Maximum Likelihood Estimation for Unrooted 3-Leaf Trees: An Analytic Solution for the CFN Model.

Maximum likelihood estimation is among the most widely-used methods for inferring phylogenetic trees from sequence data. This paper solves the problem of computing solutions to the maximum likelihood problem for 3-leaf trees under the 2-state symmetric mutation model (CFN model). Our main result is a closed-form solution to the maximum likelihood problem for unrooted 3-leaf trees, given generic data; this result characterizes all of the ways that a maximum likelihood estimate can fail to exist for generic data and provides theoretical validation for predictions made in Parks and Goldman (Syst Biol 63(5):798-811, 2014). Our proof makes use of both classical tools for studying group-based phylogenetic models such as Hadamard conjugation and reparameterization in terms of Fourier coordinates, as well as more recent results concerning the semi-algebraic constraints of the CFN model. To be able to put these into practice, we also give a complete characterization to test genericity.

A Review on Camel Milk Composition, Techno-Functional Properties and Processing Constraints.

Camel milk plays a critical role in the diet of peoples belongs to the semi-arid and arid regions. Since prehistoric times, camel milk marketing was limited due to lacking the processing facilities in the camel-rearing areas, nomads practiced the self-consumption of raw and fermented camel milk. A better understanding of the techno-functional properties of camel milk is required for product improvement to address market and customer needs. Despite the superior nutraceutical and health promoting potential, limited camel dairy products are available compared to other bovines. It is a challenging impetus for the dairy industry to provide diversified camel dairy products to consumers with superior nutritional and functional qualities. The physicochemical behavior and characteristics of camel milk is different than the bovine milk, which poses processing and technological challenges. Traditionally camel milk is only processed into various fermented and non-fermented products; however, the production of commercially important dairy products (cheese, butter, yogurt, and milk powder) from camel milk still needs to be processed successfully. Therefore, the industrial processing and transformation of camel milk into various products, including fermented dairy products, pasteurized milk, milk powder, cheese, and other products, require the development of new technologies based on applied research. This review highlights camel milk's processing constraints and techno-functional properties while presenting the challenges associated with processing the milk into various dairy products. Future research directions to improve product quality have also been discussed.

Combining unsupervised constraints on weakly supervised semantic segmentation of skin cancer.

Precise segmentation for skin cancer lesions at different stages is conducive to early detection and further treatment. Considering the huge cost of obtaining pixel-perfect annotations for this task, segmentation using less expensive image-level labels has become a research direction. Most image-level label weakly supervised segmentation uses class activation mapping (CAM) methods. A common consequence of this method is incomplete foreground segmentation, insufficient segmentation, or false negatives. At the same time, when performing weakly supervised segmentation of skin cancer lesions, ulcers, redness, and swelling may appear near the segmented areas of individual disease categories. This co-occurrence problem affects the model's accuracy in segmenting class-related tissue boundaries to a certain extent. The above two issues are determined by the loosely constrained nature of image-level labels that penalize the entire image space. Therefore, providing pixel-level constraints for weak supervision of image-level labels is the key to improving performance. To solve the above problems, this paper proposes a joint unsupervised constraint-assisted weakly supervised segmentation model(UCA-WSS). The weakly supervised part of the model adopts a dual-branch adversarial erasure mechanism to generate higher-quality CAM. The unsupervised part uses contrastive learning and clustering algorithms to generate foreground labels and fine boundary labels to assist segmentation and solve common co-occurrence problems in weakly supervised skin cancer lesion segmentation through unsupervised constraints. The model proposed in the article is evaluated comparatively with other related models on some public dermatology data sets. Experimental results show that our model performs better on the skin cancer segmentation task than other weakly supervised segmentation models, showing the potential of combining unsupervised constraint methods on weakly supervised segmentation.

Corporate digital transformation and financing constraints: The moderating effect of institutional investors.

In the age of digitization, digital transformation has emerged as a crucial pathway for companies to achieve sustainable development. In a sample of 24,103 firm-year observations from 3,508 listed companies in China's A-share market between 2007 and 2020, we investigate the relationship between corporate digital transformation and financing constraints based on dynamic capability theory. The proportion of intangible assets dedicated to digital technology is employed as a measure of the degree of digital transformation, and the SA index is utilized to assess the level of financing constraints. The findings demonstrate that digital transformation plays a significant role in alleviating financing constraints. In addition, greater institutional ownership leads to a pronounced negative correlation between digital transformation and financing constraints. From the perspective of dynamic capability theory, this study provides empirical evidence supporting research on economic consequences associated with digital transformation. Our results may contribute towards government formulation and implementation of policies promoting digital transformation to create a supportive external environment for businesses. Companies must seize opportunities associated with digital transformation to mitigate financing constraints.

The Existence-Relatedness-Growth Theory for Job Satisfaction and Motivation of Greek National Healthcare Service Employees in the Context of Severe Financial Constraints.

The hospital environment is often quite complicated due to interdisciplinary workflow procedures and multitasking staff, which are exacerbated during periods of economic crisis. This study aimed to examine the motivation and job satisfaction factors of Greek National Healthcare Service (NHS) employees in relation to the Existence-Relatedness-Growth (ERG) theory of motivation during a period of severe financial constraints. A cross-sectional study was conducted in three public hospitals in Greece from 2018 to 2019, utilizing a survey tool to measure the factors of motivation and job satisfaction among Greek NHS employees. The study also aimed to identify the most relevant motivational theory applicable to the complex Greek hospital environment. Exploratory factor analysis (EFA) was employed to extract the structural factors of the survey tool, and analysis of variance (ANOVA) was used to identify statistical differences between the means of three or more independent groups. A sample of 363 Greek NHS employees participated in this study. Statistically significant differences were detected between hospital units and job satisfaction factors, as well as between the functions of hospital clusters and job positions. Specifically, managerial staff presented higher levels of job satisfaction, while nursing staff had the lowest scores in terms of psychological contracts when compared to medical and administrative staff. This study demonstrated that job satisfaction in Greek public hospitals, in a context of severe financial constraints, was mainly driven by strong interpersonal connections and employee trust in management, despite significant cuts in salaries, staff numbers, and hospital budgets.

Clinical impact of DVH uncertainties.

Dose-volume histograms (DVH), along with dose and volume metrics, are central to radiotherapy planning. As such, errors have the potential to significantly impact the selection of appropriate treatment plans. Dose distributions that pass tests in one TPS may fail the same tests when transferred to another, even if using identical structures and dose grid information. This work shows the design and implementation of methods for assessing the accuracy of dose and volume computations performed by treatment planning systems (TPS), and other analytical tools. We demonstrate examples where differences in calculations between systems can change the assessment of a plan's clinical acceptability. Our work also provides a more detailed DVH analysis of single targets than earlier published studies. This is relevant for SRS plans and small structure dose assessments. Very small structures are a particular problem because of their coarse digital representation, and the impact of this is thoroughly examined. Reference DVH curves were derived mathematically, based on Gaussian dose distributions centered on spherical structures. The structures and dose distributions were generated synthetically, and imported into RayStation, MasterPlan, and ProKnow. Corresponding DVHs were analytically derived and taken as ground truth references, for comparison with the commercial DVH calculations. Two commonly used dose metrics PCI and MGI were used to determine the limit of calculation accuracy for small structures. In addition, to measure the DVH differences between a larger range of commercial DVH calculators, the D95 metric from a set of real clinical plans was compared across both the 3 DVH calculators under test, and across a further six TPSs from other hospitals. We show that even slight deviations between the results of DVH calculators can lead to plan check failures, and we illustrate this with the commonly used D95 planning metric. We present clinical data across eight planning systems that highlight instances where plan checks would pass in one software and fail in another due to DVH calculation differences. For the smallest volumes tested, errors of up to 20% were observed in the DVHs. RayStation was tested down to a 3 mm radius sphere (≈0.1 cc) and this showed close to 10% error, reducing to 1% for 10 mm radius (≈4.0 cc) and 0.1% for 20 mm radius (≈33 cc). In clinical plans, the variation in D95 was up to 9% for the smallest volumes, and typically around 2% in the range 0.5 cc-20 cc, and 1% in 20 cc-70 cc, falling to <0.1% for large volumes. Paddick Conformity Index (PCI) and Modified Gradient Index (MGI) are commonly used plan quality indicators for very small volumes. For volumes ≈0.1 cc we observed errors of up to 40% in PCI, and up to 75% in MGI. Our study extends the range of tested DVH calculators in published work, and shows their performance over a wider range of volume sizes. We provide quantitative evidence of the critical need to test the accuracy of DVH calculators in the TPS before clinical use. This work is particularly relevant for both stereotactic plan evaluation and for assessment of small volume doses in published dose constraint recommendations. We demonstrate that significant errors can occur in DVHs for volumes less than 1 cc, even if the volumes themselves are calculated accurately. Even for large structures, deviations between the outputs of DVH calculators can lead to indicated or reported plan check failures if they do not include appropriate tolerances. We urge caution in the use of DVH metrics for these very small volumes and recommend that appropriate DVH uncertainty tolerances are set in organ dose constraints when using them to evaluate clinical plans.

Review of the Phonological System of Contemporary Urdu Spoken in Pakistan.

PURPOSE: Urdu is the lingua franca and national language of Pakistan, and is the 10th most-spoken language worldwide with over 230 million speakers. The Urdu phonological system has been examined over the past decades. However, the system has been evolving. This paper aimed to review the available studies investigating various aspects of the Urdu phonological system and to reveal the variations noted among these studies. METHOD: Twenty-one studies examining the phonological system of Urdu were located. The studies were reviewed in terms of consonants, geminates, consonant clusters, vowels, diphthongs, syllable structure, phonotactic constraints, and stress. RESULT: The findings indicated that 38 consonants, 23 vowels, and 15 diphthongs are used in contemporary Urdu. Most consonants exist as geminates word medially. There are six syllable structures. The consonant clusters are constrained to the coda position only, and short vowels cannot exist in the word-final position. Like other syllable-timed languages, stress is not prominent in Urdu. CONCLUSION: Based on this review, a contemporary Urdu phonemic and syllable structure inventory has been proposed. This will serve as a reference for use in further acquisition research and clinical practice.

Autoclaving is at least as effective as gamma irradiation for biotic clearing and intentional microbial recolonization of soil.

Sterilization is commonly used to remove or reduce the biotic constraints of a soil to allow recolonization by soil-dwelling organisms, with autoclaving and gamma irradiation being the most frequently used approaches. Many studies have characterized sterilization impacts on soil physicochemical properties, with gamma irradiation often described as the preferred approach, despite the lower cost and higher scalability of autoclaving. However, few studies have compared how sterilization techniques impact soil recolonization by microorganisms. Here, we compared how two sterilization approaches (autoclaving; gamma irradiation) and soil washing impacted microbial recolonization of soil from a diverse soil inoculum. Sterilization method had little impact on microbial alpha diversity across recolonized soils. For sterile soil regrowth microcosms, species richness and diversity were significantly reduced by autoclaving relative to gamma irradiation, particularly for fungi. There was no impact of sterilization method on bacterial composition in recolonized soils and minimal impact on fungal composition (P = 0.05). Washing soils had a greater impact on microbial composition than sterilization method, and sterile soil regrowth had negligible impacts on microbial recolonization. These data suggest that sterilization method has no clear impact on microbial recolonization, at least across the soils tested, indicating that soil autoclaving is an appropriate and economical approach for biotically clearing soils.IMPORTANCESterilized soils represent soil-like environments that act as a medium to study microbial colonization dynamics in more "natural" settings relative to artificial culturing environments. Soil sterilization is often carried out by gamma irradiation or autoclaving, which both alter soil properties, but gamma irradiation is thought to be the gentler technique. Gamma irradiation can be cost prohibitive and does not scale well for larger experiments. We sought to examine how soil sterilization technique can impact microbial colonization, and additionally looked at the impact of soil washing which is believed to remove soil toxins that inhibit soil recolonization. We found that both gamma-irradiated and autoclaved soils showed similar colonization patterns when reintroducing microorganisms. Soil washing, relative to sterilization technique, had a greater impact on which microorganisms were able to recolonize the soil. When allowing sterilized soils to regrow (i.e., persisting microorganisms), gamma irradiation performed worse, suggesting that gamma irradiation does not biotically clear soils as well as autoclaving. These data suggest that both sterilization techniques are comparable, and that autoclaving may be more effective at biotically clearing soil.

Experiences of healthcare providers and caregivers regarding health system bottlenecks affecting child healthcare service delivery in a rural district: Empirical qualitative study.

AIM: To explore the experiences of nurses and caregivers about the health system bottlenecks to the delivery of child healthcare services in a rural district in Ghana. DESIGN: The study employed a qualitative approach using an exploratory, descriptive design. METHODS: Collection of data was through semi-structured, face-to-face interviews with 26 participants in the Nkwanta South Municipality, Ghana. Audio recordings of interviews were transcribed verbatim and analysed qualitatively. Inductive codes generated were organised into themes and sub-themes. RESULTS: The main health system bottlenecks that emerged were the poor state of in-patient facilities, inadequate basic logistics and persistent shortage of essential medicines needed for child healthcare delivery. CONCLUSIONS: Health system bottlenecks have the tendency to affect the treatment and hospitalisation outcomes of sick children and eventually impact the state of child healthcare negatively. Concerted efforts by government and local authorities to remove these barriers will help to improve child health and child health outcomes. PUBLIC CONTRIBUTION: A total of 26 participants comprising nurses and caregivers, agreed and participated in this study. Interviews with these participants were conducts either in the health facilities or in the communities where they live. Their responses contributed significantly to the content of this article.

Enhanced low-light image fusion through multi-stage processing with Bayesian analysis and quadratic contrast function.

This manuscript introduces an innovative multi-stage image fusion framework that adeptly integrates infrared (IR) and visible (VIS) spectrum images to surmount the difficulties posed by low-light settings. The approach commences with an initial preprocessing stage, utilizing an Efficient Guided Image Filter for the infrared (IR) images to amplify edge boundaries and a function for the visible (VIS) images to boost local contrast and brightness. Utilizing a two-scale decomposition technique that incorporates Lipschitz constraints-based smoothing, the images are effectively divided into distinct base and detail layers, thereby guaranteeing the preservation of essential structural information. The process of fusion is carried out in two distinct stages: firstly, a method grounded in Bayesian theory is employed to effectively combine the base layers, so effectively addressing any inherent uncertainty. Secondly, a Surface from Shade (SfS) method is utilized to ensure the preservation of the scene's geometry by enforcing integrability on the detail layers. Ultimately a Choose Max principle is employed to determine the most prominent textural characteristics, resulting in the amalgamation of the base and detail layers to generate an image that exhibits a substantial enhancement in both clarity and detail. The efficacy of our strategy is substantiated by rigorous testing, showcasing notable progressions in edge preservation, detail enhancement, and noise reduction. Consequently, our method presents significant advantages for real-world applications in image analysis.

Do pilot zones for green finance reform and innovation avoid ESG greenwashing? Evidence from China.

As ESG investments have grown, many companies are emphasizing them to impress capital markets and consumers with their responsibility and environmental consciousness. However, managers in unethical companies greenwashing ESG reports to keep clients. The present investigation employs quasi-natural experiment data obtained from a sample of 1200 Chinese A-share listed companies spanning the period from 2011 to 2021 to examine how the Green Finance Reform and Innovation Pilot Zone (GFRIPZ) affects ESG greenwashing. GFRIPZ can prevent publicly traded companies from ESG greenwashing. The statistical analysis of heterogeneity demonstrates that GFRIPZ in non-state-owned, mid-west, heavy-polluting, manufacturing industries reduces ESG greenwashing. GFRIPZ suppresses corporate ESG greenwashing better in companies with severe financial constraints and a poor corporate reputation. GFRIPZ's inhibition of corporate ESG greenwashing is enhanced by internal and external monitoring. This study shows how financial markets affect firms' ESG greenwashing. It helps implement GFRIPZ theoretically. It also recommends raising listed companies' awareness of ESG disclosure and reducing corporate ESG greenwashing.

Seasonal differences in participation and time spent in physical activity in Russia: The Know Your Heart survey.

This study aimed to assess the levels and investigate socioeconomic, demographic, and health-related predictors of winter and summer physical activity (PA) in Russia using the data from the Know Your Heart population survey conducted in Novosibirsk and Arkhangelsk (2015-2018; n = 5068; aged 35-69 years). Employing a series of probit, Tobit, and the Cragg models, we separated the predictors of the probability of participating in leisure-time PA from the predictors of time spent in PA. Our study showed that financial constraints limited males' participation in winter PA (probability of participation decreased by 12 percentage points) and females' engagement in winter and summer PA (decrease in the number of hours of practicing PA by approximately 1 h a week). Education, self-reported health, smoking, and cues to action had different impacts on both probability and time spent in PA in winter and summer. We also found significant gender differences in participation and time spent in PA across seasons. Older age, poor health, and smoking were greater obstacles to PA for males compared to females both in winter and summer. However, males were more likely to follow physician's advice to lose weight and take up physical exercise. Information campaigns that promote physical activities, including those that are free of charge, are needed to help limit barriers to PA for people with low socioeconomic status and individuals with little or no exercise experience. Also, making sports more accessible to citizens by providing free and low-cost sports facilities can increase their participation and time spent in PA, improving individual health and productivity.

Positive impacts of green finance on environmental protection investment: Evidence from green finance reform and innovations pilot zone.

After long-term development, the global economic level has improved significantly, but environmental issues generated by early extensive development seriously threaten the survival of human beings. China, in particular, urgently needs to promote sustainable development through green finance policies. For this reason, this paper regards the 2017 eight pilot zones in five provinces for green finance reform and innovations (GFRIs) as a quasi-natural experiment, and explores whether it can encourage investment in environmental protection in heavily polluting enterprises by using difference-in-differences-in-differences (DDD) model. The paper finds that: First, GFRIs can bolster investment in environmental protection in heavy polluting enterprises. The results remain consistent after several robustness checks, covering the placebo test, PSM-DID test and so on. Second, mechanism tests find that the policy promotes environmental protection investment by alleviating financing constraints and cutting financing costs. Third, heterogeneity analysis shows that the promotion effect of GFRIs on environmental protection investment is more pronounced for provinces with higher percentages of secondary industry GDP, large-scale enterprises, and enterprises with better ESG management. This paper demonstrates the beneficial influence of GFRIs on promoting the transformation of heavy polluting enterprises and provides suggestions for the improvement of such policies.

SENSE-PPI reconstructs interactomes within, across, and between species at the genome scale.

Ab initio computational reconstructions of protein-protein interaction (PPI) networks will provide invaluable insights into cellular systems, enabling the discovery of novel molecular interactions and elucidating biological mechanisms within and between organisms. Leveraging the latest generation protein language models and recurrent neural networks, we present SENSE-PPI, a sequence-based deep learning model that efficiently reconstructs ab initio PPIs, distinguishing partners among tens of thousands of proteins and identifying specific interactions within functionally similar proteins. SENSE-PPI demonstrates high accuracy, limited training requirements, and versatility in cross-species predictions, even with non-model organisms and human-virus interactions. Its performance decreases for phylogenetically more distant model and non-model organisms, but signal alteration is very slow. In this regard, it demonstrates the important role of parameters in protein language models. SENSE-PPI is very fast and can test 10,000 proteins against themselves in a matter of hours, enabling the reconstruction of genome-wide proteomes.

Investigation of Social Constraints, Psychosocial Adjustment and Optimism among Dialysis Patients.

BACKGROUND: Social constraints are perceived as unsupportive behaviors, leading to inadequate psychosocial adjustment, while optimism can help people recover from distress and reduce any negative effects of chronic disease. The aim of this study was to investigate social constraints, psychosocial adjustment and optimism among patients on dialysis. METHODS: In this study, 402 patients undergoing dialysis in Greece completed the following questionnaires: (i) the Social Constraints Scale (SCS) for the assessment of social constrains, (ii) the Psychosocial adjustment to illness scale (PAIS-SR) for the assessment of psychosocial adjustment, and (iii) the LOT-R scale for the assessment of optimism. A Mann-Whitney test was used for the comparison of continuous variables between two groups. Spearman correlation coefficients (rho) were used to explore the association of two continuous variables. Multiple linear regression analysis was used with the SCS scale. RESULTS: Greater difficulty in psychosocial adjustment in the domestic, vocational, extended family and social environments, sexual relationships, and health care as well as greater psychological distress were significantly associated with a greater occurrence of social constraints (p < 0.001). Additionally, greater optimism was significantly associated with fewer social constraints and lower difficulty in adjusting to their disease (p < 0.001). CONCLUSIONS: Greater difficulty in all dimensions of psychosocial adjustment is associated with more social constraints, while optimism is associated with fewer social constraints and better disease adjustment.

Inequality and health: Can medical practice address the consequences of inequalities?

BACKGROUND: The extent to which governments provide socioeconomic supports has been highlighted by their spending during the COVID-19 pandemic. This has implications for patterns of inequality, in particular on exacerbating unequal health and well-being. RESULTS: Inequity has expanded due to neoliberalism, a market-based approach that has endured for more than four decades. Together with COVID-19, it has developed and exposed many structural governance differences. DISCUSSION: There are a number of examples presented of the effects of inequalities on health and well-being. The role of general practice in addressing these is discussed and challenges are highlighted, especially those relating to payment systems and workforce constraints.

Minimization of peak stresses with the shape derivative.

This article is concerned with the minimization of peak stresses occurring in linear elasticity. We propose to minimize the maximal von Mises stress of the elastic body. This leads to a non-smooth shape functional. We derive the shape derivative and associate it with the Clarke sub-differential. Using a steepest descent algorithm, we present numerical simulations. We compare our results to the usual [Formula: see text]-norm regularization and show that our algorithm performs better in the presented tests.This article is part of the theme issue 'Non-smooth variational problems with applications in mechanics'.

Bimanual Coordination in Children with Bilateral Cerebral Palsy: A Cross-Sectional Study.

AIM: To compare bimanual coordination in children with bilateral cerebral palsy (BCP) with that of children with typical development (TD) and correlate bimanual coordination with clinical measures of hand function. METHODS: 3-D kinematic data were collected from 14 children with BCP (mean age 13 years 1 month; range 7.3-17.2 years, 5 females) and 14 age-matched children with TD (mean age 13 years 1 month, range 7.0-16.0 years, 7 females) as they opened a drawer with one hand and activated a switch inside it with the other hand at self-paced and as-fast-as-possible speeds. Hand roles varied in each condition. Participants' hand function levels were classified using the Manual Ability Classification System. Unimanual dexterity and bimanual performance were evaluated using the Box and Blocks Test and Both Hands Assessment respectively. RESULTS: Participants with BCP performed the bimanual task more slowly (p < 0.001) and sequentially, as evidenced by greater time differences between the two hands achieving the end goal (p = 0.01). Faster speeds, particularly when the less affected hand opened the drawer, facilitated time-related measures of bimanual coordination (p < 0.05). Bimanual coordination correlated with all clinical measures of hand function (p < 0.05). CONCLUSION: For children with BCP, speed and hand used for each subcomponent of the task influence bimanual coordination. Better bimanual coordination is associated with less impairment of both hands.

AQbD-Guided Development and Validation of an Innovative Extraction Procedure and Stability-Indicating RP-HPLC Method for Quantification of Posaconazole in Tablet Formulation.

OBJECTIVE: The objective of this work is to develop a stability-indicating HPLC method for the quantification of Posaconazole (PCZ) in tablet formulation using an Analytical Quality by Design (AQbD) approach. MATERIALS AND METHODS: The development process involved the Design of Experiments (DOE) utilizing distinctive constraints mixture design for mobile phase ratio optimization and a 2-level factorial design for selection of extraction diluent compositions. Key responses measured included % assay and system suitability parameters. Method operable design regions (MODR) were determined, and final optimum conditions were selected. Forced degradation studies were conducted to assess method stability. RESULTS: The optimized HPLC method employed a Zorbax C18 column with a mobile phase consisting of pH 3.5 10mM phosphate buffer, acetonitrile, and methanol in a ratio of 30:53:17 % v/v/v. The method demonstrated stability-indicating capabilities, with PCZ degradation observed in acidic and oxidative environments, while remaining stable in alkali. Peak purity analysis from Empower software confirmed the absence of interaction with degradants. Validation according to ICH Q2 (R2) guidelines showed precision, linearity over the range of 0.25 µg/mL to 376 µg/mL, and accuracy demonstrated through recovery studies from 50 to 150%. CONCLUSION: The developed HPLC method utilizing AQbD approach is specific, robust, precise, and accurate for the quantification of PCZ in tablet formulations, thus suitable for routine analysis.

Help or Hurt? The Impact of Digital Finance on the Physical Health of the Elderly in China.

Under the backdrop of global aging, the escalating number of elderly individuals in poor health poses a growing social burden and impacts economic development and social stability. A fundamental question arises as to whether the advancements of digital finance (DF) can effectively enhance the physical health of the elderly. This study aims to investigate the impact of DF on the physical health of the elderly by utilizing data from the China Health and Retirement Longitudinal Study (CHARLS) conducted in 2013, 2015, and 2018. The results reveal a significant positive impact of DF on enhancing the physical health of the elderly. Furthermore, the study demonstrates that this impact is particularly pronounced among the elderly with higher educational attainment, stronger intergenerational links, and those residing in central cities. A mechanism analysis further reveals that DF contributes to improving the physical health of the elderly by augmenting household disposable income, alleviating liquidity constraints, and enhancing the utilization of medical services. These findings offer valuable insights for the future development of DF and the implementation of policies promoting healthy aging and active aging.