LLukas22/scidocs huggingface dataset:
Effect of nanofiller’s size and shape on the solid state microstructure and thermal properties of poly(butylene succinate) nanocomposites

Abstract We report a study of the solid state microstructure and crystallization kinetics of poly(butylene succinate) (PBSu) reinforced with nanofillers of different shapes, sizes and geometries such as silver, silica (SiO 2 ), multi-walled carbon nanotubes (MWCNTs) and graphene oxide (GO). The solid state structure of neat polymer and nanocomposites were investigated by X-ray diffraction (XRD), polarized optical microscopy (POM) and transmission electron microscopy (TEM). The results indicated that the nanocomposite samples exhibited enhanced crystallinity and nucleation density, along with smaller spherulite size. Additionally, the spherical nanofillers were dispersed more uniformly in the polymeric matrix, than the other two filler types. The crystallization kinetics under both isothermal and dynamic conditions were also studied and as was expected, the nanocomposite samples, crystallize at higher rates due to the increased number of nucleation sites, as was calculated with Avrami, Dobreva and Friedman’s methods. From the crystallization study it was found that the nanocomposite filled with Ag nanoparticles exhibited the highest rates from all other fillers followed from SiO 2 and MWCNTs while GO showed the lowest rates.
A Survey of Dimension Reduction Methods for High-dimensional Data Analysis and Visualization

Dimension reduction is commonly defined as the process of mapping high-dimensional data to a lower-dimensional embedding. Applications of dimension reduction include, but are not limited to, filtering, compression, regression, classification, feature analysis, and visualization. We review methods that compute a point-based visual representation of high-dimensional data sets to aid in exploratory data analysis. The aim is not to be exhaustive but to provide an overview of basic approaches, as well as to review select state-of-the-art methods. Our survey paper is an introduction to dimension reduction from a visualization point of view. Subsequently, a comparison of state-of-the-art methods outlines relations and shared research foci. 1998 ACM Subject Classification G.3 Multivariate Statistics; I.2.6 Learning; G.1.2 Approximation
Execution Anomaly Detection in Distributed Systems through Unstructured Log Analysis

Detection of execution anomalies is very important for the maintenance, development, and performance refinement of large scale distributed systems. Execution anomalies include both work flow errors and low performance problems. People often use system logs produced by distributed systems for troubleshooting and problem diagnosis. However, manually inspecting system logs to detect anomalies is unfeasible due to the increasing scale and complexity of distributed systems. Therefore, there is a great demand for automatic anomalies detection techniques based on log analysis. In this paper, we propose an unstructured log analysis technique for anomalies detection. In the technique, we propose a novel algorithm to convert free form text messages in log files to log keys without heavily relying on application specific knowledge. The log keys correspond to the log-print statements in the source code which can provide cues of system execution behavior. After converting log messages to log keys, we learn a Finite State Automaton (FSA) from training log sequences to present the normal work flow for each system component. At the same time, a performance measurement model is learned to characterize the normal execution performance based on the log mes-sages’ timing information. With these learned models, we can automatically detect anomalies in newly input log files. Experiments on Hadoop and SILK show that the technique can effectively detect running anomalies.
Principal component analysis for clustering gene expression data

MOTIVATION
There is a great need to develop analytical methodology to analyze and to exploit the information contained in gene expression data. Because of the large number of genes and the complexity of biological networks, clustering is a useful exploratory technique for analysis of gene expression data. Other classical techniques, such as principal component analysis (PCA), have also been applied to analyze gene expression data. Using different data analysis techniques and different clustering algorithms to analyze the same data set can lead to very different conclusions. Our goal is to study the effectiveness of principal components (PCs) in capturing cluster structure. Specifically, using both real and synthetic gene expression data sets, we compared the quality of clusters obtained from the original data to the quality of clusters obtained after projecting onto subsets of the principal component axes.


RESULTS
Our empirical study showed that clustering with the PCs instead of the original variables does not necessarily improve, and often degrades, cluster quality. In particular, the first few PCs (which contain most of the variation in the data) do not necessarily capture most of the cluster structure. We also showed that clustering with PCs has different impact on different algorithms and different similarity metrics. Overall, we would not recommend PCA before clustering except in special circumstances.
Vacuum assisted closure: recommendations for use. A consensus document.

FOREWORD This timely initiative draws on both the research evidence and the consensus opinion of an international group of experts (see below) to provide guidance on the successful integration of vacuum assisted closure therapy (V.A.C. ® Therapy) into clinical practice. The document specifically reviews its potential use in the following selected indications*: diabetic foot ulcers, complex leg ulcers, pressure ulcers, dehisced sternal wounds, open abdominal wounds and traumatic wounds. In addition, it considers quality of life and cost-effectiveness, both of which are gaining importance when evaluating treatment. This document highlights questions for future research and is designed to be practical and adaptable for local use in countries worldwide. Supported by an unrestricted educational grant from KCI Europe Holding BV. The views expressed in this document do not necessarily reflect those of KCI. * This document provides recommendations for the use of VAC therapy in six selected wound types. It should be noted, however, that VAC therapy has a role in other wound types, which are not included in this document. Vacuum assisted closure (VAC) therapy has helped to improve wound care outcomes and has led to a number of dramatic changes in clinical practice over the past decade 1,2. VAC therapy must be used as part of an individualised, comprehensive treatment plan and is indicated for both acute and chronic wounds. PLANNING TREATMENT In all situations the underlying wound aetiology and comorbidities must first be addressed and treated. It is essential to optimise all aspects of the patient's physical, nutritional and psychosocial wellbeing to ensure treatment is suitable and of maximum benefit. Before starting VAC therapy it is important to define treatment aims, objectives and clinical endpoints 1. In some circumstances the objective will be to avoid further complications and to control symptoms, rather than to influence time to healing. Examples of clinical endpoints for VAC therapy include 50% volume reduction 3 , 80% granulation tissue formation or complete closure. In general, the key aims are to: ■ remove exudate and reduce periwound oedema ■ increase local microvascular blood flow/test vascularity ■ promote formation of granulation tissue ■ reduce complexity/size of the wound ■ optimise the wound bed prior to and following surgery ■ reduce complexity of surgical wound closure procedures 4. In addition, the application of the VAC dressing system creates a closed, moist wound environment, which may act as a barrier to bacteria and patient/caregiver interference. VAC therapy …
How users' Internet experience affects the adoption of mobile payment: a mediation model

Mobile payment becomes a convenient way to complete transactions due to the increasing popularity of mobile devices and the maturity of related technologies. Users’ experience of using computers and the Internet in financial activities largely affects their intention to use mobile payment. Combining the Technology Acceptance Model and Innovation Diffusion Theory, we examined the mediating effect of five factors, that is, perceived usefulness, perceived ease of use, compatibility, risk, and privacy concern, in the relationship between Internet experience and the adoption of mobile payment. Data from 922 mobile users supported the partial mediating effects of the five factors. ARTICLE HISTORY Received 6 March 2016 Revised 24 December 2016 Accepted 15 February 2017
Strategies and opportunities to STOP colon cancer in priority populations: pragmatic pilot study design and outcomes

Colorectal-cancer is a leading cause of cancer death in the United States, and Latinos have particularly low rates of screening. Strategies and Opportunities to STOP Colon Cancer in Priority Populations (STOP CRC) is a partnership among two research institutions and a network of safety net clinics to promote colorectal cancer screening among populations served by these clinics. This paper reports on results of a pilot study conducted in a safety net organization that serves primarily Latinos. The study assessed two clinic-based approaches to raise rates of colorectal-cancer screening among selected age-eligible patients not up-to-date with colorectal-cancer screening guidelines. One clinic each was assigned to: (1) an automated data-driven Electronic Health Record (EHR)-embedded program for mailing Fecal Immunochemical Test (FIT) kits (Auto Intervention); or (2) a higher-intensity program consisting of a mailed FIT kit plus linguistically and culturally tailored interventions delivered at the clinic level (Auto Plus Intervention). A third clinic within the safety-net organization was selected to serve as a passive control (Usual Care). Two simple measurements of feasibility were: 1) ability to use real-time EHR data to identify patients eligible for each intervention step, and 2) ability to offer affordable testing and follow-up care for uninsured patients. The study was successful at both measurements of feasibility. A total of 112 patients in the Auto clinic and 101 in the Auto Plus clinic met study inclusion criteria and were mailed an introductory letter. Reach was high for the mailed component (92.5% of kits were successfully mailed), and moderate for the telephone component (53% of calls were successful completed). After exclusions for invalid address and other factors, 206 (109 in the Auto clinic and 97 in the Auto Plus clinic) were mailed a FIT kit. At 6 months, fecal test completion rates were higher in the Auto (39.3%) and Auto Plus (36.6%) clinics compared to the usual-care clinic (1.1%). Findings showed that the trial interventions delivered in a safety-net setting were both feasible and raised rates of colorectal-cancer screening, compared to usual care. Findings from this pilot will inform a larger pragmatic study involving multiple clinics. ClinicalTrial.gov: NCT01742065
Biomechanical evaluation of dental implants with different surfaces: Removal torque and resonance frequency analysis in rabbits

STATEMENT OF PROBLEM
Macroscopic and especially microscopic properties of implant surfaces play a major role in the osseous healing of dental implants. Dental implants with modified surfaces have shown stronger osseointegration than implants which are only turned (machined). Advanced surface modification techniques such as anodic oxidation and Ca-P application have been developed to achieve faster and stronger bonding between the host bone and the implant.


PURPOSE
The purpose of this study was to investigate the effect of surface treatment of titanium dental implant on implant stability after insertion using the rabbit tibia model.


MATERIAL AND METHODS
THREE TEST GROUPS WERE PREPARED: sandblasted, large-grit and acid-etched (SLA) implants, anodic oxidized implants, and anodized implants with Ca-P immersion. The turned implants served as control. Twenty rabbits received 80 implants in the tibia. Resonance frequencies were measured at the time of implant insertion, 2 weeks and 4 weeks of healing. Removal torque values (RTV) were measured 2 and 4 weeks after insertion.


RESULTS
The implant stability quotient (ISQ) values of implants for resonance frequency analysis (RFA) increased significantly (P < .05) during 2 weeks of healing period although there were no significant differences among the test and control groups (P > .05). The test and control implants also showed significantly higher ISQ values during 4 weeks of healing period (P < .05). No significant differences, however, were found among all the groups. All the groups showed no significant differences in ISQ values between 2 and 4 weeks after implant insertion (P > .05). The SLA, anodized and Ca-P immersed implants showed higher RTVs at 2 and 4 weeks of healing than the machined one (P < .05). However, there was no significant difference among the experimental groups.


CONCLUSION
The surface-modified implants appear to provide superior implant stability to the turned one. Under the limitation of this study, however, we suggest that neither anodic oxidation nor Ca-P immersion techniques have any advantage over the conventional SLA technique with respect to implant stability.
Individualized Risk Estimation for Postoperative Complications After Surgery for Oral Cavity Cancer.

IMPORTANCE
Postoperative complications after head and neck surgery carry the potential for significant morbidity. Estimating the risk of complications in an individual patient is challenging.


OBJECTIVE
To develop a statistical tool capable of predicting an individual patient's risk of developing a major complication after surgery for oral cavity squamous cell carcinoma.


DESIGN, SETTING, AND PARTICIPANTS
Retrospective case series derived from an institutional clinical oncologic database, augmented by medical record abstraction, at an academic tertiary care cancer center. Participants were 506 previously untreated adult patients with biopsy-proven oral cavity squamous cell carcinoma who underwent surgery between January 1, 2007, and December 31, 2012.


MAIN OUTCOMES AND MEASURES
The primary end point was a major postoperative complication requiring invasive intervention (Clavien-Dindo classification grades III-V). Patients treated between January 1, 2007, and December 31, 2008 (354 of 506 [70.0%]) comprised the modeling cohort and were used to develop a nomogram to predict the risk of developing the primary end point. Univariable analysis and correlation analysis were used to prescreen 36 potential predictors for incorporation in the subsequent multivariable logistic regression analysis. The variables with the highest predictive value were identified with the step-down model reduction method and included in the nomogram. Patients treated between January 1, 2007, and December 31, 2008 (152 of 506 [30.0%]) were used to validate the nomogram.


RESULTS
Clinical characteristics were similar between the 2 cohorts for most comparisons. Thirty-six patients in the modeling cohort (10.2%) and 16 patients in the validation cohort (10.5%) developed a major postoperative complication. The 6 preoperative variables with the highest individual predictive value were incorporated within the nomogram, including body mass index, comorbidity status, preoperative white blood cell count, preoperative hematocrit, planned neck dissection, and planned tracheotomy. The nomogram predicted a major complication with a validated concordance index of 0.79. Inclusion of surgical operative variables in the nomogram maintained predictive accuracy (concordance index, 0.77).


CONCLUSIONS AND RELEVANCE
A statistical tool was developed that accurately estimates an individual patient's risk of developing a major complication after surgery for oral cavity squamous cell carcinoma.
Long-term treatment with antipsychotic drugs in conventional doses prolonged QTc dispersion, but did not increase ventricular tachyarrhythmias in patients with schizophrenia in the absence of cardiac disease

Objective: The aim of this study was to examine the hypothesis that long-term treatment with antipsychotic drugs in conventional doses prolongs QTc dispersion and increases ventricular tachyarrhythmias in patients with schizophrenia in the absence of cardiac disease. Methods: We measured QTc and QTc dispersion and ventricular tachyarrhythmias in 64 patients with schizophrenia, including 59 patients who received psychiatric medications, and five patients who did not receive psychiatric medications, and 45 healthy volunteers. None of the subjects had a history of cardiac disease or showed any abnormality in chest radiograph and transthoracic echocardiographic studies. None of the subjects had electrolyte abnormality. None of the subjects were taking drugs known to influence the QT interval, other than psychiatric medications. Results: QTc and QTc dispersion were significantly (P < 0.017) increased in patients who received psychiatric medications compared with patients who did not receive psychiatric medications, or with healthy volunteers [QTc: 0.442 (0.029), 0.418 (0.029), 0.417 (0.028) s, QTc dispersion: 0.054 (0.013), 0.038 (0.017), 0.038 (0.009) s]. Daily ventricular premature beats were 183 (689), 77 (23), and 86 (149), respectively. No ventricular tachycardia was observed. There were no correlation between QTc and QTc dispersion and ventricular premature beats. Conclusion: Long-term treatment with antipsychotic drugs in conventional doses prolonged both QTc and QTc dispersion in patients with schizophrenia, but did not increase ventricular tachyarrhythmias in patients with schizophrenia in the absence of cardiac disease. However, despite the negative findings, ventricular tachyarrhythmias may occur as a rare side-effect of antipsychotic drugs, particularly if a patient has additional risk factors.
Adaptive mechanically controlled lubrication mechanism found in articular joints.

Articular cartilage is a highly efficacious water-based tribological system that is optimized to provide low friction and wear protection at both low and high loads (pressures) and sliding velocities that must last over a lifetime. Although many different lubrication mechanisms have been proposed, it is becoming increasingly apparent that the tribological performance of cartilage cannot be attributed to a single mechanism acting alone but on the synergistic action of multiple "modes" of lubrication that are adapted to provide optimum lubrication as the normal loads, shear stresses, and rates change. Hyaluronic acid (HA) is abundant in cartilage and synovial fluid and widely thought to play a principal role in joint lubrication although this role remains unclear. HA is also known to complex readily with the glycoprotein lubricin (LUB) to form a cross-linked network that has also been shown to be critical to the wear prevention mechanism of joints. Friction experiments on porcine cartilage using the surface forces apparatus, and enzymatic digestion, reveal an "adaptive" role for an HA-LUB complex whereby, under compression, nominally free HA diffusing out of the cartilage becomes mechanically, i.e., physically, trapped at the interface by the increasingly constricted collagen pore network. The mechanically trapped HA-LUB complex now acts as an effective (chemically bound) "boundary lubricant"--reducing the friction force slightly but, more importantly, eliminating wear damage to the rubbing/shearing surfaces. This paper focuses on the contribution of HA in cartilage lubrication; however, the system as a whole requires both HA and LUB to function optimally under all conditions.
Physiological responses to humic substances as plant growth promoter

Humic substances (HS) have been widely recognized as a plant growth promoter mainly by changes on root architecture and growth dynamics, which result in increased root size, branching and/or greater density of root hair with larger surface area. Stimulation of the H+-ATPase activity in cell membrane suggests that modifications brought about by HS are not only restricted to root structure, but are also extended to the major biochemical pathways since the driving force for most nutrient uptake is the electrochemical gradient across the plasma membrane. Changes on root exudation profile, as well as primary and secondary metabolism were also observed, though strongly dependent on environment conditions, type of plant and its ontogeny. Proteomics and genomic approaches with diverse plant species subjected to HS treatment had often shown controversial patterns of protein and gene expression. This is a clear indication that HS effects of plants are complex and involve non-linear, cross-interrelated and dynamic processes that need be treated with an interdisciplinary view. Being the humic associations recalcitrant to microbiological attack, their use as vehicle to introduce beneficial selected microorganisms to crops has been proposed. This represents a perspective for a sort of new biofertilizer designed for a sustainable agriculture, whereby plants treated with HS become more susceptible to interact with bioinoculants, while HS may concomitantly modify the structure/activity of the microbial community in the rhizosphere compartment. An enhanced knowledge of the effects on plants physiology and biochemistry and interaction with rhizosphere and endophytic microbes should lead to achieve increased crop productivity through a better use of HS inputs in Agriculture.
Explaining Self-Explaining: A Contrast between Content and Generation

Self-explaining has been repeatedly shown to result in positive learning outcomes for students in a wide variety of disciplines. However, there are two potential accounts for why self-explaining works. First, those who self-explain experience more content than those who do not. Second, there are differences in the activity of generating the explanations versus merely comprehending them. To compare these two accounts, the present in vivo classroom study, conducted in the PSLC physics LearnLab, attempted to contrast robust learning from generating explanations with the actively of studying instructional explanations. The students’ learning activities (self-explaining vs. paraphrasing) were crossed with the completeness of the examples they studied (complete vs. incomplete). During a classroom period on electrodynamics, students alternated between solving problems and studying examples. On these problems, the self-explainers made fewer errors and asked for less help than paraphrasers. On homework problems done many days later, self-explainers displayed evidence of far transfer in a related, yet new domain (i.e., magnetism). In conclusion, prompting students to selfexplain while studying examples, in an authentic classroom environment, can result in positive nearand long-term learning.
Fixed abrasive diamond wire machining—part II: experiment design and results

Experimental results from fixed abrasive diamond wire machining of wood and foam ceramics are presented. Three types of wood—pine, oak, and fir, and three types of foam ceramic—silicon carbide, zirconia, and zirconia toughened alumina, are tested. The research investigates the life of diamond wire and effects of process parameters on the cutting forces, force ratio, and surface roughness. A scanning electron microscope is used to study the worn diamond wire, machined surfaces, and debris. The diamond wire saw is demonstrated to be very effective in machining foam ceramics. The wire life for cutting wood at slow feed rates is low. The short tool life for dry cutting of wood indicates that more research in new fixed abrasive diamond wire and wire saw machining technologies is necessary.  2003 Published by Elsevier Science Ltd.