Miracle-dz/UniFAR-FTUs huggingface dataset:
Promise of Fully Integrated PET/MRI: Noninvasive Clinical Quantification of Cerebral Glucose Metabolism

We describe a fully automated processing pipeline to support the noninvasive absolute quantification of the cerebral metabolic rate for glucose (CMRGlc) in a clinical setting. This pipeline takes advantage of “anatometabolic” information associated with fully integrated PET/MRI. Methods: Ten healthy volunteers (5 men and /5 women; 27 ± 7 y old; 70 ± 10 kg) underwent a test-retest 18F-FDG PET/MRI examination of the brain. The imaging protocol consisted of a 60-min PET list-mode acquisition with parallel MRI acquisitions, including 3-dimensional time-of-flight MR angiography, MRI navigators, and a T1-weighted MRI scan. State-of-the-art MRI-based attenuation correction was derived from T1-weighted MRI (pseudo-CT [pCT]). For validation purposes, a low-dose CT scan was also performed. Arterial blood samples were collected as the reference standard (arterial input function [AIF]). The developed pipeline allows the derivation of an image-derived input function (IDIF), which is subsequently used to create CMRGlc maps by means of a Patlak analysis. The pipeline also includes motion correction using the MRI navigator sequence as well as a novel partial-volume correction that accounts for background heterogeneity. Finally, CMRGlc maps are used to generate a normative database to facilitate the detection of metabolic abnormalities in future patient scans. To assess the performance of the developed pipeline, IDIFs extracted by both CT-based attenuation correction (CT-IDIF) and MRI-based attenuation correction (pCT-IDIF) were compared with the reference standard (AIF) using the absolute percentage difference between the areas under the curves as well as the absolute percentage difference in regional CMRGlc values. Results: The absolute percentage differences between the areas under the curves for CT-IDIF and pCT-IDIF were determined to be 1.4% ± 1.0% and 3.4% ± 2.6%, respectively. The absolute percentage difference in regional CMRGlc values based on CT-IDIF and pCT-IDIF differed by less than 6% from the reference values obtained from the AIF. Conclusion: By taking advantage of the capabilities of fully integrated PET/MRI, we developed a fully automated computational pipeline that allows the noninvasive determination of regional CMRGlc values in a clinical setting. This methodology might facilitate the proliferation of fully quantitative imaging into the clinical arena and, as a result, might contribute to improved diagnostic efficacy.
System identification of an unmanned quadcopter system using MRAN neural

This project presents the performance analysis of the radial basis function neural network (RBF) trained with Minimal Resource Allocating Network (MRAN) algorithm for real-time identification of quadcopter. MRAN’s performance is compared with the RBF with Constant Trace algorithm for 2500 input-output pair data sampling. MRAN utilizes adding and pruning hidden neuron strategy to obtain optimum RBF structure, increase prediction accuracy and reduce training time. The results indicate that MRAN algorithm produces fast training time and more accurate prediction compared with standard RBF. The model proposed in this paper is capable of identifying and modelling a nonlinear representation of the quadcopter flight dynamics.
Comparison of the Electromyographic Activity of the Trunk and Rectus Femoris Muscles During Traditional Crunch and Exercise Using the 5-Minute Shaper Device.

Silva, FHO, Arantes, FJ, Gregorio, FC, Santos, FRA, Fidale, TM, Bérzin, F, Bigaton, DR, and Lizardo, FB. Comparison of the electromyographic activity of the trunk and rectus femoris muscles during traditional crunch and exercise using the 5-minute Shaper device. J Strength Cond Res XX(X): 000-000, 2019-Different training devices are available to trigger greater activation of the abdominal muscles compared with that achieved during traditional abdominal exercises. This study aimed to compare the electromyographic (EMG) activity of the upper and lower rectus abdominis, external oblique abdominis, erector spinae, and rectus femoris (RF) muscles during traditional crunch and exercise using the 5-minute Shaper device. A convenience sample of 15 healthy men (mean ± SD; age: 23.65 ± 4.49 years, body fat percentage: 14.26 ± 3.56%) was selected. All men regularly participated in physical activity. Electromyographic data were collected for 5 repetitions of each abdominal exercise (traditional crunch and exercise using the 5-minute Shaper device at beginner, intermediate, advanced, and extreme levels) in a randomized and counterbalanced manner. Data were collected using simple differential surface electrodes and analyzed using repeated-measures analysis of variance (p < 0.05). Electromyographic signals were quantified using a root-mean-square analysis and normalized using the maximum voluntary isometric contraction. Traditional crunch produced greater or similar EMG activity in the abdominal muscles and minimized RF activity compared to the 5-minute Shaper device, hence, traditional crunch is preferred for training, especially for individuals with weak abdominal musculature and lower back problems. Therefore, the use of the 5-minute Shaper device may be questioned when it is intended to intensify the activity of the abdominal muscles; however, this apparatus may be used if greater variations in training are desired, depending on individual preferences.
Glycemic Variability and Hypoglycemic Excursions With Continuous Glucose Monitoring Compared to Intermittently Scanned Continuous Glucose Monitoring in Adults With Highest Risk Type 1 Diabetes

Background: The I-HART CGM study has shown that real-time continuous glucose monitoring (rtCGM) has greater beneficial impact on hypoglycemia than intermittently scanned continuous glucose monitoring (iscCGM) in adults with type 1 diabetes at high risk (Gold score ≥4 or recent severe hypoglycemia using insulin injections). In this subanalysis, we present the impact of rtCGM and iscCGM on glycemic variability (GV). Methods: Forty participants were recruited to this parallel group study. Following two weeks of blinded rtCGM (DexcomG4), participants were randomized to rtCGM (Dexcom G5; n = 20) or iscCGM (Freestyle Libre; n = 20) for eight weeks. An open-extension phase enabled participants on rtCGM to continue for a further eight weeks and those on iscCGM to switch to rtCGM over this period. Glycemic variability measures at baseline, 8- and 16-week endpoints were compared between groups. Results: At the eight-week endpoint, between-group differences demonstrated significant reduction in several GV measures with rtCGM compared to iscCGM (GRADE%hypoglycemia, index of glycemic control [IGC], and average daily risk range [ADRR]; P < .05). Intermittently scanned continuous glucose monitoring reduced mean average glucose and glycemic variability percentage and GRADE%hyperglycemia compared with rtCGM (P < .05). At 16 weeks, the iscCGM group switching to rtCGM showed significant improvement in GRADE%hypoglycemia, personal glycemic status, IGC, and ADRR. Conclusion: Our data suggest most, but not all, GV measures improve with rtCGM compared with iscCGM, particularly those measures associated with the risk of hypoglycemia. Selecting appropriate glucose monitoring technology to address GV in this high-risk cohort is important to minimize the risk of glucose extremes and severe hypoglycemia. Clinical trial registration: ClinicalTrials.gov NCT03028220
An In Vivo (Gallus gallus) Feeding Trial Demonstrating the Enhanced Iron Bioavailability Properties of the Fast Cooking Manteca Yellow Bean (Phaseolus vulgaris L.)

The common dry bean (Phaseolus vulgaris L.) is a globally produced pulse crop and an important source of micronutrients for millions of people across Latin America and Africa. Many of the preferred black and red seed types in these regions have seed coat polyphenols that inhibit the absorption of iron. Yellow beans are distinct from other market classes because they accumulate the antioxidant kaempferol 3-glucoside in their seed coats. Due to their fast cooking tendencies, yellow beans are often marketed at premium prices in the same geographical regions where dietary iron deficiency is a major health concern. Hence, this study compared the iron bioavailability of three faster cooking yellow beans with contrasting seed coat colors from Africa (Manteca, Amarillo, and Njano) to slower cooking white and red kidney commercial varieties. Iron status and iron bioavailability was assessed by the capacity of a bean based diet to generate and maintain total body hemoglobin iron (Hb-Fe) during a 6 week in vivo (Gallus gallus) feeding trial. Over the course of the experiment, animals fed yellow bean diets had significantly (p ≤ 0.05) higher Hb-Fe than animals fed the white or red kidney bean diet. This study shows that the Manteca yellow bean possess a rare combination of biochemical traits that result in faster cooking times and improved iron bioavailability. The Manteca yellow bean is worthy of germplasm enhancement to address iron deficiency in regions where beans are consumed as a dietary staple.
Incorporation of Silver Sulfadiazine into An Electrospun Composite of Polycaprolactone as An Antibacterial Scaffold for Wound Healing in Rats

Objective Fabrication of an antibiotic-loaded scaffold with controlled release properties for wound dressing is one of tissue engineering challenges. The aim of this study was to evaluate the wound-healing effectiveness of 500-µm thick polycaprolactone (PCL) nanofibrous mat containing silver sulfadiazine (SSD) as an antibacterial agent. Materials and Methods In this experimental study, an electrospun membrane of PCL nanofibrous mat containing 0.3% weight SSD with 500 µm thickness, was prepared. Morphological and thermomechanical characteristics of nanofibers were evaluated. Drug content and drug release properties as well as the surface hydrophobicity of the nanofibrous membrane were determined. Antimicrobial properties and cellular viability of the scaffold were also examined. A full thickness wound of 400 mm2 was created in rats, to evaluate the wound-healing effects of PCL/SSD blend in comparison with PCL and vaseline gas used as the control group. Results SSD at a concentration of 0.3% improved physicochemical properties of PCL. This concentration of SSD did not inhibit the attachment of human dermal fibroblasts (HDFs) to nanofibers in vitro, but showed antibacterial activity against Gram-positive Staphylococcus aureus (ST) and Gram-negative Pseudomonas aeruginosa (PS). Overall, results showed that SSD improves characteristics of PCL nanofibrous film and improves wound-healing process in one-week earlier compared to control. Conclusion Cytotoxicity of SSD in fabricated nanofibrous mat is a critical challenge in designing an effective wound dressing that neutralizes cellular toxicity and improves antimicrobial activity. The PCL/SSD nanofibrous membrane with 500- µm thickness and 0.3% (w/v) SSD showed applicable characteristics as a wound dressing and it accelerated wound healing process in vivo.
Analysis of Methanolic Extracts and Crude Polysaccharides from the Leaves of Chuanminshen violaceum and Their Antioxidant Activities

The root of Chuanminshen violaceum is used as an important edible and medicinal plant in China. However, its leaves are generally considered byproducts, and therefore do not have a use. Thus, the phenolic compounds in the methanolic extracts (CVLMs) and the chemical characteristics of crude polysaccharides (CVLPs) from the leaves of C. violaceum and their in vitro antioxidant activities were explored. The results showed that chlorogenic acid and rutin were the major individual phenolic compounds in the leaves, which ranged from 1.22 ± 0.03 to 2.87 ± 0.04 mg/g DW, and from 2.25 ± 0.04 to 4.03 ± 0.05 mg/g DW, respectively. Meanwhile, the extraction yields of CVLPs from the leaves ranged from 4.73% to 5.41%. The CVLPs consisted of mannose, rhamnose, galacturonic acid, glucose, galactose, and arabinose, suggesting the existence of pectic polysaccharides. Furthermore, both CVLMs and CVLPs exhibited strong antioxidant activities. Chlorogenic acid and rutin were major contributors to the antioxidant activities of CVLMs, and the antioxidant activities of CVLPs were closely correlated to their α-1,4-D-galactosiduronic linkages. The results are beneficial for understanding the chemical properties and in vitro antioxidant activities of CVLMs and CVLPs. The leaves of C. violaceum have potential to be developed as natural antioxidants.
Multi-Level Comparison of Machine Learning Classifiers and Their Performance Metrics

Machine learning classification algorithms are widely used for the prediction and classification of the different properties of molecules such as toxicity or biological activity. The prediction of toxic vs. non-toxic molecules is important due to testing on living animals, which has ethical and cost drawbacks as well. The quality of classification models can be determined with several performance parameters. which often give conflicting results. In this study, we performed a multi-level comparison with the use of different performance metrics and machine learning classification methods. Well-established and standardized protocols for the machine learning tasks were used in each case. The comparison was applied to three datasets (acute and aquatic toxicities) and the robust, yet sensitive, sum of ranking differences (SRD) and analysis of variance (ANOVA) were applied for evaluation. The effect of dataset composition (balanced vs. imbalanced) and 2-class vs. multiclass classification scenarios was also studied. Most of the performance metrics are sensitive to dataset composition, especially in 2-class classification problems. The optimal machine learning algorithm also depends significantly on the composition of the dataset.
Analysis of free surface anti-roll tank using URANS . Verification and validation

To prevent excessive roll motion of ships operating in seas, damping systems are often required. Exterior systems can be used like, bilge keels or active stabilizer fins, or interior systems like anti-roll tanks (ARTs). There are mainly two sorts of ARTs, i.e. free surface tanks and Utype tanks. Both types have been studied extensively in the past, e.g. by Watts (1883), Frahm (1911) and Verhagen and Wijngaarden (1965), but also more recently, e.g. by Lee and Vassalos (1996), Kerkvliet et al. (2014) and Carette (2015). The content of this paper is restricted to the free surface type ART, which is nowadays often used to increase the roll damping of ships passively. The main advantages of such an ART are the large damping moment at small roll amplitudes and the ease to adapt the response by changing the water level. The response of the tank is highly frequency and amplitude dependent with a strong non-linear character (Carette et al., 2016). Also the shape of the interior geometry, e.g. additional struts, plates or other flow obstructions, will have an effect on the response, which makes it difficult to predict the response by analytical models. Therefore, systematic oscillation tests are often performed by modelscale experiments or by use of Computational Fluid Dynamics (CFD). This paper shows the response of a twodimensional (2D) and three-dimensional (3D) modelscale free surface ART using the CFD code ReFRESCO (www.refresco.org). The objective of this paper is to show which issues are important when CFD is used as a research and design tool. A verification and validation study is performed to determine numerical settings to obtain a good trade-off between accuracy and computational costs. The CFD results are validated against model-scale experimental results, based on the work of Carette (2015). The results show that CFD can be used as a simulation driven design tool to accurately predict the response of an ART.
ESTIMATION OF CONSUMER DEMANDS : AN APPLICATION TO U . S . APPAREL EXPENDITURES

A set of new statistical methods will be presented to model the U.S. men's wear markets along with the general consumption trends among U.S. male and female populations. The Almost Ideal Demand (AID) system of Deaton and Muellbauer (1980) was extended to include general, nonlinear and nonadditive habit effects. By employing a "Habit Stock" model into a first-order differential demand system, the pattern of shifts as well as the dynamic changes in the market shares were estimated. The results of analysis on four categories of men's bottom during 1990-96 suggest that the dynamic habit stock formation is a highly promising new concept for explaining the current and emerging fashion trends and market shares. The paper will also discuss the potential of using social science data obtained from consumers’ general social behaviors during 1990-1998 for the projection of future apparel consumption trends.
Causal Inference for ATM Counterfactual Estimation

We propose that the Rubin potential outcomes framework of causal inference can be used to statistically estimate counterfactuals, by definition never observable, of Traffic Flow Management Initiatives (TFMI), as a novel means of quantifying the performance of Air Traffic Management (ATM) actions, despite confounding factors. Specifically, we apply the method of Propensity Scores to estimate counterfactuals and compute the increase in hourly average airborne delay which would have resulted without a Ground Delay Program, using an eleven month span of hourly weather, traffic, and delay data at JFK. Our introduction also summarizes the concepts of causal inference required for our analysis. We also offer suggestions to improve and extend our initial application of casual inference. Technical details of propensity score modeling are further covered in an appendix. Keywords—ATM Performance Measurement, Causal Inference, Propensity Scores
Cluster Analysis of Soybean Genotypes Based on RAPD Markers

The objective of this study was to investigate the influence of different similarity coefficients over the following cluster analysis, based on data from RAPD marker analysis of twenty soybean genotypes. The highest genetic similarity, by all four coefficients was between genotypes Kunitz and P 9272. The lowest genetic similarity was between Maple presto and P 9272 according to Sorens-Dice and Maple presto and ZPS015 according to Roger and Tanimoto coefficients. UPGMA procedure based on each of the similarity coefficient assigned the twenty genotypes in two main clusters. Six genotypes were placed into the cluster I by all four methods. The structure of second cluster differed depending on coefficient of similarity.
Allelopatic effects of some medicinal plant essential oils on plant seeds germination

Article info: Received: 14 May 2015 Accepted: 19 October 2015 ABSTRACT The effect of essential oils from some medicinal plants on seed germination was studied with the aim of assessing their potential use as bioherbicides. The experiment was conducted as factorial based on completely randomized design (CRD) with three replications. Seeds of 3 summer crops including lettuce (Lactuca sativa), pepper (Piper longum) and tomato (Solanum lycopersicum) were exposed to essential oils of rosemary (Rosmarinus officinalis), thyme (Thymus vulgaris) and anise (Pimpinella anisum) at 3 different concentrations (25 and 50% diluted and undiluted). Treated seeds were grown in a growth chamber at 25°C for 5 days. The number of germinated seeds in each Petri dish was daily counted. After five days seed germination percentage (Ge) was calculated. Biplot analysis was performed using genotype plus genotype environment interaction (GGE) method. Results showed that the allelopathic effect on Ge was varied among studied plants, which was mainly due to i) differences in the composition of the studied essential oils and ii) different allelopathic effects of the studied essential oils on Ge. Accordingly, compared to the individual use, combining several essential oils would have a greater inhibitory effect on Ge of weeds.
State Estimation for Robotics

A key aspect of robotics today is estimating the state (e.g., position and orientation) of a robot, based on noisy sensor data. This book targets students and practitioners of robotics by presenting classical state estimation methods (e.g., the Kalman filter) but also important modern topics such as batch estimation, Bayes filter, sigmapoint and particle filters, robust estimation for outlier rejection, and continuous-time trajectory estimation and its connection to Gaussian-process regression. Since most robots operate in a three-dimensional world, common sensor models (e.g., camera, laser rangefinder) are provided followed by practical advice on how to carry out state estimation for rotational state variables. The book covers robotic applications such as point-cloud alignment, pose-graph relaxation, bundle adjustment, and simultaneous localization and mapping. Highlights of this expanded second edition include a new chapter on variational inference, a new section on inertial navigation, more introductory material on probability, and a primer on matrix calculus.
Temporal Forecast Demand of Cloud Based Media Streaming Applications for Efficient Resource Allocation

Media streaming applications assumed importance as they can render multimedia services to subscribers. They became popular of late with innovative technologies like cloud computing. Cloud data centres and their scalability and availability made these applications prosper. They are associated with Video on Demand (VoD). These applications do have huge number of subscribers across the globe. Provided this fact, the subscriptions are increasing in exponential fashion. This has caused the cloud based media streaming providers an issue pertaining to resource allocation. The main problem is that when more resources are allocation, the streaming quality is good but there is wastage of resources. In the same fashion, when fewer resources are allocated, it may cause deterioration of quality besides denial of services to subscribers when there is sudden and unprecedented increase in the number of subscribers. The existing reservation based resource allocation needs to be improved for efficiency. In this paper we proposed and implemented a time-series based forecast algorithm that can have accurate predictions to help service providers. The algorithm helps in optimizing the resource allocation to media streaming applications in cloud. We built a prototype application that demonstrates the proof of concept. The empirical results revealed that the forecast is useful for efficient cloud resource allocation.
Many-particle non-equilibrium interaction potentials in the mesoparticle method

The particle methods have proved recently to be proficient tools for discretization and simulation of mechanical behavior of different systems. The crucial flaw of these methods is, however, the impossibility to describe systems with different, particularly, with very low transverse rigidity under external pressure. The present paper shows that there is a way to overcome this difficulty by using properly defined many-particle interaction potentials instead of two-particle ones. As first proposed by Ostermeyer, we introduce temperaturedependent interaction potentials and then make a further generalization step by considering a non-equilibrium potential varying with time due to the relaxation processes occurring in the system. The last section of the paper discusses the methods of describing the energy dissipation and offers a possible form of the many-particles term of the dissipation function, which satisfies the general symmetry conditions.