Explore the vast range of titles available.

This study introduces Applied Legal Linguistics (ALL) as a praxis-oriented framework that integrates linguistic theory, corpus-based analysis, and legal discourse studies to address the pedagogical, translational, and communicative challenges of legal language use in multilingual and cross-systemic legal contexts. Within this framework, the inquiry investigates the challenges encountered by Arab law students in the English section of the Faculty of Law as they translate legal texts between structurally and culturally divergent legal systems. Anchored in the framework of SDG-4, which advocates for the provision of quality education, this research specifically explores the influences of gender and academic level on the students’ translation competencies. A sample of 139 students, stratified by gender (Male Legal English Section Students (MLESSs), Female Legal English Section Students (FLESSs)), and academic level (2nd-year Legal English Section Students (2nd LESSs), and 4th-year Legal English Section Students (4th LESSs)), participated in the study. The participants translated a legal text, and their outputs were compared to a reference translation produced by two expert legal translators. Utilizing a multidimensional error analysis model assessing lexical, syntactic, spelling, punctuation, and stylistic features, this corpus-driven analysis evaluated various dimensions of the students’ translations. A qualitative examination was conducted to identify error distributions and to assess the degree to which gender and academic level influence the translational outcomes. The findings indicate that 2nd-year students made more frequent lexical, grammatical, and punctuation errors than their 4th-year counterparts, while male students exhibited higher error rates overall than female students, particularly in lexical and grammatical categories. The investigation recommends structured workshops and targeted training, especially for male and early-stage students. It contributes to legal translation research by addressing the overlooked influence of gender and academic level, and by revealing how language proficiency and legalese complexity interact within the context of Arab legal education.

Purpose>This research is a critical discourse analysis (CDA) of Trump's speech on January 6, 2021, which results in his supporters' storming the US Capitol in order to challenge certifying Biden's victory. The Democrats accused Trump of incitement of insurrection. Consequently, Trump was impeached. This article investigates Trump's speech to label it as hate speech or free speech.Design/methodology/approach>Analytical framework is tri-dimensional. The textual analysis is based on Halliday's notion of process types and Huckin's discourse tools of foregrounding and topicalization. The socio-cognitive analysis is based on Van Dijk's ideological square and his theory of mental models. The philosophical dimension is founded on Habermas's theory of discourse. These parameters are the cornerstones of the barometer that will be utilized to reach an objective evaluation of Trump's speech.Findings>Findings suggest that Trump usually endows “I, We, You” with topic positions to lay importance on himself and his supporters. He frequently uses material process to urge the crowds' action. He categorizes Americans into two conflicting poles: He and his supporters versus the media and the Democrats. Mental models are created and activated so that the other is always negatively depicted. Reports about corruption are denied in court. Despite that, Trump repeats such reports. This is immoral in Habermas's terms. The study concludes that Trump delivered hate speech in order to incite the mob to act in a manner that may change the election results.Originality/value>The study is original in its tri-dimensional framework and its data of analysis.

This study investigates how Saudi National Identity (SNI) is performed through citizen-authored multimodal texts commemorating the 94th Saudi National Day. It introduces the Multimodal Hermeneutic-Cultural Discourse (MHCD) Model—a novel triadic framework integrating Cultural Discourse Studies (CuDS), visual grammar, and philosophical hermeneutics—to analyze how meaning emerges across visual and verbal modes. Fifteen image-caption pairs were purposively selected and examined across five thematic domains: heritage and ancestral continuity, gendered kinship and relational identity, faith and moral vision, unity and national power, and youth and futurity. Visual features such as traditional dress, ritual gestures, spatial icons, and collective presence express cultural memory as embodied practice. Verbal texts reinforce belonging through speech acts that commemorate ancestry, affirm shared values, and project futurity—evident in expressions like “our roots,” “for God and the nation,” and “the future is in our hands.” The hermeneutic synthesis reveals that meaning is not inherent in image or text alone, but arises through their dialogic convergence. Findings demonstrate that Saudi identity is actively performed through multimodal composition as a lived, ethical, and future-oriented discourse. This study contributes to multimodal discourse analysis by offering a culturally grounded model for interpreting vernacular nationalism and highlights the expressive agency of ordinary citizens in shaping national belonging through symbolic participation. Telling the Nation’s Story: Saudi Identity Through Citizen-Created Images, Titles, and Captions during the 94th National Day This study introduces the Multimodal Hermeneutic-Cultural Discourse (MHCD) Model, a new analytical framework that integrates Cultural Discourse Studies, visual grammar, and philosophical hermeneutics to interpret how Saudi citizens express national identity through image-title-caption compositions. Using this model, the study analyzes fifteen visual-textual artifacts created by citizens, grouped into five main themes: heritage, gendered kinship, faith, unity, and futurity. In the visual dimension, heritage is expressed through traditional garments, architecture, and symbolic objects; gendered kinship appears through intergenerational arrangements and shared space; faith is visually represented via modest dress and color symbolism; unity is embodied in synchronized public displays; and futurity is illustrated by children in modern, aspirational environments. In the verbal dimension, both titles and captions are key to expressing cultural values. Heritage is evoked through references to ancestry and origin. Gendered kinship is affirmed through inclusive language celebrating both sons and daughters. Faith is invoked through moral and religious phrases such as “for God and the homeland.” Unity is emphasized through phrases about collective alignment and shared direction, while futurity is articulated through aspirational statements that place youth at the center of the nation’s development. In the hermeneutic dimension, meaning arises from the interaction between image, title, and caption. For example, a child in traditional dress becomes a symbol of cultural continuity when the accompanying title and caption frame the image in terms of family legacy. A fireworks display or a modern shopping mall becomes a sign of national ambition only when verbal components connect it to visions of Saudi Arabia’s future. Across all five themes, the MHCD Model reveals that Saudi identity is not merely represented but actively performed through culturally embedded signs.

The widespread integration of generative AI into academic writing has created a new communicative context in which human authorship coexists with algorithmic fluency, yet their phraseological relationship remains insufficiently understood. To address this gap, this study examines the phraseological differences between human-authored and AI-generated academic writing within the emerging framework of Human–Artificial Intelligence Togetherness (HAIT). Using a comparative corpus-based approach, it analyzes three datasets: first-year English as a Second Language (ESL) student texts (F1C), fourth-year ESL student texts (F4C), and AI-generated texts (AIC) produced by five large language models. The analysis focuses on five key features—type–token ratio (TTR), collocations, colligations, lexical bundles, and formulaic sequences—to explore how phraseological competence develops in human learners and how it contrasts with the fluency produced by algorithmic simulation. Results indicate a clear developmental trajectory between F1C and F4C: lexical variety, structural complexity, and phraseological density increase incrementally, yet both human corpora remain thematically narrow, often restricting the prompt “social” to social media contexts. In contrast, the AI corpus exhibits immediate lexical breadth, thematic diversity, and syntactic precision, with frequent use of advanced academic bundles and stable colligational forms. However, AI texts lack the hallmarks of developmental authenticity, such as revision, contextual adaptation, and evidence of cognitive effort. This asymmetry highlights the ontological divide between experiential human authorship and statistically generated fluency. The findings highlight that using AI writing as a benchmark risks obscuring L2 development, urging pedagogy centered on reflection, phraseological visibility, scaffolded authorship, and epistemic integrity. How English Learners Develop Phraseology in Academic Writing—And How This Differs from the Instant Phraseological Fluency of Artificial Intelligence This study investigates how English as a Second Language (ESL) students develop phraseology—the way words and grammatical patterns are combined—in academic writing, and how this process differs from the phraseological patterns produced by artificial intelligence (AI). We compared three collections of short academic texts written on the same topic: one by first-year ESL students, one by fourth-year ESL students, and one by AI systems including ChatGPT, Claude, Gemini, and Writesonic. The analysis focused on five features of phraseology: type–token ratio (lexical diversity), collocations (common word pairings), colligations (grammar-pattern combinations), lexical bundles (recurring 3–5 word sequences), and formulaic sequences (fixed expressions). Human learners showed a clear developmental path between the first and fourth years: vocabulary grew, sentence patterns became more stable, and phraseological density increased. However, both student groups tended to use a narrow set of topics, often limiting the word “social” to social media contexts. AI-generated texts were different. They showed wide-ranging vocabulary, thematic variety, and precise grammar, with advanced collocations, varied colligations, and polished lexical bundles appearing immediately. Yet, this fluency was not the result of gradual learning—AI outputs lacked the revision, adaptation, and cognitive effort that mark genuine phraseological development in humans. These findings have important teaching implications. Using AI-generated writing as a model may give an unrealistic picture of how phraseology is learned. Effective instruction should make learners’ phraseological growth visible, provide opportunities for scaffolded practice, and value the process of building phraseological competence over time, rather than only the final polished product.

This study offers a corpus-based comparative analysis of authorial voice in Q1 linguistics and hard science journal articles, examining how stance, engagement, and genre conventions are shaped by disciplinary epistemologies and rhetorical norms. Drawing on Hyland's stance and engagement model and Swales's genre theory, the research analyzes 100 IMRAD-structured articles across two corpora totaling over one million tokens. Quantitative frequency analysis and qualitative discourse examination reveal striking disciplinary asymmetries. Linguistics articles exhibit greater rhetorical density and interpersonal alignment, marked by extensive use of self-mention, hedges, boosters, directives, and reader pronouns-constructing a reflexive, dialogic authorial identity. In contrast, hard science writing is characterized by evidential saturation, procedural detachment, and epistemic restraint, foregrounding authorial effacement and methodological fidelity. Genre analysis shows linguistics favors pronounced gap-identification and metadiscursive commentary, while hard sciences adhere to compressed, data-driven exposition. Q1 journal conventions function as discursive gatekeepers, regulating authorial visibility in alignment with field-specific communicative values. The study reconceptualizes authorial voice as a genre-bound, ideologically embedded construct shaped by disciplinary traditions and institutional expectations. Implications are drawn for genre-based writing pedagogy and for understanding voice as a regulated performance of academic identity and epistemic legitimacy.

Antibiotics are used in the poultry industry to treat and prevent diseases. Their frequent use resulted in the appearance of antibiotic residuals in poultry meat, which is considered a serious public health issue. Among frequently used antibiotics are cefotaxime (CTX), ciprofloxacin (CIP), colistin (CST), doxycycline (DOX), flumequine (FLU), sulfamethoxazole (SMZ), trimethoprim (TMP) and tylosin (TYL). This study aimed to develop an optimized and validated method for concurrent estimation of the eight antibiotics in broiler chicken samples based on an easy extraction method followed by HPLC-UV and LC/MS/MS analysis. An experimental design was used for the optimization of the extraction procedure. Optimal conditions for separation were determined by using a central composite design after studying (1) mobile phase initial concentration, (2) column temperature, and (3) flow rate. The method was validated on the bases of ICH guidelines. The detection limits ranged from 3 to 5 µg kg−1 for HPLC- UV and ranged from 0.01 to 0.05 µg kg−1 for LC/MS/MS, while quantification limits ranged from 10 to 16 µg kg−1 for HPLC- UV and ranged from 0.01 to 0.11 µg kg−1 for LC/MS/MS. The chromatographic techniques were utilized for the analysis of spiked broiler chicken samples at a concentration range from 30 to 300 µg kg−1) for HPLC-UV and 0.01–20 µg kg−1 for LC/MS/MS. The proposed methods were used for quantification of the residues of the studied antibiotics in real broiler samples obtained from local supermarkets in Ismailia governorate, Egypt. The detected levels of residual antibiotics were within the permissible limits.

The main objectives of this study were for comparing the effect of batteries and deep litter rearing systems of domesticated Japanese quail, , on the concentration levels of cadmium, copper, lead, and zinc from the quail meat and offal in Ismailia, Egypt. A total of 40 quail meat and their offal samples were randomly collected from two main quail rearing systems: Battery (Group I) and deep litter system (Group II) for determination of concentration levels of cadmium, copper, lead, and zinc. In addition, 80 water and feed samples were randomly collected from water and feeders of both systems in the Food Hygiene Laboratory, Faculty of Veterinary Medicine, Suez Canal University for heavy metals determination. The mean concentration levels of cadmium, copper, lead, and zinc in Group I were 0.010, 0.027, 1.137, and 0.516 ppm and for Group II were 0.093, 0.832, 0.601, and 1.651 ppm, respectively. The mean concentration levels of cadmium, copper, lead, and zinc in quail feed in Group I were 1.114, 1.606, 5.822, and 35.11 ppm and for Group II were 3.010, 2.576, 5.852, and 23.616 ppm, respectively. The mean concentration levels of cadmium, copper, lead, and zinc in quail meat for Group I were 0.058, 5.902, 10.244, and 290 ppm and for Group II were 0.086, 6.092, 0.136, and 1.280 ppm, respectively. The mean concentration levels of cadmium, copper, lead, and zinc for liver samples in Group I were 0.15, 8.32, 1.05, and 3.41 ppm and for Group II were 0.13, 8.88, 0.95, and 4.21 ppm, respectively. The mean concentration levels of cadmium, copper, lead, and zinc in kidney samples for the Group I were 0.24, 4.21, 1.96, and 4.03 ppm and for Group II were 0.20, 5.00, 1.56, and 3.78 ppm, respectively. Kidney had the highest concentration levels of heavy metals followed by liver then muscles. The highest concentration levels of copper were observed in liver samples. The order of the levels of these trace elements obtained from the four different quail organs is Ca > Pb > Zn > Cu. Lead and cadmium concentration levels in quail meat samples were exceeded the Egyptian standardization limits and suggesting a health threat from lead and cadmium to the quail consumers. Battery rearing system is more hygienic than deep litter system from the point of heavy metals pollution of water and feeds of quail. Feed samples from battery system had means concentration levels of lead not significantly higher (p>0.05) than those samples from deep litter system. Meanwhile, water samples from battery system had means concentration levels of cadmium, copper, and zinc significantly higher (p>0.05) than those samples from deep litter system. Quail may carry health risks to consumers.

This paper is a stylistic/cognitive analysis of a narrative based on Text World Theory (TWT) in an attempt to identify the text worlds, the discourse worlds and the subworlds in the text under analysis. Cognitive Linguistics is an interdisciplinary approach incorporating language and cognitive abilities. Emphasis is on the manner by which humans process language and build mental representations, text-worlds, to reach a thorough comprehension of meaning structures. The short story analyzed is \"Beneath the Cracks\", by Nicole Disney. This research tries to prove that context dependent text world analysis of narratives is useful in rendering participants' senses. (TWT), in the works of Werth (1999) and Gavins (2007a, 2007b), provides an explanatory account of the way readers build mental models based on the linguistic items presented. TWT explains the process of readers' moving from textual information towards the deep nature of text worlds. It is concluded that TWT demonstrates the cognitive processes taking place through the process of reading, the process that leads to text interpretation and accessing meaning. The short narrative is evidence that TWT is a tool that reveals human mental representations and their changing stages according to life defiance and struggles. This paper is original in its interpretation of new scopes of text meanings based on Text World Theory.

Autism Spectrum Disorder causes difficulties in interaction and communication, hence this study is an attempt to shed some light on autistic children's discourse concerning the way they employ cohesive ties and show cooperation during conversation. This is a preliminary step to propose some suggestions that may help these children with their troubles and challenging conditions. Research method is based on an analysis of the autistic discourse regarding two points: children's observance of the Cooperative Principle in conversation and their use of cohesive ties. Grice's notion of The Cooperative Principle (1975) that governs conversational behaviors assume that conversation is a cooperative endeavor between interactants. Halliday and Hasan (1976) discuss the notion of cohesion in discourse and consider that any text should be unified by certain cohesive devices. This study approaches autistic children's discourse from the two perspectives: cooperation and cohesion. It concludes that autistic children employ echolalia to implicate their acceptance of the activity presented, which is a cooperative act. It is concluded that using words relating to the same relevant topic is nearly the only cohesive device employed by autistic children. Research limitation has to do with conducting an analysis of a child's discourse despite the child's inability to communicate and his repetitive linguistic behaviors. The study may be practical in suggesting some directions to improve autistic children's performance and social communication. Echolalia, for instance, may be considered as a positive act of cooperation, and be taken as a step to move forward and train the child to repeat and utter a comment or express his desire. Autistic children should be trained to use various cohesive devices, such as synonymy and antonymy. This paper tries to make better language activities related to autistic children.

This paper investigates the frequency and contextual uses of the metadiscoursal devices of evidentials, code glosses, hedges and boosters in four academic disciplines, namely, linguistics, literature, chemistry and medicine. Hyland and Hinkel’s taxonomies of metadiscourse provided the search items. The data analyzed consisted of a corpus of forty research articles, divided into four subcorpora equally drawn from the four disciplines. The corpus was randomly selected from leading international journals and processed by the corpus analysis toolkit, AntConc. The AntConc concordancer was employed so that each metadiscourse item could be counted and examined in its context. The findings show that hedges were the most frequent metadiscoursal device, which may be seen as an indication of the academic authors’ tendency to use language of caution and uncertainty. The second rank in frequency was occupied by evidentials, which reflects the need for academic writing to establish credibility. Code glosses and boosters have the least frequency, which may measure for the value of conciseness in academic discourse. The analysis also shows that linguistics and literature exceed the two scientific disciplines, chemistry and medicine, in the frequency of the four metadiscoursal devices. Linguistics manifests the highest distribution of hedges and code glosses, medicine the highest number of boosters, literature the highest frequency of evidentials. Chemistry has the lowest frequency of all metadiscoursal devices. This study aims to help students of academic writing to learn about the use of the selected metadiscoursal devices in many disciplines. Future studies need to investigate more metadiscoursal devices in other academic disciplines.