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Abstract: This study aims to understand the role of algorithms in information misinformation by marginalizing media information, which in turn hinders media literacy. The rapid spread of artificial intelligence and algorithmic systems raises concerns due to their lack of transparency, complicating assessments of compliance with human rights and labor laws. Algorithms can exhibit bias based on the training data and their correlation with processed data features. This issue has spurred discussions within the scientific community about biases and the ethical, computational, and media effects of algorithms. Keywords : Algorithms, Misinformation, Media Literacy, Bias, Transparency

Abstract: The current study examined vowel identification among 72 phonetically trained and untrained Algerian students of English enrolled in Master 2 English Language and Letters and Mathematics courses, respectively, at Mentouri University of Constantine. The study used a multiple alternative forced choice (m-AFC) classification test to assess participants’ identification rates of isolated RP prototypic vowels across varying temporal manipulations. It was hypothesised that phonetically trained and untrained participants would use acoustic features of examined vowels differently to identify vowels, with phonetically trained participants showing higher identification rates compared to untrained ones. Analysis of results demonstrated that the use of temporal and spectral features of vowels varied non-significantly across phonetically trained and untrained participants. The results show that vowel identification may be subject to specific speech mechanisms and non-significantly affected by phonetic training, suggesting the limited role of explicit phonetic instruction in vowel perception among L2 learners and the need for more effective teaching methods. Keywords: vowel identification rate, acoustic, durational manipulations, phonetically trained, untrained

Article accepted. The article will be published here soon. Pending final quality checks.

Article accepted. The article will be published here soon. Pending final quality checks.

ABSTRACT Forty male Naemi lambs were used to evaluate the effect of total mixed rations (TMR) alone or in combination with supplementation of alfalfa hay offered at different schedules on growth, carcass characteristics, and meat quality. Lambs at the age of three months, with an average weight of 28.85±1.09 kg, were randomly selected and distributed into four different feeding systems, 10 lambs each, as follows: TMR diet (control); TMR plus 100 g alfalfa hay; TMR plus 200 g alfalfa hay every two days; and TMR plus 300 g alfalfa hay every three days. The TMR and fresh drinking water were offered ad libitum. Lambs in the treated groups (with alfalfa hay) had significantly higher body weight, body weight change, dry matter intake, and feed conversion ratio compared with the control. Similarly, slaughter weight, carcass weight (hot and cold), and internal organs weight significantly increased in the treated groups, except for dressing weight percentage, which improved only in the treatment with TMR plus 300 g alfalfa hay. By contrast, mesentery fat, back fat, and body wall fat decreased in treated groups. Meat quality characteristics indicated that cooking loss and pH values did not differ between the control and treated groups; however, meat colour (lightness, yellowness, and redness) and pH (1 and 24 h) improved in post-slaughter treated groups. Furthermore, no difference was found in texture profile analysis (hardness, springiness, cohesiveness, and chewiness), although the shear force decreased significantly in treated groups. Addition of alfalfa hay offered at the present plan may not only improve the growth and carcass characteristics, but also enhance the meat quality of Naemi lambs. From the labour and economic point of view, TMR plus 300 g alfalfa hay every three days may be adopted while taking into account the management decision.

The advent of telecommunication era and the constant development of hardware and network structures have encouraged the decentralization of data while increasing the needs to access information from different sites.