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BackgroundEffective treatment of hypertension requires careful self-management. With the ongoing development of mobile technologies and the scarcity of health care resources, mobile health (mHealth)–based self-management has become a useful treatment for hypertension, and its effectiveness has been assessed in many trials. However, there is a paucity of comprehensive summaries of the studies using both qualitative and quantitative methods. ObjectiveThis systematic review aimed to measure the effectiveness of mHealth in improving the self-management of hypertension for adults. The outcome measures were blood pressure (BP), BP control, medication adherence, self-management behavior, and costs. MethodsA systematic search was conducted using 5 electronic databases. The snowballing method was used to scan the reference lists of relevant studies. Only peer-reviewed randomized controlled trials (RCTs) published between January 2010 and September 2019 were included. Data extraction and quality assessment were performed by 3 researchers independently, adhering to the validation guideline and checklist. Both a meta-analysis and a narrative synthesis were carried out. ResultsA total of 24 studies with 8933 participants were included. Of these, 23 studies reported the clinical outcome of BP, 12 of these provided systolic blood pressure (SBP) and diastolic blood pressure (DBP) data, and 16 articles focused on change in self-management behavior and medication adherence. All 24 studies were included in the narrative synthesis. According to the meta-analysis, a greater reduction in both SBP and DBP was observed in the mHealth intervention groups compared with control groups, −3.78 mm Hg (P

Abstract Coral reconstruction often serves as a major proxy of high-resolution sea surface temperature (SST) variability beyond the instrumental era. However, coral reconstructions are sparse and are usually studied for interannual variability, with few studies on the monthly features. In this study, we reconstruct the monthly SST spatial field by applying the paleoclimate data assimilation method to the coral records of the latest CoralHydro2k data set for the instrument period of 1880–2000. A comparison with observed SST variability shows that our assimilated tropical SST variability performs reasonably well for the seasonal cycle and monthly ENSO characteristics, notably the phase-locking and onset timing, and more realistic spatial fields relative to the model simulations. This study suggests the feasibility of applying paleoclimate data assimilation to reconstruct the monthly SST in the historical period.

Abstract The coherent continental-wide speleothem water isotope records are accompanied by regionally inconsistent moisture patterns within the Asian summer monsoon (ASM) region, leaving a disputed explanation of monsoonal hydroclimate variability at the orbital timescale. Here, the transient simulation forced by orbital parameters during the past 300,000 years in an isotope-enabled fully coupled model shows that the complex ASM response can be understood as a grand dipole pattern of oxygen isotope and rainfall between South Asia and Japan, with South China lying in a hybrid transition region. While the dipole monsoon rainfall change between South Asia and Japan is related to the large-scale circulation adjustment in response to Northern Hemisphere summer insolation, the dipole oxygen isotope pattern is associated with the changing contribution of moisture sources. Our results provide new clues to reconcile ASM hydroclimate patterns at orbital timescale as revealed by the water isotope records and other hydrological proxies.

Abstract Upwelling-induced productivity in the Arabian Sea infers an out-of-phase relation between the Indian summer monsoon and Northern Hemisphere summer insolation at the precession band but an in-phase relation at the obliquity band. These records contrast speleothem oxygen records showing an in-phase relation between the monsoon and summer insolation in two bands, leaving the driving mechanism for the Indian summer monsoon still unknown. Here we use an isotope-enabled Community Earth System Model, showing that the Indian summer monsoon rainfall and water isotopes respond directly to Northern Hemisphere summer insolation in two bands. This contrasts with the Arabian Sea upwelling which is weakened at precessional minimum but strengthened at obliquity maximum by a stronger northward shift of the monsoon wind due to the stronger summer insolation at precessional minimum compared with obliquity maximum. This paper resolves the longstanding question, supporting the Northern Hemisphere-driving mechanism for the Indian summer monsoon at orbital timescale.

Abstract Background Acute ankle injuries are commonly seen in emergency rooms, with significant social impact and potentially devastating consequences. While several clinical practice guidelines (CPGs) related to ankle injuries have been developed by various organizations, there is a lack of critical appraisal of them. The purpose of this systematic review is to identify and critically appraise evidence-based clinical practice guidelines (EB-CPGs) related to acute ankle injuries in adults. Method We conducted searches in the Cochrane Library, MEDLINE, EMBASE databases, WHO, and reviewed 98 worldwide orthopedic association websites up until early 2023. Two authors independently applied the inclusion and exclusion criteria, and each evidence-based clinical practice guideline (EB-CPG) underwent independent critical appraisal of its content by all four authors using the Appraisal of Guidelines for REsearch and Evaluation (AGREE II) instrument. AGREE II scores for each domain were then calculated. Results This review included five evidence-based clinical practice guidelines. The mean scores for all six domains were as follows: Scope and Purpose (87.8%), Stakeholder Involvement (69.2%), Rigour of Development (72.5%), Clarity of Presentation (86.9%), Applicability (45.6%), and Editorial Independence (53.3%). Conclusion The number of EB-CPGs related to ankle injuries are limited and the overall quality of the existing evidence-based clinical practice guidelines (EB-CPGs) for ankle injuries is not strong, with three of them being outdated. However, valuable guidance related to Ottawa rules, manual therapy, cryotherapy, functional supports, early ambulation, and rehabilitation has been highlighted. Challenges remain in areas such as monitoring and/or auditing criteria, consideration of the target population’s views and preferences, and ensuring editorial independence. Future guidelines should prioritize improvements in these domains to enhance the quality and relevance of ankle injury management. Systematic review Systematic review.

Abstract Background Hypercoagulability emerges as a central pathological feature and clinical complication in nephrotic syndrome. Increased platelet activation and aggregability are closely related to hypercoagulability in nephrotic syndrome. Monocyte-platelet aggregates (MPAs) have been proposed to represent a robust biomarker of platelet activation. The aim of this study was to investigate levels of the circulating MPAs and MPAs with the different monocyte subsets to evaluate the association of MPAs with hypercoagulability in nephrotic syndrome. Methods Thirty-two patients with nephrotic syndrome were enrolled. In addition, thirty-two healthy age and sex matched adult volunteers served as healthy controls. MPAs were identified by CD14 monocytes positive for CD41a platelets. The classical (CD14 + + CD16-, CM), the intermediate (CD14 + + CD16+, IM) and the non-classical (CD14 + CD16++, NCM) monocytes, as well as subset specific MPAs, were measured by flow cytometry. Results Patients with nephrotic syndrome showed a higher percentage of circulating MPAs as compared with healthy controls (p

Abstract Future projections indicate that Indian Summer Monsoon Rainfall (ISMR) faces a “wetter and more variable” climate. However, the reasons remain uncertain. The Last Interglacial (LIG) climate provides a potential analog for future warming. Investigating ISMR responses to these two warming scenarios could help understand the causes of ISMR changes. Using PMIP4 simulations, we find that ISMR became “wetter and more stable” during the LIG, contrasting the future climate. The opposing changes in ISMR variability are related to divergent changes in the El Niño‐Southern Oscillation (ENSO) amplitudes, ENSO‐ISMR relationships, and ENSO‐induced large‐scale atmospheric circulation anomalies. During the LIG, orbital forcing weakened ENSO variability and its impacts on ISMR. A westward positioning of ENSO shifted the atmospheric circulation anomalies westward, suppressing extreme ISMR anomalies. These processes are supported by atmospheric model simulations. Our results suggest that different warming patterns (dynamic effects) are more critical than moisture‐increasing effects in controlling regional climate variability.

With the rapid development of the national economy, power security is very important for the security of the country and people's happiness. Electricity is an important energy source for a country. Even if the power system malfunctions for a short period of time, it would cause incalculable losses to social production and people's lives. Among them, one of the most important reasons for power system faults is the occurrence of power line faults, so diagnosing faulty lines has great research significance. On the basis of analyzing the structure and working principle of the deep learning model convolutional neural network (CNN), this article used the CNN model to diagnose faults in power lines and analyzed the simulation results. It was found that different CNN structures have different fault diagnosis accuracy for power lines. The fewer the number of batches in the network structure and the more the number of training sessions, the higher its fault determination accuracy. In the power line fault diagnosis based on three deep learning algorithms, the CNN has the highest stable fault diagnosis accuracy of 100%; the recursive neural network has the second stable fault diagnosis accuracy of 93.4%; the deep belief network has the lowest stable fault diagnosis accuracy of 91.5%. In the comparison of power line fault diagnosis stability, the accuracy standard deviation of CNN is close to 0, and they are also the most stable in power circuit fault diagnosis. The stability of algorithmic recurrent neural networks is between the two, and the accuracy standard deviation of deep belief networks is 1.84% when trained 12 times. Their fault diagnosis stability is also the worst.

Abstract For Paleoclimate data assimilation (PDA), a hybrid gain analog offline ensemble Kalman filter (HGAOEnKF) is proposed. It keeps the benefits of the analog offline ensemble Kalman filter (AOEnKF) that constructs analog ensembles from existing climate simulations with joint information of the proxies. The analog ensembles can provide more accurate prior ensemble mean and “flow‐dependent” error covariances than randomly sampled ensembles. HGAOEnKF further incorporates the benefits of static prior error covariances that better capture large‐scale error correlations and mitigate sampling errors than the sample prior error covariances, through a hybrid gain approach within an ensemble framework. Observing system simulation experiments are conducted for various data assimilation methods, using ensemble simulations from the Community Earth System Model‐Last Millennium Ensemble Project. Results show that using the static prior error covariances estimated from a sufficiently large sample set is beneficial for the traditional offline ensemble Kalman filter (OEnKF) and AOEnKF. HGAOEnKF method is superior to the OEnKF and AOEnKF with and without static prior error covariances, especially for the reconstruction of extreme events. The advantages of HGAOEnKF over OEnKF and AOEnKF with and without static prior error covariances are persistent with varying sample sizes and presence of model errors.