Microstructure Evolution, Hardness, and Tribological Behaviors of Ti-50.8Ni SMA Alloy with Ultrasonic Surface Shot Peening Treatment.

To explore a new method to improve the wear resistance of TiNi shape memory alloy (SMA), Ti-50.8Ni alloy was treated by the method of ultrasonic surface shot peening. The microstructure evolution, hardness, and tribological behaviors have been further investigated to evaluate the effect of ultrasonic surface shot peening (USSP). The surface microstructure can be refined to some extent while the basic phase composition has little change. USSP can facilitate the martensitic transformation in the surface layer, which benefits improving the surface hardness. Additionally, the hardness of Ti-50.8Ni alloy increases first and then decreases with the increase of applied load, but the USSP-treated alloy tends to be more sensitive to load. USSP treatment can improve the wear resistance and reduce the coefficient of friction (COF) in case of a low sliding wear speed of 5 mm/s. However, the tribological properties of USSP-treated alloy are reversely worse in the case of 10 mm/s. This is mainly attributed to the combined effect of stress-induced martensite transformation and degeneration resulting from the frictional heating during the dry sliding wear process.

Semi-supervised learning in diagnosis of infant hip dysplasia towards multisource ultrasound images.

Background: Automated diagnosis of infant hip dysplasia is heavily affected by the individual differences among infants and ultrasound machines. Methods: Hip sonographic images of 493 infants from various ultrasound machines were collected in the Department of Orthopedics in Yangzhou Maternal and Child Health Care Service Centre. Herein, we propose a semi-supervised learning method based on a feature pyramid network (FPN) and a contrastive learning scheme based on a Siamese architecture. A large amount of unlabeled data of ultrasound images was used via the Siamese network in the pre-training step, and then a small amount of annotated data for anatomical structures was adopted to train the model for landmark identification and standard plane recognition. The method was evaluated on our collected dataset. Results: The method achieved a mean Dice similarity coefficient (DSC) of 0.7873 and a mean Hausdorff distance (HD) of 5.0102 in landmark identification, compared to the model without contrastive learning, which had a mean DSC of 0.7734 and a mean HD of 6.1586. The accuracy, precision, and recall of standard plane recognition were 95.4%, 91.64%, and 94.86%, respectively. The corresponding area under the curve (AUC) was 0.982. Conclusions: This study proposes a semi-supervised deep learning method following Graf's principle, which can better utilize a large volume of ultrasound images from various devices and infants. This method can identify the landmarks of infant hips more accurately than manual operators, thereby improving the efficiency of diagnosis of infant hip dysplasia.

Corrosion Studies of Temperature-Resistant Zinc Alloy Sacrificial Anodes and Casing Pipe at Different Temperatures.

In order to solve the problem of external corrosion of deep well casing in oil and gas fields, a new type of high-temperature-resistant zinc alloy sacrificial anode material was used. The temperature and corrosion resistance of the new anode material and TP140 casing were investigated by simulating the high-temperature working conditions of a deep well in an oil field using high-temperature and high-pressure corrosion tests and electrochemical tests. The results showed that at 100-120 °C, the corrosion rate of TP140 protected by a sacrificial anode was only one-tenth of that under unprotected conditions, and the minimum corrosion rate of TP140 protected by a sacrificial anode at 100 °C was 0.0089 mm/a. The results of the dynamic potential polarization curve showed that the corresponding corrosion current density of TP140 first increased and then decreased with the increase in temperature. The self-corrosion potential in sacrificial anode materials first increased and then decreased with the increase in temperature, and the potential difference with TP140 gradually decreased.

Application of machine learning algorithm in prediction of lymph node metastasis in patients with intermediate and high-risk prostate cancer.

PURPOSE: This study aims to establish the best prediction model of lymph node metastasis (LNM) in patients with intermediate- and high-risk prostate cancer (PCa) through machine learning (ML), and provide the guideline of accurate clinical diagnosis and precise treatment for clinicals. METHODS: A total of 24,470 patients with intermediate- and high-risk PCa were included in this study. Multivariate logistic regression model was used to screen the independent risk factors of LNM. At the same time, six algorithms, namely random forest (RF), naive Bayesian classifier (NBC), xgboost (XGB), gradient boosting machine (GBM), logistic regression (LR) and decision tree (DT) are used to establish risk prediction models. Based on the best prediction performance of ML algorithm, a prediction model is established, and the performance of the model is evaluated from three aspects: area under curve (AUC), sensitivity and specificity. RESULTS: In multivariate logistic regression analysis, T stage, PSA, Gleason score and bone metastasis were independent predictors of LNM in patients with intermediate- and high-risk PCa. By comprehensively comparing the prediction model performance of training set and test set, GBM model has the best prediction performance (F1 score = 0.838, AUROC = 0.804). Finally, we developed a preliminary calculator model that can quickly and accurately calculate the regional LNM in patients with intermediate- and high-risk PCa. CONCLUSION: T stage, PSA, Gleason and bone metastasis were independent risk factors for predicting LNM in patients with intermediate- and high-risk PCa. The prediction model established in this study performs well; however, the GBM model is the best one.

Advancements in the treatment of metastatic hormone-sensitive prostate cancer.

In the last decade, there have been substantial improvements in the outcome of the management of metastatic hormone-sensitive prostate cancer (mHSPC) following the development of several novel agents as well as by combining several therapeutic strategies. Although the overall survival (OS) of mHSPC is shown to improve with intense androgen deprivation therapy (ADT), combined with docetaxel, as well as other novel hormonal therapy agents, or alongside local intervention to the primary neoplasm. Notably, luteinizing hormone-releasing hormone (LHRH) antagonists are known to cause fewer cardiovascular side effects compared with LHRH agonists. Thus, in this mini review, we explore the different approaches in the management of mHSPC, with the aim that we may provide useful information for both basic scientists and clinicians when managing relevant clinical situations.

Electrochemical behavior of 2205 duplex stainless steel in simulated solution containing high concentration Cl- and saturated CO2 at different temperatures.

2205 duplex stainless steel (DSS) has good corrosion resistance due to its typical duplex organization, but the increasingly harsh CO2-containing oil and gas environment leads to different degrees of corrosion, especially pitting corrosion, which seriously threatens the safety and reliability of oil and gas development. In this paper, the effect of temperature on the corrosion behavior of 2205 DSS in a simulated solution containing 100 g/L Cl- and saturated CO2 was investigated with immersion tests and electrochemical tests and combined with characterization techniques such as laser confocal microscopy and X-ray photoelectron spectroscopy. The results show that the average critical pitting temperature of 2205 DSS was 66.9 °C. When the temperature was higher than 66.9 °C, the pitting breakdown potential, passivation interval, and self-corrosion potential decreased, while the dimensional passivation current density increased, and the pitting sensitivity was enhanced. With a further increase in temperature, the capacitive arc radius of 2205 DSS decreased, the film resistance and charge transfer resistance gradually decreased, the carrier density of the donor and acceptor in the product film layer with n + p bipolar characteristics also increased and the inner layer of the film with Cr oxide content decreased, while the outer layer with Fe oxide content increased, the dissolution of the film layer increased, the stability decreased, and the number and pore size of pits increased.

Corrosion Resistance Mechanism of Mica-Graphene/Epoxy Composite Coating in CO2-Cl- System.

The working environment for tubing in oil and gas fields is becoming more and more serious due to the exploration of unconventional oil and gas resources, leading to the increasing need for a protective internal coating to be used in tubing. Therefore, a new mica-graphene/epoxy composite coating with different graphene contents (0.0, 0.2, 0.5, 0.7, and 1.0 wt.%) was prepared to improve the tubing resistance to a corrosive medium, an autoclave was used to simulate the working environment, and an electrochemical workstation assisted by three-electrodes was used to study the electrochemical characteristics of the coating. The results showed that the addition of a certain amount of graphene into the mica/epoxy coating significantly improved the corrosion resistance of the composite coating, and when the graphene content increased, the corrosion resistance of the mica/epoxy coating first increased and then decreased when the corrosion current density of a 35 wt.% 800# mica/epoxy coating with a 0.7 wt.% graphene content was the lowest (7.11 × 10-13 A·cm-2), the corrosion potential was the highest (292 mV), the polarization resistance was the largest (3.463 × 109 Ω·cm2), and the corrosion resistance was improved by 89.3% compared to the coating without graphene. Furthermore, the adhesion of the coating with 0.7 wt.% graphene was also the largest (8.81 MPa, increased by 3.4%) and had the smallest diffusion coefficient (1.566 × 107 cm2·s-1, decreased by 76.1%), and the thermal stability improved by 18.6%. Finally, the corrosion resistance mechanism of the composite coating with different graphene contents at different soaking times was revealed based on the electrochemistry and morphology characteristics other than water absorption and contact angle.

Identification and functional analysis of novel oncogene DDX60L in pancreatic ductal adenocarcinoma.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is a lethal cancer. Approximately 80% of patients initially diagnosed with locally advanced or metastatic disease survive only 4-11 months after diagnosis. Tremendous efforts have been made toward understanding the biology of PDAC. RESULTS: In this study, we first utilized next-generation sequencing technique and existing microarray datasets to identify significant differentially expressed genes between PDAC and non-tumor adjacent tissue. By comparing top significant survival genes in PDAC Gene Expression Profiling Interactive Analysis database and PDAC transcriptome data from patients, our integrated analysis discovered five potential central genes (i.e., MYEOV, KCNN4, FAM83A, S100A16, and DDX60L). Subsequently, we analyzed the cellular functions of the potential novel oncogenes MYEOV and DDX60L, which are highly expressed in PDAC cells. Notably, the knockdown of MYEOV and DDX60L significantly inhibited the metastasis of cancer cells and induced apoptosis. Further RNA sequencing analyses showed that massive signaling pathways, particularly the TNF signaling pathway and nuclear factor-kappa B (NF-κB) signaling pathway, were affected in siRNA-treated cancer cells. The siDDX60L and siMYEOV significantly inhibited the expression of chemokine CXCL2, which may potentially affect the tumor microenvironment in PDAC tissues. CONCLUSIONS: The present findings identified the novel oncogene DDX60L, which was highly expressed in PDAC. Transcriptome profiling through siRNA knockdown of DDX60L uncovered its functional roles in the PDAC in humans.

Research on Rotational Angle Measurement for the Smart Wheel Force Sensor.

The measurement of the rotational angle of the wheel is critical for the smart wheel force sensor (SWFS) to obtain the wheel forces defined in the vehicle coordinates. To simplify the structure of the SWFS and overcome the shortcomings of the traditional angular transducer, a new method to evaluate the rotational speed of the wheel and then calculate the rotational angle is proposed in this paper. In this method, the centripetal acceleration caused by the rotation is recorded by three accelerometers and used carefully. What's more, the possible sources of error are classified and analyzed. Simulations and stand experiment are carried out to demonstrate the effectiveness of the proposed method.

Panax notoginseng saponins improve recovery after spinal cord transection by upregulating neurotrophic factors.

Saponins extracted from Panax notoginseng are neuroprotective, but the mechanisms underlying this effect remain unclear. In the present study, we established a rat model of thoracic (T10) spinal cord transection, and injected Panax notoginseng saponins (100 mg/kg) or saline 30 minutes after injury. Locomotor functions were assessed using the Basso, Beattie, and Bresnahan (BBB) scale from 1 to 30 days after injury, and immunohistochemistry was carried out in the ventral horn of the spinal cord at 1 and 7 days to determine expression of nerve growth factor (NGF) and brain-derived neurotrophic factor (BDNF). Our results show that at 7-30 days post injury, the BBB score was higher in rats treated with Panax notoginseng saponins than in those that received saline. Furthermore, at 7 days, more NGF- and BDNF-immunoreactive neurons were observed in the ventral horn of the spinal cord of rats that had received Panax notoginseng saponins than in those that received saline. These results indicate that Panax notoginseng saponins caused an upregulation of NGF and BDNF in rats with spinal cord transection, and improved hindlimb motor function.