Tool Thanks Research Articles

Statistical Application Using Visual Basic For Application (VBA) Excel

BandiStats, a statistical application, was developed with the aim of being a simple and easy-to-use statistical analysis tool thanks to its base on Microsoft Excel, a well-known platform. The development method used the Visual Basic for Application (VBA) programming language. The application test results showed the success of all implemented menus. This research produced an application that can facilitate users in analyzing statistical data. It is hoped that this application can be a useful tool for those who need statistical analysis in their daily work without having to have in-depth knowledge of statistics or computer programming. With its easy-to-use interface and comprehensive features, BandiStats provides an efficient and effective solution for statistical data analysis.

A Sequential Pattern Mining Method for the Individualized Detection of Online Banking Fraudulent Transactions

Financial institutions are facing a growing number of challenges as a result of the growth in fraudulent activities in online banking, which calls for the implementation of systems that are more advanced in their identification of fraud.Traditional rule-based techniques have difficulties when it comes to handling rule modifications and do not provide sufficient detail to particular users. This study presents the User-Specific Sequence Pattern Mining Framework for Online Banking Fraud Detection (USPM-FrauD) as a solution to the challenges that have been highlighted. The framework was developed in order to detect fraudulent activity in online banking.This system makes use of sequence pattern mining algorithms in order to examine the transaction logs of every user and find variations that may be indicative of fraudulent conduct. By concentrating on individualised transaction patterns, the USPM-FrauD model provides a method that is both more efficient and more specifically targeted to the identification of fraudulent activity in online banking. When compared to rule-based and Markov chain models, the experimental findings reveal that the USPM-FrauD model has greater performance. This demonstrates that the model has the potential to be practically implemented in online banking systems that are used in the real world. In order to battle the ever-changing world of online banking fraud, financial institutions now have access to a more complex and user-specific tool thanks to the USPM-FrauD framework, which marks a substantial improvement in fraud detection approaches.

COVID-19 Lung Ultrasound Scores and Lessons from the Pandemic: A Narrative Review.

The WHO recently declared that COVID-19 no longer constitutes a public health emergency of international concern; however, lessons learned through the pandemic should not be left behind. Lung ultrasound was largely utilized as a diagnostic tool thanks to its feasibility, easy application, and the possibility to reduce the source of infection for health personnel. Lung ultrasound scores consist of grading systems used to guide diagnosis and medical decisions, owning a good prognostic value. In the emergency context of the pandemic, several lung ultrasound scores emerged either as new scores or as modifications of pre-existing ones. Our aim is to clarify the key aspects of lung ultrasound and lung ultrasound scores to standardize their clinical use in a non-pandemic context. The authors searched on PubMed for articles related to "COVID-19", "ultrasound", and "Score" until 5 May 2023; other keywords were "thoracic", "lung", "echography", and "diaphragm". A narrative summary of the results was made. Lung ultrasound scores are demonstrated to be an important tool for triage, prediction of severity, and aid in medical decisions. Ultimately, the existence of numerous scores leads to a lack of clarity, confusion, and an absence of standardization.

Predicting systemic risk in financial systems using Deep Graph Learning

Systemic risk is the risk of infection from an individual financial entity to the financial system due to existing interconnections. Having powerful tools to analyze and predict systemic risk in large financial networks is essential to ensure the stability of the financial system, avoiding the negative externalities derived from the failure of a systemically important financial institution. In this context, Machine Learning (ML) has proved to be a useful tool thanks to its ability to deal with complex relations. However, traditional techniques are limited in their use of the interactions between entities and the network structure, which has been shown to be of great importance for systemic risk. Thus, this work proposes Graph Neural Networks (GNNs) for systemic risk analysis. GNNs use the network structure and feature information to deal with large-scale financial networks, providing the benefits of ML while using all the available information (node inter-relations and node, edge, and graph features). We also present C2R, an approach to reduce the pre-labeling effort for costly systemic risk metrics by pre-labeling into a small number of classes while predicting continuous risk scores. We have tested GNNs against traditional ML in classifying entities by systemic risk importance in two different networks, comparing their generalization capabilities with different amounts of available data. GNNs achieve a 94% and 15% Matthew's Correlation Coefficient (MCC) average percentage increase compared to ML, achieving statistically significant MCC improvements in most scenarios. When combining C2R with GNNs to predict the systemic risk quantile from the class labels, the models achieve statistically significant improvements in the quantile RMSE. From our experiments, we can confirm that GNN models are better suited for systemic risk prediction on financial networks and should be preferred over traditional Machine Learning. The results obtained also confirm the fact that the network structure and the features of the relations (edge features) hold useful information for our task.

Investigation of Drillability of CFRP/Al 7075 Stack

Composite/metal stack materials, which have excellent mechanical properties, are wideyl used in aerospace industry. However, their machining operation is challenging due to two different material. In this study stack materials consisting of CFRP and Al 7075-T6 were drilled with different drilling parematers to investigate delamination defect, thrust force, inner surface roughness of hole and wear of the cutting tool. Cutting speeds of 50 and 200 m/min, feed rates of 0.10 and 0.20 mm/rev were selected as cutting parameters. The materials were drilled respectively in CFRP/Al 7075 and Al 7075/CFRP directions to observe effect of machining direction in the experiments Drilling experiments were carried out with an uncoated 9 mm diameter drill at variable and constant speeds. Experimental results showed that the surface roughness increased with the increase of cutting speed and feed rate, delamination increased in experiments where cutting tool came out of CFRP, thrust force at variable speeds increased and low amount of wear of cutting tool thanks to internal cooling.

Label-Free Higher Order Structure and Dynamic Investigation Method of Proteins in Solution Using an Enzymatic Reactor Coupled to Electrospray High-Resolution Mass Spectrometry Detection.

For decades, structural analysis of proteins have received considerable attention, from their sequencing to the determination of their 3D structures either in the free state (e.g., no host-guest system, apoproteins) or (non)covalently bound complexes. The elucidation of the 3D structures and the mapping of intra- and intermolecular interactions are valuable sources of information to understand the physicochemical properties of such systems. X-ray crystallography and nuclear magnetic resonance are methods of choice for obtaining structures at the atomic level. Nonetheless, they still present drawbacks which limit their use to highly purified systems in a relatively high amount. On the contrary, mass spectrometry (MS) has become a powerful tool thanks to its selectivity, sensitivity, and the development of structural methods both at the global shape and the residue level. The combination of several MS-based methods is mandatory to fully assign a putative structure in combination with computational chemistry and bioinformatics. In that context, we propose a strategy which complements the existing methods of structural studies (e.g., circular dichroism, hydrogen/deuterium exchange and cross-links experiments, nuclear magnetic resonance). The workflow is based on the collection of structural information on proteins from the apparition rates and the time of appearance of released peptides generated by a protease in controlled experimental conditions with online detection by electrospray high-resolution mass spectrometry. Nondenaturing, partially or fully denatured proteins were digested by the enzymatic reactor, i.e., β-lactoglobulin, cytochrome c, and β-casein. The collected data are interpreted with regard to the kinetic schemes with time-dependent rates of the enzymatic digestion established beforehand, considering kinetics parameters in the Michaelis-Menten formalism including kcat (the turnover number), k1 (formation of the enzyme-substrate complex), k-1 (dissociation of the enzyme-substrate complex), koff (local refolding of the protein around the cleavage site), and kon (local unfolding of the protein around the cleavage site). Solvent-accessible surface analysis through digestion kinetics was also investigated. The initial apparition rates of released peptides varied according to the protein state (folded vs denatured) and informs the koff/kon ratio around the cleavage site. On the other hand, the time of appearance of a given peptide is related to its solvent accessibility and to the resilience of the residual protein structure in solution. Temperature-dependent digestion experiments allowed estimation of the type of secondary structures around the cleavage site.

An ontology-based modelling and reasoning for alerts correlation

SIEM is a modern and powerful security tool thanks to several functions that it provides to take benefit of collected data, such as normalisation and aggregation. The main important function is events correlation, when security operators can get a precise and quick picture about threats and attacks in real-time. The quality of that picture depends on the efficiency of the adopted reasoning approach to putting together pieces of information provided by several analysers. In this paper, we propose a semantic approach based on description logics (DLs) which is a powerful tool for knowledge representation and reasoning. Indeed, ontology provides a comprehensive environment to represent information for intrusion detection and allows easy maintaining of information or adding new ones. We implemented a rule-based engine for alert correlation based on the proposed ontology and two attack scenarios are carried out to show the usefulness of our approach.

Safe short circuit in cataract surgery: Incidence and risk factors for intraoperative medical action

Cataract surgery has become the most frequent surgical procedure performed every year in Western countries. Perioperative patient circuit has to be adapted to the important medical needs and progress. Hence, a secure short circuit (SSC) for surgeries of the anterior segment of the eye under topical anaesthesia was created. Patients included in the circuit are selected first by surgeons and answer a medical questionnaire, they do not have any preoperative evaluation by anaesthesiologist, are monitored during surgery by the surgical team and in case of problem an intraoperative medical action (IMA) can be performed. We conducted a retrospective observational incidence study of the occurrence of the IMA, followed by a case control study. The primary outcome was to identify risk factors of IMA among the patients’ medical history. Out of 2744 screened patients, 1592 patients were included during the period of November 2015 to November 2017. The rate of IMA was 5%, 81% of them presenting with intraoperative high blood pressure (HBP). In the case control study part, stepwise regression analysis revealed that a history of HBP and insulin-dependent diabetes (IDD) was significantly correlated with IMA (respectively, adjusted odds ratio 1.7, P=0.005 and 2.6, P=0.002). The low incidence of IMA showed that the SSC is a safe tool thanks to a selection and an optimised and secure pathway. A history of HBP and IDD was significantly associated with the occurrence of IMA. Therefore, an optimisation of the perioperative period would be beneficial in these cases.

Fiber-optic distributed seismic sensing data generator and its application for training classification nets.

Distributed acoustic sensing (DAS) is a powerful tool thanks to its ease of use, high spatial and temporal resolution, and sensitivity. Growing demand for long-distance distributed seismic sensing (DSeiS) measurements, in conjunction with the development of efficient algorithms for data processing, has led to an increased interest in the technology from industry and academia. Machine-learning-based data processing, however, necessitates tedious in situ calibration experiments that require significant effort and resources. In this Letter, a geophysics-driven approach for generating synthetic DSeiS data is described, analyzed, and tested. The generated synthetic data are used to train DSeiS classification algorithms. The approach is validated by training an artificial neural-network-based classifier using synthetic data and testing its performance on experimental DSeiS records. Accuracy is greatly improved thanks to the incorporation of a geophysical model when generating training data.

Social participation in designing urban spaces related to green areas on the example of Białystok

Social participation is a tool thanks to which newly designed places can be adapted to the needs of residents as much as possible. People can also decide to extend the functional program of the housing estates where they live. Therefore, this phenomenon has a real influence on shaping their close surroundings. The article analyses how social participation takes place in Bialystok on the example of the Civic Budget organized by the Municipal Office.

Open field inoculation with PGPR as a strategy to manage fertilization of ancient Triticum genotypes

Ancient wheats are characterized by high nutritional value, low nitrogen requirements, and good adaptability which make them particularly suitable for marginal areas or low-input agricultural systems. Among environmental-friendly fertilizers, plant growth-promoting rhizobacteria represent a promising tool thanks to their ability to colonize soil and plant roots. In this study, a consortium of plant growth-promoting rhizobacteria was applied on three ancient wheat varieties (durum wheat: Senatore Cappelli, Saragolla; emmer: Molisano). Colonization and survival of bacteria in wheat seedling roots were investigated on in vitro cultures. The effects of the bacteria on crop growth, yield, and grain protein accumulation were studied in a 2-year open field experiment (split-plot arranged on a randomized block). Three different fertilization strategies were compared: (i) one bacterial application at sowing, (ii) two bacterial applications at sowing and tillering stages, (iii) zero bacterial application. Scanning electron microscope imaging revealed the ability of the bacteria to colonize effectively seedling roots thanks to biofilm formation on root surfaces. In both years, double bacterial application positively affected plant physiology, growth, and yield. Plants with double bacterial application showed highest physiological traits, and resulting enhanced yield and grain protein contents. The applied bacterial consortium positively performs on ancient wheats, even if the magnitude of its success depends on timing and rate of application.

Studium upadku. Proces Anny Boleyn (1536)

<p>Powszechnie uznaje się, że egzekucja Anny Boleyn w maju 1536 była rezultatem naruszenia wszelkich humanitarnych norm rządzących procesem karnym w dobie nowożytnej. Podważając dowodową stronę postępowania, pomija się z reguły zasady które angielska procedura karna znała i które miały zastosowanie w <em>state trials, </em>w tym również w przypadku procesu angielskiej królowej. Choć niewątpliwym jest, że prawo, gdy idzie o przestępstwa kwalifikowane jako polityczne, stawało się narzędziem, dzięki któremu władza realizowała swoje cele to nie można nie dostrzegać, iż proces Anny Boleyn konstrukcyjnie pozostaje tożsamy z innymi podobnymi postępowaniami, które miały miejsce w XVI w. Należy zatem spoglądać na wydarzenia, które doprowadziły do skazania Anny Boleyn, nie z punktu widzenia obecnych reguł prawnych i aksjologicznych, a z uwzględnieniem kontekstu historyczno-prawnego.</p>

Preparation for Baby-Friendly Designation With Innovative Education Methods

To prepare nursing staff for a Baby-Friendly designation visit using a reeducation method that will engage learners and reignite interest in the project. In the past, many educational offerings consisted of PowerPoint lectures. The educators did not feel this would be effective for this content and these learners. An educational activity was planned using an escape-room format. Surveys were conducted to determine knowledge gaps. An educational activity was designed to reinforce knowledge. A pretest was given. The educators of the labor and mom–baby units created an escape-room format to convey important concepts using an innovative method. An escape room requires the participants to solve puzzles to move through the room as a team. Our puzzles used learning points from the identified knowledge gaps. This activity created a scenario of a zombie apocalypse that required new mothers to successfully breastfeed to prevent neonatal transmission of the zombie virus. The team had to work together to answer questions. A correct answer would reveal a clue to unlock the next phase of the room. A posttest assessed knowledge following the activity. Pre–posttest results were evaluated from three important Baby-Friendly assessment areas. When discussing benefits of rooming-in, learners correctly answered 57% of the questions in the pretest and 84% in the posttest, an increase of 27%. When discussing benefits to hand expression, learners correctly answered 45% of the questions in the pretest and 79% in the posttest, an increase of 34%. When discussing reasons not to use artificial nipples, learners correctly answered 35% of the questions in the pretest and 66% in the posttest, an increase of 33%. Feedback from participants was overwhelmingly positive, with statements such as, “I liked the interactive format,” “It was creative,” “It made education fun,” “Great way to present topic/skills,” “Love the hands on activity,” “It was different and kept our interest,” “It was great to have information not presented in another lecture, but a more creative way,” and “Great learning tool—thanks for the variety.” Reeducation of subject matter can be challenging for educators. This project shows a method that could be used for a variety of subject matter to engage learners and impact long-term retention of knowledge.

Joint inversion of gravity gradiometry and magnetic data using Gramian structural constraints: A case study from the McFaulds Lake survey, Ontario

Abstract Potential field data form an important frontline exploration tool thanks to the modern-day airborne platforms capable of collecting large amounts of data over large areas. Interpretation of these data using a 3D inversion is still a challenging problem due to the large amount of data and the need to discretize the inversion volume into a huge number of elements.

From e-learning to VR-learning: an example of learning in an immersive virtual world

A first experience of use of “In Your Eyes”, an Immersive Virtual Reality (IVR) game to foster Spatial Perspective Taking (SPT) skills in young adults with mild cognitive impairments is described along with a brief discussion of the outcomes. IVR is an innovative tool thanks to which a new chapter in the history of e-learning begun. It is now possible to have a personal direct experience of virtual situations as if they were real, involving all the five senses and allowing for a kinaesthetic approach to learning. All those skills that have an embodied component find in the immersive world a perfect training situation. Spatial Perspective Taking is an important skill for orientation in space and mastering it supports independent mobility in town. The fact that the virtual world is perceived as if it was real, and the possibility to move freely into it, allows stimulating the embodied component of spatial reasoning. The gaming situation helps in keeping the player’s interest high and therefore helps in having as much training as needed. Furthermore, IVR makes learning transfer to real situations easier, especially for our target users.

Multi approach for real-time systems specification: case study of GPU parallel systems

Specifying and modelling real-time systems (RTS) is not an easy task to do because there are many aspects to treat such as time constraints, scheduling and multi-tasking processing. Current RTS parallel applications deal with large amounts of data which require using devices such as GPUs. GPU is one of the main architectures that guaranties parallel execution. The specification of scheduling and timing on GPUs had always been a research problematic. UML/MARTE is an efficient semi-formal specification tool thanks to the UML's diagrams and MARTE's profiles. But it still none valid specification because it is not proved. That is why we propose to couple MARTE with the formal method Event B to have a valid specification and to validate the task scheduling on the GPU. A set of refinements had been proposed to cover the GPU specification and to generate an executable pre-code CUDA and OpenCL.

Cluster phenomenon and partial differential aging in RAP mixtures

The present study defines a procedure for gaining a better understanding of the interaction between the aged and the virgin binders and what actually occurs during a mix process. Indeed, the authors propose a methodology to determine and quantify the cluster phenomenon in mixtures containing RAP, defining how the aged binder interacts in the mix. Rheology, in particular the complex modulus, becomes the tool thanks to which it is possible to support the hypothesis of the composition of clusters of RAP particles surrounded by the virgin binder during the new mix production, considering different percentages of RAP. Moreover, the authors aim to establish the basis for the hypothesis of the existence of a partial differential aging: the RAP binder on the external surface (i.e. the crust around the aggregate) is more exposed to external factors and oxidation and is over-aged with respect to the binder under the crust that is more protected and less oxidated.

Role of modern 3D echocardiography in valvular heart disease.

Three-dimensional (3D) echocardiography has been conceived as one of the most promising methods for the diagnosis of valvular heart disease, and recently has become an integral clinical tool thanks to the development of high quality real-time transesophageal echocardiography (TEE). In particular, for mitral valve diseases, this new approach has proven to be the most unique, powerful, and convincing method for understanding the complicated anatomy of the mitral valve and its dynamism. The method has been useful for surgical management, including robotic mitral valve repair. Moreover, this method has become indispensable for nonsurgical mitral procedures such as edge to edge mitral repair and transcatheter closure of paravaluvular leaks. In addition, color Doppler 3D echo has been valuable to identify the location of the regurgitant orifice and the severity of the mitral regurgitation. For aortic and tricuspid valve diseases, this method may not be quite as valuable as for the mitral valve. However, the necessity of 3D echo is recognized for certain situations even for these valves, such as for evaluating the aortic annulus for transcatheter aortic valve implantation. It is now clear that this method, especially with the continued development of real-time 3D TEE technology, will enhance the diagnosis and management of patients with these valvular heart diseases.

Glacier surface velocity estimation using repeat TerraSAR-X images: Wavelet- vs. correlation-based image matching

For the observation and monitoring of glacier surface velocity (GSV), remote sensing is an increasingly suitable tool thanks to the high temporal and spatial resolution of the data. Radar sensors have the specific advantage over optical sensors of being nearly weather and time-independent.Two image pairs separated by 11days, acquired with the high-resolution spotlight (HS) and stripmap (SM) modes of the German sensor TerraSAR-X, were used to estimate GSV over Switzerland’s Aletsch Glacier. The SM mode covers larger ground swaths, making it more suitable for glacier-wide observations, while the HS images cover less area but offer the highest-possible spatial resolution, approximately 1×1m on the ground. The images were acquired during the summer to maximise feature visibility by minimal snow cover.GSV estimation was performed using two methods, the comparison of which was a major goal of this study: traditional cross-correlation optimisation and a dense image matching algorithm based on complex wavelet decomposition. Each method was found to have unique advantages and disadvantages, but it was concluded that for GSV monitoring, cross-correlation is probably preferable to the wavelet-based approach. While it generates fewer estimates per unit area, this is not necessarily a critical requirement for all glaciological applications, and the method requires less initial “tuning” (calibration) than the wavelet algorithm, making it a slightly better tool in operational contexts. Also, the use of the highest-resolution spotlight datasets is recommended over stripmap mode images when large-area coverage is less critical. The comparative lack of visible features at the resolution of the stripmap images made reliable GSV estimation difficult, with the exception of several small areas dominated by large crevasses.

Design an Apparatus for Obtaining to High Precision Surface of Miniature Parts Based on Magnetized Abrasive Grains Finishing Process

Obtaining to high quality surfaces of industrial parts is an important manner for manufacturing involves. Different finishing process are capable to providing the require surface roughness in most cases, considering that, in some special parts, depending on shape, material and dimension of parts, the prevalent methods are limited, especially in finishing of sculptural and curvilinear surfaces. In this research, a new applied apparatus is represented based on magnetized abrasive grains finishing process. In this way, abrasive grains gathering around a rotational cylindrical tool thanks to a permanent magnetic field and work-piece, which usually is a formed thin metal sheet, located on a rotary table. Therefore, coinciding of those motions providing the require machining forces for finishing of surface without any physical contact between tool and work-piece. Presented process may carry out dry and wet in case of changing the main machining parameters such as: material and size of abrasive grains, tool and work-piece surface gap distance, tool and/or table rotational speed (r.p.m) and work-piece material. The recommended process has remarkable advantages such as: non-contact surface finishing, high finishing of non-flat surfaces, no need to clamping for work-piece because of low machining forces, responsibility for finishing of a wide range of materials except magnetizable parts, low machining costs and easy set up. This method has a lot of applications in production of optical lens, orthopedic prosthetic components and jewellery. For approve of the designed apparatus advantages, relative to other existed MR fluid machining system, some samples of very thin complex formed sheet have been successfully polished.