LLukas22/scidocs huggingface dataset:
Using the Multiple Sclerosis Impact Scale to estimate health state utility values: mapping from the MSIS-29, version 2, to the EQ-5D and the SF-6D.

OBJECTIVES
The 29-item Multiple Sclerosis Impact Scale (MSIS-29) is a psychometrically validated patient-reported outcome measure increasingly used in trials of treatments for multiple sclerosis. However, it is non-preference-based and not amenable for use across policy decision-making contexts. Our objective was to statistically map from the MSIS-29, version 2, to the EuroQol five-dimension (EQ-5D) and the six-dimension health state short form (derived from short form 36 health survey) (SF-6D) to estimate algorithms for use in cost-effectiveness analyses.


METHODS
The relationships between MSIS-29, version 2, and EQ-5D and SF-6D scores were estimated by using data from a cohort of people with multiple sclerosis in South West England (n=672). Six ordinary least squares (OLS), Tobit, and censored least adjusted deviation (CLAD) regression analyses were conducted on estimation samples, including the use of subscale and item scores, squared and interaction terms, and demographics. Algorithms from models with the smallest estimation errors (mean absolute error [MAE], root mean square error [RMSE], normalized RMSE) were then assessed by using separate validation samples.


RESULTS
Tobit and CLAD. For the EQ-5D, the OLS models including subscale squared terms, and item scores and demographics performed comparably (MAE 0.147, RMSE 0.202 and MAE 0.147, RMSE 0.203, respectively), and estimated scores well up to 3 years post-baseline. Estimation errors for the SF-6D were smaller (OLS model including squared terms: MAE 0.058, RMSE 0.073; OLS model using item scores and demographics: MAE 0.059, RMSE 0.08), and the errors for poorer health states found with the EQ-5D were less pronounced.


CONCLUSIONS
We have provided algorithms for the estimation of health state utility values, both the EQ-5D and SF-6D, from scores on the MSIS-29, version 2. Further research is now needed to determine how these algorithms perform in practical decision-making contexts, when compared with observed EQ-5D and SF-6D values.
OpenMusic: visual programming environment for music composition, analysis and research

OpenMusic is an open source environment dedicated to music composition. The core of this environment is a full-featured visual programming language based on Common Lisp and CLOS (Common Lisp Object System) allowing to design processes for the generation or manipulation of musical material. This language can also be used for general purpose visual programming and other (possibly extra-musical) applications.
Most patients with minimal histological residuals of gastric MALT lymphoma after successful eradication of Helicobacter pylori can be managed safely by a watch and wait strategy: experience from a large international series.

BACKGROUND
Eradication of Helicobacter pylori is the established initial treatment of stage I MALT (mucosa associated lymphoid tissue) lymphoma. Patients with minimal persisting lymphoma infiltrates after successful eradication of H pylori are considered treatment failures and referred for radiation, chemotherapy, immunotherapy, or surgery.


AIM
To report a watch and wait strategy in such patients.


METHODS
108 patients were selected from a larger series of patients treated at various European institutions. Their mean age was 51.6 years (25 to 82), and they were all diagnosed as having gastric marginal zone B cell lymphoma of MALT type stage I. After successful H pylori eradication and normalisation of the endoscopic findings, lymphoma infiltrates were still present histologically at 12 months (minimal histological residuals). No oncological treatment was given but the patients had regular follow up with endoscopies and multiple biopsies.


FINDINGS
Based on a follow up of 42.2 months (2-144), 102 patients (94%) had a favourable disease course. Of these, 35 (32%) went into complete remission. In 67 (62%) the minimal histological residuals remained stable and no changes became evident. Local lymphoma progression was seen in four patients (5%), and one patient developed a high grade lymphoma.


CONCLUSIONS
Most patients with minimal histological residuals of gastric MALT lymphoma after successful eradication of H pylori had a favourable disease course without oncological treatment. A watch and wait strategy with regular endoscopies and biopsies appears to be safe and may become the approach of choice in this situation. Longer follow up is needed to establish this definitively.
Mining Techniques and its Applications in Banking Sector

Data mining is becoming strategically important area for many business organizations including banking sector. It is a process of analyzing the data from various perspectives and summarizing it into valuable information. Data mining assists the banks to look for hidden pattern in a group and discover unknown relationship in the data. Today, customers have so many opinions with regard to where they can choose to do their business. Early data analysis techniques were oriented toward extracting quantitative and statistical data characteristics. These techniques facilitate useful data interpretations for the banking sector to avoid customer attrition. Customer retention is the most important factor to be analyzed in today’s competitive business environment. And also fraud is a significant problem in banking sector. Detecting and preventing fraud is difficult, because fraudsters develop new schemes all the time, and the schemes grow more and more sophisticated to elude easy detection. This paper analyzes the data mining techniques and its applications in banking sector like fraud prevention and detection, customer retention, marketing and risk management. Keywords— Banking Sector, Customer Retention, Credit Approval, Data mining, Fraud Detection,
A Generic Model of Memristors With Parasitic Components

In this paper, a generic model of memristive systems, which can emulate the behavior of real memristive devices is proposed. Non-ideal pinched hysteresis loops are sometimes observed in real memristive devices. For example, the hysteresis loops may deviate from the origin over a broad range of amplitude A and frequency f of the input signal. This deviation from the ideal case is often caused by parasitic circuit elements exhibited by real memristive devices. In this paper, we propose a generic memristive circuit model by adding four parasitic circuit elements, namely, a small capacitance, a small inductance, a small DC current source, and a small DC voltage source, to the memristive device. The adequacy of this model is verified experimentally and numerically with two thermistors (NTC and PTC) memristors.
Detection and Prevention of SQL Injection Attack : A Survey

SQL (structure query language) injection is one of threats to the applications, which are Web-based application, Mobile application and even desktop application, which are connected to the database. By implementing SQL injection, attacker can gain full access to the application or database so that it can remove or change significant data irresponsibly. Applications that do not properly validate the user’s input make them vulnerable against SQL injection. SQL Injection Attacks (SQLIA) occurs when an attacker is able to insert a series of malicious SQL statements into a ―query‖ through manipulating user input data for execution by the back-end database. Using this type of threats, applications could be hacked easily and steal the confidential data by the attacker. In this paper we present classical and modern types of SQLIA and display different existing technique and tools which are used to detect or prevent these attacks. Keywords— SQL injection, Database security, PDO, Web application, SQLite.
Effects of a music therapy group intervention on enhancing social skills in children with autism.

BACKGROUND
Research indicates that music therapy can improve social behaviors and joint attention in children with Autism Spectrum Disorder (ASD); however, more research on the use of music therapy interventions for social skills is needed to determine the impact of group music therapy.


OBJECTIVE
To examine the effects of a music therapy group intervention on eye gaze, joint attention, and communication in children with ASD.


METHOD
Seventeen children, ages 6 to 9, with a diagnosis of ASD were randomly assigned to the music therapy group (MTG) or the no-music social skills group (SSG). Children participated in ten 50-minute group sessions over a period of 5 weeks. All group sessions were designed to target social skills. The Social Responsiveness Scale (SRS), the Autism Treatment Evaluation Checklist (ATEC), and video analysis of sessions were used to evaluate changes in social behavior.


RESULTS
There were significant between-group differences for joint attention with peers and eye gaze towards persons, with participants in the MTG demonstrating greater gains. There were no significant between-group differences for initiation of communication, response to communication, or social withdraw/behaviors. There was a significant interaction between time and group for SRS scores, with improvements for the MTG but not the SSG. Scores on the ATEC did not differ over time between the MTG and SSG.


CONCLUSIONS
The results of this study support further research on the use of music therapy group interventions for social skills in children with ASD. Statistical results demonstrate initial support for the use of music therapy social groups to develop joint attention.
Glucometer use and glycemic control among Hispanic patients with diabetes in southern Florida.

BACKGROUND
Self-monitoring of blood glucose (SMBG) has been deemed a critical component of diabetes care in the United States. To be effective, patients must have some diabetes knowledge, glucometer proficiency, and an ability to take appropriate actions when certain readings are obtained. However, most patients take no action in response to out-of-range glucometer readings, and in many populations, SMBG practices are not associated with improved glycemic control. Thus, SMBG utilization is being reconsidered in other countries. Nonetheless, SMBG behaviors are increasingly recommended in the United States, where the Hispanic population represents the fastest-growing minority group and is disproportionately affected by suboptimal diabetes outcomes. Because a growing number of interventions aim to reduce diabetes disparities by improving glycemic control among minorities, it is essential to determine whether efforts should focus on SMBG practices. We present data on SMBG behaviors and glycemic control among participants from the Miami Healthy Heart Initiative (MHHI), a National Institutes of Health/National Heart, Lung, and Blood Institute-sponsored trial assessing a community health worker (CHW) intervention among Hispanic patients with poorly controlled diabetes.


OBJECTIVE
This study examined the effects of a CHW intervention on SMBG practices, glycosylated hemoglobin (HbA1c), and knowledge of appropriate responses to glucometer readings among Hispanic patients with diabetes.


METHODS
This study was an ancillary investigation within MHHI, a randomized, controlled trial in 300 Hispanic patients. Participants were intervention-group members who received 12 months of CHW support. Assessments were administered at baseline and poststudy to determine potential barriers to optimal health. Items from validated instruments were used to determine knowledge of appropriate responses to different glucose readings. These data were linked to HbA1c values. Means and frequencies were used to describe population characteristics and glucometer proficiency. Paired-sample t tests examined potential differences in HbA1c outcomes and SMBG practices. Qualitative data were collected from the CHWs who worked with study participants.


RESULTS
Our population was diverse, representing several countries. Mean HbA1c improved significantly, from 10% to 8.8% (P ≤ 0.001). SMBG practices did not change. At baseline, 96% of patients reported owning a glucometer and 94% reported knowing how to use it. However, quantitative assessments and qualitative data suggested that participants had suboptimal knowledge regarding actions that could cause an out-of-range reading or how to respond to certain readings.


CONCLUSIONS
SMBG behaviors were not associated with glycemic control in our sample. We conclude that a CHW intervention may improve glycemic control without improving SMBG practices. Future interventions may reconsider whether efforts should be directed toward improving SMBG behaviors.
Clinical outcomes from the use of Medication Report when elderly patients are discharged from hospital

Objective The objective of this study was to investigate whether a Medication Report also can reduce the number of patients with clinical outcomes due to medication errors. Method A prospective intervention study with retrospective controls on patients at three departments at Lund University Hospital, Sweden that where transferred to primary care. The intervention group, where patients received a Medication Report at discharge, was compared with a control group with patients of the same age, who were not given a Medication Report when discharged from the same ward one year earlier. For patients with at least one medication error all contacts with hospital or primary care within 3 months after discharge were identified. For each contact it was evaluated whether this was caused by the medication error. We also compared medication errors that have been evaluated as high or moderate clinical risk with medication errors without clinical risk. Main outcome measures Need for medical care in hospital or primary care within three months after discharge from hospital. Medical care is readmission to hospital as well as visits of study population to primary and out-patient secondary health care. Results The use of Medication Report reduced the need for medical care due to medication errors. Of the patients with Medication Report 11 out of 248 (4.4%) needed medical care because of medication errors compared with 16 out of 179 (8.9%) of patients without Medication Report (p = 0.049). The use of a Medication Report significantly reduced the risk of any consequences due to medication errors, p = 0.0052. These consequences included probable and possible care due to medication error as well as administrative procedures (corrections) made by physicians in hospital or primary care. Conclusions The Medication Report seems to be an effective tool to decrease adverse clinical consequences when elderly patients are discharged from hospital care.
Active airborne localisation and exploration in unknown environments using inertial SLAM

Future unmanned aerial vehicle (UAV) applications will require high-accuracy localisation in environments in which navigation infrastructure such as the Global Positioning System (GPS) and prior terrain maps may be unavailable or unreliable. In these applications, long-term operation requires the vehicle to build up a spatial map of the environment while simultaneously localising itself within the map, a task known as simultaneous localisation and mapping (SLAM). In the first part of this paper we present an architecture for performing inertial-sensor based SLAM on an aerial vehicle. We demonstrate an on-line path planning scheme that intelligently plans the vehicle's trajectory while exploring unknown terrain in order to maximise the quality of both the resulting SLAM map and localisation estimates necessary for the autonomous control of the UAV. Two important performance properties and their relationship to the dynamic motion and path planning systems on-board the UAV are analysed. Firstly we analyse information-based measures such as entropy. Secondly we perform an observability analysis of inertial SLAM by recasting the algorithms into an indirect error model form. Qualitative knowledge gained from the observability analysis is used to assist in the design of an information-based trajectory planner for the UAV. Results of the online path planning algorithm are presented using a high-fidelity 6-DoF simulation of a UAV during a simulated navigation and mapping task
Differences in task demands influence the hemispheric lateralization and neural correlates of metaphor

This study investigated metaphor comprehension in the broader context of task-difference effects and manipulation of processing difficulty. We predicted that right hemisphere recruitment would show greater specificity to processing difficulty rather than metaphor comprehension. Previous metaphor processing studies have established that the left inferior frontal gyrus strongly correlates with metaphor comprehension but there has been controversy about whether right hemisphere (RH) involvement is specific for metaphor comprehension. Functional MRI data were recorded from healthy subjects who read novel metaphors, conventional metaphors, definition-like sentences, or literal sentences. We investigated metaphor processing in contexts where semantic judgment or imagery modulates linguistic judgment. Our findings support the position that the type of task rather than figurative language processing per se modulates the left inferior gyrus (LIFG). RH involvement was more influenced by processing difficulty and less by the novelty or figurativity of linguistic expressions. Our results suggest that figurative language processing depends upon the effects of task-type and processing difficulty on imaging results.
Gigantomastia due to retromammary lipoma: An aesthetic management.

INTRODUCTION
A "giant" lipoma is defined as a tumor having dimensions greater than 10 cm. Giant lipomas are rare and giant breast lipomas are exceptionally uncommon. Only six cases have been described in world literature till date. Herein we describe a case of giant breast lipoma and discuss its surgical management.


CASE REPORT
A 43-year-old lady presented with left sided unilateral gigantomastia. Clinical examination, radiology and histopathology diagnosed lipoma. Excision of the tumor was planned, together with correction of the breast deformity by reduction mammoplasty using McKissok technique. A tumor measuring 19 cm × 16 cm × 10 cm and weighing 1647 grams was removed. The nipple areola complex was set by infolding of the vertical pedicles and the lateral and medial flaps were approximated to create the final breast contour. The patient is doing well on follow up.


DISCUSSION
Giant lipomas are rare and of them, giant breast lipomas are extremely uncommon. They can grow to immense proportions and cause significant aesthetic and functional problems. The treatment is excision. But reconstruction of the breast is almost always necessary to achieve a symmetric breast in terms of volume, shape, projection and nipple areola complex symmetry compared to the normal opposite breast. Few authors have used various mammoplasty techniques for reconstruction of the breast after giant lipoma excision. Our case has the following unique features: (i) It is the third largest breast lipoma described in the literature till date, weighing 1647 grams; (ii) The Mckissock technique has been used for parenchymal reshaping which has not been previously described for giant breast lipoma.


CONCLUSION
This case demonstrates that reduction mammoplasty after giant lipoma removal is highly rewarding, resulting in a smaller-sized breast that is aesthetically more pleasing, has better symmetry with the contralateral breast, and provides relief from functional mass deficit.
Artificial bee colony programming for symbolic regression

Artificial bee colony algorithm simulating the intelligent foraging behavior of honey bee swarms is one of the most popular swarm based optimization algorithms. It has been introduced in 2005 and applied in several fields to solve different problems up to date. In this paper, an artificial bee colony algorithm, called as Artificial Bee Colony Programming (ABCP), is described for the first time as a new method on symbolic regression which is a very important practical problem. Symbolic regression is a process of obtaining a mathematical model using given finite sampling of values of independent variables and associated values of dependent variables. In this work, a set of symbolic regression benchmark problems are solved using artificial bee colony programming and then its performance is compared with the very well-known method evolving computer programs, genetic programming. The simulation results indicate that the proposed method is very feasible and robust on the considered test problems of symbolic regression. 2012 Elsevier Inc. All rights reserved.
The Knowledge Economy and Urban Economic Growth

In this paper we contribute to the longstanding discussion on the role of knowledge to economic growth in a spatial context. We observe that in adopting the European policy strategy towards a competitive knowledge economy, The Netherlands is – as most European countries mainly oriented towards industrial, technological factors. The policy focus is on R&D specialized regions in their spatial economic strategies. We place the knowledge economy in a broader perspective. Based on the knowledge economy literature, we value complementary indicators: the successful introduction of new products and services to the market (‘ innovation’ ) and indicators of skills of employees (‘knowledge workers’ ). Using econometric analysis, we relate the three factors ‘R&D’ , ‘ innovation’ and ‘knowledge workers’ to regional economic growth. We conclude that the factors ‘ innovation’ and ‘knowledge workers’ are more profoundly related to urban employment and productivity growth than the R&D-factor. Preferably, urban research and policymakers should therefore take all three knowledge factors into account when determining economic potentials of cities.
Evolutionary Ensemble for Stock Prediction

We propose a genetic ensemble of recurrent neural networks for stock prediction model. The genetic algorithm tunes neural networks in a two-dimensional and parallel framework. The ensemble makes the decision of buying or selling more conservative. It showed notable improvement on the average over not only the buy-and-hold strategy but also other traditional ensemble approaches.
Prediction of tool life in end milling of hardened steel AISI D2

Most published research works on the development of tool life model in machining of hardened steels have been mainly concerned with the turning process, whilst the milling process has received little attention due to the complexity of the process. Thus, the aim of present study is to develope a tool life model in end milling of hardened steel AISI D2 using PVD TiAlN coated carbide cutting tool. The hardness of AISI D2 tool lies within the range of 56-58 HRC. The independent variables or the primary machining parameters selected for this experiment were the cutting speed, feed, and depth of cut. First and second order models were developed using Response Surface Methodology (RSM). Experiments were conducted within specified ranges of the parameters. Design-Expert 6.0 software was used to develop the tool life equations as the predictive models. The predicted tool life results are presented in terms of both 1 and 2 order equations with the aid of a statistical design of experiment software called Design-Expert version 6.0. Analysis of variance (ANOVA) has indicated that both models are valid in predicting the tool life of the part machined under specified condition and the prediction of average error is less than 10%.