bluuebunny/crossref_metadata_2025 huggingface dataset:
A Study of the Effects of Transactional Leadership on Employee Motivation and Performance in the Malaysian Retail Sector
Authors: Thivaashini Selvarajah  , Mohammed Reyasudin Basir Khan  , Chong Peng Lean  , Tatchanaamoorti Purnshatman
Published: April 2024

Effective leadership is an essential factor in managing organizations as it significantly impacts employee behaviour and performance. One such leadership style commonly employed in the business world is transactional leadership, which focuses on providing rewards and punishments to motivate employees towards achieving specific objectives. Nevertheless, the extent to which transactional leadership affects employee motivation and performance within the retail sector of Malaysia has not been fully explored. Therefore, this journal study aimed to explore the potential effect of transactional leadership on employee motivation and performance within the retail sector in Malaysia. The findings indicate that transactional leadership significantly and positively influenced both employee motivation and performance. Furthermore, employee motivation was found to mediate the relationship between transactional leadership and performance. These results highlight the importance of transactional leadership in the promotion of employee motivation and performance, suggesting that organizations within the Malaysian retail sector should consider adopting transactional leadership practices to enhance employee outcomes. Implications and future research directions are discussed.
Application of Regression Analysis in Forecasting Mobile Broadband Subscriptions Growth for Malaysia
Authors: Kar Woh Lon  , Mohammed Reyasudin Basir Khan  , Chong Peng Lean  , Tatchanaamoorti Purnshatman
Published: April 2024

This paper forecasts the growth of Mobile Broadband Subscriptions in Malaysia using regression analysis, specifically focusing on linear regression to model trends. The analysis considers factors such as Mobile Broadband Traffic usage and Fixed Broadband Traffic, especially as the 5G network expands and Mobile Broadband becomes a potential alternative for enterprise and education sectors seeking faster broadband solutions. The study also examines Fixed Broadband Traffic in the context of Fixed Mobile Convergence, which impacts Mobile Broadband Subscription growth rates, necessitating the use of multiple linear regression analysis. This work provides a strategic growth plan for Mobile Broadband Subscriptions, highlighting the potential impact of growth trends. Exponential regression is also applied, offering readers a better understanding and the ability to choose results and analyses that best suit their business needs. Trendline reliability is assessed to measure how well the trendline fits the data, enhancing the accuracy of the regression model. For telecommunication companies, this analysis can help identify potential addressable markets and guide network expansion decisions, as well as inform the development of new mobile broadband plans. Original Equipment Manufacturers (OEMs) can use this information to introduce cost-effective mobile broadband devices, while enterprises can strategize their digital transformation efforts based on the findings. The forecast suggests that Mobile Broadband Subscriptions in Malaysia will reach 45.6 million by the second quarter of 2024.
Assessment of Cow Urine as a Nutrient Medium for Indoor Cultivation of Spirulina sp.
Authors: Chaudhari Ankit , Manoj Kapila
Published: April 2024

This study aims to explore the feasibility of utilizing cow urine as an economical alternative nutrient source for microalgae cultivation. By leveraging its mineral content and cost-effectiveness, this research investigates the potential to reduce production expenses associated with nutrient mediums, thus enhancing the value proposition of microalgae-derived products on a commercial scale. In order to assess its efficacy, cow urine was gathered, diluted, and introduced into our Spirulina-modified medium. This concoction was subjected to 8 hours of daily light exposure. Following an 18-day incubation period, we analysed the biomass quantity, specific growth rate, density, chlorophyll level, and total carotenoid content. In the Aquatic Biology laboratory at VNSGU, an experiment was conducted utilizing five distinct concentrations (0.2 ml, 1 ml, 2 ml, 3 ml, and 4 ml in 200 ml) over an 18-day period. The control flask (0 ml) did not contain cow urine. In our current investigation, Spirulina cultivated in a cow urine extract at a concentration of 0.2 ml/200 ml exhibited a dry weight of 0.034±0.0029 g, a specific growth rate of 0.0016±0.00015, and a carotenoid content of 4.683±0.015. The density of Spirulina peaked at 0.0052±0.00005 with a concentration of 1 ml/200 ml of cow urine extract. Across various concentrations of cow urine extract, including 2 ml/200 ml (8.022±0.016 mg/L), 0.2 ml/200 ml (2.191±0.021 mg/L), and 4 ml/200 ml (0.631±0.020 mg/L), Spirulina exhibited higher levels of chlorophyll a, b, and c compared to the control medium in indoor culture setups.
The Music of Fausto Romitelli: Concerning the Question of “Musical Material”
Authors:   Gnesin Russian Academy of Music, Tsaregradskaya Tatiana V.
Published: April 2024

The end of the 20th century demonstrates an expansion of horizons of the comprehension of musical sonorities, the conception of their transformation from music into “sound,” which radically changes the perception of timbre: this element becomes transformed from a peripheral component of sound to the primary element, thereby changing entirely the entire conception of musical material. Thus, the theory of music material developed by outstanding German philosopher Theodor Adorno in the middle of the 20th century has found its confirmation. The latter’s concept of the historicity of music material was upheld and further developed by Italian composer Luigi Nono, who fundamentally changed the sphere of perception of this phenomenon, which subsequently was testified by his German student Helmut Lachenmann. This required not only new combinations of sound, but a reevaluation of the attitude of working with them. Fausto Romitelli (1963–2004) pertains to the generation of composers that discovered new paths for work with sound. In his musical output sound becomes a complex multicomponent phenomenon presuming an interaction between acoustic instruments, electronic sounds and reverberation — the sound “aura” and the sound “halo,” both of which are also composed consciously (presenting “composed resonance”). Romitelli’s individuality demonstrates itself in the fact that he builds this component of his musical material, basing himself on sonar discoveries in the sphere of rock music, in particular, the Pink Floyd ensemble, which finds reflection in such of his works as EnTrance, Professor Bad Trip, etc. Romitelli characterized the “aura” of his sound as “dirty,” comprehending this as a specific resonance of the sound of the electric guitar in rock music. Romitelli’s “composed resonance” is not characteristic solely of him; “composed resonance” as an element of musical material may be discerned in the works of other composers, in particular, Kaija Saariaho in her Amers for solo cello and ensemble.
The Forms of Interaction of the Folk Song Creativity and Instrumental Music (on the Example of Traditional Solo and Group Singing of the Peoples of the Caucasus)
Authors:   Northern-Caucasus State Institute of Arts, Ashkhotov Beslan G.
Published: April 2024

The article examines the interconnection of the vocal-choral and instrumental music in the traditional solo-and-group performance among the different peoples throughout the Caucasus (the Adyghians, Abkhazians, Osetians, Balkars and Karachays). The present problem range has not yet become a topic of special academic comprehension. In this connection,the aim of the article is to draw the attention of specialists towards studying it and defining the role of the instrumental strata within the standard texture of broadly disseminated song performance in the Caucasus region. The traditional regional type of texture of song composition includes two main strata: the solo declamatory presentment of the tune and the choral (i.e., ensemble) accompaniment existing in dialogic interaction with each other. Frequently, we can find a third stratum, as well — the instrumental, as a rule, existing in performance on a traditional bowed string instrument. As living folk music practice confirms, its participation in the solo-and-group singing is not a mandatory factor. The place and the role of the instrumental stratum in the examined folk musical material is determined in this article. The author highlights the main functions of all the textural strata, the parity of the first two lines of the song texture and the forms of their interaction, in which the traditional standard and self-sufficient structure of characteristic polyphonic singing of the peoples of the Northern Caucasus is reflected.
Application of the K-Nearest Neighbors (KNN) Algorithm on the Brain Tumor Dataset
Authors: Najwaini Effan , Thomas Edyson Tarigan  , Fajri Profesio Putra  , Sulistyowati
Published: April 2024

Brain tumors pose significant challenges in the medical domain, necessitating advanced diagnostic techniques for early and accurate detection. This research paper presents a comprehensive study on the application of the K-Nearest Neighbors (KNN) algorithm to a dataset comprising brain tumor images. The methodology involved segmenting the images using the Canny method, extracting relevant features via Hu Moments, and subsequently employing the KNN algorithm for classification. Using a 5-fold cross-validation, the system consistently achieved an average accuracy of approximately 62%. These findings highlight the potential of traditional machine learning algorithms in medical imaging, providing valuable insights for both researchers and practitioners. While the results are promising, the study also underscores the importance of integrating such algorithms with other diagnostic methods for optimal results
Classification Optimization of Skin Cancer Using the Adaboost Algorithm
Authors: Sumiyatun  , Maulidinnawati Andi
Published: April 2024

Early detection of melanoma skin cancer is crucial in improving prognosis and saving lives. This research aimed to optimize the classification of melanoma images using the Adaboost algorithm. Employing a dataset of 10,000 melanoma images, the study combined the Canny method for image segmentation, Hu Moments for feature extraction, and the Adaboost algorithm for classification. The 5-fold cross-validation results revealed an average accuracy of 61.52%. While the precision consistently surpassed recall, indicating the model's conservative nature in predicting positive cases. The outcomes align with previous research, emphasizing the challenges in melanoma classification. This study contributes to the domain by showcasing the potential and areas of improvement for machine learning in early melanoma detection. Future research is recommended to explore hybrid models and diversify data sources for enhanced robustness and generalizability.
Assessing Bagging-meta Estimator in Imbalanced CT Kidney Disease Classification: A Focus on Sobel and Hu Moment Techniques
Authors: Setiawan Rudi , Kadir Parewe Andi Maulidinnawati Abdul , Latipah Asslia Johar , Puji Astuti Nur Rochmah Dyah , Murdiyanto Aris Wahyu , Putra Fajri Profesio
Published: April 2024

This study investigates the efficacy of the Bagging-meta estimator in classifying CT kidney diseases, focusing on an imbalanced dataset processed through Sobel segmentation and Hu moment feature extraction. The research utilized a quantitative approach, applying the Bagging-meta estimator to a dataset comprising CT images classified into four categories: Normal, Cyst, Tumor, and Stone. These images were preprocessed using Sobel segmentation to highlight critical structures and Hu moment feature extraction for robust classification features. The study employed a 5-fold cross-validation method to evaluate the model's performance, assessing metrics such as accuracy, precision, recall, and F1-Score. The results indicated a significant variation in the model's performance across different folds, with accuracy ranging from 49.86% to 66.17%, precision between 51.86% and 65.93%, recall from 57.95% to 64.44%, and F1-Scores spanning 48.26% to 60.74%. These findings suggest that while the Bagging-meta estimator can achieve reasonable accuracy in classifying kidney diseases from CT images, its performance is affected by the imbalanced nature of the dataset. This study contributes to the understanding of the challenges and potential of machine learning in medical imaging, particularly in the context of imbalanced datasets. It highlights the need for specialized approaches to handle such datasets and underscores the importance of preprocessing techniques in enhancing model performance. Future research directions include exploring methods to address data imbalance, investigating alternative feature extraction techniques, and testing the model on diverse datasets to enhance its generalizability and reliability in clinical settings. This research offers valuable insights into the development of automated diagnostic tools in medical imaging and advances the field of computer-aided diagnosis in nephrology.
Advancing Healthcare Diagnostics: A Study on Gaussian Naive Bayes Classification of Blood Samples
Authors: As'ad Ihwana
Published: April 2024

This research paper presents a comprehensive analysis of the Gaussian Naive Bayes (GNB) classifier's application in predicting health conditions from blood samples, underpinned by a handcrafted dataset representative of typical physiological ranges. Through a meticulous 5-fold cross-validation approach, the study assesses the GNB model's performance in terms of accuracy, precision, recall, and F1-score, revealing not only high efficacy but also consistent improvement in predictive capability across successive folds. A detailed confusion matrix provides further insights into the model's classification proficiency. The results affirmatively address the research hypotheses, indicating the GNB classifier's reliability and effectiveness as a diagnostic tool. With the increasing need for rapid and accurate medical diagnostics, the study's findings underscore the potential of even simple machine learning models to augment traditional blood test analyses, thereby offering significant contributions to the field of biomedical informatics. The research lays the groundwork for future explorations into the integration of machine learning in clinical settings, advocating for the verification of these promising results with real-world clinical data and the comparative analysis of various machine learning models. The potential for automated, precise diagnostic processes paves the way for enhanced patient care and resource optimization in healthcare.
Evaluating Thresholding-Based Segmentation and Humoment Feature Extraction in Acute Lymphoblastic Leukemia Classification using Gaussian Naive Bayes
Authors: Rismayanti Nurul , Naswin Ahmad , Zaky Umar , Zakariyah Muhammad , Purnamasari Dwi Amalia
Published: April 2024

This study, titled "Evaluating Thresholding-Based Segmentation and HuMoment Feature Extraction in Acute Lymphoblastic Leukemia Classification using Gaussian Naive Bayes," investigates the application of image processing and machine learning techniques in the classification of Acute Lymphoblastic Leukemia (ALL). Utilizing a dataset of microscopic blood smear images, the research focuses on the efficacy of thresholding-based segmentation and Hu moment feature extraction in distinguishing between benign and malignant cases of ALL. Gaussian Naive Bayes, known for its simplicity and effectiveness, is employed as the classification algorithm. The study adopts a 5-fold cross-validation approach to evaluate the model's performance, with particular emphasis on metrics such as accuracy, precision, recall, and F1-score. Results indicate a high precision rate across all folds, averaging approximately 84.13%, while exhibiting variability in accuracy, recall, and F1-scores. These findings suggest that while the model is effective in identifying malignant cases, further refinements are necessary for improving overall accuracy and consistency. This research contributes to the field of medical image analysis by demonstrating the potential of combining simple yet efficient techniques for the automated diagnosis of hepatological diseases. It highlights the importance of integrating image processing with machine learning to enhance diagnostic accuracy in medical applications.
Federated Learning for Bronchus Cancer Detection Using Tiny Machine Learning Edge Devices
Authors: Dima Genemo Musa
Published: April 2024

In deep learning, acquiring sufficient data is crucial for making informed decisions. However, due to concerns regarding security and privacy, obtaining enough data for training models in the era of deep learning is challenging. There is a growing need for machine learning (ML) solutions that can derive accurate conclusions from small data while preserving privacy. Smartphones, which are widely used and generate large amounts of data, can serve as an excellent source for data generation. One suitable approach for regularly evaluating real-world data from edge devices is Tiny Machine Learning (TinyML). With the increasing number of edge devices involved in transmitting private data, it's vital to have a method that allows computations to be performed on edge devices and pushed to the edge rather than over the network. Considering these obstacles, the combination of TinyML edge devices and Federated Learning can be applied in the early treatment of Bronchus Cancer. Under the framework of federated learning, local edge devices are trained independently and then integrated into the server without exchanging edge device data. This approach enables the creation of secure models without sharing information, resulting in a highly efficient solution with enhanced data security and accessibility. This article provides a comprehensive discussion of the key challenges addressed in recent literature, accompanied by an extensive examination of relevant studies. Additionally, a novel model based on edge devices and federated learning is proposed.
Advancements in Agricultural Automation: SVM Classifier with Hu Moments for Vegetable Identification
Authors: Waluyo Poetro Bagus Satrio , Maria ⁠⁠Eny , Zein Hamada , Najwaini Effan , Zulfikar Dian Hafidh
Published: April 2024

This study investigates the application of Support Vector Machine (SVM) classifiers in conjunction with Hu Moments for the purpose of classifying segmented images of vegetables, specifically Broccoli, Cabbage, and Cauliflower. Utilizing a dataset comprising segmented vegetable images, this research employs the Canny method for image segmentation and Hu Moments for feature extraction to prepare the data for classification. Through the implementation of a 5-fold cross-validation technique, the performance of the SVM classifier was thoroughly evaluated, revealing moderate accuracy, precision, recall, and F1-scores across all folds. The findings highlight the classifier's potential in distinguishing between different vegetable types, albeit with identified areas for improvement. This research contributes to the growing field of agricultural automation by demonstrating the feasibility of using SVM classifiers and image processing techniques for the task of vegetable identification. The moderate performance metrics emphasize the need for further optimization in feature extraction and classifier tuning to enhance classification accuracy. Future recommendations include exploring alternative machine learning algorithms, advanced feature extraction methods, and expanding the dataset to improve the classifier's robustness and applicability in agricultural settings. This study lays a foundation for future advancements in automated vegetable sorting and quality control, offering insights that could lead to more efficient agricultural practices.
Estimating Obesity Levels Using Decision Trees and K-Fold Cross-Validation: A Study on Eating Habits and Physical Conditions
Authors: Admojo Fadhila Tangguh , Nurul Rismayanti
Published: April 2024

This study harnesses the predictive capabilities of machine learning to explore the determinants of obesity within populations from Mexico, Peru, and Colombia, using a Decision Tree algorithm bolstered by 5-fold cross-validation. Our comprehensive analysis of 2111 individuals' lifestyle and physical condition data yielded accuracy, precision, recall, and F1-scores that notably peaked in the third and fifth folds. The findings affirmed the significance of dietary habits and physical activity as substantial predictors of obesity levels. The variability in model performance across the folds underscored the importance of robust cross-validation in enhancing the model's generalizability. This research contributes to the burgeoning field of data science in public health by providing a viable model for obesity prediction and laying the groundwork for targeted health interventions. Our study's insights are pivotal for public health officials and policymakers, serving as a stepping stone towards more sophisticated, data-driven approaches to combating obesity. The study, however, recognizes the inherent limitations of self-reported data and the need for broader datasets that encompass more diverse variables. Future research directions include the analysis of longitudinal data to establish causal relationships and the comparison of various machine learning models to optimize predictive performance
Automated Classification of COVID-19 Chest X-ray Images Using Ensemble Machine Learning Methods
Authors: Sinra A. , Husni Angriani
Published: April 2024

This study delves into the efficacy of ensemble machine learning techniques for classifying chest X-ray images into three distinct categories: Normal, COVID-19, and Lung Opacity. Employing the Random Forest Classifier and a rigorous k-5 cross-validation framework, we aimed to enhance diagnostic accuracy for one of the most urgent medical challenges today—rapid and reliable COVID-19 detection. The analysis revealed an average accuracy of 51%, with varying precision and recall across different folds. The F1-score remained consistently around 35%, indicating a need for improved balance between precision and recall. Visualizations such as performance metric trends and a confusion matrix provided further insight into the classifier's performance, highlighting a notable degree of misclassification. Despite moderate success in the automated classification of the images, our research illustrates the complexity of applying machine learning to medical imaging, especially in differentiating between diseases with overlapping radiographic features. The study’s findings emphasize the potential of machine learning models to support diagnostic processes and suggest the necessity of advanced pre-processing techniques and extended datasets for enhanced model training. The research contributes to the growing body of knowledge in computational diagnostics and underscores the importance of developing robust, accurate machine learning tools to aid in the global healthcare crisis precipitated by the pandemic.
Buen docente desde las percepciones de estudiantes de la Escuela Profesional de derecho en una Universidad Peruana
Authors: Vargas Tipula Wilmer Guido , Núñez Huamantica Yoni , Serna Silva Vivianett , García Rodríguez Erik Boris , Villena Huayllapuma Cesar
Published: April 2024

Un docente de calidad se caracteriza por su humanidad, mostrando amabilidad y comprensión hacia sus estudiantes. Son capaces de crear un entorno acogedor mediante un trato cercano y afectuoso. Además, confían en las habilidades de sus alumnos y los motivan hacia el éxito académico. Por tanto, este estudio se centró en analizar las cualidades de un buen docente según la percepción de estudiantes de la Escuela de Derecho de la Universidad Andina del Cusco, Filial Quillabamba, durante el año 2023. La investigación se basó en un enfoque cualitativo, utilizando un diseño fenomenológico para explorar en profundidad las opiniones de los estudiantes. Se empleó la técnica de entrevistas semiestructuradas, entrevistando a una muestra de 12 estudiantes de II a V ciclo. Los datos fueron organizados y analizados considerando diversas subcategorías. Los resultados revelaron que un buen docente se distingue por su compromiso y dedicación a la enseñanza, reflejados en aspectos como los valores profesionales, la planificación de actividades de aprendizaje, el trato respetuoso y el dominio del contenido.
Estrategias didácticas para fortalecer la lectoescritura en estudiantes con necesidades especiales no asociada a la discapacidad en trastornos del comportamiento
Authors: Bravo Ibarbo Angela Mercedes , Agama Zapata Ligia Maribel , Guillin Fierro Mayra Elizabeth , Farfan Piedra Eduardo Enrique , Baidal Quinto Nancy Magdalena
Published: April 2024

En el contexto educativo, fortalecer la lectura y escritura en estudiantes con necesidades especiales no asociadas a discapacidades específicas, como trastornos del comportamiento, requiere estrategias didácticas efectivas. Este resumen revisa la literatura académica sobre el tema y destaca varias estrategias clave respaldadas por la investigación. Las adaptaciones curriculares son fundamentales, incluyendo simplificar tareas y modificar materiales para que sean accesibles. Un enfoque multisensorial, según Berninger et al. (2002), que involucre varios sentidos en actividades de lectura y escritura, mejora la comprensión. Además, la instrucción diferenciada, ofreciendo opciones de lectura y retroalimentación individualizada, según Tomlinson (2001), es esencial para abordar las diversas necesidades de los estudiantes. La tecnología también desempeña un papel crucial. Higgins y Raskind (2000) destacan el uso de software especializado y herramientas de asistencia tecnológica para compensar las dificultades y mejorar el rendimiento académico. Además, adoptar un enfoque basado en las fortalezas de los estudiantes, identificando y capitalizando sus habilidades e intereses individuales, puede aumentar la motivación y el compromiso, como sugieren Mastropieri y Scruggs (2000). La investigación previa respalda la efectividad de estas estrategias para mejorar la comprensión lectora y la expresión escrita en este grupo de estudiantes (Baker & Zigmond, 2005; Berninger et al., 2002; Higgins & Raskind, 2000; Mastropieri & Scruggs, 2000; Tomlinson, 2001). Este estudio científico busca ofrecer una comprensión más profunda de cómo estas estrategias pueden ser implementadas de manera efectiva para promover el éxito académico y social de los estudiantes con necesidades especiales no asociadas a discapacidades en trastornos del comportamiento.
Comparación de Mecánicas de Tracción Dental en Incisivos Centrales Ectópico y Retenido y sus Consecuencias: Reporte de Caso
Authors: Aguilar  Rojas José Daniel , Obando Zamora Angélica Vanessa , Meléndez Véliz Andrea Alejandra , Mérida Donis Ericka Anaí , Herrera Donis Claudia María , Zuñiga Cifuentes José Roberto , Peláez Achtmann Edlin Anahí , Vesco Leiva Leopoldo Raúl
Published: April 2024

Introducción: La erupción dental puede verse afectada por agenesis, quistes, dientes impactados o erupciones dentales en posiciones ectópicas. El tratamiento de esta condición se considera difícil para el ortodoncista, ya que requiere de mecánicas y movimientos complejos. Objetivo: Este reporte compara los resultados en la reabsorción radicular luego de las mecánicas de tracción ortodóntica entre dos incisivos maxilares en pacientes Guatemaltecos de 10 y 11 años. Métodos: El incisivo maxilar ectópico fue tratado con expansión maxilar para crear espacio y corregir la mordida cruzada posterior, se hizo la desrotación y tracción con cadenas elásticas. El incisivo maxilar impactado fue sometido a exposición quirúrgica cerrada y la tracción inmediata de la corona del diente a través de cadenas elásticas y doble arco. Resultados: Al finalizar el tratamiento, los incisivos maxilares afectados fueron ubicados en sus posiciones ideales en el arco dental. Sin embargo, el incisivo maxilar impactado presentó reabsorción radicular leve.
INFANTILE COLIC
Authors: Новикова Валерия Павловна , Магамедова Динара Мафрутдиновна
Published: April 2024

Лекция посвящена актуальной проблеме педиатрии — младенческим коликам. Они рассматриваются в свете рекомендаций Римских критериев, отражающих мнение экспертов — педиатров, гастроэнтерологов, аллергологов. Ключевым моментом в постановке диагноза младенческих колик является исключение органической патологии («красные флаги»), которая составляет не более 5%. В статье рассмотрены современные представления о патогенетических механизмах младенческих колик и основанные на этих данных современные принципы их лечения. Терапия младенческих колик включает психологическую поддержку семьи, сохранение грудного вскармливания и применение пробиотиков.

The lecture is devoted to the current problem of pediatrics — infant colic. They are in the light of the recommendations of the Rome criteria, refl ecting the opinion of experts — pediatricians, gastroenterologists, allergists. The key to diagnosing infant colic is to exclude organic pathology (“red flags”), which accounts for no more than 5%. The article discusses modern ideas about the pathogenetic mechanisms of infant colic and modern principles of their correction based on these data. Correction of infant colic includes psychological support for the family, continued breastfeeding and the use of probiotics.
CLINICAL CASE OF A PATIENT WITH DISTAL RENAL TUBULAR ACIDOSIS WITH HEARING LOSS
Authors: Прокопьева Наталья Эдуардовна , Фирсова Людмила Алексеевна , Новикова Валерия Павловна , Козловская Ольга Васильевна , Кирюхина Любовь Владимировна
Published: April 2024

Дистальный ренальный тубулярный ацидоз с глухотой (OMIM 267300) — это редкое заболевание, характеризующееся тяжелым метаболическим ацидозом вследствие нарушения экскреции водородных ионов в дистальном отделе нефрона. Нарушение физического и психомоторного развития, деформация конечностей, электролитные нарушения без должного и своевременного лечения могут приводить к инвалидизации уже в самом раннем возрасте. В статье описан клинический случай, отражающий сложность и коварность диагностики дистального ренального тубулярного ацидоза у ребенка первого года жизни.

Distal renal tubular acidosis with deafness (OMIM 267300) is a rare disease characterized by severe metabolic acidosis due to impaired excretion of hydrogen ions in the distal nephron. Violation of physical and psychomotor development, deformation of limbs, electrolyte disturbances without proper and timely treatment can lead to disability at a very early age. The article describes a clinical case that refl ects the complexity and insidiousness of diagnosing distal renal tubular acidosis in a child of the fi rst year of life.
Penciptaan Busana Pesta dengan Sumber Ide Bunga Aster
Authors: Rufaydah Indana , Wahyuningsih Urip
Published: April 2024

Bunga aster sering disebut sebagai bintang, memiliki banyak jenis warna yang membuat siapapun terpana melihatnya. Dengan keindahannya, bunga aster dijadikan sebagai sumber ide penciptaan salah satu koleksi busana pesta malam. Penelitian ini bertujuan untuk mengetahui proses penciptaan desain busana pesta malam dengan sumber ide bunga aster. Metode penelitian ini menggunakan Double Diamond Design Prosses, yang dibagi dalam 4 tahap antara lain discover merupakan eksplororasi tema yang dibahas dalam penelitian ini adalah “bunga aster” yang penampilan sosok bunga mirip bintang, helaian bunga aster berbentuk lingkaran, mulai dari bulat hingga berbentuk seperti cakram. Hasil yang didapatkan dari penerapan sumber ide pada sebuah karya yang berupa moodboard. Tahap define, dari hasil moodboard kemudian membuat 10 pengembangan desain. Tahap develop yaitu tahap memilih 2 desain untuk diwujudkan sesuai dengan inspiration picture yang muncul dari sumber ide untuk diwujudkan dalam teknik pola draping dengan menggunakan ukuran medium pada dressfoam. Tahap deliver merupakan proses pembuatan detail hiasan berbentuk bunga aster yang diambil dari bentuk mahkota bunga aster dengan cara mengunting staplek sesuai pola, dipress dengan kain satin/organza untuk membuat helaian mahkota bunga dan terakhir diberi hiasan taburan payet dan menyusun lace pada dress yang sudah di beri payet dan ditikam jejak. Hasil penelitian yaitu hasil jadi busana menggunakan teknik drapping dan pembuatan detai hiasan sesuai sumber ide yang menerapkan prinsip desain center of interest dan proposi.
Pengaruh Agile Methodology dalam Strategi Digitalisasi Di PT. Satoru Prima Internasional
Authors: Dalimunthe Miftah Mujahir , Juma'adi Juma'adi , Madiistriyatno Harries
Published: April 2024

Digitalisasi telah menjadi faktor penting bagi perusahaan untuk berkembang di tengah perubahan yang cepat di era digital. Metodologi tangkas telah menjadi terkenal sebagai pendekatan yang efektif untuk transformasi digital yang sukses. Penelitian ini bertujuan untuk menguji pengaruh metodologi Agile dalam strategi digitalisasi PT. Satoru Prima Internasional. Dengan menggunakan metode penelitian kualitatif, penelitian ini menggunakan pendekatan studi kasus. Data dikumpulkan melalui wawancara mendalam dengan manajemen kunci dan personel terkait, disertai dengan analisis dokumen internal dan observasi langsung. Melalui pendekatan induktif, data yang terkumpul dianalisis untuk mengidentifikasi dan mengeksplorasi tema-tema kunci yang muncul dari penggunaan metodologi Agile dalam strategi digitalisasi perusahaan. Temuan menyoroti pengaruh positif metodologi Agile di PT. Strategi digitalisasi Satoru Prima Internasional. Metodologi tangkas memungkinkan perusahaan untuk tanggap terhadap perubahan, memitigasi risiko proyek, dan meningkatkan efisiensi tim. Selain itu, metodologi Agile memupuk komunikasi yang efektif antara tim proyek dan pemangku kepentingan, sambil memberikan fleksibilitas untuk memenuhi kebutuhan yang terus berkembang. Penelitian ini mengidentifikasi beberapa faktor penentu keberhasilan penerapan metodologi Agile dalam strategi digitalisasi. Faktor-faktor tersebut meliputi dukungan manajemen puncak, keterlibatan tim yang kuat, pemahaman mendalam tentang metodologi Agile, dan budaya organisasi yang mendukung inovasi dan kolaborasi. Studi ini berkontribusi pada pemahaman yang lebih baik tentang bagaimana metodologi Agile dapat memengaruhi strategi digitalisasi perusahaan. Temuan ini menjadi referensi berharga bagi organisasi yang ingin mengadopsi metodologi Agile dalam perjalanan transformasi digital mereka. Implikasi praktis dari penelitian ini menunjukkan bahwa perusahaan harus mempertimbangkan metodologi Agile sebagai pendekatan yang efektif untuk mencapai kesuksesan dalam strategi digitalisasi mereka.
Eleştirel Düşünme ve Akademik Başarının Doğasını Anlamak: Fen Eğitimi Kapsamında Bir Analiz / Understanding the Nature of Critical Thinking and Academic Success: An Analysis in the Context of Science Education
Authors: Demirel Ozan Emre
Published: April 2024

Bu araştırmada fen bilimleri dersi madde ve ısı ünitesi kapsamında altıncı sınıf öğrencilerinin eleştirel düşünme becerilerinin akademik başarılarına etkisi test edilmiştir. Araştırmada nicel araştırma yöntemlerinden ilişkisel tarama modeli kullanılmıştır. Araştırmaya 2023-2024 eğitim öğretim yılında, Bursa ili İnegöl ilçesinde bulunan Milli Eğitim Bakanlığına Bağlı özel bir okulda öğrenim gören 47 altıncı sınıf öğrencisi katılmıştır. Araştırmada veri toplama aracı olarak; araştırmacı tarafından geliştirilen 12 maddelik “Madde ve Isı Eleştirel Düşünme Becerileri Testi” kullanılmıştır. Ayrıca öğrencilerin madde ve ısı ünitesindeki akademik başarılarının ölçülebilmesi için araştırmacı tarafından geliştirilen “Üç Aşamalı Madde ve Isı Akademik Başarı Testi” kullanılmıştır. Araştırma sonuçlarına göre; akademik başarı ve eleştirel beceri puanlarına göre, kız ve erkek öğrenciler arasında anlamlı derecede fark görülmüştür. Kız öğrencilerin her iki testten elde ettikleri puanların aritmetik ortalaması, erkek öğrencilere kıyasla daha yüksek bulunmuştur. Alt ve Üst eleştirel düşünme beceri düzeylerindeki öğrencilerin akademik başarı puanları arasında istatistiksel olarak anlamlı bir fark olduğu görülmüştür. Öğrencilerin eleştirel düşünme ve akademik başarı arasında pozitif yönlü yüksek derecede bir ilişki olduğu görülmüştür. Bu bağlamda fen bilimleri derslerinde öğrencilere problem çözme, eleştirel analiz yapma ve bilgiyi sorgulama gibi beceriler kazandırmak için etkileşimli öğrenme yöntemleri benimsenebilir. Ayrıca fen bilimleri derslerinde kullanılan materyaller cinsiyet temelli stereotiplere karşı duyarlı olabilir.
Beden Eğitimi ve Spor Öğretmeni Adaylarının Egzersize Dayalı Psikososyal Gelişim Düzeylerinin İncelenmesi / Investigation of Exercise-Based Psychosocial Development Levels of Physical Education and Sports Teacher Candidates
Authors: Medeni Mehmet Bilgi , Goktas Zekeriya
Published: April 2024

Bu çalışmanın amacı başarılı bir meslek hayatı geçirmelerinde büyük öneme sahip olan rol model olma özelliğinden yola çıkılarak beden eğitimi ve spor öğretmeni adaylarının psikososyal gelişiminin egzersize dayalı etkilerini tespit etmek ve onların kendi gelişimlerinin ne durumda olduğunu belirlemektir. Araştırmada Bengoechea (2017) tarafından geliştirilen Gençlik ve spor etkinlik ölçeğinin (GSEÖ) Türkçeye uyarlanması Medeni ve Göktaş (2023) tarafından gerçekleştirilmiştir. Bireylerin psikososyal gelişimlerinin tespit edilmesi çalışması sonucunda ölçek 12 madde ve güdülenme, kullanışlılık, öğrenme olmak üzere üç alt boyuttan oluşmaktadır. Araştırmanın evrenini bir devler üniversitenin spor bilimleri fakültesi’nde öğrenim gören beden eğitimi ve spor öğretmenliği adayları oluışturmuştur. Çalışmayı 115 Kadın, 165 Erkek olmak üzere 280 kişi oluşturmaktadır. Araştırmaya katılan bireylerin “gençlik ve spor etkinlik ölçeği psikososyal gelişimleri yaş değişkeni” “ Kruskal Wallis” testi sonuçlarına göre incelendiğinde; güdülenme ve kullanışlılık, sınıf değişkeni kullanışlılık ve öğrenme, haftalık spor saati değişkeni güdülenme, kullanışlılık ve öğrenme, yerleşim yeri değişkeni güdülenme, kullanışlılık ve öğrenme alt boyutlarında anlamlı fark tespit edilmiştir (p<0.05).
EFFICACY OF BIOPESTICIDES AGAINST POMEGRANATE SUCKING PESTS UNDER LABORATORY CONDITION
Authors:   Department of Agricultural Entomology, Tamil Nadu Agricultural University, Coimbatore-641003, Tamil Nadu, India., E Elango , S Sridharan ,   Department of Agricultural Entomology, Tamil Nadu Agricultural University, Coimbatore-641003, Tamil Nadu, India., P A Saravanan ,   Department of Agricultural Entomology, Tamil Nadu Agricultural University, Coimbatore-641003, Tamil Nadu, India., S Balakrishnan ,   Department of Spices and Plantation Crops, Tamil Nadu Agricultural University, Coimbatore-641003, Tamil Nadu, India.
Published: April 2024

ABSTRACT The acute toxicity of Spinosad, NSKE, horticultural mineral oil and entomopathogens at the recommended concentration was evaluated against pomegranate sucking pests like thrips, Scirtothrips dorsalis Hood, whitefly, Siphoninus phillyreae Haliday, two tailed mealy bug, Ferrisia virgata (Cockerell). The study revealed that among all treatments,spinosad 45% SC (0.0125%) were showing more mortality in thrips (53.33%), whitefly (55.55%) and mealy bugs (48.88%) followed by NSKE (5%) thrips (43.33%), whitefly (45.55%) and mealy bugs (42.22%). Azadirachtin 10000 ppm (0.02%) at 48 hours after treatment showed more percent mortality in thrips (40.83%), whitefly (41.11%) and mealy bugs (39.99%) respectively.
ANTI-INSECT ACTIVITY OF ETHYL ACETATE EXTRACT OF CITRULLUS COLOCYNTHIS (L.) SCHRAD FRUIT AGAINST SPODOPTERA LITURA (FAB.)(NOCTUIDAE: LEPIDOPTERA)
Authors:   Department of Agricultural Entomology, Pandit Jawaharlal Nehru College of Agriculture and Research Institute, Karaikal-609 603, U.T. of Puducherry, India., M Kandibane , K Seerisha ,   Department of Agricultural Entomology, Pandit Jawaharlal Nehru College of Agriculture and Research Institute, Karaikal-609 603, U.T. of Puducherry, India., S Thulasi ,   Department of Agricultural Entomology, Pandit Jawaharlal Nehru College of Agriculture and Research Institute, Karaikal-609 603, U.T. of Puducherry, India., D Prakash ,   Department of Agricultural Entomology, Pandit Jawaharlal Nehru College of Agriculture and Research Institute, Karaikal-609 603, U.T. of Puducherry, India.
Published: April 2024

ABSTRACT The effect of ethyl acetate extract of bitter apple, Citrullus colocynthis fruit was studied against S. litura using poison food bioassay experiments. Extraction of toxic compounds from the fruits of C. colocynthis with Soxhlet and purification of extracts with column chromatography were done. In this study, there were seven treatments – five elutions, control and absolute control replicated thrice. The results showed that among the five elutions, ethyl acetate elution 3 had registered 80.00 and 83.33 per cent adult malformation, followed by ethyl acetate elution 1, 2 and 4 compared to control and absolute control in preliminary and confirmation screenings, respectively. The determination of promising dose exhibited that, ethyl acetate elution 3 exhibited the LC50value of 29.62 per cent concentration. In ethyl acetate elutions, it was found that among the elutions, the lowest mean faecal and pupal weight were registered in ethyl acetate elution 3 compared to control and absolute control. Similar trend of results were also observed in confirmation and dose determination experiments.
SIMAROUBA GLAUCA DC: AN EFFECTIVE BIOPESTICIDE AGAINST LEAF DEFOLIATORS OF AILANTHUS AND TEAK PLANTS
Authors:   Division of Chemistry and Bioprospecting, Institute of Forest Genetics and Tree Breeding (IFGTB), R. S. Puram, Coimbatore-641002, Tamil Nadu, INDIA., N Santhana Bharathi , D Suresh Babu ,   Division of Chemistry and Bioprospecting, Institute of Forest Genetics and Tree Breeding (IFGTB), R. S. Puram, Coimbatore-641002, Tamil Nadu, INDIA., R Sumathi ,   Division of Chemistry and Bioprospecting, Institute of Forest Genetics and Tree Breeding (IFGTB), R. S. Puram, Coimbatore-641002, Tamil Nadu, INDIA., N Senthilkumar ,   Division of Chemistry and Bioprospecting, Institute of Forest Genetics and Tree Breeding (IFGTB), R. S. Puram, Coimbatore-641002, Tamil Nadu, INDIA.
Published: April 2024

ABSTRACT Simarouba glauca DC seeds were collected and oil was extracted by using n-Hexane solvent in soxhlet apparatus. Phytochemical screening of n-Hexane extract of S. glauca seed oil showed the presence of cardiac glycosides, saponin and steroids. Physicochemical analysis showed that density of oil was 0.441 g/cc, free fatty acid value was 1.6 mg KOH/g, iodine value was 27.74 g/100g oil, peroxide value was 1.14 meq/kg oil, acid value was 3.21, saponification value was 208 mg KOH/g and unsaponifiable matter was 3%. Gas Chromatography and Mass Spectrometry analysis revealed that the presence of oleic acid, steric acid, palmitic acid, and linoleic acid as major fatty acids with the area percentage of 44.6%, 24.03%, 15.44% and 0.232% respectively. Further laboratory experiment was setup to evaluate S. glauca seed oil against Ailanthus and Teak defoliators viz., Eligma narcissus Cramer (Lepidoptera: Nolidae) and Hyblaea puera Cramer (Lepidoptera: Hyblaeidae). Spraying of S. glauca seed oil had resulted in 100% larval mortality in both E. narcissus and H. puera. The larval mortality was due to the insecticidal property of oil through hydrolytic dissociation and excess loss of water. Simarouba glauca seed oil acts as a contact poison and it could be used as a biopesticide to control the E. narcissus and H. puera in the early developmental stages.
COMBINED TOXICITY EFFECTS OF NEEM OIL AND MILD SOAP ON MYLLOCERUS VIRIDANUS IN MORUS ALBA
Authors:   Department of Zoology, Kandaswami Kandar’s College, Namakkal, Tamil Nadu, India., Arthanari Mohan , Senthilkumar Dhanapalan ,   Department of Zoology, Kandaswami Kandar’s College, Namakkal, Tamil Nadu, India., Jayachandran Ravikumar ,   Silkworm Seed Production Centre, NSSO, Central Silk Board, Chintamani, Karnataka, India.
Published: April 2024

ABSTRACT The insect Myllocerus viridanus in mulberry cultivation (Morus alba) causes significant harm to sericulture industry throughout the year which hampers leaf quality, silkworm rearing, and cocoon production. In this study, the treatment with neem oil (Azadirachta indica) in five different concentrations (1 to 5ml/L) along with mild soap solution (Khadi) to assess the mortality of M. viridanus at laboratory conditions. The lethal concentrations (LC30 – 3.096;LC50 – 3.471; LC90 - 4.589) were determined by spraying of the neem oil solution to adults of M. viridanus. The results showed that neem oil effectively suppressed M. viridanus and that the mortality of M. viridanus increased gradually (34 %, 44 %, 60 %, 78 %, and 100%) over the control as the concentration of neem oil increased.
ISOLATION OF BEAUVERIA BASSIANA (DEUTEROMYCOTINA: HYPHOMYCETES) FROM THE SOILS OF COFFEE FIELDS AND INSECTICIDE ACTIVITY AGAINST HYPOTHENEMUS HAMPEI (COLEOPTERA: SCOLYTIDAE)
Authors:   Plant Production, Institute of Agricultural Research for Development, P.O.BOX. 2123, Yaoundé, Cameroon 2 Plant Biology and Physiology, Faculty of Sciences, University of Yaoundé 1, P.O.BOX. 812, Yaoundé, Cameroon, Essouma François Manga , Golda Danièle Ndo Eunice ,   Plant Production, Institute of Agricultural Research for Development, P.O.BOX. 2123, Yaoundé, Cameroon, Valteri Audrey Voula ,   Plant Production, Institute of Agricultural Research for Development, P.O.BOX. 2123, Yaoundé, Cameroon, Animal Biology and Physiology, Faculty of Sciences, University of Yaoundé I, P.O.BOX. 815, Yaoundé, Cameroon, Nganti Dorothée Mvondo ,   2 Plant Biology and Physiology, Faculty of Sciences, University of Yaoundé 1, P.O.BOX. 812, Yaoundé, Cameroon, Laure Huguette Assena ,   2 Plant Biology and Physiology, Faculty of Sciences, University of Yaoundé 1, P.O.BOX. 812, Yaoundé, Cameroon, Zachée Ambang ,   2 Plant Biology and Physiology, Faculty of Sciences, University of Yaoundé 1, P.O.BOX. 812, Yaoundé, Cameroon
Published: April 2024

ABSTRACT Coffee berry borer (CBB), Hypothenemus hampei (Ferrari) is one of the most important pests of coffee marketed in Cameroon and the world. This insect lives an endophytic life in the berries and remains very difficult to fight with the spraying of synthetic pesticides. This study aims at investigating the potential impact of two native strains of Beauveria bassiana (Balsamo) Vuillemen (Deuteromycotina: Hyphomycetes) from Cameroon against the CBB. B. bassiana strains were isolated from rhizosphere strains of coffee farms. The efficiency tests were conducted on adult H. hampei. Five treatments of B.bassiana were used compared with Pyriforce (Chlorpyriphos-ethyl). Results indicate that, the B. bassiana strains were different in terms of their macromorphological characteristics. They were virulent against the CBB irrespective of the mode of application of spores directly to the borer as well as to the berries. These results clearly showed that the two isolates of B. bassiana, native to coffee growing areas in Cameroon, can be used as potential biological control agents against H. hampei and as alternatives to chemical insecticides in integrated pest management programmes for coffee.