LLukas22/scidocs huggingface dataset:
Increased risk of dementia in people with previous exposure to general anesthesia: A nationwide population-based case–control study

BACKGROUND
Dementia, which leads to disability, is one of the important diseases occurring among older populations. However, the exact mechanism of the disease remains unknown. The potential risk factor of general anesthesia (GA) in the development of dementia is a controversial topic. Therefore, this study aimed to evaluate the association between previous exposure to different GA types and the incidence of dementia.


METHODS
Using the claims data of 1 million insured residents covered by Taiwan's universal health insurance from 2005 to 2009, 5345 newly diagnosed dementia patients older than 50 years were eligible for the study group. The control group, which consisted of 21,380 individuals without dementia, was matched for age, gender, and index date. GA was categorized into three subtypes: endotracheal tube intubation general anesthesia (ETGA), intravenous injection general anesthesia (IVGA) or intramuscular injection general anesthesia (IMGA), and heavy sedation. The multiple logistic regression model was used for analyses.


RESULTS
Individuals exposed to surgery under ETGA (odds ratio [OR], 1.34; 95% confidence interval [CI], 1.25-1.44) and those exposed to surgery under IVGA or IMGA (OR, 1.28; 95% CI, 1.14-1.43) were at significantly higher risk of dementia in a dose-response relationship (P < .0001), whereas surgery under heavy sedation was not associated with increased risk of dementia (OR, 1.04; 95% CI, 0.68-1.59). The dementia risk for subjects with diabetes mellitus who received surgery under ETGA (OR, 1.59; 95% CI, 1.42-1.78), hypertension (OR, 1.98; 95% CI, 1.78-2.21), atherosclerosis (OR, 1.35; 95% CI, 1.22-1.50), or after having experienced a stroke (OR, 3.52; 95% CI, 3.13-3.97), but no interaction was found between surgery under ETGA and depression for the risk of dementia.


CONCLUSIONS
A history of previous exposure to surgery under GA might be associated with an increased risk of dementia, particularly in subjects who have undergone repeated exposure to GA. In addition, subjects who had received surgery under ETGA with comorbidities such as stroke, hypertension, diabetes mellitus, and atherosclerosis could have a potential relationship with dementia risk.
Churn Prediction in Social Networks

With the high speed development of online social networks, mobile devices and wireless technologies in the social network systems are increasingly available. Many people are integrated with social networking sites such as Facebook, Twitter and LinkedIn in their daily lives. Social networks have become major source of news, along with the traditional information propagation mediums such as television and newspapers. In social networks influence takes place in the form of “word-ofmouth”. Customer churn take place due to the termination of contract or the customer move to the other service providers. It is fundamental issue to find a subset of most influential nodes (i.e. the customers) that are going to churn. By concentrating on these influential nodes initially we can restrict the churning of customers early. These influential nodes are nothing but existing customers which are using the service provided by the company. The customers are terminating the contract due to unsatisfactory service or they are moving to other service providers due to influence from others. Keywords— Churn prediction, influence, Social Networks, Customer Churn, and Rumor International Journal of Engineering Research & Technology (IJERT)
Etanercept and sulfasalazine, alone and combined, in patients with active rheumatoid arthritis despite receiving sulfasalazine: a double-blind comparison.

OBJECTIVE
To compare the efficacy and safety of etanercept and sulfasalazine, alone and in combination, in patients with active rheumatoid arthritis despite sulfasalazine treatment.


METHODS
A double-blind, randomised study in adult patients with active rheumatoid arthritis despite stable sulfasalazine (2-3 g/day) treatment. The primary end point was a 20% response by the American College of Rheumatology (ACR) criteria at 24 weeks.


RESULTS
At baseline, the three treatment groups (sulfasalazine, n = 50; etanercept, n = 103; etanercept and sulfasalazine, n = 101) were comparable for demographic variables and disease activity. Lack of efficacy was the primary reason for discontinuation (sulfasalazine, n = 12; etanercept, n = 1; etanercept and sulfasalazine, n = 4; p<0.001). Significantly more patients receiving etanercept, alone or in combination (74% for each), achieved ACR 20 responses at 24 weeks than those receiving sulfasalazine (28%; p<0.01). Similarly, more patients in the etanercept groups achieved ACR 50 and ACR 70 responses than those in the sulfasalazine group (p<0.01). In the groups receiving etanercept, significant differences in the ACR core components were observed by week 2 compared with those receiving sulfasalazine alone (p<0.01). The incidences of several common adverse events (headache, nausea, asthenia) were lower with etanercept alone than with the combination (p<0.05), but infections and injection site reactions were higher with etanercept alone (p<0.05). The safety profiles of both etanercept treatment groups were comparable with previous experience of etanercept.


CONCLUSIONS
For all efficacy variables assessed, etanercept alone or in combination with sulfasalazine resulted in substantial and similar improvement in disease activity from baseline to week 24 compared with sulfasalazine alone in patients with active rheumatoid arthritis despite their sulfasalazine treatment. All three treatments were generally well tolerated.
Calibration of PD Term Structures : To Be Markov Or Not To Be

Term structures of default probabilities are omnipresent in credit risk modeling: time-dynamic credit portfolio models, default times, and multi-year pricing models, they all need the time evolution of default probabilities as a basic model input. Although people tend to believe that from an economic point of view the Markov property as underlying model assumption is kind of questionable it seems to be common market practice to model PD term structures via Markov chain techniques. In this paper we illustrate that the Markov assumption carries us quite far if we allow for nonhomogeneous time behaviour of the Markov chain generating the PD term structures. As a ‘proof of concept’ we calibrate a nonhomogeneous continuous-time Markov chain (NHCTMC) to observed one-year rating migrations and multi-year default frequencies, hereby achieving convincing approximation quality. 1 Markov Chains in Credit Risk Modeling The probability of default (PD) for a client is a fundamental risk parameter in credit risk management. It is common practice to assign to every rating grade in a bank’s masterscale a one-year PD in line with regulatory requirements; see [1]. Table 1 shows an example for default frequencies assigned to rating grades from Standard and Poor’s (S&P). D AAA 0.00% AA 0.01% A 0.04% BBB 0.29% BB 1.28% B 6.24% CCC 32.35% Table 1: One-year default frequencies (D) assigned to S&P ratings; see [17], Table 9. Moreover, credit risk modeling concepts like dependent default times, multi-year credit pricing, and multi-horizon economic capital require more than just one-year PDs. For multi-year credit risk modeling, banks need a whole term structure (p R )t≥0 of (cumulative) PDs for every rating grade R; see, e.g., [2] for an introduction to PD term structures and [3] for their application to structured credit products. Every bank has its own (proprietary) way to calibrate PD term structures to bank-internal and external data. A look into the literature reveals that for the generation of PD term structures various Markov chain approaches, most often based on homogeneous chains, dominate current market practice. A landmarking paper in this direction is the work by Jarrow, Lando, and Turnbull [7]. Further research has been done by various authors, see, e.g., Kadam [8], Lando [10], Sarfaraz et al. [12], Schuermann and Jafry [14, 15], Trueck and Oezturkmen [18], just to mention a few examples. A new approach via Markov mixtures has been presented recently by Frydman and Schuermann [5]. In Markov chain theory (see [11]) one distinguishes between discrete-time and continuous-time chains. For instance, a discrete-time chain can be specified by a one-year migration or transition 1In the literature, PD term structures are sometimes called credit curves. 2A Markov chain is called homogeneous if transition probabilities do not depend on time.
A robust and scalable clustering algorithm for mixed type attributes in large database environment

Clustering is a widely used technique in data mining applications to discover patterns in the underlying data. Most traditional clustering algorithms are limited to handling datasets that contain either continuous or categorical attributes. However, datasets with mixed types of attributes are common in real life data mining problems. In this paper, we propose a distance measure that enables clustering data with both continuous and categorical attributes. This distance measure is derived from a probabilistic model that the distance between two clusters is equivalent to the decrease in log-likelihood function as a result of merging. Calculation of this measure is memory efficient as it depends only on the merging cluster pair and not on all the other clusters. Zhang et al [8] proposed a clustering method named BIRCH that is especially suitable for very large datasets. We develop a clustering algorithm using our distance measure based on the framework of BIRCH. Similar to BIRCH, our algorithm first performs a pre-clustering step by scanning the entire dataset and storing the dense regions of data records in terms of summary statistics. A hierarchical clustering algorithm is then applied to cluster the dense regions. Apart from the ability of handling mixed type of attributes, our algorithm differs from BIRCH in that we add a procedure that enables the algorithm to automatically determine the appropriate number of clusters and a new strategy of assigning cluster membership to noisy data. For data with mixed type of attributes, our experimental results confirm that the algorithm not only generates better quality clusters than the traditional k-means algorithms, but also exhibits good scalability properties and is able to identify the underlying number of clusters in the data correctly. The algorithm is implemented in the commercial data mining tool Clementine 6.0 which supports the PMML standard of data mining model deployment.
Learning about natural human-robot interaction styles

If we are to achieve natural human–robot interaction, we may need to complement current vision and speech interfaces. Touch may provide us with an extra tool in this quest. In this paper we demonstrate the role of touch in interaction between a robot and a human. We show how infrared sensors located on robots can be easily used to detect and distinguish human interaction, in this case interaction with individual children. This application of infrared sensors potentially has many uses; for example, in entertainment or service robotics. This system could also benefit therapy or rehabilitation, where the observation and recording of movement and interaction is important. In the long term, this technique might enable robots to adapt to individuals or individual types of user. c © 2006 Published by Elsevier B.V.
Cross-national comparison and validation of the Alzheimer's Disease Assessment Scale: results from the European Harmonization Project for Instruments in Dementia (EURO-HARPID).

BACKGROUND
The Alzheimer's Disease Assessment Scale (ADAS) is often used in international multicenter trials. Use across countries presupposes correct translation and adaptation of the scale, and maintenance of its psychometric properties.


OBJECTIVES
To compare the various translations of the ADAS used in Western Europe, to design internationally harmonized translations and to validate these.


SETTING
International cooperative study in eight European countries.


METHODS
An inventory was made of existing versions of the ADAS-Cog used in eight European countries, and adaptations were made. The concurrent validity of the harmonized versions of the ADAS was tested in 283 patients with probable or possible Alzheimer's disease. The Nurses Observation Scale for Geriatrics (NOSGER), CAMCOG-R and MMSE was used to assess concordance between cognitive and behavioral measures.


RESULTS
Differences between the versions mainly involved object naming, items for verbal memory, such as the number of trials allowed, the imagery value of the words selected as targets or distractors, and the number of parallel versions. These differences were eliminated by adapting and harmonizing the various versions of the ADAS-Cog. Thereafter, only small differences between the different countries were found, and patterns of correlation between ADAS-Cog, and the NOSGER, CAMCOG-R and MMSE were consistent.


CONCLUSIONS
The study underlines the need to use harmonized versions of instruments for rating dementia in multinational studies. The findings indicate that the harmonization of the ADAS-Cog was successful.
40 Inventive (Business) Principles With Examples

Interest in the possible applicability of TRIZ tools and techniques to the world of management and organisational innovation issues continues to grow. The aim of this article is to place the 40 Inventive Principles of TRIZ in the context of this business environment. The format of the article is based closely on an earlier text (1) in which examples of technical deployment of the Principles were given.
Measuring social class differences in cancer patient survival: is it necessary to control for social class differences in general population mortality? A Finnish population-based study.

STUDY OBJECTIVES
Estimation of cancer patient survival by social class has been performed using observed, corrected (cause specific), and relative (with expected survival based on the national population) survival rates. Each of these measures are potentially biased and the optimal method is to calculate relative survival rates using social class specific death rates to estimate expected survival. This study determined the degree to which the choice of survival measure affects the estimation of social class differences in cancer patient survival.


SETTING AND PARTICIPANTS
All Finnish residents diagnosed with at least one of 10 common malignant neoplasms during the period 1977-1985 were identified from the Finnish Cancer Registry and followed up for deaths to the end of 1992.


DESIGN
Survival rates were calculated by site, sex, and age at 5, 10, and 15 years subsequent to diagnosis for each of three measures of survival; relative survival, corrected (cause specific) survival, and relative survival adjusted for social class differences in general mortality. Regression models were fitted to each set of rates for the first five years of follow up.


MAIN RESULTS
The degree of variation in relative survival resulting from social class decreased, although did not disappear, after controlling for social class differences in general mortality. The results obtained using corrected survival were close to those obtained using relative survival with a social class correction. The differences between the three measures were largest when the proportion of deaths from other causes was large, for example, in cancers with high survival, among older patients, and for longer follow up times.


CONCLUSIONS
Although each of the three measures gave comparable results, it is recommended that relative survival rates are used with expected survival adjusted for social class when studying social class variation in cancer patient survival. If this is not an available option, it is recommended that corrected survival rates are used. Relative survival rates without the social class correction overestimate social class differences and should be used with caution.
Smartphones for Smarter Delivery of Mental Health Programs: A Systematic Review

BACKGROUND
The rapid growth in the use of mobile phone applications (apps) provides the opportunity to increase access to evidence-based mental health care.


OBJECTIVE
Our goal was to systematically review the research evidence supporting the efficacy of mental health apps for mobile devices (such as smartphones and tablets) for all ages.


METHODS
A comprehensive literature search (2008-2013) in MEDLINE, Embase, the Cochrane Central Register of Controlled Trials, PsycINFO, PsycTESTS, Compendex, and Inspec was conducted. We included trials that examined the effects of mental health apps (for depression, anxiety, substance use, sleep disturbances, suicidal behavior, self-harm, psychotic disorders, eating disorders, stress, and gambling) delivered on mobile devices with a pre- to posttest design or compared with a control group. The control group could consist of wait list, treatment-as-usual, or another recognized treatment.


RESULTS
In total, 5464 abstracts were identified. Of those, 8 papers describing 5 apps targeting depression, anxiety, and substance abuse met the inclusion criteria. Four apps provided support from a mental health professional. Results showed significant reductions in depression, stress, and substance use. Within-group and between-group intention-to-treat effect sizes ranged from 0.29-2.28 and 0.01-0.48 at posttest and follow-up, respectively.


CONCLUSIONS
Mental health apps have the potential to be effective and may significantly improve treatment accessibility. However, the majority of apps that are currently available lack scientific evidence about their efficacy. The public needs to be educated on how to identify the few evidence-based mental health apps available in the public domain to date. Further rigorous research is required to develop and test evidence-based programs. Given the small number of studies and participants included in this review, the high risk of bias, and unknown efficacy of long-term follow-up, current findings should be interpreted with caution, pending replication. Two of the 5 evidence-based mental health apps are currently commercially available in app stores.
Knowledge convergence in computer-mediated learning environments . Effects of collaboration scripts Theoretical Background

So far, knowledge convergence has been a widely neglected aspect of collaborative knowledge construction. Collaborative learners contribute their individual knowledge resources, discuss the contributions of their learning partners, and eventually synthesize their individual perspectives. In collaborative knowledge construction groups of learners may be characterized by convergence or divergence of knowledge. Knowledge convergence is defined here as the amount of knowledge concepts that learners share. Different aspects of knowledge convergence can be investigated in collaborative knowledge construction (Fischer & Mandl, 2001). (1) Resource homogeneity. Resources of the learning partners, e.g., prior knowledge, may vary or can be highly similar. (2) Process convergence. Process convergence means that learners communicate individual knowledge and that learning partners internalize these knowledge concepts. (3) Outcome convergence. Finally, the group-to-individual-transfer of shared knowledge must be considered. Outcome convergence indicates to what extent learning partners are able to apply the shared knowledge in the individual condition. Learners may converge with respect to different knowledge aspects. In the context of collaborative knowledge construction, learners may focus on central aspects of a problem case and also regard multiple perspectives on a problem case (Weinberger, Fischer, & Mandl, 2003). In this study we distinguish therefore focused and multi-perspective knowledge and inquire to what extent learners converge towards each of these knowledge aspects. Cooperation scripts aim at the facilitation of processes of collaborative learning. Scripts specify, sequence and possibly assign activities to collaborative learners. Learners are expected (or to some degree coerced) to follow the script prescriptions and consequently, engage in productive learning activities (O'Donnell, 1999). These activities can be allocated to various process dimensions in problem-oriented learning environments (Fischer, Bruhn, Gräsel, & Mandl, 2002). (1) Scripts may provide a structure for the epistemic activities of collaborative learners. Epistemic activities describe how learners deal with the learning tasks. Epistemic collaboration scripts (ECOS) may therefore facilitate process convergence by providing a shared focus on the task. (2) Scripts may also structure the social modes of interaction of learners. The social modes indicate how learners interact with each other, e.g., how they relate their contributions to contributions of their learning partners. Social collaboration scripts (SCOS) may, for instance, facilitate knowledge convergence by guiding learners to contribute their individual knowledge resources. The combination of both social and epistemic scripts may focus the learners on specific tasks and simultaneously demand learners to share their knowledge resources. Social and epistemic scripts may have differentiated effects on process …
A new instrument to describe indicators of well-being in old-old patients with severe dementia – The Vienna List

BACKGROUND
In patients with very severe dementia self-rating of quality of life usually is not possible and appropriate instruments for proxy-ratings are not available. The aim of this project is to develop an instrument of clinical proxy-ratings for this population.


METHODS
Using electronic instruments, physicians and nurses recorded patient behaviour and changes of behaviour over a period of one year. Based on these data a list of 65 items was generated and subsequently allocated to 14 categories. This list was tested in 217 patients (61-105 yrs) with dementia diagnosed according to ICD-10 by both physicians and nurses. The severity of dementia was assessed by means of the Global Deterioration Scale (GDS) and the Brief Cognitive Rating Scale (BCRS). The Spitzer-Index (proxy-rating) was used as a global quality of life measure. Activity of daily living was rated using the Barthel Index.


RESULTS
A factor analysis of the original 65 items revealed 5 factors (communication, negative affect, bodily contact, aggression, and mobility). By stepwise removing items we obtained satisfactory internal consistencies of the factors both for nurses' and physicians' ratings. The factors were generally unrelated. The validity of the instrument was proven by correlations of the factors communication and mobility with the Brief Cognitive Rating Scale (BCRS) and the Barthel-Index.


CONCLUSION
The results demonstrate the reliability and validity of the Vienna List as a proxy rating measurement of quality of life in patients with severe dementia. The psychometric properties of the scale have to be proved in further studies.
What can we learn from b->s gamma?

We review some recent theoretical progress in the understanding of weak radiative B meson decay, and discuss the implications of present and improved measurements of b -> s gamma for supersymmetric models.