Aid Of Tools Research Articles

Factors of interregional poverty differentiation: Absolute and deprivation approaches

Subject. This article examines the socio-demographic and economic factors of interregional differentiation of absolute poverty and material deprivation in the regions of the Siberian Federal District. Objectives. The article aims to analyze the changes in the poverty rate and identify socio-demographic and economic factors of interregional differentiation of poverty by income and material deprivation. Methods. For the study, we used the methods of correlation analysis, synthesis, and comparison. Results. The article reveals a persistent direct relationship between absolute poverty, the prevalence of material deprivation, and certain factors. Conclusions. Regional policies to reduce absolute and deprivation poverty should be based on understanding the various factors that cause poverty, and using effective aid tools.

Whole-Tumor Histogram and Texture Imaging Features on Magnetic Resonance Imaging Combined With Epstein-Barr Virus Status to Predict Disease Progression in Patients With Nasopharyngeal Carcinoma.

Purpose: We aimed to investigate whether Epstein–Barr virus (EBV) could produce differences on MRI by examining the histogram and texture imaging features. We also sought to determine the predictive value of pretreatment MRI texture analyses incorporating with EBV status for disease progression (PD) in patients with primary nasopharyngeal carcinoma (NPC).Materials and Methods: Eighty-one patients with primary T2-T4 NPC and known EBV status who underwent contrast-enhanced MRI were included in this retrospective study. Whole-tumor-based histogram and texture features were extracted from pretreatment T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), and contrast-enhanced (CE)-T1WI images. Mann–Whitney U-tests were performed to identify the differences in histogram and texture parameters between EBV DNA-positive and EBV DNA-negative NPC images. The effects of clinical variables as well as histogram and texture features were estimated by using univariate and multivariate logistic regression analyses. Receiver operating characteristic (ROC) curve analysis was used to predict the EBV status and PD. Finally, an integrated model with the best performance was built.Results: Of the 81 patients included, 54 had EBV DNA-positive NPC, and 27 had EBV DNA-negative NPC. Patients who were tested EBV DNA-positive had higher overall stage (P = 0.016), more lymphatic metastases (p < 0.0001), and easier distant metastases (P = 0.026) than the patients who were tested EBV DNA-negative. Tumor volume, T1WISkewness and T2WIKurtosis showed significant differences between the two groups. The combination of the three features achieved an AUC of 0.783 [95% confidence interval (CI) 0.678–0.888] with a sensitivity and specificity of 70.4 and 74.1%, respectively, in differentiating EBV DNA-positive tumors from EBV DNA-negative tumors. The combination of overall stage and tumor volume of T2WIKurtosis and EBV status was the most effective model for predicting PD in patients with primary NPC. The overall accuracy was 84.6%, with a sensitivity and specificity of 93.8 and 66.2%, respectively (AUC, 0.800; 95% CI 0.700–0.900).Conclusion: This study demonstrates that MRI-based radiological features and EBV status can be used as an aid tool for the evaluation of PD, in order to develop tailored treatment targeting specific characteristics of individual patients.

Effects of patient decision aids in patients with type 2 diabetes mellitus: A systematic review and meta-analysis.

This study aimed to systematically evaluate the effectiveness of patient decision aids on knowledge, decisional conflict and decisional self-efficacy outcomes in patients with diabetes. A comprehensive database search was performed using the Web of Science, Cochrane Library, PubMed, Embase, PsycINFO (Ovid), CINAHL (EBASCO), CNKI, VIP, Wan Fang Database and the Ottawa Decision Aid Library Inventory (http://decisionaid.ohri.ca/index.html) from inception to 13 October 2019. Two reviewers independently searched databases, screened articles, extracted data and evaluated the risk bias of included studies. Then Rev Man 5.3 software was adopted for statistical analysis. Ten articles containing 1,452 people with diabetes were selected. The results of meta-analysis showed that patient decision aids had a positive effect on reducing decisional conflict and improving decisional self-efficacy among patients with type 2 diabetes. Meanwhile, this article also revealed that patient decision aids have beneficial short-term effects on improving knowledge, but there was no significant long-term effect. Patient decision aids are capable of becoming support tools to improve shared decision making. Further implementation studies are required to transform patient decision aids tools into clinical practice.

Arbovirus Rash in the Febrile Returning Traveler as a Diagnostic Clue.

Purpose of ReviewThis review aims to describe briefly the general information of arboviruses dengue, Zika, and chikungunya infections and emphasize the clinical manifestations of each, to help identify and make a quick diagnosis of each.Recent FindingsThe most relevant advances in the study of these arboviruses’ infections have been in the epidemiological distribution, mainly due to international travel, migration, and climate change; in the clinical manifestations of these diseases, the development of clinical decision-making software, which can help improve the management and outcomes of these patients; and in the prevention of this disease.SummaryAlthough arboviruses infections constitute a clinical challenge for the attending physician in the scope of a febrile returning traveler, a thorough clinical history and exam can help to aid diagnostic reasoning. The characteristics of the rash are a very helpful clue in the evaluation of these patients. Currently, there are clinical decision aid tools that help to get the diagnosis more quickly.

An Interpretable Aid Decision-Making Model for Flag State Control Ship Detention Based on SMOTE and XGBoost

The reasonable decision of ship detention plays a vital role in flag state control (FSC). Machine learning algorithms can be applied as aid tools for identifying ship detention. In this study, we propose a novel interpretable ship detention decision-making model based on machine learning, termed SMOTE-XGBoost-Ship detention model (SMO-XGB-SD), using the extreme gradient boosting (XGBoost) algorithm and the synthetic minority oversampling technique (SMOTE) algorithm to identify whether a ship should be detained. Our verification results show that the SMO-XGB-SD algorithm outperforms random forest (RF), support vector machine (SVM), and logistic regression (LR) algorithm. In addition, the new algorithm also provides a reasonable interpretation of model performance and highlights the most important features for identifying ship detention using the Shapley additive explanations (SHAP) algorithm. The SMO-XGB-SD model provides an effective basis for aiding decisions on ship detention by inland flag state control officers (FSCOs) and the ship safety management of ship operating companies, as well as training services for new FSCOs in maritime organizations.

A game proposal for teaching math operations to 6th / 9th grade students

The purpose of this work is to serve as an aid tool for the teacher, for the students and for the development of the classes, however, we hope that the game is developed in an appropriate way so that it does not harm their performance. The objective of this work is to analyze the possibilities of teaching / learning of mathematical operations from the application of the game "the awakening of mathematics" for 6th and 9th grade students. The work methodology was developed for the students in order to solve such difficulties that some students were presenting during the math classes, developed from cardboard paper, A4 paper in 9x9 square format (9 squares in height and width), containing a total of 81 cells on the board, where the mental calculation of the four mathematical operations is proposed. It was realized that the use of the game should not be applied only as a means of interaction between students, therefore, if the teacher proposes the game as a teaching strategy, he should treat it as a vehicle for building knowledge, creating and experimenting.

Vertalen in het vreemdetalenonderwijs: Wikipedia als didactisch hulpmiddel?

This article relates to the field of the didactics of foreign language teaching, and presents the results of a preliminary study carried out in order to determine the extent to which Wikipedia can be used as a didactic aid and learning tool in the translation lectures of foreign language teaching in the Master’s degree in Dutch at the John Paul II Catholic University of Lublin (Poland). In view of the free access to this online encyclopedia, on the one hand, and the richness of texts (in Polish and Dutch) with a cultural content on the other, we investigated to what extent Wikipedia translation can be successfully used as a tool in L2 translation classes. The increasing importance of technological tools (such as electronic dictionaries, terminological databases, and machine translation software) for translation and its use in language teaching, on the one hand, and, on the other, the fact that Polish graduates in Dutch philology often work as translators, were the starting point for this research, which was conducted as a preliminary phase (case study) of a more extensive study into the practical application of Wikipedia translation activities in language acquisition classes.

A Survey on the Application of Educational Lighting Board as an Educational Aid Tool of Occupational Health Students

A Survey on the Application of Educational Lighting Board as an Educational Aid Tool of Occupational Health Students

A Decision Support Framework for National Crop Production Planning

This paper proposes a decision support framework for defining planning parameters for national crop production. The proposed framework addresses the gaps in policymaking, the role of all stakeholders, and uses historical data of crop production in different sectors of land in optimizing the profits that shall meet the defined constraints including national requirement, and export demand of different crops. There are many agro-economy-based countries where agriculture is the main contributor to their GDP, while there are others who always struggle to meet their national need while optimizing the agro-economy component of their earnings. Crops are not always produced with keeping the demand and production balance. Rather, the crops are mostly produced according to the farmer’s ease and last year’s prices for profit maximization leading to excessive production of one type of crop, lowering of profit margins, and shortage of some key crops for national need. This paper presents a decision aiding tool that can be used for farmer’s awareness for crop production planning that meets the national and export needs while maximizing farmer’s earnings. The model is tested on historical data of different segments of cultivated lands in Pakistan for validation, with the first experiment performed on single farmland with multi-fields while the second performed for multi-locations and multi-fields. The results are promising and provide estimates of net profit, expected production against the demand for each crop, and analysis that aids in crop planning, before and after the application of our model while meeting all necessary constraints.

COVID-19 identification from volumetric chest CT scans using a progressively resized 3D-CNN incorporating segmentation, augmentation, and class-rebalancing

The novel COVID-19 is a global pandemic disease overgrowing worldwide. Computer-aided screening tools with greater sensitivity are imperative for disease diagnosis and prognosis as early as possible. It also can be a helpful tool in triage for testing and clinical supervision of COVID-19 patients. However, designing such an automated tool from non-invasive radiographic images is challenging as many manually annotated datasets are not publicly available yet, which is the essential core requirement of supervised learning schemes. This article proposes a 3D Convolutional Neural Network (CNN)-based classification approach considering both the inter-and intra-slice spatial voxel information. The proposed system is trained end-to-end on the 3D patches from the whole volumetric Computed Tomography (CT) images to enlarge the number of training samples, performing the ablation studies on patch size determination. We integrate progressive resizing, segmentation, augmentations, and class-rebalancing into our 3D network. The segmentation is a critical prerequisite step for COVID-19 diagnosis enabling the classifier to learn prominent lung features while excluding the outer lung regions of the CT scans. We evaluate all the extensive experiments on a publicly available dataset named MosMed, having binary- and multi-class chest CT image partitions. Our experimental results are very encouraging, yielding areas under the Receiver Operating Characteristics (ROC) curve of 0.914±0.049 and 0.893±0.035 for the binary- and multi-class tasks, respectively, applying 5-fold cross-validations. Our method’s promising results delegate it as a favorable aiding tool for clinical practitioners and radiologists to assess COVID-19.

Multi-Class Probabilistic Atlas-Based Whole Heart Segmentation Method in Cardiac CT and MRI

Accurate and robust whole heart substructure segmentation is crucial in developing clinical applications, such as computer-aided diagnosis and computer-aided surgery. However, the segmentation of different heart substructures is challenging because of inadequate edge or boundary information, the complexity of the background and texture, and the diversity in different substructures’ sizes and shapes. This article proposes a framework for multi-class whole heart segmentation employing non-rigid registration-based probabilistic atlas incorporating the Bayesian framework. We also propose a non-rigid registration pipeline utilizing a multi-resolution strategy for obtaining the highest attainable mutual information between the moving and fixed images. We further incorporate non-rigid registration into the expectation-maximization algorithm and implement different deep convolutional neural network-based encoder-decoder networks for ablation studies. All the extensive experiments are conducted utilizing the publicly available dataset for the whole heart segmentation containing 20 MRI and 20 CT cardiac images. The proposed approach exhibits an encouraging achievement, yielding a mean volume overlapping error of 14.5% for CT scans exceeding the state-of-the-art results by a margin of 1.3% in terms of the same metric. As the proposed approach provides better results to delineate the different substructures of the heart, it can be a medical diagnostic aiding tool for helping experts with quicker and more accurate results.

A Novel LUTI Model Calibration Using Differential Evolution Algorithm

LUTI (Land-Use and Transportation Interaction) models are decision-making aid tools that simulate complex dynamic bilateral feedback between transportation and land-use models within a territory. Although calibration (parameter estimation) is a crucial requirement of LUTI models, fully automated approaches with the usage of multi-objective functions have not been fully addressed. To address this limitation, a generic calibration approach is proposed for the parameters of the land-use model using a differential evolution algorithm. A global sensitivity analysis was performed to identify the most important land-use model parameters. These parameters were then calibrated using the differential evolution algorithm with the Root Mean Square Error (RMSE) and Mean Absolute Normalized Error (MANE) as multi-objective functions. Five key capabilities are provided in the suggested technique for calibration of LUTI models including 1) global estimation rather than local estimation, 2) consideration of multi-objective functions, 3) continuously improving the results, 4) easily adaptability, and 5) involving multi parameters in the calibration process. The TRANUS land-use model was used to test the performance of the suggested calibration technique. The validation and consolidation of the approach were tested based on convergence, minimization of errors, and modeled/observed data ratio by comparing with the genetic algorithm and particle swarm optimization techniques. The suggested approach using a deferential evaluation algorithm outperformed both genetic and particle swarm optimization techniques and provided the most stable and diverse solutions.

Translation and validation of the LittlEars auditory questionnaire in Kannada

ObjectiveThe aim of the study was to translate and validate the LittlEARS Auditory Questionnaire (LEAQ) in Kannada. MethodThe translation procedure followed a traditional translation, back translation, and content validity process before administering. The finalized version was administered on 87 children with 67 normal hearing children and 20 hearing-impaired children. ResultsThe tool had good internal consistency, good reliability, and a norm curve could be established. The Cronbach alpha value for item correlation ranged from 0.26 to 0.79. A significant difference was found between normal hearing individuals and hearing impaired. ConclusionThe LEAQ tool has been translated and validated for the Kannada speaking population and can be used as a screening tool for children up to two years of age and as a subjective outcome measuring tool for hearing aid and Cochlear Implant user.

Pahlawan Qarin: The Concept of Collaborative Learning Game Environment in the Understanding and Translation of the Quran among Youngsters

Computer game can be engaging learning resources, motivators and interest drivers and, as a consequence, an efficient way to enhance student learning and success ineveryday educational practice.These computer game inspire youngsters speciallyto work incredibly hard, earning even-needed practice repeatedly.Research has consistently shown that Game-Based Learning (GBL) is a way of engaging users and appealing to various modes of learning.Pahlawan Qarinis a game-based framework designed to serve as a way of understanding and interpreting Al Quran to understand its meaning and use in everyday life. It is presented as a desktop(personal computer) game featuring a Collaborative Learning Game (CLG) in which more than one player can play in a group or room using the internet link (network) simultaneously (multiplayer feature).It can be used as an aid tool for teachers in the recitation and education of the Al Quran subject, which is also taught in schools in Islamic Studies.When collaboration with other partners is carried out, youngstersare seen to be highly active in a game playing session, thus motivating them to complete any assignment given.In future, effectiveness of Pahlawan Qarinon a broader sample volume (usage by more students and teachers) will be further studied.

Self-care of Frontline Health Care Workers: During COVID-19 Pandemic.

The world is amidst the COVID-19 pandemic that has used social distancing as a tool for containing the virus from spreading exponentially among other individuals. Previous literature suggests that human contact and attachment is a key for well-being which is why punishments like solitary confinement in detention centers like jail has always been debated as being torturous (Wolfendal 2020). With this notion, anxiety and stress may become more prevalent in individuals who experience self-isolation or are under a forced lockdown. For health-care workers like doctors and psychologists, who advocate for physical health, mental health and wellbeing; the challenges might increase during the pandemic phase as they are expected to go through the crises just like others while simultaneously contributing in rendering services related to dealing with physical and psychological health issues present in patients and clients with their continued practice from either on-site or online platforms. Although all health care professional's training inoculates the ill effects of compassion fatigue by other's overwhelming situations and discussions but they might still be prone to vicarious burnout, trauma and stress. Hence, they may become exposed to being at risk of experiencing anxiety more than the general population. This review discusses facets of the importance of self-care as mental health first aid tool for health care professionals including doctors and psychologists using research and supportive techniques to help them process stress and anxiety during and after the global pandemic.

Multidimensional assessment demonstrates sustainability of new low-input viticulture systems in north-eastern France

Current demand for more environmentally, socially, and economically sustainable farming practices requires multicriteria assessment of innovative agricultural systems to help enhance cropping systems. We assessed the sustainability of 11 systems intended to substantially reduce inputs, especially pesticides, to viticulture systems. Pesticide use was reduced using three methods: (i) technical (e.g., essential oils instead of some copper use, 100 % soil covering applied); (ii) organizational (e.g., new spraying decision rules, decision aid tools); and (iii) redesign of the entire system (e.g., resistant grape varieties planted). Sustainable performance of the new low-input vine systems (NLIVS) was assessed over 6 years (2013–2018) based on 25 indicators. They covered all aspects of system sustainability: environmental, agronomic, economic, and social. This included the evaluation of human capital and the quality of the wines produced. The results showed that it is possible to combine good environmental performance, such as reducing treatment frequency by up to 89 %, with good agronomic and wine quality performances. The socio-economic performance of these NLIVS was more moderate. Nonetheless, the results demonstrated that the NLIVS are sustainable according to many diversified indicators. NLIVS are also resilient, as shown by the consistent sustainability results over six consecutive years. They are a realistic tool enabling winegrowers to consider reducing viticulture inputs.

ABCDE cognitive aid tool in patient assessment \u2013 development and validation in a multicenter pilot simulation study

BackgroundThe so called ABCDE approach (Airway-Breathing-Circulation-Disability-Exposure) is a golden standard of patient assessment. The efficacy of using cognitive aids (CA) in resuscitation and peri-arrest situations remains an important knowledge gap. This work aims to develop an ABCDE CA tool (CAT) and study its potential benefits in patient condition assessment.MethodsThe development of the ABCDE CAT was done by 3 rounds of modified Delphi method performed by the members of the Advanced Life Support Science and Education Committee of the European Resuscitation Council.A pilot multicentre study on 48 paramedic students performing patient assessment in pre-post cohorts (without and with the ABCDA CAT) was made in order to validate and evaluate the impact of the tool in simulated clinical scenarios.The cumulative number and proper order of steps in clinical assessment in simulated scenarios were recorded and the time of the assessment was measured.ResultsThe Delphi method resulted in the ABCDE CAT. The use of ABCDE CAT was associated with more performed assessment steps (804: 868; OR = 1.17, 95% CI: 1.02 to 1.35, p = 0.023) which were significantly more frequently performed in proper order (220: 338; OR = 1.68, 95% CI: 1.40 to 2.02, p < 0.0001). The use of ABCDE CAT did not prolong the time of patient assessment.ConclusionThe cognitive aid for ABCDE assessment was developed. The use of this cognitive aid for ABCDE helps paramedics to perform more procedures, more frequently in the right order and did not prolong the patient assessment in advanced life support and peri-arrest care.

Incorporating Geogebra into Teaching Circle Properties at High School Level and it’s Comparison with the Classical Method of Teaching

The most influential books on geometry are those of Euclid called “Elements”. In our century, in addition to classical learning, various interactive software are used in teaching geometry. Among them, we can mention Geogebra. GeoGebra is an interactive math measurement program that consists of teaching and learning from elementary to university level. This software is offered as a pedagogical and mathematical aid tool. GeoGebra helps in teaching math because using this software, students see different mathematical formulas, algebraic and geometric presentations. In this paper, using GeoGebra software, the pedagogical, methodological, and statistical data into teaching circle properties are presented. The study involved 112 students. Of these 40% excellent, 35% average, 25% below average. The research aims to prepare high school students aged 15-18, from grades 1, 2, 3, and 4 in teaching, working, and explaining geometry through Geogebra software. Special emphasis is placed on the circle properties and their presentations. This content includes the district tangent, the potency, the application of the circle in regular polygons with special emphasis on the inscribed, circumscribed circle in the equilateral triangle, and other important properties.

A patient decision aid for prescribing pain medication: Results from a pilot test in two emergency departments

ObjectiveThis study piloted a patient education and decision aid tool about prescription pain relievers to determine potential impact on: comfort receiving an opioid prescription; knowledge about opioids; decisional conflict about whether to take an opioid; and shared decision making with the prescribing physician. MethodsPatients with acute pain were recruited from two emergency departments (ED), and randomized to complete the tool (N = 65) or a time-matched control (N = 59) on a tablet. Data collection involved: a baseline survey; a post-test immediately following the assigned program; a discharge survey after seeing the physician; and a 6-week follow-up survey. ResultsKnowledge increased and comfort receiving an opioid decreased as hypothesized, but did not reach statistical significance. Despite the lack of knowledge differences, the tool had significant positive impact on patients feeling more informed and experiencing less decisional conflict. Shared decision making with the prescribing physician was not impacted. ConclusionA patient decision aid can help ED patients feel more informed and less conflicted about prescription pain relievers but did not impact shared decision-making. Practice ImplicationsPatient education programs implemented in the ED should consider engaging physicians in the program to help to promote patient-centered approaches in the treatment of acute pain.

Environmental, social and corporate governance framework for corporate disclosure: a multicriteria dimension analysis approach

PurposeThe purpose of this paper is to provide to the Board of Directors and CEOs of a firm to be aware of and accountable for the information they provide to the public. As long as the quality of the companies’ public information is high, it will be able to retain its investors as well as to obtain new ones more easily.Design/methodology/approachThis paper introduces a Multi-Criteria Decision Aid (MCDA) tool with the use of the PROMETHEE II method to formulate an alternative aggregate ESG quality approach. We conduct comparisons in a sectorial and regional based perspective during different exam periods before and after the implementation of International Financial Reporting Standards (IFRS), in an attempt to provide a robust framework for corporate disclosure reporting.FindingsThe findings are of particular interest to both scholars and decision-makers, including providers of corporate governance indices and rating agencies. The innovation of this paper lies among others in using the MCDA method with the ESG framework, which proposes a combination of qualitative and quantitative criteria, enabling experienced and/or not experienced analysts to avoid manipulating techniques in business information.Research limitations/implicationsThe sample of companies based on the US and Europe companies incorporating only large-sized ones.Practical implicationsFindings are of particular interest to both scholars and decision-makers including providers of corporate governance indices and rating agencies.Social implicationsBetter understanding features pay key importance for increasing the “quality” information in firms financial statements, especially after the use of IFRS in reporting standards.Originality/valueThe authors proceed to analysis using a multiple perspective use that is decomposed into the following options: (a) Time-period oriented option, (b) Regional-oriented option and (c) Sectoral-oriented option respectively.