bluuebunny/crossref_metadata_2025 huggingface dataset:
Design and Implementation of a Hotel Recommendation System Using Deep Learning
Authors: Badouch Mohamed , Boutaounte Mehdi
Published: July 2024

Accurate hotel recommendations play a crucial role in enhancing the overall travel experience. In recent years, recommendation systems have gained significant popularity in the tourism industry. These systems use various techniques and algorithms to analyze user preferences and provide personalized hotel recommendations. One of the emerging methods in recommendation systems is deep learning, a branch of machine learning that focuses on training neural networks with multiple layers to make accurate predictions or classifications. Deep learning algorithms have shown great success in various domains such as image processing and natural language processing. This chapter aims to propose a hotel recommendation system that utilizes deep learning techniques for analyzing user preferences and providing personalized recommendations. The proposed hotel recommendation system will leverage user reviews and hotel descriptions to extract meaningful features and train a deep learning model.
Navigating Uncharted Waters
Authors: Shan Richard
Published: July 2024

This chapter explores the evolution and future trajectory of Python-driven generative AI, highlighting Python's role in advancing this technology. It discusses the integration of Python with emerging technologies like neuromorphic computing and reinforcement learning, focusing on their potential to revolutionize art, design, and media. Through detailed analysis of the open-source implementation of a technology platform designed, the chapter provides insights into Python's facilitation of innovative AI applications. It addresses potential challenges and ethical considerations, along with the mitigation and call to action, emphasizing the importance of responsible innovation. The narrative underscores Python's influence in making advanced AI technologies accessible and scalable, preparing readers to engage with future developments in the field of generative AI.
AI Generative Models for the Fashion Industry
Authors: Firos A. , Khanum Seema
Published: July 2024

Fashion designers and brands use GANs to create new and unique patterns, styles, and textures. GANs consist of a generator and a discriminator, which work together to produce high-quality, realistic outputs. VAEs are another type of generative model that is applied to generate new fashion designs. VAEs are known for their ability to generate diverse outputs by sampling from a learned latent space. Fashion designers can use VAEs to explore different design variations and styles. StyleGAN and its successor, StyleGAN2, are advancements of GANs that specifically focus on generating high-resolution and realistic images with control over different style elements. These models have been employed in fashion to create detailed and visually appealing designs. These AI generative models have the potential to revolutionize the fashion industry by facilitating creativity and providing new avenues for artistic expression. However, it's essential to consider ethical implications, intellectual property rights, and the responsible use of AI technologies in the context of fashion design.
Foundations of Generative AI
Authors: Babu Tina , Nair Rekha R. , M. Ebin P.
Published: July 2024

The chapter delves into the foundations of generative artificial intelligence (AI), offering an introductory overview and a nuanced understanding of its basic principles, history, and evolution. It navigates through core technologies underpinning generative AI, including neural networks, machine learning models, and key algorithms. The introduction traces generative AI's roots, unraveling its historical trajectory. It progresses to elucidate fundamental concepts, exploring neural networks' structures, functionalities, and applications. The study examines diverse machine learning models and pivotal algorithms crucial to generative AI, shedding light on their roles in generating innovative outputs. This abstract encapsulates a comprehensive journey through generative AI's core elements, serving as a foundational guide for understanding its origins, principles, and technologies.
Core Technologies
Authors: Saraf Atharva , Das Susanta
Published: July 2024

The purpose of the chapter is to provide an overview of artificial intelligence (AI) to the knowledge seekers. This chapter aims to provide the historical development of AI over the years. It provides an overview of machine learning. It talks about supervised, semi-supervised, and unsupervised, reinforcement learning, and transfer learning. It delves into the generative adversarial networks (GAN). It further provides an overview of various components of neural network (NN) such as input layers, hidden layers, output layers, forward propagation, backward propagation, training, optimization, inference, fine tuning, transfer learning, etc. The chapter will leverage academic journals, conferences, and online repositories to shed light on the dynamic landscape of AI technology.
The Power of Intelligent Automation
Authors: Kalare Kailash Wamanrao , Bhagat Dhananjay , Jajulwar Kapil Kamalakar , Bhave Roshni , Raut Saundarya Vinodrao , Dorle Sanjay
Published: July 2024

This chapter explores the transformative impact of intelligent automation across various industries, reshaping conventional practices to enhance efficiency, productivity, and innovation. From manufacturing to healthcare, finance, logistics, and education, intelligent automation revolutionizes processes through advanced robotics, AI algorithms, and real-time tracking. Examples include streamlined assembly lines, AI diagnostics, and personalized learning experiences. This chapter articulates the unparalleled transformative potential of intelligent automation, urging organizations to embrace its innovative capacity for sustained growth amidst dynamic evolution.
Affordable Internet of Things Sleep Monitor System
Authors: Ciufudean Calin , Buzduga Corneliu
Published: July 2024

Sleep monitoring offers significant benefits in understanding and optimizing a person's sleep experience by identifying problems, optimizing sleep routines, and evaluating the effectiveness of interventions. This raises the question of what factors affect the average person during sleep and what constitutes restful sleep. To cover a wide range of factors that influence the quality of sleep and to collect both the vital data, and the disturbing factors that may appear during sleep, the system presented in this work uses sensors that measure and detect the temperature, humidity, light level, air quality, room noise. The person's pulse and movements will also be monitored. To verify possible correlations between the measured data and sleep quality, the sleeping person is recorded in video and audio, so that the person's state can be checked by the data detected by the sensors at a certain moment. Long-term storage of accumulated information is necessary to evaluate the evolution of sleep quality.
Paperless Paradigm
Authors: Bhambri Pankaj , Rani Sita , Pareek Piyush Kumar
Published: July 2024

In the contemporary landscape of business operations, the transformative impact of intelligent automation in document and record management stands as a pivotal paradigm shift. This chapter comprehensively examines the integration of technologies such as robotic process automation (RPA), artificial intelligence (AI), and optical character recognition (OCR) in the context of document digitization and management. By presenting real-world applications and success stories, the chapter sheds light on how organizations can streamline their workflows, enhance data accuracy, and achieve unparalleled efficiency in document-centric processes. From automated data extraction to dynamic file organization, “Paperless Paradigm” offers a strategic guide for businesses seeking to embrace intelligent automation for a seamless transition into a paperless future.
Financial Innovations
Authors: Bhambri Pankaj , Rani Sita , Pareek Piyush Kumar
Published: July 2024

With the convergence of advanced technologies such as robotic process automation (RPA), artificial intelligence (AI), and data analytics, financial institutions and insurance companies are experiencing a paradigm shift in their operational models. The chapter explores how intelligent automation is revolutionizing traditional financial processes, including risk assessment, fraud detection, and compliance management. It analyzes the integration of automation tools in insurance underwriting, claims processing, and customer service, shedding light on the enhanced efficiency, accuracy, and customer satisfaction achieved through these innovations. Additionally, the chapter scrutinizes the challenges and ethical considerations associated with deploying intelligent automation in the financial sector, offering insights into best practices for achieving a harmonious synergy between technology and regulatory frameworks.
Navigating the Social Media Maze
Authors: Singha Surjit
Published: July 2024

Integrating digital marketing and social media is crucial for organizations to navigate the ever-changing global media environment. Amidst polarization, fragmentation, and convergence, marketers can utilize social media's potential to foster connections, increase brand recognition, and involve communities. Attainment requires manoeuvring through the digital environment, adjusting to shifting consumer preferences and imbibing novel ideas. Methods encompass data analytics to obtain valuable insights, develop engaging content experiences, and emphasize genuineness and adaptability. Anticipating forthcoming developments and adopting novel strategies will be essential for optimizing the influence of marketing efforts. In our interconnected world, social media marketing presents various opportunities and challenges that necessitate a strategic, audience-focused, and data-driven approach to achieve success.
The Disinformation Divide
Authors: Jahan Tasnim , Saurav Shashikant , Jahan Shabnam
Published: July 2024

Communication is one of the oldest tools that have been utilized in all the possible sectors/institutions that can have a positive impact on a developing society. There are no doubts about the role and importance of the same but at the same time, all such instruments can have negative connotations as well. Since time immemorial, vocabulary, conversations, and other forms of communication were given high regard with respect to the impact that any such instrument can have and were used for different purposes other than friendly and informal discussions. With time and tech-advancements, the world witnessed the expansion and blooming of the communication methods and also the impact, both positive and negative, it brought along with. This chapter deals with one of such issues that misuse of communication can cause, that is ‘the disinformation divide' and their impact on society. This study firstly conceptualizes the problem in order to understand the origin of the same, secondly it explores all the mediums that are responsible for the above defined problem.
Decoding Customer DNA
Authors: Bhujanga Rao Patcha , Vijaya Bhaskar Reddy Meegada , Chakradhar P. , D. Deepak , Inampudi Preethi
Published: July 2024

Exploring the depths of customer essence - their DNA - holds the key to unlocking profound marketing intelligence and cultivating enduring engagement. This paper delves into the concept of customer DNA, illustrating its transformative potential in shaping tailored marketing strategies and fostering meaningful customer connections. Through meticulous examination of demographics, behaviors, and preferences, businesses can uncover invaluable insights into customer desires and tendencies. Armed with this nuanced understanding, organizations can craft laser-focused marketing campaigns, curate personalized product offerings, and orchestrate exceptional customer journeys. However, navigating the ethical complexities surrounding customer data privacy and security necessitates conscientious data handling practices. This paper provides a comprehensive exploration of unlocking customer DNA, its influential impact on marketing intelligence and customer engagement, and the imperative for ethical considerations in this data-driven landscape.
Enhancing Customer Experiences With Service Robots
Authors: Joghee Shanmugan , Ramakrishnan Swamynathan , Kabiraj Sajal , Alzoubi Haitham
Published: July 2024

Due to the 4th Industrial Revolution, Artificial Intelligence and other internet technologies such as RAISA (Robots, Artificial Intelligence, and Service Automation) have been adopted in various industries, including the hospitality and tourism industry. As the industry traditionally offers services through a manual labor force, more companies adopt RAISA through a commercial service in the form of chatbots, delivery robots, robot concierge, conveyor restaurants, self-service information/check-in/check-out kiosks, and many others. This book chapter explores the dynamic interplay between consumer behavior, customer orientation, emotional intelligence, and the integration of service robots into the customer service landscape. It delves into the transformative potential of service robots in various industries and the profound impact they have on customer satisfaction. In this chapter used holistic approach to examining the intersection of technology and human empathy in the context of customer experiences, offering insights into how service robots can enhance, rather than replace, human interactions within the customer service industry.The chapter also examines how understanding consumer behavior, cultivating customer orientation, and leveraging emotional intelligence can maximize the effectiveness of service robots in enhancing customer experiences. The integration of these components is crucial in achieving a harmonious synergy between technology and human interaction, ultimately shaping the future of customer service.
Unleashing the Power of Customer Personalization in the Digital Age With Artificial Intelligence
Authors: Sahu Premendra , Mandal Pinaki
Published: July 2024

The days of simple marketing are long gone. In today's digital world, personalization is the key to standing out from the crowd and engaging consumers. Customers are surrounded by devices and bombarded with content from digital pipes. The best way to cut through this digital clutter and create lasting connections with your customers is to personalize their experience with your brand. Artificial intelligence is essential to achieve the high level of personalization that customers expect. Artificial intelligence algorithms can analyze vast amounts of data about consumer behavior, preferences and interactions. This data is then used to create personalized customer profiles, allowing marketers to deliver highly targeted marketing messages. According to a SmarterHQ report, 72% of consumers only engage with marketing messages that are tailored to their specific interests.
The Alien Series
Authors: Balcı Gülpınar Dilara
Published: July 2024

The history of colonialism and colonial discourse constitutes a profoundly influential historical framework for the science fiction genre, from early literary works to contemporary cinema. The majority of science fiction stories inherently possess a colonial narrative, whether comprehended by the audience or not. This study aims to highlight the trauma experienced by imperialists during the decolonization process and its affect on post-World War II films, a period marked by the emergence of postcolonial theory. Drawing from the assumption that colonial policies are reproduced and reinforced in 1970s sci-fi films, Alien (Ridley Scott, 1979) and its sequels will be ideologically analyzed in accordance with the perspectives of authors such as Said, Fanon, and Memmi. The analysis of representations in the films will specifically address the justification of galactic colonization, the rationalization of the massacre of the colonized, and the monsterization of the 'other.'
Kieślowski's Manifesto of Inner Europeanness
Authors: Kökek Duygu Güles
Published: July 2024

One of the most prominent representatives of the European auteur director tradition, Krzysztof Kieślowski, created the Three Colours trilogy: Blue, White, Red (1993-1994). This series, the influence of which transcended the borders of Europe in terms of its subject matter, formal features, and narrative techniques, established a notable presence in world cinema history. The three colours of the French flag -blue, white, red- constitute the Trilogy, symbolizing the foundational concepts of Enlightenment ideology: liberty, equality, and fraternity, respectively. These notions hold central significance, embodying principles that originated in Europe and permeated the entire world. Kieślowski, with his unique auteur style, explored these concepts on an individual-inner level rather than a political-social one, crafting a universal work of art through the new narrative possibilities he achieved. The study subjects Kieślowski's work to a fresh form and narrative analysis in line with Gilles Deleuze's cinema theory, drawing from the extensive literature that has emerged around the Trilogy.
Experimental Investigation and Comparative Analysis of an Efficient Machine Learning Algorithm for Distribution System Reconfiguration
Authors: S. Kavitha , M. R. Dileep , S. Sampath Kumar , Shahid Mohammad , Hemachandu P. , Kaliappan S.
Published: July 2024

This study studies the implementation of machine learning (ML) algorithms to improve power distribution in an industrial context, concentrating on the essential issue of anticipating energy consumption. Various ML models, including Support Vector Machine (SVM), Artificial Neural Network (ANN), Decision Trees (DT), and Random Forests (RF), were extensively examined and compared for their usefulness in anticipating demand patterns within a sector encompassing machining, forging, CNC, and packaging stations. The models revealed various strengths, with SVM leading with an accuracy of 95.6%, closely followed by ANN at 94.33%, while DT and RF displayed accuracies of 87.6% and 85.6%, respectively. The research additionally gives a thorough comparison of actual vs expected demand levels over hourly intervals, illustrating the models' responsiveness to dynamic energy use patterns throughout the day.
Machine Learning for the Detection of Uniform Resource Locator Phishing
Authors: S. Muthuselvan , R. Karthikeyan , M. Rajasekaran , K. Rajakumari , S. Rajes kannan , S. Anupriya
Published: July 2024

In recent times, phishing attempts have grown in frequency as fraudsters employ diverse tactics to deceive gullible victims into divulging confidential information, like financial details or login credentials. One of the most common methods of phishing is through the use of URLs, where attackers create fake web pages that mimic legitimate sites and use them to steal information from users to combat this threat, researchers and security experts have turned to machine learning techniques to develop algorithms that can accurately detect phishing URLs. In this paper,review the current state of the art in URL phishing detection using machine learning, including the various approaches and algorithms that have been developed.
Meta-Heuristics Algorithm for Computer Communications
Authors: Venket Krithikaa , Ambica Anju , Freeda Adline R.
Published: July 2024

Communication technology's advancement has revolutionized industries and shaped social norms by changing how we connect and communicate. Every technological development, from the earliest days of telegraphy to the present day of wireless connectivity and high-speed internet, has brought the world closer together. Global networks have made it easier to interchange data, which has improved commercial operations and changed human interactions by erasing the need for physical boundaries. The need for reliable and efficient computer communications has grown in the digital age at present. The complicated optimization problems that arise in network design, routing protocols, resource allocation, and quality of service management can now be solved successfully with the help of metaheuristic algorithms. Such algorithms like Simulated Annealing (SA), Ant Colony Optimization (ACO), Genetic Algorithms (GA), and Particle Swarm Optimization (PSO).
Metaheuristic Algorithms for Robot Path Planning
Authors: T. Raja , M. Shanmugapriya , K. K. Manivannan
Published: July 2024

This book chapter provides an in-depth exploration of metaheuristic algorithms in the context of robot path planning, addressing the challenges and opportunities in this dynamic field. Robot path planning is crucial for autonomous navigation in diverse environments, and traditional methods often struggle with complex scenarios. Metaheuristic algorithms offer promising solutions by leveraging optimization and search techniques. This chapter presents an overview of prominent metaheuristic algorithms, including genetic algorithms, simulated annealing, particle swarm optimization, ant colony optimization, and evolutionary strategies, discussing their principles and applicability. It also examines factors influencing algorithm performance and recent advancements, such as hybridization and machine learning integration. Through real-world examples and case studies, this chapter aims to provide insights and guidance for researchers, practitioners, and students interested in employing metaheuristic algorithms for effective robot path planning.
Dual-Level Location Suitability Index for Optimum Site Selection
Authors: Ismail Hytham Mahmoud Mohammed , Ali El Mekawy Mohamed Sobaih , Nasr Mona , Belal Mohamed
Published: July 2024

COVID-19 pandemic has spread rapidly affecting the entire world. During the fight against the pandemic, hospitals are insufficient to meet the needs. This study aims to set the basis for optimal site selection of quarantine hospitals. Further, to determine the critical factors influencing this selection. The Dual Level Location Suitability Index (DLLSI) proposed methodology provides decision maker with the optimal city and the optimal sites in the selected city for hospital construction. Analytical Hierarchy Process approach is implemented as a part of this study with 14 criteria used to evaluate the alternatives. Safety, accessibility, and availability criteria are also influencing the site selection. The results of DLLSI proposed methodology implementation show the optimal city and the optimal potential sites. It is observed that potential optimal sites located in optimal city. This is considered as self-evaluation, one of the contributions for the proposed methodology. Furthermore, the results of the proposed model are robust, realistic, and supportive for decision makers.
Artificial Intelligence (AI) for Talent Acquisition
Authors: Alam Mohammad Sarwar , Munira Kazi Sirajum , Rahman Md. Sahidur , Uddin Md. Aftab , Akter Ayesha
Published: July 2024

The present study's aim is to investigate the intention to use and actual use of a artificial intelligence (AI) for talent acquisition in Bangladesh. The authors used deductive reasoning approach in a positive paradigm. The study finally collected 243 responses through self-administered questionnaire and used the PLS-based structural equation modeling to analyze the data. The findings of this study revealed that each of the predictors is significantly associated with the intention to use and actual use of AI for recruiting talents, excepting the influence of facilitation conditions on actual use of AI. The influence of age demonstrated that there is no moderating effect of the influence of users' intention to use on actual use of AI for talent acquisition. This study also advances knowledge in AI adoption for recruiting talents, and enhances literature in the fields of AI adoption for recruiting talents by providing insights for the policy makers in a developing country's context. Furthermore, the study also provides insightful directions for future researchers.
Automated Ruleset Generation for “HTTPS Everywhere”
Authors: Alharbi Fares , Kashyap Gautam Siddharth , Allehyani Budoor Ahmad
Published: July 2024

This paper details the implementation of a Web crawler aimed at automating ruleset construction for “HTTPS Everywhere,” with a goal to convert HTTP URLs to secure HTTPS equivalents for enhanced communication security. Developed within a seven-month timeframe, the crawler faced challenges in verifying HTTPS support, varying based on SSL certificate existence and validity. Successful ruleset creation and testing in Firefox and Chrome, adhering to stylistic standards, demonstrated the potential for effective development. The paper explores improving productivity through alternative libraries like Scrapy and Scrapy Cloud. While certain goals, such as in-depth cryptocurrency analysis and web crawler background reading, were unmet due to time constraints, valuable insights were gained. The conclusion underscores the difficulties, successes, and promises of automating ruleset generation through web crawlers for “HTTPS Everywhere,” offering valuable recommendations for advancing web security.
Emerging immunological challenges in post-COVID individuals: insights from a case series and review
Authors: Karmakar Saurabh , Sharma Priya
Published: July 2024

The Coronavirus Disease 2019 (COVID-19) pandemic has unveiled diverse immunological complications extending beyond the acute phase of infection. We present a case series of four patients who developed autoimmune vasculitis and sarcoidosis post-recovery from COVID-19. Case presentations include recurrent fever and respiratory symptoms in a 36-year-old female, granulomatous liver lesions in a 63-year-old male, progressive dyspnea in a 44-year-old female, and diffuse alveolar hemorrhage in a 74-year-old female following severe pneumonia. These cases underscore the importance of vigilance for immunological sequelae in post-COVID-19 patients, particularly those with predisposing comorbidities. We tried to elucidate pathophysiological mechanisms and optimize management strategies for these rare but clinically significant manifestations.
Measurement and optimization of nonlinear damping systems for agricultural engineering vehicle cab
Authors: Zhang Xin , Liu Yuanyou , Li Zhanlong , Xiao Zengliang
Published: July 2024

The issue of nonlinear dampness in the cab of agricultural engineering vehicles is examined by analyzing the vibration reduction system of a specific agricultural loader. Firstly, the specific loader was tested under different conditions. Then, the nonlinear vibration reduction system model of the cab–seat–human body is established by using the measured frame vibration signal as input. Finally, the multi–objective genetic algorithm is used to optimize the root mean square (RMS) value of vertical acceleration of the cab and seat. The test results show that the seat vibration is significantly greater than the acceleration of the cab floor under driving and working conditions, so the seat vibration is amplified and the seat parameter setting is unreasonable; the engine and the working device are also an important part of the cab vibration source, in addition to the uneven road surface. Comparing the RMS values of the vertical acceleration of the cab and seat, which were calculated by the model and obtained from the vehicle test, the error does not exceed 6%, indicating that the model’s accuracy meets the requirement. The vehicle experiment proves that the RMS value of the vertical acceleration of the cab and seat is reduced by 16% and 53%, respectively, after optimization. This study provides a theoretical basis for the design of the damping system for the cab of agricultural engineering vehicles.
The Antibacterial Activity of Lactophenol, Safranin, and Methyl Red Dyes Against Clinically Isolated Escherichia Coli
Authors: Ahmeed Haneen Waheed , Al-Khikani Falah Hasan Obayes , Khudair Khadeeja Kareem
Published: July 2024

Abstract

Background:

Escherichia coli(E. coli) is a type of bacteria commonly found in the intestines of humans and animals that can be pathogenic and develop resistance to various antibiotics through different mechanisms, making them difficult to treat with standard therapies. So using alternative strategies to treatE. coliis urgent, such as utilizing certain dyes that may be a promising branch in microbial therapy.

Materials and Methods:

The bacteria (E. coli) were isolated from the urinary tract and cultured in three media (blood agar, macConkey agar, and EMB agar), then they were incubated for 24-h at a temperature of 37°C to grow. Well diffusion method used to evaluate the antimicrobial activity of lactophenol, methyl red, and safranin stains. The antibiotic discs (Gentamicin) were used by the disc diffusion method. All the statistical analysis was done by using SPSS 26 software and the Excel app.

Results:

The participants in this study were 66.67% women, while 33.33% were men, with significant differences (P< 0.05). Gentamicin showed high a rate of sensitivity (88.89%). All isolates ofE. coli(100%) were sensitive to lactophenol; in contrast, all isolates (100%) were resistant to methyl red dye.E. coliisolates revealed 55.56% resistance to safranin.

Conclusions:

Lactophenol inhibition zone was 20.78 ± 5.40 mm, which revealed a great inhibition zone compared to gentamicin’s 17.22 ± 6.55 mm with no significant differences (P= 0.22). That means lactophenol is equal in activity to gentamicin to treatE. coli.
Sealing efficacy of various rubber dam barrier materials used for isolation procedures: A randomized controlled trial
Authors: Patel Jaimini J. , Shah Nimisha Chinmay , Janani Krishnamachari , Mahalaxmi Sekar , Porwal Priya S. , Jain Aishwarya D.
Published: July 2024

Aim:

The aim of the study was to assess the sealing efficacy of three dam seal materials.

Methods:

Ninety participants were enrolled after obtaining consent. After the placement of rubber dam (RD), a stream of air was applied at the interface area and visualized at ××6 magnification to identify sealing ability. Dam seal materials were divided into Group A: Liquid Dam, Group B: Kool-Dam, and Group C: OraSeal caulking putty substance. Leakage was assessed using self-designed criteria such as sealing ability, retention, ease of adaptability, and removal. The data were tabulated and analyzed using IBM SPSS 20 software.

Results:

Kool-Dam (Group B) demonstrated superior effectiveness in controlling saliva seepage around the clamp and teeth (P = 0.039) compared to other groups. In addition, it was evident that Kool-Dam (Group B) had greater effectiveness as compared to Liquid Dam and OraSeal (Group C) with relation to the retention of dam seal material (P = 0.039). There was no statistically significant difference (P < 0.05) in the ease of adaptation or removal of dam seal material.

Conclusion:

This study highlights the importance of dam seal materials as an adjunct material to establish a tight seal over a RD placement. From the present study, it was evident that Kool-Dam exhibited superior performance over Liquid Dam and OraSeal dam seal material in terms of better sealing ability and retention of the dam seal materials.
Difficulties in clinical nursing education: perspectives of nurse educators in a selected faculty of nursing
Authors: Salem Mohamed Z. , Mohamed Sayeda M. , Ayoub Amany S.
Published: July 2024

Background

Clinical education is an essential part of nursing education. It aims to prepare students to be able to provide safe and quality nursing care. However, despite its significance, it carries many difficulties for responsible nurse educators due to its unique nature.

Aim

To determine the difficulties of clinical nursing education from nurse educators’ perspectives.

Design

A descriptive design was used.

Setting

The current study was conducted at the Faculty of Nursing, Cairo University.

Sample

A purposive sample consisting of 180 nurse educators who met the inclusion criteria were included in the study.

Tools

(a) Nurse educator’s characteristics sheet and (b) difficulties in clinical nursing education from perspectives of nurse educator’s questionnaire.

Results

The study results revealed that the difficulties from the perspectives of nurse educators included students/educator ratio (48.9%), availability of conference rooms (57.2%), availability of sufficient numbers of clinical settings (51.1%), availability of changing rooms for faculty staff members (48.9%), availability of needed supplies and equipment for training (45.0%), and overcrowding as a result of presence of students from other programs that result in lack of learning opportunities (46.7%).

Conclusion

There are many difficulties in clinical nursing education from the perspective of nurse educators. On top of these difficulties were the increasing number of students and the lack of educational facilities in clinical settings.

Recommendation

Faculty administration should plan carefully in relation to student/educator ratio as well as provide adequate facilities and resources to achieve educational objectives.
The Fukuda stepping test is associated with various patterns of displacement
Authors: Paquet Nicole , Michaud Lucas , Lajoie Yves
Published: July 2024

Objective:

This study was to characterize individual path trajectories during the 50-step Fukuda stepping test (FST) and to determine the impact of step height on these trajectories.

Methods:

Kinematic data from the shoulders and feet were recorded in 12 young healthy adults while performing the FST at a comfortable step height (CoStep) and while stepping with lifting the knees high (HiStep). Path trajectories were depicted by step-by-step displacement of the right and left toes, and body rotation was obtained from the rotation of the shoulders. The effect of step height on the distance traveled and the final anteroposterior (AP) and mediolateral displacements and rotation were determined with paired t-tests.

Results:

Path trajectories were composed of various combinations of forward displacement, lateral deviation, and rotation to the left or right. In comparison with CoStep, the mean AP displacement and mean distance traveled were significantly shorter in HiStep (P < 0.05) while the mean rotation was significantly larger in HiStep (P < 0.05), but the displacement patterns were not modified.

Conclusion:

We found that the path trajectories vary greatly among participants, and that step height has a significant impact on the magnitude of displacements and rotation during the FST.
Effect of auditory memory load on speech-evoked P300 in healthy adolescents
Authors: Ranjan Rajesh , Bhat Jayashree S. , Kalaiah Mohan Kumar
Published: July 2024

Background:

The P300 is a late cortical neurophysiological response that can be elicited with auditory and visual stimulation, by presenting the stimuli in an odd-ball paradigm. When deviant stimuli are elicited using auditory stimuli, the P300 is recorded as a large positive peak approximately 300 ms after the stimulus onset in the waveform. Adolescent brain development is heavily influenced by hormonal and physical transitions. Most of the investigations have been done in children and adults, with a limited focus on adolescents. Hence, there is a need to understand the characteristics of P300 in this group.

Objective:

The current research was planned to measure the effect of auditory memory load on speech-evoked P300 in healthy adolescents.

Methods:

A total of 14 late adolescents aged between 18.1 and 24 years participated in the study. The P300 was used to record speech stimuli in N-back (zero-back, one-back, and two-back) tasks using 64 channels.

Results:

There was a significant difference in the latency and amplitude of P300 across the N-back tasks. The mean amplitude of P300 was the highest in a zero-back task and the lowest in a one-back task, and the mean latency of P300 was the lowest in a zero-back task and the highest in a one-back task.

Conclusion:

Prolonged latency and smaller amplitude of the P300 as the N-back difficulty level increased from zero-back to one-back and then two-back tasks in healthy adolescents.
Role of adaptive radiotherapy during concomitant chemoradiotherapy for limited-stage small-cell lung cancer
Authors: Ozdemir Beyza Sirin , Yavuz Ali A
Published: July 2024

Background:

Tumor shrinkage is frequently observed during conventionally fractionated chemoradiotherapy for limited-stage small-cell lung cancer (SCLC). The specific goals of this study are to evaluate the gross tumor volume (GTV) changes due to treatment-induced tumor reduction during the course of radiotherapy (RT) and to examine its potential use in adaptive radiotherapy (ART) for tumor dose escalation or normal tissue sparing in patients with SCLC.

Materials and Methods:

A total of 10 patients with SCLC eligible for chemoradiotherapy underwent computed tomography (CT) scan after Fractions 13 and 23 (at nominal doses of 23.4 Gy and 41.4 Gy, respectively). The GTV was delineated on the repeat CT scans, and two treatment plans were generated with or without adaptation to tumor shrinkage during RT for each patient. Dosimetric and volumetric analyses were performed.

Results:

The average GTV reduction observed over 13 fractions was 58.5% (range: 13.2%–92.3%; P < 0.001) and over 23 fractions was 70% (range: 36.9%–84.5%; P < 0.001). Compared with the plan without adaptation, ART resulted in mean lung dose relative decreases of 8.7%, mean lung volume receiving ≥20 Gy relative decreases of 5%, mean lung volume receiving ≥5Gy relative decreases of 10%, mean medulla spinalis dose relative decreases of 21 cGy, mean esophagus volume receiving ≥50 Gy relative decreases of 19%, and mean heart volume receiving ≥42 Gy relative decreases of 13%. The benefits of ART were the greatest for tumor volumes ≥30 cm3 and are directly dependent on GTV reduction during treatment.

Conclusion:

ART for SCLC achieved a significant benefit in terms of organ at risk (OAR) and dose escalation.
Exploring risk factors and determinants: A scoping review of factors associated with nomophobia
Authors: Rajguru Akanksha J. , Mishra Ashwani K. , Bhargava Rachna , Sarkar Siddharth , Balhara Yatan Pal Singh
Published: July 2024

Background:

Nomophobia or no-mobile-phone phobia, defined as the fear of being unable to use or being unreachable via one’s mobile phone. The pervasive concern has varied bio-psychosocial and clinical implications in an individual’s life. Nomophobia is currently in an exploratory phase.

Methods:

A scoping review was conducted to systematically map the relevant evidence and literature on nomophobia. The review of scholarly literature spanning from January 2010 to May 2023 employed a narrative synthesis methodology to succinctly encapsulate the research findings. Additionally, it encompassed a meticulous examination and visual representation of studies, detailing both the frequency of investigation into specific variables and the instances in which said variables exhibited a statistically significant association with nomophobia.

Results:

A thorough examination of 92 studies revealed a total of 133 variables spanning demographic, lifestyle-related, academic, smartphone-related, psychosocial, and clinical domains. Notably, 42.86% of these variables have only been investigated in a single research study, underscoring the imperative for replication to enhance the generalizability, validity, and applicability of research findings. Moreover, the review identifies Nomophobia Questionnaire (NMP-Q) by Yildirim and Correia as the most widely used tool for measuring the severity of nomophobia.

Conclusion:

There is a crucial need for homogeneity and consistency in reporting nomophobia scores and establishing corresponding gradations indicative of functional ramifications or clinical severity of nomophobia. The findings elucidate significant research gaps in existing literature on nomophobia, hold implications for further synthesis of data, and contribute to a comprehensive understanding of nomophobia; ensuring superior diagnostic accuracy and precision, and facilitating successful delivery of targeted interventions.
Assessment of Severity of Substance use for Outcomes Research and Treatment (ASSORT): A substance use severity scale developed and validated across six tertiary care centers in India
Authors: Basu Aniruddha , Bhad Roshan , Bharadwaj Balaji , Bharti Ayushi , Choudhury Shinjini , Das Prioma , Dinesh M. , Guin Aparajita , Joshi Tanmay , Krishnan Vijay , Kumar Pankaj , Mansoori Saba , Mishra Ashwani Kumar , Nebhinani Naresh , Rajpurohit Surendra S. , Ranjan Rajeev , Sarkar Siddharth , Shekhar Saurabh , Singh Pranshu , Sood Esha , Swami Mukesh K.
Published: July 2024

Background and Aims:

Assessment of the severity of substance use disorders (SUDs) in a culture-sensitive manner can help gauge the current condition of the substance user and assess change with time. The present study aimed to develop a scale for the assessment of the severity of SUDs in the Indian clinical context.

Methods:

Based upon the review of literature on previously available instruments and a consultative meeting of experts, a clinician-rated scale was developed that finally comprised 41 items. A briefer 5-item scale with current and lifetime versions was also developed. The scales were applied to patients with SUDs at six different clinical sites.

Results:

The instrument was applied to 720 patients (98.2% males, mean age: 34.6 years). The Cronbach’s alpha of the full scale was 0.852. The inter-rater reliability Pearson correlation coefficient of the full-scale was r = 0.821 (P < 0.001), and the intra-class correlation coefficient single measure was 0.800 (95% confidence interval: 0.724–0.956). A four-factor solution was suggested to be the most tenable. The mean application duration of the full scale was 13.4 minutes, and that of the briefer version was 2 minutes.

Conclusion:

This validated scale could be a potentially useful assessment measure for the severity of SUDs in the Indian context. The utility lies in the simplicity of administration and scoring and the balance between brevity and thorough assessment.
Welcoming the new, revisiting the old: a brief glance at cytopathology reporting systems for lung, pancreas, and thyroid
Authors: Luis Rita , Thirunavukkarasu Balamurugan , Jain Deepali , Canberk Sule
Published: July 2024

This review addresses new reporting systems for lung and pancreatobiliary cytopathology as well as the most recent edition of The Bethesda Reporting System for Thyroid Cytopathology. The review spans past, present, and future aspects within the context of the intricate interplay between traditional morphological assessments and cutting-edge molecular diagnostics. For lung and pancreas, the authors discuss the evolution of reporting systems, emphasizing the bridge between past directives and more recent collaborative efforts of the International Academy of Cytology and the World Health Organization in shaping universal reporting systems. The review offers a brief overview of the structure of these novel systems, highlighting their strengths and pinpointing areas that require further refinement. For thyroid, the authors primarily focus on the third edition of The Bethesda System for Reporting Thyroid Cytopathology, also considering the two preceding editions. This review serves as an invaluable resource for cytopathologists, offering a panoramic view of the evolving landscape of cytopathology reporting and pointing out the integrative role of the cytopathologist in an era of rapid diagnostic and therapeutic advancements.
Prawna ochrona dziedzictwa naturalnego w Polsce – wyzwania i perspektywy
Authors: Zębek Elżbieta
Published: July 2024

Przedmiotem artykułu jest stan prawny i stan ochrony obiektów dziedzictwa naturalnego wpisanych na Listę światowego dziedzictwa UNESCO w Polsce. W skład dóbr naturalnych wpisanych na Listę wchodzą dobra przyrodnicze i krajobrazy kulturowe jako obiekty towarzyszące zabytkom. Prawna ochrona zasobów przyrodniczych i krajobrazowych jest uregulowana głównie w ustawie o ochronie przyrody, ustawie o ochronie zabytków i opiece nad zabytkami oraz ustawie o planowaniu i zagospodarowaniu przestrzennym. Jednakże brak jest jednoznacznego wyodrębnienia ochrony dóbr przyrodniczych będących przedmiotem ochrony Konwencji UNESCO w sprawie ochrony światowego dziedzictwa kulturalnego i naturalnego w polskim systemie prawnym, co powoduje wiele problemów natury prawnej, związanych z ochroną tych dóbr, zarządzaniem nimi i ich monitoringiem. Konsekwencją takiego stanu może być degradacja dóbr przyrodniczych, w szczególności unikatowych siedlisk przyrodniczych, których prawnokarna ochrona jest niezadowalająca. W Polsce są tylko dwa obiekty dziedzictwa naturalnego – Puszcza Białowieska i pradawne lasy bukowe w Bieszczadzkim Parku Narodowym. Należy zatem dążyć do poszerzenia Listy światowego dziedzictwa, jednakże wcześniej należy rozważyć wzmocnienie ochrony prawnej takich obiektów w ustawie o ochronie przyrody poprzez wyodrębnienie tej formy lub ustanowienie odrębnych aktów prawnych, regulujących użytkowanie i ochronę takich obiektów. Tylko ochrona prawna na poziomie krajowym będzie najskuteczniejsza.
Wykonanie zastępcze jako środek ochrony bezpieczeństwa obywateli i zabytków nieruchomych przed zniszczeniem
Authors: Lis Wojciech
Published: July 2024

Funkcjonowanie społeczeństwa w ramach organizacji państwowej wiąże się z wieloma obowiązkami i ograniczeniami, które są konsekwencją uwzględniania przez władze publiczne różnych wartości. Należą do nich: zapewnienie ochrony własności prywatnej, której przedmiotem są obiekty zabytkowe, bezpieczeństwo fizyczne wszystkich, którzy przebywają na terytorium państwa, oraz strzeżenie dziedzictwa narodowego, którego częścią są zabytki nieruchome. Nie zawsze zabytki te są odpowiednio zabezpieczone przed zniszczeniem lub uszkodzeniem, co stanowi zagrożenie dla bezpieczeństwa ludzi i dla bezpieczeństwa kulturowego. Wzgląd na ochronę tych wartości uzasadnia wkroczenie państwa w prawo własności w przypadku zagrożenia zabytków nieruchomych zniszczeniem lub uszkodzeniem, czemu służy instytucja wykonania zastępczego. Celem artykułu jest próba udzielenia odpowiedzi na pytanie, czy przeprowadzenie niezbędnych prac konserwatorskich i robót budowlanych w ramach wykonania zastępczego jest skutecznym środkiem ochrony zabytków nieruchomych w kontekście obowiązku zapewnienia przez państwo bezpieczeństwa obywateli i strzeżenia dziedzictwa narodowego.
Savaş Gibiydi: Sağlık Bilimlerinde Çalışan Kadın Akademisyenlerin COVID-19 Pandemisi Döneminde Rolleri ile İlgili Deneyimleri Üzerine Nitel Bir Çalışma
Authors: Çelik Nigar , Güçlü Sultan
Published: July 2024

Amaç: Çalışmada sağlık bilimlerinde çalışan kadın akademisyenlerin Koronavirüs (COVID-19) pandemisi sürecinde evden çalışmanın yaşamları üzerine etkisinin incelenmesi amaçlanmıştır.
Gereç ve Yöntem: Nitel araştırma tasarımlarından fenomenolojik yöntem kullanılmıştır. Örneklemi COVID-19 pandemi sürecinde uzaktan çalışan 15 kadın akademisyen oluşturmuştur. Veriler “yarı yapılandırılmış görüşme” formu ile toplanmış, “içerik analizi” ile değerlendirilmiştir. Verilerin değerlendirilmesinde tematik yaklaşım kullanılmıştır. Çalışma “Consolidated criteria for reporting qualitative research” kriterlerine göre gerçekleştirilip raporlanmıştır.
Bulgular: Tematik yaklaşıma göre dört ana tema altında 13 alt tema belirlenmiştir. Temalar sırasıyla “salgına hazırlıksız yakalanmak”, “savaş gibiydi”, “fizyolojik ve psikolojik tükenmişlik”, “deneyimlerden öğrenme” olarak adlandırılmıştır.
Sonuç: Çalışmada sağlık bilimlerinde çalışan kadın akademisyenlerin COVID-19 pandemi sürecinde fiziksel, psikolojik, sosyal ve akademik açıdan çok yönlü etkilendikleri tespit edilmiştir. Toplumsal cinsiyet rollerindeki eşitsizlikler nedeni ile aile rolleri ve akademik rolleri arasında çatışma yaşadıkları, her konuda kendilerini yetersiz hissettikleri, akademik verimliliklerinin azaldığı gözlemlenmiştir. Salgın sürecinde sağlık politikaları ile ilgili planlamalar yapılırken cinsiyete özgü etkilerin göz önünde bulundurulması, kadınların desteklenmesi, kadının toplumdaki konumunun ve sağlığının iyileştirilmesi açısından önemlidir.