bluuebunny/crossref_metadata_2025 huggingface dataset:
The Scholarly Ustad: Hindustani Music's Muslim Hereditary Professionals and Their Textual Traditions
Authors: Katz Max
Published: July 2024

Hindustani music's Muslim hereditary professional performers—known as ustād-s—have long been depicted as essentially nonliterate. Colonial and nationalist texts condemned the ustads for their ignorance and illiteracy; latter-day ethnomusicological texts celebrate the same ustads for their orality and embodiment. Based on original translations of twentieth-century sources in Urdu, Hindi, and Bengali, this article highlights a contrasting dimension of the Muslim hereditary tradition in Hindustani music: a three-hundred-year commitment by the ustads themselves to the saṅgītaśāstra, a succession of technical musical treatises traceable to antiquity.
Music, Shared Histories, and Futures in Toyama City, Japan: Owara Kaze no Bon and Celebrating a New Tram Connection in the Early Pandemic
Authors: Scally W. Donnie
Published: July 2024

The full impacts of the Covid-19 pandemic on musical life are not yet understood. This article draws on eleven years of contact with Toyama City, culminating in eight months of in-person fieldwork beginning in August 2019, and subsequent analysis of online materials. I discuss Covid-19’s interruptions to local music festivals and the social implications of these interruptions. I argue that responses to the pandemic exemplified by these festivals reveal ongoing divisions between Toyama City's older and younger and rural and urban residents. This article contributes to emergent ethnomusicological literature considering the pandemic's varying local expressions.
“Systems Are Changeable”: Reading Moments through Movements
Authors: Ouyang Lei X
Published: July 2024

This article considers how recent moments of racism and violence in the United States, ethnomusicology, and the Society for Ethnomusicology are linked to larger movements. I examine the work of Asian American and Asian Canadian artists and activists to engage with conversations about violence, racialization, and solidarity. I bring these conversations in concert with recent discussions of racism in music studies to connect moments to movements and examine models for change through processes of decolonization. I call upon readers to embrace discomfort, listening, and reflection to engage with work that is relational and intergenerational and that demonstrates hope, care, and solidarity.
SPECTRUM OF CONGENITAL HEART DISEASE DIAGNOSED BY ECHOCARDIOGRAPHY EVALUATION IN NEONATES PRESENTING TO TERTIARY CARE HOSPITAL
Authors: KHAN I , AYESHA . , MUHAMMAD A
Published: July 2024

Neonatal morbidity and mortality are significantly impacted by congenital heart disease (CHD). Echocardiography plays a crucial role in this condition's early diagnosis and management. This research aims to determine the prevalence of CHD diagnosed by echocardiography among neonates admitted to Lady Reading Hospital (LRH), Peshawar. Objective: To identify the rate and variety of CHD in neonates using echocardiography. Methods: A prospective study was conducted in the Department of Pediatrics at LRH Peshawar from January 2023 to January 2024. The study included 100 neonates up to 28 days old with clinical manifestations of CHD. Routine echocardiographic examinations were performed for diagnosis. Descriptive statistics were used to determine the prevalence and type of CHD, while inferential statistics compared means, standard deviations, and p-values. Results: Out of 100 neonates, 72 were diagnosed with CHD. The mean age was 15 days (± 7 days). The most frequently reported defect was ventricular septal defect (VSD), observed in 35% of cases. Atrial septal defects (ASD) were seen in 20% of cases, tetralogy of Fallot (TOF) in 10%, and transposition of the great arteries (TGA) in 8%. The p-value for the prevalence of CHD in males compared to females was 0.03, indicating a significant difference. Conclusion: CHD is relatively frequent in neonates, and neonatal echocardiography is a valuable tool for early diagnosis. Early detection allows for timely management, improving prognosis in affected infants.
Augmented Reality Introduction To Cirebon Mask At Setia Darma Mask House Gianyar
Authors: Ariantini Made Suci , Rajasyah Alfatino Yohan , Ariasih Ni Kadek , Indradewi I Gusti Ayu Agung Diatri , Parwita Wayan Gede Suka
Published: July 2024

This research aims to explore the application of Augmented Reality (AR) technology in the context of introducing Cirebon Masks at the Setia Darma Mask House, Gianyar using Marker Based. Cirebon masks have high cultural and artistic value in traditional Indonesian art, and the Setia Darma Mask House is an important place in introducing and preserving this art to the wider community. Using AR as a tool, this research investigates ways in which this technology can be used to provide visitors with an interactive and immersive learning experience about Cirebon Masks. The research methodology involved developing a custom AR application that allows users to see, hear, and interact with a virtual representation of the Cirebon Mask. Data was collected through observation, interviews and literature study to evaluate the effectiveness of the application. From the test results of 8 tests on the menu in the system using the black box testing method, the system is in accordance with the expected results, namely there are no errors when the system is used. the results of usability testing with the values obtained, namely Application Learnability is 89.4% which means Very Good, Efficiency gets 89.8% which means Very Good, Memorability gets 91.7% which means Very Good, Error gets 63.7% which means Fairly Good and Satisfaction gets 90, 1% which means Very Good
Encoding images to 3D by sequential model with single target feature extractor
Authors: Luo Chengchao
Published: July 2024

Assisted driving is a necessary way to realize autonomous driving, in which bird's-eye-view (BEV) is an ideal solution to perceive the targets around the body, i.e., the information acquired by the sensors of the body is extracted and semantic features are integrated into the BEV plane for downstream tasks such as target detection, scene segmentation, and path planning, etc. BEV-based pure vision target detection refers to the use of ordinary cameras without relying on other sensors to perceive the targets around the body. BEV-based pure visual target detection, on the other hand, refers to the use of ordinary cameras to perceive targets around the body without relying on other sensors, and Lift Splat Shoot (LSS) is a more typical solution among the existing schemes. Since the information obtained by each camera in assisted driving is always continuous, incorporating the temporal information into the model can achieve better detection results. We design the model (Sequential and Single Target based LSS) SSTL, and the experiment proves that our model has a certain performance improvement based on the original model.
Systematic analysis of hyperspectral imaging and intelligent sensor systems in multiscale agriculture
Authors: Zhang Yinan
Published: July 2024

This article delves into the systematic analysis of Hyperspectral Imaging Technology (HSI) and Intelligent Sensor Systems in the context of multiscale agriculture, showcasing their critical role in enhancing efficiency and sustainability in agricultural production amid the challenges posed by global population growth. It highlights the pressing need to optimize agricultural processes through advanced technologies to tackle issues such as resource scarcity and environmental pollution. By presenting case studies, the article illustrates the effective integration of HSI and intelligent sensors in key agricultural processessoil analysis, crop monitoring, and pest detectionunderscoring their significance in advancing precision agriculture. The discussion extends to the potentials of data fusion and decision support systems in elevating crop yield and quality. Concluding, the paper emphasizes that despite facing hurdles like technical barriers and maintenance costs, the application of these technologies not only boosts production efficiency and precision but also contributes to agricultural sustainability, underlining the importance of continued research and innovation for a more sustainable and efficient agricultural future.
Laddernet retinal vessel segmentation algorithm fusing attentional mechanisms
Authors: Tan Hui , Gan Caijun
Published: July 2024

A retinal blood vessel segmentation algorithm fusing the attention mechanism is proposed to address the problems of insufficient accuracy and incorrect segmentation of minutiae in existing retinal blood vessel segmentation algorithms. The network structure used in this algorithm is Laddernet (LCT-UNet for short), which fuses the Convolutional Block Attention Module (CBAM) and Transformer, i.e., the residual module of Laddernet, which shares the weights, is structurally optimised to decrease the parameter count; After the residual module, CBAM is incorporated to adaptively adjust the weights of channels and spatial features to enhance the feature representation; Transformer with global self-attention mechanism is introduced at the bottom of the network to overcome the shortcomings of UNet's inability to model long-range relationships and spatial dependencies, and gradually refine the features so that the segmentation results have finer boundary and detail information. The model validity was verified on the public datasets DRIVE and CHASEDB1, and the experimental results showed that the ACC of LCT-UNet was 95.81% and 96.88%, SE was 79.74% and 81.12%, SP was 98.15% and 98.83%, and AUC was 98.22% and 98.99%, and the F1 values were 82.88% and 85.14%, respectively, and the comprehensive segmentation performance of the LCT-UNet network showed significant enhancement over the algorithms such as U-Net, R2UNet, and Laddernet.
Challenges and strategies of software engineering in big data environment
Authors: Cheng Bruce
Published: July 2024

Software engineering in a big data environment involves developing and maintaining large-scale, scalable, data-intensive applications in a rapidly evolving technology domain. As data volumes grow exponentially, so do the requirements for software systems to process and analyze this data. These systems need to be able to efficiently store, retrieve, process and analyze data collected from sources such as social media, IoT devices, enterprises and scientific research. Software engineers must address challenges including data heterogeneity and quality, scalability of data storage and computation, and real-time processing of high-speed data streams. With the evolution of technology, new architecture and database technologies have emerged, such as NoSQL and distributed computing frameworks. These technologies have challenged traditional methods of software engineering practice and also brought new design and implementation strategies.
Surgical robot open surgery trajectory planning based on machine vision and improved genetic algorithm
Authors: Chen Zhenggang
Published: July 2024

Aiming at the difficulty of trajectory planning for open surgery of surgical robot, a method based on machine vision and improved genetic algorithm is proposed to solve the trajectory planning of open surgery of surgical robot. This method extracts the contour curve of the incision site of human open surgery from the image through the feature recognition algorithm, and discretizes it into the trajectory planning stage. Based on the discretized model, the optimal surgical incision trajectory is obtained. Combined with the biological characteristics of the human abdomen and the improved genetic algorithm (GA), the spline curve is segmented trajectory planning, and the minimum number of segments is optimized. Finally, the trajectory planning results are converted to Cartesian space for programming according to the spatial pose relationship, and the optimal surgical trajectory is obtained to realize the preoperative planning of the content of open surgery.
Se-PSD: A sequence-based parking-slot detection approach for indoor parking
Authors: Zhang Jiaxin
Published: July 2024

Accurate parking slot detection is crucial for autonomous vehicles to navigate automatic parking. In recent years, significant progress has been made in research in this field, with some methods achieving high accuracy and efficiency on specific datasets. However, existing methods still face some challenges in practical applications, such as: when the ground reflection covers the parking-slot marking lines, the recognition accuracy of existing methods will significantly decrease; The generalization performance of existing methods is not strong enough, and the recognition accuracy will decrease after changing the place or camera model. To address these limitations, this paper introduces Se-PSD, a novel parking slot detection method utilizing image sequences. Se-PSD analyzes a series of images to predict individual marking point locations, shapes, and orientations. Finally, through geometric rules, parking-slots can be found on the last image of the image sequence. Se-PSD prioritizes generalizability without sacrificing accuracy compared to existing methods. While real-time performance may be slightly impacted, the relaxed time constraints of automatic parking applications make Se-PSD a promising solution.
Comparative analysis and prospect of RNN and Transformer
Authors: Li Xingyu
Published: July 2024

Deep learning techniques have emerged as a key catalyst for innovation in the rapid advancement of artificial intelligence and machine learning. Deep learning has significantly transformed the field of natural language processing (NLP) and voice processing. It has revolutionized the processing and comprehension of linguistic data, leading to advancements in various applications, ranging from simple text categorization to intricate speech recognition. The progress made in this area would not have been feasible without the utilization of two crucial neural network models: the Recurrent Neural Network (RNN) and the Transformer. These models, with their distinctive processing skills, have attained significant accomplishments in the domains of NLP, computer vision, and several other sectors. Nevertheless, although they demonstrate exceptional performance in their specific application scenarios, there are notable distinctions in processing techniques, performance enhancement, and application range. This study aims to thoroughly investigate and compare the efficacy of two models, namely RNN and Transformer, in processing natural language and speech data. This will be achieved using the research methods of literature analysis and literature review. Through the analysis of their structures, strengths, flaws, and performance in practical applications, it offers a more comprehensive viewpoint and benchmark for future study and applications. As technology advances, we anticipate the emergence of more novel models and methodologies in the field of natural language processing and voice processing. This will further facilitate the development of these technologies.
Control system for automatic adjustment of departure intervals of public transport vehicles
Authors: Fan Yichen
Published: July 2024

In numerous urban areas, fine-tuning bus schedules to align with fluctuating passenger numbers poses a sizable challenge, compounded by diverse factors such as weather and unexpected events. This paper conducts a comprehensive examination of existing optimization methods aimed at enhancing the departure intervals of public transport systems, particularly focusing on the Bidirectional Coordination Optimization Algorithm (BCOA) and the genetic algorithm. Through systematic analysis, these methodologies are meticulously explored for their effectiveness in addressing the scheduling challenges faced by urban transit systems. Additionally, it delves into specific instances where the Proportional-Integral-Derivative (PID) control mechanism has been employed to adeptly adjust the timing of bus departures based on real-time demand. The PID system's proven reliability and efficacy spotlight its potential as a transformative tool for advancing public transit systems. By leveraging such technology, there's tangible optimism for achieving a more responsive, efficient, and passenger-friendly public transportation network in the years to come.
Automatic dressing change and monitoring infusion speed control system
Authors: Song Siying
Published: July 2024

Intravenous drip is a common form of treatment, but the wrong rate of injection or dose of medication can have serious consequences for patients. Monitoring devices can detect the speed of drug infusion and drug response in real time, helping medical care personnels adjust treatment regimens in a timely manner and reduce the risk of human error. At present, some rooms in the Intensive Care Unit (ICU) require a sterile environment. In view of the above situation, this paper proposes a new device, which adds the function of automatic dressing change to the intravenous injection monitoring device, and synchronizes the obtained data to the user interface in real time by using the Internet of Things (IoT), so as to reduce the frequency of medical staff entering and leaving the ICU, realize remote monitoring of the intravenous injection process and data related to automatic dressing change, and improve the treatment effect of patients and the work efficiency of medical staff.
Balancing performance and efficiency: A CNN-LSTM hybrid model for sentiment analysis
Authors: Zeng Yizhen
Published: July 2024

In the era of rapid e-commerce and social networks, the recognition of textual emotion has garnered escalating interest in recent years. This area of study proves pivotal for applications such as content recommendation and human-robot interaction. Prominent models such as CNN, LSTM, and Roberta have been used in natural language processing to decipher the subtleties of textual emotion. Despite the commendable accuracy achieved by Roberta, its extensive model parameters come at the cost of sluggish training speeds. To address this issue, we propose a novel hybrid approach that integrates Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks. We employ this hybrid model to address the emotion classification problem using a dataset named "Emotion", and we compare its performance with that of individual models like Roberta, CNN, and LSTM. The new hybrid model exhibits a more compact architecture while maintaining a relatively high accuracy rate, boasting an impressive 91%. This hybrid architecture can provide a good compromise between efficiency and performance. This research contributes to the ongoing exploration of efficient and accurate models for textual emotion recognition, emphasizing the significance of balancing model complexity and training speed in practical applications.
Methods of information search for unstructured data
Authors: Ауезова А.С. , Муратова К.Н. , Синчев Б.
Published: July 2024

В статье предложен новый метод, применяемый для решения задачи информа- ционного поиска неструктурированных (текстовых) данных. Поиск документов осуществляется по ключевым словам, на естественном языке, применяемым в поисковых машинах. Таким образом, на основе полиномиальных алгоритмов создается универсальная машина выборки по нескольким клю- чам с улучшенными характеристиками по времени и пространству. Данная предлагаемая машина может быть применена для обработки больших данных в различных областях экономики. Для до- стижения цели в основе новых полиномиальных алгоритмов использована задача о сумме подмно- жеств, которая относится к классу NP-complete. Эти алгоритмы значительно эффективнее по времени и пространству существующих лучших полиномиальных и экспоненциальных алгоритмов.
Development of a client profile formation system based on Big data using semantic analysis
Authors: Нәдіров Н.Қ. , Дуйсебекова К.С.
Published: July 2024

По мере того, как бизнес-процессы становятся все более и более ориентирован- ными на клиента, чрезвычайно важны маркетинговые и управленческие отношения с клиентами, что заслуживает особого внимания с учетом глобализации и растущей конкуренции на рынке. На данном этапе возникает много всевозможных вопросов «Кто такие клиенты?» и «Как их иденти- фицировать?». В настоящее время «Какую информацию необходимо собирать о потенциальных клиентах?» и «Каковы сейчас уровни обслуживания?». Цель разработчика заглянуть в «голову» собственного клиента и осознать, чего он желает. Эти познания станут неоценимыми позднее, когда найденные данные и информация будут изучены, осознание всех задач и вопросов станет неотъемлемой частью успеха будущего проекта. В данной статье представлен способ подготовительной обработки данных для умственного изучения данных, доктрина использования, способы изучения больших размеров данных и извлечения полезной информации, содержащейся в них полезной информации для формирования профиля клиен-та.
Project Management: Communication challenges and Impacts
Authors: Омарова А.Ш. , Махбаева Ә.Н.
Published: July 2024

Коммуникация – это процесс получения всей соответствующей информации, ин-терпретации этой информации и эффективного распространения информации среди лиц, которые могут в ней нуждаться. Цель этой статьи состояла в том, чтобы определить, может ли комму-никация быть основополагающей областью управления проектами. Вторая цель состояла в том, чтобы определить, можно ли рассматривать коммуникацию как область, которая объединяет и координирует различные процессы по управлению проектами и в чем заключаются проблемы неэффективной коммуникации.
The impact of big data analytics on the effectiveness of project management processes
Authors: Момбекова А. , Бекболова М.Б.
Published: July 2024

Аналитика больших данных в процессах управления проектами может выявить несколько причин и последствий для влияния. Внедрение технологии больших данных - это новый шаг в научном и технологическом развитии, охватывающем различные сферы общества. Цель данного исследования - изучить и проанализировать влияние аналитики больших данных на процессы управ-ления проектами. Высокая корреляция между большими данными и машинным обучением требует дальнейшего исследования, которое включает более подробное исследование в таких областях, как влияние искусственного интеллекта на управление проектами и их взаимосвязь с большими данными.
АЛГОРИТМ АВТОМАТИЗАЦИИ КЛАССИФИКАЦИИ ФИНАНСОВЫХ АКТИВОВ ПРИ РОЗНИЧНОМ КРЕДИТОВАНИИ
Authors: Омарова Е.Г.
Published: July 2024

В статье представлен кейс по составлению алгоритма автоматизации класси-фикации финансовых активов при розничном кредитовании. Приведено заполнение спецификации основных бизнес требований, а также описан порядок разработки и внедрения в работу классифи-кации. В табличном виде составлен Справочник пулов в виде портфеля однородных кредитов. Блок-схема иллюстрирует сущность предложений авторов по автоматизации процесса группировки роз-ничных финансовых активов. С учетом технических особенностей и в целях реализации возможно-сти расчета объема провизий по однородным кредитам, необходимо на каждом конкретном пуле завести поля.
Instrumentos de avaliação: marcas de suas concepções no espaço escolar
Authors: Lacerda Mitsi Pinheiro de , Viana Rogério Tadeu Sá
Published: July 2024

O artigo reflete acerca de instrumentos de avaliação utilizados na escola e sua mediação junto à produção do espaço escolar. Busca ainda conhecer, nas relações sociais, os resquícios de concepções presentes na avaliação, quando tomada enquanto mensuração. O estudo foi desenvolvido desde os caminhos metodológicos dos estudos em cotidianos. Dentre os deslocamentos ocorridos na pesquisa, são apresentados um instrumento formal e um instrumento informal de avaliação. Os resultados apontam que, embora os instrumentos de avaliação não atuem soberanamente na produção de um espaço fragmentado e excludente, não há como desconsiderar sua atuação neste propósito. Ao pensar em uma escola que se constrói em bases democráticas e libertadoras, é preciso discutir acerca dos critérios com os quais as práticas, metodologias e instrumentos são estabelecidos, de forma a reconhecer, em sua gênese, as orientações que se deseja imprimir à produção do espaço escolar.
Paulo Freire: inspirações para pensar a educação da infância
Authors: Mesomo Lira Aliandra Cristina , Ferreira Rayane
Published: July 2024

O objetivo da reflexão foi conhecer as principais ideias de Paulo Freire e as recentes produções científicas inspiradas em sua pedagogia. Trata-se de pesquisa de natureza quanti-qualitativa, de caráter exploratório, por meio de estudo bibliográfico com levantamento de publicações de artigos científicos no Portal de Periódicos da Capes, com recorte temporal de 2013 a 2022. Paulo Freire não abordou especificamente a educação infantil na sua obra, entretanto, é possível afirmar que há nela uma conotação político-pedagógica apresentada de forma crítica muito interessante para pensar a educação da infância. Paulo Freire defende uma educação plural, democrática, libertadora e humanizadora, com a valorização do ser criança, de sua participação e do diálogo nos processos educativos.
Análise sobre o Teatro Brechtiano e sua influência em bodas de café: reflexões literárias, artísticas e didáticas
Authors: Demarchi André Luiz , Souza Ravelli Henrique de , Farias Eduardo Augusto , Furlan Marta Regina
Published: July 2024

O presente artigo tem por sustentação a reflexão acerca de elementos políticos presentes no texto dramático Bodas de café, produzido pela autora londrinense Nitis Jacon, em 1984. O ponto de partida para a reflexão sobre a peça é a teoria do teatro épico do dramaturgo alemão Bertolt Brecht, o qual se opõe ao teatro dramático, propondo a reflexão crítica por parte do espectador. Dessa forma o objetivo primário da pesquisa é promover uma reflexão das relações humanas com seu meio social no texto dramático, a trajetória do homem e suas transformações. E os objetivos secundários são destacar o trabalho de dramaturgia londrinense, que ainda é pouco pesquisado, e por fim, também contribuir para novas pesquisas acerca do tema dramaturgia londrinense. A pesquisa resgata uma grande época do teatro londrinense, em que se produzia e encenava textos teatrais com uma linguagem própria. Tanto o grupo PROTEU quanto a autora Nitis Jacon fizeram história e abriram caminhos para que Londrina se tornasse esse grande polo cultural e que ainda é pouco conhecido. E nela também enfatizamos a importância da liberdade com príncípio fundamental dos direitos humanos e educacionais.
Femoral Head Fractures: Evaluation, Management, and Outcomes
Authors: Schaffer Nathaniel E. , Luther Lauren , Tatman Lauren M. , Mitchell Phillip M.
Published: July 2024

Fractures of the femoral head typically occur after high-energy trauma. Radiographs and cross-sectional imaging are used to appropriately classify and identify associated injuries or morphologic characteristics that may influence management. Identification of the radiographic and clinical hallmarks of an irreducible variant is critical to optimizing the patient's outcome. Nonsurgical treatment can be used in the setting of small, infrafoveal femoral head fractures without hip instability. When surgical treatment is indicated, an anterior (Smith-Petersen), posterior (Kocher-Langenbeck), or surgical hip dislocation approach may be used depending on injury details and surgeon preference. The purpose of this review was to summarize current evidence on femoral head fractures regarding indications, variant patterns, surgical approaches, and outcomes.
Eating Habits and Lifestyle Practice of Young Adults in Karachi, Pakistan; a Cross-Sectional Survey
Authors: Irfan Fahima Mohammad , Irfan Faryal Muhammad , Rehman Sami ur , Faiz Aqsa , Afzal Mubushara , Ahmed Muhammad
Published: July 2024

Each year in Pakistan about 35% to 40% of deaths occur due to cardiovascular disease that is mainly caused by decreased physical activity and unhealthy food consumption. Obesity among young people is a serious public health issue because it is frequently associated with multiple metabolic syndromes. Objective: To determine young adults' eating habits and lifestyle practices and compare this among male and female genders. Methods: A total of 249 participants aged between 18 to 25 years young adults were recruited from different universities using a non-probability convenient sampling technique. The participants' eating habits and lifestyle practices were analyzed using a self-designed questionnaire. Results: Among 249 students, 43.8% were male 56.2% were female. Statistically, there was a significant difference found between the two genders in the consumption of water (p<0.001), and meal consumption daily (p=0.007), Eating habits after joining university (p=0.44), thinking of physically strong (p=0.001), Physical inactivity (p<0.001) and their preferred living place in leisure time (p<0.001). Conclusions: This study concluded that most of the female were involved in unhealthy dietary habits concerning skipping meals and having fast food, whereas there is no difference found between genders in their physical activity. However further research should be conducted to explore the relation of eating habits and lifestyle in gender
Perception of Student Nurses about their Clinical Learning Environment at Shaukat Khanum Memorial Cancer Hospital and Research Center Lahore
Authors: Ali Shazia Salamat , Munir Asim , Majeed Faisal , Ullah Saif , Rasool Ghulam , Hyder Ali
Published: July 2024

Student nurses perceive that learning environment is a clinical area where students can learn new things according to their set objectives and enhance their knowledge and skills, there are a lot of challenges that students face during clinical placement. Objective: To explore perception of student nurses about their clinical learning environment at Shaukat Khanum Memorial Cancer Hospital & Research Center Lahore. Methods: This study was a cross sectional survey conducted at Shaukat Khanum Memorial Cancer Hospital from May 2022 to June 2022. Interprofessional clinical learning environment inventory tool was used for data collection from 37 student nurses. Data analysis was done by SPSS version 20.0. P-value<0.05 will be considered as significant. Results: There were 14 males and 23 female student is current study. 79% of the students showed positive perception and only 21% shows negative perception about their clinical learning environment. More than 94% nurse students suggested that clinical orientation was relevant and well organized according to their objectives.56% Students during their clinical rotation felt that they belonged to the same clinical area and 89% reported that the behavior of that area staff was friendly. There was insignificant association between gender and Clinical Learning Environment (P-value>0.05). Conclusions: The students showed positive perception and satisfaction about the clinical learning environment which indicates that the clinical learning environment is crucial for nursing students, enhancing their clinical, communication, and problem-solving skills.
Social enterprises transformation and its effects on socio-economic development in developed and developing countries
Authors: Mito Hero Rana Barua , Qi Li , Akter Mousumi
Published: July 2024

In the twenty-first century, the idea of social enterprises influencing global socio-economic growth has gained much attention and has momentous implications for the modern economy. Both emerging and developed countries frequently observe its considerable impact on their economy as social enterprise transformation has such a wide-ranging effect on socioeconomic growth. The purpose of this study is to present evidence of the impacts of global social enterprise transformation on global socio-economic development. However, there are no official statistics available on the effects of the transformation of global social companies on global socio-economic development. The debate in this research demonstrates how social enterprise transform like a collaboration between the private, public, and civil sectors, continually honing their approach to their goals, based on the review of several case studies of social enterprises from around the world. Revamp, acquisitions, and improved performance are all efforts to achieve sustainable societal progress in the fields of economics, culture, and politics. The results indicate that social enterprises transformation causes the socio-economic development of the world. Our results also suggest that social enterprise transformation impact and outcome are more significant in developed countries than in developing countries.
La periodicidad: Significados desde su uso en la huerta escolar para la matemática escolar
Authors: Balda Paola , Buendía Ábalos Gabriela
Published: July 2024

Una de las tensiones en el discurso Matemático Escolar es la poca relación entre la matemática escolar y aquella propia de escenarios fuera de la escuela. Como estrategia para tratar esta situación proponemos un cambio que busca descentrar la mirada en el objeto matemático, hacia una centración en las prácticas de las cuales el objeto emerge, es decir, una base de significación fundamentada no en la matemática misma, sino en el saber considerado como conocimiento en uso. Se presenta el caso de la propiedad periódica y una epistemología de usos como antecedente; se analiza el uso de lo periódico en la huerta escolar considerándola como un contexto de significación.  Se da evidencia de cómo más allá de la aplicación del conocimiento, el uso significa al saber resultando en una forma funcional de ver, interpretar y dar sentido a la propiedad periódica. Se presenta entonces una propuesta centrada en un cambio epistemológico, la cual considera al uso del conocimiento como base de significación para la matemática escolar.
Clinical and Molecular Characterisation of Multi Drug Resistant Hypervirulent Klebsiella pneumoniae (MDR-HvKp) Isolated from Patient Attending ATBU Teaching Hospital Bauchi
Authors: Usman Nazeef , Umar Ahmed , Iliyasu Mahmud
Published: July 2024

Background and Aim: K. pneumoniae exhibits increasing multidrug resistance and a global rise in hypervirulent strains, particularly prevalent in various African countries, posing significant challenges in managing infections ranging from pneumonia to neonatal septicemia and urinary tract infections. The study aimed to identify and detect virulence characteristics of MDR-HvKp from clinical samples.
Method: Two hundred and fourteen (214) clinical samples were identified and drug resistance was measured using the Vitek 2 system, the isolates were phenotypically characterized for mucoviscosity and hypermucoviscosity using a string test and mucoid sedimentation test. The isolated K. pneumoniae were further assessed for the presence of rmpA, magA, BlaCTX-M, and BlaKPC-2 genes using PCR, Gel electrophoresis, and Sequencing, the rmpA gene sequence peculiar to K. pneumoniae was used for phylogenetic analysis using NCBI BLAST for nucleotide suite.
Result: Twenty-four (24) K. pneumoniae were identified, phenotypically and molecularly characterized for drug resistance and virulence genes. The prevalence of K. pneumoniae was recorded at 24(17.3%), with higher rates observed among females 15(10.79%) compared to male patients with 9(6.47%), while the difference in prevalence between genders was not statistically significant, p = 0.06 (χ2 = 2.59), this is also similar to marital status with p = 0.025 (χ2 = 5.37). A total of 11(45.83%) K. pneumoniae were isolated from urine 59(42.45%), which is the highest followed by sputum 29(20.86%), blood 26(18.70%), and swab 25(17.99%); HvKp strain Kp128 demonstrated mucoviscosity and carried genes associated with mucoid phenotype and resistance, Antibiotic susceptibility testing revealed resistance to several antibiotics, particularly beta-lactams and carbapenems.
Conclusion: The study reveals a rising prevalence of MDR-HvKp strains in Nigerian and Bauchi state in particular, emphasizing the critical need for effective management strategies against infections across diverse clinical settings.
Foliar Zinc Application Enhances the Grain Yield of Mungbean (Vigna radiata L.)
Authors: Rashid Md , Jahan Israt , Islam Md , Uddin Md , Sadia Halima , Ahmed Riad
Published: July 2024

Mungbean (Vigna radiata L.) is a legume widely recognized for diverse uses. Like other legumes, mungbean plants also possess a remarkable ability to interact with nitrogen-fixing bacteria by inhabiting plant roots. This experiment aimed to investigate the effects of foliar Zn application on the growth and yield contributing traits of mungbean, and to determine the best Zn fertilizer management for optimum mungbean growth and yield. The experiment was comprised of one factor, viz. management of the zinc fertilizer, and seven treatments, viz. (i) No zinc application (Control) [T1], (ii) Basal application of ZnSO4.7H2O @ 10 kg ha-1 [T2], (iii) Foliar application of 0.5% ZnSO4.7H2O solution at pre-flowering stage (i.e. 40 days after sowing (DAS)) [T3], (iv) Foliar application of 0.5% ZnSO4.7H2O solution at flowering stage (i.e., 50 DAS) [T4], (v) Foliar application of 0.5% ZnSO4.7H2O solution at pod formation stage (i.e. 60 DAS) [T5], (vi) Foliar application of 0.5% ZnSO4.7H2O solution at 40 DAS and 50 DAS [T6], (vii) Foliar application of 0.5% ZnSO4.7H2O solution at 40, 50 and 60 DAS [T7]. The experimental treatments were laid out in a randomized complete block design (RCBD) with three replications. Plant characteristics such as plant height, shoot dry weight, root dry weight, and yield contributing characteristics including number of pods plant-1, number of good pods plant-1, number of grains pod-1, and weight of 1000 grains were significantly influenced by Zn fertilization. The highest values for all parameters, including maximum grain yield (0.84 ± .06 t ha-1) and stover yield (4.64 ± 0.85 t ha-1), were recorded at T7, where foliar application of 0.5% ZnSO4.7H2O was applied at 40, 50 and 60 DAS.
Growth pattern, Protein quantification, and Antibiotic responses of four Halophilic Bacterial Strains in different salt concentration
Authors: DAS ANKUR , Choudhury Mahua
Published: July 2024

Abstract:
Background: Halophilic bacteria are studied extensively to explore molecular basis of adaptation, enzymatic potential, drug resistance and their other biotechnological implications. Their ability to survive in hypersaline condition is often linked to the potential of biosynthesizing a well-known compatible solute, namely ectoine.
Aim: In this study, four bacterial strains, which were previously identified from hypersaline environment were studied for their growth pattern and ectoine biosynthesis proteins expression under varying NaCl concentration. In addition, antibiotic susceptibility of the strains was also investigated.
Methods: The growth pattern of the bacterial strains were studied in LB broth supplemented with different NaCl concentration. Bradford method was employed for protein estimation, and optical densities of the samples were quantified through UV-Vis spectrophotometer. Moreover, expression of the ectoine proteins were detected through SDS-PAGE, and disc diffusion method was used for profiling the antibiotic resistance of the strains.
Results: The results indicated distinct growth patterns, with each strain demonstrating preferences for specific salinity levels. Notably, Staphylococcus cohnii strain F exhibited optimal growth at 10% NaCl, while Jeotgalicoccus huakuii strain 3.7 thrived at 15% NaCl. Total protein analysis revealed a consistent trend of decreasing protein content with rising NaCl concentrations, elucidating a potential adaptive strategy. Staphylococcus cohnii strain F stood out, maintaining higher protein levels at 20% NaCl, indicative of unique adaptive mechanisms. Antibiotic susceptibility testing uncovered diverse resistance profiles, emphasizing the strain-specific nature of responses. The expression of ectoine biosynthesis genes in Staphylococcus cohnii strain F underlines its adaptive advantage in high salinity.
Conclusion: The findings contribute not only to basic microbial physiology knowledge but also hold implications for biotechnological applications and clinical practices, emphasizing the importance of tailored approaches in antibiotic therapy and highlighting the strain-specific nature of bacterial adaptations.
Flunarizine versus topiramate in migraine prophylaxis and their effect on psychomotor ability: A prospective open-label study
Authors: Dixit Alok , Pandey Devesh , Khan Nasreen , Singh Chandraveer , Pathak Asha , Yadav Ramakant
Published: July 2024

Background: About 9% of the overall population suffers from migraine headaches, with a female majority. For the prevention of migraines, the two most often prescribed drugs are topiramate (TPM) and flunarizine. Regarding TPM and flunarizine’s long-term efficacy, safety, and adverse effects on migraine prevention, little is known. To evaluate the effectiveness of flunarizine against TPM in migraine prophylaxis and its impact on psychomotor ability, the current study was designed.

Aims and Objectives: The aim of the study was to compare the efficacy of flunarizine and TPM in the prophylaxis of migraine and to assess change in the psychomotor ability of the brain using different psychomotor analysis scoring systems.

Materials and Methods: A comparative, open-label, and prospective study was carried out on patients with chronic migraine from the outpatient department of the neurology department at Uttar Pradesh University of Medical Sciences, Saifai, Uttar Pradesh, with flunarizine and TPM treatment (n = 20/group) for 2 months. Data regarding patient’s scores of headache severity on the Visual Analogue Scale (VAS), digit later substitution test, 6 letter cancellation test, digit span test, mathematical ability test, and flicker fusion apparatus test were recorded and analyzed.

Results: When compared to the baseline, the mean±standard deviation pain severity score on the VAS was 2.9 ± 0.8 in the flunarizine group and 3.7 ± 1.4 in the TPM group, with a P < 0.001. Furthermore, the flunarizine group showed less decline in performances in the scores of each psychomotor test as compared with the scores of the TPM treatment group when baseline values were compared at 1 and 2 months.

Conclusion: Flunarizine is well tolerated, has a better safety profile, and has less cognitive decline as compared to TPM.
How accurate are NT-proBNP, ANP, and cTnI levels in diagnosing dogs with myxomatous mitral valve disease?
Authors: Chanmongkolpanit Kittara , Riengvirodkij Nattapon , Channgam Phuttipan , Kaenchan Pemika , Buayam Wasana , Janhirun Yada , Phonarknguen Rassameepen , Tansakul Mookmanee , Sakcamduang Walasinee
Published: July 2024

Background:
Myxomatous mitral valve disease (MMVD) is prevalent in dogs. Specialized diagnostics (radiography, echocardiography) may be unavailable in some veterinary settings. Cardiac biomarkers offer potential alternatives.
Aim:
This study evaluated diagnostic value of N-terminal fragments of pro-brain natriuretic peptides (NT-proBNPs), atrial natriuretic peptides (ANPs), and cardiac troponin I (cTnI) levels in dogs with MMVD.
Methods:
69 dogs with MMVD (asymptomatic and symptomatic) and 19 healthy controls were assessed. Biomarker levels were measured using commercial kit rapid tests.
Results:
Our results showed that the median NT-proBNP level in the symptomatic group was higher than those in the asymptomatic (P < 0.001) and control (P < 0.001) groups. Moreover, the median NT-proBNP level in the asymptomatic group was higher than that in the control group (P < 0.001). The cTnI level in the control group was lower than those in the asymptomatic (P = 0.039) and symptomatic (P = 0.001) groups. No statistically significant difference in the cTnI level was noted between the asymptomatic and symptomatic groups. The best cutoff value of the NT-proBNP level to differentiate the normal controls from dogs with MMVD with or without congestive heart failure was > 505.65 pmol/L (sensitivity, 76.8%; specificity, 89.5%; and area under the curve [AUC], 0.862). The suggested cutoff value of the NT-proBNP level to differentiate symptomatic MMVD from asymptomatic MMVD was >787.65 pmol/L (sensitivity, 78.38%; specificity, 72.55%; and AUC, 0.792).
Conclusion:
NT-proBNP and cTnI may serve as point-of-care tests for dyspneic dogs, aiding MMVD assessment where specialized diagnostics are limited.
Diversity of hard ticks parasitizing farm animals in the Qarabulli region, Northwestern Libya
Authors: Shebani Sara , Albbani Alayadi , Saadawi Walid , Shaibi Taher
Published: July 2024

Background:
There are 26 species of ticks known to exist in Libya. Despite the presence of a number of investigations on ticks in Libya, there are no published studies on ticks in the Al-Qarboulli area.
Aim:
The aim of this study was to identify the ticks species infesting farm animals in the Qarabulli region.
Methods:
Ticks were collected manually on a monthly basis from the examined hosts (cattle, sheep, dogs, and camels) that were selected randomly in the period between July 2021 and June 2022.
Results:
717 ticks individuals were collected on 775 hosts, eight tick species were encountered: Hyalomma excavatum (41.00%), Rhipicephalus sanguineus (23.43%), H. dromedarii (12.13%), H. marginatum (9.21%), H. anatolicum (8.51%), R. annulatus (5.30%), H. rufipes (0.28%), and B. microplus (0.14%). The mean prevalence of all species was 22.32%. The mean intensity of all species was 0.93 ticks per host. The presence of ticks among the months of the year varied among tick species.
Conclusions:
The results showed high tick infestation in farm animals of Qarabulli, Libya, suggesting increased risk of tick-borne diseases. This highlights the need for preventative measures and public awareness to reduce tick populations. Further studies are recommended to understand the spread of tick-borne diseases in the area.
Validation of the method for determining lincomycin levels and calculating lincomycin levels in broiler chicken plasma using High-Performance Liquid Chromatography
Authors: Wibisono Cahyo , Wijayanti Agustina , Muzaki Alfian , Widiasih Dyah , Noviatri Aldila
Published: July 2024

Background:
Antibiotic residues come from food of animal origin, such as broiler chicken, have a variety of consequences on human health and increase the likelihood of antibiotic resistance. Lincomycin residue investigations in broiler chicken especially in plasma broiler chicken should be undertaken utilising the validation method analysis.
Aim:
The purpose of this study is to determine the high-performance liquid chromatography (HPLC) as a validation method for calculating the residual concentration of lincomycin in broiler chicken blood plasma and compare it with the Minimum Inhibitor Concentration (MIC) and Maximum Residue Limits (MRL) standards for lincomycin.
Methods:
Thirty-five-day-old broiler chickens cobb 700 were weighed and randomly allocated to and separated into control (placebo) and six treatment groups of varying doses and duration. The treatment group's suggested dosage of lincomycin was 50, 100, or 150 mg/kg/day given to 18-day-old chicken, along with drinking water for a week (A group) and two weeks (P group). Lincomycin levels in blood plasma were validated using HPLC. The residual lincomycin concentrations 24 hours and one week after injection were compared to the lincomycin MIC and the Indonesian National Standard of MRL.
Result:
The validation of lincomycin reveals a linear value in blood plasma with an R2 of 0.9983. Precision and accuracy levels indicate promising results for detecting lincomycin. The retention duration for 100 µg/mL lincomycin was 10.0-10.5 minutes. Lincomycin had LOD and LOQ values of 13.98 and 4.86 µg/mL, respectively. After one week of dosing at 50 and 100 mg/kg dosages, lincomycin residue detection was 0.00, which was below the MRL criterion of <0.1 ppm. The study found that the residual concentration of 150 mg/kg dosages for a week and 100/150 mg/kg doses for two weeks above the lincomycin MIC limits against Mycoplasma synoviae, Staphylococcus aureus, and Salmonella enteritidis.
Conclusion:
Lincomycin detection by HPLC in chicken blood plasma showed promising results in terms of linearity, accuracy, precision, specificity, and sensitivity. Lincomycin administration for one week at doses of 50 and 100 mg/kg resulted in the lowest residual concentration below the lincomycin MIC and MRL standards.