Self-management education interventions for persons with schizophrenia: a meta-analysis

Although self-management education programs for persons with schizophrenia are being developed and advocated, uncertainty about their overall effectiveness remains. The purpose of this meta-analysis was to examine outcomes of self-management education interventions in persons with schizophrenia. Six electronic databases were searched. Manual searches were conducted of the reference lists of the identified studies and major psychiatric journals. Randomized controlled trials of self-management education interventions aimed at reducing relapse and hospital readmissions, as well as improving symptoms, psychosocial functioning, and adherence to medication treatment were identified. Data were extracted and the quality of included studies were rated by two authors independently. Finally, 13 studies with 1404 patients were included. Self-management education interventions were associated with a significant reduction of relapse events and re-hospitalizations. Patients who received self-management education were more likely to improve adherence to medication and symptoms compared to patients receiving other care. However, a benefit on psychosocial functioning was not confirmed in the current meta-analysis. The study concludes that self-management education intervention is a feasible and effective method for persons with schizophrenia and should be routinely offered to all persons with schizophrenia

Environmental effects on satellite galaxies from the perspective of cold gas

Environment plays a pivotal role in shaping the evolution of satellite galaxies. Analyzing the properties related to the cold gas phase of satellites provides insights into unravelling the complexity of environmental effects. We use the hydro-dynamical simulations Illustris TNG and Eagle, and the semi-analytic models (SAMs) GAEA and L-Galaxies, in comparison with recent observations from the Westerbork Synthesis Radio Telescope (WSRT), to investigate the properties of satellite galaxies hosted by halos with mass $M_{200}>10^{12.8}M_\odot$, and within projected regions $\le 1.1$ virial radius $R_{200}$. Generally, satellite galaxies selected from semi-analytic models have more HI than those selected from hydro-dynamical simulations across all projected radii, e.g. more than 30% of satellites in the two hydro-simulations are HI depleted, while this fraction is almost zero in SAMs. Furthermore, both hydro-dynamical simulations and SAMs reproduce the observed decrease of HI content and specific star-formation rate (sSFR) towards the halo centre. However, the trend is steeper in two hydro-dynamical simulations TNG and EAGLE, resulting in a better agreement with the observational data, especially in more massive halos. By comparing the two version of GAEA, we find that the inclusion of ram-pressure stripping of cold gas significantly improves the predictions on HI fractions. The refined hot gas stripping method employed in one of the two L-Galaxies models also yields improved results.Comment: 13 pages, 8 figures, 2 table. Accepted by MNRA

Modeling and identification of a class of servomechanism systems with stick-slip friction

This paper describes a technique for modeling and identifying a class of nonlinear servomechanism systems with stick-slip friction. The physics of the stick-slip friction is considered in modeling the process. Identification of the system parameters is formulated as a nonlinear optimization problem. A modified simplex algorithm is pro- I Introduction When operating with small amplitude and low frequency signal input, the presence of stick-slip friction in a servomechanism cannot be ignored. To accurately predict or simulate the performance of the system, the effects of friction on the motor behavior should be taken into consideration by appropriate modeling of the friction. This paper describes a modeling and identification technique for a class of servomechanism systems with stick-slip friction. In the paper [1], Karnopp presented a novel model for describing the effect of stick-slip friction in mechanical dynamic systems. The model proposed by Karnopp takes the physics of the stick-slip friction process into account by considering the rate of change of momentum in the mechanical system. The main parameters in the model include the inertia of the system, the slip coefficient, the threshold for the momentum rate and the saturation stick force. The stick-slip friction model of Karnopp is adapted to a class of servomechanism in this paper. For the present discussion, the dc servomotor is considered. The proposed adaptation can be extended to other classes of servomechanisms. This paper next addresses an identification technique and the choice of input signals for estimating the parameters associated with the nonlinear stick-slip model. The identification problem is posed as an optimization problem to be solved using nonlinear programming methods II Modeling A typical armature-controlled dc motor is shown in 324/Vol. 110, SEPTEMBER 1988 The schematic block diagram for the system is given in The friction torque T f consists of two components, r s i ip and r stick . In the slip region where \6 m \>Dj, the switching Rm Lrr Transactions of the AS M

GastroBot: a Chinese gastrointestinal disease chatbot based on the retrieval-augmented generation

IntroductionLarge Language Models (LLMs) play a crucial role in clinical information processing, showcasing robust generalization across diverse language tasks. However, existing LLMs, despite their significance, lack optimization for clinical applications, presenting challenges in terms of illusions and interpretability. The Retrieval-Augmented Generation (RAG) model addresses these issues by providing sources for answer generation, thereby reducing errors. This study explores the application of RAG technology in clinical gastroenterology to enhance knowledge generation on gastrointestinal diseases.MethodsWe fine-tuned the embedding model using a corpus consisting of 25 guidelines on gastrointestinal diseases. The fine-tuned model exhibited an 18% improvement in hit rate compared to its base model, gte-base-zh. Moreover, it outperformed OpenAI’s Embedding model by 20%. Employing the RAG framework with the llama-index, we developed a Chinese gastroenterology chatbot named “GastroBot,” which significantly improves answer accuracy and contextual relevance, minimizing errors and the risk of disseminating misleading information.ResultsWhen evaluating GastroBot using the RAGAS framework, we observed a context recall rate of 95%. The faithfulness to the source, stands at 93.73%. The relevance of answers exhibits a strong correlation, reaching 92.28%. These findings highlight the effectiveness of GastroBot in providing accurate and contextually relevant information about gastrointestinal diseases. During manual assessment of GastroBot, in comparison with other models, our GastroBot model delivers a substantial amount of valuable knowledge while ensuring the completeness and consistency of the results.DiscussionResearch findings suggest that incorporating the RAG method into clinical gastroenterology can enhance the accuracy and reliability of large language models. Serving as a practical implementation of this method, GastroBot has demonstrated significant enhancements in contextual comprehension and response quality. Continued exploration and refinement of the model are poised to drive forward clinical information processing and decision support in the gastroenterology field

Chloride Binding Mechanism in Seawater-Mixed UHPC

The rapid development of marine concrete structures and the sharp shortage of freshwater resources contribute to the wide investigation of seawater-mixed ultra-high-performance concrete (swuhpc). However, few studies have investigated the chloride ions (cl-) binding mechanism of swuhpc. Herein, the chloride binding experiments and molecular dynamics (md) simulation were carried out to reveal the physically and chemically bound cl- mechanisms of swuhpc. The results of the experiments clearly demonstrate that the addition of silica fume (sf) led to a significant decrease in the capacity of cl- binding. Conversely, the incorporation of metakaolin (mk) resulted in a marked increase in the content of chemically bound cl-. Furthermore, it is revealed through md simulations that the amount of physically bound cl- heavily depends on the ca/si ratio of c-s-h. A higher ca/si ratio results in a stronger electrostatic effect of the c-s-h surface on cl-, which increases the physical binding of cl- via ca-cl bonds. In addition, it is found that al[6] and ca in the interlayer region of c-a-s-h formed the main structure layer (ca4al2(oh)122+) of friedel\u27s salt, and then chemically adsorbed cl- in the pore solution. These findings provide novel nanoscale insights regarding the physically and chemically bound cl- mechanisms of swuhpc

Framework to Create Cloud-Free Remote Sensing Data Using Passenger Aircraft as the Platform

Cloud removal in optical remote sensing imagery is essential for many Earth observation applications.Due to the inherent imaging geometry features in satellite remote sensing, it is impossible to observe the ground under the clouds directly; therefore, cloud removal algorithms are always not perfect owing to the loss of ground truth. Passenger aircraft have the advantages of short visitation frequency and low cost. Additionally, because passenger aircraft fly at lower altitudes compared to satellites, they can observe the ground under the clouds at an oblique viewing angle. In this study, we examine the possibility of creating cloud-free remote sensing data by stacking multi-angle images captured by passenger aircraft. To accomplish this, a processing framework is proposed, which includes four main steps: 1) multi-angle image acquisition from passenger aircraft, 2) cloud detection based on deep learning semantic segmentation models, 3) cloud removal by image stacking, and 4) image quality enhancement via haze removal. This method is intended to remove cloud contamination without the requirements of reference images and pre-determination of cloud types. The proposed method was tested in multiple case studies, wherein the resultant cloud- and haze-free orthophotos were visualized and quantitatively analyzed in various land cover type scenes. The results of the case studies demonstrated that the proposed method could generate high quality, cloud-free orthophotos. Therefore, we conclude that this framework has great potential for creating cloud-free remote sensing images when the cloud removal of satellite imagery is difficult or inaccurate

Advances in biological activities of rape bee pollen and its development and utilization

The research and development value of rape bee pollen, a natural health raw material, is increasing as public awareness of health issues develops. This review introduced the various nutrients and active substances contained in rape bee pollen and summarized the biological activities and pharmacological effects of rape bee pollen in antioxidant, anti-inflammatory, immune enhancement, antibacterial, prostate protection, anti-diabetic complications, anti-tumor, intestinal regulation, and ovarian protection. The application of rapeseed bee pollen in bee products, health care products, food, medicine and cosmetics was discussed. The development direction of rapeseed bee pollen was prospected

Safety and immunogenicity of a modified Omicron-adapted inactivated vaccine in healthy adults: a randomized, double-blind, active-controlled Phase III clinical trial

BackgroundUpdated vaccine strategies are needed to protect against new SARS-CoV-2 variants with increased immune escape. Here, information on the safety and immunogenicity of an inactivated Omicron-adapted vaccine is presented, as compared with CoronaVac.MethodsA randomized, double-blind, active-controlled, phase III clinical trial was conducted to compare a modified Omicron-adapted vaccine (Omicron vaccine) with the authorized prototype vaccine (CoronaVac®) as a booster dose. Healthy adults aged ≥18 years, who have previously received 2 or 3 doses of CoronaVac (2C or 3C cohort) at least 6 months before, were enrolled to get a booster dose of Omicron vaccine or CoronaVac in a ratio of 2:1 (2C/3C+1O/1C). Back-up serums after two initial doses of CoronaVac (2C+0) for adults aged 26-45 years were collected from a previous study. Immunogenicity and safety data at 28 days after vaccination were collected and analyzed. One of the primary objectives was to evaluate the superiority of immunogenicity of Omicron vaccine booster against Omicron BA.1, compared with CoronaVac booster against BA.1. Another objective was to evaluate the non-inferiority of immunogenicity of Omicron vaccine booster against BA.1, compared with two initial doses of CoronaVac against ancestral strain.ResultsBetween June 1st and July 21st, 2022, a total of 1,500 healthy adults were enrolled. Results show that all pre-specified superiority criteria for BA.1 neutralizing antibody were met. Specifically, within the 3C cohort (3C+1O vs. 3C+1C), the geometric mean titers’ (GMT) ratio and 95% confidence interval (CI) was 1.64 (1.42, 1.89), with the lower 95%CI ≥1; a GMT ratio of 1.84 (1.57, 2.16) was observed for 2C+1O versus 3C+1C. For seroconversion rate, the lower 95%CIs of differences between immuno-comparative groups (2/3C+1O vs. 3C+1C) were all above the superiority criterion 0%. However, the non-inferiority criterion of the lower 95%CI of GMT ratio ≥2/3 was unfulfilled for 2C/3C+1O against BA.1 versus 2C+0 against ancestral strain. Safety profiles were similar between groups, with no safety concerns identified.ConclusionThe Omicron-adapted vaccine was well-tolerated and could elicit superior immune responses as compared with CoronaVac against Omicron, while it appeared inferior to CoronaVac against ancestral strain.Clinical trial registrationhttps://classic.clinicaltrials.gov/ct2/show/NCT05381350?term=NCT05381350&draw=2&rank=1, identifier NCT05381350