Seasonal Variations in the Organization and Structure of Apis cerana cerana Swarm Queen Cells

This paper describes the organization and structure of the swarm queen cells of Apis cerana cerana in spring, summer, and autumn in Kunming, Yunnan Province, China. We measured the following indices to reveal the organization rule of swarm cells: number of swarm cells built by each colony during different seasons; the shortest distance between two adjacent swarm cells on the comb; distance between swarm cell base and bottom bar of movable frame. We revealed the swarm cells structural characteristics using the following indicators: maximum diameter of swarm cell, the length between mouth and bottom of swarm cell, depth between maximum diameter and bottom of swarm cell, and the ratio of maximum diameter to depth between maximum diameter and bottom of swarm cell. Regarding seasonal differences, results indicated a significant variation in the distance between the swarm cell base and the bottom bar of the movable frame. Still, no such effect was observed in the shortest distance between two adjacent swarm cells. The maximum swarm cell diameter was not considerably influenced either, while the distance between the maximum diameter and the bottom of the swarm cell had substantial variation. The detected ratio of the maximum diameter to the depth between the maximum diameter and the bottom of theswarm cell indicated seasonal changes in the bottom shape of the swarm cell. This study clarifies the temporal and spatial distribution and structure of swarm cells of A. c. cerana. It establishes the basis for predicting the time and position of appearing swarm cells, thus allowing for a more precise determination of the shape and size of queen-cell punch and the ideal position of a cell cup on the bar of queen cup frames in artificial queen rearing

Fluid‐driven soft CoboSkin for safer human–robot collaboration: fabrication and adaptation

In human–robot collaboration, the wrapping material on robots is not only required to have the sensing ability to adapt to the external environment but also need to have the function of cushioning the collision between human and robot. Herein, a fluid‐driven soft robot skin with sensing and actuating function is successfully applied to a collaborative robot and working well with the host robot. The skin is an integration of sponge force sensors and pneumatic actuators. By altering the internal air pressure in pneumatic actuators, the developed robot skin can provide more than ten times tunable stiffness and sensitivity. In addition, the skin can reduce the peak force of the collision and achieve the actuating function. Using three‐dimensional printing and computer‐aided design, the skin is fabricated and attached to a collaborative robot conformally. Drawing upon the data acquisition and control system, the experiment for illustrating the applications of the CoboSkin is successfully performed. The skin provides the robot with multi‐functions, which are similar to the human muscle and skin attached to human bones. By mimicking human skin and muscle with tactile sensing function and stiffness tuning function, CoboSkin can enhance the adaptability of the robot to human daily life

Synergistic Effects of Clopidogrel and Fufang Danshen Dripping Pills by Modulation of the Metabolism Target and Pharmacokinetics

Background and Objective. The aim was to evaluate the synergistic effects of clopidogrel and FDDP by modulating the metabolism target and the pharmacokinetics. Methods. The inhibition effect of FDDP on the CES1 was first investigated by the molecular simulation method, and the synergistic effects on the pharmacokinetics of CPGS were studied as follows: SD rats were treated with oral clopidogrel alone at a dosage of 30 mg/kg or the combination of clopidogrel and FDDP at dosages of 30 mg/kg and 324 mg/kg, respectively, for 21 days. The concentrations of CPGS in the blood plasma samples were determined and the calculated concentrations were used to determine the pharmacokinetic parameters. Results. 20 compounds in FDDP potentially interacted with CES1 target. The CPGS showed a two-compartment model pharmacokinetic profile. The concentration-time course of CPGS was not changed by FDDP, but FDDP decreased the peak plasma concentration and area under the curve of CPGS. Conclusion. The CES1’s activity could be partly inhibited by FDDP through the molecular simulation investigation. The concentration-time course of CPGS was altered slightly by FDDP. The results demonstrated the synergistic effects of clopidogrel and FDDP by modulating both the pharmacokinetics and the target metabolism

The effect of subacromial decompression on the curative effect of arthroscopic treatment of shoulder calcific tendinitis

ObjectiveTo observe and analyze the surgical efficacy of arthroscopic debridement of calcified deposits and arthroscopic debridement combined with subacromial decompression in patients with supraspinatus tendon calcific myositis. To observe the effect of Subacromial decompression on the efficacy of arthroscopic treatment of shoulder calcific tendinitis.Patients and methodsFrom 2016 to 2021, 48 cases of shoulder arthroscopic debridement due to supraspinatus calcific tendinitis met the inclusion criteria and were included, with 24 cases assigned to the arthroscopic debridement group and 24 cases to the arthroscopic debridement combined with subacromial decompression group. Changes between preoperative and postoperative shoulder pain and shoulder function were statistically analyzed.ResultsThe 24 patients in the arthroscopic debridement group were better than the arthroscopic debridement combined with subacromial decompression group in terms of short-term postoperative shoulder pain and shoulder joint function recovery (P < 0.05). There was no significant difference in the postoperative long-term shoulder pain and shoulder function recovery between the two groups (P > 0.05).ConclusionsCompared with arthroscopic debridement combined with subacromial decompression, arthroscopic debridement alone is a better surgical option for the treatment of calcific tendinitis

HierFedML: aggregator placement and UE assignment for hierarchical federated learning in mobile edge computing

Federated learning (FL) is a distributed machine learning technique that enables model development on user equipments (UEs) locally, without violating their data privacy requirements. Conventional FL adopts a single parameter server to aggregate local models from UEs, and can suffer from efficiency and reliability issues – especially when multiple users issue concurrent FL requests . Hierarchical FL consisting of a master aggregator and multiple worker aggregators to collectively combine trained local models from UEs is emerging as a solution to efficient and reliable FL. The placement of worker aggregators and assignment of UEs to worker aggregators plays a vital role in minimizing the cost of implementing FL requests in a Mobile Edge Computing (MEC) network. Cost minimization associated with joint worker aggregator placement and UE assignment problem in an MEC network is investigated in this work. An optimization framework for FL and an approximation algorithm with an approximation ratio for a single FL request is proposed. Online worker aggregator placements and UE assignments for dynamic FL request admissions with uncertain neural network models, where FL requests arrive one by one without the knowledge of future arrivals, is also investigated by proposing an online learning algorithm with a bounded regret. The performance of the proposed algorithms is evaluated using both simulations and experiments in a real testbed with its hardware consisting of server edge servers and devices and software built upon an open source hierarchical FedML (HierFedML) environment. Simulation results show that the performance of the proposed algorithms outperform their benchmark counterparts, by reducing the implementation cost by at least 15% per FL request. Experimental results in the testbed demonstrate the performance gain using the proposed algorithms using real datasets for image identification and text recognition applications

Sex Differences in the Association of HOMA-IR Index and BDNF in Han Chinese Patients With Chronic Schizophrenia

Background: Previous research has indicated that there are significant sex differences in serum BDNF levels and metabolic indicators in patients with schizophrenia. Studies have found that BDNF is involved in blood sugar regulation. Homeostasis model assessment of insulin resistance (HOMA-IR) is currently a sensitive indicator for measuring insulin resistance. Our study aims to explore the sex differences in the relationship between serum BDNF levels and HOMA-IR in patients with chronic schizophrenia (CS).Methods: A total of 332 patients with CS were enrolled in this study. General information of all participants was collected. Haematological indicators were collected, and the Positive and Negative Syndrome Scale (PANSS) was used to evaluate psychiatric symptoms. Sex differences in serum BDNF levels, HOMA-IR index and other metabolic indexes were investigated. Then, linear regression analysis was used to analyse the relationship between the HOMA-IR index and BDNF levels in male and female patients.Results: The HOMA-IR index of female patients was significantly higher than that of males, but there was no significant difference in serum BDNF levels between male patients and female patients. There was a positive correlation between BDNF level and HOMA-IR index, and this relationship only existed in female patients.Conclusion: The results show that there are significant sex differences in HOMA-IR in patients with CS. In addition, only in female patients was there a positive correlation between the HOMA-IR index and BDNF level, which suggests that sex factors should be taken into account in evaluating the relationship between BDNF and blood glucose in patients with CS

Laser spectroscopic studies of hafnium ions confined in a Paul trap

A Paul trap has been constructed for laser spectroscopic studies of the isotope shifts (IS) and hyperfine structures (hfs) of radioactive isotopes. With a sample placed near the inner surface of the ring electrode, the target atoms are evaporated by a Nd:YAG laser pulse, and then selectively ionized inside the trap by a synchronized dye laser pulse through resonance ionization spectroscopy (RIS). A cw beam from a ring dye laser is used to probe the ions, and laser-induced fluorescence (LIF) is monitored for spectroscopic measurements. The stored ions can also be analyzed by the ion-ejection time-of-flight spectrum. With an ultra-high vacuum base pressure, Hf ion storage times of one hour can be readily achieved by introducing H$sb2$ as a buffer gas. It is demonstrated that with a very dilute sample, Hf ions can be accumulated in the trap through successive heating and RIS pulses. Through LIF measurements, both the ion cooling time and the dependence of the mean ion kinetic energy on the RF phase and trap operating conditions have been studied. A phase-locked counting technique has been applied to improve the spectroscopic resolution. The hfs of $sp{177}$Hf and $sp{179}$Hf with the transition a $rm sp2D sb{3/2}$--$z sp4{ rm F} sbsp{5/2}{ circ} ( lambda$ = 340 nm) in HfII has been studied with a resolution of about 1 GHz, and their hfs A and B constants have been deduced. The IS of the radioactive $sp{172}$Hf has been carried out with a sample containing $7 times10 sp{11} sp{172}$Hf atoms. Based on the observation of the laser-induced formation of HfH, a new spectroscopic method capable of selectively suppressing the ion population of a particular contaminant isotope has been developed to enhance the $sp{172}$Hf signal-to-noise ratio. Deduced changes of mean-square nuclear charge radii in Hf, together with the existing data in the literature, are discussed and compared with theoretical variations obtained from Finite-Range Droplet Model calculations

Improving Continual Relation Extraction by Distinguishing Analogous Semantics

Continual relation extraction (RE) aims to learn constantly emerging relations while avoiding forgetting the learned relations. Existing works store a small number of typical samples to re-train the model for alleviating forgetting. However, repeatedly replaying these samples may cause the overfitting problem. We conduct an empirical study on existing works and observe that their performance is severely affected by analogous relations. To address this issue, we propose a novel continual extraction model for analogous relations. Specifically, we design memory-insensitive relation prototypes and memory augmentation to overcome the overfitting problem. We also introduce integrated training and focal knowledge distillation to enhance the performance on analogous relations. Experimental results show the superiority of our model and demonstrate its effectiveness in distinguishing analogous relations and overcoming overfitting.Comment: Accepted in the 61st Annual Meeting of the Association for Computational Linguistics (ACL 2023