Fully automatic AI segmentation of oral surgery-related tissues based on cone beam computed tomography images.

Accurate segmentation of oral surgery-related tissues from cone beam computed tomography (CBCT) images can significantly accelerate treatment planning and improve surgical accuracy. In this paper, we propose a fully automated tissue segmentation system for dental implant surgery. Specifically, we propose an image preprocessing method based on data distribution histograms, which can adaptively process CBCT images with different parameters. Based on this, we use the bone segmentation network to obtain the segmentation results of alveolar bone, teeth, and maxillary sinus. We use the tooth and mandibular regions as the ROI regions of tooth segmentation and mandibular nerve tube segmentation to achieve the corresponding tasks. The tooth segmentation results can obtain the order information of the dentition. The corresponding experimental results show that our method can achieve higher segmentation accuracy and efficiency compared to existing methods. Its average Dice scores on the tooth, alveolar bone, maxillary sinus, and mandibular canal segmentation tasks were 96.5%, 95.4%, 93.6%, and 94.8%, respectively. These results demonstrate that it can accelerate the development of digital dentistry.

Pure cellulose nanofiber separator with high ionic conductivity and cycling stability for lithium-ion batteries.

Conventional polyolefin separators are constrained by poor electrolyte wettability, inferior thermal stability, and low ionic conductivity, which seriously restrict their application in high-performance lithium-ion batteries (LIBs). Herein, cellulose nanofiber (CNF) as the matrix and tert-butyl alcohol (TBA) as the dispersion medium were used to prepare the pure CNF separators for LIBs by a facile filtration method. The effects of the drying temperature on the pore structure, electrolyte wettability, mechanical properties, thermal stability, and ionic conductivity of the separators were comprehensively investigated. The results showed that the freeze-dried separator at -80 °C with TBA as the dispersion medium (TBA-FD) had the best overall performance, with the porosity and electrolyte uptake up to 70.8 % and 296 %, respectively, as well as the ionic conductivity up to 1.90 mS/cm. The CNF separators had no apparent thermal shrinkage at 160 °C, illustrating good thermal stability. Moreover, the LiFePO4/lithium metal battery assembled with the TBA-HD (tert-butyl alcohol as the dispersion medium for heat-drying at 80 °C) and TBA-FD separators displayed superior cycling stability (with a capacity retention rate up to 97.5 % and 96.4 %, respectively) and rate performance. The pure CNF separators with good performance prepared by the facile method are greatly promising for high-performance LIBs.

Direct Photo-Patterning of Efficient and Stable Quantum Dot Light-Emitting Diodes via Light-Triggered, Carbocation-Enabled Ligand Stripping.

Next generation displays based on quantum dot light-emitting diodes (QLEDs) require robust patterning methods for quantum dot layers. However, existing patterning methods mostly yield QLEDs with performance far inferior to the state-of-the-art individual devices. Here, we report a light-triggered, carbocation-enabled ligand stripping (CELS) approach to pattern QLEDs with high efficiency and stability. During CELS, photogenerated carbocations from triphenylmethyl chlorides remove native ligands of quantum dots, thereby producing patterns at microscale precision. Chloride anions passivate surface defects and endow patterned quantum dots with preserved photoluminescent quantum yields. It works for both cadmium-based and heavy-metal-free quantum dots. CELS-patterned QLEDs show remarkable external quantum efficiencies (19.1%, 17.5%, 12.0% for red, green, blue, respectively) and a long operation lifetime (T95 at 1000 nits up to 8700 h). Both are among the highest for patterned QLEDs and approach the records for nonpatterned devices, which makes CELS promising for building high-performance QLED displays and related integrated devices.

Effects of Cavity Thickness and Mold Surface Roughness on the Polymer Flow during Micro Injection Molding.

In micro injection molding, the cavity thickness and surface roughness are the main effects factors of polymer flow in the die designing and affect the quality of molded products significantly. In this study, the effects of cavity thickness and roughness of cavity surface were investigated mainly on polymer flow during molding and on the roughness of molded products. The parts were molded in the cavities with the thickness from 0.05 mm to 0.25 mm and surface roughness from Ra = 46.55 nm to Ra = 462.57 nm, respectively. The filling integrities and roughness replication ratio of molded parts were used to evaluate the statements of polymer flow and microstructure replication during micro injection molding, respectively. The results showed that the filling integrity changing trends in the thinner cavities were obviously different or even opposite to those in the thicker cavities with the changing of cavity surface roughness instead of single trend in the conventional studies. For each cavity surface roughness, the filling integrity showed an upward trend with the increasing cavity thickness. In different cavity thickness, the maximum gap of filling integrity was 23.76 mm, reaching 544.94% from 0.05 mm to 0.25 mm. Additionally, the surface roughness ratio was slightly smaller than one before, reaching the polymer surface roughness limit around Ra = 71.27 nm, which was decided by the nature of the polymer itself. This study proposed the references for the design and fabrication of mold cavities and parts, and saved time and cost in the actual product manufacturing.

Autonomous aspirating robot for removing saliva blood mixed liquid in oral surgery.

Saliva blood mixed liquid (SBML) appears in oral surgery, such as scaling and root planning, and it affects surgical vision and causes discomfort to the patient. However, removing SBML, i.e. frequent aspiration of the mixed liquid, is a routine task involving heavy workload and interruption of oral surgery. Therefore, it is valuable to alternate the manual mode by autonomous robotic technique. The robotic system is designed consisting of an RGB-D camera, a manipulator, a disposable oral aspirator. An algorithm is developed for detection of SBML. Path planning method is also addressed for the distal end of the aspirator. A workflow for removing SBML is presented. 95% of the area of the SBML in the oral cavity was removed after liquid aspiration among a group of ten SBML aspiration experiments. This study provides the first result of the autonomous aspirating robot (AAR) for removing SBML in oral surgery, demonstrating that SBML can be removed by the autonomous robot, freeing stomatology surgeon from tedious work.

A self-supported sodium alginate composite hydrogel membrane and its performance in filtering heavy metal ions.

A novel self-supported polysaccharide based hydrogel membrane was prepared by adding cellulose nanofiber (CNF) and micron-sized biochar (BC) into sodium alginate (SA) hydrogel with in-situ free water evaporation ("cooking") process and ionic crosslinking, in which the polyethylene glycol (PEG) was used as a pore-forming agent. Herein, CNF can not only enhance the mechanical property of the matrix, but also assist the homogeneous dispersion of BC. As a result, the prepared membrane had a maximum tensile strength of up to 5.69 MPa, which was more than 2-3 times higher than the previously reported self-supported hydrogel membranes. The flux reached 61.5 Lm-2 h-1 under 0.35 MPa pressure, and the anti-fouling property was also excellent due to its hydrophilicity. In filtration tests, the rejection of Cr (III) and Cr (VI) of 50 mg/l could reach 96.8 % and 91.4 %, respectively. Moreover, the mechanism behind the exceptional high rejection for both cationic and anionic heavy metal was delineated.

Tissue Recognition Based on Electrical Impedance Classified by Support Vector Machine in Spinal Operation Area.

OBJECTIVE: One of the major difficulties in spinal surgery is the injury of important tissues caused by tissue misclassification, which is the source of surgical complications. Accurate recognization of the tissues is the key to increase safety and effect as well as to reduce the complications of spinal surgery. The study aimed at tissue recognition in the spinal operation area based on electrical impedance and the boundaries of electrical impedance between cortical bone, cancellous bone, spinal cord, muscle, and nucleus pulposus. METHODS: Two female white swines with body weight of 40 kg were used to expose cortical bone, cancellous bone, spinal cord, muscle, and nucleus pulposus under general anesthesia and aseptic conditions. The electrical impedance of these tissues at 12 frequencies (in the range of 10-100 kHz) was measured by electrochemical analyzer with a specially designed probe, at 22.0-25.0°C and 50%-60% humidity. Two types of tissue recognition models - one combines principal component analysis (PCA) and support vector machine (SVM) and the other combines combines SVM and ensemble learning - were constructed, and the boundaries of electrical impedance of the five tissues at 12 frequencies of current were figured out. Linear correlation, two-way ANOVA, and paired T-test were conducted to analyze the relationship between the electrical impedance of different tissues at different frequencies. RESULTS: The results suggest that the differences of electrical impedance mainly came from tissue type (p < 0.0001), the electrical impedance of five kinds of tissue was statistically different from each other (p < 0.0001). The tissue recognition accuracy of the algorithm based on principal component analysis and support vector machine ranged from 83%-100%, and the overall accuracy was 95.83%. The classification accuracy of the algorithm based on support vector machine and ensemble learning was 100%, and the boundaries of electrical impedance of five tissues at various frequencies were calculated. CONCLUSION: The electrical impedance of cortical bone, cancellous bone, spinal cord, muscle, and nucleus pulposus had significant differences in 10-100 kHz frequency. The application of support vector machine realized the accurate tissue recognition in the spinal operation area based on electrical impedance, which is expected to be translated and applied to tissue recognition during spinal surgery.

Beyond a Linker: The Role of Photochemistry of Crosslinkers in the Direct Optical Patterning of Colloidal Nanocrystals.

Surface chemistry mediated direct optical patterning represents an emerging strategy for incorporating colloidal nanocrystals (NCs) in integrated optoelectronic platforms including displays and image sensors. However, the role of photochemistry of crosslinkers and other photoactive species in patterning remains elusive. Here we show the design of nitrene- and carbene-based photocrosslinkers can strongly affect the patterning capabilities and photophysical properties of NCs, especially quantum dots (QDs). Their role beyond physical linkers stems from structure-dictated electronic configuration, energy alignment and associated reaction kinetics and thermodynamics. Patterned QD layers with designed carbene-based crosslinkers fully preserve their photoluminescent and electroluminescent properties. Patterned light emitting diodes (QLEDs) show a maximum external quantum efficiency of ≈12 % and lifetime over 4800 h, among the highest for reported patterned QLEDs. These results would guide the rational design of photoactive species in NC patterning and create new possibilities in the monolithic integration of NCs in high-performance device platforms.

Spine-transformers: Vertebra labeling and segmentation in arbitrary field-of-view spine CTs via 3D transformers.

In this paper, we address the problem of fully automatic labeling and segmentation of 3D vertebrae in arbitrary Field-Of-View (FOV) CT images. We propose a deep learning-based two-stage solution to tackle these two problems. More specifically, in the first stage, the challenging vertebra labeling problem is solved via a novel transformers-based 3D object detector that views automatic detection of vertebrae in arbitrary FOV CT scans as a one-to-one set prediction problem. The main components of the new method, called Spine-Transformers, are a one-to-one set based global loss that forces unique predictions and a light-weighted 3D transformer architecture equipped with a skip connection and learnable positional embeddings for encoder and decoder, respectively. We additionally propose an inscribed sphere-based object detector to replace the regular box-based object detector for a better handling of volume orientation variations. Our method reasons about the relationships of different levels of vertebrae and the global volume context to directly infer all vertebrae in parallel. In the second stage, the segmentation of the identified vertebrae and the refinement of the detected centers are then done by training one single multi-task encoder-decoder network for all vertebrae as the network does not need to identify which vertebra it is working on. The two tasks share a common encoder path but with different decoder paths. Comprehensive experiments are conducted on two public datasets and one in-house dataset. The experimental results demonstrate the efficacy of the present approach.

A 4arm-PEG macromolecule crosslinked chitosan hydrogels as antibacterial wound dressing.

In order to develop better wound dressings, a novel chitosan hydrogel (Cn-Nm gel) was designed and fabricated by using aldehyde-4-arm polyethylene glycol (4r-PEG-CHO) to crosslink the chitosan dissolved in alkaline solution, amino-4-arm polyethylene glycol (4r-PEG-NH2) was chosen as the additive simultaneously. The special dissolution technique and macromolecular crosslinking structure endows the Cn-Nm gels with better performance than that of gels prepared by acid dissolving method with micromolecule crosslinker. First, Cn-Nm gels own strong toughness with 500 kPa tensile strength and 1000% elongation, about 400% swelling ratio and fast water absorption rate. Second, about 300 kPa adhesive strength and strippability between the gels and skin is achieved. More importantly, Cn-Nm gels show nearly 100% antibacterial rate towards Escherichia coli and Staphylococcus aureus. Excellent biocompatibility is also proved by the mouse fibroblasts tests. All of the performance makes this developed chitosan-based gel be the potential candidate as a wound dressing.

Reducing the Burn Marks on Injection-Molded Parts by External Gas-Assisted Injection Molding.

A burn mark is a sort of serious surface defect on injection-molded parts. In some cases, it can be difficult to reduce the burn marks by traditional methods. In this study, external gas-assisted injection molding (EGAIM) was introduced to reduce the burn marks, as EGAIM has been reported to reduce the holding pressure. The parts with different severities of burn marks were produced by EGAIM and conventional injection molding (CIM) with the same molding parameters but different gas parameters. The burn marks were quantified by an image processing method and the quantitative method was introduced to discuss the influence of the gas parameters on burn marks. The results show that the burn marks can be eliminated by EGAIM without changing the structure of the part or the mold, and the severity of the burn marks changed from 4.98% with CIM to 0% with EGAIM. Additionally, the gas delay time is the most important gas parameter affecting the burn marks.

Stereotactic technology for 3D bioprinting: from the perspective of robot mechanism.

Three-dimensional (3D) bioprinting has been widely applied in the field of biomedical engineering because of its rapidly individualized fabrication and precisely geometric designability. The emerging demand for bioprinted tissues/organs with bio-inspired anisotropic property is stimulating new bioprinting strategies. Stereotactic bioprinting is regarded as a preferable strategy for this purpose, which can perform bioprinting at the target position from any desired orientation in 3D space. In this work, based on the motion characteristics analysis of the stacked bioprinting technologies, mechanism configurations and path planning methods for robotic stereotactic bioprinting were investigated and a prototype system based on the double parallelogram mechanism was introduced in detail. Moreover, the influence of the time dimension on stereotactic bioprinting was discussed. Finally, technical challenges and future trends of stereotactic bioprinting within the field of biomedical engineering were summarized.

Warpage Prediction of RHCM Crystalline Parts Based on Multi-Layers.

Warpage is a typical defect for injection-molded parts, especially for crystalline parts molded by rapid heat cycle molding (RHCM). In this paper, a prediction method is proposed for predicting the warpage of crystalline parts molded by the RHCM process. Multi-layer models were established to predict warpage with the same thicknesses as the skin-core structures in the molded parts. Warpages were defined as the deformations calculated by the multi-layer models. The deformations were solved using the classical laminated plate theory by Abaqus. A model was introduced to describe the elastic modulus with the influence of temperature and crystallinity. The simulation process was divided into two procedures, before ejection and after ejection. Thermal stresses and thermal strains were simulated, respectively, in the procedure before ejection and after ejection. The prediction results were compared with the experimental results, which showed that the average errors between predicted warpage and average experimental warpage are, respectively, 7.0%, 3.5%, and 4.4% in conventional injection molding (CIM), in RHCM under a 60 °C heating mold (RHCM60), and in RHCM under a 90 °C heating mold (RHCM90).

Applications of 3D bioprinting in tissue engineering: advantages, deficiencies, improvements, and future perspectives.

Over the past decade, 3D bioprinting technology has progressed tremendously in the field of tissue engineering in its ability to fabricate individualized biological constructs with precise geometric designability, which offers us the capability to bridge the divergence between engineered tissue constructs and natural tissues. In this work, we first review the current widely used 3D bioprinting approaches, cells, and materials. Next, the updated applications of this technique in tissue engineering, including bone tissue, cartilage tissue, vascular grafts, skin, neural tissue, heart tissue, liver tissue and lung tissue, are briefly introduced. Then, the prominent advantages of 3D bioprinting in tissue engineering are summarized in detail: rapidly prototyping the customized structure, delivering cell-laden materials with high precision in space, and engineering with a highly controllable microenvironment. The current technical deficiencies of 3D bioprinted constructs in terms of mechanical properties and cell behaviors are afterward illustrated, as well as corresponding improvements. Finally, we conclude with future perspectives about 3D bioprinting in tissue engineering.

Biopsy Needle System With a Steerable Concentric Tube and Online Monitoring of Electrical Resistivity and Insertion Forces.

OBJECTIVE: Biopsies are the gold standard for clinical diagnosis. However, a discrepancy between the biopsy sample and target tissue because of misplacement of the biopsy spoon can lead to errors in the diagnosis and subsequent treatment. Thus, correctly determining whether the needle tip is in the tumor is crucial for accurate biopsy results. METHODS: A biopsy needle system was designed with a steerable, flexible, and superelastic concentric tube; electrodes to monitor the electrical resistivity; and load cells to monitor the insertion force. The degrees of freedom were analyzed for two working modes: straight-line and deflection. RESULTS: Experimental results showed that the system could perceive the tissue type in online based on the electrical resistivity. In addition, changes in the insertion force indicated transitions between the interfaces of adjacent tissue layers. CONCLUSION: The two monitoring methods guarantee that the biopsy spoon is at the desired position inside the tumor during an operation. SIGNIFICANCE: The proposed biopsy needle system can be integrated into an autonomous robotic biopsy system.

High efficiency blue light-emitting devices based on quantum dots with core-shell structure design and surface modification.

Blue quantum dot (QD) light emitting diode (QLED) developments are far lagging behind the red and green ones as it becomes difficult to balance charge injection and photo stability than the latter. Here, we introduced a combination of a low band energy shell with better surfactants, which largely meet both abovementioned requirements. Our simulation pinpoints that it is the exposed Se on the QD surface, which causes non-radiative relaxations. By adding tributyl phosphine (TBP), which is a good ligand to Se, we recover photoluminescence quantum yield (PLQY) from less than 8.0% up to above 85.0%. The corresponding external quantum efficiency (EQE) of QLEDs increases from 3.1% to 10.1%. This demonstrates that the low bandgap shell with effective surfactant passivation is a promising strategy to enhance QLED performance.

A novel fluoroscopy-based robot system for pedicle screw fixation surgery.

BACKGROUND: Robot-assisted pedicle screw insertion has gained popularity in the spinal surgery field. Due to high cost, these spinal robots are not extensively applied in clinical surgeries. Developing an effective robot system with low cost and high clinical acceptability is one of the future trends. METHODS: We developed a novel fluoroscopy-based robot system for pedicle screw insertion. Four live pigs were conducted with percutaneous pedicle screw insertion. Robot-assisted surgery was performed on the left side of pedicle, while the right opposite side is placed by freehand. The respect accuracy, surgical time and fluoroscopy time were recorded. RESULTS: Robot-assisted group achieved 100% (23/23) accuracy. The average times (6.4 ± 1.7) for intraoperative fluoroscopy usage per procedure were lesser than freehand group (12.5 ± 3.6), and the surgical time (6.8 ± 2.1 min) per screw was reduced compared with freehand group (12.1 ± 4.8 min). CONCLUSIONS: Our robot system is cost-effective and feasible for pedicle screw placement. Low economic cost makes it easier for extensive application in primary hospitals.

High efficiency and stability of ink-jet printed quantum dot light emitting diodes.

The low efficiency and fast degradation of devices from ink-jet printing process hinders the application of quantum dot light emitting diodes on next generation displays. Passivating the trap states caused by both anion and cation under-coordinated sites on the quantum dot surface with proper ligands for ink-jet printing processing reminds a problem. Here we show, by adapting the idea of dual ionic passivation of quantum dots, ink-jet printed quantum dot light emitting diodes with an external quantum efficiency over 16% and half lifetime of more than 1,721,000 hours were reported for the first time. The liquid phase exchange of ligands fulfills the requirements of ink-jet printing processing for possible mass production. And the performance from ink-jet printed quantum dot light emitting diodes truly opens the gate of quantum dot light emitting diode application for industry.

Tailoring ordered microporous structure of cellulose-based membranes through molecular hydrophobicity design.

Ordered porous polymer membranes can be facilely prepared by breath figures. Previous studies have confirmed that the solidifying of polymer is crucial for the formation of ordered porous structures, which directly depends on the hydrophobicity of polymer. However, it is still unknown how strong hydrophobicity is required. Here, cellulose acetate derivatives (CADs) were used to investigate the effect of hydrophobicity on ordered porous structures. The CADs with different hydrophobicity were firstly synthesized via simple reactions, and then the porous membranes were fabricated by the breath figure method. It was found that the pore size showed a decreasing trend with hydrophobicity, and the degree of order of porous structures firstly increased and then dropped, showing a critical hydrophobicity value for the transition of the degree of order. Therefore, it was confirmed that suitable hydrophobicity is critical for ordered porous structures of CADs while excessive hydrophobicity may impair the ordered structures.

Hot-electron dynamics in quantum dots manipulated by spin-exchange Auger interactions.

The ability to effectively manipulate non-equilibrium 'hot' carriers could enable novel schemes for highly efficient energy harvesting and interconversion. In the case of semiconductor materials, realization of such hot-carrier schemes is complicated by extremely fast intraband cooling (picosecond to subpicosecond time scales) due to processes such as phonon emission. Here we show that using magnetically doped colloidal semiconductor quantum dots we can achieve extremely fast rates of spin-exchange processes that allow for 'uphill' energy transfer with an energy-gain rate that greatly exceeds the intraband cooling rate. This represents a dramatic departure from the usual situation where energy-dissipation via phonon emission outpaces energy gains due to standard Auger-type energy transfer at least by a factor of three. A highly favourable energy gain/loss rate ratio realized in magnetically doped quantum dots can enable effective schemes for capturing kinetic energy of hot, unrelaxed carriers via processes such as spin-exchange-mediated carrier multiplication and upconversion, hot-carrier extraction and electron photoemission.