Simple and Efficient Synthesis of Novel Tetramers with Enhanced Glass Transition Temperature for High-Performance and Stable Organic Solar Cells.

Oligomer acceptors in organic solar cells (OSCs) have garnered substantial attention owing to their impressive power conversion efficiency (PCE) and long-term stability. However, the simple and efficient synthesis of oligomer acceptors with higher glass transition temperatures (Tg ) remains a formidable challenge. In this study, we propose an innovative strategy for the synthesis of tetramers, denoted as Tet-n, with elevated Tg s, achieved through only two consecutive Stille coupling reactions. Importantly, our strategy significantly reduces the redundancy in reaction steps compared to conventional methods for linear tetramer synthesis, thereby improving both reaction efficiency and yield. Furthermore, the OSC based on PM6:Tet-1 attains a high PCE of 17.32 %, and the PM6:L8-BO:Tet-1 ternary device achieves an even more higher PCE of 19.31 %. Remarkably, the binary device based on the Tet-1 tetramer demonstrates outstanding operational stability, retaining 80 % of the initial efficiency (T80 ) even after 1706 h of continuous illumination, which is primarily attributed to the enhanced Tg (247 °C) and lower diffusion coefficient (1.56×10-27  cm2 s-1 ). This work demonstrates the effectiveness of our proposed approach in the straightforward and efficient synthesis of tetramers materials with higher Tg s, thus offering a viable pathway for developing high-efficiency and stable OSCs.

Directly Cross-Linked Conjugated Polymer Donor Enables Efficient Polymer Solar Cells with Extraordinary Mechanical Robustness.

A cross-linking strategy can result in a three-dimensional network of interconnected chains for the copolymers, thereby improving their mechanical performance. In this work, a series of cross-linked conjugated copolymers, named PC2, PC5, and PC8, constructed with different ratios of monomers are designed and synthesized. For comparison, a random linear copolymer, PR2 is also synthesized based on the similar monomers. When blended with Y6 acceptor, the cross-linked polymers PC2, PC5, and PC8-based polymer solar cells (PSCs) achieve superior power conversion efficiencies (PCEs) of 17.58%, 17.02%, and 16.12%, respectively, which are higher than that (15.84%) of the random copolymer PR2-based devices. Moreover, the PCE of PC2:Y6-based flexible PSC retains ≈88% of the initial efficiency value after 2000 bending cycles, overwhelming the PR2:Y6-based device with the remaining 12.8% of the initial PCE. These results demonstrate that the cross-linking strategy is a feasible and facile approach to developing high-performance polymer donors for the fabrication of flexible PSCs.

Gender Differences in the Nonspecific and Health-Specific Use of Social Media Before and During the COVID-19 Pandemic: Trend Analysis Using HINTS 2017-2020 Data.

The use of social media has changed since the outbreak of coronavirus disease 2019 (COVID-19). However, little is known about the gender disparity in social media use for nonspecific and health-specific issues before and during the COVID-19 pandemic. Based on a gender difference perspective, this study aimed to examine how the nonspecific and health-specific uses of social media changed in 2017-2020. The data came from the Health Information National Trends Survey Wave 5 Cycle 1-4. This study included 10,426 participants with complete data. Compared to 2017, there were higher levels of general use in 2019 and 2020, and an increased likelihood of health-related use in 2020 was reported among the general population. Female participants were more likely to be nonspecific and health-specific users than males. Moreover, the relationship of gender with general use increased in 2019 and 2020; however, concerning health-related use, it expanded in 2019 but narrowed in 2020. The COVID-19 global pandemic led to increased use of social media, especially for health-related issues among males. These findings further our understanding of the gender gap in health communication through social media, and contribute to targeted messaging to promote health and reduce disparities between different groups during the pandemic.

Association Between Social Media Use and Cancer Screening Awareness and Behavior for People Without a Cancer Diagnosis: Matched Cohort Study.

BACKGROUND: The use of social media in communications regarding cancer prevention is rapidly growing. However, less is known about the general population's social media use related to cancer screening awareness and behavior for different cancers. OBJECTIVE: We aimed to examine the relationship between social media use and cancer screening awareness and behavior among people without a cancer diagnosis. METHODS: Data were collected from the Health Information National Trends Survey 5 Cycle 1 to 3 in the United States (n=12,227). Our study included 10,124 participants without a cancer diagnosis and 3 measures of screening awareness (those who had heard of hepatitis C virus [HCV], human papillomavirus [HPV], and the HPV vaccine) and 4 measures of behavior (those who had prostate-specific antigen tests, Papanicolaou tests for cervical cancer, as well as breast cancer and colon cancer tests). Propensity-score matching was conducted to adjust for the sociodemographic variables between the social media user and nonuser participants. Multivariable logistic regression was used to assess the association of social media use by gender. Jackknife replicate weights were incorporated into the analyses. RESULTS: Of the 3794 matched participants, 1861 (57.6% weighted) were male, and the mean age was 55.5 (SD 0.42) years. Compared to social media nonusers, users were more likely to have heard of HCV (adjusted odds ratio [aOR]=2.27, 95% CI, 1.29-3.98 and aOR=2.86, 95% CI, 1.51-5.40, for male and female users, respectively) and HPV (aOR=1.82, 95% CI, 1.29-2.58 and aOR=2.35, 95% CI, 1.65-3.33, for male and female users, respectively). In addition, female users were more likely to have heard of the HPV vaccine (aOR=2.06, 95% CI, 1.41-3.00). No significant associations were found between social media use and prostate-specific antigen tests in males, Papanicolaou tests and breast cancer tests in females, or colon cancer tests in both male and female users. CONCLUSIONS: While social media services can potentially promote cancer screening awareness in the general population, but they did not improve screening behavior after adjusting for socioeconomic status. These findings strengthened our understanding of social media use in targeting health communications for different cancers.

Erectile Dysfunction Is Not a Predictor of Atrial Fibrillation: A Population-Based Propensity-Score Matched Cohort Study.

INTRODUCTION: Erectile dysfunction (ED) has been regarded a marker of cardiovascular diseases. Nevertheless, the association between ED and incident atrial fibrillation (AF) remains unknown. AIM: To determine the association between ED and incident AF. METHODS: This population-based cohort study was conducted using the National Health Insurance Research Database in Taiwan. In total, 6,273 of patients with ED without a prior diagnosis of AF were enrolled from January 1, 2001 through December 31, 2009, and a propensity-score matching method was used to identify 3,516 patients in the ED and control groups. MAIN OUTCOME MEASURES: Newly incident AF at follow-up was recorded as the end point. RESULTS: The mean age of the study population was 40.0 ± 17.1 years, and the follow-up period was 8.0 ± 0.5 years. Compared with the control group, patients with ED were older and had more of the following comorbidities: D'Hoore Charlson Comorbidity Index, hypertension, congestive heart failure, diabetes mellitus, dyslipidemia, chronic kidney disease, coronary artery disease, stroke, chronic lung disease, major depression disorder, obstructive sleep apnea, and hyperthyroidism. After adjusting for confounders, the ED group was not associated with more incident AF compared with the control group (hazard ratio = 1.031, 95% confidence interval = 0.674-1.578, P =.888). In these patients, ED of an organic origin was associated with a trend of having AF more often compared with ED of a psychosexual type (P =.272 by log-rank test). CONCLUSION: Although ED is known as a predictor of atherosclerotic cardiovascular diseases, it is not independently associated with incident AF in men.

Illness, medical expenditure and household consumption: observations from Taiwan.

BACKGROUND: Illness conditions lead to medical expenditure. Even with various types of medical insurance, there can still be considerable out-of-pocket costs. Medical expenditure can affect other categories of household consumptions. The goal of this study is to provide an updated empirical description of the distributions of illness conditions and medical expenditure and their associations with other categories of household consumptions. METHODS: A phone-call survey was conducted in June and July of 2012. The study was approved by ethics review committees at Xiamen University and FuJen Catholic University. Data was collected using a Computer-Assisted Telephone Survey System (CATSS). "Household" was the unit for data collection and analysis. Univariate and multivariate analyses were conducted, examining the distributions of illness conditions and the associations of illness and medical expenditure with other household consumptions. RESULTS: The presence of chronic disease and inpatient treatment was not significantly associated with household characteristics. The level of per capita medical expenditure was significantly associated with household size, income, and household head occupation. The presence of chronic disease was significantly associated with levels of education, insurance and durable goods consumption. After adjusting for confounders, the associations with education and durable goods consumption remained significant. The presence of inpatient treatment was not associated with consumption levels. In the univariate analysis, medical expenditure was significantly associated with all other consumption categories. After adjusting for confounding effects, the associations between medical expenditure and the actual amount of entertainment expenses and percentages of basic consumption, savings, and insurance (as of total consumption) remained significant. CONCLUSION: This study provided an updated description of the distributions of illness conditions and medical expenditure in Taiwan. The findings were mostly positive in that illness and medical expenditure were not observed to be significantly associated with other consumption categories. This observation differed from those made in some other Asian countries and could be explained by the higher economic status and universal basic health insurance coverage of Taiwan.

Longitudinal Through-Hole Architecture for Efficient and Thickness-Insensitive Semitransparent Organic Solar Cells.

Semi-transparent organic solar cells (ST-OSCs) have great potential for application in vehicle- or building-integrated solar energy harvesting. Ultrathin active layers and electrodes are typically utilized to guarantee high power conversion efficiency (PCE) and high average visible transmittance (AVT) simultaneously; however, such ultrathin parts are unsuitable for industrial high-throughput manufacturing. In this study, ST-OSCs are fabricated using a longitudinal through-hole architecture to achieve functional region division and to eliminate the dependence on ultrathin films. A complete circuit that vertically corresponds to the silver grid is responsible for obtaining high PCE, and the longitudinal through-holes embedded in it allow most of the light to pass through,where the overall transparency is associated with the through-hole specification rather than the thicknesses of active layer and electrode. Excellent photovoltaic performance over a wide range of transparency (9.80-60.03%), with PCEs ranging from 6.04% to 15.34% is achieved. More critically, this architecture allows printable 300-nm-thick devices to achieve a record-breaking light utilization efficiency (LUE) of 3.25%, and enables flexible ST-OSCs to exhibit better flexural endurance by dispersing the extrusion stress into the through-holes. This study paves the way for fabricating high-performance ST-OSCs and shows great promise for the commercialization of organic photovoltaics.

Dental scaling and lower risk of spontaneous intracranial hemorrhage.

Background: -Spontaneous intracranial hemorrhage (ICH) has high fatality while has few proven treatments. We aim at investigating the association between dental scaling (DS) and the risk of ICH. Methods: -In this cohort study, two cohorts were matched by propensity score based on potential confounders. Data from ICH between January 2008 and December 2014 in Taiwan were analyzed. The subjects underwent DS at least 6 times between January 1, 2002, and December 31, 2007, while the matched controls did not undergo any DS during the same period. Cumulative incidences and hazard ratios (HRs) were calculated after adjusting for competing confounders. Results: -Each cohort consisted of 681,126 subjects. Compared with the non-DS cohort, the regular-DS cohort had a significantly lower incidence of ICH (0.8% vs 1.2%; P < 0.0001), and the adjusted hazards ratio (aHR) of 7-year ICH was 0.61 (95% confidence interval, CI, 0.59-0.63; P < 0.0001). The 30-39-year age group of the regular-DS cohort had the lowest HR (0.57; 95% CI, 0.52-0.61; P < 0.0001) of 7-year ICH when compared with similar controls. Compared with the controls, the regular-DS cohort also had significantly lower HR (0.82; 95% CI, 0.81-0.82; P < 0.0001) of 7-year hypertension. Compared with those without DS, the lowest risk of intracerebral hemorrhage was observed in the male participants with regular DS (0.43; 95% CI, 0.40-0.47; P < 0.0001). Conclusions: -Regular DS was consistently associated with lower ICH risk in subjects aged 30-59 years, which may benefit from the decreased HBP risk. DS had a potential role in the prophylaxis for ICH, a condition with a high disability or mortality.

Identifying the predictors of severe psychological distress by auto-machine learning methods.

Social stress in daily life and the COVID-19 pandemic have greatly impacted the mental health of the population. Early detection of a predisposition to severe psychological distress is essential for timely interventions. This paper analyzed 4036 samples participating in the 2019-2020 National Health Information Trends Survey (HINTS) and identified 57 candidate predictors of severe psychological distress based on univariate chi-square and t-test analyses. Five machine learning methods, namely logistic regression (LR), automatic generalized linear models (Auto-GLM), automatic random forests (Auto-Random Forests), automatic deep neural networks (Auto-Deep learning) and automatic gradient boosting machines (Auto-GBM), were employed to model synthetic minority oversampling technique-based (SMOTE) resampled data and identify predictors of severe psychological distress. Predictors were evaluated by odds ratios in logistic models and variable importance in the other models. Forty-seven variables were identified as significant predictors of severe psychological distress, including 13 sociodemographic variables and 34 variables related to individual lifestyle and behavioral habits. Among them, new potentially relevant variables related to an individual's level of concern and trust in cancer information, exposure to health care providers, and cancer screening and awareness are included. The performance of each model was evaluated using five-fold cross-validation. The optimal model performance-wise was Auto-GBM with an accuracy of 89.75%, a precision of 89.68%, a recall of 89.31%, an F1-score of 89.48% and an AUC of 95.57%. Significant predictors of severe psychological distress were identified in this study and the value of machine learning methods in predicting severe psychological distress is demonstrated, thereby enhancing pre-prediction and clinical decision-making of severe psychological distress problems.

Using the H2O Automatic Machine Learning Algorithms to Identify Predictors of Web-Based Medical Record Nonuse Among Patients in a Data-Rich Environment: Mixed Methods Study.

BACKGROUND: With the advent of electronic storage of medical records and the internet, patients can access web-based medical records. This has facilitated doctor-patient communication and built trust between them. However, many patients avoid using web-based medical records despite their greater availability and readability. OBJECTIVE: On the basis of demographic and individual behavioral characteristics, this study explores the predictors of web-based medical record nonuse among patients. METHODS: Data were collected from the National Cancer Institute 2019 to 2020 Health Information National Trends Survey. First, based on the data-rich environment, the chi-square test (categorical variables) and 2-tailed t tests (continuous variables) were performed on the response variables and the variables in the questionnaire. According to the test results, the variables were initially screened, and those that passed the test were selected for subsequent analysis. Second, participants were excluded from the study if any of the initially screened variables were missing. Third, the data obtained were modeled using 5 machine learning algorithms, namely, logistic regression, automatic generalized linear model, automatic random forest, automatic deep neural network, and automatic gradient boosting machine, to identify and investigate factors affecting web-based medical record nonuse. The aforementioned automatic machine learning algorithms were based on the R interface (R Foundation for Statistical Computing) of the H2O (H2O.ai) scalable machine learning platform. Finally, 5-fold cross-validation was adopted for 80% of the data set, which was used as the training data to determine hyperparameters of 5 algorithms, and 20% of the data set was used as the test data for model comparison. RESULTS: Among the 9072 respondents, 5409 (59.62%) had no experience using web-based medical records. Using the 5 algorithms, 29 variables were identified as crucial predictors of nonuse of web-based medical records. These 29 variables comprised 6 (21%) sociodemographic variables (age, BMI, race, marital status, education, and income) and 23 (79%) variables related to individual lifestyles and behavioral habits (such as electronic and internet use, individuals' health status and their level of health concern, etc). H2O's automatic machine learning methods have a high model accuracy. On the basis of the performance of the validation data set, the optimal model was the automatic random forest with the highest area under the curve in the validation set (88.52%) and the test set (82.87%). CONCLUSIONS: When monitoring web-based medical record use trends, research should focus on social factors such as age, education, BMI, and marital status, as well as personal lifestyle and behavioral habits, including smoking, use of electronic devices and the internet, patients' personal health status, and their level of health concern. The use of electronic medical records can be targeted to specific patient groups, allowing more people to benefit from their usefulness.

Heterogeneous Trajectory Classes of Social Engagement and Sex Differences for Older Adults in China.

This study aimed to identify the heterogeneous trajectory classes of social engagement among older adults in China and examine sex differences to determine how sociodemographic characteristics and health status impact these trajectory classes. A sample of 8117 participants aged ≥65 years from the Chinese Longitudinal Healthy Longevity Survey was included. Growth mixture modeling was conducted to estimate the trajectory classes of social engagement. Logistic regression was adopted to analyze the associations between individual characteristics and trajectory classes. Three trajectory classes of social engagement were identified: the high-decline (35.3%), medium-decline (57.6%), and low-increase (7.1%). Men were less likely to be in the medium-decline and low-increase classes than women. Older men benefited from economic factors more than women. Education exhibited a stronger protective effect on the high-decline class for older women. High physical functioning might enable older adults with the lowest initial level of social engagement to make efforts to engage in social activities, which was stronger for older men than women. For both men and women, a proper cognitive state and positive emotions were in favor of social engagement. These findings are valuable for achieving sex equity in social engagement development for healthy and active aging.

Optimized active layer morphology toward efficient and polymer batch insensitive organic solar cells.

Morphology control in laboratory and industry setting remains as a major challenge for organic solar cells (OSCs) due to the difference in film-drying kinetics between spin coating and the printing process. A two-step sequential deposition method is developed to control the active layer morphology. A conjugated polymer that self-assembles into a well-defined fibril structure is used as the first layer, and then a non-fullerene acceptor is introduced into the fibril mesh as the second layer to form an optimal morphology. A benefit of the combined fibril network morphology and non-fullerene acceptor properties was that a high efficiency of 16.5% (certified as 16.1%) was achieved. The preformed fibril network layer and the sequentially deposited non-fullerene acceptor form a robust morphology that is insensitive to the polymer batches, solving a notorious issue in OSCs. Such progress demonstrates that the utilization of polymer fibril networks in a sequential deposition process is a promising approach towards the fabrication of high-efficiency OSCs.

An Optimized Fibril Network Morphology Enables High-Efficiency and Ambient-Stable Polymer Solar Cells.

Morphological stability is crucially important for the long-term stability of polymer solar cells (PSCs). Many high-efficiency PSCs suffer from metastable morphology, resulting in severe device degradation. Here, a series of copolymers is developed by manipulating the content of chlorinated benzodithiophene-4,8-dione (T1-Cl) via a random copolymerization approach. It is found that all the copolymers can self-assemble into a fibril nanostructure in films. By altering the T1-Cl content, the polymer crystallinity and fibril width can be effectively controlled. When blended with several nonfullerene acceptors, such as TTPTT-4F, O-INIC3, EH-INIC3, and Y6, the optimized fibril interpenetrating morphology can not only favor charge transport, but also inhibit the unfavorable molecular diffusion and aggregation in active layers, leading to excellent morphological stability. The work demonstrates the importance of optimization of fibril network morphology in realizing high-efficiency and ambient-stable PSCs, and also provides new insights into the effect of chemical structure on the fibril network morphology and photovoltaic performance of PSCs.

Unraveling the influence of non-fullerene acceptor molecular packing on photovoltaic performance of organic solar cells.

In non-fullerene organic solar cells, the long-range structure ordering induced by end-group π-π stacking of fused-ring non-fullerene acceptors is considered as the critical factor in realizing efficient charge transport and high power conversion efficiency. Here, we demonstrate that side-chain engineering of non-fullerene acceptors could drive the fused-ring backbone assembly from a π-π stacking mode to an intermixed packing mode, and to a non-stacking mode to refine its solid-state properties. Different from the above-mentioned understanding, we find that close atom contacts in a non-stacking mode can form efficient charge transport pathway through close side atom interactions. The intermixed solid-state packing motif in active layers could enable organic solar cells with superior efficiency and reduced non-radiative recombination loss compared with devices based on molecules with the classic end-group π-π stacking mode. Our observations open a new avenue in material design that endows better photovoltaic performance.

Effect of the Energy Offset on the Charge Dynamics in Nonfullerene Organic Solar Cells.

The energy offset, considered as the driving force for charge transfer between organic molecules, has significant effects on both charge separation and charge recombination in organic solar cells. Herein, we designed material systems with gradually shifting energy offsets, including both positive and negative values. Time-resolved spectroscopy was used to monitor the charge dynamics within the bulk heterojunction. It is striking to find that there is still charge transfer and charge generation when the energy offset reached -0.10 eV (ultraviolet photoelectron spectroscopy data). This work not only indicates the feasibility of the free carrier generation and the following charge separation under the condition of a negative offset but also elucidates the relationship between the charge transfer and the energy offset in the case of polymer chlorination.

Multidimensional Health Groups and Healthcare Utilization Among Elderly Chinese: Based on the 2014 CLHLS Dataset.

Based on multidimensional health, we aimed to identify health groups among the elderly Chinese population, and examine its relationship with socio-demographic factors on healthcare utilization. Chinese Longitudinal Healthy Longevity Survey in 2014 was adopted. For 2981 participants aged ≥65 years, without missing any health indicators, latent class analysis was adopted to identify health groups. For 1974 participants with complete information, the two-part model was used to assess how health groups and socio-demographic characteristics influence the outpatient and inpatient expenditure. Four health groups were identified and labeled as "Lacking Socialization" (10.4%), "High Comorbidity" (16.7%), "Severe Disability" (7.8%), and "Relative Health" (65.1%). Compared with the relative health group, the lacking socialization group cost higher inpatient expenditure (p = 0.02). Those in the high comorbidity and severe disability groups were more likely to use healthcare services and cost higher outpatient expenditure (p < 0.01 for all). The effects of socio-demographic factors were also discussed. The findings enhanced our understanding of the heterogeneity of multidimensional health status and complex healthcare demands in the elderly Chinese population. Moreover, it is valuable for improving the allocation of healthcare resource targeted for different groups of the ageing population.

Noninvasive scoring system for significant inflammation related to chronic hepatitis B.

Although a liver stiffness measurement-based model can precisely predict significant intrahepatic inflammation, transient elastography is not commonly available in a primary care center. Additionally, high body mass index and bilirubinemia have notable effects on the accuracy of transient elastography. The present study aimed to create a noninvasive scoring system for the prediction of intrahepatic inflammatory activity related to chronic hepatitis B, without the aid of transient elastography. A total of 396 patients with chronic hepatitis B were enrolled in the present study. Liver biopsies were performed, liver histology was scored using the Scheuer scoring system, and serum markers and liver function were investigated. Inflammatory activity scoring models were constructed for both hepatitis B envelope antigen (+) and hepatitis B envelope antigen (-) patients. The sensitivity, specificity, positive predictive value, negative predictive value, and area under the curve were 86.00%, 84.80%, 62.32%, 95.39%, and 0.9219, respectively, in the hepatitis B envelope antigen (+) group and 91.89%, 89.86%, 70.83%, 97.64%, and 0.9691, respectively, in the hepatitis B envelope antigen (-) group. Significant inflammation related to chronic hepatitis B can be predicted with satisfactory accuracy by using our logistic regression-based scoring system.