Aid Applications Research Articles

Auditory attention decoding based on neural-network for binaural beamforming applications

Individuals have the remarkable ability to differentiate between speakers and focus on a particular speaker, even amidst complex acoustic environments with multiple speakers, background noise and reverberations. This selective auditory attention, often illustrated by the cocktail party problem, has been extensively researched. With a considerable portion of the population experiencing hearing impairment and requiring hearing aids, there arises a necessity to separate and decode auditory signals artificially. The linearly constrained minimum variance (LCMV) beamforming design criterion has proven effective in isolating the desired source by steering a beam toward the target speaker while creating a null toward the interfering source. Preserving the binaural cues, e.g., interaural time difference (ITFD) and interaural level difference (ILD), is a prerequisite for producing a beamformer output suitable for hearing aid applications. For that, the binaural linearly constrained minimum variance (BLCMV) beamformer generates two outputs that satisfy the standard LCMV criterion while preserving the binaural cues between the left-ear and right-ear outputs. Identifying the attended speaker from the separated speakers and distinguishing it from the unattended speaker poses a fundamental challenge in the beamformer design. Several studies showed the ability to encode essential features of the attended speech from the cortex neural response, as recorded by the electroencephalography (EEG) signals. This led to the development of several algorithms addressing the auditory attention decoder (AAD) task. This paper investigates two neural network architectures for the AAD task. The first architecture leverages transfer learning. It is evaluated using both same-trial and cross-trial experiments. The second architecture employs an attention mechanism between the speech signal represented in the short time Fourier transform (STFT) domain and a multi-band filtered EEG signal. With the goal of alleviating the problem of same-trial overfitting, this architecture employs a new data organization structure that presents the neural network (NN) with a single speaker’s speech and the corresponding EEG signal as inputs. Finally, posterior probability post-processing is applied to the outputs of the NN to improve detection accuracy. The experimental study validates the applicability of the proposed scheme as an AAD method. Strategies for incorporating the AAD into BLCMV beamformer are discussed.

Male-female young learners' perspective on the use of crossword puzzle aids to enrich their vocabulary

Vocabulary is very essential in communication, but the fact indicates that lack of vocabulary still hampers the effective communication. This paper investigates the perspective of young female and male learners on the application of Crossword puzzle aids to enrich their vocabulary. The goal of this study is to find out male and female young learners’ perspectives on the use of crossword puzzle aids to enrich their vocabulary. The research design of this current study uses the type of case study so that twenty-one students from grade seven in a Junior High School in Ciamis were involved. The data come from a questionnaire which deals with the perspective of young female and male learners on the application of Crossword puzzle aids to increase their vocabulary. The close-ended questionnaire data are then analyzed and proceeded. The result shows that the young female and male learners perceive the application of Crossword puzzle as the aids to enrich their vocabulary. In learning, vocabulary can enrich their vocabulary with different skills based on gender because gender differences can influence young and female learners to increase their vocabulary skills. Besides that, Crossword puzzle aids are interesting, gives many opportunities, and helps male and female learners to receive and understand the vocabulary more easily. Further, using crossword puzzles aids learning vocabulary and can increase the achievement of male and female young learners. Also, it makes change towards the situations such as playing games when learning vocabulary process.

A Methodology for Rapid Deployment of Diagnostic Applications for Human Gait & Posture Analysis and Exoskeleton Configurations, Combining AI with a Biomimetic Rig

Research has shown that certain simple, yet valuable gait and posture diagnostic tests can be conducted without the involvement of human experts using optical detection software employing Artificial Intelligence (AI), either on par with some physicians or, in some cases, even better in terms of availability, productivity, ease, and cost. The purpose of the current paper is to propose a methodology that uses dedicated AI models for partial body frames instead of full-body pose trackers. To achieve this, we obtain training dataset (photos/ videos) using a biomimetic rig instead of humans. In this research, we also study existing applications using already available AI pose trackers, their methodology, limitations regarding partial body views, and limitations in detecting mechanical devices and systems. Finally, to support our study, we present stand2squatAI_biorig software as an example of an AI-automated, diagnostic, real-time test that does not require physicians to complete the examination. We developed this software as a proof-of-concept to illustrate the proposed methodology and confirm our findings. Software applications developed in this manner can be used to study and diagnose various human conditions. The value of the proposed approach, which includes a biomimetic rig, is that it increases precision, reduces costs, and increases human safety; for example, during the application of mechanical aids while ensuring personal data privacy and overcoming ethical issues. Received: 16 June 2024 | Revised: 20 September 2024 | Accepted: 16 October 2024 Conflicts of Interest The authors declare that they have no conflicts of interest to this work. Data Availability Statement The Teachable machine AI model used in this study is openly available in figshare at http://doi.org/10.6084/m9.figshare.27894876. Author Contribution Statement Christos Kampouris: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Resources, Data curation, Writing – original draft, Writing – review & editing, Visualization, Project administration, Funding acquisition. Philip Azariadis: Supervision.

A Methodology for Rapid Deployment of Diagnostic Applications for Human Gait & Posture Analysis and Exoskeleton Configurations, Combining AI with a Biomimetic Rig

Research has shown that certain simple, yet valuable gait and posture diagnostic tests can be conducted without the involvement of human experts using optical detection software employing Artificial Intelligence (AI), either on par with some physicians or, in some cases, even better in terms of availability, productivity, ease, and cost. The purpose of the current paper is to propose a methodology that uses dedicated AI models for partial body frames instead of full-body pose trackers. To achieve this, we obtain training dataset (photos/ videos) using a biomimetic rig instead of humans. In this research, we also study existing applications using already available AI pose trackers, their methodology, limitations regarding partial body views, and limitations in detecting mechanical devices and systems. Finally, to support our study, we present stand2squatAI_biorig software as an example of an AI-automated, diagnostic, real-time test that does not require physicians to complete the examination. We developed this software as a proof-of-concept to illustrate the proposed methodology and confirm our findings. Software applications developed in this manner can be used to study and diagnose various human conditions. The value of the proposed approach, which includes a biomimetic rig, is that it increases precision, reduces costs, and increases human safety; for example, during the application of mechanical aids while ensuring personal data privacy and overcoming ethical issues. Received: 16 June 2024 | Revised: 20 September 2024 | Accepted: 16 October 2024 Conflicts of Interest The authors declare that they have no conflicts of interest to this work. Data Availability Statement The Teachable machine AI model used in this study is openly available in figshare at http://doi.org/10.6084/m9.figshare.27894876. Author Contribution Statement Christos Kampouris: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Resources, Data curation, Writing – original draft, Writing – review & editing, Visualization, Project administration, Funding acquisition. Philip Azariadis: Supervision.

Exploring electrochemical impedance spectroscopy for the early diagnosis of Mycobacterium tuberculosis using CFP10:ESAT6 protein detection

Tuberculosis (TB) was, until SARS-CoV-2 pandemic, the leading cause of death by a single infectious agent contaminating over 10.6 million people with 1.6 million deaths in 2021 worldwide. Herein, we present a proof-of-principle strategy for detecting the recombinant protein CFP10:ESAT6 using an impedimetric immunosensor, which could aid in the diagnosis of tuberculosis. The immunosensor was developed using indium tin oxide electrodes modified by 3-aminopropyltrimethoxysilane monolayer to covalently immobilize anti-CFP10 antibodies. The protein interaction with the antibody recognition platform was directly monitored and measured by cyclic voltammetry and electrochemical impedance spectroscopy, respectively. After the analytical features optimization, a Langmuir isotherm response from 0.5 ng mL-1 to 50 ng mL-1 of pCFP10:ESAT6, limit of detection of 4.80 ng mL-1 and limit of quantification of 15.97 ng mL-1 were achieved, in a 4-hour assay time. Selectivity tests conducted in the presence of DENV NS1 and SARS-CoV-2 Spike proteins at a concentration of 20 ng mL-1, which is one-tenth of the concentration used to optimize pCFP10, indicate that the immunosensor is selective for pCFP10:ESAT6. Additionally, repeatability and reproducibility tests confirm that the immunosensor is suitable, accurate, and selective for detecting the CFP10:ESAT6 protein. The small sample volume required, and short testing time underscore the remarkable capabilities of this immunosensor and its potential for point-of-care screening and diagnostic aid applications.

The right of persons with disabilities to free legal aid as an element of access to justice

The article analyzes international and national standards for ensuring the right of persons with disabilities to free legal aid. The study clarifies the essence of the right of access to court under the Convention for the Protection of Human Rights and Fundamental Freedoms of 1950, the UN Convention on the Rights of Persons with Disabilities of 2006, and the case law of the European Court of Human Rights. Special attention is paid to the development of the system of free legal aid in Ukraine. In analyzing the provisions of international treaties that are part of national legislation, the concept and meaning of the principles of equality and non-discrimination were investigated, taking into account their role in ensuring the rights of persons with disabilities. The author examines the right of access to court in the light of Article 6 of the European Convention on Human Rights. The author analyzes its complex structure and comprehensive nature due to a broad interpretation of the concept of accessibility, which includes, in addition to legal regulation, effective mechanisms for practical implementation of the right under consideration. One of these effective mechanisms is the system of free legal aid. Although the obligation to establish it does not directly follow from Article 6 of the Convention, more than forty years of ECtHR case law has confirmed that a person’s inability to use the relevant types of services free of charge constitutes a violation of his or her right of access to court. The author analyzes the regulatory framework for the right to free primary and secondary legal aid in Ukrainian legislation. It is found that persons with disabilities have access to primary legal aid services free of charge on a general basis. In contrast, an application for secondary legal aid may be granted only if certain grounds are met. At the same time, the legislator uses a financial criterion - the applicant’s income - to decide whether a person with a disability has the relevant right. The author analyzes the statistical information of free legal aid centers for 2023, which shows the importance of the system for persons with disabilities, who accounted for 12% of the total number of applicants in 2023. The use of the services of state lawyers in civil, administrative, and criminal proceedings demonstrates the significant role of the free legal aid system in the effective protection of the rights and interests of persons with disabilities, which has become an integral aspect of the right to access to justice.

A Step Forward in Long COVID Research: Validating the Post-COVID Cognitive Impairment Scale.

Long COVID, or post-acute sequelae of SARS-CoV-2 infection, includes a variety of enduring symptoms that endure beyond the acute phase of the illness, impacting multiple facets of patients' psychological and physical health. The persistent symptoms encompass fatigue, breathing difficulties, musculoskeletal pain, and cognitive impairments, which can significantly affect daily functioning and overall quality of life. The objective of this study was to create and validate the accuracy of the Post-COVID Cognitive Impairment Scale, which is used to evaluate cognitive impairments resulting from a COVID-19 infection. This study was conducted in Iran between January and September 2023. It consisted of three phases: developing the scale, evaluating its content validity with experts, and validating its structure with 454 participants using exploratory and confirmatory factor analysis. The exploratory factor analysis revealed two variables, namely memory and attention, which accounted for 40.38% of the variation. Confirmatory factor analysis verified the model's fit, with indices indicating satisfactory alignment: CMIN/DF = 2.80, RMSEA = 0.06, SRMR = 0.05, CFI = 0.93, and TLI = 0.92. The factor loadings were statistically significant (p < 0.001), and Cronbach's Alpha values indicated strong internal consistency (working memory = 0.81, attention = 0.80). These results affirm the Post-COVID Cognitive Impairment Scale is a valid and reliable instrument for evaluating cognitive deficiencies in individuals with long COVID. Its application in clinical and research environments aids in the prompt detection and tracking of the treatment of such impairments.

AI-Driven Transformations in Higher Education: A Citation and Co-citation Analysis

Integrating artificial intelligence (AI) in the educational field can revolutionize teaching and learning outcomes, increase research capacity, and expedite administrative processes. The application of AI-powered virtual learning aids, customized learning platforms, and intelligent educational platforms, can boost the engagement of students, offer real-time feedback and support, and aid customized learning. Additionally, AI-based administrative systems may automate repetitive processes like financial aid processing, enrolment, and admissions, freeing up important resources for more strategic endeavors. Thus, this study aims to synthesize the literature exploring AI’s impact on higher education through citation and co-citation analysis. Data from the Scopus database from 2015 to 2024 yielded 1140 papers. The data was analyzed using Biblioshiny and Vosviwer software to determine the publishing pattern, the most cited papers, the most prolific writers, sources, nations, and the network of co-citations between authors and references. The findings reveal a sharp and rapid growth (79.24%) in this industry, suggesting a significant spike in interest. In terms of overall citations, the UK became one of the top countries (1689). The author "Tan S" obtained the most citations (1869) with 10 publications, whereas "Kerr S" and "Poenici Sad" produced just one article and had the highest average citation (588). "Research And Practice in Technology-Enhanced Learning" and "Journal of Applied Learning and Teaching" were the most influential journals in terms of average and total citations, respectively. The uniqueness of the study is that it assesses the literature on AI's impacts in the fields of business and management as well as social science using citation and co-citation analysis. The outcomes of the study will have substantial implications that can help professionals, researchers, and decision-makers create policies.

Financial Aid as Whiteness as Property: Implications for Research and Practice

ABSTRACT In this article, I demonstrate how financial aid is a valued property of whiteness. Utilizing critical race theory, critical race policy analysis, and whiteness as property, I examine how financial aid has historically and continues to be valued and protected as a benefit for white people. I apply characteristics of property expectations and the function of exclusion to the history of financial aid and contemporary federal student aid processes to demonstrate how federal policy laid the groundwork for a financial aid process that continues to impede People of Color. I rely upon the examples of the GI Bill, aid applications, income verification, and satisfactory academic progress policies to illustrate where and how racist inequities exist within the financial aid process. I conclude the article with implications for applying a critical race perspective to research, policy, and practice with the goal of recognizing how racism influences financial aid administration.

Silk fibroin aerogels with AIE-featured berberine and MXene for rapid hemostasis and efficient wound healing

Rapid hemostasis and wound healing are crucial in emergency trauma situations for saving patients' lives. Traditional hemostatic materials often have drawbacks such as slow hemostasis and susceptibility to post-hemostasis bacterial infections. Therefore, there is an urgent need for advanced wound dressing materials that can provide both rapid hemostasis and antimicrobial properties. In this study, we designed and fabricated a biocompatible hemostatic silk fibroin (SF) aerogel loaded with aggregation-induced emission (AIE)-featured berberine (BBr) and Ti3C2Tx MXene. The resulting SFMB aerogel demonstrates robust mechanical properties and a porous structure that enables quick hemostasis. This aerogel exhibits photodynamic and photothermal responses for antimicrobial activity, releases BBr upon light exposure to enhance bacterial-killing efficiency (99.33 % in vitro and 99.09 % in vivo), and effectively promotes the healing of infected wounds in vivo through combined photothermal/photodynamic antibacterial and anti-inflammatory mechanisms. Furthermore, the aerogel shows high hemocompatibility and cytocompatibility, supporting its potential biomedical applications. Overall, the synthesized SFMB aerogel holds promise for treating bacteria-infected wounds and for use in first aid applications in clinical settings.

Brain-computer interface applications in the aging population with Alzheimers and Parkinsons disease

Abstract. The rapidly aging population faces increasing prevalence of neurodegenerative conditions like Alzheimer's Disease (AD) and Parkinson's Disease (PD), which significantly impair cognitive and motor functions. There is an urgent need for increased research, awareness, and development of effective treatments to mitigate their impact on the affected individuals and their families. This paper delves into the history, mechanisms, and applications of brain-computer interfaces (BCIs) as innovative solutions to mitigate these impacts. BCIs enable direct brain-to-device communication, circumventing conventional neuromuscular routes. We highlight how neurofeedback and neuroplasticity facilitated by BCIs not only restore motor skills and cognitive functions but also enhance the overall quality of life for sufferers. Through applications in cognitive training, motor assistance, and advanced communication aids, BCIs present a significant promise despite the ethical and practical challenges they pose. The continual advancement of this technology promises to a future when its incorporation into treatment plans will be widely used and provide significant advantages for those with PD and AD.

Polarization-selective metamaterial absorber using tailored Y-shaped SRR for UWB device and Doppler navigation aids applications

In this paper, we present an unprecedented metamaterial absorber design exhibiting exceptional characteristics in electromagnetic wave absorption. The proposed bent Y-shaped structure, fabricated on an FR-4 substrate with copper patches, showcases remarkable performance across a diverse frequency spectrum. Through exhaustive simulations in CST, this design manifests eight distinct resonant frequencies, achieving absorption rates exceeding 90 % at each resonance. The resonances, strategically spanning from L-band (3.728 GHz) through S-band, C-band, X-band, Ku-band, and K-band up to 22.664 GHz, signify unparalleled versatility and efficacy in mitigating electromagnetic radiation. It investigates the equivalent circuit parameters of a proposed metamaterial absorber design, focusing on inductance (L), capacitance (C), and resistance (R). This paper investigates the applications of UWB devices at 3.728 GHz and Doppler navigation aids at the 13.4 GHz frequency as regulated by the Federal Communications Commission. It includes a discussion on near-zero refractive Index Metamaterials (NZRIM), highlighting their potential utilization in achieving extraordinary control over wave behaviour. Notably, the absorber's inherent polarization insensitivity fortifies its adaptability in various applications. Additionally, the metamaterial exhibits near-zero or negative permittivity, altering electric response, while simultaneously demonstrating permeability absolute zero throughout all frequency bands sparking new avenues for exploration and challenging conventional electromagnetic theories.

The Efficacy of Nutritional Strategies and Ergogenic Aids on Acute Responses and Chronic Adaptations to Exertional-Heat Exposure: A Narrative Review.

Global warming is attributed to an increased frequency of high ambient temperatures and humidity, elevating the prevalence of high-temperature-related illness and death. Evidence over recent decades highlights that tailored nutritional strategies are essential to improve performance and optimise health during acute and chronic exertional-heat exposure. Therefore, the purpose of this review is to discuss the efficacy of various nutritional strategies and ergogenic aids on responses during and following acute and chronic exertional-heat exposure. An outline is provided surrounding the application of various nutritional practices (e.g., carbohydrate loading, fluid replacement strategies) and ergogenic aids (e.g., caffeine, creatine, nitrate, tyrosine) to improve physiological, cognitive, and recovery responses to acute exertional-heat exposure. Additionally, this review will evaluate if the magnitude and time course of chronic heat adaptations can be modified with tailored supplementation practices. This review highlights that there is robust evidence for the use of certain ergogenic aids and nutritional strategies to improve performance and health outcomes during exertional-heat exposure. However, equivocal findings across studies appear dependent on factors such as exercise testing modality, duration, and intensity; outcome measures in relation to the ergogenic aid's proposed mechanism of action; and sex-specific responses. Collectively, this review provides evidence-based recommendations and highlights areas for future research that have the potential to assist with prescribing specific nutritional strategies and ergogenic aids in populations frequently exercising in the heat. Future research is required to establish dose-, sex-, and exercise-modality-specific responses to various nutritional practices and ergogenic aid use for acute and chronic exertional-heat exposure.

Retraction notice: Machine learning improvements to compressive sensing for speech enhancement in hearing aid applications

Retraction notice: Machine learning improvements to compressive sensing for speech enhancement in hearing aid applications

Elastomeric Toothbrushing Aid to Improve the Toothbrushing Skills of Children with Disabilities

Background: In 12 years old children with disabilities, 30.2% had caries and in 15 years old children it increased by 2.3%.Limited handgrip motor skills in children with disabilities is 0.09% 1.5-3% have such limitations which the incidence is related to socioeconomic status. Therefore, 80-90% of children require assistive devices to facilitate their handgrip motor activities. Objective: To produce a feasible and effective elastomeric tooth brushing aid to improve tooth brushing skills and reduce debris index in children with disabilities. Methods: The study used quasi experimental (pre-post with control group design). The sampling technique was purposive sampling, consisting of 11 children in the intervention group with the application of elastomeric tooth brushing aids and 11 children in the control group with the application of conventional adult toothbrushes, with the length of treatment given 10 days. By making elastomeric tooth brushing aids manually combining elastomeric materials on conventional toothbrush handles. Results: The results of expert validation of elastomeric tooth brushing aids showed a p-value of 0.104 which means that this model is feasible as an effort to improve tooth brushing skills in children with disabilities. This model is effective in improving the teeth brushing skills of children with disabilities (p = 0.041) and reducing the debris index score of children with disabilities (p = 0.000) and reducing the debris index score of children with disabilities (p = 0.000). Conclusion: Elastomeric tooth brushing aids are feasible and effective in improving tooth brushing skills and reducing the debris index of children with disabilities.

A recursive framework of vehicle trajectory planning at mixed‐traffic signalized intersections

AbstractThis study aims to introduce a new strategy for anticipating the behaviour of human‐driven vehicles (HDVs) and designing trajectories for connected and automated vehicles (CAVs) at signalized intersections under mixed traffic scenarios. To tackle the challenge of unreliable HDV trajectory predictions stemming from driving unpredictability, a recursive framework is developed. This framework integrates real‐time tracking data from both traffic detectors and CAVs, continuously updating HDV predictions. The proposed approach employs the updated predictions to formulate optimal control problems recursively to optimize or adjust CAV trajectories, enhancing travel and energy efficiency. Besides, the recomputing of CAV trajectories will only be conducted when the variation in predictions rises to a certain threshold, balancing efficiency and computing consumption, inspired and modified based on MPC methods. The application of the Pontryagin maximum principle aids in finding solutions efficiently by transforming necessary conditions into a system of equations and consolidating elementary unconstrained and constrained arcs. Numerical simulations were carried out to evaluate the performance of the proposed recursive framework, revealing its superiority over the one‐time approach, particularly in isolated intersections with high traffic demands. Additionally, the recursive framework exhibited more robust and effective enhancements throughout the road network.

Are nursing students ready to respond to disasters? A study on self-efficacy of nursing students to apply psychological first aid

BackgroundPsychological first aid (PFA) is an effective initial response to disasters. Nursing students are an important human resource for supporting health services during and after disasters. Improving nursing students' PFA application competencies is necessary for both themselves and aid providers. AimThis study aimed to determine sernior nursing students' self-efficacy in psychological first aid application in disaster situations. DesignThis was a descriptive cross-sectional study. Setting and participantsA total of 536 senior nursing students who had received undergraduate nursing education in Turkey participated in this study. MethodsData were collected between March and June 2022, using an online questionnaire comprising a “Personal Information Form” and “PFA Application Self-Efficacy Scale.” The data obtained were analyzed using descriptive statistics, independent samples t-test, Mann–Whitney U test, one-way analysis of variance, Kruskal–Wallis test, multiple comparison tests, and linear regression analysis. ResultsThe average age of the senior nursing students was 21.82 ± 2.23 years. Overall, 89.6 % of the students had not received PFA service from any institution. Furthermore, 91.4 % had not received PFA training at any institution. The students' mean score on the PFA application self-efficacy scale was 123.37 ± 22.92. Students who received PFA training had high average scores. ConclusionsIt is necessary to develop senior nursing students' self-efficacy in PFA application. In this context, it is recommended that systematic training, including training on the application of PFA, be conducted regularly along with applied studies on disaster response situations.

Artificial Intelligence in Otology, Rhinology, and Laryngology: A Narrative Review of Its Current and Evolving Picture.

With technological advancements, artificial intelligence (AI) has progressed to become a ubiquitous part of human life. Its aspects in otorhinolaryngology are varied and are continuously evolving. Currently, AI has applications in hearing aids, imaging technologies, interpretation of auditory brain stem systems, and many more in otology. In rhinology, AI is seen to impact navigation, robotic surgeries, and the determination of various anomalies. Detection of voice pathologies and imaging are some areas of laryngology where AI is being used. This review gives an outlook on the diverse elements, applications, and advancements of AI in otorhinolaryngology. The various subfields of AI including machine learning, neural networks, and deep learning are also discussed. Clinical integration of AI and otorhinolaryngology has immense potential to revolutionize the healthcare system and improve the standards of patient care. The current applications of AI and its future scopes in developing this field are highlighted in this review.

Impact of application volume and spray droplet size on soybean harvest aid efficacy

AbstractThroughout the mid‐southern United States, indeterminate maturity group (MG) IV soybean (Glycine max L. Merr.) have largely taken the place of determinate MG V and VI soybean in order maximize yield. However, this shift towards earlier maturity groups results in more green plant material at physiological maturity. Consequently, harvest aids are of interest to producers who seek to defoliate and desiccate soybean in a timely and uniform manner. Field experiments were conducted from 2019 to 2020 to evaluate the impact of harvest aid, application volume, and spray droplet volume mean diameter (VMD) on soybean harvest aid efficacy in Mississippi. Applications of paraquat, saflufenacil, and sodium chlorate were made when soybean averaged 65% brown pods, with application volumes of 5 and 20 gal. acre−1, and VMDs of 200, 500, and 800 µm. Defoliation, desiccation, and green stems were evaluated at 3, 7, 10, and 14 days after treatment (DAT). Soybean grain yield was obtained at harvest and adjusted to 13% moisture. Harvest aid efficacy did not vary due to application volume. Spray droplet spectra with a VMD of 200 µm maximized both defoliation and desiccation efficacy. At 14 DAT, applications of paraquat and sodium chlorate resulted in 95% defoliation but were similar to saflufenacil at 89%. Applications of paraquat resulted in desiccation of 16 more percentage points than saflufenacil, and 8 more percentage points than sodium chlorate. These data indicate soybean harvest aid applications should contain paraquat. Although efficacy was maximized with spray droplet spectra with a VMD of 200 µm, the total variance in efficacy due to VMD of spray droplets was minimal.

Adolescent-Centered mHealth Applications in a Collaborative Care Model: A Virtual Focus Group Study With Audiologists.

Technology-enabled care, including the use of mobile health (mHealth), is emerging as a viable hearing health care delivery method. While the integration of mHealth with adult populations currently supports a wide array of hearing services, a better understanding of the implementation across the lifespan is needed. Literature surrounding the unique population of adolescent hearing aid users is currently lacking. Research is needed to highlight factors important to the use and clinical integration of mHealth hearing aid applications (apps) with adolescents. This study explored two primary objectives: (a) audiologists' perceptions around the use of mHealth apps to enable collaborative, child-inclusive hearing aid personalization, and (b) person-centered ideation around potential app design components to benefit users aged 12 to 17 years. Twelve audiologists participated in virtual synchronous focus groups, across three group sessions using Cisco Webex. Sessions were recorded, transcribed, and analyzed using an inductive, codebook thematic analysis approach. Six main themes resulted from group discussion analyses: (a) client candidacy: characteristics impacting suitability for mHealth use; (b) clinical implementation: organizational, professional, or patient-level strategies for mHealth adoption; (c) collaboration: the use of two or more individuals working together; (d) empowerment: process of acquiring and using knowledge, skills, and strategies; (e) remote technology: technologies enabling remote hearing aid personalization; and (f) application functionality and design: features and characteristics important to an adolescent-focused app. Findings identified the potential for clinical integration of hearing aid apps with adolescents in a collaborative care model, including consideration of child-specific use patterns, outcomes, and key design and technology components to support real-world implementation and use. Results may guide development and tailoring efforts around existing and future hearing aid apps for use with adolescent populations.