bluuebunny/crossref_metadata_2025 huggingface dataset:
Serum Levels of Growth Differentiation Factor 15 as a Biomarker for Chronic Kidney Disease in Patients with Type 2 Diabetes Mellitus
Authors: Indarwati Uli Mas’uliyah , Wardhani Puspa , Muhamad Robi’ul Fuadi , Soelistijo Soebagijo Adi
Published: April 2024

Background: Growth Differentiation Factor 15 (GDF-15) has been identified as a biomarker of cellular stress conditions and has demonstrated functional implications in kidney disease, metabolic disorders, and diabetes. However, the relationship between GDF-15 and the coexistence of type 2 diabetes mellitus (T2DM) and chronic kidney disease (CKD) remains unclear. This study aims to investigate the association between GDF-15 levels and the presence of CKD in patients with T2DM, then analyze the cut off value. Method: A cross-sectional study was conducted, enrolling a total of 60 patients. T2DM patients were categorized into two groups based on the presence or absence of CKD. Serum GDF-15 levels were quantified using an enzyme-linked immunosorbent assay (ELISA) kit. Results: The study population (n=60) predominantly consisted of male individuals with an average age of 53 years. The receiver operating characteristic (ROC) curve analysis yielded an area under the curve (AUC) of 0.846 (95% CI = 0.748 – 0.945) with a statistically significant p-value of < 0.001. The optimal cut-off value for serum GDF-15 to detect the presence of CKD was determined as 362.80 pg/mL, with corresponding sensitivity and specificity values of 77% and 79%, respectively. Furthermore, a significant association between GDF-15 levels and both T2DM without CKD and T2DM with CKD was observed (p < 0.001). Conclusion: There is a significant association observed between serum GDF-15 levels in patients with type 2 diabetes mellitus (DM) and the presence of CKD. The cut of value GDF-15 to detect the presence of CKD was determined as 362.80 pg/mL with sensitivity and specificity values of 77% and 79%, this is can be considered as a potential biomarker for the detection of CKD in individuals with T2DM.
Clinical Management practice and Therapeutic Outcomes of Chronic Liver Disease patients in the Conflicted area of North Ethiopia
Authors: Shewatetak Hawaz , Yarlagadda Raghavendra , Silakabattini Kotaiah , Tatiparthi Ramanji Reddy , Jallepalli Venkateswara Rao
Published: April 2024

Background: In the 21st century, low- and middle income, war prone and drought-prone areas in developing nations have seen a fast rise in the prevalence of chronic liver disease (CLD). An estimated 240 million people worldwide are infected with HIV, and 780,000 deaths are attributed to it each year, according to the World Health Organization (WHO). Objective: We want to assess the efficacy of in-hospital care for CLD patients by verifying and evaluating current management practices. Method: A retrospective descriptive study of patients with chronic liver disease who were followed up on at Debre Berhan Hospital between July 2018 and January 2021 was conducted. Results: Out of a total of 209 patients tested, 127 (or 60.74%) were males aged 41.44±12.89 of years. Ascites complications were presented in over 44% of cases. Using the laboratory data, 65 patients (31.10%) and 71 patients (33.97%) were found to have abnormally high AST and ALT values on LFTs testing. AUROC analysis was carried out with a 95% CI for Child-Pugh of 0.61 (0.53-0.75, P=0.14), MELD 0.75 (0.63-0.72, P=0.26), and ALBI 0.53 (0.31-0.54, P=0.29). Conclusion: Based on the predictive data, 87 (41.63%) patients were successfully treated and released, whereas 57(27.27%) were recommended for further care, and 47 died due to co-morbid conditions. Although, the study period coincides with the COVID-19 pandemic, more analysis of the obtained data is necessary.
Secure Pixel-Level Data Concealment: A Novel Approach for Securing Black and White Images within Color Images
Authors: Sriharipriya K. C.
Published: April 2024

In the era of rampant digital data transfer, concerns regarding the secure and reliable transmission of information persist, with numerous attempts at concealing and transporting data globally. Despite the plethora of existing techniques, issues persist, ranging from misinterpretation to malicious misuse of data during the transfer process. To address some of these challenges, this research introduces an innovative method centered on the modification of pixel data to embed concealed information. The primary objective is to alter pixel values in a manner that accommodates the storage of data pertaining specifically to black and white image pixel data. The proposed technique is designed to exclusively encode information related to two-pixel values, with careful adjustments made to ensure the masked image remains non-deceptive. Pixel values undergo subtle alterations to mitigate susceptibility issues associated with corner values, particularly at the border values of 254 and 255 for RGB values. The developed method presents a simplified yet robust data hiding technique, allowing the storage of black and white images within color images while achieving a high Peak Signal-to-Noise Ratio (PSNR) compared to standard ".png" images. Crucially, the developed approach addresses the challenge of minimizing drastic changes in pixel color, enhancing the overall fidelity of the stego image. Furthermore, the versatility of the proposed method is showcased by its potential to accommodate more than three images when the stego image size is appropriately large and segmented. A practical and efficient solution has been contributed to the persistent issues associated with secure data transfer, presenting a novel methodology for concealing black and white images within color images.
Analyzing Existing Algorithms and Identifying Gaps in Brain Stroke Detection
Authors: Rohini B. Jadhav
Published: April 2024

One of the global issues that matters most right now is healthcare. The primary cause of death globally is brain stroke. A valuable contribution to medicine is the early prediction and identification of brain stroke events. Numerous factors, including BMI (body mass index), age, sex, family history, gender, smoking status, hypertension, and so on, are linked to brain stroke deaths. While forecasting heart illness has received a great deal of interest in the medical community, predicting a brain stroke has received less attention. This study's primary goal is to evaluate various previously published research publications and select the most effective machine learning methods for brain stroke prediction for our next projects. It was shown that mortality rate and functional outcomes are the expected outcomes for the majority of the study work done after analyzing the various machine learning techniques used for stroke predictions and after accounting for the previously published studies. The techniques that were used most commonly were LR, DTC, RFC, SVM, KNN.
Machine Learning Approaches of Lung Cancer Image Processing for Detecting and Identifying Various Stages of Analysis
Authors: A. Harshavardhan
Published: April 2024

The current paper is aimed at examining the use of machine learning approaches for lung cancer detection and classification using medical imaging data. In order to create the model, we collected a comprehensive dataset of 2400 images of lung cancer at different stages and healthy pictures. These data were preprocessed, and several approaches to the feature extraction were considered, namely Histogram of Oriented Gradients , and Local Binary Patterns . In addition, we attempted to use deep learning representations to determine their usefulness in this case. Moreover, these features were used for four ML models, namely Convolutional Neural Network , ResNet-18, , and VGG-19, to determine the most suitable one. To evaluate the general performance of these models, all the characteristic points were taken into account, such as the precision, recall, F1 score, accuracy, and confusion matrices. The results of the primary analysis indicate that the accuracy of our proposed model was the highest, 96.86%. The other places were taken by other deep learning architectures, which also demonstrate high level performance. In general, we may conclude that the findings show it is possible to use ML algorithms to improve the quality of clinical decisions and make the process of lung cancer detection and classification more accurate. At the same time, we were able to provide a comprehensive evaluation of all these results and the thorough analysis of the general performance of each model. This may serve as the basis for the subsequent improvements and changes that would allow enhancing the general quality of diagnostics and training more advanced models.
Machine learning-Based Energy Efficient and Enhancing Communication Reliability for MANETs of Balanced Less Loss Routing Protocol
Authors: Mohammad Arif
Published: April 2024

The aim of the presented research was the utilization of machine learning methods, for example, SOM, MARL, and DQN, to promote the increase of energy efficiency and communication reliability in MANET. For the purpose of the research conduction, 10 trials of the experiment were carried out with the view to establish the performance of the proposed approaches from various perspectives. DQN demonstrated superior performance throughout all experiment trials as compared to both SOM and MARL. The model recorded an average energy efficiency of 95%, indicating that it was highly successful in optimizing routing strategies and communication policies. Furthermore, the average packet delivery ratio was shown to be 96%, meaning that DQN provided guarantees of timely and reliable data exchange across the MANET infrastructure. Finally, the average delay was determined to be from 4 ms to 9 ms, evidencing the quick delivery of packets with little temporal latency. The results obtained demonstrate that DQN is able to alleviate the challenges associated with the energy efficiency and communication reliability of MANETs. Notably, deep reinforcement learning with DQN appears to offer viable solutions for more energy-efficient routing, minimized energy consumption in these networks, and improvement to their communication reliability. Thus, the study under consideration has contributed to the development of the existing knowledge as it has expanded the existing understanding of the fact that machine learning, in general, and DQN, in particular, can be utilized to optimize the operation of MANETs.
A novel Conceptualization of AI Literacy and Empowering Employee Experience at Digital Workplace Using Generative AI and Augmented Analytics: A Survey
Authors: Amit Dubey , Sanjeev Kumar Sharma , Saurabh Karsoliya Prashant Chandra
Published: April 2024

With the fast, rapid, and expeditious integration of Artificial Intelligence (AI) technologies, particularly Generative AI and Augmented Analytics, organizations are presented with new opportunities to transform their operations and empower their workforce. This paper explores the intersection of AI literacy, Generative AI, and Augmented Analytics to propose strategies for fostering a culture of AI fluency among employees.  This paper reviews the literature on AI literacy and its potential implications for employee experience (Ex) in digital workplaces. AI literacy and competency is the ability to understand, interact with, and thoughtfully assess the applications and ramifications of artificial intelligence (AI) across diverse domains. The paper argues that AI literacy is a key competence for employees in the digital era, as it enables them to leverage the potential of generative AI and augmented analytics, two of the most promising technologies for enhancing Ex. Generative AI refers to the use of AI to create novel and diverse outputs, such as text, images, music, or designs, while augmented analytics drives potential capability to make use of Artificial Intelligence technologies to automate and augment data analysis and decision-making. The paper discusses how these technologies can empower employees to be more creative, productive, collaborative, and engaged in their work and the challenges and risks they pose. This paper additionally highlights the obstacles, deficiencies, and proposed pathways for further research advancement concerning AI technological competency and literacy, aiming to enhance the employee experience significantly in digital workplaces.
GIS Constructed Water Monitoring Network System Via IOT
Authors: L Priyanka ,K Saritha ,S Deepika ,R Suma P Kishor Kumar
Published: April 2024

Monitoring the quality of water plays a vital role in the advancement towards intelligent and smart agriculture. It also facilitates the seamless transition to automated monitoring of essential components of human daily needs, as new technologies continue to be developed and adopted in both agricultural and human daily life, particularly in relation to water. Assessing water stress requires accurate measurement of water usage [1]. The objective of this study is to optimize the distribution strategy and achieve more efficient and rapid distribution, while also making better use of technology to address the urgent need for water conservation. One of the criteria for the second filtering phase, which utilized a realtime data collection system, focused on the implementation of water quality monitoring and characterization methods. Water measurement sensors and the Internet of Things (IoT) can provide immediate information on water flow and pressure rates. This information is crucial for the analysis and surveillance of water [2]. At the RCEW campus, online smart water monitoring is imperative to ensure a more efficient and sustainable use of water. By combining the Internet of Things and geographic information systems (GIS), an online smart water monitoring prototype was developed specifically for RCEW [3]. This cutting-edge technology has proven to be highly successful in providing real-time information on water parameters, saving both time and money, while enabling the continuous study of water consumption patterns. This innovative technology seamlessly integrates IoT and GIS for effective water surveillance [4,5].
A Study on Identifying and Addressing the Gaps in Academia and Industry Demands with reference to selective Higher Education Institutions in Telangana State
Authors: K. Narendra Kumar , Rakesh Kumar Patra D. Sudheer Reddy
Published: April 2024

The industry and Academic institutions are expected to go hand in hand to accelerate the growth of any nation. But unfortunately, there is something that resists the equilibrium of skills needed for the industry and academic excellence. This study is a small attempt of  highlights the essential need to recognize and evaluate gaps among the assortment of abilities needed in evolving job environments and the soft abilities and technical abilities obtained by students at colleges and universities. The basic objective is to ensure that educational institutions maintain contemporary with market developments, developments in technology, and appropriate requirements, with a final objective of educating graduates for profitable and significant employment. This objective can be accomplished through employing an integrated technique which involves interviews, questionnaires, and statistical analysis in order to conduct a comprehensive review of present shortcomings regarding both soft as well as technical skills. Discussions with stakeholders, including corporate executives, instructors, and former students, offer vital insight into the ever-evolving requirements of the employment marketplace. Experts anticipate that by completing this investigation, researchers will be able to shed light on components of the educational curriculum that are currently outdated date or fall short of the requirements of industry.
Integrating machine learning techniques with IoT sensors and connected vehicles to enable real-time traffic monitoring and Adaptive signal control systems
Authors: P. Swathika B. Vinothkumar
Published: April 2024

This research investigates machine learning algorithms to traffic monitoring and adaptive signal control coordinated in the context of the Internet of things sensors and connected vehicles for real-time traffic supervision. It measures the efficiency of machine learning algorithms, simulates adaptive control strategies for signal systems, and addresses the challenges of deploying signal system changes. The performance metrics suggest better traffic flow, leading to a decrease in traffic congestion. Further study should be made towards parametrization of algorithms, improvement of communication standards and training of integration models.
Efficient Training of Colorectal Cancer Diagnosis Model through Unsupervised Learning Composite Network
Authors: Deepak T. Mane Pradeep Kundlik Deshmukh
Published: April 2024

The use of machine learning algorithms for precise and effective colorectal cancer diagnosis has gained popularity as a result of advancements in medical imaging. Through the use of an Unsupervised Learning Composite Network (ULCN) model this study suggests a novel method for training a diagnosis model. Conventional training techniques for these models frequently rely on sizable labelled datasets, which can be labour and resource-intensive to create. The ULCN, on the other hand, incorporates unsupervised learning into the training process, decreasing the need on labelled input. In order to address this issue, our study offers a revolutionary method known as the DL-Kmeans (Deep Learning with Unsupervised K-Means Clustering), which combines the effectiveness of the unsupervised K-means clustering algorithm with the power of deep learning. When compared to manual screening and annotation techniques, the DL-Kmeans ability to more quickly refine medical images serves as evidence of its effectiveness. The use of DL- Kmeans processed photos resulted in a two-fold acceleration in the training process for deep learning models used to diagnose colorectal cancer, which is very notable. Notably, this speeding up did not degrade performance quality; the DL- Kmeans enhanced method showed superior results in terms of training loss and accuracy attained. DL- Kmeans importance goes beyond only improving images. It is a useful tool for handling the growing volume of medical photos, which will help with the later creation of artificial intelligence models.
Efficient and Secure Blockchain-Based Access Control for Fog-Assisted IoT Cloud in Electronic Medical Records Sharing
Authors: Nidhi Ranjan
Published: April 2024

Fog-assisted IoT Cloud environments have emerged as a result of the rapid spread of Internet of Things (IoT) devices and the requirement for seamless data sharing in the healthcare industry. The effective and safe management of access control to sensitive data, such as Electronic Medical Records (EMRs), becomes crucial in such configurations. The Efficient and Secure Blockchain-Based Access Control (ESBAC) framework, designed specifically for Fog-assisted IoT Cloud scenarios in EMR sharing, is our creative approach to this problem. The ESBAC architecture makes use of the blockchain's openness and immutability to provide reliable access control and auditability. The implementation of a consortium blockchain includes participants including healthcare providers, patients, and authorised entities. Each EMR has a smart contract attached to it that specifies access restrictions and permissions to make sure that only authorised parties are able to access and edit the data. Because of the decentralisation provided by the blockchain, security and privacy are improved because no single party has overwhelming control. Proposed framework uses attribute-based access control and lightweight encryption methods to provide a fair trade-off between security and efficiency. As a result, there can be fine-grained access control policies with the least amount of computing overhead. Comprehensive simulations are used to evaluate the suggested solution and compare it to current methods. The outcomes show that ESBAC improves security in EMR sharing and greatly lowers access latency.
A Metaphor Analysis on Vehicle License Plate Detection using Yolo-NAS and Yolov8
Authors: Deepak Mane
Published: April 2024

There have been significant advancements in object detection in recent years, notably with the emergence of the YOLO approach. In this paper, we proposed a thorough comparison between YOLO-NAS and YOLOv8 specifically for detecting vehicle license plates based on the analysis of experimental results. Real-time vehicle license plate detection can have a wide range of applications like crime prevention, surveillance, traffic-pattern analysis, automated toll collection, etc. Our evaluation uses a diverse dataset capturing vehicle images from various angles and levels of occlusion to ensure a comprehensive assessment of the models' capabilities. The metrics considered include precision, recall, and mAP, offering insights into detection accuracy and false positive rates. The results reveal nuanced performance differences between YOLO-NAS and YOLOv8 in vehicle license plate detection tasks. YOLO-NAS demonstrates superior accuracy in specific scenarios due to its optimized architecture. Conversely, YOLOv8 shows notable efficiency gains, especially regarding inference speed, making it a compelling choice for real-time applications. Here, we contribute valuable insights to the ongoing discussion on object detection methodologies, assisting practitioners in making informed decisions when selecting a model for vehicle license plate detection applications. The findings underscore the importance of considering trade-offs between accuracy and computational efficiency in specific use cases
Navigating Industry 4.0 Frontiers: A Scalable and Resilient Next-Generation IoT Framework to Implement Future Advancements in Smart and Adaptive Industrial Systems
Authors: Bireshwar Ganguly,
Published: April 2024

The emergence of Industry 4.0 signifies a paradigm shift in industrial systems, characterized by the amalgamation of digital technologies with tangible operations. The goal of this study is to present a state-of-the-art, scalable, and robust Internet of Things (IoT) framework that will enable future innovations in intelligent and adaptable industrial systems to be seamlessly integrated. Our framework gives scalability first priority in response to Industry 4.0's dynamic nature, which is marked by fast technical evolution and rising connection in order to handle the expanding ecosystem of networked devices. The suggested structure places a strong emphasis on resilience and is designed to resist setbacks and guarantee the continuation of vital industrial processes. Our framework improves industrial systems' intelligence by utilizing edge computing, machine learning techniques, and improved communication protocols. This allows the systems to self-adapt to changing situations. Moreover, it adopts a modular architecture that facilitates interoperability and makes it simple to integrate various devices and technologies. Our IoT framework creates a solid, flexible, and future-proof industrial environment with this all-encompassing strategy, enabling businesses to confidently and effectively traverse Industry 4.0's frontiers.
Machine Learning Techniques to Predict Rainfall of Vidarbh Region
Authors: Jayshri Shinde Nirmal Mungale  ,
Published: April 2024

Accurate daily rainfall forecasting is vital for proper agricultural planning and managing resources efficiently. This study evaluates the performance of various methods, with an emphasis on temperature and precipitation, such as linear regression, random forest, SVM regression, and XGBoost. Linear regression displays minimal RMSE and a flawless R-squared, whereas random forest performs effectively with low RMSE and encouraging R2 results. However, the presence of a negative R-squared indicates potential overfitting. The MAE, MSE, and RMSE statistics for SVM are competitive. The study draws attention to the unexplored Vidarbha region, which includes 11 districts, using Nagpur district as a representative instance. Additionally, future plans involve the utilization of deep learning models like ARIMA and LSTM to enhance rainfall prediction accuracy across Vidarbha. This investigation yields valuable insights into climate prediction, offering support for well-informed decision-making.
Presenting the Model of Acceptance and Use of Insurance Technologies Using the ISM-DEMATEL Method
Authors: Morteza Honarmand Azimi, Mohammad Pasban Mehdi Haddad Oskouee, Samad Aali,
Published: April 2024

This research sought to study and examine the model of acceptance and use of insurance technologies using the ISM-DEMATEL method. According to the purpose and nature of this research, in terms of method, it was a qualitative research that was conducted by interviewing research experts. The statistical population was university professors in the field of insurance and senior managers of insurance companies, beneficiaries and policyholders. In this section, sampling was done theoretically. In theoretical sampling, events are sampled, not necessarily individuals. If people are also referred to, the main and key goal is to explore events. The interviews continued until theoretical saturation was ensured. In this study, saturation happened with 12 experts (university professors in the field of insurance and senior managers of insurance companies, beneficiaries and policy holders). The results showed that based on the research findings, it can be seen that the first level includes practical factors, knowledge management, infrastructure, behavioral factors, the second level includes managerial factors, and the third level includes technology perception. Based on the findings, it can be seen that practical factors, knowledge management, infrastructure, behavioral factors are connected factors, managerial factors are autonomous factors, and technology perception is an influencing factor.
DOI: https://doi.org/10.52783/pst.273
Structural Equation Modeling of the Impact of Intellectual Capital on the Organizational Performance of Sports Federations.
Authors: Victoria Zaborova,
Published: April 2024

The present study seeks to conduct a Structural equation modeling to examine the impact of intellectual capital on the organizational performance of sports federations. The method is correlational and survey. The population consists of all sports federations. A sample of 242 individuals were selected by Morgan's table and the random sampling method. The research utilizes Bontis' (2007) intellectual capital questionnaire and Yang's (2004) organizational performance questionnaire as measurement tools. The surveys' validity was verified by 8 professors specializing in sports management. The reliability of the research questionnaires was assessed using Cronbach's alpha coefficient, yielding values of 0.83 and 0.91 for the relevant questionnaires. The data analysis employed Pearson's correlation test and structural equation modelling. The GFI index of 0.95, AGFI index of 0.96, NFI index of 0.97, CFI index of 0.95, and RMSEA index of 0.031 all suggested that the structural modelling fit. The findings indicated that intellectual capital, as evidenced by a beta coefficient of 0.63, was a reliable predictor of organizational performance. The overall findings indicate that the augmentation of intellectual capital and its various components within the firm resulted in improved employee performance.
DOI: https://doi.org/10.52783/pst.283
Dynamic Modeling of a Concentrating Solar Thermal Plant With a Packed Bed Energy Storage
Authors: Jin Eric , Oles Andrew , Harding Kathryn , Thomas Nate
Published: April 2024

The Air-packed bed system is a cost-competitive concentrating solar thermal system that employs air as the heat transfer fluid and a solid packed bed as the thermal energy storage medium. The thermocline behavior of the packed bed plays an important role in the performance and operation of the system, so a dynamic model of the TES is needed to evaluate the design and performance of the system. A high-fidelity first-principle TES model is often too computationally expensive to incorporate into a larger system model for simulation and optimization at an annual time scale. Here, we develop in Modelica a system model for a CST concept plant with a reduced order TES model to ensure the necessary thermocline fidelity while maintaining suitable computational performance. The validity of the reduced order model is quantified both against simulation results from a first-principle finite-difference model and against real-world test data taken at the Heliogen Test Facility in Lancaster, CA. The thermocline fidelity and computational performance of the system model are then demonstrated with an annual simulation run of the concept air-packed bed plant.
FENOMENOLOGI ISLAM UNTUK PENELITIAN AKUNTANSI
Authors: Niswatin Niswatin
Published: April 2024

Buku ini menawarkan sebuah paradigma, meto-dologi, dan metode penelitian yang dapat digunakan dalam penelitian kualitatif, khususnya untuk bidang akuntansi Islam. Pada bagian awal buku ini menguraikan bagaimana diskusi tentang paradigma Islam dijadikan pondasi dalam mengembangkan metodologi penelitian yang sekuler. Berikutnya menguraikan fenomenologi Islam sebagai metodologi penelitian sekaligus sebagai metode yang dapat digunakan oleh peneliti, khususnya bagi peneliti bidang akuntansi.
AKUNTANSI GORONTALO: LANGGA SEBAGAI PEMBENTUK KARAKTER AKUNTANSI
Authors: Rismawati Rismawati
Published: April 2024

da sesuatu yang memiliki nilai lebih besar dibandingkan dengan pengeluaran yang dilakukan. Nilai lebih tersebut penting untuk diungkap dengan melakukan penelusuran kepada para informan yang tepat, apa makna biaya pada pembuatan lantang pangngan dalam budaya Rambu Solo' bagi mereka, sehingga bagi masyarakat Tallung Penanian dan Pata'padang, ada hal lebih yang besar dan bernilai diperoleh dari perayaan tersebut, jika dibandingkan dengan pengeluaran biaya yang dilakukan. Banyak penelitian bersifat interdisipliner, mencakup bidang seperti psikologi, sosiologi, antropologi, dan tentu saja akuntansi. Ini menunjukkan adanya kebutuhan dan keinginan untuk menggali lebih dalam hubungan antara spiritualitas dan ilmu sosial, memahami bagaimana keduanya dapat saling melengkapi untuk membentuk pemahaman yang lebih holistik dan inklusif tentang dunia kita. Dua alinea di atas merupakan kutipan dari sebagian narasi bernas yang disajikan oleh para penulis buku ini. Mereka mencoba memberikan makna yang lebih mendalam terhadap budaya Langga yang lahir di ranah Gorontalo untuk menjadi lebih dari sekedar bingkai, akan tetapi mampu memberikan warna bagi terbentuknya karakter akuntansi yang lebih "Gorontalo".
MANIFESTASI FOLKLOR DEWI PADI: Simbol Kearifan Lokal tentang Keberlanjutan Pangan
Authors: Wulansary Wulansary
Published: April 2024

Isu tentang ancaman krisis pangan dan krisis identitas budaya di Indonesia menjadi hal yang makin memompa semangat penulis untuk mengerahkan seluruh energi. Buku ini menawarkan wacana yang bisa dipertimbangkan sebagai jawaban dari kedua krisis yang vital tersebut, meskipun cukup kom-pleks dan meramunya dalam sebuah analisa yang lebih mudah dipahami. Buku ini menyandingkan antara pengetahuan tradisional, di mana salah satunya menyangkut astronomi, dengan
Mortality rate after total knee arthroplasty or total hip arthroplasty in patients with a history of liver transplant
Authors: Rodriguez-Merchan E Carlos
Published: April 2024

In this editorial I comment on the article by Ahmed et al published in a recent issue of the World J Orthop 2023; 14: 784-790. It is well known that patients who have undergone a liver transplant (LT) may need to have a total hip arthroplasty (THA) or total knee arthroplasty (TKA) implanted. Ahmed et al stated that the mortality rate in these patients was similar to the one of the general population. However, there are three articles previously published that found higher mortality in LT patients who experienced THA/TKA than in the general population (individuals without LT). Therefore, in this Editorial I would like to point out that there is controversy in the literature regarding whether LT patients undergoing THA/TKA have higher mortality than the general population. Therefore, future research should attempt to resolve this controversy.
Expandable endoprostheses in skeletally immature patients: Where we are
Authors: Öztürk Recep
Published: April 2024

Approximately 45 percent of malignant bone tumors are seen under the age of 16 and one of the important results of growth plate sacrification in patients with immature skeletons is limb inequality. Until the early 1990s, the treatment options for these patients were rotationplasty or amputation. Multimodal approaches that combine imaging, chemotherapy, and surgical techniques have enabled the development of limb-preserving methods with satisfactory results. In order to overcome inequality problems, expandable prostheses have been developed in the 1980s. Extendable endoprosthesis replacements have been improved over the years and are now an established and safe alternative. Noninvasive prostheses appear to be advantageous compared to minimally invasive expandable prostheses that require multiple surgical procedures, but the complication rate remains high. Therefore, although expandable prostheses are not the definitive answer to the treatment of bone sarcomas in skeletally immature children, they are still a suitable interim choice until full adulthood is achieved. Due to reported high complication rates, the procedures require significant experience and are recommended for use only in specialized cancer centers.
Effect of weight-adjusted antimicrobial antibiotic prophylaxis on postoperative dosage and surgical site infection incidence in total joint arthroplasty
Authors: Gupta Ashim , Jain Vijay Kumar
Published: April 2024

Surgical site infections (SSI) following total joint arthroplasty pose a significant concern for both providers and patients across the globe. Currently, administration of antimicrobial antibiotic prophylaxis is used throughout the world to reduce the incidence of SSI. However, the correct dosage and frequency of administration remains debatable. In this editorial, we emphasized the determination of the effect of administration of weight-adjusted antimicrobial antibiotic prophylaxis regime on the incidence of SSI and postoperative dosage reduction compared to the conventionally used regime during total joint arthroplasty. The results demonstrated similar efficacy between both regimes with respect to the incidence of SSI. In addition, weight-adjustment led to reduced postoperative dosage and has the potential to reduce chances of achieving lower therapeutic concentration, drug resistance, drug toxicity, and costs.
Exercise promotes osteogenic differentiation by activating the long non-coding RNA H19/microRNA-149 axis
Authors: Zhou Xu-Chang , Wang Dong-Xue , Zhang Chun-Yu , Yang Ya-Jing , Zhao Ruo-Bing , Liu Sheng-Yao , Ni Guo-Xin
Published: April 2024

BACKGROUND

Regular physical activity during childhood and adolescence is beneficial to bone development, as evidenced by the ability to increase bone density and peak bone mass by promoting bone formation.

AIM

To investigate the effects of exercise on bone formation in growing mice and to investigate the underlying mechanisms.

METHODS

20 growing mice were randomly divided into two groups: Con group (control group, n = 10) and Ex group (treadmill exercise group, n = 10). Hematoxylin-eosin staining, immunohistochemistry, and micro-CT scanning were used to assess the bone formation-related indexes of the mouse femur. Bioinformatics analysis was used to find potential miRNAs targets of long non-coding RNA H19 (lncRNA H19). RT-qPCR and Western Blot were used to confirm potential miRNA target genes of lncRNA H19 and the role of lncRNA H19 in promoting osteogenic differentiation.

RESULTS

Compared with the Con group, the expression of bone morphogenetic protein 2 was also significantly increased. The micro-CT results showed that 8 wk moderate-intensity treadmill exercise significantly increased bone mineral density, bone volume fraction, and the number of trabeculae, and decreased trabecular segregation in the femur of mice. Inhibition of lncRNA H19 significantly upregulated the expression of miR-149 and suppressed the expression of markers of osteogenic differentiation. In addition, knockdown of lncRNA H19 significantly downregulated the expression of autophagy markers, which is consistent with the results of autophagy-related protein changes detected in mouse femurs by immunofluorescence.

CONCLUSION

Appropriate treadmill exercise can effectively stimulate bone formation and promote the increase of bone density and bone volume in growing mice, thus enhancing the peak bone mass of mice. The lncRNA H19/miR-149 axis plays an important regulatory role in osteogenic differentiation.
Different Assessment Methods in a Civil Engineering Course
Authors: Hellum Vidar
Published: April 2024

Due to the outbreak of Covid-19, there has been a need for exploring different assessment methods and approaches to teaching. The purpose of the present paper is to share the experiences and discuss three different assessment methods that have been used in the same university course within civil engineering studies over the last three years. The three assessment methods which have been explored are (i) a conventional four-hour unseen exam with calculation tasks performed at the campus, (ii) a 24-hour home exam with calculation tasks and (iii) a portfolio-based assessment with an additional oral exam.

The choice of assessment method clearly influenced the grades where the portfolio-based assessment with the additional oral exam produced more than a grade higher average than the two other assessment methods. Interestingly, there were no indications of gender differences between the assessment methods. Females and males achieved similar average grades in all the introduced modes of assessments.

Based on comparisons between the portfolio results and the following oral exam there are indications that the improved grades were not only a function of an “easier assessment method” but might also be because of better performance which may partly be induced by the mode of assessment.
Modernização, desenvolvimento e dependência nas relações Brasil-Estados Unidos durante a Guerra Fria:
Authors: Carvalho Oliveira Pedro
Published: April 2024

este artigo examina a Aliança para o Progresso como ponte para relações paternalistas e de dependência entre os Estados Unidos e o Brasil. Sob o véu da promessa de desenvolvimento e modernização, o programa preconizava o reforço ao vínculo entre o modelo capitalista liberal estadunidense em franca expansão e as economias dos países latino-americanos. Nosso exame foca na atuação do programa no Nordeste brasileiro, região onde um bloco político relativamente coeso e conservador intencionou fortalecer a dependência do Brasil como mecanismo para a manter suas estruturas de poder.
historiografia sobre a Guerra Fria:
Authors: Alves Combat Flávio
Published: April 2024

O objetivo do artigo é analisar criticamente as contribuições centrais do historiador pós-revisionista John Lewis Gaddis ao debate historiográfico sobre a Guerra Fria. A análise propõe uma comparação entre as teses pós-revisionistas e as teses ortodoxas, de modo a sustentar a hipótese de que o pós-revisionismo se converteu numa corrente historiográfica antirrevisionista. Para tal, o texto está organizado em três seções. Na primeira, propõe-se uma análise das críticas seminais de Gaddis às teses que ele atribuiu ao revisionismo, destacando as suas limitações. Na segunda seção, é realizada uma comparação entre o pós-revisionismo e a historiografia revisionista, tomando como referência as reflexões de Gaddis. Na terceira seção, sustenta-se que a agenda de pesquisa defendida por Gaddis representou a reassunção das teses ortodoxas, convertendo-se, nesse sentido, numa ortodoxia antirrevisionista.
Antissemitismo e Anticomunismo no pensamento de Julio Meinvielle
Authors: Da Rocha Botega Leonardo
Published: April 2024

Julio Meinvielle (1905-1973) foi um padre católico que atuou na Argentina ao longo das décadas de 1930-1970. Foi um dos principais intelectuais do nacionalismo católico argentino, corrente de pensamento conservadora de forte influência na política argentina, sobretudo, na extrema-direita militar. Iniciou sua trajetória intelectual polemizando com o pensamento renovador católico liderado por Jacques Maritain. Ao longo do governo Arturo Frondizi (1958-1962), proferiu inúmeras conferências e palestras denunciando que se estava pavimentando o caminho para a implantação do comunismo na Argentina. Em um contexto marcado pela Guerra Fria, Julio Meinvielle aproximava em seus posicionamentos o antissemitismo e o anticomunismo na defesa dos autênticos valores católicos nacionais argentinos.
Apresentação dos Artigos
Authors: Sidarta Machado Domingos Charles , Souza Angeli Douglas , Simões Fernandes Ananda
Published: April 2024

Apresentação dos Artigos
O PERFIL MOTIVACIONAL DE PROFESSORES E A QUALIDADE MOTIVACIONAL DOS ALUNOS DO ENSINO MÉDIO NA DISCIPLINA DE FÍSICA
Authors: De Sousa Francisco Antonio , Coelho Marcelo Nunes
Published: April 2024

Apresentamos uma pesquisa cujo objetivo central foi analisar a relação existente entre o perfil motivacionaldocente e a qualidade motivacional em alunos de física do ensino médio. Para sustentação de nossasanálises e conclusões, partimos do referencial da Teoria da Autodeterminação e de discussões querelacionam esse referencial com a motivação para aprender. Para perseguir o objetivo, a metodologiacomporta uma abordagem quali-quantitativa. Os dados foram coletados mediante as seguintes etapas: (1)entrevista semiestruturada com os professores acerca do perfil de aula motivacional; (2) aplicação daEMADF – Escala de Motivação: Atividades Didáticas de Física que foi realizada por meio do Google Forms,obtendo 119 respostas; e, por último, (3) entrevista semiestruturada com 11 alunos, por meio de um roteirocomposto por 15 perguntas. Os dados foram tratados com auxílio do software IRAMUTEQ e análise deconteúdo. Como resultados: a) identificamos o perfil motivacional dos professores, b) observamos o realperfil motivacional dos discentes e como se dá a interação professor-aluno e aluno-aluno; c)compreendemos em termos motivacionais como os alunos se comportam frente às atividades sugeridaspara a disciplina de Física e d) extraímos categorias que indicam os níveis de satisfação das necessidadespsicológicas básicas (autonomia, pertencimento e competência) nos alunos
PROMOÇÃO DA ALFABETIZAÇÃO CIENTÍFICA E TECNOLÓGICA NOS ANOS INICIAIS A PARTIR DE UMA ILHA INTERDISCIPLINAR DE RACIONALIDADE SOBRE A PANDEMIA DE CORONAVÍRUS COMO CONTROVÉRSIA SOCIOCIENTÍFICA
Authors: Mesquita Adriano Santos de , Grando Regina Célia
Published: April 2024

Temática pouco explorada nos anos iniciais da Educação Básica, a Alfabetização Científica e Tecnológica possibilita análise crítica da realidade sob a ótica da formação de indivíduos reflexivos, críticos, agentes de transformação, comprometidos com a sociedade e com questões científicas e tecnológicas a ela relacionadas. Neste artigo, reflito sobre a promoção da alfabetização científica e tecnológica nos anos iniciais do Ensino Fundamental a partir da pandemia de coronavírus enquanto Controvérsia Sociocientífica; ao final, com o intuito de contribuir com a prática pedagógica de professores que atuam nos primeiros anos de escolarização, e para possibilitar reflexões pelas crianças, proponho o desenvolvimento de uma Ilha Interdisciplinar de Racionalidade com a abordagem da temática em tela. Entendo que este estudo pode contribuir com a pesquisa em Ensino de Ciências na perspectiva da promoção de práticas de alfabetização científica e tecnológica nos anos iniciais considerando controvérsias sociocientíficas, a exemplo da pandemia de Covid-19.
UM OLHAR SOBRE O PROCESSO DE GENERALIZAÇÃO EM PESQUISAS SOBRE A FORMAÇÃO DE PROFESSORES QUE ENSINAM MATEMÁTICA
Authors: Hobold Ediséia Suethe Faust , Rosa Josélia Euzébio da
Published: April 2024

Nesta investigação, de natureza bibliográfica do tipo revisão integrativa, apresentamos algumas reflexões teóricas sobre o processo de generalização como elemento essencial para a formação de conceitos e o desenvolvimento do pensamento. O objetivo consiste em analisar como o processo de generalização é contemplado em pesquisas sobre formação de professores que ensinam Matemática à luz da Teoria Histórico-Cultural. Os dados foram obtidos por meio do mapeamento de artigos científicos publicados na plataforma Scientific Eletronic Library Online (SciELO). A análise foi sustentada nos pressupostos da Teoria Histórico-Cultural. Os resultados indicam que generalização é um processo essencial para o desenvolvimento do pensamento, porém ainda são escassos os elementos teórico-metodológicos que possibilitem sua concretização no processo de formação de conceitos matemáticos.
O LÓGICO-HISTÓRICO NA ORGANIZAÇÃO DO ENSINO: UMA SITUAÇÃO DESENCADEADORA DA APRENDIZAGEM ACERCA DO CONCEITO DE FUNÇÃO
Authors: Silva Maria Marta da , Silvestre Bruno Silva
Published: April 2024

O artigo apresenta-se na temática da formação inicial de professores de matemática na perspectiva de organizar um ensino capaz de superar a racionalidade técnica por meio do movimento lógico-histórico dos conceitos. Nessa perspectiva, apresenta-se como questão de pesquisa: quais os indícios elucidados por um coletivo de professores de Matemática em formação acerca da apropriação do conceito de função, a partir do desenvolvimento de uma Situação Desencadeadora da Aprendizagem (SDA)abalizada no movimento lógico-histórico? Conexo à questão, tem-se o objetivo de: investigar os indícios dados por um coletivo de professores de Matemática em formação acerca da apropriação do conceito de função, a qual está alicerçada numa proposta de organização do ensino e aprendizagem desse conceito, firmada a partir do desenvolvimento de uma situação desencadeadora de aprendizagem fundamentada no movimento lógico-histórico. A metodologia de pesquisa se desenvolve por meio de um experimento formativo que teve como foco o desenvolvimento de uma SDA que foi planejada durante a disciplina: Organização do ensino dos conceitos matemáticos a partir dos pressupostos da teoria histórico cultural. A referida disciplina fazia parte da matriz curricular de uma Especialização Lato Sensu sediada na mesma Instituição de Ensino Superior onde se encontrava a turma de Pré-Cálculo da licenciatura em Matemática, que teve seus trinta alunos como sujeitos de pesquisa durante o desenvolvimento da SDA. Uma das tarefas propostas nessa disciplina era que os grupos de alunos elaborassem uma SDA que abordasse um conceito matemático. Um dos grupos organizou uma SDA no formato de uma história virtual denominada ‘O Código de Turake’, sendo que a mesma abordava o conceito de função.  Todo o desenvolvimento da SDA foi registrado de forma audiovisual e, posteriormente, serviu para montarmos nossa estrutura de análise que foi composta de unidade, cenas e flashes.  A análise dos dados dá indícios de que a organização do ensino de conceitos matemáticos que valoriza o movimento lógico-histórico pode aportar-se teórico-metodologicamente na propositura de SDAs, as quais possuam em seu seio a essência do conceito. Também mostra sinais de que os sujeitos admitem a lógica do conceito em unidade com a produção histórico-humana desse conhecimento, onde a unidade lógico-histórica possibilitou compreender o processo de construção do conceito de função a partir de sua estrutura interna.