bluuebunny/crossref_metadata_2025 huggingface dataset:
Smart car parking system model for urban areas
Authors: Rahman Atiqur
Published: May 2024

This article is on the smart car parking system. In which we going to utilize the ultrasonic sensor to distinguish the vehicle and it will assist the proprietor with finding an advantageous parking spot. Parking spots are significant in city urban areas. In view of the expansion in a huge number of vehicles, the requirement for parking spots is a need, and henceforth an earnest need to build up a system that can deal with these parking spots. To determine these necessities, we build up a system to show the empty path in the parking spots. This includes a system that incorporates an ultrasonic sensor, Raspberry pi 4, Wi-Fi module, and a light emitting diode (LED) show outside the vehicle parking entryway. Parking spots are observed by the staff of the concerned power. The paper incorporates the subtleties of parts that are utilized and about the working of this system. The paper likewise shows that our system's looking through an ideal opportunity to locate a free spot is more productive than some other existing system.
Enhancing the fuzzy inference system using genetic algorithm for predicting the optimum production of a scientific publishing house
Authors: Siti Kania Kushadiani  , Agus Buono  , Budi Nugroho
Published: May 2024

As a scientific publishing house, Indonesian Institute of Sciences (LIPI) Press' encountered some problems in publication planning, mainly predicting the optimum production of publications. This study aimed to enhance a fuzzy inference system (FIS) parameters using the genetic algorithm (GA). The enhancements led to optimally predict the number of LIPI Press publications for the following year. The predictors used were the number of work units, the number of workers, and the publishing process duration. The dataset covered a five years range of total production of LIPI Press. Firstly, an expert set up the parameters of the fuzzy inference system denoted as a FIS expert. Next, we performed a FIS GA by applying the genetic algorithm and K-fold validation in splitting the training data and testing data. The FIS GA revealed optimum prediction with parameters that were composed of both population size (30), the probability of crossover (0.75), the probability of mutation (0.01), and the number of generations (150). The experiment results show that our enhanced FIS GA outperformed FIS expert approach.
Text classification to predict skin concerns over skincare using bidirectional mechanism in long short-term memory
Authors: Fitrianah Devi , Wangsa Andre Hangga
Published: May 2024

There are numerous types of skincare, each with its own set of benefits based on key ingredients. This may be difficult for beginners who are purchasing skincare for the first time due to a lack of knowledge about skincare and their own skin concerns. Hence, based on this problem, it is possible to find out the right skin concern that can be handled in each skincare product automatically by multi-class text classification. The purpose of this research is to build a deep learning model capable of predicting skin concerns that each skincare product can treat. By comparing the performance and results of predicting the correct skin condition for each skincare product description using both long short-term memory (LSTM) and bidirectional long short-term memory (Bi-LSTM), The best results are given by Bi-LSTM, which has an accuracy score of 98.04% and a loss score of 19.19%. Meanwhile, LSTM results have an accuracy score of 94.12% and a loss score of 19.91%.
Automatic model transformation on multi-platform system development with model driven architecture approach
Authors: Aila Gema Safitri  , Firas Atqiya
Published: May 2024

Several difficulties commonly arise during the software development process. Among them are the lengthy technical process of developing a system, the limited number and technical capabilities of human resources, the possibility of bugs and errors during the testing and implementation phase, dynamic and frequently changing user requirements, and the need for a system that supports multi-platforms. Rapid application development (RAD) is the software development life cycle (SDLC) that emphasizes the production of a prototype in a short amount of time (30-90 days). This study discovered that implementing a model-driven architecture (MDA) approach into the RAD method can accelerate the model design and prototyping stages. The goal is to accelerate the SDLC process. It took roughly five weeks to construct the system by applying all of the RAD stages. This time frame does not include iteration and the cutover procedure. During the prototype test, there were no errors with the create, read, update, and delete (CRUD) procedure. It was demonstrated that automatic transformation in MDA can shorten the RAD phases for designing the model and developing an early prototype, reduce code errors in standard processes like CRUD, and construct a system that supports multi-platform.
Comparative study of ensemble deep learning models to determine the classification of turtle species
Authors: Faurina Ruvita , Wijanarko Andang , Heryuanti Aknia Faza , Ishak Sahrial Ihsani , Agustian Indra
Published: May 2024

Sea turtles are reptiles listed on the international union for conservation of nature (IUCN) red list of threatened species and the convention on international trade in endangered species of wild fauna and flora (CITES) Appendix I as species threatened with extinction. Sea turtles are nearly extinct due to natural predators and people who are frequently incorrect or even ignorant in determining which turtles should not be caught. The aim of this study was to develop a classification system to help classify sea turtle species. Therefore, the ensemble deep learning of convolutional neural network (CNN) method based on transfer learning is proposed for the classification of turtle species found in coastal communities. In this case, there are five well-known CNN models (VGG-16, ResNet-50, ResNet-152, Inception-V3, and DenseNet201). Among the five different models, the three most successful were selected for the ensemble method. The final result is obtained by combining the predictions of the CNN model with the ensemble method during the test. The evaluation result shows that the VGG16 - DenseNet201 ensemble is the best ensemble model, with accuracy, precision, recall, and F1-Score values of 0.74, 0.75, 0.74, and 0.76, respectively. This result also shows that this ensemble model outperforms the original model.
Optimization of an inset-fed calculations for rectangular microstrip antenna
Authors: Dase Sulwan , Razak Irawati
Published: May 2024

This paper offers an alternative solution to produce a formula to calculate the inset-fed (????????)  feed distance from the edge of the patch in order to obtain the impedance of a rectangular patch microstrip antenna as close to 50 Ohm as possible. The basic calculation refers to Ramesh's calculation formula to calculate the inset-fed (????????) on a rectangular patch microstrip antenna. From this research it is hoped that a number of correction factors will be obtained which will be multiplied by the Ramesh formula in order to obtain an inset-fed calculation which results in a lower return loss (????????????) and voltage standing wave ratio (VSWR). From several calculation attempts, the approximate value for the correction factor is s=0.83477. This s correction factor is then multiplied by Ramesh's calculation formula. In this experiment, a microstrip antenna was simulated using an FR4 epoxy printed circuit board (PCB) with a relative permittivity, ???????? = ????. ????, with a thickness of h=1.6 mm. The specified antenna nominal input impedance is 50 Ohms. The transmission line used is a microstrip line with a characteristic impedance of 50 Ohm. The test method used is to compare the results of simulation calculations using the Ramesh formula with the results of simulation calculations using the Ramesh formula multiplied by the correction factor. Tests are carried out using varying working frequencies. From the experimental results it can be seen that the average Return Loss (????????????) and VSWR of the antenna are lower when using the Ramesh formula with a correction factor compared to the original Ramesh formula.
Net impact implementation application development life-cycle management in banking sector
Authors: Pramitasari Noviana , Ruldeviyani Yova , Zarkasie Irvan Ramadhan
Published: May 2024

Digital transformation in the banking sector creates a lot of demand for application development, either new development or application enhancement. Continuous demand for reimagining, revamping, and running applications reliably needs to be supported by collaboration tools. Several big banks in Indonesia use Atlassian products, including Jira, Confluence, Bamboo, Bitbucket, and Crowd, to support strategic company projects. We need to measure the net impact of application development life-cycle management (ADLM) as a collaboration tool. Using the deLone and McLean model, process questionnaire data from banks in Indonesia that use ADLM. Processing data using structural equation modeling (SEM), multiple variables are analyzed statistically to establish, estimate, and test the causation model. The conclusions highlight that system quality strongly affected only User Satisfaction (p=0.049 and β=0.39). Information quality strongly affected use (p=0.001 and β=0.84) and strongly affected user satisfaction (p=0.169 and β=0.28). Service quality strongly affected only use (p=0.127 and β=0.31). Conclusion research verifies the information system's achievement approach described by DeLone and McLean. Importantly, it was discovered that system usability and quality were key indicators of ADLM success. To fulfill their objective, ADLM must be developed in a way that is simple to use, adaptable, and functional.
Privacy in computer ethics: Navigating the digital age
Authors: Zostant Maxwell , Chataut Robin
Published: May 2024

In this digital age, privacy has become a crucial issue due to the vast amount of personal information we share online. As a fundamental aspect of computer ethics, it concerns the appropriate use of information and communication technologies. This paper will discuss five key points related to privacy in computer ethics: the concept of privacy and its significance in the context of computer ethics; ethical considerations surrounding personal information in the digital space, including issues of consent, transparency, and data protection; the legal framework surrounding privacy in different jurisdictions, such as data protection laws and international standards; the role of technology in protecting privacy, including the use of encryption and other security measures; and finally, the challenges associated with protecting privacy in the digital age, such as the risk of data breaches, identity theft, and other forms of online exploitation. Through these five key points, this paper aims to provide a comprehensive understanding of privacy in computer ethics and emphasize the importance of promoting responsible and ethical use of technology.
Social media and optimization of the promotion of Lake Toba tourism destinations in Indonesia
Authors: Harahap Muhammad Said , Khadafi Rizal , Hasibuan Effiati Juliana , Saputra Agung , Hardiyanto Sigit , Lubis Faizal Hamzah
Published: May 2024

Tourism is one of the largest contributors to Indonesia's foreign exchange earnings, surpassing taxation, energy, and gas. This study seeks to investigate the use of social media to optimize the promotion of Lake Toba as a tourist destination, which has been impacted by the COVID-19 pandemic. Using interview techniques and live field observations, it was discovered that social media, particularly the Instagram platform, play a significant role in promoting Lake Toba tourism. The Department of Culture and Tourism of the North Sumatra Province uses landscape photography as its primary promotion method, which has proved to be more effective and interesting than conventional methods such as the distribution of brochures or the use of manuals. The capture procedure and techniques for landscape photography were carried out by professional photographers in collaboration with the Department of Culture and Tourism of the North Sumatra Province. In addition to providing information, tourism_sumut's Instagram account functions as a platform to raise public awareness about Lake Toba tourism and as a promotional medium for North Sumatra's tourist attractions on an international scale. Department of Culture and Tourism of the North Sumatra Province collaborates with travel agencies and local communities to disseminate Lake Toba tourism information.
Development reference model to build management reporter using dynamics great plain aggregated
Authors: Wijaya Santo Fernandi , Wiratama Jansen , Kuswanto Verri
Published: May 2024

The digital technology transformation impacts changes in business patterns that require companies to innovate to act appropriately in making strategic decisions quickly, precisely, and accurately to increase efficiency, be practical company performance, and impacts changes in business patterns that require companies to innovate to act appropriately in making strategic decisions quickly to improve the performance. An enterprise resource planning (ERP) system is one step toward achieving performance. ERP system is one step to achieving performance. ERP system is essential for companies to automate the efficiency of business processes. The decisions from management in implementing the ERP system are necessary for ERP implementation to be successful. However, in practice, companies still experience complexity. For that, it needs to be considered related a business process reference model is essential to enhance efficiency in implementing the ERP used. This research discusses the business process reference model based on the ERP dynamics great plain (GP) application aggregated using management reporter (MR) to help users better understand the practical overview. The methodology utilizes a reference model based on Microsoft Dynamics GP guidelines with a business process redesign approach. This contributes to developing business processes to help users understand using the ERP dynamics GP application.
Predicting students' success level in an examination using advanced linear regression and extreme gradient boosting
Authors: Wahyuningsih Tri , Iriani Ade , Purnomo Hindriyanto Dwi , Sembiring Irwan
Published: May 2024

This research employs a hybrid approach, integrating advanced linear regression and extreme gradient boosting (XGBoost), to forecast student success rates in exams within the dynamic educational landscape. Utilizing Kaggle-sourced data, the study crafts a model amalgamating advanced linear regression and XGBoost, subsequently assessing its performance against the primary dataset. The findings showcase the model's efficacy, yielding an accuracy of 0.680 on the fifth test and underscoring its adeptness in predicting students' exam success. The discussion underscores XGBoost's prowess in managing data intricacies and non-linear features, complemented by advanced linear regression offering valuable coefficient interpretations for linear relationships. This research innovatively contributes by harmonizing two distinct methods to create a predictive model for students' exam success. The conclusion emphasizes the merits of an ensemble approach in refining prediction accuracy, recognizing, however, the study's limitations in terms of dataset constraints and external factors. In essence, this study enhances comprehension of predicting student success, offering educators insights to identify and support potentially struggling students.
Deep learning technique for plant disease detection
Authors: Adekunle Temitope Samson , Lawrence Morolake Oladayo , Alabi Oluwaseyi Omotayo , Afolorunso Adenrele A. , Ebong Godwin Nse , Oladipupo Matthew Abiola
Published: May 2024

A nation's economy is primarily reliant on agricultural growth. However, several plant diseases seriously impair crop growth, both in terms of quantity and quality. Due to a lack of subject matter specialists and low contrast data, accurate diagnosis of many diseases by hand is highly difficult and time-consuming. The farm management system is therefore looking for a method for automatically detecting early illnesses. To overcome these challenges and correctly classify the different diseases, an efficient and small deep learning-based framework (E-GreenNet) is proposed. A MobileNetV3Small model is used as the foundation of our end-to-end architecture to produce finely tuned, discriminative, and noticeable features. Furthermore, the new plant composite (PC), plantvillage (PV), and data repository of leaf images (DRLI) datasets are used to independently train our proposed model, and test samples are used to evaluate its actual performance. The suggested model achieved accuracy rates of 1.00 percent, 0.96 percent, and 0.99 percent on the given datasets after a rigorous experimental study. Additionally, a comparative investigation of our proposed technique against the state-of-the-art (SOTA) reveals extremely high discriminative scores.
Sentiment analysis of online licensing service quality in the energy and mineral resources sector of the Republic of Indonesia
Authors: Hizqil Ahmad , Ruldeviani Yova
Published: May 2024

The Ministry of Energy and Mineral Resources of the Republic of Indonesia regularly assessed public satisfaction with its online licensing services. User rated their satisfaction at 3.42 on a scale of 4, below the organization's average of 3.53. Evaluating public service performance is crucial for quality improvement. Previous research relied solely on survey data to assess public satisfaction. This study goes further by analyzing user feedback in text form from an online licensing application to identify negative aspects of the service that need enhancement. The dataset spanned September 2019 to February 2023, with 24,112 entries. The choice of classification methods on the highest accuracy values among decision tree, random forest, naive bayes, stochastic gradient descent, logistic regression (LR), and k-nearest neighbor. The text data was converted into numerical form using CountVectorizer and term frequency-inverse document frequency (TF-IDF) techniques, along with unigrams and bigrams for dividing sentences into word segments. LR bigram CountVectorizer ranked highest with 89% for average precision, F1-score, and recall, compared to the other five classification methods. The sentiment analysis polarity level was 36.2% negative. Negative sentiment revealed expectations from the public to the ministry to improve the top three aspects: system, mechanism, and procedure; infrastructure and facilities; and service specification product types.
Implementing lee's model to apply fuzzy time series in forecasting bitcoin price
Authors: Farida Yuniar , Ainiyah Lailatul
Published: May 2024

Over time, cryptocurrencies like Bitcoin have attracted investor's and speculators' interest. Bitcoin's dramatic rise in value in recent years has caught the attention of many who see it as a promising investment asset. After all, Bitcoin investment is inseparable from Bitcoin price volatility that investors must mitigate. This research aims to use Lee's Fuzzy Time Series approach to forecast the price of Bitcoin. A time series analysis method called Lee's Fuzzy Time Series to get around ambiguity and uncertainty in time series data. Ching-Cheng Lee first introduced this approach in his research on time series prediction. This method is a development of several previous fuzzy time series (FTS) models, namely Song and Chissom and Cheng and Chen. According to most previous studies, Lee's model was stated to be able to convey more precise forecasting results than the classic model from the FTS. This study used first and second orders, where researchers obtained error values from the first order of 5.419% and the second order of 4.042%, which means that the forecasting results are excellent. But of both orders, only the first order can be used to predict the next period's Bitcoin price. In the second order, the resulting relations in the next period do not have groups in their fuzzy logical relationship group (FLRG), so they can not predict the price in the next period. This study contributes to considering investors and the general public as a factor in keeping, selling, or purchasing cryptocurrencies.
Construcción de subjetividades en procesos de participación juvenil e incidencia en el desarrollo comunitario
Authors: Bermúdez Romero Diana Janneth , Parra Espejo Diana Paola , Patarroyo Gómez Laura Jinneth , Peña Reyes Maria Helena
Published: May 2024

El propósito de esta investigación, consiste en comprender la construcción de subjetividades en los procesos de participación juvenil y su incidencia en el desarrollo social comunitario. En el estudio participaron jóvenes pertenecientes a dos colectividades: Movimiento de Hip Hoppers y Movimiento Vida Estudiantil, de la ciudad de Bogotá. La investigación es de corte cualitativo y se desarrolló bajo el enfoque de la teoría fundamentada propuesta por Strauss y Corbin (2002); las técnicas empleadas para la recolección de la información fueron la entrevista yla observación.
¿El sistema educativo está favoreciendo procesos cognitivos y emocionales en los estudiantes, que les permitan formarse y fortalecerse en habilidades para la vida?
Authors: Arias Alba Rocio
Published: May 2024

Este artículo presenta una “experiencia significativa” desarrollada en la Escuela Normal Superior de Caldas en Manizales. En él se plantea cómo la música y la gimnasia cerebral son empleadas como estrategias que conducen a una integración de los hemisferios cerebrales, propiciando una mejor disposición del estudiante hacia el aprendizaje. La experiencia muestra un recorrido desde sus inicios y la forma como se está desarrollando hasta la fecha, expone además las alternativas de aplicación en el aula, como un aporte a los docentes que deseen ponerla en práctica en su institución. Por último se hace una reflexión para los docentes que ven en las propuestas innovadoras, una opción de trascender su misión y transformar paradigmas para llegar a una verdadera revolución en el aprendizaje.
Association Between Family History and Early‐Onset Atrial Flutter Across Racial and Ethnic Groups
Authors: Shah Anish S. , Ongtengco Ana , Qiao Victor , Chen Yining , Diaz Annette , Hill Michael , Bhan Adarsh , Tofovic David S. , Darbar Dawood
Published: May 2024

Background

Genetic and familial contributions to early‐onset atrial fibrillation are described primarily in individuals of European ancestry. However, the role of racial and familial contributions in the pathogenesis of early‐onset atrial flutter (
EOAFL
) is unclear.

Methods and Results

In this cross‐sectional study, participants were enrolled prospectively from 2015 to 2021 in multiple academic centers with a diagnosis of atrial flutter (
AFL)
confirmed by ECG.
EOAFL
was defined as a diagnosis of
AFL
before age 66 years with no concomitant or previous diagnosis of atrial tachyarrhythmias. Family history was adjudicated through baseline questionnaires and direct family interviews about the diagnosis of atrial tachyarrhythmias, stroke, and cardiomyopathy. The primary exposure was a positive family history in first‐degree relatives, and the primary outcome was the odds of
EOAFL
versus late‐onset
AFL
. A total of 909 patients were enrolled. Participants with a positive family history of atrial tachyarrhythmias were younger, less likely to be of Black race, and more likely to have
EOAFL
. The adjusted odds ratio (
OR
) for
EOAFL
in those with a positive family history was 1.8 (95%
CI
, 1.1–3.0). There was an increased odds of
EOAFL
in those of Black race (
OR,
2.1 [95%
CI,
1.4–3.2]), alcohol use (
OR,
1.6 [95%
CI,
1.0–2.6]), and obstructive sleep apnea (
OR,
1.9 [95%
CI,
1.0–3.4]). Use of cardioselective β blockers or calcium channel blockers before the diagnosis of
AFL
were associated with a lower odds of
EOAFL
(
OR,
0.5 [95%
CI,
0.2–0.9]).

Conclusions

These findings suggest a potentially hereditary predisposition to
EOAFL
across race and ethnicity, warranting further study of the genetic contributions to
AFL
.
Prediction of 24‐Hour Urinary Sodium Excretion Using Machine‐Learning Algorithms
Authors: Hamaya Rikuta , Wang Molin , Juraschek Stephen P. , Mukamal Kenneth J. , Manson JoAnn E. , Tobias Deirdre K. , Sun Qi , Curhan Gary C. , Willett Walter C. , Rimm Eric B. , Cook Nancy R.
Published: May 2024

Background

Accurate quantification of sodium intake based on self‐reported dietary assessments has been a persistent challenge. We aimed to apply machine‐learning (ML) algorithms to predict 24‐hour urinary sodium excretion from self‐reported questionnaire information.

Methods and Results

We analyzed 3454 participants from the NHS (Nurses' Health Study), NHS‐II (Nurses' Health Study II), and HPFS (Health Professionals Follow‐Up Study), with repeated measures of 24‐hour urinary sodium excretion over 1 year. We used an ensemble approach to predict averaged 24‐hour urinary sodium excretion using 36 characteristics. The TOHP‐I (Trial of Hypertension Prevention I) was used for the external validation. The final ML algorithms were applied to 167 920 nonhypertensive adults with 30‐year follow‐up to estimate confounder‐adjusted hazard ratio (HR) of incident hypertension for predicted sodium. Averaged 24‐hour urinary sodium excretion was better predicted and calibrated with ML compared with the food frequency questionnaire (Spearman correlation coefficient, 0.51 [95% CI, 0.49–0.54] with ML; 0.19 [95% CI, 0.16–0.23] with the food frequency questionnaire; 0.46 [95% CI, 0.42–0.50] in the TOHP‐I). However, the prediction heavily depended on body size, and the prediction of energy‐adjusted 24‐hour sodium excretion was modestly better using ML. ML‐predicted sodium was modestly more strongly associated than food frequency questionnaire‐based sodium in the NHS‐II (HR comparing Q5 versus Q1, 1.48 [95% CI, 1.40–1.56] with ML; 1.04 [95% CI, 0.99–1.08] with the food frequency questionnaire), but no material differences were observed in the NHS or HPFS.

Conclusions

The present ML algorithm improved prediction of participants' absolute 24‐hour urinary sodium excretion. The present algorithms may be a generalizable approach for predicting absolute sodium intake but do not substantially reduce the bias stemming from measurement error in disease associations.
Silencing PDCD4 Mediates Transcription Factor EB Overexpression Promoting Proliferation, Migration, and Invasion of Cervical Cancer Hela Cells
Authors: Gao Xing , Liang Ziying , Yuan Yanan , Liu Wenbo
Published: May 2024

Cervical cancer is a common gynecologic malignant tumor, the occurrence and development of which are related to multiple genetic and environmental factors. Recent studies have shown that Programmed Cell Death 4 (PDCD4) plays a crucial role in cervical cancer, and that silencing PDCD4
mediates Transcription Factor EB (TFEB) overexpression, promoting cell proliferation, migration, and invasion in this disease. This study utilized the Hela cell line as a cervical cancer model to investigate the changes in TFEB expression levels and the proliferation, migration, invasion,
and EMT processes of cervical cancer cells through the silencing of PDCD4. Real-time quantitative PCR and Western blot were employed to assess the expression levels of PDCD4 and TFEB, while CCK-8, scratch assay, Transwell invasion assay, and Western blot were used to evaluate changes in cell
proliferation, migration, invasion capabilities, and EMT processes. The experimental results demonstrated that silencing PDCD4 significantly increased the expression level of TFEB. Simultaneously, silencing PDCD4 also significantly accelerated the proliferation rate of Hela cells, enhanced
the cells’ migration, invasion capabilities, and promoted the EMT processes. Further experimental results showed that silencing TFEB could partially reverse the promoting effects of PDCD4 silencing on cell proliferation, migration, and invasion. In cervical cancer, silencing PDCD4 can
lead to TFEB overexpression, thereby promoting the proliferation, migration, and invasion of Hela cells. These findings provide crucial clues for the in-depth study of molecular mechanisms in cervical cancer and indicate that the PDCD4-TFEB pathway could potentially serve as a target for the
treatment and prevention of this disease.
Unveiling the Behavior of Perfluoro (2-Ethoxyethane) Sulfonic Acid Potassium (PESK) in Water/Gas System: Molecular Dynamics Simulation
Authors: Chen Ke , Jing Xianwu , Zhang Huali , Wang Yezhong , Xie Wuping , Shuai Chungang , Wen Bo , Zhang Nanqiao , Zhang Peiyu , Wu Hao , Wang Lijia
Published: May 2024

Molecular dynamics method (MD) was used to study the distribution of potassium perfluoro (2-ethoxyethane) sulfonic acid (PESK) in water/gas systems. When the PESK aqueous solution system reaches equilibrium, the vast majority the fluorocarbon chain is facing toward the gas phase, while
the sulfonic acid radical faces toward the water, with a very small quantity of PES− is still in the bulk solution. The weak intermolecular interactions were analyzed by IGMH method, and the interaction energy between PES− and water mainly comes from the h-bonds
formed by the oxygen atom in the sulfonic acid group and hydrogen atom in water molecules. K+ are mainly distributed inside the aqueous solution, and there is only van der Waals interaction between K+ and H2O molecules. According to the distribution of ESP
analysis of PES−, it is mainly the sulfonic acid groups that are negatively charged.
Green Synthesis of Nanomaterials: Properties and Their Potential Applications
Authors: Ansari Noureen , Basree  , Tripathi Ayush , Ameen Sadia , Shaheer Akhtar M. , Jabeen Fakhra , Rahman Khan Abdul , Luqman Mohammad , Rahman Qazi Inamur
Published: May 2024

This review paper aims to provide an overview of the synthesis and applications of nano-dimensional materials. For the last few decades, nanotechnology has emerged as an excellent tool for a wide range of applications due to the phenomenal and splendid properties of materials at the
nano-level. It finds applications almost in every sector from industrial applications to biomedical applications. Any particles in the range of 1–100 nm have been considered as NPs. NPs can be synthesized by either of the two ways “bottom-up” and “top-down” approaches.
Due to the certain drawbacks of some of the methods which consume chemicals and generate toxic byproducts, green synthesis has been considered the most effective method using various plant extracts. Biogenic synthesis of the NPs by reducing the metal precursors to NPs is safe cost-effective
and eco-friendly and it doesn’t utilize any chemicals. Green synthesis, a bottom-up approach is quite efficient for the synthesis of a number of NPs. A comparative study of the synthesis of NPs using various plant extracts has been discussed along with their application.
Increasing Musical Persistence and Engagement in the Contemporary Music Classroom
Authors: Schatt Matthew
Published: May 2024

With many activities vying for students’ time and attention, helping young musicians achieve their potential while inspiring them to continue engaging with music throughout their lifetime is a vital part of the music educator’s role. To accomplish this important function, the teacher may strive to fulfill students’ psychological needs, leading to improved student achievement and well-being, enjoyment of learning, and greater participation in class, among other positive outcomes. Through an understanding of the basic human needs for autonomy, relatedness, and competence, this article applies these fundamental components of human psychology to the music classroom. Teachers can readily implement meaningful activities to guide students in lifelong music learning, leading to increased engagement and decreased attrition in musical study.
Examining the Associations Between Substance Misuse and Suicide Bereavement
Authors: Feigelman William , Cerel Julie , Gutin Nina , McIntosh John L. , Gorman Bernard S. , Bottomley Jamison S. , Edwards Alice
Published: May 2024

Focusing on the understudied question of substance misuse among suicide bereaved adults we investigated patterns of binge drinking and non-prescribed drug use among a recently bereaved sample ( n = 1,132). Comparing our respondents to the non-bereaved, those in the 2022 National Survey of Drug Use and Health ( n = 71,369), we did not find heightened problematical substance misuses among our respondents. With t-tests and multiple regression analyses we examined whether binge drinkers and non-prescribed drug users had heightened levels of grief difficulties, PTSD, self-blaming and depression compared to others not bingeing or using non-prescribed drugs. Results showed binge drinkers had more of all these grieving problems when important confounding variables were also considered. Analysis of the demographic correlates of bingeing showed them dimly aware of their own additional grieving and substance misusing problems. Since 75% indicated being under the care of counseling professionals, this represents an important opportunity for psycho-educational helping.
Improved fiber orientation measurement in nonwovens with corner removal
Authors: Li Chengzu , Wang Rongwu
Published: May 2024

The orientation of fibers or filaments in nonwovens is critical in determining their mechanical characteristics. Image processing techniques, prized for their minimal human intervention and rapid processing speed, are widely utilized in nonwoven fiber orientation measurement. However, these techniques often face substantial challenges, such as low accuracy in corner detection, errors in fiber segmentation, and inefficiencies in fiber orientation calculation. Addressing these concerns, this study introduces a novel, enhanced method accompanied by two innovative optimization algorithms to enhance accuracy. The first innovation involves the development of a newly developed fiber corner detection algorithm, dubbed the T-detector, specifically tailored for the unique characteristics of fiber images, enabling efficient corner point detection and removal. Subsequently, we introduce and employ a fiber length restriction algorithm to further segment the processed longer fibers into the remaining fiber fragments and utilize a skeleton projection algorithm to calculate the fiber orientation. These algorithms overcome the existing technology’s inherent shortcomings, thereby heightening measurement accuracy. The results illustrate an improvement in measurement precision over other orientation distribution measurement algorithms, with the fiber information retention (covering ratio) reaching an impressive 95%. Our proposed method not only calculates fiber orientation distribution in nonwovens with remarkable accuracy and efficiency, but its innovative approach also stands to provide a theoretical foundation for the design of three-dimensional filtering models with specific fiber orientation.
Distributed finite-time optimization for networked Euler–Lagrange systems under a directed graph
Authors: Liu Yuan , Liu Pinxiao , Zhang Bing
Published: May 2024

In this paper, we investigate the finite-time distributed optimization problem for multiple Euler–Lagrange systems. A new distributed optimization control scheme is presented to achieve the state agreement in finite time while minimizing the sum of each agent’s local cost function. The proposed algorithm has the advantage of being able to achieve distributed finite-time optimization consensus under general unbalanced connected directed communication graphs. By virtue of finite-time Lyapunov theory and convex optimization, the finite-time convergence for the algorithm is analyzed. A numerical example is also presented to illustrate the effectiveness of the obtained results.
Irish teacher practice of differentiation for gifted students
Authors: Hinch Leeanne , Cross Jennifer Riedl , Cross Tracy L. , O'Reilly Colm , Bilgic-Erdem Serife
Published: May 2024

In this study, we aimed to analyze Irish educators' differentiation practices and their relationship to teachers' sense of efficacy. We examined teachers' ( N = 470) reports of their curriculum modification practices and their provision of challenge or choice. When their students had mastered the required class work, more than half of teachers were willing to substitute assignments on a weekly or daily basis for both their average and gifted students. However, the frequency of differentiation was not high in practices that eliminate mastered curricular material or allow students to work at their own pace, which would allow gifted students to work at their ability level. More than 40% of teachers reported practicing these forms of differentiated instruction once a month or less frequently. Fifteen percent of teachers reported never engaging in these effective differentiation practices. Differentiation practice was positively correlated with teachers’ sense of efficacy, particularly for instructional strategies.
Spiral complete coverage path planning based on conformal slit mapping in multi-connected domains
Authors: Shen Changqing , Mao Sihao , Xu Bingzhou , Wang Ziwei , Zhang Xiaojian , Yan Sijie , Ding Han
Published: May 2024

The generation of smoother and shorter spiral complete coverage paths in multi-connected domains is a crucial research topic in path planning for robotic cavity machining and other related fields. Traditional methods for spiral path planning in multi-connected domains typically incorporate a subregion division procedure that leads to excessive subregion bridging, requiring longer, more sharply turning, and unevenly spaced spirals to achieve complete coverage. To address this issue, this paper proposes a novel spiral complete coverage path planning method using conformal slit mapping. It takes advantage of the fact that conformal slit mapping can transform multi-connected domains into regular disks or annuluses without the need for subregion division. Firstly, a slit mapping calculation technique is proposed for segmented cubic spline boundaries with corners. Secondly, a spiral path spacing control method is developed based on the maximum inscribed circle radius between adjacent conformal slit mapping iso-parameters. Thirdly, the spiral coverage path is derived by offsetting iso-parameters. Numerical experiments indicate that our method shares a comparable order-of-magnitude in computation time with the traditional PDE-based spiral complete coverage path method, but it excels in optimizing total path length, smoothness, and spacing consistency. Finally, we performed experiments on cavity milling and dry runs to compare the new method with the traditional PDE-based method in terms of machining duration and steering impact, respectively. The comparison reveals that, with both algorithms achieving complete coverage, the new algorithm reduces machining time and steering impact by 12.34% and 22.78%, respectively, compared with the traditional PDE-based method.
A Critical Review of Methods for Backfill Soil Modulus in Design of Flexible Culverts
Authors: Sukuvara Dan Sergei , Vaslestad Jan , Scibilia Elena , Baardvik Gunvor , Grimstad Gustav
Published: May 2024

Flexible culverts made of corrugated steel or plastic are cost-effective and environmentally friendly alternatives to conventional small road and railway bridges. These structures interact with the backfill by deflecting when subjected to overburden loads, enabling them to utilize the surrounding soil by carrying loads in ring compression. In low soil cover situations, the relationship between bending and backfill soil (stiffness) modulus increasingly influences bearing capacity, and therefore must be considered in design. Backfill soil modulus is a direct result of the execution of the backfilling, and recognized as the most important design parameter because of local uncertainties during construction and material variability. This paper gives a review of some of the existing methods for determining backfill soil modulus. It covers development history, theoretical approximations, aspects of crushed rock materials and their quality, and ease of use in routine design. By applying the methods on different materials and comparing the end results with a compilation of large-scale compression tests and materials from various origins, the performance of the reviewed methods is evaluated. It is found that the reviewed methods have specific drawbacks depending on the actual stress condition and backfill material being applied. In addition, most methods are based on reference laboratory tests carried out on specific and sometimes high-quality materials, and therefore fail to reflect how the quality of rock materials influences the backfill modulus. These shortcomings are used to suggest a new outlook that should be considered in future research on backfill design.
Aeroelastic analysis of a lightweight topology-optimized sandwich panel
Authors: Najafi Maliheh , Ferreira António J. M. , Marques Flávio D.
Published: May 2024

Sandwich structures with lattice cores are novel, lightweight composite structures and are widely used in the aerospace industry. Besides, the aeroelastic behavior of sandwich panels in a supersonic flow regime still needs to be thoroughly studied. This work investigates the supersonic flutter of a sandwich panel whose core is topology-optimized. A finite element model of a sandwich panel based on the layerwise theory, coupled with the first-order piston theory, is presented. The sandwich panel core is assessed using a topology optimization approach with flutter loading constraints. The subsequent analytical homogenization scheme is developed to provide the equivalent mechanical properties of the topology-optimized panel. The modeling approach is fully validated, and the results demonstrate that the sandwich panel is capable of enlarging the flutter-free operational flight range when compared with other conventional panel designs. A parametric analysis of the topology-optimized sandwich panel regarding the critical flutter conditions is performed.
Merrem's Hump-Nosed Viper (Hypnale hypnale) Bite on the Tongue of an Infant Leading to Upper Airway Obstruction: An Unusual Presentation
Authors: Gunawardena Chanaka , Samarathunga Hemal , Bandara Dayananda , Kiridena Anuruddha , Silva Anjana
Published: May 2024

Snakebites in unusual anatomical locations may lead to life-threatening consequences. Merrem's hump-nosed viper ( Hypnale hypnale) is a medically important snake in Sri Lanka and India that causes many bites and envenomings. Their bites occur almost exclusively on upper and lower limbs and commonly result in local effects, with some patients developing systemic envenoming. No antivenom is available for treating envenoming by H. hypnale. We report an unusual case of H. hypnale bite on the tongue of a 10-month-old infant resulting in rapid local swelling of the tongue and floor of the mouth, requiring prompt intervention to prevent life-threatening upper airway obstruction. Early tracheostomy prevented upper airway obstruction and, along with supportive steroid therapy and antibiotics, led to a complete resolution of the local effects of the infant without permanent disability, despite the unavailability of antivenom.
Economic impacts of digital home-sharing platform: Creative destruction in the hospitality industry
Authors: Um Taehyee , Lee Yejin , Koo Jakeun
Published: May 2024

This paper describes an empirical study that was conducted by applying creative destruction theory to examine structural changes in the hospitality industry due to the growth of digital home-sharing platforms. To achieve these research aims, the current study considered the hospitality industry, which encompasses the accommodation and restaurant sectors, as well as Airbnb, representing the digital home-sharing platform. The findings revealed that there is a significant relationship between the exit of the accommodation industry and the supply of the digital home-sharing platform, while both entry and exit in the restaurant industry are significantly associated with the supply or performance of the digital home-sharing platform. Over time, this leads to industry transformations as certain segments of the lodging industry are replaced by digital home-sharing platforms, and as the restaurant industry undergoes a process of creative destruction, with establishments unable to adapt to changing business environments and the emergence of new facilities tailored to new technologies or accommodation models.
The reflective function questionnaire for youth: Hungarian adaptation and evaluation of associations with quality of life and psychopathology
Authors: Szabó Brigitta , Sharp Carla , Futó Judit , Boda Márton , Losonczy Laura , Miklósi Mónika
Published: May 2024

An important correlate of mental health problems is mentalizing capacity, which appears to be particularly influential during adolescence. However, quality of life has not been studied in relation to mentalizing capacity among adolescents. This study aimed to translate the Reflective Function Questionnaire for Youth (RFQY) into Hungarian, present its psychometric properties, and assess its relationship with demographic characteristics, psychopathology and quality of life. A community sample of 384 youths aged 12–18 years completed the RFQY, the Measure of Quality of Life for Children and Adolescents, and the Strengths and Difficulties Questionnaire. First, we conducted an exploratory factor analysis with direct oblimin rotation on the RFQY items. Next, we assessed the associations between the RFQY and demographics, quality of life, and psychopathology. The EFA resulted in four factors: Internal-self, Internal-other, Self-other, and Strong emotions. The Cronbach’s alpha coefficients of the scales were .81, .82, .67, and .80, respectively. The subscales were uniquely associated with psychopathology and quality of life. Our study provides the first psychometric support for the Hungarian version of the RFQY and indicates that adolescents suffering from internalizing, externalizing symptoms or lower levels of quality of life could benefit from interventions aimed at enhancing mentalizing capacity.
Acoustic tones generated by impinging jets: Differences between laminar and highly-disturbed nozzle-exit boundary layers
Authors: Varé Mathieu , Bogey Christophe
Published: May 2024

The differences between the acoustic tones generated by impinging jets with laminar and highly-disturbed nozzle-exit boundary layers are investigated. For that, jets at Mach numbers between 0.6 and 1.3 impinging on a flat plate at a distance of 8 nozzle radii from the nozzle exit are computed using large-eddy simulations. The amplitudes of the tones generated by the jets through feedback loops establishing between the nozzle and the plate are found to be significantly affected by the exit turbulent disturbances. In the present study, overall, they are lower for the initially laminar jets than for the initially disturbed ones. The level decrease varies from a few dB up to 15 dB, depending on the tones, which can change the frequencies of the dominant tones and the numbers and azimuthal structures of their associated feedback modes. For Mach numbers 0.75 and 0.8, for instance, the dominant tone frequencies are approximately two times lower for the initially laminar jets than for the other ones, yielding a better agreement with experiments of the literature in the former case. For a Mach number of 1.1, as a second example, the dominant tone is associated with the axisymmetric third feedback mode in the laminar case but with the helical fifth feedback mode in the disturbed case. The differences in the tone amplitude are finally discussed by estimating the power gains of the shear-layer instability waves between the nozzle and the plate using linear stability analysis for the axisymmetric mode. In most cases, at the frequency of a specific tone, the higher the gain, the stronger the acoustic tone.