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Background/Objective: This study aims to utilize advanced artificial intelligence (AI) image recog-nition technologies to establish a robust system for identifying features in lung computed tomog-raphy (CT) scans, thereby detecting respiratory infections such as SARS-CoV-2 pneumonia. Spe-cifically, the research focuses on developing a new model called Residual-Dense-Attention Gates U-Net (RDAG U-Net) to improve accuracy and efficiency in identification. Methods: This study employed Attention U-Net, Attention Res U-Net, and the newly developed RDAG U-Net model. RDAG U-Net extends the U-Net architecture by incorporating ResBlock and DenseBlock modules in the encoder to retain training parameters and reduce computation time. The training dataset in-cludes 3,520 CT scans from an open database, augmented to 10,560 samples through data en-hancement techniques. The research also focused on optimizing convolutional architectures, image preprocessing, interpolation methods, data management, and extensive fine-tuning of training parameters and neural network modules. Result: The RDAG U-Net model achieved an outstanding accuracy of 93.29% in identifying pulmonary lesions, with a 45% reduction in computation time compared to other models. The study demonstrated that RDAG U-Net performed stably during training and exhibited good generalization capability by evaluating loss values, model-predicted lesion annotations, and validation-epoch curves. Furthermore, using ITK-Snap to convert 2D pre-dictions into 3D lung and lesion segmentation models, the results delineated lesion contours, en-hancing interpretability. Conclusion: The RDAG U-Net model showed significant improvements in accuracy and efficiency in the analysis of CT images for SARS-CoV-2 pneumonia, achieving a 93.29% recognition accuracy and reducing computation time by 45% compared to other models. These results indicate the potential of the RDAG U-Net model in clinical applications, as it can accelerate the detection of pulmonary lesions and effectively enhance diagnostic accuracy. Additionally, the 2D and 3D visualization results allow physicians to understand lesions' morphology and distribution better, strengthening decision support capabilities and providing valuable medical diagnosis and treatment planning tools.

This study proposes a bile duct stent based on indirect 3D printing technology. Four ratio materials were synthesized from lactic acid (LA) and glycolide (GA) monomers by melt polymerization: PLA, PLGA (70:30), PLGA (50:50), and PLGA (30:70). The four kinds of material powders were preliminarily degraded, and the appearance was observed with an optical microscope (OM) and a camera. The weight and appearance of the four materials changed significantly after four weeks of degradation, which met the conditions for materials to be degraded within 4–6 weeks. Among them, PLGA (50:50) lost the most—the weight dropped to 13.4%. A stent with an outer diameter of 10 mm and an inner diameter of 8 mm was successfully manufactured by indirect 3D printing technology, demonstrating the potential of our research. Then, the degradation experiment was carried out on a cylindrical stent with a diameter of 6 mm and a height of 3 mm. The weight loss of the sample was less than that of the powder degradation, and the weight loss of PLGA (50:50) was the largest—the weight dropped to 79.6%. The nano-indenter system measured the mechanical properties of materials. Finally, human liver cancer cells Hep-3B were used to conduct in vitro cytotoxicity tests on the scaffolds to test the biocompatibility of the materials. A bile duct stent meeting commercial size requirements has been developed, instilling confidence in the potential of our research for future medical applications.

This study proposed a composite tibia defect scaffold with radial gradient porosity, utilizing finite element analysis to assess stress in the tibial region with significant critical-sized defects. Simulations for scaffolds with different porosities were conducted, designing an optimal tibia defect scaffold with radial gradient porosity for repairing and replacing critical bone defects. Radial gradient porosity scaffolds resulted in a more uniform stress distribution, reducing titanium alloy stiffness and alleviating stress shielding effects. The scaffold was manufactured using selective laser melting (SLM) technology with stress relief annealing to simplify porous structure fabrication. The study used New Zealand white rabbits’ tibia defect sites as simulation parameters, reconstructing the 3D model and implanting the composite scaffold. Finite element analysis in ANSYS-Workbench simulated forces under high-activity conditions, analyzing stress distribution and strain. In the simulation, the titanium alloy scaffold bore a maximum stress of 122.8626 MPa, while the centrally encapsulated HAp material delivered 27.92 MPa. The design demonstrated superior structural strength, thereby reducing stress concentration. The scaffold was manufactured using SLM, and the uniform design method was used to determine a collection of optimum annealing parameters. Nanoindentation and compression tests were used to determine the influence of annealing on the elastic modulus, hardness, and strain energy of the scaffold.

The challenges of respiratory infections persist as a global health crisis, placing substantial stress on healthcare infrastructures and necessitating ongoing investigation into efficacious treatment modalities. The persistent challenge of respiratory infections, including COVID-19, underscores the critical need for enhanced diagnostic methodologies to support early treatment interventions. This study introduces an innovative two-stage data analytics framework that leverages deep learning algorithms through a strategic combinatorial fusion technique, aimed at refining the accuracy of early-stage diagnosis of such infections. Utilizing a comprehensive dataset compiled from publicly available lung X-ray images, the research employs advanced pre-trained deep learning models to navigate the complexities of disease classification, addressing inherent data imbalances through methodical validation processes. The core contribution of this work lies in its novel application of combinatorial fusion, integrating select models to significantly elevate diagnostic precision. This approach not only showcases the adaptability and strength of deep learning in navigating the intricacies of medical imaging but also marks a significant step forward in the utilization of artificial intelligence to improve outcomes in healthcare diagnostics. The study’s findings illuminate the path toward leveraging technological advancements in enhancing diagnostic accuracies, ultimately contributing to the timely and effective treatment of respiratory diseases.

Ti-based metallic glasses have a high potential for implant applications. The feasibility of a new biocompatible Ti-based bulk metallic glass composite for selective laser melting (SLM) had been examined. Therefore, it is necessary to design a high-glass-forming-ability Ti-based metallic glass (∆Tx = 81 K, γ = 0.427, γm = 0.763), to fabricate a partial glass-formable spherical powder (the volume fraction of the amorphous phase in the atomized Ti-based powders being 73% [size < 25 μm], 61% [25–37 μm], and 50% [37–44 μm]), and establish an SLM parameter (a scan rate of 600 mm/s, a power of 120 W, and an overlap of 10%). The Ti42Zr35Si5Co12.5Sn2.5Ta3 bulk metallic glass composite was successfully fabricated through SLM. This study demonstrates that the TiZrSiCoSnTa system constitutes a promising basis for the additive manufacturing process in terms of preparing biocompatible metallic glass composites into complicated graded foam shapes.

A novel piezoelectric fiber sensor based on polyvinylidene fluoride piezoelectric (PVDF) doped with graphene is presented. The near-field electrospinning technology was used for developing the sensor. The uniform experimental design method was introduced to determine the ranges of experimental parameters, including the applied voltage, the drum speed range, the graphene doping ratios from 0% to 11 wt% in PVDF solution, and the electrode gap. By experimental results, the conductivities of PVDF solutions with different doping ratios of graphene increased from 19.6 μS/cm to 115.8 μS/cm. Tapping tests were performed to measure the voltages and currents produced by the piezoelectric fibers. The maximum output voltage was 4.56 V at 5 wt% graphene doping ratio in PVDF fibers, which was 11.54 times that of the pure PVDF sensors. Moreover, mechanical properties of the proposed sensor were measured. Motion intention and swallowing test, such as saliva-swallowing and eating, were carried out. When the subject spoke normally, the output voltage of the sensor was between 0.2 and 0.4 V, approximately. Furthermore, when the subject drank water and ate food, the output voltage of the sensor was between 0.5 and 1 V, approximately. The proposed sensor could be used to detect signals of the human body and serve as a wearable device, allowing for more diagnosis and medical treatment.

The research was based on the image recognition technology of artificial intelligence, which is expected to assist physicians in making correct decisions through deep learning. The liver dataset used in this study was derived from the open source website (LiTS) and the data provided by the Kaohsiung Chang Gung Memorial Hospital. CT images were used for organ recognition and lesion segmentation; the proposed Residual-Dense-Attention (RDA) U-Net can achieve high accuracy without the use of contrast. In this study, U-Net neural network was used to combine ResBlock in ResNet with Dense Block in DenseNet in the coder part, allowing the training to maintain the parameters while reducing the overall recognition computation time. The decoder was equipped with Attention Gates to suppress the irrelevant areas of the image while focusing on the significant features. The RDA model was used to identify and segment liver organs and lesions from CT images of the abdominal cavity, and excellent segmentation was achieved for the liver located on the left side, right side, near the heart, and near the lower abdomen with other organs. Better recognition was also achieved for large, small, and single and multiple lesions. The study was able to reduce the overall computation time by about 28% compared to other convolutions, and the accuracy of liver and lesion segmentation reached 96% and 94.8%, with IoU values of 89.5% and 87%, and AVGDIST of 0.28 and 0.80, respectively.

This paper presented the mechanical design and control of a lower limb rehabilitation exoskeleton named “the second lower limb rehabilitation exoskeleton (LLRE-II)”. The exoskeleton with a lightweight mechanism comprises a 16-cm stepless adjustable thigh and calf rod. The LLRE-II weighs less than 16 kg and has four degrees of freedom on each leg, including the waist, hip, knee, and ankle, which ensures fitted wear and comfort. Motors and harmonic drives were installed on the joints of the hip and knee to operate the exoskeleton. Meanwhile, master and slave motor controllers were programmed using a Texas Instruments microcontroller (TMS320F28069) for the walking gait commands and evaluation boards (TMS320F28069/DRV8301) of the joints. A self-tuning multiaxis control system was developed, and the performance of the controller was investigated through experiments. The experimental results showed that the mechanical design and control system exhibit adequate performance. Trajectory tracking errors were eliminated, and the root mean square errors reduced from 6.45 to 1.22 and from 4.15 to 3.09 for the hip and knee, respectively.

Nanotechnology utilizes engineered materials and devices which function with biological systems at the molecular level and could transform the management of neurodegenerative diseases (NDs) by provoking, reacting to, and intermingling with target sites to stimulate physiological responses while minimizing side effects. Blood–brain barrier (BBB) protects the brain from harmful agents, and transporting drugs across the BBB is a major challenge for diagnosis, targeting, and treatment of NDs. The BBB provides severe limitations for diagnosis and treatment of Alzheimer’s disease (AD), Parkinson’s disease (PD), and various other neurological diseases. Conventional drug delivery systems generally fail to cross the BBB, thus are inefficient in treatment. Although gradual development through research is ensuring the progress of nanotheranostic approaches from animal to human modeling, aspects of translational applicability and safety are a key concern. This demands a deep understanding of the interaction of body systems with nanomaterials. There are various plant-based nanobioactive compounds which are reported to have applicability in the diagnosis and treatment of these NDs. This review article provides an overview of applications of nanotheranostics in AD and PD. The review also discusses nano-enabled drug delivery systems and their current and potential applications for the treatment of various NDs.

Polyvinylidene fluoride (PVDF) and AgNO3/PVDF composite piezoelectric fibers were prepared using near-field electrospinning technology. The prepared fibers are attached to the electrode sheet and encapsulated with polydimethylsiloxane to create an energy acquisition device and further fabricated into a dynamic sensing element. The addition of AgNO3 significantly increased the conductivity of the solution from 40.33 μS/cm to 883.59 μS/cm, which in turn made the fiber drawing condition smoother with the increase of high voltage electric field and reduced the fiber wire diameter size from 0.37 μm to 0.23 μm. The tapping test shows that the voltage signal can reach ~0.9 V at a frequency of 7 Hz, and the energy conversion efficiency is twice that of the PVDF output voltage. The addition of AgNO3 effectively enhances the molecular bonding ability, which effectively increases the piezoelectric constants of PVDF piezoelectric fibers. When the human body is exercised for a long period of time and the body is overloaded, the biceps muscle is found to produce 8 to 16 tremors/second through five arm flexion movements. The voltage output of the flexible dynamic soft sensor is between 0.7–0.9 V and shows an orderly alternating current waveform of voltage signals. The sensor can be used to detect muscle tremors after high-intensity training and to obtain advance information about changes in the symptoms of fasciculation, allowing for more accurate diagnosis and treatment.

The tibia of New Zealand White rabbits was used as a model of critical bone defects to investigate a new design of composite scaffold for bone defects composed of dual materials. The all-in-one design of a titanium alloy (Ti-6Al-4V) scaffold comprised the structure of a bone plate and gradient porosity cage. Hydroxyapatite (HAp), a biodegradable material, was encapsulated in the center of the scaffold. The gradient pore structure was designed with 70%-65%-60%-55%-50% porosity, since the stresses could be distributed more uniformly when the all-in-one scaffold was placed on the bone contact surface. By covering the center of the scaffold with a low strength of HAp to contact the relatively low strength of bone marrow tissues, the excessive stiffness of the Ti-6Al-4V can be effectively reduced and further diminish the incidence of the stress shielding effect. The simulation results show that the optimized composite scaffold for the 3D model of tibia had a maximum stress value of 27.862 MPa and a maximum strain of 0.065%. The scaffold prepared by selective laser melting was annealed and found that the Young’s coefficient increased from 126.44 GPa to 131.46 GPa, the hardness increased from 3.9 GPa to 4.12 GPa, and the strain decreased from 2.27% to 1.13%. The result demonstrates that the removal of residual stress can lead to a more stable structural strength, which can be used as a reference for the design of future clinical tibial defect repair scaffolds.

Due to the fact that previous studies have rarely investigated the recognition rate discrepancy and pathology data error when applied to different databases, the purpose of this study is to investigate the improvement of recognition rate via deep learning-based liver lesion segmentation with the incorporation of hospital data. The recognition model used in this study is H-DenseUNet, which is applied to the segmentation of the liver and lesions, and a mixture of 2D/3D Hybrid-DenseUNet is used to reduce the recognition time and system memory requirements. Differences in recognition results were determined by comparing the training files of the standard LiTS competition data set with the training set after mixing in an additional 30 patients. The average error value of 9.6% was obtained by comparing the data discrepancy between the actual pathology data and the pathology data after the analysis of the identified images imported from Kaohsiung Chang Gung Memorial Hospital. The average error rate of the recognition output after mixing the LiTS database with hospital data for training was 1%. In the recognition part, the Dice coefficient was 0.52 after training 50 epochs using the standard LiTS database, while the Dice coefficient was increased to 0.61 after adding 30 hospital data to the training. After importing 3D Slice and ITK-Snap software, a 3D image of the lesion and liver segmentation can be developed. It is hoped that this method could be used to stimulate more research in addition to the general public standard database in the future, as well as to study the applicability of hospital data and improve the generality of the database.

The objective of this study aimed to develop biodegradable calcium alginate microspheres carrying doxorubicin (Dox) at the micrometer-scale for sustained release and the capacity of pH regulatory for transarterial chemoembolization. Ultrasonic atomization and CaCl2 cross-linking technologies were used to prepare the microspheres. A 4-by-5 experiment was first designed to identify imperative parameters. The concentration of CaCl2 and the flow rate of the pump were found to be critical to generate microspheres with a constant volume median diameter (~39 μm) across five groups with different alginate: NaHCO3 ratios using each corresponding flow rate. In each group, the encapsulation efficiency was positively correlated to the Dox-loading %. Fourier-transform infrared spectroscopy showed that NaHCO3 and Dox were step-by-step incorporated into the calcium alginate microspheres successfully. Microspheres containing alginate: NaHCO3 = 1 exhibited rough and porous surfaces, high Young’s modulus, and hardness. In each group with the same alginate: NaHCO3 ratio, the swelling rates of microspheres were higher in PBS containing 10% FBS compared to those in PBS alone. Microspheres with relatively high NaHCO3 concentrations in PBS containing 10% FBS maintained better physiological pH and higher accumulated Dox release ratios. In two distinct hepatocellular carcinoma-derived cell lines, treatments with microspheres carrying Dox demonstrated that the cell viabilities decreased in groups with relatively high NaHCO3 ratios in time- and dose-dependent manners. Our results suggested that biodegradable alginate microspheres containing relatively high NaHCO3 concentrations improved the cytotoxicity effects in vitro.

This paper developed a rotatable multi-axis motion platform combined with virtual reality (VR) immersion for flight simulation purposes. The system could simulate the state of the flight operation. The platform was mainly comprised of three crank linkage mechanisms to replace an expensive six degrees of freedom (DoF) Stewart platform. Then, an independent subsystem which could rotate ±180° was installed at the center of the platform. Therefore, this platform exhibited 4-DoF movement, such as heave, roll, pitch, and yaw. In the servo motor control unit, Visual Studio C# was applied as the software to establish a motion control system to interact with the motion controller and four sets of servo motors. Ethernet Control Automation Technology (EtherCAT) was utilized to communicate the commands and orders between a PC and each servo motor. The optimum controller parameters of this system were obtained using Simulink simulation and verified by experiment. The multiple sets of servo motors and crank linkage mechanisms were synchronized with flight VR imagery. For VR imagery, the software Unity was used to design the flying digital content. The controller was used to transmit the platform’s spatial information to meet the direction of the pilot commands and to compensate the direction of the deviation in spatial coordinates. To achieve synchronized response and motion with respect to the three crank linkage mechanism platform and VR imagery on the tester’s goggle view, the relation of the spatial coordinate of VR imagery and three crank linkage mechanisms was transformed to angular displacement, speed and acceleration which were used to command the motor drive system. As soon as the position of the VR imagery changed, the computer instantly synchronized the VR imagery information to the multi-axis platform and performed multi-axis dynamic motion synchronously according to its commanded information. The testers can thus immerse in the VR image environment by watching the VR content, and obtain a flying experience.

Piezoresistive tactile sensors made using nanocomposite polymeric materials have been shown to possess good flexibility, electrical performance, and sensitivity. However, the sensing performance, especially in the low-pressure range, can be significantly improved by enabling uniform dispersion of the filler material and utilization of effective structural designs that improve the tactile sensing performance. In this study, a novel flexible piezoresistive tactile sensor with a grid-type microstructure was fabricated using polymer composites comprising multi-walled carbon nanotubes (MWCNTs) as the conductive filler and polydimethylsiloxane (PDMS) as the polymeric matrix. The research focused on improving the tactile sensor performance by enabling uniform dispersion of filler material and optimizing sensor design and structure. The doping weight ratio of MWCNTs in PDMS varied from 1 wt.% to 10 wt.% using the same grid structure-sensing layer (line width, line spacing, and thickness of 1 mm). The sensor with a 7 wt.% doping ratio had the most stable performance, with an observed sensitivity of 6.821 kPa−1 in the lower pressure range of 10–20 kPa and 0.029 kPa−1 in the saturation range of 30–200 kPa. Furthermore, the dimensions of the grid structure were optimized and the relationship between grid structure, sensitivity, and sensing range was correlated. The equation between pressure and resistance output was derived to validate the principle of piezoresistance. For the grid structure, dimensions with line width, line spacing, and thickness of 1, 1, and 0.5 mm were shown to have the most stable and improved response. The observed sensitivity was 0.2704 kPa−1 in the lower pressure range of 50–130 kPa and 0.0968 kPa−1 in the saturation range of 140–200 kPa. The piezoresistive response, which was mainly related to the quantum tunneling effect, can be optimized based on the dopant concentration and the grid microstructure. Furthermore, the tactile sensor showed a repeatable response, and the accuracy was not affected by temperature changes in the range of 10 to 40 °C and humidity variations from 50 to 80%. The maximum error fluctuation was about 5.6% with a response delay time of about 1.6 ms when cyclic loading tests were performed under a normal force of 1 N for 10,200 cycles. Consequently, the proposed tactile sensor shows practical feasibility for a wide range of wearable technologies and robotic applications such as touch detection and grasping.

Environmental and economic concerns are driving the demand for electric vehicles. However, their development for mass transportation hinges largely on improvements in the separators in lithium-ion batteries (LIBs), the preferred energy source. In this study, innovative separators for LIBs were fabricated by near-field electrospinning (NFES) and the sol-gel method. Using NFES, poly (vinylidene fluoride) (PVDF) fibers were fabricated. Then, PVDF membranes with pores of 220 nm and 450 nm were sandwiched between a monolayer and bilayer of the electrospun fibers. Nanoceramic material with organic resin, formed by the sol-gel method, was coated onto A4 paper, rice paper, nonwoven fabric, and carbon synthetic fabric. Properties of these separators were compared with those of a commercial polypropylene (PP) separator using a scanning electron microscope (SEM), microtensile testing, differential scanning calorimetry (DSC), ion-conductivity measurement, cyclic voltammetry (CV), and charge-discharge cycling. The results indicate that the 220 nm PVDF membrane sandwiched between a bilayer of electrospun fibers had excellent ionic conductivity (~0.57 mS/cm), a porosity of ~70%, an endothermic peak of ~175 °C, better specific capacitance (~356 mAh/g), a higher melting temperature (~160 °C), and a stable cycle performance. The sol-gel coated nonwoven fabric had ionic conductivity, porosity, and specific capacitance of ~0.96 mS/cm., ~64%, and ~220 mAh/g, respectively, and excellent thermal stability despite having a lower specific capacitance (65% of PP separator) and no peak below 270 °C. The present study provides a significant step toward the innovation of materials and processes for fabricating LIB separators.

In this study, three-dimensional simulations of the ultrasonic vibration bonding process of micro-copper blocks were conducted using the finite element method. We analyzed the effects of ultrasonic vibration frequency on the stress field, strain field, and temperature field at the copper bump joint surface. The results showed that the bonding process is successfully simulated at room temperature. The stress curve of the bonding process could be divided into three stages: stress rising stage, stress falling stage, and stress stabilization stage. Moreover, it was found that the end of the curve exhibited characteristics of a solid solution phase at higher frequencies. It is hypothesized that the high-density dislocations formed at this stage may result in conveyance channels that facilitate the atomic diffusion at the contact surface. The simulation results indicated that copper micro-bump bonding occurs at an ultrasonic frequency of 50 kHz or higher.

Intervertebral fusion surgery for spinal trauma, degeneration, and deformity correction is a major vertebral reconstruction operation. For most cages, the stiffness of the cage is high enough to cause stress concentration, leading to a stress shielding effect between the vertebral bones and the cages. The stress shielding effect affects the outcome after the reconstruction surgery, easily causing damage and leading to a higher risk of reoperation. A porous structure for the spinal fusion cage can effectively reduce the stiffness to obtain more comparative strength for the surrounding tissue. In this study, an intervertebral cage with a porous gradation structure was designed for Ti64ELI alloy powders bonded by the selective laser melting (SLM) process. The medical imaging software InVesalius and 3D surface reconstruction software Geomagic Studio 12 (Raindrop Geomagic Inc., Morrisville, NC, USA) were utilized to establish the vertebra model, and ANSYS Workbench 16 (Ansys Inc., Canonsburg, PA, USA) simulation software was used to simulate the stress and strain of the motions including vertical body-weighted compression, flexion, extension, lateral bending, and rotation. The intervertebral cage with a hollow cylinder had porosity values of 80–70–60–70–80% (from center to both top side and bottom side) and had porosity values of 60–70–80 (from outside to inside). In addition, according to the contact areas between the vertebras and cages, the shape of the cages can be custom-designed. The cages underwent fatigue tests by following ASTM F2077-17. Then, mechanical property simulations of the cages were conducted for a comparison with the commercially available cages from three companies: Zimmer (Zimmer Biomet Holdings, Inc., Warsaw, IN, USA), Ulrich (Germany), and B. Braun (Germany). The results show that the stress and strain distribution of the cages are consistent with the ones of human bone, and show a uniform stress distribution, which can reduce stress concentration.

In this study, near-infrared (NIR) technology was utilized to develop a low-cost real-time near infrared (NIR) guiding device for cannulation. A portable device that can be used by medical practitioners and also by students for their skills development training in performing cannulation. Methods. First, is the development of a reflectance type optical vein finder using three (3) light emitting diode (LED) lights with 960 nm wavelength, complementary metal-oxide-semiconductor-infrared (CMOS-IR) sensor camera with 1920 × 1080 UXGA (1080P), IR filter set for the given wavelength, and an open-source image processing software. Second, is the actual in-vitro human testing in two sites: the arm and dorsal hand of 242 subjects. The following parameters were included, such as gender, age, mass index (BMI), and skin tone. In order to maximize the assessment process towards the device, the researchers included the arm circumference. This augmented subcutaneous vein imaging study using the develop vein finder device compared the difference in the captured vein images through visual and digital imaging approaches. The human testing was performed in accordance with the ethical standards of the Trinity University of Asia—Institutional Ethics Review Committee (TUA—IERC). Results. The NIR imaging system of the developed vein finder in this study showed its capability as an efficient guiding device through real-time vein pattern recognition, for both sites. Improved captured vein images were observed, having 100% visibility of vein patterns on the dorsal hand site. Fourteen (5.79%) out of 242 subjects reported non-visible peripheral subcutaneous veins in the arm sites. Conclusions. The developed vein finder device with the NIR technology and reflected light principle with low-energy consumption was efficient for real-time peripheral subcutaneous vein imaging without the application of a tourniquet. This might be utilized as a guiding device in locating the vein for the purpose of cannulation, at a very low cost as compared to the commercially available vein finders. Moreover, it may be used as an instructional device for student training in performing cannulation.

The objective was to investigate the anti-cancer effects and underlying molecular mechanisms of cytostasis which were activated by an anti-microtubule drug, ABT-751, in two urinary bladder urothelial carcinoma (UBUC)-derived cell lines, BFTC905 and J82, with distinct genetic backgrounds. A series of in vitro assays demonstrated that ABT-751 induced G2/M cell cycle arrest, decreased cell number in the S phase of the cell cycle and suppressed colony formation/independent cell growth, accompanied with alterations of the protein levels of several cell cycle regulators. In addition, ABT-751 treatment significantly hurdled cell migration and invasion along with the regulation of epithelial–mesenchymal transition-related proteins. ABT-751 triggered autophagy and apoptosis, downregulated the mechanistic target of rapamycin kinase (MTOR) and upregulated several pro-apoptotic proteins that are involved in extrinsic and intrinsic apoptotic pathways. Inhibition of autophagosome and autolysosome enhanced apoptosis was also observed. Through the inhibition of the NFκB signaling pathway, ABT-751 suppressed S-phase kinase associated protein 2 (SKP2) transcription and subsequent translation by downregulation of active/phospho-AKT serine/threonine kinase 1 (AKT1), component of inhibitor of nuclear factor kappa B kinase complex (CHUK), NFKB inhibitor alpha (NFKBIA), nuclear RELA proto-oncogene, NFκB subunit (RELA) and maintained a strong interaction between NFKBIA and RELA to prevent RELA nuclear translocation for SKP2 transcription. ABT-751 downregulated stable/phospho-SKP2 including pSKP2(S64) and pSKP2(S72), which targeted cyclin-dependent kinase inhibitors for degradation through the inactivation of AKT. Our results suggested that ABT-751 may act as an anti-cancer drug by inhibiting cell migration, invasion yet inducing cell cycle arrest, autophagy and apoptosis in distinct UBUC-derived cells. Particularly, the upstream molecular mechanism of its anticancer effects was identified as ABT-751-induced cytostasis through the inhibition of SKP2 at both transcriptional and post-translational levels to stabilize cyclin dependent kinase inhibitor 1A (CDKN1A) and CDKN1B proteins.

Cancer is one of the common diseases. Quantitative biomarkers extracted from standard-of-care computed tomography (CT) scan can create a robust clinical decision tool for the diagnosis of hepatocellular carcinoma (HCC). According to the current clinical methods, the situation usually accounts for high expenditure of time and resources. To improve the current clinical diagnosis and therapeutic procedure, this paper proposes a deep learning-based approach, called Successive Encoder-Decoder (SED), to assist in the automatic interpretation of liver lesion/tumor segmentation through CT images. The SED framework consists of two different encoder-decoder networks connected in series. The first network aims to remove unwanted voxels and organs and to extract liver locations from CT images. The second network uses the results of the first network to further segment the lesions. For practical purpose, the predicted lesions on individual CTs were extracted and reconstructed on 3D images. The experiments conducted on 4300 CT images and LiTS dataset demonstrate that the liver segmentation and the tumor prediction achieved 0.92 and 0.75 in Dice score, respectively, by as-proposed SED method.

The correlations between the microstructure and nanomechanical properties of a series of thermal annealed Co thin films were investigated. The Co thin films were deposited on glass substrates using a magnetron sputtering system at ambient conditions followed by subsequent annealing conducted at various temperatures ranging from 300 °C to 800 °C. The XRD results indicated that for annealing temperature in the ranged from 300 °C to 500 °C, the Co thin films were of single hexagonal close-packed (hcp) phase. Nevertheless, the coexistence of hcp-Co (002) and face-centered cubic (fcc-Co (111)) phases was evidently observed for films annealed at 600 °C. Further increasing the annealing temperature to 700 °C and 800 °C, the films evidently turned into fcc-Co (111). Moreover, significant variations in the hardness and Young’s modulus are observed by continuous stiffness nanoindentation measurement for films annealed at different temperatures. The correlations between structures and properties are discussed.

In this study, the mechanical deformation behaviors of Au nanotubes (Au-NTs) under torsional stress are investigated using molecular dynamics (MD) simulations. The inter-atomic interaction is modeled using the embedded-atom potential. In particular, the effects of loading rate, thickness and length of the nanotube, as well as the thermal effects were systematically explored. The results indicated that higher loading rate, longer length and thinner wall thickness all led to a larger value of critical torsional angle (θcr), which signifies the onset of plastic deformation. On the other hand, θcr decreases with increasing temperature in all simulated results. Moreover, the torsional buckling deformation behavior and geometrical instability are found to strongly depend on the length of Au-NTs, the applied strain rate and temperature with vastly different underlying mechanisms.

This study presents an innovative design of a microtab system for aerodynamic load control on horizontal-axis wind-turbine rotors. Microtabs are small devices located near the trailing edge of the rotor blades and enable a rapid increase or decrease of the lift force through deployment of the tabs on the pressure or suction side of the airfoil, respectively. The new system has been designed to replace an earlier linearly-actuated microtab mechanism whose performance was limited by space restrictions and stiction. The newly-designed microtab system is based on a four-bar linkage that overcomes the two drawbacks. Its improved kinematics allows for the tab height to increase from 1.0% to 1.7% of the airfoil chord when fully deployed, thereby making it more effective in terms of aerodynamic load control. Furthermore, the modified four-bar link mechanism provides a more robust and reliable mechanical structure.

This study presents a misalignment light-guiding module to increase the effectiveness of absorbing light. For a general fixed-type photovoltaic (PV) panel, the misalignment light decreases the efficiency of the system. A solar tracking system was installed for obtaining higher power generation. However, the cost of the PV system and maintenance was 5−10 times higher than the general type. In this study, this module is composed of an array of misalignment light-guiding units that consist of a non-axisymmetric compound parabolic curve (NACPC) and a freeform surface collimator. The NACPC efficiently collects the misalignment light within ±30° and guides the light to the collimator. The light has a better uniformity and smaller angle at the exit aperture. The simulation results show that the optical efficiency of the unit was above 70% when the misalignment angle was smaller than 20°. The experimental results show that the power generation of the light-guiding unit was 1.8 times higher than the naked PV panel.

The electronic package interconnects electronic signals from one area to another and package delamination is a serious problem in the configuration of materials. This study focused on decreasing the delamination of the low-profile fine pitch ball grid array (LFBGA) and plastic ball grid array (PBGA) packages in terms of polymer thermal issue, metal bonding and bonding mechanisms. PBGA and LFBGA are a very common type of packaging processes in the electronics industry. The present study dealt first with delamination of the LFBGA packaging, through characterization and determination of physical and chemical properties such as surface roughness, surface energy, and contact angle. The relationship between surface roughness and delamination was verified through various roughness bonding experiments. In addition, the surface energy was determined by measuring the contact angle after cleaning the metal surface of Cu, Ni and Cr with Ar + O2 gas, and, this gas plasma treatment was applied to enhance the adhesive properties. The compositions of the surface were analyzed through an X-ray photoelectron spectroscopy (XPS). Also, the delamination issue between the corner of the heat sink cap and the epoxy resin was observed for delamination of the LFBGA packaging. Further, this study analyzed the PBGA packaging process through the finite element analysis simulation software ANSYS. To improve the heat sink cap delamination issue of the PBGA, a new chamfer design of the corner seat was streamlined to decrease the stress value and delamination. Besides, the simulation results demonstrated that the stress value reduced after increasing the shoulder length. The results implicate that the stress value is inversely proportional to the shoulder width and the chamfer radius. This study demonstrated that the optimization in design was able reduce the delamination phenomena in configuration material.