Abstract The present study was carried out to investigate the palynoflora of Murree formation using microscopic techniques to understand the climatic changes and vegetation’s evolution. In this palynological study, 31 samples were collected, analyzed, and then identified as palynomorphs using different previous published literature. The results of this study will be described in terms of the evolutionary history of plants and the depositional environment of the reported taxa in the study area. The botanical affinities and systematic description of the taxa were examined using light and scanning electron microscopy. The floral record identified Asteraceae as the dominant family and Pinus as a genus. Most of angiosperms i.e Fabaceae and Poaceae, have a poor fossil record but have an abundant palynological record in the study area. The highest polar diameter (75.75 μm), colpus length (34.5 μm) and colpus width (31 μm) were examined for the Convolvulus. Most of the taxa explained here had a wide geographical occurrence in Southeast Asia and show the abundance of angiosperms in the Miocene epoch. The palynological record of Holocene samples is important to know about the vegetation’s origin and environmental fluctuations in the study area. vegetations vegetation s evolution 3 collected analyzed literature area microscopy genus ie i e Poaceae 75.75 7575 75 (75.7 μm, μm , 34.5 345 34 5 (34. (3 Convolvulus epoch 75.7 757 7 (75. 34. (34 ( 75. (75 (7

RESUMO Objetivos: Este estudo busca preencher a lacuna em relação a análises eficazes de avaliações feitas por consumidores online sobre smartphones, que são frequentemente em grande número e complexas do ponto de vista linguístico. Seu objetivo final é oferecer uma compreensão capaz de subsidiar tomadas de decisão e ações práticas em relação ao aprimoramento das características do produto e das estratégias de marketing. Propomos um modelo dual utilizando representações de codificadores bidirecionais de transformadores (BERT) para análise de sentimento e transformadores de frases para a modelagem de tópicos. Esta abordagem visa aumentar a precisão e a profundidade da análise de sentimento do consumidor. Método: a análise de sentimento e a modelagem de tópicos são aplicadas a um grande conjunto de dados de avaliações de smartphones obtido nas plataformas Kaggle e Amazon. O modelo BERT é usado para entender o contexto e o sentimento das palavras, enquanto os transformadores de frases geram representações para agrupar avaliações em tópicos temáticos. Resultados: A análise revelou fortes sentimentos positivos em relação ao desempenho do smartphone e à experiência do usuário, identificando também preocupações sobre a câmera e a duração da bateria. O modelo captura efetivamente o feedback positivo, mas apresenta dificuldade ao examinar avaliações negativas e sentimentos neutros em particular. Isso ocorre porque o conjunto de dados é enviesado favorecendo avaliações positivas. Conclusões: a aplicação dos modelos BERT e transformadores de sentenças representa um avanço tecnológico significativo no campo da análise de texto ao aumentar a granularidade em relação a detecção de sentimentos, bem como ao oferecer uma estrutura robusta para interpretar conjuntos de dados complexos. Nesse sentido, o estudo contribui tanto para o conhecimento teórico quanto para as aplicações práticas em análises envolvendo consumidores online. Objetivos linguístico marketing (BERT consumidor Método Amazon palavras temáticos Resultados usuário bateria positivo particular positivas Conclusões complexos sentido

ABSTRACT Objectives: this study aims to bridge the gap in effectively analyzing online consumer feedback on smartphones, which is often voluminous and linguistically complex. The ultimate goal is to provide smartphone manufacturers with actionable insights to refine product features and marketing strategies. We propose a dual-model framework using bidirectional encoder representations from transformers (BERT) and sentence transformers for sentiment analysis and topic modeling, respectively. This approach is intended to enhance the accuracy and depth of consumer sentiment analysis. Method: sentiment analysis and topic modeling are applied to a large dataset of smartphone reviews sourced from Kaggle and Amazon. The BERT model is used to understand the context and sentiment of words, while sentence transformers generate embeddings for clustering reviews into thematic topics. Results: our analysis revealed strong positive sentiments regarding smartphone performance and user experience, while also identifying concerns about camera and battery life. However, while the model effectively captures positive feedback, it may struggle with negative feedback and especially neutral sentiments, due to the dataset’s bias toward positive reviews. Conclusions: the application of BERT and sentence transformers provides a significant technological advancement in the field of text analysis by enhancing the granularity of sentiment detection and offering a robust framework for interpreting complex data sets. This contributes to both theoretical knowledge and practical applications in digital consumer analytics. Objectives smartphones strategies dualmodel dual (BERT respectively Method Amazon words topics Results experience life However datasets s Conclusions sets analytics

Abstract: This research examined a moderated mediation model for answering how and why work-life balance affects employee job performance, and how satisfaction with coworkers is contingent upon it by enhancing employee’s psychological wellbeing. Data were collected from subordinates and their supervisors in the banking sector (N = 284). Empirical results indicate that psychological wellbeing mediates the link between work-life balance and job performance, and employees’ satisfaction with coworkers enhances job performance by strengthening the effect of work-life balance on psychological wellbeing. This research contributes to personnel management literature by describing moderated mediation mechanisms through which work-life balance influences employee job performance, and guides practitioners by emphasizing that employees with greater work-life balance perform better when their psychological wellbeing is reinforced by their satisfaction with coworkers.

Resumen: Esta investigación examina un modelo de mediación moderada para responder cómo y por qué el equilibrio entre vida personal y laboral afecta el desempeño del trabajo de los empleados y cómo la satisfacción con los compañeros de trabajo influye en ello al mejorar el bienestar psicológico de los empleados. Se recabaron datos de subordinados y sus supervisores del sector bancario (N = 284). Los resultados empíricos indican que el bienestar psicológico media el vínculo entre el equilibrio de vida personal y laboral y el desempeño del trabajo, y la satisfacción de los empleados con los compañeros de trabajo mejora el desempeño del trabajo, fortaleciendo el efecto de este equilibrio en el bienestar psicológico. La investigación contribuye a los estudios sobre gestión de personal mediante la descripción de mecanismos de mediación moderada, a través de los cuales el equilibrio entre la vida personal y la vida laboral influye en el desempeño laboral de los empleados, y sirve de guía a los gestores de personal al destacar que los empleados con mayor equilibrio entre vida personal y laboral obtienen mejor desempeño cuando su bienestar psicológico se ve reforzado por su satisfacción con los compañeros de trabajo.