Miracle-dz/UniFAR-FTUs huggingface dataset:
Rab18 is not necessary for lipid droplet biogenesis or turnover in human mammary carcinoma cells

Rab GTPases recruit peripheral membrane proteins and can define organelle identity. Rab18 localizes to the endoplasmic reticulum (ER) but also to lipid droplets (LDs), where it has been implicated in effector protein recruitment and in defining LD identity. Here, we studied Rab18 localization and function in a human mammary carcinoma cell line. Rab18 localized to the ER and to LD membranes on LD induction, with the latter depending on the Rab18 activation state. In cells lacking Rab18, LDs were modestly reduced in size and numbers, but we found little evidence for Rab18 function in LD formation, LD turnover on cell starvation, or the targeting of several proteins to LDs. We conclude that Rab18 is not a general, necessary component of the protein machinery involved in LD biogenesis or turnover.
Analysis of Intrusion Detection in Big Data

– Big Data refers to technologies and initiatives that involve data that is too diverse, fast-changing or massive for conventional technologies. This paper describes the Big Data usage and the security issues associated with it. With Big Data databases, enterprises can save money, grow revenue, and achieve many other business objectives by building new applications, improving the effectiveness and lowering the cost of existing applications, realizing new sources of competitive advantage. The continuous collection of traffic data by the network leads to Big Data problems that are caused by the volume, variety and velocity properties of Big Data. This paper also focuses on the problem and probability of intrusion in Big Data. Intrusion refers to the hacking of the system or a network which poses a security risk to the private information of the organization. To address the problem of network intrusion, a network intrusion detection system is used which detects such intrusions through the analysis of traffic on the network to monitor signs of malicious activity. It also keeps an eye on the packets on a network wire and its main objective is to look out for discrepancies. This paper describes the various techniques for intrusion detection and tries to identify the best technique.
Decreased Appetite after High-Intensity Exercise Correlates with Increased Plasma Interleukin-6 in Normal-Weight and Overweight/Obese Boys

Abstract Background: High-intensity exercise (HIEX) suppresses appetite in adults and is thought to be mediated by appetite-regulating hormones. However, the effects of HIEX-induced inflammatory and stress biomarkers on appetite control and body weight have not been reported in children or adults. Objective: The objective of this study was to describe the effects of acute HIEX at 70% peak oxygen consumption (VO2peak) on postexercise appetite and selective biomarkers of inflammation, stress, and appetite regulatory hormones in normal-weight (NW) and in overweight/obese boys. Methods: NW (n = 11) and overweight/obese (n = 11) boys aged 10–18 y were randomly assigned in a crossover design to either rest or HIEX. Visual analog scale appetite ratings and plasma biomarkers of appetite, inflammation, stress, and glucose control were measured after HIEX or rest. Results: Appetite increased from baseline to 110 min (P < 0.001), but was lower after HIEX (P = 0.04), with no difference between body weight groups. HIEX also resulted in lower active ghrelin (P < 0.001) and increased interleukin-6 (IL-6; P < 0.001), tumor necrosis factor-α (P < 0.001), and cortisol (P < 0.001) concentrations, independent of body weight. It increased blood glucose (P = 0.002) and insulin (P = 0.028) concentrations in NW but not overweight and obese boys. Leptin, glucagon-like peptide 1, peptide tyrosine tyrosine, C-reactive protein, and cortisol were not affected by HIEX. An inverse correlation was found between IL-6 and appetite (r = −0.379; P = 0.012), but not any other biomarkers. Conclusions: HIEX resulted in reduced appetite that correlated with an increase in IL-6 in both NW and overweight/obese boys. However, although a role for IL-6 in the response can be suggested, the suppression of appetite was potentially mediated by the decrease in active ghrelin and/or increase in cortisol. This trial was registered at clinicaltrials.gov as NCT02619461.
Impact of psychological profile on drug adherence and drug resistance in patients with apparently treatment-resistant hypertension

Abstract Purpose: Patients with apparent treatment-resistant hypertension (a-TRH) are often poorly adherent to drug treatment and have an unusual personal history and psychological profile. The aim of this study was to identify predictors of drug adherence and drug resistance in a cohort of patients with aTRH, with emphasis on psychological characteristics. Methods: All patients with confirmed aTRH on standardized antihypertensive treatment were eligible. Drug adherence was assessed by drug dosages in urine using Liquid Chromatography coupled with tandem Mass Spectrometry (LC-MS/MS). Drug resistance was assessed by 24-hour ambulatory blood pressure adjusted for the number of antihypertensive drugs and for drug adherence. Psychological profile was assessed using a broad array of validated questionnaires. Results: The analysis included 35 consecutive patients. The proportion of adherent, partly adherent and totally non-adherent patients was 29, 40 and 31%, respectively. In regression analysis, independent predictors of poor drug adherence were recent hospital admission for hypertension, a lower ability to put things into perspective when facing negative events and a higher tendency to somatize, accounting for 51% of variability in drug adherence. Independent predictors of treatment resistance were a higher recourse to the strategies of blaming others and oneself, accounting for 37% of variability in drug treatment resistance. Conclusion: In patients with aTRH, poor adherence is frequent but does not entirely account for treatment resistance. Psychological characteristics appear as strong predictors of both drug adherence and drug resistance. Our results suggest that therapeutic drug monitoring and psychological evaluation should be an integral part of assessment of patients with aTRH.
AmpUMI: design and analysis of unique molecular identifiers for deep amplicon sequencing

Motivation Unique molecular identifiers (UMIs) are added to DNA fragments before PCR amplification to discriminate between alleles arising from the same genomic locus and sequencing reads produced by PCR amplification. While computational methods have been developed to take into account UMI information in genome-wide and single-cell sequencing studies, they are not designed for modern amplicon based sequencing experiments, especially in cases of high allelic diversity. Importantly, no guidelines are provided for the design of optimal UMI length for amplicon-based sequencing experiments. Results Based on the total number of DNA fragments and the distribution of allele frequencies, we present a model for the determination of the minimum UMI length required to prevent UMI collisions and reduce allelic distortion. We also introduce a user-friendly software tool called AmpUMI to assist in the design and the analysis of UMI-based amplicon sequencing studies. AmpUMI provides quality control metrics on frequency and quality of UMIs, and trims and deduplicates amplicon sequences with user specified parameters for use in downstream analysis. AmpUMI is open-source and freely available at http://github.com/pinellolab/AmpUMI. Contact Ipinello@mgh.harvard. edu
Medical Image Denoising and Compression via a 2-D Wavelet Transform

Medical Images generally exhibits high level artefacts called noise. De-noising a medical image is essential in medical field. Transmitting medical image over the internet needs to be compressed and also remove noise to produce excellent result that can be easily viewed and interpreted by medical professionals. Wavelet transform enhances the superiority of an image and reduces noise level that is been transmitted. The image to be process is loaded and decomposed into level 3 using wavelet type known as biorthogonal via 2D wavelet transform. Furthermore, soft threshold is chosen to reduce the noise in the image. Unlike, hard threshold is an opposite of soft thresholding. Soft thresholding minimizes the coefficients above the threshold value. Medical image compression & de-noising using wavelet-based decomposition without discarding image originality describes horizontal, vertical and diagonal details of the image. Keywords— Discrete Wavelet Transform, Medical Images, De-Noising, 2D Wavelet, Image Compression.
Running Demands and Activity Profile of the New Four-Quarter Match Format in Men's Field Hockey.

Ihsan, M, Yeo, V, Tan, F, Joseph, R, Lee, M, and Aziz, AR. Running demands and activity profile of the new four-quarter match format in men's field hockey. J Strength Cond Res XX(X): 000-000, 2018-This study determined the running demands of men's field hockey with regards to the revised four-quarter match format. Twenty-eight male field hockey players were equipped with global positioning system units while competing in 14 competitive international games over a 1-year period. All matches allowed for unlimited substitutions, and consisted of four 15-minute quarters (i.e., Q1-Q4). A progressive decline in total distance (TD) was observed in Q2 (2,072 ± 141 m) to Q4 (2,055 ± 212 m) compared with Q1 (2,171 ± 195 m, p < 0.05). However, the decline in TD was due to decreases in low-intensity activity (<15 km·h, p < 0.05), as high-intensity running (HIR; >15 km·h) distances were similar throughout Q1-Q4 (p = 0.263). Positional data demonstrated a similar profile, where significant decreases in TD, but not in HIR, was observed across all playing positions at some point over the 4 quarters (p < 0.05). DEF accumulated the lowest amount of TD (7,631 ± 753 m), HIR (2,257 ± 498 m), and high-intensity decelerations (60 ± 9, >-2m·s) compared with MID and FWD (p < 0.05). By contrast, FWD performed the highest amount of HIR (3,090 ± 565 m) and high-intensity accelerations (110 ± 9, >2 m·s) compared with MID and DEF (p < 0.05). In conclusion, our results showed that although there was a progressive decline in TD over the 4 quarters of match play, high-intensity running performance (i.e., HIR and high-intensity acceleration) was maintained throughout the match regardless of playing position.
MC64-Cluster: Many-Core CPU Cluster Architecture and Performance Analysis in B-Tree Searches

Servicio de Informática, Edificio Ramón y Cajal, Campus Rabanales, Universidad de Córdoba, 14071 Córdoba, Spain Dep. Lenguajes y Ciencias de la Computación, ETSI Informática, Campus de Teatinos, Universidad de Málaga, 29071 Málaga, Spain Instituto de Agricultura Sostenible (IAS-CSIC), Alameda del Obispo s/n, 14080 Córdoba, Spain Q2 Dep. Estadística, Campus Rabanales C2-20N, Universidad de Córdoba, 14071 Córdoba, Spain Dep. Bioquímica y Biología Molecular, Campus Rabanales C6-1-E17, Campus de Excelencia Internacional Agroalimentario (ceiA3), Universidad de Córdoba, 14071 Córdoba, Spain Corresponding author: fjesteban@uco.es
Real-time 3 D Semantic Segmentation of Timber Loads with Convolutional Neural Networks

Volume measurements of timber loads is done in conjunction with timber trade. When dealing with goods of major economic values such as these, it is important to achieve an impartial and fair assessment when determining price-based volumes. With the help of Saab’s missile targeting technology, CIND AB develops products for digital volume measurement of timber loads. Currently there is a system in operation that automatically reconstructs timber trucks in motion to create measurable images of them. Future iterations of the system is expected to fully automate the scaling by generating a volumetric representation of the timber and calculate its external gross volume. The first challenge towards this development is to separate the timber load from the truck. This thesis aims to evaluate and implement appropriate method for semantic pixel-wise segmentation of timber loads in real time. Image segmentation is a classic but difficult problem in computer vision. To achieve greater robustness, it is therefore important to carefully study and make use of the conditions given by the existing system. Variations in timber type, truck type and packing together create unique combinations that the system must be able to handle. The system must work around the clock in different weather conditions while maintaining high precision and performance.
Oxidation-induced negative Poisson’s ratio of phosphorene

Mechanical properties of phosphorene oxides are investigated by using density functional theory calculations. Intriguingly, as the oxygen coverage approaches 50%, negative Poisson’s ratios are found in the in-plane principal directions, originating from the asymmetric atomic structure upon oxygen adsorption. It is demonstrated that the structure of phosphorene oxide is largely weakened compared with that of pristine phosphorene. Our work indicates that certain unconventional mechanical properties, such as the negative Poisson’s ratio, can be achieved by tuning the atomic structure through simple processes, which offers a new avenue to design specific properties at the nanoscale.
Water vapor heterogeneity related to tropopause folds over the North Atlantic revealed by airborne water vapor differential absorption lidar

[1] Airborne differential absorption lidar (DIAL) measurements of tropospheric water vapor and aerosol/clouds are presented from transfers across the North Atlantic on 13–15 May and 16–18 June 2002. The intense dynamical activity over the Atlantic is reflected in complex structures like deep tropopause folds, extended dry layers, and tilted aerosol filaments. Intrusions with H2O mixing ratios below 0.03 g kg−1 regularly develop along the storm track over intense cyclones and correspond to analyzed (European Centre for Medium-Range Weather Forecasts (ECMWF)) or simulated (MM5) potential vorticity anomalies. Sloping folds are typically 1 km thick in vertical profiles but on horizontal sections resemble long filaments with widths of a few hundred kilometers. Filaments of solid, roughly micron-sized particles occur inside and along the axes of the tropopause folds. The particles most likely originate in forest fires, from where they are injected to the lower stratosphere by deep convection and later on reenter the troposphere in developing baroclinic disturbances. Their laminar appearance indicates that these intrusions have not yet been mixed but are eroded on timescales significantly larger than a few days by stretching-thinning, stirring, and only finally, turbulent diffusion. MM5 mesoscale model simulations and, with less accuracy, also ECMWF analyses are capable of reproducing the dynamical structures associated with the observed dry intrusions. However, deep inside the intrusions where scales are small, even the MM5-simulated water vapor mixing ratios are more than twice those observed. The large dynamical range of water vapor mixing ratios (3 orders of magnitude) and large gradients (>2 g kg−1 km−1 at the intrusions' boundaries) constitute a challenge for future space-borne water vapor DIAL systems.
Optimal Design and Evaluation of Cantilever Probe for Multifrequency Atomic Force Microscopy

1. Abstract In multifrequency atomic force microscopy (AFM) to simultaneously measure topography and material properties of specimens, it is highly desirable that the higher order resonance frequencies of the cantilever probe are assigned to be integer harmonics of the excitation frequency. In this paper, a structural optimization technique is employed to design cantilever probes so that the ratios between one or more higher order resonance frequencies and the fundamental natural frequency are ensured to be equal to specified integers. A one-layer probe with variable width is optimally designed for assigning single and multiple resonance frequencies. Moreover, a three-layer model is proposed to provide more frequency choices. All the designs are verified by experiments, through the focused ion beam (FIB) milling based fabrication technique and AFM measurement. 2.
Accurate and robust localization for walking robots fusing kinematics, inertial, vision and LIDAR

In this article, we review methods for localization and situational awareness of biped and quadruped robotics. This type of robot is modelled as a free-floating mechanical system subject to external forces and constrained by whole-body distributed rigid contacts. Measurements of the state of the robot can be made using a variety of sensor information—such as kinematics (the sensing of the joint angles of the robot), contact force (pressure sensors in the robot's feet), accelerometers and gyroscopes as well as external sensors such as vision and LIDAR. This high-frequency state estimate is then passed to the control system of the robot to allow it to traverse terrain or manipulate its environment. In this article, we describe the development of an estimator for the Boston Dynamics Atlas humanoid robot. It was later adapted to the HyQ2 quadruped, developed by the Istituto Italiano di Tecnologia. Some discussion is given as to future trends while also considering briefly the relationship with biological systems.
Spreading activation simulation with semantic network skeletons

—Spreading activation algorithms are a well-known tool to determine the mutual relevance of nodes in a semantic network. Although often used, the conﬁguration of a spreading activation algorithm is usually problem-speciﬁc and experience-driven. However, an excessive exploration of spreading behavior is often not applicable due to the size of most semantic networks. A semantic network skeleton provides a comprised summary of a semantic network for better understanding the network’s structural characteristics. In this article, we present an approach for spreading activation simulation of semantic networks utilizing their semantic network skeletons. We show how expected spreading activation behavior can be estimated and how the results allow for further effect detection. The appropriateness of the simulation results as well as time-related advantages are demonstrated in a case study.
Visual Information Fusion through Bayesian Inference for Adaptive Probability-Oriented Feature Matching

This work presents a visual information fusion approach for robust probability-oriented feature matching. It is sustained by omnidirectional imaging, and it is tested in a visual localization framework, in mobile robotics. General visual localization methods have been extensively studied and optimized in terms of performance. However, one of the main threats that jeopardizes the final estimation is the presence of outliers. In this paper, we present several contributions to deal with that issue. First, 3D information data, associated with SURF (Speeded-Up Robust Feature) points detected on the images, is inferred under the Bayesian framework established by Gaussian processes (GPs). Such information represents a probability distribution for the feature points’ existence, which is successively fused and updated throughout the robot’s poses. Secondly, this distribution can be properly sampled and projected onto the next 2D image frame in t+1, by means of a filter-motion prediction. This strategy permits obtaining relevant areas in the image reference system, from which probable matches could be detected, in terms of the accumulated probability of feature existence. This approach entails an adaptive probability-oriented matching search, which accounts for significant areas of the image, but it also considers unseen parts of the scene, thanks to an internal modulation of the probability distribution domain, computed in terms of the current uncertainty of the system. The main outcomes confirm a robust feature matching, which permits producing consistent localization estimates, aided by the odometer’s prior to estimate the scale factor. Publicly available datasets have been used to validate the design and operation of the approach. Moreover, the proposal has been compared, firstly with a standard feature matching and secondly with a localization method, based on an inverse depth parametrization. The results confirm the validity of the approach in terms of feature matching, localization accuracy, and time consumption.
Fusing lidar and digital aerial photography for object-based forest mapping in the Florida Everglades

The Florida Everglades has a diverse forest community which needs to be accurately mapped to support the ongoing Comprehensive Everglades Restoration Plan (CERP). In this study, we examined whether a combination of light detection and ranging (lidar) and digital aerial photography can improve the accuracy of forest mapping in the Everglades, compared with using fine spatial resolution digital aerial photographs alone. We extracted lidar elevation and intensity features from original point cloud data at the object level to avoid the errors and uncertainties in the raster-based lidar methods. These features were combined with lidar-derived topographic information, and aerial photograph derived texture measures to map 7 forest communities in a portion of the Everglades. An overall accuracy of 71% and Kappa value of 0.64 were produced. We found that low-posting-density lidar data (i.e., <4 pts/m2) can significantly increase forest classification accuracy by providing important elevation, intensity, and topography information. It is anticipated that the modern lidar remote-sensing techniques can benefit the Everglades mapping to reduce the cost in CERP.
A unified approach to Fiedler-like pencils via strong block minimal bases pencils

The standard way of solving the polynomial eigenvalue problem associated with a matrix polynomial is to embed the matrix polynomial into a matrix pencil, transforming the problem into an equivalent generalized eigenvalue problem. Such pencils are known as linearizations. Many of the families of linearizations for matrix polynomials available in the literature are extensions of the so-called family of Fiedler pencils. These families are known as generalized Fiedler pencils, Fiedler pencils with repetition and generalized Fiedler pencils with repetition, or Fiedler-like pencils for simplicity. The goal of this work is to unify the Fiedler-like pencils approach with the more recent one based on strong block minimal bases pencils introduced in \cite{canonical}. To this end, we introduce a family of pencils that we have named extended block Kronecker pencils, whose members are, under some generic nonsingularity conditions, strong block minimal bases pencils, and show that, with the exception of the non proper generalized Fiedler pencils, all Fiedler-like pencils belong to this family modulo permutations. As a consequence of this result, we obtain a much simpler theory for Fiedler-like pencils than the one available so far. Moreover, we expect this unification to allow for further developments in the theory of Fiedler-like pencils such as global or local backward error analyses and eigenvalue conditioning analyses of polynomial eigenvalue problems solved via Fiedler-like linearizations.