A Study of Social Chatbots Affordances Mitigating Loneliness

Loneliness is a significant concern and is linked to negative health outcomes such as depression and anxiety. Chatbots are gaining attention as potential companions to militate against loneliness. However, IS studies on the effects of human-AI relationships on mental wellness are limited, leaving unclear what enables humans to find companionship and intimate relationships with chatbots, and under what conditions human-chatbot interaction can alleviate loneliness. This study aims to develop a model of how chatbots alleviate loneliness and test it using a longitudinal study. Specifically, this research argues that shared identity affordance and social support affordance help mitigate loneliness directly and indirectly through enhanced intimacy feeling. The effects of chatbots’ affordances on loneliness and intimacy depend on users’ emotion regulation beliefs. Upon successful completion, this research has the potential to offer insight into the design of chatbots and how to leverage AI for social good

Tackling the Non-IID Issue in Heterogeneous Federated Learning by Gradient Harmonization

Federated learning (FL) is a privacy-preserving paradigm for collaboratively training a global model from decentralized clients. However, the performance of FL is hindered by non-independent and identically distributed (non-IID) data and device heterogeneity. In this work, we revisit this key challenge through the lens of gradient conflicts on the server side. Specifically, we first investigate the gradient conflict phenomenon among multiple clients and reveal that stronger heterogeneity leads to more severe gradient conflicts. To tackle this issue, we propose FedGH, a simple yet effective method that mitigates local drifts through Gradient Harmonization. This technique projects one gradient vector onto the orthogonal plane of the other within conflicting client pairs. Extensive experiments demonstrate that FedGH consistently enhances multiple state-of-the-art FL baselines across diverse benchmarks and non-IID scenarios. Notably, FedGH yields more significant improvements in scenarios with stronger heterogeneity. As a plug-and-play module, FedGH can be seamlessly integrated into any FL framework without requiring hyperparameter tuning

Comprehensive Evaluation of Fruit Quality of Actinidia arguta Based on Principal Component Analysis and Cluster Analysis

In order to scientifically evaluate the fruit quality of different Actinidia arguta varieties and establish the quality evaluation system, 10 Actinidia arguta varieties were used as experimental materials, and the indexes of fruit appearance quality and nutritional quality were measured and compared under edible conditions. The fruit quality of Actinidia arguta was comprehensively evaluated by correlation analysis, principal component analysis and cluster analysis. The results showed that the quality indexes of different varieties of Actinidia arguta were different and correlated. The difference of the content of Vitamin C was largest, and the coefficient of variation was 53.08%. The difference of fruit color brightness (L* value) was the smallest, and the coefficient of variation was 6.04%. By principal component analysis, 18 quality indicators were simplified into 6 principal components, and the cumulative variance contribution rate was 90.571%, which could reflect most of the information of the original quality indexes. The comprehensive scores of quality indexes of 10 Actinidia arguta varieties were ranked as ‘Longcheng No.2’, ‘Kuilü’, ‘Jialü’, ‘Wanlü’, ‘Tianxinbao’, ‘Lübao’, ‘Xinlü’, ‘Cuiyu’, ‘Fenglü’ and ‘Pingllü’. According to cluster analysis, 10 Actinidia arguta varieties were divided into five categories, among which ‘Longcheng No.2’ and ‘Kuilü’ in the first category had better comprehensive quality traits. The study provided a reference for the variety breeding, planting, extension and rational processing and utilization of Actinidia arguta

Visualization balloon occlusion-assisted technique in the treatment of large or giant paraclinoid aneurysms: A study of 17 cases series

ObjectiveAlthough balloon-assisted techniques are valuable in aneurysm clipping, repeated angiography and fluoroscopy are required to understand the location and shape of the balloon. This study investigated the value of visualization balloon occlusion-assisted techniques in aneurysm hybridization procedures.MethodsWe propose a visualization balloon technique that injects methylene blue into the balloon, allowing it to be well visualized under a microscope without repeated angiography. This study retrospects the medical records of 17 large or giant paraclinoid aneurysms treated by a visualization balloon occlusion-assisted technique in a hybrid operating room. Intraoperative surgical techniques, postoperative complications, and immediate and long-term angiographic findings are highlighted.ResultsAll 17 patients had safe and successful aneurysm clipping surgery with complete angiographic occlusion. Under the microscope, the balloon injected with methylene blue is visible through the arterial wall. The position and shape of the balloon can be monitored in real time without repeated angiography and fluoroscopic guidance. Two cases of intraoperative visualization balloon shift and slip into the aneurysm cavity were detected in time, and there were no cases of balloon misclipping or difficult removal. Of 17 patients, four patients (23.5%) experienced short-term complications, including pulmonary infection (11.8%), abducens nerve paralysis (5.9%), and thalamus hemorrhage (5.9%). The rate of vision recovery among patients with previous visual deficits was 70% (7 of 10 patients). The mean follow-up duration was 32.76 months. No aneurysms or neurological deficits recurred among all patients who completed the follow-up.ConclusionOur study indicates that microsurgical clipping with the visualization balloon occlusion-assisted technique seems to be a safe and effective method for patients with large or giant paraclinoid aneurysms to reduce the surgical difficulty and simplify the operation process of microsurgical treatment alone

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Extinction and Ergodic Stationary Distribution of COVID-19 Epidemic Model with Vaccination Effects

Human society always wants a safe environment from pollution and infectious diseases, such as COVID-19, etc. To control COVID-19, we have started the big effort for the discovery of a vaccination of COVID-19. Several biological problems have the aspects of symmetry, and this theory has many applications in explaining the dynamics of biological models. In this research article, we developed the stochastic COVID-19 mathematical model, along with the inclusion of a vaccination term, and studied the dynamics of the disease through the theory of symmetric dynamics and ergodic stationary distribution. The basic reproduction number is evaluated using the equilibrium points of the proposed model. For well-posedness, we also test the given problem for the existence and uniqueness of a non-negative solution. The necessary conditions for eradicating the disease are also analyzed along with the stationary distribution of the proposed model. For the verification of the obtained result, simulations of the model are performed

Extinction and Ergodic Stationary Distribution of COVID-19 Epidemic Model with Vaccination Effects

Human society always wants a safe environment from pollution and infectious diseases, such as COVID-19, etc. To control COVID-19, we have started the big effort for the discovery of a vaccination of COVID-19. Several biological problems have the aspects of symmetry, and this theory has many applications in explaining the dynamics of biological models. In this research article, we developed the stochastic COVID-19 mathematical model, along with the inclusion of a vaccination term, and studied the dynamics of the disease through the theory of symmetric dynamics and ergodic stationary distribution. The basic reproduction number is evaluated using the equilibrium points of the proposed model. For well-posedness, we also test the given problem for the existence and uniqueness of a non-negative solution. The necessary conditions for eradicating the disease are also analyzed along with the stationary distribution of the proposed model. For the verification of the obtained result, simulations of the model are performed