bluuebunny/crossref_metadata_2025_split huggingface dataset:
The knowledge level of rheumatoid arthritis patients about their disease in a developing country. A study in 168 Bangladeshi RA patients
Authors: Kamruzzaman A. K. M. , Chowdhury Minhaj Rahim , Islam Md Nazrul , Sultan Imtiaz , Ahmed Shamim , Shahin Abu , Alam Mohammad Mahbubul , Azad Md. Ak , Hassan M. Masudul , Amin Md Zahid , Sinha Sudeshna , Ahmad Habib Imtiaz , Shazzad Md Nahiduzzamane , Ahmad Sonia Nasreen , Haq Syed Atiqul , Rasker Johannes Jacobus 
Published: December 2019

Abstract
Objectives
To assess disease-related knowledge of rheumatoid arthritis (RA) patients

Patients and methods
Consecutive RA patients were invited from the rheumatology departments of BSMM University, Dhaka, Bangladesh. The Bangla version of the Patient Knowledge Questionnaire (B-PKQ) was used. Correlations between the B-PKQ scores and clinical-demographic data were measured using Pearson’s correlation coefficient. Impact of independent variables on the level of knowledge about RA was analyzed through multiple regression analysis. Possible explanatory variables included the following: age, disease duration, formal education level, and Bangla Health Assessment Questionnaire (B-HAQ) score. Analysis of variance (ANOVA) was used to test the difference between demographical, clinical, and socioeconomic variables. For statistical analysis, SPSS statistics version 20 was used.

Results
A total of 168 RA patients could be included. The mean B-PKQ score was 9.84 (range 1–20) from a possible maximum of 30. The mean time for answering the questionnaire was 24.3 min (range 15–34). Low scores were observed in all domains but the lowest were in medications and joint protection/energy conservation. Knowledge level was higher (15.5) in 6 patients who had RA education before enrollment. B-PKQ showed positive correlation with education level (r = 0.338) and negative correlation with HAQ (r = −0.169). The B-PKQ showed no correlation with age, disease duration, having first degree family member with RA, education from other sources (neighbor, RA patient, nurses), or information from mass media.

Conclusions
Disease-related knowledge of Bangladeshi RA patients was poor in all domains. Using these findings, improved education and knowledge will result in better disease control.Key Points• Little is known about the knowledge of RA patients regarding their disease and its treatment in Bangladesh and in developing countries in general.• We found that the knowledge of Bangladeshi RA patients regarding their disease was poor in all domains; it correlated positive with education level and negative with function (HAQ), but showed no correlation with age or disease duration.• The findings of this study can be used for improving current patient education programs by health professionals and through mass media.• Better disease control of RA may be achieved by improving patient knowledge in a developing country like Bangladesh, but also in other parts of the world.
Dotinurad: a novel selective urate reabsorption inhibitor as a future therapeutic option for hyperuricemia
Authors: Kuriyama Satoru 
Published: December 2019

AbstractGout is a chronic inflammatory disease caused by precipitation of urate crystals in the joints, kidneys, and urinary tract. Independent of urate deposition disorders, recent studies have shown a positive association between circulating uric acid (UA) levels and cardiovascular (CV) diseases. These results indicate that UA is a precipitating factor of both gout and the progression of CV diseases, including hypertension and/or chronic kidney disease (CKD). A large body of evidence has shown that UA-lowering therapies are effective in preventing the progression of hypertension/CKD and that a causal relationship exists between serum UA level and CV diseases. Despite the urgent need for effective UA-lowering drugs that can be used to obtain better therapeutic outcomes and prognosis, only few drugs have been developed in the past decades. Recently, febuxostat and topiroxostat, which are xanthine oxidoreductase inhibitors, were developed and used in clinical practice. Of note, after the approval of lesinurad, which is a urate transporter-1 (URAT-1) inhibitor, in the United States in 2015, dotinurad (Fig. 1), a novel promising drug with selective UA reabsorption inhibitory property, was recently developed in Japan in 2018. Dotinurad is indicated for patients with hyperuricemia/gout as most patients with hyperuricemia are classified into “underexcretion type”, which requires the inhibition of URAT-1 to excrete excess UA via the kidney. Focusing on dotinurad, the present study highlighted the multifaceted preliminary new trials that assessed for drug efficacy and safety, pharmacokinetics (PK) according to age and gender, the presence or absence of liver and kidney disorders, drug interactions with NSAID, and non-inferiority of dotinurad to either febuxostat or benzbromarone. A series of studies included in this supplemental review indicate that dotinurad reduces serum UA levels, and its efficacy and safety are similar to those of other UA-lowering agents currently used even in hyperuricemic patients with various clinical conditions. Moreover, two exploratory studies with a small sample size were conducted to compare PK parameters between patients with overproduction- and underexcretion-type hyperuricemia, and results showed that the effects of UA-lowering agents were comparable between the two subtype groups.
A minimal-variable symplectic method for isospectral flows
Authors: Viviani Milo 
Published: December 2019

AbstractIsospectral flows are abundant in mathematical physics; the rigid body, the the Toda lattice, the Brockett flow, the Heisenberg spin chain, and point vortex dynamics, to mention but a few. Their connection on the one hand with integrable systems and, on the other, with Lie–Poisson systems motivates the research for optimal numerical schemes to solve them. Several works about numerical methods to integrate isospectral flows have produced a large varieties of solutions to this problem. However, many of these algorithms are not intrinsically defined in the space where the equations take place and/or rely on computationally heavy transformations. In the literature, only few examples of numerical methods avoiding these issues are known, for instance, the spherical midpoint method on $${{\mathfrak {s}}}{{\mathfrak {o}}}(3)$$

s
o
(
3
)

. In this paper we introduce a new minimal-variable, second order, numerical integrator for isospectral flows intrinsically defined on quadratic Lie algebras and symmetric matrices. The algorithm is isospectral for general isospectral flows and Lie–Poisson preserving when the isospectral flow is Hamiltonian. The simplicity of the scheme, together with its structure-preserving properties, makes it a competitive alternative to those already present in literature.
The Synthesis of Hydrobenzoin-Based Monoaza Crown Ethers and Their Application as Recyclable Enantioselective Catalysts
Authors: Nemcsok Tamás , Rapi Zsolt , Bagi Péter , Oláh Attila , Keglevich György , Bakó Péter 
Published: December 2019

Abstract
New recyclable monoaza-15-crown ethers have been synthesized starting from (R,R)-(+)- and (S,S)-(−)-hydrobenzoin. These macrocycles proved to be efficient and reusable phase transfer catalysts in a few asymmetric reactions under mild conditions. The asymmetric epoxidation of trans-chalcone took place with up to 81% ee, while using other chalcone derivatives, the products were formed with 68–88% ee. The hydrobenzoin-based lariat ethers were also tested in the cyclopropanation of a few electron deficient olefins using diethyl bromomalonate to afford the product with good enantioselectivities (54–75% ee). The catalysts were recovered by salt formation, followed by extraction, and were reused without the loss of the activity and effect on the enantioselectivity.

Graphic Abstract

The synthesis of hydrobenzoin-based monaza crown ethers and their application as recyclable enantioselective catalysts.
Protecting Consumer Protection Values in the Fourth Industrial Revolution
Authors: Howells G. 
Published: December 2019

AbstractWe are entering into an era of new technological possibilities. Many benefits will be derived for consumers from the development of data and computer-driven innovation. We will have new products and services and new ways of making and supplying goods and services.Without wanting to inhibit innovation, this article calls for the legal system to remain committed to an ideology and legal framework that supports consumer protection. It will counsel against assuming that the law should give way unduly to the technology agenda, whilst accepting that adaptations should be made and also that there should be a critical review of whether traditional forms of regulation are needed in the Fourth Industrial Age.
Mapping of QTLs for source and sink associated traits under elevated CO2 in rice (Oryza sativa L.)
Authors: Dai Li-Ping , Lu Xue-Li , Zou Wei-Wei , Wang Chang-Jian , Shen Lan , Hu Jiang , Zhang Guang-Heng , Ren De-Yong , Chen Guang , Zhang Qiang , Xue Da-Wei , Dong Guo-Jun , Gao Zhen-Yu , Guo Long-Biao , Zhu Li , Mou Tong-Min , Qian Qian , Zeng Da-Li 
Published: December 2019

AbstractRice source- and sink-associated traits are important for grain yield and are sensitive to environmental conditions. The continuing increase of CO2 concentrations in the atmosphere will become a major challenge for rice growth and development in the future due to changes in our climate such as extremes in temperature. To guarantee food safety, novel genetic loci need to be identified for source- and sink-associated traits that are specifically expressed under elevated CO2 conditions. Eighty chromosome segment substitution lines carrying japonica (Nipponbare) chromosome segments in the indica (9311) background were used in this study. QTL analysis was conducted for source- and sink-related traits, including flag leaf length, flag leaf width, flag leaf fresh weight, flag leaf dry weight, primary branch number, secondary branch number, grain number per panicle, panicle weight per plant, chlorophyll a, chlorophyll b, and carotenoid contents, under ambient CO2 concentrations and free-air CO2 enrichment. A total of 49 QTLs for these traits were detected on chromosomes 1, 3, 5, 6, 7, 9, and 12 under the two conditions; the variance explained by these QTLs varied from 6.22 to 38.15%. Among these QTLs, 19 of them were detected under the natural field conditions and 30 were detected in the elevated CO2 conditions. In addition, 2 and 13 QTLs were specifically expressed in the natural and CO2-enriched conditions, respectively. Our findings have important implications on the utilization of germplasm resources for ensuring food security under elevated CO2 levels, especially for QTLs that were specifically detected under the elevated CO2 condition.
Comparison of Parent Questionnaires, Examiner-Led Assessment and Parents’ Concerns at 14 Months of Age as Indicators of Later Diagnosis of Autism
Authors:   The BASIS Team, Pasco Greg , Davies Kim , Ribeiro Helena , Tucker Leslie , Allison Carrie , Baron-Cohen Simon , Johnson Mark H. , Charman Tony 
Published: December 2019

AbstractParents participating in a prospective longitudinal study of infants with older siblings with autism completed an autism screening questionnaire and were asked about any concerns relating to their child’s development, and children were administered an interactive assessment conducted by a researcher at 14 months. Scores on the parent questionnaire were highest for children later diagnosed with autism. Parental concerns and scores from the examiner-led assessment distinguished children with later developmental difficulties (both autism and other developmental atypicalities) from those who were developing typically. Children about whom parents expressed concern scored higher on both the questionnaire and the interactive assessment than those without concerns. There were no significant associations between total or individual item scores from the questionnaire and interactive assessment.
Reliable workflow for inversion of seismic receiver function and surface wave dispersion data: a “13 BB Star” case study
Authors: Chrapkiewicz Kajetan , Wilde-Piórko Monika , Polkowski Marcin , Grad Marek 
Published: December 2019

AbstractNon-linear inverse problems arising in seismology are usually addressed either by linearization or by Monte Carlo methods. Neither approach is flawless. The former needs an accurate starting model; the latter is computationally intensive. Both require careful tuning of inversion parameters. An additional challenge is posed by joint inversion of data of different sensitivities and noise levels such as receiver functions and surface wave dispersion curves. We propose a generic workflow that combines advantages of both methods by endowing the linearized approach with an ensemble of homogeneous starting models. It successfully addresses several fundamental issues inherent in a wide range of inverse problems, such as trapping by local minima, exploitation of a priori knowledge, choice of a model depth, proper weighting of data sets characterized by different uncertainties, and credibility of final models. Some of them are tackled with the aid of novel 1D checkerboard tests—an intuitive and feasible addition to the resolution matrix. We applied our workflow to study the south-western margin of the East European Craton. Rayleigh wave phase velocity dispersion and P-wave receiver function data were gathered in the passive seismic experiment “13 BB Star” (2013–2016) in the area of the crust recognized by previous borehole and refraction surveys. Final models of S-wave velocity down to 300 km depth beneath the array are characterized by proximity in the parameter space and very good data fit. The maximum value in the mantle is higher by 0.1–0.2 km/s than reported for other cratons.
Learning higher-order logic programs
Authors: Cropper Andrew , Morel Rolf , Muggleton Stephen 
Published: December 2019

AbstractA key feature of inductive logic programming is its ability to learn first-order programs, which are intrinsically more expressive than propositional programs. In this paper, we introduce techniques to learn higher-order programs. Specifically, we extend meta-interpretive learning (MIL) to support learning higher-order programs by allowing for higher-order definitions to be used as background knowledge. Our theoretical results show that learning higher-order programs, rather than first-order programs, can reduce the textual complexity required to express programs, which in turn reduces the size of the hypothesis space and sample complexity. We implement our idea in two new MIL systems: the Prolog system $$\text {Metagol}_{ho}$$

Metagol

ho

and the ASP system $$\text {HEXMIL}_{ho}$$

HEXMIL

ho

. Both systems support learning higher-order programs and higher-order predicate invention, such as inventing functions for and conditions for . We conduct experiments on four domains (robot strategies, chess playing, list transformations, and string decryption) that compare learning first-order and higher-order programs. Our experimental results support our theoretical claims and show that, compared to learning first-order programs, learning higher-order programs can significantly improve predictive accuracies and reduce learning times.
Priorities and Preferences in Water Quality Management - a Case Study of the Alsterån River Basin
Authors: Ek Kristina , Persson Lars 
Published: December 2019

AbstractSweden is a decentralised country where local managers, who are key actors in water management, often deal with relatively difficult prioritisations, tradeoffs and conflicting goals. Many of these challenges relate to the effective implementation of the European Union Water Framework Directive. As an input to these challenges, the present paper elicits and analyses local and semi-local citizens’ preferences for water quality attributes related to the European Water Framework directive in a river basin located in southeast of Sweden. Based on a choice experiment tailored to the case study area, the paper analyses preferences for selected attributes based on real criteria for ecological water status in the implementation of the directive. The target population lives in the municipalities through which the river passes, or in municipalities neighbouring those. Despite this spatial proximity to the river, the analysis reveals limited knowledge and interest in matters related to the environmental quality of the river. There is no evidence that preferences differ between respondents with regard to experience or knowledge about the water basin, nor with regard to recreational habits in the area. These results offer input to local water management by providing information about preferences for explicit water quality attributes.
Predicting Limit-Setting Behavior of Gamblers Using Machine Learning Algorithms: A Real-World Study of Norwegian Gamblers Using Account Data
Authors: Auer Michael , Griffiths Mark D. 
Published: December 2019

AbstractPlayer protection and harm minimization have become increasingly important in the gambling industry along with the promotion of responsible gambling (RG). Among the most widespread RG tools that gaming operators provide are limit-setting tools that help players limit the amount of time and/or money they spend gambling. Research suggests that limit-setting significantly reduces the amount of money that players spend. If limit-setting is to be encouraged as a way of facilitating responsible gambling, it is important to know what variables are important in getting individuals to set and change limits in the first place. In the present study, 33 variables assessing the player behavior among Norsk Tipping clientele (N = 70,789) from January to March 2017 were computed. The 33 variables which reflect the players’ behavior were then used to predict the likelihood of gamblers changing their monetary limit between April and June 2017. The 70,789 players were randomly split into a training dataset of 56,532 and an evaluation set of 14,157 players (corresponding to an 80/20 split). The results demonstrated that it is possible to predict future limit-setting based on player behavior. The random forest algorithm appeared to predict limit-changing behavior much better than the other algorithms. However, on the independent test data, the random forest algorithm’s accuracy dropped significantly. The best performance on the test data along with a small decrease in accuracy in comparison to the training data was delivered by the gradient boost machine learning algorithm. The most important variables predicting future limit-setting using the gradient boost machine algorithm were players receiving feedback that they had reached 80% of their personal monthly global loss limit, personal monthly loss limit, the amount bet, theoretical loss, and whether the players had increased their limits in the past. With the help of predictive analytics, players with a high likelihood of changing their limits can be proactively approached.
A new model for predicting the total tree height for stems cut-to-length by harvesters in Pinus radiata plantations
Authors: Shan Chenxi , Bi Huiquan , Watt Duncan , Li Yun , Strandgard Martin , Ghaffariyan Mohammad Reza 
Published: December 2019

AbstractA new model for predicting the total tree height for harvested stems from cut-to-length (CTL) harvester data was constructed forPinus radiata(D.Don) following a conceptual analysis of relative stem profiles, comparisons of candidate models forms and extensive selections of predictor variables. Stem profiles of more than 3000 trees in a taper data set were each processed 6 times through simulated log cutting to generate the data required for this purpose. The CTL simulations not only mimicked but also covered the full range of cutting patterns of nearly 0.45 × 106stems harvested during both thinning and harvesting operations. The single-equation model was estimated through the multiple-equation generalized method of moments estimator to obtain efficient and consistent parameter estimates in the presence of error correlation and heteroscedasticity that were inherent to the systematic structure of the data. The predictive performances of our new model in its linear and nonlinear form were evaluated through a leave-one-tree-out cross validation process and compared against that of the only such existing model. The evaluations and comparisons were made through benchmarking statistics both globally over the entire data space and locally within specific subdivisions of the data space. These statistics indicated that the nonlinear form of our model was the best and its linear form ranked second. The prediction accuracy of our nonlinear model improved when the total log length represented more than 20% of the total tree height. The poorer performance of the existing model was partly attributed to the high degree of multicollinearity among its predictor variables, which led to highly variable and unstable parameter estimates. Our new model will facilitate and widen the utilization of harvester data far beyond the current limited use for monitoring and reporting log productions inP. radiataplantations. It will also facilitate the estimation of bark thickness and help make harvester data a potential source of taper data to reduce the intensity and cost of the conventional destructive taper sampling in the field. Although developed forP. radiata, the mathematical form of our new model will be applicable to other tree species for which CTL harvester data are routinely captured during thinning and harvesting operations.
Prevention and treatment of pancreatic fistula after pancreatic body and tail resection: current status and future directions
Authors: Jiang Li , Ning Deng , Chen Xiaoping 
Published: December 2019

AbstractPostoperative pancreatic fistula (POPF) is the most common and critical complication after pancreatic body and tail resection. How to effectively reduce the occurrence of pancreatic fistula and conduct timely treatment thereafter is an urgent clinical issue to be solved. Recent research standardized the definition of pancreatic fistula and stressed the correlation between POPF classification and patient prognosis. According to the literature, identification of the risk factors for pancreatic fistula contributed to lowering the rate of the complication. Appropriate management of the pancreatic stump and perioperative treatment are of great significance to reduce the rate of POPF in clinical practice. After the occurrence of POPF, the treatment of choice should be determined according to the classification of the pancreatic fistula. However, despite the progress and promising treatment approaches, POPF remains to be a clinical issue that warrants further studies in the future.
Geomechanical Modelling of Railroad Ballast: A Review
Authors: Alabbasi Yahia , Hussein Mohammed 
Published: December 2019

AbstractTraditional ballasted tracks have been used intensively around the world with ballast as the main material for tracks. Ballast has a significant contribution to the track alignment, stability and sustainability. After service, ballast deforms and degrades. Periodic ballast maintenance is needed which is a time and cost expensive activity. Understanding the mechanical behaviour of railroad ballast leads to better design and efficient maintenance. From the literature, there are two main approaches used to understand the mechanical behaviour of railroad ballast; large scale experimental and modelling. This paper aims to review the state of the art of literature on the modelling approaches used to understand ballast mechanical behaviour. It discusses the key findings from each modelling approach in understanding ballast mechanical behavior. It presents the main concerns and limitations of each modelling approach from different perspectives related to ballast modelling. It summarizes the limitations, gaps and gaps’ developments of the researches used to understand ballast behaviour via modelling approach.