Good Application Research Articles

A retrospective comparison of endoscopic nasobiliary drainage (ENBD) and endoscopic retrograde biliary drainage (ERBD) in the treatment of acute cholangitis

Endoscopic nasobiliary drainage (ENBD) and endoscopic retrograde biliary drainage (ERBD) can rapidly alleviate obstruction, facilitate bile drainage, and reduce pressure in the bile duct. In this study, to evaluate the effect of plastic biliary stent on the recurrence rate of choledocholithiasis in patients with actual cholangitis after endoscopic retrograde cholangioangiography (ERCP), we a comparative analysis of the efficacy and safety between ENBD and ERBD in inflammatory remission rate, complication rate, and success rate of secondary or multiple endoscopic lithotomy. A total of 347 patients undergoing ENBD and ERBD were enrolled in this retrospective study. Preoperative assessments including blood tests, electrocardiography, abdominal ultrasonography, CT scans, MRI, or MRCP were conducted on all participants. Additionally, serum CRP and amylase levels were measured using a magnetic nanobead-based immunoassay. We found that The success rate of stone removal in the ENBD group was higher than that in the ERBD group (90.8% vs. 72.7%) (P <0.0001). The remission rate of inflammation in the ERBD group (100.0%) was higher than that in the ENBD group (98.7%) (P >0.05). No significant difference was observed between the ERBD group and the ENBD group in preoperative and postoperative inflammatory indexes (total bilirubin, direct bilirubin, white blood cells, neutrophils, CRP, and serum amylase). Moreover, there were significant differences in post-ERCP pancreatitis between the ERBD group and ENBD group. These results suggest that both ENBD and ERBD can effectively improve clinical efficacy. Moreover, magnetic nanobeads have good application in serum index detection to increase detection efficiency.

Quality-by-design optimized RP-HPLC approach for the therapeutic drug monitoring of glibenclamide and fluoxetine in human plasma

Glibenclamide (GLB) and fluoxetine (FLX) were reported to have a potential drug-drug interaction when clinically co-administered. FLX is an inhibitor of CYP2C9 (the enzyme responsible for the metabolism of GLB), thus resulting in increased serum levels of GLB followed by severe hypoglycemia. Therefore, a sensitive, simple, and selective HPLC method is urgently needed for their simultaneous determination in plasma to be utilized for monitoring their therapeutic blood concentration levels. The current study introduces the first RP-HPLC approach for the simultaneous estimation of this binary mixture in less than 7 min. Adopting a quality-by-design (QbD) approach allowed for the designed approach to be optimized. Using a two-level full factorial design (25), the effects of various variables on the chromatographic responses were investigated and optimized. Hypersil BDS C18 column was used for the achievement of the optimum chromatographic separation at 19.9 °C using acetonitrile: sodium dihydrogen phosphate buffer (7.5 mM; pH 4, 60:40 % v/v) as a mobile phase, pumped isocratically at a flow rate of 1.036 mL/min. An injection volume of 30.0 μL was used for the binary mixture with UV detection at 230 nm. FLX and GLB calibration curves revealed an excellent linearity over the ranges of 0.025–10.00 and 0.02–10.00 µg/mL with limits of quantitation of 0.018 and 0.02 µg/mL, respectively. Due to the high sensitivity and selectivity, the method was successfully applied to the assay of the two drugs in spiked human plasma samples with reasonable % recoveries (92.70–108.50 %), indicating good bioanalytical applicability. Therefore, this study could be applied for the therapeutic drug monitoring of GLB and FLX in human plasma to control their potential drug-drug interaction. The suggested approach was also applied to estimate the investigated drugs in their dosage forms with reasonable % recoveries (96.80–102.80 %) and small % RSD values (less than 2 %). The method's excellent greenness was evaluated using three metric tools, including Analytical Eco-Scale, Green Analytical Procedure Index (GAPI), and Analytical Greenness (AGREE). Validation of the proposed method was performed according to ICH and US FDA guidelines.

Application of Acoustic Emission Technology for Bearing Condition Monitoring on Passenger Ropeway

Rolling bearings are important stressed components of driving wheels and detour wheels on passenger ropeway, and their failure may lead to accidents and casualties. After the ropeway is installed and put into operation, the rolling bearings in the wheels are difficult to disassemble. Once disassembled, the bearing may be damaged. Due to the installation position and the complex operation environment, the health status of the rolling bearings is a blind spot for ropeway inspection and detection. Acoustic emission detection technology is used to monitor the rolling bearings of passenger ropeways. After a large number of field tests, the acoustic emission monitoring program and signal analysis method of rolling bearing on ropeway were proposed. The parameter characteristics of acoustic emission signals obtained in bearing operating were analyzed from two aspects: the ropeway operating cycle and the bearing operating cycle. Spectrum analysis of typical signals was performed, and the spectrum characteristics of typical acoustic emission signals of rolling bearing during the operation of the ropeway were obtained. On-site tests results show that using acoustic emission technology to perform condition monitoring and fault diagnosis of low-speed rolling bearings on passenger ropeways has good application prospects.

Lignin-enhanced wet strength and UV-Blocking properties of nanocellulose-based composite films obtained by casting/hot-pressing methods

We composited nanocellulose, lignin and polyvinyl alcohol (PVA) by using borax as a cross-linking agent, and prepared nanocellulose-based composite films by two simple and convenient methods of the casting and hot-pressing. Results showed that the molding method affected the film properties. The hot-pressing composite film exhibited smoother surface and tighter structures, while the casting one exhibited better stretchability. The composite films showed a good tensile strength (casting: 149.56 MPa; hot-pressing: 179.68 MPa). Due to the addition of lignin, the composite films were endowed with good UV-blocking capabilities, wet strength, oxidation resistance and bacteriostatic properties. The composite film has good application prospects in the field of food packaging and UV-shielding.

Research on Hot Deformation Behavior of Cu-Ti Alloy Based on Machine Learning Algorithms and Microalloying

High strength and high elasticity copper alloys have good application prospects due to their excellent mechanical properties. The deformation and heat treatment in its preparation process are important steps to ensure the service performance. In this work, Cu-Ti based alloys were employed and hot compression experiments were conducted at 500-800℃ under four different strain rates. Their constitutive equations and thermal processing maps were constructed. The influence of microalloying elements on activation energy was also analyzed. The microstructure evolution and recrystallization behavior under hot deformation conditions were studied based on the results of TEM. At the same time, Arrhenius, back propagation neural network (BPNN) and support vector machine (SVM) algorithms were used to predict the flow stress of the alloy. The results indicate that the relationship between flow stress and the input factors (strain rate, temperature and deformation) can be well predicted using the support vector machine algorithm. Microalloying can increase the activation energy of copper alloys, and the sensitivity of activation energy to temperature changes is related to the interaction between precipitates and dislocations.

Nanopore single molecule ATP detection based on the dual effects of specific capturing and signal amplification

Adenosine triphosphate (ATP) plays a crucial role in energy metabolism. Some serious diseases such as Alzheimer’s disease are related to abnormal ATP concentrations. Fast, sensitive, and specific ATP detection is important and challenging in disease diagnosis and biomedical research. In present study, conical nanopore was designed and employed to detect ATP at single molecule level. For overcoming the inherent defects such as non-selectivity and low sensitivity of nanopore in sensing small target molecule, two collaborative improvements of specific identification and signal amplification were proposed. We first used split aptamer capture probes (H1 and S1) to anchor ATP molecule, and then used auxiliary probes (H2 and H3) to form a long-nicked duplex ATP-DNA concatemer by hybridization chain reaction (HCR). Referring ATP-DNA concatemer rather than native ATP to nanopore sensor, characteristic current signals with high signal-to-noise ratio were obtained. By such indirect way, specific and sensitive ATP detection was realized with a linear range from 20 pM to 5 nM and a detection limit of 3.9 pM (S/N = 3). Additionally, the sensor exhibited many merits such as simplify, anti-interference, and especially allowing ATP detection in real sample. So, we believe that the nanopore sensor has good application prospects in screening and management of ATP-related diseases.

Huge redshift of absorption edge in a novel Z-type Bi2Sn2O7/α-Bi2O3 junction for highly efficiently visible light degradation of norfloxacin and bisphenol AF

Heterojunction was mainly used to realize the separation of charge carrier in current studies, but it did not bring about any other effect. In this paper, Bi2Sn2O7 was introduced into α-Bi2O3 to construct a direct Z-type Bi2Sn2O7/α-Bi2O3 heterojunction. It not only accelerated the rapid separation of electrons and holes, but also induced a huge redshift of absorption edge to enlarge the visible light absorption range. Such result led into the optimal sample being able to degrade 95% of norfloxacin and 92% of bisphenol AF for 90min of visible light irradiation. Under the same testing conditions, the removal efficiency of these two pollutants in the drinking water also attained 94% and 90% to demonstrate a good application. Moreover, the cycling test results indicated that the Bi2Sn2O7/α-Bi2O3 could be sustainably utilized. The electrons, holes, superoxide radical (•O2-) and hydroxyl radical (•OH) were the active substances in the process of degradation. The numbers of the Escherichia coli were 0.69×106 CFU/mL and 0.75×106 CFU/mL in the solutions after degradation to denote non-toxicity of the final products. Thus the Bi2Sn2O7/α-Bi2O3 composite could be applied in purification of various waste waters.

Laser-induced graphene decorated with Ni[sbnd]Pt alloy nanoparticles for non-enzymatic electrochemical quantification of glucose

Enzyme-free electrochemical glucose (Glu) sensors, adopting electrochemically active catalysts, are of vital significance to effectively monitoring and analyzing the blood Glu level in diabetes diagnosis. Meanwhile, developing novel electrode substrates have been the hot research pot to meet the demand for constructing flexible sensors. In this work, porous laser-induced graphene (LIG) was prepared through a facile one-step laser-engraving technique on a polyimide thin film, and then used directly as the electrode. Furthermore, NiPt alloyed nanoparticles (NPs) were electrodeposited on the LIG electrode surface to gain the NiPt/LIG composite electrode, which was applied to construct the nonenzymatic electrochemical Glu sensor. The morphology, element and electrochemical performance of NiPt/LIG composite was characterized through various techniques. NiPt alloyed NPs were homogeneously distributed on the LIG scaffolds, which possess plenty of porous structure, high surface area and many active sites. The cooperative effect between the outstanding electrocatalytic capacity of NiPt alloyed NPs, the extraordinary electroconductibility of LIG and the numerous exposed active sites endow the NiPt/LIG sensor outstanding electrocatalytic performance for electrochemical oxidation of Glu. Under the most appropriate conditions, the obtained NiPt/LIG sensor was adopted to detect Glu, showing a broad detection concentration range of 0.5 μM to 2.1 mM and 2.1 mM to 5.6 mM, good sensitivities of 1.824 and 0.467 μA μM−1 cm−2, a low detection limit of 0.03 μM. The as-fabricated nonenzymatic Glu sensor also displays high selectivity, stability considering ageing effects under different environment conditions and prominent reproducibility. Additionally, this novel NiPt/LIG nonenzymatic Glu sensor was applied to quantify Glu successfully in blood serum and food samples and the results were in good agreement with that by UV–vis spectrophotometer, demonstrating high precision and accuracy as well as excellent recovery, showing good application prospects in Glu monitoring. This research confirmed the potential of exploiting NiPt/LIG as a highly sensitive Glu nonenzymatic electrochemical sensor and provided a practicable and suitable approach for construction of novel electrochemical sensors.

The effectiveness of mobile app usage in facilitating weight loss: An observational study.

With increasing rates of global obesity and associated health issues, there is an ever-increasing need for weight management solutions to be more accessible. Mobile applications offer accessible support systems and have the potential to offer a viable and effective weight management solution as an alternative to traditional healthcare models. To evaluate the effectiveness of the SIMPLE mobile application for time-restricted eating in achieving weight loss (WL). User data were analyzed between January 2021 and January 2023. In-app activity was calculated as the proportion of active days over 12, 26 and 52weeks. A day is considered active if it contains at least one in-app action (e.g., logging weight, food, fasting, or physical activity). Users were categorized into four in-app activity levels: inactive (in-app activity <33%), medium activity (33%-66%), high activity (66%-99%), and maximal activity (100%). Weight change among in-app activity groups was assessed at 12, 26, and 52weeks. Out of 53,482 users, a positive association was found between the use of the SIMPLE app and WL. Active app users lost more weight than their less active counterparts. Active users had a median WL of 4.20%, 5.04%, and 3.86% at 12, 26, and 52weeks, respectively. A larger percentage of active users-up to 50.26%-achieved clinically significant WL (≥5%) when compared to inactive users. A dose-response relationship between WL and app usage was found after adjusting for gender, age, and initial Body Mass Index; a 10% increase in app activity correlated with increased WL by 0.43, 0.66 and 0.69kg at 12, 26, and 52weeks, respectively. The study demonstrates that the SIMPLE app enables effective WL directly associated with the level of app engagement. Mobile health applications offer an accessible and effective weight management solution and should be considered when supporting adults to lose weight.

Athlete Performance Prediction Using Random Forest

Abstract: Fitness and health applications are increasingly being integrated into athletes' training routines, providing new opportunities for personalized performance optimization. This research paper investigates the utilization of smartwatch metrics and machine learning algorithms for predicting athlete performance, focusing on metrics such as power. Through a comprehensive analysis of collected data and employing advanced machine learning techniques, the study aims to provide insights into the predictive capabilities of smartwatch data in the realm of sports science. The introduction of a user-friendly athlete interface further enhances the accessibility and usability of this innovative technology. Smartwatch metrics combined with machine learning algorithms offer a potent toolset for predicting athlete performance. Smartwatches collect vast amounts of data on an athlete's biometrics, such as heart rate, activity levels, and more. Machine learning algorithms analyse this data to uncover patterns, correlations, and trends that are often imperceptible to human observation. By training models on historical data from athletes and their performances, these algorithms can make predictions about future performance, injury risk, optimal training schedules, and even suggest personalized strategies for improvement. This fusion of technology enables coaches and athletes to make data-driven decisions, optimize training regimens, and enhance overall performance while minimizing the risk of injury.

Impact of chemotherapy delay on long-term prognosis of laparoscopic radical surgery for locally advanced gastric cancer: a pooled analysis of four randomized controlled trials.

Adjuvant chemotherapy following curative surgery for locally advanced gastric cancer (AGC) significantly improves long-term patient prognosis. However, delayed chemotherapy (DC), in which patients are unable to receive timely treatment, is a common phenomenon in clinical practice for various reasons. This study aimed to investigate the impact of DC on the prognosis of patients with stage II-III locally AGC and explore the associated risk factors. Data from four prospective studies were included in the pooled analysis. The planned chemotherapy (PC) group was defined as the time interval between surgery and the first chemotherapy ≤ 49 d, while the DC group was defined as the time interval between surgery and chemotherapy > 49 d. The prognosis, recurrence, and risk factors were compared, and a nomogram for predicting DC was established. In total, 596 patients were included, of whom 531 (89.1%) had PC and 65 (10.9%) had DC. Survival analysis revealed that the 5-year overall survival (OS) and disease-free survival (DFS) were significantly lower in the DC group than those in the PC group (log-rank P < 0.001). Cox univariable and multivariable analyses showed that DC was an independent risk factor for OS and DFS in stage II-III patients (P < 0.05). Based on the significant factors for DC, a prediction model was established that had a good fit, high accuracy (AUC = 0.780), and clinical applicability in both the training and validation sets. Delayed chemotherapy after gastrectomy is associated with poor long-term prognosis in patients with locally advanced stage II-III GC disease. But standardized, full-cycle adjuvant chemotherapy after surgery may play a remedial role, and can to a certain extent compensate the poor effects caused by delayed chemotherapy.

"I'm Staring at the Screen All the Time": Technology Use and Mindfulness in Adolescents with Type 1 Diabetes.

Type 1 diabetes (T1D) is a chronic, complex medical condition associated with higher rates of anxiety in adolescents. Higher rates of anxiety are associated with poorer glycemic control. Although technological advancements have been made to improve self-management of glycemia, few technological interventions aim to mitigate anxiety symptoms. Adolescents frequently use technology every day for school and socialization in addition to management of glycemia. Technology has not yet been leveraged to provide evidence-based interventions, such as mindfulness, for anxiety symptoms and other psychosocial comorbidity in adolescents with T1D. We aimed to examine technology preferences in adolescents with type 1 diabetes, their experiences with mindfulness practices, and their perceived acceptability of a mobile health application delivering mindfulness training. Twenty participants aged 14 to 17 years old with T1D participated in this qualitative descriptive study. Interview transcripts were organized using the ATLAS.ti software version 8 and coded using an in vivo approach and thematic analysis. Descriptive statistics regarding participant demographics and hemoglobin A1c levels were analyzed using SAS statistical software version 9.2. Findings supported heavy technology use, limited experience with mindfulness, and positive receptivity regarding an app that delivered a mindfulness training program specifically for adolescents with T1D. Thus, a mobile health application may be a feasible and acceptable way to deliver an evidence-based psychosocial intervention to this vulnerable population.

Study on efficient drying process of industrial silicon powder

AbstractThe drying procedure is an important consideration for the silicon powder processing. Herein, a comparative investigation of the drying efficiency, drying performance, and energy consumption of silicon powder after separation and purification of monocrystal silicon cutting slurry by using the hot air, far‐infrared and microwave drying treatments. The results show that microwave drying of 30 g silicon powder takes only 12 min, which is much shorter than hot air drying of 200 min and far infrared drying of 40 min. The water evaporation energy consumption of microwave drying reached 73.5 g/kW·h, which was 3.3 times than that of far infrared drying and 16.5 times than that of hot air drying. For 1 kg of silicon powder, the power consumption of microwave drying was 8 kW·h, while the far‐infrared drying was 26.7 kW·h, and the hot air drying was 133.4 kW·h, respectively. Therefore, effects of microwave power, drying temperature and drying time on the dehydration rate of silicon powder were investigated and optimized by response surface method, demonstrating that the microwave drying dehydration rate of 30 g silicon powder could reach 97.65%, and the power consumption could be reduced to 6.7 kW·h/kg under the conditions of microwave power of 1000 W, drying temperature of 89°C and drying time of 12 min. The present study shows that microwave drying of silicon powder is an energy‐saving and efficient process with good industrial application prospects.

Mapping model between lateral responses of bridges under random traffic loads based on data-driven approach

Abstract The lateral distribution characteristic of a bridge is one of the important features reflecting its in-service state. Conventional deterministic indicators often struggle to consider this time-varying feature. In this study, a data-driven approach is employed to establish the mapping model among responses at the different lateral positions using the eXtreme Gradient Boosting model optimized by the Bayesian optimization algorithm. The proposed method is validated based on both data from a bridge health monitoring system equipped on an actual bridge and data from numerical simulation. At different lateral positions of the actual bridge, the overall coefficient of determination (R2) of the strain response mapped by the model is above 0.991, and the overall root mean squared error (RMSE) of the strain response mapped by the model are below 1.159 με. The numerical simulation method is used to consider a variety of working conditions with different road surface roughness and different traffic densities. Under different working conditions, the overall R2 of the deflection response mapped by the model is still above 0.961, and the overall RMSE of the deflection response mapped by the model is below 0.249 mm. These indicate that the proposed model can consider time-varying mapping relationships among responses at different lateral positions, and has good accuracy and applicability.

Design of overhead ground wire repair robot based on unmanned aerial vehicles

AbstractAiming at the problem that it is impossible to accurately transport the aerial ground wire repair robot to the repair point and efficiently repair the ground wire broken strands and scattered strands, this paper designs an aerial ground wire repair robot based on Unmanned Aerial Vehicle (UAV). Firstly, the mechanical structure of the overhead ground wire repair robot is selected and designed, and the information transmission and the cooperative operation of each module are realized. A landing mark based on ArUco code is designed, which uses C++ for visual navigation, and then uses the double closed‐loop Proportional Integral Derivative (PID) control method to control the position and attitude of the UAV, so as to realize the tracking of the robot position by the UAV. At the same time, the mechanical structure and the control method of the UAV hanging device are designed to cooperate with the overhead ground wire repair robot to ensure the accurate completion of the repair operation. Finally, a UAV‐based aerial ground wire repair robot prototype was developed and successfully applied to the repair operation of the broken strand of the aerial ground wire of the 66 to 67 tower of the 500 kV Jiangzi line in Ya'an. It is verified that the UAV‐based aerial ground wire repair robot studied in this paper has a good engineering application value.

Biosynthesis and Biotechnological Synthesis of Hydroxytyrosol

Hydroxytyrosol (HT), a plant-derived phenolic compound, is recognized for its potent antioxidant capabilities alongside a spectrum of pharmacological benefits, including anti-inflammatory, anti-cancer, anti-bacterial, and anti-viral properties. These attributes have propelled HT into the spotlight as a premier nutraceutical and food additive, heralding a new era in health and wellness applications. Traditional methods for HT production, encompassing physico-chemical techniques and plant extraction, are increasingly being supplanted by biotechnological approaches. These modern methodologies offer several advantages, notably environmental sustainability, safety, and cost-effectiveness, which align with current demands for green and efficient production processes. This review delves into the biosynthetic pathways of HT, highlighting the enzymatic steps involved and the pivotal role of genetic and metabolic engineering in enhancing HT yield. It also surveys the latest progress in the biotechnological synthesis of HT, examining innovative strategies that leverage both genetically modified and non-modified organisms. Furthermore, this review explores the burgeoning potential of HT as a nutraceutical, underscoring its diverse applications and the implications for human health. Through a detailed examination of both the biosynthesis and biotechnological advances in HT production, this review contributes valuable insights to the field, charting a course towards the sustainable and scalable production of this multifaceted compound.

Stretchable Unsymmetrical Piezoelectric BiO2-x Deposited-Hydrogel as Multimodal Triboelectric Nanogenerators for Biomechanical Motion Harvesting.

Enhancing the output performance of triboelectric nanogenerators (TENGs) is essential for increasing their application in smart devices. Oxygen-vacancy-rich BiO2-x nanosheets (BiO2-x NSs) are advanced-engineered nanomaterials with excellent piezoelectric properties. Herein, a stretchable unsymmetrical BiO2-x NSs deposited-hydrogel made of polyacrylamide (PAM) as a multimodal TENG is rationally fabricated, and the performance of TENG can be tailored by controlling the BiO2-x NSs deposition amount and spatial distribution. The alteration of resistance caused by the Poisson effect of PAM/BiO2-x composite hydrogel (H-BiO2-x) can be used as a piezoresistive sensor, and the piezoelectricity of BiO2-x NSs can effectively enhance the density of transfer charge, thus improving the output performance of the H-BiO2-x-based TENG. In addition, the chemical cross-linking between the BiO2-x NSs and the PAM polymer chain allows the hydrogel electrode to have a higher tensile capacity (867%). Used for biomechanical motion signal detection, the sensors made of H-BiO2-x have high sensitivity (gauge factor = 6.93) and can discriminate a range of forces (0.1-5.0 N) at low frequencies (0.5-2.0Hz). Finally, the prepared TENG can collect biological energy and convert it into electricity. Consequently, the improved TENG shows a good application prospect as multimodal biomechanical sensors by combining piezoresistive, piezoelectric, and triboelectric effects.

Detection and diagnosis of automated breast ultrasound in patients with BI-RADS category 4 microcalcifications: a retrospective study

BackgroundAutomated Breast Ultrasound (AB US) has shown good application value and prospects in breast disease screening and diagnosis. The aim of the study was to explore the ability of AB US to detect and diagnose mammographically Breast Imaging Reporting and Data System (BI-RADS) category 4 microcalcifications.Methods575 pathologically confirmed mammographically BI-RADS category 4 microcalcifications from January 2017 to June 2021 were included. All patients also completed AB US examinations. Based on the final pathological results, analyzed and summarized the AB US image features, and compared the evaluation results with mammography, to explore the detection and diagnostic ability of AB US for these suspicious microcalcifications.Results250 were finally confirmed as malignant and 325 were benign. Mammographic findings including microcalcifications morphology (61/80 with amorphous, coarse heterogeneous and fine pleomorphic, 13/14 with fine-linear or branching), calcification distribution (189/346 with grouped, 40/67 with linear and segmental), associated features (70/96 with asymmetric shadow), higher BI-RADS category with 4B (88/120) and 4 C (73/38) showed higher incidence in malignant lesions, and were the independent factors associated with malignant microcalcifications. 477 (477/575, 83.0%) microcalcifications were detected by AB US, including 223 malignant and 254 benign, with a significantly higher detection rate for malignant lesions (x2 = 12.20, P < 0.001). Logistic regression analysis showed microcalcifications with architectural distortion (odds ratio [OR] = 0.30, P = 0.014), with amorphous, coarse heterogeneous and fine pleomorphic morphology (OR = 3.15, P = 0.037), grouped (OR = 1.90, P = 0.017), liner and segmental distribution (OR = 8.93, P = 0.004) were the independent factors which could affect the detectability of AB US for microcalcifications. In AB US, malignant calcification was more frequent in a mass (104/154) or intraductal (20/32), and with ductal changes (30/41) or architectural distortion (58/68), especially with the both (12/12). BI-RADS category results also showed that AB US had higher sensitivity to malignant calcification than mammography (64.8% vs. 46.8%).ConclusionsAB US has good detectability for mammographically BI-RADS category 4 microcalcifications, especially for malignant lesions. Malignant calcification is more common in a mass and intraductal in AB US, and tend to associated with architectural distortion or duct changes. Also, AB US has higher sensitivity than mammography to malignant microcalcification, which is expected to become an effective supplementary examination method for breast microcalcifications, especially in dense breasts.

Enhanced performance of a Na3.5Co4[Bi2Co2W19.75O70(H2O)6]/porous graphitic carbon nitride heterojunction based photocatalyst realized by the addition of copper sulfide nanoparticles.

Photocatalytic hydrogen (H2) evolution can effectively solve the global energy problem, in which the key factor is the synthesis of efficient photocatalytic materials. In this study, we successfully synthesized a novel photocatalyst, BiWCo/CuS/PGCN, by functionalizing porous graphitic carbon nitride (PGCN) with sandwich-type polyoxometalate Na3.5Co4[Bi2Co2W19.75O70(H2O)6]·39.5H2O (BiWCo) and introducing copper sulfide (CuS) nanoparticles as a cocatalyst. This approach was aimed at enhancing the built inner electric field between interfaces, resulting in a significant improvement in photocatalytic H2 evolution performance. This research adopts a step-by-step method to synthesize BiWCo/CuS/PGCN composites with p-n heterojunctions, which has high visible light absorption and a synergistic effect of multiple elements. PGCN with a high specific surface area contributes to the uniform distribution of active sites. In addition, the nano-CuS cocatalyst provides abundant active sites and more electron transfer pathways for photocatalysis. Therefore, the H2 production efficiency of BiWCo/CuS/PGCN is 6.3 times that of PGCN, 4.5 times that of BiWCo and 2.5 times that of BiWCo/PGCN under visible light. The H2 production rate of BiWCo/CuS/PGCN reaches 3477.58 μmol g-1 h-1. At the same time, the ternary photocatalyst shows high stability after 30 hours and 5 cycles. This work demonstrates that BiWCo/CuS/PGCN has good application prospects in H2 evolution, and provides a new strategy for the design of efficient ternary photocatalytic materials.

EDA-Graph: Graph Signal Processing of Electrodermal Activity for Emotional States Detection.

The continuous detection of emotional states has many applications in mental health, marketing, human-computer interaction, and assistive robotics. Electrodermal activity (EDA), a signal modulated by sympathetic nervous system activity, provides continuous insight into emotional states. However, EDA possesses intricate nonstationary and nonlinear characteristics, making the extraction of emotion-relevant information challenging. We propose a novel graph signal processing (GSP) approach to model EDA signals as graphical networks, termed EDA-graph. The GSP leverages graph theory concepts to capture complex relationships in time-series data. To test the usefulness of EDA-graphs to detect emotions, we processed EDA recordings from the CASE emotion dataset using GSP by quantizing and linking values based on the Euclidean distance between the nearest neighbors. From these EDA-graphs, we computed the features of graph analysis, including total load centrality (TLC), total harmonic centrality (THC), number of cliques (GNC), diameter, and graph radius, and compared those features with features obtained using traditional EDA processing techniques. EDA-graph features encompassing TLC, THC, GNC, diameter, and radius demonstrated significant differences (p<0.05) between five emotional states (Neutral, Amused, Bored, Relaxed, and Scared). Using machine learning models for classifying emotional states evaluated using leave-one-subject-out cross-validation, we achieved a five-class F1 score of up to 0.68.