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The friction pair gap affects not only the temperature increase of the multi-disc wet clutch, but also the efficiency of the helicopter transmission system. Consequently, a rotational–axial engagement and disengagement-coupled kinetic model of a wet multi-disc clutch considering asperity contact, hydrodynamic lubrication, spline resistance, and a separating spring model are developed in this paper. The effects of operating conditions on the dynamic characteristics of the wet clutch are investigated. Further, the gap deviation coefficient is proposed to characterize the dynamic behavior of the friction pair gap. As the control oil pressure increases from 1.3 MPa to 1.7 MPa, the gap deviation coefficient increases by 8.6%. Moreover, as the rotation speed increases from 888 rpm to 2488 rpm and the lubricant oil temperature increases from 25 °C to 85 °C, the gap deviation coefficient decreases by 1.1% and 4.44%, respectively. Therefore, an appropriate increase in lubricant oil temperature and rotation speed can facilitate the friction pair gap to be more uniform. These results are useful for the development of optimal control strategies for aviation wet clutch systems. [ABSTRACT FROM AUTHOR]

This study explores memristor-based true random number generators (TRNGs) through their evolution and optimization, stemming from the concept of memristors first introduced by Leon Chua in 1971 and realized in 2008. We will consider memristor TRNGs coming from various entropy sources for producing high-quality random numbers. However, we must take into account both their strengths and weaknesses. The comparison with CMOS-based TRNGs will serve as an illustration that memristor TRNGs stand out due to their simpler circuits and lower power consumption— thus leading us into a case study involving electroless YMnO3 (YMO) memristors as TRNG entropy sources that demonstrate good security properties by being able to produce unpredictable random numbers effectively. The end of our analysis sees us pinpointing challenges: post-processing algorithm optimization coupled with ensuring reliability over time for memristor-based TRNGs aimed at next-generation security applications. [ABSTRACT FROM AUTHOR]

A vehicle detection algorithm is an indispensable component of intelligent traffic management and control systems, influencing the efficiency and functionality of the system. In this paper, we propose a lightweight improvement method for the YOLOv5 algorithm based on integrated perceptual attention, with few parameters and high detection accuracy. First, we propose a lightweight module IPA with a Transformer encoder based on integrated perceptual attention, which leads to a reduction in the number of parameters while capturing global dependencies for richer contextual information. Second, we propose a lightweight and efficient multiscale spatial channel reconstruction (MSCCR) module that does not increase parameter and computational complexity and facilitates representative feature learning. Finally, we incorporate the IPA module and the MSCCR module into the YOLOv5s backbone network to reduce model parameters and improve accuracy. The test results show that, compared with the original model, the model parameters decrease by about 9%, the average accuracy (mAP@50) increases by 3.1%, and the FLOPS does not increase. [ABSTRACT FROM AUTHOR]

The interconnectivity of advanced biological systems is essential for their proper functioning. In modern connectomics, biological entities such as proteins, genes, RNA, DNA, and metabolites are often represented as nodes, while the physical, biochemical, or functional interactions between them are represented as edges. Among these entities, metabolites are particularly significant as they exhibit a closer relationship to an organism's phenotype compared to genes or proteins. Moreover, the metabolome has the ability to amplify small proteomic and transcriptomic changes, even those from minor genomic changes. Metabolic networks, which consist of complex systems comprising hundreds of metabolites and their interactions, play a critical role in biological research by mediating energy conversion and chemical reactions within cells. This review provides an introduction to common metabolic network models and their construction methods. It also explores the diverse applications of metabolic networks in elucidating disease mechanisms, predicting and diagnosing diseases, and facilitating drug development. Additionally, it discusses potential future directions for research in metabolic networks. Ultimately, this review serves as a valuable reference for researchers interested in metabolic network modeling, analysis, and their applications. [ABSTRACT FROM AUTHOR]

Macau, recognized as a global tourism hub and the world's most densely populated region, provides a unique environment conducive to methicillin-resistant Staphylococcus aureus (MRSA) transmission in healthcare and community settings, posing a significant public health concern both locally and globally. The epidemiology and molecular characteristics of MRSA in the distinct city of Macau remain largely unelucidated. This five-year longitudinal study (2017–2022) examined the local prevalence and molecular typing of MRSA in Macau, with future MRSA type distribution predicted through ARIMA modeling. We subsequently analyzed the epidemiological characteristics of MRSA, including specimen source, clinical department, collection year, season, patient age, sex, and the annual number of tourists. Comprehensive antibiotic resistance profiles of the strains were also assessed. Of 504 clinically isolated S. aureus strains, 183 (36.3%) were identified as MRSA by the cefoxitin disk diffusion method and validated through multi-locus sequence typing (MLST). The MRSA detection rate showed an upward trend, increasing from 30.1% in 2017 to 45.7% in 2022. SCCmec type IV was predominant (28.9%), followed by types II (25.4%), III (22.1%), and V (22.1%). The primary sources of MRSA isolates were sputum (39.2%) and secretions (25.6%). Older age emerged as a risk factor for MRSA infection, whereas no significant associations were found with seasonal variations, gender, or the annual number of tourists. Despite displaying universal resistance to cefoxitin, oxacillin, and benzylpenicillin, MRSA isolates in Macau remained fully sensitive to vancomycin, tigecycline, quinupristin, nitrofurantoin, and linezolid. Continuous surveillance and analysis of MRSA distribution in Macau could provide invaluable insights for the effective management of MRSA prevention and control measures within healthcare settings. [ABSTRACT FROM AUTHOR]

The pursuit of higher recognition accuracy and speed with smaller model sizes has been a major research topic in the detection of surface defects in steel. In this paper, we propose an improved high-speed and high-precision Efficient Fusion Coordination network (EFC-YOLO) without increasing the model's size. Since modifications to enhance feature extraction in shallow networks tend to affect the speed of model inference, in order to simultaneously ensure the accuracy and speed of detection, we add the improved Fusion-Faster module to the backbone network of YOLOv7. Partial Convolution (PConv) serves as the basic operator of the module, which strengthens the feature-extraction ability of shallow networks while maintaining speed. Additionally, we incorporate the Shortcut Coordinate Attention (SCA) mechanism to better capture the location information dependency, considering both lightweight design and accuracy. The de-weighted Bi-directional Feature Pyramid Network (BiFPN) structure used in the neck part of the network improves the original Path Aggregation Network (PANet)-like structure by adding step branches and reducing computations, achieving better feature fusion. In the experiments conducted on the NEU-DET dataset, the final model achieved an 85.9% mAP and decreased the GFLOPs by 60%, effectively balancing the model's size with the accuracy and speed of detection. [ABSTRACT FROM AUTHOR]

With the popularity of ChatGPT, there has been increasing attention towards dialogue systems. Researchers are dedicated to designing a knowledgeable model that can engage in conversations like humans. Traditional seq2seq dialogue models often suffer from limited performance and the issue of generating safe responses. In recent years, large-scale pretrained language models have demonstrated their powerful capabilities across various domains. Many studies have leveraged these pretrained models for dialogue tasks to address concerns such as safe response generation. Pretrained models can enhance responses by carrying certain knowledge information after being pre-trained on large-scale data. However, when specific knowledge is required in a particular domain, the model may still generate bland or inappropriate responses, and the interpretability of such models is poor. Therefore, in this paper, we propose the KRP-DS model. We design a knowledge module that incorporates a knowledge graph as external knowledge in the dialogue system. The module utilizes contextual information for path reasoning and guides knowledge prediction. Finally, the predicted knowledge is used to enhance response generation. Experimental results show that our proposed model can effectively improve the quality and diversity of responses while having better interpretability, and outperforms baseline models in both automatic and human evaluations. [ABSTRACT FROM AUTHOR]

Interleaved DC–DC converters have significant advantages in improving the capability of power converters, and coupling the filtering inductor of the converter could further increase the power density. However, existing modeling and controller designs are complex and require multiple sensors to be involved in the control, which is not conducive to engineering implementation and reducing production costs. In view of this problem, taking a two-phase interleaved boost converter with a coupled inductor as an example, the small-signal models of the converter are derived for the resistive load and constant voltage source load using the state averaging method. The total inductor current is engaged in the control as a feedback signal, avoiding the coupling effect of the inductor on increasing the complexity of the controller. Based on this, a double closed-loop controller is designed, and a prototype of the two-phase interleaved boost converter with coupled inductor is built. Only one current sensor and one voltage sensor are required to participate in the control. The effectiveness of the analysis and design in this paper are verified by experiments. [ABSTRACT FROM AUTHOR]

In the context of COVID-19, the research on various aspects of the venipuncture robot field has become increasingly hot, but there has been little research on robotic needle insertion angles, primarily performed at a rough angle. This will increase the rate of puncture failure. Furthermore, there is sometimes significant pain due to the patients' differences. This paper investigates the optimal needle entry angle decision for a dorsal hand intravenous injection robot. The dorsal plane of the hand was obtained by a linear structured light scan, which was used as a basis for calculating the needle entry angle. Simulation experiments were also designed to determine the optimal needle entry angle. Firstly, the linear structured optical system was calibrated and optimized, and the error function was constructed and solved iteratively by the optimization method to eliminate measurement error. Besides, the dorsal hand was scanned to obtain the spatial point clouds of the needle entry area, and the least squares method was used to fit it to obtain the dorsal hand plane. Then, the needle entry angle was calculated based on the needle entry area plane. Finally, the changes in the penetration force under different needle entry angles were analyzed to determine the optimal needle insertion angle. According to the experimental results, the average error of the optimized structured light plane position was about 0.1 mm, which meets the needs of the project, and a large angle should be properly selected for needle insertion during the intravenous injection. [ABSTRACT FROM AUTHOR]

Retinal vessel segmentation remains a challenging task because the morphology of the retinal vessels reflects the health of a person, which is essential for clinical diagnosis. Therefore, achieving accurate segmentation of the retinal vessel shape can determine the patient's physical condition in a timely manner and can prevent blindness in patients. Since the traditional retinal vascular segmentation method is manually operated, this can be time-consuming and laborious. With the development of convolutional neural networks, U-shaped networks (U-Nets) and variants show good performance in image segmentation. However, U-Net is prone to feature loss due to the operation of the encoder convolution layer and also causes the problem of mismatch in the processing of contextual information features caused by the skip connection part. Therefore, we propose an improvement of the retinal vessel segmentation method based on U-Net to segment retinal vessels accurately. In order to extract more features from encoder features, we replace the convolutional layer with ResNest network structure in feature extraction, which aims to enhance image feature extraction. In addition, a Depthwise FCA Block (DFB) module is proposed to deal with the mismatched processing of local contextual features by skip connections. Combined with the two public datasets on retinal vessel segmentation, namely DRIVE and CHASE_DB1, and comparing our method with a larger number of networks, the experimental results confirmed the effectiveness of the proposed method. Our method is better than most segmentation networks, demonstrating the method's significant clinical value. [ABSTRACT FROM AUTHOR]

The coal gangue after composite activation treatment is considered a potential low-carbon and green cementitious material, so the feasibility of employing composite-activated gangue to partially or entirely replace cement for building materials is systematically studied in this paper. The effects of alkali content, slag content, and water-to-binder ratio on the mechanical properties and frost resistance of alkali-activated coal gangue mortar (AACGM) were experimentally investigated. An ESEM was employed to observe the microstructure of the AACGM. Moreover, the microstructure damage to the AACGM was analyzed by a pixel-based image processing algorithm. The research was carried out in accordance with standards JGJ/T70-2009 and GB/T 50082-2009. Experimental results indicated that the mechanical properties and frost resistance of the AACGM were superior to those of ordinary Portland cement mortar (OPCM). Compared with the OPC group, the compressive and flexural strength of the W0.50 group increased by 16.01% and 14.19%. Moreover, the loss rate of mass, flexural strength, compressive strength, and microstructure damage of the AACGM were less than those of the OPCM. Between freeze–thaw cycles 25 and 100, the cracks and pores of specimens gradually grew, and the maximum crack width increased by 277.78%. In addition, the slag was beneficial in improving the flexural strength, compressive strength, and frost resistance of the AACGM. Finally, the freeze–thaw damage mechanism of the CGBG mortar was systematically analyzed. [ABSTRACT FROM AUTHOR]

The feasibility of composite-activated coal gangue (CACG) as the primary cementitious material for concrete was experimentally studied in this paper. The effects of concrete strength grade on slump and slump flow, compressive strength, splitting tensile strength, axial compressive strength, elastic modulus, and drying shrinkage of alkali-activated coal gangue concrete (AACGC) were experimentally investigated. Experimental results indicated that the slump and slump flow of the AACGC were smaller than that of ordinary Portland cement concrete (OPCC). The mechanical properties of the AACGC were superior to those of the OPCC. The compressive strength, splitting tensile strength, axial compressive strength, and elastic modulus of the AACGC were 1.17 times, 1.04 times, 1.47 times, and 1.04 times those of the OPCC, respectively. With the increase in concrete strength grade, the mechanical properties of the AACGC have gradually increased. The difference in failure modes of axial compressive strength between the AACGC and OPCC was analyzed. Moreover, the empirical formulas of the elastic modulus and compressive strength for the OPCC in various regions codes were summarized, and found that the empirical formula in GB 50010-2002 code and EN 1922 Eurocode 2 was also applicable to the AACGC. Finally, the mass-loss rate and drying shrinkage for the AACGC at different concrete strength grades were systematically analyzed, and a hyperbolic prediction model was proposed to reflect the drying shrinkage behavior of the AACGC. [ABSTRACT FROM AUTHOR]

As artificial intelligence develops, deep learning algorithms are increasingly being used in the field of dorsal hand vein (DHV) recognition. However, deep learning has high requirements regarding the number of samples, and current DHV datasets have few images. To solve the above problems, we propose a method based on the fusion of ResNet and Histograms of Oriented Gradients (HOG) features, in which the shallow semantic information extracted by primary convolution and HOG features are fed into the residual structure of ResNet for full fusion and, finally, classification. By adding Gaussian noise, the North China University of Technology dataset, the Shandong University of Science and Technology dataset, and the Eastern Mediterranean University dataset are extended and fused to from a fused dataset. Our proposed method is applied to the above datasets, and the experimental results show that our proposed method achieves good recognition rates on each of the datasets. Importantly, we achieved a 93.47% recognition rate on the fused dataset, which was 2.31% and 26.08% higher than using ResNet and HOG alone. [ABSTRACT FROM AUTHOR]

Compared to the equiatomic or near-equiatomic NiTinol alloys, Ni-rich NiTi alloys are suitable to be employed in structural applications as they exhibit higher hardness and are dimensionally stable. This research aimed to process two different grades of Ni-rich NiTi alloys, 58NiTi and 60NiTi, from Ni–Ti powder mixtures having about 58 wt.% and 60 wt.% Ni, respectively. This was performed by a laser powder bed fusion technique. At the first stage of this research, the printability of the used powder mixtures was investigated by applying different sets of printing parameters. Two appropriate sets were then selected to print the samples. Microstructural study of the printed parts revealed the existence of inhomogeneity in the microstructures. In addition, depending on the applied set of parameters, some amounts of cracks and pores were also present in the microstructure of these parts. Postprinting hot isostatic pressing procedures, performed at different temperatures, were developed to cause the reaction of phases, homogenize the parts, and possibly eliminate the existing flaws from the samples. Effects of these applied treatments on the microstructure, phase composition, density, dimensional integrity, and hardness of parts were sequentially studied. In essence, 58NiTi and 60NiTi parts having phase compositions complying with those of the equilibrium phase diagram were obtained in this research. However, the mentioned cracks and pores, formed in the microstructure of as-printed parts, could not be fully removed by postprocessing treatments. [ABSTRACT FROM AUTHOR]

Total dissolved gas (TDG) is suggested to be one possible explanation for the extensive mortality of endemic fish suffered from gas bubble disease (GBD). We investigated the effects of water depth on adult Schitzothorax prenanti susceptibility to GBD in TDG supersaturated water 11.5 km downstream of Dagangshan dam in a two-year (2016–2017) live cage study. The probability of survival significantly increased at greater depth. The mortality of fish at 1–2 m was reduced to 50% of that at 0–1 m and the mortality rate for fish at 2–3 m was reduced to 25% of that at 0–1 m. Fish that survived in-situ TDG exposure in 2016 were relocated to equilibrated water and observed for 274 d to investigate sublethal effects of GBD. The surviving fish showed a substantial reduction in growth compared to the control group. During the flood discharge period in 2017, fish were re-exposed to TDG supersaturated water after a period of recovery (274 d) in equilibrated water. The mortality rate of re-exposed fish decreased to 35% compared to newly introduced fish. Our results contribute to the protection of aquatic organisms and the improvement of eco-friendly hydroelectric dam operations in the Yangtze River. [ABSTRACT FROM AUTHOR]

Physical exercise is effective in enhancing cognitive function, reducing anxiety and depressive symptoms, reducing cravings, and improving quality of life in methamphetamine (METH) addiction. However, little is known about the effect of exercise on metabolic profiles. We performed LC/MS-based targeted metabolic profiling on serum samples to investigate the metabolic characteristics of METH dependence and find the differences between METH-dependent individuals and nonusers and evaluated the metabolomic profiles of individuals with METH dependence following aerobic exercise training. We identified a total of 201 metabolites, among which 115 were differentially expressed under METH use. Among the differentially regulated metabolites, 72 were selected as potential biomarkers. Further analysis identified 19 pathways, among which glyoxylate and dicarboxylate metabolism; alanine, aspartate, and glutamate metabolism; and citrate cycle were most significantly affected by METH. The aerobic exercise intervention differentially regulated 55 metabolites, of which 51 were selected as potential biomarkers and were mainly enriched in 10 pathways. Interestingly, alanine, aspartate, and glutamate metabolism and nitrogen metabolism were the remarkably affected pathways. Furthermore, METH increased the serum levels of glutamate and decreased GABA, whereas exercise decreased the serum levels of glutamate and increased GABA. Results suggested that METH dependency disturbed normal metabolic homeostasis, whereas exercise restored metabolism. [ABSTRACT FROM AUTHOR]

This study involved a randomized, controlled, single-blind 12-month treatment study of a comprehensive nutritional and dietary intervention. Participants were 67 children and adults with autism spectrum disorder (ASD) ages 3-58 years from Arizona and 50 non-sibling neurotypical controls of similar age and gender. Treatment began with a special vitamin/mineral supplement, and additional treatments were added sequentially, including essential fatty acids, Epsom salt baths, carnitine, digestive enzymes, and a healthy gluten-free, casein-free, soy-free (HGCSF) diet. There was a significant improvement in nonverbal intellectual ability in the treatment group compared to the non-treatment group (+6.7 ± 11 IQ points vs. -0.6 ± 11 IQ points, p = 0.009) based on a blinded clinical assessment. Based on semi-blinded assessment, the treatment group, compared to the non-treatment group, had significantly greater improvement in autism symptoms and developmental age. The treatment group had significantly greater increases in EPA, DHA, carnitine, and vitamins A, B2, B5, B6, B12, folic acid, and Coenzyme Q10. The positive results of this study suggest that a comprehensive nutritional and dietary intervention is effective at improving nutritional status, non-verbal IQ, autism symptoms, and other symptoms in most individuals with ASD. Parents reported that the vitamin/mineral supplements, essential fatty acids, and HGCSF diet were the most beneficial. [ABSTRACT FROM AUTHOR]

A new method was proposed for the damage identification of box girder bridges under moving load, wherein the difference of strain influence line (DSIL) was taken as an index to represent the long-gauge strain difference before and after damage. The damage identification theory based on long-gauge strain influence lines was derived for box girder bridges with shear lag effect under consideration, and a regularized index DSIL was proposed for the quantitative identifications of damage location and extent. A series of experiments were carried out to study the influences of speed, vehicle type, and vehicle weight on the damage identification, and the experimental data were obtained by long-gauge fiber Bragg grating strain sensors. Moreover, numerical simulations were performed to confirm the method. The experimental and numerical results show that the method can locate the damage accurately, and quantitatively identify the damage extent under different working conditions. The experimental damage extent is generally slightly higher than the theoretical, with an average identification error smaller than 5%. Additionally, the relative error of damage extent is smaller than 3% under different working conditions. Thus, the effectiveness of this method was verified. [ABSTRACT FROM AUTHOR]

Dried blood spots (DBS) have proven to be a powerful sampling and storage method for newborn screening and many other applications. However, DBS methods have not yet been optimized for broad-spectrum targeted metabolomic analysis. In this study, we developed a robust, DBS-based, broad-spectrum, targeted metabolomic method that was able to measure over 400 metabolites from a 6.3 mm punch from standard Whatman 903TM filter paper cards. The effects of blood spot volumes, hematocrit, vacutainer chemistry, extraction methods, carryover, and comparability with plasma and fingerstick capillary blood samples were analyzed. The stability of over 400 metabolites stored under varying conditions over one year was also tested. No significant impacts of blood volume and hematocrit variations were observed when the spotted blood volume was over 60 µL and the hematocrit was between 31% and 50%. The median area under the curve (AUC) of metabolites in the DBS metabolome declined by 40% in the first 3 months and then did not decline further for at least 1 year. All originally detectable metabolites remained within detectable limits. The optimal storage conditions for metabolomic analysis were −80 °C with desiccants and without an O2 scavenger. The method was clinically validated for its potential utility in the diagnosis of the mitochondrial disease mitochondrial encephalomyopathy, lactic acidosis, and stroke-like episodes (MELAS). Our method provides a convenient alternative to freezing, storing, and shipping liquid blood samples for comparative metabolomic studies. [ABSTRACT FROM AUTHOR]

A quantitative feeding system of molten metal was designed based on a special vehicle cover, which achieved the quantitative transport of molten metal in a fully enclosed environment. There are lots of advantages of this novel device, such as improving the accuracy of the molten metal pouring, reducing the oxide inclusions defects, improving the quality of forming parts, etc. The numerical simulation of the casting process of filling mold was carried out based on the software ProCAST, which optimized the processing parameters of the quantitative feeding device. The result shows that the optimal movement speed of the punch piston is 0.08 m/s. The forming process of the aluminum alloy cover was designed and the process was conducted on the novel quantitative feeding device of molten metal. The structure and process performance of the forming parts were summarized and the defects were analyzed. The influence of technological parameters such as pouring temperature, filling speed, initial mold temperature, and feeding distance on the quality of forming parts was studied, which resulted in the optimum process parameters for the dosing device. [ABSTRACT FROM AUTHOR]

The shear behaviors of reinforced concrete (RC) beams externally strengthened with engineered cementitious composite (ECC) layers were studied and the strengthening effect was evaluated based on a truss and arch model. The beams were designed without web reinforcement in the middle part and ECC was sprayed onto both sides of the beams to the designed thicknesses, which were 20 mm and 40 mm. A series of four-point bending experiments were conducted and analyzed. The development of the shear strain in each side of the beams was recorded by strain rosettes formed with three fiber Bragg grating (FBG) sensors. The thickness of ECC layers, reinforcement ratios, and shear span-to-depth ratios were considered and analyzed. This is an effective way to shear strengthen RC beams with ECC layers. The ultimate load of the strengthened specimen can be improved by 89% over the control specimen. Strengthening an RC beam into an under-reinforced beam should be avoided. The FBG sensors are suitable to measure and monitor the development of shear strain in the side of the strengthened specimen. Based on the truss and arch model, an evaluation of the shear strengthening effect was established and the results agree well with the experimental results. [ABSTRACT FROM AUTHOR]

Vinegar and wine processing of medicinal plants are two traditional pharmaceutical techniques which have been used for thousands of years in China. Tetrahydropalmatine (THP), dehydrocorydaline (DHC) and protopine are three major bioactive molecules in Rhizoma Corydalis. In this study, a simple and reliable HPLC method was developed for simultaneous analysis of THP, DHC and protopine in rat tissues after gastric gavage administration of Rhizoma Corydalis. The validated HPLC method was successfully applied to investigate the effect of wine and vinegar processing on the compounds' distribution in rat tissues. Our results showed that processing mainly affect the T(max) and mean residence time (MRT) of the molecules without changing their C(max) and AUC(0-24)( )(h) Vinegar processing significantly increased the T(max) of DHC in heart, kidney, cerebrum, cerebrellum, brain stem and striatum and prolonged the T(max) of protopine in brain. No significant changes were observed on the T(max) of THP in rat tissues after vinegar processing. Wine processing reduced the T(max) of protopine and DHC in liver and spleen and T(max) of protopine in lung, but increased the T(max) of THP in all the rat tissues examined. To our knowledge, this is the first report on the effects of processing on the tissue distribution of the bioactive molecules from Rhizoma Corydalis.