicates the estimator design. In this paper, we develop an adaptation method for the channel estimation filter that is suitable for the following: 1) the short frame length in IEEE 802.11p; 2) the given pilot structure; and 3) the requirement of only a single received short frame for filter adaptation. We define a set of hypotheses on the support of the DSD and a second set of hypotheses on the support of the PDP. Each hypothesis is represented by a specific subspace spanned by orthogonal basis vectors. For basis vector calculation, we develop a numerically stable algorithm utilizing generalized discrete prolate spheroidal sequences. The adaptation algorithm chooses a hypothesis from both sets such that a probabilistic bound on the channel estimation error is minimized. We implement the hypothesis test by means of a novel subspace selection algorithm that allows utilizing correlated observations of a time- and frequency-selective (2-D) fading process. We validate the adaptive channel estimation scheme in an IEEE 802.11p compliant link level simulation for a relative velocity range from 0 to 111 m/s ≈ 400 km/h ≈ 249 mi/h. Adaptive filtering enables an up to fourfold reduction in the number of required iterations to reach an FER below 10-1 for an Eb/N0 = 12 dB.
Fatal hyperpyrexia following the use of pancuronium bromide in the pig.

Atropine (0.04 mg/kg) was given half an hour before the operation by intramuscular injection. Anaesthesia was induced using 10 per cent halothane in an oxygen and nitrous oxide mixture (4 l./min of each) via a Magill circuit, using a Hall dog mask. After intubation, pancuronium bromide (0.13 mg/kg) was given by intravenous injection and anaesthesia was maintained with a mechanical ventilator using oxygen 3 l. /min, nitrous oxide 5 l. /min and occasional additions of 0.5 per cent halothane. The apparatus was adjusted to give a tidal volume of 450-500 ml at a ventilation rate of 18-20/min. The same dose of pancuronium bromide was repeated after 10 min and subsequently half the quantity administered at 10-15 min intervals during dissection of the liver. Little pancuronium was required during the anhepatic phase of the transplant operation.
Genetics-Based Machine Learning for Rule Induction : Taxonomy , Experimental Study and State of the Art

The classification problem can be addressed by numerous techniques and algorithms, which belong to different paradigms of Machine Learning. In this work, we are interested in evolutionary algorithms, the so-called Genetics-Based Machine Learning algorithms. In particular, we will focus on evolutionary approaches that evolve a set of rules, i.e., evolutionary rule-based systems, applied to classification tasks, in order to provide a stateof-the-art in this field. This study has been done with a double aim: to present a taxonomy of the Genetics-Based Machine Learning approaches for rule induction, and to develop an empirical analysis both for standard classification and for classification with imbalanced data sets. We also include a comparative study of the GBML methods with some classical non-evolutionary algorithms, in order to observe the suitability and high power of the search performed by evolutionary algorithms and the behaviour for the GBML algorithms in contrast to the classical approaches, in terms of classification accuracy.
Fast Overlapping Group Lasso

The group Lasso is an extension of the Lasso for feature selection on (predefined) non-overlapping groups of features. The non-overlapping group structure limits its applicability in practice. There have been several recent attempts to study a more general formulation, where groups of features are given, potentially with overlaps between the groups. The resulting optimization is, however, much more challenging to solve due to the group overlaps. In this paper, we consider the efficientoptimization of the overlapping group Lasso penalized problem. We reveal several key properties of the proximal operator associated with the overlapping group Lasso, and compute the proximal operator by solving the smooth and convex dual problem, which allows the use of the gradient descent type of algorithms for the optimization. We have performed empirical evaluations using the breast cancer gene expression data set, which consists of 8,141 genes organized into (overlapping) gene sets. Experimental results demonstrate the efficiency and effectiveness of the proposed algorithm.
Concatenated Convolutional Codes for Deep Space Mission

In satellite communication deep space mission are the most challenging mission, where system has to work at very low Eb/No. Concatenated codes are the ideal choice for such deep space mission. ISRO is planning to send unmanned mission for Mars and several deep space missions in future to study and detailed understanding of our own universe. This paper basically reviews the concatenated convolutional code structure and selects the suitable candidate for our future deep space mission. The complete simulation using Simulink is done and results are presented in this paper.
G-FREE COLORABILITY AND THE BOOLEAN PRIME IDEAL THEOREM

We show that the compactness of G-free k-colorability is equivalent to the Boolean prime ideal theorem for any graph G with more than two vertices and any k ≥ 2. 1 Introduction In 1951, de Bruijn and Erdos (4) proved that a graph is k-colorable if every finite subgraph is k-colorable. We shall refer to this statement as Pk. In 1961, Mycielski (14) asked about the strength of Pk as a set theory axiom, pointing out that it follows from BPI, the prime ideal theorem for Boolean algebras. Ten years later, in 1971, Lauchli (13) showed that Pk is in fact one of the equivalent forms of BPI, even for fixed k, k ≥ 3. (P2 is much weaker.) BPI is weaker than the Axiom of Choice or AC((10)), but like AC has a large number of equivalent formulations and can often be substituted for AC in mathematical proofs (see (11)). Many other graph coloring notions for both vertices and edges have been introduced in the last 30 years, leading Borowiecki and Mihok (3) to formulate their notion of generalized colorings. In a recent paper (8), we have shown that several of these colorings lead to compactness theorems which are also equivalent to BPI. In this paper, we continue this work by showing the very general notion of G-free k-colorability, introduced by Achlioptas (1) has a compactness theorem which is equivalent to BPI for any graph G with more than two vertices and any k ≥ 2. (A graph is G-free k-colorable if its vertex set can be partitioned into k classes, each of which induces a a graph which does not contain G.) Thus we see that the result of Lauchli is far from unique; in fact it seems that almost any vertex coloring compactness theorem is equivalent to BPI. The inspiration for this work is the paper of Achlioptas (1), in which it is proved that G-free k-colorability is NP-Complete for any graph G with more than two vertices and any k ≥ 2. We have noticed this connection between NP-Completeness and BPI before ((6), (7), ((8)), and it remains a fruitful source of new results.
Anti-diarrhoeal and CNS Depressant Activity of Methanolic Extract of Saccharum spontaneum Linn.

Preliminary phytochemical screening of the methanolic extract of the whole plant of Saccharum spontaneum Linn. (FamilyGramineae) revealed the presence of alkaloids, flavonoids, reducing sugar, tannins and saponins. The antidiarrhoeal activity of the extract (200 and 400 mg/kg) was assessed on experimental animal and a dose dependent decrease in the total number of faecal dropping was obsereved in castor oil induced diarrhoea in mice. The plant extract was also assessed for effect on the central nervous system (CNS) using a number of neuropharmacological experimental models in mice. The extract produced a dosedependent reduction of the onset and duration of pentobarbitone-induced hypnosis, reduction of locomotor and exploratory activities in the open field and hole cross tests. These results suggest that the extract possesses antidiarrhoeal and CNS depressant activity.
Drying Peanuts with Intermittent Airflow

ABSTRACT PEANUTS at different initial moistures were dried by periodically interrupting airflow for 15, 30, or 45 min/h, or for 1 h in 4, as a method for conserving energy. Two airflow rates (12.5 and 25 m3 of air/min/m3 of peanuts) were used in the dryers. Solar-heated water or liquified petroleum gas (LPG) was used to heat the dry-ing air. Results indicate that interruptions of 15 min/h at the low airflow rate did not significantly affect drying time and reduced heat-energy consumption by 10 per-cent. Longer periods of interruption decreased heat-energy use but increased drying time. Treatments with high airflow rates showed results similar to those for the low airflow rates. High airflow increased heat-energy use by 20 percent. Moisture was more uniform at the high airflow rate than at the low airflow rate. No differences were noted in milling quality among the treatments. No differences were noted in drying time, heat-energy use or milling quality between dryers using LPG and solar energy.
Disparities in Risk Factors Associated with Obesity between Zanzibar and Tanzania Mainland among Women of Reproductive Age Based on the 2010 TDHS

The occurrence of overweight and obesity has serious health implications. The 2010 Tanzania Demographic and Health Survey data set was reanalysed to compare the prevalences of overweight and obesity between Mainland Tanzania and Zanzibar and to determine how demographic factors can predict overweight and obesity across the United Republic of Tanzania. About 7.92% of the Tanzanian women of reproductive age were obese, 15% were overweight, and 11.5% were underweight. Women from Mainland Tanzania (6.56%) were significantly less likely (AOR = 0.66, 95% CI: 0.53–0.82) to be affected by obesity as compared to women from Zanzibar (12.19%). The common predictors of obesity in Mainland Tanzania and Zanzibar were wealth index, marital status, and age. Whereas the place of residence and education level emerged as predictors of obesity in the Mainland Tanzania alone, the number of meals per day did so in Zanzibar. Most importantly, Zanzibar had a greater prevalence of obesity compared to Mainland Tanzania.
Facial micro-expressions recognition using high speed camera and 3D-gradient descriptor

Facial micro-expressions were proven to be an important behaviour source for hostile intent and danger demeanour detection. In this paper, we present a novel approach for facial micro-expressions recognition in video sequences. First, 200 frame per second (fps) high speed camera is used to capture the face. Second, the face is divided to specific regions, then the motion in each region is recognized based on 3D-Gradients orientation histogram descriptor. For testing this approach, we create a new dataset of facial micro-expressions, that was manually tagged as a ground truth, using a high speed camera. In this work, we present recognition results of 13 different micro-expressions. (6 pages)
The value of the MDR 1 reversal agent PSC-833 in addition to daunorubicin and cytarabine in the treatment of elderly patients with previously untreated acute myeloid leukemia ( AML ) , in relation to MDR 1 status at diagnosis

Bronno van der Holt, Bob Löwenberg, Alan K. Burnett, Wolfgang U. Knauf, John Shepherd, Pier Paolo Piccaluga, Gert J. Ossenkoppele, Gregor E. G. Verhoef, Augustin Ferrant, Michael Crump, Dominik Selleslag, Matthias Theobald, Martin F. Fey, Edo Vellenga, Margaret Dugan, and Pieter Sonneveld, on behalf of the Dutch-Belgian Hemato-Oncology Cooperative Group (HOVON) and the United Kingdom Medical Research Council (MRC)
Flow Fields: Dense Correspondence Fields for Highly Accurate Large Displacement Optical Flow Estimation

Modern large displacement optical flow algorithms usually use an initialization by either sparse descriptor matching techniques or dense approximate nearest neighbor fields. While the latter have the advantage of being dense, they have the major disadvantage of being very outlier prone as they are not designed to find the optical flow, but the visually most similar correspondence. In this paper we present a dense correspondence field approach that is much less outlier prone and thus much better suited for optical flow estimation than approximate nearest neighbor fields. Our approach is conceptually novel as it does not require explicit regularization, smoothing (like median filtering) or a new data term, but solely our novel purely data based search strategy that finds most inliers (even for small objects), while it effectively avoids finding outliers. Moreover, we present novel enhancements for outlier filtering. We show that our approach is better suited for large displacement optical flow estimation than state-of-the-art descriptor matching techniques. We do so by initializing EpicFlow (so far the best method on MPI-Sintel) with our Flow Fields instead of their originally used state-of-the-art descriptor matching technique. We significantly outperform the original EpicFlow on MPI-Sintel, KITTI and Middlebury.