bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparison of Two At-home Whitening Products of Similar Peroxide Concentration and Different Delivery Methods
Authors: da Costa JB , McPharlin R , Hilton T , Ferracane JL , Wang M 
Published: March 2012

SUMMARY

Purpose
This study compared the whitening efficacy, side effects, and patients' preferences/perceptions of two whitening systems of similar peroxide concentration but different formulation and delivery methods.

Methods
The tooth color change of 24 participants was measured using a shade guide (BSG) and a spectrophotometer (ES). Color difference was calculated: ΔE* = [(ΔL*)2 + (Δa*)2 + (Δb*)2]1/2. One whitening treatment was randomly applied to the right or left maxillary anterior teeth and the other was applied to the contralateral teeth, at-home with 35% carbamide peroxide in a tray (TW) or with 14% hydrogen peroxide in strips (WS). The tooth color was evaluated at baseline, 15 and 30 days (15 days postwhitening). Participants rated their tooth and soft tissue sensitivity (1–10 scale) and completed a questionnaire on their preferences. Results were analyzed by repeated measurement regression analysis/Tukey and Mann-Whitney (p&lt;0.05).

Results
At 15 days, the teeth treated with TW and WS presented ΔE* = 7 and 6, respectively (ΔBSG=3 for both), and at 30 days, they presented ΔE* = 7.5 and 6.5, respectively (ΔBSG=3 for both). There was no significant difference in tooth and soft tissue sensitivity between treatments. No participant reported tooth and gingival sensitivity at the postwhitening appointment. Of the participants, 83% preferred the TW over WS.

Conclusion
Both ΔE* and ΔBSG showed no significant difference in tooth color change between TW and SW at either time point. By the end of the study no participants reported tooth and gingival sensitivity. Participants preferred TW over SW.
User Response to the Simulation of a Virtual Patient with Cranial Nerve Injury
Authors: Lin Chen , Laserna Candelario , Lind D. Scott , Kalaria Chandni , Aryal Tia , Lok Benjamin , Johnsen Kyle , Kotranza Aaron , Cendan Juan , Pruitt J. Ned 
Published: March 2012

Abstract
Technology has rarely attempted to simulate a CN exam. NERVE simulates a life-size virtual patient (VP), using speech recognition with a Nintendo Wiimote� serving as a virtual hand, ophthalmoscope, and eye-chart. This study assesses the introductory reception, ability to identify the CN lesion, and students' preference of NERVE. Our goal is to evaluate the responses from medical students, residents, and clinicians using the Neurological Examination Rehearsal Virtual Environment (NERVE), a cranial nerve (CN) exam simulator. Medical College of Georgia participants from a variety of medical specialties, including 9 clinicians, 7 residents, and 8 MS3 and 4s, 20 MS 2s, and 25 MS 1s performed a CN examination on a VP. There were no statistically significant differences in measures related to the actual performance of the exam, the controller, overall benefit of the experience, use of technology or satisfaction with the technology. Even with technical limitations, overall medical student's reported NERVE having educational value. Residents had the lowest rate of correct CN identification, indicating they could be the group that most benefits from repeat exposure to CN exams. Medical students and clinicians were the best groups at identifying the correct deficit for our simulation. The next step is to assess NERVE's capability to teach students and residents the cranial nerve exam.
Automatic Protein Abbreviations Discovery and Resolution from Full-Text Scientific Papers: The PRAISED Framework
Authors: Toti Daniele , Atzeni Paolo , Polticelli Fabio 
Published: March 2012

Abstract
This paper describes a methodology for discovering and resolving protein names abbreviations from the full-text versions of scientific articles, implemented in the PRAISED framework with the ultimate purpose of building up a publicly available abbreviation repository. Three processing steps lie at the core of the framework: i) an abbreviation identification phase, carried out via domain-independent metrics, whose purpose is to identify all possible abbreviations within a scientific text; ii) an abbreviation resolution phase, which takes into account a number of syntactical and semantic criteria in order to match an abbreviation with its potential explanation; and iii) a dictionary-based protein name identification, which is meant to select only those abbreviations belonging to the protein science domain. A local copy of the UniProt database is used as a source repository for all the known proteins.
The PRAISED implementation has been tested against several known annotated corpora, such as the Medstract Gold Standard Corpus, the AB3P Corpus, the BioText Corpus and the Ao and Takagi Corpus, obtaining significantly high levels of recall and extremely fast performance, while also keeping promising levels of precision and overall f-measure, in comparison to the most relevant similar methods. This comparison has been carried out up to Phase 2, since those methods stop at expanding abbreviations, without performing any entity recognition. Instead, the entity recognition performed in the last phase provides PRAISED with an effective strategy for protein discovery, thus moving further from existing context-free techniques. Furthermore, this implementation also addresses the complexity of full-text papers, instead of the simpler abstracts more generally used. As such, the whole PRAISED process (Phase 1, 2 and 3) has been also tested against a manually annotated subset of full-text papers retrieved from the PubMed repository, with significant results as well.
A survey of FPGA implementations of Artificial Spiking Neurons Models
Authors: Maślanka Michał , Gorgoń Marek 
Published: March 2012

Abstract
Spiking Neural Networks (SNNs) seems to be now the best way to model and simulate brain structures and functions. SNNs give also possibilities to better understanding of mechanism that are responsible for consciousness and abstract thinking. Furthermore they can also change our look on information processing and modern computing. Most common software implementations need great computing power and because of that they are not suitable for real time applications. Additionally, biological neurons process information in parallel which is impossible with simulation on conventional computer. Thus we present alternative way to implement models of SNNs incorporating FPGAs. In this paper we compared most common models that are used to implement SNNs in reconfigurable hardware and also we made review of recent works that were done in this subject.
New Approach to Prostate Diagnosis - Perfusion CT Images Analysis using "Life Belt" Method
Authors: Śmietański Jacek , Tadeusiewicz Ryszard 
Published: March 2012

Abstract
The most important task that could improve the efficacy of managing the prostate cancer (PCa) is to develop the technique which will be able to detect an existing PCa even in cases when currently used methods are insufficient.
It is supposed that the perfusion computed tomography technology (p-CT) can improve the diagnosis of early PCa. Unfortunately, the perfusion prostate images are very difficult to analyze especially for doctors who are not enough experienced with such a kind of images. Therefore there is a need to find a computational method which could help the doctors to make the decision whether the prostate cancer exists or not and (if the results are positive) to correctly point out the cancerous region.
In research which results are presented in the paper we analyzed a great number of prostate images derived from over 50 patients with proven or suspected PCa. We propose the new method, named "life-belt" which has significant potential for identifying cancerous regions.
A Quadratic Convergence Yielding Iterative Method for Nonlinear Ill-posed Operator Equations
Authors: George Santhosh , Elmahdy Atef Ibrahim 
Published: March 2012

AbstractIn this paper, we consider an iterative method for the approximate
solution of the nonlinear ill-posed operator equation Tx = y. The
iteration procedure converges quadratically to the
unique solution of the equation for the regularized approximation. It is known that (Tautanhahn (2002)) this solution converges
to the solution of the given ill-posed operator equation. The convergence analysis and
the stopping rule are based on a suitably constructed majorizing
sequence. We show that the adaptive scheme considered by
Perverzev and Schock (2005) for choosing the regularization
parameter can be effectively used here for obtaining an optimal
order error estimate.
Computer Integrated Enterprise in the MRP/ERP Software Implementation
Authors: Kamiński Andrzej 
Published: March 2012

Computer Integrated Enterprise in the MRP/ERP Software Implementation
The aim of this elaboration is to present selected methodology, application and design issues connected with the process of complex enterprise informatization in the implementation process of an IT system. Role of the integration process in economic information processing and directions of integration activities in the scope of the IT systems of the enterprise are presented in the first part of this elaboration. Afterwards, technical features of an integrated IT system are characterized. Thesis that particular systems are comparable in the scope of functionality of the basic areas of activity of the enterprise, such as: accounting, material and stock planning, sales and invoicing, human resources, wages, can be formulated on the basis of the national portfolio of ERP (Enterprise Recourses Planning) packages. On the other hand, the cost of license purchase as well as the implementation activities, reaches the level from tens of thousands to few million PLN. Differences in the levels of investments are determined with: scope and complexity of the endeavor, functionality and system architecture as well as the cost of extension and modification of provided program modules.
Functional Enhancements to Project Management Information Systems
Authors: Moszkiewicz Jacek , Rostek Katarzyna 
Published: March 2012

Functional Enhancements to Project Management Information SystemsPresented research work relates to information systems of projects management support. The aim of the work is to propose solutions, that will help achieve improved efficiency of information systems class PMIS implementations (Project Management Information System) especially given the scope of functionalities and implementation process realization. Presented in this article research results were obtained in the analysis of projects implemented in enterprises of the sector: construction and building, service with particular emphasis on the IT industry, and investment. Summary of the article includes both the results of the research analysis and proposed directions for their further development.
How to Perform Discounted Cash Flow Valuation?
Authors: Janiszewski Sławomir 
Published: March 2012

How to Perform Discounted Cash Flow Valuation?Within the last few decades the quickly accelerating globalization processes contributed to rapid increase in the value of the global capital markets, and mergers and acquisitions transactions. This implicated the rising importance of methodologies that enable investors to efficiently value the companies. The aim of this elaboration is to present practical approach towards the discounted cash flow company valuation method, considered one of the most effective but simultaneously one of the most sophisticated among all. The article comprises purely theoretical as well as practical knowledge, based on the author's broad professional experiences.
Evaluation of the Effects of Quality Management System Improvement
Authors: Szczepańska Katarzyna , Urbaniak Maciej 
Published: March 2012

Evaluation of the Effects of Quality Management System ImprovementThe article presents the tools that enable organizations to assess the effects of improvement of the quality management system, such as internal and external audits; risk management, measures of effectiveness and efficiency of processes, evaluation of customer satisfaction, quality cost analysis; analysis of best practices and self-assessment. The effectiveness use of these tools depends on the progress of the efforts of organizations in activities related to its improvement, knowledge and skills of employees and managers, who should show the positive attitude of leadership and involvement.
Soil microbial activity as influenced by compaction and straw mulching
Authors: Siczek A. , Frąc M. 
Published: March 2012

Soil microbial activity as influenced by compaction and straw mulchingField study was performed on Haplic Luvisol soil to determine the effects of soil compaction and straw mulching on microbial parameters of soil under soybean. Treatments with different compaction were established on unmulched and mulched with straw soil. The effect of soil compaction and straw mulching on the total bacteria number and activities of dehydrogenases, protease, alkaline and acid phosphatases was studied. The results of study indicated the decrease of enzymes activities in strongly compacted soil and their increase in medium compacted soil as compared to no-compacted treatment. Mulch application caused stimulation of the bacteria total number and enzymatic activity in the soil under all compaction levels. Compaction and mulch effects were significant for all analyzed microbial parameters (P<0.001).
Comparison of soil texture determined by two dispersion units of Mastersizer 2000
Authors: Sochan A. , Bieganowski A. , Ryżak M. , Dobrowolski R. , Bartmiński P. 
Published: March 2012

Comparison of soil texture determined by two dispersion units of Mastersizer 2000The comparison of particle size distributions measured by sedimentation methods and laser diffraction shows the underestimation of the fine (clay) fraction. This is attributed mainly to the shape of clay particles being different than spherical. The objective of this study was to demonstrate differences in the results of particle size distributions of soils determined with the method of laser diffraction using two different dispersion units of the Malvern Mastersizer 2000.
In-Hospital Use of Long-Acting Injectable Antipsychotics and Readmission Risk in Patients With First-Admission Schizophrenia in Taiwan
Authors: Chen Wei , Wu Chi-Shin , Liu Chen-Chung , Kuo Po-Hsiu , Chan Hung-Yu , Lin Yi-Hsuan , Chung Yu-Chu Ella , Chen Wei J. 
Published: June 2024

ImportanceLong-acting injectable antipsychotics (LAIs) can help decrease the rate of nonadherence to medications in patients with schizophrenia, but these drugs are underutilized in clinical practice, especially in Asian countries. One strategy for the early prescription of LAIs is to administer the drugs during patients’ first admission, when they have more time to absorb medication-related knowledge.ObjectiveTo estimate the prevalence of and risk factors for in-hospital use of LAIs among first-admission patients with schizophrenia in Taiwan and to examine the association of early discontinuation with readmission risk among patients receiving LAIs.Design, Setting, and ParticipantsThis cohort study included data from a claims database for patients with a first admission for schizophrenia at psychiatric wards in Taiwan from 2004 to 2017. Eligible patients were diagnosed with schizophrenia or schizoaffective disorder at discharge and aged between 15 and 64 years. Data analysis was performed from April to September 2022.ExposureIn-hospital use of LAIs with or without early discontinuation.Main Outcome and MeasuresReadmission for any psychotic disorder following discharge from first admission, with risk estimated via multivariable survival regression analysis, including the Cox proportional hazards (CPH) model and accelerated failure time (AFT) model.ResultsOf the 56 211 patients with a first admission for schizophrenia (mean [SD] age, 38.1 [12.1] years; 29 387 men [52.3%]), 46 875 (83.4%) did not receive any LAIs during admission, 5665 (10.1%) received LAIs with early discontinuation, and 3671 (6.5%) received LAIs without early discontinuation. The prevalence of receiving LAIs increased by 4%, from 15.3% (3863 of 25 251 patients) to 19.3% (3013 of 15 608 patients) between 2004-2008 and 2013-2017. After controlling for sex, year, prior antipsychotic use, age at first admission, and length of stay, the CPH regression analysis revealed that the readmission risk increased among patients receiving LAIs with early discontinuation (adjusted hazard ratio [aHR], 1.25; 95% CI, 1.21-1.30) but decreased among patients receiving LAIs without early discontinuation (aHR, 0.88; 95% CI, 0.84-0.92) compared with patients not receiving LAIs. Results remained similar for the AFT model.Conclusions and RelevanceThe incidence of in-hospital use of LAIs among patients with a first admission for schizophrenia has remained low. In this study, early discontinuation of LAIs was associated with readmission risk—specifically, early discontinuation with a higher risk while the lack of early discontinuation with a lower risk compared with treatment with oral antipsychotics alone—which suggests our results have implications for improving the efficacy of LAI administration among patients with a first admission for schizophrenia.
Being confident in confidence scores: calibration in deep learning models for camera trap image sequences
Authors: Dussert Gaspard , Chamaillé‐Jammes Simon , Dray Stéphane , Miele Vincent 
Published: June 2024

AbstractIn ecological studies, machine learning models are increasingly being used for the automatic processing of camera trap images. Although this automation facilitates and accelerates the identification step, the results of these models may lack interpretability and their immediate applicability to ecological downstream tasks (e.g. occupancy estimation) remains questionable. In particular, little is known about their calibration, a property that allows confidence scores to be interpreted as probabilities that model's predictions are true. Using a large and diverse European camera trap dataset, we investigate whether deep learning models for species classification in camera trap images are well calibrated. Additionally, as camera traps are often configured to take multiple photos of the same event, we also explore the calibration of predictions aggregated across sequences of images. Finally, we study the effect and the practicality of a post‐hoc calibration method, i.e. temperature scaling, for predictions made at image and sequence levels. Based on five established models and three independent test sets, we show that averaging the logits over the sequence, selecting an appropriate architecture, and optionally using temperature scaling can produce well‐calibrated models. Our findings have clear implication for, for instance, the calculation of error rates or the selection of confidence score thresholds in ecological studies making use of artificial intelligence models.
Deep learning and satellite remote sensing for biodiversity monitoring and conservation
Authors: Pettorelli Nathalie , Williams Jake , Schulte to Bühne Henrike , Crowson Merry 
Published: June 2024

AbstractIn the context of the current nature crisis, being able to reliably and cost‐effectively track subtle changes in the biosphere across adequate spatial and temporal extents and resolutions is crucial. Deep learning represents a group of versatile approaches to image processing tasks that are increasingly combined with satellite remote sensing imagery to monitor biodiversity and inform ecology and conservation, yet an overview of the opportunities and challenges associated with this development has so far been lacking. Here, we provide an interdisciplinary perspective on current research and technological developments associated with satellite remote sensing and deep learning that have the potential to make a difference in biodiversity monitoring and wildlife conservation; highlight challenges to the broader adoption of these approaches by experts operating at the interface between satellite remote sensing and ecology and conservation; and discuss how these can be overcome. By enabling the leveraging of big data and by providing new ways to learn about biodiversity and its dynamics, deep learning approaches promise to become a powerful tool to help address current monitoring needs and knowledge gaps. In certain situations, deep learning approaches may moreover substantially reduce the time and resources required to analyse satellite imagery. However, issues relating to capacity building, reference data access, environmental costs as well as model interpretability, robustness and alignment need to be addressed to successfully capitalize on these opportunities.
GABA-fortified synbiotic guava beverage: formulation and evaluation of neuroprotective properties using cell-based assays
Authors: Divyashri G. , Suprajaa V. , Nairy Chirag Umesh , Sastry Aditi , Sanjana R. M. , Sharada B. , Murthy T. P. Krishna 
Published: June 2024

AbstractIn recent years, the use of fermented fruit juices to offer protection against mental illness has been increasing enormously. The present study, aimed at formulating a synbiotic fruit beverage for mental well-being using fructo-oligosaccharide (FOS), Gamma-aminobutyric acid (GABA) and Lactobacillus rhamnosus. Guava extract (abbreviated as fruit extract, FE; 10%) supplemented with FOS (1%) fermented for 48 h using L. rhamnosus, was then fortified with 0.05% GABA (FE + FOS + GABA). This GABA-fortified fermented guava beverage exhibited significant in-vitro antioxidant activity as measured by using 2,2-diphenyl-1-picrylhydrazyl (IC50 value of 0.451 ± 0.05 mg/ml) and ferrous reducing antioxidant capacity (A700 nm value of 0.68 ± 0.06) assays. Fermentation also enhanced total phenolics and flavonoids by 27.63% and 27.41%, respectively. Furthermore, GABA-fortified fermented guava beverage showed a significant neuroprotective effect by negatively modulating oxidative stress and upregulating activity of antioxidant enzymes (superoxide dismutase and catalase) in rotenone treated neuronal cell lines. Taken together, our research findings clearly indicate the propensity of GABA-fortified fermented guava beverage to protect against rotenone mediated neuronal cell damage. Even though the underlying molecular mechanisms need further research, in conclusion, our study demonstrates that the GABA-fortified fermented guava beverage effectively confers neuroprotective effects in vitro, suggesting its potential as a functional beverage for promoting brain health.
Graphical Abstract