bluuebunny/crossref_metadata_2025 huggingface dataset:
Removal of infected bone in-growth pelvic fixation implants and microcomputed tomography analysis of osseous integration: illustrative case
Authors: Spence Bradley S , Godlewski Matthew W , Haselhuhn Jason J , Jones Kristen E , Polly David W
Published: August 2024

BACKGROUND

A novel pelvic fixation screw fusion device (iFuse Bedrock Granite implant) was designed to promote bony fusion through self-harvesting fenestrations throughout the outer screw shank. Bone on-growth and in-growth using this design have been demonstrated in a sheep model, but data from human subjects have not been reported. A 66-year-old medically complex female with 2 prior spine fusions developed spondylodiscitis cephalad to a prior fusion, requiring the removal of instrumentation, which included screw fusion devices.

OBSERVATIONS

Within this case report, the authors present a novel bone-preserving technique for the removal of well-fixed screw fusion devices. One screw backed out with a driver, and the other 3 had to be trephined out. One screw sheared off the T30 torque driver, implying a removal torque greater than 270 inch-lbs (30.5 Nm). In addition, the removed implants were analyzed using microcomputed tomography (micro-CT) and demonstrated bone on-growth, in-growth, and through-growth in all 4 screws.

LESSONS

Micro-CT clearly demonstrated osseous integration of the screw fusion devices and provided significant support for the use of these implants for lumbopelvic fixation. The authors’ hope is that the novel bone-preserving technique will help other surgeons when faced with the difficult removal of well-fixed screw fusion devices.

https://thejns.org/doi/10.3171/CASE24274
Dorsal arachnoid web of the thoracic spine associated with an arachnoid cyst and a presyrinx state as an unexplained cause of thoracic myelopathy: illustrative case
Authors: Halloran Patrick J , Leclair Nathan K , Bulsara Ketan R , Chozick Bruce S , Moss Isaac L , Becker Kevin P , Gershon Abner S , Onyiuke Hilary C
Published: August 2024

BACKGROUND

Dorsal thoracic arachnoid web is a rare diagnosis and is not commonly seen in neurosurgical practice. Patients can present with symptoms and signs of thoracic myelopathy in the setting of an arachnoid cyst and a presyrinx state.

OBSERVATIONS

A 57-year-old male with a 10-year history of worsening bilateral leg weakness and chronic back pain re-presented to the neurosurgery clinic after being seen by neurology and orthopedic spine surgery. Initial imaging was concerning for myelomalacia and syringomyelia, and repeat delayed computed tomography myelography findings were consistent with an evolving thoracic arachnoid web, now demonstrating spinal cord compression secondary to arachnoid cyst formation and consistent with the signs of thoracic myelopathy. Intraoperative ultrasound displayed the arachnoid web as the cause of the evolving arachnoid cyst, edematous spinal cord, and a presyrinx-like state. The patient underwent surgical decompression, which restored cerebrospinal fluid (CSF) dynamics, resulting in clinical improvement.

LESSONS

Dorsal thoracic arachnoid web is a dynamic condition that can occur in the setting of an arachnoid cyst. There appears to be a relationship between dorsal thoracic arachnoid web formation and the presence of an arachnoid cyst resulting from a ball-valve mechanism leading to the creation of a pressure gradient effect that alters CSF fluid dynamics.

https://thejns.org/doi/10.3171/CASE24313
An innovative neural network-based technique for identifying power quality issues
Authors: Jayabalan Bhuvana , Yadav Rakesh Kumar , Batra Raman , Saxena Ashendra Kumar
Published: August 2024

Power quality (PQ) is defined as a combination of voltage quality and current quality. PQ is fast and difficult to predict. The primary issues that customers in the industry are consider being related to transitory interruptions, drawback include voltage sags, surges, harmonics and interruptions. To overcome this problem, we proposed an Adaptive Feedforward Bidirectional Gated Recurrent Neural Network (AF-BiGRNN) method to improve power quality issues. A PQ measurement shows a much more valuable asset. In the study, we gather the Reference Energy Disaggregation (REDD) dataset. The collected data is preprocessed using min max normalization to clean the data. Wavelet Packet Transform (WPT) is employed to extract the data features. The selected appropriate data is used to test the process using AF-BiGRNN method. The simulation findings of the result use a Python tool. As a result, our proposed method achieves significant outcomes with Accuracy (96%), Energy consumption (67.8%), Computational time (2.0%) and Voltage stability (97%). The Conclusion that identifies power quality issues is crucial for ensuring the reliability and efficiency of electrical systems.
A novel reinforcement learning-based framework for defect identification and analysis in remote sensor networks
Authors: Bharadwaj Shambhu , Dhandapani Ganesh , Kumar Ritesh , Joshi Apoorva
Published: August 2024

In remote sensing networks, defect detection and analysis are essential to preserve the networks' performance. A sensor based defect detection and diagnostic system for the internet of things (IoT) network is the focus of this research. However, this goal presents issues because of the sensors' limited processing power, storage capacity and operational energy. Furthermore, defect detection is crucial, but recognition is sometimes time-sensitive. In this research, we propose a unique framework to tackle this issue using reinforcement learning (RL). Data gathering from the remote sensor network is the initial stage in our approach. To build a large dataset for analysis, we collect sensor data. To gather data, various network-deployed sensors' readings must be gathered. Data preparation includes tokenization, which is performed on the acquired data before analysis. Data tokenization is the process of dividing data into more manageable portions. An essential part of our methodology is feature extraction, where we translate the tokenized information into a format appropriate for defect identification. We use wavelet transform, a robust method for gleaning informative features from time-series data. This procedure improves the quality of the data participation, making it more appropriate for further analysis. We present a novel classification method based on the Enhanced Squirrel Optimized Effective Reinforcement Neural Network (ESSO-ERNN) in our study. To categorize data examples into defect or non-defect categories, this neural network model integrates optimization approaches with the concepts of RL. Fault detection performance is evaluated by determining the F1-measure, detection accuracy (DA), precision and recall rates by using python software. In addition, the metric for classification accuracy demonstrates the efficacy of defect diagnostics.
An innovative transfer-learning-based deep learning approach to identify agriculture pest
Authors: Agarwal Trapty , Shukla Amita , Gupta Mohan Vishal , Kannagi A.
Published: August 2024

Agricultural pests are living organisms that cause damage or hinder the typical growth and development of crops, resulting in reduced yields and financial losses for the farming industry. Agriculture has been a crucial source of nutrition across all of human history. It is the foundation of the economy in many nations, with over 90% of the population depending on it for a living. Outbreaks of pests increase the problems with agricultural crop production. This study suggested a deep learning (DL) architecture based on an Attentive deep convolutional generative adversarial network (ADCGAN) that includes transfer learning to identify agricultural pest that helps farmers for cultivation. For this study, the IP102 insect pest dataset was used. The preprocessing stage comprises the sliding window cropping method, an essential tool in modern agriculture. We use Gabor Filter for feature extraction, enabling pattern identification and image enhancement. To detect pests in agriculture, the target data training network uses the initial values of the parameters learned using ResNet networks on the accessible ImageNet dataset. Realistic images can be produced with ADCGANs with simplicity. With a collection of pest images as training data, the generator can generate artificially manufactured once incredibly real images of pests. Training the strong pest detection models using this enhanced dataset could be beneficial. We evaluate the effectiveness of the suggested method by contrasting it with existing identification approaches that employ evaluation parameters such as the AUC score, f1-score, recall, accuracy and precision. The results indicate that the suggested ADCGAN performs more effectively than the conventional techniques. The flexibility of the ADCGAN method enables customized pest control plans. It can adapt its identification method to various agricultural settings by taking inputs from particular agro-ecosystems.
Machine learning insights into surface processing's impact on tool metal tribology
Authors: Upadhyay Satish , Singh B. P. , Pandey Pratik , Patil Nagraj
Published: August 2024

The processing of their surfaces can greatly influence the tribological behavior of tools used in different machining processes. In the study, we proposed the potential of a machine learning (ML) approach known as multi-objective gravitational search optimized adaptive naive bayes algorithm (MGSO-ANBA) for forecasting and enhancing tools' tribological performance in response to a wide range of surface processing variables. The first step is to gather extensive tribological data under different surface processing settings using the NEU metal dataset. A Box Cox transformation is used for preprocessing to improve the dataset's quality by correcting for abnormality and reducing variation in tribological measures. To describe the interactions between the tool and the metal, acoustic emission (AE) is used extensively. The dynamics of the tribological processes are clarified with the help of the extracted characteristics. By acquiring insights into the effect of surface processing on tool metal tribology, our suggested technique MGSO-ANBA can be utilized for classification purposes to increase understanding and optimize performance across various industrial applications. Significant tribological results, such as Surface roughness (96%), Wear rate (94%) and Coefficient of friction (97%), can be predicted with great accuracy using the suggested model.
Developing a novel deep learning optimization method for forecasting soil friction gradient
Authors: Lone Zeeshan Ahmad , Upadhyay Satish , Babu R. Dushyanth V. , Agrawal Trpaty
Published: August 2024

In this study, the crucial factor in geotechnical design, soil friction, is predicted using artificial neural networks (ANN). Additionally, the Stochastic Henry gas solubility (SHGSO) optimization approach was used to determine the best number of hidden layers and neurons in each hidden layer, that is, the optimal structural ANN parameters to enhance the performance of ANN. We suggested an innovative way for forecasting Soil Friction Gradient (SFG) using a Stochastic Henry gas solubility optimization-based improved artificial neural network (SHGSO-IANN). A database with 316 laboratory test results was collected for forecasting the SHGSO-IANN model. This research aims to improve comprehension of internal SFG determination by investigating experimental and theoretical approaches. The main goal is to evaluate the viability of a theoretical approach that has been offered as a substitute for conventional exploratory testing to estimate soil friction angle. The SHGSO-IANN method is assessed based on its RMSE (5.74), R2 (96.7%), MAE (5.21) and MAPE (5.95), demonstrating robust performance metrics. This work requires an integrated approach that combines theoretical and experimental techniques to improve the effectiveness of internal friction angle calculation in soil mechanics.
Wear and frictional training of alumina base compositions using tribology-strategy based on a machine learning approach
Authors: Lone Zeeshan Ahmad , Thimmappa Arunkumar Devalapura , Kaushik Naresh , Singh B. P.
Published: August 2024

Due to the intricate and dynamic relationships that exist between the material and its working surroundings, tribological reactions in alumina-based composites are a considerable problem. Conventional approaches for comprehending Wear and friction fail to capture the complex interactions among variables influencing these characteristics. To address this, study leverages a machine learning (ML) approach to create a thorough knowledge base regarding the tribological qualities of compositions that use Alumina. To anticipate wear and friction qualities, a novel dynamic grey wolf-driven support vector machine (DGW-SVM) technique is presented in this paper. The compositions are undertaken through Wear and frictional study in which a variety of material elements and production circumstances are methodically investigated. The suggested model incorporates experimental evidence from tribological testing and it is developed to identify trends and relationships in the dataset. The proposed approach is developed in Python and its achievement is evaluated using multiple variables, including RMSE (0.098), MAE (0.114) and R2 (0.998). The learned algorithm is then applied to unproved compositions to forecast their Wear and frictional performance, allowing for fast and intelligent decision-making. A contrast with conventional experimental approaches is used to evaluate the effectiveness of the suggested methodology, which shows promise for substantial reductions in time and resources.
Employing a combination of thermo simulations in the CDF-DEA connection to analyze the course of heat transport in a fluidized bed
Authors: Chaudhary Pavan , Shekhawat Jyoti , Nagappan Beemkumar , Upadhyay Satish
Published: August 2024

Fluidized bed heat transfer is a complex and broad subject, and as such, there are many scientific and commercial applications. The three primary regions of fluid-to-particle, particle-to-fluid, and wall-to-particle and fluid-to-fluid heat transmission were the main topics of heat transfer experiments in fluidized beds. In many industrial processes, it is very necessary to have a solid understanding of the mechanisms via which fluidized bed structures transfer mass and heat production. Fluidized beds' exchange of mass and heat is a complex and wide-ranging subject with many potential uses in science and industry. The Computational Dynamics Fluid -Discrete Element Approach (CDF- DEA) connection is used in this numerical study to examine how heat energy is transported in a fluidized bed. During a mathematical test, the outcomes of an analysis and quantitative test are contrasted for a solitary particle inside a section. Comparison is made between two different cooling and heating situations. The mathematical findings are in excellent alignment with the analytical findings. The improvement of the structures of these units depends on the growth of fluidized bed units inside fluidized bed units. As a result, the simulations have suggested three different ways to heat a column, including base heating, wall heating, and wall plus base heating. The results demonstrate that it is incorrect for the fluid input frequency to rise when fluidized beds are heated. Because the particles must provide the thermal transfer mechanism enough time, the fluidized bed heating process depends on the fluid's proper input frequency and enforced temperatures.
Assessing the environmental impact of recyclable aggregate through life cycle analysis
Authors: Shankar S. Amar , Chaudhary Deeksha , Ul Hassan Inzimam , Homavazir Zuleika
Published: August 2024

All aspects of a product or system's life cycle, from raw materials to disposal extraction, can be evaluated for their effects on the environment using the Life Cycle Analysis (LCA) technique. When considering the environmental impact of recyclable aggregate, such as recycled concrete or asphalt, LCA provides valuable insights into the potential benefits and drawbacks. This study used ISO 14044 (LCA) to assess the effects of matter cleared during recycled aggregate (RA) manufacturing (dry/wet) on acidification potential (AP), ozone depletion potential (ODP), global warming potential (GWP), biotic resource depletion potential (ADP), and eutrophication potential (EP). When contrast to recycled aggregate (dry), wet recycled aggregate had an environmental effect that was up to 16–40% greater. This difference was mostly due to the energy consumption of impact crushers during the construction of wet RA. The use of RA was shown to have an environmental impact that was up to double as large as of utilizing natural aggregate (NA), partly because the manufacture of NA was more energy-efficient and simpler. The usage of RA is made from leftover building waste, whereas the utilization of NA depletes natural resources and results in an ADP that is roughly 20 times greater. When compared to artificial “light-weight aggregate (LWA)” although higher than “slag aggregate (SA)”, RA GWP was less in the life cycle effects evaluation.
Analysing the role of semiotics in films – from an architect’s perspective
Authors: Chandran Vharshini , Jagadisan Sharmila
Published: August 2024

In recent years film Industry and tv program are hugely popular across the globe and it is considered as a main stream activity. India has a long standing reputation and fame for its acclaimed world class movies. This industry has a significant positive impact on our economy and it has grown phenomenally in terms of media market globally. Being the largest entertainment industry for more than 125 years it is very evident that Indian cinema is attracting more footfalls in theatres. As per the fiscal year 2020 the film industry was valued 183 billion Indian rupees and so it does make sense that pursuing career in film industry is highly coveted. The role of set designer plays a pivotal and integral role in films creative part as they oversee all visual elements and closely associate themselves with art department. In modern cinema the concept of semiotics has gained more importance and they play a significant role in the representation of films as they provide indirect visual cues.  To make a successful film, using semiotics set designers employ various images as part of the story telling mechanism and apply culturally informed strategies which is of recent trend. Being in a creative field many architects have successfully taken set designer as their passion and career. Film has been part of our life – a dominant mode of expression where little research has been done on the role of semiotics. Shall one look at a film as art or story telling medium or communication? What is the role of semiotics in set design? The objective of the paper is to see how architects can enhance the role of semiotic expressions in set design.
Applying a novel deep learning technique to credit hazard modeling in business financial management
Authors: Khanna Roma , Tiwary Angad , Sharma Geeti , Gupta Poonam
Published: August 2024

In financial management, where precise credit default forecasting is crucial for well-informed decision-making, credit hazard modeling is an essential part of risk assessment. Predicting the possibility of a borrower failing on their financial commitments, such as loans or credit card payments, is the primary goal of credit hazard modeling. In this paper, we provide an innovative technique called Adaptive Gravitational Search Dynamic Convolutional NeuroNet (AGS-DCNN) for credit hazard modeling. The large-scale examination of consumers who have established accounts ultimately yields information relevant to the financial standing of medium-sized and small-sized businesses from various industries. Over the course of five years, we obtained 410 financial data in total from 80 distinct companies. The Z-Score preprocessing approach is used to normalize and transform financial data to make it more suitable for study. Principle Component Analysis (PCA) is a feature extraction approach used to minimize dimensionality and capture the most important characteristics, enhancing model efficiency and interpretability. AGSA is an innovative optimization approach that adapts to the scenario and optimizes the suggested architecture, guaranteeing that the network is well-tailored to the unique needs of credit hazard modeling. To estimate credit default events, the suggested AGS-DCNN approach is tested using real-world financial data. The results show that it outperforms existing credit risk models regarding the estimated recall, f1-score, accuracy, precision, and resilience. Furthermore, the AGS-DCNN approach is adaptable to varied datasets. It has the potential to understand complicated patterns in financial data, making it suited for a wide range of financial management applications.
Advanced skin disease detection: Image processing and modified genetic optimization with supervised k-nearest neighbors
Authors: Meena Dilip , Sharma U. S. Upendra , Mohanan M. , Patel Geetika M.
Published: August 2024

The use of modern technology to improve skin disease diagnosis includes things like artificial intelligence (AL), deep learning (DL) and computer vision. Medical images of skin lesions, dermatoscopic images, or thermal imaging can be analyzed by automated algorithms and image processing techniques to diagnose skin diseases. Diseases can cause physical and emotional suffering, making them silent killers. Extreme instances might cause skin cancer. skin disease diagnosis from clinical photographs is a key medical image processing challenge. Manual skin diagnosis takes time and it is subjective for doctors. Computerized skin disease prediction can simplify patient and dermatologist treatment planning. To tackle these issues, we proposed a genetic optimization and supervised K-Nearest Neighbor (MGO-SKNN) technique for detecting advanced skin diseases. The research gathers clinical data for detecting advanced skin diseases. Three methods were used to preprocess our data: noise reduction, hair removal and image resizing. The Grey Level Co-Occurrence Matrix (GLCM) approach was used in this work to extract features.  The integration of image processing into MGO-SKNN represents a significant step forward in the quest for accurate, efficient and cutting-edge skin disease diagnosis. The metrics like accuracy (97.53%), precision (95.20%), recall (96.74%) and f1-score (98.06%) of our suggested technique, MGO-SKNN, exceed the traditional approaches for skin detection.
Effects of coping mechanisms on nurses' practices and psychological well-being
Authors: Pandey Noopur , Arun Jagdish Kumar , Pallavi  , Disawala Hansika , Upadhye Vijay J.
Published: August 2024

Lockdown procedures brought on by the COVID-19 outbreak have severely limited athletes' possibilities to exercise, creating both physical and psychological difficulties. This study looked into how lockdowns affected people who participated in adventure sports, including cycling, swimming, and running. Examining the effect of lockdown on athletes' perceptions of instruction barriers. The study's specific goal was to look into the relationships between instruction volume, lockdown-specific resilience, perceptions of movement limitations, and instruction hurdles. The study also sought to examine the relationship between athletes' personal dedication to their sports and lockdown resilience, coping mechanisms, and perceived instruction constraints. An online survey was used to collect participant information. The survey was used to examine variables such as age, gender, country of residence, personal involvement in endurance sports, resilience, emotion regulation mechanisms, mobility limits, instruction regimens, and mental health. To find participants on pertinent internet sites, convenience sampling techniques were used. The data were examined statistically using multiple regression analysis and nonparametric testing. According to the study's findings, poorer instruction volume, a lower level of lockdown-specific resilience, and more unfavorable views of lockdown mobility limits were all linked to higher levels of perceived instruction barriers during the lockdown. According to the data, athletes that had a strong personal commitment to their sport showed stronger mental resilience. COVID-19 pandemic lockdown had an effect on athletes' preparation and mental health. Reduced instruction, a lack of resilience, and unfavorable opinions all increased hurdles. Strongly devoted athletes showed resilience, adaptive coping, and less burdens. Personal dedication and coping skills are essential for athletes' wellbeing through trying circumstances.
Relationship between patient and therapist counter transference in transference and non-transference practices
Authors: Mahida Navghan , Zuleika Homavazir  , Khan Nishat , Pallavi  , Singh Neelesh
Published: August 2024

The importance of therapists' emotional reactions, or Counter Transference (CT), in the therapeutic process has received attention in recent studies. The communication potential of CT has been highlighted by the systematic correlations these researchers have found between therapists' CT and numerous patient variables. To better understand the function of Transference Work (TW) in psychodynamic therapy and how it relates to therapist cognitive treatment (CT), we conducted a Randomized Controlled Trial (RCT). New study data has shown a consistent link among therapists' emotional response and Counter Transference (CT) in treatment, as well as a number of patient variables, illuminating the collaborative potential of CT. We looked into whether patient pretreatment interpersonal issues, the severity of personality dysfunction and the urge for psychodynamic therapy were associated with the therapist's transference work (TW) used in psychodynamic treatment in a Randomized Controlled Experiment (RCT) evaluating the role of TW. The second thing we looked at was whether or not the therapists employed TW in their sessions regarding these relationships. 100 outpatients received psychodynamic counseling (with or without TW). The Feelings Word Checklist-68 (FWC-68) was used to gauge their therapists' post-session emotional responses (CT). Patient characteristics differently predicted four FWC-68 subscales: insufficient, self-assured, extricate, and benevolent feelings. The level of pathology associated with PD. was connected with therapists in the non-TW group feeling less competent, according to some relationships that relied on the treatment situation. Patients' treatment desire was correlated with less troubling CT sentiments, including insufficient and distracted CT plus felt more self-assured CT. Depends on whether psychologists use transfer work in psychodynamic therapy, patient characteristics predict therapists' emotional Counter Transference in different ways.
Study to explore the facilitators and barriers of infant and young children feeding (IYCF) practices among mothers of infants and young children attending referral centres - A MMR
Authors: Perdita A. Helen Mary , Jemima Sornamalar
Published: August 2024

Ideal infant and young children feeding, (IYCF) includes initiation of breastfeeding within half an hour to one hour of birth, exclusive breastfeeding for six months of birth. The Government is spending huge amount of time and sources towards improving the health of mother and children still the mothers are not aware of importance of IYCF practices. The aim of the study was to explore the facilitators and barriers of IYCF practices among mothers of infants and young children attending urban and rural Health centers at Madurai. The majority of the mothers (86.6%) had inadequate level of feeding practices. In the qualitative phase the researcher noted facilitators and barriers. The facilitators were appropriate ante natal health check-ups, institutional deliveries etc Regarding the barriers influence of social media, economic crisis, cultural barriers etc. the researcher concluded that still continuous step to be taken by VHN in the health centres to promote IYCF practices.
Pesan Motivasi pada Lirik Lagu “Jalan Pulang” karya Yura Yunita
Authors: Annisa Lutfyyah
Published: August 2024

Penelitian ini berfokus pada pesan motivasi yang terdapat dalam lirik lagu “Jalan Pulang” karya Yura Yunita. Pada lirik lagu “Jalan Pulang” yang berisikan 6 bait tersebut Yura Yunita menyampaikan pesan motivasi secara eksplisit maupun implisit yang akan didengarkan oleh para pendengarnya. Oleh sebab itu, peneliti akan membedah pesan motivasi perjalanan dalam meraih mimpi dan pesan motivasi pencarian makna pulang pada lirik lagu “Jalan Pulang” karya Yura Yunita. Penelitian ini memakai metode analisis isi kualitatif deskriptif Miles dan Huberman dalam memaknai setiap lirik lagu “Jalan Pulang” karya Yura Yunita. Adapun aspek pendukung dalam penelitian ini adalah data dokumentasi eksternal seperti jurnal dan wawancara teks. Penemuan dari hasil penelitian menunjukkan adanya dua aspek penelitian yang merujuk pada tema utama yaitu: proses meraih mimpi dan mencari jalan pulang. Kedua aspek tersebut kemudian dikerucutkan kembali menjadi dua tema analisis yaitu: pesan motivasi perjalanan dalam meraih mimpi dan pesan motivasi pencarian makna pulang. Lirik lagu dapat menjadi media komunikasi bagi khalayak umum untuk merepresentasikan pesan motivasi dalam setiap bait.
 
Kata-kata Kunci: Analisis Isi Kualitatif; Pesan Motivasi; Lirik Lagu
Perceived Ease Of Use and User Experience Using Chat GPT
Authors: Wulandari Ajeng Ayu , Ohorella Noviawan Rasyid , Nurhaipah Titih
Published: August 2024

This research analyzes the impact of Perceived Ease Of Use, Performance Expectations, Effort Expectations, Social Influence, and Facilitating Conditions communication on the Interaction Efficiency of communication interactions with machines. Analysis of these factors is important because they have a direct influence on communication interactions with GPT Chat. Understanding the impact will drive improvements and improve the overall user experience. The theoretical framework in this research is the Unified Theory of Technology Acceptance and Use (UTAUT) and Human Machine Interaction (HCI). Data was collected through a questionnaire with a Likert scale and tested on 100 respondents using the Purposive Sampling method on GPT Chat users. The results of the research show that five variables, namely Effort Expectancy, Social Influence, User Experience, Performance Expectancy, and Customer Satisfaction have a positive and significant influence on user experience, Interaction Efficiency, and Interaction Efficiency. Meanwhile, the other two variables are Facilitation Conditions and Perceived Ease of Use. , has no significant effect on user communication. The results of the determination analysis show that Perceived Ease of Use and the UTAUT Model contribute 25.8% to User Experience, while User Experience contributes 6.2% to Interaction Efficiency. This research improves the Chat and Interaction Efficiency user experience. It contributes to the field of technology acceptance and communication of how humans interact with machines.
Analisis Framing Terhadap Branding Politik Anies Baswedan Sebagai Gubernur Daerah Khusus Ibu Kota (DKI) Jakarta
Authors: Anam Muhammad Syafi'il
Published: August 2024

Penelitian ini berfokus mengenai analisis tentang kepemimpinan Anies Baswedan selama menjabat sebagai Gubernur Daerah Khusus Ibu Kota (DKI) Jakarta, penelitian ini di analisis menggunakan teori gaya kemimpinan yakni (gaya kepemimpinan partisipasi, gaya kepemimpinan otoriter, gaya kepemimpinan idealized influence) dan teori sosiologi politik Ibnu Khaldun yang menempatkan rakyat menjadi faktor penentu keberadaan suatu negara, yang tidak terlepas dari solidaritas sosial. sehingga mendapatkan informasi dari dua perspektif yang berbeda untuk mengkaji permasalahannya. Metode pada penelitian ini menggunakan studi kepustakaan yang sumber datanya diperoleh dari artikel, jurnal, karya ilmiah dan pemberitaan media sosial mengenai Anies Baswedan sehingga dengan metode tersebut diharapkan mampu untuk mensuksekkan jalannya penelitian. Hasil dari penelitian ini menunjukkan bahwa Gubernur DKI Jakarta Anies Baswedan membawa perubahan pada Kota Jakarta dengan mega proyek 1). Pembangunan Stadion JIS, 2). Penerbitan Aplikasi JakLingko, 3). Pelebaran Trotoar Kota Jakarta, 4). Pembangunan Jalur Sepeda, 5). Penyelenggaran Event Formula E, 6). Revitalisasi Kota Tua Batavia Jakarta. Sehingga dengan fokus, metode dan hasil penelitian tersebut dapat memiliki tujuan yang jelas yaitu menggali bagaimana perkembangan Kota Jakarta pasca dipimpin oleh Anies Baswedan serta bagaimana branding politik seorang Anies Baswedan, penelitian ini juga dapat menjadi pembaharuan pada penelitian baru dan juga diharapkan mampu memberikan informasi yang manfaat serta motivasi baru untuk para pemimpin di Indonesia.Kata kunci: Anies, Gubernur, Jakarta, Kepemimpinan, Branding Politik
Potret Politisi Perempuan Kabupaten Dharmasraya (Studi tentang Potret Anggota Legislatif Perempuan Kabupaten Dharmasraya periode Tahun 2019-2024)
Authors: Andola Weli , Budiman Novi
Published: August 2024

It is illustrated that women in Indonesia, including in Dharmasraya Regency, still face various obstacles in entering and surviving in politics. Patriarchal culture, internal constraints such as domestic roles, and external constraints such as a political system that still favors men are the main factors that hinder women's participation in politics. So this research aims to find out how the portrait background of female legislative members of Dharmasraya Regency in the 2019-2024 period, the strategy of female legislative members in winning Pileg in Dharmasraya Regency, and the role of female legislative members of Dharmasraya Regency in the formation of local policiesThis research method uses a qualitative method. The data collection techniques that researchers use are observation, interviews and documentation. The data obtained were analyzed using three stages, namely data reduction, data presentation, and drawing conclusionsWomen Legislative Members of Dharmasraya Regency still do not meet the 30% quota. The lack of women's representation in the 2019 legislative elections held in Dharmasraya Regency only had 2 female candidates who managed to occupy parliamentary seats: Elisa Septiani and Sasmi Erli. The strategies used by the legislature in winning the legislative general election include: formulation of vision and mission, assessment of the situation and evaluation of the role of the Dhamasraya Regency Women's DPRD as a form of community representation in controlling gender responsive policies related to development in Dharmasraya Regency. Because women's thoughts and feelings will be able to collaborate to prioritize ongoing gender-responsive policies. Therefore, the role of women politicians is very important in the process of making until the birth of the 2019-2024 Dharmasraya Regency regional regulations.
Innovation in Local Digital Media: The Case of Sevilla Directo
Authors: Caro-González Francisco J. , Moreno Mesa Juan Manuel , Lora Manuel Garrido
Published: August 2024

Introduction: The journalistic company is immersed in a process of permanent transformation to overcome a crisis context. In this scenario, marked by disruptive changes in technology and in the behaviour of audiences and advertisers, a communication ecosystem emerges that facilitates the emergence of new media. Community social media, data journalism, and specialisation are some of the characteristics present in these business models. The objective of this research is to identify and understand the role of innovation in media adaptation to the current communication paradigm. Methodology: The case study will be used. For this, we will analyse a digital native medium in a city of approximately 700,000 inhabitants, Sevilla Directo. The techniques of information collection have been observation, analysis of websites, in-depth interviews, a discussion group between journalists, and reports and databases of the sector. Results and discussion: The results show that technological advances and the reach of social networks are fundamental for the growth of local media. However, it is observed that adaptive changes predominate with little disruption and little concern for R&D&I. The organisation under study lacks a business model that guarantees its long-term sustainability and bases its subsistence on traditional income routes. At the same time, social capital stands as a key element in financing.
Speaking about Restorative Justice
Authors: Castell-Britton Sigifredo
Published: August 2024

Restorative Justice (RJ) offers a transformative approach to addressing criminal behavior by focusing on healing and restitution rather than punishment. This manuscript examines RJ’s foundational principles, highlighting its roots in indigenous practices and its contrast with traditional retributive justice models. Evidence from diverse cultural and legal contexts demonstrates RJ’s effectiveness in reducing recidivism, promoting offender rehabilitation, and enhancing community cohesion. However, the manuscript also addresses challenges, such as implementation difficulties and limitations in cases of gender-based violence. By presenting a comprehensive analysis of RJ’s benefits and obstacles, this manuscript underscores its potential to create a more compassionate and effective criminal justice system.
Fintech Revolution: Empowering Entrepreneurial Intentions through Crowdfunding, Cryptocurrency, Blockchain, Mobile Payments, and Artificial Intelligence
Authors: Khan Sharbaz , Munir Mehtab , Ghauri Saghir Pervaiz
Published: August 2024

PURPOSE – Financial technology, also known as “FinTech,” has evolved to disrupt nearly every aspect of traditional financial services and it has become increasingly important in the world’s economic system. The main purpose of the study is to explore the relationship between Financial Technology (Fintech) and Entrepreneurial Intentions. It focuses on the impact of specific Fintech innovations such as Crowdfunding, Mobile Payments, Blockchain, Cryptocurrency, and Artificial Intelligence (AI), on Entrepreneurial Finance.

The study examines how these Fintech advancements have affected the overall entrepreneurial ecosystem, fostering innovation, supporting startups, and driving economic growth. Using mixed-methods, the research combines qualitative interviews and quantitative surveys to reveal key factors that have completely shaped the entrepreneurial ecosystem in the context of fintech.

EXECUTIVE SUMMARY – Financial technology revolution unleashing a wave of technological innovations has transformed the entrepreneurial landscape. Crowdfunding, cryptocurrency, blockchain, mobile payments, and artificial intelligence (AI) play key roles in empowering aspiring entrepreneurs, fueling financial inclusion, and driving economic growth. This report examines the impact of these fintech advancements on entrepreneurial intentions, exploring their benefits, challenges, and future prospects.
The Impact of Dietary Intake and Nutritional Status on Birth Outcomes Among Pregnant Adolescents: A Systematic Review
Authors: Gyimah Linda
Published: August 2024

Birth outcomes have been linked to the overall maternal general health including nutrition as well as maternal age during pregnancy. Compared to adults, delivery outcomes during adolescence are poor. Nutrient intake and nutrition status during adolescent pregnancy may be linked to birth outcomes. This review aims to identify the association between dietary intake and nutrition status of pregnant adolescents and their maternofetal outcomes. Literature search on nutrient intake and nutritional status of pregnant adolescents (aged 11-19 years) which identified 17 English papers from 1995 to 2019 was reviewed. Papers that did not include data on birth outcomes in relation to nutrient intake or nutritional status were excluded. The review showed that most micronutrients with the exception of Riboflavin, vitamins B12 and C were below the recommended levels whilst macronutrients levels were above the recommended levels. Energy intakes were also below the recommended levels. Most studies presented normal hemoglobin levels in the first trimester of pregnancy but these levels decreased as pregnancy progressed to the third trimester leading to a high prevalence of anemia. Well-regulated provision and intake of micronutrient supplementation and nutrition education to improve healthy eating habits will significantly reduce poor birth outcomes such as low birth weights (LBW), still births, preterm deliveries, small or large for gestational age (SGA and LGA) and intrauterine growth restrictions in pregnant adolescents. This review provides to a large extent evidence to support the importance of adolescent nutrition and birth outcomes. There is the need to implement policies to improve adolescent nutrition through a multisectoral approach.
Effect of Animal-Assisted Activities on Symptoms and Emotions of Children with Neoplastic Disease: A Systematic Review with Meta-Analysis
Authors: Re Luca Giuseppe , Porcarelli Silvia , Ripari Camilla , Marotta Sara
Published: August 2024

BACKGROUND: Animal-assisted activities (AAAs) have long been present in pediatric oncology as a nonpharmacological intervention aimed at helping children cope with symptoms and negative emotions during hospitalization and antineoplastic treatment. Among the systematic reviews in the literature, there is a lack of one with meta-analysis that includes only RCTs centered on the effect of the intervention on symptoms and emotions in children with neoplastic disease.

OBJECTIVE: To synthesize the effect of AAAs on symptoms and emotions of children with neoplastic disease.

METHODS: Studies were searched from biomedical databases, trial registries, and web resources. The risk of bias of included studies was assessed with RoB 2, and the overall effect size of the intervention was calculated by creating random-effects meta-analyses graphically represented by forest plots. The summary of findings was illustrated with a table in accordance with the GRADE method.

RESULTS: Three parallel-group randomized controlled trials with low risk of bias were included (N = 151, mean age: 8.5-11.2 years). AAAs are promising for anxiety reduction (N = 134; SMD = -0.07 [95% CI: -0.40, 0.27], p > 0.05) and quality of life improvement (N = 84; SMD = -0.11 [95% CI: -0.53, 0.31], p > 0.05) in children and for anxiety reduction (N = 154; SMD = -0.50 [95% CI: -1.52, 0.52], p > 0.05) in parents/caregivers. The certainty/quality of evidence is low to very low.

CONCLUSIONS: The effect of animal-assisted activities to reduce anxiety and improve the quality of life of children with neoplastic disease and to reduce the anxiety of parents/caregivers is promising. However, more studies need to be conducted on the topic that overcome the important methodological limitations manifested by current research in order to collect more data in favor of implementing the intervention in pediatric oncology.
ОСОБЛИВОСТІ ФОРМУВАННЯ ТА РЕАЛІЗАЦІЇ КУРСІВ ФІЗИКИ БАЗОВОГО ТА ПРОФІЛЬНОГО РІВНІВ НОВОЇ УКРАЇНСЬКОЇ ШКОЛИ
Authors: Головко Микола
Published: August 2024

У статті актуалізовано проблему формування цілісного курсу фізики Нової української школи. Узагальнено концептуальні підходи щодо структури та змісту навчання фізики на базовому рівні, особливостей та моделей його реалізації в освітній практиці, розроблення сучасного підручника фізики для гімназії, що реалізує вимоги Державного стандарту базової середньої освіти та розроблених на його основі модельних навчальних програм, запровадження яких розпочинається у 2024‒2025 навчальному році.
Проаналізовано зарубіжний досвід функціонування профільної школи та особливості реалізації на рівні профільної освіти фізичного складника природничої освітньої галузі. Акцентовано увагу на необхідності дидактико-методичного обґрунтування процедур формування профілів навчання, змісту та обсягів компонентів, зокрема й фізичної, модулів профільної та загальноосвітньої підготовки.
Окреслено підходи щодо конкретизації ключових змістових ліній фізичного складника поглибленого та базового рівнів профільного навчання та особливостей реалізації їх дидактичного забезпечення, а також обов’язкових результатів навчання фізики та орієнтирів їх оцінювання.  
Визначено перспективи формування курсу фізики профільного рівня повної загальної середньої освіти як другого концентру, що у взаємозв’язку з базовим курсом утворюють спірально-концентричну систему шкільної фізичної освіти, її переваги та труднощі практичного втілення.
ОСВІТНІ РЕФОРМИ У ДЗЕРКАЛІ ЗОВНІШНЬОГО НЕЗАЛЕЖНОГО ОЦІНЮВАННЯ
Authors: Жук Юрій , Науменко Світлана
Published: August 2024

У статті розглянуто проблему аналізу ефективності управлінських, методичних та економічних втручань у систему освіти, які спрямовані на покращення академічних результатів учнів на популяційному рівні, як одного з важливих завдань педагогічної науки. У дослідженні автори виходили з того, що зовнішнє незалежне оцінювання (ЗНО), яке можна розглядати як об’єктивний показник рівня академічної успішності випускників закладів загальної середньої освіти (ЗЗСО), дає можливість охарактеризувати стан системи освіти в Україні на момент сесії ЗНО.
На основі аналізу офіційних звітів зовнішнього незалежного оцінювання, які опубліковані у відкритому доступі, зроблено спробу з’ясувати вплив загальної результативності заходів, реалізованих у системі освіти України, на рівень навчальних досягнень випускників ЗЗСО за період 2009–2021 рр. Для аналізу обрано навчальні предмети, іспити з яких випускники складали на всіх сесіях ЗНО у цей проміжок часу, і результати оцінювання з яких містяться в офіційних звітах Українського центру оцінювання якості освіти (УЦОЯО). Низку сесій ЗНО розглянуто як ряд рандомізованих неконтрольованих квазіекспериментів національного масштабу, які спрямовані на вимірювання певного параметра – рівня академічної успішності випускників ЗЗСО. Результатом зазначеного квазіексперименту є дані, що отримані в результаті проведення певної кількості сесій ЗНО. Методами математичної статистики на основі отриманих даних проведено аналіз результативності впливу заходів, які здійснювалися в системі освіти (освітніх втручань) упродовж тривалого часу, на рівень академічної успішності випускників ЗЗСО.
У статті зроблено висновок, що у визначений період в цілому підвищилася успішність виконання випускниками ЗЗСО як окремих предметних тестів, так і середня успішність за результатами ЗНО. Висунуто гіпотезу, що одним з основних чинників такого підвищення стала позитивна поведінкова реакція соціуму на впровадження ЗНО, яке є складовою множини освітніх реформ в Україні.
СТАНДАРТИЗАЦІЯ ПРОФЕСІЙНОЇ ДІЯЛЬНОСТІ ДИРЕКТОРА СЕРЕДНЬОЇ ШКОЛИ ЯК МЕХАНІЗМ УПРАВЛІННЯ ЯКІСТЮ ОСВІТИ: ЗАРУБІЖНІ ПІДХОДИ
Authors: Лукіна Тетяна
Published: August 2024

Статтю присвячено порівняльному аналізу концептуальних підходів, змісту та структури зарубіжних і вітчизняного стандартів професійної діяльності керівника закладу середньої освіти. Обґрунтовано тезу про те, що професійний стандарт керівника школи виступає своєрідним засобом гарантування проголошеної якості освіти та важливим інструментом механізму управління якістю освіти. З’ясовано, що ключовими моментами, на яких ґрунтується розмаїття означених стандартів та особливості їх використання є: мета і сфера застосування, зміст і статус стандарту. Акцентовано увагу на тому, що професійні стандарти керівника мають різний статус та можуть бути використані з різною метою, зокрема для вирішення адміністративних завдань (окреслення посадових функцій, формування відповідних посадових інструкцій та змісту трудової угоди); визначення кола професійних компетенцій при формуванні цільових освітніх програм підготовки майбутніх менеджерів;  проведення професійного відбору; оцінюванні результатів професійної діяльності; атестації, ліцензуванні та сертифікації директорів шкіл. Доведено, що основоположним принципом, що лежіть в основі сучасних зарубіжних підходів до розробки змістових ліній стандартів ефективності директора школи, є лідерство. Виявлено та схарактеризовано  схожі та відмінні риси вітчизняного та зарубіжних підходів до побудови професійних стандартів керівника середньої школи.