Merging of the Short-Story Genres

Story writing craft evolved through the centuries before rising as a separate genre. Unity is an essential element of short story through which it exhibits singularity of effect, unity of impression, and the totality of interest. After the success of the short story, writers further shortened their narratives and eventually short fiction arose as a sub-category of short story. Short fiction further differentiated into a sub-category called the “sudden fiction” that referred to all shortened forms of short fiction. Having mastered artistic brevity, writers began writing even more condensed narratives, and the sudden fiction differentiated into two types: the new sudden fiction and the flash fiction. The new sudden fiction was akin to the traditional story comprising of up to 1500 words; whereas, the flash fiction was similar to the Hemingway’s classic The Very Short Story consisting of up to 750 words. However, the flash fiction later reconfigured to include all short-short stories comprising of 50-1500 words. This paper briefly overviews the evolution of the short story genre and reviews the delicate merger of the short story with the contemporary short-short story

Flash Fiction: A Unique Writer-Reader Partnership

The proliferation of an unconventional miniature story, in the digital age, is a testament to its rising popularity. In response to the expanding demand for very short stories, writers have delivered the briefest possible stories falling under the short-short fiction umbrella. Short-short fiction is identified with various labels; however, flash fiction is more commonly used in America. The term ‘flash fiction’ was initially used for short-short stories of up to 750 words. However, since then, stories ranging from 50 words to 1,500 words have also been included in the classification of the flash fiction genre. Flash fiction is a hybrid style that mixes verse with narrative to form a story that captures a ‘moment’ of a larger narrative sequence akin to a series of still photographs taken from a movie. Flash Fiction is not plot driven and precisely includes only essential information in a compressed manner. Flash fiction writers deliberately sketch scenes with strokes of ambiguity to keep readers fully attuned to each word. They also withhold details regarding the story’s characters, events, scenes, and atmosphere that watchful readers try to compensate with an active imagination. Apparently, the readers also are inclined towards making sense of each word based on their individual experiences and perceptions. Typically ending with an ironic twist, flash fiction’s ending surprises the readers and leaves them stimulated that encourages multiple re-readings for closure. This paper argues that flash fiction uniquely draws the reader into a partnership with the writer and it is with their combined contribution that the story is completed and remains memorable

EEG-based image classification using an efficient geometric deep network based on functional connectivity

To ensure that the FC-GDN is properly calibrated for the EEG-ImageNet dataset, we subject it to extensive training and gather all of the relevant weights for its parameters. Making use of the FC-GDN pseudo-code. The dataset is split into a "train" and "test" section in Kfold cross-validation. Ten-fold recommends using ten folds, with one fold being selected as the test split at each iteration. This divides the dataset into 90% training data and 10% test data. In order to train all 10 folds without overfitting, it is necessary to apply this procedure repeatedly throughout the whole dataset. Each training fold is arrived at after several iterations. After training all ten folds, results are analyzed. For each iteration, the FC-GDN weights are optimized by the SGD and ADAM optimizers. The ideal network design parameters are based on the convergence of the trains and the precision of the tests. This study offers a novel geometric deep learning-based network architecture for classifying visual stimulation categories using electroencephalogram (EEG) data from human participants while they watched various sorts of images. The primary goals of this study are to (1) eliminate feature extraction from GDL-based approaches and (2) extract brain states via functional connectivity. Tests with the EEG-ImageNet database validate the suggested method's efficacy. FC-GDN is more efficient than other cutting-edge approaches for boosting classification accuracy, requiring fewer iterations. In computational neuroscience, neural decoding addresses the problem of mind-reading. Because of its simplicity of use and temporal precision, Electroencephalographys (EEG) are commonly employed to monitor brain activity. Deep neural networks provide a variety of ways to detecting brain activity. Using a Function Connectivity (FC) - Geometric Deep Network (GDN) and EEG channel functional connectivity, this work directly recovers hidden states from high-resolution temporal data. The time samples taken from each channel are utilized to represent graph signals on a topological connection network based on EEG channel functional connectivity. A novel graph neural network architecture evaluates users' visual perception state utilizing extracted EEG patterns associated to various picture categories using graphically rendered EEG recordings as training data. The efficient graph representation of EEG signals serves as the foundation for this design. Proposal for an FC-GDN EEG-ImageNet test. Each category has a maximum of 50 samples. Nine separate EEG recorders were used to obtain these images. The FC-GDN approach yields 99.4% accuracy, which is 0.1% higher than the most sophisticated method presently availabl

A Determinant Of Healthy Ageing Women Education In Saudi Arabia

An increase in the number of elderly people has major implications for society, affecting such areas as health and social services and public spending. The economic effects of an ageing population are considerable. Older people have more savings than younger people, but spend less on consumer goods. The rise in ageing populations will also increase some categories of expenditure, like health care, whose cost is likely to increase dramatically as the population ages. Saudi Arabians, while relatively enthusiastic about saving in general, see retirement as a less important incentive to save and have reduced retirement savings as a result of the current economic downturn. At the same time, life expectancy will be higher and birth rate will decline because of the increase of education levels. People's concepts of birth and health care will be improved under the function of education. Education is the single most important indicator of the socioeconomic status of an individual, which affects almost all aspects of human life, including demographic health behavior. Change of the increase of population ageing that is caused by the change of the relative number of independent variables, such as education, is more of a concern

Neural network to investigate gaming addiction and its impact on health effects during the COVID-19 Pandemic

The Playing games become a serious issue and may have adverse effects on the quality of life of children. The research aims at identify in the factors and degree of influence which lead to gaming addiction and its impact on the quality of life of world children employing a comprehensive. Our method collects 2,526 children and adults’ data for five significant regions globally contain schools and universities in municipal and non-municipal areas. The research also aims to investigate the effect that gaming addiction has on the quality of life of children. Structural equation test and the (NNM) were uutilized to analyze the data. The results indicate some differences between boys and girls as to what factors lead to gaming addiction. The average Root Means Square Error (RMSE) of the neural network model is relatively low (.0103 for male training data and .0113 for male examining data, while for females it was .0103 for exercising data and .0104 for examining data), But gaming addiction was found to harm the life for both genders. Discussions comprising both academic as well as practical perspectives are also presented

Process Evaluation for Wheat Germ Oil Degumming

The objectives of this study are to optimize a degumming process that will efficiently remove phospholipids from crude wheat germ oil (CWGO) with minimal oil loss and to examine the effect of degumming processes on oil quality and bioactive compounds naturally present in wheat germ oil (WGO). The following methods were used to remove phospholipids: water, acid (citric and phosphoric acids) and enzymatic (Lecitase Ultra and Lysomax) degumming processes. The phosphorus content was 1,860 mg/kg in hexane- extracted and 1,360 mg/kg in mechanically pressed CWGO. After the water degumming, about 56 and 23% phosphorus reduction were achieved in hexane- extracted and mechanically pressed WGO, respectively. Both citric and phosphoric acid degumming were less effective than water degumming and reduced the amount of phosphorus about 39 and 47% in hexane- extracted and 16 and 13% in mechanically extracted WGO, respectively. Enzymatic degumming, which decreased the amount of phosphorus content about 88, 84 and 69% in hexane- extracted WGO and 82, 78 and 53% in mechanically pressed CWGO using Lecitase Ultra, Lysomax, and Gumzyme, respectively. Lecitase Ultra was the most effective enzyme to reduce phospholipid content of both hexane-extracted and mechanically pressed CWGO. Enzymatic degumming significantly increased the FFA content of the oil. All degumming processes resulted in tocopherol loss.Biosystems & Agricultural Engineerin

Flexible Job Shop Scheduling Problem-Solving Using Apiary Organizational-Based Optimization Algorithm

Flexible job shop scheduling problem (FJSSP) is a complex and challenging problem that plays a crucial role in industrial and manufacturing production. FJSSP is an expansion of the standard job shop scheduling problem (JSSP). One of FJSSP’s objectives that the manufacturing system competing for is minimizing the makespan. This paper uses a new nature-inspired metaheuristic optimization algorithm called the Apiary Organizational-Based Optimization algorithm (AOOA) to solve the FJSSP. This Algorithm simulates the organizational behavior of honeybees inside the apiary and translates their activities and vital processes during their lifecycle into phases that can solve such NP-hard problems. Two benchmark datasets, Brandimarte and Hurink, with 10 MK instances and 24 (edata, rdata, and vdata) instances respectively, were used to demonstrate the ability of AOOA to solve FJSSP. Moreover, the results of AOOA were compared with a set of state-of-the-art algorithms and statistically measured using the paired samples t-test and p-value, RPD, and group-based superiority statistical analysis to test its performance. AOOA outperformed Elitism GA, Enhanced GA, Improved GA, and MOGWO in solving all 10 MK instances and HICSA in solving 9 MK instances out of 10. Moreover, AOOA overcame CS, CS-BNG, CS-ILF, CHA, and MCA in solving 24, 12, 12, 23, and 24 instances of edata, rdata, and vdata, respectively. AOOA proved its robustness, showing promising outcomes

Perspective des résidents : Est-ce que le programme saoudien de formation de résidence en chirurgie générale met en œuvre les compétences CanMEDS et prépare les leaders de demain?

Background: This study investigates leadership skills and Canadian Medical Education Directives for Specialists (CanMEDS) competencies acquisition within the General Surgery Residency Training Program (GSRTP). The Saudi Commission for Health Specialties (SCFHS) incorporates the CanMEDS Competency Framework into its curriculum to prepare the resident for healthcare needs. Methods: This is a descriptive-analytical study. A questionnaire was used to collect data from 117 General Surgery residents (GS) at seven institutes in Jeddah, Saudi Arabia. Results: The GS residents reported an acceptable self-perceived level of Clinical Leadership Skills (mean ± standard deviation). The most dominant skill was working with others (1.98 ± 1.03), followed by demonstrating personal qualities (2.07 ± 0.88), the ability to manage services (2.21 ± 1.37), improving services (2.22 ± 1.84) and last, setting directions (2.39 ± 0.95). Regarding the CanMEDS competencies, the respondents showed a generally positive perception with an “agree” level (Mean = 1.83). Of the CanMEDS competency roles, Collaborator ranked first followed by Professional and then Communicator. Leader competency ranked fourth followed by Health Advocate, Medical Expert and last, Scholar. Conclusion: The GSRTP residents showed satisfactory self-assessed clinical leadership skills and acquirement of the CanMEDS competencies during their training, which will prepare them to lead in the future.Contexte : Cette étude se penche sur les compétences en leadership et l’acquisition de compétences CanMEDS (Canadian Medical Education Directives for Specialists - directives canadiennes en formation médicale pour les spécialistes) au sein du GSRTP (programme de formation en résidence en chirurgie générale). La SCFHS (commission saoudienne pour les spécialistes de la santé) intègre le cadre des compétences CanMEDS dans son programme pour préparer les résidents aux besoins en matière de soins de santé. Méthodes : Il s’agit d’une étude descriptive et analytique. Un questionnaire a été utilisé pour collecter des données auprès de 117 résidents en chirurgie générale dans sept instituts médicaux à Djeddah, Arabie saoudite. Résultats : Les résidents en chirurgie générale ont rapporté un niveau perçu acceptable de compétences en leadership clinique (moyenne ± écart type) La compétence la plus dominante était le travail avec les autres (1,98 ± 1,03), suivi par la démonstration de qualités personnelles (2,07 ± 0,88), la capacité de gérer les services (2,1 ± 1,37), l’amélioration des services (2,22 ± 1,84) et, finalement, l’établissement des orientations (2,39 ± 0,95). En ce qui a trait aux compétences CanMEDS, les répondants ont montré une perception généralement positive avec un niveau « d’accord » (moyenne = 1,83). En ce qui a trait aux rôles associés aux compétences CanMEDS, celui de collaborateur s’est classé au premier rang, suivi par celui de professionnel et ensuite de communicateur.  Le rôle de chef de file s’est classée quatrième en matière de compétence, suivie de défenseur de la santé, d’expert médical et, finalement, d’érudit. Conclusion : Les résidents du GSRTP ont montré une satisfaction en matière de compétences de leadership clinique autoévaluées et d’acquisition des compétences CanMEDS lors de leur formation, laquelle les préparera à jouer un rôle de premier plan dans l’avenir

Perceptions of Social Media Impact on Students' Social Behavior: A Comparison between Arts and Science Students

Abstrac