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This work explores a spatial printing method to fabricate continuous fiber-reinforced thermoplastic composites (CFRTPCs), which can achieve exceptional mechanical performance. For models giving complex 3D stress distribution under loads, typical planar-layer based fiber placement usually fails to provide sufficient reinforcement due to their orientations being constrained to planes. The effectiveness of fiber reinforcement could be maximized by using multi-axis additive manufacturing (MAAM) to better control the orientation of continuous fibers in 3D-printed composites. Here, we propose a computational approach to generate 3D toolpaths that satisfy two major reinforcement objectives: (1) following the maximal stress directions in critical regions and (2) connecting multiple load-bearing regions by continuous fibers. Principal stress lines are first extracted in an input solid model to identify critical regions. Curved layers aligned with maximal stresses in these critical regions are generated by computing an optimized scalar field and extracting its iso-surfaces. Then, topological analysis and operations are applied to each curved layer to generate a computational domain that preserves fiber continuity between load-bearing regions. Lastly, continuous fiber toolpaths aligned with maximal stresses are generated on each surface layer by computing an optimized scalar field and extracting its iso-curves. A hardware system with dual robotic arms is employed to conduct the physical MAAM tasks depositing polymer or fiber reinforced polymer composite materials by applying a force normal to the extrusion plane to aid consolidation. When comparing to planar-layer based printing results in tension, up to 644% failure load and 240% stiffness are observed on shapes fabricated by our spatial printing method. We demonstrate the versatility of our approach through various complex load cases which demonstrate their successful implementation of continuous fiber printing in 3D., Emerging Materials, Group Masania

Introduction: This study aimed to synthesise the best available evidence on the safety and efficacy of using moxibustion and/or acupuncture to manage cancer-related insomnia (CRI). Methods: The PRISMA framework guided the review. Nine databases were searched from its inception to July 2020, published in English or Chinese. Randomised clinical trials (RCTs) of moxibustion and or acupuncture for the treatment of CRI were selected for inclusion. Methodological quality was assessed using the method suggested by the Cochrane collaboration. The Cochrane Review Manager was used to conduct a meta-analysis. Results: Fourteen RCTs met the eligibility criteria. Twelve RCTs used the Pittsburgh Sleep Quality Index (PSQI) score as continuous data and a meta-analysis showed positive effects of moxibustion and or acupuncture (n = 997, mean difference (MD) = −1.84, 95% confidence interval (CI) = −2.75 to −0.94, p < 0.01). Five RCTs using continuous data and a meta-analysis in these studies also showed significant difference between two groups (n = 358, risk ratio (RR) = 0.45, 95% CI = 0.26–0.80, I2 = 39%). Conclusion: The meta-analyses demonstrated that moxibustion and or acupuncture showed a positive effect in managing CRI. Such modalities could be considered an add-on option in the current CRI management regimen.

Despite the recent advances in artificial tissue and organ engineering, how to generate large size viable and functional complex organs still remains as a grand challenge for regenerative medicine. Three-dimensional bioprinting has demonstrated its advantages as one of the major methods in fabricating simple tissues, yet it still faces difficulties to generate vasculatures and preserve cell functions in complex organ production. Here, we overcome the limitations of conventional bioprinting systems by converting a six degree-of-freedom robotic arm into a bioprinter, therefore enables cell printing on 3D complex-shaped vascular scaffolds from all directions. We also developed an oil bath-based cell printing method to better preserve cell natural functions after printing. Together with a self-designed bioreactor and a repeated print-and-culture strategy, our bioprinting system is capable to generate vascularized, contractible, and long-term survived cardiac tissues. Such bioprinting strategy mimics the in vivo organ development process and presents a promising solution for in vitro fabrication of complex organs., Materials and Manufacturing, Industrial Design Engineering

Introduction: This study aimed to synthesise the best available evidence on the safety and efficacy of using moxibustion and/or acupuncture to manage cancer-related insomnia (CRI). Methods: The PRISMA framework guided the review. Nine databases were searched from its inception to July 2020, published in English or Chinese. Randomised clinical trials (RCTs) of moxibustion and or acupuncture for the treatment of CRI were selected for inclusion. Methodological quality was assessed using the method suggested by the Cochrane collaboration. The Cochrane Review Manager was used to conduct a meta-analysis. Results: Fourteen RCTs met the eligibility criteria. Twelve RCTs used the Pittsburgh Sleep Quality Index (PSQI) score as continuous data and a meta-analysis showed positive effects of moxibustion and or acupuncture (n = 997, mean difference (MD) = −1.84, 95% confidence interval (CI) = −2.75 to −0.94, p < 0.01). Five RCTs using continuous data and a meta-analysis in these studies also showed significant difference between two groups (n = 358, risk ratio (RR) = 0.45, 95% CI = 0.26–0.80, I2 = 39%). Conclusion: The meta-analyses demonstrated that moxibustion and or acupuncture showed a positive effect in managing CRI. Such modalities could be considered an add-on option in the current CRI management regimen.

This article presents an efficient learning-based method to solve the inverse kinematic (IK) problem on soft robots with highly nonlinear deformation. The major challenge of efficiently computing IK for such robots is due to the lack of analytical formulation for either forward or inverse kinematics. To address this challenge, we employ neural networks to learn both the mapping function of forward kinematics and also the Jacobian of this function. As a result, Jacobian-based iteration can be applied to solve the IK problem. A sim-to-real training transfer strategy is conducted to make this approach more practical. We first generate a large number of samples in a simulation environment for learning both the kinematic and the Jacobian networks of a soft robot design. Thereafter, a sim-to-real layer of differentiable neurons is employed to map the results of simulation to the physical hardware, where this sim-to-real layer can be learned from a very limited number of training samples generated on the hardware., Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Materials and Manufacturing, Mechatronic Design

Soft robots can safely interact with environments because of their mechanical compliance. Self-collision is also employed in the modern design of soft robots to enhance their performance during different tasks. However, developing an efficient and reliable simulator that can handle the collision response well, is still a challenging task in the research of soft robotics. This paper presents a collision-aware simulator based on geometric optimization, in which we develop a highly efficient and realistic collision checking / response model incorporating a hyperelastic material property. Both actuated deformation and collision response for soft robots are formulated as geometry-based objectives. The collision-free body of a soft robot can be obtained by minimizing the geometry-based objective function. Unlike the FEA-based physical simulation, the proposed pipeline performs a much lower computational cost. Moreover, adaptive remeshing is applied to achieve the improvement of the convergence when dealing with soft robots that have large volume variations. Experimental tests are conducted on different soft robots to verify the performance of our approach., Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Emerging Materials

In this paper, a deep learning framework combined with isogeometric analysis (IGA for short) called IGA-Reuse-Net is proposed for efficient reuse of numerical simulation on a set of topology-consistent models. Compared with previous data-driven numerical simulation methods only for simple computational domains, our method can predict high-accuracy PDE solutions over topology-consistent geometries with complex boundaries. UNet3+ architecture with interlaced sparse self-attention (ISSA) module is used to enhance the performance of the network. In addition, we propose a new loss function that combines a coefficients loss and a numerical solution loss. Several training datasets with topology-consistent models are constructed for the proposed framework. To verify the effectiveness of our approach, two different types of Poisson equations with different source functions are solved on three datasets with different topologies. Our framework can achieve a good trade-off between accuracy and efficiency. It outperforms the physics-informed neural network (PINN for short) model and yields promising results of prediction., Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Materials and Manufacturing

Reconstruction of high-fidelity 3D objects or scenes is a fundamental research problem. Recent advances in RGB-D fusion have demonstrated the potential of producing 3D models from consumer-level RGB-D cameras. However, due to the discrete nature and limited resolution of their surface representations (e.g., point or voxel based), existing approaches suffer from the accumulation of errors in camera tracking and distortion in the reconstruction, which leads to an unsatisfactory 3D reconstruction. In this article, we present a method using on-the-fly implicits of Hermite Radial Basis Functions (HRBFs) as a continuous surface representation for camera tracking in an existing RGB-D fusion framework. Furthermore, curvature estimation and confidence evaluation are coherently derived from the inherent surface properties of the on-the-fly HRBF implicits, which are devoted to a data fusion with better quality. We argue that our continuous but on-the-fly surface representation can effectively mitigate the impact of noise with its robustness and constrain the reconstruction with inherent surface smoothness when being compared with discrete representations. Experimental results on various real-world and synthetic datasets demonstrate that our HRBF-fusion outperforms the state-of-the-art approaches in terms of tracking robustness and reconstruction accuracy., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright older of this work and the author uses the Dutch legislation to make this work public., Urban Data Science, Materials and Manufacturing

Despite the recent advances in artificial tissue and organ engineering, how to generate large size viable and functional complex organs still remains as a grand challenge for regenerative medicine. Three-dimensional bioprinting has demonstrated its advantages as one of the major methods in fabricating simple tissues, yet it still faces difficulties to generate vasculatures and preserve cell functions in complex organ production. Here, we overcome the limitations of conventional bioprinting systems by converting a six degree-of-freedom robotic arm into a bioprinter, therefore enables cell printing on 3D complex-shaped vascular scaffolds from all directions. We also developed an oil bath-based cell printing method to better preserve cell natural functions after printing. Together with a self-designed bioreactor and a repeated print-and-culture strategy, our bioprinting system is capable to generate vascularized, contractible, and long-term survived cardiac tissues. Such bioprinting strategy mimics the in vivo organ development process and presents a promising solution for in vitro fabrication of complex organs., Materials and Manufacturing

Objective: To assess the association of baseline anti-Mullerian hormone (AMH) levels with ovulation, time to ovulation and fertility outcomes in women with polycystic ovary syndrome (PCOS) receiving clomiphene citrate (CC) and compare this with placebo. Design(s): Secondary analysis of the PCOSAct trial (NCT01573858). Setting(s): 27 trial centres in mainland China. Population or sample: 1000 infertile women with PCOS receiving either CC or placebo. Method(s): Baseline serum AMH was measured and analysed as a continuous and as a categorical variable. Interaction between AMH and CC was tested. Predictive values of AMH for ovulation, time to ovulation and fertility outcomes were assessed. Main Outcome Measure(s): Ovulation and time to ovulation. Result(s): 900 baseline AMH data were available for analysis. There were no significant interactions with ovulation or conception for AMH and CC treatment (P = 0.782 and 0.419, respectively). Women in the upper quartile of AMH >15.88 ng/ml had significant lower ovulation (odds ratio [OR] 0.34, 95% CI 0.20-0.58) and conception rates (OR 0.65, 95% CI 0.42-1.00) compared with women in the lower quartile. Associations of AMH with clinical pregnancy (OR 0.98, 95% CI 0.95-1.01) and live birth (OR 0.98, 95% CI 0.96-1.01) were not significant. Ovulation rate increased until baseline AMH levels >=7.0 ng/ml in women treated with CC but decreased when AMH increased in women with placebo. When AMH <7.0 ng/ml, an AMH threshold at 4.11 ng/ml predicted ovulation in women receiving CC (area under the curve [AUC] 0.64, 95% CI 0.42-0.86), with a sensitivity of 64% and a specificity of 62%, whereas prediction was poor for AMH >=7.0 ng/ml (AUC 0.38, 95% CI 0.28-0.47). Median time to ovulation was 35 days in the lower quartile for women with placebo but this was significantly prolonged up to 98 days in the upper quartile. CC significantly shortened the time to ovulation up to 56 days. Conclusion(s): Among women with PCOS, high baseline AMH levels w

Objective: To assess the association of baseline anti-Mullerian hormone (AMH) levels with ovulation, time to ovulation and fertility outcomes in women with polycystic ovary syndrome (PCOS) receiving clomiphene citrate (CC) and compare this with placebo. Design(s): Secondary analysis of the PCOSAct trial (NCT01573858). Setting(s): 27 trial centres in mainland China. Population or sample: 1000 infertile women with PCOS receiving either CC or placebo. Method(s): Baseline serum AMH was measured and analysed as a continuous and as a categorical variable. Interaction between AMH and CC was tested. Predictive values of AMH for ovulation, time to ovulation and fertility outcomes were assessed. Main Outcome Measure(s): Ovulation and time to ovulation. Result(s): 900 baseline AMH data were available for analysis. There were no significant interactions with ovulation or conception for AMH and CC treatment (P = 0.782 and 0.419, respectively). Women in the upper quartile of AMH >15.88 ng/ml had significant lower ovulation (odds ratio [OR] 0.34, 95% CI 0.20-0.58) and conception rates (OR 0.65, 95% CI 0.42-1.00) compared with women in the lower quartile. Associations of AMH with clinical pregnancy (OR 0.98, 95% CI 0.95-1.01) and live birth (OR 0.98, 95% CI 0.96-1.01) were not significant. Ovulation rate increased until baseline AMH levels >=7.0 ng/ml in women treated with CC but decreased when AMH increased in women with placebo. When AMH <7.0 ng/ml, an AMH threshold at 4.11 ng/ml predicted ovulation in women receiving CC (area under the curve [AUC] 0.64, 95% CI 0.42-0.86), with a sensitivity of 64% and a specificity of 62%, whereas prediction was poor for AMH >=7.0 ng/ml (AUC 0.38, 95% CI 0.28-0.47). Median time to ovulation was 35 days in the lower quartile for women with placebo but this was significantly prolonged up to 98 days in the upper quartile. CC significantly shortened the time to ovulation up to 56 days. Conclusion(s): Among women with PCOS, high baseline AMH levels w

In this paper, we present a new computational pipeline for designing and fabricating 4D garments as knitwear that considers comfort during body movement. This is achieved by careful control of elasticity distribution to reduce uncomfortable pressure and unwanted sliding caused by body motion. We exploit the ability to knit patterns in different elastic levels by single-jersey jacquard (SJJ) with two yarns. We design the distribution of elasticity for a garment by physics-based computation, the optimized elasticity on the garment is then converted into instructions for a digital knitting machine by two algorithms proposed in this paper. Specifically, a graph-based algorithm is proposed to generate knittable stitch meshes that can accurately capture the 3D shape of a garment, and a tiling algorithm is employed to assign SJJ patterns on the stitch mesh to realize the designed distribution of elasticity. The effectiveness of our approach is verified on simulation results and on specimens physically fabricated by knitting machines., Accepted Author Manuscript, Materials and Manufacturing, Mechatronic Design

In this paper, we present a new computational pipeline for designing and fabricating 4D garments as knitwear that considers comfort during body movement. This is achieved by careful control of elasticity distribution to reduce uncomfortable pressure and unwanted sliding caused by body motion. We exploit the ability to knit patterns in different elastic levels by single-jersey jacquard (SJJ) with two yarns. We design the distribution of elasticity for a garment by physics-based computation, the optimized elasticity on the garment is then converted into instructions for a digital knitting machine by two algorithms proposed in this paper. Specifically, a graph-based algorithm is proposed to generate knittable stitch meshes that can accurately capture the 3D shape of a garment, and a tiling algorithm is employed to assign SJJ patterns on the stitch mesh to realize the designed distribution of elasticity. The effectiveness of our approach is verified on simulation results and on specimens physically fabricated by knitting machines., Accepted Author Manuscript, Materials and Manufacturing, Mechatronic Design

The anisotropy of mechanical strength on a 3D printed model can be controlled in a multi-axis 3D printing system as materials can be accumulated along dynamically varied directions. In this paper, we present a new computational framework to generate specially designed layers and toolpaths of multi-axis 3D printing for strengthening a model by aligning filaments along the directions with large stresses. The major challenge comes from how to effectively decompose a solid into a sequence of strength-aware and collision-free working surfaces. We formulate it as a problem to compute an optimized governing field together with a selected orientation of fabrication setup. Iso-surfaces of the governing field are extracted as working surface layers for filament alignment. Supporting structures in curved layers are constructed by extrapolating the governing field to enable the fabrication of overhangs. Compared with planar-layer based Fused Deposition Modeling (FDM) technology, models fabricated by our method can withstand up to 6.35× loads in experimental tests., Materials and Manufacturing

We present a method for effectively planning the motion trajectory of robots in manufacturing tasks, the tool paths of which are usually complex and have a large number of discrete time constraints as waypoints. Kinematic redundancy also exists in these robotic systems. The jerk of motion is optimized in our trajectory planning method at the meanwhile of fabrication process to improve the quality of fabrication. Our method is based on a sampling strategy and consists of two major parts. After determining an initial path by graph search, a greedy algorithm is adopted to optimize a path by locally applying adaptive filers in the regions with large jerks. The filtered result is obtained by numerical optimization. In order to achieve efficient computation, an adaptive sampling method is developed for learning a collision-indication function that is represented as a support-vector machine. Applications in robot-Assisted 3-D printing are given in this article to demonstrate the functionality of our approach. Note to Practitioners-In robot-Assisted manufacturing applications, robotic arms are employed to realize the motion of workpieces (or machining tools) specified as a sequence of waypoints with the positions of tool tip and the tool orientations constrained. The required degree of freedom (DOF) is often less than the robotic hardware system (e.g., a robotic arm has six-DOF). Specifically, rotations of the workpiece around the axis of a tool can be arbitrary (see Fig. 1 for an example). By using this redundancy, i.e., there are many possible poses of a robotic arm to realize a given waypoint, the trajectory of robots can be optimized to consider the performance of motion in velocity, acceleration, and jerk in the joint space. In addition, when fabricating complex models, each tool path can have a large amount of waypoints. It is crucial for a motion planning algorithm to compute a smooth and collision-free trajectory of robot to improve the fabrication quality. The t, Materials and Manufacturing, Mechatronic Design

3D printing techniques such as Fused Deposition Modeling (FDM) have enabled the fabrication of complex geometry quickly and cheaply. Objects are produced by filling (a portion of) the 2D polygons of consecutive layers with contour-parallel extrusion toolpaths. Uniform width toolpaths consisting of inward offsets from the outline polygons produce over- and underfill regions in the center of the shape, which are especially detrimental to the mechanical performance of thin parts. In order to fill shapes with arbitrary diameter densely the toolpaths require adaptive width. Existing approaches for generating toolpaths with adaptive width result in a large variation in widths, which for some hardware systems is difficult to realize accurately. In this paper we present a framework which supports multiple schemes to generate toolpaths with adaptive width, by employing a function to decide the number of beads and their widths. Furthermore, we propose a novel scheme which reduces extreme bead widths, while limiting the number of altered toolpaths. We statistically validate the effectiveness of our framework and this novel scheme on a data set of representative 3D models, and physically validate it by developing a technique, called back pressure compensation, for off-the-shelf FDM systems to effectively realize adaptive width., Materials and Manufacturing, Mechatronic Design

The anisotropy of mechanical strength on a 3D printed model can be controlled in a multi-axis 3D printing system as materials can be accumulated along dynamically varied directions. In this paper, we present a new computational framework to generate specially designed layers and toolpaths of multi-axis 3D printing for strengthening a model by aligning filaments along the directions with large stresses. The major challenge comes from how to effectively decompose a solid into a sequence of strength-aware and collision-free working surfaces. We formulate it as a problem to compute an optimized governing field together with a selected orientation of fabrication setup. Iso-surfaces of the governing field are extracted as working surface layers for filament alignment. Supporting structures in curved layers are constructed by extrapolating the governing field to enable the fabrication of overhangs. Compared with planar-layer based Fused Deposition Modeling (FDM) technology, models fabricated by our method can withstand up to 6.35× loads in experimental tests., Materials and Manufacturing

We present a method for effectively planning the motion trajectory of robots in manufacturing tasks, the tool paths of which are usually complex and have a large number of discrete time constraints as waypoints. Kinematic redundancy also exists in these robotic systems. The jerk of motion is optimized in our trajectory planning method at the meanwhile of fabrication process to improve the quality of fabrication. Our method is based on a sampling strategy and consists of two major parts. After determining an initial path by graph search, a greedy algorithm is adopted to optimize a path by locally applying adaptive filers in the regions with large jerks. The filtered result is obtained by numerical optimization. In order to achieve efficient computation, an adaptive sampling method is developed for learning a collision-indication function that is represented as a support-vector machine. Applications in robot-Assisted 3-D printing are given in this article to demonstrate the functionality of our approach. Note to Practitioners-In robot-Assisted manufacturing applications, robotic arms are employed to realize the motion of workpieces (or machining tools) specified as a sequence of waypoints with the positions of tool tip and the tool orientations constrained. The required degree of freedom (DOF) is often less than the robotic hardware system (e.g., a robotic arm has six-DOF). Specifically, rotations of the workpiece around the axis of a tool can be arbitrary (see Fig. 1 for an example). By using this redundancy, i.e., there are many possible poses of a robotic arm to realize a given waypoint, the trajectory of robots can be optimized to consider the performance of motion in velocity, acceleration, and jerk in the joint space. In addition, when fabricating complex models, each tool path can have a large amount of waypoints. It is crucial for a motion planning algorithm to compute a smooth and collision-free trajectory of robot to improve the fabrication quality. The t, Materials and Manufacturing, Mechatronic Design

3D printing techniques such as Fused Deposition Modeling (FDM) have enabled the fabrication of complex geometry quickly and cheaply. Objects are produced by filling (a portion of) the 2D polygons of consecutive layers with contour-parallel extrusion toolpaths. Uniform width toolpaths consisting of inward offsets from the outline polygons produce over- and underfill regions in the center of the shape, which are especially detrimental to the mechanical performance of thin parts. In order to fill shapes with arbitrary diameter densely the toolpaths require adaptive width. Existing approaches for generating toolpaths with adaptive width result in a large variation in widths, which for some hardware systems is difficult to realize accurately. In this paper we present a framework which supports multiple schemes to generate toolpaths with adaptive width, by employing a function to decide the number of beads and their widths. Furthermore, we propose a novel scheme which reduces extreme bead widths, while limiting the number of altered toolpaths. We statistically validate the effectiveness of our framework and this novel scheme on a data set of representative 3D models, and physically validate it by developing a technique, called back pressure compensation, for off-the-shelf FDM systems to effectively realize adaptive width., Materials and Manufacturing, Mechatronic Design

Silicones have desirable properties such as skin-safety, high temperature-resistance, and flexibility. Many applications require the presence of a hard body connected to the silicone. Traditionally, it has been difficult to create strong bonding between silicones and hard materials. In this study, a technique is presented to control the bonding strength between silicones and thermoplastics through mechanical interlocking. This is realized through a hybrid fabrication method where silicone is cast onto a 3D-printed mold and interlocking structure. The influence of the structure's design parameters on the bonding strength is explored through theoretical modeling and physical testing, while the manufacturability of the 3D-printed structure is ensured. A CAD tool is developed to automatically apply the interlocking structure to product surfaces. The user interface visualizes the theoretical strength of the cells as the designer adjusts the cell parameters, allowing the designer to iteratively optimize the structure to the product's load case. The bonding strength of the presented mechanical interlocking structure is more than 5.5 times higher than can be achieved with a commercially available primer. The presented technique enables custom digital design and manufacturing of durable free-form parts. This is demonstrated through application of the technique in over-molded products, airtight seals, and soft pneumatic actuators., Materials and Manufacturing, Mechatronic Design

Research question: The study aimed to evaluate the associations of endocrine and ultrasound characteristics with metabolic syndrome in women with polycystic ovary syndrome (PCOS), and whether these associations were modified by body mass index (BMI). Design(s): The study was a secondary analysis of baseline data from a randomized controlled trial of induction of ovulation in women with PCOS. Result(s): Among 947 Chinese women with PCOS, 153 (16.2%) were diagnosed with metabolic syndrome. The prevalence of metabolic syndrome in women with normal (<24 kg/m2) and high (>=24 kg/m2) BMI was 3.6% and 30.5%, respectively. In all women, a high free androgen index (FAI >=5%) was positively associated with metabolic syndrome (adjusted odds ratio [OR] 2.06, 95% confidence interval [CI] 1.11-3.82). High FAI was positively associated with metabolic syndrome among women with high BMI (adjusted OR 3.37, 95% CI 1.78-6.37), but the association was not significant in women with normal BMI (adjusted OR 1.27, 95% CI 0.34-4.70). The presence of polycystic ovary morphology was negatively associated with metabolic syndrome (adjusted OR 0.52, 95% CI 0.26-1.03) in all women (normal BMI adjusted OR 0.42, 95% CI 0.11-1.67; high BMI adjusted OR 0.54, 95% CI 0.23-1.28). LH, sex hormone-binding globulin (SHBG) and anti-Mullerian hormone (AMH) were negatively associated with metabolic syndrome. The associations of FAI, SHBG and AMH in relation to metabolic syndrome were significantly modified by BMI. Conclusion(s): The associations of endocrine characteristic with metabolic syndrome were modified by BMI in women with PCOS. Women with PCOS and normal BMI did not have an increased risk of metabolic syndrome.Copyright © 2019

Introduction The tremendous popularity of acupuncture in Australia demands continual safety assessment. This review aimed to determine the characteristics of acupuncture related adverse events, analyse their possible causes, and inform future research and practice. Methods Across 8 databases, all types of clinical trials, surveys, and case reports from 2012 to 2018 reporting adverse events associated with the use of acupuncture in Australia on human subjects were systematically reviewed. Types of acupuncture including manual acupuncture, electro acupuncture and laser acupuncture. Incidence and form of acupuncture related adverse events were the key outcomes of this study. In addition, the quality of adverse events reporting and the likelihood of causality were examined by two reviewers and checked by two experts specialised in acupuncture. Results The 17 analysed studies encompassed ten randomised controlled trials, two nonrandomised controlled trials, three uncontrolled clinical trials, and two case reports, with a total of 1160 participants receiving true acupuncture. Feelings of dizziness, fatigue and nausea were the most common adverse events identified in our review across all acupuncture modalities. Conclusions Acupuncture is generally a safe modality and serious adverse events after treatment are uncommon when supported with well-established guidelines and practiced by licensed, qualified practitioners.

Research question: The study aimed to evaluate the associations of endocrine and ultrasound characteristics with metabolic syndrome in women with polycystic ovary syndrome (PCOS), and whether these associations were modified by body mass index (BMI). Design(s): The study was a secondary analysis of baseline data from a randomized controlled trial of induction of ovulation in women with PCOS. Result(s): Among 947 Chinese women with PCOS, 153 (16.2%) were diagnosed with metabolic syndrome. The prevalence of metabolic syndrome in women with normal (<24 kg/m2) and high (>=24 kg/m2) BMI was 3.6% and 30.5%, respectively. In all women, a high free androgen index (FAI >=5%) was positively associated with metabolic syndrome (adjusted odds ratio [OR] 2.06, 95% confidence interval [CI] 1.11-3.82). High FAI was positively associated with metabolic syndrome among women with high BMI (adjusted OR 3.37, 95% CI 1.78-6.37), but the association was not significant in women with normal BMI (adjusted OR 1.27, 95% CI 0.34-4.70). The presence of polycystic ovary morphology was negatively associated with metabolic syndrome (adjusted OR 0.52, 95% CI 0.26-1.03) in all women (normal BMI adjusted OR 0.42, 95% CI 0.11-1.67; high BMI adjusted OR 0.54, 95% CI 0.23-1.28). LH, sex hormone-binding globulin (SHBG) and anti-Mullerian hormone (AMH) were negatively associated with metabolic syndrome. The associations of FAI, SHBG and AMH in relation to metabolic syndrome were significantly modified by BMI. Conclusion(s): The associations of endocrine characteristic with metabolic syndrome were modified by BMI in women with PCOS. Women with PCOS and normal BMI did not have an increased risk of metabolic syndrome.Copyright © 2019

Actuators using soft materials feature a large number of degrees of freedom. This tremendous flexibility allows a soft actuator to passively adapt its shape to the objects under interaction. In this paper, we propose a novel proprioception method for soft actuators during real-time interaction with previously unknown objects. First, we design a color-based sensing structure that instantly translates the inflation of a bellow into changes in color, which are subsequently detected by a miniaturized color sensor. The color sensor is small and, thus, multiple of them can be integrated into soft pneumatic actuators to reflect local deformations. Second, we make use of a feed-forward neural network to reconstruct a multivariate global shape deformation from local color signals. Our results demonstrate that deformations of the actuator during interaction, including sigmoid-like shapes, can be accurately reconstructed. The accurate shape sensing represents a significant step toward closed-loop control of soft robots in unstructured environments., Materials and Manufacturing, Mechatronic Design

2D coil design limits the use of wireless power transfer (WPT) in many products with freeform outer shapes. In this paper, enabled by 3D printed electronics, we propose a systematic approach to design and fabricate 3D coils for WPT. Based on the circular spiral and rectangular spiral patterns, 3D receiver and transmitter coils can be generated on an arbitrarily selected region of a product and its offset, respectively. Mathematical models are proposed to estimate the self-inductance and the mutual-inductance of the 3D arbitrarily shaped coils for 3D WPT. This leads to a new design approach of a 3D WPT system. Several sets of 3D printed WPT systems were designed, simulated, and prototyped to demonstrate the effectiveness of the proposed design approach as well as the mathematical models. The calculation speed of the proposed mathematical models is 30 times faster than the simulation, and compared with the measurement results, the calculation results have mean absolute errors of 2.63% and 4.45% regarding the self- and the mutual-inductance, where the simulation results have mean absolute errors of 1.20% and 2.38%, respectively. Measurements also indicate that with a 5V input, the prototypes are able to deliver 1-watt power at an efficiency ranging between 20.9% and 25.3%. It was concluded that the proposed approach is feasible and promising for designing and manufacturing WPT using 3D printed electronics., Mechatronic Design

Bas-relief is characterized by its unique presentation of intrinsic shape properties and/or detailed appearance using materials raised up in different degrees above a background. However, many bas-relief modeling methods could not manipulate scene details well. We propose a simple and effective solution for two kinds of bas-relief modeling (i.e., structure-preserving and detail-preserving), which is different from the prior tone mapping alike methods. Our idea originates from an observation on typical 3D models which are decomposed into a piecewise smooth base layer and a detail layer in normal field. Proper manipulation of the two layers contributes to both structure-preserving and detail-preserving bas-relief modeling. We solve the modeling problem in a discrete geometry processing setup that uses normal-based mesh processing as a theoretical foundation. Specifically, using the two-step mesh smoothing mechanism as a bridge, we transfer the bas-relief modeling problem into a discrete space, and solve it in a least-squares manner. Experiments and comparisons to other methods show that (i) geometry details are better preserved in the scenario with high compression ratios, and (ii) structures are clearly preserved without shape distortion and interference from details., Accepted author manuscript, Materials and Manufacturing

Introduction The tremendous popularity of acupuncture in Australia demands continual safety assessment. This review aimed to determine the characteristics of acupuncture related adverse events, analyse their possible causes, and inform future research and practice. Methods Across 8 databases, all types of clinical trials, surveys, and case reports from 2012 to 2018 reporting adverse events associated with the use of acupuncture in Australia on human subjects were systematically reviewed. Types of acupuncture including manual acupuncture, electro acupuncture and laser acupuncture. Incidence and form of acupuncture related adverse events were the key outcomes of this study. In addition, the quality of adverse events reporting and the likelihood of causality were examined by two reviewers and checked by two experts specialised in acupuncture. Results The 17 analysed studies encompassed ten randomised controlled trials, two nonrandomised controlled trials, three uncontrolled clinical trials, and two case reports, with a total of 1160 participants receiving true acupuncture. Feelings of dizziness, fatigue and nausea were the most common adverse events identified in our review across all acupuncture modalities. Conclusions Acupuncture is generally a safe modality and serious adverse events after treatment are uncommon when supported with well-established guidelines and practiced by licensed, qualified practitioners.

Actuators using soft materials feature a large number of degrees of freedom. This tremendous flexibility allows a soft actuator to passively adapt its shape to the objects under interaction. In this paper, we propose a novel proprioception method for soft actuators during real-time interaction with previously unknown objects. First, we design a color-based sensing structure that instantly translates the inflation of a bellow into changes in color, which are subsequently detected by a miniaturized color sensor. The color sensor is small and, thus, multiple of them can be integrated into soft pneumatic actuators to reflect local deformations. Second, we make use of a feed-forward neural network to reconstruct a multivariate global shape deformation from local color signals. Our results demonstrate that deformations of the actuator during interaction, including sigmoid-like shapes, can be accurately reconstructed. The accurate shape sensing represents a significant step toward closed-loop control of soft robots in unstructured environments., Materials and Manufacturing, Mechatronic Design

2D coil design limits the use of wireless power transfer (WPT) in many products with freeform outer shapes. In this paper, enabled by 3D printed electronics, we propose a systematic approach to design and fabricate 3D coils for WPT. Based on the circular spiral and rectangular spiral patterns, 3D receiver and transmitter coils can be generated on an arbitrarily selected region of a product and its offset, respectively. Mathematical models are proposed to estimate the self-inductance and the mutual-inductance of the 3D arbitrarily shaped coils for 3D WPT. This leads to a new design approach of a 3D WPT system. Several sets of 3D printed WPT systems were designed, simulated, and prototyped to demonstrate the effectiveness of the proposed design approach as well as the mathematical models. The calculation speed of the proposed mathematical models is 30 times faster than the simulation, and compared with the measurement results, the calculation results have mean absolute errors of 2.63% and 4.45% regarding the self- and the mutual-inductance, where the simulation results have mean absolute errors of 1.20% and 2.38%, respectively. Measurements also indicate that with a 5V input, the prototypes are able to deliver 1-watt power at an efficiency ranging between 20.9% and 25.3%. It was concluded that the proposed approach is feasible and promising for designing and manufacturing WPT using 3D printed electronics., Mechatronic Design

Bas-relief is characterized by its unique presentation of intrinsic shape properties and/or detailed appearance using materials raised up in different degrees above a background. However, many bas-relief modeling methods could not manipulate scene details well. We propose a simple and effective solution for two kinds of bas-relief modeling (i.e., structure-preserving and detail-preserving), which is different from the prior tone mapping alike methods. Our idea originates from an observation on typical 3D models which are decomposed into a piecewise smooth base layer and a detail layer in normal field. Proper manipulation of the two layers contributes to both structure-preserving and detail-preserving bas-relief modeling. We solve the modeling problem in a discrete geometry processing setup that uses normal-based mesh processing as a theoretical foundation. Specifically, using the two-step mesh smoothing mechanism as a bridge, we transfer the bas-relief modeling problem into a discrete space, and solve it in a least-squares manner. Experiments and comparisons to other methods show that (i) geometry details are better preserved in the scenario with high compression ratios, and (ii) structures are clearly preserved without shape distortion and interference from details., Accepted author manuscript, Materials and Manufacturing

The design of optimal structures and the planning of (additive manufacturing) fabrication sequences have been considered typically as two separate tasks that are performed consecutively. In the light of recent advances in robot-assisted (wire-arc) additive manufacturing which enable addition of material along curved surfaces, we present a novel topology optimization formulation which concurrently optimizes the structure and the fabrication sequence. For this, two sets of design variables, i.e., a density field for defining the structural layout, and a time field which determines the fabrication process order, are simultaneously optimized. These two fields allow to generate a sequence of intermediate structures, upon which manufacturing constraints (e.g., fabrication continuity and speed) are imposed. The proposed space-time formulation is general, and is demonstrated on three fabrication settings, considering self-weight of the intermediate structures, process-dependent critical loads, and time-dependent material properties., Materials and Manufacturing, Computational Design and Mechanics

The fabrication flexibility of 3D printing has sparked a lot of interest in designing structures with spatially graded material properties. In this paper, we propose a new type of density graded structure that is particularly designed for 3D printing systems based on filament extrusion. In order to ensure high-quality fabrication results, extrusion-based 3D printing requires not only that the structures are self-supporting, but also that extrusion toolpaths are continuous and free of self-overlap. The structure proposed in this paper, called CrossFill, complies with these requirements. In particular, CrossFill is a self-supporting foam structure, for which each layer is fabricated by a single, continuous and overlap-free path of material extrusion. Our method for generating CrossFill is based on a space-filling surface that employs spatially varying subdivision levels. Dithering of the subdivision levels is performed to accurately reproduce a prescribed density distribution. We demonstrate the effectiveness of CrossFill on a number of experimental tests and applications., Accepted author manuscript, Materials and Manufacturing

This paper presents a 3-D printing system that uses a low-cost off-the-shelf consumer projector to fabricate large models. Compared with traditional digital light processing (DLP) 3-D printers using a single vertical carriage, the platform of our DLP 3-D printer using delta mechanism can also move horizontally in the plane. We show that this system can print 3-D models much larger than traditional DLP 3-D printers. The major challenge to realize 3-D printing of large models in our system comes from how to cover a planar polygonal domain by a minimum number of rectangles with fixed size, which is NP-hard. We propose a simple yet efficient approximation algorithm to solve this problem. The key idea is to segment a polygonal domain using its medial axis and afterward merge small parts in the segmentation. Given an arbitrary polygon Ω with n generators (i.e., line segments and reflex vertices in Ω), we show that the time complexity of our algorithm is O(n²log² n) and the number of output rectangles covering Ω is O(Kn), where K is an input-polygon-dependent constant. A physical prototype system is built and several large 3-D models with complex geometric structures have been printed as examples to demonstrate the effectiveness of our approach., Accepted author manuscript, Materials and Manufacturing

STUDY DESIGN, SIZE, DURATION: This study was a secondary analysis of the Polycystic Ovary Syndrome Acupuncture and Clomiphene Trial (PCOSAct), a large randomized controlled trial conducted at 27 hospitals from 2012 to 2015 in mainland China. PARTICIPANTS/MATERIALS, SETTING, METHODS: Out of 1000 women with PCOS, SHS exposure status were available in 500 women, of whom 271 women were non-exposed and 229 exposed to cigarette smoke (170 women ?10 cigarettes per day as low-SHS exposed and 59 women >10 cigarettes per day as high-SHS exposed). We compared circulating sex steroids, glucose and lipid metabolism, metabolic syndrome and phenotypes, fertility and obstetric outcomes between non-exposed and exposed women. MAIN RESULTS AND THE ROLE OF CHANCE: Women exposed to SHS, compared to non-exposed women, had a higher serum total testosterone (1.7 vs 1.5 nmol/L, P = 0.01), free androgen index (5.7 vs 4.0, P = 0.001) and lower sex hormone binding globulin (30.1 vs 35.6 nmol/L, P = 0.03). Metabolic syndrome, but not other phenotypes, was more frequent in exposed women as compared to nonexposed women (21.8 vs 13.3%, adjusted odds ratio (OR)=1.66; 95% CI, 1.022.71, P = 0.04). Ovulation rates between exposed and nonexposed groups were not significantly different (76.9 vs 82.9%, adjusted OR=0.72; 95% CI, 0.451.15, P = 0.17). Conception rates were significant lower in the exposed group (26.6 vs 36.9%; adjusted OR=0.61; 95% CI, 0.410.91; P = 0.01), while clinical pregnancy and live birth rates showed a similar trend that was not statistically significant. Gestational age, birth weight and other obstetric outcomes were not affected by SHS exposure. LIMITATIONS, REASONS FOR CAUTION: Data on SHS exposure were missing in 50% of the women. We did not assay serum nicotine or cotinine levels to quantify the SHS exposure status. WIDER IMPLICATIONS OF THE FINDINGS: These data suggest that smoking partners of infertile women with PCOS who seek treatment should be advised to quit smoking.Copyr

STUDY DESIGN, SIZE, DURATION: This study was a secondary analysis of the Polycystic Ovary Syndrome Acupuncture and Clomiphene Trial (PCOSAct), a large randomized controlled trial conducted at 27 hospitals from 2012 to 2015 in mainland China. PARTICIPANTS/MATERIALS, SETTING, METHODS: Out of 1000 women with PCOS, SHS exposure status were available in 500 women, of whom 271 women were non-exposed and 229 exposed to cigarette smoke (170 women ?10 cigarettes per day as low-SHS exposed and 59 women >10 cigarettes per day as high-SHS exposed). We compared circulating sex steroids, glucose and lipid metabolism, metabolic syndrome and phenotypes, fertility and obstetric outcomes between non-exposed and exposed women. MAIN RESULTS AND THE ROLE OF CHANCE: Women exposed to SHS, compared to non-exposed women, had a higher serum total testosterone (1.7 vs 1.5 nmol/L, P = 0.01), free androgen index (5.7 vs 4.0, P = 0.001) and lower sex hormone binding globulin (30.1 vs 35.6 nmol/L, P = 0.03). Metabolic syndrome, but not other phenotypes, was more frequent in exposed women as compared to nonexposed women (21.8 vs 13.3%, adjusted odds ratio (OR)=1.66; 95% CI, 1.022.71, P = 0.04). Ovulation rates between exposed and nonexposed groups were not significantly different (76.9 vs 82.9%, adjusted OR=0.72; 95% CI, 0.451.15, P = 0.17). Conception rates were significant lower in the exposed group (26.6 vs 36.9%; adjusted OR=0.61; 95% CI, 0.410.91; P = 0.01), while clinical pregnancy and live birth rates showed a similar trend that was not statistically significant. Gestational age, birth weight and other obstetric outcomes were not affected by SHS exposure. LIMITATIONS, REASONS FOR CAUTION: Data on SHS exposure were missing in 50% of the women. We did not assay serum nicotine or cotinine levels to quantify the SHS exposure status. WIDER IMPLICATIONS OF THE FINDINGS: These data suggest that smoking partners of infertile women with PCOS who seek treatment should be advised to quit smoking.Copyr

Offsetting-based hollowing is a solid modeling operation widely used in 3D printing, which can change the model's physical properties and reduce the weight by generating voids inside a model. However, a hollowing operation can lead to additional supporting structures for fabrication in interior voids, which cannot be removed. As a consequence, the result of a hollowing operation is affected by these additional supporting structures when applying the operation to optimize physical properties of different models. This paper proposes a support-free hollowing framework to overcome the difficulty of fabricating voids inside a solid. The challenge of computing a support-free hollowing is decomposed into a sequence of shape optimization steps, which are repeatedly applied to interior mesh surfaces. The optimization of physical properties in different applications can be easily integrated into our framework. Comparing to prior approaches that can generate support-free inner structures, our hollowing operation can reduce more volume of material and thus provide a larger solution space for physical optimization. Experimental tests are taken on a number of 3D models to demonstrate the effectiveness of this framework., Accepted author manuscript, Materials and Manufacturing

Wireframe models are becoming a popular option in 3D printing. Generating sparse wireframe models using classic mesh simplification methods leads to models that require a lot of support structures in the layer-upon-layer additive process. In this paper we present a mesh simplification method that takes into account the overhang angle. Specifically, we propose a metric for self-supportability. By combining this novel metric together with the classic error metrics for mesh simplification, our method generates sparse wireframe models that need much less supports. Moreover, the operations of vertex position optimization and edge flipping are used to further increase self-supportability of the wireframe models. We demonstrate the effectiveness of the proposed method on a number of 3D models., Accepted author manuscript, Materials and Manufacturing

Manufacturing-oriented topology optimization has been extensively studied the past two decades, in particular for the conventional manufacturing methods, for example, machining and injection molding or casting. Both design and manufacturing engineers have benefited from these efforts because of the close-to-optimal and friendly-to-manufacture design solutions. Recently, additive manufacturing (AM) has received significant attention from both academia and industry. AM is characterized by producing geometrically complex components layer-by-layer, and greatly reduces the geometric complexity restrictions imposed on topology optimization by conventional manufacturing. In other words, AM can make near-full use of the freeform structural evolution of topology optimization. Even so, new rules and restrictions emerge due to the diverse and intricate AM processes, which should be carefully addressed when developing the AM-specific topology optimization algorithms. Therefore, the motivation of this perspective paper is to summarize the state-of-art topology optimization methods for a variety of AM topics. At the same time, this paper also expresses the authors’ perspectives on the challenges and opportunities in these topics. The hope is to inspire both researchers and engineers to meet these challenges with innovative solutions., Accepted author manuscript, Materials and Manufacturing

Handle-driven image warping based on linear blending is widely used in many applications because of its merits on intuitiveness, efficiency, and ease of implementation. In this paper, we develop a method to compute high-quality weights within a closed domain for image warping. The property of C2 continuity in weights is guaranteed by the carefully formulated basis functions. The efficiency of our algorithm is ensured by a closed-form formulation of the computation for weights. The cost of inserting a new handle is only the time to evaluate the distances from the new handle to all other sample points in the domain. A virtual handle insertion algorithm is developed to allow users to freely place handles within the domain while preserving the satisfaction of all expected criteria on weights for linear blending. Experimental examples for real-time applications are shown to demonstrate the effectiveness of this method., Accepted author manuscript, Materials and Manufacturing

Handle-driven image warping based on linear blending is widely used in many applications because of its merits on intuitiveness, efficiency, and ease of implementation. In this paper, we develop a method to compute high-quality weights within a closed domain for image warping. The property of C2 continuity in weights is guaranteed by the carefully formulated basis functions. The efficiency of our algorithm is ensured by a closed-form formulation of the computation for weights. The cost of inserting a new handle is only the time to evaluate the distances from the new handle to all other sample points in the domain. A virtual handle insertion algorithm is developed to allow users to freely place handles within the domain while preserving the satisfaction of all expected criteria on weights for linear blending. Experimental examples for real-time applications are shown to demonstrate the effectiveness of this method., Accepted author manuscript, Materials and Manufacturing

Wireframe models are becoming a popular option in 3D printing. Generating sparse wireframe models using classic mesh simplification methods leads to models that require a lot of support structures in the layer-upon-layer additive process. In this paper we present a mesh simplification method that takes into account the overhang angle. Specifically, we propose a metric for self-supportability. By combining this novel metric together with the classic error metrics for mesh simplification, our method generates sparse wireframe models that need much less supports. Moreover, the operations of vertex position optimization and edge flipping are used to further increase self-supportability of the wireframe models. We demonstrate the effectiveness of the proposed method on a number of 3D models., Accepted author manuscript, Materials and Manufacturing

Offsetting-based hollowing is a solid modeling operation widely used in 3D printing, which can change the model's physical properties and reduce the weight by generating voids inside a model. However, a hollowing operation can lead to additional supporting structures for fabrication in interior voids, which cannot be removed. As a consequence, the result of a hollowing operation is affected by these additional supporting structures when applying the operation to optimize physical properties of different models. This paper proposes a support-free hollowing framework to overcome the difficulty of fabricating voids inside a solid. The challenge of computing a support-free hollowing is decomposed into a sequence of shape optimization steps, which are repeatedly applied to interior mesh surfaces. The optimization of physical properties in different applications can be easily integrated into our framework. Comparing to prior approaches that can generate support-free inner structures, our hollowing operation can reduce more volume of material and thus provide a larger solution space for physical optimization. Experimental tests are taken on a number of 3D models to demonstrate the effectiveness of this framework., Accepted author manuscript, Materials and Manufacturing

Manufacturing-oriented topology optimization has been extensively studied the past two decades, in particular for the conventional manufacturing methods, for example, machining and injection molding or casting. Both design and manufacturing engineers have benefited from these efforts because of the close-to-optimal and friendly-to-manufacture design solutions. Recently, additive manufacturing (AM) has received significant attention from both academia and industry. AM is characterized by producing geometrically complex components layer-by-layer, and greatly reduces the geometric complexity restrictions imposed on topology optimization by conventional manufacturing. In other words, AM can make near-full use of the freeform structural evolution of topology optimization. Even so, new rules and restrictions emerge due to the diverse and intricate AM processes, which should be carefully addressed when developing the AM-specific topology optimization algorithms. Therefore, the motivation of this perspective paper is to summarize the state-of-art topology optimization methods for a variety of AM topics. At the same time, this paper also expresses the authors’ perspectives on the challenges and opportunities in these topics. The hope is to inspire both researchers and engineers to meet these challenges with innovative solutions., Accepted author manuscript, Materials and Manufacturing

This paper presents a new method to fabricate 3D models on a robotic printing system equipped with multi-axis motion. Materials are accumulated inside the volume along curved tool-paths so that the need of supporting structures can be tremendously reduced - if not completely abandoned - on all models. Our strategy to tackle the challenge of tool-path planning for multi-axis 3D printing is to perform two successive decompositions, first volume-to-surfaces and then surfaces-to-curves. The volume-to-surfaces decomposition is achieved by optimizing a scalar field within the volume that represents the fabrication sequence. The field is constrained such that its isovalues represent curved layers that are supported from below, and present a convex surface affording for collision-free navigation of the printer head. After extracting all curved layers, the surfaces-to-curves decomposition covers them with tool-paths while taking into account constraints from the robotic printing system. Our method successfully generates tool-paths for 3D printing models with large overhangs and high-genus topology. We fabricated several challenging cases on our robotic platform to verify and demonstrate its capabilities., Accepted author manuscript, Materials and Manufacturing

Item does not contain fulltext, Membrane cholesterol modulates a variety of cell signaling pathways and functions. While cholesterol depletion by high-density lipoproteins (HDLs) has potent anti-inflammatory effects in various cell types, its effects on inflammatory responses in macrophages remain elusive. Here we show overt pro-inflammatory effects of HDL-mediated passive cholesterol depletion and lipid raft disruption in murine and human primary macrophages in vitro. These pro-inflammatory effects were confirmed in vivo in peritoneal macrophages from apoA-I transgenic mice, which have elevated HDL levels. In line with these findings, the innate immune responses required for clearance of P. aeruginosa bacterial infection in lung were compromised in mice with low HDL levels. Expression analysis, ChIP-PCR, and combinatorial pharmacological and genetic intervention studies unveiled that both native and reconstituted HDL enhance Toll-like-receptor-induced signaling by activating a PKC-NF-kappaB/STAT1-IRF1 axis, leading to increased inflammatory cytokine expression. HDL's pro-inflammatory activity supports proper functioning of macrophage immune responses.

Self-reconfigurable modular robots (SRRobot) that can change their shape and function in different environments according to different tasks have caught a lot of attention recently. Most existing prototypes use professional electronic components with relatively expensive cost and high barrier of fabrication. In this paper, we present a low-cost SRRobot with double-cube modules. Our system is easy-to-build even for novices as all electric components are off-the-shelf and the structural components in plastics are made by 3D printing. To have a better design of interior structures, we first construct a design space for all feasible solutions that satisfy the constraints of fabrication. Then, an optimized solution is found by an objective function incorporating the factors of space utilization, structural sound-ness and assembly complexity. Thirty EasySRRobot modules are manufactured and assembled. The functionality of our algorithm is demonstrated by comparing an optimized interior design with other two feasible designs and realizing different motions on an EasySRRobot with four modules., Accepted author manuscript, Materials and Manufacturing

Recently, 3D printing has become a powerful tool for personal fabrication. However, the price of some materials is still high which limits its applications in home users. To optimize the volume of the model, while not largely affecting the strength of the objects, researchers propose algorithms to divide the model with different kinds of lightweight structures, such as frame structure, honeycomb cell structure, truss structure, medial axis tree. However, these algorithms are not suitable for the model whose internal space needs to be reused. In addition, the structural strength and static stability of the models, obtained with modern 3D model acquirement methods, are not guaranteed. In consequence, some models are too fragile to print and cannot be survived in daily usage, handling, and transportation or cannot stand in a stable. To handle the mentioned problems, an algorithm system is proposed based on cross sections in this work. The structural weak cross sections are enhanced, and structural strong cross sections are adaptively hollowed to meet a given structural strength, static stability, printability, etc., while the material usage is minimized. The proposed algorithm system has been tested on several typical 3D models. The experimental results demonstrate the effectiveness and practicability of our system., Author Accepted Manuscript, Materials and Manufacturing

Item does not contain fulltext, Membrane cholesterol modulates a variety of cell signaling pathways and functions. While cholesterol depletion by high-density lipoproteins (HDLs) has potent anti-inflammatory effects in various cell types, its effects on inflammatory responses in macrophages remain elusive. Here we show overt pro-inflammatory effects of HDL-mediated passive cholesterol depletion and lipid raft disruption in murine and human primary macrophages in vitro. These pro-inflammatory effects were confirmed in vivo in peritoneal macrophages from apoA-I transgenic mice, which have elevated HDL levels. In line with these findings, the innate immune responses required for clearance of P. aeruginosa bacterial infection in lung were compromised in mice with low HDL levels. Expression analysis, ChIP-PCR, and combinatorial pharmacological and genetic intervention studies unveiled that both native and reconstituted HDL enhance Toll-like-receptor-induced signaling by activating a PKC-NF-kappaB/STAT1-IRF1 axis, leading to increased inflammatory cytokine expression. HDL's pro-inflammatory activity supports proper functioning of macrophage immune responses.

Item does not contain fulltext, Membrane cholesterol modulates a variety of cell signaling pathways and functions. While cholesterol depletion by high-density lipoproteins (HDLs) has potent anti-inflammatory effects in various cell types, its effects on inflammatory responses in macrophages remain elusive. Here we show overt pro-inflammatory effects of HDL-mediated passive cholesterol depletion and lipid raft disruption in murine and human primary macrophages in vitro. These pro-inflammatory effects were confirmed in vivo in peritoneal macrophages from apoA-I transgenic mice, which have elevated HDL levels. In line with these findings, the innate immune responses required for clearance of P. aeruginosa bacterial infection in lung were compromised in mice with low HDL levels. Expression analysis, ChIP-PCR, and combinatorial pharmacological and genetic intervention studies unveiled that both native and reconstituted HDL enhance Toll-like-receptor-induced signaling by activating a PKC-NF-kappaB/STAT1-IRF1 axis, leading to increased inflammatory cytokine expression. HDL's pro-inflammatory activity supports proper functioning of macrophage immune responses.

Self-reconfigurable modular robots (SRRobot) that can change their shape and function in different environments according to different tasks have caught a lot of attention recently. Most existing prototypes use professional electronic components with relatively expensive cost and high barrier of fabrication. In this paper, we present a low-cost SRRobot with double-cube modules. Our system is easy-to-build even for novices as all electric components are off-the-shelf and the structural components in plastics are made by 3D printing. To have a better design of interior structures, we first construct a design space for all feasible solutions that satisfy the constraints of fabrication. Then, an optimized solution is found by an objective function incorporating the factors of space utilization, structural sound-ness and assembly complexity. Thirty EasySRRobot modules are manufactured and assembled. The functionality of our algorithm is demonstrated by comparing an optimized interior design with other two feasible designs and realizing different motions on an EasySRRobot with four modules., Accepted author manuscript, Materials and Manufacturing