LLukas22/scidocs huggingface dataset:
Etoposide phosphate with carboplatin in the treatment of elderly patients with small-cell lung cancer: a phase II study.

BACKGROUND
Although the average age of lung cancer patients is increasing, many elderly patients remain undertreated, mainly because of the fear of higher treatment toxicity in this category of patients. We conducted a study to evaluate the efficacy and tolerability of a combination therapy with carboplatin (C) and etoposide phosphate (EP) in elderly patients with Small-Cell Lung Cancer (SCLC).


PATIENTS AND METHODS
Previously untreated patients older than 70 years with stage IIIB/IV SCLC received a combination of EP (100 mg/m2 D1, D2, D3) and C (D1, dose calculated according to the Calvert formula). Response rate, survival and toxicity were assessed.


RESULTS
Thirty-eight patients (mean age 76 years, range 70-88 years) received a total of 162 cycles. Eighteen patients (47%) received the six scheduled cycles. Thirty patients were evaluable for efficacy (2 CR and 20 PR). The median survival was 237 days and the one-year probability of survival was 26%. The most common adverse effect was transient grade 3 or 4 neutropenia, observed during 57% of evaluable cycles, while five episodes of febrile neutropenia also occurred, with one fatal (bacteremia). It is noteworthy that no renal or liver toxicity was observed, and no mucitis was noted. Unfortunately, a relatively high proportion of patients died shortly after the start of the study. Although most deaths seemed unrelated to the treatment, the possibility of its exacerbatory effect on comorbidities, especially cardiovascular, cannot be excluded.


CONCLUSION
The two-drug regimen of carboplatin and etoposide phosphate is feasible in most elderly patients with an acceptable toxicity, and the overall results suggest that patients even older than 70 years may benefit from full treatment. Therefore, consideration should be given to offering active treatment to most patients with SCLC, regardless of age but with special attention paid to comorbidities.
Modelling debris flows down general channels

This paper is an extension of the single-phase cohesionless dry granular avalanche model over curved and twisted channels proposed by Pudasaini and Hutter (2003). It is a generalisation of the Savage and Hutter (1989, 1991) equations based on simple channel topography to a twophase fluid-solid mixture of debris material. Important terms emerging from the correct treatment of the kinematic and dynamic boundary condition, and the variable basal topography are systematically taken into account. For vanishing fluid contribution and torsion-free channel topography our new model equations exactly degenerate to the previous Savage-Hutter model equations while such a degeneration was not possible by the Iverson and Denlinger (2001) model, which, in fact, also aimed to extend the Savage and Hutter model. The model equations of this paper have been rigorously derived; they include the effects of the curvature and torsion of the topography, generally for arbitrarily curved and twisted channels of variable channel width. The equations are put into a standard conservative form of partial differential equations. From these one can easily infer the importance and influence of the pore-fluid-pressure distribution in debris flow dynamics. The solid-phase is modelled by applying a Coulomb dry friction law whereas the fluid phase is assumed to be an incompressible Newtonian fluid. Input parameters of the equations are the internal and bed friction angles of the solid particles, the viscosity and volume fraction of the fluid, the total mixture density and the pore pressure distribution of the fluid at the bed. Given the bed topography and initial geometry and the initial velocity profile of the debris mixture, the model equations are able to describe the dynamics of the depth profile and bed parallel depth-averaged velocity distribution from the initial position to the final deposit. A shock capturing, total variation diminishing numerical scheme is implemented to solve the highly non-linear equations. Simulation results present the combined effects of curvature, torsion and pore pressure Correspondence to: S. P. Pudasaini (pudasain@mechanik.tu-darmstadt.de) on the dynamics of the flow over a general basal topography. These simulation results reveal new physical insight of debris flows over such non-trivial topography. Model equations are applied to laboratory avalanche and debris-flow-flume tests. Very good agreement between the theory and experiments is established.
UNIFIED THEORY OF ACCEPTANCE AND USE OF TECHNOLOGY ( UTAUT ) MODEL-MOBILE BANKING

Purpose: The study makes an attempt to understand the drivers of mobile banking adoption within the framework of the unified theory of acceptance and use of technology (UTAUT) model. Design/methodology/approach: Considering the business implication of mobile banking in Jordan, the authors were inspired to explore the theoretical concept with a randomly selected group of people. The data collected through questionnaire was analyzed using IBM SPSS and AMOS. In this study structural equation modeling technique was applied to understand how the UTAUT model factors can predict the behavioral intention to adopt mobile banking. Findings: Analysis illustrated that performance expectancy; effort expectancy and risk perception significantly influence user's intention to adopt mobile banking services. However, no significant relations could be established for social influence and trust. Authors acknowledged that the adoption of technology is also influenced by several factors external to the scope of this research. Practical implications: The banking organizations in Jordan are eager to leverage their mobile banking services. However, in spite of their endeavors, significant advancement is yet to be made. As per the findings of the study, m-banking organizations should focus on improving the performance and safety and ease of JIBC December 2017, Vol. 22, No.3 2 use of the mobile banking system. Originality/value: This study focused on detailed review of Jordan based literature on mobile banking adoption. Things are rapidly changing as technology is evolving. This study tends to capture the very recent picture of m-banking adoptability.
Security Evaluation of Pattern Classifiers under Attack

Pattern classification systems are commonly used in adversarial applications, like biometric authentication, network intrusion detection, and spam filtering, in which data can be purposely manipulated by humans to undermine their operation. As this adversarial scenario is not taken into account by classical design methods, pattern classification systems may exhibit vulnerabilities,whose exploitation may severely affect their performance, and consequently limit their practical utility. Extending pattern classification theory and design methods to adversarial settings is thus a novel and very relevant research direction, which has not yet been pursued in a systematic way. In this paper, we address one of the main open issues: evaluating at design phase the security of pattern classifiers, namely, the performance degradation under potential attacks they may incur during operation. We propose a framework for empirical evaluation of classifier security that formalizes and generalizes the main ideas proposed in the literature, and give examples of its use in three real applications. Reported results show that security evaluation can provide a more complete understanding of the classifier’s behavior in adversarial environments, and lead to better design choices micans infotech +91 90036 28940 +91 94435 11725 MICANS INFOTECH, NO: 8 , 100 FEET ROAD,PONDICHERRY. WWW.MICANSINFOTECH.COM ; MICANSINFOTECH@GMAIL.COM +91 90036 28940; +91 94435 11725 IEEE Projects 100% WORKING CODE + DOCUMENTATION+ EXPLAINATION – BEST PRICE LOW PRICE GUARANTEED
Classification of MRI brain images using combined wavelet entropy based spider web plots and probabilistic neural network

Magnetic Resonance Imaging (MRI) is a non-invasive diagnostic tool very frequently used for brain 8 imaging. The classification of MRI images of normal and pathological brain conditions pose a challenge from 9 technological and clinical point of view, since MR imaging focuses on soft tissue anatomy and generates a large 10 information set and these can act as a mirror reflecting the conditions of the brain. A new approach by 11 integrating wavelet entropy based spider web plots and probabilistic neural network is proposed for the 12 classification of MRI brain images. The two step method for classification uses (1) wavelet entropy based spider 13 web plots for the feature extraction and (2) probabilistic neural network for the classification. The spider web 14 plot is a geometric construction drawn using the entropy of the wavelet approximation components and the areas 15 calculated are used as feature set for classification. Probabilistic neural network provides a general solution to 16 the pattern classification problems and the classification accuracy is found to be 100%. 17 Keywords-Magnetic Resonance Imaging (MRI), Wavelet Transformation, Entropy, Spider Web Plots, 18 Probabilistic Neural Network 19
Personalization Method for Tourist Point of Interest (POI) Recommendation

Today, travelers are provided large amount information which includes Web sites and tourist magazines about introduction of tourist spot. However, it is not easy for users to process the information in a short time. Therefore travelers prefer to receive pertinent information easier and have that information presented in a clear and concise manner. This paper proposes a personalization method for tourist Point of Interest (POI) Recommendation.
A Constraint Integer Programming Approach for Resource-Constrained Project Scheduling

We propose a hybrid approach for solving the resource-constrained project scheduling problem which is an extremely hard to solve combinatorial optimization problem of practical relevance. Jobs have to be scheduled on (renewable) resources subject to precedence constraints such that the resource capacities are never exceeded and the latest completion time of all jobs is minimized. The problem has challenged researchers from different communities, such as integer programming (IP), constraint programming (CP), and satisfiability testing (SAT). Still, there are instances with 60 jobs which have not been solved for many years. The currently best known approach, lazyFD, is a hybrid between CP and SAT techniques. In this paper we propose an even stronger hybridization by integrating all the three areas, IP, CP, and SAT, into a single branch-and-bound scheme. We show that lower bounds from the linear relaxation of the IP formulation and conflict analysis are key ingredients for pruning the search tree. First computational experiments show very promising results. For five instances of the well-known PSPLib we report an improvement of lower bounds. Our implementation is generic, thus it can be potentially applied to similar problems as well.
Convergence results for function spaces over o-minimal structures

We begin the development of a theory of Banach spaces in the definable setting of o-minimal structures. We outline several results which develop the theory of compact embeddings for explicitly given function spaces. One aim is to explain the substantive underpinnings of an important observation used in the proof of the Reparameterization Theorem of Pila and Wilkie in (2). We place this observation in the broader context of our theory and demonstrate how it may be refined further. 2000 Mathematics Subject Classification 03C64 (primary); 46B99 (secondary)
Family factors associated with suicide attempts among Chinese adolescent students: a national cross-sectional survey.

PURPOSE
To determine the prevalence and associated family factors of suicide attempts among junior and/or senior high school students, so as to provide bases for preventive measures of suicide in China.


METHODS
A total of 13,512 students from 32 junior and/or senior high schools in grades 7 to 11 in eight cities of China participated in a self-administered anonymous survey to report their frequency of suicide attempts during the past year. Sociodemographic characteristics, tobacco, and alcohol use in the past 30 days were asked. Stressful family life events were used to evaluate the subjects' family characteristics.


RESULTS
Overall, 2.7% (338/12,470) in-school adolescents reported a suicide attempt during the past year, girls significantly more often than boys. Considered independently, all stressful family life events were strongly associated with increased risk for self-reported suicide attempts. When taking sociodemographic characteristics, life style, and all the five family factors selected from factor analysis into consideration, there was a significant independent impact of three family factors on increasing suicide attempts risk among adolescents. The most notable risks were derived from improper parental rearing behavior, separation from parents, and social problems of the family members. However, neither poor material conditions of family life nor family member's adversity contribute significantly to the risk.


CONCLUSIONS
This study not only indicates that suicide attempt is a significant public health issue among in-school adolescents in China, but also confirms that adolescents with family problems commonly manifest suicide attempts, which highlights the importance of considering family environmental factors when assessing suicide risk.
Tag-Weighted Topic Model for Mining Semi-Structured Documents

In the last decade, latent Dirichlet allocation (LDA) successfully discovers the statistical distribution of the topics over a unstructured text corpus. Meanwhile, more and more document data come up with rich human-provided tag information during the evolution of the Internet, which called semistructured data. The semi-structured data contain both unstructured data (e.g., plain text) and metadata, such as papers with authors and web pages with tags. In general, different tags in a document play different roles with their own weights. To model such semi-structured documents is nontrivial. In this paper, we propose a novel method to model tagged documents by a topic model, called Tag-Weighted Topic Model (TWTM). TWTM is a framework that leverages the tags in each document to infer the topic components for the documents. This allows not only to learn document-topic distributions, but also to infer the tag-topic distributions for text mining (e.g., classification, clustering, and recommendations). Moreover, TWTM automatically infers the probabilistic weights of tags for each document. We present an efficient variational inference method with an EM algorithm for estimating the model parameters. The experimental results show that our TWTM approach outperforms the baseline algorithms over three corpora in document modeling and text classification.
Gaussian Conditional Random Field Network for Semantic Segmentation

In contrast to the existing approaches that use discrete Conditional Random Field (CRF) models, we propose to use a Gaussian CRF model for the task of semantic segmentation. We propose a novel deep network, which we refer to as Gaussian Mean Field (GMF) network, whose layers perform mean field inference over a Gaussian CRF. The proposed GMF network has the desired property that each of its layers produces an output that is closer to the maximum a posteriori solution of the Gaussian CRF compared to its input. By combining the proposed GMF network with deep Convolutional Neural Networks (CNNs), we propose a new end-to-end trainable Gaussian conditional random field network. The proposed Gaussian CRF network is composed of three sub-networks: (i) a CNN-based unary network for generating unary potentials, (ii) a CNN-based pairwise network for generating pairwise potentials, and (iii) a GMF network for performing Gaussian CRF inference. When trained end-to-end in a discriminative fashion, and evaluated on the challenging PASCALVOC 2012 segmentation dataset, the proposed Gaussian CRF network outperforms various recent semantic segmentation approaches that combine CNNs with discrete CRF models.
Recursive function data allocation to scratch-pad memory

This paper presents the first automatic scheme to allocate local (stack) data in recursive functions to scratch-pad memory (SPM) in embedded systems. A scratch-pad is a fast directly addressed compiler-managed SRAM memory that replaces the hardware-managed cache. It is motivated by its significantly lower access time, energy consumption, real-time bounds, area and overall runtime. Existing compiler methods for allocating data to scratch-pad are able to place only code, global, heap and non-recursive stack data in scratch-pad memory; stack data for recursive functions is allocated entirely in DRAM, resulting in poor performance.
 In this paper we present a dynamic yet compiler-directed allocation method for recursive function stack data that for the first time, is able to place a portion of recursive stack data in scratch-pad. It has almost no software-caching overhead, and is able to move recursive function data back and forth between scratch-pad and DRAM to better track the program's locality characteristics. With our method, all code, global, stack and heap variables can share the same scratch-pad. When compared to placing all recursive function data in DRAM and all other variables in scratch-pad, our results show that our method reduces the average runtime of our benchmarks by 29.3%, and the average power consumption by 31.1%, for the same size of scratch-pad fixed at5% of total data size. Furthermore,significant savings were observedwhen comparing our method against cache-based alternatives for SPM allocation. Finally, we show results that analyze the effects of profile variation on our allocation approach and present a modified version of our method which minimizes variation for profile-based allocations.
Split bolus technique in polytrauma: a prospective study on scan protocols for trauma analysis.

BACKGROUND
For the evaluation of severely injured trauma patients a variety of total body computed tomography (CT) scanning protocols exist. Frequently multiple pass protocols are used. A split bolus contrast protocol can reduce the number of passes through the body, and thereby radiation exposure, in this relatively young and vitally threatened population.


PURPOSE
To evaluate three protocols for single pass total body scanning in 64-slice multidetector CT (MDCT) on optimal image quality.


MATERIAL AND METHODS
Three total body CT protocols were prospectively evaluated in three series of 10 consecutive trauma patients. In Group A unenhanced brain and cervical spine CT was followed by chest-abdomen-pelvis CT in portovenous phase after repositioning of the arms. Group B underwent brain CT followed without arm repositioning by a one-volume contrast CT from skull base to the pubic symphysis. Group C was identical to Group A, but the torso was scanned with a split bolus technique. Three radiologists independently evaluated protocol quality scores (5-point Likert scale), parenchymal and vascular enhancement and artifacts.


RESULTS
Overall image quality was good (4.10) in Group A, more than satisfactory (3.38) in Group B, and nearly excellent (4.75) in Group C (P < 0.001). Interfering artifacts were mostly reported in Group B in the liver and spleen.


CONCLUSION
In single pass total body CT scanning a split bolus technique reached the highest overall image quality compared to conventional total body CT and one-volume contrast CT.
An Introduction to Multilevel Modeling for Social and Personality Psychology

Multilevel modeling is a technique that has numerous potential applications for social and personality psychology. To help realize this potential, this article provides an introduction to multilevel modeling with an emphasis on some of its applications in social and personality psychology. This introduction includes a description of multilevel modeling, a rationale for this technique, and a discussion of applications of multilevel modeling in social and personality psychological research. Some of the subtleties of setting up multilevel analyses and interpreting results are presented, and software options are discussed. Once you know that hierarchies exist, you see them everywhere. (Kreft and de Leeuw, 1998, 1) Whether by design or nature, research in personality and social psychology and related disciplines such as organizational behavior increasingly involves what are often referred to as multilevel data. Sometimes, such data sets are referred to as ‘nested’ or ‘hierarchically nested’ because observations (also referred to as units of analysis) at one level of analysis are nested within observations at another level. For example, in a study of classrooms or work groups, individuals are considered to be nested within groups. Similarly, in diary-style studies, observations (e.g., diary entries) are nested within persons. What is particularly important for present purposes is that when you have multilevel data, you need to analyze them using techniques that take into account this nesting. As discussed below (and in numerous places, including Nezlek, 2001), the results of analyses of multilevel data that do not take into account the multilevel nature of the data may (or perhaps will) be inaccurate. This article is intended to acquaint readers with the basics of multilevel modeling. For researchers, it is intended to provide a basis for further study. I think that a lack of understanding of how to think in terms of hierarchies and a lack of understanding of how to analyze such data inhibits researchers from applying the ‘multilevel perspective’ to their work. For those simply interested in understanding what multilevel
[Studies and Publication Practice in Pediatric Hematology and Oncology in Germany--An Analysis of the Period 1970-2006].

BACKGROUND
Several therapy optimization studies (TOSs) for the treatment of hematologic and oncologic disorders in children and adolescents have been conducted in Germany. The publication of research results is necessary to ensure that future studies are well designed and based on relevant and unanswered questions. This retrospective cohort study was conducted to analyze the study- and publication practice in this field.


METHODS
All study protocols in the field of the pediatric oncology and hematology in Germany were collected. Relevant data from study protocols were extracted, beginning with 1) general information about the study protocol, and 2) information about each methodological trial. In a second step, the publication practice was characterized by searching in electronic databases and by contacting principal investigators. Relevant Data of each publication was extracted.


RESULTS
The research activity has increased significantly in the past few years. The found publication rate of 85% represents an outstanding publication practice. Additionally, German, as being the main publication language a few decades ago, has been almost completely replaced with English. An acceptable methodological conduct was observed in the analyzed study protocols.


DISCUSSION AND CONCLUSION
Studies have been principally based on the concept of TOS, without considering a detailed breakdown into each methodological trial. A markedly subdivision of studies into methodologically identifiable trials would allow a clear definition of their parameters, while increasing transparency of the study conduct and its results.