bluuebunny/crossref_metadata_2025 huggingface dataset:
Producción animal tropical sustentable
Authors: Araujo-Febres Omar , Vergara-Lopez Juan A.
Published: November 2024

La producción animal es un sector importante de la agricultura que proporciona alimentos, ingresos y empleo a millones de personas en todo el mundo. Los sistemas originales tradicionales de la América tropical fueron alterados para introducir sistemas de producción copiados de otras latitudes, destruyendo el ecosistema original. La alteración del ecosistema se refiere a la perturbación del equilibrio natural y de su funcionamiento. Se caracteriza por la pérdida de biodiversidad, cambios en la dinámica poblacional, modificación de los ciclos de nutrientes y de los servicios ecosistémicos, disminución de la resiliencia de los ecosistemas, cambios en los ciclos del agua, erosión del suelo, interrupción en los procesos de polinización, control de plagas. La producción ganadera regenerativa implica prácticas como: manejo del pastoreo: imitación de patrones de pastoreo naturales con altas cargas (Pastoreo de Ultra Alta Densidad - PUAD); eliminar la dependencia de biocidas; multiplicar la carga animal 5 o 6 veces. El consumo de leguminosas nativas, con alta carga de polifenoles, contribuyen a mantener animales más sanos y libres de parásitos. Se generan grandes beneficios para el medio ambiente. El suelo se convierte en un gran secuestrador de carbono, los árboles ayudan a reducir la temperatura ambiente, se mejora el ciclo del agua, aumenta la biodiversidad. Es urgente adaptar los sistemas de producción ganadera para conservar y mejorar los beneficios que suministran. El objetivo de este trabajo es resaltar la importancia de acoger un sistema de producción ganadera adecuado para el trópico.
La proteína recombinante de choque térmico HSPA1A incrementa la crioresistencia de espermatozoides de toro
Authors: Sancho José L. , Carrión Edison P. , Largo Estefany M. , Pando Heydi I. , Duma Mauricio , Vallecillo Antonio J. , Galarza Diego A.
Published: November 2024

Esta investigación evaluó el efecto de la proteína recombinante de choque térmico HSPA1A en espermatozoides bovinos sometidos a refrigeración durante 96 horas (5 °C), y congelación. Un experimento inicial determinó la concentración óptima de HSPA1A (0, 15, 30, y 45 µg/mL) suplementado al diluyente OPTIXcell, utilizando 18 eyaculados (de 2 toros) refrigerados durante 96 horas. Posteriormente, se evaluó el efecto de la suplementación de 45 µg/mL de HSPA1A (como concentración óptima) al diluyente OPTIXcell, utilizando 6 eyaculados sometidos a congelación mediante vapores de nitrógeno líquido estático. Los resultados indicaron que todas las concentraciones de HSPA1A produjeron mayores valores de las variables cinemáticas, de viabilidad y de integridad acrosomal que su control, durante 96 horas de refrigeración (p < 0,05). Además, con 45 µg/mL HSPA1A mostraron un valor más alto de frecuencia de batida de flagelo (BCF) que las otras concentraciones de HSPA1A (p < 0,05). Tras la descongelación, las motilidades, la BCF y los índices de crioresistencia de motilidad, viabilidad e integridad acrosomal fueron mayores en muestras congeladas con la proteína HSPA1A comparadas con el control (p < 0,05). En conclusión, la proteína recombinante HSPA1A mejoró la motilidad, viabilidad e integridad acrosomal de espermatozoides de toro refrigerados y congelados.
Estimación del índice de temperatura humedad (ITH) para sistemas de producción bovina en Morona Santiago, resultado preliminar
Authors: Congo Carlos D. , Chuquimarca Edgar J. , Torres Néstor F. , Quezada Nelly G. , Garzón Juan P.
Published: November 2024

El objetivo del estudio fue caracterizar las condiciones climáticas durante el periodo de mayor pluviosidad en la Amazonía sur del Ecuador (marzo a julio de 2024), utilizando el índice de temperatura y humedad (ITH). Los datos se recopilaron mediante un datalogger (SensorPush) y fueron sistematizados en el software GANADERO TP®. En total, se analizaron 218.915 registros de temperatura y humedad, los cuales fueron descargados en formato compatible con Microsoft Excel. El análisis se realizó aplicando estadística descriptiva y los umbrales preestablecidos por el Instituto Nacional de Investigación Agropecuaria de Uruguay para determinar el riesgo de estrés calórico. Se consideraron estados de alerta para sistemas lecheros con un ITH entre 68 y 71,9, y para sistemas de carne entre 69 y 74,9. No se detectaron olas de calor en el periodo estudiado, sin embargo, se observó un efecto acumulativo con un ITH ≥72, lo que implica alerta y peligro en la producción de carne y leche, afectando potencialmente la salud, bienestar y reproducción de los animales. Estos resultados preliminares son fundamentales para el desarrollo de una herramienta predictiva de bajo costo que ayude a mitigar los efectos del estrés térmico en los sistemas ganaderos de la región. Es crucial continuar los estudios de caracterización climática en la Amazonía sur ecuatoriana para crear soluciones que permitan a los productores y asesores tomar decisiones informadas y aplicar estrategias que reduzcan los impactos adversos del calor.
Enriquecimiento ambiental con música durante el ordeño: efecto sobre la producción, calidad de la leche y comportamiento de la vaca
Authors: Garay Gabriela , Sarango Mildred , Dávila Karla , Narváez Dalia , Ayala Luis
Published: November 2024

La investigación fue realizada en la granja experimental de Nero de la Universidad de Cuenca. El objetivo de la investigación fue evaluar el efecto de dos géneros musicales sobre la producción, calidad de leche y la conducta animal durante el proceso de ordeño. Para esto se evaluaron 33 vacas Holstein multíparas durante cinco semanas consecutivas, que se encontraban dentro del primer tercio de su producción láctea. Las variables analizadas fueron la producción de leche diaria (Lts/día), calidad de leche (grasa, solidos no grasos, proteína y recuento de células somáticas) y se valoró la conducta animal mediante un etograma (movimiento de la cabeza, orejas, cola, extremidades posteriores, mugidos, micción y defecación). La primera semana fue considerada como el tratamiento testigo, la segunda como de ambientación al género musical clásico, en la tercera se valoró este género, en la cuarta semana se procedió a realizar ambientación del género musical electrónico y en la quinta semana se tomó las valoraciones del mismo. La implementación de música durante el ordeño no influyó sobre la producción láctea de 13,6±0,66 Lts/día (1era semana), 14,1±0,53 Lts/día (3ra semana) y 5ta semana 15,4±0,87 Lts/día. Igual sucedió con el porcentaje de grasa, solidos no grasos y proteína; sin embargo, los animales al ser expuestos a los dos géneros musicales disminuyeron sustancialmente el número de células somáticas (P<0,05); además, se mostraron más tranquilas ya que realizaron menos movimientos de cabeza, cola, extremidades posteriores, mugidos, defecaciones y micciones (P<0,01). Se concluye que ambientar la sala de ordeño con música permite que los animales mejoren su conducta, lo cual se refleja en una mayor calidad de la leche.
Vesículas extracelulares: Mediadoras en la interacción materno-embrionaria bovina
Authors: Cajas Yulia Nathaly , Burbano Espín Kevin , Gonzalez Martínez Maria Encina , Cañon-Beltran Karina
Published: November 2024

Las vesículas extracelulares (VEs) son cruciales para la comunicación intercelular, transportando proteínas, lípidos y ácidos nucleicos. Desempeñan un papel vital en las interacciones materno-embrionarias, esenciales para establecer y mantener de la gestación. Las VEs del oviducto mejoran el desarrollo temprano del embrión al influir en la proliferación celular, la actividad mitocondrial y la expresión génica. La interacción es bidireccional y los embriones también afectan el oviducto a través de microARN y proteínas. Posteriormente, cuando el embrión se implanta en el útero, las VEs son cruciales para la elongación del concepto y el reconocimiento de la preñez al afectar la proliferación celular y la expresión génica. Esta revisión resume el papel de las VEs en el apoyo al desarrollo previo a la implantación y la gestación temprana, destacando su importancia en el éxito reproductivo y el potencial para mejorar la eficiencia de la reproducción animal.
Exploring the interplay between students' scientific competence and teaching instructors' TPACK: A comprehensive analysis
Authors: Sonsupap Kanyarat , Cojorn Kanyarat , Sitti Somsong
Published: November 2024

This exploratory research investigates the scientific competence levels among secondary school students in the North Eastern region of Thailand in the post-COVID-19 era and examines the relationship between teachers’ Technological Pedagogical Content Knowledge (TPACK) and students' scientific competency. The study collects data from 76 science teachers and 1878 students representing 76 schools in the northeast of Thailand. The study employs a set of instruments, including 1) the 28 items of the TPACK questionnaire and 2) the scientific competency measurement tool. The findings reveal that the overall scientific competency score among students reflects a moderate level. Specifically, students demonstrated moderate competence in "explaining phenomena scientifically" and "evaluating and designing scientific inquiry," while their ability to "interpret evidence and data scientifically" was found to be at a low level. Furthermore, there is a significant but low-level correlation between the scientific competency of students and the TPACK of their teachers. The findings highlight the urgent need for a pedagogical shift in educational practices. There is a pressing need to design learning experiences that emphasize scientific inquiry and critical thinking rather than focusing solely on subject matter expertise. Strengthening teachers' capacity to integrate technology with pedagogy alongside fostering inquiry-based learning approaches will be crucial in improving students' scientific competencies and preparing them to handle challenging problems in the contemporary world.
Marketing in the spa industry: How does marketing affect the performance of spa businesses in Slovakia?
Authors: Viera Kubickova , Jozef Gall , Maria Halenarova
Published: November 2024

This research delves into the influence of marketing on the performance of spa businesses in Slovakia, a sector with a rich historical background and significant potential for growth. This study aims to examine the role of marketing in the spa industry in Slovakia and its impact on the performance of selected spa businesses. This study utilizes regression analysis in statistical software R to assess financial data from twenty-five spa businesses in Slovakia spanning from 2012 to 2022 comprising 198 data points. In addition, the study investigates the use of social media platforms in spa marketing by examining the online communication practices of selected Slovak spa businesses and their international counterparts. The results indicate that although the use of social media in the marketing strategies of Slovak spa businesses is currently limited, marketing expenditures significantly influence the sales of these businesses. This highlights the potential for improved performance through more strategic marketing, particularly digital channels. The limitation of this study is the availability of statistical data in the environment of spa businesses in Slovakia which significantly limits the results of the study. The findings emphasize the importance of effective marketing implementation in the Slovak spa industry with a specific focus on the necessity for increased digitization and the use of social media platforms. This insight is essential for spa businesses seeking to optimize their marketing efforts and enhance overall business performance.
Narcissism, Self-Esteem, and Compulsive Buying: Unraveling the Role of Social Media Usage
Authors: Dhewi Titis Shinta , Sumarsono Hadi , Narmaditya Bagus Shandy , Ridzuan Abdul Rahim
Published: November 2024

This paper aims to examine the effect of social media on compulsive buying among youth in Indonesia, using narcissism and self-esteem as mediators to predict compulsive buying. To obtain the data, a self-administered online survey using a 5-point Likert scale was completed by Indo­nesian youth. More than 300 online questionnaires were distributed to the targeted respondents with a purposive sampling approach. Structural equation modeling is provided in partial least squares for a visual representation of the linkage between variables. The statistical analysis indicates that narcissism is significantly related to social media usage and compulsive buying, while self-esteem is not linked with compulsive buying among youth in Indonesia. The presence of social media can solely mediate the connection between narcissism and compulsive buying. However, it found that social media failed to mediate the linkage between self-esteem and compulsive buying. The output of this study will provide practical and theoretical implications for con­sidering the primary role of social media. This research guides policy scholars, educational institutions, and governments in Indonesia on how to pay special attention to compulsive buying behavior among youth.
The Impact of the Business Life Cycle on the Relationship between Excessive ESG and Firm Value
Authors: Kim Suyon
Published: November 2024

This study aims to investigate the impact of the business life cycle on the relationship between excessive ESG and firm value through regression analysis. The study targeted Korean firms from 2016 to 2021, and the findings revealed a negative correlation between excessive ESG investment and firm value. After including the business life cycle in the analysis, no relationships were found during the introduction and decline stages between these two factors. However, excessive ESG positively impacts firm value during both the growth and mature stages of the business life cycle. In the growth stage, firms need a strategy that distinguishes them from other competitors. Thus, ESG investments serve as a method for differentiation in a competitive market, resulting in a positive association between the two factors. Additionally, firms in the mature stage possess substantial cash flow, enabling them to engage in a wider array of socially responsible initiatives. Therefore, in both stages, excessive ESG aligns with strategic objectives and is critical for enhancing firm value. This study suggests that companies can strategically leverage ESG investments to maximize firm value according to the different stages of the business life cycle.
Research Progress of Deep Learning in Diagnosis, Treatment and Prognosis Assessment of Hepatocellular Carcinoma
Authors: Lin Mianlei , Wu Qian , Zhao Caitao , Wu Yingning
Published: November 2024

Hepatic carcinoma (HCC) is a common malignant tumor in the abdominal system in China. Due to its high degree of malignancy, poor prognosis and easy recurrence, there are many therapeutic programs available, but the results are not satisfactory. The use of deep learning (DL) for diagnosis, treatment and prognosis assessment of HCC patients has become a hot topic at present. Therefore, this paper reviews the application of DL in early diagnosis, microvascular infiltration, pathological grading and postoperative evaluation of HCC.
Short Term Prediction of Urban Traffic Flow based on Machine Learning Algorithms
Authors: Wang Conghe
Published: November 2024

With the increasing per capita car ownership worldwide, existing transportation facilities are unable to fully meet people's travel needs. The massive traffic flow can lead to traffic congestion, so predicting traffic flow can play a crucial role in urban traffic management. This study predicts the westbound traffic flow data of the Minnesota Department of Transportation (MN DoT) ATR 301 station on Interstate 94 in the United States for 28 consecutive days using a Long Short-Term Memory Network (LSTM) data prediction model. The Random Forest is utilized to analyze the association between attributes and the historical data has been separated into 1-hour intervals. The highway displays a bimodal pattern on weekdays and a unimodal pattern on holidays, according to the final forecast results. Furthermore, after making the necessary adjustments to the parameters, the simulated trend closely resembles the real value, proving that LSTM can be used to model short-term traffic flow. Accurately predicting urban traffic flow can make the management of urban traffic management systems more comprehensive and provide citizens with higher quality travel planning references.
Traffic Accident Prediction based on CNN and Time of Commuting after Accident
Authors: Wang Sibo
Published: November 2024

To address the challenges associated with traffic accident detection and the subsequent impact on commute times, a method combining CNN and Linear Regression models is proposed. Initially, this approach involves classifying specific accident data using images and detailed accident records. The images are then categorized into binary groups—accident and non-accident. Post-accident detection does not necessitate high-speed detection or extensive data processing; CNN are sufficiently capable for this purpose. Traffic accidents are an inevitable part of daily driving and can lead to significant delays in commuting. In rare cases, accidents may result in participants falling into a coma, further delaying rescue efforts. The proposed method aims to enhance road safety and traffic efficiency by promptly identifying accidents and minimizing the disruption caused to commute times through advanced technological solutions. By leveraging CNN for image analysis and Linear Regression for data modeling, this approach seeks to streamline accident detection processes, thereby improving overall traffic management and safety measures. This methodological framework underscores the importance of integrating cutting-edge technology to mitigate the adverse effects of traffic accidents on daily commuting.
Applications and Challenges of Protein Quality Assessment in Food
Authors: Cong Yang , Zhang Ruiming
Published: November 2024

As a key nutrient to maintain normal physiological functions of the human body, protein plays an increasingly important role in people's pursuit of a healthy life. With the growing demand for healthy dietary standards, the evaluation of protein quality in food has become particularly critical, providing a scientific basis for the innovation and development of healthy foods. Given the diversity of protein sources, fluctuations in content, and the complexity of amino acid composition, it is crucial to choose appropriate evaluation methods to accurately analyze the protein quality in food. This article deeply explores the protein quality evaluation methods widely used internationally, with a particular focus on the two evaluation systems of digestible amino acid score (DIAAS) and protein digestibility corrected amino acid score (PDCAAS). This article analyzes in detail the application scope, advantages, and challenges that may be encountered in practical applications of these two methods, aiming to provide a solid theoretical support for the development of high-quality protein foods.
Study on dynamic response distribution of excavated highway slope under dynamic action
Authors: Wang Zhixiang , Xie Shuli , Liu Linlin
Published: November 2024

In order to study the dynamic response distribution law of highway foundation pit slope under seismic dynamics, the dynamic response distribution law of cutting slope at different grading heights was compared and studied, and the dynamic instability model under gravity instability and seismic disturbance was established by using UDEC700 software, and the simulation calculation was carried out. The difference between static instability and dynamic instability of fractured rock slope is compared and analyzed, and the post-earthquake stress is greater than that before the earthquake. Under the action of power, the velocity at the top of the slope is greater than the velocity at the bottom of the slope, the velocity outside the upper platform is greater than the velocity inside, and the velocity inside the lower platform is greater than the velocity outside. This provides a new perspective for understanding the dynamic response of highway foundation pit slope under seismic dynamics.
Short-term Subway Passenger Flow Prediction based on LSTM and ARIMA Model
Authors: Ma Yunhao
Published: November 2024

With the acceleration of urbanization, urban traffic problems have become increasingly severe. To alleviate urban traffic congestion, the development of public transportation has been greatly emphasized. As a convenient and rapid means of urban travel, the metro has become the preferred choice for citizens, leading to significant passenger flow pressure. Therefore, it is crucial to forecast passenger flow in advance. This paper utilizes passenger flow data from Chengdu Metro Line 1 from May to September 2019 to conduct a study. LSTM and ARIMA models were constructed to simulate the actual passenger flow data. The prediction performance of both models shows that the trends simulated by these models fit the original data well, verifying their applicability in passenger flow forecasting. Furthermore, it was found that the LSTM model outperformed the ARIMA model among the constructed models in this paper. Accurate metro passenger flow forecasting can help relevant departments manage the metro system more effectively, thereby improving passenger travel efficiency and safety.
Effectiveness of Systemic Immune-Inflammatory Index in Predicting Bone Metastasis in Newly Diagnosed Prostate Cancer Patients
Authors: Song Rilian , Wei Gaomeng , Lu Baode , Jian Dingxi , Zhang Zilu
Published: November 2024

Objective To explore the effectiveness of systemic immune inflammation index (Systemic immune-inflammation index, SII) in predicting bone metastasis in patients with newly diagnosed prostate cancer (Prostatic cancer, PCa). Methods The retrospective analysis of 200 cases of prostate cancer from January 2020 to June 2023 and 70 cases of bone metastasis compared the expression difference of SII between the two groups and analyzed the clinical diagnostic value of SII in prostate cancer bone metastasis. The resulting SII in the bone metastasis group was 500.63(351.24-696.57) 109/ L, the SII in the no-bone metastasis group was 350.12(258.41-529.40) 109/ L, statistically significant, P <0.05. The ROC curve analysis revealed that its sensitivity was 68.63% and its specificity was 60.95%. Conclusion System immune inflammation index (SII) has certain application value for bone metastasis in patients with newly diagnosed prostate cancer (PCa), and high level of SII indicates poor prognosis, which is worth further clinical study.
Text Mining for Ford Car Review Data – Based on Sentiment Analysis, LDA Topic Model, Semantic Web Analysis
Authors: He Qiongli , Li Jie , Li Linchao
Published: November 2024

As an established automotive brand with its origins in the early twentieth century, the Ford brand has developed a distinctive global influence over the course of decades. In order to gain insight into customer perceptions of the brand, this study employs a data set comprising customer evaluations of the Ford automobile between 2002 and 2018. Firstly, word frequency statistics are calculated in order to demonstrate the key points that are predominantly mentioned by customers. Subsequently, a sentiment analysis is conducted to categorise the keywords into two distinct groups: the positive and the negative. These groups represent the positive and constructive feedback provided by customers, respectively. Subsequently, latent Dirichlet allocation based on sentiment analysis was employed to identify five themes comprising positive and negative words. These included car appearance, user experience, car performance, comfort, and brand recognition. Furthermore, in order to gain insight into the semantic relationships between these reviews, a semantic network analysis was employed to demonstrate the interactions between the key points. In conclusion, the above analysis provides an overview of the Ford brand based on user reviews. The findings of this study may prove valuable in informing future improvements to Ford's automobile sales and manufacturing processes.
The Construction of a Mathematical Modeling Curriculum System Oriented by New Engineering Talents
Authors: Chen Huiqin
Published: November 2024

This article provides an overview of the research progress on mathematical modeling courses both domestically and internationally, and points out the main problems that currently exist. Propose to no longer include competition results in the evaluation criteria, and establish its own training model based on the actual situation of the school. With the assistance of teachers, establish cross disciplinary projects. Teach students to apply knowledge to new problems, allowing more students to achieve more lasting results. The role and significance of research projects in promoting teaching work and improving teaching quality, and the specific research objects and contents. The main research subjects are students from most majors in science and engineering at our university. The main value lies in the exploration and practical work done in the field of new engineering education to cultivate students' mathematical literacy and numerical calculation ability.
Research on Traffic Scene Element Recognition for Autonomous Driving Based on Deep Learning
Authors: Zhang Yangguoer
Published: November 2024

This paper introduces the overall research status in the field of autonomous driving, followed by an overview of the research status of multi-lane line recognition algorithms, 3D object detection algorithms, and multi-target tracking algorithms in autonomous driving. However, the road scene in the real environment is complex and changeable, and there is still room for improvement in the real-time performance and accuracy of existing traffic sign detection and recognition methods.
From Selective Recall to Collective Memory: On Moll Flanders’ Insinuation about 18th-century England
Authors: Wang Qin
Published: November 2024

As a male author, Defoe breaks the traditional literary paradigm and depicts the memoirs of working women who took the initiative to commit crimes due to the fear of poverty. With the help of memory theory, this paper employs memory theory in conjunction with literary works to examine specific situations that the main character, Moll Flanders, either selectively recalls or ignores. The social context of eighteenth-century England, which is the image of collective memory, is recreated from the perspective that individual memories are constructed in interactive experiences and are always associated with the social context of the time. This includes the social disparity between the rich and the poor, moral and ethical dilemmas, and social class disparities; additionally, the reasons behind the protagonist's decisions and behaviors in a particular situation are explored.
Study on Propeller Positioning and Trajectory Control of Underwater Robots Based on Bayesian Inference and Multi-Objective Optimization
Authors: Yang Xiaohan , Tang Yidong , Yan Chengyu , Xu Chenxi , Ding Feiyang
Published: November 2024

In ocean exploration, the positioning and trajectory optimization of underwater vehicles are critical research areas that directly impact the success of ocean resource exploration, environmental monitoring, and search and rescue missions. However, the complex and uncertain marine environment poses significant challenges. This study first determines the three-dimensional spatial position of the underwater vehicle, calculates the vehicle's speed in the marine environment through mechanistic analysis, traversing the initial position, velocity, acceleration, angular velocity and angular acceleration of the submersible, fits the motion trajectory using a random walk, and uses Bayesian inference to estimate maximum probability positions of submersibles and select the optimal initial deployment point. To better cope with real-world scenarios involving ocean currents and the diverse motion modes of underwater vehicles, this study further used an improved genetic algorithm to divide the motion trajectory of the submersible into a series of discrete path points, and constructed a multi-objective optimization model with the shortest search and rescue time and the maximum probability of successful search and rescue as the objective function to realize the precise positioning of the lost underwater vehicle.
Research on traffic congestion prediction based on analyzable machine learning
Authors: Li Yixin , Zhang Wenqi
Published: November 2024

As motor vehicles proliferate around the world, traffic congestion increases, hindering travel, polluting the environment and hampering economic growth. Accurate congestion prediction is the key to optimizing traffic flow. In this study, the interaction between different traffic modes and congestion degree is deeply investigated, and a high-fidelity prediction model is established. The study analyses monthly, weekly, daily and hourly multi-modal traffic and congestion data and identifies congestion patterns. In this paper, Pearson's coefficient is applied to identify the key influencing factors, and congestion is predicted by KNN, logistic regression, decision tree and random forest models. The random forest model reaches 99.88% accuracy after 5-fold cross-validation and grid search optimisation. Further analysis using the Random Forest's feature importance scores revealed that traffic volume was the most important predictor of congestion, while time factors such as time and date played a smaller role. This study not only establishes a robust congestion prediction model, but also emphasizes the importance of traffic volume in congestion prediction. The findings provide valuable insights for traffic management agencies to take proactive measures to alleviate traffic congestion. By harnessing the predictive power of random forest models, these agencies can increase the efficiency of traffic management, improve the overall travel experience, and contribute to sustainable urban development. This study also lays a solid foundation for future research in the field of traffic congestion prediction and management.
Traffic Prediction of Urban Intersections based on ARIMA Model
Authors: Chen Huihui
Published: November 2024

In the urban planning, road traffic planning as an important part, through the formation of traffic layout network, can further accelerate the pace of urban development. However, the blockage will cause the car to start and stop regularly, and the car engine will emit a large amount of exhaust gas in these two stages, resulting in increased environmental pollution. Therefore, the focus needs to be on how to predict traffic flow efficiently. This paper focuses on the traffic flow density of intersections in one month, presents the change of traffic density by means of mapping, reasonably divides the training set and the test set, and uses ARIMA model to make effective prediction. It shows the changing relationship between traffic flow and time. Through reasonable prediction, the congestion problem is found in the first time, and at the same time, the solution measures are given, the traffic infrastructure is scientifically allocated, and the safety control system is set up, which provides reference for the later urban traffic development.
Progress in PGK1 in Prostate Cancer
Authors: Lu Zhao , Su Lize , Qiu Rong , Huang Meiqiu , Huang Minyu
Published: November 2024

Phosphoglycerol kinase 1 (PGK1) is the first key metabolic enzyme that produces ATP during glycolysis and is involved in the glycolytic pathway of prostate cancer. PGK 1 can not only act as a metabolic enzyme to affect tumor growth, but also affect the gene expression, energy metabolism, molecular regulation and other processes of tumor cells through its non-metabolic enzyme function, and then mediate the growth, migration and invasion of tumors, and aggravate the biological characteristics of malignant cancer cells. In this review, we reviewed the structure and function of PGK1 and its relationship with prostate cancer to clarify the important role of PGK1 in the progression of advanced adenoma and provide a theoretical basis for targeting PGK1 for drug development.
ASSOCIATION OF VITAL SIGNS AND PAIN SCORE IN EMERGENCY DEPARTMENT
Authors: WAHEED A , IFTIKHAR H , WAHEED A , HUMAIRA . , KHAN AS
Published: November 2024

Accurate pain assessment is essential in emergency settings to ensure timely and effective management. Although self-reported pain scores are commonly used, healthcare providers often rely on vital signs, such as heart rate, respiratory rate, blood pressure, and temperature, as additional indicators of pain. However, the reliability of these vital signs in predicting pain remains unclear. Objective: To investigate the relationship between vital signs (heart rate, respiratory rate, blood pressure, and temperature) and self-reported pain scores in adult emergency department (ED) patients, evaluating the reliability of vital signs as pain indicators. This prospective obseMethods: rvational study was conducted over one month in the emergency department of a tertiary care hospital in Islamabad, Pakistan. A total of 201 adult patients (aged ≥16 years) presenting with pain were included, while those with altered mental status, non-painful complaints, or terminal illness were excluded. Upon arrival, vital signs and self-reported pain scores were documented using a standardized form. Pearson correlation coefficients were used to assess the association between each vital sign and pain score. Subgroup analyses further examined differences by demographics, pain etiology (traumatic vs. non-traumatic), and pain severity. Results: No significant correlation was observed between vital signs and pain scores (p < 0.001), suggesting that vital signs are not reliable indicators of pain intensity in ED patients. Conclusion: Vital signs, such as heart rate, respiratory rate, and blood pressure, show limited reliability as indicators of pain. Self-reported pain scores should be prioritized in pain assessment to ensure timely and accurate pain management, potentially improving patient satisfaction. Further multi-centre research is recommended to explore variations in pain relief strategies based on pain type and demographics.
EFFECTS OF ANESTHETIC STRATEGY ON PATIENTS' OUTCOMES WITH ACUTE BASILAR ARTERY OCCLUSION UNDERGOING MECHANICAL THROMBECTOMY
Authors: AMJAD MH , FAIZUDDIN . , ALASMAR O , AZIZ A , TARIQ M , FATIMA . , KHAN S
Published: November 2024

The anaesthetic strategy employed during mechanical thrombectomy for patients with acute basilar artery occlusion (ABAO) has become a topic of great interest in recent years. Objective: The main objective of the study is to find the effects of anaesthetic strategy on patients' outcomes with acute basilar artery occlusion undergoing mechanical thrombectomy. Methods: This retrospective observational study was conducted at Hameed Latif Hospital, Lahore, from January 2023 to September 2023. Data were collected from 85 patients divided into two groups based on the anaesthetic strategy used during the mechanical thrombectomy procedure. Group A consisted of patients who received general anaesthesia (n = 45), while Group B comprised those treated under conscious sedation (n = 40).Results: The time to procedure was significantly shorter in the CS group (28 ± 6 minutes) compared to the GA group (38 ± 7 minutes, p < 0.01). Both groups had similar procedure durations and revascularization success rates (80% for GA and 78% for CS, p = 0.8). In terms of functional outcomes, the CS group had a higher, though not statistically significant, percentage of patients with favorable mRS scores at 90 days (55% vs. 44%, p = 0.3). The GA group experienced higher rates of peri-procedural hypotension (24% vs. 10%, p = 0.05), while 90-day mortality rates were slightly lower in the CS group, but not significantly different (25% vs. 33%, p = 0.4). Conclusion: It is concluded that both general anaesthesia (GA) and conscious sedation (CS) are effective anaesthetic strategies for patients undergoing mechanical thrombectomy for acute basilar artery occlusion, with no significant difference in revascularization success or mortality.
COMPARATIVE STUDY OF FUNCTIONAL OUTCOME OF HAMSTRING VERSES BPTB GRAFT IN ACL RECONSTRUCTION
Authors: ULLAH N , KHAN B , HUSSAIN AM , SHOIB M , KAKAR KK , KAKAR SU
Published: November 2024

Anterior cruciate ligament (ACL) injuries are among the most common knee injuries requiring surgical intervention. The choice of graft for ACL reconstruction—hamstring or bone-patellar tendon-bone (BPTB)—remains debatable due to differences in functional outcomes and complications. Objective: To compare the functional outcomes of ACL reconstruction using hamstring and BPTB grafts regarding knee stability, range of motion (ROM), patient satisfaction, and complication rates. Methods: This retrospective study included 150 patients who underwent ACL reconstruction, divided into two groups: 75 received hamstring grafts (Group A), and 75 received BPTB grafts (Group B). Clinical evaluations and patient-reported outcomes were assessed at 6 and 12 months post-surgery. Statistical analysis was performed using SPSS software, with a p-value <0.05 considered significant. Results: Knee stability was achieved in 90% of patients in the hamstring group and 94% in the BPTB group. Group A demonstrated better ROM recovery (130° ± 5 vs. 125° ± 5) and a lower complication rate (12% vs. 25%). Patient satisfaction was higher in the hamstring group (92% vs. 85%), while return-to-sport rates were slightly higher in the BPTB group (82% vs. 78%). Anterior knee pain was more prevalent in the BPTB group (28% vs. 10%). Conclusion: Both grafts are effective for ACL reconstruction, but each has distinct advantages and limitations. The BPTB graft offers superior initial stability and return-to-sport rates but is associated with higher complications. The hamstring graft provides better ROM, fewer complications, and higher patient satisfaction, making it a preferred choice for smoother rehabilitation. Graft selection should be individualized based on patient needs and activity levels.
Ex-situ conservation studies on some rare, endangered and endemic plant species at NBRI Botanic Garden
Authors: Goel Anil
Published: November 2024

Plants diversity is recognized universally as a vital part of world’s natural heritage and most essential living source on this planet. They are considered as key component for the global sustainability. The present era has been of significant biological extinction due to loss of various habitats of plants arising primarily through the human interference for his materialistic needs. It has been now seriously realised that the conservation of plant diversity should be accorded topmost global priority under the biodiversity conservation programmes. In order to face the challenge towards threats to plant diversity, Botanic Gardens have to play a leading role to conserve the plant resources during 21st century. The Botanic Gardens are developing fast as the important protectors of species of wild plants. The present communication deals with the ex-situ conservation studies in the Botanic Garden at NBRI, Lucknow.
Improving Statistical Literacy for Physician Scientists: Sampling Distributions
Authors: Troy Jesse D. , Falvey Caroline , Angermeier Suzanne , Pomann Gina-Maria , Grambow Steven C. , Neely Megan L. , Samsa Gregory P.
Published: November 2024

This is the first in a multi-part series on teaching statistical inference to physician-scientists training to work as members of interdisciplinary scientific teams. This unique student audience has greater scientific sophistication than a typical statistics student but less background in mathematics and computer programming, which presents challenges for traditional approaches to teaching statistics. Here, we illustrate an innovative approach to teaching sampling distributions to physician-scientists. Sampling distributions are a fundamental element of statistical inference; they are a building block of confidence intervals and hypothesis tests which are vital tools for performing clinical research. As such, it is essential that physician-scientists have a strong foundation in sampling distributions. Key elements of our innovative approach include the use of a running example, delivery of content in small pieces to reduce cognitive burden, preceding formulae with pictures, combining static and dynamic content using an R Shiny app, and use of self-graded quizzes to provide immediate feedback. The resulting course module can be reused in multiple contexts, including as part of self-directed, asynchronous learning or by incorporation into a traditional or flipped classroom setting.
A Deep Reinforcement Learning Framework for Optimized Container Scheduling and Load Balancing
Authors: Bhukya Sreedar , P Suraj Goud , K Yuvraj , K. Harin Goud
Published: November 2024

Unlike VMs, containerization is a modern method for packaging and deploying software in distributed environments like the cloud. Containers are widely used due to their efficient software packaging and deployment. Efficient management of containers is crucial in dynamic cloud environments with heterogeneous infrastructure. Deep learning techniques are being applied to optimize resource utilization in cloud environments, including mapping containers to suitable nodes for energy conservation. However, the existing works on container scheduling have limitations like inability to cope with dynamic runtime scenarios. To overcome this problem, the aim of this paper is to design and implement a framework using deep reinforcement learning techniques to improve container scheduling and load balancing. The proposed algorithm, Reinforcement Learning based Container Scheduling (RLbCS), uses an action-reward iterative approach to optimize container scheduling. Experimental results showed that RLbCS outperformed existing methods, achieving a 92% success rate in placing containers and optimizing resource utilization. The proposed method can be integrated with cloud-based systems to automatically schedule containers for resource optimization and load balancing.
Nanotechnology in Food: Processing, Packaging, and Preservation
Authors: Jamshaid Aqsa , Ibrahim Shumaila , Ali Adeeba , Basim Muhammad , Atta Aliyya , Haseeb Muhammad Asjad , Ullah Sami , Saleem Muhammad Bin , Walait Manam
Published: November 2024

Nanotechnology entails creating, characterizing, and employing structures with sizes ranging from 1 to 100, significantly influencing medicine, engineering, agriculture, and food. Nanomaterials hold potential for the development of high-quality, healthier, and safer foods improving shelf life and reducing contaminations. Food safety and security are gaining much attention globally to maintain a consistent supply of nutrient-rich and safe food. Many disciplines of food science have been changed by the rapid growth of nanotechnology, particularly those involving food storage, processing, functioning, packaging, transportation, and other safety considerations. This review focuses on current advancements in food nano-packaging, such as active, smart, and improved packing. Nano-encapsulation improves food processing by releasing bioactive chemicals, increasing bioavailability, and extending shelf life. Additionally, applications of nanotechnology in agriculture and food, including nano-sensors, nano-encapsulation, nanocomposites, food packaging, and nano-emulsions are discussed. Despite tremendous advancements in nanotechnology in food items, nanomaterials and nanoparticle toxicity are not fully understood. If the chemical mechanisms through which nanomaterials interact with food are not completely understood, we may face a nano-toxicity catastrophe, hence they must be further characterized and their usage must be carefully controlled.
Development and Quality, Chemical and Sensory Evaluation of Nutritive Herbal Blend
Authors: Manzoor Shanza , Shahbaz Muhammad , Khan Muzaffar Ali , Raza Nighat , Sibt-E-Abbas Muhammad , Naeem Hammad , Hammad Ul Hassan Muhammad , Momal Ushna , Mujtaba Ahmad , Qaisrani Tahira Batool
Published: November 2024

Herbal blends have obtained popularity due to their health benefits, good fragrance and antioxidant capacity. Herbal tea is a famous drink due to its low cost, attractive taste and aroma. Objectives: To assess the nutritional properties of herbal blends and to develop an herbal blend using locally available herbs. Methods: The developed herbal blend was 40% rose, 15% lemongrass, 15% Tulsi leaves, 10% cinnamon, 10% ginger and 10% fennel. Rose, Tulsi and lemongrass leave was dried in a hot air oven. All ingredients were ground. Then this prepared ground herbal mixture was subjected to proximate analysis for moisture, ash content, crude protein, crude fat and crude fiber. Afterwards, physiochemical and sensory tests of prepared tea were done to check the pH, colour and sensory evaluation of the tea. Then the developed tea was subjected to phytochemical and antioxidant activity assays to check total phenolic contents and 1,1-Diphenyl-2-picrylhydrazyl. Proximate analysis and physiochemical analysis of the product were done at regular intervals. Results: Sensory characteristics and consumer acceptability of mixed herbal blends as tea alternative was evaluated through the hedonic survey. Sensory scores were higher for the prepared herbal blend as compared to the control. Conclusions: It was concluded that the developed herbal blend possessed significant nutritional value and antioxidant activity, making it an attractive alternative to tea. Its pleasant taste and ability to stay stable over time indicate that herbs can be used to make healthy, inexpensive drinks. Further studies are required to enhance its functional applications.