Predicting nickel concentration in soil using fractional-order derivative and visible-near-infrared spectroscopy indices.

Accurate monitoring and estimation of heavy metal concentrations is an important process in the prevention and treatment of soil pollution. However, the weak correlation between spectra and heavy metals in soil makes it difficult to use spectroscopy in predicting areas with a risk of heavy metal pollution. In this paper, a method for detection of Ni in soil in eastern China using the fractional-order derivative (FOD) and spectral indices was proposed. The visible-near-infrared (Vis-NIR) spectra were preprocessed using the FOD (range: 0 to 2, interval: 0.1) to solve the problems of baseline drift and overlapping peaks in the original spectra. The product index (PI), ratio index (RI), sum index (SI), difference index (DI), normalized difference index (NDI), and brightness index (BI) were applied and compared. The results showed that the spectral detail increased as the FOD increased, and the interference of the baseline drift and overlapping peaks was eliminated as the spectral reflectance decreased. Furthermore, the FOD extracted the spectral sensitivity information more effectively and improved the correlation between the Vis-NIR spectra and the Ni concentration, and the NDI had a maximum correlation coefficient (r) of 0.803 for order 1.9. The estimation model based on the NDI dataset constructed after FOD processing had the best performance, with a validation accuracy [Formula: see text] of 0.735, RMSE of 3.848, and RPD of 2.423. In addition, this method is easy to carry out and suitable for estimating other heavy metal elements in soil.

Enhanced osteogenesis and antibacterial activity of dual-functional PEEK implants via biomimetic polydopamine modification with chondroitin sulfate and levofloxacin.

Polyetheretherketone (PEEK) implants have emerged as a clinically favored alternative to titanium alloy implants for cranial bone substitutes due to their excellent mechanical properties and biocompatibility. However, the biological inertness of PEEK has hindered its clinical application. To address this issue, we developed a dual-functional surface modification method aimed at enhancing both osteogenesis and antibacterial activity, which was achieved through the sustained release of chondroitin sulfate (CS) and levofloxacin (LVFX) from a biomimetic polydopamine (PDA) coating on the PEEK surface. CS was introduced to promote cell adhesion and osteogenic differentiation. Meanwhile, incorporation of antibiotic LVFX was essential to prevent infections, which are a critical concern in bone defect repairing. To our delight, experiment results demonstrated that the SPKD/CS-LVFX specimen exhibited enhanced hydrophilicity and sustained drug release profiles. Furthermore, in vitro experiments showed that cell growth and adhesion, cell viability, and osteogenic differentiation of mouse calvaria-derived osteoblast precursor (MC3T3-E1) cells were significantly improved on the SPKD/CS-LVFX coating. Antibacterial assays also confirmed that the SPKD/CS-LVFX specimen effectively inhibited the growth of Escherichia coli and Staphylococcus aureus, attributable to the antibiotic LVFX released from the PDA coating. To sum up, this dual-functional PEEK implant showed a promising potential for clinical application in bone defects repairing, providing excellent osteogenic and antibacterial properties through a synergistic approach.

Telemedicine Research Trends in 2001-2022 and Research Cooperation Between China and Other Countries Before and After the COVID-19 Pandemic: Bibliometric Analysis.

BACKGROUND: Advancements in technology have overcome geographical barriers, making telemedicine, which offers remote emergency services, healthcare, and medication guidance, increasingly popular. COVID-19 restrictions amplified its global importance by bridging distances. OBJECTIVE: This study aimed to analyze Chinese and global literature data, present new global telemedicine research trends, and clarify the development potential, collaborations, and deficiencies in China's telemedicine research. METHODS: We conducted bibliometrics and network analyses on relevant documents from the Web of Science database from 2001 to 2022. Data collection was completed on October 30, 2023. Considering COVID-19's impact, 2020 was used as a baseline, dividing the data into 2 periods: 2001-2019 and 2020-2022. The development potential was determined based on publication trends. An international coauthorship network analysis identified collaboration statuses and potential. Co-occurrence analysis was conducted for China and the world. RESULTS: We identified 25,333 telemedicine-related research papers published between 2001 and 2022, with a substantial increase during the COVID-19 period (2020-2022), particularly in China (1.93-fold increase), moving its global publication rank from tenth to sixth. The United States, the United Kingdom, and Australia contributed 62.96% of the literature, far ahead of China's 3.90%. Globally, telemedicine research increased significantly post-2020. Between 2001 and 2019, the United States and Australia were central in coauthor networks; post-2020, the United States remained the largest node. Network hubs included the United States, the United Kingdom, Australia, and Canada. Keyword co-occurrence analysis revealed 5 global clusters from 2001 to 2019 (system technology, health care applications, mobile health, mental health, and electronic health) and 2020 to 2022 (COVID-19, children's mental health, artificial intelligence, digital health, and rehabilitation of middle-aged and older adults). In China, the research trends aligned with global patterns, with rapid growth post-2020. From 2001 to 2019, China cooperated closely with Indonesia, India, Japan, Taiwan, and South Korea. From 2020 to 2022, cooperation expanded to Japan, Singapore, Malaysia, and South Korea, as well as Saudi Arabia, Egypt, South Africa, Ghana, Lebanon, and other African and Middle Eastern countries. Chinese keyword co-occurrence analysis showed focus areas in system technology, health care applications, mobile health, big data analysis, and electronic health (2001-2019) and COVID-19, artificial intelligence, digital health, and mental health (2020-2022). Although psychology research increased, studies on children's mental health and middle-aged and older adults' rehabilitation were limited. CONCLUSIONS: We identified the latest trends in telemedicine research, demonstrating its significant potential in China and providing directions for future development and collaborations in telemedicine research.

Promoting the social implementation of digital and mobile health: effects of regulation on user and non-user behavior in East Asia.

This study conducted policy and regulation analyses and user acceptance surveys in three East Asian countries with developed telecommunication infrastructure (China, South Korea, and Japan) to determine the most effective way to implement mobile health (mHealth). Regional differences in users' emphasis on the purpose of mHealth, including medical information referral or health management, appear to be influenced by regional regulation, thus making regulation analysis important when considering mHealth penetration strategies. Potential mHealth users have high expectations for medical information and correspondence, which is crucial for the pharmaceutical industry in terms of providing information and retaining patients. Furthermore, potential users are willing to use the system medically, which is beneficial to the pharmaceutical industry when introducing mHealth and prescriptions in combination.

How Social Influence Promotes the Adoption of Mobile Health among Young Adults in China: A Systematic Analysis of Trust, Health Consciousness, and User Experience.

As mobile health (mHealth) offers several advantages in healthcare, researchers are exploring the motivational factors for its adoption. However, few studies have elucidated the complex relationship between social influence and behavioral intentions to adopt mHealth among young adults in China. This study explored the impact of social influence on young adults' behavioral intentions to adopt mHealth, the mediating roles of trust and health consciousness, and the moderating effect of mHealth user experience on the relationship between the predictors. In total, 300 valid responses were collected from a university in China, and a research model was developed. The partial least squares structural equation modeling method was used to verify the relationship between the main research variables. mHealth adoption behavioral intentions among young adults were significantly positively impacted by social influence; it indirectly increased mHealth adoption behavioral intentions by positively affecting trust and health consciousness. mHealth use weakened the positive impact of social influence on trust and health consciousness, while user experience positively moderated the relationship between health consciousness and behavioral intentions. Trust and health consciousness play important roles in the complex multivariate relationships between social influence and behavioral intentions to adopt mHealth. Future research should consider the moderating role of the mHealth user experience. These findings enrich the mHealth technology acceptance theory framework and provide specific guidance strategies for marketing mHealth applications.

3D Printed Multifunctional Biomimetic Bone Scaffold Combined with TP-Mg Nanoparticles for the Infectious Bone Defects Repair.

Infected bone defects are one of the most challenging problems in the treatment of bone defects due to the high antibiotic failure rate and the lack of ideal bone grafts. In this paper, inspired by clinical bone cement filling treatment, α-c phosphate (α-TCP) with self-curing properties is composited with ß-tricalcium phosphate (ß-TCP) and constructed a bionic cancellous bone scaffolding system α/ß-tricalcium phosphate (α/ß-TCP) by low-temperature 3D printing, and gelatin is preserved inside the scaffolds as an organic phase, and later loaded with a metal-polyphenol network structure of tea polyphenol-magnesium (TP-Mg) nanoparticles. The scaffolds mimic the structure and components of cancellous bone with high mechanical strength (>100 MPa) based on α-TCP self-curing properties through low-temperature 3D printing. Meanwhile, the scaffolds loaded with TP-Mg exhibit significant inhibition of Staphylococcus aureus (S.aureus) and promote the transition of macrophages from M1 pro-inflammatory to M2 anti-inflammatory phenotype. In addition, the composite scaffold also exhibits excellent bone-enhancing effects based on the synergistic effect of Mg2+ and Ca2+. In this study, a multifunctional ceramic scaffold (α/ß-TCP@TP-Mg) that integrates anti-inflammatory, antibacterial, and osteoinduction is constructed, which promotes late bone regenerative healing while modulating the early microenvironment of infected bone defects, has a promising application in the treatment of infected bone defects.

Evaluation of polyetheretherketone composites modified by calcium silicate and carbon nanotubes for bone regeneration: mechanical properties, biomineralization and induction of osteoblasts.

Desired orthopedic implant materials must have a good biological activity and possess appropriate mechanical property that correspond to those of human bone. Although polyetheretherketone (PEEK) has displayed a promising application prospect in musculoskeletal and dentistry reconstruction thanks to its non-biodegradability and good biocompatibility in the body, the poor osseointegration and insufficient mechanical strength have significantly limited its application in the repair of load-bearing bones and surgical operations. In this study, carbon nanotubes (CNT)/calcium silicate (CS)/polyetheretherketone ternary composites were fabricated for the first time. The addition of CS was mainly aimed at improving biological activities and surface hydrophilicity, but it inevitably compromised the mechanical strength of PEEK. CNT can reinforce the composites even when brittle CS was introduced and further upgraded the biocompatibility of PEEK. The CNT/CS/PEEK composites exhibited higher mechanical strengths in tensile and bending tests, 64% and 90% higher than those of brittle CS/PEEK binary composites. Besides, after incorporation of CNT and CS into PEEK, the hydrophilicity, surface roughness and ability to induce apatite-layer deposition were significantly enhanced. More importantly, the adhesion, proliferation, and osteogenic differentiation of mouse embryo osteoblasts were effectively promoted on CNT/CS/PEEK composites. In contrast to PEEK, these composites exhibited a more satisfactory biocompatibility and osteoinductive activity. Overall, these results demonstrate that ternary CNT/CS/PEEK composites have the potential to serve as a feasible substitute to conventional metal alloys in musculoskeletal regeneration and orthopedic implantation.

Progress in the application of 3D-printed sodium alginate-based hydrogel scaffolds in bone tissue repair.

In recent years, hydrogels have been widely used in the biomedical field as materials with excellent bionic structures and biological properties. Among them, the excellent comprehensive properties of natural polymer hydrogels represented by sodium alginate have attracted the great attention of researchers. At the same time, by physically blending sodium alginate with other materials, the problems of poor cell adhesion and mechanical properties of sodium alginate hydrogels were directly improved without chemical modification of sodium alginate. The composite blending of multiple materials can also improve the functionality of sodium alginate hydrogels, and the prepared composite hydrogel also has a larger application field. In addition, based on the adjustable viscosity of sodium alginate-based hydrogels, sodium alginate-based hydrogels can be loaded with cells to prepare biological ink, and the scaffold can be printed out by 3D printing technology for the repair of bone defects. This paper first summarizes the improvement of the properties of sodium alginate and other materials after physical blending. Then, it summarizes the application progress of sodium alginate-based hydrogel scaffolds for bone tissue repair based on 3D printing technology in recent years. Moreover, we provide relevant opinions and comments to provide a theoretical basis for follow-up research.

[Health Risk Assessment of Heavy Metals in Soil and Wheat Grain in the Typical Sewage Irrigated Area of Shandong Province].

Sewage irrigation is a common alternative to make up for the shortage of agricultural irrigation in intensive agricultural areas. Abundant organic matter and nutrients in sewage can improve soil fertility and crop yield, but hazardous materials, such as heavy metals, will damage the soil environmental quality and threaten human health. To better understand the characteristics of heavy metal enrichment and potential health risk in a sewage irrigated soil-wheat system, a total of sixty-three pairs of topsoil and wheat grain samples were collected from the sewage irrigated area of Longkou City in Shandong Province. The contents of Cr, Cu, Ni, Pb, Zn, As, Cd, and Hg were determined to analyze heavy metal contamination and calculate bio-accumulation factor (BAF), estimated daily absorption (EDA), as well as hazard quotient (HQ). The results showed that the average contents of the eight heavy metals were 61.647, 30.439, 29.769, 36.538, 63.716, 8.058, 0.328, and 0.028 mg·kg-1, respectively, which all exceeded the background values of corresponding heavy metals in the eastern Shandong Province. Especially, the average content of Cd was higher than the current standard value of soil environmental quality of agricultural land soil pollution risk control, indicating the apparent soil contamination. However, the correlations between the heavy metal contents in soil and wheat grains were not significant, suggesting that it is difficult to conclude the enrichment degree of heavy metals in wheat grains merely by the heavy metal contents in soil. The results of BAF showed that the high enrichment capacity of wheat grain was primarily obtained with Zn, Hg, Cd, and Cu. According to the national food safety limit standard, the over-limit ratios of Ni (100%) and Pb (96.8%) in wheat grains were the most serious. As a result, under the current consumption of local wheat flour, the EDAs of Ni and Pb were high, accounting for 28.278% and 1.955% of the acceptable daily intakes (ADI) for adults and 131.980% and 9.124% of the ADIs for children. The results of the health risk assessment exhibited that As and Pb were the main sources causing health risks, accounting for approximately 80% of the total risk. Although the sums of the HQ of the eight heavy metals for adults and children were below 10, the total HQ of children was 1.245 times higher than that of adults. The food safety of children should receive more attention. When considering spatial characteristics, the health risk in the southern study area was higher than that in the northern part of the study area. The prevention and control of heavy metal contamination in the southern area should be strengthened in the future.

Examining the Effects of Socioeconomic Development on Fine Particulate Matter (PM2.5) in China's Cities Based on Spatial Autocorrelation Analysis and MGWR Model.

Understanding the characteristics of PM2.5 and its socioeconomic factors is crucial for managing air pollution. Research on the socioeconomic influences of PM2.5 has yielded several results. However, the spatial heterogeneity of the effect of various socioeconomic factors on PM2.5 at different scales has yet to be studied. This paper collated PM2.5 data for 359 cities in China from 2005 to 2020, as well as socioeconomic data: GDP per capita (GDPP), secondary industry proportion (SIP), number of industrial enterprise units above the scale (NOIE), general public budget revenue as a proportion of GDP (PBR), and population density (PD). The spatial autocorrelation and multiscale geographically weighted regression (MGWR) model was used to analyze the spatiotemporal heterogeneity of PM2.5 and explore the impact of different scales of economic factors. Results show that the overall economic level was developing well, with a spatial distribution trend of high in the east and low in the west. With a large positive spatial correlation and a highly concentrated clustering pattern, the PM2.5 concentration declined in 2020. Secondly, the OLS model's statistical results were skewed and unable to shed light on the association between economic factors and PM2.5. Predictions from the GWR and MGWR models may be more precise than those from the OLS model. The scales of the effect were produced by the MGWR model's variable bandwidth and regression coefficient. In particular, the MGWR model's regression coefficient and variable bandwidth allowed it to account for the scale influence of economic factors; it had the highest adjusted R2 values, smallest AICc values, and residual sums of squares. Lastly, the PBR had a clear negative impact on PM2.5, whereas the negative impact of GDPP was weak and positively correlated in some western regions, such as Gansu and Qinghai provinces. The SIP, NOIE, and PD were positively correlated with PM2.5 in most regions. Our findings can serve as a theoretical foundation for researching the associations between PM2.5 and socioeconomic variables, and for encouraging the coequal growth of the economy and the environment.

Estimating Soil Salinity with Different Levels of Vegetation Cover by Using Hyperspectral and Non-Negative Matrix Factorization Algorithm.

Hyperspectral technology has proven to be an effective method for monitoring soil salt content (SSC). However, hyperspectral estimation capabilities are limited when the soil surface is partially vegetated. This work aimed to (1) quantify the influences of different fraction vegetation coverage (FVC) on SSC estimation by hyperspectra and (2) explore the potential for a non-negative matrix factorization algorithm (NMF) to reduce the influence of various FVCs. Nine levels of mixed hyperspectra were measured from simulated mixed scenes, which were performed by strictly controlling SSC and FVC in the laboratory. NMF was implemented to extract soil spectral signals from mixed hyperspectra. The NMF-extracted soil spectra were used to estimate SSC using partial least squares regression. Results indicate that SSC could be estimated based on the original mixed spectra within a 25.76% FVC (R2cv = 0.68, RMSEcv = 5.18 g·kg-1, RPD = 1.43). Compared with the mixed spectra, NMF extraction of soil spectrum improved the estimation accuracy. The NMF-extracted soil spectra from FVC below 63.55% of the mixed spectra provided acceptable estimation accuracies for SSC with the lowest results of determination of the estimation R2cv = 0.69, RMSEcv = 4.15 g·kg-1, and RPD = 1.8. Additionally, we proposed a strategy for the model performance investigation that combines spearman correlation analysis and model variable importance projection analysis. The NMF-extracted soil spectra retained the sensitive wavelengths that were significantly correlated with SSC and participated in the operation as important variables of the model.

Estimating soil salinity using Gaofen-2 imagery: A novel application of combined spectral and textural features.

Gaofen-2 (GF-2) imagery data has been playing an important role in environmental monitoring. However, the scarcity of spectral bands makes GF-2 difficult to use in soil salinity estimation. In this paper, we combined spectral and textual features for soil salinity estimation from GF-2 imagery. The spectral features comprised five classes of predictors: spectral value, vegetation index, salinity index, brightness index, and intensity index. Four gray-level co-occurrence matrix (GLCM) indices were used as the textural features. The least absolute shrinkage and selection operator (LASSO) was applied to select features. Four methods, namely, Random forest (RF), support vector machine (SVM), back propagation neural network (BPNN), and partial least squares regression (PLSR) were applied and compared. To this end, 211 soil samples were collected in the Yellow River Delta through field investigation. The results showed that GF-2 imagery could successfully estimate soil salinity by integrating spectral and texture features, and among the four methods, the RF had the highest accuracy with the determination coefficient for cross-validation (R2CV), a root mean square error for cross-validation (RMSECV), and the ratio of the standard deviation to the root mean square error of prediction (RPD) of 0.82, 2.36 g kg-1, and 2.28, respectively. Especially, the impact of different scale features on the soil salinity estimation accuracy was evaluated. The optimal window size for features was 9 × 9 pixels, and increasing or decreasing the window size will decrease the estimation accuracy. The study provides a novel application to soil salinity estimation from remote sensing imagery.

Determination of Waste Management Workers' Physical and Psychological Load: A Cross-Sectional Study Using Biometric Data.

Waste management workers experience high stress and physical strain in their work environment, but very little empirical evidence supports effective health management practices for waste management workers. Hence, this study investigated the effects of worker characteristics and biometric indices on workers' physical and psychological loads during waste-handling operations. A biometric measurement system was installed in an industrial waste management facility in Japan to understand the actual working conditions of 29 workers in the facility. It comprised sensing wear for data collection and biometric sensors to measure heart rate (HR) and physical activity (PA) based on electrocardiogram signals. Multiple regression analysis was performed to evaluate significant relationships between the parameters. Although stress level is indicated by the ratio of low frequency (LF) to high frequency (HF) or high LF power in HR, the results showed that compared with workers who did not handle waste, those who did had lower PA and body surface temperature, higher stress, and lower HR variability parameters associated with higher psychological load. There were no significant differences in HR, heart rate interval (RRI), and workload. The psychological load of workers dealing directly with waste was high, regardless of their PA, whereas others had a low psychological load even with high PA. These findings suggest the need to promote sustainable work relationships and a quantitative understanding of harsh working conditions to improve work quality and reduce health hazards.

Social Acceptance of Mobile Health among Young Adults in Japan: An Extension of the UTAUT Model.

The unprecedented development of information and communication technologies has opened up immense possibilities in the field of health care. Mobile health (mHealth) is gaining increasing attention as an important technology for solving health-related problems. Although a high rate of smartphone usage among young people in Japan has been identified, smartphone usage for health management is not high. As Japanese youth are important potential users of mHealth, it is necessary to explore theories that influence the behavioral intention of Japanese youth to adopt mHealth. This study conducted a questionnaire survey in a Japanese university and collected 233 valuable responses. This study was adapted and extended from the unified theory of acceptance and use of technology (UTAUT) model to measure eight constructs: health consciousness, social influence, facilitation conditions, perceived risk, trust, performance expectancy, effort expectancy, and behavioral intention. Structural equation modeling was used for hypothesis testing. We found that trust, performance expectancy, and effort expectancy directly influenced the behavioral intention to use mHealth. Health consciousness and social influence indirectly influence behavioral intention through trust and performance expectancy. Facilitation conditions indirectly influenced behavioral intention through effort expectancy. This study makes a vital theoretical contribution to policymakers and product developers for the further diffusion of mHealth among young people in Japan.

3D-Printed Poly (P-Dioxanone) Stent for Endovascular Application: In Vitro Evaluations.

Rapid formation of innovative, inexpensive, personalized, and quickly reproducible artery bioresorbable stents (BRSs) is significantly important for treating dangerous and sometimes deadly cerebrovascular disorders. It is greatly challenging to give BRSs excellent mechanical properties, biocompatibility, and bioabsorbability. The current BRSs, which are mostly fabricated from poly-l-lactide (PLLA), are usually applied to coronary revascularization but may not be suitable for cerebrovascular revascularization. Here, novel 3D-printed BRSs for cerebrovascular disease enabling anti-stenosis and gradually disappearing after vessel endothelialization are designed and fabricated by combining biocompatible poly (p-dioxanone) (PPDO) and 3D printing technology for the first time. We can control the strut thickness and vessel coverage of BRSs by adjusting the printing parameters to make the size of BRSs suitable for small-diameter vascular use. We added bis-(2,6-diisopropylphenyl) carbodiimide (commercial name: stabaxol®-1) to PPDO to improve its hydrolytic stability without affecting its mechanical properties and biocompatibility. In vitro cell experiments confirmed that endothelial cells can be conveniently seeded and attached to the BRSs and subsequently demonstrated good proliferation ability. Owing to the excellent mechanical properties of the monofilaments fabricated by the PPDO, the 3D-printed BRSs with PPDO monofilaments support desirable flexibility, therefore offering a novel BRS application in the vascular disorders field.

Modulating optical properties and interfacial electron transfer of CsPbBr3 perovskite nanocrystals via indium ion and chlorine ion co-doping.

In this work, we demonstrated an in situ approach for doping CsPbBr3 nanocrystals (NCs) with In3+ and Cl- with a ligand-assisted precipitation method at room temperature. The In3+ and Cl- co-doped NCs are characterized by the powder x-ray diffraction patterns, ultraviolet-visible, photoluminescence (PL) spectroscopy, time-resolved PL (TRPL), ultraviolet photoelectron spectroscopy, x-ray photoelectron spectroscopy, and transmission electron microscopy. Based on PL and TRPL results, the non-radiative nature of In3+-doping induced localized impurity states is revealed. Furthermore, the impact of In3+ and Cl- doping on charge transfer (CT) from the NCs to molecular acceptors was investigated and the results indicate that the CT at the interface of NCs can be tuned and promoted by In3+ and Cl- co-doping. This enhanced CT is attributed to the enlarged energy difference between relevant states of the molecular acceptor and the NCs by In3+ and Cl- upon co-doping. This work provides insight into how to control interfacial CT in perovskite NCs, which is important for optoelectronic applications.

Psychological Effects of Heart Rate and Physical Vibration on the Operation of Construction Machines: Experimental Study.

BACKGROUND: A construction method has emerged in which a camera is installed around a construction machine, and the operator remotely controls the machine while synchronizing the vibration of the machine with the images seen from the operator's seat using virtual reality (VR) technology. Indices related to changes in heart rate (HR) and physical vibration, such as heart rate variability (HRV) and multiscale entropy (MSE), can then be measured among the operators. As these indices are quantitative measures of autonomic regulation in the cardiovascular system, they can provide a useful means of assessing operational stress. OBJECTIVE: In this study, we aimed to evaluate changes in HR and body vibration of machine operators and investigate appropriate methods of machine operation while considering the psychological load. METHODS: We enrolled 9 remote operators (18-50 years old) in the experiment, which involved 42 measurements. A construction machine was driven on a test course simulating a construction site, and three patterns of operation-riding operation, remote operation using monitor images, and VR operation combining monitor images and machine vibration-were compared. The heartbeat, body vibration, and driving time of the participants were measured using sensing wear made of a woven film-like conductive material and a three-axis acceleration measurement device (WHS-2). We used HRV analysis in the time and frequency domains, MSE analysis as a measure of the complexity of heart rate changes, and the ISO (International Standards Organization) 2631 vibration index. Multiple regression analysis was conducted to model the relationship among the low frequency (LF)/high frequency (HF) HRV, MSE, vibration index, and driving time of construction equipment. Efficiency in driving time was investigated with a focus on stress reduction. RESULTS: Multiple comparisons conducted via the Bonferroni test and Kruskal-Wallis test showed statistically significant differences (P=.05) in HRV-LF/HF, the vibration index, weighted acceleration, motion sickness dose value (MSDVz), and the driving time among the three operation patterns. The riding operation was found to reduce the driving time of the machine, but the operation stress was the highest in this case; operation based on the monitor image was found to have the lowest operation stress but the longest operation time. Multiple regression analysis showed that the explanatory variables (LH/HF), RR interval, and vibration index (MSDVz by vertical oscillation at 0.5-5 Hz) had a negative effect on the driving time (adjusted coefficient of determination R2=0.449). CONCLUSIONS: A new method was developed to calculate the appropriate operating time by considering operational stress and suppressing the physical vibration within an acceptable range. By focusing on the relationship between psychological load and physical vibration, which has not been explored in previous studies, the relationship of these variables with the driving time of construction machines was clarified.

Exploring the Shift in International Trends in Mobile Health Research From 2000 to 2020: Bibliometric Analysis.

BACKGROUND: Smartphones have become an integral part of our lives with unprecedented popularity and a diverse selection of apps. The continuous upgrading of information technology has also enabled smartphones to display great potential in the field of health care. OBJECTIVE: We aimed to determine the future research direction of mobile health (mHealth) by analyzing its research trends and latest research hotspots. METHODS: This study collected mHealth-related literature published between 2000 and 2020 from the Web of Science database. Descriptive statistics of publication trends of mHealth research were determined by analyzing the annual number of publications in the literature and annual number of publications by country. We constructed visualization network maps of country (or regional) collaborations and author-provided keyword co-occurrences, as well as overlay visualization maps of the average publication year of author-provided keywords to analyze the hotspots and research trends in mHealth research. RESULTS: In total, 12,593 mHealth-related research papers published between 2000 and 2020 were found. The results showed an exponential growth trend in the number of annual publications in mHealth literature. JMIR mHealth and uHealth, the Journal of Medical Internet Research, and JMIR Research Protocols were the 3 top journals with respect to number of publications. The United States remained the leading contributor to the literature in this area (5294/12,593, 42.0%), well ahead of other countries and regions. Other countries and regions also showed a clear trend of annual increases in the number of mHealth publications. The 4 countries with the largest number of publications-the United States, the United Kingdom, Canada, and Australia-were found to cooperate more closely. The rest of the countries and regions showed a clear geographic pattern of cooperation. The keyword co-occurrence analysis of the top 100 authors demonstrated 5 clusters, namely, development of mHealth medical technology and its application to various diseases, use of mHealth technology to improve basic public health and health policy, mHealth self-health testing and management in daily life, adolescent use of mHealth, and mHealth in mental health. The research trends revealed a gradual shift in mHealth research from health policy and improving public health care to the development and social application of mHealth technologies. CONCLUSIONS: To the best of our knowledge, the most current bibliometric analysis dates back to 2016. However, the number of mHealth research published between 2017 and 2020 exceeds the previous total. The results of this study shed light on the latest hotspots and trends in mHealth research. These findings provide a useful overview of the development of the field; they may also serve as a valuable reference and provide guidance for researchers in the digital health field.

Chitosan-coated hydroxyapatite and drug-loaded polytrimethylene carbonate/polylactic acid scaffold for enhancing bone regeneration.

Biocompatible polymers and drug-delivery scaffolds have driven development in bone regeneration. In this study, we fabricated a chitosan (CS)-coated polytrimethylene carbonate (PTMC)/polylactic acid (PLLA)/oleic acid-modified hydroxyapatite (OA-HA)/vancomycin hydrochloride (VH) microsphere scaffold for drug release with excellent biocompatibility. The incorporation of PLLA, OA-HA, and VH into PTMC microspheres not only slowed the biodegradability of the scaffold but also enhanced its mechanical properties and surface properties. Moreover, the CS coating stimulated extensive adhesion of osteoblasts before OA-HA incorporation, which facilitated the controlled release of OA-HA. The scaffolds were characterized via scanning electron microscopy, in vitro comprehensive performance testing, cell culturing, and microcomputer tomography scanning. The results indicated that the surface of the composite microsphere scaffold was suitable for osteoblast adhesion. Additionally, the release of OA-HA stimulated osteogenic proliferation. Our findings suggest that the CS-PTMC/PLLA/OA-HA/VH microsphere scaffold is promising for bone tissue engineering applications.

Pollution status and ecological risk of heavy metals in the soils of five land-use types in a typical sewage irrigation area, eastern China.

Sewage irrigation has been widespread in the water shortage area of eastern China and inevitably tends to result in heavy metal accumulation in soils. A total of 148 surface soil samples from five land-use types were collected in Longkou, a typical sewage irrigation area of China, and As, Cd, Cu, Pb, and Zn concentrations were determined. The Nemerow index method and improved fuzzy comprehensive evaluation method were used to examine the pollution status of heavy metals. The potential ecological risk was evaluated by the Hakanson model by adjusting the assessment threshold, and its spatial distribution was interpolated using geostatistical techniques. As, Cd, Cu, Pb, and Zn accumulated in different amounts in the five land-use types. Urban industrial land and mining land were moderately polluted, irrigated land was slightly polluted, orchards were minimally polluted, and bare land was at a safe level of pollution. Cd exhibited high percentages of strong and severe levels of potential ecological risks. For Cd, irrigated land, orchard, and bare land mainly presented moderate risks, whereas urban industrial land and mining land mainly presented high risks. The comprehensive ecological risk of the five heavy metals was at a severe level for all tested land-use classes except for bare land.