bluuebunny/crossref_metadata_2025_split huggingface dataset:
What do we know about grant peer review in the health sciences?
Authors: Guthrie Susan , Ghiga Ioana , Wooding Steven 
Published: March 2018

Background: Peer review decisions award an estimated >95% of academic medical research funding, so it is crucial to understand how well they work and if they could be improved. Methods: This paper summarises evidence from 105 papers identified through a literature search on the effectiveness and burden of peer review for grant funding. Results: There is a remarkable paucity of evidence about the efficiency of peer review for funding allocation, given its centrality to the modern system of science. From the available evidence, we can identify some conclusions around the effectiveness and burden of peer review. The strongest evidence around effectiveness indicates a bias against innovative research. There is also fairly clear evidence that peer review is, at best, a weak predictor of future research performance, and that ratings vary considerably between reviewers. There is some evidence of age bias and cronyism. Good evidence shows that the burden of peer review is high and that around 75% of it falls on applicants. By contrast, many of the efforts to reduce burden are focused on funders and reviewers/panel members. Conclusions: We suggest funders should acknowledge, assess and analyse the uncertainty around peer review, even using reviewers’ uncertainty as an input to funding decisions. Funders could consider a lottery element in some parts of their funding allocation process, to reduce both burden and bias, and allow better evaluation of decision processes. Alternatively, the distribution of scores from different reviewers could be better utilised as a possible way to identify novel, innovative research. Above all, there is a need for open, transparent experimentation and evaluation of different ways to fund research. This also requires more openness across the wider scientific community to support such investigations, acknowledging the lack of evidence about the primacy of the current system and the impossibility of achieving perfection.
Dlaczego pytanie o granice politologii jest ważne?
Authors: Ulicka Grażyna 
Published: March 2018

Why is the question about limits of political science important?
The text discusses the following issues: how limits of political science are defined, how their comprehension determines the strategies adopted by individual researchers and collective bodies representing the discipline, at what stages of the discipline development and at what critical moments in its development the question about the limits becomes particularly important. What determines the topicality of the question about the limits of the discipline is issues such as: the necessity to fully engage in international cooperation, in particular the European one; the need to establish proper relations with the political science sub‑disciplines which make attempts at becoming independent; the necessity to combine the discipline development with labour market needs. According to the Author, this requires that Polish political science should cross the limits of those areas which have not fallen into the domain of its broader interests to date: especially empirical and comparative research on political systems, economics of politics (political economics), historical sociology of politics.
Behavior-Based Pricing in Marketing Channels
Authors: Li Krista J. 
Published: March 2018

With behavior-based pricing (BBP), firms use customers’ purchase history data to price discriminate between past and new customers. Prior research has examined BBP in a non-channel setting. In this paper, we investigate BBP in a channel setting in which manufacturers sell to customers through exclusive retailers. We examine how channel members’ adoption of BBP affects wholesale and retail prices, profits, consumer surplus, and social welfare. We find that BBP decreases channel members’ profits when retailers use BBP and manufacturers use uniform pricing. However, BBP increases channel members’ profits when manufacturers and retailers use BBP. In addition, BBP by retailers alone increases consumer surplus, whereas BBP by manufacturers and retailers decreases consumer surplus. When manufacturers also use BBP, BBP decreases social welfare to a greater degree than when only retailers use BBP. Furthermore, when manufacturers cannot use BBP, their profits are higher with long-term wholesale price contracts. When manufacturers can use BBP, short-term wholesale price contracts yield higher profits for manufacturers and retailers. The online appendix is available at https://doi.org/10.1287/mksc.2017.1070 .
An Analysis of Price vs. Revenue Protection: Government Subsidies in the Agriculture Industry
Authors: Alizamir Saed , Iravani Foad , Mamani Hamed 
Published: March 2018

The agriculture industry plays a critical role in the U.S. economy, and various industry sectors depend on the output of farms. To protect and raise farmers’ income, the U.S. government offers two subsidy programs to farmers: the Price Loss Coverage (PLC) program, which pays farmers a subsidy when the market price falls below a reference price, and the Agriculture Risk Coverage (ARC) program, which is triggered when farmers’ revenue is below a threshold. Given the unique features of PLC and ARC, we develop models to analyze their impacts on consumers, farmers, and the government. Our analysis generates several insights. First, while PLC always motivates farmers to plant more acres compared to the no-subsidy case, farmers may plant fewer acres under ARC, leading to a lower crop supply. Second, despite the prevailing intuition that ARC generally dominates PLC, we show that both farmers and consumers may be better off under PLC for a large range of parameter values, even when the reference price represents the historical average market price. Third, the subsidy that increases consumer surplus results in higher government expenditure. Finally, we calibrate our model with U.S. Department of Agriculture (USDA) data and provide insights about the effects of crop and market characteristics on the relative performance of PLC and ARC. We provide guidelines to farmers for enrolling crops in the subsidy programs, and show that our guidelines are supported by farmers’ enrollment statistics. We also show that if the economic and political frictions caused by running the subsidy programs is significant, the subsidy that benefits both consumers and farmers may actually result in lower social welfare.The online appendix is available at https://doi.org/10.1287/mnsc.2017.2927 .This paper was accepted by Serguei Netessine, operations management.
Joint Dynamic Pricing and Order Fulfillment for E-commerce Retailers
Authors: Lei Yanzhe (Murray) , Jasin Stefanus , Sinha Amitabh 
Published: March 2018

We consider an e-commerce retailer (e-tailer) who sells a catalog of products to customers from different regions during a finite selling season and fulfills orders through multiple fulfillment centers. The e-tailer faces a joint pricing and fulfillment (JPF) optimization problem: at the beginning of each period, the e-tailer needs to jointly decide the price for each product and how to fulfill an incoming order (i.e., from which warehouse to ship the order). The objective of the e-tailer is to maximize its total expected profits defined as total expected revenues minus total expected shipping costs. (All other costs are fixed in this problem.) The exact optimal policy for JPF is difficult to solve; so, we propose two heuristic controls that have provably good performance compared to reasonable benchmarks. Our first heuristic control directly uses the solution of a deterministic approximation of JPF as its control parameters. Our second heuristic control improves the first one by adaptively adjusting the original control parameters according to the realized demand. An important feature of the second heuristic control is that it decouples the real-time pricing and fulfillment decisions, making it easy to implement. We show theoretically and numerically that the second heuristic control significantly outperforms the first heuristic control and is very close to a benchmark that jointly reoptimizes the full deterministic problem at the beginning of every period. The online appendix is available at https://doi.org/10.1287/msom.2017.0641 .
Trinta anos da escala Clinical Dementia Rating: o que sabemos sobre o CDR?
Authors: Pinto Roberta Borlido Ribeiro , Perez Mariangela 
Published: March 2018

Introdução: Há uma crescente demanda por instrumentos padronizados, tanto para o rastreio quanto para o diagnóstico de demência, em ambientes de assistência e de pesquisa. A escala Clinical Dementia Rating (CDR) foi desenvolvida há 30 anos, permite uma avaliação global cognitiva e funcional, e foi submetida a adaptações ao longo dos anos. Objetivos: Detalhar o desenvolvimento do CDR, com ênfase na cronologia das principais publicações e nas validações disponíveis no Brasil. Método: Revisão narrativa por meio de busca eletrônica no Pubmed e em referências bibliográficas dos artigos identificados. Foram selecionados 23 artigos. Resultados: O CDR foi desenvolvido por Hughes no Memory Aging Project, da Universidade de Washington, em 1977, e publicado no Bristish Journal of Psychiatry, em 1982. É composto por um questionário estruturado e uma escala que avaliam seis domínios cognitivos: memória, orientação, julgamento e resolução de problemas, assuntos da comunidade, casa e lazer e autocuidado. Os indivíduos são classificados em quatro categorias: 0 = ausência de demência; 0.5 = demência questionável; 1 = demência leve; 2 = demência moderada; e 3 = demência avançada. Em 2008, uma simplificação da pontuação foi proposta e validada, usando a soma de cada domínio, chamada Sum of Box (CDR-SOB). No Brasil, foram identificados dois estudos de validação do CDR e um estudo do uso do CDR-SOB. Conclusões: O CDR é um instrumento útil com alta confiabilidade na avaliação das demências, com duas validações disponíveis no Brasil. As versões mais recentes parecem possibilitar uma melhor avaliação dos estágios iniciais dos quadros demenciais.Descritores: Clinical Dementia Rating; Validação; Demência.
Identifying the Correlates and Barriers of Future Planning Among Parents of Individuals With Intellectual and Developmental Disabilities
Authors: Burke Meghan , Arnold Catherine , Owen Aleksa 
Published: March 2018

Abstract
Although individuals with intellectual and developmental disabilities (IDD) are living longer lives, fewer than half of parents of individuals with IDD conduct future planning. The correlates and barriers to future planning must be identified to develop targeted interventions to facilitate future planning. In this study, 388 parents of individuals with IDD responded to a national, web-based survey. Participants who were older, more educated, attended more parent training and support activities, and had children with fewer functional abilities, were more likely to engage in future planning. Reported barriers to future planning included: (a) lack of available services, (b) financial challenges, (c) reluctance of family members, (d) lack of time, (e) the emotional nature of future planning, (f) inertia, and (g) a lack of family members to be caregivers. Implications for policy, practice, and future research are discussed.
Comparison of mechanical and wearing properties between LM13 matrix and Stir cast LM13/B4C/Gr hybrid composites of various composition
Authors: Faisal M.H. , Prabagaran S. , Vishnu T.S. 
Published: March 2018

Aluminium/graphite composites are the need of modern times for addressing the fuel saving issues. The graphite in such composites act as solid lubricant and it reduce external fuel requirements. But such composites are having degraded mechanical properties due to the graphite content in composite. In order to solve the negative effect of graphite on mechanical properties of LM13/Gr self-lubricating composite this study was conducted to find out the mechanical properties of LM13/B4C/Gr Metal Matrix Composites. Boron carbide was selected as reinforcement because of its better reinforcement properties compared to alumina and silicon carbide. The properties of the hybrid composites were compared with the LM13/Gr self-lubricating composite to study the enhancement in mechanical properties that has been caused by the boron carbide particles. Using computerized universal testing machine and rock-well hardness tester mechanical properties such as hardness and tensile strength were tested. Pin on disk testing machine was used to analyse the wear behavior. The test results indicates that by raising weight % of boron carbide particles in the LM13, tensile strength and hardness of the hybrid composites was increased compared to self-lubricating composite accompanied by better tribological properties.
Scalable dynamic key management for location based services
Authors: Ramamani S. , Karthika S. 
Published: March 2018

A Scalable key management for enforcing spatial-quality access control on public broadcast services. This authorization model is used to construct Authorization keys using efficient, secure and scalable Hierarchical key. Secure media broadcast over Internet poses unique security challenges. One important problem for public broadcast location- services (LBS) is to enforce access control on a large number of subscribers. This is achieved by providing an authorization model in constructing authorization keys using efficient, secure and scalable Hierarchical key graphs. And minimizes number of keys that needs to be distributed is thus scalable to a large number of subscribers and the dimensionality of the authorization model. In an offline basis the map viewer is loaded with collection of tiles or segments. The entire map is not loaded fully. If the user key and the segment key is matched with each other then the requested regions are loaded and displayed. Otherwise is blocked for the unauthorized user.
Ontology based search result optimisation using singular matrix
Authors: Divya R. , Angel Latha Mary S. 
Published: March 2018

In recent era, today a many firms share their service/product descriptions. With that, many meaningful information in the textual form is hidden under the unstructured text. Algorithms like information extraction enable the identification of structured relations and they does not produce an optimal result and it is much costlier to operate with headlines of a text which has no examples of the target structured information. We propose a new approach which facilitates the formation of a structured metadata by recognizing documents which are likely to have some type and this information is to be subsequently used for both segregation and search process. Our approach is based on an idea that some attributes of a text will match with the query object which acts as identifier both for segregation as well as for storage and retrieval. Our implementation results show that our approach provides some superior results than existing approaches which rely only on query content or on textual information, to discover the key attributes.
An advanced ilrcpsd technique for bridging the competency and cognitive skills of students in higher education
Authors: Christy A. Joy 
Published: March 2018

Data mining refers to the extraction of meaningful knowledge from large data sources as it may contain hidden potential facts. In general the analysis of data mining can either be predictive or descriptive. Predictive analysis of data mining interprets the inference of the existing results so as to identify the future outputs and the descriptive analysis of data mining interprets the intrinsic characteristics or nature of the data. Clustering is one of the descriptive analysis techniques of data mining which groups the objects of similar types in such a way that objects in a cluster are closer to each other than the objects of other clusters. K-means is the most popular and widely used clustering algorithm that starts by selecting the k-random initial centroids as equal to number of clusters given by the user. It then computes the distance between initial centroids with the remaining data objects and groups the data objects into the cluster centroids with minimum distance. This process is repeated until there is no change in the cluster centroids or cluster members. But, still k-means has been suffered from several issues such as optimum number of k, random initial centroids, unknown number of iterations, global optimum solutions of clusters and more importantly the creation of meaningful clusters when dealing with the analysis of datasets from various domains. The accuracy involved with clustering should never be compromised. Thus, in this paper, a novel classification via clustering algorithm called Iterative Linear Regression Clustering with Percentage Split Distribution (ILRCPSD) is introduced as an alternate solution to the problems encountered in traditional clustering algorithms. The proposed algorithm is examined over an educational dataset to identify the hidden group of students having similar cognitive and competency skills. The performance of the proposed algorithm is well-compared with the accuracy of the traditional k-means clustering in terms of building meaningful clusters and to prove its real time usefulness.
Development of surface coating for underwater concrete structures
Authors: Sharmila S , Keerthana P 
Published: March 2018

Surface coating is the most focused research problem in the construction sites to repair the deteriorated concrete. Surface coating is an most necessary process to be performed in concrete to avoid the issues such as aesthetics, sealing, chemical resistance or abrasion resistance. These coatings are termed as special resins with proper compositions of materials which can prevent the transmission of water and contaminants while at the same time keeping the structure safe. This research work focuses on preparation of surface and the protective surface coating to protect the concrete. High performance coal tar with polyurethane coating materials are used to protect concrete from chemical and mechanical attack in interior, exterior and marine environments. Coal tar with polyurethane coating systems consist of two or more components blended and applied as a film, reacted chemically to form a protective film of high integrity, excellent adhesion, toughness and impact resistance. The coating were applied on 4”x4”x4” concrete cubes and kept for one week curing the samples, thickness of the coating were ~70±5μm measured using hegman gauge. The tests such as Abrasion resistance, pull off test, water absorption test, chloride resistance test and Rapid chloride penetration testwere performed and the results exemplifies that coal tar mixed with polyurethane coating can be used for underwater concrete structures.
Smart farming: disease detection in crops
Authors: Balram G , Kiran Kumar K 
Published: March 2018

Automation in the market has been for decades now in the market. These systems run all through the day but there has not been any design which regards to identifying and classifying objects in specific and giving apt solution to them. Latest technologies like image processing and advanced machine learning mechanisms have become the core of the science and innovations. Our project’s idea is a broad concept that integrates various subjects and generates solutions to energy saving, cooling, automation and structural design. To get the desired results, above are the few constraints which play a major role in yielding high productivity from the crops. And besides them, the classification of objects through image processing and machine learning is used instead of the man power to accomplish the target to reduce the amount of hardware used
A brief exploration of fog computing architecture, technologies and challenges
Authors: Challa Ramaiah , Kiran Kumar K 
Published: March 2018

Now a day’s IoT systems are being used in rapid rate, so much data is being generated by massive ubiquitous things handling of that much data is not a simple issue it very critical task. Then again, despite the fact that that distributed computing has filled in as an efficient approach to process and store these information, in any case, challenges, for example, the expanding requests of ongoing or dormancy delicate applications and the impediment of system data transfer capacity, still can't be tackled by utilizing just cloud computing. Accordingly, another computing known as fog computing was proposed as extension of cloud computing. It brings the cloud services that are communication, computation and storage near to edge devices and users so latency can be reduced. In this papers details of fog computing are discussed.
Implementation methodology for android application development
Authors: Babu Bulli , Naveen Jada , Rajinikanth Kondaveeti , Sai Ram Krishna Pothagani 
Published: March 2018

As the tuning flow of the modern world of technology, the mobile APKs are tremendous extracting segment of the globalization smart marketing technology. smart APKs applications are involving to a meteor pace to rise level of n utilizes and users a rich in report. AS on the paper , Android Platform for the developing the mobile applications. Firstly, we are Here To explain about the develop the android application as by our learnt knowledge we have created the application According to my college Website as the Business users pattern mode. Majorly we have to describe in this app is website users have to use the systems to check the recent updates and announcements and other regarding the things about related to the academic details. for that sake we have created the application by the tutorial knowledge and basics. This app can used as same as website with as the single tap in the smart mobile. As we are tried the app as best as possible manner in our way of our knowledge. This knowledge and creation of our works we have learnt lots things .I acquired good progress report in the creation of the application.
Facial recognition enabled smart door unlock system
Authors: Vamsi Krishna M , Bhargav Reddy A , Sandeep V 
Published: March 2018

To verify that our daily life is going in a secure way. Lot of research programmers are going on in this entire society. The turning point comes through the internet of things, industry has been emerged with the lots of elements provided from IOT. We can able to connect our daily life things or objects with this had successfully evolved lots of things. This Facial recognition door unlock system is a process is which will detect the face and identifies the among people. People are having different types of face cut, in that particularly there are many unique faces which are different from each other which inspired us, from that concept this process has been established. Our main aim to create the smart door system to a house, that will secure the house and all your personal things at your home. In this concept of our system we have been used alive web camera in the front side of the door, along with the display monitor. this web camera shows the owner/particular viewer the whom the house is his control, this shows the person who stood front of the door, the system is setup the voice output is being processed by the processor that which is used to show the answers/instructions as the output on the screen. We are using a stepper motor that which is used to lock/open then the by sliding method, so that a normal person stand in front of the door and access it. This process is done through this Microsoft face API application. The display is being operated on a Microsoft Visual Studio application.