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The increasing interest in plant-based diets due to health concerns, sustainability, and allergenicity of animal proteins has led to a surge in the use of plant proteins. However, their low functionality has made it challenging to use them in developing drugs and digesting new foods. The Maillard reaction which occurs naturally between proteins and polysaccharides presents a potential solution to this problem. However, its sensitivity to temperature, pH levels, and ionic strength makes its use in the food and pharmaceutical sectors problematic. This review explores different Maillard conjugation strategies using plant proteins and polysaccharides to provide a better understanding of their potential for generating protein functions in the food industry. The review highlights the importance of this technique in creating new and functional food products that are safe and sustainable. [ABSTRACT FROM AUTHOR]

Background: With the ever‐increasing integration of artificial intelligence (AI) into health care, it becomes imperative to gain an in‐depth understanding of how health care professionals, specifically nurse practitioners, perceive and approach this transformative technology. Objectives: This study aimed to gain insights into nurse practitioners' perceptions and attitudes toward AI adoption in health care. Methods: This qualitative research employed a descriptive and phenomenological approach using in‐depth interviews. Data were collected through a semi‐structured questionnaire with 37 nurse practitioners selected through purposive sampling, specifically Maximum Variation Sampling and Expert Sampling techniques, to ensure diversity in characteristics. Trustworthiness of the research was maintained through member checking and peer debriefing. Thematic analysis was employed to uncover recurring themes and patterns in the data. Results: The thematic analysis revealed nine main themes that encapsulated nurse practitioners' perceptions and attitudes toward AI adoption in health care. These included nurse practitioners' perceptions of AI implementation, attitudes toward AI adoption, patient‐centered care and AI, quality of health care delivery and AI, ethical and regulatory aspects of AI, education and training needs, collaboration and interdisciplinary relationships, obstacles in integrating AI, and AI and health care policy. While this study found that nurse practitioners held a wide range of perspectives, with many viewings AI as a tool to enhance patient care. Conclusions: This research provides a valuable contribution to the evolving discourse surrounding AI adoption in health care. The findings underscore the necessity for comprehensive education and training in AI, accompanied by clear and robust ethical and regulatory guidelines to ensure the responsible integration of AI in health care practice. Furthermore, fostering collaboration and interdisciplinary relationships is pivotal for the successful incorporation of AI in health care. Policymakers should also address the challenges and opportunities that AI presents in the health care sector. This study enhances the ongoing conversation on AI adoption in health care by shedding light on the perspectives of nurses, thereby shaping future strategies for AI integration. [ABSTRACT FROM AUTHOR]

Context: The COVID-19 epidemic has had a substantial influence on the mental health of chronic disease patients. However, there is a scarcity of research on them in Bangladesh. Aims: This study aims to explore the prevalence of and identify the risk factors for depression, anxiety, and stress symptoms during the COVID-19 pandemic among people with chronic diseases in Bangladesh. Materials and Methods: This cross-sectional study involving face-to-face and telephone interviews was carried out among Bangladeshi people diagnosed with chronic diseases between September and November 2020. The total sample size was 878, and a convenient sampling technique was used. Logistic regression analysis was performed to investigate potential influencing factors for depression, anxiety, and stress. Results: The mean age of respondents was 50.10 years. Among them, 35.0%, 36.0%, and 29.0% suffered from depression, anxiety, and stress symptoms, respectively. In multivariable logistic regression, depression had a significant positive association with higher age (≥60 years), lower income, rural residency, and loss of close family members due to COVID-19. Anxiety had a significant positive association with higher age (≥40 years), lower education, lower income, rural residency, and loss of close family members due to COVID-19. Stress had a significant positive association with higher age (≥40 years), no income, rural residency, and loss of close family members due to COVID-19. Conclusion: It is urgent to consider the risk of developing mental health distress among chronic disease patients, especially aged people, by health service providers and generate effective programs for emergency situations. [ABSTRACT FROM AUTHOR]

Background: The current study explores the integration of a motor imagery (MI)-based BCI system with robotic rehabilitation designed for upper limb function recovery in stroke patients. Methods: We developed a tablet deployable BCI control of the virtual iTbot for ease of use. Twelve right-handed healthy adults participated in this study, which involved a novel BCI training approach incorporating tactile vibration stimulation during MI tasks. The experiment utilized EEG signals captured via a gel-free cap, processed through various stages including signal verification, training, and testing. The training involved MI tasks with concurrent vibrotactile stimulation, utilizing common spatial pattern (CSP) training and linear discriminant analysis (LDA) for signal classification. The testing stage introduced a real-time feedback system and a virtual game environment where participants controlled a virtual iTbot robot. Results: Results showed varying accuracies in motor intention detection across participants, with an average true positive rate of 63.33% in classifying MI signals. Discussion: The study highlights the potential of MI-based BCI in robotic rehabilitation, particularly in terms of engagement and personalization. The findings underscore the feasibility of BCI technology in rehabilitation and its potential use for stroke survivors with upper limb dysfunctions. [ABSTRACT FROM AUTHOR]

The increasing prevalence of upper and lower extremity (ULE) functional deficiencies presents a significant challenge, as it restricts individuals' ability to perform daily tasks independently. Robotic devices are emerging as assistive devices to assist individuals with limited ULE functionalities in activities of daily living (ADLs). While assistive manipulators are available, manual control through traditional methods like joysticks can be cumbersome, particularly for individuals with severe hand impairments and vision limitations. Therefore, autonomous/semi-autonomous control of a robotic assistive device to perform any ADL task is open to research. This study addresses the necessity of fostering independence in ADLs by proposing a creative approach. We present a vision-based control system for a six-degrees-of-freedom (DoF) robotic manipulator designed for semi-autonomous "pick-and-place" tasks, one of the most common activities among ADLs. Our approach involves selecting and training a deep-learning-based object detection model with a dataset of 47 ADL objects, forming the base for a 3D ADL object localization algorithm. The proposed vision-based control system integrates this localization technique to identify and manipulate ADL objects (e.g., apples, oranges, capsicums, and cups) in real time, returning them to specific locations to complete the "pick-and-place" task. Experimental validation involving an xArm6 (six DoF) robot from UFACTORY in diverse settings demonstrates the system's adaptability and effectiveness, achieving an overall 72.9% success rate in detecting, localizing, and executing ADL tasks. This research contributes to the growing field of autonomous assistive devices, enhancing independence for individuals with functional impairments. [ABSTRACT FROM AUTHOR]

The use of thermally modified timber (TMT) in outdoor applications is well established, but its performance against the stresses of outdoor conditions is not comprehensively understood. This study investigates the changes in density, surface chemical composition, color, equilibrium moisture content (EMC), checking, hardness, and cupping of thermally modified boards of Scots pine (Pinus sylvestris L.), Norway spruce (Picea abies (L.) H. Karst.), and European ash (Fraxinus excelsior L.) during a two-year weather exposure test in Eastern Finland. Unmodified pine, spruce, and ash and copper salt impregnated pine boards were used as controls. The results show that a two-year weather exposure period causes degradation of hydrophobic lignin, and the leaching of the degraded compounds changed the color, increased the EMC, and decreased the hardness of specimens. Although the EMC of TMT specimens was lower compared with unmodified and impregnated ones during weathering, the changes were more obvious in TMT than in the controls. More checks occurred in the TMT specimens than in unmodified ones after the exposure. On the other hand, the TMT specimens had a lower degree of cupping. These findings also indicate that an increase in modification temperature induces more checks but improves the durability of all studied species by reducing the chemical degradation, color change, cupping, and hygroscopicity during weather exposure. Key words: thermally modified wood, weathering, FTIR, checking, cupping. L'utilisation du bois modifie thermiquement (BMT) pour des usages exterieurs est bien etablie mais sa performance face aux stress dus aux conditions exterieures n'est pas completement connue. Cette etude examine les changements dans la densite, la composition chimique en surface, la couleur, le degre d'humidite d'equilibre (EMC), le fendillement, l'indice de durete et le voilement de planches de pin sylvestre (Pinus sylvestris L.), d'epicea commun (Picea abies (L.) H. Karst.) et de frene commun (Fraxinus excelsior L.) modifiees thermiquement durant un test d'exposition aux intemperies d'une duree de deux ans dans l'est de la Finlande. Des planches non modifiees de pin, d'epicea et de frene ainsi que des planches de pin impregnees de sel de cuivre ont ete utilisees comme temoins. Les resultats montrent qu'une periode d'exposition aux intemperies de deux ans a cause une degradation de la lignine hydrophobe et que le lessivage des composes engendres par la degradation a change la couleur, augmente l'EMC et diminue l'indice de durete des specimens. Bien que l'EMC des specimens de BMT ait ete plus faible comparativement a ceux qui ont ete impregnes ou qui n'ont pas ete modifies lors du vieillissement aux intemperies, les changements etaient plus evidents chez le BMT que chez les temoins. Davantage de fendillement est survenu chez les specimens de BMT que chez les specimens non modifies suivant l'exposition aux intemperies. Par contre, les specimens de BMT avaient un plus faible degre de voilement. Ces resultats indiquent aussi qu'une augmentation de la temperature du traitement thermique entraine davantage de fendillement mais ameliore la durabilite de toutes les especes etudiees en reduisant la degradation chimique, le changement de couleur, le voilement et l'hygroscopicite durant l'exposition aux intemperies. [Traduit par la Redaction] Mots-cles: bois modifie thermiquement, vieillissement aux intemperies, FTIR, fendillement, voilement., Introduction Thermal modification (TM) reduces the hygroscopicity and equilibrium moisture content (EMC) of wood without using chemicals and, consequently, increases its dimensional stability and biological durability (Hill 2006). Due to [...]

In this paper, we focus on the human upper limb rehabilitation scheme that utilizes the concept ofteleoperation. Teleoperation can help the therapist demonstrate different rehab exercises to a different group of people at the same time remotely. Different groups of people from a different place connected to the same network can get therapy from the same therapist at the same time using the telerehabilitation scheme. Here, we presented a humanoid robot NAO that can be operated remotely by a therapist to demonstrate the exercise to a patient. To mimic the movement demonstrated by the therapist, Kinect V2 sensor which is a markerless vision-based motion-tracking device, was used. Modified Denavit-Hartenberg (DH) convention was used for the kinematic modeling of the human upper arm. From the Kinect data, a geometric solution was developed to find a unique inverse kinematic solution of human upper-extremity. Experimental results revealed that NAO could be teleoperated successfully to instruct and demonstrate patients to perform different arm movement exercises in real-time.