Search Results (110)

A substantial number of students with hearing impairments are enrolled in higher education, motivating the development of inclusive assistive technologies that reduce communication barriers. This study developed and evaluated a prototype electronic glove that translates Mexican Sign Language (LSM) signs into Spanish text using machine learning. Eight participants (four deaf and four hearing with LSM proficiency) completed four sessions involving 12 signs; three sessions (S1–S3) were used for model development and one session (T) was held out for evaluation. Models were trained on S1–S3 and tested on T using a session-level split without window mixing across sessions; therefore, results represent a speaker-dependent, inter-session pilot assessment rather than a speaker-independent generalization test. The glove integrates flex sensors and an inertial measurement unit IMU MPU6050 connected to an ESP32-C3 SuperMini microcontroller. These components were selected due to their low cost, availability, and ease of integration, making them suitable for the development of accessible wearable assistive technologies. Under this protocol, the system achieved a window-level overall test accuracy of 97.0% (95% CI computed at the window level: 96.00–97.00), with higher performance for the dynamic subset (98.0%) than for the static subset (95.0%), and an algorithmic decision delay of 1.2 s. Usability and acceptance were evaluated using the System Usability Scale (SUS) and a Technology Acceptance Model (TAM)-based questionnaire. The mean SUS score was 50.6 ± 1.8 (marginal usability), while participants reported positive perceptions across TAM constructs. Overall, findings demonstrate technical feasibility under controlled inter-session conditions and provide a foundation for iterative user-centered refinement, followed by strict speaker-independent validation and classroom deployment studies in future work. Full article

In today’s world, characterised by rapid technological advances, particularly in AI, companies are compelled to acquire knowledge through employee training. This article seeks to empirically validate four hypotheses derived from a theoretical model identifying key factors firms should consider when investing in training. The hypotheses concern the most suitable type of knowledge for companies to invest in, according to their production processes, as well as the mechanisms for preventing opportunistic behaviour by trained employees. Cross-frequency tables are analysed using data obtained from a sample of 105 Mexican companies operating in both manufacturing and services sectors, representing an appropriate approach given the nature of the data. The results partially support the model. Manufacturing firms tend to train employees in specific skills and use simultaneous training to prevent opportunistic behaviour, whereas companies with heterogeneous production processes predominantly invest in general knowledge. However, firms providing professional services invest more in general knowledge than predicted by the model, contrasting with evidence from Spanish companies in the same industry. These findings suggest that the model should be refined to account for the possible complementarity between specific and general knowledge in training and for differences in institutional, cultural, and economic environments. Full article

In the pragmaticalization of ya ves que… ‘you see that…’, the perceptual basis of the verb becomes diluted, keeping its deictic profile. Most of its pragmatic values extend to non-perceptual phenomena, implying shared knowledge. Further extensions involve bleaching the concrete referent into abstract shared information in the form of (i) first and second-hand evidentials: shared and alien facts presented as familiar; (ii) mitigators: small appeal to shared information; (iii) miratives missing crucial information; and (iv) a continuity discourse marker where shared information is not relevant. Based on spontaneous oral data from Mexican Spanish, we propose that intersubjectivity prevails given its common ground deictic schema, allowing for assumed information to become diluted into a fictive common space where the speaker assumes the existence of notions the speaker may not always have. Diachronic data support the analysis: data from the 16th–17th century from Spain show the prevalence of testimonial references with no presence of shared knowledge; from the 19th century onward, shared knowledge becomes crucial, and it is not until current informal Mexican Spanish that even referential and shared knowledge may be diluted, and the assessment is validated by incorporating the hearer into the speaker’s mental space. Full article

Grassland-based livestock systems across Mexico’s arid and semi-arid belt are increasingly exposed to drought, degrading forage reliability, and soil function. This review synthesizes evidence on native C4 grasses and forage shrubs as complementary building blocks of drought-resilient swards. We searched Web of Science, Scopus, CAB Abstracts and key grey sources (USDA/NRCS Plant Guides, USFS FEIS, Tropical Forages, SNICS) for 1990–2025 studies in English/Spanish. Dominant native grasses (Bouteloua spp., Hilaria belangeri, Digitaria californica, Trichloris crinita, Sporobolus airoides, Panicum hallii) provide high warm-season digestibility and structural cover via C4 physiology, basal/intercalary meristems, and deep/fibrous roots. Forage shrubs (Atriplex canescens, Desmanthus bicornutus, Leucaena leucocephala, Flourensia cernua, Prosopis spp.) bridge the dry-season protein/energy gap and create “resource islands” that enhance infiltration, provided anti-nutritional risks (mimosine/DHP, tannins, salts/oxalates, terpenoids) are managed by dose and diet mixing. We integrate these findings into a Resistance–Recovery–Persistence framework and translate them into operations: (i) site-matching rules for species/layouts, (ii) PLS (pure live seed)-based seed specifications and establishment protocols, (iii) grazing TIDD (timing–intensity–distribution–duration) with a practical monitoring dashboard (CP targets, stubble/cover thresholds, NDVI/SPEI triggers). Remaining bottlenecks are seed quality/availability and uneven extension; policy alignment on PLS procurement and regional seed increase can accelerate adoption. Mixed native grass–shrub systems are a viable, scalable pathway to strengthening drought resilience in Mexican rangelands. Full article

Background/Objectives: The Montreal Cognitive Assessment (MoCA) is a widely used cognitive screening tool designed to detect cognitive impairment. However, evidence indicates that the original cut-off score of 26 and the one-point correction for low education may not be appropriate across diverse populations. In Latin America, and particularly in Mexico, existing validation studies are scarce and limited by small sample sizes. The objective of this study was to examine the effects of age and education on MoCA performance in Mexican adults and to develop regression-based normative data for more accurate interpretation. Methods: MoCA performance of 2546 cognitively healthy participants aged 18–99 years from two public health institutions in Mexico City was analyzed. Inclusion criteria required preserved cognition, functionality, independence, and absence of conditions directly affecting brain health. The Spanish version 8.1 of the MoCA was administered. Age-adjusted normative values were obtained. Then, regression analyses were applied to generate age- and education-adjusted norms. Results: MoCA total scores correlated negatively with age and positively with education, while sex showed no significant effect. Regression-based norms revealed that identical raw total scores have different normative interpretations depending on age and education. Conclusions: This study provides the first regression-based MoCA norms for Mexican adults, demonstrating that both age and education exert a substantial influence on test performance. These norms enable a more precise, culturally sensitive interpretation than fixed cut-off scores and reduce the risk of misclassification in clinical and research settings. Full article

Background/Objectives: This study aims to evaluate whether the Dietary Guidelines for Americans (DGA) are effective for maintaining a healthy diet among Mexican-descent populations in the US or if a more culturally tailored policy approach is warranted. Methods: As a first outcome, 20 healthy women of Mexican descent from the Seattle area participated in a pilot randomized controlled trial. They were randomly assigned (10 participants each) to either a group receiving instruction on the standard 2015 DGA or a group receiving an adaptation of the DGA focused on traditional Mexican cuisine and culture. In this 12-week study (with follow-ups at 3 and 6 months), participants’ acceptability of the cultural adaptation of the DGA was compared with that of the standard DGA with end-of-study surveys. Ten blood-based metabolic biomarkers were assessed at baseline and 3 months. Dietary changes at 3 months were assessed with a Food Frequency Questionnaire (FFQ) that was translated into Spanish but not culturally adapted. The secondary outcome was dietary change at 6 months. Results: The primary findings at 3 months showed that serum free fatty acids were reduced for the standard DGA arm. Carbohydrate consumption was reduced in the standard DGA arm only. The end-of-study survey results suggested that both interventions were well received by participants. Conclusions: The preliminary findings from this small sample size suggest that depending on a person’s priorities, either intervention could be offered, with each arm showing slightly different dietary and biomarker outcomes. Full article

The proliferation of social media has made Sentiment Analysis an essential tool for understanding user opinions, particularly in underrepresented language variants such as Mexican Spanish. Recent advances in Large Language Models have made effective sentiment analysis through in-context learning techniques, reducing the need for supervised training. This study compares the performance of zero and few-shot with traditional fine-tuning approaches of tourism-related texts in Mexican Spanish. Two annotated datasets from the REST-MEX 2022 and 2023 shared tasks were used for this purpose. Results show that fine-tuning, particularly with the MarIA model, achieves the best overall performance. However, modern LLMs that use in-context learning strategies, such as Mixtral 8x7B for zero-shot and Mistral 7B for few-shot, demonstrate strong potential in low-resource settings by closely approximating the accuracy of fine-tuned models, suggesting that in-context learning is a viable alternative to fine-tuning for sentiment analysis in Mexican Spanish when labeled data is limited. These approaches can enable intelligent, data-driven digital services with applications in tourism platforms and urban information systems that enhance user experience and trust in large-scale socio-technical ecosystems. Full article

This study investigates how Mexican Spanish/U.S. English heritage bilinguals process scope ambiguities in sentences containing the existential quantifiers a/una and the universal quantifiers every/cada in English and Spanish. Sentences like ‘A person bought every book’ are syntactically ambiguous in both languages, allowing for multiple possible interpretations. Research suggests that one interpretation is often preferred due to lower cognitive demand, though degree of preference varies across languages. Notably, heritage bilinguals may have distinct interpretation preferences in each language, highlighting the complexity of bilingual processing. Sixty Spanish/English heritage bilinguals (Age M = 25.48, SD = 2.65) completed a timed and graded truth-value judgment task in both languages, along with language proficiency tests. We analyzed interpretation ratings, response times, and potential effects of proficiency. Results reveal nearly identical preferred interpretation ratings (Spanish: M = 4.19, SD = 0.56; English: M = 4.14, SD = 0.66) and response times (Spanish: M = 6.97 s, SD = 2.70; English: M = 6.67 s, SD = 1.80) across languages, with one interpretation consistently favored and associated with faster response times. Language proficiency had no significant impact. Our experimental findings offer new insights into heritage bilinguals’ processing of competing linguistic structures and inform models of bilingual syntax and cognitive flexibility. Full article

This study investigates how second language (L2) learners of Spanish identify the regional origin of native Spanish speakers and whether specific phonetic cues predict dialect identification accuracy across proficiency levels. Situated within a growing body of work on sociolinguistic competence, this research addresses the development of learners’ ability to use linguistic forms not only for communication but also for social interpretation. A dialect identification task was administered to 111 American English-speaking learners of Spanish and 19 native Spanish speakers. Participants heard sentence-length stimuli targeting regional phonetic features and selected the speaker’s country of origin. While L2 learners were able to identify regional dialects above chance, accuracy was low and significantly below that of native speakers. Higher-proficiency learners demonstrated improved identification, especially for speakers from Spain and Argentina, and relied more on salient phonetic cues (e.g., [θ], [ʃ]). No significant development was found for identification of Mexican or Puerto Rican varieties. Unlike native speakers, L2 learners did not show sensitivity to broader macrodialect groupings; instead, they frequently defaulted to high-exposure varieties (e.g., Spain, Mexico) regardless of the phonetic cues present. Findings suggest that sociophonetic perception in L2 Spanish develops gradually and unevenly, shaped by cue salience and exposure. Full article

In the Hispanic world, the analysis of discourse particles from a microdiachronic perspective has emerged as a relatively recent area of research that has already demonstrated its efficacy, particularly in the context of Spain. However, in the case of Mexico, this type of study is still marginal. The objective of this paper is to analyze hacer de cuenta in Mexican Spanish during the 20th and 21st centuries to illustrate its processes of grammaticalization and pragmatization. To this end, a comprehensive analysis of the CREA and CORDE corpora, as well as six corpora of Mexican Spanish, was conducted. This methodological approach was proposed for three reasons. Firstly, it facilitated the acquisition of a diverse sample of examples. Secondly, it ensured the inclusion of corpora from different decades. Thirdly, it obtained examples that approximate orality. The findings suggest that during this period, hacer de cuenta was undergoing a process of pragmatization. Consequently, it can be regarded as a discourse particle that primarily encodes an intersubjective value, through which the speaker attempts to share with the interlocutor the way she/he conceptualizes a particular event. Full article

This article presents a comparative analysis of digital manufacturing laboratories (DMLs) in Mexico and Spain. It is argued that DMLs, also known as makerspaces or FabLabs, play a key role in innovation and experimentation, but that their success depends on the relationships they establish with social actors, such as local governments, universities, and firms. Key concepts of the transformative innovation approach such as “protective space” and “embeddedness” are introduced, which allow us to understand how DMLs operate within a complex system. The comparative analysis of a DML in Mexico City (Mexico) and a DML in Valencia (Spain) allows us to identify similarities and differences in their operational contexts. While the Mexican DML faces a lack of government support and dependence on the private sector, the Spanish one benefits from strong institutional support and public policies that facilitate its development. This results in greater stability and capacity for action for the Valencian FabLab VLC compared to the Mexican FabLab Finally, we reflect on how the embeddedness received from different social actors affects the autonomy and transformative capacity of DMLs, suggesting that while both labs have the potential to innovate, their contexts and relationships determine their effectiveness and sustainability in the digital sociotechnical system. Full article

Readability formulas are mathematical functions that assess the ‘difficulty’ level of a given text. They play a crucial role in aligning educational texts with student reading abilities; however, existing models are often not tailored to specific linguistic or regional contexts. This study aims to develop and evaluate two novel readability formulas specifically designed for the Mexican Spanish language, targeting elementary education levels. The formulas were trained on a corpus of 540 texts drawn from official elementary-level textbooks issued by the Mexican public education system. The first formula was constructed using multiple linear regression, emulating the structure of traditional readability models. The second was derived through genetic programming (GP), a machine learning technique that evolves symbolic expressions based on training data. Both approaches prioritize interpretability and use standard textual features, such as sentence length, word length, and lexical and syntactic complexity. Experimental results show that the proposed formulas outperform several well-established Spanish and non-Spanish readability formulas in distinguishing between grade levels, particularly for early and intermediate stages of elementary education. The GP-based formula achieved the highest alignment with target grade levels while maintaining a clear analytical form. These findings underscore the potential of combining machine learning with interpretable modeling techniques and highlight the importance of linguistic and curricular adaptation in readability assessment tools. Full article

Research in Loanword Phonology has extensively examined the adaptation processes of Anglicisms into recipient languages. In the Tijuana–San Diego border region, where English and Spanish have reciprocally existed, Anglicisms exhibit two main phonetic patterns: some structures exhibit Spanish phonetic properties, while others preserve English phonetic features. This study analyzes 131 vowel tokens drawn from spontaneous conversations with 28 bilingual speakers in Tijuana, recruited via the sociolinguistic ‘friend-of-a-friend’ approach. Specifically, it focuses on monosyllabic Anglicisms with monophthongs by examining the F1 and F2 values using Praat. The results were compared with theoretical vowel targets in English and Spanish through Euclidean distance analysis. Dispersion plots generated in R further illustrate the acoustic distribution of vowel realizations. The results reveal that some vowels closely match Spanish targets, others align with English, and several occupy intermediate acoustic spaces. Based on these patterns, the study proposes two phonetically based corpora—Phonetically Adapted Anglicisms (PAA) and Phonetically Non-Adapted Anglicisms (PNAA)—to capture the nature of Anglicisms in this contact setting. This research offers an empirically grounded basis for cross-dialectal comparison and language contact studies from a phonetically based approach. Full article

Background: MSLQ is a self-report instrument that measures motivational orientations and learning strategies of college students and is widely used to measure self-regulated learning. MSLQ has not been translated into Spanish and validated in the Spanish-speaking Latin American population. Objective: The objective of the study is to adapt, validate, and perform a factorial reduction of 9 out of 15 scales of the MSLQ instrument and correlate the scales with the grade point average (GPA) of a sample of health sciences university students. Methods: Nine scales (48 items) of the MSLQ were translated into Spanish and adapted to the Mexican population. Students were invited directly in their classrooms and filled out an electronic questionnaire with personal variables and these nine scales of the MSLQ instrument. We performed exploratory and confirmatory factor analysis (EFA and CFA) and based on the EFA a reduced version of the instrument was proposed. Results: A total of 439 students were included. The CFA showed unacceptable fit parameters with the original scale, therefore an item reduction and rearrangement were performed according to the EFA, and this yielded a reduced version with six scales and 25 items which showed acceptable fit parameters. This new reduced version rearranged the items of the effort regulation scale (ERE) into two different scales newly created in this version: time regulation (TRE) and self-regulation (SRE). The scales that disappeared in the reduced version were: intrinsic goal orientation (IGO), meta-cognitive self-regulation (MSR), and elaboration (ELA). Conclusions: The reduced version showed acceptable fit parameters that included the creation of two new scales (TRE and SRE). In addition, two scales were reduced (TVA and CTH), three scales were modified (MSE, TSE and ERE), two were unmodified (RHE and ORG), and two scales were eliminated (IGO and ELA). Full article

Corn is a globally important crop, requiring extensive soils and intensive practices to meet the growing human and animal consumption demand. However, intensive agriculture has caused soil deterioration and fertility loss. In response, the Mexican government established the National Soil Strategy for Sustainable Agriculture (ENASAS, acronym in Spanish) to ensure food security and maintain soil fertility. This study develops “Soil Quality Indexes” ($SQI$) to monitor soil quality under corn cultivation using four methodologies (additive ($SQ{I}_a$), weighted ($SQ{I}_w$), unified weighted ($SQ{I}_u$), and Nemoro ($SQ{I}_n$)) in the Bajio region of Guanajuato, Mexico. Twenty-four physicochemical indicators were analyzed, with four (CLY, WHC, Na, and C/N) identified as key indicators of soil quality and fertility through principal component analysis. Among these, $SQ{I}_a$ was the most sensitive and efficient (SI = 2.32, ER = 50) in assessing soil quality, showing values from very low to low ($SQ{I}_a=0.13$ and $SQ{I}_a=0.39$ respectively). Aligned with the ENASAS program, $SQ{I}_a$ can help monitor and improve soil quality under corn cultivation, supporting food security through soil conservation. Moreover, $SQ{I}_a$ performed similarly to the globally recognized Soil Management Assessment Framework (SMAF), making it a valuable tool for managing and improving agricultural soil quality under similar conditions in both Mexico and worldwide. Full article