BackgroundPorcine circovirus-associated diseases (PCVAD), caused by porcine circovirus type 2 (PCV2), threaten the pig industry worldwide. Five genotypes of PCV2 were recently identified: PCV2a, PCV2b, PCV2c, PCV2d and PCV2e. In addition, a novel porcine circovirus from a case of a sow with dermatitis, nephropathy syndrome and reproductive failure has been identified based on metagenomic analysis and classified as porcine circovirus type 3 (PCV3). Therefore, the current study was conducted to determine the prevalence and genetic characteristics of PCV2 and PCV3 in clinical samples.ResultsA total of 471 samples (161 tissue samples of lungs and lymph nodes from 34 farms and 310 serum samples from 47 farms) were tested for PCV2. Among them, 171 samples from 59 farms that had been positive for PCV2 were genotyped. Another 690 samples (296 tissue samples of lungs and lymph nodes from 91 farms, 108 samples of aborted foetuses from 26 farms, and 286 serum samples from 47 farms) were tested for PCV3. Based on PCV2 genotyping results, PCV2d was the most prevalent genotype (107 of 171 samples), and co-infections with combinations of PCV2a, 2b and 2d were identified in 48 samples from 17 farms. A total of 14 samples from 11 farms were also positive for both PCV2 and PCV3. For PCV3, 57 samples (9.8%) from 32 farms (23.2%) were positive. Among the 108 aborted foetuses from 26 farms, only 2 samples were positive for PCV3. Based on sequence comparisons, PCV2d shares 89.6–91.0% and 93.2–94.3% homology with PCV2a and PCV2b, respectively; 98.6–100% homology is shared among PCV2d strains. The PCV3 strains identified in this study share 98.0–99.5% homology.ConclusionsOur study concludes that PCV2d has become the most predominant genotype in Korea. PCV3 was also identified in clinical samples, though no significant association with clinical symptoms was observed in PCV3-positive cases.

An MRC (Magneto-Rheological Clutch), a device to transmit torque by shear stress of MR fluids, has the property that its power transmissibility changes quickly in response to control signal. In this study, we consider methods to predict performance of an MRC. First, we anticipate the performance of an MRC with a simplified mathematical model and second, we predict the performance in consideration of the applied magnetic field and viscosity distribution of fluids caused by the field. Between the two methods, compared with experimental results, it is shown that the numerical method is closer to reality than the simplified one.

This paper introduces a robotic biopsy device for capsule endoscopes. The proposed device consists of three modules for the complete process of biopsy, which includes monitoring the intestinal wall by a tissue monitoring module (TMM), aligning onto a polyp by an anchor module (AM), and sampling of the polyp tissue by a biopsy module (BM). The TMM utilizes a trigonal mirror as well as an on-board camera; since the TMM continuously takes images through lateral apertures, an operator such as a medical doctor is able to anchor the capsule endoscope onto the polyp and biopsy it with the visual feedback in real-time. When the operator finds a polyp using the TMM and the frontal camera of a capsule endoscope, then the AM is used to approach the polyp for biopsy. When the AM is in use, outriggers are extruded by shape-memory-alloy (SMA) springs, which results in the swelling of capsule endoscope body. In addition, an alignment module, which is a part of the AM, rotates the body of the capsule endoscope such that the biopsy razor can be aligned onto the polyp. Then, the BM excises a part of the polyp and seals the aperture, and the capsule endoscope continues exploring the intestine. The concept and working principles of the proposed device are introduced in this paper and are verified by a prototype that successfully integrates the three modules.

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In exoskeletal robots, the quantification of the user’s muscular effort is important to recognize the user’s motion intentions and evaluate motor abilities. In this paper, we attempt to estimate users’ muscular efforts accurately using joint torque sensor which contains the measurements of dynamic effect of human body such as the inertial, Coriolis, and gravitational torques as well as torque by active muscular effort. It is important to extract the dynamic effects of the user’s limb accurately from the measured torque. The user’s limb dynamics are formulated and a convenient method of identifying user-specific parameters is suggested for estimating the user’s muscular torque in robotic exoskeletons. Experiments were carried out on a wheelchair-integrated lower limb exoskeleton, EXOwheel, which was equipped with torque sensors in the hip and knee joints. The proposed methods were evaluated by 10 healthy participants during body weight-supported gait training. The experimental results show that the torque sensors are to estimate the muscular torque accurately in cases of relaxed and activated muscle conditions.