Background/Objectives: Liver Transplantation (LT) is the second most common solid organ transplantation. Medication adherence on LT patients is key to avoiding graft failure, mortality, and important quality of life losses. The aim of this study is to identify risk-factors for non-adherence to treatment of liver transplant patients according to reliable published evidence. Methods: An umbrella review within the context of adherence to immunosuppressant medication of LT patients, was conducted. The review was performed in accordance with the principles of the preferred reporting items for systematic reviews and meta-analysis (PRISMA) guidelines. Results: A total of 11 articles were finally included for the review. Non-adherence factors were identified and allocated using the WHO classification of factors for non-adherence. Each of these groups contains a subset of factors that have been shown to influence adherence to medication, directly or indirectly, according to literature findings. Conclusions: The results of the review indicate that sociodemographic factors, factors related to the patient, factors related to the treatment, condition-related and health system-related factors are good categories of predictors for both adherence and non-adherence to immunosuppressive medication in LT patients. This list of factors may help physicians in the treating and recognizing of patients with a potential risk of non-adherence and it could help in the designing of new tools to better understand non-adherence after LT and targeted interventions to promote adherence of LT patients. Full article

The Resin Transfer Moulding process receives great attention from both academia and industry, owing to its superior manufacturing rate and product quality. Particularly, the progression of its mould filling stage is crucial to ensure a complete reinforcement saturation. Contemporary process simulation methods focus primarily on physics-based approaches to model the complex resin permeation phenomenon, which are computationally expensive to solve. Thus, the application of machine learning and data-driven modelling approaches is of great interest to minimise the cost of process simulation. In this study, a comprehensive dataset consisting of mould filling patterns of the Resin Transfer Moulding process at different injection locations for a composite dashboard panel case study is presented. The problem description and significance of the dataset are outlined. The distribution of this comprehensive dataset aims to lower the barriers to entry for researching machine learning approaches in composite moulding applications, while concurrently providing a standardised baseline for evaluating newly developed algorithms and models in future research works. Full article

Extracardiac anomalies (ECAs) are strong predictors of genetic disorders in infants with congenital heart disease (CHD), but there are no prior studies assessing performance of ECA status as a screen for genetic diagnoses in CHD patients. This retrospective cohort study assessed this in our comprehensive inpatient CHD genetics service focusing on neonates and infants admitted to the intensive care unit (ICU). The performance and diagnostic utility of using ECA status to screen for genetic disorders was assessed using decision curve analysis, a statistical tool to assess clinical utility, determining the threshold of phenotypic screening by ECA versus a Test-All approach. Over 24% of infants had genetic diagnoses identified (n = 244/1013), and ECA-positive status indicated a 4-fold increased risk of having a genetic disorder. However, ECA status had low–moderate screening performance based on predictive summary index, a compositive measure of positive and negative predictive values. For those with genetic diagnoses, nearly one-third (32%, 78/244) were ECA-negative but had cytogenetic and/or monogenic disorders identified by genetic testing. Thus, if the presence of multiple congenital anomalies is the phenotypic driver to initiate genetic testing, 13.4% (78/580) of infants with isolated CHD with identifiable genetic causes will be missed. Given the prevalence of genetic disorders and limited screening performance of ECA status, this analysis supports genetic testing in all CHD infants in intensive care settings rather than screening based on ECA. Full article

Age-associated deep-subcortical white matter lesions (DSCLs) are an independent risk factor for dementia, displaying high levels of CD68⁺ microglia. This study aimed to characterize the transcriptomic profile of microglia in DSCLs and surrounding radiologically normal-appearing white matter (NAWM) compared to non-lesional control white matter. CD68⁺ microglia were isolated from white matter groups (n = 4 cases per group) from the Cognitive Function and Ageing Study neuropathology cohort using immuno-laser capture microdissection. Microarray gene expression profiling, but not RNA-sequencing, was found to be compatible with immuno-LCM-ed post-mortem material in the CFAS cohort and identified significantly differentially expressed genes (DEGs). Functional grouping and pathway analysis were assessed using the Database for Annotation Visualization and Integrated Discovery (DAVID) software, and immunohistochemistry was performed to validate gene expression changes at the protein level. Transcriptomic profiling of microglia in DSCLs compared to non-lesional control white matter identified 181 significant DEGs (93 upregulated and 88 downregulated). Functional clustering analysis in DAVID revealed dysregulation of haptoglobin–haemoglobin binding (Enrichment score 2.5, p = 0.017), confirmed using CD163 immunostaining, suggesting a neuroprotective microglial response to blood–brain barrier dysfunction in DSCLs. In NAWM versus control white matter, microglia exhibited 347 DEGs (209 upregulated, 138 downregulated), with significant dysregulation of protein de-ubiquitination (Enrichment score 5.14, p < 0.001), implying an inability to maintain protein homeostasis in NAWM that may contribute to lesion spread. These findings enhance understanding of microglial transcriptomic changes in ageing white matter pathology, highlighting a neuroprotective adaptation in DSCLs microglia and a potentially lesion-promoting phenotype in NAWM microglia. Full article

Artificial Intelligence (AI) is one of the science fields with huge potential to create a cognitive and tech-leaping type of future smart city design/development. However, extant studies lag behind recent applications, potential growth areas, and the challenges associated with AI implementation. This study examines AI’s current role, trend, and future potential impacts in enhancing smart city drivers. The methodology entails conducting a Systematic Literature Review (SLR) of publications from 2022 onwards. The approach involves qualitative deductive coding methods, descriptive statistical analysis, and thematic analysis. The findings revealed the impacts of AI in (i) public services and connectivity, (ii) improving accessibility and efficiency, (iii) quality healthcare, (iv) education, and (v) public safety. Likewise, strategies, such as collaborative ecosystems, digital infrastructure, capacity building, and clear guidelines and ethical framework, were proposed for fostering the integration of AI in potential future smart cities. This research fills a notable gap in the current understanding of AI’s specific contributions to smart cities, offering insights for stakeholders in urban planning, computer science, sociology, economics, environmental science, and smart city initiatives. It serves as a strategic guideline and scholarly research output for enhancing smart city design. It also underscores the potential of AI in creating dynamic, sustainable, and efficient urban environments. Full article

Epilepsy, a prevalent neurological disorder characterized by recurrent seizures, significantly impacts individuals’ neurobiological, cognitive, and social lives. This report presents a feasibility study investigating the effects of a computerized cognitive training program on enhancing executive functions, particularly inhibitory control, in children and adolescents with epilepsy. Employing a pre-test–intervention–post-test design, the study involved 26 participants with diverse epileptic syndromes, focusing on those without severe intellectual disabilities. The intervention, based on the CogniFit Inc. platform, consisted of personalized tasks aiming to improve participants’ inhibitory skills over 16 weeks, with an average of 40 sessions completed per participant. Results indicated significant improvements in reaction times and error rates in an anti-saccade task, demonstrating enhanced inhibitory control and general performance post-intervention. These findings suggest that targeted cognitive training is a feasible approach to bolster executive functions in young individuals with epilepsy, potentially improving their academic performance, employability, and social interactions. The study underscores the importance of early cognitive interventions in epilepsy management, highlighting the potential for computerized programs to aid in mitigating cognitive deficits associated with the condition. Full article

The premortem understanding of the role of feline coronavirus (FeCoV) in the lungs of cats is limited as viruses are seldom inspected in the bronchoalveolar lavage (BAL) specimens of small animal patients. This study retrospectively analyzed the prevalence of FeCoV in BAL samples from cats with atypical lower airway and lung disease, as well as the clinical characteristics, diagnostic findings, and follow-up information. Of 1162 clinical samples submitted for FeCoV RT-nPCR, 25 were BAL fluid. After excluding 1 case with chronic aspiration, FeCoV was found in 3/24 (13%) BAL specimens, with 2 having immunofluorescence staining confirming the presence of FeCoV within the cytoplasm of alveolar macrophages. The cats with FeCoV in BAL fluid more often had pulmonary nodular lesions (66% vs. 19%, p = 0.14) and multinucleated cells on cytology (100% vs. 48%, p = 0.22) compared to the cats without, but these differences did not reach statistical significance due to the small sample size. Three cats showed an initial positive response to the corticosteroid treatment based on the clinical signs and radiological findings, but the long-term prognosis varied. The clinical suspicion of FeCoV-associated pneumonia or pneumonitis was raised since no other pathogens were found after extensive investigations. Further studies are warranted to investigate the interaction between FeCoV and lung responses in cats. Full article

This study presents a Two-Layer Deep Deterministic Policy Gradient (TL-DDPG) energy management strategy for Hydrogen fuel cell hybrid train, that aims to solve the problem that traditional reinforcement learning strategies require high initial values and are difficult to optimize global variables. Augmenting the optimization capabilities of the inner layer, a frequency decoupling algorithm integrates into the outer layer, furnishing a fitting initial value for strategy optimization. This addition aims to bolster the stability of fuel cell output, thereby enhancing the overall efficiency of the hybrid power system. In comparison with the traditional reinforcement learning algorithm, the proposed approach demonstrates notable improvements: a reduction in hydrogen consumption per 100 km by 16.3 kg, a 9.7% increase in the output power stability of the fuel cell, and a 1.8% enhancement in its efficiency. Full article

Teachers in secondary vocational education face challenges in interdisciplinary teaching due to their traditional teacher education within specific subject domains. Collaborative efforts—like those implemented in Teacher Design Teams (TDTs)—can prepare and support teachers for interdisciplinary teaching. Research has demonstrated the factors determining the effectiveness of TDTs. However, it is noted that the sustainable continuation of TDTs remains uncertain over the years. This research investigates the conditions that facilitate the sustainability of TDTs within the context of interdisciplinary teaching. Over the course of three school years, this qualitative study monitored 14 teachers participating in four TDTs within the context of an interdisciplinary vocational education course. During the initial two school years, the TDTs received external support from the main researcher, transitioning to an autonomous operation in the third school year. A yearly interview with each participating teacher and meeting reports were collected and analysed with thematic analysis. One of the main findings reveals that while the internal coach contributes to supporting TDTs’ progress, the support of the school leader is particularly crucial for sustainability. Although this study focused on school-based TDTs, it underscores the importance of support from outside the school for TDTs’ sustainability. Full article

Structural superlubricity refers to the lubrication state in which the friction between two crystalline surfaces in incommensurate contact is nearly zero; this has become an important branch in recent tribological research. Two-dimensional (2D) materials with structural superlubricity such as graphene, MoS₂, h-BN, and alike, which possess unique layered structures and excellent friction behavior, will bring significant advances in the development of high-performance microelectromechanical systems (MEMS), as well as in space exploration, space transportation, precision manufacturing, and high-end equipment. Herein, the review mainly introduces the tribological properties of structural superlubricity among typical 2D layered materials and summarizes in detail the underlying mechanisms responsible for superlubricity on sliding surfaces and the influencing factors including the size and layer effect, elasticity effect, moiré superlattice, edge effect, and other external factors like normal load, velocity, and temperature, etc. Finally, the difficulties in achieving robust superlubricity from micro to macroscale were focused on, and the prospects and suggestions were discussed. Full article

A liquid nitrogen cooling circulating unit is a necessary condition for the stable operation of a cryogenic oscillator, which can provide a stable working environment for the oscillator. In this paper, according to the user’s functional requirements and performance parameters, a closed cooling system with supercooled liquid nitrogen as the medium was designed using SOLIDWORKS 2021 software, which can provide a suitable working environment for the cryogenic oscillator. Combined with the system heat load analysis, theoretical calculation for and the design of the coil heat exchanger, one of the core pieces of equipment of the unit, were carried out. The performance of the designed nitrogen exhaust heater was studied using FLUENT 2021 software, and the velocity field and temperature field of the nitrogen exhaust heater were analyzed. The results show that the outlet temperature of the nitrogen exhaust heating device can reach up to 310 K, and the outlet flow rate of the heating device is 0.01528 kg/s. The experiments on the liquid nitrogen circulating unit using the simulated load equipment show that the refrigeration power of the unit can reach a design index of 600 W, and the temperature of the liquid nitrogen at the liquid outlet of the unit can reach 77.8 K. The experiments also show that the unit meets the design requirements. Full article

Water scarcity is one of the significant constraints on sustainable agricultural development in arid and semi-arid regions. The challenges faced in forage production are even more severe than those encountered with general crops. The industry still struggles to achieve water-efficient, high-yield quality forage in water-scarce pastoral areas. This study focuses on alfalfa, a high-quality forage crop, employing a combination of “subsurface drip irrigation (SDI) + alternate partial root-zone irrigation (APRI)” and establishing three water supply gradients (full irrigation, 75% deficit, 50% deficit), in comparison with the widely used subsurface drip irrigation, to study the effects of two irrigation methods and three moisture gradients on alfalfa. The aim is to provide some theoretical basis and data support for achieving water-saving and high-yield quality forage in water-scarce pastoral areas. The main findings are as follows: First, compared with SDI, the two-year alternate dry and wet environment provided by alternate partial root-zone drip irrigation (ARDI) significantly increased the specific root length, specific surface area, and root length density of alfalfa at 20~40 cm depth, increasing by 33.3~76.8%, 6.4~32.97%, and 15.2~93.9%, respectively, compared to SDI. Under ARDI irrigation, the alfalfa root system has a greater contact area with the soil, which lays a solid foundation for the water and nutrient supply needed for the accumulation of its above-ground biomass. Secondly, over the two-year production process, the plant height of alfalfa under ARDI treatment was 12~14.5% higher than that under SDI, the total fresh forage yield was 43.5~64% higher, and the total dry forage yield was 23.2~33.8% higher than SDI. Under ARDI, the 75% water deficit treatment could still maintain the plant height and stem thickness of alfalfa compared to full irrigation with SDI and increased the dry forage yield by 6.6% without significantly reducing the quality, significantly enhancing the productive performance of alfalfa. Moreover, during the two years of production and utilization, the nutritional quality of alfalfa under the ARDI irrigation mode did not significantly decrease compared to SDI, maintaining the stable nutritional quality of alfalfa over multiple years of production. Lastly, thanks to the improved root system and increased yield of alfalfa under ARDI irrigation, and based on this, its water evapotranspiration did not significantly increase compared to SDI; the annual average Alfalfa Water Productivity Index (AWP_I) and Alfalfa Water Productivity of Crop (AWP_C) under ARDI irrigation increased by 28.8% and 37.2%, respectively, improving the water use efficiency of alfalfa production. In summary, in the production of alfalfa in water-scarce pastoral areas, ARDI and its water deficit treatment have more potential for water-saving than SDI as a water-saving irrigation strategy. Full article

Acid hydrolysis serves as the primary method for determining the monosaccharide composition of polysaccharides. However, inappropriate acid hydrolysis conditions may catalyze the breakdown of monosaccharides such as fructans (Fru), generating non-sugar by-products that affect the accuracy of monosaccharide composition analysis. In this study, we determined the monosaccharide recovery rate and non-sugar by-product formation of inulin-type fructan (ITF) and Fru under varied acid hydrolysis conditions using HPAEC-PAD and UPLC-Triple-TOF/MS, respectively. The results revealed significant variations in the recovery rate of Fru within ITF under different hydrolysis conditions, while glucose remained relatively stable. Optimal hydrolysis conditions for achieving a relatively high monosaccharide recovery rate for ITF entailed 80 °C, 2 h, and 1 M sulfuric acid. Furthermore, we validated the stability of Fru during acid hydrolysis. The results indicated that Fru experienced significant degradation with an increasing temperature and acid concentration, with a pronounced decrease observed when the temperature exceeds 100 °C or the H₂SO₄ concentration surpasses 2 M. Finally, three common by-products associated with Fru degradation, namely 5-hydroxymethyl-2-furaldehyde, 5-methyl-2-furaldehyde, and furfural, were identified in both Fru and ITF hydrolysis processes. These findings revealed that the degradation of Fru under acidic conditions was a vital factor leading to inaccuracies in determining the Fru content during ITF monosaccharide analysis. Full article

Background: In the evolving field of maxillofacial surgery, integrating advanced technologies like Large Language Models (LLMs) into medical practices, especially for trauma triage, presents a promising yet largely unexplored potential. This study aimed to evaluate the feasibility of using LLMs for triaging complex maxillofacial trauma cases by comparing their performance against the expertise of a tertiary referral center. Methods: Utilizing a comprehensive review of patient records in a tertiary referral center over a year-long period, standardized prompts detailing patient demographics, injury characteristics, and medical histories were created. These prompts were used to assess the triage suggestions of ChatGPT 4.0 and Google GEMINI against the center’s recommendations, supplemented by evaluating the AI’s performance using the QAMAI and AIPI questionnaires. Results: The results in 10 cases of major maxillofacial trauma indicated moderate agreement rates between LLM recommendations and the referral center, with some variances in the suggestion of appropriate examinations (70% ChatGPT and 50% GEMINI) and treatment plans (60% ChatGPT and 45% GEMINI). Notably, the study found no statistically significant differences in several areas of the questionnaires, except in the diagnosis accuracy (GEMINI: 3.30, ChatGPT: 2.30; p = 0.032) and relevance of the recommendations (GEMINI: 2.90, ChatGPT: 3.50; p = 0.021). A Spearman correlation analysis highlighted significant correlations within the two questionnaires, specifically between the QAMAI total score and AIPI treatment scores (rho = 0.767, p = 0.010). Conclusions: This exploratory investigation underscores the potential of LLMs in enhancing clinical decision making for maxillofacial trauma cases, indicating a need for further research to refine their application in healthcare settings. Full article

Two mixed peri-substituted phosphine-chlorostibines, Acenap(PiPr₂)(SbPhCl) and Acenap(PiPr₂)(SbCl₂) (Acenap = acenaphthene-5,6-diyl) reacted cleanly with Grignard reagents or nBuLi to give the corresponding tertiary phosphine-stibines Acenap(PiPr₂)(SbRR’) (R, R’ = Me, iPr, nBu, Ph). In addition, the Pt(II) complex of the tertiary phosphine-stibine Acenap(PiPr₂)(SbPh₂) as well as the Mo(0) complex of Acenap(PiPr₂)(SbMePh) were synthesised and characterised. Two of the phosphine-stibines and the two metal complexes were characterised by single-crystal X-ray diffraction. The peri-substituted species act as bidentate ligands through both P and Sb atoms, forming rather short Sb-metal bonds. The tertiary phosphine-stibines display through-space J(CP) couplings between the phosphorus atom and carbon atoms bonded directly to the Sb atom of up to 40 Hz. The sequestration of the P and Sb lone pairs results in much smaller corresponding J(CP) being observed in the metal complexes. QTAIM (Quantum Theory of Atoms in Molecules) and EDA-NOCV (Energy Decomposition Analysis employing Naturalised Orbitals for Chemical Valence) computational techniques were used to provide additional insight into a weak n(P)→σ*(Sb-C) intramolecular bonding interaction (pnictogen bond) in the phosphine-stibines. Full article

This paper presents a comprehensive study on the spectral properties of mimetic finite-difference operators and their application in the robust fluid–structure interaction (FSI) analysis of aircraft wings under uncertain operating conditions. By delving into the eigenvalue behavior of mimetic Laplacian operators and extending the analysis to stochastic settings, we develop a novel stochastic mimetic framework tailored for addressing uncertainties inherent in the fluid dynamics and structural mechanics of aircraft wings. The framework integrates random matrix theory with mimetic discretization methods, enabling the incorporation of uncertainties in fluid properties, structural parameters, and coupling conditions at the fluid–structure interface. Through spectral and localization analysis of the coupled stochastic mimetic operator, we assess the system’s stability, sensitivity to perturbations, and computational efficiency. Our results highlight the potential of the stochastic mimetic approach for enhancing reliability and robustness in the design of aircraft wings, paving the way for optimization algorithms that integrate uncertainties directly into the design process. Our findings reveal a significant impact of stochastic perturbations on the spectral radius and eigenfunction localization, indicating heightened system sensitivity. The introduction of randomized singular value decomposition (RSVD) within our framework not only enhances computational efficiency but also preserves accuracy in low-rank approximations, which is critical for handling large-scale systems. Moreover, Monte Carlo simulations validate the robustness of our stochastic mimetic framework, showcasing its efficacy in capturing the nuanced dynamics of FSI under uncertainty. This study contributes to the fields of numerical methods and aerospace engineering by offering a rigorous and scalable approach for conducting uncertainty-aware FSI analysis, which is crucial for the development of safer and more efficient aircraft. Full article

In recent years, the demand for foods without animal proteins has increased, both for health and ethical reasons. Replacing animal protein in foods can result in unappealing textures, hindering consumer acceptance. In this context, interfacial properties also play a crucial role in food systems like foam or emulsions. Therefore, the interfacial rheological behavior at the air–water interface of pea protein isolate (PPI) has been investigated to understand how affects food foam production. The PPI has been studied without modification and also through enzymatic treatment with transglutaminase (TG) to understand the interfacial properties of the modified proteins. Data obtained by static measurements have shown a surface activity of PPI comparable with other vegetable proteins, while the treatment with TG does not significantly alter the surface tension value and the interfacial adsorption rate. Differences have been found in the rearrangement rate, which decreases with TG, suggesting a possible crosslinking of the pea proteins. The PPI modified with TG, studied in dynamic conditions both in dilation and shear kinematics, are less elastic than PPI that is untreated but with a higher consistency, which may lead to poor foam stability. The lower complex interfacial modulus obtained under shear conditions also suggests a low long-time stability. Full article

This study investigated the effect of copper (Cu) doping content on zinc oxide with varied weight percentages and the dispersion of Cu-doped ZnO (CZO) by adding polyvinylpyrrolidone (PVP), coated on a glass substrate, through a physical assessment and optical property and thermal insulation testing. CZO NPs were synthesized by using the sol–gel method with a zinc acetate precursor. The powder X-ray diffraction (XRD) patterns of the CZO showed that the solid solubility limit was below 5 mol% without a secondary phase. A field-emission scanning electron microscopy (FE-SEM) micrograph demonstrated that the particle size of CZO was in nanoscale with the packing of a quasi-spherical shape. The UV-Vis-NIR reflectance spectra of the powder showed that 1 mol% CZO has the highest near-infrared (NIR) reflectivity in the wavelength 780–2500 nm, with great visible light transmission. The CZO NPs were loaded in acrylic copolymer in different weight percentages ranging from 25 wt% to 75 wt%, the film thickness of the coating was varied from 5 µm to 100 µm, and PVP was added into this nanocomposite polymer to disperse through an ultrasonication method. The results showed that the highest loading of CZO powder in a polymer at 75 wt% in 100 µm of thickness with polyvinylpyrrolidone (PVP) as a dispersant showed better sample dispersion and retained good transparency to the naked eye. Full article

Background: Currently, there are no reports describing lead break (LB) during transvenous lead extraction (TLE). Methods: This study conducted a retrospective analysis of 3825 consecutive TLEs using mechanical sheaths. Results: Fracture of the lead, defined as LB, with a long lead fragment (LF) occurred in 2.48%, LB with a short LF in 1.20%, LB with the tip of the lead in 1.78%, and LB with loss of a free-floating LF in 0.57% of cases. In total, extractions with LB occurred in 6.04% of the cases studied. In cases in which the lead remnant comprises more than the tip only, there was a 50.31% chance of removing the lead fragment in its entirety and an 18.41% chance of significantly reducing its length (to less than 4 cm). Risk factors for LB are similar to those for major complications and increased procedure complexity, including long lead dwell time [OR = 1.018], a higher LV ejection fraction, multiple previous CIED-related procedures, and the extraction of passive fixation leads. The LECOM and LED scores also exhibit a high predictive value. All forms of LB were associated with increased procedure complexity and major complications (9.96 vs. 1.53%). There was no incidence of procedure-related death among such patients, and LB did not affect the survival statistics after TLE. Conclusions: LB during TLE occurs in 6.04% of procedures, and this predictable difficulty increases procedure complexity and the risk of major complications. Thus, the possibility of LB should be taken into account when planning the lead extraction strategy and its associated training. Full article

Superconducting electric motors are required in order to deliver lower-carbon aviation. Critical to the success and viability of operating superconducting electric motors in aviation is keeping the superconducting coils at their operating temperature. This paper examines the challenges of keeping a superconducting motor cold if it were used on a single aisle passenger aircraft such as an Airbus A320. The cooling problem is defined and different cooling scenarios are investigated to determine viability. The investigation has shown that for a motor with a superconducting rotor only (copper stator), a Stirling-type cryocooler would be sufficient. However, if the motor is to be fully superconducting, then the cooling loads of the stator, which are much higher, make mechanical refrigeration impractical and the only option is to cool the motor with the heat sink of a liquid hydrogen fuel. Full article

(1) Background: This study evaluated the clinical implications of a new measurement technique for muscle mass using discrete multi-wavelength near-infrared spectroscopy (DMW-NIRS) compared with multifrequency bioelectrical impedance analysis (BIA) in older adults. (2) Methods: In a cross-sectional study involving 91 participants aged 65 years, the agreement of total lean mass for each measurement was assessed using the intraclass correlation coefficient (ICC) and Pearson’s correlation analysis. The study was conducted at a university hospital from 10 July 2023 to 1 November 2023. (3) Results: A total of 45 men (mean age, 74.1) and 46 women (mean age, 73.6) were analyzed. In the comparisons of total lean mass between DMW-NIRS and BIA, ICC (2.1) was 0.943 and Cronbach’s α coefficient was 0.949 (p < 0.001). Across all segments of lean mass, we found excellent agreement with the ICCs (>0.90) and acceptable values of the correlation coefficients (>0.6) between DMW-NIRS and BIA. (4) Conclusions: This study confirmed agreement in the measurements of muscle mass between portable devices using DMW-NIRS and BIA among community-dwelling older adults. A simple screening of muscle mass in a home setting would help to detect early decreases in muscle mass. Full article