Deformation modeling based on mechanical properties of liver tissue for virtuanormal vectors of trianglesl surgical simulation.

PURPOSE: In this paper, a method for rapidly constructing a virtual surgical simulation system is proposed. A deformation model based on the mechanical properties of the liver and a rapid collision detection between the surgical micro-instruments and the liver tissue are included in this method. The purpose of this work is to improve the accuracy and real time of particle model deformation interaction in virtual surgery system. METHODS: Firstly, a finite element model is established based on the constitutive model parameters of liver tissue. According to the simulation results, a mathematical model of node displacement is established. Secondly, the virtual liver is established based on the fast model reconstruction method, and the virtual manipulator is controlled by Geomagic Touch manipulator. Based on the hybrid bounding box, a rapid collision detection process between the instrument and liver is realized and the proposed deformation method is used to simulate the deformation of liver tissue. RESULTS: The simulation and experiment results show that the proposed deformation model can achieve high deformation interaction accuracy. The collision detection algorithm based on the hybrid bounding boxes can realize the collision between the liver and the instrument, and the established virtual surgical simulation system can simulate the liver tissue deformation in the case of small loading displacement. CONCLUSIONS: The effectiveness of the collision detection algorithm and deformation model was verified by an established virtual surgery simulation system. The proposed rapid construction method of virtual surgical simulation is feasible.

The whiplash effect: The (moderating) role of attributed motives in emotional and behavioral reactions to abusive supervision.

Although extant research shows a clear link between abusive supervision and detrimental consequences for organizations and their members, the popular press and media are replete with suggestions that abusive supervision can be positive and motivating. Drawing from the social functional view of emotions and emerging research on attributed motives of abusive supervision, we examine this phenomenon, which we refer to as the whiplash effect-the notion that subordinates may display different emotional and behavioral reactions to supervisory abuse depending on their attributions for abuse. We conduct 3 studies to examine this effect at both the between- and within person level. Results from a multisource, time-lagged field study (between-person) and a laboratory-based experiment (between-person) indicate that when subordinates believe that the abusive supervisor is motivated by desires to cause harm (i.e., injury initiation attribution is higher), abusive supervision is more likely to engender anger, which, in turn, elicits more deviant behaviors and fewer organizational citizenship behaviors; however, when subordinates believe the abusive supervisor is motivated by desires to improve performance (i.e., performance promotion attribution is higher), abusive supervision is more likely to evoke guilt, which, in turn, elicits fewer deviant behaviors and more organizational citizenship behaviors. These results were then expanded in an experience sampling study (within-person), which allowed us to further examine how general interpretations of supervisors' motives behind abusive supervision shape employees' momentary emotional and behavioral responses toward daily abusive supervisor behavior. Theoretical and practical implications are discussed. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

MASSD: Multi-scale attention single shot detector for surgical instruments.

Surgical instrument detection is a significant task in computer-aided minimal invasive surgery for providing real-time feedback to physicians, evaluating surgical skills, and developing a training plan for surgeons. In this study, a multi-scale attention single detector is designed for surgical instruments. In the field of object detection, accurate detection of small objects is always a challenging task. We propose an innovative feature fusion technique aimed at small surgical instrument detection. First, the attention map is created from high-level features to act on the low-level features and enrich the semantic information of the low-level features. The original and processed features are then fused by skip connection. Finally, multi-scale feature maps are created to predict fusion features. The experiments on the ATLAS Dione dataset yielded results with a detection time of 0.066 s per frame and a mean average precision of 90.08%. Our proposed feature fusion module can obtain more semantic information for low-level features and significantly enhance the performance of small surgical instrument detection.

A Holistically-Nested U-Net: Surgical Instrument Segmentation Based on Convolutional Neural Network.

Surgical instrument segmentation is an essential task in the domain of computer-assisted surgical system. It is critical to increase the context-awareness of surgeons during the operation. We propose a new model based on the U-Net architecture for surgical instrument segmentation, which aggregates multi-scale feature maps and has cascaded dilated convolution layers. The model adopts dense upsampling convolution instead of deconvolution for upsampling. We set the side loss function on each side-output layer. The loss function includes an output loss function and all side loss functions to supervise the training of each layer. To validate our model, we compare our proposed model with advanced architecture U-Net in the dataset consisting of laparoscopy images from multiple surgical operations. Experiment results demonstrate that our model achieves good performance.

A Clamping Force Estimation Method Based on a Joint Torque Disturbance Observer Using PSO-BPNN for Cable-Driven Surgical Robot End-Effectors.

The ability to sense external force is an important technique for force feedback, haptics and safe interaction control in minimally-invasive surgical robots (MISRs). Moreover, this ability plays a significant role in the restricting refined surgical operations. The wrist joints of surgical robot end-effectors are usually actuated by several long-distance wire cables. Its two forceps are each actuated by two cables. The scope of force sensing includes multidimensional external force and one-dimensional clamping force. This paper focuses on one-dimensional clamping force sensing method that do not require any internal force sensor integrated in the end-effector's forceps. A new clamping force estimation method is proposed based on a joint torque disturbance observer (JTDO) for a cable-driven surgical robot end-effector. The JTDO essentially considers the variations in cable tension between the actual cable tension and the estimated cable tension using a Particle Swarm Optimization Back Propagation Neural Network (PSO-BPNN) under free motion. Furthermore, a clamping force estimator is proposed based on the forceps' JTDO and their mechanical relations. According to comparative analyses in experimental studies, the detection resolutions of collision force and clamping force were 0.11 N. The experimental results verify the feasibility and effectiveness of the proposed clamping force sensing method.

[The elimination method of preloading force for soft tissue based on the linear loading region].

Aiming at the problem of the influence of preloading force on its mechanical response in soft tissue compression experiments, an elimination method of preloading force based on linear loading region is proposed. Unconfined compression experiments under a variety of different preloading forces are performed. The influence of the preloading force on the parameters of constitutive model is analyzed. In the preload phase, the mechanical response of the soft tissue is taken as a linear model. The preloading force is eliminated by taking the preloading phase into account throughout the response process. According to five different preloading forces of the unconfined compression experiments, the elimination method is validated with two different constitutive models of soft tissue, and the error between the models obtained by the preloading force elimination method and the traditional method with the experimental results is compared. The results show that the error obtained by preloading force elimination method is significantly smaller than the traditional method. The preloading force elimination method can eliminate the influence of preloading force on mechanical response to a certain extent, and constitutive model parameters which are closer to the true properties of soft tissue can be obtained.

The estimation method of friction in unconfined compression tests of liver tissue.

In traditional unconfined compression tests, the friction between platform and specimen is often considered negligible or minimized by lubrication or other means. However, friction can affect the estimation of material parameters. The percentage difference in radial deformation was investigated in this study. A novel friction estimation method was established and verified using a finite element method. The proposed method was based on the radial deformation during the compression process. Three different hyperelastic material parameters of liver tissue were applied in the simulations. The hyperelastic parameters H1 were obtained by no-slip compression tests, while the others were extracted from the literature. The results showed that the percentage difference in radial deformation was mainly influenced by the friction coefficient and diameter-to-height ( d/ h) ratio of the specimen in unconfined compression tests. The percentage difference increased as the friction coefficient and d/ h increased. Different d/ h and friction coefficient values were tested to validate the proposed method, and the accuracy was estimated to exceed 86%. An optimization strategy for material parameters in unconfined compression tests was proposed accordingly.

Fabrication and application of enzyme-incorporated peptide nanotubes.

Enzyme engineering is a fast-growing field in the pharmaceutical and food markets. For those applications, various substrates have been examined to immobilize and stabilize enzymes. In this report, we examined peptide nanotubes as supports for enzymes. When a model enzyme, Candida rugosa lipase, was encapsulated in peptide nanotubes, the catalytic activity of nanotube-bound lipases was increased 33% as compared to free-standing lipases at room temperature. At an elevated temperature, 65 degrees C, the activity of lipases inside the nanotubes was 70% higher than free-standing lipases. The activity enhancement of lipases in the peptide nanotubes is likely induced by the conformation change of lipases to the open form (the enzymatically active structure) as lipases are adsorbed on the inner surfaces of peptide nanotubes.

Room-temperature Wurtzite ZnS nanocrystal growth on Zn finger-like peptide nanotubes by controlling their unfolding peptide structures.

ZnS nanocrystal, a class of wide-gap semiconductors, has shown interesting optical, electrical, and optoelectric properties via quantum confinement. For those applications, phase controls of ZnS nanocrystals and nanowires were critical to tune their physical properties to the appropriate ones. The wurtzite ZnS nanocrystal growth at room temperature is the useful fabrication; however, the most stable ZnS structure in nanoscale is the zinc blende (cubic) structure, and scientists have just begun exploring the room-temperature synthesis of the wurtzite (hexagonal) structure of ZnS nanocrystals. In this report, we applied the Zn finger-like peptides as templates to control the phase of ZnS nanocrystals to the wurtzite structure at room temperature. The peptide nanotubes, consisting of a 20 amino acids (VAL-CYS-ALA-THR-CYS-GLU-GLN-ILE-ALA-ASP-SER-GLN-HIS-ARG-SER-HIS-ARG-GLN-MET-VAL, M1 peptide) synthesized based on the peptide motif of the Influenza Virus Matrix Protein M1, could grow the wurtzite ZnS nanocrystals on the nanotube templates in solution. In the M1 protein, the unfolding process of the helical peptide motif via pH change creates a linker region between N- and C-terminated helical domains that contains a Zn finger-like Cys2His2 motif. Because the higher pH increases the uptake of Zn ions in the Cys2His2 motif of the M1 peptide by unfolding more helical domains, the pH change can essentially control the size and the number of the nucleation sites in the M1 peptides to grow ZnS nanocrystals with desired phases. Here we optimized the nucleation sites in the M1 peptides by unfolding them via pH change to obtain highly monodisperse and crystalline wurtzite ZnS nanocrystals on the template nanotubes at room temperature. This type of peptide-induced biomineralization technique will provide a clean and reproducible method to produce semiconductor nanotubes due to its efficient nanocrystal formation, and the band gaps of resulting nanotubes can also be tuned simply by phase control of ZnS nanocrystal coatings via the optimization of the unfolding peptide structures.

Attachment of ferrocene nanotubes on beta-cyclodextrin self-assembled monolayers with molecular recognitions.

Ferrocene nanotubes were fabricated by binding carboxylic acid-derivatized ferrocenes onto template peptide nanotubes via hydrogen bonding. When these ferrocene-functionalized nanotubes were incubated with beta-cyclodextrin (beta-CD) self-assembled monolayers (SAMs) coated on patterned Au substrates in solution, the ferrocene nanotubes recognized and attached onto the beta-CD SAMs via host-guest molecular recognition. The ferrocene nanotubes were also observed to recognize the certain cavity size of CD. The attachment/detachment of nanotubes on the beta-CD SAMs was controlled electrochemically by tuning the redox states of ferrocene nanotubes. This electric field-responsive building block may be applied to build nanometer-sized switching components in electronics and sensors.

Biological bottom-up assembly of antibody nanotubes on patterned antigen arrays.

Application of biotechnology in nanofabrication has an advantage to produce functional building-block materials that may not have synthetic counterparts. Here we introduced a new type of building block, antibody nanotubes, and demonstrated anchoring them on complementary antigen arrays via antibody-antigen recognition. Biological recognition between the antibody nanotubes and the antigen arrays permitted recognition-driven assembly of ordered nanotube arrays. The array of antigens was written by using the tip of an atomic force microscope (AFM) on alkylthiol self-assembled monolayer (SAM)-coated Au substrates via nanografting. After antigens were immobilized onto the shaved regions of the alkylthiol SAMs with the AFM tip, antibody nanotubes, produced by incubating antibodies in template nanotube solutions, were selectively attached onto the antigen regions. This technique is very useful when multiple building blocks are necessary to address specific locations on substrates because simultaneous immobilization of multiple antibody nanotubes at specific complementary binding positions can be achieved in a single process.

Direct growth of shape-controlled nanocrystals on nanotubes via biological recognition.

The new biological approach was examined to fabricate shape-controlled Ag nanocrystals grown directly on surfaces, inspired by nature that various shapes of nanocrystals are produced accurately and reproducibly in biological systems. Here we demonstrate the direct growth of hexagon-shaped Ag nanocrystals on sequenced peptide-coated nanotubes via biological recognition. When the peptide, Asn-Pro-Ser-Ser-Leu-Phe-Arg-Tyr-Leu-Pro-Ser-Asp, recognizing and effecting the Ag nanocrystal growth on the (111) face, was sequenced and incorporated onto template nanotube surfaces, the biomineralization of Ag ions on the nanotubes led the isotropic hexagon-shaped Ag nanocrystal coating under pH control of the growth solution. Multiple Ag nanocrystal shapes were observed when the peptide mineralized Ag ions without the template nanotubes, and therefore the template nanotube has a significant influence on regulating the majority of Ag nanocrystals into the hexagonal shape. This biological approach, using specific peptide sequences on surfaces to control nanocrystal shapes, may be developed as a simple and economical method to produce building blocks with desired physical properties for new generation of electronics, sensors, and optical devices.

Cu nanocrystal growth on peptide nanotubes by biomineralization: size control of Cu nanocrystals by tuning peptide conformation.

With recent interest in seeking new biologically inspired device-fabrication methods in nanotechnology, a new biological approach was examined to fabricate Cu nanotubes by using sequenced histidine-rich peptide nanotubes as templates. The sequenced histidine-rich peptide molecules were assembled as nanotubes, and the biological recognition of the specific sequence toward Cu lead to efficient Cu coating on the nanotubes. Cu nanocrystals were uniformly coated on the histidine-incorporated nanotubes with high packing density. In addition, the diameter of Cu nanocrystal was controlled between 10 and 30 nm on the nanotube by controlling the conformation of histidine-rich peptide by means of pH changes. Those nanotubes showed significant change in electronic structure by varying the nanocrystal diameter; therefore, this system may be developed to a conductivity-tunable building block for microelectronics and biological sensors. This simple biomineralization method can be applied to fabricate various metallic and semiconductor nanotubes with peptides whose sequences are known to mineralize specific ions.

Application of host-guest chemistry in nanotube-based device fabrication: photochemically controlled immobilization of azobenzene nanotubes on patterned alpha-CD monolayer/Au substrates via molecular recognition.

Azobenzene-functionalized nanotubes recognized and attached onto well-defined complementary regions of thiolated alpha-CD SAM/Au substrates via host-guest molecular recognition. The binding between the azobenzene nanotubes and the alpha-CD SAM/Au substrates was controlled by UV irradiation. The light-induced attachment-detachment of the azobenzene nanotubes on the alpha-CD SAMs was reversible. Some of the nanotubes were capable of interconnecting two Au substrates. This smart building block may be applied to build photoactive nanometer-sized mechanical switches in electronics.