bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of the High-Intensity Early Mobilization on Long-Term Functional Status of Patients with Mechanical Ventilation in the Intensive Care Unit
Authors: Zhang Chuanlin , Wang Xueqin , Mi Jie , Zhang Zeju , Luo Xinyi , Gan Ruiying , Mu Shaoyu
Published: March 2024

Objective. Intensive care unit (ICU)-acquired weakness often occurs in patients with invasive mechanical ventilation (IMV). Early active mobility may reduce ICU-acquired weakness, improve functional status, and reduce disability. The aim of this study was to investigate whether high-intensity early mobility improves post-ICU discharge functional status of IMV patients. Methods. 132 adult patients in the ICU who were undergoing IMV were randomly assigned into two groups with a ratio of 1 : 1, with one group received high-intensity early mobility (intervention group, IG), while the other group received conventional treatment (control group, CG). The functional status (Barthel Index (BI)), capacity of mobility (Perme score and ICU Mobility Scale (IMS)), muscle strength (Medical Research Council sum scores (MRC-SS)), mortality, complication, length of ICU stay, and duration of IMV were evaluated at ICU discharge or after 3-month of ICU discharge. Results. The patient’s functional status was improved (BI scores 90.6 ± 18.0 in IG vs. 77.7 ± 27.9 in CG; p=0.005), and capacity of mobility was increased (Perme score 17.6 ± 7.1 in IG vs. 12.2 ± 8.5 in CG, p<0.001; IMS 4.7 ± 2.6 in IG vs. 3.0 ± 2.6 in CG, p<0.001). The IG had a higher muscle strength and lower incidence of ICU-acquired weakness (ICUAW) than that in the CG. The incidence of mortality and delirium was also lower than CG at ICU discharge. However, there were no differences in terms of length of ICU stay, duration of IMV, ventilator-associated pneumonia, and venous thrombosis. Conclusions. High-intensity early mobility improved the patient’s functional status and increased capacity of mobility with IMV. The benefits to functional status remained after 3 month of ICU discharge. Other benefits included higher muscle strength, lower incidence of ICUAW, mortality, and delirium in IG.
Current Distribution of the Turkestan White Stork (Ciconia ciconia asiatica) in Kazakhstan
Authors: Fedorenko Vassiliy , Zima Yuliya
Published: March 2024

Over the last 100 years, the range of the White Stork Ciconia ciconia asiatica (Linnaeus, 1758) in Kazakhstan has greatly diminished; it has entirely disappeared in its former eastern and northern ranges, while the number of nesting sites has decreased in the remaining part of its habitat. The most recent specialized studies on the distribution of the White Stork here were conducted in the 1980s. Subsequently, ornithologists were only aware of isolated nests, and in the last 15 years, up until recently, in Kazakhstan, there was only one known active nest in the Zhambyl region. To clarify the current distribution of the White Stork in Kazakhstan, we conducted field research during the breeding season in places of its former distribution in the Zhambyl and Turkestan Regions. Nest surveys were conducted by visual observations using binoculars and a camera with a telephoto lens. During the expedition, 43 inhabited nests of the White Stork were found; information about another 4 nests was obtained from data survey and social networks. Analysis of satellite images allowed us to identify 12 nests located on power line pylons in the southern regions of the republic, specifically in the Keles, Zhetisay, and Maktaaral districts. In total, 59 White Stork nests were found in Kazakhstan. In addition, satellite images revealed more than 120 power line pylons with White Stork nests in the territory of Uzbekistan in close proximity to the Kazakhstan border. All literary and electronic sources available to the authors have been meticulously reviewed. By synthesizing these data, two maps were created: one delineating all recorded White Stork nesting sites across Kazakhstan and its neighboring territories, and the other illustrating the known contemporary and historical ranges of the White Stork in Kazakhstan. A cadastral survey accompanies new nest discoveries of the White Stork. Based on the newly acquired data, we conclude that the White Stork population in Kazakhstan is currently on the rise.
Comparison of Treatment Approaches and Subsequent Outcomes within a Pulmonary Embolism Response Team Registry
Authors: Weekes Anthony J. , Trautmann Ariana , Hambright Parker L. , Ali Shane , Pikus Angela M. , Wellinsky Nicole , Goonan Kelly L. , Bradford Sarah , O’Connell Nathaniel S.
Published: March 2024

Objectives. To characterize the association between pulmonary embolism (PE) severity and bleeding risk with treatment approaches, outcomes, and complications. Methods. Secondary analysis of an 11-hospital registry of adult ED patients treated by a PE response team (August 2016–November 2022). Predictors were PE severity and bleeding risk. The primary outcome was treatment approach: anticoagulation monotherapy vs. advanced intervention (categorized as “immediate” or “delayed” based on whether the intervention was received within 12 hours of PE diagnosis or not). Secondary outcomes were death, clinical deterioration, and major bleeding. Results. Of the 1832 patients, 139 (7.6%), 977 (53.3%), and 9 (0.5%) were classified as high-risk, intermediate-high, intermediate-low, and low-risk severity, respectively. There were 94 deaths (5.1%) and 218 patients (11.9%) had one or more clinical deterioration events. Advanced interventions were administered to 86 (61.9%), 195 (27.6%), and 109 (11.2%) patients with high-risk, intermediate-high, and intermediate-low severity, respectively.Major bleeding occurred in 61/1440 (4.2%) on ACm versus 169/392 (7.6%) with advanced interventions (p <0.001): bleeding withcatheter-directed thrombolysiswas 19/145 (13.1%) versus 33/154(21.4%) with systemic thrombolysis,p= 0.07. High risk was twice as strong as intermediate-high risk for association with advanced intervention (OR: 5.3 (4.2 and 6.9) vs. 1.9 (1.6 and 2.2)). High risk (OR: 56.3 (32.0 and 99.2) and intermediate-high risk (OR: 2.6 (1.7 and 4.0)) were strong predictors of clinical deterioration. Major bleeding was significantly associated with advanced interventions (OR: 5.2 (3.5 and 7.8) for immediate, 3.3 (1.8 and 6.2)) for delayed, and high-risk PE severity (OR: 3.4 (1.9 and 5.8)). Conclusions. Advanced intervention use was associated with high-acuity patients experiencing death, clinical deterioration, and major bleeding with a trend towards less bleeding with catheter-directed interventions versus systemic thrombolysis.
Missed Opportunities for Addressing Maternal Mental Health: A Thematic Analysis of Mothers’ Experiences of Using the Well Child Tamariki Ora Service in Aotearoa NZ
Authors: Clapham Bethany , Breheny Mary , Reweti Angelique , Severinsen Christina , Ware Felicity
Published: March 2024

Maternal mental health plays a vital role in the overall wellbeing of mothers, children, families, whānau (core support network) and communities. However, many mothers face mental health challenges during the transition to parenthood. In this study, we used an online story‐sharing platform to collect the experiences of mothers who have faced unmet needs while using the Well Child Tamariki Ora (WCTO) service in Aotearoa New Zealand. From the 420 submitted stories, 125 stories related to mental health need while using the WCTO service. Using thematic analysis, we identified three main themes that highlighted the experiences of mothers with the service. This includes (1) making it seem that I’m coping: Mothers’ fear of being judged; (2) i wish I had connected with my WCTO nurse: Fostering meaningful relationships to facilitate personal information sharing; and (3) beyond the baby: Mothers desire for recognition and support during WCTO visits. These findings point to several missed opportunities for WCTO providers to inquire about mental health and offer support needed by mothers. To address this, a relational approach to care would prioritise families and whānau as the focus of care rather than just monitoring the development of babies.
The Hautus-Type Inequality for Abstract Fractional Cauchy Problems and Its Observability
Authors: Chen-Yu Li
Published: March 2024

In this paper, we investigate the observability of the fractional resolvent family, and we prove two main results: the first result shows a generalization of the Hautus-type test for observable exponentially stable semigroups to the fractional resolvent family and the second result shows the equivalence of the observability and the below boundedness of the linear operator on the wave packet when the generator conforms to a specific form.
Advancements in Food Printing Technologies and Their Potential Culinary Applications: A Contemporary Exploration
Authors: Shabir Irtiqa , Dar Aamir Hussain , Manzoor Sobiya , Pandey Vinay Kumar , Srivastava Shivangi , Shams Rafeeya , Dash Kshirod Kumar , Bashir Iqra , Fayaz Ufaq , Prithviraj V. , Singh Punit , Rustagi Sarvesh , Ramniwas Seema , Pandiselvam R.
Published: March 2024

Food printing is a cutting-edge manufacturing technique that uses advanced printing methods such as binder jetting, extrusion-based printing, and inkjet printing to build an object layer by layer to achieve the required shape of food items such as chocolate and cheese. 3DFP (3-dimensional food printing) has the potential to combine delicate and easily degradable bioactive compounds and other functional elements into functional 3DFP food products, contributing greatly to the development of nutritious food. Many nations make different types of 3D food printers nowadays, creating specialty meals like space food, restaurants, elderly food, and floating food. Numerous benefits of 3DFP include the development of individualized food items with regard to taste and nutrition, the decentralisation of food production, the decrease of food waste, and commercial innovation. Based on the benefits of customizing current food to one’s taste and use, three-dimensional food printing technology can be applied to a variety of food categories. One of the reasons for the increase in research into this technology is the ability to produce modified products that are tailored to suit the taste preferences and specific nutritional demands of consumers. In this review, the industrial situation of 3DFP technology was examined along with recommendations for expanding the market for 3D-printed food in the new typical age.
Biological Parameters and Spermatogenesis in Razorfish (Pelecus cultratus) Population Inhabiting the Largest Shallow Lake of Central Europe (Lake Balaton): Studies for In Vitro Conservation Purposes
Authors: Bokor Zoltán , Fodor Ferenc , Várkonyi Levente , Nagy Borbála , Láng Zete Levente , Ferincz Árpád , Staszny Ádám , Molnár József , Lefler Kinga Katalin , Csorbai Balázs , Vancsura Zoltán , Szári Zsolt , Urbányi Béla , Bernáth Gergely
Published: March 2024

The study aimed to investigate body parameters and the process of spermatogenesis from April to September. In addition, it sought to test the applicability of sperm cryopreservation for conservation purposes in a razorfish (Pelecus cultratus) population of Lake Balaton, the largest shallow lake in Central Europe. During the aforementioned period, measurements were taken for the standard length (SL, cm) and body weight (BW, g), and the sex of specimens was determined. Cells at different stages of spermatogenesis (spermatogonia‐SG, spermatocytes‐SC, spermatids‐ST, and spermatozoa‐SZ) were quantified monthly for each male sample. Sperm samples collected at the end of May were cryopreserved using a method designed for common carp. No significant differences were found between males (SL: 25 ± 2 cm and BW: 146 ± 38 g) and females (SL: 26 ± 3 cm and BW: 168 ± 53 g) in terms of measured body parameters. No significant correlations were found between the sex, SL, and BW. High standard deviations were observed for all mean values in all sampling periods, possibly due to the low number of individual samples per month. A significantly higher proportion of SC compared to SZ was found in April. In May, no differences were observed between the four groups. Significantly more SG and SZ than SC and ST were observed in June. In August and September, a slight dominance in the number of SG was recorded, with no differences measured among the cells in different developmental stages. The males studied exhibited a low gonadosomatic index (0.92% ± 0.27%). A significant reduction was recorded in motility (MOT), progressive motility (pMOT), and in most of the kinetic parameters (distance curved line‐DCL, curvilinear velocity‐VCL, straight line velocity‐VSL, and beat cross frequency‐BCF). The spermiation of males could have started in May and conceivably lasted until the end of June. It is recommended to increase sperm quality and quantity before cryopreservation.
Comparison of Approximate Analytical and Numerical Solutions of the Allen Cahn Equation
Authors: Hussain Safdar , Haq Fazal , Shah Abdullah , Abduvalieva Dilsora , Shokri Ali
Published: March 2024

Allen Cahn (AC) equation is highly nonlinear due to the presence of cubic term and also very stiff; therefore, it is not easy to find its exact analytical solution in the closed form. In the present work, an approximate analytical solution of the AC equation has been investigated. Here, we used the variational iteration method (VIM) to find approximate analytical solution for AC equation. The obtained results are compared with the hyperbolic function solution and traveling wave solution. Results are also compared with the numerical solution obtained by using the finite difference method (FDM). Absolute error analysis tables are used to validate the series solution. A convergent series solution obtained by VIM is found to be in a good agreement with the analytical and numerical solutions.
Editorial
Authors: Torres Zapata Isabel
Published: March 2024

En este nuevo número de Summa de Arithmetica dedicado a investigaciones de nuestros estudiantes y académicos en torno al desarrollo sostenible. Por medio de los trabajos que acá se presentan queremos dar cuenta del desarrollo de la temática y el estrecho vínculo de los ODS y la formación de los Contadores públicos y auditores especialmente, de acuerdo con la normativa que ha surgido que compele a las grandes corporaciones a transparentar sus impactos sociales, económicos y ambientales. Sin embargo, y tal como señala el colega Samuel Mantilla (https://samuelmantilla.com) esta es una carrera a la cual llegamos atrasados, hay muchas otras profesiones que son parte del tema del cambio climático y la sostenibilidad y en quienes nos deberíamos apoyar desde una mirada interdisciplinaria: ingenieros agrónomos, geógrafos, geólogos, sociólogos, por mencionar a algunos. En este sentido, de los trabajos acá recopilados podemos señalar que buscan reunir desde la mirada de los contadores públicos y auditores los temas de los que debemos estar preocupados y necesitamos ponernos al día lo antes posible. En este sentido, hemos recopilado una diversidad de temas que se vinculan a la sostenibilidad y nuestros ámbitos de actividad, a saber tributación con Determinación de los efectos del impuesto verde incorporado mediante la ley N°20.780 en Chile, Desafíos y responsabilidades de un Contador Público y Auditor frente a la contabilidad ambiental, un trabajo más aplicado al mundo de las empresas con Estudio de Caso sobre implementación de economía circular en Walker Market. Apuntando al mundo de las grandes corporaciones y sostenibilidad tenemos el artículo denominado Actividades de Gobierno Corporativo y sostenibilidad: Efectos financieros en algunas empresas pertenecientes al IPSA en Chile. Por otra parte, en este número damos la bienvenida a la sección historia de la Contabilidad, donde daremos espacio a personajes, hitos y situaciones que han acontecido a lo largo de la historia de la contabilidad en nuestro país y el mundo, dejando un espacio amplio para el conocimiento de diversos temas y situaciones de interés en este ámbito, siendo la inauguración de este con la trayectoria del colega del área de finanzas Ramón Ramos A. Agradecemos a nuestros lectores y a quienes han hecho posible este nuevo número y los dejamos comprometidos para los próximos.
Determinación de los efectos del impuesto verde incorporado mediante la ley N°20.780 en Chile
Authors: Barraza Mora Paul , Lizama Pacheco Antonia
Published: March 2024

En Chile existen diversos impuestos con implicancia ecológica como, el impuesto a cigarrillos, a los combustibles, a la compra de vehículos y a las emisiones al aire. Este trabajo buscó determinar los efectos de los impuestos implementados mediante los artículos N°3 y N°8 de la ley 20.780, los cuales son el impuesto a la compra de vehículos nuevos livianos y medianos y el impuesto a las emisiones al aire de material particulado y otros gases contaminantes respectivamente. Se realizó un análisis de las emisiones al aire históricas en Chile y de la generación de energía antes y después de la implementación de los impuestos respectivos. Se encontró que los impuestos de estos artículos no han tenido ningún efecto real en disminuir y desincentivar la emisión de gases al aire, ni en la venta de vehículos contaminantes, ya que los pequeños cambios se relacionan con otros factores, a su vez se pudo determinar las principales razones de mal desempeño de los impuestos en este ámbito, los cuales son por un lado, el bajo precio del impuesto como tal, pero más importante aún el hecho de no existir una contramedida o plan que acompañe al impuesto.
Data from Pilot Phase II Trial of Neoadjuvant Immunotherapy in Locoregionally Advanced, Resectable Cutaneous Squamous Cell Carcinoma of the Head and Neck
Authors: Ferrarotto Renata , Amit Moran , Nagarajan Priyadharsini , Rubin M. Laura , Yuan Ying , Bell Diana , El-Naggar Adel K. , Johnson Jason M. , Morrison William H. , Rosenthal David I. , Glisson Bonnie S. , Johnson Faye M. , Lu Charles , Mott Frank E. , Esmaeli Bita , Diaz Eduardo M. , Gidley Paul W. , Goepfert Ryan P. , Lewis Carol M. , Weber Randal S. , Wargo Jennifer A. , Basu Sreyashi , Duan Fei , Yadav Shalini S. , Sharma Padmanee , Allison James P. , Myers Jeffrey N. , Gross Neil D.
Published: March 2024

AbstractPurpose:
In locoregionally advanced, resectable cutaneous squamous cell carcinoma of the head and neck (CSCC-HN), surgery followed by radiotherapy is standard but can be cosmetically and functionally devastating, and many patients will have recurrence.
Patients and Methods:
Newly diagnosed or recurrent stage III–IVA CSCC-HN patients amenable to curative-intent surgery received two cycles of neoadjuvant PD-1 inhibition. The primary endpoint was ORR per RECIST 1.1. Secondary endpoints included pathologic response [pathologic complete response (pCR) or major pathologic response (MPR; ≤10% viable tumor)], safety, DSS, DFS, and OS. Exploratory endpoints included immune biomarkers of response.
Results:
Of 20 patients enrolled, 7 had recurrent disease. While only 6 patients [30%; 95% confidence interval (CI), 11.9–54.3] had partial responses by RECIST, 14 patients (70%; 95% CI, 45.7–88.1) had a pCR (n = 11) or MPR (n = 3). No SAEs ocurred during or after the neoadjuvant treatment. At a median follow-up of 22.6 months (95% CI, 21.7–26.1), one patient progressed and died, one died without disease, and two developed recurrence. The 12-month DSS, DFS, and OS rates were 95% (95% CI, 85.9–100), 89.5% (95% CI, 76.7–100), and 95% (95% CI, 85.9–100), respectively. Gene expression studies revealed an inflamed tumor microenvironment in patients with pCR or MPR, and CyTOF analyses demonstrated a memory CD8+ T-cell cluster enriched in patients with pCR.
Conclusions:
Neoadjuvant immunotherapy in locoregionally advanced, resectable CSCC-HN is safe and induces a high pathologic response rate. Pathologic responses were associated with an inflamed tumor microenvironment.
Data from NKG7 Is a T-cell–Intrinsic Therapeutic Target for Improving Antitumor Cytotoxicity and Cancer Immunotherapy
Authors: Wen Ti , Barham Whitney , Li Ying , Zhang Henan , Gicobi Joanina K. , Hirdler Jacob B. , Liu Xin , Ham Hyoungjun , Peterson Martinez Kodi E. , Lucien Fabrice , Lavoie Roxane R. , Li Hu , Correia Cristina , Monie Dileep D. , An Zesheng , Harrington Susan M. , Wu Xiaosheng , Guo Ruifeng , Dronca Roxana S. , Mansfield Aaron S. , Yan Yiyi , Markovic Svetomir N. , Park Sean S. , Sun Jie , Qin Hong , Liu Minetta C. , Vasmatzis George , Billadeau Daniel D. , Dong Haidong
Published: March 2024

Abstract
Cytotoxic CD8+ T cells (CTL) are a crucial component of the immune system notable for their ability to eliminate rapidly proliferating malignant cells. However, the T-cell intrinsic factors required for human CTLs to accomplish highly efficient antitumor cytotoxicity are not well defined. By evaluating human CD8+ T cells from responders versus nonresponders to treatment with immune checkpoint inhibitors, we sought to identify key factors associated with effective CTL function. Single-cell RNA-sequencing analysis of peripheral CD8+ T cells from patients treated with anti–PD-1 therapy showed that cells from nonresponders exhibited decreased expression of the cytolytic granule-associated molecule natural killer cell granule protein-7 (NKG7). Functional assays revealed that reduced NKG7 expression altered cytolytic granule number, trafficking, and calcium release, resulting in decreased CD8+ T-cell–mediated killing of tumor cells. Transfection of T cells with NKG7 mRNA was sufficient to improve the tumor-cell killing ability of human T cells isolated from nonresponders and increase their response to anti–PD-1 or anti–PD-L1 therapy in vitro. NKG7 mRNA therapy also improved the antitumor activity of murine tumor antigen–specific CD8+ T cells in an in vivo model of adoptive cell therapy. Finally, we showed that the transcription factor ETS1 played a role in regulating NKG7 expression. Together, our results identify NKG7 as a necessary component for the cytotoxic function of CD8+ T cells and establish NKG7 as a T-cell–intrinsic therapeutic target for enhancing cancer immunotherapy.

See related article by Li et al., p. 154.
Modeling of web-based collaborative learning management system
Authors: Lahmadi Youssef , Ouadoud Mohammed , Mouzouri Hasnae , Oughdir Lahcen
Published: March 2024

The challenges faced by most learning management systems (LMS) can be classified into two main areas: pedagogical and technical issues. A comprehensive exploration of these interrelated challenges provides valuable insights for developing a new and more effective model for LMS. In this paper, a novel conceptual model for a web-based collaborative LMS is introduced, merging two distinct learning theories: behaviorism and social constructivism. Through an analysis of the strengths and limitations of each theory, the study moves on to outline the fundamental principles and technical features of the proposed LMS model, which stems from this integration. In conclusion, the paper explores the implications of creating user-centered LMS solutions, with a specific focus on addressing the varied requirements of learners.
Enhancing Moroccan legal cases analysis through ontology-based information extraction
Authors: Belhoucine Kaoutar , Zame Nadia , Mourchid Mohammed
Published: March 2024

The efficient organization of diverse disorder cases within a unified memory necessitates an adaptable representation. This study introduces an ontology-based approach for extracting facts from Moroccan legal cases. Leveraging ontological frameworks, a comprehensive case architecture is established, enabling advanced information extraction. Utilizing rules, patterns, and knowledge modeling harmonizes cases and identifies pervasive legal concepts. Statistical techniques unveil latent entities within complex legal textual discourse. Empirical validation demonstrates proficiency, extracting up to 25 regular entities. The rule-based mechanism achieves an F1-score of 99.5%, highlighting precision, while the statistical extractor achieves an 88.3% F1-score, revealing concealed entities. This work presents an innovative ontology-based paradigm for legal information extraction, contributing to advanced knowledge management in the legal domain.
Comparison of ARIMA boost, Prophet boost, and TSLM models in forecasting Davao City weather data
Authors: B. Rogers Jamal Kay , R. Mercado Tamara Cher , Galleto Jr. Fredelino A.
Published: March 2024

The geography of the Philippines experiences climate variability thus, providing accurate and timely weather forecasts to the population is crucial. Climate forecasts, which are issued and disseminated by government agencies, serve as essential risk management tools. However, the country faces challenges in forecasting, further exacerbated by climate change. Thus, exploring the use of artificial intelligence has emerged as a strategy to enhance weather prediction accuracy. This research focuses on time series forecasting of rainfall, mean temperature, relative humidity, and wind speed weather data using a machine learning approach. Specifically, it aims to compare and identify the most beneficial forecasting models among autoregressive integrated moving average (ARIMA) boost, Prophet boost, and time series linear model (TSLM). It also seeks to evaluate the performance of these models using mean absolute error (MAE), mean absolute percentage error (MAPE), mean absolute scaled error (MASE), symmetric mean absolute percentage error (SMAPE), root mean squared error (RMSE), and R squared (RSQ) metrics. Results showed that the selection of the forecasting model varies based on the specific parameter under consideration, with no hyperparameter tuning in the analysis. For wind speed, ARIMA boost proves to be a favorable choice. At the same time, TSLM demonstrates effectiveness for relative humidity and mean temperature. Both ARIMA boost and TSLM exhibit strong performance for rainfall. Prophet boost consistently ranks as the least-performing model.
A hybrid framework for routing and channel assignment in WMN’s
Authors: Sheenam Sheenam , Chadha Raman
Published: March 2024

Wireless mesh network (WMNs) can replace the physical existence of wired network; nevertheless, to solve the problem of traffic and congestion, they must carefully arrange radio resource assignment. In this paper, we focus on the major issues while transferring the data over the network and optimization of resources. WMN mainly suffers from congestion problem when numbers of channel transfer data at a same time which indirectly leads to overlapping channels and sometime data cannot be mitigated to destination. To overcome this problem and provide optimal solution we proposed hybrid channel assignment technique which offers four phase solution technique, in this technique firstly by mitigating the traffic than assigning the optimal path based on greedy and BFS. The purpose of this congestion control hybrid ant based greedy-BFS-load balancing (CCHAGBL) technique is to diminish the number of used slots, which is directly related to the overall resource assignment. We also provide optimal solution using Ant colony optimization technique with hybrid algorithm to achieve the network efficiency and resource utilization with randomly generated traffic. With the help of hybrid ant based greedy-BFS-load balancing (GBL) channel assignment algorithm throughput and packet delivery ratio is upgraded and delay is reduced to minimum.
Assessing the effectiveness of data mining tools in classifying and predicting road traffic congestion
Authors: Arabiat Areen , Altayeb Muneera
Published: March 2024

Traffic congestion is a significant issue in cities, impacting the environment, commuters, and the economy. Predicting congestion is crucial for efficient network operation, but high-quality data and computational techniques are challenging for scientists and engineers. The revolution of data mining and machine learning has enabled the development of effective prediction methods. Machine learning (ML) approaches have shown potential in predicting traffic congestion, with classification being a key area of study. Open-source software tools WEKA and Orange are used to predict and classify traffic congestion. However, there is no single best strategy for every situation. This study compared the effectiveness of both data mining tools for predicting congestion in one of the areas of the capital of the Hashemite Kingdom of Jordan, Amman, by testing several classifiers including support vector machine (SVM), K-nearest neighbors (KNN), logistic regression (LR), and random forest (RF) classifications. The results showed that the Orange mining tool was superior in predicting traffic congestion, with a prediction accuracy of 100% for Random forest, logistic regression, and 99.8% for KNN. On the other hand, results were better in WEKA for the SVM classifier with an accuracy of 99.7%.
A randomized blockchain consensus algorithm for enhancing security in health insurance
Authors: Al-Sarayrah Najah , Turab Nidal , Hussien Abdelrahman
Published: March 2024

Health insurance fraud is a significant problem affecting insurance providers and policyholders. To address the rising problem of fraudulent activities in the health insurance sector, this paper proposes a pioneering blockchain-based system aimed at increasing transparency and security. Utilizing a hybrid Blockchain architecture, the system incorporates a consensus algorithm influenced by practical byzantine fault tolerance (PBFT) and proof of activity (PoA) to ensure reliability and efficiency in distributing mining power. Developed using Python, extensive testing confirms the system's performance and security metrics. Results show that a block size containing one transaction is 1.63 KB, with 1.2 KB for data and 0.43 KB for identification and hashing. Operational tests demonstrate that a single participant can upload 850 transactions to the transaction pool, with validation completed in just 7.49 seconds. Block appending time for these transactions is a swift 10 seconds. Notably, the system exhibits resilience against data tampering, detecting unauthorized changes within 881.3 milliseconds across 10,000 blocks and identifying irregularities in the transaction pool within 8.78 seconds. Additionally, to enhance data privacy, patient information is accessible only through a unique QR code, providing an extra layer of security; this research represents a significant advancement in combatting fraud and safeguarding data privacy.
An effective secondary personalization file system driven by FileForge module
Authors: Liu Gaojian , Hu Yufei , Cheong Ngai
Published: March 2024

Digital service platforms provided by academic support departments in Macao assist academic staff and students in various areas such as registry, student affairs, academic activities, and research. As the number of undergraduate students increases and new departments are established, academic staff often face the challenge of dealing with paperwork that contains similar content but different formats. This situation results in redundancies and a waste of time. This paper presents our endeavors to simplify administrative procedures in higher education by automating restructured documentation and developing secondary file systems. The paper presents two case studies: Scenario One focuses on streamlining the publication system for academic staff who submit papers in different formats. At the same time, Scenario Two aims to simplify the daily paperwork process for academic staff. Both cases involve transforming the distribution of administrative documents, transitioning from a standardized form with guidelines to a customized form with concise tips. This approach allows academic staff to handle only the necessary information, which may not be available in the database or requires verification. The case studies serve to demonstrate the effectiveness of this administrative simplification.
An Intrusion Detection System against RPL-based Routing Attacks for IoT Networks
Authors: Hebbaka Shivanajappa Manjula , Maidanahalli Seetharamaiah Roopa , Viswaraju Sai Bharath , Jakkanahally Siddegowda Arunalatha , Kuppanna Rajuk Venugopal
Published: March 2024

The significant improvement in the Internet, Internet of Things (IoT), communication, and cloud computing have created considerable challenges in providing security for data and devices.  In IoT networks, “Routing Protocol for Low power and Lossy networks”- (RPL) is a communication protocol that enables devices to exchange information and communicate with limited resources like low processing capabilities, less memory and energy. Through the Internet, unauthorised users can access RPL-based IoT networks, making these networks susceptible to routing attacks. Therefore, it is crucial to design Intrusion Detection System-(IDS) to address attacks from IoT communication devices. In this paper, we have proposed GCNConv, a Graph Neural Network (GNN) method that allows capturing the edge and node features of a graph to identify routing attacks. The proposed   system   has experimented on the RADAR dataset and experimental findings proved that, our approach performs well compared to state-of-the-art method with reference to precision, F1-score, accuracy and recall.
An efficient test suit reduction methodology for regression testing
Authors: Gupta Shailendra , Choudhary Jitendra
Published: March 2024

This paper's goal is to provide a more effective algorithm for reducing the amount of test cases in a test suit during the regression testing phase. This algorithm divide the entire test suit into equivalence classes in first step and then apply boundary value coverage to select test case out of repeated test cases which has same importance in test suit. This algorithm is based on the concept that before selecting best test cases out of repeated test case in test suit to prepare reduced test suit we can divide all test cases in number of equivalence classes so number of test case under consideration reduced by great extend. This paper proposed a method of experimentation involving test cases from different software application areas; minimization algorithms and the maths and algorithms of minimization algorithms in details. Test case techniques are equivalence portioning and boundary value analysis. Along with this concept, I also discuss a case study to verify and check new algorithm for its efficiency, for that I apply my algorithm on one of the program or group of program. This complete proposed methodology shall be applied to different software applications belonging to soft computing, Engineering software, Financial Software, Cloud Applications, Business Applications, AI and Machine Learning, Data Analytics are being identified. This selection has been made keeping in mind the trends, industrial importance, economic values and research challenges. Minimization in test cases would lead to lesser testing effort and desirable test completion.
A novel FFNN-AHO hybrid predictive model for enhancing the performance of jet-cooled PVT system
Authors: Essa Mohamed A. , Rashad Alaa M. , Hatata Ahmed Y.
Published: March 2024

Photovoltaic-thermal (PVT) systems are common in the conversion of solar energy to electrical and thermal energy. The performance of such systems depends on the environmental conditions in which these systems are applied. This paper presents a parametric study of a jet-cooling PVT system with a staggered distribution of the jets. A feedforward neural network (FFNN) is proposed as a novel predictive model for analyzing the characteristics of the PVT system and its thermal and electrical performance. Moreover, a novel optimization algorithm called archerfish hunting optimizer (AHO) is applied to obtain the optimal structure and elements of the proposed FFNN. The PVT system variables considered as inputs to the FFNN-AHO model are flow rate, wind speed, solar irradiance, and ambient temperature. The average temperature of the PV reaches a maximum of 45.84 ºC, and the maximum temperature un-uniformity reaches to 3.59 ºC. The studied PVT system achieved maximum electrical, thermal, and overall efficiencies of 14.23%, 54.43%, and 68.1%, respectively. Moreover, the results demonstrate that the FFNN-AHO hybrid model provides highly accurate PVT system performance prediction. The correlation coefficient between the actual and predicted data is close to 1, indicating a strong correlation and confirming the reliability and effectiveness of the FFNN-AHO model.
Implementation and feasibility of green hydrogen in Colombian kitchens: an analysis of innovation and sustainability
Authors: Vidal-Durango Jhon , Baena-Navarro Rubén , Therán-Nieto Kevin
Published: March 2024

This study explores the potential of green hydrogen as a sustainable energy solution in domestic cooking, focusing on Colombia. It employs a systematic literature review following the PRISMA framework, analyzing articles published between 2018 and 2023 to assess the feasibility and challenges of implementing green hydrogen in the culinary sector. The research emphasizes the projected growth in the demand for clean hydrogen, particularly in the industrial sector by 2030 and in new applications by 2050, with an estimated increase from less than 1% currently to about 30% of the total hydrogen demand. It is anticipated that green hydrogen production will dominate the global supply mix by 2050, reflecting a share of between 50% and 65% in various scenarios. The study concludes that while green hydrogen holds great potential for transforming Colombia's energy matrix towards a cleaner, more sustainable future, it faces significant regulatory and technical challenges that require concerted, collaborative action, aligning with the sustainable development goals.
Modeling and adaptive neuro-fuzzy inference system control of quarter electric vehicle
Authors: Baz Rachida , El Majdoub Khalid , Giri Fouad , Ammari Ossama
Published: March 2024

Electric vehicles (EVs) have gained importance in recent years, prompting the development of several control systems to improve their efficiency and performance. In this work, a quarter electric vehicle (QEV) was controlled using a conventional proportional integral derivative (PID) and fuzzy controller to examine and compare with the response of the adaptive neuro-fuzzy inference system (ANFIS) controller. The response of the ANFIS controller was evaluated using MATLAB/Simulink according to different parameters and compared with those of other controllers. In addition, the simulation was based on different driving conditions such as the acceleration and deceleration modes and the type of road: wet and dry. The simulations were carried out on a longitudinal electric vehicle model based on a brushless DC motor, including the Pacejka tire model. The results showed that the ANFIS controller outperformed the PID and fuzzy logic controllers, providing superior dynamic responsiveness and stability when the ANFIS controller smoothly followed the input speed and the longitudinal slip value reached 3%.
Potential microgrid model based on hybrid photovoltaic/wind turbine/generator in the coastal area of North Sumatra
Authors: Satria Habib , Syah Rahmad , Ramdan Dadan , Zuhanda Muhammad Khahfi , Windarta Jaka , Syafii Syafii , Youssef Abdelaziz Almoataz
Published: March 2024

The high potential for renewable energy in the North Sumatra region, especially the coast of the Belawan area, needs to be exploited properly. The design that will be carried out is to explore the potential in coastal areas by simulating microgrid systems and hybrid system-based electricity installations. The method that will be used is to find the accuracy of strategic location points by considering the panel surface temperature which will later influence the power output of the power plant. Then find the ideal installation location as a reliable system when irregular climate conditions occur, of course this phenomenon will have a significant effect on energy balance and energy conversion, especially in coastal areas. The potential for installation construction will be carried out with a hybrid system using power sources from photovoltaics, wind turbines and diesel generators assisted by HOMER Pro software. The results of testing with simulations and information data that have been recorded in the software can later be used as a benchmark in planning electrical installations and also for identifying microgrid protection challenges. Then the measurement results that have been obtained for the installation of a hybrid-based microgrid system on Photovoltaic (PV) are DC output power of 618.80 W with measurements of sunny weather conditions, then the potential wind speed on the wind turbine reaches 5 m/s and the potential use of a diesel generator reaches 40% with power output capacity 1 kW.
Multi-modal fusion deep transfer learning for accurate brain tumor classification using magnetic resonance imaging images
Authors: Gottipati Srinivas Babu , Thumbur Gowri
Published: March 2024

Early identification and treatment of brain tumors depend critically on accurate classification. Accurate brain tumor classification in medical imaging is essential for clinical decisions and individualized treatment plans. This paper introduces a novel method for classifying brain tumors called multimodal fusion deep transfer learning (MMFDTL) using original, contoured, and annotated magnetic resonance imaging (MRI) images to showcase its capabilities. The MMFDTL can capture complex tumor features frequently missed in analyzing individual modalities. The MMFDTL model employs three deep learning models for extracting features VGG16, Inception V3, and ResNet 50. The accuracy rate improves when combined with decision based multimodal fusion. It produces impressive outcomes of sensitivity 92.96%, specificity 98.54%, precision 93.60%, accuracy 98.80%, F1-score 93.26%, and kappa 91.86%. This research can improve medical imaging and brain tumor analysis through its multi modal fusion approach. It could give healthcare practitioners vital insights for personalized treatment plans and informed decision making.
Cumulative error correction of inertial navigation systems using LIDAR sensors and extended Kalman filter
Authors: Ath Thahirah Al Azhima Silmi , Hakim Dadang Lukman , Nulfatwa Robby Ikhfa , Arief Hakim Nurul Fahmi , Al Qibtiya Mariya
Published: March 2024

Autonomous robots have gained significant attention in research due to their ability to facilitate human work. Navigation systems, particularly localization, present a challenge in autonomous robots. The inertial navigation system is a localization system that uses inertial sensors and a wheel odometer to estimate the robot’s relative position to the initial position. However, the system is susceptible to continuous error accumulation over time due to factors like sensor noise and wheel slip. To address these issues, external sensors are required to measure the robot’s position in the environment. The extended Kalman filter (EKF) method is utilized to estimate the robot’s position based on wheel odometer and light detection and ranging (LIDAR) sensor measurements. In the prediction stage, the input to the EKF is the position measurement from the wheel odometer, while the LIDAR sensor’s position measurement is used in the update stage to improve the prediction stage results. The test results reveal that the EKF’s estimated position has a lower average error compared to the position measurement using the wheel odometer. Therefore, it can be concluded that the EKF technique is effectively applied to the robot and can correct the wheel odometer's cumulative error with the assistance of the LIDAR sensor.
An ontology-based knowledge representation using OWL for Indonesian local regulations
Authors: Kurniawan Tri Astoto , Safa’at Rachmad , Santoso Nurudin , Ismail Muhammad Farabi
Published: March 2024

Inconsistencies in legislation can significantly hinder the effectiveness and efficiency of the central and local government administrations. The Indonesian government requires standard harmonization of each piece of legislation to prevent such problems. However, this process is often manual and requires the involvement of multiple experts with varying backgrounds. This leads to high resource expenses regarding human resources, cost, and time. To address this, a software system should be developed to detect potential disharmony among legislation. However, the system requires a well-constructed legislation conceptual model represented in an appropriate modeling language. This research aims to develop the Indonesian local regulation ontology in web ontology language (OWL), where no such ontology exists. The ontology was created using the Ontology Development 101 methodology and evaluated using competency questions and expert judgment approaches. The resulting ontology becomes a basis for developing an automatic recommendation system to detect potentially inconsistent legislation in future works.
An overview of emerging trends in robotics and automation
Authors: Sutikno Tole
Published: March 2024

Robotics has experienced significant growth and development over the past few decades, with the first industrial robots introduced in the 1950s. As technology advances, robotics has become more intelligent, smart, and flexible, with the introduction of artificial intelligence (AI) and machine learning (ML). Robots are now being integrated into various fields, including healthcare, agriculture, transportation, and space exploration. Robots are set to revolutionize our daily lives, transforming interactions and work processes as technology advances. Emerging trends in robotics, such as AI and ML, soft robotics, and swarm robotics, can transform industries and improve efficiency. The future of robotics and automation promises safer workplaces, improved healthcare, and enhanced environmental sustainability. Society must adapt to this changing landscape, requiring continuous learning and upskilling to remain relevant in the workforce.
Human Rights Standards as a Bar to Extradition from the European Union to the United Kingdom
Authors: van Zyl Smit Dirk
Published: March 2024

Since 1 January 2021, the Trade and Cooperation Agreement between the United Kingdom and the European Union has regulated extradition to and from the United Kingdom and Member States of the European Union. A recent judgment of a German court denying extradition of a suspect to the United Kingdom illustrates the subtle differences between the terms and operation of the Trade and Cooperation Agreement Warrant and those of the European Arrest Warrant that had applied previously.

This paper notes the absence of mutual trust as an underlying principle in the Trade and Cooperation Agreement, and the failure of the British authorities to grasp and respond to the changed criteria. At the same time, it highlights the implications of a judgment that finds that the treatment of prisoners in British prisons might be so inhuman and degrading that persons should not be extradited to face imprisonment in the United Kingdom.
The Antiquarian Alessandro Totti da Brescia: his Annotated Copy of the Epigrammata Antiquae Urbis (Rome, 1521) and his Autograph Papers in Vat. lat. 5237
Authors: González Germain Gerard
Published: March 2024

In 2022 the Johns Hopkins University purchased an annotated copy of the Epigrammata Antiquae Urbis (Rome, 1521), the earliest published collection of inscriptions from Rome. A paleographical comparison shows that the annotator was the Servite friar Alessandro Totti (1498–1570), a little-studied Brescian antiquarian. The present study confirms him as the source of numerous papers within Vat. lat. 5237 (a composite epigraphic manuscript assembled by Aldo Manuzio the Younger), and sheds light on his exchange of antiquarian information with Ottavio Pantagato, Paolo Manuzio, and his son Aldo Manuzio. The analysis of Totti’s annotations in the Epigrammata, written in the 1550s, reveals not only his detailed study of Rome’s inscriptions, but also his interest in two of the most heated antiquarian debates at the time: Roman chronology as attested by the discovery of the Fasti Capitolini, and the identification of the 35 Roman tribes.