Suitable Format Research Articles

Considerations on the partial safety factor format for reinforced concrete structures accounting for multiple failure modes

The increasing usage of nonlinear analyses for the design of reinforced concrete structures and the necessity of codes of practice to provide a consistent safety format for them is one of the challenges that new generations of codes of practice are facing. Suitable safety formats shall thus account for the peculiarities of nonlinear analysis, such as the possibility of having multiple potential failure modes. In this paper, the applicability of the classical Partial Safety Factor Format (PSFF) for the resistance of reinforced concrete structures (composed of two safety factors: γC for concrete compressive strength and γS for reinforcement yield strength) is investigated accounting for the possibility of multiple failure modes in nonlinear analysis. In addition, the similarities between nonlinear analysis and typical simple cases in the design of structural concrete are shown. Reliability analysis is performed for the design resistance of concrete structures according to PSFF under different design situations (cross-sectional resistance or load-bearing capacity of structural elements and of simple structural systems). The results show that the PSFF applied to material strength variables leads to a satisfactory level of reliability, independently of the development of different failure modes induced by material uncertainties in nonlinear analysis. In addition, it is also observed that the simplification of integrating geometrical and model uncertainties into the partial safety factors for material strength variables can potentially underestimate their influence on the structural reliability in some cases. The case studies shows that occurrence of multiple failure modes can result into significantly different distribution characteristics between the tail and most probable region of the resistance of concrete structures. Attention should also be paid to a proper tail approximation of the probability distribution of the resistance when calibrating safety formats for concrete structures.

The Software System LingvoDoc and the Possibilities It Offers for Documentation and Analysis of Ob-Ugric Languages

—The LingvoDoc system (http://lingvodoc.ispras.ru) provides a service for collaborative language documentation and computations on the collected data. This software system provides GraphQL HTTP API for all the system components and allows its users to build their own extensions for data analysis or even to integrate it with their own software. Thanks to a special database and application design pattern, it is possible to construct offline applications integrated with the LingvoDoc system: these applications would need to have an internet connection only once to synchronize basic data types and for authentification purposes. The system itself allows users to construct multilayer dictionaries, attach them to the geographical map, fill documents with metadata, share access to dictionaries with other users or with everyone. The LingvoDoc system provides fine-grained access control lists for sharing, which allows to separate users into groups of dictionary editors, proofreaders and read-only users. The system also provides some computational algorithms on the stored data: phonology computations, automatic and guided deduplication inside the dictionaries etc. The system allows users to choose the dictionary structure. The system supports the following data types: text, images, sounds (wav, mp3, and flac), markups (ELAN and Praat formats), directed and undirected links between stored entities. A user can choose the most suitable format for their dictionary. Also, the system provides ELAN corpora storage, viewer and processing. In LingvoDoc there are 13 programs made for authors of the dictionary (only 4 of them are available for all users of the system). These programs analyze language data from phonetical, morphological and etymological point of view. This analysis previously was performed manually by linguists. Our programs allows do it tens and sometimes hundreds times faster. This paper presents the documentation and an analysis of Ob-Ugric languages using the LingvoDoc system.

Auto-Selection of an Optimal Sparse Matrix Format in the Neuro-Simulator ANNarchy.

Modern neuro-simulators provide efficient implementations of simulation kernels on various parallel hardware (multi-core CPUs, distributed CPUs, GPUs), thereby supporting the simulation of increasingly large and complex biologically realistic networks. However, the optimal configuration of the parallel hardware and computational kernels depends on the exact structure of the network to be simulated. For example, the computation time of rate-coded neural networks is generally limited by the available memory bandwidth, and consequently, the organization of the data in memory will strongly influence the performance for different connectivity matrices. We pinpoint the role of sparse matrix formats implemented in the neuro-simulator ANNarchy with respect to computation time. Rather than asking the user to identify the best data structures required for a given network and platform, such a decision could also be carried out by the neuro-simulator. However, it requires heuristics that need to be adapted over time for the available hardware. The present study investigates how machine learning methods can be used to identify appropriate implementations for a specific network. We employ an artificial neural network to develop a predictive model to help the developer select the optimal sparse matrix format. The model is first trained offline using a set of training examples on a particular hardware platform. The learned model can then predict the execution time of different matrix formats and decide on the best option for a specific network. Our experimental results show that using up to 3,000 examples of random network configurations (i.e., different population sizes as well as variable connectivity), our approach effectively selects the appropriate configuration, providing over 93% accuracy in predicting the suitable format on three different NVIDIA devices.

Accessibility of Information Resources and Services in the Library for the Users with Disabilities: A Study

The library is recognized as the hub of academic learning. As a result of this cluster of ladders, library services for disabled people in underdeveloped nations are typically limited. Dr. Shakuntala Misra Rehabilitation National University, Lucknow, India, provided library materials and services for disabled people. In contrast, the common users and users with disabilities have required highly appropriate and suitable access to the library facilities. The study reveals the majority of the differently-abled users that access library resources and services with special needs especially in areas of technology enhancement. The precise study has shown the availability of library services designed specifically for students with disabilities, students often face challenges due to the unavailability of resources and not suitable formats, insufficient internet accessibility, and insufficient instruction about how to access the library. The core problems opine the reasonable fact that the disabled users were allocated getting support from an unskilled library professional to manage and operate the library services. The study suggests that the university appoint more skilled staff in the audio-Braille section of the library to support users with disabilities includes modern assistive technologies.

Development and validation of questionnaire to assess exposure of children to enteric infections in the rural northwest Ethiopia

In areas where children have multiple environmental exposures to enteric pathogens, identifying the sources of exposure by measuring external and internal exposures to enteric pathogens and complementing by questionnaire and observational checklist to capture behaviors resulting risk of exposure is critical. Accordingly, this study was conducted to design valid and reliable questionnaire to assess behaviors and environmental conditions resulting exposure to enteric pathogens in the rural northwest Ethiopia. We began with a thorough exploration of relevant literature to understand the theoretical framework on the research objectives to identify variables to highlight what the questionnaire is measuring. We then generated items in each domain that can effectively address the study objectives and we refined and organized the items in a suitable format. Then after, we conducted face and content validity by involving experts on the research subject. After pre-testing a pre-final version of the instrument generated in the content validity study, we conducted a pilot study in 150 randomly selected rural households to test the internal consistency reliability. We used content validity ratio (CVR), item-level content validity index (I-CVIs), scale-level content validity index (S-CVI/UA), and modified kappa statistics to measure content validity of items. Moreover, we used agreement and consistency indices (i.e., Cronbach’s alpha) to assess the internal consistency of items. The content validity test result showed that the value of CVR was 0.95, I-CVIs was 0.97, and modified kappa was 0.97 for the whole items, indicating all the items are appropriate. The scale-level content validity index (S-CVI/UA) was 0.95 for the whole items indicating the agreement among judges to each items is higher. The internal consistency reliability test result indicated that Cronbach’s alpha for the pre-final version of the pre-final tool was 0.85, indicating the strong reliability of the tool. The final version of the questionnaire was, therefore, prepared with 8 dimensions and 80 items. In this study, we designed valid and reliable questionnaire to assess behaviors and environmental conditions that result high risk of exposure to enteric infections in rural settings. The questionnaire can be used as a tool in the rural settings of developing countries with some amendments to account local contexts. However, this questionnaire alone does not measure exposure of children to enteric infections. It only complements external and internal exposure assessments.

MalSPM: Metamorphic malware behavior analysis and classification using sequential pattern mining

Malware pose a serious threat to the computers of individuals, enterprises and other organizations. In the Windows operating system (OS), Application Programming Interface (API) calls are an attractive and distinguishable feature for malware analysis and detection as they can properly reflect the actions of portable executable (PE) files. In this paper, we propose MalSPM, an intelligent malware detection system based on sequential pattern mining (SPM) for the analysis and classification of malware behavior during executions. A dataset that contains sequences of API calls made by different malware on Windows OS is abstracted into a suitable format. SPM algorithms are first used on the corpus to find frequent API calls and their patterns. Moreover, sequential rules between API calls patterns as well as maximal and closed frequent API calls patterns are discovered. Obtained frequent patterns are then used for the classification of different malware. Seven classifiers are used and their performance is compared by using various metrics. Moreover, the performance of MalSPM is compared with existing state-of-the-art malware detection approaches and obtained results show that MalSPM outperforms these approaches.

Frequent Itemset Generation Using Association Rule Mining Based on Hybrid Neural Network Based Billiard Inspired Optimization

The concept based on data mining has drawn considerable attention from various database professionals and research scholars. The progression of computer-based advancements, namely database management and data storage has facilitated the storage of large data and the data mining approaches are employed to gain valuable information from huge databases. Recently, several techniques to association rule mining (ARM) and frequent itemset mining (FIM) have been established; yet the efficiency based on execution time and scalability continues to be seen as a significant limitation that results in poor solution quality. Therefore, it is necessary to enhance the consistency that signifies the total number of frequently discovered frequent itemsets. This paper proposes three different phases namely the pre-processing phase, FIM phase and ARM phase. In the first pre-processing phase, the Twitter databases are pre-processed and converted into a suitable format for FIM. Here, the tweets are converted into related feature sets and items. In the second FIM phase, an improved Apriori algorithm is 1utilized in mining and extracting the frequent Then in the final phase, an adaptive billiard inspired optimization (ABIO) algorithm which is the integration of neural network (NN) optimization algorithm and billiard inspired optimization (BIO) algorithm is proposed for the optimal generation of association rules with minimum support and confidence from the huge itemsets. Finally, the recent tweets based on covidvaccine, BTSlivestreaming, KFC, McDonald’s as well as lockdown achieved using the hashtag is evaluated for various performance measures, like precision, recall, [Formula: see text]-measure, execution time and memory utilization. Also, comparative analyses are performed to evaluate the efficiency of the proposed technique.

Microsoft Teams desktop application forensic investigations utilizing IndexedDB storage

While the COVID-19 virus remolded the routines of the establishments, remote collaboration and distant communication gained more popularity. As the way electronic communications are handled changes drastically, new applications and storage mechanisms are introduced. Microsoft Teams is an application offered within the scope of Microsoft Office 365 that offers services for hosting virtual meetings, team communication, and comprehensive team resource management. It is prevalently used by organizations and indicates a great potential to be a source of digital forensic investigations. This paper scrutinizes the artifacts created by Microsoft Teams in IndexedDB persistent storage. IndexedDB is a fast-growing client-side storage technology that is relatively new as a source for digital forensic investigations. A single-case pretest-posttest quasi experiment was conducted to produce artifacts in Microsoft Teams IndexedDB storage. The artifacts were extracted without user credentials indicating security flaws in the application. Extracted artifacts were processed based on signature patterns and evaluated for their significance. Traditional database queries were utilized to link and present the information clustered according to their relevancy. A time-frame analysis was constructed to display information in a suitable format for investigators. The results indicate that Microsoft Teams IndexedDB storage artifacts contain significant potential for digital investigations with extraction of complete contents of private chat messages, voice mails, and team extensions with efficient time-frame analysis.

Determining Severity of Lateral and Torsional Downhole Vibrations While Drilling Surface Holes Using Three Machine Learning Techniques

Summary Downhole vibrations while drilling surface holes could pose significant operational risks, such as premature failure of drillstring components. Using expensive downhole sensors is the most accurate and reliable technique to monitor downhole vibrations in real time. The high cost, however, hinders the operator to use such sensors in each well. This research aims to build different machine learning (ML) models, namely, K-nearest neighbors (K-NN), logistic regression (LR), and random forests (RF), to determine the severity of downhole vibrations (i.e., lateral and torsional while drilling surface holes). Actual field data of 10 wells, where the operator used downhole sensors to monitor downhole vibrations, were used to build predictive models. The input variables included drilling surface parameters and daily operational drilling reports, while the output variables were the severity of the downhole vibrations. One-hot encoding was applied to all categorical variables to convert them to a suitable format for ML modeling. During the model’s development, a new approach that considers the previous actual and predicted vibrations was applied to enable the ML models to learn from the past to classify the severity of vibrations in the future. The developed models were optimized by tuning specific hyperparameters for each technique to reach the optimum models’ performance. Well 11 was used to validate the developed models. The analysis showed that the data set of Well 11 is not balanced in terms of the severity of vibrations. Therefore, the performance of the models was evaluated using macroaveraging and microaveraging methods to depict the actual performance of the models in all classes of the severity of vibrations. The results showed that the LR model outperformed the other models in predicting the severity of downhole lateral and torsional vibrations in Well 11. This indicates that there is a stronger relationship between the input variables and the output variables in our data set in the case of the LR model compared with other models. The approach described in this paper shows potential for continuous monitoring of downhole vibrations in the subsequent offset wells without the need for installing downhole sensors, hence reducing the overall cost of the well.

Contact networks in RNA: a structural bioinformatics study with a new tool.

Base pairing in RNA are significantly rich and versatile due to the potential non-canonical base pairing amongst nucleotides. Not only that, one base in RNA can pair with more than one bases simultaneously. This opens up a new dimension of research to detect such types of base-base pair networks in RNA and to analyze them. Even if a base do not form a pair, it may have significant extent of [Formula: see text]-[Formula: see text] stacking overlap that can stabilize the structures. In this work, we report a software tool, called BPNet, that accepts a mmCIF or PDB file and computes the base-pair/[Formula: see text]-[Formula: see text] contact network components using graph formalism. The software can run on Linux platform in both serial and parallel modes. It generates several information in suitable file formats for visualization of the networks. This paper describes the BPNet software and also presents some interesting results obtained by analyzing several RNA structures by the software to show its effectiveness.

Continuing Education of Nurses in Patient Handovers: Development and Evaluation of a Digitally Enabled Problem-Based Learning Course.

Communication deficits belong to the most frequent errors in patient handovers calling upon specialized training approaches to be implemented. This study aims to harness problem-based learning (PBL) methods in handover education and evaluated the learning process. A digitally enabled PBL course was developed and implemented at Klinikum Osnabrück from which eight nurses participated in the course. They agreed on the stimulating effect of the setting regarding self-directed learning and on the potential to translate the new knowledge and skills into the daily clinical practice. In conclusion, the findings are promising that a digitally enabled PBL course is a suitable learning format for handover education.

Serial album on Continuous Insulin Infusion System as an innovative educational technology in diabetes.

to build and validate a serial album content and appearance on insulin therapy using a Continuous Infusion System. a methodological study, carried out in three stages in Fortaleza, Ceará, Brazil, from August to November 2018. The serial album construction and content and appearance validity were carried out by experts, and assessment, by the target audience. Content Validity Index and Concordance Index were calculated. the judges considered the serial album content and appearance to be valid, which means that the material is suitable as an educational technology. Experts suggested adjustments, incorporated into the material for print production of the final version. The target audience also assessed the serial album positively. we realized that the serial album was considered an innovative educational technology in diabetes, valuable for promoting knowledge about Continuous Insulin Infusion System, with rich, updated content, combined with clarity, suitable format and explanatory illustrations.

RETRACTED ARTICLE: Ultrasound microbubble-mediated miR-150-5p inhibits gastric cancer cell growth by targeting the expression of NR2F2

We, the Editor and Publisher of the Journal of Receptors and Signal Transduction, have retracted the following article: Ultrasound microbubble-mediated miR-150-5p inhibits gastric cancer cell growth by targeting the expression of NR2F2; Wei Wei, Xiaoguang Wei, Minyu Zhang & Cheng Peng; https://doi/10.1080/10799893.2021.1884260 Since publication, concerns have been raised about the integrity of the following figures in the article. 2(A) miR-NC and 2(D) miR-NC-MBs; 2(A) Control and 5(C) NR2F2-MBs + miR-NC-MBs When approached for an explanation, the authors were unable to provide original data in a suitable format that would confirm the authenticity of the data. The authors have been notified of the retraction but have not responded. We have been informed in our decision-making by our policy on publishing ethics and integrity and the COPE guidelines on retractions. The retracted article will remain online to maintain the scholarly record, but it will be digitally watermarked on each page as ‘Retracted’.

Knowledge of danger signals of pregnancy among clients of maternal health services in tertiary care teaching hospital, Pune

Background: India is among countries with a high maternal mortality rate. Every pregnant woman is at risk of developing pregnancy-related complication. It is not understood if and how the information and education on danger signals of pregnancy; translates into appropriate actions when a woman experiences a danger signal. Knowledge and recognition of danger signals during pregnancy would result in timely emergency obstetric care. Aims and Objectives: This study aims to determine the knowledge of key danger signals of pregnancy and its associated factors among the clients of maternal health services in tertiary care teaching hospital, Pune. Materials and Methods: This was a cross-sectional study conducted in obs. and gyne. dept. of tertiary care hospital for a period of 1 month that enrolled 55 eligible women who attended ANC and PNC clinic within study period. Ethical approval for the study was obtained from the IEC. The women were interviewed using a pre-tested questionnaire. All the women attending ANC and PNC clinic with a minimum of four ANC visits qualified the women for the inclusion in the study. Data analysis was performed using SPSS Version 20. The analyzed data were presented in suitable tabular format. Results: Out of 55 mothers, 43.6% know about four or more danger signals whereas 56.4% have knowledge of <4. The most recalled danger signals by the clients was labor pain before 8 months (70.9%), while no one is aware about the danger signal failure of placenta to come out (0%). Conclusion: This study indicated that the knowledge level of women regarding danger signals of pregnancy was low and affected by education level. Therefore, the identified deficiencies in awareness should be addressed through maternal and child health services.

Data Collection for Implementation of the Mechanistic-Empirical Pavement Design Guide (MEPDG) in Izmir, Turkey

Developing countries like Turkey are trying to implement the Mechanistic-Empirical Pavement Design Guide (MEPDG). The implementation of this method requires comprehensive local data collection, evaluation, and, if necessary, a local calibration. The objective of this study is to prepare local data such as climate, traffic, and materials for evaluation and local calibration of MEPDG for Izmir City. For this purpose, the climate and traffic data were obtained, analysed, and converted to the MEPDG format. Besides, the bound and unbound pavement material properties were determined. Since some of the obtained local data like climate, vehicle classification, traffic growth factor, and axle load distribution cannot be directly used as design inputs, they were developed and converted to a suitable format to be used in the MEPDG. The output of this study can be used as design inputs for the evaluation and local calibration the MEPDG in Izmir and serves as a guide for data preparation for other parts of the country.

Potnet: Online Potable Water Quality Monitoring Network for Overhead Water Tanks in Rural Water Supply Schemes in India

Background: Monitoring the quality of potable water is a challenging endeavor due to the significant sources of contaminants, the majority of which are human-induced. Limited access to drinking water owing to acceleration in industrialization, urbanization in consort with growing inhabitants, unprocessed sewage discharge, and toxic industrial effluents causes different life-threatening diseases. Manual water quality monitoring techniques vividly aggravate quality deterioration. Considering the significance of the automatic water quality monitoring system, we need an in-situ, real-time, continuous surveillance system to ascertain the quality of potable water. Wireless Sensor Network (WSN) motivated us for a practical water quality monitoring system due to their continuous, real-time, and adaptive infrastructure to provide an early alert in hazardous conditions. Objective: To design and implement an online potable water quality monitoring network for rural water supply schemes in Nagapattinam district, Tamilnadu, India, to sense physiochemical parameters of potable water such as pH, turbidity, conductivity and temperature. Methods: Online POTable water quality monitoring NETwork (POTNET) integrates the reimbursements of WSN and different information and communication technologies for data acquisition, data processing, and data visualization. The core hardware of POTNET contains off-the-shelf sensors (i.e., electrodes), a microcontroller, a data transmission system, a customized buoyage, and a sink node. It senses physiochemical parameters of potable water such as pH, turbidity, conductivity, and temperature in a pre-programmed time interval. Furthermore, it enables cloud storage for gathered information and generates an alert to the preregistered user via mobile phones when there is a deviation of quality measures from threshold values. Results: The system was implemented in three overhead tanks for seven days in order to validate the stability of the buoy and efficiency of energy source, storage, and data transmission. It senses physiochemical parameters of potable water such as pH, turbidity, conductivity, and temperature in its predefined interval of 30 minutes. To check the system accuracy, the measured data values from developed sensors were compared with the observed data values using a commercial multi-parameter water checker, the Horiba® probe. Measured data were sent through the transceivers to the base station for data logging in a suitable format for ease of data visualization and utilization. Conclusion: Extensive experimental results reveal that our POTNET can be employed for potable water quality surveillance to help consumers or concern authorities to make a sound decision by providing appropriate and real-time data.

Modeling and Visualization of Man’s ‘Digital Shadow’ at Enterprises

The article studies the potential of introducing systems of the situational center in order to build a system providing safe life in the real range of time and effective management of production and organization processes within the frames of the concept of shifting to industry 4.0. On the basis of research findings today's enterprises and organizations should form strategy of their development with due regard to the necessity to digitalize the man. The key goals of this process are monitoring of employees' vital functions, extrapolation and modeling of substandard situations and visualization of generalized information in a suitable format in the range of real time. By analyzing the condition and problems of enterprise digitalization the authors systematized key factors, which should be taken into account for building the advanced system of providing labour safety in the range of real time, proposed the automated management system of providing labour safety based on the system of the situational center and the procedure of developing strategy of enterprise digitalization with regard to HR digitalization, which includes introduction of the system of situational center. By using situational center the modulus for modeling and visualization of ‘digital shadow' was worked out to monitor vital functions of enterprise employees.

254 An Audit to Assess the Completion of Consent Forms in the Department of Trauma and Orthopaedics

Abstract Aim The objective was to audit how well the consent forms were being completed by junior doctors and registrars in the orthopaedic ward. This helped to assess whether the consent forms before orthopaedic procedures were being filled out according to the standards stated in the RCS and NICE guidelines. Method The initial audit was carried out in January 2020 in the three orthopaedic surgery wards at the Queen’s Medical Centre in Nottingham. Cross sectional data was collected by checking the consent forms to assess whether the important headings and sub-headings were filled out legibly with adequate information. Results All consent forms filled up in the study sample had the patient details and the name of the surgery written completely and accurately. 75.6% of the forms had the name of the Responsible Health Professional written, while the remaining had left the space blank or wrote an incorrect name. More than 90% of the forms had the intended benefit, and the possible risks of the orthopaedic operation written in the most suitable format. The likelihood of a blood transfusion being required was filled out in 78.6% of the forms. All consent forms were signed by a doctor, however, only 53% of the doctors provided both their name in print and contact number in the consent form. Conclusions Consent is an essential prerequisite for any operative procedure. By detecting the parts of the consent form that were frequently filled out inadequately, awareness was raised about the possible legal consequences of it.

Behavioral Analysis of Personality, Branding and Emotional State in e-Sports

E-sports have grown in popularity on a worldwide scale. Recent assessments place the industry's value at more than $612 million, with operations spanning Europe, North America, and Asia's emerging economies. Nowadays, e-Sports are being hailed as a highly effective marketing channel for businesses. The current study attempted to analyze the personal profiles of e-sports players in order to offer them with marketing privileges that would enable them to promote their companies more effectively. Three self-report questionnaires were used to collect data: the Profile of Mood States, the Eysenck Personality Questionnaire, the Emotional Intelligence Questionnaire, and the Brand Personality Appeal Questionnaire. The collected data were analyzed using appropriate transformations to provide a suitable format for implementing the corresponding machine learning algorithms available in the R software package. The findings of this study demonstrate, among other things, that mood state, emotional intelligence, and brand personality can all serve as critical variables and are prevalent in marketing literature covering a broad range of topics, including evidence that the mood state, emotional intelligence, and brand personality profiles of e-sports players can all serve as significant variables.

БЪЛГАРИЯ – МОЯТА ДРЕВНА И МЛАДА РОДИНА

Every teacher knows that raising a pupil is a constant exchange of thoughts and feelings between the teacher and the children. Somewhere in the process of this exchange it happens that the teacher feels the spark of the national feeling in the pupils’ souls, so he must support it with the relevant knowledge in order to ignite and intensify the feeling. The education of a worthy citizen of his country is one of the leading tasks of the preschool education. Its essence consists of the creation and implementation of a well-thought-out system of pedagogical actions, aimed at the formation of a civic consciousness and feelings in the child. The main goals in my work with the children in the group „Flame“ of kindergarten „Brezichka“ in Vratsa was to get them acquainted with the concept of the Motherland in a suitable format, to instill in them a sense of pride for their country, a desire to actively participate in public life and last, but not least – in the preservation of the Bulgarian language.