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The Analysis of Video Game Title Translation: A Case Study of Iranian Darinoos Publishing
Get PDFWith video games gaining popularity worldwide and becoming one of the most common forms of entertainment in the digital age, the game's title holds both commercial and entertainment value. This study aims to analyze foreign video game titles that have been translated into Persian by the Iranian Darinoos publishing. The practical analysis in the research study is based on Vinay and Darbelnet (1995) and Chaume’s (2020) translation strategies. Those models were applied to compare the translation strategies used by the Darinoos with the translation strategies used by participant translators and to identify the most commonly used translation strategies by both groups. The overall results showed that literal translation remained the most widely used translation strategies in title translation. The Darinoos team used new translation, partial translation, and modulation to translate video game titles into Persian in a more creative way than the other participants. In some instances, participants didn't consider titles to be translatable and used the original title in the target language. These obtained results will be benefical to journalists, video game publishers, content writers, and game localizers
Chrysophyllum albidum (African star apple) Fruit-Skin Attenuates Hyperglycemia-Mediated Oxidative Stress in Experimental Diabetic Rats
Get PDFDiabetes mellitus, a chronic metabolic disturbance characterized by hyperglycemia has become a health problem affecting millions of people worldwide. Hyperglycemia mediated oxidative stress performs a key role in diabetic complications. The fruit-skin of Chrysophyllum albidum (African star apple) has been reported to have anti-hyperglycemic, hypolipidemic and in vitro antioxidant properties, but its effect on oxidative damage in diabetic animals has not been well investigated. This study investigated the effect of Chrysophyllum albidum fruit-skin (CAFS) in mitigating hyperglycemia induced oxidative stress in diabetic rats. Oxidative stress markers included superoxide dismutase (SOD) and catalase (CAT), lipidperoxidation status using malondialdehyde and non-enzymatic antioxidants in serum, hepatic and pancreatic tissues. Non-diabetic and streptozotocin-diabetic rats were compared after 4 weeks of treatment. The diabetic untreated group showed significant (p< 0.05) elevation of malondialdehyde and depression of non-enzymatic antioxidants levels, while suppressing SOD and CAT activities in serum, hepatic and pancreatic tissues when compared to normal rats. CAFS supplemented diet treatment ameliorated these metabolic disturbances and increased the activities of hepatic and pancreatic SOD from 0.28±0.25 to 0.61±0.13 Unit/mg protein and 0.08±0.01 to 0.15±0.01 Unit/mg protein respectively and CAT from 0.21±0.06 to 0.81±0.17 Unit/mg protein and 0.07±0.01 to 0.50±0.15 Unit/mg protein respectively. The findings suggest that CAFS treatment in diabetic rats exerts a protective effect via attenuation of oxidative stress mediated by hyperglycemia and improves the antioxidant status.
 
Chemical Composition Study of Three Varieties of Date seeds (Iraqi, Saudi and Yemeni) and their Utilization as caffeine-free coffee alternative
Get PDFThe study aimed to investigate the chemical composition of three widely available types of date seed in the Yemeni market (Iraqi, Saudi, and Yemeni) and their potential use as caffeine-free coffee alternative.
Quantitative estimation was conducted for moisture, ash, protein, fiber, fat, carbohydrates, and caffeine, along with a descriptive estimation for alkaloids, tannins, and resins. Date seed coffee was prepared and sensory evaluation was performed by trained panelists.
The results showed that Yemeni date seeds had the highest extraction Rate on average (30%), while Saudi date seeds had higher moisture, protein, fat, and fiber contents on average (8.997, 6.897, 11.167, and 16.333%, respectively).
Yemeni date seeds contained the highest carbohydrate content on average (58.290%). All tested date seeds were caffeine-free, while the chemical composition for Yemeni coffee were 7, 0.9, 13.9, 14.4, 12.8, 4.1, and 1.5% for moisture, ash, protein, fat, fiber, carbohydrates, and caffeine, respectively. Descriptive estimation results showed the absence of alkaloids in all date seeds and coffee samples, with the presence of both tannins and resins. For sensory evaluation indicated high values for all attributes of date seeds coffee alternative, with Saudi date seeds coffee outperforming other types, suggesting its potential use as a caffeine-free coffee alternative and its associated health benefits
Effects of Chitosan-based Coating Enriched with Peanut (Arachis hypogaea) Skin Extract on Physicochemical, Microbiological and Sensory Characteristics of Beef Burger During Cold Storage
Get PDFThe current study aimed to create a chitosan-based coating enriched with peanut skin extract (PSE) at a concentration of 0.5, 1 and 1.5%, and evaluate its impact on the physicochemical, microbiological and sensory characteristics of fresh beef burger stored at 4±1°C for 15 days. All coated burgers had significantly higher L*, a* and b* values than the uncoated control during storage. Also, the results showed that application of chitosan coating enriched with 0.5, 1 and 1.5% PSE significantly increased total phenolic content (TPC) and antioxidant activity (AA), inhibited lipid oxidation as evaluated by thiobarbituric acid reactive substances (TBARS) and peroxide value (PV), retarded microbial growth and enhanced sensory characteristics of burger samples. Moreover, the positive effects of PSE on all investigated quality characteristics were proportional with the extract concentration. Therefore, using chitosan-based coating enriched with PSE enhances the stability of beef burger during cold storage and can be utilized in the meat industry
Utilizing Deep Learning Methods for Heart Defect Identification via Electrocardiogram (ECG): A Literature Review
Get PDFIn recent years the application of Deep Learning is widely used in various fields of science, such as in the military, agriculture, health and even in other fields. In the field of health many studies use deep learning, especially related to heart disorders. Identification and detection of heart defects that are widely used are by using an electrocardiogram (ECG). Research related to ECG and the application of deep learning methods is very interesting for researchers, because researchers trace that there are still few studies that focus on researching related to it. This article aims to explain the trend of ECG research using deep learning approaches in recent years. We reviewed journals with the keyword title "ECG Deep Learning" and published from 2016 to October 2023. The articles that have been obtained are then classified based on the most frequently discussed topics including: data sets, pre-processing, feature extraction, and classification/identification methods. The approach used by some researchers is mostly to get the best results from the use of deep learning methods. This article will provide further explanation of the most widely used algorithms for ECG research with a deep learning approach. Of the deep learning methods used, almost 84% use the Convolutional Neural Network method. In this article, critical aspects of ECG research can be carried out in the future, namely the use of data in the form of other data from ECG, and the use of deep learning is a very big opportunity for researchers in the future
A Comparative Analysis of FaceNet, VGGFace, and GhostFaceNets Face Recognition Algorithms For Potential Criminal Suspect Identification
No full textThe escalating concerns surrounding criminal activities underscore the imperative for bolstered security measures to safeguard public welfare. Despite concerted efforts, the identification of suspects remains fraught with limitations, hindering the attainment of comprehensive individual profiles. Leveraging advancements in facial detection and identification technologies, this study assesses the efficacy of three prominent deep learning models—FaceNet, VGGFace, and GhostFaceNets—in the domain of facial recognition for suspect identification. Drawing upon data collected in 2023, the investigation scrutinizes FaceNet's intricate methodologies, including triplet loss optimization and Euclidean space mappings, yielding exceptional accuracy rates of 97.05% during validation and 97.4% during testing. Conversely, VGGFace, while displaying commendable accuracies, registers marginally lower accuracy metrics, standing at 97.05% and 96.1% during validation and testing, respectively. GhostFaceNets, integrating novel architectural components, exhibit diminished accuracy rates, signaling avenues for refinement. These empirical insights underscore FaceNet's prowess in furnishing robust and reliable facial recognition outcomes, while delineating the imperative for iterative enhancements in GhostFaceNets to foster their pragmatic applicability in security domains
Linear α −Differential Equations
Get PDFy α −differential equations, we mean that the branch studies differential equations containing fractional or real order derivatives. In [1], Shehata has overcome the problem of multiple previous definitions offractional calculus by putting an accurate definition of the α− fractional calculus using the normal way. Heconcluded from this definition that the α fractional calculus is a complex-valued function that depends onthe principal root of the real number. As an extension of the study of fractional calculus and its importancein applications, in this paper, we study differential equations that contain fractional differentials based on theShehata definition. We define and study the so-called linear α− differential equations of the first extension,higher extension, and system of the first extension. We give the closed formula for each case. To illustrate ourresult, we give some numerical examples of fractional differential equations and their solutions
Unlocking the Power of Language: Navigating Linguistic Diversity in Cross-Cultural Research
Get PDFIn the expansive realm of cross-cultural and intercultural research, the power of language lies in its direct and indirect influence on scholarly investigations and outcomes. This paper investigates the intricate relationship between language, culture, and interpretation. It unveils the transformative power of language in modifying communication styles, influencing study outcomes, and shaping societal perspectives. The challenges posed by diverse languages are addressed while concurrently providing valuable guidance to research enthusiasts to enhance research methods, minimize linguistic prejudice, and foster empathy within society. Through insightful instances and case studies, it vividly portrays the notable impact linguistic variations have on the communication and results of cross-cultural research while signaling potential zones for upcoming multicultural exploration regarding lingual philosophy.
A Critical Pragmatic Analysis of some Selected Songs of Ilerioluwa Oladimeji Aloba (MohBad)
Get PDFThis study investigates a critical pragmatic analysis of some selected songs of Ilerioluwa Oladimeji Aloba (MohBad). Specifically, the study focuses on Speech Act analysis of the selected songs and ascertains the ways speech acts are expressed in these songs. Two research questions: What speech acts are represented in Mohbad’s songs? And to what extent are the tenets of speech acts expressed in Mohbad’s Songs? guided this study. The theory of the Pragmatic Act introduced by Jacob Mey (2001) is used as the theoretical foundation of the study. The research is categorized as descriptive qualitative research. The data for the study consists of selected songs of Ilerioluwa Oladimeji Aloba: ‘Ask About Me’, ‘Feel Good’ and ‘Peace’. These songs were selected based on the complex and multifaceted narratives which mirror the songwriter’s life and struggles. The songs’ lyrics are made available and readily accessed from music streaming platforms like Spotify, Apple Music, and YouTube for lyric references. The findings of the study reveal that the lyrics of Aloba’s songs show a variety of speech acts such as assertions, declarations, interrogatives, expressive utterances and commission, all of which help reveal his journey from hardship to fame and how he accomplished acceptance, his challenges and resilience, his defiance and self-assuredness; and his boldness in engaging his listeners. These have revealed the depth of meaning and intention of the songwriter beyond the lyrics of the songs
CardiacNet: A Neural Networks Based Heartbeat Classifications using ECG Signals
Get PDFObtaining information about the electrical activity of the heart in the form of electrocardiograms (ECG) has become a standard way of monitoring patients’ heart rhythm and function. It is used for diagnosing a variety of cardiac anomalies such as arrhythmia and other heart diseases. However, the interpretation of ECGs requires the expertise of trained physicians, thus bearing the need for tools that automatically classify such signals. In this study we train deep convolutional neural networks (CNNs) to perform binary classification of ECG beats to normal and abnormal. We use transfer learning in order to build models that are fine-tuned on specific patients’ data, after pre-training a generic network on a set of different ECGs selected from the MIT-BIH arrhythmia database. We then compare the performance of the fine-tuned networks against that of individual networks, which are trained only on the ECG data of a single patient, in order to evaluate the overall efficacy of transfer learning on the given problem. We managed to achieve adequate results on both scenarios as the individual classifiers yielded an average of 94.6% balanced accuracy on the test set, whereas the fine-tuned models a marginally worse 93.5%