bluuebunny/crossref_metadata_2025_split huggingface dataset:
Sociocultural Awareness, Cultural Perspectives and Strategies in Language Assistants’ Academic Papers in Spain / Conciencia sociocultural, perspectivas culturales y estrategias en trabajos académicos elaborados por auxiliares de conversación en España
Authors: Vitalaru Bianca 
Published: January 2024

Este artículo incluye un análisis de trabajos académicos escritos por estudiantes de máster en el programa ‘Teach & Learn in Spain’ en el Instituto Franklin-UAH, que se centran en aspectos culturales. El porcentaje de trabajos académicos de estas características escritos por estos estudiantes que actuaron como auxiliares de conversación en colegios bilingües en España es bastante alto, lo que sugiere la importancia del componente cultural en la enseñanza del inglés como segunda lengua y su alto nivel de conciencia sociocultural. Por lo tanto, este artículo tiene varios objetivos: a) determinar la existencia de una conciencia sociocultural específica en los trabajos de investigación; b) identificar los aspectos culturales que fueron considerados esenciales por los AC en este programa y mostrar las estrategias utilizadas para proporcionar información; y c) comparar hallazgos considerando antecedentes teóricos. El método se basará en un enfoque mixto basado en análisis cuantitativos y cualitativos y será específico para cada uno de los objetivos.
Abstract
This paper includes an analysis of academic papers that focus on cultural aspects written by MA students in the ‘Teach & Learn in Spain’ program at Instituto Franklin-UAH. The percentage of academic papers focusing on cultural aspects written by these students who acted as Language Assistants in bilingual schools in Spain is quite high, which suggests the importance of the cultural component in the teaching of English as a second language and their high level of sociocultural awareness. Thus, this paper has several objectives: a) to determine the existence of a specific sociocultural awareness in research papers; b) to identify the cultural aspects that were considered essential by the LAs in this program and show the strategies used to provide information, and c) to compare findings considering the theoretical background. The method will rely on a mixt approach considering quantitative and qualitative analyses and will be specific for each of the objectives.
Keywords: Culture; Research; Sociocultural Awareness; Language Assistants; Academic Papers.
Native English Speakers in Madrid’s Classrooms: Difficulties Reported by Assistants / Hablantes nativos de inglés en las aulas de Madrid: Dificultades señaladas por auxiliares
Authors: Litzler Mary Frances 
Published: January 2024

This article examines difficulties encountered by 40 native English-speaking language assistants working in classrooms in the Madrid region, as reported in their teaching portfolios, a requirement of the Master’s degree programs they completed during the same period. The 187 comments obtained were analyzed by sorting them according to theme; the findings confirm those of prior studies while bringing to light challenges not mentioned to date in research. Some aspects discussed by the native English speakers were differences in classroom methodology and discipline, the need for increased communication with local teachers, the policy to use only English at the schools, an inability to help students with special needs effectively, and responsibilities that go beyond those of a language assistant.

Abstract
This article examines difficulties encountered by 40 native English-speaking language assistants working in classrooms in the Madrid region, as reported in their teaching portfolios, a requirement of the Master’s degree programs they completed during the same period. The 187 comments obtained were analyzed by sorting them according to theme; the findings confirm those of prior studies while bringing to light challenges not mentioned to date in research. Some aspects discussed by the native English speakers were differences in classroom methodology and discipline, the need for increased communication with local teachers, the policy to use only English at the schools, an inability to help students with special needs effectively, and responsibilities that go beyond those of a language assistant.

Keywords: Bilingual Education; Teacher Aides; English (Foreign Language); Native Speakers.
THE PREVALENCE OF VITAMIN B12 DEFICIENCY IN HEMODIALYSIS PATIENTS
Authors: Alkrush Alaa , Mahmood Sarhad 
Published: January 2024

BackgroundVitamin B12 is a water-soluble vitamin in several normal cellular functions. Low vitamin B12 has been associated with high concentrations of homocysteine and can lead to health complications. In addition to metabolic alteration and restricted food products allowable in renal failure patients, vitamin B12 is actively removed by hemodialysis with high flux membranes.
ObjectiveTo detect the prevalence of vitamin B12 levels in hemodialysis patients and its relation to the duration of dialysis and daily protein intake.
MethodThis cross-section observational multicenter study was conducted on 169 hemodialysis patients in four Sulaimani Governorate centres. A questionnaire used to gather data included patient, dialysis, diet, and medication information. Blood investigation was taken to detect the vitamin B12 level and mean corpuscular volume.
ResultsTwenty-nine patients (17.1 %) had vitamin B12 deficiency. High flux filter hemodialysis was not used in all the centres included in this study. No cases with four hours of dialysis sessions had vitamin B12 deficiency. All the patients were on sub-optimum protein diet restriction. No cases of vitamin B12 deficiency were present in patients receiving protein of 0.6-0.7 gm/kg/day. All our patients had normochromic normocytic anaemia.
ConclusionOur patients have an average percentage of vitamin B12 deficiency compared to other centres worldwide. The main causes of vitamin B12 deficiency in our patients were the sub-optimum restriction of protein diet and the sub-optimum dialysis.
PATTERN AND PROGRESSION OF CHRONIC KIDNEY DISEASE IN A GROUP OF PATIENTS IN SULAIMANI CITY
Authors: Munthir Neiran , Sharif Dana , Ismail Serwan , Abdul Rbaz 
Published: January 2024

BackgroundChronic kidney disease (often underdiagnosed, and its complications often undertreated) is a worldwide public health problem associated with a significant increase in mortality.
ObjectiveTo find out the common causes of chronic kidney disease in Sulaimani to prevent and accurately assess risk factors for target intervention to prevent or slow down the progression.
Patients and MethodsAn observational case series study was accomplished on 192 patients with chronic kidney disease in Sulaimani City from September 2018 to March 2019. Following informed consent, a questionnaire collected demographic and clinical details. Laboratory data of the patients were also collected and statistically analyzed.
ResultsThe majority (58.9%) of the participants were 18-64 years old, 66.7% lived in urban areas, and 66.1% had a low socioeconomic status. The leading causes of chronic kidney disease in children were glomerular diseases (45.4%) and congenital urological malformations (31.8%), while in adults and elderly group, diabetic nephropathy (25.9%), glomerular diseases (19.4%), and hypertension (16.5%) were the most common causes. About 50% of all patients were diagnosed when they reached advanced stages (stage IV, V), and about 90% of patients diagnosed at early stages progressed to advanced stages. Uncontrolled diabetes, proteinuria (≥ 1gm), and uncontrolled blood pressure were significant risk factors for progression.
ConclusionChronic kidney disease is underdiagnosed and undertreated in our region. Early detection and measures to slow disease progression should be encouraged.
Privacy Preserving Data Mining using Jaya based Genetic Algorithm
Authors: Srutipragyan Swain Et al. 
Published: January 2024

Privacy protection has emerged as a key concern in the field of data mining because of the rise in the sharing of sensitive data across networks among organizations, governments, and other parties. For knowledge extraction from these huge set of data, association rule mining is used to analyze the patterns of data. For a variety of optimization issues encountered in the real world, evolutionary algorithms (EAs) offer efficient solutions. The available EA solutions in the privacy-preserving area are limited to specific issues like cost function evaluation. Here, a JAYA based Genetic algorithm has been proposed for privacy preservation.“JAYA” means victory a word from Sanskrit origin..This algorithm doesn't need any parameters that are specific to it and it moves towards best solution avoiding the worst. Hence the name Jaya. Jaya based genetic algorithm is applied to original dataset of chromosomes. Privacy preservation is achieved by comparing the support of original dataset of chromosome with the simulation output.
Activity Reimagined: The Effects of a Tailored Exercise Protocol on Post-Myocardial Infarction Recovery
Authors: Poovishnu Devi Thangavelu Et al. 
Published: January 2024

Introduction: Global health issues include cardiovascular diseases, notably CHD. Continuing ischemia causes irreparable heart muscle damage, or MI. An important cause of death in India is CHD. Lifestyle worsens heart disease. The Structured Exercise Protocol (SEP) in this study targets post-MI rehabilitation with resistance and aerobic training. Results may improve survivors' quality of life by affecting post-MI therapy. Exploration follows the study guides post-MI care.
Objectives: The purpose of the study is to evaluate how a structured exercise protocol affects a person's exercise tolerance and activity level after a myocardial infarction. The research, which involves 45 participants and a 12-week intervention, compares the results of traditional workouts with the Structured Protocol in an effort to ascertain the efficacy of the protocol in enhancing cardiovascular health and general well-being in post-MI people.
Result: The outcomes of the study show that those who underwent the Structured Exercise Protocol after a myocardial infarction experienced notable improvements in their exercise tolerance and activity status. The efficiency of the regimen in boosting cardiovascular recovery is highlighted by statistical analysis. The results call for more research on cardiac rehabilitation techniques and show how customized exercise interventions might improve post-MI care regimens.
Conclusion: The study concludes that exercise tolerance and activity status are considerably improved in post-myocardial infarction individuals by the Structured Exercise Protocol. The results demonstrate the effectiveness of the regimen as a helpful intervention for cardiovascular rehabilitation and point to its potential to improve long-term outcomes for this population.
An Efficient Encryption System on 2D Sine Logistic Map based Diffusion
Authors: Akshay Chamoli Et al. 
Published: January 2024

An optimal cryptographic model is proposed, enabling the feature of 2D sine logistic map-based diffusion algorithm. The 2D sine logistic map process is merged with the algorithm as it has the ability to provide random number generator as well as to overcome blank. The previous existing models based on image encryption use to work on raw images but without alteration for the process of confusion and diffusion. The main disadvantage as the nearby pixel values for an image always remains similar. This issue is resolved by a Pseudo random generator process which is based on key stream that alters pixel value. Furthermore 2D sine logistic map based diffusion process has shown an improvement in the key sensitivity and the complex relationships that use to get developed between cipher and test image.2D sine logistic map with diffusion method used to keep pixels intact with each other to such an extent as even a single bit modification in the intensity value of an original image pixel will lead to a huge change in most of the pixels of the cipher and thus makes the model very sensitive to make any changes in the pixel value or secret key for an image. As seen and analyzed with a variety of test results that strategic model used for encryption can easily encrypt the plain image into a cipher of a random binary sequence.
Proto-oncogene Protein Sequence Classification using RNN and CNN with Attention Mechanism
Authors: M.Vijayalakshmia Et al. 
Published: January 2024

The fundamental tool for uncontrolled tumour progression is the lack of regulatory capacity of tumour suppression genes (TSG) and mutations in proto-oncogenes (OG). Even though tumour is a diverse complex of several diseases, discovering possibilities of genes connected to OG activity by computational research can aid in the development of medications that specifically target the disease. Attention mechanism in Deep learning has recently become an innovative approach for classifying protein sequences. The attention-based approach can offer a trustworthy and understandable method that aids in overcoming the existing difficulties in describing deep neural networks for classifying protein sequences. In this study, we classify proto-oncogenes (OG) with the help of CNN, Bi_LSTM and Bi_GRUwith attentionmechanisum. of all the three attention mechanisms, Bi_LSTM significantly performs far better than the other two approaches and achives F1-Score upto 97.3% and it is 3% more traditional ML Random Forest approach.
Alzheimer Disease Detection of 3D-CNN with SE-Net Model using SVM Classifier
Authors: R. Hemalatha Et. al 
Published: January 2024

Alzheimer disease is a fatal progressive neurological brain disorder. Earlier detection of Alzheimer's disease can help with proper treatment and prevent brain tissue damage. In this work we proposed two methods. First, proposed connected median filter using PSO feature extraction from MRI images and Analysis of Alzheimer’s diseases state by using 3D-CNN based SE-Net. In the first phase, the algorithm first normalizes and removes skull from the MRI images. Connected median filter using Particle Swarm Optimization algorithm is used to partition the image into white matter (WM), grey matter (GM) and black holes (BH). The relevant diagnostic features are extracted from the segmented image component. The classifier is trained by the training data to predict the test data. The features are defined to construct classification model by using Support Vector Machine with Squeeze- Excitation block. Here, database contains total of 1000 images which are resized into 350 × 350 without loss of information. Deep Learning demands large number of images and its strength was increased as per requirement by augmentation technique. In the first phase of the method takes 1000 images of different features are selected to train SVM classifier and the accuracy obtained is 98.37% and contribution of this work is classification of images into categories such as Alzheimer (AD) and normal. First phase of work emphasized program specific applications to extract features. In the second phase the CNN multiple layers which are studied from lower level to the higher-level image characteristics.
Predicting Customer Churn in E-Commerce Using Statistical and Machine Learning Methods
Authors: Vidya Rajasekaran Et al. 
Published: January 2024

This research work aims to develop prediction models and analytical insights to overcome customer churn issues through data-driven approaches. The attrition rate of consumers in e-commerce is a significant issue requiring effective retention strategies. A novel methodology is proposed comprising data preprocessing, using statistical analysis techniques developing the model and carrying out tailored retention strategies. The model is used to identify crucial churn influencers and propose practical recommendations for enhancing consumer retention. The significance of this work lies in its potential to allow e-commerce ventures with insights with the intention of price savings strategies, enhanced revenue measures, and better consumer fulfillment. This research will influence the e-commerce business by facilitating evidence-based methods for reducing customer turnover and increasing long-term customer value. The resulting accuracy of the proposed model using Logistic Regression results in 87 percentage of accuracy which is a good metric to assess overall model performance. The Kaplan-Meier curve is used to check the survival probability of consumers and identify consumers more likely to churn over time.
Analysis of Quality of Experience Evaluation Framework for RPL Protocol in Mobile IoT Environments under Manhattan Grid Mobility
Authors: Kablian K Et al. 
Published: January 2024

This research paper introduces a novel and advanced framework for assessing the Quality of Experience (QoE) implications associated with the utilization of the Routing protocol for low power and lossy networks (RPL) in the context of the Internet of Things (IoT). The study undertakes a thorough investigation into RPL's performance under the influence of Manhattan grid (MG) mobility scenarios, addressing a notable gap in current research. By meticulously incorporating essential Quality of Service (QoS) metrics like average packet delivery ratio (PDR), average power consumption (Avg_P), and average inter-packet time (Avg_IPT), the framework enables an in-depth evaluation of QoE. The uniqueness of this work lies in its incorporation of a comprehensive dependency matrix (DM) and the subsequent application of a dependency function (DF) that comprehensively captures the multifaceted aspects of the system's perceived quality.
Beyond its methodological innovation, this research enhances our comprehension of RPL's adaptability through the shift from static to dynamic environments. Furthermore, the study systematically explores various scalability levels, contributing novel insights into how RPL performs across diverse IoT scenarios.Based on the Quality of Experience (QoE) analysis, it can be deduced that the network effectively maintains the performance of a static model even under conditions of MG scenarios. In the static model, the RPL's performance was measured at 67.73%. However, when exposed to the MG mobility model, its performance decreased to 42.93%. Given that RPL is primarily optimized for static models and considering its static model performance as a reference benchmark, it manages to retain approximately 63.38% of the static model's performance when subjected to the MG mobility model.
Examine the Properties of Nanostructured Ni, Mn, and Co Synthesized Materials using precipitation method and synthesized material used battery.
Authors: Serfraz Najeer Shaikh, Et al. 
Published: January 2024

Libatteries are secondary batteries containing a lithium anode and Li+ ions dissolved in carbon. The cathode material contains a solution that releaseslithium. With high energy density and low resistivity, it is "one of the three types of electric power acid, or battery, and is heavy and has more energy than nickel-ion batteries." Twice the size of a hydrogen battery, it is only half the size andweight of a nickel-metal hydride battery for the same energy. These advantages make lithium ion batteries an important factor in driving the technological revolution. Lithium-ion batteries also work well in temperatures from 20 degrees Celsius to +50 degrees Celsius and can with stand hundreds of charges and discharges. In this paper we are using nano material (Ni0.250Mn0.750) CO3 for synthesis to get the porous nano material, that synthesized nano porous material we are characterizing under different technique to know the characteristics of that material like size and shape, thermal effect and other. The same material will be used to prepare battery and the performance of that battery will be analysed and study on the performance will be done.
Complex Seismotectonic Characteristics in the Midland Basin of Texas: Constrained by Seismicity and Earthquake Source Mechanisms
Authors: Huang Guo-chin Dino , Chen Yangkang , Savvaidis Alexandros 
Published: January 2024

Abstract
Earthquake activities in areas across the Midland basin and the Central Basin Platform of West Texas have significantly increased since mid-2019 because of continuing industrial activities involving wastewater injection. The induced seismicity has allowed us to discover previously unknown seismogenic structures. This article presents a study focusing on seismotectonic characteristics of the Midland basin. For this purpose, we first delineated seismicity to identify seismogenic structures. In addition, we performed waveform moment tensor inversion to determine earthquake source mechanisms; subsequently, we inverted for the regional stress field using the obtained source mechanisms. As a result, we have obtained 150 focal mechanisms (from 2017 to November 2023). Based on the seismicity distribution and source mechanism patterns, we have identified 15 distinctive seismogenic zones. A vast majority of seismicity are located in the crystalline basement. Most of the 15 seismicity zones contain seismogenic structures commonly presenting linear geometry but with various orientation. Although the inverted focal mechanisms are a mix of strike-slip and normal faulting, the inverted stress field contains the least compression axes (S3) commonly oriented in 330° azimuth across the 15 identified seismogenic zones. A combination of all seismogenic features has demonstrated that the Midland basin contains fault architectures resulting from the latest extensional tectonic activities, creating a series of basement-rooted strike-slip and normal faults. The two types of basement-rooted faults coexist in our study area, where a presumed basement-rooted rift system transects the Midland basin. They are reactivated by the current fluid injection.
Assistance and Development of MSMEs’ Nata de coco Product to Increase Product Value in Godegan, Srandakan, Special Region of Yogyakarta
Authors: Gunawan Barbara 
Published: January 2024

Abstract. Partners in this PPM[1] KKN service program are Micro, Small, and Medium Enterprises (MSMEs) entrepreneurs and residents in Godegan, Srandakan, Bantul, Special Region of Yogyakarta. The partner is stated to be an MSME because the main program of the Community Service Team will accompany several MSMEs in Godegan hamlet, especially MSMEs’ nata de coco product; besides that, it will also organize an auxiliary program in the form of Population Data Digitization. The purpose of this service is to increase the value of processed nata de coco products, which in turn can increase the income of citizens until economic independence occurs. The problems faced by MSMEs’ nata de coco product are that managers only process nata de coco in semi-finished form and do not have the knowledge to increase the value of products so that they have a better selling value. Packaging, logos, and product brands are also obstacles to marketing processed finished products. In addition to the problems found in the nata de coco MSME business, there are also problems in the hamlet, namely the administration of population data that is not updated because it is recorded manually. Based on these problems, the Community Service Team solves problems by carrying out activities divided into production, marketing, and Financial Records. In the production aspect, training and assistance in product processing and attractive nata de coco packaging to increase product value. From the marketing aspect, assistance is needed in online product marketing, while from a financial point of view, assistance is carried out in managing business finances. The Community Service Team also provides training and assistance in terms of creating company profiles and digitizing population data. The outputs of this service program are news in the mass media, videos of activities, participation in national seminars on community service, and scientific manuscripts published in the form of Sinta-accredited journals.