bluuebunny/crossref_metadata_2025 huggingface dataset:
Diagnóstico sobre rasgos de inteligencia emocional en estudiantes de educación superior pública
Authors: Armenta Verdugo Estrella Evelyn , Olayo-Valles Jorge Alberto , Ramírez-Castillejo Griselda , Romero-Ruiz María Estela , Reyes Mérida César Ponciano Adrián
Published: December 2024

La inteligencia emocional en el ámbito laboral y en la formación de profesionistas cobra cada vez más importancia. Dada la retroalimentación recibida por parte de los empleadores de los egresados del Tecnológico Nacional de México campus Tláhuac (TecNM – Tláhuac), se llevó a cabo este estudio de diagnóstico sobre los niveles de inteligencia emocional (IE) en estudiantes de último año del TecNM – Tláhuac, con el objetivo de identificar factores demográficos que puedan influir significativamente en su formación en IE. Se utilizó el Cuestionario de Rasgos de Inteligencia Emocional (TEIQue-SF) y se realizó un análisis estadístico que incluyó pruebas de normalidad y cálculo del coeficiente de correlación de Pearson entre variables demográficas y los puntajes de IE. Los resultados mostraron que hay una correlación directa moderada entre la situación laboral y el puntaje global de IE (r = 0.49); la situación laboral y el aspecto de sociabilidad (r = 0.53); así mismo, una correlación inversa moderada entre vivir con ambos padres y el aspecto de la emocionalidad (r = -0.57); y una correlación directa moderada entre tener dependientes económicos y el aspecto del bienestar (r = 0.49). Estos resultados sugieren que el empleo y las responsabilidades económicas pueden estar asociados con mayores niveles de IE, mientras que vivir con ambos padres podría tener un efecto contrario. Se concluye que estos hallazgos proporcionan información útil para planear estrategias de intervención, así como las variables para identificar a los estudiantes a quienes deben ir dirigidas, para fortalecer la formación en habilidades emocionales de los estudiantes de manera efectiva.
Rol de la Enfermería en la Promoción de la Salud y Prevención de Enfermedades en Comunidades Vulnerables
Authors: Herrera Guanopatin Mónica Silvana
Published: December 2024

La atención primaria de salud es esencial para garantizar sistemas de salud equitativos y accesibles, especialmente en comunidades vulnerables. La enfermería desempeña un papel crucial en la promoción de la salud y la prevención de enfermedades mediante estrategias educativas, cuidado integral y liderazgo en la implementación de innovaciones. Este estudio tiene como objetivo analizar las funciones de la enfermería, las barreras enfrentadas y las estrategias innovadoras aplicadas en APS, utilizando una revisión integrativa de la literatura. Se identificaron 38 artículos relevantes en bases de datos como Google Scholar, SciELO y PubMed, tras filtrar 970 resultados iniciales. Los hallazgos destacan que la enfermería contribuye significativamente a reducir riesgos, mejorar la adherencia a tratamientos y empoderar a las comunidades mediante modelos educativos y organizativos. Sin embargo, enfrenta barreras como la sobrecarga laboral, limitaciones de recursos y restricciones regulatorias, que afectan la calidad del cuidado. Las estrategias innovadoras, como modelos virtuales de atención, talleres educativos y clínicas autogestionadas, han demostrado ser efectivas para superar estas limitaciones. Este estudio concluye que, a pesar de los desafíos, la enfermería tiene un impacto transformador en APS, especialmente al implementar prácticas basadas en evidencia que fortalecen el acceso y la calidad del cuidado. Es crucial continuar fortaleciendo el liderazgo, la formación y la integración tecnológica en la práctica de enfermería para garantizar sistemas de salud más sostenibles y equitativos.
Vermiestabilización de Lodos con Contenido Ruminal Generados en el Camal de Sama, Tacna-Perú
Authors: Rodriguez Quispe Alejandra Marlitt , Alvarez Mayta Axel Andre
Published: December 2024

Los residuos de camal constituyen un potencial contaminante, en especial el contenido ruminal. En esta investigación se busca llevar un proceso de vermiestabilización de lodos con contenido ruminal generados en el camal de Sama, mediante la inoculación de la Lombriz Roja Californiana (Eisenia foetida). Se realizó un precompostaje de los lodos (L) y de residuos orgánicos domiciliarios (ROD) durante 4 semanas, después se aplicaron 4 tratamientos: T1 (L100%), T2 (L75% + ROD25%), T3 (L50% + ROD50%), T4 (L25% + ROD75%); y 3 repeticiones, 12 Unidades Experimentales (UE); se depositaron en total 1 kg de sustrato mezcla y 15 lombrices para cada UE en baldes de plástico, bajo sombra, durante 10 semanas. Se evaluaron las características fisicoquímicas contenido de pH, Conductividad Eléctrica, Nitrógeno, Fósforo y Potasio (N, P, K),  los resultados se analizaron estadísticamente y se compararon las medias con la prueba de rango múltiple de Tukey (p<0.05). La especie se adecuó de manera óptima en las UE, sobresaliendo el T3 con una mayor reproducción. En todos los tratamientos los parámetros se estabilizaron a condiciones óptimas para su uso edáfico a excepción de la Conductividad Eléctrica, solo el pH presentó diferencias estadísticas.
Análisis del Uso Problemático de TIC En Estudiantes Universitarios Mediante el MULTICAGE-TIC: Influencia de Género, Clasificación Generacional y Procedencia Cultural
Authors: Solano Pérez Gabriel , Salazar Partida Juan Miguel , Rodríguez Antonia Esparza , Márquez Pinedo Mónica , Trujillo García Fabricio Raúl
Published: December 2024

La presente investigación analiza la problemática del uso de las Tecnologías de la Información y la Comunicación (TIC) entre estudiantes universitarios, examinando variables como género, generación y origen cultural. Mediante el cuestionario MULTICAGE-TIC se identificaron los posibles problemas que éstos tienen con relación a la utilización del teléfono móvil, el Internet, los videojuegos, la mensajería instantánea y las redes sociales. Los resultados indican que los estudiantes tienen una existencia confirmada en el uso problemático de las tecnologías analizadas, con una mayor dependencia de las mujeres y la Generación Z. En los estudiantes indígenas también se identificaron problemas en el uso de algunas de estas tecnologías, los cuales surgen posiblemente por algunos factores culturales. Los resultados indican que el uso excesivo de las TIC impacta negativamente el rendimiento académico y el bienestar emocional, incidiendo en las psicopatologías como la ansiedad, el aislamiento y la comunicación cara a cara. Este estudio destaca la necesidad de intervenciones y estrategias de apoyo para el uso responsable de las TIC entre los estudiantes universitarios.
Usucapião de bem imóvel objeto de herança: resolvendo impasses familiares de décadas
Authors: Ferrazza Julia
Published: December 2024

Analisa-se no presente artigo a possibilidade de usucapião de imóvel objeto de herança, enfatizando seu papel na resolução de conflitos familiares e na regularização de bens. A partir da análise da jurisprudência do Superior Tribunal de Justiça (STJ), demonstra-se que, desde que comprovada a posse exclusiva, com efetivo animus domini pelo prazo legal e sem qualquer oposição dos demais herdeiros condôminos, a usucapião é meio de aquisição viável ao herdeiro que está na posse direta do bem. Conclui-se que tal solução valoriza o uso efetivo do bem imóvel, prestigiando a função social tanto da posse quanto da propriedade e atendendo às necessidades dos herdeiros, como moradia e renda.
Editorial: Artificial Intelligence and Operations Research in the Supply Chain
Authors: Bernábe-Loranca Maria Beatriz
Published: December 2024

Different authors during the development of computer science have dedicated appropriate words to define Artificial Intelligence (AI), almost all of them equally valid. In a wide sense, it has been defined considering its origin and the way that intelligence is coded and transferred to devices to perform operations or to optimize processes for decision-making. In this way, it is notable the relation with multiple areas, for example, Operations Research (OR), which makes use of techniques from mathematical modelling, statistical analysis and optimization for decision-making. As it can be seen, both AI and OR have an intersection in the area known as decision-making, which does not mean that this is the only aspect where they cross.
 
Even though many areas use AI to solve their problems, it is and will remain a branch of computer science. AI introduces efficient algorithms for computational applications to present an intelligent human-like behaviour while performing tasks with a lot more precision and speed; furthermore, AI aims to simulate human behaviours such as reasoning and even creativity, as in the case of artificial art. AI has made great progress in the last years, which has spread to many areas and also to many different places.  An area of interest where many domains, concepts, processes, etc. intersect is OR. For example, OR is usually identified as a sub-area of applied mathematics, however, it includes sundry techniques and methods to improve decision-making and the prized efficiency of a system; these include optimization, queuing theory and simulation.
Training an Artificial Neural Network to Compute the Euler Number of a 2-D Binary Image based on Vertex Chain Codification
Authors: Sossa Azuela Juan Humberto , Arce-Vega Fernando , Gómez-Flores Wilfrido , Lira Laura
Published: December 2024

So-called Vertex Chain Codes have been widely used to describe the shape of the objects. From these codes, several describing features can be obtained, e.g., the Euler characteristic. In this research, we show how Vertex Chain Codes can be used to train an Artificial Neural Network to compute the Euler characteristic of a 2-D binary image. We experimentally demonstrate how a simple linear neuron is enough to attain the goal. We present results with sets of 2-D binary images and objects of different complexity and size
A description of the Shapley value using a binary procedure
Authors: Tellez Ivan
Published: December 2024

We introduce a binary recursive procedure to extend the standard solution to solve 2-player cooperative games. This procedure uses adjusted games and the binary total partitions of the set of players. We show that the resulting extension is a solution concept for n-player cooperative games which satisfies a recursive formula and we prove that this formula is satisfied by a solution concept if and only if the solution concept is the Shapley value.
Endogenous Prediction of Bankruptcy using a Support Vector Machine
Authors: Zazueta Gutierrez Jorge , Chávez-Heredia Andrea , Zazueta-Hernández Jorge Antonio
Published: December 2024

We build a global bankruptcy prediction model using a support vector machine trained only on firms' endogenous information in the form of financial ratios. The model is tested not only on entirely random unseen data but on samples taken from specific global regions and industries to test for prediction bias, achieving satisfactory prediction performance in all cases. While support vector machines are not easily interpretable, we explore variable importance and find it consistent with economic intuition.
Fuzzy Filter: a method to solve a dynamic portfolio selection problem with preference incorporation
Authors: Martínez-Vega Daniel A. , Cruz-Reyes Laura , Gomez-Santillan Claudia , Fraire-Huacuja Hector , Rangel-Valdez Nelson
Published: December 2024

Many real-world optimization problems involve changes related to the passage of time; this characteristic is known as dynamism. In this paper, we approach a dynamic multi-objective project portfolio selection problem with preferences. The objective of the general problem consists of determining the set of projects that optimize a vector of benefits considering the budget constraints. Both benefits and budgets are periodically changing, impacting the definition of the problem. Besides, the problem difficulty increases with the preferences of a decision-maker and more than one objective to satisfy. In this work, we present a new formulation of the described problem and a novel fuzzy method to incorporate the preferences of a decision maker. The method, called Fuzzy Filter (FF), uses fuzzy outranking relations to include controlled intensification and diversification to the solution process. For intensification, it keeps only non-dominated solutions that are in agreement with a decision maker. For diversification, it creates a nadir point from the filtered solutions and generates new solutions from this point. In order to provide an optimization benchmark of a real problem, instances with controlled difficulty were generated, and two algorithms of state of art were adapted to incorporate FF and dynamism. An analysis of extensive experimentation is presented as part of the benchmark.
English mispronunciation detection module using a Transformer network integrated into a chatbot
Authors: Martinez-Quezada Marcos  E. , Sánchez-Solís J.  Patricia , Rivera Gilberto , Florencia Rogelio , López-Orozco Francisco
Published: December 2024

Today it is crucial to have up-to-date information for companies to be more competitive in this business world. There are applications based on speech recognition that allows access to data stored in databases. However, the proper functioning of these applications lies in good pronunciation, a skill that most people do not have. In this paper, the architecture of an English mispronunciation detection module integrated into a chatbot is proposed. It allows users to enter the audio of the phrases in which they want to evaluate their pronunciation. The output is the mispronounced words, thus helping the user to practice their English language pronunciation. The proposed architecture consists of an Automatic Speech Recognizer (ASR) model based on a Transformer network that converts the audio signal to text and an algorithm for string alignment that identifies mispronounced words using the Levenshtein distance. The Transformer network was trained using the LibriSpeech and L2-ARTIC datasets. The module was evaluated using the Accuracy metrics, reaching 90%, and the Character Error Rate metric, reaching 9.5%. Additionally, its performance was evaluated on a group of real users, showing promising results.
Multicriteria ordinal classification to improve strategic planning in the financial sector of the company
Authors: Solares Efraín , De-León-Gómez Victor , Fernández Eduardo , Contreras-Medina Emmanuel , Lopez Orlando
Published: December 2024

Globalization has changed the way companies do business in the world, always with the objective of having a greater presence in more countries through company purchases, strategic alliances, company acquisitions, investment projects. Companies also need to support decision-making to generate a strategy that considers the demands of consumers, the strategies of companies to consolidate their presence. The purpose of this study is to propose a system for decision making in presence of multiple criteria, to facilitate the generation of efficient strategic planning in the economic area of the company. The proposed approach is based on historical recognition of patterns and prediction of scenarios for multi-criteria ordinal classification using a recent classifier method
Data-Driven Enterprises for Economic Recovery after Pandemic
Authors: Contreras Masse Roberto , Ochoa-Zezzatti Alberto , Perez-Dominguez Luis , Naudascher Karen
Published: December 2024

Businesses across Latin America are working towards economic recovery. Among the different strategies in place, organizations are transforming to data-driven enterprises to use analytics to achieve their goals in a variety of business processes. This Consumer-Packaged Goods (CPG) industry study case shows how business intelligence can help to reach their goals, applying business analytics and machine learning to forecast the demand. The study focuses in one product in one presentation, which has more than thirty flavors available sold by 275 stores across country. The study case discusses how enterprise current use of traditional forecasting methods such as autoregression and moving average are being used, the results they are getting and more important, what limitations and challenges they are facing.  The current situation is compared against the proposed machine learning based approach leveraging sales data from two whole years, data visualization was transformed from static and manual procedures into an automated continuous delivery approach with insights available near real time. Also, it is discussed why data granularity played an important factor to create the proposed forecasting models and how machine learning capabilities provide a better and more accurate results. Lastly, it is discussed the implementation of data-driven philosophy explaining what components were required, how they interact among each other, data gathering alternatives, what types of transformation were required, and what technologies were selected. This comprehensive study case can help other enterprises looking to start their quest to become data-driven organization relaying on business analytics to make better decisions during their efforts for economic recovery.
Multi-retailer Sales Model under Uncertain Demand in a Pharmaceutical Two-Echelon Supply Chain with Vendor Managed Inventory System
Authors: Caballero Morales Santiago Omar , Carreón-Nava Luis-Fernando
Published: December 2024

In recent years, the Vendor Managed Inventory (VMI) system, in which the vendor manages its own and its retailers’ inventories, has been studied to improve the performance of two-echelon supply chains. However, most of these studies consider the pattern demands of the retailers as deterministic, which is very unlikely in practice where variability is significant. Thus, VMI systems based on deterministic demand patterns can lead to inefficient results, compromising the benefits of this system. Particularly within the pharmaceutical industry, an efficient supply chain through VMI is vital. The present work contributes within this context by proposing a multi-retailer VMI model to maximize the profits of a two-echelon supply chain in the presence of non-deterministic or uncertain demand. Due to the complexity of the model, a micro-genetic algorithm is developed to determine the lot size strategy to address the variable pattern of the non-deterministic demand within the profit function and reduce the stockout risk. The proposed model was validated through computer simulation, which is important to dynamically evaluate the performance of the model’s parameters. The dynamic evaluation showed that the proposed model is more efficient to reduce stockout events than models with consider deterministic demand patterns.
Fatal Cyclist-car Accidents Scenarios at Intersections from the Guadalajara Metropolitan Area
Authors: Briseño Ramon A. , Maciel Arellano Rocio , Cossio Franco Edgar Gonzalo , Larios Víctor M. , Beltrán Raul J. , Orizaga José Antonio
Published: December 2024

Faced with the imminent high fatal cyclist-car accident rate in the Guadalajara Metropolitan Area in recent years, it is necessary to implement mechanisms to improve the safety of cyclist mobility. This research analyzes the principal factors and patterns in cyclist-car accidents at intersections in the Guadalajara Metropolitan Area through machine learning algorithms and statistical methods to identify risk scenarios. The data show that the most dangerous intersection consists of one main street and a street. The type of vehicle most involved in accidents with cyclists is public transport. Factors such as the speed limit can increase the risk on some roads. Furthermore, with relevant factors and patterns, some risk scenarios were identified. Also, the scenarios show different interest situations. Women might prefer to travel on main streets, public transport vehicles are hazardous in secondary streets, and cycling infrastructure can decrease the risk at an intersection.
Detection of Risk Factors for Diabetes Mellitus with Machine Learning
Authors: Tovar Vidal Mireya , Cancino Gordillo Juan Manuel
Published: December 2024

One of the most important diseases worldwide in public health is Diabetes Mellitus (DM) since this is one of the most severe and frequent non-communicable diseases with various chronic complications. In this paper, we propose a procedure to detect the most common risk factors in patients suffering from the disease known as diabetes mellitus, through principal components analysis (PCA) and non-negative matrix factorization (NMF). We then check the results using these factors like features, through the machine learning algorithms, improving the classification results. According to the experimental results, accuracy of more than 80% was obtained.
Deep Learning for greenhouse internal temperature forecast
Authors: Esparza-Gómez Juan M. , Guerrero-Osuna Héctor A. , Ornelas-Vargas Gerardo , Luque-Vega Luis F.
Published: December 2024

The microclimate inside a greenhouse forecast has been a case of study in recent years; an adequate forecast of variables such as internal temperature helps farmers prevent losses in the harvest. In this investigation, the forecast of the greenhouse internal temperature is implemented through Recurrent Neural Networks (RNN) topology with Long-Short Term Memory (LSTM) algorithm. The analysis is performed with the many to one configuration for a sequence of three input elements and one output element for each of the year's four seasons. The metrics used for the analysis and validation of the data were the RMSE, MAE, R2, and Ceff. These metrics provide the level of efficiency and goodness of the RNN-LSTM showing how the variables considered provide significance to the forecast of one hour into the future of the internal temperature. It is shown that the LSTM algorithm within the RNN is an effective tool for a good internal temperature forecast in time series for each season, significantly helping the forecast of climatic variables inside a greenhouse.
Smart White Cane for Visually Impaired People for Hearing Recreation in Tourist Environment
Authors: Díaz-Parra Ocotlán , Xicotencatl-Pérez Juan M. , Ramos-Fernández Julio C. , Porfirio Espejel-Flores  , Toledo-Navarro Yadira , Ruiz-Vanoye Jorge A. , Eric Simancas-Acevedo  , Jaime Aguilar-Ortiz
Published: December 2024

The tourist cities apply technologies to strengthen and facilitate the communication of the tourists with the sporting, cultural, scientific and other aspects of a city. Smart tourism is the innovation and the adoption of information and communication technologies in tourism. The Smart white cane gives smart tourism to Blind people. The smart white cane is a white cane for blind people supplemented with Electronic Travel Aids, Electronic Orientation Aids, and Position Locator Devices. This paper proposes a smart white cane for visually impaired people for hearing recreation in tourist environments (smart tourist white cane or Smart White Cane for Smart Tourism).
How to determine whether the covid-19 infection series are stationary and can be predicted or whether they are non-stationary and cannot be predicted?
Authors: Medrano Meneses Mitzunory Enrique , Hernández Veleros Zeus Salvador , Torres González Miguel Angel
Published: December 2024

Lopez-Gatell, who has managed the public policy to control the SARS-CoV-2 virus, has on several occasions made forecasts on the dynamics of infections and deaths; but if such series are non-stationary, this implies a very serious error. In our opinion, many of these series have a non-stationary data generating process and, therefore, forecasts cannot be made. To determine this, we will use various econometric techniques such as unit root tests and, in addition, we will see if the series responds to a regime shift process. As results we have that the series of weekly contagions by COVID-19 in 8 entities of the country, only one of them is stationary, in addition, when analyzing the trajectory of the contagions through Markov chains to determine the performance of these states to control the contagions, we found that one of them had a very bad performance, 5 with bad performance and 1 with good performance.
Mevlânâ İle Yeniden 'Felsefe'
Authors: Ünal Mehmet Fatih
Published: December 2024

Varlık, bilgi ve değer ayakları üzerine inşa olan felsefi kavramlar, teorik bir zemin üzerine konumlanırlar. Bu felsefi kurucu kavramların en önemlilerinden biri de 'özne' dir. Her özgün felsefe kendi içinde özgün kavramlar barındırır. Bu çalışma, bu felsefi kaidelerin ışığında kültürümüze ait özgün bir felsefi gelenek ve bu geleneğe ait özgün kavramların olanağını araştırmaya çalışacaktır. Bu noktada 13. yüzyılda yaşamış büyük mutasavvıf Mevlânâ'nın görüşlerine başvurulacaktır. Mevlânâ düşüncelerini şiir ve misaller gibi sanatsal yöntemlerle ifade ettiği için öncelikle bu ifadeler, bir tür felsefileştirme ile kavramsal hale getirilmeye çalışılacaktır. Ardından metafizik bir bütünlüğe sahip olduğunu düşündüğümüz Mevlânâ düşüncesinin kültürümüze ait müstakil bir özne anlayışına nasıl kapı araladığı gösterilmeye çalışılacaktır. Böylece var olduğunu ve epeydir ihmal edildiğini düşündüğümüz 'bu özne'nin yeşerebileceği teorik ve metafizik zeminin, Mevlana'nın düşüncesinde nasıl konumlandığı ortaya çıkarılacaktır. Umuyoruz ki, kurucu insan modelinin olgun bir şekilde Mevlana'nın düşüncelerinde içerildiğini gösterme gayretiyle yapılan bu çalışma, bu hevesi güçlendirir ve başka araştırmacıları da bu alana yönlenmeye teşvik eder.
Unveiling the Cosmos Advances and Challenges in Supernova Exploration
Authors: Ujjal Adhikary
Published: December 2024

Supernovae the cataclysmic explosions marking the demise of certain stars serve as essential cosmic laboratories, slipping light on astral elaboration, nucleosynthesis, and galactic dynamics. Over recent decades, advancements in experimental tools, theoretical models, and computational ways have greatly enhanced our understanding of these marvels. Despite this progress, challenges persist, similar as characterizing ancestor systems, understanding explosion mechanisms, and detecting faint transients. This paper delves into recent improvements in winner exploration, outlines current hurdles, and explores promising avenues for unborn discovery.
Optimizing Norfloxacin Bioavailability: Formulation and Evaluation of Cyclodextrin-Based Tablets
Authors: Pakolu Apoorva
Published: December 2024

The present study focuses on the formulation of norfloxacin tablets using β-cyclodextrin and evaluates the tablets to enhance their bioavailability. Initially, compatibility studies, including FTIR analysis of norfloxacin and norfloxacin-excipient mixtures, were conducted to ensure the stability of the formulation components. The complexation of norfloxacin with β-cyclodextrin was carried out to improve the drug's solubility and, consequently, its bioavailability. Norfloxacin tablets were then prepared using the direct compression technique, a method known for its simplicity and effectiveness in tablet production. The formulated tablets were subjected to various evaluation parameters, including weight variation, hardness, friability, drug content, disintegration time, and drug dissolution profile. Among the formulations tested, the F5 formulation emerged as the optimized formulation, demonstrating superior performance in comparison to the marketed product. The study concludes that the norfloxacin-β-cyclodextrin complex significantly enhanced the bioavailability of norfloxacin, with the F5 formulation showing the most promising results.
Higher linguistic functions in patients with cerebral strokes.
Authors: MARKOVÁ Jana , ČIERNIK KEVICKÁ Viktória , DŘÍMALOVÁ Ľubica , MELIŠOVÁ Magdaléna
Published: December 2024

Starting point: In communication, not only the understanding and production of words and sentences is important, but also the processing of additional linguistic information, the so-called linguistic contexts. Most research focuses on the word and sentence level, less often on text and rarely on linguistic contexts. At the same time, their results are inconsistent: some claim that the subdominant brain hemisphere is responsible for the processing of contexts, according to others, both brain hemispheres participate in these processes. The aim of the research was to investigate with the Test of Linguistic Contexts patients with vascular strokes in the right or left cerebral hemispheres and to find out which of them has a greater influence on the processing of additional linguistic information.
Group: The sample consisted of 44 patients after stroke: 15 with a stroke in the left cerebral hemisphere and 29 with a stroke in the right hemisphere. For these clinical groups, control groups of healthy participants of the same education, gender and approximately the same age were created.
Methods: In the research, a set of tasks was created for the diagnosis of six areas: pragmatics, macrostructure and inferences, figurative language, semantic system, paralinguistics and spatial perception. The obtained data were statistically processed using the methods of descriptive and inferential statistics. 
Results: Statistical processing confirmed significant differences between the clinical and respective control groups in almost all monitored areas. Between clinical groups, a significant difference appeared only in pragmatics and spatial perception.
Conclusions: The results indicate that both cerebral hemispheres are involved in the perception and processing of linguistic contexts, and problems with their interpretation are present in the case of a lesion of any of them. These deficits can have a significant impact on the patient's communication and daily life.
THE INFLUENCE OF ASSET EFFICIENCY, FINANCIAL PERFORMANCE, AND FINANCIAL LEVERAGE ON SUSTAINABLE GROWTH RATE THROUGH GOOD CORPORATE GOVERNANCE
Authors: Rosiati Parapat  , Endang Ruhiyat  , Sugiyanto
Published: December 2024

This study aims to examine the Effect of Asset Efficiency, Financial Performance and Financial Leverage on Sustainable Growth Rate Through Good Corporate Governance. This study is classified as an associative quantitative study. The type of data used is secondary data obtained from www.idx.co.id and the company's website. The population in this study is the Manufacturing Companies in the Consumer Goods Industry Sector listed on the IDX for the 2018-2022 Period. While the sample of this study was determined by the sampling technique used in this study is non-probability sampling, namely purposive sampling so that 20 sample companies were obtained that met the criteria. The analysis method used is Panel Data Model Regression analysis. The results of this study indicate that asset efficiency does not affect the Sustainable Growth Rate (1), financial performance does not affect the Sustainable Growth Rate (2), financial leverage affects the Sustainable Growth Rate (3), asset efficiency affects Good Corporate Governance (4), financial performance affects Good Corporate Governance (5), financial leverage affects Good Corporate Governance (6). Sustainable Growth Rate has an effect on Good Corporate Governance (7), Asset Efficiency does not have a significant effect on the Sustainable Growth Rate variable through the Good Corporate Governance variable (8), Financial Performance does not have a significant effect on the Sustainable Growth Rate variable through the Good Corporate Governance variable (9), Financial Performance does not have a significant effect on the Sustainable Growth Rate variable through the Good Corporate Governance variable (10). Leverage does not have a significant effect on the Sustainable Growth Rate variable through the Good Corporate Governance variable (10).
THE EFFECT OF EMOTIONAL INTELLIGENCE ON RESILIENCE WITH SELF-EFFICACY AS MEDIATION: A STUDY ON GENERATION Z
Authors: Olivia Winda Ony Panjaitan  , Dian Mutiasari
Published: December 2024

Currently, resilience is an ability that is expected to be possessed by every individual because with resilience a person can rise from the problems faced in a productive way. Resilience itself is influenced by how well a person manages emotions and is able to be calm, and how confident the individual is in his ability to solve the problems faced. The purpose of this study was to determine the effect of emotional intelligence on resilience with self-efficacy as mediation. The research respondents were 96 Gen Z respondents. The research instrument was an online questionnaire. Analysis technique with SEM-PLS. The results showed that self-efficacy perfectly mediates the effect of emotional intelligence on individual resilience.
Utilizing the One Stays Rest Stray Strategy to Teach Reading Comprehension
Authors: Sulaiman Masagus , Larasati Finza , Lestari Ade Putri
Published: December 2024

This study aimed at finding out whether or not one stays rest stray technique was effective to teach recount text reading comprehension achievements to the Eighth Grade Students of SMP Muhammadiyah 6 Palembang. This study used pre-experimental method. The samples of this study were 38 persons of the eighth-grade students of SMP Muhammadiyah 6 Palembang. The data was obtained from pretest and posttest and calculated by using t-test. The result showed t-obtained was 4.608, higher than the critical value of t-table was 1.689 at the significant level of p<0.05 for two tailed and degree of freedom (df) is 35 which means that Ho (Null Hypothesis) was rejected and Ha (Alternative Hypothesis) was accepted. In conclusion, one stays rest stray technique was effective to teach recount text reading comprehension achievements to the Eighth Grade Students of SMP Muhammadiyah 6 Palembang
Assessing English Proficiency of Management and Accounting Students Using Linguaskill Business Tests Aligned with CEFR Standards
Authors: Kaloeti Ade Kristianus
Published: December 2024

This study aims to analyze the English language proficiency of students in Management and Accounting programs using the Linguaskill Business test and the CEFR standards. The research sample consists of 10 undergraduate students from the Management program and 10 students from the Diploma program in Management. Data, represented by test scores, were collected through the Linguaskill Business assessment. Subsequently, the data were statistically analyzed to determine the minimum, maximum, mean scores, and frequency distribution. This data was then converted into a CEFR standard table for further analysis of English language proficiency according to CEFR criteria. The findings indicate that the majority of Management and Accounting students possess basic English language skills, primarily at or below the A1 level. Some students demonstrated relatively good proficiency at the A1, A2, and a maximum of B1 levels. Therefore, it is essential to enhance the English language skills of these students, as they have not yet reached the higher levels of B2 and C1.
Impact of Cash Holding on Firm Performance: Empirical Evidence from Pakistan
Authors: Raja Sania Sarfraz , Raja Shahjahan Sarfraz , Zainab Eman , Raja Shahnawaz Sarfraz
Published: December 2024

The study investigates the impact of cash holdings on firm performance, in the presences of firm size, debt ratio, and asset turnover. Using data from 91 firms over a six-year period (2017-2022), the study demonstrates the importance of cash reserves for boosting firm value and operating efficiency. The finding show a positive correlation between liquidity and business performance, emphasizing the strategic importance of cash management in corporate finance. This study, which examines key firm characteristics as well as cash holdings, gives insights into the intricate elements driving corporate success and valuable information for managers and policymakers trying to improve financial strategies for long-term growth.
ENHANCING SURVEILLANCE SECURITY: USING GENERATIVE ADVERSARIAL NETWORKS AND COMPUTER VISION TO PREVENT IDENTITY SPOOFING IN FACIAL RECOGNITION SYSTEMS
Authors: Mahmood Alyha , Zahid Fatima
Published: December 2024

Facial recognition systems have become integral to modern security infrastructures, offering a reliable method for identity verification. However, these systems are vulnerable to spoofing attacks, where adversaries use images, videos, or 3D masks to impersonate individuals and bypass authentication. Traditional anti-spoofing methods often fail to detect sophisticated attacks, necessitating the development of more robust solutions. The primary objective of this research was to explore the potential of GANs in generating synthetic data to train advanced facial recognition models and improve their resistance to spoofing. The study aimed to evaluate the effectiveness of integrating GANs with computer vision techniques for detecting and mitigating spoofing attempts in real-time surveillance scenarios. The results indicate that GAN-based models significantly improve the ability of facial recognition systems to identify and reject spoofed identities. By generating adversarial examples, the GANs enhanced the training process, enabling the facial recognition system to learn subtle patterns indicative of spoofing, such as inconsistencies in facial texture or lighting. The integration of computer vision techniques further strengthened the model's performance, allowing it to detect spoofing attacks in various conditions, including different angles, lighting variations, and partial occlusions. The system demonstrated increased accuracy in distinguishing genuine identities from spoofed ones, with improved adaptability to real-world challenges. This study demonstrates that GANs, when combined with computer vision, offer a promising solution to enhance the security of facial recognition systems against identity spoofing. The approach improves the resilience of these systems in real-world applications by detecting more sophisticated spoofing techniques. However, limitations include the need for large, high-quality datasets to train the models effectively and the computational resources required for real-time processing.
Android Security Vulnerabilities, Malware, Anti-Malware Solutions, and Evasion Techniques
Authors: Khalid Mahtab , Sajid Ahthasham , Usman Muhammad , Saeed Mehak , Muhammad Nadeem Malik , Sharma Ishu
Published: December 2024

This paper investigates the vulnerabilities inherent in the Android operating system architecture and examines how malware developers exploit these weaknesses to execute a variety of attacks. These include aggressive advertising, remote control capabilities, financial fraud, privilege escalation, and the leaking of sensitive information. In this paper, we survey a collection of anti-malware techniques and organize these techniques into three canonical classes (static methods, dynamic methods, hybrid methodologies) according to how they are used or implemented with respect to the host operating system. We also evaluate the effectiveness of these techniques against certain types of attacks and summarize them under test categories for reporting results. We also examine the typical countermeasures used by malware authors to disguise their approaches against existing detection methods, such as reintegrating with real applications, using update payloads, executing dynamic code, scrambling dangerous content, and setting traps to act upon only purposely triggered situations. In future work, we suggest research into the capability of reinforcement learning methods to further increase sustainability and adaptability of anti-malware strategies. This Research study aimed at creating more dynamic detection systems for malware by utilizing machine learning techniques that could change in parallel with the tactics used by malware developers. By leveraging this technique, you could drastically boost the efficacy of existing anti-malware solutions that are unable to respond to new threats. As the digital environment changes (and continues to change), Mobile provides threat analysts, fraud / security managers and legal authorities up-to-date circumstantial direction so users can move with confidence within their mobile landscapes.
Effectiveness and side effects associated with Doxycycline as sclerotherapyin pediatric head and neck lymphangiomas
Authors: Rahman Tawfiqur , Rahman Masroor , Anwar Hossain Mohammad , Jewel Arif Mahmud , Al-Mamun Abdullah , Miraj A. K. Al
Published: December 2024

Introduction: Common side effects of doxycycline include diarrhoea, itch and skin sensitivity. Doxycycline makes your skin more sensitive, so it's extra important to protect your skin from the sun, if you are taking it. Lymphangiomas are the congenital malformations of the lymphatic system which are benign in nature. They are classified as microcystic (capillary lymphangiomas), macrocystic (cavernous lymphangiomas) and cystic hygromas. Objective: To assess the effectiveness of intralesional Doxycyline sclerotherapy in pediatric head and neck lymphangioma. Methods: This was a retrospective review of chart of all children who underwent Doxycycline sclerotherapy for lymphangiomas of head and neck region in six months duration between January to June 2023. A total of 50 cases were treated with intralesional doxycycline. Medical records were reviewed and evaluated for following variables like age, sex, history, examination findings including site of lesion, ultrasonographic findings, number of injection, dose of Doxycycline and any side effectsnoted and the final outcome of sclerotherapy. Results: There was complete resolution of the macrocysticlesion infourcases (12.0%) after two sessions of Doxycycline sclerotherapy. The partial resolution of lymphangioma occurred in 31 cases (62.0%) with mixed type of lymphangioma whereas, in 13 cases (26.0%), there was no response observed even after six sessions of sclerotherapy. Minor side effects like local site erythema and swelling were observed in 31 cases. Secondary infection was seen in 13 cases. Six patients developed fever after injection which was resolved within 24 hours. Conclusion: Doxycycline sclerotherapy is safe and effective in the treatment of head and neck lymphangioma in the pediatric population. DS has distinct advantages over other sclerotherapy agents including that it is inexpensive and widely available, and has minimal side effects.
Will the use of nanobodies in camel bodily fluids to treat various cancers Be successful?
Authors: Jassim Al-Raw Qutaiba Kafi , Shafeeq Alrawi MD Omar Ziad , Alhamdani Furdos
Published: December 2024

Cancer is a major health issue and one of the world's top causes of mortality. Innovative methods are needed to aid in the detection and treatment of different types of cancer. The use of nanobodies generated from camels as cancer therapy techniques has gained popularity recently. Nanotechnology, which uses nanobodies, is a novel and fascinating subject that holds promise for scientists hoping to progress a number of scientific domains, including medicine and oncology. Nano bodies are small biologics that have a large surface area that permits deep tissue penetration and the spread of cancer cells. They also have exceptional stability at high pH and temperature. The current research highlights the Single-domain antibodies, such as the camelid variable region of the heavy chain and the antigen-binding variable domains of the shark immunoglobulin new antigen receptor are the smallest antigen recognition domains (approximately 15 kDa) and differ from conventional antibodies in certain ways. The majority of antibodies, which are molecules that patrol our tissues and blood for invaders, are quite heavy for proteins. However, sharks, camels, and their close cousins produce smaller, simpler antibodies. Since their discovery in the late 1980s, scientists have discovered that these antibodies are extremely potent; they have the ability to attach to molecules' hidden components and pierce tissues more deeply, which increases their potential as treatments for many cancer kinds.
Objeto, métodos, principios y funciones de la bioética en el campo de la Informática Médica
Authors: González Arencibia Mario , Mar Cornelio Omar
Published: December 2024

El avance de la tecnología y el uso cada vez más frecuente de sistemas informáticos en el campo de la medicina ha planteado nuevos desafíos éticos. La Informática Médica se refiere a la aplicación de sistemas de información y comunicación en el ámbito de la atención médica, con el objetivo de mejorar la eficiencia y calidad de la atención. En este contexto, es necesario situar y definir el objeto, métodos, principios y funciones de la bioética. El objetivo de la investigación es analizar y comprender los aspectos éticos relacionados con la informática médica y cómo se pueden abordar desde la bioética. Los principales hallazgos de la investigación destacan la importancia de garantizar la privacidad y seguridad de los datos médicos, así como la necesidad de contar con políticas y regulaciones éticas claras en el uso de sistemas informáticos en la atención médica. En conclusión, la bioética es un campo fundamental para abordar los dilemas éticos que surgen en el uso de sistemas informáticos en la medicina. Su objeto, métodos, principios y funciones son indispensables para guiar la correcta aplicación de la Informática Médica y garantizar la ética en el uso de la tecnología de la información en la atención médica.
IMPLEMENTASI TERAPI NEBULIZER UNTUK MENGENCERKAN SPUTUM PADA ANAK BRONCHPONEUMONIA DI RUMAH SAKIT TK II PUTRI HIJAU MEDAN
Authors: Firdayani Sianturi  , Purwaningsih Purwaningsih , Sinuraya Evamona
Published: December 2024

Latar belakang Implementasi adalah serangkaian kegiatan yang dilakukan oleh perawat untuk membantu pasien dari masalah status kesehatan yang dihadapi disertai tujuan/kriteria hasil yang diharapkan. Pemberian terapi inhalasi (nebulizer) yaitu tehnik yang dilakukan dengan pemberian uap dengan menggunakan obat Ventolin 1 ampul dan Flexotide 1 ampul. Obat Ventolin adalah obat yang digunakan untuk membantu mengencerkan sekret yang diberikan dengan cara diuap dan Flexotide digunakan untuk mengencerkan sekret yang terdapat dalam bronkus. Tujuan penelitian ini memberikan asuhan keperawatan Medikal Bedah Pada Pasien Bronchopneumonia. Metode penelitian ini adalah penelitian studi kasus dengan pendekatan asuhan keperawatan.Penelitian dilakukan pada Februari 2024 pada dua orang pasien Bronchopneumonia.Hasil penelitian didapatkan bahwa kedua pasien mengalami ketidakefektifan bersihan jalan nafas pada Bronchopneumonia. Setelah dilakukan tindakan nebulizer, ketidakefektifan berihan jalan nafas pada kedua pasien pada hari kedua dan ketiga dapat tertasi. Kesimpulan dari intervensi yang dilakukan dengan pemberian terapi nebulizer dapat dikatakan efektif untuk mengurangi atau bahkan mengatasi bersihan jalan napas tidak efektif pada pasien Bronchopneumonia .