Search Results (239)

This study investigates the complex relationship between the performance of logistics and Environmental, Social, and Governance (ESG) performance, drawing upon the multi-methodological framework of combining econometrics with state-of-the-art machine learning approaches. Employing Instrumental Variable (IV) Panel data regressions, viz., 2SLS and G2SLS, with data from a balanced panel of 163 countries covering the period from 2007 to 2023, the research thoroughly investigates how the performance of the Logistics Performance Index (LPI) is correlated with a variety of ESG indicators. To enrich the analysis, machine learning models—models based upon regression, viz., Random Forest, k-Nearest Neighbors, Support Vector Machines, Boosting Regression, Decision Tree Regression, and Linear Regressions, and clustering, viz., Density-Based, Neighborhood-Based, and Hierarchical clustering, Fuzzy c-Means, Model-Based, and Random Forest—were applied to uncover unknown structures and predict the behavior of LPI. Empirical evidence suggests that higher improvements in the performance of logistics are systematically correlated with nascent developments in all three dimensions of the environment (E), social (S), and governance (G). The evidence from econometrics suggests that higher LPI goes with environmental trade-offs such as higher emissions of greenhouse gases but cleaner air and usage of resources. On the S dimension, better performance in terms of logistics is correlated with better education performance and reducing child labor, but also demonstrates potential problems such as social imbalances. For G, better governance of logistics goes with better governance, voice and public participation, science productivity, and rule of law. Through both regression and cluster methods, each of the respective parts of ESG were analyzed in isolation, allowing us to study in-depth how the infrastructure of logistics is interacting with sustainability research goals. Overall, the study emphasizes that while modernization is facilitated by the performance of the infrastructure of logistics, this must go hand in hand with policy intervention to make it socially inclusive, environmentally friendly, and institutionally robust. Full article

This study examines the impact of vocal fold (VF) lesions located on the superior surface on glottal airflow dynamics and tissue oscillatory behaviors using biomechanical simulations of a two-layered realistic VF model. It is hypothesized that morphological changes in the VFs due to the presence of a lesion cause changes in tissue elasticity and rheological properties, contributing to dysphonia. Previous research has lacked the integration of lesions in computational simulations of anatomically accurate larynx-VF models to explore their effects on phonation and contribution to voice disorders. Addressing the current gap in literature, this paper considers a computational model of a two-layered VF structure incorporating a lesion that represents a hemorrhagic polyp. A three-dimensional, subject-specific, multilayered geometry of VFs is constructed based on STL files derived from a human larynx CT scan, and a fluid–structure interaction (FSI) methodology is employed to simulate the coupling of glottal airflow and VF tissue dynamics. To evaluate the effects of the lesion’s presence, two FSI models, one with a lesion embedded in the cover layer and one without, are simulated and compared. Analysis of airflow dynamics and tissue vibrational patterns between these two models is used to determine the impact of the lesion on the biomechanical characteristics of phonation. The polyp is found to slightly increase airflow resistance through the glottis and disrupt vibratory symmetry by decreasing the vibration frequency of the affected fold, leading to weaker and less rhythmic oscillations. The results also indicate that the lesion increases tissue stress in the affected fold, which agrees with clinical observations. While quantitative ranges depend on lesion size and tissue properties, these consistent and physically meaningful trends highlight the biomechanical mechanisms by which lesions influence phonation. Full article

Through a series of over 100 bilingual interviews with Hispanic San Antonians, the COVID-19 Oral Historias Project documents the Latino/a/e community’s experiences through the pandemic by sharing individual stories, amplifying local voices, and creating compassion in a fragmented time. The present article documents the project itself, contextualizing its creation, detailing its methodology, highlighting the most common themes across interviews, and pointing out its novel contributions. While the interviewees’ experiences are inarguably diverse, narrative threads were found throughout the corpus, united by the duality of the narrators’ experiences; throughout this period, they simultaneously negotiated community norms and official health directives, local and international anxieties, and hopelessness and hope. The project is unique in (1) its language use, privileging minoritized ways of speaking (Spanish and Spanglish); (2) its size, with over 100 interviews; and (3) its clearly delimited scope, with all respondents living in San Antonio. This massive, unified resource creates a public collection of bilingual stories, highlighting non-hegemonic voices that are of value to the community itself, as well as to the recorded history of the pandemic, filling in historical gaps and providing real, lived accounts of this period that might otherwise be lost over time. Full article

Music performance anxiety (MPA) can be examined within the framework of music performance ecosystems, wherein performers’ musical self-concept is shaped through complex social and cultural interactions. This research aims to identify ecosystemic interactions contributing to the emergence of MPA, and to promote a shift in its understanding, from a focus on individual symptomatology to the recognition of collective influences. A qualitative analysis was conducted using biographical-narrative interviews with 11 established musical performers (six female, five male), aged 23 to 62, representing a range of instruments, including violin, viola, cello, flute, piano, harp, and voice. Their experience encompasses solo, chamber, and orchestral performance, as well as pedagogical work, all rooted in the traditional educational framework of Western classical music. The analysis, based on the grounded theory methodology, highlights four key dimensions: the demanding stage; the development of psychological resilience in performers; the musical self-concept as a reflection of the performer’s experience; and performance as a process of transformation. The findings suggest that an ecosystemic perspective may support preventive interventions for MPA, particularly by reframing the traditional virtuoso performance model. Often internalized early in music education, this prestigious ideal continues to shape professional careers, placing heavy self-reflective demands on performers. To support healthier artistic development, music performance ecosystems can bridge the gap between skill acquisition and performer attunement. This is not merely a divide between learning and performing, but a structural loop in which training-oriented processes—such as analysis, self-criticism, and control—may hinder stage performance if not transformed into holistic, embodied execution. Full article

Vuoiŋŋalaš Eanadat/Spirit Land is a transdisciplinary practice-based artistic research project around Sámi cosmology and the act of giving voice to indigenous reclamation of sacred spaces. The Sámi are the indigenous people of Sweden, Norway, Finland and Russia. Vuoiŋŋalaš Eanadat/Spirit Land is a hybrid fusion between textile art, music, poetry and theology, aiming at taking part in the decolonizing processes of indigenous people’s lands and cultures in Scandinavia. Practice-based artistic research is characterized by the fact that the research process proceeds by and through the act of artistic making. The artistic process is the core, and research methodologies and theoretical perspectives are built around it, functioning as a supporting framework. Reflective writing is used as means to get access to transpersonal depths of the creative process. Reflections upon different aspects of the artwork are developed and, simultaneously, on how it can be a seen as a vehicle for indigenous voices in order to be heard in sacred spaces of our time. Vuoiŋŋalaš Eanadat/Spirit Land is an artistic performance that functions as a ceremonial act of giving voice, a liberation from the silence of the colonized past. Full article

This article reassesses Ezra Pound’s Cathay as translation from Chinese Tang poetry rather than autonomous modernist verse. Building on Pound’s own poetics and compact coordinates from Chinese lyric theory, we argue that Cathay maintains translational fidelity by preserving and sharpening images while accepting losses in prosodic form and thinning some culture-specific encyclopaedias. Methodologically, we conduct a qualitative, contrastive microanalysis of two Li Bai poems “送友人” (Taking Leave of a Friend) and “长干行” (The River-Merchant’s Wife: A Letter), aligning the Chinese text, a neutral interlinear gloss, and Pound’s English version. A coding scheme tracks image handling, cultural markers, prosody, and the balance of phanopoeia, melopoeia, and logopoeia alongside domestication/foreignization choices. Findings show a stable hierarchy—image (phanopoeia)–stance (logopoeia)–sound/form (melopoeia)—that aligns with Chinese esthetic dynamics of yi/xiang (idea/form) and qing/jing (emotion/scene). Pound’s practice preserves correlative imagery (mountains/river/sunset; moss/leaves/butterflies) and voice, while paratextual titling, address terms, folklore allusions, toponyms, and a fifth-month calendar line reveal domestications, distortions, or omissions traceable to mediation via Fenollosa’s notes. We propose mechanism-sensitive criteria for evaluating distant-pair lyric translation: not formal replication, but reconstruction of the poem’s image–scene–emotion economy. On that basis, Cathay functions as translation—at justified costs. Rather than resolving the long-standing debate on Cathay, we offer a mechanism-sensitive account of how, in two central Li Bai poems, Pound’s image-centred poetics yields a limited but defensible form of translational fidelity within a relay-translation setting. Full article

Background: Age-related hearing loss (ARHL) is associated with decreased communication, reduced social engagement, cognitive decline and an increased risk of dementia globally. Although increasing studies report the benefits of combing auditory and cognitive training for older adults with ARHL, more evidence is needed to examine its effects. Moreover, existing training programs have been developed with minimal end-user involvement leading to low adherence rates. This study aimed to investigate the role of co-design in the development of an auditory–cognitive training system for older adults with ARHL. Methods: A co-design methodology was employed. Digital recordings of the co-design workshops were transcribed verbatim. An established reflexive thematic analysis methodology was used. Results: Fifteen older adults with ARHL, referred to as “co-researchers”, participated in three co-design workshops until data saturation was achieved. Consultations were held with two key service providers. Three key themes emerged: (1) older adults with ARHL prefer a user-friendly auditory–cognitive training system; (2) clear, localized and colloquial instructions for the training tasks are necessary; and (3) diversified, tailor-made and dual-task training tasks, performed in an interactive and game-like mode, can motivate and sustain usage of the training system. As a result, a prototype of a web-based, gamified, and adaptive auditory–cognitive dual-task training system was co-designed. Conclusions: Our findings affirmed the importance of genuinely listening to the voices of end-users and creating a system that is responsive to their needs and preferences. Future study is recommended to examine the effects of this system on older adults with ARHL. Full article

Coming from the “end of the world”, from the south of the planet, Pope Francis first challenged global consciousness with his Encyclical Letter Laudato Si’: On Care for Our Common Home, then turned the attention of the Church and people of good will to the Amazon region. The convening of the Synod of Bishops for the Pan-Amazon Region was an initiative deeply attuned to the climate crisis, one of the most pressing challenges of our time. Faithful to the Second Vatican Council and the spirituality of liberation, Francis invites the whole world to admire and recognize the Amazon region as a sacred mystery as well as to heed the voices of its poor communities, precisely those whose resistance has preserved the rainforest. Using an exploratory bibliographical methodology, this article aims to contribute to the reflection on how 21st-century Liberation Theology might address challenges, with an emphasis on the ecological crisis central to Pope Francis’s magisterium, particularly articulated in his Post-Synodal Apostolic Exhortation Querida Amazonia: To the People of God and to All Persons of Good Will. As a result, we tried to demonstrate that Francis, in Querida Amazonia, proposes that a Church with an Amazonian face, located in the heart of Latin America, without forgetting the feminine protagonism, should be an inspiration for integral conversion on the planet. Full article

This scoping review systematically maps the rapidly evolving application of Artificial Intelligence (AI) in Autism Spectrum Disorder (ASD) diagnostics, specifically focusing on computational behavioral phenotyping. Recognizing that observable traits like speech and movement are critical for early, timely intervention, the study synthesizes AI’s use across eight key behavioral modalities. These include voice biomarkers, conversational dynamics, linguistic analysis, movement analysis, activity recognition, facial gestures, visual attention, and multimodal approaches. The review analyzed 158 studies published between 2015 and 2025, revealing that modern Machine Learning and Deep Learning techniques demonstrate highly promising diagnostic performance in controlled environments, with reported accuracies of up to 99%. Despite this significant capability, the review identifies critical challenges that impede clinical implementation and generalizability. These persistent limitations include pervasive issues with dataset heterogeneity, gender bias in samples, and small overall sample sizes. By detailing the current landscape of observable data types, computational methodologies, and available datasets, this work establishes a comprehensive overview of AI’s current strengths and fundamental weaknesses in ASD diagnosis. The article concludes by providing actionable recommendations aimed at guiding future research toward developing diagnostic solutions that are more inclusive, generalizable, and ultimately applicable in clinical settings. Full article

This paper introduces a comprehensive approach to building natural-sounding Urdu Text-to-Speech (TTS) and voice cloning systems, addressing the lack of computational resources for Urdu. We developed a large-scale dataset of over 100 h of Urdu speech, carefully cleaned and phonetically aligned through an automated transcription pipeline to preserve linguistic accuracy. The dataset was then used to fine-tune Tacotron2, a neural network model originally trained for English, with modifications tailored to Urdu’s phonological and morphological features. To further enhance naturalness, we integrated voice cloning techniques that capture regional accents and produce personalized speech outputs. Model performance was evaluated through mean opinion score (MOS), word error rate (WER), and speaker similarity, showing substantial improvements compared to previous Urdu systems. The results demonstrate clear progress toward natural and intelligible Urdu speech synthesis, while also revealing challenges such as handling dialectal variation and preventing model overfitting. This work contributes an essential resource and methodology for advancing Urdu natural language processing (NLP), with promising applications in education, accessibility, entertainment, and assistive technologies. Full article

Voice assistants have become increasingly common in everyday devices such as smartphones and smart speakers. Improving their user experience (UX) is crucial to ensuring usability, acceptance, and long-term effectiveness. Heuristic evaluation is a widely used method for UX evaluation due to its efficiency in detecting problems quickly and at low cost. Nonetheless, existing usability/UX heuristics were not designed to address the specific challenges of voice-based interaction, which relies on spoken dialog and auditory feedback. To overcome this limitation, we developed HEUXIVA, a set of 13 heuristics specifically developed for evaluating UX with voice assistants. The proposal was created through a structured methodology and refined in two iterations. We validated HEUXIVA through heuristic evaluations, expert judgment, and user testing. The results offer preliminary but consistent evidence supporting the effectiveness of HEUXIVA in identifying UX issues specific to the voice assistant “Google Nest Mini”. Experts described the heuristics as clear, practical, and easy to use. They also highlighted their usefulness in evaluating interaction features and supporting the overall UX evaluation process. HEUXIVA therefore provides designers, researchers, and practitioners with a specialized tool to improve the quality of voice assistant interfaces and improve user satisfaction. Full article

Aim: The aim of this study was to develop and test a surface electromyography (sEMG) assessment protocol to characterise the activity of the extrinsic laryngeal muscles (suprahyoid and infrahyoid) during phonatory tasks and vocal techniques. Methodology: The protocol of assessment was based on electromyographic assessment guidelines and on clinical voice evaluation needs and was tested in six healthy adults with no vocal disorders. Surface electromyographic activity of suprahyoid and infrahyoid muscles was acquired during different reference tasks (rest, reading, maximum contractions) and six vocal tasks, including nasal sounds, fricatives, and semi-occluded vocal tract exercises. A laryngeal accelerometer was used for detecting the beginning and end of each exercise. The average activity during each task was normalised by the signal obtained in the incomplete swallowing task for the SHM and by the sniff technique for the IHM. Results: The range of activation values varied across tasks, with higher percentages observed in plosive production and in the “spaghetti” technique, while nasal and fricative sounds tended to show lower activation values within the group. A consistent pattern of simultaneous activation of suprahyoid and infrahyoid muscles was observed during phonation. Conclusions: The protocol proved potential for clinical application in speech–language pathology as it enabled the characterisation of muscle activity in determinant muscles for vocal function. Larger samples and further validation of the time-marking system are needed. This study provides a foundation for integrating sEMG measures into functional voice assessment. Full article

This paper presents the Women’s Wise Walkshops (WWW) project, a participatory feminist methodology for urban co-design implemented in Ferrara, Italy. The research explores how women’s situated knowledge and lived experiences can inform inclusive urban planning through collaborative urban traversals and participatory design processes. Drawing on feminist epistemologies and combining elements of flâneuserie and Situationist dérive, the WWW methodology employs a seven-phase approach including semi-structured interviews, focus groups, urban walkshops, and collective mapping exercises. The study involved approximately 110 women across two distinct neighborhoods—Arianuova-Giardino and Krasnodar—representing diverse socio-demographic backgrounds. Through a thematic analysis of interviews, visual documentation, and post-walkshop discussions, six key thematic clusters emerged: safety, public space, mobility systems, community spaces and associations, public services for citizens, and participatory processes. The findings reveal that women’s perspectives from marginalized positions provide critical insights into urban inequalities and offer transformative visions for more inclusive cities. The research shows that structured participatory processes not only generate valuable urban policy recommendations but also foster community cohesion, democratic engagement, and spatial justice. The WWW methodology represents a significant contribution to feminist urban studies and participatory planning, offering a replicable framework for integrating women’s voices into urban governance and design processes. Full article

This study explores Hong Kong residents’ perceptions of their city’s smart city transformation, set against a backdrop of political and economic changes. It investigates residents’ awareness and support for Hong Kong’s development as a smart city and their familiarity with the Smart City Blueprint. Despite the global emphasis on smart city initiatives, there is a significant gap in understanding residents’ perceptions, with the existing literature often focusing on technological and policy aspects while neglecting citizen voices. Employing a mixed-methods research design, the study integrates quantitative survey data (N = 808) with qualitative interviews (N = 25) and focus group discussions (4 groups, N = 43) to capture diverse perspectives. The findings reveal a generally low level of understanding of the Smart City Blueprint among residents, alongside a positive attitude towards its key dimensions like mobility, living, and the environment. Older citizens, those with lower educational attainment, and individuals from mainland China showed greater understanding and support. Interviews highlighted concerns about coordination, bureaucratic processes, data privacy, and public involvement. Focus group discussions revealed varied viewpoints, with some participants drawing comparisons to smart city developments in mainland China and expressing privacy concerns. The study underscores the importance of aligning smart city initiatives with residents’ needs and preferences through inclusive communication strategies and addressing concerns about data privacy and job displacement. Methodological triangulation enhances the validity and reliability of the research, revealing complex patterns and contradictions. Full article

Background: There is an emerging need for new scalable behavioral assays, i.e., assays that are feasible to administer from the comfort of the person’s home, with ease and at higher frequency than clinical visits or visits to laboratory settings can afford us today. This need poses several challenges which we address in this work along with scalable solutions for behavioral data acquisition and analyses aimed at diversifying various populations under study here and to encourage citizen-driven participatory models of research and clinical practices. Methods: Our methods are centered on the biophysical fluctuations unique to the person and on the characterization of behavioral states using standardized biorhythmic time series data (from kinematic, electrocardiographic, voice, and video-based tools) in naturalistic settings, outside a laboratory environment. The methods are illustrated with three representative studies (58 participants, 8–70 years old, 34 males, 24 females). Data is presented across the nervous systems under a proposed functional taxonomy that permits data organization according to nervous systems’ maturation and decline levels. These methods can be applied to various research programs ranging from clinical trials at home, to remote pedagogical settings. They are aimed at creating new standardized biometric scales to screen and diagnose neurological disorders across the human lifespan. Results: Using this remote data collection system under our new unifying statistical platform for individualized behavioral analysis, we characterize the digital ranges of biophysical signals of neurotypical participants and report departure from normative ranges in neurodevelopmental and neurodegenerative disorders. Each study provides parameter spaces with self-emerging clusters whereby data points corresponding to a cluster are probability distribution parameters automatically classifying participants into different continuous Gamma probability distribution families. Non-parametric analysis reveals significant differences in distributions’ shape and scale (p < 0.01). Data reduction is realizable from full probability distribution families to a single parameter, the Gamma scale, amenable to represent each participant within each subclass, and each cluster of similar participants within each cohort. We report on data integration from stochastic analyses that serve to differentiate participants and propose new ways to highly scale our research, education, and clinical practices. Conclusions: This work highlights important methodological and analytical techniques for developing personalized and scalable biometrics across various populations outside a laboratory setting. Full article