Miracle-dz/UniFAR-FTUs huggingface dataset:
A study on nanofiber-reinforced thermoplastic composites (II): Investigation of the mixing rheology and conduction properties

This article is portion of a comprehensive study on the development of nanofiber-reinforced polymer composites for electrostatic discharge materials and structural composites. Vapor-grown carbon fibers with an average diameter of 100 nm were used as a precursor and model fiber system for carbon nanotubes. These nanofibers were purified and functionalized to provide for an open network of high-purity nanofibers. Banbury-type mixing was used to disperse the nanofibers in the polymer matrix. Rheological and microscopic analysis showed that the high shear processing of the polymer/nanofiber mixture led to a homogeneous dispersion of nanofibers with no agglomerates present and no shortening of the nanofibers. The shear thinning behavior of polymeric materials helps in the mixing of the nanofibers to form the composites. A percolation threshold for electrical conduction of 9–18 wt % was observed for the highly dispersed nanofiber networks. The electrical behavior of these materials was not affected by changes in humidity. Microscopic analysis showed highly dispersed nanofibers with no indications of porosity. These conducting polymers are well suited for electrostatic discharge applications, and might well become multifunctional materials for strength/electrical applications. © 2001 John Wiley & Sons, Inc. J Appl Polym Sci 80: 1162–1172, 2001
Prevalence and associated factors of active smoking among individuals living with hypertension and/or diabetes in Africa: a systematic review and meta-analysis protocol

Introduction Tobacco use significantly increases cardiovascular complications in people living with hypertension and/or diabetes. We aim to summarise data on the prevalence and factors associated with active smoking in these conditions in Africa. Method and analysis We will search PubMed, Embase, Google Scholar and African Journals Online for relevant abstracts of studies on active smoking in individuals living with diabetes and/or hypertension published from 1 January 2000 to 31 December 2016, with no language restriction. Additionally, relevant unpublished papers and conference proceedings will be checked, as well as references of included articles. Two investigators will independently screen, select studies, extract data and assess the risk of bias in each study. Data will be analysed using Stata software (Stata V.14, Texas, USA). The study-specific estimates will be pooled through a random-effects meta-analysis model to obtain an overall summary estimate of the prevalence of smoking across studies. Also, we will assess factors associated to smoking. Heterogeneity of studies will be evaluated by the χ2 test on Cochrane’s Q statistic. Funnel plots analysis and Egger’s test will be done to detect publication bias. Results will be presented by geographic region (central, eastern, northern, southern and western Africa). A p value less than 0.05 will be considered significant for factors associated to smoking. Ethics and dissemination This study is based on published data, and therefore ethical approval is not a requirement. This systematic review and meta-analysis is expected to serve as a basis for designing cost-effective interventions to reduce and prevent smoking in patients with diabetes and/or hypertension, and as a guide for future research based on the remaining gaps. The final report of this study in the form of a scientific paper will be published in peer-reviewed journals. Findings will further be presented at conferences and submitted to relevant health authorities.
Correcting the Bias of Empirical Frequency Parameter Estimators in Codon Models

Markov models of codon substitution are powerful inferential tools for studying biological processes such as natural selection and preferences in amino acid substitution. The equilibrium character distributions of these models are almost always estimated using nucleotide frequencies observed in a sequence alignment, primarily as a matter of historical convention. In this note, we demonstrate that a popular class of such estimators are biased, and that this bias has an adverse effect on goodness of fit and estimates of substitution rates. We propose a “corrected” empirical estimator that begins with observed nucleotide counts, but accounts for the nucleotide composition of stop codons. We show via simulation that the corrected estimates outperform the de facto standard estimates not just by providing better estimates of the frequencies themselves, but also by leading to improved estimation of other parameters in the evolutionary models. On a curated collection of sequence alignments, our estimators show a significant improvement in goodness of fit compared to the approach. Maximum likelihood estimation of the frequency parameters appears to be warranted in many cases, albeit at a greater computational cost. Our results demonstrate that there is little justification, either statistical or computational, for continued use of the -style estimators.
PAS: Visual odometry with Perspective Alignment Search

Visual odometry is typically formulated as a descriptor-based image feature tracking problem, followed by outlier rejection and simultaneous estimation of the scene structure and camera motion. We propose a fundamentally different formulation for the stereo case: a multi-scale search over pose to estimate the transformation that best aligns two sparse point clouds in image space. This has three main consequences. First, data association is descriptorless and implicit, supporting the use of features with indistinct appearance, such as edge features. Second, outlier rejection is subsumed by the use of a robust kernel and a joint feature alignment objective. Third, the method is robust to local minima, in contrast to coarse-to-fine or iterative approaches. This paper details the proposed method, which we call Perspective Alignment Search (PAS), integrated into an edge feature visual odometry system, and an evaluation against a LIDAR-based SLAM solution.
Positioning the laparoscopic camera with industrial robot arm

This paper introduces a solution for the movement control of the laparoscopic camera employing a teleoperated robotic assistant. The project propose an autonomous robotic solution based on an industrial manipulator, provided with a modular software which is applicable to large scale. The robot arm is envisioned to orient and move the optic device in direction of a fixed point, the incision on the wall of the abdominal cavity, accordingly to the surgeon's request. To manage the movements of the laparoscope around the fulcrum point a Cartesian control strategy is exploited. A six degrees of freedom industrial robot arm is designated to accomplish this manipulation task. The software is implemented in ROS in order to facilitate future extensions. The experimental results shows a manipulator capable of moving fast and smoothly the surgical tool around a remote center of motion.
Statistical analysis of power transformer component life time data

With statistical analysis it is possible to describe the ageing processes of power transformers components statistically. Because of the complexity of power transformers it is interesting to show the failure behaviour of the different components. As input for the analysis a population of power transformers with different ratings, designs and makes is used. From the reported failures the different failure modes of the components are distinguished. The failure data is fitted with mathematical statistical distributions and its parameters can be estimated. From the analysis it can be seen in which life phase the components are and what can be expected for the future regarding failures of some transformer components. The results can be used to determine if there is a reason for concern in the next coming years and if replacement or maintenance is necessary to secure a reliable network operation. It can also help to determine in what way a population of spare transformers is needed.
Adaptive task allocation for search area coverage

Many operations require an area search area function, including search-and-rescue, surveillance, hazard detection, structures or sites inspection and agricultural spraying. Furthermore, these area search applications often involve varying vehicle and environmental conditions. This paper explores the problem of optimizing the behavior of a swarm of heterogeneous robotic vehicles executing a search area coverage task. Each vehicle is equipped with a sensing apparatus and the swarm must collectively explore an occluded environment to achieve a required probability of detection for each location in the search area. The problem is further complicated with the introduction of dynamic vehicle and environmental properties making adaptability a necessary requirement in order to achieve a high level of mission assurance using unmanned vehicles. Novel methods for search space decomposition and task allocation are presented, with simulated and real-world results utilizing the Boeing Vehicle Swarm Technology Laboratory.
Dynamics of nuclear actin bundle induction by dimethyl sulfoxide and factors affecting its development

We have reported in a previous paper that dimethyl sulfoxide (DMSO) induces the formation of huge bundles of actin filaments in the nuclei of Dictyostelium mucoroides. The present study was performed to provide electron microscope data on the induction of nuclear actin bundles, illustrating both their formation and their reversion, as well as on the effects of various factors on the induction. The large nuclear bundles of actin appeared after 20--30 min of treatment with 10% DMSO. A DMSO concentration of 5 or 10% was optimal for the induction of the bundles. The nuclear actin bundle reverted to the original morphology within 5 min after removing DMSO. Induction of nuclear actin bundles was inhibited by Mg++ and low temperatures, but not by Na+, K+, Ca++, ATP, 3'5'-cyclic adenosine monophosphate (cAMP), phosphate buffer, or cytochalasin B. Neither NaN3 nor cycloheximide totally inhibited the induction of the bundles.
Supporting Folk-Song Research by Automatic Metric Learning and Ranking

In folk song research, appropriate similarity measures can be of great help, e.g. for classification of new tunes. Several measures have been developed so far. However, a particular musicological way of classifying songs is usually not directly reflected by just a single one of these measures. We show how a weighted linear combination of different basic similarity measures can be automatically adapted to a specific retrieval task by learning this metric based on a special type of constraints. Further, we describe how these constraints are derived from information provided by experts. In experiments on a folk song database, we show that the proposed approach outperforms the underlying basic similarity measures and study the effect of different levels of adaptation on the performance of the retrieval system.
Mitigation of Detrimental Effects of Alkali-Silica Reaction in Cement-Based Composites by Combination of Steel Microfibers and Ground-Granulated Blast-Furnace Slag

The effect of combining brass-coated steel microfiber and ground-granulated blast-furnace slag (GGBS) on the mitigation of deleterious expansion due to alkali-silica reaction (ASR) was investigated in this research. A potentially reactive basaltic aggregate was chosen as a reactive material. Two series of specimens containing different amounts of microfiber were prepared. One of them was cured in 1 M NaOH solution at 80°C to obtain a similar maturity; the other series was cured in 80°C water up to 120 days. ASR expansion, strength development, and toughness properties were observed for 120 days in NaOH solution and the results were compared with specimens kept in water. Test results indicate that the combination of GGBS and steel fibers reduced ASR expansion significantly. Furthermore, the combination was very effective at preventing the mechanical property loss due to ASR, such as flexural strength, compressive strength, and toughness. Microstructural investigations revealed that the reaction products had a different morphology (e.g., fibrous, network appearance) when the specimens were kept in NaOH solution.
The First-Order Theory of Ground Tree Rewrite Graphs

We prove that the complexity of the uniform first-order theory of ground tree rewrite graphs is in ATIME(2^{2^{poly(n)}},O(n)). Providing a matching lower bound, we show that there is some fixed ground tree rewrite graph whose first-order theory is hard for ATIME(2^{2^{poly(n)}},poly(n)) with respect to logspace reductions. Finally, we prove that there exists a fixed ground tree rewrite graph together with a single unary predicate in form of a regular tree language such that the resulting structure has a non-elementary first-order theory.
Effect of surface roughness of MgO substrate on size distribution of inclusions

Experiments were carried out to investigate the effect of surface roughness of MgO substrate on the formation and size distribution of inclusion particles employing new experimental methodology. The reaction of MgO refractory with Al deoxidised liquid Fe can take place, which results in forming both MgO and spinel type of inclusions. The number density of inclusions increases with increasing surface roughness of the substrate, which could be explained by Gibbs–Thompson effect. Activated interfacial reactions between the substrate and liquid Fe are believed to be more dominant than the effect of increased surface roughness of the substrate on the number density of inclusions. It is recommended to use Al2O3 based nozzle than MgO based one of similar surface roughness from a viewpoint of the generation of lower number density of inclusions.
Tracking the Evolution of Chemical Computing Networks

How do chemical reaction networks that process information evolve? This is not only a fundamental question in the study of the origin of life, but also in diverse fields like molecular computing, synthetic biology, and systems biology. Here, we study the evolution of chemical flip-flops by means of chemical organisation theory. Additionally, we compare evolved circuits with manually constructed ones. We found that evolution selects for an organisational structure that is related to function. That is, the resulting computation can be explained as a transition between organisations. Furthermore, an evolutionary process can be tracked as a change of the organisational structure, which provides a fundamentally different view than looking at the structural changes of the reaction networks. In our experiments, 90% of evolutionary improvement coincide with a change in the organisational structure. We conclude that our approach provides a novel and useful perspective to study evolution of chemical information processing systems.
Human Activity Recognition and Prediction

Human activity recognition (HAR) has become one of the most active research topics in image processing and pattern recognition (Aggarwal, J. K. and Ryoo, M. S., 2011). Detecting specific activities in a live feed or searching in video archives still relies almost completely on human resources. Detecting multiple activities in real-time video feeds is currently performed by assigning multiple analysts to simultaneously watch the same video stream. Manual analysis of video is labor intensive, fatiguing, and error prone. Solving the problem of recognizing human activities from video can lead to improvements in several applications fields like in surveillance systems, human computer interfaces, sports video analysis, digital shopping assistants, video retrieval, gaming and health-care (Popa et al., n.d.; Niu, W. et al., n.d.; Intille, S. S., 1999; Keller, C. G., 2011). This area has grown dramatically in the past 10 years, and throughout our research we identified a potentially underexplored sub-area: Action Prediction. What if we could infer the future actions of people from visual input? We propose to expand the current vision-based activity analysis to a level where it is possible to predict the future actions executed by a subject. We are interested in interactions which can involve a single actor, two humans and/or simple objects. For example try to predict if “a person will cross the street” or “a person will try to steal a handbag from another” or where will a tennis-player target the next volley. Using a hierarchical approach we intend to represent high-level human activities that are composed of other simpler activities, which are usually called sub-events which may themselves be decomposable. We expect to develop a system capable of predicting the next action in a sequence initially using offline-learning to bootstrap the system and then with self-improvement/task specialization in mind, using online-learning. 2 OUTLINE OF OBJECTIVES
Determination of strain sensitivity of free fiber Bragg gratings

Strain sensitivities of free, uncoated fiber Bragg gratings at λB ~1535 nm in a SMF28 standard telecommunication fiber and in a highly GeO2 doped photosensitive fiber (F86) were determined at room temperature. Both fibers showed similar strain sensitivities of kSMF28 = (0.7951 ± 0.0041) for the SMF28 and kF86 = (0.7912 ± 0.0023) for the F86 fiber. The stress sensitivities of both fibers were found to be slightly different with the values of (Δλ/F)SMF28 = (1.347 ± 0.006) nm/N for the SMF 28 fiber and (Δλ/F)F86 = (1.309 ± 0.001) nm/N for the F86 fiber.
Community-Acquired Pneumonia: Genomics, Epigenomics, Transcriptomics, Proteomics, and Metabolomics

Abstract Community-acquired pneumonia remains a significant health problem with very little progress having been made over the past 2 to 3 decades. Recent technological advances have opened up whole new avenues of exploration in the fields of genomics, epigenomics, transcriptomics, proteomics, and metabolomics. Although data in pneumonia are relatively scant with the exception of genomics due to the early stages of the science, some intriguing insights and clear avenues of application are already emerging. This review discusses recent studies in pneumonia using these new approaches as well as relevant research in sepsis and other diseases. Current and potential future uses of these platforms are discussed, and both key findings and key barriers to further progress are highlighted.
Effect of Nano-Silica Loading on Barrier and Mechanical Properties of Food Packaging Based LLDPE Film

In the present work, nano-silica was used in preparing LLDPE/nano-silica as an outer layer film for LLDPE reinforced nano-silica/LDPE/LLDPE multilayer film for microwavable packaging materials in future work. Thus, the objective of this work was studied the optimal of modified nano-silica loading into LLDPE film on barrier and mechanical properties. The experiments were divided into 2 main steps: surface treatment of nano-silica with vinyltriethoxysilane by ultrasonic agitation, and preparation of linear low density polyethylene film reinforced with untreated and treated nano-silica which different silica quantities are 1, 3, and 5 phr by blown film extruder. And then the surface morphology of films was examined by SEM. The properties of the film were analysis, oxygen transmission rate of film was characterized by OTR, water vapor transmission rate of film was characterized by WVTR, and tensile properties (tensile strength, % elongation and modulus) of films were examined by universal testing machine. Results indicated that the LLDPE loaded with 1 phr of nano-silica treated with vinyltriethoxysilane had better tensile strength and % elongation than at 3 and 5 phr of treated and untreated nano-silica.
LiveWeb: visualizing live user activities on the Web

Currently, Web users have little knowledge about the activities of fellow users. They cannot see the flow of online crowds or identify centers of on-line activity. LiveWeb seeks to enrich Web users’ experience by visualizing the real-time activities of other users. The visualizations can help answer user questions about overall patterns and specifics such as What are other people looking at? What is hot? Who is interested in what I am interested in?
Efficiency of labriform swimming in the bluegill sunfish (Lepomis macrochirus)

SUMMARY Bluegill sunfish (Lepomis macrochirus) swim in the labriform mode at low speeds, generating lift and thrust by beating their pectoral fins. The maximal power output available from the two largest pectoral fin adductor and abductor muscles, constituting half of the total pectoral girdle muscle mass, was measured in vitro and used to estimate the muscle mechanical power output during maximal labriform swimming (Pmech; 0.15–0.21 W kg–1 body mass). Respirometry was used to estimate the total metabolic power input (Ptotal; 0.95 W kg–1 body mass) and the metabolic power available to the active muscle mass (Pmuscle; Ptotal minus standard metabolic rate, 0.57 W kg–1 body mass) at this swimming speed. Drag measurements made on towed, dead fish were used to estimate the mechanical power required to overcome body drag (Pdrag; 0.028 W kg–1 body mass). Efficiency estimates based on these data fell into the following ranges: overall swimming efficiency (ηgross=Pmech/Ptotal), 0.16–0.22; muscle efficiency (ηmuscle=Pmech/Pmuscle), 0.26–0.37; and propeller efficiency (ηprop=Pdrag/Pmech), 0.15–0.20. Comparison with other studies suggests that labriform swimming may be more efficient than swimming powered by undulations of the body axis.
Identification of Increased Amounts of Eppin Protein Complex Components in Sperm Cells of Diabetic and Obese Individuals by Difference Gel Electrophoresis*

Metabolic disorders like diabetes mellitus and obesity may compromise the fertility of men and women. To unveil disease-associated proteomic changes potentially affecting male fertility, the proteomes of sperm cells from type-1 diabetic, type-2 diabetic, non-diabetic obese and clinically healthy individuals were comparatively analyzed by difference gel electrophoresis. The adaptation of a general protein extraction procedure to the solubilization of proteins from sperm cells allowed for the resolution of 3187 fluorescent spots in the difference gel electrophoresis image of the master gel, which contained the entirety of solubilized sperm proteins. Comparison of the pathological and reference proteomes by applying an average abundance ratio setting of 1.6 and a p ≤ 0.05 criterion resulted in the identification of 79 fluorescent spots containing proteins that were present at significantly changed levels in the sperm cells. Biometric evaluation of the fluorescence data followed by mass spectrometric protein identification revealed altered levels of 12, 71, and 13 protein species in the proteomes of the type-1 diabetic, type-2 diabetic, and non-diabetic obese patients, respectively, with considerably enhanced amounts of the same set of one molecular form of semenogelin-1, one form of clusterin, and two forms of lactotransferrin in each group of pathologic samples. Remarkably, β-galactosidase-1-like protein was the only protein that was detected at decreased levels in all three pathologic situations. The former three proteins are part of the eppin (epididymal proteinase inhibitor) protein complex, which is thought to fulfill fertilization-related functions, such as ejaculate sperm protection, motility regulation and gain of competence for acrosome reaction, whereas the putative role of the latter protein to function as a glycosyl hydrolase during sperm maturation remains to be explored at the protein/enzyme level. The strikingly similar differences detected in the three groups of pathological sperm proteomes reflect a disease-associated enhanced formation of predominantly proteolytically modified forms of three eppin protein complex components, possibly as a response to enduring hyperglycemia and enhanced oxidative stress.