Face swapping is an intriguing and intricate task in the field of computer vision. Currently, most mainstream face swapping methods employ face recognition models to extract identity features and inject them into the generation process. Nonetheless, such methods often struggle to effectively transfer identity information, result in generated results failing to achieve a high identity similarity with the source face. Furthermore, if we can accurately disentangle identity information, we can achieve controllable face swapping, thereby providing more choices to users. In pursuit of this goal, we propose a new face swapping framework (ControlFace) based on the disentanglement of identity information. We disentangle the structure and texture of the source face, encoding and characterizing them in the form of feature embeddings separately. According to the semantic level of each feature representation, we inject them into the corresponding feature mapper and fuse them adequately in the latent space of StyleGAN. Owing to such disentanglement of structure and texture, we are able to controllablely transfer parts of the identity features. Extensive experiments and comparisons with state-of-the-art face swapping methods demonstrate the superiority of our face swapping framework in terms of transferring identity information, producing high-quality face images and controllable face swapping.

Endoscopic medical images can suffer from uneven illumination, low contrast, and lack of texture information due to the use of point directional light sources and the presence of narrow tissue structures, posing diagnostic difficulties for physicians. In this paper, a deep learning-based su-pervised illumination enhancement network is designed for low-light endoscopic images, aiming to improve both global illumination and local details. Initially, a global illumination enhancement module is formulated utilizing a higher-order curve function to improve global illumination. Sec-ondly, a local feature extraction module incorporating dual attention is designed to capture local detailed features. Considering the significance of color fidelity in biomedical scenarios, the designed loss function prioritizes introducing color loss to alleviate image color distortion. Compared with seven state-of-the-art enhancement algorithms on Endo4IE endoscopic datasets, experimental re-sults show that the proposed method can better enhance low-light endoscopic images and avoid image color distortion. It provides an efficient method to enhance images captured by endoscopes which can effectively assist clinical diagnosis and treatment.

Hypsizygus marmoreus has become one of the most popular edible mushrooms due to its high nu-tritional and economic value. Previous researchers found that Serratia odorifera could promote the growth of H. marmoreus by producing and secreting some of its inducers. However, the specific mechanism of action was still unclear. In this study, we found that exogenous addition of sterile fermentation filtrate (HZSO-1), quorum sensing (QS signaling molecules, 3-oxo-C6-HSL, cy-clo(Pro-Leu), and cyclo(Tyr-Leu) could significantly promote the growth of H. marmoreus, increase the number of clamp junctions, and the diameter of mycelium (P < 0.05). In addition, non-targeted metabolomic analysis has revealed that 706 metabolites were detected in the treated group. Of these, 307 metabolites were significantly different (P < 0.05). Compared with the control, 54 and 86 metabolites were significantly increased and decreased in the HZSO-1 group, respec-tively (P < 0.05). We speculated that the sterile fermentation filtrate of S. odorifera could mediate the carbohydrate and amino acid metabolism of H. marmoreus by influencing the pentose phosphate pathway (PPP) to increase the energy supply for the growth and development of the mycelium. The above results will further reveal the growth-promoting mechanism of S. odorifera on H. mar-moreus.

The residual content of the only carbon source increases at the end of the exponential growth phase when P. putida BS3701 cells are cultured under nitrogen deficiency. Moreover, the mRNA quantity of some genes involved in carbon catabolism decreases. There are no available data on regulators capable of stimulating the target mRNA degradation in pseudomonads under nitrogen deficiency in the literature. We have applied both comparative genomics methods and a number of biomolecular ones to identify new small P. putida BS3701 RNAs. This is due to the fact that the formation of ncRNA-mRNA duplexes, recognized by RNases, is one of the main mechanisms for reducing the number of transcripts in a cell. We have used the following selection criteria: 1) the presence of the interest gene of the NtrC binding site and a sigma54-dependent promoter in the upstream area, 2) the conservative location of the interest gene in the P. putida and P. aeruginosa genomes, 3) increase in the product quantity of the interest gene in a cell under nitrogen deficiency on two different carbon sources (succinate and naphthalene), 4) the product detection of the interest gene in a fraction enriched with small RNAs. The expression of two new small RNAs has increased twice or more times under nitrogen deficiency on both succinate and naphthalene: expression of ng171 and ng379. ng379 contains narK RNA motif.

The management of blunt abdominopelvic trauma with combined hemoperitoneum and pelvic fractures is challenging for trauma surgeons. Although angioembolization can achieve hemostasis in most visceral organ injuries and pelvic fractures after blunt abdominal trauma, it cannot effectively control hemorrhage in patients with blunt bowel mesenteric injury (BBMI). This study aimed to determine the risk factors associated with hemodynamically unstable patients with BBMI and to test the hypothesis that pelvic fracture is an independent risk factor for patients with unstable BBMI and concomitant pelvic fracture to guide the therapeutic sequence for difficult-to-manage patients. This retrospective study reviewed the data of hospitalized patients with trauma between 2009 and 2021 and included 158 adult patients with surgically proven BBMI. The patients were divided on the basis of the presence of a shock episode before emergency laparotomy. The shock group included 44.3% of all patients in the study (n = 70). Clinical injury severity and prognosis for patients in the shock group were poorer than those for patients in the non-shock group, and more invasive treatments and transfusions were performed for patients in the shock group than for those in the non-shock group. Pelvic fractures were more frequently associated in the shock group than in the non-shock group (21.4% vs. 5.7%; p = 0.003). In multivariate analysis, the presence of intracerebral hemorrhage (odds ratio [OR] = 10.87, 95% confidence intervals [CIs]: 1.70–69.75) and rib fracture (OR = 5.94, 95% CIs = 1.06–33.45) were identified as independent predictors of shock, whereas the effect of pelvic fracture did not achieve statistical significance (OR = 2.94, 95% CIs = 0.66–13.13) after adjusting for confounding factors. For patients with BBMI, outcomes need to be improved during early diagnosis and treatments should be expeditiously performed on the basis of the rapid identification of unstable hemodynamic status. In unstable patients with concomitant pelvic fractures, we support the current management algorithm that recommends performing laparotomy first.

In this comprehensive survey, we delve into the multifaceted role of palmitoylation across vari-ous cell death modalities in the oncological context. From its intricate correlations with tumor-igenesis, steered by the DHHC family, to the counter-process of depalmitoylation mediated by enzymes like PPT1. Innovations in detection methodologies have paralleled our growing under-standing, transitioning from rudimentary techniques to sophisticated modern methods. Central to our discourse are agents like GNS561 and DC661, promising heralds in palmitoylation-targeted cancer therapy. Collectively, this review accentuates palmitoylation's transformative potential in oncology, foreshadowing groundbreaking therapeutic strategies and deepening our molecular comprehension of cancer dynamics.

In recent years, the use of solid waste fillers to partially replace natural fillers in asphalt mixtures to produce high-performance asphalt mixtures has received widespread attention. However, differences in the material properties of solid waste fillers remain a problem for this recycling method. To address this issue, limestone powder in asphalt mixtures was replaced by three solid waste fillers (steel slag powder, tailings powder and calcium carbide slag powder) in this study. The chemical composition of the fillers was first characterized to assess the homogeneity of the material. Then, AC and SMA asphalt mixtures were designed and produced and characterized for wet stability. The results showed that asphalt mixtures with solid waste fillers were superior to LP asphalt mixtures in terms of resistance to water damage, and steel slag powder showed the best improvement in moisture stability of asphalt mixtures. The optimum substitution of solid waste filler for limestone filler was 25%. In addition, the moisture stability of asphalt mixture with limestone filler was significantly improved with the addition of anti-stripping agents. In contrast, the moisture stability of asphalt mixtures with solid waste filler was slightly improved. Solid waste fillers could be used in asphalt mixtures and have a similar function as the anti-stripping agent. In summary, the use of solid waste fillers to replace mineral fillers in asphalt mixtures is a reliable, value-added, recycling option.

To conduct a precise impact assessment of marine diesel engines, a 200t floating impact platform was utilized to simulate realistic testing conditions. The testing generated the acceleration time curve and the impact response spectrum for the diesel engine. According to the applicable standards, the spectral velocity was chosen as the evaluation index, and an evaluation of the longitudinal, transverse, and vertical impact environment of the diesel engine was conducted. The shock factor interpolation method was corrected using the confidence interval based on normal distribution, and the interpolated confidence interval of the shock factor was determined. The findings reveal that: The 200t-class floating shock platform is capable of providing a reliable shock environment for diesel engine tests. The shock wave serves as the primary external force during the experiment, and the impact of bubble pulsation can be disregarded when assessing using the floating shock platform. To more accurately describe the experimental shock intensity when presented with dispersed data, the confidence interval can be utilized, and the resulting prediction formula provides a higher level of impact safety. The obtained conclusions can serve as a reference for predicting the shock environment of large shipboard equipment using the shock platform.

Chromium poisoning strongly influences the performance of solid oxide fuel cell (SOFC) stacks. A three-dimensional, time-dependent, computational fluid dynamics model of a single channel of a F10 SOFC stack in Forschungszentrum Jülich GmbH is developed to investigate chromium poisoning for different stack designs, temperatures and absolute air humidities. The model takes into account both chemical and electrochemical mechanisms of chromium poisoning and is able to predict the spatial distribution of SrCrO4 and Cr2O3. The voltage degradation over 100 kh can be simulated quantitatively. According to the simulation results, chromium poisoning is almost eliminated by the application of the protective coating fabricated by the atmospheric plasma-spraying (APS) technology. Besides, with the help of the APS protective coating, operating a SOFC stack with less dehumidified air at 650 oC is possible according to the simulation.

The optical reflection characteristics of asphalt pavement are an important influencing factor in road lighting design, and the macro and micro textures of asphalt pavement significantly affect its reflection characteristics. To investigate the impact of texture parameters on the retroreflection coefficient of asphalt pavement, this study obtained the macroscopic and microscopic texture properties of rutting board specimens and on-site asphalt pavement using a pavement texture tester. The macro- and microtexture parameters, such as macroscopic texture distribution density (D1), microscopic texture distribution density (D2), profile height root-mean-square (Rq), profile slope root-mean-square (Δq), skewness Rsk and kurtosis Rku, were measured, and the corresponding retroreflection coefficient RL was measured using a retro-reflectometer. In the laboratory ex-periments, rutting specimens of AC-13, SMA-13, and OGFC-13 asphalt mixtures were formed. The changes in texture parameters and retroreflection coefficient of different rutting specimens before and after crushing were studied, and a factor influence model between macro- and microtexture parameters and RL was established. And the correlation models of texture index and RL of asphalt pavement are further established. The results showed that in the single factor model, the param-eters can be used to characterize RL with high prediction accuracy, whereas for the on-site meas-urements, the three parameters of Δq, Rsk, and Rku can characterize the RL well. The nonlinear model established on the basis of the B-P neural network algorithm improves its prediction ac-curacy. This research can provide ideas for optimizing the reflection characteristics of asphalt pavement and further provide a decision-making basis for road lighting design.

Constructed wetlands (CWs) is a kind of green environmental protection technology, which is widely used in sewage treatment. The traditional CWs is faced with the problem of low treatment effect of high concentration sewage. In recent years, biochar, as a new type of adsorption material, has been used in CWs because of its advantages of large specific surface area, strong adsorption capacity and wide material sources. This paper systematically summarized the characteristics of biochar and the preparation of biochar by studying the changes of microorganisms added to CWs, and compared the effects of different treatment methods coupled with biochar on the treatment performance of CWs, the effects of biochar coupled with CWs on enzyme activity, functional genes, metabolites and microbial communities were investigated. This review summarizes how different preparation methods affect the properties of biochar and how these biochar cause changes in the microorganisms added to CWs.

Our image recognition system mainly judges whether the left upper limb in the image is the left upper limb or the right upper limb through our deep learning model in the image. The doctor then could give the correct surgical position. From the experimental results, it could be found that the precision rate and recall rate of the intelligent image recognition system proposed in this paper for preventing the upper limb dislocation surgery could reach 98% and 93%, respectively. It proved that our artificial intelligent image recognition system, AIIRS, could indeed assist orthopedic surgeons to prevent the occurrence of left and right dislocation in upper limb surgery. At the same time, this paper also completes the IRB application approval through the prototype experimental results and will conduct the second phase of human trials in the future. It showed that the research results of this paper will be of great benefit and research value to upper limb orthopedic surgery.

Recently, “mature” silkworms (MS) of Bombix mori have been considered as a potential nutraceutical, with a number of health benefits reported for steamed and lyophilized MS powder (SMSP). However, no obesity-related effects have been reported for SMSP. In the present study, anti-obesity effects of SMSP were investigated in adult mice in vivo, aged 12 weeks at the onset of drug administration, fed normal diet (ND) and high-fat diet (HFD), respectively, for 12 weeks. SMSP significantly suppressed body weight gain, intra-abdominal adipose tissue, and food efficiency in both ND-fed and HFD-fed adult mice. In addition, SMSP significantly decreased food intake and liver weight in HFD-fed mice, indicating that SMSP suppressed appetite and simultaneously reduced the conversion of feed into body weight in HFD-fed mice. SMSP also significantly lowered serum levels of glucose, triglyceride, total cholesterol, low-density lipoprotein cholesterol, asparagine transaminase, alanine transaminase, and alkaline phosphatase. However, SMSP had no significant effect on the weights of kidney, spleen, and thymus and serum levels of blood urea nitrogen and creatinine. Taken together, the above results suggest that SMSP has potent anti-obesity effects and is safe for long-term use as a potential therapeutic and/or nutraceutical in both obese patients and non-obese individuals.

Background: this study aimed to describe the distribution of the genotype and allele frequencies of GJB2 variants in the Chinese population of the Dongfeng Tongji cohort and to analyze the features of the hearing phenotype. Methods: we used data from 9910 participants in the Dongfeng Tongji cohort in 2013 and selected nine GJB2 variants. Pure-tone audiometry was employed to measure hearing. Differences in genotype and allele frequencies were analyzed by chi-squared test or Fisher's exact test. Results: of the 9910 participants, 5742 had hearing loss. The genotype frequency of the GJB2 variant p.V37I was statistically significantly distributed between the normal and impaired hearing groups, but not for the variant c.235delC. A higher frequency of the p.V37I homozygous genotype was found in the hearing loss group (0.5%) than in the normal hearing group (0.1%). Patients with p.V37I and c.235delC homozygous mutations exhibited varying degrees of hearing loss, mainly presenting sloping and flat audiogram shapes. Conclusions: a significant difference was found in the genotype frequency of the GJB2 variant p.V37I between the case and control groups, but not for the variant c.235delC. Different degrees of hearing loss and various audiogram shapes were observed in patients with p.V37I and c.235delC homozygous mutations.

The current deformation and stable state of slopes with historical shatter signs is a concern for engineering construction. Suspected landslide scarps were discovered at the rear edge of the slope of the Genie in the Sichuan-Tibet transportation corridor during a field investigation. In order to qualitatively determine the current status of the surface deformation of this slope, this paper uses high-resolution optical remote sensing, airborne LiDAR and InSAR technologies for comprehensive analysis. The interpretation of high-resolution optical and airborne LiDAR data revealed that the rear edge of the slope exhibits three levels of scarps. However, no deformation was detected with the D-InSAR analysis of ALOS-1 radar images from 2007 to 2008 or with the Stacking-InSAR and SBAS-InSAR processing of Sentinel-1A radar images from 2017 to 2020. A geological model of the slope was established in combination with field investigation stipulating that the slope is composed of steep anti-dip layered dolomite limestone and that the scarps at the rear edge of the slope were caused by historical shallow toppling. Further research is recommended to determine the extent of toppling deformation and evaluate the slope stability under the disturbance of tunnel excavation.

No-till and cereal-legume intercropping have been recognized as favorable cropping practices to increase crop yields while maintaining soil quality in arid and semiarid environment, but the bio-logical mechanisms are poorly understood. The present study was to determine the response of soil properties, enzyme activities, and microbial community diversity and composition in mono- and inter-cropping under conventional and no-tillage conditions. We initiated a field experiment in Wuwei, a typical arid area of China, in 2014. Soil was sampled in August 2022 and, yields, soil properties, enzyme activities, and the microbial community diversity and composition were de-termined in the maize and pea strips in inter- and mono-cropping systems. Results revealed that the maize and pea strips in the no-till intercropping significantly increased yields, total and or-ganic carbon stocks, decreased NO3--N, and obtained the highest total and organic P in the soil. The α- and β-diversity of archaea and eukaryotes were significantly affected by planting patterns, while α- and β-diversity of the bacterial community were significantly affected by tillage practices. Both no-tillage and intercropped maize significantly increased the abundance of archaea phylum Thaumarchaeota and bacterial phylum Nitrospirae, benefiting nitrogen fixation of intercropped pea from the atmosphere under the no-tillage cereal/legume intercropping. No-till intercropping was conducive to the accumulation of organic carbon, while decreasing the abundance of Prote-obacteria, Acidobacteria, and Verrucomicrobia. Limited soil enzyme activities (ACP, ALP, DP, NAG, BG, AG, CB) led to decreases in organic carbon turnover and utilization. Intercropping al-tered soil microbial community diversity and composition due to changes in soil properties and enzyme activities. These findings suggest that no-tilled cereal-legume intercropping is a sustaina-ble cropping practice for improving soil properties and enhancing microbial (archaea, bacterial, Eukaryota) diversity, but the long-term persistence is not conducive to rapid turnover of soil nu-trients due to limited enzyme activities.

Despite their anti-icing ability, hydrophobic coatings have the disadvantages of easy falling off and poor wear resistance, resulting in insufficient durability of ice/snow melting. To improve the surface stability and durability of superhydrophobic coatings, nanoparticle/epoxy coatings were prepared with three types of nanoparticles, two types of dispersion methods, three types of application methods and two types of introduction methods of epoxy resin. Water contact angles, ice adhesion force and icing rate of asphalt concrete coated with hydrophobic coatings were tested. The molecular structures of coatings were analyzed by Fourier transform infrared spectroscopy. The surface morphology of hydrophobic coatings was observed using Scanning electron microscopy. Results indicated that nano-ZnO, TiO2 and SiO2 particles can be modified into hydrophobicity by stearic acid. The hydrophobic coating could improve the hydrophobicity of concrete, reduce the adhesion strength of ice and asphalt concrete and delay the beginning icing time. Moreover, The dosages of stearic acid, nanoparticle and epoxy resin need to be in a certain range to ensure the best hydrophobicity and durability of coatings.

Ankle joint flexion and extension exercises play an important role in the rehabilitation training of patients who have been injured or bedridden for a long time before and after surgery. Accurately guiding patients to perform ankle flexion and extension exercises can significantly reduce deep vein thromboembolism. Currently, most ankle rehabilitation devices focus on assisting patients with ankle flexion and extension movements, and there is a lack of devices for effectively monitoring these movements. In this study, we designed an ankle joint flexion and extension movement monitoring device based on a pressure sensor. It is composed of an STM32 microcontroller, a pressure sensor, an HX711A/D conversion chip, and an ESP8266 WiFi communication module. The value of force and effective number of ankle joint flexion and extension movements were obtained. An experimental device was designed to verify the accuracy of the system. The results showed that the device can effectively monitor and control ankle flexion and extension movements remotely, ultimately ensuring that the patient can effectively monitor and grasp the active ankle pump movement.

Ion beam-assisted deposition (IBAD) has been proposed as a promising texturing technology that uses film epitaxy method to obtain biaxial texture on a non-textured metal or compound substrate. Magnesium oxide (MgO) is the most well explored texturing material. In order to obtain the optimal biaxial texture, the actual thickness of the IBAD-MgO film must be controlled within 12 nm. Due to the bombardment of ion beams, IBAD-MgO has large lattice deformation, poor texture and many defects in the films. In this work, an additional homogeneous epitaxy MgO (epi-MgO) layer has been deposited on the IBAD-MgO layer by electron-beam evaporation. The biaxial texture can be optimized by the deposition of additional epi-MgO layer. The effects of growth temperature, film thickness, deposition rate and oxygen flux on the texture and morphology of the epi-MgO film were systematically studied. After the research of epi-MgO process, the best full width at half maximum (FWHM) values were 2.2 for the out-of-plane texture and 4.8° for the in-plane texture, respectively. Subsequently, the LaMnO3 cap layer and YBa2Cu3O7-x (YBCO) functional layer was deposited on the epi-MgO layer to test the quality of MgO layer. Finally, the critical current density of YBCO films is 6MA/cm2 (77K, 500nm, self-field), indicating that this research provides a high-quality MgO substrate for the YBCO layer.

Our image recognition system mainly judges whether the left upper limb in the image is the left upper limb or the right upper limb through our deep learning model in the image. The doctor then could give the correct surgical position. From the experimental results, it could be found that the precision rate and recall rate of the intelligent image recognition system proposed in this paper for preventing the upper limb dislocation surgery could reach 98% and 93%, respectively. It proved that our intelligent image recognition system could indeed assist orthopedic surgeons to prevent the occurrence of left and right dislocation in upper limb surgery. At the same time, this paper also completes the IRB application approval through the prototype experimental results and will conduct the second phase of human trials in the future. It showed that the research results of this paper will be of great benefit and research value to upper limb orthopedic surgery.

Andrographis paniculata leaves have been widely used in traditional medicine due to their rich content of phenolic compounds. In this study, we evaluated the total phenolic and flavonoid content of Andrographis paniculata leaf extracts (ALE), as well as its antioxidant activities against DPPH, ABTS, and hydrogen peroxide radicals. Additionally, we conducted cell viability assays, RT-PCR, and western blot analysis to investigate the biochemical effects of ALE on UVB-induced HaCaT cells. Our results revealed that ALE exhibited a high concentration of polyphenols and flavonoids, which were associated with potent abiotic antioxidant properties. Furthermore, ALE treatment effectively abrogated the damage caused by UVB radiation on key molecules such as hyaluronan synthase 1, Aquaporin 3, and loricrin in HaCaT cells. ALE also demonstrated the ability to reduce the overactivation of mitogen-activated protein kinases (MAPKs) and the expression of pro-inflammatory cytokines, including interleukin-6 and interleukin-1β in UVB-induced HaCaT cells. Additionally, ALE positively influenced the peroxisome proliferator-activated receptor alpha in these cells. Overall, our findings highlight the antioxidant and anti-inflammatory effects of ALE, as well as its significant role in modulating skin barrier functions. These results contribute to the growing body of evidence supporting the therapeutic potential of ALE in skincare and dermatological applications.

Alternative splicing can produce transcripts that affect cancer development and shows potential for cancer diagnosis and treatment. However, intron retention (IR), a type of alternative splicing, has been less systematically studied in cancer biology research. Here, we generated a pan-cancer IR landscape for more than 10,000 samples across 33 cancer types from The Cancer Genome Atlas (TCGA). We characterized differentially retained introns between tumor and normal samples and identified retained introns associated with survival. We discovered 988 differentially retained introns in 14 cancers, some of which demonstrated diagnostic potential in multiple cancer types. We also inferred a large number of prognosis-related introns in 33 cancer types, and the associated genes included well-known cancer hallmarks such as angiogenesis, metastasis, and DNA mutations. Notably, we discovered a novel intron retention event inside 5′UTR of STN1 that is associated with the survival of lung cancer patients. The retained intron reduces translation efficiency by producing upstream open reading frames (uORFs) and thereby inhibits colony formation and cell migration of lung cancer cells. Besides, the IR-based prognostic model achieved good stratification on certain cancers, as illustrated in acute myeloid leukemia. Taken together, we performed a comprehensive IR survey at a pan-cancer level, and the results implied that IR has the potential to be diagnostic and prognostic cancer biomarkers, as well as new drug targets.

Reinforcement Learning (RL) has demonstrated considerable potential in solving challenges across various domains, notably in autonomous driving. Nevertheless, implementing RL in autonomous driving comes with its own set of difficulties, such as the overestimation phenomenon, extensive learning time, and sparse reward problems. Although solutions like Hindsight Experience Replay (HER) have been proposed to alleviate these issues, the direct utilization of RL in autonomous vehicles remains constrained due to the intricate fusion of information and the possibility of system failures during the learning process. In this paper, we present a novel RL-based autonomous driving system technology that combines Obstacle Dependent Gaussian (ODG) RL, Soft Actor-Critic (SAC), and meta-learning algorithms. Our approach addresses key issues in RL, including the overestimation phenomenon and sparse reward problems, by incorporating prior knowledge derived from the ODG algorithm. We evaluated our proposed algorithm on official F1 circuits, using high-fidelity racing simulations with complex dynamics. The results demonstrate exceptional performance, with our method achieving up to 89% faster learning speed compared to existing algorithms in these environments.

Small molecule kinase inhibitors (SMKIs) are one of the heightened concerns in the field of drug research and development. There are seventy-nine (up to July 2023) small molecule kinase inhibitors have been approved by FDA and hundreds kinase inhibitors candidates in clinical trials, which shed light on the treatment of some major diseases. As an important strategy of drug design, computer-aided drug design (CADD) plays an indispensable role in the discovery of SMKIs. CADD methods, such as docking, molecular dynamic, pharmacophore have been applied to the design and optimization of small molecule kinase inhibitors. In the review, we provide an overview of recent advances in CADD and SMKIs; and the application of CADD for discovery of SMKIs.

2,3,5,6-Tetramethyl-1,4-diisocyanobenzene (1), 1,4-diisocyanobenzene (2), and 1,4-dicyanobenzene (3) were co-crystallized with 1,3,5-triiodotrifluorobenzene (1,3,5-FIB) to give three cocrystals, 1·1,3,5-FIB, 2·2(1,3,5-FIB), and 3·2(1,3,5-FIB), which were studied by XRD. Common feature of the three structures is the presence of I···Cisocyanide or I···Nnitrile HaBs occurred between an iodine -hole and the isocyanide C- (or the nitrile N-) atom. The diisocyanide and dinitrile cocrystals, 2·2(1,3,5-FIB) and 3·2(1,3,5-FIB), are isostructural thus providing a basis for accurate comparison of the two types of noncovalent linkages of CN/NC groups in the composition of structurally similar entities and in one crystal environment. The bonding situation was studied by a set of theoretical methods. Diisocyanides are more nucleophilic than the dinitrile and they exhibit stronger binding to 1,3,5-FIB. In all structures, the HaBs are mostly determined by the electrostatic interactions, but the dispersion and induction components also provide a noticeable contribution and make the HaBs attractive. Charge transfer has a small contribution (<5%) to the HaB and it is higher for the diisocyanide than for the dinitrile systems. At the same time, diisocyanide and dinitrile structures exhibit typical electron-donor and -acceptor properties in relation to the HaB donor.

Eco-innovation denotes developing green practices using environmentally friendly innovative approaches or technologies. Although, eco-innovation has been broadly applied in different in-dustries, such as low-carbon production and manufacturing, how to implement such innovation in education for sustainable development (ESD) has rarely been studied. Therefore, this research considered a reflective and cooperative learning approach to science, technology, engineering, arts, and math (STEAM) education. A case study examined Wanluan Township of Pingtung County in southern Taiwan. Four departments’ students and teachers at Meiho University were involved in situated learning. Students of hospitality management played farm owners who en-gaged in organic agriculture to produce food and beverages. These agricultural products were farm-to-table, cooked and served for customers in a natural dining setting through the students’ teamwork. Students of tourism, sports & leisure management, and food science & nutrition played tourists in a self-guided travel context, who engaged in acts such as visiting buildings to understand heritage while observing that the houses were still in use a dwelling. This encouraged reflection on the importance of cultural preservation. According to the results from the role-play farm owners and tourists, eco-innovation can represent a sustainable marketing strategy for im-proving the local-community economy and can be implemented in a practical situation in STEAM. The goal of ESD for 2030 — societal transformation — is to foster students’ responsible behavior and attitudes in a personally authentic manner, thereby fostering sustainability learning and understanding.

The advancement of mass spectrometry technologies has revolutionised plant metabolomics research by enabling the acquisition of raw metabolomics data. However, the identification, analysis, and visualisation of these data require specialised tools. Existing solutions lack a dedicated plant-specific metabolite database and pose usability challenges. To address these limitations, we developed PlantMetSuite, a web-based tool for comprehensive metabolomics analysis and visualisation. PlantMetSuite encompasses interactive bioinformatics tools and databases specifically tailored for plant metabolomics data, facilitating upstream-to-downstream analysis in metabolomics and supporting integrative multi-omics investigations. PlantMetSuite can be accessed directly through a user's browser without the need for installation or programming skills. The tool is freely available at https://plantmetsuite.verygenome.com/ and will undergo regular updates and expansions to incorporate additional libraries and newly published metabolomics analysis methods. The tool's significance lies in empowering researchers with an accessible and customisable platform for unlocking plant metabolomics insights.

Carbon dots have received much attention due to their unique physicochemical properties and diverse applications in bioimaging, optoelectronic devices, catalysis, and agriculture. Here in this work, we report a simple hydrothermal synthesis of nitrogen and phosphorus-doped carbon dots (N, P-CDs). The optical and physical properties of the synthesized N, P-CDs were analyzed using systematical spectroscopy and electrical characterization. The synthesized N, P-CDs show strong photoluminescence at 626 nm and demonstrate high stability under UV light and other conditions. Moreover, we incorporate the synthesized N, P-CDs into water spinach by root spraying and leaf spraying. It was found that N, P-CDs could effectively promote the growth of water spinach by increasing the photosynthetic rate, and the content of total phenols and anthocyanins in water spinach

Is there any possible synergic effect of fertility outcome between spindle view-assisted intracyto-plasmic sperm injection (SV-ICSI) with or without assisted oocyte activation (AOA) for patients with low fertilization rate history? To explore the answer, a retrospective study was held in our fertility center by reviewing patients receiving SV-ICSI during 2019/03 to 2023/06. Total 47 pa-tients were included, the fertility outcomes of intervention group (AOA-SV-ICSI, 14 patients) and control group (SV-ICSI, 33 patients), such as fertilization rate, blastocyst formation rate and clin-ical pregnancy rate, were analyzed. The blastocyst formation rate between groups was signifi-cantly higher in AOA-SV-ICSI group (p=0.020), but the fertilization rate and clinical pregnancy rate did not reach any statistical significance. This discovery of increased blastocyst formation rate in low fertilization rate patients could possibly help them in getting more usable embryos in fertility treatment.

GNSS time series prediction plays a significant role in monitoring crustal plate motion, landslide detection, and maintenance of the global coordinate framework. Long Short-Term Memory (LSTM), a deep learning model has been widely applied in the field of high-precision time series prediction especially when combined with Variational Mode Decomposition (VMD) to form the VMD-LSTM hybrid model. To further improve the prediction accuracy of the VMD-LSTM model, this paper proposes a dual variational modal decomposition long short-term memory (DVMD-LSTM) model to effectively handle the noise in GNSS time series prediction. This model extracts fluctuation features from the residual terms obtained after VMD decomposition to reduce the prediction errors associated with residual terms in the VMD-LSTM model. Daily E, N, and U coordinate data recorded at multiple GNSS stations between 2000 and 2022 are used to validate the performance of the proposed DVMD-LSTM model. The experimental results demonstrate that compared to the VMD-LSTM model, the DVMD-LSTM model achieves significant improvements in prediction performance across all measurement stations. The average RMSE is reduced by 9.86%, and the average MAE is reduced by 9.44%. Furthermore, the average accuracy of the optimal noise model for the predicted results is improved by 36.50%, and the average speed accuracy of the predicted results is enhanced by 33.02%. These findings collectively attest to the superior predictive capabilities of the DVMD-LSTM model, thereby enhancing the reliability of the predicted results.

The total ionizing dose (TID) effect significantly impacts the electrical parameters of fully depleted silicon on insulator (FDSOI) devices and even invalidates the on-off function of devices. At present, most of the irradiation research on the circuit level is focused on the single event effect, and the research on the total ionizing dose effect is very little. Therefore, this study mainly analyzes the influence of TID effects on a CMOS inverter circuit based on 22 nm FDSOI transistors. First, we constructed and calibrated an N-type FDSOI metal-oxide semiconductor (NMOS) structure and P-type FDSOI metal-oxide semiconductor (PMOS) structure. The transfer characteristics and trapped charge distribution of these devices were studied under different irradiation doses. Next, we studied the TID effect on an inverter circuit composed of these two MOS transistors. The simulation results show that when the radiation dose is 400 krad (Si), the logic threshold drift of the inverter is approximately 0.052 V. These results help further investigate the impact on integrated circuits in the irradiation environment.

Light Detection and Ranging (LiDAR) technology, a cutting-edge advancement in mobile applications, presents a myriad of compelling use cases, including enhancing low-light photography, capturing and sharing 3D images of fascinating objects, and elevating the overall augmented reality (AR) experience. However, its widespread adoption has been hindered by the prohibitive costs and substantial power consumption associated with its implementation. To surmount these obstacles, this paper proposes a low-power, low-cost, SPAD-based system-on-chip (SoC) which packages the microlens arrays (MLA) and incorporates with a light-weight RGB-guided sparse depth imaging completion neural network for 3D LiDAR imaging. The proposed SoC integrates an 8x8 Single-Photon Avalanche Detectors (SPADs) macro pixel array with time-to-digital converters (TDC) and charge pump, fabricated using a 180nm bipolar-CMOS-DMOS (BCD) process. A random MLA-based homogenizing diffuser efficiently transforms Gaussian beams into flat-topped beams with a 45° field of view (FOV), enabling flash projection at the transmitter. To further enhance resolution and broaden application possibilities, a lightweight neural network employing RGB-guided sparse depth complementation is proposed, enabling a substantial expansion of image resolution from 8x8 to quarter video graphics array level (QVGA; 256x256). Experimental results demonstrate the effectiveness and stability of the hardware encompassing the SoC and optical system, as well as the lightweight features and accuracy of the algorithmic neural network. This integrated state-of-the-art hardware-software solution offers a promising and inspiring foundation for developing consumer-level 3D imaging applications.

Wastes from social economic activities had great impact on water quality thereby limiting water usability for domestic purposes. Sewages discharge from people activities, usually consist of undesirable concentrations of soluble chemicals that infiltrate into the surrounding surface and underground water, and then constitute health risk to the populace. In order to investigate the concentration characteristics and health risk for the local residents in Nandong Underground River Watershed (NURW), eleven common heavy metals in the water body analysis were conducted. Health risk assessment (HRA) was taken to analyze eleven heavy metals of 84 water samples from surface and underground waters in NURW: 36 samples underground water and 48 samples surface water. Our results showed that the heavy metals concentration order is that of Fe > Al > Mn > Zn > As > Cd > Pb > Cr > Ni > Cu > Hg. Correlation analysis indicates that these eleven metal elements have certain similarity on material source and migration transformation. The health risks for local residents exposed to metal elements in the water of NURW mainly from carcinogenic risk (10−6～10−4 a−1) through drinking way, and the health risk of heavy metals exposed to children through drinking way was much higher than adults. The maximum exposing health risks of Cr in both underground and surface water were higher than the recommendation standard (5.0×10-5 a-1) from ICRP, and all the values over the standard (5.0×10-6 a-1) recommended by the Swedish Environmental Protection Agency and the Dutch Ministry of Construction and Environment and the British Royal Society. The results of health risk assessment shows that Cr in the water of NURW was the mainly source of carcinogenic risk for the local residents, following by Cd and As. Consequently, it is necessary to control the three carcinogenic metals when the water was used as drinking water source.

Traffic shaping is a critical task in software-defined -IoT networks (SDN-IoTs) to efficiently manage network resources and ensure Quality of Service (QoS) for end-users. However, traditional traffic shaping approaches based on queuing theory or static policies may not be effective due to the dynamic and unpredictable nature of network traffic. In this paper, we propose a novel approach that leverages Graph Neural Networks (GNNs) and Multi-arm Bandit algorithms to dynamically optimize traffic shaping policies based on real-time network traffic patterns. Specifically, our approach uses a GNN model to learn and predict network traffic patterns and a Multi-arm Bandit algorithm to optimize traffic shaping policies based on these predictions. We evaluate the proposed approach on three different datasets, including a simulated corporate network (KDD Cup 1999), a collection of network traffic traces (CAIDA), and a simulated network environment with both normal and malicious traffic (NSL-KDD). The results demonstrate that our approach outperforms other state-of-the-art traffic shaping methods, achieving higher throughput, lower packet loss, and lower delay, while effectively detecting anomalous traffic patterns. The proposed approach offers a promising solution to traffic shaping in SDNs, enabling efficient resource management and QoS assurance

Background: Pulmonary sequestration (PS), generally diagnosed using computed tomography pulmonary angiography (CTPA), is a rare congenital developmental malformation of the lung that is characterized by nonfunctional lung tissue independent of the normal lung tissue. This study summarizes the imaging features of the supplying arteries and draining vessels in patients with PS with an aim to assist with timely clinical diagnosis and operation guidance. Materials and Methods: A total of 55 patients with PS diagnosed on CTPA from multiple clinical centers were retrospectively analyzed. Data included demographic characteristics, imaging features, disease location, isolation type, and the features of supplying and draining vessels, as shown on CTPA images. Results: Of the 55 patients reviewed, 3 (5.45%) were children, 3 (5.45%) were adolescents, and 49 (89.09%) were adults, with a mean age of 44 years. Fifty-four (98.18%) patients had intralobar sequestration and one (1.82%) had extralobar sequestration. PS was noted 3.5 times more frequently in the left lower lobe than in the right lower lobe. For the supplying arteries, 47 (85.45%) were derived from the descending thoracic aorta, 1 (1.82%) from the abdominal aorta, 7 (12.73%) from the celiac axis, and 1 (1.82%) from the bronchial artery. The draining vessels were the pulmonary veins in 49 patients (89.09%), the umbilical vein in 1 (1.82%), the venae intercostal in 1 (1.82%), the pulmonary arteries in 11 (20.00%), and not shown on the images in 2 (3.64%). Conclusion: Clinical presentations of PS are non-specific and can be easily missed or misdiagnosed. However, CTPA can help improve the diagnostic accuracy and identify the supplying arteries and draining vessels, which significantly contribute to surgical planning.

Patients receiving hemodialysis are at risk of vascular access infections (VAIs) and particularly vulnerable to the opportunistic pathogen Staphylococcus aureus. Hemodialysis patients were also at increased risk of infection during the COVID-19 pandemic. Therefore, this study determined the change in the molecular and antibiotic resistance profiles of S. aureus isolates from VAIs during the pandemic compared with before. 102 S. aureus isolates were collected from VAIs between November 2013 and December 2021. Before the pandemic, 69 isolates were collected, 58%, 39.1%, and 2.9% from arteriovenous grafts (AVGs), tunneled cuffed catheters (TCCs), and arteriovenous fistulas (AVFs), respectively. The prevalence of AVG and TCC isolates changed to 39.4% and 60.6%, respectively, of 33 isolates during the pandemic. Sequence type (ST)59 was the predominant clone in TCC-methicillin-resistant S. aureus (MRSA) and AVG-MRSA before the pandemic, whereas the predominant clone was ST8 in AVG-MRSA during the pandemic. ST59 carrying the ermB gene was resistant to clindamycin and erythromycin. By contrast, ST8 carrying the msrA gene was exclusively resistant to erythromycin. The ST distribution for different VAIs changed from before to during the pandemic. The change in antibiotic resistance rate for different VAIs was closely related to the distribution of specific STs.

The nucleon-pair shell model (NPSM) with broken symmetry basis is studied. The results demonstrate the validity of NPSM with symmetry broken basis, which leads to a significant reduction in the dimensionality of the multi-pair configuration space. We have observed that the axial-deformed basis provides a satisfactory description of the low-lying spectrum, even without the need for the projection procedure. In the case of the triaxial-deformed basis, we have investigated the variation after angular momentum projection, indicating the potential for NPSM to find exact solutions in the half-closed system.

The process of shock wave focusing can make the strength of shock waves be continuously accumulated and turned into detonation wave in Pulse Detonation Engine (PDE). However, its effective application needs the inlet jets be in high temperature and velocity, which is difficult to be satisfied under certain conditions. Therefore, in this paper, metal magnesium assisted detonation initiation is proposed and the effect of magnesium particle addition on the shock wave focusing process in a kerosene-fueled PDE with cavity configuration is investigated through numerical simulation. The result showed that when the temperature of the premixed fuel/air jets injected in opposite direction was set as 650 K, the collision of leading shock waves on the central axis was the main source of energy deposition and the shock wave focusing could make the detonation be initiated in the cavity. When the temperature of jets is reduced to 550 K, fuel ignition and detonation could not be achieved through shock wave focusing. Then adding metal magnesium particles into the combustor made the energy deposition be enhanced and the detonation be induced. The diffusion of metal particles can significantly change the structure, motion, merging and dissipation of vortices in the flow field. Generally, the shock wave focusing process is basically not affected with metal particles injection. Therefore, this method can be successfully employed for detonation initiation in the cavity when the fuel/air premixed jet temperature is not high for PDE.

(1) Background: Breast cancer is the second leading cause of cancer death among women. The accurate prediction of survival intervals will help physicians make informed decisions on treatment strategies or the use of palliative care for patients; (2) Methods: The gene expression is predictive and correlates to patient prognosis. To establish a reliable prediction tool, we collected the RNA-seq data of breast cancer patients, a total of 1187 RNA-seq data (median age 58 years), in FPKM format from the TCGA database. Among them, 144 RNA-seq data with date of death information was selected to establish the SaBrcada-AD dataset. We first normalized the SaBrcada-AD dataset to transcripts per million (TPM) to build survival prediction model SaBrcada. After normalization and dimension raising, the differential gene expression data were used for testing eight different deep learning architectures. Among them, GoogLeNet performed the best. Considering the effect of age on prognosis, we examined all ages between the lower and upper quartiles of patient age for a stratified random sampling test; (3) Results: Stratifying by age based on a cut-off of 61 years of age improved the accuracy of SaBrcada compared to previous findings, resulting in an accuracy of 0.798. We also built a free website tool to provide 5 kinds of predicted survival period information for clinician reference; (4) Conclusions: We established a breast cancer survival analysis prediction model, SaBrcada, and a website tool with the same name. Through this highly reliable survival analysis model and website tool, information on survival intervals will be provided for clinicians as part of precision medicine.

Pulmonary fibrosis is a chronic, progressive and fatal disease of the interstitial lung， there still lack of efficient therapy to reverse the prognosis of patients currently. In this study, a fucoidan from Costaria costata was isolated and its anti-idiopathic fibrosis activity was investigated both in vitro and in vivo. The chemical composition analysis results show that Costaria costata polysaccharide (CCP) is consisting of galactose and fucose as the main monosaccharides with a sulfate group content of 18.54%. The results found that CCP could resist TGF-β1-induced epithelial-mesenchymal transition (EMT) in A549 cells by inhibiting the TGF-β/Smad and PI3K/AKT/mTOR signaling pathways. In vivo data found that CCP treatment alleviated bleomycin (BLM)-stimulated fibrosis and inflammation in mice lung tissue. This study suggests that CCP could protect the lung from fibrosis by relieving the EMT process and inflammation in lung cells.

In recent years, with the rapid development of technology, artificial intelligence(AI) security issues represented by adversarial sample attack have aroused widespread concern in society. Adversarial samples are often generated by surrogate models and then transfer to attack the target model, and most AI models in real-world scenarios belong to black boxes, thus transferability becomes a key factor to measure the quality of adversarial samples. The traditional method relies on the decision boundary of the classifier and takes the boundary crossing as the only judgment metric without considering the probability distribution of the sample itself, which results in an irregular way of adding perturbations to the adversarial sample, an unclear path of generation, and a lack of transferability and interpretability. In the probabilistic generative model, after learning the probability distribution of the samples, a random term can be added to the sampling to gradually transform the noise into a new independent and identically distributed sample. Inspired by this idea, we believe that by removing the random term, the adversarial sample generation process can be regarded as static sampling of the probabilistic generative model, which guides the adversarial samples out of the original probability distribution and into the target probability distribution, and helps to improve transferability and interpretability. Therefore, we propose a Score Matching-Based Attack(SMBA) method to perform the adversarial sample attacks by manipulating the probability distribution of the samples, which can show good transferability in the face of different datasets and models, and give reasonable explanations from the perspective of mathematical theory and feature space. In conclusion, our research establishes a bridge between probabilistic generative models and adversarial samples, provides a new entry angle for the study of adversarial samples, and brings new thinking to AI security.

The paradigm of drug delivery via nano- and microcarriers is one of the leading ideas that enable overcoming the limitations of traditional chemotherapy. The trend toward more complex drug carriers capable of multifunctionality is observed in the literature. To date, prospects of stimuli-responsive systems to control the cargo release in the lesion nidus are widely accepted. Both endogenous and exogenous stimuli are employed for this purpose, however, endogenous pH is one of the most common triggers. Unfortunately, scientists face difficulties in the implementation of this idea since a range of biological barriers, drug bioavailability issues, and challenges in the synthesis of carriers with required properties have arisen. Here, we discuss fundamental strategies of pH-responsive drug delivery as well as limits in its application and reveal the main problems, weak sides, and reasons for poor clinical results. Also, we have made an attempt to formulate the profiles of "ideal" drug carrier in the frame of different strategies and considered recently published studies through the lens of these profiles. This approach enables the identification of current trends and promising vectors in the development of pH-responsive drug delivery systems, as well as challenges to be resolved in the next generation of carriers.

A rapid and efficient method using an alkyl functionalized magnetic nanoparticles-based extraction technique combined with Ultra-High Performance Liquid Chromatography was developed for the detection of trace amounts of polycystic aromatic hydrocarbons in tea leaves. As a popular coating for chromatographic column packing materials, C18-alkyl has been demonstrated to be effective in separating polycystic aromatic hydrocarbons. And the magnetism of the nanomaterials accelerates the extraction process while their high surface ratio enables desirable dispersity in the sample matrix. Meanwhile, the adsorbents can be washed and reused 30 times without compromise on recovery, which greatly reduced the budget. The effects of various parameters were investigated and optimized, and the recoveries for five analytes were in the range of 84.8–103.7%. The reproducibility rate of intra-day and inter-day were below 7.1% and 11.3% respectively. The limits of detection and limits of quantification ranged from 1.69–9.97 ng g-1 and 5.12–30.21 ng g-1, indicating satisfactory sensitivity. Thus, the proposed methodology is rapid, highly efficient, and economical, and it expands the application of magnetic cleanup approaches in complex food matrices.

A new photocatalytic hydroxyapatite (HA) synthesis method has been developed. This method is based on the unique ability of the TiO2 photocatalyst to decompose the Ca(EDTA) complex under UV illumination. As a result, released Ca2+ ions react with PO43- ions forming the HA particles. The photocatalytic formation of hydroxyapatite is found to have a fractional order, which may indicate the complex reaction mechanism and the presence of several limiting stages. The TNT-HA samples were studied by XRD, FTIR, SEM, GDOES, and biocompatibility study. High biocompatibility of the surfaces is proven by pre-osteoblast cell growth.

Different inlet structures have a significant impact on the internal flow characteristics of a solid-magnesium powder water ramjet engine. Based on the magnesium-water reaction model, a computational fluid dynamics (CFD) method is applied to establish a numerical simulation method for the internal flow field of the engine, and the internal flow characteristics of the engine under different inlet structure conditions are studied. The simulation results show that high-temperature gas can effectively promote the ignition of magnesium powder at the top of the combustion chamber, while accelerating the evaporation of the first inlet water and increasing the combustion rate of magnesium powder. The secondary inlet has the most significant effect on the temperature inside the combustion chamber. When the secondary inlet flow rate increases towards the top of the combustion chamber, it increases the amount of heat absorbed by the evaporating water at the top of the chamber, thereby reducing the temperature at the top of the combustion chamber. However, when the flow rate is low, it results in insufficient oxidizer at the top of the combustion chamber, which is unfavorable for the combustion of magnesium powder.

Solid oxide cells are capable of efficiently converting various chemical energy carriers to electricity and vice versa. The urgent challenge nowadays is the faster degradation rate compared with other fuel cell/electrolyzer technologies. To understand the degradation mechanisms, simulation of a solid oxide cell is helpful. Since most previous research developed models using commercial software, such as COMSOL and ANSYS Fluent, a gap for knowledge transfer is being gradually formed between academia and industry due to licensing issues. This paper introduces a multiphysics model, developed by a computational code, openFuelCell2. The code is implemented with an open-source library, OpenFOAM. It accounts for momentum transfer, mass transfer, electrochemical reactions and metal interconnect oxidation. The model can precisely predict I-V curves under different temperatures, fuel humidity and operation modes. Comparison between OpenFOAM and COMSOL simulations shows good agreement. The metal interconnect oxidation is modelled, which can predict the thickness of the oxide scale under different protective coatings. Simulations are conducted by assuming an ultra-thin film resistance on the rib surface. It is revealed that coatings fabricated by atmospheric plasma spraying can efficiently prevent metal interconnect oxidation, with a contribution of only 0.53 \% to the total degradation rate.

The human serotonin transporter (hSERT) terminates neurotransmission by removing serotonin from the synaptic cleft, which is an essential process plays an important role in depression. In addition to substrate serotonin, hSERT is also the target of drugs of abuse like cocaine and clinically used antidepressants such as escitalopram and paroxetine. To date, few studies attempt to investigate the unbinding mechanism underlying the orthosteric and allosteric modulation of hSERT. The high-resolution X-ray structure of hSERT resolved recently enables us to theoretically study the unbinding of the above four ligands against the S1 or S2 site of hSERT, by means of molecular docking, molecular dynamics (MD) and potential of mean force (PMF) simulations. We proved that for either the S1 or S2 site, the other three ligands (cocaine, escitalopram and paroxetine) are much more favorable than the original substrate serotonin, whether in kinetics along the unbinding pathways or in thermodynamics at the equilibrium states. Furthermore, the S1 site is much more favorable than the S2 site, for each ligand. Interestingly, inspection revealed that there are ~ 3Å lengths between the allosteric site of serotonin and cocaine, and an unseen un-binding pathway for escitalopram at the S1 site except for verification of the broadest trail.

The conductor aluminum alloys Al-0.25wt.%Zr doped additionally with Х = Er, Si, Hf, and Nb were the objects of investigations. The fine-grained microstructure in the alloys was formed by Equal Channel Angular Pressing and Rotary Swaging. The thermal stability of the microstructure, specific electrical resistivity, and microhardness of the novel conductor aluminum alloys was investigated. The mechanisms of nucleation of the Al3(Zr,X) secondary particles during annealing the fine-grained aluminum alloys were determined using Jones-Mehl-Avrami-Kolmogorov equation. Using Zener equation, the dependencies of the mean secondary particle sizes on the annealing time were obtained on the base of analysis of the data on the grain growth in the aluminum alloys. The secondary particle nucleation during long-time low-temperature annealing (300 оC, 1000 hrs) was shown to go preferentially at the cores of the lattice dislocations. The Al-0.25%Zr-0.25%Er-0.20%Hf-0.15%Si alloy subjected to long-time annealing at 300 оC has the optimal combination of the microhardness and electrical conductivity (59.8%IACS, Hv = 480 ± 15 MPa).

Steam Generator Level Control System (SGLCS) is one of the key instrumentations and control subsystems to ensure the safe operation of nuclear power plants. It is highly recommended to perform reliability analysis for SGLCS for making better maintenance strategy. SGLCS is a digital control system with complex redundant configuration and failure\self-diagnosis\repair action, traditional fault tree is not applicable due to its static property, Markov model is not a good choice too because of heavy burden of creating state transition graph for even medium-size system. Boolean Logic Driven Markov Process (BDMP) can describe complex failure-repair state transition via ‘trigger link’ and three kinds of leaf nodes, as well as keep compact and easy-read struct like fault tree. So BDMP is adopted to analysis reliability of SGLCS. Graphical BDMP modeling environment KB3 and Monte Carlo simulator YAMS is used for BDMP modeling and quantitative analysis respectively, and unavailability of SGLCS is obtained. The contribution of three parts of SGLCS to the unavailability of the system is also evaluated, and it is found that the water supply flow control part contributes the most to the failure of SGLCS.

Reparative osteogenesis in the damaged vertebrae is a complex cascade of morphological and biochemical processes that result in the consolidation of the vertebral body. This research was aimed at studying the features of reparative osteogenesis in damaged thoracic and lumbar vertebral bodies at different time points after injury. We analyzed the morphological findings of the vertebral tissues harvested during surgical interventions in 43 patients with recent, subacute and long-standing injuries to thoracic and lumbar spine, and found that cell differentiation in osteogenesis is closely related to angiogenesis and the metabolic cascade. In areas with sufficient oxygenation, good partial pressure of oxygen, and active growth of microvasculature the normal cycle of development and differentiation of osteoblasts and osteocytes occurs, and hypoxia and acidosis lead to pathological osteogenesis. The reclination maneuver with dorsal tools on Day 10-12 of the injury may be ineffective due to the formation of adhesions between fragments, and reclination of the body of the damaged vertebra two weeks or more after the injury is apparently doomed to failure. Timely ventral fusion performed for objective indications is the key to successful rehabilitation of patients, on the one hand, and reduction of the surgical trauma volume in the future, on the other.

The purpose of this work is to study quasi-stationary wave structure in the mid-latitude stratosphere and mesosphere (40–50°N) and its role in the formation of the annual ozone cycle. Geopotential height and ozone from Aura MLS data are used and winter climatology for January–February 2011–2020 is considered. More closely examined is the 10-degree longitude segment centered on Longfengshan Brewer station, China, and located in the region of the Aleutian Low influence associated with the quasi-stationary zonal maximum of total ozone. Annual and semi-annual oscillations in ozone were compared using units of ozone volume mixing ratio and concentration, as well as changes in ozone peak altitude and in time series of ozone at individual pressure levels between 316 hPa (9 km) and 0.001 hPa (96 km). The ozone maximum in the vertical profile is higher in volume mixing ratio (VMR) values than in concentration by about 15 km (5 km) in the stratosphere (mesosphere), in consistency with some previous studies. We found that the properties of the annual cycle are better resolved in the altitude range of the main ozone maximum: middle–upper stratosphere in VMR and lower stratosphere in concentration. Both approaches reveal SAO/AO-related changes in the of ozone peak altitudes in a range of 4–6 km during the year. In the lower-stratospheric ozone of the Longfengshan domain, an earlier development of the annual cycle takes place with a maximum in February and a minimum in August compared to spring and autumn, respectively, in zonal means. This is presumably due to the higher rate of dynamical ozone accumulation in the region of the quasi-stationary zonal ozone maximum. The “no-annual-cycle” transition layers are found in the stratosphere and mesosphere. These layers with undisturbed ozone volume mixing ratio throughout the year are of interest for more detailed future study.

Nitric oxide (NO) is a key molecule in cardiovascular homeostasis and its abnormal delivery is highly associated with the occurrence and development of cardiovascular disease (CVD). The assessment and manipulation of NO delivery is crucial to the diagnosis and therapy of CVD, such as endothelial dysfunction, atherosclerotic progression, pulmonary hypertension, and cardiovascular manifestations of Coronavirus (COVID-19). However, due to the low concentration and fast reaction characteristics of NO in cardiovascular system, the clinical applications centered on the NO delivery are challenging. In this tutorial review, we first summarized the methods to estimate the in vivo NO delivery process based on the clinical images and mathematical modeling to assess the endothelial function and vulnerability of atherosclerotic plaque. Then, the emerging bioimaging technologies that have the potential to directly measure the arterial NO concentration were discussed, including the Raman spectroscopy and electrochemical sensor. Aside from the diagnostic methods, therapies aimed at controlling NO delivery to regulate CVD were reviewed, including the inhaled NO therapy to treat the pulmonary hypertension and COVID-19, stem cell therapy and NO-releasing platform to treat endothelial dysfunction and atherosclerosis.

Heavy metals contamination in groundwater often occurs in various industrial processes. Stud-ies have confirmed that polysulfide could reduce hexavalent chromium to trivalent chromium, achieving the effect of in-situ stabilization. For other heavy metals contamination in groundwa-ter, whether polysulfide also had a stabilizing ability to achieve in-situ remediation. This re-search focused on heavy metals except for chromium that often contaminated in groundwater, including lead, nickel, zinc, copper, and cadmium to explore the feasibility of using calcium polysulfide (CaSx) as an in-situ stabilization technology for these heavy metals contamination groundwater. Results showed that CaSx had a great removal efficiency for heavy metals lead, nickel, zinc, copper, and cadmium. However, for nickel, zinc, copper and cadmium, when CaSx was added excessively, complexes would be formed, causing the result of re-dissolve and this would also reduce the removal efficiency. Since it is difficult to accurately control the dosage of agents for in-situ groundwater remediation, the concentration of re-dissolved nickel, zinc, cop-per, and cadmium may not be able to meet the groundwater control standards. CaSx had high lead removal efficiency, and it would not cause re-dissolution due to excessive CaSx dosing. CaSx can be used as an in-situ stabilization technique for lead contaminated groundwater.

Planetary waves in the mesosphere are studied using observational data and models to establish their origin, as there are indications of their generation independently of waves in the stratosphere. The quantitative relationships between zonal wave numbers m = 1 (wave 1) and m = 2 (wave 2) were studied with a focus on the mid-latitude mesosphere at 50N latitude. Aura Microwave Limb Sounder measurements were used to estimate wave amplitudes in geopotential height during the 2020–2021 winter major sudden stratospheric warming. The moving correlation between the wave amplitudes shows that, in comparison with the anticorrelation in the stratosphere, wave 2 positively correlates with wave 1 and propagates ahead of it in the mesosphere. A positive correlation r = 0.5–0.6, statistically significant at the 95% confidence level, is observed at 1–5-day time lag and in the 75–91 km altitude range, which is the upper mesosphere–mesopause region. Wavelet analysis shows a clear 8-day period in waves 1 and 2 in the mesosphere at 0.01 hPa (80 km), while in the stratosphere–lower mesosphere the period is twice as long at 16-days; this is statistically significant only in wave 2. Possible sources of mesospheric planetary waves are discussed.

A method of direction-of-arrival (DoA) estimation for FMCW radars is presented. In addition to MUSIC and ESPRIT, which are well-known high-resolution DoA estimation algorithms, deep learning has recently emerged as a very promising alternative. It is proposed in this paper to use a 3D convolutional neural network (CNN) for DoA estimation. The 3D-CNN extracts from the radar data cube spectrum features of the region of interest (RoI) centered on the potential positions of the targets, thereby capturing the spectrum phase shift information, which corresponds to DoA, along the antenna axis. Finally, the results of simulations and field experiments are provided to demonstrate the superior performance, as well as the limitations, of the proposed 3D-CNN.

The antioxidant potential (capacity and activity) of aqueous fullerene dispersions (AFD) of non-functionalized C₆₀, C₇₀, and Gd@C₈₂ endofullerene (in micromolar concentration range) was estimated based on chemiluminescence measurements of the model of luminol and generation of organic radicals by 2,2’-azobis(2-amidinopropane) dihydrochloride (ABAP). The antioxidant capacity was estimated by the TRAP method, from the concentration of half-suppression, and from the suppression area in the initial period. All three approaches agree and show that the antioxidant capacity of AFDs increased in the row Gd@C₈₂ < C₇₀ < C₆₀. Mathematical modeling of the long-term kinetics data was used for antioxidant activity estimation. The effect of C₆₀ and C₇₀ is found to be quenching of the excited product of luminol with ABAP-generated radical and not an actual antioxidant effect; quenching constants differ insignificantly. Apart from quenching with a similar constant, the AFD of Gd@C₈₂ exhibits actual antioxidant action. The antioxidant activity in Gd@C₈₂ is 300-fold higher than quenching constants.

Fatigue loading is critical to fibre reinforced polymer composites due to their anisotropic and heterogenous nature. This study investigated the tensile fatigue behaviour of polyester and vinyl ester based GFRP laminates to understand the critical aspects of failure mode and fatigue life under cyclic loading. GFRP laminates with two different resin systems (polyester and vinyl ester), two different stress ratios (0.1 and 0.5) and two different environmental conditions (air and water) were investigated at an applied stress of 80%, 60% and 40% of the ultimate capacity. Based on the investigated parameters (i.e., resin types, stress ratio, environmental conditioning and maximum applied stress), a fatigue model was proposed. Results show that the resin system plays a great role in fatigue failure mode while the stress ratio and environmental condition significantly affect the tensile fatigue life of GFRP laminates. The types of resin used in GFRP laminates and environmental conditions as input parameter in the proposed fatigue model is a unique contribution.

Alfalfa (Medicago sativa L.) is a perennial, outcrossing legume crop predominantly grown for hay, silage, or pasture. Intensive selection has resulted in dramatic improvement in fitness traits, including winter survival and disease resistance. However, there has been minimal improvement in other economically important traits, such as hay yield, which is still comparable to 30 years ago. Intensive phenotyping costs on this type of trait hinder high selection pressure to identify superior outcross individuals. Severe inbreeding depression inhibits the development of inbred lines with accumulated favorable alleles that exhibit heterosis. This review highlights the outcomes of inbreeding depression as well as the causes, including unmasking deleterious alleles and triggering self-incompatibility. We tracked the research efforts that unveil the genetic bases underlying deleterious alleles and self-incompatibility. The magnitudes of inbreeding depression were compared with the rate of heterozygous halved time in diploid and tetraploid organisms. To fill in the gaps between the controversy and existing hypotheses, we theorized a dosage dominant model of inheritance. The dosage dominant model is similar to the Mendelian dominance model, in which a genotype exhibits a dominant phenotype if there is a dominant allele (alphabet dominant). The difference is that in the dosage dominant model, a genotype will result in a dominant phenotype if the number of dominant alleles is equal to or greater than the number of recessive alleles. This review also includes a discussion on the development of pseudo inbreds and a hypothesis to identify deleterious alleles using bulked segregant analysis and consequently to purge deleterious alleles using marker-assisted selection, to progress toward the successful development of pure inbred lines in alfalfa.

Exercise training influences the risk of vascular thrombosis in patients with peripheral arterial disease (PAD). Mitochondrial functionalities in platelets involve the cellular bioenergetics and thrombogenesis. This study aimed to elucidate the effect of cycling exercise training (CET) on platelet mitochondrial bioenergetics in PAD patients. Forty randomly selected patients with PAD engaged in general rehabilitation (GR) with CET (i.e., cycling exercise at ventilation threshold for 30 min/day, 3 days/week) (GR+CET, n=20) or to a control group that only received GR course (n=20) for 12 weeks. Systemic aerobic capacity and platelet mitochondrial bioenergetics that included oxidative phosphorylation (OXPHOS) and electron transport system (ETS) were measured using automatic gas analysis and high-resolution respirometry, respectively. The experimental results demonstrated that GR+CET for 12 weeks significantly (i) elevated VO2peak and lowered VE-VCO2 slope, (ii) raised resting ankle-brachial index and enhanced cardiac output response to exercise, (iii) increased the distance in 6-minute walk test and raised the Short Form-36 physical/mental component scores, and (iv) enhanced capacities of mitochondrial OXPHOS and ETS in platelets by activating FADH2 (Complex II)-dependent pathway. Moreover, changes in VO2peak levels were positively associated with changes in platelet OXPHOS and ETS capacities. However, no significant changes in systemic aerobic capacity, platelet mitochondrial bioenergetics, and health-related quality of life (HRQoL) occurred following GR alone. Hence, we conclude that CET effectively increases the capacities of platelet mitochondrial bioenergetics by enhancing Complex II activity in patients with PAD. Moreover, the exercise regimen also enhanced functional exercise capacity, consequently improving HRQoL in PAD patients.

Coronavirus-infected diseases have posed great threats to human health. In past years, highly infectious coronavirus-induced diseases, including COVID-19, SARS, and MERS, have resulted in world-wide severe infections. Our literature annotations identified 110 chemical drugs and 26 antibodies effective against at least one human coronavirus infection in vitro or in vivo. Many of these drugs inhibit viral entry to cells and viral replication inside cells or modulate host immune responses. Many antimicrobial drugs, including antimalarial (e.g., chloroquine and mefloquine) and antifungal (e.g., terconazole and rapamycin) drugs as well as antibiotics (e.g., teicoplanin and azithromycin) were associated with anti-coronavirus activity. A few drugs, including remdesivir, chloroquine, favipiravir, and tocilizumab, have already been reported to be effective against SARS-CoV-2 infection in vitro or in vivo. After mapping our identified drugs to three ontologies ChEBI, NDF-RT, and DrON, many features such as roles and mechanisms of action (MoAs) of these drugs were identified and categorized. For example, out of 57 drugs with MoA annotations in NDF-RT, 47 have MoAs of different types of inhibitors and antagonists. A total of 29 anticoronaviral drugs are anticancer drugs with the antineoplastic role. Two clustering analyses, one based on ChEBI-based semantic similarity, the other based on drug chemical similarity, were performed to cluster 110 drugs to new categories. Moreover, differences in physicochemical properties among the drugs were found between those inhibiting viral entry and viral replication. A total of 163 host genes were identified as the known targets of 68 anti-coronavirus drugs, resulting in a network of 428 interactions among these drugs and targets. Chlorpromazine, dasatinib, and anisomycin are the hubs of the drug-target network with the highest number of connected target proteins. Many enriched pathways such as calcium signaling and neuroactive ligand-receptor interaction pathways were identified. These findings may be used to facilitate drug repurposing against COVID-19.

Background Critical patients with novel coronavirus pneumonia ( COVID-19) have worse outcome and high mortality. However, the histopathology of critical patient with COVID-19 remains undisclosed. Methods We performed the whole lung biopsy, and described the pathological changes of critical COVID-19 patient done with transplant by HE staining, immunohistochemistry and special staining observed under the microscopy. Findings The whole lungs displayed diffuse congestive appearance and partly haemorrhagic necrosis on gross examination. The haemorrhagic necrosis was prominently present in outer edge of the right lower lung. The cut surfaces of the lung displayed severe congestive and haemorrhagic changes. The main pathological changes showed massive pulmonary interstitial fibrosis, and partly hyaline degeneration, variable degrees of hemorrhagic pulmonary infarction. Small vessels hyperplasia, vessel wall thickening, lumen stenosis, occlusion and microthrombosis formation. Focal monocytes, lymphocytes and plasma cells infiltrating into pulmonary interstitium. Bronchiolitis and alveolitis with proliferation, atrophy, desquamation and squamous metaplasia of epithelial cells. Atrophy, vacuolar degeneration, proliferation, desquamation and squamous metaplasia in alveolar epithelial cells. Alveolar cavity congestion was prominent, and contained mucus, edema fluid, desquamated epithelial cells, and inflammatory cells. We also found several multinucleate giant cells and intracytoplasmic viral inclusion bodies. Special stains including Masson stain, sirius red staining, reticular fibers staining indicated massive pulmonary interstitial fibrosis. Immunohistochemistry showed positive for immunity cells including CD3, CD4, CD8, CD20, CD79a, CD5, CD38 and CD68. Interpretation We demonstrate the pathological findings of critical patient with COVID-19, which might provide a deep insight of the pathogenesis and severity of this disease.

This paper outlines our effort on optimizing Pulsed Magneto-Oscillation (PMO) design in order to improve the efficiency of ingot manufacturing under PMO. Our calculation and experiment provided optimized PMO coil design and special configuration. Our optimized PMO design offered us a device that enabled the operator to examine and operate the melt without losing the efficiency. In one of the designs, the equipment even refined the grain sizes. Our work also showed an optimized distance range between the coil and the melt surface that maximized the refinement effects.

Currently, data regarding optimal treatment modality, response, and outcome specifically for N3 head and neck cancer are lacking. This study aimed to compare the treatment outcomes between definitive concurrent chemoradiotherapy (CCRT) to the neck and upfront neck dissection followed by adjuvant CCRT. 93 N3 squamous cell carcinoma head and neck cancer patients were included. Primary tumor treatment was divided to definitive CCRT (CCRT group) or curative surgery followed by adjuvant CCRT (surgery group). Neck treatment was also classified into two treatment modalities: definitive CCRT to the neck (CCRT group) or curative neck dissection followed by adjuvant CCRT (neck dissection group). Overall, the 2-year overall survival (OS), local recurrence-free survival (LRFS), regional recurrence-free survival (RRFS), and distant metastasis-free survival (DMFS) were 51.8%, 47.3%, 45.6%, and 43.6%, respectively. In both oropharyngeal cancer and nonoropharyngeal cancer patients, in terms of OS, LRFS, RRFS or DMFS no difference was noted regarding primary tumor treatment (CCRT vs. surgery) or neck treatment (CCRT vs. neck dissection). In summary, N3 neck patients treated with definitive CCRT can achieve similar outcomes to those treated with upfront neck dissection followed by adjuvant CCRT. Cautions should be made to avoid overtreatment for this group of patients.

Polydimethylsiloxane with hydroxy groups was functionalized to form functionalized polydimethylsiloxane, which subsequently underwent an addition reaction with isophorone diisocyanate to form the prepolymer. Next, 3-aminopropyltriethoxysilane (APTS) reacted with 3-glycidoxypropyltrimethoxysilane (GPTS) to produce bridged polysilsesquioxanes, and the sol–gel technology was employed to form hyperbranched polysiloxane nanoparticles with hydroxy groups, which was used as the additive. The hyperbranched polysiloxane and the prepolymer containing NCO functional groups then underwent an addition reaction to produce the hybrid materials. Fourier-transform infrared spectroscopy and 29Si nuclear magnetic resonance were used to characterize the structure of the polyurethane hybrid. Regarding thermal stability, after the hyperbranched polysiloxane nanoparticles was introduced, the integral procedural decomposition temperature increased from 348 ºC for polyurethane matrix to 859 ºC for the hybrid material. The results revealed that the thermal stability of the hybrid material substantially increased by approximately 247%.

K417G Ni-based superalloy is widely used in aeroengine turbine blade for its excellent properties. However, the aeroengine rotor blade zigzag crown appears early failure frequently, which is because of the wear problems occurring in the working process. Laser forming repairing (LFR) is a promising technique to repair these damaged blades. Unfortunately, the laser formed Ni-based superalloys with high content of (Al + Ti) have a high cracking sensitivity. In this paper, the crack characterization of the LFRed K417G, the microstructure, microhardness and tribological properties of the coating before and after laser remelting are presented. The results show that the microstructure of as-deposited K417G consists of γ phase, γ′ precipitated phase, γ + γ′ eutectic and carbide. Cracking mechanisms including solidification cracking, liquation cracking and ductility dip cracking are proposed based on the composition of K417G and processing characteristics to explain the cracking behavior of the K417G superalloy during LFR. After laser remelting, the microstructure of the coating has been refined, and the microhardness and tribological properties has been improved. Laser remelting can decrease the size of the cracks in the LFRed K417G but not the number. Therefore, laser remelting can be applied as an effective method for strengthening coating and as an auxiliary method for controlling cracking.

In this work, nylon 6/ P(N-phenylmaleimide-alt-styrene) blends were prepared by melt blending, and the mechanical, heat-resistant, crystallographic and dynamical mechanical properties of nylon 6/ P(N-phenylmaleimide-alt-styrene) blends with different contents were investigated and analyzed. The results showed that the mechanical properties decreased with increasing PNS, while the heat deflection temperature (HDT), relative crystallinity (Xn), and storage modulus (G’) increased with increasing PNS. The results of differential Scanning Calorimetry (DSC) proved the PNS played the positive role of nucleating PA6. And the results of dynamic mechanical analysis (DMA) proved the PNS could improve the rigidity of PA6/PNS blends. From the SEM, these PNS domains were between 0.2 and 4 μm in diameter. The experimental results indicated that the addition of PNS improved the rigidity of PA6/PNS blends, and then improved the heat-resistant property.

T-2 toxin produced by fungi of Fusarium genus is highly toxic to human and animals and has been shown to induce apoptosis in various organs/tissues. Apoptosis and autophagy are interconnected processes and these interactions are important for cellular homeostasis as well as pathogenesis. In this study, we report for the first time that T-2 toxin induced autophagy in human liver cells (L02). We showed that T-2 toxin induced the formation of acidic vesicular organelles, concordant with the time and dose-dependent alterations in LC3-phosphatidylethanolamine conjugate (LC3-II) LC3-I/II and p62/SQSTM1 suggesting an enhanced autophagic flux. The T-2 toxin-induced formation of autophagosome and lysosomal fusion was observed by expressing mRFP-GFP-LC3 in L02 cells by lentiviral transduction, and autophagosome was observed by transmission electron microcopy. We found that while T-2 toxin activated both apoptosis and autophagy, activation of autophagy appears to be a leading event reflecting the protective mechanism of cells against the insults by T-2 toxin. Activating autophagy by rapamycin (RAPA) inhibited the apoptosis while suppressing autophagy by chloroquine greatly enhanced the T-2 toxin-induced apoptosis suggesting the crosstalk of autophagy and apoptosis. In summary, our study showed that activation of autophagy protects liver cells from T-2 toxin-induced apoptosis suggesting autophagy may be targeted for prevention of the T-2 toxin-induced toxicity in human and animals.

It is currently difficult to obtain accurate fine dust information in residential areas due to the insufficient number of air quality monitoring systems and spatial imbalances. Therefore, a detailed particulate matter dispersion model including factors such as land use and meteorological information was developed in this study and used to create fine dust concentration distribution maps. The fine dust concentration distribution maps currently available to citizens were compared with those obtained by dispersion modeling, and population distribution data were employed to compare the populations exposed to fine dust according to the two methods. The results of the existing method and the developed particulate matter dispersion model differed significantly. For instance, the PM2.5 concentrations in Daejeon, South Korea, on February 17, 2018, were 56% “Good” and 44% “Moderate,” according to the existing method, while they were 31% “Good,” 26% “Moderate,” 28% “Unhealthy,” and 15% “Very Unhealthy,” according to the dispersion model. Furthermore, the existing method indicated that no portion of the population was exposed to poor fine dust concentrations, while the proposed model revealed that over 170 thousand people were exposed to such concentrations. These results on fine dust distributions will contribute to sustainable urban and environmental planning.

Actinobaculum massiliense, a Gram-positive anaerobic coccoid rod colonizing the human urinary tract, belongs to the taxonomic class of Actinobacteria. We identified A. massiliense as a cohabitant of urethral catheter biofilms (CB). The CBs also harbored common uropathogens such as Proteus mirabilis and Aerococcus urinae, supporting the notion that A. massiliense is adapted to a life style in polymicrobial biofilms. We isolated a strain from an agar colony derived from a clinical sample. Using 16S rRNA gene sequencing and shotgun proteomics, we identified and characterized A. massiliense, comparing the isolate grown in vitro and four clinical ‘in vivo’ samples. Based on abundances of proteins in the in vivo milieu, we assessed their functions related to nutrient import and responses to hostile host conditions characterized by neutrophil infiltration. Two putative subtilisin-like proteases and a heme/oligopeptide transporter were highly expressed in vivo and are perhaps important for survival in the host milieu. The uptake of xylose/glucuronate and oligopeptides apparently enables feeding metabolites into mixed acid fermentation and peptidolysis pathways, respectively, to generate energy. A putative polyketide synthase which may generate a secondary metabolite interacting with either the host or co-colonizing microbes was identified. The enzyme may contribute to A. massiliense persistence in CBs.

Wave steepness is presented as an extension and a valuable add-on to the conventional set of sea state parameters retrieved from satellite altimetry data. Following physical model based on recent advances of weak turbulence theory wave steepness is estimated from directly measured spatial gradient of wave height. In this way the method works with altimetry trajectories rather than with point-wise data. Moreover, in contrast to widely used parametric models this approach provides us with instantaneous values of wave steepness and period. Relevance of single-track estimates of wave steepness (period) is shown for wave climate studies and confirmed by a simple probabilistic model. The approach is verified via comparison against buoy and satellite data including crossover points for standard 1 second data of Ku-band altimeters. High quality of the physical model and robustness of the parametric ones are examined in terms of global wave statistics. Prospects and relevance of both approaches in the ocean wave climate studies are discussed.

A series of novel N-n-butyl-1,8-naphthalimide derivatives were synthesized via a three-step reaction involving nucleophilic substitution and acylation. All of the compounds were characterized by IR, ¹H NMR, ¹³C NMR, MS, and elemental analysis, and the crystal structure of N-n-butyl-4-[N’,N’-bis(2`,4`-dichlorobenzoyl)ethylamino]-1,8-naphthalimide was determined. The π-π stacking interactions and hydrogen bonds between the two molecular core planes (naphthalimide ring) and the van der Waals forces between the flexible n-butyl groups resulted in a 3D long-chain structure. The UV-vis and fluorescence properties of the title compounds were investigated. The results indicated that the monosubstituted 1,8-naphthalimide derivatives bearing an electron-donating group on the benzene ring or a structure with a larger conjugative effect exhibited enhanced fluorescence properties.

To solve large scale linear equations involved in the Fast Multipole Boundary Element Method (FM-BEM) efficiently, an iterative method named the generalized minimal residual method (GMRES)(m)algorithm with Variable Restart Parameter (VRP-GMRES(m) algorithm) is proposed. By properly changing a variable restart parameter for the GMRES(m) algorithm, the iteration stagnation problem resulting from improper selection of the parameter is resolved efficiently. Based on the framework of the VRP-GMRES(m) algorithm and the relevant properties of generalized inverse matrix, the projection of the error vector r_m+1 on r_m is deduced. The result proves that the proposed algorithm is not only rapidly convergent but also highly accurate. Numerical experiments further show that the new algorithm can significantly improve the computational efficiency and accuracy. Its superiorities will be much more remarkable when it is used to solve larger scale problems. Therefore, it has extensive prospects in the FM-BEM field and other scientific and engineering computing.

The impact of antecedent soil moisture content on soil erosion is a complicated phenomenon, which is still under argument with contradictions in research results. Hence, the objective of this study is to investigate the impact of antecedent soil moisture content to soil loss on clay soil by conducting two-year field experiments under natural rainfall on runoff plots with length of 10 meters, width of 3 meters, and uniform slope of 9%. Volumetric soil moisture sensors were used to log soil moisture changes, and soil moisture readings were used along with rainfall records to quantify the antecedent soil moisture conditions for each rainfall event. Results of this study show duration of the effective erosion event outranks the antecedent volumetric soil moisture content. Field study also suggests that accumulative rain falling within 48 hours (Pp48) prior to an effective erosion event strongly correlated with soil loss per Rainfall-Runoff Erosivity Index (Soil Loss / EI30), particularly when the duration of an effective erosion event is either between 3 ~ 7 hours or 10~ 30 hours. Hence, Pp48 can be considered as an alternative to replace antecedent soil moisture content in RUSLE 2’s cover and management factor.

Objective: To explore three novel fasting blood glucose (FBG)-based novel indicators, including FBG-to-albumin ratio (FAR), FBG-to-lymphocytes ratio (FLR), and FBG-to-hemoglobin ratio (FHR), in predicting prognosis and detecting metastasis for patients with pancreatic neuroendocrine neoplasms after resection. Materials and methods: A total of 178 pNEN patients underwent surgical resection were included in this study. Receiver operating characteristic (ROC) curves were used to evaluate the diagnosis values of FAR, FLR, and FHR, and the cut-off values were obtained for further analyses. Univariate and multivariate analyses were conducted to determine the independent predictors. The Kaplan-Meier method was used to evaluate the progression-free survival (PFS) and overall survival (OS) of the pNEN patients. Results: The optimal cut-off values of FAR, FLR, and FHR were 0.17, 2.85, and 0.028, respectively. As for PFS, the area under the curve (AUC) was 0.693 for FAR, 0.690 for FLR, and 0.661 for FHR, respectively. The AUC was 0.770, 0.692, and 0.715 accordingly for OS. The groups with lower FAR, FLR, and FHR were significantly associated with prolonged PFS and OS (p < 0.05). In patients with metastasis, the lower FAR group was correlated with significantly longer PFS and OS (p = 0.022 and 0.002, respectively). The FLR was an independent predictor of PFS in pNEN patients, and the FAR was a predictor of OS. FAR was an independent indicator of PFS in patients with metastasis. Conclusion: Preoperative FAR, FLR, and FHR are effective in predicting the prognosis of pNEN patients and detecting the synchronous metastases.

Time-modulated sparse circular array (TMSCA) with elements uniformly excited is designed and synthesized in this paper. By utilizing rotationally symmetric structure, the array geometry and the time modulation of the TMSCA is presented, and the radiation patterns in frequency domain are formulated. In order to achieve the desired radiation pattern at the operating frequency and suppress the sideband radiation, the synthesis problem is established and solved by the proposed harmony search-convex programming (HS-CP) algorithm in two dependent optimizations. Two designs are presented, and the numerical results indicate that the TMSCA with rotationally symmetric structure has the advantages of designing time-modulated sparse arrays with superior performance.

Cordycepin has good antitumor activity, but its clinical application is limited due to the easy deamination of N6 in structure. In this study, a large lipopolysis group was introduced at the cordycepin N6 to improve the problem, Cordycepin derivatives(3a-4c) were synthesized, and biological evaluation of compounds were studied. In the study, the vitro antitumor activity of the compounds against MCF7 cells, HepG2 cells and SGC-7901 cells was evaluated by MTT assay. In the results, compound 4a showed the most obvious inhibitory effect on MCF7 cells with IC50 value of 27.566±0.52 μM, which was much lower than cordycepin. Compound 4a showed high selectivity between MCF7 and normal MCF-10A cells. Further biological evaluation showed that compound 4a promoted apoptosis and blocked the cell cycle in G0/G1 phase. Then, Western Blot was used to detect related apoptotic proteins. It was found that Compound 4a could down-regulate the expression of Bcl-2 protein and up-regulate the expression of p53, Bax, Caspase-3, and Caspase-9 proteins. The mitochondrial membrane potential decreased continuously and the positive expression rate decreased. It was speculated that compound 4a induced the apoptosis of MCF7 cells through the mitochondrial pathway.

Defect detection plays a pivotal role in quality control for fabrics. In order to enhance the accuracy and efficiency of fabric defect detection, we have proposed the PRC-Light YOLO model for fabric defect detection and have established a detection system. Firstly, we add new convolution operators in Backbone for the YOLOv7 and integrate them with Extended-Efficient Layer Aggregation Network. This combination constructs a new feature extraction module that not only reduces the computational effort of the network model, but also extracts spatial features effectively. Secondly, we employ multi-branch dilated convolutions feature pyramid, and introduce lightweight upsampling operators to improve performance of the feature fusion network. This module achieves an expanded receptive field by generating real-time adaptive convolution kernels, allowing for the collection of crucial information from regions with a richer contextual context. To further minimize the computation during network model training, we adopt the HardSwish activation function. Finally, we apply the Wise-IOU v3 bounding box loss function as a dynamic non-monotonic focusing mechanism, which decreases adverse gradients from low-quality instances. We conduct data augmentation on real fabric dataset to raise the generalization capability of the PRC-Light YOLO model. Compared with the YOLOv7 model, numerous simulation experiments show that our proposed methods reduce the model’s parameters and computation by 18.03% and 20.53%, respectively. Simultaneously, there has been a 7.6% improvement in mAP.

Scaffolds used for tissue/ bone defect repair must possess versatile properties suitable for each specific application. The issue of antibiotic resistance poses a significant challenge in bone tissue engineering especially when dealing with microbial infections. The most effective approach to address this challenge is to promote the integration of tissue before bacteria can adhere to it, hence preventing the proliferation of certain bacterial strains on the implant. The utilization of 3D printing and or the use of various composite polymers in scaffolds to create antibacterial scaffolds that possess both adequate mechanical strength and exceptional biocompatibility is an attractive approach for addressing the challenges associated with microbial infections in tissue. Herein, a new phage functionalized scaffold was created through surface charge modification of the composite scaffold with polyethyleimine (PEI). Afterwards, the PEI polymerized Scaffolds were incubated with phage lysate for approximately 2h prior to rinsing with ethanol. The morphological and physiochemical properties of formed scaffold were assessed through Raman spectrophotometry while the antibacterial assays were done through growth inhibition zones/ cell viability assays. The polymerized phage composite SF20_PEI.AR9 possessed the highest antimicrobial effect with clear inhibition zones of about 78.30 mm. This could be attributed to the lytic effect of phages on the bacterial cells. Moreover, the enhanced phage effect on the scaffolds was also associated to the improved surface charge on the scaffold, 78,3±7,6 mm which ultimately promoted phage scaffold interface integration hence the high antibacterial activity. The PEI polymerization approach could serve as a model for future development of phage scaffolds.

To reveal the antibacterial effect of wound secretions of different Chinese fir strains on five kinds of bacteria. Three 3-year-old seedlings of Taxus chinensis var.koraiensis and Yangkou and the 3-year-old container seedlings of Taxus chinensis var.pendula, Yang061 and Yang020, were used as the research objects. The antibacterial effect of wound secretions was determined by the filter paper diffusion method, and the antibacterial effect was analyzed. Results showed that the wound secretions of different strains of Chinese fir bark had noticeable bacteriostatic effects on Bacillus subtilis, Salmonella paratyphi B, Pseudomonas aeruginosa, Escherichia coli, and Staphylococcus aureus. However, the bacteriostatic effects of different strains of Chinese fir secretions differed. The minimum inhibitory concentrations (MICs) of the wound secretions of different strains of Chinese fir against the five test bacteria differed. The mean MIC of Pseudomonas aeruginosa was the highest, and the mean MIC of Escherichia coli was the lowest. The antibacterial ability of the wound secretions of different Chinese fir strains was mainly determined by the composition of the wound secretions. There was no noticeable relationship with the number of wound secretions.

The effects of organic metabolites produced by a sulfate-reducing prokaryote (SRP) in seawater on the anode corrosion process of magnesium alloy were analyzed by open circuit potential, electrochemical impedance spectroscopy, polarization curve, and other electrochemical methods, combined with scanning electron microscopy and X-ray diffraction. It was found that the product film produced by magnesium alloy anode corrosion was not dense, and the surface of the magnesium anode substrate was exposed during the corrosion process. The corrosion of magnesium anode matrix was accelerated by the simulation of different organic metabolites including mannose, glucuronic acid, and glucose. Thus, the synergistic effect of various metabolites produced by SRP in the corrosion process of magnesium alloy may be considered in future studies.

The chromatographic conditions were optimized using headspace gas chromatography, and a simple and rapid method was established for the simultaneous determination of five residual solvents in ursodeoxycholic acid raw materials. The corresponding quality standards were revised. The results showed that the concentration of methanol ranged from 0.06mg/ml to 0.3mg/ml, and the concentrations of acetone, tert butanol, ethyl acetate, and triethylamine showed a good linear relationship with the peak area within the range of 0.1mg/ml to 0.5mg/ml (r=0.999); The quantitation limits for methanol, acetone, tert-butanol, ethyl acetate, and triethylamine were 4.2, 0.9, 1.5, 1, and 0.1 μg/ml, respectively, with detection limits of 1.2, 0.25, 0.025, 0.3, and 0.025 μg/ml, respectively. The recovery rates of each solvent ranged from 92.9% to 106.0%, with RSD% (n=9) less than 3.8%; The method exhibited good repeatability, with RSD% (n=6) less than 2.5%. Furthermore, the durability is good. The established method is simple, accurate, specific, and highly sensitive, and can be used for the simultaneous and rapid determination of five residual solvents in ursodeoxycholic acid raw materials.

The investigation on the issue of damage diagnosis based on strain modal parameters is conducted in this paper using simply supported wooden Beams as the study's object. First, ABAQUS is utilized to create finite element models of intact wooden beams as well as wooden beams with varying degrees of damage and perform modal analyses on them. Next, damage identification studies are conducted on the wooden beam structure using various strain modal parameters (strain mode strain modal difference, strain modal curvature difference), the timber beam damage identification test then yields the modal parameters of timber beams under various damage situations, and the test findings are contrasted with those of the numerical simulation. The outcomes demonstrate that the damage identification of the test data using the three types of damage identification indexes is consistent with the results of the numerical simulation; the three types of damage identification indexes can locate the damage to timber beams, but the identification effect of the indexes is different, the best-recognized metric is the strain mode curvature difference; the next best is the strain mode difference, and the worst is the strain modes. The study's findings can serve as a guide for future damage detection on wood beams.

Legume-rhizobial symbiosis leads to to the formation of root nodules, where rhizobia reside and develop into bacteroids to reduce nitrogen into ammonium for plant growth, which leaves an opening question as how plant immunity is attenuated in nodules in the presence of large number of foreign bacteria. In Medicago truncatula, mutation in NAD1 (Nodules with Activated Defense 1) only produces necrotic nodules with overactivated immunity, indicating NAD1 is an indispensable component required for suppressing immunity in nodules. In this study, a dual RNA-seq transcriptomic technology was performed to extensively analyze gene expressions in nad1-1 mutant nodules. We indenifited 89 DEGs in symbiotic nitrogen fixation and 89 DEGs in immunity in Medicago truncatula at 10 dpi. Simultaneously, we indenifited 27 DEGs in fix and nif genes in Sinorhizobium meliloti. Then we identified 56 DEGs related to stress, including ROS, NO, and NCR, most of which were upregulated in Sinorhizobium meliloti. Our analyses of nitrogen fixation-defective plant nad1-1 mutants with overactivated defense indicate that host use plant immunity to control massive bacterial colonization during early and late symbiotic stages. Our findings provide insight into the function of NAD1 in improvement or inhibition of plant immune response to maintain symbiosis during rhizobial endosymbiosis.

This paper explores the use of different deep learning models for predicting precipitation in 56 meteorological stations in Jilin Province, China. The models used include Stacked-LSTM, Transformer, and SVR, and Gaussian noise is added to the data to improve their robustness. Results show that the Stacked-LSTM model performs the best, achieving high prediction accuracy and stability. The study also conducts variable attribution analysis using LightGBM and finds that temperature, dew point, precipitation in previous days, and air pressure are the most important factors affecting precipitation prediction, which is consistent with traditional meteorological theory. The paper provides detailed information on the data processing, model training, and parameter settings, which can serve as a reference for future precipitation prediction tasks. The findings suggest that adding Gaussian noise to the dataset can improve the model's generalization ability, especially for predicting days with zero precipitation. Overall, this study provides useful insights into the application of deep learning models in precipitation prediction and can contribute to the development of meteorological forecasting and applications.

Underwater target detection is widely used in various applications such as underwater search and rescue, underwater environment monitoring, and Marine resources survey. However, the visibility of the underwater environment and the accuracy of target detection can be affected by complex underwater light changes and unpredictable background noise. To address these issues, we propose an improved underwater target detection algorithm based on YOLOv8n. Our algorithm focuses on three aspects. Firstly, we replace the original C2f module with Deformable Convnets v2 to enhance the adaptive ability of the target region in the convolution check feature map and extract the target region's features more accurately. Secondly, we introduce SimAm, a non-parametric attention mechanism, which can deduce and assign three-dimensional attention weights without adding network parameters. Lastly, we optimize the loss function by replacing the CIOU loss function with the Wise-IOU loss function. To conduct our experiments, we create our own dataset of underwater target detection for experimentation. Meanwhile, we also utilized the Pascal VOC dataset to evaluate our approach. The [email protected] and [email protected]:0.95 of the original YOLOv8n algorithm on the underwater target detection were 88.6% and 51.8%, respectively, and the improved algorithm [email protected] and [email protected]:0.95 can reach 91.8% and 55.9%. The original YOLOV8n algorithm was 62.2% and 45.9% [email protected] and [email protected]:0.95 on the Pascal VOC dataset, respectively. The improved YOLOV8n algorithm [email protected] and [email protected]:0.95 were 65.7% and 48.3%, respectively. The floating-point computation volume of the model is reduced by about 6%. The above experimental results prove the effectiveness of our method.

To date, recanalization interventions are the only available treatments for ischemic stroke patients, however, there are no effective therapies for reducing stroke-induced neuroinflammation. We recently reported that H+ extrusion protein Na+/H+ exchanger-1 (NHE1) plays an important role in stroke-induced inflammation and white matter injury. In this study, we tested the efficacy of two potent NHE1 inhibitors, HOE642 and Rimeporide, with a delayed administration regimen starting at 24 h post-stroke in adult C57BL/6J mice. Post-stroke HOE642 and Rimeporide treatments accelerated motor and cognitive function recovery without affecting the initial ischemic infarct, neuronal damage or reactive astrogliosis. However, delayed administration of NHE1 blockers after ischemic stroke significantly reduced microglial inflammatory activation while enhanced oligodendrogenesis and white matter myelination, with increased proliferation and decreased apoptosis of the oligodendrocytes. Our findings suggest that NHE1 protein plays an important role in microglia-mediated inflammation and white matter damage. Pharmacological blockade of NHE1 protein activity reduced microglia inflammatory responses and enhanced oligodendrogenesis and white matter repair, leading to motor and cognitive function recovery after stroke. Our study reveals the potential of targeting NHE1 protein as therapeutic strategy for ischemic stroke therapy.

Sugarcane mosaic virus (SCMV) is a deleterious pathogen which causes widespread Sugarcane mosaic disease (SCMD) and is classified in the genus Potyvirus (Potyviridae), disseminated by the aphid vector. RNA interference (RNAi)-mediated antiviral innate immunity is a key biological process and antiviral defence system to interfere with viral genomes for controlling plant pathogens. The current study aims to analyze sugarcane (Saccharum officinarum L. and Saccharum spp.) locus-derived microRNAs (sof-miRNAs/ssp-miRNAs) with predicted potential for targeting the SCMV +ssRNA-encoded mRNAs, using ‘five algorithms’ approach. The ultimate goal in this research is to mobilize the in silico endogenous predicted sof-miRNAs/ssp-miRNAs to trigger RNAi catalytic pathway experimentally and generate sugarcane cultivars for evaluating potential antiviral resistance monitoring capability and capacity for SCMV. Experimentally validated mature sugarcane (S. officinarum, 2n = 8X = 80) and (S. spp., 2n = 100-120) sof-miRNAs/ssp-miRNAs (n = 28) were acquired for alignment with the SCMV genome. Of the 28 targeting mature locus-derived sof-miRNAs/ssp-miRNAs investigated, one sugarcane miRNA homolog, sof-miR159c, was concluded to localize potential binding site at genomic nucleotide site 3847 targeting CI ORF of SCMV. In order to validate target prediction accuracy, whether the sugarcane sof-miRNA/ssp-miRNA might bind predicted SCMV mRNA target(s), we created an integrated Circos plot. Genome-wide in-silico-predicted miRNA-mediated target gene regulatory network validated interactions that warrant in vivo analysis. The current work provides valuable evidence and biological material for generating SCMV-resistant sugarcane varieties.

Bright morning light (BML) entrains the body clock, modulates circadian rhythm, and improves sleep-wake disturbances. However, its impact on the autonomic nervous system (ANS) at night remains unclear. Hence, we investigated the effects of BML exposure on activities of the parasympathetic nervous system (PSNS) and sympathetic nervous system (SNS) at night. This non-randomized controlled pilot study included participants ≥60 years, diagnosed with a type of dementia or cognitive disorder. We excluded participants with pacemakers. The treatment group received 2500 lx BML, whereas the control group received approximately 200 lx of general lighting. We measured the heart rate variability to quantify ANS activity. The treatment group displayed significantly increased high-frequency (HF) power (Roy's largest root=2.44; P<.01) and insignificantly decreased normalized low-frequency (LF%) power. The corresponding low-frequency/high-frequency ratio (LF/HF), insignificant decrease, and cognitive function were correlated with PSNS activity (Roy's largest root=3.92; P<.01), which is effective for moderate dementia. BML exposure reduced SNS activity and enhanced PSNS activity at night, which consequently affected cognitive function. Furthermore, the light washout intervention markedly increased SNS activity at night. BML therapy may be a useful clinical tool for alleviating the deterioration of cognitive function.

Carrot juice and its associated beverage products are well-known healthy drinks all over the world. However, what effect carrot juice has on the human gut microbiota and how it is fermented by the intestinal microbes have not been studied. Here, using an in vitro model of anaerobic fermentation, we demonstrated that carrot juice could be fermented into lactate and acetate by the human gut microbiota. 16S high-throughput sequencing and bioinformatic analyses indicated that fermentation of carrot juice could significantly change the composition of the human gut microbiome. Interestingly, carrot juice remarkably increased the abundances of beneficial bacteria, including Lactobacillus fermentum, Lactobacillus salivarius, Lactobacillus mucosae and Bacteroides uniformis and decreased the population of opportunistic pathogenic bacteria, such as Enterococcus faecium in the gut. Collectively, our study illustrates a favorable effect of carrot juice on the human gut microbiota and lays a foundation for the development of carrot juice as a novel prebiotic agent.

In response to the increasing energy demand in Taiwan and the global trend of renewable energy development, Kuroshio energy is a potential energy source. How to extract this invaluable natural resource has then become an intriguing and important question in engineering practices. This study conducted a study for a nozzle-diffuser duct (NDD) as the Kuroshio currents energy harvester. The computational fluid dynamics (CFD) software ANSYS Fluent was employed to calculate the drag and added mass coefficients of the duct anchored to the seabed. Those coefficients were further imported into Orcaflex to simulate the motion of the duct under normal and storm wave conditions. Results showed that the duct was stable 25 m below the sea surface under normal wave condition. When the wave condition changed to storm waves, the duct needed to dive into at least 90 m below the sea surface to regain its stability and obtain high power take-off (PTO). An optimal design nozzle-diffuser-duct was reported and a PTO peak of 15 kW was expectable in the Kuroshio currents. Once a suitable offshore platform can be developed with sixty-six NDDs, a Megawatt Kuroshio ocean current power generation system is feasible in the near future.

Exploring the effect of the sample size on the estimation accuracy of airborne LiDAR forest attributes in a large-scale area can help in optimizing the technical application scheme of operational ALS-based large-scale forest stand inventories. In our study, sample datasets composed of different sample plots were constructed by repeated sampling from 1003 sample plots in a subtropical study area covering 2376 × 103 km2. Sixteen multiplicative power models were built in each forest type consisting of four forest attributes. Through these models, the variations of standard deviation (SD) and coefficient of variation (CV) of R2 and rRMSE of forest attribute estimation models for different quantity levels of sample plots were also analyzed. The results showed that, first, when the sample size increased from 30 to the top limit, the SD of the forest attributes and LiDAR variables showed a decreasing trend. Second, as the sample size increased, the rRMSE of the 16 forest attribute estimation models gradually decreased, while the R2 gradually increased. Third, when the sample size was small, both the SD of R2 and rRMSE of the models were large, and the SD of R2 and rRMSE gradually decreased as the sample size increased. In 50 models conducted for each attribute at the same sample size, for the mean standard deviations of forest attributes, the ten best performing models were lower than those of the total 50 models, and the worst ten models were the opposite. When the sample size increased, the accuracy of each forest attribute estimation model for each forest type gradually improved. The variation of forest attributes and the LiDAR variable of the construction model are critical factors that affect the model’s accuracy. To efficiently apply airborne LiDAR in order to survey large-scale subtropical forest resources, the sample size of the Chinese fir forest, pine forest, eucalyptus forest, and broad-leaved forest should be 110, 80, 85, and 70, respectively.

Ovarian cancer is the most frequent cause of deaths in gynecologic malignancies. Many possible mechanisms have been proposed via RNAseq and DNAseq technique recently. However, the driving factors are still obscure. The possible reasons are attributed to the incomplete human reference. This study integrated the canonical mapping-based and mapping-free protocols to extract reliable variations and novel events. We eventually obtained 450 reliable SNVs from the WES data and novel events from the RNAseq data, including 154 SNVs, 462 intron events, two repeats and six splice events. We identified six differentially expressed genes and six contigs that are significantly related to survival prognosis. The recurrent SNVs in significantly differentially expressed genes can be validated in an independent cohort of 20 Chinese ovarian cancer patients.

This study investigated the spatial variability of soil organic carbon (SOC), total nitrogen (TN), soil microbial biomass carbon (SMBC) and soil microbial biomass nitrogen (SMBN) in Hongqipao reservoir dominated by different vegetation types and the possible relationships with other soil properties. Top 0–50cm soil samples were collected in sites dominated by different vegetation types within the reservoir littoral zone. There was high spatial variability for SOC, TN, SMBC and SMBN in the Hongqipao reservoir. In addition, the SOC, TN, SMBC and SMBN contents decreased with increasing soil depth. This could be attributed by the fact that when plants detritus decompose, most of their organic matter is mineralized and a new soil layer which contains a greater amount of organic carbon is formed at the top. According to Pearson's correlation values and redundancy analysis (RDA) results, SOC was significantly and positively correlated with TN likely because the vegetation organic matter and liter could be the main nitrogen sources. Similarly, soil moisture content (MC) was significant positive correlated with SOC and TN. Conversely, BD was significant negative correlated with SOC and TN contents in the 0-50 cm soil profiles. However, no significant correlations were observed between SOC, TN, SMBC and SMBN contents and soil pH values. SMBN was significantly and positive correlated with C:N ratio and BD and negative related with MC. Multiple linear regression model revealed that all measures soil properties in this study could explain higher significant variability of the response variables (SOC, TN, SMBC and SMBN contents). This implies that all the measured soil variables within the different vegetation types in the reservoir played a crucial role in determining the contents of SOC, TN, SMBC and SMBN. This study further suggests that vegetation types play a major role in determining the spatial characteristics of SOC and TN. Any changes in the vegetation types in the reservoir may influence the distribution of SOC and TN. This may affect the global carbon budget and the atmospheric greenhouse gas concentration significantly.

In this paper, we present a complete, flexible and safe convex-optimization-based method to solve speed planning problems over a fixed path for autonomous driving in both static and dynamic environments. Our contributions are five fold. First, we summarize the most common constraints raised in various autonomous driving scenarios as the requirements for speed planner developments and metrics to measure the capacity of existing speed planners roughly for autonomous driving. Second, we introduce a more general, flexible and complete speed planning mathematical model including all the summarized constraints compared to the state-of-the-art speed planners, which addresses limitations of existing methods and is able to provide smooth, safety-guaranteed, dynamic-feasible, and time-efficient speed profiles. Third, we emphasize comfort while guaranteeing fundamental motion safety without sacrificing the mobility of cars by treating the comfort box constraint as a semi-hard constraint in optimization via slack variables and penalty functions, which distinguishes our method from existing ones. Fourth, we demonstrate that our problem preserves convexity with the added constraints, thus global optimality of solutions is guaranteed. Fifth, we showcase how our formulation can be used in various autonomous driving scenarios by providing several challenging case studies in both static and dynamic environments. A range of numerical experiments and challenging realistic speed planning case studies have depicted that the proposed method outperforms existing speed planners for autonomous driving in terms of constraint type covered, optimality, safety, mobility and flexibility.

Immobilized metal ion affinity adsorbents have been widely used in separation technique to purify proteins. Due to the leakage of metal ion from the adsorbents, there is no metal ion affinity adsorbent for hemoperfusion has been applied to clinical trial. In this study, in order to prevent the leakage of Zn²⁺ loaded from cellulose beads based adsorbent, improve its stability and adsorption capacity for testosterone, Freeze-drying method was used to enhance the porosity of cellulose beads, improve the surface area of the cellulose beads and adsorption capacity for testosterone. Chitosan was used to coat the adsorbents for preventing the leakage of Zn²⁺ loaded and improve the adsorbent’s stability. Moreover, the factors affecting adsorption ability and some components in plasma were also investigated. The results indicate the adsorption ability of the adsorbent can be significantly improved by freeze-drying. After the adsorbent was coated with 0.02% chitosan solution, the highest adsorption percentage reached 48%. During adsorption, the Zn²⁺ concentration in plasma did not rise. In addition, the adsorption percentage for total proteins was below 15%. The results may be caused by the pore size and surface area of the adsorbent enlarged via freeze-drying, and the chitosan solution went into the pores and coated the outer and inner surface of the adsorbent. The adsorbent has a potential clinical application to remove testosterone in patients with recurrent and metastatic prostate cancer.

The emergence of SARS-CoV-2 mutations pose significant challenges to diagnostic tests as these mutations can reduce the sensitivity of commonly used RT-PCR assays. Therefore, there is a need to design diagnostic assays with multiple targets to enhance sensitivity. In this study, we identified a novel diagnostic target, nsp10 gene, using nanopore sequencing. Firstly, we determined the analytical sensitivity and specificity of our COVID-19-nsp10 assay. The COVID-19-nsp10 assay had the limit of detection of 74 copies/mL (95% confidence interval: 48-299 copies/mL) and did not show cross-reactivity with other respiratory viruses. Next, we determined the diagnostic performance of the COVID-19-nsp10 assay using 261 respiratory specimens, including 147 SARS-CoV-2-positive specimens belonging to ancestral strain and Alpha, Beta, Gamma, Delta, Mu, Eta, Kappa, Theta and Omicron lineages. Using the LightMix E-gene RT-PCR assay as the reference method, the diagnostic sensitivity and specificity of the COVID-19-nsp10 assay were 100%. The median Cp values for the LightMix E-gene RT-PCR and our COVID-19-nsp10 RT-PCR were 22.48 (range: 12.95-36.60) and 25.94 (range 16.37-36.87), respectively. The Cp values of the COVID-19-nsp10 RT-PCR assay correlated well with those of the LightMix E-gene RT-PCR assay (Spearman’s ρ = 0.968; P&lt;0.0001). In conclusion, nsp10 is a suitable target for SARS-CoV-2 RT-PCR assay.

Thermally-induced moisture flow in unsaturated soils is a complex coupled thermal-hydro process involving moisture flow both in vapor and liquid phases. Thermally-induced moisture flow in unsaturated sands is usually less pronounced than fine soils due to their low field capacity. It is affected by many factors, including soil density, particle size, moisture content, and gravity-induced flow. Besides, soil moisture sensors need to be highly accurate and calibrated for temperature effects in order to monitor the thermally induced moisture flow accurately. A silty sand with 35% non-plastic fines was selected to study the coupled thermo-hydro processes in a closed heat cell. The heat cell consists of two temperature-controlled heat exchanger plates at the top and bottom, heat flux sensors, moisture sensors, thermocouples, and heat conductivity sensors. The soil was prepared at various initial moisture content and tested under a constant 1-D temperature gradient. The soil moisture sensors were first calibrated in the test soil at room temperature and then at elevated temperatures. The soil moisture redistribution, temperature and thermal conductivity profiles were determined. The critical moisture content, corresponding to maximum moisture movement, was also determined. The results offer new insights into coupled moisture-heat flow in unsaturated sands.

In response to the fairness issue arising from the unequal delay of vehicles in different phases at intersections, considering the actual situation of small and variable delays for vehicles in low-saturation intersection phases, this paper proposes the concept of "sacrificing efficiency for fairness." Firstly, the universality of unfair delay phenomena at intersection phases is explained, especially at low-saturation intersections where the fluctuation in phase delays is 1.87 times higher than at other intersections. Then, a fairness evaluation index is constructed using information entropy, and the feasibility of the proposed approach is demonstrated. Subsequently, a signal optimization model that balances efficiency and fairness is proposed. Finally, the proposed model is validated through case studies, showing that it not only simultaneously considers efficiency and fairness but also has minimal impact on efficiency. Moreover, the changes to timing schemes in the efficiency model are much smaller compared to the model that only considers fairness. Sensitivity analysis reveals that the model performs better under low-saturation intersection conditions.

Developing effective trend estimators is a main method to solve the online portfolio selection problem. Although the existing portfolio strategies have demonstrated good performance through the development of various trend estimators, it is still challenging to determine in advance which estimator will yield the maximum final cumulative wealth in online portfolio selection tasks. This paper studies an online ensemble approach for online portfolio selection by leveraging the strengths of multiple trend estimators. Specifically, a return-based loss function and a cross-entropy-based loss function are first designed to evaluate the adaptiveness of different trend estimators in a financial environment. On this basis, a passive aggressive ensemble model is proposed to weigh these trend estimators within a unit simplex according to their adaptiveness. Extensive experiments are conducted on benchmark datasets from various real-world stock markets to evaluate the performance. The results show that the proposed strategy achieves the state-of-the-art performance including efficiency and cumulative return.

Glucagon-like peptide-1 (GLP-1) is an incretin hormone that acts on the pancreas to increase insulin and decrease glucagon secretion. Albuminuria is the pivotal marker for diabetic nephropathy, which is the leading microvascular complication of diabetes mellitus. Most of the previous studies mainly focused on the clinical trials of the therapeutic renal protective effect after administration of GLP-1 receptor agonists (GLP-1 RAs), not prior to administration. Therefore, this study aimed to investigate the association between fasting plasma GLP-1 levels and albuminuria before GLP-1 RA administration. A cross-sectional study was designed to evaluate the association between fasting plasma GLP-1 levels and albuminuria in patients with type 2 diabetes mellitus (T2DM). A total of 68 T2DM participants were analyzed from the data at Wonkwang University Hospital in Iksan, Korea. Logistic regression analysis was performed to evaluate the odds ratio (OR) and 95% confidence interval (CI) of the incidence of albuminuria between the GLP-1 low group (Group L) and the high group (Group H). The OR (95% CI) for the incidence of albuminuria comparing the Group L with the Group H of fasting plasma GLP-1 levels was 3.410 (1.160-10.023), p = 0.026 after adjustment for age, gender, fasting plasma glucose, HbA1c, C-peptide, the use of ACE inhibitors or ARBs, SGLT-2 inhibitors, and DPP-4 inhibitors. As a continuous variable, the OR (95% CI) for the incidence of albuminuria associated with the reduction of each 1 pmol/L in fasting plasma GLP-1 levels was 1.673 (1.173-1.870), p = 0.018, after full adjustment. This study showed the negative association between fasting plasma GLP-1 levels and the incidence of albuminuria in Korean patients with T2DM, before GLP-1 RA administration. This result suggests that endogenous GLP-1 may play a role in attenuating albuminuria.