Resection of malignant lesions in the oral and maxillofacial area causes functional and morphological defects. To recover from these defects, reconstruction surgery is needed such as a primary closure or a flap. There are advantages and disadvantages to the method of using the primary closure and the flap, and the choice of procedure is entirely up to a surgeon. The purpose of this study is to evaluate availability of primary closure in patients. For 10 years from January 2010 to May 2020, patients who recovered using flaps after removing malignant lesions from the oral cavity and those who closed the lesion using primary closure were investigated. The investigation was conducted by searching the database of the hospital. There were 85 patients who removed malignant lesions in the oral and maxillofacial area, and among them 16 patients closed the soft tissue defects using primary closure. Operation time, histologic types, stages, wound status, and period of hospitalization according to the patients' medical records were investigated retrospectively. Between the staging and the primary closure, statistically significant differences were observed between stage I and stage II patients in 13 patients using the primary closure. (P=0.046). Statistically significant differences were identified between operation time and primary closure, with an average of 4.02 hours (P=0.015). The average period of hospitality for patients who underwent primary closure was 13.4 days, compared to 26.7 days for those who underwent flap surgery. This difference was statistically significant (P=0.0003). This study evaluated the use of primary closure in patients who underwent resection of malignant lesions in the oral and maxillofacial area. Although the majority of patients underwent reconstruction with flaps, our results showed that primary closure can be a viable option for certain patients with early-stage lesions. Therefore, oral and maxillofacial surgeons should carefully consider various evaluation criteria and select appropriate reconstruction methods to optimize functional and aesthetic outcomes for each patient.

With the increasing prominence of renewable energy sources providing flexibility to the power grid, there is a growing recognition of the need to expand virtual Energy Storage Systems (ESS) to replace traditional ESS, which faces challenges in terms of supply and scalability. Grid-connected microgrids can supply power stably and are being built, so they can be used as virtual ESS to provide flexibility to the power system. This study proposes an approach to determine the optimal Power Conversion System (PCS) and battery capacity for a Virtual Energy Storage System(VEES) based on a grid-connected microgrid incorporating Photovoltaic (PV) and ESS. In this paper, it is assumed that microgrids can provide flexibility to the grid by participating in the energy trading market, there are corresponding profits and penalties for order. Numerical examples are performed to demonstrate the effectiveness of the proposed method.

Background and Objectives: Chemokines have various biological functions and potential roles in the development or progression of neuroinflammatory diseases. However, the specific pathogenic roles of chemokines in age-related macular degeneration (AMD), the leading cause of blindness in older individuals, remain elusive. Chemokines interact with their receptors expressed in the endothelium and on leukocytes. The sulfation of tyrosine residues in chemokine receptors increases the strength of ligand–receptor interaction and modulates signaling. Therefore, in the present study, we aimed to construct a human recombinant sulfated CXCR3 peptide trap (hCXCR3-S2) and mouse recombinant sulfated CXCR3 peptide trap (mCXCR3-S2) to demonstrate in vivo effects in preventing choroidal neovascularization and chemotaxis. Materials and Methods: First, the effect of hCXCR3-S was validated in vitro. Interestingly, hCXCR3-S2 inhibited the migration and invasion of two human cancer cell lines. Subsequently, the in vivo efficacy of mCXCR3-S2 was investigated using a mouse model of neovascular AMD. Results: Intravitreal injection of mCXCR3-S2 attenuated choroidal neovascularization and macrophage recruitment in neovascular lesions. These in vitro and in vivo effects were significantly stronger with CXCR3-S2 than with wild-type CXCR3 peptides. Conclusion: These findings demonstrate that the sulfated form of the CXCR3 peptide trap is a valuable tool that could be supplemented with antivascular endothelial growth factors in AMD treatment.

Rapeseed (Brassica napus L.) is one of the most oil crop, and its commercial value is contingent upon its agronomic characteristics and oil quality. In this study, 73,226 single nucleotide polymorphisms (SNPs) across 95 rapeseed mutant lines derived from gamma rays and their original cultivar (‘Tamra’) obtained from genotyping-by-sequencing (GBS) was investigated gene ontology (GO) analysis and genome-wide association study (GWAS). GWAS was conducted on agronomic (plant height, ear length, thousand seed weight and seed yield) and oil (fatty acid and crude fat) traits. GO analysis showed that many genes displaying SNPs were involved in cellular processes, intracellular anatomical structures and organic cyclic compound binding. A total of 149 significant SNPs were associated with the agronomic traits (76 SNPs) and oil traits (73 SNPs). Bna.A05p02350D (SFGH) and Bna.C02p22490D (MDN1) were selected as novel candid genes for thousand seed weight. In addition, Bna.C03p14350D (EXO70) and Bna.A09p05630D (PI4Kα1) were selected as novel candidate genes for the erucic acid and crude fat content, respectively. These findings could facilitate the identification of optimal genotypes for breeding new cultivars, and association studies represent an economically efficient tool for mutant screening and the selection of elite rapeseed-breeding lines.

Non-alcoholic steatohepatitis (NASH) is diagnosed by the occurrence of fat buildup, inflammation, and fibrotic changes within the liver. NASH has the capacity to proceed to the advancement of decompensated cirrhosis and carcinoma by inflammation and oxidative stress. Although Agrimonia pilosa has traditionally been used medicinal purposes, its effects on the liver remains incompletely elucidated. In this research, we assessed the therapeutic outcomes of Agrimonia pilosa extract (APE) on free fatty acid (FFA)-treated HepG2 cellular hepatic steatosis and in a choline-deficient, L-amino acid-defined, high-fat diet with 0.1% methionine (CDAHFD)-induced NASH mouse model. In FFA-treated cells, APE inhibited intracellular lipid accumulation, and regulated the mRNA and protein expressions of modulators of fatty acid (FA) synthesis as well as FA oxidation proteins, through down-regulation of the AMP-activated protein kinase/sirtuin 1 signaling pathway. In the CDAHFD-induced NASH mouse model, APE significantly enhanced liver histology and serum levels of liver damage. APE also significantly attenuated hepatic expression of mRNA and proteins related to FA synthesis, inflammation, and fibrosis. Furthermore, APE mitigated the expression levels of oxidative stress and endoplasmic reticulum stress. Overall, these discoveries indicate that Agrimonia pilosa has the potential to treat NASH by regulating hepatic lipid metabolism, alleviating inflammation, and mitigating oxidative stress.

eDNA extracted from the gut contents of filter feeders with unique feeding habits can be used to identify biodiversity in aquatic ecosystems. In this study, we used eDNA from the gut contents of the clam Corbicula fluminea to examine estuarine ecosystem biodiversity. The field survey was conducted at three study sites in the Nakdong River Estuary, which is characterised by closed estuarine features resulting from the presence of an estuarine barrage. The collected C. fluminea samples were dissected to separate the gut contents, and the extracted eDNA was amplified using the 18S V9 primer targeting all eukaryotes. The amplified DNA was sequenced using next generation sequencing (NGS) techniques, and BLASTn was performed based on the NCBI database. We obtained 21 unique operational taxonomic units (OTUs), including fish (approximately 9.52%), copepods (approximately 14.29%), and green algae (approximately 23.81%), which represented a wide range of habitats such as marine, brackish, freshwater, and terrestrial environments. These results suggest that various organisms living in aquatic ecosystems can be identified through eDNA from the gut contents of C. fluminea and support the potential application of bivalves as eDNA samplers in diverse aquatic ecosystems.

Additive manufactured interlocking structures often face challenges in achieving suitable joinability due to thermal deformation. This issue becomes particularly interesting when fabricating structures that require high density but not fully connected layers, such as soft-magnetic materials. This study focuses on systematical investigation of the deformation as a function of finger thickness and building direction in model interlocking structure. In the perpendicular direction to the build plate, the distortions of joint part were significantly reduced due to lower thermal stress. In addition, the effect of laser power and scan speed on interlocking structure are systematically discussed. Additionally, through stress and thermal simulations of additive manufacturing process, it was confirmed that the compensated model can enhance the joinability of interlocking structures. These findings contribute to the development of optimal design for additive manufactured parts of soft magnetic materials such as stators in electric motor components, which needs insulations and density.

The aim of this study is to evaluate the optimal conditions of membrane filtration process. Both laboratory test and pilot-scale test were conducted to examine a treated water on blending water. The water sample were prepared by blending a raw water and the effluent water filtered through an organic membrane. The optimal efficiency in the treatment of water quality at the lab-scale test was generated under conditions of flux at 2.0 m³/m²∙day, the blending ratio of 4:1, and the optimal dosage of coagulant at 20 ppm. The pilot-scale test resulted in that the optimal efficiency was obtained under conditions of flux at 2.0 m³/m²∙day and the blending ratio of 6.0:1. However, the different results between lab-scale and pilot-scale tests on the optimal dosage of coagulant implied that it is difficult to achieve the stable condition of process operation at the low level of coagulant. In summary, the results indicated that, in the combination process of organic membrane and ceramic membrane, the recovery efficiency was achieved above the level of 98.4 %. Compared to 92.1 % in a single organic membrane process, the combination process is 6.3 % more efficient than the single one. This combination process of water treatment lead to stable recovery rates by the optimal input of dosage, less pollution load to water, and a stabilized filtration system.

The phenolics concentrations of rapeseed are important because they are antinutritional com-pound or directly positive related to antioxidant actives. In this study, single nucleotide poly-morphisms (SNPs) identified from genotyping-by-sequencing (GBS), and genome-wide associa-tion study of phenolic contents were investigated in 95 rapeseed mutant lines derived from gamma rays and their original cultivar. A total of 3,196,318 SNPs were detected, identifying a set of 70,208 union SNPs used to perform association studies. Six phenolics and glucosinolate (pro-goitrin) were identified, sinapine was the major phenolic compound (91.2–99.2%) in all geno-types. The association study was conducted for six phenolic compounds, progoitrin, total sinap-ine content (TSC), total phenolic content (TPC) and seed yield. The association study identified 241 SNPs that were significantly associated with six phenolic compounds, progoitrin, TSC and TPC. Based on the detected SNP markers, BnaA06g31740D, a gene associated progoitrin, BnaC-nng39930D, a gene associated trans-sinapine 1, BnaA07g31720D, a gene associated trans-sinapine 2, BnaC03g31950D and BnaA06g09180D, a gene associated TSC, and BnaAnng27700D, a gene associ-ated TPC, were selected as candidate genes. The SNP makers associated major phenolic com-pounds identified and could be used as targets for breeding programs aimed at improving anti-oxidant contents and reducing antinutritional components.

Static and dynamic analysis of website security risks is generally used for website security meas-urements. The website security measurements method recently proposed includes similarity hash-based website security risk analysis and machine learning-based website security risk anal-ysis. In this study, a method that can be performed through information disclosed on the Internet was proposed to measure the risk of a website. DNS information, IP information, and website history information are required to measure the risk of a website. In addition, global traffic rank-ing, malicious code distribution history, and HTTP access status can be checked in the website history information. In this study, information related to the security risk of websites in a total of 2,000 domains was collected and analyzed in 1,000 normal and malicious domains. Through the experiment results, 11 open information collection items were selected to measure the security risk of the website. This study presented the possibility of using public information collection to measure website security risk.

The common dolphin is the second most bycaught species in Korean waters. To provide key information about their habitat boundaries and hotspots for spatial conservation and management, the spatial use of this species was examined using data obtained from sighting and bycatch surveys of cetacean during the past 20 years. The 95% minimum convex polygon and 95% density contour of fixed kernel suggested that the boundary of home range of common dolphins is limited to the coastal region (Busan-Sokcho) of the East Sea/Sea of Japan. From 50% density contours dawn by kernel density estimation, it was suggested that their hotspots are around the cost of Ulsan-Pohang, Doghae, and Sokcho within the home range. Common dolphins are not at all distributed in the Yellow Sea. Hence, shallow waters, such as the coastal region of the Yellow Sea, are not suitable habitats for common dolphins.

This paper examines the moral community thesis in the secular context of China. Using multilevel logistic regression, we test (1) whether both individual- (measured by affiliation with institutional religion) and aggregate-level religiosity (measured by the number of religious sites per 10,000 people in province) are inversely related to law and rule violations at the individual level and (2) whether the province-level religiosity enhances the inverse relationship between individual religiosity and the deviant behaviors. Results from analyzing data from the 2010 China General Social Survey and the Spatial Explorer of Religions show that both individual- and aggregate-level religiosity are inversely related to the odds of violating the law and various rules of government, transportation, workplace, and other organizations. However, the cross-level interactions are not significant across models, indicating that the contextual religiosity does not increase the effect of individual-level religiosity on deviance. Implications of findings for the moral community thesis are discussed.

Intrahepatic cholangiocarcinoma (ICCA) is a malignant epithelial neoplasm characterized by biliary differentiation within the liver. ICCA is molecularly heterogeneous and exhibits a broad spectrum of histopathological features. It is a highly aggressive carcinoma with high mortality and poor survival rates. ICCAs are classified into two main subtypes: small duct type and large duct types. These two tumor types have different cell origins and clinicopathological features. ICCAs are characterized by numerous molecular alterations, including mutations in KRAS, TP53, IDH1/2, ARID1A, BAP1, BRAF, SAMD4, and EGFR, and FGFR2 fusion. Two main molecular subtypes–inflammation and proliferation–have been proposed. Recent advances in high-throughput assays using next-generation sequencing have improved our understanding of ICCA pathogenesis and molecular genetics. The diagnosis of ICCA poses a significant challenge for pathologists because of its varied morphologies and phenotypes. Accurate diagnosis of ICCA is essential for effective patient management and prognostic determination. This article provides an updated overview of ICCA pathology, focusing particularly on molecular features, histological subtypes, and diagnostic approaches.

We have identified a new human voltage-gated potassium channel (hKv1.3) blocker, NnK-1, in the jellyfish Nemopilema nomurai, based on its genomic information. The gene sequence encoding NnK-1 contains 5,408 base pairs, with five introns and six exons. The coding sequence of the NnK-1 precursor is 894 nucleotides long and encodes 297 amino acids, containing five presumptive ShK-like peptides. An electrophysiological assay demonstrated that the chemically synthesized fifth peptide, NnK-1, is an effective hKv1.3 blocker. A multiple sequence alignment with cnidarian Shk-like peptides, which have Kv1.3-blocking activity, revealed that four residues (3Asp, 25Lys, 33Lys, and 34Thr) of NnK-1, together with six cysteine residues, are conserved. Therefore, we hypothesize that these four residues are crucial for the binding of the toxins to voltage-gated potassium channels.

This study examines the causal relationships between interest rates in the Korean financial market using a vector error correction model (VECM) and a Bayesian network. The Bayesian network, a novel approach in this context, identifies two distinct transmission channels: one led by call rates (reflecting monetary policy) and another by 10-year Treasury bond yields (reflecting fiscal policy). While the call rate channel aligns with traditional views, affecting bank lending rates, corporate bond spreads, and commercial paper rates, the 10-year Treasury yield channel highlights a separate fiscal policy transmission mechanism, influencing commercial paper rates indirectly through 30-year Treasury yields and directly impacting merchant bank lending rates. This finding suggests that fiscal intervention could potentially interfere with monetary policy, emphasizing the need for coordinated macroeconomic policy measures. The study also emphasizes the role of 10-year Treasury bonds as a benchmark in the Korean bond market, reflecting medium- to long-term economic outlooks and serving as the underlying asset for various derivatives.

This study evaluated the effects of high-temperature and high-pressure treatment on the antioxidant and anti-inflammatory activities of carrot extracts. The total polyphenol and flavonoid content of heated carrot extract increased as the heating temperature increased, with 403.93 mg GAE/100 g and 53.14 mg CE/100 g at 150°C. DPPH and ABTs radical scavenging activity (IC50) of heated carrot extract also increased as the heating temperature increased, with 4.65 mg/mL and 7.31 mg/mL, respectively, at 150°C. The reducing power increased with the heating temperature. Heated carrot extract did not exhibit any temperature- or concentration-dependent cytotoxicity. Nitric oxide (NO) generation was suppressed as the heating temperature and NO production increased. The heated carrot extract showed a decrease in the production of dose-dependent TNF-α, IL-1β, and IL-6 compared to the control group. The above results show that heated carrot extract had effective antioxidant and anti-inflammatory activities.

Malnutrition and cognitive dysfunction are typical features of alcoholic liver disease (ALD) and are correlated with the development of complications. The aim of this study is to explore the effect of nutritional state and diet on cognitive function in ALD. A total of 43 patients with compensated alcoholic cirrhosis were enrolled, and neuropsychological test was assessed according to body mass index (BMI, <22 and ≥22). In the ALD animal study, mice were divided into 5 groups (n=9/group; normal liquid, 5% EtOH+regular liquid, 5% EtOH+high-carbohydrate liquid, 5% EtOH+high-fat liquid, and 5% EtOH+high-protein liquid diet) and fed the same calories for 8-week. To assess cognitive function, we performed T-maze studies weekly before/after alcohol binging. In cognitive function (BMI <22 /≥22), language score of Korea mini-mental state (7.4±1.4/7.9±0.4), Rey-complex figure (72.0±25.9/58.4±33.6), Boston naming (11.7±2.7/13.0±1.8), forward digit span (6.7±1.8/7.5±1.6), Korean Color Word Stroop (24.2±26.5/43.6±32.4), and interference score (33.9±31.9/52.3±33.9) revealed significant differences. In the T-maze test, alcohol significantly delayed the time to reach food, and binge drinking provided a temporary recovery in cognition. The alcohol-induced delay was significantly reduced in the high-carbohydrate and high-fat diet groups. Synaptic function exhibited no changes in all groups. Cognitive dysfunction is affected by nutritional status and diet in ALD.

Croton L. (Euphorbiaceae) is a very specious genus and consists of about 1,250 species, mainly distributed in tropical Asia and China. The first complete plastome sequence from the genus, Croton tiglium, is reported in this study (NCBI acc. No. MH394334). The plastome is 150,021 bp in length. The lengths of LSC and SSC are 111,654 bp and 18,167 bp, respectively. However, the length of the IR region is only 10,100 bp and includes only four rrn and four trn genes, and a small part of the ycf1 gene. We propose two-step IR contractions to explain this unique IR region of the C. tiglium plastome. First, the IR contracted from rps19-rpl2 to ycf2-trnL-CAA on the LSC/IRb boundary. Second, the IR contracted from ycf2-trnL-CAA to rrn16-trnV-GAC on the LSC/IRa boundary. In addition, duplicated copies of psaI genes were discovered in the C. tiglium plastome. Both copies were located side by side between accD and ycf4 genes, but one copy was pseudogenized because of a five-basepair (TAGCT) insertion in the middle of the gene following frameshift mutation. The plastome contains 112 genes, of which 78 are protein-coding genes, 30 are tRNA genes, and four are rRNA genes. Sixteen genes contain one intron and two genes have two introns. The infA gene is lost. Twelve large repeats were detected in the plastome. All large repeats are located in the LSC region. Also, 272 simple sequence repeats (SSRs) were identified. The penta-SSRs accounted for 45% of total SSRs, followed by mono- (32%), di- (12%), tetra (6%) and tri-SSRs (5%). Most of them were distributed in the large single copy (LSC) region (85%). In addition, 76% of the SSRs were located in the intergenic spacer (IGS). Phylogenetic analysis suggested that C. tiglium is a sister group of Jatropha curcas with 100% bootstrap support. Seven Euphorbiaceae species formed one clade with 100% bootstrap support.

This paper first introduces the main classification of brain diseases and the main causes of these diseases. It is followed by wavelet analysis, which is a mathematical function or wave-like pattern used to transform data, which can decompose the signal into different wavelet functions, each of which is related to a specific scale or frequency. Wavelet analysis has been applied in many fields such as image processing, data analysis and engineering. In addition, wavelet is also used in the analysis of biological signals. Wavelet analysis breaks down brain signals, such as EEG or fMRI data, into various frequency components at different scales. Wavelet analysis provides time-frequency localization. Pattern recognition can be enhanced by isolating salient features in the data. Wavelet denoising can effectively separate noise from underlying brain signals. Wavelet denoising usually adopts threshold method. Wavelet analysis can enhance pattern recognition by isolating salient features in the data. Researchers can train machine learning models based on these wavelet-derived features to recognize specific patterns associated with different neurological disorders. Wavelet analysis can track these changes by continuously evaluating the frequency content of the neuroimage data over time. Through continuous efforts, wavelet theory and technology have become valuable tools in the field of neuroscience and brain disease research.

In this paper, we investigate the new degenerate Daehee polynomials and numbers which are called the degenerate Daehee polynomials of the second kind, and derive some new and interesting identities and properties of those polynomials.

Flammability was evaluated and the results showed the values of critical flux at extinguishment (CFE) as 49.5kW/㎡ on average, total heat release (Qt) as 0.21MJ on average, and peak heat release rate (Qp) as 0.66kW on average, which satisfied all of the thresholds presented by the IMO. Therefore, flame-retardant plywood, of which the flame-retardant performance was evaluated, was determined to be an applicable finishing material that satisfies fire safety standards.

Oscillometric blood pressure (BP) devices currently estimate a single point but do not identify fluctuations in BP or distinguish them from variations in response to physiological properties. In this paper, to analyze BP normality based on oscillometric measurements, we use statistical approaches including kurtosis, skewness, Kolmogorov-Smirnov, and correlation tests. Then, to mitigate uncertainties, we use a deep neural network (DNN) to determine the confidence limits (CLs) of BP measurements based on their normality. The proposed DNN regression model decreases the standard deviation of error (SDE) of the mean error (ME) and the mean absolute error (MAE) and reduces the uncertainty of the CLs and SDEs of the proposed technique. We validate the normality of the distribution of the BP estimation distribution which fits the Gaussian distribution very well. We use a rank test in the DNN regression model to demonstrate the independence of the artificial SBP and DBP estimations. First, we perform statistical tests to verify the normality of the BP measurements for individual subjects. The proposed methodology provides accurate BP estimations and reduces the uncertainties associated with the CLs and SDEs based on the DNN regression estimator.

Standardized protocols were specifically designed and developed for clinical information collection and obtaining trio genomic information from infants affected with congenital anomalies (CA) and their parents, as well as securing human biological resources. Two large areas of these protocols include clinical and genomic information collection on CA which were difficult to diagnose using pre-existing screening methods. The following are three essential items for the clinical information collection protocol: establishment of a consent system for collecting and utilizing research resources, establishment of criteria for target patient selection, and collection of clinical and epidemiological information. A total of 138 cases consisting of 45 families of infants with CA and their parent trios have provided human-derived resources and genomic information. Whole genome sequencing data have been generated for all participants, and standardized protocols for resource collection and manufacturing have been developed. Phenotype information according to the Human Phenotype Ontology term and major test findings were recorded. It is important to keep updating and recording clinical symptoms and genetic diagnosis that are newly added or changed over time. The unique significance of this study is to develop a protocol that enables long-term tracking by adding growth and development tests that reflect important characteristics of newborns. By using these clinical and genetic information collection protocols for CA, it will be possible to establish an essential platform for early genetic diagnosis and diagnostic research, and further present new genetic diagnostic guidelines in the near future.

Background: Albumin has a pivotal role in the homeostasis of osmotic pressure and is associated with cardiovascular, nephrotic, hepatic, and nutritional diseases. The detection of hypoalbuminemia is a cornerstone for diagnosis of hidden diseases and patient deterioration. We developed and validated a deep-learning-based model (DLM) for detection of hypoalbuminemia using electrocardiography (ECG). Methods: This historical cohort study included data from consecutive patients from two hospitals. The patient data in one hospital were divided into development (82,499 ECGs from 54,248 patients) and internal validation (20,664 ECGs from 20,664 patients) datasets, whereas the patient data in the other hospital were included in only an external validation (37,421 ECGs from 37,421 patients) dataset. An DLM was developed using a 12-lead ECG signal, age, and sex from the development dataset. The endpoint was hypoalbuminemia, defined by serum albumin concentration below 3.5 g/dL. Results: During the internal and external validations, the areas under the receiver operating characteristic curve of the DLM for the detection of hypoalbuminemia were 0.887 (0.877–0.897) and 0.888 (0.880–0.896), respectively. Among the 27,400 individuals without hypoalbuminemia at the initial laboratory exam, those identified by the DLM as higher-risk patients had a significantly larger change in developing hypoalbuminemia than those in the low-risk group (7.09% vs. 1.01%, p < 0.001) during 24 months. The sensitivity map showed that the DLM focused on the T wave and QRS complex for the detection of hypoalbuminemia. Conclusions: The DLM exhibited a high accuracy for hypoalbuminemia detection and prediction using 12-, 6-, and single-lead ECGs.

In recent decades, with the ever-growing scale of video data, near-duplicate videos continue to emerge. Data quality issue caused by near-duplicate videos is becoming more and more prominent, which has affected the application of normal videos. Although current studies on near-duplicate video detection can be helpful to uncover data quality issues for videos, they still lack a process of automatic merging for the video data represented by high-dimensional features, which are difficult to automatically clean the near-duplicate videos to improve data quality for video datasets. At present, there are few studies on near-duplicate video data cleaning. The existing studies have the sensitive problems of video data orderliness and clustering initial center under a condition that prior distribution is unknown, which seriously affect the accuracy of near-duplicate video data cleaning. To address the above issues, an automatic near-duplicate video data cleaning method based on a consistent feature hash ring is proposed in this paper. First, a residual network with convolutional block attention modules, a long short-term memory deep network, and an attention model are integrated to construct an RCLA deep network with the multi-headed attention mechanism to extract spatiotemporal features of video data. Then, a consistent feature hash ring is constructed, which can effectively alleviate the sensitivity of video data orderliness while providing a condition of near-duplicate video merging. To reduce the sensitivity of the initial cluster centers to results of near-duplicate video cleansing, an optimized feature distance-means clustering algorithm is constructed by utilizing a mountain peak function on a consistent feature hash ring, which can implement automatic cleaning of near-duplicate video data. Finally, experiments are conducted based on a commonly used dataset named CC_WEB_VIDEO and a coal mining video dataset. Compared with some existing works, simulation results demonstrate that the performance of the proposed method.

The runtime environment is an important concern for self-adaptive systems (SASs). Although researchers have proposed many approaches for developing SASs that address the issue of uncertain runtime environments, the understanding of these environments varies depending on the objectives, perspectives, and assumptions of the research. Thus, the current understanding of the environment in SAS development is ambiguous and abstract. To make this understanding more concrete, we describe the landscape in this area through a systematic literature review (SLR). We examined 128 primary studies and 14 unique environment models. We investigated concepts of the environment depicted in the primary studies and the proposed environment models based on their ability to aid in understanding. This illustrates the characteristics of the SAS environment, the associated emerging environmental uncertainties, and what is expressed in the existing environment models. This paper makes explicit the implicit understanding about the environment made by the SAS research community and organizes and visualizes them.

Recent scholarship highlights the significant environmental impact of the expanding hydraulic fracturing industry, necessitating up-to-date, comprehensive, national-scale assessments. Addressing this gap, this literature review provides a thorough analysis of the contamination and induced seismicity associated with shale-gas hydraulic fracturing in the United States. Employing systematic reviews of literature and federal reports up until July 2023, this study reveals multiple areas of concern. Notably, water and soil contamination, seismic activity, and air pollution are identified as significant challenges linked to shale gas extraction. However, ongoing studies are actively exploring remediation strategies, including advancements in monitoring and treatment technologies, aimed at mitigating the impact of contamination. These findings underscore the need for stringent regulations, continuous research, and effective management practices. This work emphasizes the importance of a collaborative approach that leverages field studies, experimental investigations, and computational advancements to ensure the responsible development of shale gas resources.

This study presents structural analysis and optimization for the lightweight design of a buoyant rotor-type permanent magnet (BRPM) generator, which was first presented in Bang (2010), and compares its structural performances to a conventional generator with a spoke arm-type rotor and stator. The main benefit of a BRPM is that it can be realized as a bearing-less drive system, free from the mechanical failure of rotor bearings, by using a buoyant rotor. Also, the deformation of a generator by blade vibration can be effectively suppressed using joint couplings between the blades and the rotor. For the design optimization, the objective is set as the mass of the rotor and the stator, and the maximum deformation of the airgap clearance between the rotor and the stator by external forces is constrained below 10% of the gap width. The commercial software Optistruct is used for the analysis and optimization. In this investigation, the analysis and optimization are conducted for a 10 MW wind turbine generator. However, the proposed methods can be extended to larger generator designs without requiring considerable modification. The mass of the opti-mized 10MW BRPM generator is 160.7 tons (19.3 tons for the rotor and 141.4 tons for the stator) while that of an optimized conventional spoke arm-type generator is obtained as 325.6 tons.

Today’s export-based manufacturers face the need to implement green supply chains more efficiently in order to overcome environmental barriers in increasingly competitive export markets and to improve export performance. This study examines the structural relationship between environmental collaboration, green innovation capacity, and performance based on the findings of previous studies in order to identify the factors affecting the green supply chain management (GSCM) performance of Korean export-based manufacturers. The study finds that environmental collaboration in the green supply chain environment is an important driver of green innovation capacity for export-based Korean manufacturers. It also finds that green innovation capacity has a positive effect on export performance through environmental performance. This study establishes a theoretical basis for the systematic study of the structural mechanisms of green supply chains and suggests strategic directions for export-based manufacturing firms’ successful GSCM implementation.

With continued technological innovation in the fields of mixed reality (MR), wearable-type MR devices, such as helmets, have been released and are frequently used in various fields, such as entertainment, training, and education. However, because each product has different parts and specifications in terms of the design and manufacturing process, users feel that the virtual objects overlaying real environments in MR are visualized differently depending on the scale and color used by the MR device. In this paper, we compare the effect of scale and color parameters on users’ perception in using different types of MR devices to improve MR experience. We conducted two experiments (scale and color), and our experimental study showed that the subjects who participated in the scale perception experiment clearly tended to underestimate virtual objects, compared with real objects, and overestimate color in MR environments. [MM1]Please confirm meaning.

This study aims to identify the factors determining the income of forestry household in South Korea. We examine an empirical analysis using 3-year panel data conducted by the Korea Forest Service charged with maintaining South Korea's forest lands. The hypothesized factors determining the income of forestry household are classified into four types of assets and three types of livelihood strategies. We divided the income of forestry household (IFH) into three elements: forestry income (FI), non-forestry income (NFI), and transfer income (TI). We assessed the influences of household assets and livelihood strategies on each income. A random effect model was used as a statistical analysis with valid 979 of forestry household for three years. We found that household head's age, labor hours, savings, business category, cultivated land size, and region are significantly associated with IFH. Also, FI is influenced by labor capacity, cultivated size, business category, forestry business portfolio, and region while NFI is determined by household head's age, household head's gender, forestry business portfolio, and savings. TI is affected by household head's age, household head's education level, forestry business portfolios, savings, and region. The effect sizes and directions vary across different types of income (IFH, FI, NFI, and TI). The findings show that forestry in South Korea is highly dependent on sustainable assets and strategies. It is therefore expected that the effectiveness of forest policies to increase the income of forestry household would be differed by the source of each income. The results of this study draw attention to the need for an income support policy that should consider the characteristics of household assets and livelihood strategies in order to enhance IFH in South Korea.

A real-time flight simulation tool is proposed using a Virtual Reality Head-Mounted Display (VR-HMD) for airships operating in beyond the line-of-sight (BLOS) conditions. Particularly, the VR-HMD is developed for stratospheric airships flying at low/high altitudes. The proposed flight simulation tool uses the corresponding aerodynamics characteristics of the airship, the buoyancy effect, mass balance, added mass, propulsion contributions and ground reactions in the FlightGear Fight Simulator (FGFS). The VR headset has been connected to the FGFS along with the radio controller containing the real-time orientation/state of each button that is also simulated to provide better situational awareness and a Head-Up Display (HUD) that has been developed to provide the required flight data. In this work, a system was developed to connect the FGFS and the VR-capable graphics engine, Unity, to a PC and a wireless VR-HMD in real-time with minimal lag between data transmission. A balance was found for FGFS to write to a CSV file at a period of 0.01s. For Unity, the file was read every frame which translates to around 0.0167s (60 Hz). A test procedure was also conducted with a similar rating technique based on the NASA TLX questionnaire that identifies the pilot’s spare mental capacity when completing an assigned task to assure the comfortability of the proposed VR-HMD. Accordingly, a comparison has been made for the aircraft control using the desktop simulator and the VR-HMD tool. Results, showed that the current iteration of the system is ideal to train pilots on using similar systems in a safe and immersive environment. Furthermore, such an advanced portable system may even increase the situational awareness of pilots and allow them to complete a sizeable portion of actual flight tests with the same data transmission procedures in simulation. The resulting VR-HMD flight simulator is also conceived to express the ground control station (GCS) concept and transmit flight information as well as the point of view (POV) visuals in real-time using the real environment broadcasted using an onboard camera.

The purpose of this study was to identify subgroups of quality of life (QOL) changes in breast cancer survivors (BCS) and to determine factors associated with subgroups of consistently low or deteriorated QOL. We enrolled 101 women recently diagnosed with breast cancer in South Korea and asked them to complete a questionnaire at baseline (within 1 month of diagnosis), 1 year later (Year 1), 2 years later (Year 2), and 3 years later (Year 3). We assessed QOL using the global QOL subscale from the EORTC QLQ-C30. We defined low QOL as a global QOL score 10 points below the mean score of the general population. Based on low QOL as defined in this study, we identified subgroups of QOL changes over 3 years. We identified four subgroups of QOL changes: improved (47.4%), stable (30%), continuously low (8.8%), and deteriorated (13.8%) and considered the last two categories (22.6%) as poor QOL. Logistic regression analyses demonstrated that significant determinants of poor QOL were insomnia at Year 1, fatigue and anxiety at Year 2, and fatigue, depression, and comorbidity at Year 3. In conclusion, persistent symptoms of insomnia, fatigue, anxiety, depression, and comorbidity are potential risk factors for poor QOL in BCS.

Considering the isotropic release process of nanoelectromechanical systems (NEMS), defining the active region of NEM memory switches is one of the most challenging process technologies for the implementation of monolithic-three-dimensional (M3D) CMOS-NEM hybrid circuits. In this paper, we propose a novel encapsulation method of NEM memory switches. It uses alumina (Al2O3) passivation layers which are fully compatible with CMOS baseline process. The Al2O3 bottom passivation layer can protect intermetal dielectric (IMD) and metal interconnection layers from vapor hydrogen fluoride (HF) etch process. Thus, the controllable formation of the cavity for the mechanical movement of NEM memory switches can be achieved without causing any damage to CMOS baseline circuits as well as metal interconnection lines. As a result, NEM memory switches can be located in any places and metal layers of an M3D CMOS-NEM hybrid chip, which makes circuit design easier and more volume-efficient. The feasibility of our proposed method is verified based on experimental results.

Background: Little information exists regarding the differences in the clinical and laboratory characteristics of Kikuchi-Fujimoto disease (KFD) according to age. Objective: To evaluate the clinical and laboratory characteristics of KFD according to age. Methods: We retrospectively evaluated patients diagnosed with KFD at Pusan National University Hospital between 2010 and 2020. Results: Eighty patients (46 children and 34 adults) with a mean age of 21.5 ± 11.8 years (range, 3–49 years) were included in the study. Among children, the male sex ratio was higher, in adults, the female sex ratio was higher. Fever, tenderness in the lymph node, and skin rashes were more common in children, while myalgia and weight loss were more common in adults. In children, the recurrence rate was significantly higher among boys than among girls (15.8% vs 0.0%, P=0.001). EBV and ANA positivity rates were higher in boys than in girls. In adults, the recurrence rate was significantly higher in women than in men (18.2% vs 0.0%, P=0.005). ANA positivity rates were higher in women than in men. Conclusion: The clinical features, laboratory findings, and recurrence of KFD may differ depending on age and sex. Clinicians should be aware of this.

Background: In long-term care facilities, there are many residents who do not have the ability to seek shelter by themselves in the case of an emergency. Thus, it is extremely important that the staff of nursing homes are equipped with correct disaster prevention concepts, emergency survival responses, and hazard mitigation measures. Purpose: Discuss the intervention effectiveness of different fire prevention and emergency response trainings at nursing homes and the relationship and predictivity of awareness to self-efficacy. Method: Recruit staff from two nursing homes through purposive sampling, using a two-team pre-and post-test design to collect results from 41 individuals in the experiment group and 40 individuals in the control group. The research tool is the “Nursing Home Fire Prevention and Emergency Response Awareness and Self-Efficacy Scale,” to compare the effectiveness of advanced and general fire safety trainings. Result: After receiving improved advanced fire safety training, the total score and the result of the experiment group on fire prevention and emergency response awareness and self-efficacy had both performed better than the control group who received general fire safety training (p < .001); fire prevention and emergency response awareness has significant and positive correlation with self-efficacy (r=.601, p < .001), and awareness is a significant predictor variable to self-efficacy (p < .001). Conclusion/Practical Application: This study finds that the key to improving learning effectiveness includes adding fire science concept chapter when creating fire safety training material in order to strengthen basic awareness; fire safety training should comprehensively introduce all related duty responsibilities of staff fire defense formation, in turn enabling mutual responsive support for the needs of the site; also, to become familiarized with the knowledge requires appropriate frequency of training and enhancing the staff’s awareness to fire prevention and emergency response, which is the most important key of learning effectiveness.

Reducing sedentary behaviours can help prevent non-communicable diseases, particularly among young adolescents with long term illnesses or disabilities (LTID). Much of young people’s voluntary sedentary time is related to screen-time behaviours (STBs) such as TV viewing, playing computer games, and using the computer for other activities. Although public health data on adolescents’ STB is growing, information about adolescents with LTID is currently lacking in a European context. The purpose of this study is to compare time on STBs between adolescents with and without LTID in European Countries through the HBSC 2013/14 study. Young adolescents (n = 61,329; boys 47.8%) from 15 European countries reported the time spent on TV viewing, playing computer games, and using the computer for other purposes on weekdays and the weekend. STBs were dichotomised based on international recommendations of less than 2 h per day, and Chi-square tests of independence were performed to investigate differences. STB time was combined to produce a sum score as dependent variable in multiple analysis of covariance with age and family affluence as covariates. There were statistically significant differences in computer gaming among boys and other computer use among girls for both weekdays and weekends, whereby adolescents with LTID reported higher use. In addition, both boys and girls with LTID spent more time on STBs than their same sex peers without LTID (Boys, F = 28.17, p < 0.001; Girls, F = 9.60, p = 0.002). The results of this study indicate a need for preventive strategies to address high levels of STB among young adolescents with LTID and reduce the risk of poor health outcomes associated with higher levels of sedentary behaviour.

Edge computing reduces the response time of real-time services with handling dynamic traffics reliably. Edge servers with limited resources utilize container technology that provides a lightweight execution environment. When deploying containers in edge servers, a container image is required and is downloaded from a remote registry. Therefore, these operations are dependent on network overhead between the container deployment system and the remote registry. Through motivation experiments, we show that container pooling time increases in proportion to physical distance and has characteristics that vary flexibly depending on runtime time. In this study, we define a system model for high-speed registry deployment in this edge system and propose a clustering technique into k groups based on the network overhead and affinity of the regionally distributed edge servers that make up the edge system. Also, considering idle resources, we propose a technique to deploy a registry after electing a leader for each cluster. A simulation experiment is conducted to verify the performance of the proposed technique and shows that performance improvement can be achieved regardless of the number of edge servers and the k value.

In wireless sensor networks (WSNs), each sensor node can estimate the global parameter from the local data in distributed manner. This paper proposed a robust diffusion estimation algorithm based on minimum error entropy criterion with self-adjusting step-size, which are referred to as diffusion MEE-SAS (DMEE-SAS) algorithm. The DMEE-SAS algorithm has fast speed of convergence and is robust against non-Gaussian noise in the measurements. The detailed performance analysis of the DMEE-SAS algorithm is performed. By combining the DMEE-SAS with diffusion minimum error entropy (DMEE) algorithms, an Improving DMEE-SAS algorithm is proposed, in non-stationary environment where tracking is very important. The Improving DMEE-SAS algorithm can avoid insensitivity of the DMEE-SAS algorithm due to the small effective step-size near the optimal estimator, and obtain a fast convergence speed. Numerical simulations are given to verify the effectiveness and advantages of these proposed algorithms.

In recent years, Chinese manufacturing enterprises compete to chase the wave of "digital revolution", digital empowerment has become an important strategic path of technological reform for many manufacturing enterprises. Based on the micro data of listed companies, this paper investigates the impact of digital transformation of Chinese listed companies on the quality of their export products. It is found that digital transformation can significantly improve the quality of enterprises' export products. After a series of robustness tests, this conclusion is still valid, and there are two ways to improve innovation performance and total factor productivity. The export product quality enhancement effect of enterprise digital transformation also has the heterogeneity of ownership, region and industry. In the further study, this paper also examines the impact of digital transformation on the internal salary gap of enterprises, and finds that digital transformation may increase the internal salary gap of enterprises, and form a "masking effect" on the quality of export products. To a certain extent, this paper deepens the understanding of the study of enterprise digital transformation on the quality of export products and its differences, and provides certain guidance for enterprises to implement the strategy of digital transformation.

Proteomics research has become one of the most important topics in the fields of life science and natural science. At present, research on protein–protein interaction networks (PPINs) mainly focuses on detecting protein complexes or function modules. However, existing approaches are either ineffective or incomplete. In this paper, we investigate function module detection mechanisms in PPIN, including open databases, existing detection algorithms and recent solutions. After that, we describe the proposed solution based on simplified swarm optimization (SSO) algorithm and gene ontology knowledge. The proposed solution implements SSO algorithm for clustering proteins with similar function, and imports biological gene ontology knowledge for further identifying function complexes and improving detection accuracy. Furthermore, we use four different categories of species dataset for experiment: Fruitfly, Mouse, Scere, and Human. The testing and analysis result show that the proposed solution is feasible, efficient and could achieve a higher accuracy of prediction than existing approaches.

To estimate the degree of quantum entanglement, it is important to understand the statistical behavior of functions of spectrum of density matrices such as von Neumann entropy, quantum purity, and entanglement capacity. These entangle- ment metrics over different generic state ensembles have been studied intensively in the literature. As an alternative metric, in this work we study sum of square root spectrum of density matrices, which is relevant to negativity and fidelity in quantum information processing. In particular, we derive the exact mean and vari- ance of sum of square root spectrum over the Bures-Hall generic state ensemble extending known results obtained recently over the Hilbert-Schmidt ensemble.

We propose a deep learning algorithm that directly compensates for luminance degradation owing to the deterioration of organic light emitting diode (OLED) devices to address the burn-in phenomenon of OLED displays. Conventional compensation circuits are encumbered by a high cost of development and manufacturing processes owing to their complexity. However, given that deep learning algorithms are typically mounted on a system on chip (SoC), the complexity of the circuit design is reduced, and the circuit can be reused by re-learning only the changed characteristics of the new pixel device. The proposed approach comprises deep feature generation and multi-stream self-attention, which decipher the importance of the variables, and the correlation between burn-in-related variables. It also utilizes a deep neural network that identifies the nonlinear relationship between the extracted features and luminance degradation. Thereafter, the luminance degradation is estimated from the burn-in-related variables, and the burn-in phenomenon can be addressed by compensating for the luminance degradation. The experimental results revealed that compensation was successfully achieved within an error range of 4.56%, and demonstrate the potential of a new approach that can mitigate the burn-in phenomenon by directly compensating for pixel-level luminance deviation.

The article focuses on breast cancer, mammography, and artificial intelligence. First, breast cancer is a widespread health problem that affects millions of people worldwide, and mammography is a widely adopted screening method. Then it introduced the advantages of mammography after AI participation, and introduced the importance of early detection of breast cancer and the application of artificial intelligence in breast cancer detection and treatment. From these aspects extend to the entire medical field of artificial intelligence issues. Several times throughout the paper, ethical issues that could arise from applying AI to healthcare are highlighted. At the end of the article, the paper describes the continued development of AI-based mammography analysis over the next period of time.

This study examined the impact of Vibration-Assisted Drilling (VAD) on hole quality and residual stress in Ti-6Al-4V ELI material. Ti-6Al-4V ELI possesses excellent mechanical properties but presents challenges in machining, including chip evacuation, burr formation, and elevated cutting temperatures. VAD, particularly Low-Frequency Vibration-Assisted Drilling (LF-VAD), has been explored as a potential solution to address these issues. The research com-pares LF-VAD with conventional drilling (CD) under various cutting and cooling conditions. LF-VAD exhibits higher maximum cutting forces under specific conditions, which result in accel-erated tool wear. However, it also demonstrates lower RMS (Root Mean Square) forces com-pared to CD, offering better control over chip formation, reduced burr formation, and improved surface roughness within the hole. Furthermore, LF-VAD generates greater compressive residual stresses on the hole's inner surface compared to CD, suggesting enhanced fatigue performance. These findings indicate that LF-VAD holds promise for improving hole quality, fatigue life, and overall component durability in Ti-6Al-4V machining applications.

The aim of this study is to investigate transient dynamic flow characteristics of the fluid flow through 5-way electric coolant valve (PCCV : Penta-Control Coolant Valve). To achieve this goal, the present paper attempts the three-dimensional dynamic simulation of the fluid flow through the valve using a commercial CFD solver with moving mesh technique to consider flow inertia and dynamic flow in the opening and closing stages of the ball valve rotating motion. Firstly, dynamic flow characteristics and the thermal mixing inside the PCCV ball valve during the opening and closing stage was analyzed. It is found that the discrepancies between dynamic and steady state simulation is remarkable when fluxes with different levels of enthalpy and momentum flow into the PCCV leads to strong flow interference and flow inertia, while the discrepancies are relatively small at low rotation speed and weak flow interference. Then, the effect of dynamic flow characteristics of the valve on dynamic thermal mixing characteristics at two different ball valve rotational speeds and rotational directions were investigated. It was found that the dynamic flow and thermal mixing characteristics inside the PCCV are greatly affected by the rotation speed, rotation direction, and degree of flow interference between fluxes. It is helpful for the design of the better coolant control strategies and the improvement of the FCEV thermal management system.

In industrial settings, gears play a crucial role by assisting various machinery functions such as speed control, torque manipulation, and altering motion direction.The malfunction or failure of these gear components can have serious repercussions, resulting in production halts and financial losses. As a result, there is an increasing requirement to monitor the state of these components in order to avoid such issues from occurring. To address this need, research efforts have focused on early defect detection in gears in order to reduce the impact of possible failures. This study focused on analyzing vibration and thermal datasets from two extruder machine gearboxes using an autoencoder Long Short-Term Memory (LSTM) model. The major goal is to implement an outlier detection approach to detect and classify defects. The results of this study highlighted the extraordinary performance of the Autoencoder LSTM model, which achieved an impressive accuracy rate of 94.42% in recognizing malfunctioning gearboxes within the extruder machine system. Furthermore, the study used a thorough global metrics evaluation methodology to further test the model’s dependability and efficacy, consequently substantiating the proposed approach’s validity.

Burrs form due to plastic deformation of materials during machining processes, such as milling and drilling. Deburring can be very difficult when the burrs are not easily accessible for removal. In this study, abrasive flow machining (AFM) was adopted for deburring the edges of milling specimens. Based on the experimental observations on AL6061 specimens, the deburring performance was characterized in terms of flow speed, the local curvature of the streamline near the burr edge, and shear stress. A new objective function that can predict the extent of deburring is proposed based on these characteristics and validated through experiments. Based on this new objective function, a prediction of deburring performance on the burr edge of the intersecting holes with offset was performed. The results between the predicted and experimental observation results were in reasonable agreement.

Background In this study, we describe our clinical experience with the fifth-generation of a breast implant with a smooth, fine surface from a Korean manufacturer (BellaGel^Ò SmoothFine; HansBiomed Co. Ltd., Seoul, Korea) in Asian women. Methods We analyzed 223 women (mean age=35.28±9.45 years and mean follow-up period=12.03±2.48 months), comprising 118 bilateral cases and 109 unilateral ones, who received breast augmentation using the BellaGel^Ò SmoothFine at our hospital between June 4, 2018 and February 28, 2019. For safety assessment, we analyzed frequencies of postoperative complications and overall survival of the BellaGel^Ò SmoothFine. Results Postoperatively, complications (12 cases, 5.38%) include asymmetry (3 cases, 1.35%), hematoma (2 cases, 0.90%), hypertrophic scars (2 cases, 0.90%), wound disruption (2 cases, 0.90%), rippling (1 case, 0.45%), capsular contracture (1 case, 0.45%), stretch deformities with skin excess (1 case, 0.45%). In addition, time-to-events were calculated as 10.94±0.64 months (95% CI 9.69-12.19) and the survival rate reached 0.290±0.168 (95% CI 0.094-0.901) at 12 months postoperatively. Conclusions Here, we describe our clinical experience with the BellaGel^Ò SmoothFine. Our results are of significance in that this is the first report about the fifth-generation of a breast implant with a smooth, fine surface from a Korean manufacturer in Asian women.

Although chronic obstructive pulmonary disease (COPD) and interstitial lung disease (ILD) have distinct clinical features, both diseases may coexist in a patient because they share similar risk factors such as smoking, male sex, and old age. Patients with both emphysema in upper lung fields and diffuse ILD are diagnosed with combined pulmonary fibrosis and emphysema (CPFE), which causes substantial clinical deterioration. Patients with CPFE have higher mortality compared with patients who have COPD alone, but results have been inconclusive compared with patients who have idiopathic pulmonary fibrosis (IPF). Poor prognostic factors for CPFE include exacerbation, lung cancer, and pulmonary hypertension. The presence of interstitial lung abnormalities, which may be an early or mild form of ILD, is notable among patients with COPD, and is associated with poor prognosis. Various theories have been proposed regarding the pathophysiology of CPFE. Biomarker analyses have implied that this pathophysiology may be more closely associated with IPF development, rather than COPD or emphysema. Patients with CPFE should be advised to quit smoking and undergo routine lung function tests, and pulmonary rehabilitation may be helpful. Various pharmacologic agents may be beneficial in patients with CPFE, but further studies are needed.

The two-scale method (TSM) is an effective approach to simulate electromagnetic (EM) scattering from rough sea surface, to interpret physical interaction of EM wave with rough sea surfaces. The sea surface roughness spectrum and the cutoff wavenumber are two key factors affecting the accuracy of TSM simulation. This paper takes the geophysical model functions (GMFs) of different band as reference, and quantitatively studies the two factors based on the numerical simulation of different polarization backscattering coefficients. The numerical simulation demonstrates that Apel spectrum is more suitable for the backscattering simulation in C/X/Ku-band, and the optimal cutoff wavenumbers are also derived for TSM simulation of EM scattering in C/X/Ku-band. Then an empirical model function of optimal cutoff wavenumbers with respect to frequency, incident angle and wind speed are obtained with regression method. Finally, the simulation results with the new model function of cutoff wavenumber are compared with the GMF and measured data in different bands and they are all consistent. Moreover, a physical explanation for the optimal cutoff wavenumber is also given.

This paper studies a model of dynamic compensation and capital structure with managerial traits. We show that Optimistic manager perceives equity as more undervalued than debt, while, confident manager perceives debt as more undervalued than equity. Managerial risk aversion mitigates manager’s bias. The risk aversion of the optimistic manager has a convex effect on the optimal coupon. There exists the level of risk aversion eliminating the bias on the leverage. The managerial optimist has an ambiguous effect on the owner’s bankruptcy level. The risk aversion has a convex effect on the owner’s bankruptcy level. The optimistic/confident manager underestimates the credit spread. The risk aversion has convex effect on the credit spread. In contrast to rational manager, the optimistic/confident manger has higher level of effort. The risk aversion has a negative effect on the effort.

Bearings are widely used in various types of electrical machinery and equipment. As their core components, failures will often cause serious consequences . At present, most methods of parameter adjustment are still manual adjustment of parameters. This adjustment method is susceptible to prior knowledge and easy to fall into the local optimal solution, failing to obtain the global optimal solution and requires a lot of resources.Therefore, this paper proposes a new method of bearing fault diagnosis based on wavelet packet transform and convolutional neural network optimized by simulated annealing algorithm.The experimental results show that the method proposed in this paper has a more accurate effect in feature extraction and fault classification compared with traditional bearing fault diagnosis methods. At the same time, compared with the traditional artificial neural network parameter adjustment, this paper introduces the simulated annealing algorithm to automatically adjust the parameters of the neural network, thereby obtaining an adaptive bearing fault diagnosis method. To verify the effectiveness of the method, the Case Western Reserve University bearing database was used for testing, and the traditional intelligent bearing fault diagnosis method was compared. The results show that the method proposed in this paper has good results in bearing fault diagnosis. Provides a new way of thinking in the field of bearing fault diagnosis in parameter adjustment and fault classification algorithms

Chronic obstructive pulmonary disease (COPD) is associated with high morbidity and mortality globally. Studies show that airway mucus hypersecretion strongly compromises lung function, leading to frequent hospitalization and mortality, highlighting an urgent need for effective COPD treatments. MUC5AC is known to contribute to severe muco-obstructive lung diseases, worsening COPD pathogenesis. Various pathways are implicated in the aberrant MUC5AC production and secretion MUC5AC. These include signaling pathways associated with mucus-secreting cell differentiation [ nuclear factor-κB (NF-кB)and IL-13-STAT6- SAM pointed domain containing E26 transformation-specific transcription factor (SPDEF), as well as epithelial sodium channel (ENaC) and cystic fibrosis transmembrane conductance regulator (CFTR)], and signaling pathways related to mucus transport and excretion-ciliary beat frequency (CBF). Various inhibitors of mucus hypersecretion are in clinical use but have had limited benefits against COPD. Thus, novel therapies targeting airway mucus hypersecretion should be developed for effective management of muco-obstructive lung disease. Here, we systematically review the mechanisms and pathogenesis of airway mucus hypersecretion, with emphasis on multi-target and multi-link intervention strategies for the elucidation of novel inhibitors of airway mucus hypersecretion.

Perinatal brain injury is a major public health problem burdened with high morbidity, mortality and severe neurological sequelae. Despite advances in neonatal life-saving technologies, neonatal encephalopathy lacks specific and effective treatment. Therefore, mechanisms of central nervous system changes associated with perinatal brain injury have been a hot topic of neonatology research. In recent years, researchers have shifted more focus from neurons themselves to perineuronal cells and intercellular interactions. As a member of the nervous system network, astrocytes are one of the dominant glial cells that regulate ion homeostasis, blood flow, and antioxidant function in the brain. Their changes in molecular mechanisms (e.g., alterations in RNA regulatory networks) during brain injury storms deserve further attention. Non-coding RNAs participate in and promote reactive pathophysiologic changes in astrocytes. The review summarizes and discusses the role of non-coding RNAs in astrocytes in recent years in studies of neonatal brain injury. It focuses on the most studied disease-related ncRNAs: miRNAs, lncRNAs and circRNAs, and hopes to provide possible directions for pathophysiological studies and therapeutic approaches of neonatal brain injury.

Accurate evaluation of thermo-fluid dynamic characteristics in tank are critically important for designing liquid hydrogen tank of small-scale hydrogen liquefier to minimize heat in-leak into the liquid and ullage. Due to the huge cost, most future liquid hydrogen storage tank designs will have to rely on predictive computational models for storage tank pressurization and heat-leak minimization. Thus, reliable on predictive numerical models to aid design process of tank design have been required. Therefore, in this study, in order to improve the storage efficiency of the small-scale hydrogen liquefier, a three-dimensional CFD model that can predict the boil-off rate and the thermo-fluid characteristics due to heat penetration has been developed. The prediction performance and accuracy of the CFD model is validated on the basis of the comparisons between its results and previous experimental data and a good agreement is obtained. To evaluate insulation performance of polyurethane foam according to thickness, the pressure change and thermo-fluid characteristics in a partially liquid hydrogen tank, subject to fixed ambient temperature and wind velocity, has been investigated numerically. Three different insulation thickness were considered to investigate not only interfacial characteristics between liquid and ullage but thermo-fluid dynamics in hydrogen storage tank for various heat-leak situation. The results indicate that as the insulation thickness becomes thinner and more heat penetration exists, natural convection by buoyancy develops stronger, so strong vortices are created near the interfacial zone by upward flow driven by buoyancy. In particular, as the amount of heat in-leak increased, wider and stronger heat accumulation was found in the top dished head area of the ullage area. In addition, it was confirmed that the CFD model developed in this study could well describe the phenomenon in which the temperature of the tank wall and the insulation mat increased at a faster rate due to faster heat transfer from the vapor and interface. In the future, the numerical model developed in this study will be used for optimizing insulation system of storage tank for small-scale hydrogen which is cost-effective and highly efficient.

Slot-die coatings are advantageous when used for coating large-area flexible devices; in particular, the coating width can be controlled, and simultaneous multi-layer coatings can be processed. Till date, the effects of ink widening and coating gap on the coating thickness have only been considered in a few studies. To this end, we developed two mathematical models to accurately estimate the coating width and thickness considering these two effects. We used root mean square deviation (RMSD) to experimentally verify the developed method. The coating width was seen to increase and the coating thickness was seen to decrease when the coating gap was increased. Experimental results showed that the estimation performances of the coating width and thickness models were as high as 98.46 % and 95.8 %, respectively. We believe that the developed models can be useful for determining the coating conditions according to the ink properties to coat a functional layer with user-defined widths and thicknesses in both lab- and industrial-scale roll-to-roll slot-die coating processes.

Autonomous vehicles (AVs) may not only reduce parking demand, but also free up on-street parking spaces. From the perspective of bus priority, converting on-street parking lots into dedicated bus lanes can both ensure bus priority and accommodate non-bus traffic, helping to reduce congestion and pollution. In order to study the impact of conversion of on-street parking lots to bus lanes on traffic flow, a microscopic simulation framework based on VISSIM is proposed in this paper. Data was collected using the floating car method and video recording method to quantify the factors affecting traffic flow due to the conversion of on-street parking. The VISSIM simulation model was then calibrated. According to the proportion of the on-street parking lots into a bus lane, the on-street parking lots conversion simulation model of different scenarios was established, and the influence of different on-street parking lots conversion ratio on traffic efficiency and pollution emission was quantitatively analyzed. Finally, the optimization method based on bus lane network connectivity is discussed. The results indicate that: When the on-street parking lots conversion ratio is approximately 100%, bus speed increases by 21.03%, bus delays decrease by 14.27%, and bus parking instances decrease by 11.31%. Total emissions are negatively correlated with vehicle speed. As the conversion rate of on-street parking increases, the emissions of road segments and the entire road network gradually decrease. At a conversion ratio of 100%, the average total emissions for road segments have the highest reduction rate, decreasing by 4.12%. At a conversion ratio of 50%, the average emission total for the road network shows the largest reduction, falling by 2.88%.

One of the most serious concerns about mega event-related changes to small cities is how to effectively utilize newly developed public attractions after the Olympic Games. Making connections with existing local amenities and forming attraction networks can be effective strategies for continuing a city’s revitalization. However, despite the expected benefits, attraction network research shows that these benefits often fail to materialize. With the case of Gangneung, a 2018 winter Olympic hosting city, this study investigated visitation patterns to nineteen selected attractions using network analysis. The results indicate that the most influential nodes are located on the northern coast, the eastern coast, and in the south downtown area, those nodes being the central locations where the strongest of connections are made. New attractions such as the Olympic Park and Walwha Linear Park were rather isolated. While seasonal and periodic variations, visitors’ residences, and destination choice attitudes had a significant effect on visitation patterns, the attraction networks, modes of transportation, proximity to region, and type similarity were not significant factors in the forming of visitation patterns. The results make a methodological contribution to tourist behavior and network research. In addition, beyond individual attraction development, the results provide practical implications in regard to networking and cooperation between multiple attractions using temporal and spatial strategies such as management/investment prioritizing, travel route development, and program scheduling.

In this work, the Ni/Ti/Nb multilayer composite was successfully manufactured by accumulative pack-roll bonding. The microstructure evolution and mechanical properties of the composite during the accumulative roll bonding (ARB) process were investigated by scanning electron microscopy(SEM), energy dispersive spectrometer(EDS), transmission electron microscopy (TEM), micro-hardness and tensile tests. The results showed that after 5 passes of the ARB process, the deformations of layers were relatively uniform, and no large number of interlayer fractures occurred. The microstructures of Ni and Ti were both equiaxed grains with a grain size of 200 nm and 150 nm, respectively, and finer equiaxed grains of the Ni layer were observed at the interface. The laminar structure of Nb layer was observed. The tensile strength and micro-hardness increased significantly as the number of ARB increased. After 5 passes of the ARB process, the tensile strength of the composite reached 792.3 MPa, and the micro-hardness of Ni, Ti, and Nb were increased to 270.2, 307.4, and 243.4 HV, respectively.

Strawberry root rot caused by Neopestalotiopsis clavispora is one of the main diseases of strawberry and significantly impacts the yield and quality of strawberry fruit. There are now no effective control techniques available except for fungicide sprays, which may directly impact consumers. Biological control is becoming an alternative method for the control of plant diseases to replace or decrease the application of traditional synthetic chemical fungicides. Trichoderma is widely used as a biological agent for controlling strawberry root rot. In order to provide resources for screening the highly effective biocontrol fungus for controlling strawberry root rot caused by Neopestalotiopsis clavispora, the biocontrol mechanism,the control effects of Trichoderma asperellum CMT10 against strawberry root rot and growth-promoting effects on strawberry seedlings were investigated by plate culture, microscopy observation and root drenching methods.The results showed that CMT10 had obvious competitive, antibiotic and hyperparasitism effects on Neopestalotiopsis clavispora CMGF3. The CMT10 could quickly occupy nutritional space, and the inhibition rates of CMT10 against CMGF3 in confrontation culture on 7 d was 65.49%. The inhibition rates of volatile metabolite and fermentation metabolite produced by CMT10 against CMGF3 were 79.67% and 69.84%, respectively. The mycelium of strain CMT10 can act as hyperparasites by making contacting, winding and penetrating hyphae of CMGF3. Pot experiment showed that the biocontrol efficacy of CMT10 on strawberry root rot caused by Neopestalotiopsis clavispora was 63.00%. CMT10 had obvious promotion effect on strawberry growth, the plant height, root length, total fresh weight, root fresh weight, stem fresh weight and root dry weight, with the promotion rates were 20.09%, 22.39%, 87.11%, 101.58%, 79.82% and 72.33%, respectively. Overall, this study showed the ability of Trichoderma asperellum CMT10 to control strawberry root rot and their potential to develop as novel biocontrol agents to replace chemical fungicides for eco-friendly, sustainable agriculture.

Perfluorinated compounds (PFCs) are used in the manufacturing process of the semiconductor and display industries, and the need for emission reduction is growing as a greenhouse gas with a very large global warming potential. The decomposition characteristics of etch type and water film (WF) type plasma-wet scrubbers were investigated. The PFCs used in the study were CF4, SF6, NF3, CHF3, C2F6, C3F8, and C4F8, and the destruction removal efficiency (DRE) and by-product gas generation rate according to the changes in the parameters (total flow rate and power) of the plasma-wet scrubber were confirmed. When the total flow rate was 100 L/min and the measured maximum power (11 kW), the reduction efficiency of CF4 in the etch type was 95.60 % and the DRE of other PFCs was 99.99 %. And, in the WF type, the DRE of CF4 was 90.06 %, that of SF6 was 96.44 %, and that of other PFCs was 99.99 %. When the total flow rate was 300 L/min and 11 kW, the DRE of SF6 in the etch type was 99 %, and the DRE of NF3, CHF3, C2F6, C3F8, and C4F8 were 99.80 %, 95.34 %, 85.38 %, 88.49 %, and 98.22 %, respectively. And, in the WF type, the DRE of SF6 was 94.39 %, and the DRE of NF3, CHF3, C2F6, C3F8, and C4F8 were 99.80 %, 95.34 %, 85.38 %, 88.49 %, and 98.22 %, respectively. The by-product gas generation rate was significantly lower in the WF type.

Background: Autonomic neuropathy commonly arises as a long-term complication in end stage kidney disease (ESKD) and can be diagnosed from heart rate variability (HRV), calculated from electrocardiogram (ECG) recordings. There is limited data about HRV using real-time ECG to predict HD efficiency in patients with ESKD who are routinely doing HD in real-world practice. Methods: Total of 50 patients (62.1 ± 10.7 years) with ESKD underwent continuous real-time ECG monitor (237.4 ± 15.3 min) during HD for HRV using remote monitoring system and checked electrolyte levels before/after HD. And we compared HRV according to electrolyte levels. Results: During the monitor, we checked total 2374 times of ECG and electrolyte level simultaneously of all patients. Both time and frequency domain HRV were higher when the patients had lower K+ level (&lt;0.5 mEq/L) and P+ level change (&lt;2 mEq/L) before/after HD as compared with those with higher K+ level (≥0.5 mEq/L) and P+ level (≥2 mEq/L) change respectively. In addition, there were higher incidence of arrhythmic events including atrial/ventricular premature complexes, even though no difference of mean heart rate in patients with lower K+ and P+ level change group (p &lt; 0.001). Conclusions: Higher HRV was independently associated with poor controlled K+ and P+ level during hemodialysis in patients with ESKD. This is further substantiated by independent continuous associations between real-time measures of higher HRV and K+ and P+ level. These data strongly suggest that cardiac autonomic dysfunction can be caused by lower change of electrolytes before/after hemodialysis alone.

The hospital indoor environment plays a significant role in shaping the microbial exposures that humans encounter. Resistance to antibiotics is one of the mechanisms employed by bacteria to develop resilience against stress in indoor environments. The extensive usage of antibiotics has been a key factor in driving changes in the ecological function of antibiotic resistance genes (ARGs) and their acquisition by pathogenic bacteria. By integrating the 16S rRNA Illumina sequencing and high throughput-qPCR approaches with water and air dust samples across seven departments at Peking University Shenzhen Hospital, China, this study yielded intriguing findings regarding the department-specific variation, transmission, and correlation of bacteria, ARGs and MGEs within the hospital indoor environment. One notable observation was that the seasonal variation played a vital role in shaping the bacterial composition in the overall hospital indoor environment across seven studied departments. Nevertheless, a similar significant seasonal impact was only observed in the blood test room and emergency departments, rather than in the other five departments. Another intriguing finding was the correlation between ARGs and MGEs abundance. This correlation was evident in the overall hospital indoor environment, which was conversely not found in the emergency, pneumology and gynecology departments. Additionally, while there was no significant relationship that occurred between bacterial communities and ARGs/MGEs within the hospital, the gynecology department demonstrated a close link between bacterial communities and the presence of ARGs/MGEs. Notably, the gynecology department also stood out as an important source of bacteria and ARGs/MGEs for other departments. This study underscores the need for careful surveillance and monitoring of antibiotic resistance, particularly in Legionella spp. in man-made water systems. The findings also show the importance of monitoring and understanding the genetic elements such as Tp614 involved in gene transfer and recombination, as well as their impact on antimicrobial treatment efficacy.

Accurately predicting electrical signals of three-phase Direct Torque Control (DTC) induction motors is crucial for optimal motor performance and effective condition monitoring. However, multiple DTC motors’ complexity and operating conditions’ variations pose challenges for traditional prediction methods. To overcome these challenges, we propose an innovative approach that combines Fast Fourier Transform (FFT) to transform electrical motor simulation data and a Bi-directional Long Short-Term Memory (Bi-LSTM) network to forecast processed motor data. By transforming the DTC induction motor signals from the time domain to the frequency domain, we enhance the capability of learning models to capture subtle differences and generate various input features. The Bi-LSTM model effectively captures both forward and backward dependencies in time series data, enabling accurate prediction of electrical signals. We evaluate the proposed approach using our simulated dataset and compare the proposed method to a state-of-the-art model, the Gated Recurrent Unit (GRU), demonstrating its effectiveness in improving the accuracy and reliability of induction motor signals forecasting. The finding provides valuable insights for advancing motor control and operation in industrial applications.

Focused microwave breast hyperthermia (FMBH) employs a phased antenna array to perform beamforming that can focus microwave energy at targeted breast tumors. Selective heating of the tumor endows the hyperthermia treatment with high accuracy and low side effects. The effect of FMBH is highly dependent on the applied phased antenna array. This work investigates the effect of polarizations of antenna elements on the microwave focusing results by simulations. We explore two kinds of antenna arrays with the same number of elements using different digital realistic human breast phantoms. The first array has all the elements’ polarization in the vertical plane of the breast while the second array has half elements’ polarization in the vertical plane and the other half in the transverse plane, i.e., cross polarization. In total 96 sets of different simulations are performed, and the results show that the second array leads to a better focusing effect in dense breasts than the first array. This work is very meaningful for the potential improvement of the antenna array for FMBH, which is of great significance for the future clinical applications of FMBH. The antenna array with cross polarization can also be applied in micro-wave imaging and sensing for biomedical applications.

In accordance with regulations set forth by the Ministry of Land, Infrastructure, and Transport in Korea regarding the "Flame Retardant Performance of Building Finishing Materials and Fire Spread Prevention Structure," it is mandated that semi-noncombustible materials have a total heat emission less than 8 MJ/m². Consequently, our study aimed to determine the ideal quantity of flame-retardant treatment required to meet the fire safety standards for Korean larch and Japanese cedar, commonly used exterior materials in Korean construction. To this end, we investigated using a cone calorimeter to observe changes in the THR (Total Heat Released) based on the AFI (Amount of Flame-retardant Impregnation) in Korean larch and Japanese cedar. Our findings indicated that the AFI needed to satisfy the prescribed flame-retardant standard of 8 MJ/m² was THR 299 MJ/m² for Korean larch and THR 526 MJ/m² for Japanese cedar. As a result, we established optimal impregnation levels of flame retardant for both species.

Purpose: Carotid intraplaque hemorrhage (IPH) increases risk of territorial cerebral ischemic events, but different sequences or criteria have been used to diagnose or quantify carotid IPH. The purpose of this study was to compare manual segmentation and semi-automatic segmentation for quantification of carotid IPH on magnetization-prepared rapid acquisition with gradient-echo (MPRAGE) sequences. Methods: Forty patients with 16–79% carotid stenosis and IPH on MPRAGE sequences were reviewed by two trained radiologists with more than five years of specialized experience in carotid plaque characterization with carotid plaque MRI. Initially, the radiologists manually viewed the IPH based on the MPRAGE sequence. IPH volume was then measured by three different semi-automatic methods, with high signal intensity 150%, 175%, and 200%, respectively, above that of adjacent muscle on the MPRAGE sequence. Agreement on measurements between manual segmentation and semi-automatic segmentation was assessed using the intraclass correlation coefficient (ICC). Results: There was near-perfect agreement between manual segmentation and the 150% and 175% criteria for semi-automatic segmentation in quantification of IPH volume. The ICC of each semi-automatic segmentation were as follows: 150% criteria: 0.861, 175% criteria: 0.809, 200% criteria: 0.491. The ICC value of manual vs. 150% criteria and manual vs. 175% criteria were significantly better than the manual vs. 200% criteria (p < 0.001). Conclusions: The ICC of 150% and 175% criteria for semi-automatic segmentation are more reliable for quantification of IPH volume. Semi-automatic classification tools may be beneficial in large-scale multicenter studies by reducing image analysis time and avoiding bias between human reviewers.

Recently, the demand for electric vehicle is increasing worldwide due to eco-friendly policies and stricter emission regulations. As a traction motor for electric vehicle, interior permanent magnet synchronous motors are mainly used. For the design of the interior permanent magnet synchronous motor, the magnetic equivalent circuit method, which is a method of lumped constant circuit, and the finite element method, which is a method of distributed constant circuit, mainly are used. Magnetic equivalent circuit method is useful for simple design through fast and intuitive parameters, but it cannot derive the distribution of magnetic field. The finite element method can derive an accurate magnetic field distribution, but it takes a long time to analyze and it is difficult to analyze intuitive design parameters. In this paper, magnetic equivalent circuit method and Carter coefficient are mixed for rotor structure design. This design method will be called the hybrid magnetic equivalent circuit method. Intuitive design parameters are derived through this hybrid magnetic equivalent circuit method. We will derive the Air gap flux density distribution according to rotor shape, no-load induced voltage, and cogging torque, and compare and verify it with the finite element method.

This paper compares a series of traditional and deep learning methodologies for the segmentation of textures. Six well-known texture composites first published by Randen and Hus{\o}y were used to compare traditional segmentation techniques (co-occurrence, filtering, local binary patterns, watershed, multiresolution sub-band filtering) against a deep-learning approach based on the U-Net architecture. For the latter, the effects of depth of the network, number of epochs and different optimisation algorithms were investigated. Overall, the best results were provided by the deep-learning approach. However, the best results were distributed within the parameters, and many configurations provided results well below the traditional techniques.

Suppressors of cytokine signaling (SOCS) influence cytokine and growth factor signaling by negatively regulating the JAK-STAT pathway. This maintains homeostasis during host immune response. However, functional characterization of SOCS family members in invertebrates is limited. In this study, we discovered the Type-I subfamily of the SOCS genes in the mealworm beetle, T. molitor. The full-length ORFs of TmSOCS5, TmSOCS6, and TmSOCS7 consisted of 1,389, 897 and 1,458 nucleotides, encoding polypeptides of 462, 297 and 485 amino acids, respectively, The C-terminal region of TmSOCS was highly conserved in the SH2 and SOCS box domains. Phylogenetic analysis revealed that the three SOCS genes clustered within the same sub-family and the highest amino acid identity was with the Tribolium castaneum SOCS genes (TcSOCS). While the expression of TmSOCS5 and TmSOCS6 was low in larval, pupal, and adult stages of the insect, TmSOCS7 showed higher expression. The expression of TmSOCS5 and TmSOCS6 was higher in larval hemocytes and adult ovary. The microbes expressed the three TmSOCS genes to varying degrees. C. albicans elicited the strongest response in the host with highest 15-fold expression in TmSOCS7 3 h post-inoculation. Collectively, these data suggest that the Type I TmSOCS could play a role in eliciting host immunity.

Surface acoustic wave (SAW) is effective for the manipulation of fluids and particles in microscale. The current approach of integrating interdigitated transducers (IDTs) for SAW generation into microfluidic channels involves complex and laborious microfabrication steps. These steps often require the full access to clean room facilities and hours to align the transducers to the precise location. This work presents an affordable and innovative method for fabricating SAW-based microfluidic devices without the need of clean room facilities and alignment. The IDTs and microfluidic channels are fabricated in the same process and thus precisely self-aligned in accordance with the device design. With the use of the developed fabrication approach, a few types of different SAW-based microfluidic devices have been fabricated and demonstrated for particle separation and active droplet generation.

Research on piezo-composite actuators has been actively conducted over the past two decades as a response to strong demand for light, compact actuators to replace electro-magnetic motor actuators in micro robots, small flying drones, and compact missile systems. Layered piezo-composite unimorph actuators have been studied to provide active vibration control of thin-walled aerospace structures, control the shapes of aircraft wing airfoils, and control the fins of small missiles, because they require less space and provide better frequency responses than conventional electro-magnetic motor actuator systems. However, based on the limited actuation strains of conventional piezo-composite unimorph actuators with poly-crystalline piezoelectric ceramic layers, they have not been implemented effectively as actuators for small aerospace vehicles. In this study, a lightweight piezo-composite unimorph actuator (LIPCA-S2) was manufactured and analyzed to predict its flexural actuation displacement. It was found that the actuated tip displacement of a piezo-composite cantilever could be predicted accurately using the proposed prediction model based on the nonlinear properties of the piezoelectric strain coefficient and elastic modulus of a piezoelectric single crystal.

This paper studies the pilot control strategy and workload of tilt-rotor aircraft dynamic conversion procedure between helicopter mode and fixed-wing mode. A nonlinear flight dynamics model of tilt-rotor aircraft with full flight modes is established. On this basis, a nonlinear optimal control model of dynamic conversion is constructed, considering factors such as conversion corridor limitations, pilot control, flight attitude, engine rated power, and wing stall effects. To assess pilot workload, an analytical method based on wavelet transform is proposed, which examines the mapping relationship between pilot control input's amplitude, constituent frequencies, and control tasks. By integrating the nonlinear optimal control model and the pilot workload evaluation method, the analysis of pilot control strategy and workload during the conversion procedure is conducted, leading to the identification of strategies to reduce pilot workload. The results indicate that incorporating the item of pilot workload in the performance index results in a notable reduction in the magnitude of collective stick inputs and longitudinal stick inputs. Moreover, it facilitates smoother adjustments in altitude and pitch attitude. Additionally, the conversion of the engine nacelle can be achieved at a lower and constant angular velocity. In summary, the conversion and reconversion procedures are estimated to have a low workload (Level 1 ~ Level 2), with relatively simple and easy manipulation for the pilot.

Regional Climatic Comfort Index (CCI) deteriorated significantly due to the climate change and anthropogenic interference. Knowledge regarding the long-term temporal dynamics of CCI in typical regions should be strengthened. In this study, we analyze the temporal and spatial evolution of CCI from 1969 to 2018 in Guangdong Province, based on meteorological indicators, including heat, humidity, wind and cloth loading etc.. Additionally, the population exposure to climate unconformity was examined since 1990 with the help of population data. Our study found that: (1) the warming and humidifying of the summer climate served as the main driving force for the continuous deterioration of CCI, with the comfortable days decreased by 1.06d/10a and the extremely muggy days increased by 2.83d/10a; (2) spatially, the lowest climate comfortability concentrated in southwestern Guangdong with more than 50 uncomfortable days each year, while the climate comfortability in northeastern Guangdong tends to deteriorated whit higher rate, which can reach as high as 6d/10a; (3) in summer, the population exposure to uncomfortable climate highly centralized in the Pearl River Delta, Shantou, Jieyang, and the surrounding areas, and both area and population exposure showed increasing trends. Particularly, Shenzhen held the highest growth rate of population exposure with an increase rate of 2.94 million/10a; (4) although the discomfort distribution and deterioration rate vary across the province, the spatial heterogeneity of comfortability is diminishing in Guangdong Province. This study will provide scientific reference for regional urban planning, thermal environment improvement, local resident health risk analysis, and key strategy implementation, etc.

Facing the charging difficulties of free-floating shared electric vehicle and the high cost of mobile charging for single demand, this article proposes a collaborative charging planning method based on the complementary advantages of fixed charging stations and mobile charging vehicles, which can charge shared electric vehicles more efficiently and reduce the charging cost at the same time. A bi-level programming model for fixed and mobile cooperative charging is constructed. The upper level of the model is the minimization model of system charging total cost, seeking the optimal charging scheme and the number of mobile charging vehicles. The lower model is a fixed and mobile cooperative charging path planning model, which calculates the optimal routes for mobile charging vehicles and the shared electric vehicles that need to be transferred to the fixed charging station. The example results show that the cost of the proposed fixed-mobile cooperative charging scheme is reduced by 12.6% compared with the pure fixed charging scheme and 14.9% compared with the pure mobile charging scheme

The potential effect of implementing environmental regulations on economic growth is a controversial issue for a long time. As portrayed by Porter hypothesis, environmental regulations may impact on economic growth by reconstructing the economic structure. A number of previous literature proved the connections between the above three parties. With the intention of exploring the nature of this mechanism, it is important to understand the internal inter-relation of the three parties, requiring data from a large economy experiencing the transition in economic structure. By constructing a panel containing data from 30 Chinese provinces over 10 years (2008-2019), this paper investigate the dynamic inter-relation of the three parties by introducing PVAR model with Granger Test. Results reveal that environmental regulations give a “U” shaped impact to economic growth. In return, economic growth promotes the development of economy with a weakening strength. In addition, results also support the hypothesis that economic structure is the intermediate of economic growth and environmental regulations. There is a rooftop for the effect of economic structure to environmental regulations. The rooftop may signify the best optimization of primary structure.

The Shimensi super-large tungsten polymetallic deposit is located in Late Jurassic- Early Cretaceous Porphyry-Skarn tungsten ore belt in the south Yangtze metallogenic belt. There are 3 types of mineralization: veinlet-disseminated type, thick quartze vein type and hydrothermal crypto-explosive breccia type. Based on geological studies, this paper presents new petrographic, microthermometric, laser Raman spectroscopic and hydrogen and oxygen isotope research of the fluid inclusions from the deposit. The results show that there are five different types of fluid inclusions: liquid-rich inclusions, vapor-rich inclusions, pure liquid inclusions, pure vapor inclusions, and fluid inclusions containing a solid crystal. The homogenization temperatures of the fluid inclusion range from 140℃-270℃, the salinities are 3%-5% NaCleq and the densities of ore-forming fluid range from 0.64 g/cm3 to 0.99 g/cm3. For the analyses of Laser Raman spectroscopic, the ore-forming fluids can be approximated by a Ca2+-Na+-SO42--Cl- fluid system with small amount of CO2, CH4 and N2. Otherwise, the datas of the pressure, pH and Eh show a fluid metallogenic environment of low pressure, weak acid and weak reduction. The values of the homogenization temperature in 3 types of orebodies suggest that the mineralization is characterized by the decrease of the temperature under the condition of the fluid immiscibility. The H-O isotope values are interpreted to indicate that the ore-forming fluids are mainly composed of magmatic water, and also the meteoric water was added with the process of the magma rising.

Background: There is considerable evidence to support the association between environmental tobacco smoke (ETS) exposure and children’s burden of disease. However, literature on the health outcomes of prenatal ETS exposure among Chinese children has not yet been comprehensively reviewed. Objective: This systematic scoping review examines the currently available evidence and identifies gaps for further research on the health consequences of prenatal ETS exposure among Chinese children. Methods: Following the JBI scoping review methodological framework, we conducted a computer-aid search of three electronic databases-- PubMed, EBSCOhost, and ProQuest to include studies from January 2011 to May 2023 that addressed the health outcomes of Chinese children whose mothers were exposed to ETS at any stage of the pregnancy. Further, a methodological quality assessment of the selected articles was conducted, using JBI Critical Appraisal Checklists. Results: A total of 30 articles were reviewed, including eleven high-quality studies and nineteen moderate-quality studies. Five main themes, including hypertension, foetal and children’s development, behavioural disorders, respiratory outcomes, and other health outcomes. Majority of studies showed positive link between prenatal ETS exposure and increase risk of preterm birth, and moderately, foetal growth restriction. Few studies explored other potential adverse outcome of ETS, including hypertension, respiratory morbidity, lung function and asthma in their children. Conclusion: The current available evidence on prenatal ETS exposure in Chinese children has unveiled a wide range of health outcomes, including preterm birth, foetal development, behavioural disorders and much more. However, Chinese studies in this area are still lacking and a gap still exists in relation to the strength of association between prenatal ETS exposure and some health risks. Efficient anti-smoking policies and smoking cessation programs should be developed to promote maternal and child health. Further research is also needed to provide better evidence in this field.

The nuclear reactor measurement system is a crucial component of the nuclear measurement system in a nuclear power plant. Its primary function is to measure the power distribution within the reactor core using detectors, calibrate, and provide data on core fuel consumption. Therefore, the study of the detectors' reliability is crucial for ensuring the safe operation of the nuclear power system. The article describes the operational mechanism of the gas ionization chamber detector utilized in the intermediate-range detector of the off-board nuclear measurement system. It also analyzes the movement of particles between the plates during the ionization process of the nuclear reaction taking place in the detector. The functional relationship between the current in the recombination region and the ionization region involved in the actual working condition, and the change with the increase of voltage between the plates, is deduced. A mathematical model is established for the number of pulses generated between the plates and the magnitude of the voltage between the plates. Subsequently, the change in the offset of the voltage corresponding to the inflection point of the ping curve and the change rule of the slope of the ping curve are investigated. Combined with the analysis of experimental data, the results show that the initial particle energy of Ar+, the primary sensitive particle on the detector surface, follows a normal distribution and is influenced by the energy loss associated with the initial velocity and the voltage between the plates. The trends of the inflection points and slopes of the ping curves can be utilized to evaluate the performance and operational status of the detector. Combined with the results of the experimental data analysis, the fit is good, and the inflection point currents in the normal state decrease by about 1.5% annually. The intelligent diagnostic system, based on the method studied in this paper, has been successfully implemented in the RPN digital retrofit and upgrade project at Qinshan No. 2 Plant.

The automotive industry needs to improve energy efficiency rapidly to achieve carbon neutrality while creating a safe, secure, comfortable driving environment for customers. Porous sound-absorbing materials and porous thermal insulators are typically used to satisfy these requirements despite limitations in mass and space. While these porous materials are similar, the microstructures they offer for high performance differ in the size and connectivity of their fluid phases, which enhances the difficulty of achieving excellent sound absorption and thermal insulation in the same material. In this study, a hydrophobic cellulose nanofiber–poly(methylsiloxane) xerogel composite was developed using computational microstructure modeling. This porous material has high porosity and excellent thermal insulation and sound absorption properties.

3D object detection is essential for an accurate and reliable autonomous driving system. Currently, the methods used by the state-of-the-art two-stage detectors are not flexible enough and their fea-ture extraction capabilities are very limited to cope effectively with the disorder and irregularity of point clouds. In this paper, we combine the advantages of both PV-RCNN and PAConv (Position Adaptive Convolution) to create a completely new network, FANet, in order to overcome the ir-regularity and disorder of point clouds. The convolution in our network builds convolutional ker-nels from a basic weight matrix, whose combined coefficients are learned adaptively by LearnNet from relative points. This network allows for flexible modeling of complex spatial variations and geometric structures in the 3D point cloud, enabling better extraction of point cloud features and producing high-quality 3D proposal boxes. Compared to other methods, FANet is superior in terms of 3D object detection accuracy. Extensive experiments on the KITTI dataset have shown a signif-icant improvement in our approach.

Autonomous Underwater Vehicles (AUVs) are emerging as pivotal tools in underwater applications such as seafloor exploration and the inspection of pipelines or cables. Traditional land-based avoidance methods prove insufficient when applied to the complex underwater environment, largely due to the unique constraints presented by marine environments and the specific dynamics of AUVs. In this study, we introduce an improved stream function-based obstacle avoidance algorithm specifically tailored for autonomous underwater vehicles. The proposed algorithm is based on a stream function that is derived from the stream function. The stream function is characterized by a radial histogram for the cost function. In addition, constraints related to the maximum path curvature are discussed to optimize the utility of the path. Our exhaustive simulation cases validate the robustness and adaptability of the proposed algorithm, demonstrating its ability to produce feasible and optimized avoidance paths in a variety of scenarios.

Cell-penetrating peptides (CPPs), a group of small peptides capable of promoting the transport of molecular cargo across the plasma membrane, have become important tools in promoting the cellular uptake of exogenously delivered macromolecules. GV1001, a peptide derived from a reverse-transcriptase subunit of telomerase (hTERT) and developed as a vaccine against various cancers, reportedly has unexpected CPP properties. Unlike typical CPPs, such as the HIV-1 TAT peptide, GV1001 enabled the cytosolic delivery of macromolecules such as proteins, DNA and siRNA via extracellular heat shock protein 90 (eHSP90) and 70 (eHSP70) complexes. The eHSP-GV1001 interaction may have biological effects in addition to its cytosolic delivery function. GV1001 was originally designed as a MHC class II-binding cancer epitope, but its CPP properties may contribute to its strong anti-cancer immune response relative to other telomerase peptide-based vaccines. Cell signaling via eHSP-GV1001 binding may lead to unexpected biological effects, such as direct anticancer or antiviral effects. In this review, we focus on the CPP effects of GV1001 bound to eHSP90 and ehsp70.

Due to the uniqueness of the underwater environment, traditional data aggregation schemes face many challenges. Most existing data aggregation solutions do not fully consider node trustworthiness, which may result in the inclusion of falsified data sent by malicious nodes during the aggregation process, thereby affecting the accuracy of the aggregated results. Additionally, because of the dynamically changing nature of the underwater environment, current solutions often lack sufficient flexibility to handle situations such as node movement and network topology changes, significantly impacting the stability and reliability of data transmission. To address the aforementioned issues, this paper proposes a secure data aggregation algorithm based on a trust mechanism. By dynamically adjusting the number and size of node slices based on node trust values and transmission distances, the proposed algorithm effectively reduces network communication overhead and improves the accuracy of data aggregation. Due to the variability in the number of node slices, even if attackers intercept some slices, it is difficult for them to reconstruct the complete data, thereby ensuring data security.

The e-commerce platform in the digital economy era has evolved into a data platform ecosystem built around data resources and data mining technology systems. The most typical applications of big data are also concentrated in the field of e-commerce. E-commerce companies should first grasp the interactive relationship among the three major factors of data, technology and innovation, e-commerce platform operation is a multidisciplinary research field. It is not easy for researchers to obtain a panoramic view of the knowledge structure in this field. Knowledge graph is a kind of graph that shows the development process and structure relationship of knowledge with the field of knowledge as the object. It is not only a visual knowledge mapping, but also a serialized knowledge pedigree, which provides researchers with a quantitative research method for the development trend of statistics and academic status. The purpose of this research is to help researchers understand the key knowledge, evolutionary trends and research frontiers of current research. This study uses Citespace bibliometric analysis to analyze the data of the Science Net database and finds that: 1) The development of the research field has gone through three stages, and some representative key scholars and key documents have been recognized; 2) the common knowledge mapping of literature The co-occurrence of citations and keywords shows research hotspots; 3) The results of burst detection and central node analysis reveal research frontiers and development trends. Today, the visualization of big data brings different challenges. The abstraction between the world and today's data visualization occurs when the data is captured. Every user sees his own visualization data generated by standardized calculations. At the same time, there are still many controversies in the theoretical model, structure and structural dimensions. This is the direction that future researchers need to further study.

Based on a rich data set of recoveries donated by a debt collection business, recovery rates for non-performing loans taken from a single European country are modelled using linear regression, linear regression with Lasso, beta regression and inflated beta regression. We also propose a two-stage model: beta mixture model combined with a logistic regression model. The proposed model allows us to model the multimodal distribution we find for these recovery rates. All models are built using loan characteristics, default data and collections data prior to purchase by the debt collection business. The intended use of the models is to estimate future recovery rates for improved risk assessment, capital requirement calculations and bad debt management. They are compared using a range of quantitative performance measures under K-fold cross validation. Among all the models, we find that the proposed two-stage beta mixture model performs best.

Melon pest management relies on the excessive application of pesticides. Reducing pesticide spraying has become a global issue for environmental sustainability and human health. Therefore, developing a new cropping system that is sustainable and eco-friendly is important. This study found that melon seedlings irrigated with ultrafine water containing H2 and O2 (UFW) produced more root hairs, increased shoot height, and produced more flowers than the control irrigated with reverse osmosis (RO) water. Surprisingly, we also discovered that UFW irrigation significantly reduced aphid infestation in melon. Based on cryo-scanning electron microscope (cryo-SEM) observations, UFW treatment enhanced trichome development and prevented aphid infestation. To investigate whether it was H2 or O2 that helped to deter insect infestation, we prepared UF water enrichment of H2 (UF+H2) and O2 (UF+O2) separately and irrigated melons. Cryo-SEM results indicated that both UF+H2 and UF+O2 can increase the density of trichomes in melon leaves and petioles. RT-qPCR showed that UF+H2 significantly increased the gene expression level of the trichome-related gene GLABRA2 (GL2). We planted melons in a plastic greenhouse and irrigated them with ultrafine water enrichment of hydrogen (UF+H2) and oxygen (UF+O2). The SPAD value, photosynthetic parameters, root weight, fruit weight, and fruit sweetness were all better than the control without ultrafine water irrigation. UFW significantly increased trichome development, enhanced insect resistance, and improved fruit traits. This system thus provides useful water management for pest control and sustainable agricultural production.

With the rapid development of network science, Turing pattern on complex networks has attracted extensive attention from researchers. In this paper, we focus on spatial patterns in multiplex ER (Erdös-Rényi) random networks, taking the predator-prey model with Allee effect and hyperbolic mortality as an example. In theory, the threshold condition for generating Turing pattern is given using the Turing instability theory of multiplex networks. Numerically, we design relevant experiments to explore the impact of network topology on Turing pattern. The factors considered include model parameters, diffusion rate, average degree of the network, and differences in the average degree of different layers. The results indicate that the importance of diffusion rate and network average degree for Turing pattern is affirmed on the single-layer network. For multiplex networks, the differentiation of average degrees in different layers controls the generation of Turing pattern, which is not affected by the diffusion rates of the two populations. More interestingly, we observe the switching of Turing pattern and spatiotemporal pattern. We believe that these findings contribute to a better understanding of self-organization on complex networks.

The Connor–Davidson Resilience Scale (CD-RISC) and the Brief Resilience Scale (BRS) are two widely used scales to measure resilience. Although both scales seek to assess an individual’s ability to recover from and adapt to disruptions or stressful events, they may capture different aspects of resilience. While the CD-RISC focuses on resources that can help individuals recover from and adapt to disruptions or stressful events, the BRS directly measures one’s ability to bounce back or be resilient. The aim of this study is to empirically examine the differences between the CD-RISC and the BRS. Two samples (n = 202, 246) consisting of undergraduate students from Taiwan were used. The results of confirmatory factor analysis show that the CD-RISC and the BRS are highly correlated but still distinct. The results of regression analyses show that the CD-RISC and the BRS have unique predictive effects on depression and life satisfaction. The research findings suggest that the CD-RISC and the BRS capture different aspects of resilience. For future research on resilience, researchers should pay attention to the differences between these scales and choose the one that most closely fits their research purpose.

Tulou dwellings in Southeast China have captivated global interest due to their distinctive appearance, sustainable construction materials and technologies, and their defensive and collective housing functions. Despite several recognized as World Cultural Heritage sites, the vast majority of tulou buildings are undergoing irreversible decline and destruction, necessitating a comprehensive and systematic study. Taking 83 Tulou buildings in Raoping County, Chaozhou City, Guangdong Province as the research object, this study reconstructs the historical scenes and systematically reveals the emergence, popularity, and consolidation process of tulou dwellings as integrated defensive and residential buildings for ordinary people by conducting a comprehensive analysis of historical documents and local chronicles. Based on an extensive field investigation, the study systematically analyzes the geospatial distribution and the spatial characteristics of Raoping tulou and its residential unit. The results demonstrate the adaptability and flexibility of tulou dwellings, showcasing their developmental process and revealing the inclusive nature of these traditional residences, as well as the initiative of those who reside within them. The research findings contribute to a more dynamic, comprehensive, and authentic understanding of tulou and Chinese traditional residences, providing valuable references for the preservation and sustainable development of tulou architectural heritage.

In this paper, by evaluating extreme value of the qth-power current, a torque sharing function (TSF) family for reducing the torque ripples in the switched reluctance motor (SRM) is proposed. The optimization criteria of the TSF has two secondary objectives, including the maximization of the torque-speed range and the minimization of copper loss. The evaluation indices in terms of the peak phase current, the rms phase current, and the torque ripple factor are compared between the proposed TSF family and four conventional TSFs including linear, sinusoidal, exponential, and cubic TSFs. An optimization objective function that combines the maximum absolute value of the rate-of-change of the flux linkage (MAV-RCFL) and the qth-power of current is proposed and a weighting factor is used to balance the influence of the two optimization objectives. An optimal TSF can be easily obtained by solving the optimization problem from the TSF family. The proposed TSF is validated by using simulations and experiments with a three-phase 6/4 SRM with 7.5 kW, 3000 rpm, and 270 V DC-link voltage. The dynamic simulation model is implemented in Matlab/Simulink. The results demonstrate the validity and superiority of the proposed control method; the optimal TSF provides better torque-speed performance, and a better reduction in copper loss and torque ripples at high speed compared to the conventional TSFs obviously.

This study mainly experimentally investigates and explores the effects of local low-frequency vibrations on the starting-up and heat transfer characteristics of the pulsating heat pipe. A micro motors with the vibration frequency of 200 Hz were imposed on the external surface of evaporation, condensation and adiabatic section of the pulsating heat pipe, respectively, and the starting-up temperature and the average temperatures along the evaporation section as well as the thermal performances of the vibrating heat pipe were experimentally scrutinized under the local vibrations of different positions. The following important conclusions can be achieved by the experimental study: 1) The effect of vibrations at the evaporation section and at the adiabatic section on the starting-up time of pulsating heat pipe is more significant than that at the condensation section. 2) The vibrations at different positions can reduce the starting-up temperature of the pulsating heat pipe. The effect of the vibrations at the evaporation section is the best as the heating power is lower, and the effect of the vibration at the adiabatic section is the best as the heating power is higher. 3) The vibrations at the evaporation section and at the adiabatic section can reduce the thermal resistance of the pulsating heat pipe. However, the vibrations at the condensation section have little effect on the thermal resistance of the pulsating heat pipe. 4) The vibrations at the evaporation section and at the adiabatic section can effectively reduce the temperature of evaporation section of the pulsating heat pipe, but the vibrations at the condensation section have no effect on the temperature of evaporation section of the pulsating heat pipe.

Hemodynamics is the eternal theme of the circulatory system. Abnormal hemodynamics and cardiac and pulmonary development intertwine to form the most important features of children with congenital heart diseases (CHDs), thus determining these children’s long-term quality of life. However, due to the lack of neonatal rodent models of CHDs, it is unclear how CHD-associated hemodynamics shape postnatal cardiac and pulmonary development. Here, we review the varieties of hemodynamic abnormalities that exist in children with CHDs, the recently developed neonatal rodent models of CHDs, and the inspirations these models have brought us in the areas of cardiomyocyte proliferation and maturation, and in alveolar development. Furthermore, current limitations, future directions, and clinical decision-making based on these inspirations are highlighted. Understanding how CHD-associated hemodynamic scenarios shape postnatal heart and lung development may provide a novel path to improving the long-term quality of life of children with CHDs, transplantation of stem cell–derived cardiomyocytes, and cardiac regeneration.

The article delves into the intricate phase transitions of 1-Octadecanol and n-Nonadecane within a binary system, unveiling dynamic structural changes under varying conditions. Through Fouri-er-transform infrared (FTIR) analysis, specific molecular vibrations were identified, shedding light on the molecular composition and interactions. The study highlights the challenges in detecting subtle phase transitions and emphasizes the individuality of molecular behaviours in closely related compounds. The findings underscore the complexity of phase transitions in binary systems and advocate for a nuanced approach to studying molecular structures and behaviours. Addi-tionally, the research contributes valuable insights into the molecular dynamics of Organic Polymer Functional Adsorption Materials, offering implications for synthetic waxy layers in plant epidermis.

The development of hybrid unmanned aerial underwater vehicles (HAUVs) compatible with the advantages of the aerial vehicles and the underwater vehicles is of great significance. This paper presents the first study on a new HAUV layout using four rotors to realize the medium crossing motion of a transverse slender body similar to the fuselage of a missile or a submarine, that is the hybrid aerial underwater quadrotor (HAUQ). Then a robust control strategy is proposed for the take-off HAUQ on the water in the presence of unknown disturbances and complex model dynamic uncertainties. As a semi-submersible HAUQ rises straightly from the water, the inside of the slender fuselage placed horizontally is filled with water. The center of the mass, the moment of inertia, and the arm of force of the HAUQ will change rapidly in the takeoff phase from the water since the rapid non-uniform change of mass caused by the passive fast drainage. It is difficult to establish a accurate mathematical model of the complex dynamic changes caused by the multi-media dynamics, the fast changing buoyancy, and the added mass crossing air–water surface. Therefore, an uncertain kinematic and dynamic model is established through the passive fast nonuniform change and the complex dynamics are considered as the unknown terms, and the external disturbances of gust and other factors are assumed as the bounded disturbance input. A robust design approach is introduced to deal with the fast time-varying mass disturbance based on the input-to-state stability (ISS) theorem. The complex dynamics are estimated using the basis function and the unknown weight parameters, and the adaptive laws are adopted for the on-line estimation of the unknown weight parameters. Consider the residual disturbance of the uncertain nonlinear system as a total disturbance term, a disturbance observer is introduced for disturbance observation. The numerical simulation shows the feasibility and robustness of the proposed algorithm.

Material identification based on R_value (transparency natural logarithm ratio of low-energy to high-energy) of line-scan dual-energy X-ray transmission (DE-XRT) has a good prospect for industrial application. Unfortunately, the DE-XRT signals before attenuation cannot be directly measured, whereas their precision is very important to R_value. Therefore, a context-based signal synthesis method which takes the filtered signals that remove high-frequency noises and retain low-frequency actual fluctuations as the reference value, and takes into account the vertical (forward/column) direction and horizontal (scanning/row) direction anisotropy of line-scan images was proposed. The vertical is a time series with continuity of signal trend; the horizontal is a spatial characteristic with the fluctuation synchronization within the same row signals. The special synthesis evaluations of curve synthesis difference and surface synthesis difference were also proposed. Experimental results show that the tow evaluations are both only about 0.0007, and it only takes 35 ms to complete the surface synthesis of 119×119 pixels on the CPU with 3.4 GHz main frequency. The presented method can achieve high signal synthesis precision and calculation real-time, so as to facilitate DE-XRT material identification. It can be extended to improve the precision of numerical synthesis in other line-scan uncomplete signals.

We report a self-assembly synthesis of silicon nanoparticles/nitrogen-doped reduced graphene oxide/ carbon nanofiber (Si@N-doped rGO/CNF) composites as potential high-performance anodes for rechargeable lithium-ion batteries (LIB) through the electrostatic attraction between amino and carboxyl groups. Nitrogen atoms generate a large number of vacancies or defects on the graphite plane, providing additional transmission channels for the diffusion of lithium ions, and improving the conductivity of the electrode. Carbon nanofiber (CNF) can help maintain the stability of the electrode structure and prevent silicon nanoparticles from falling off the electrode, prevent silicon nanoparticles from being directly exposed to the electrolyte, and can form a stable solid electrolyte interface (SEI) film. The three-dimensional conductive structure composed of Si, nitrogen atom-doped reduced graphene oxide (N-doped rGO), and CNF can effectively buffer the volume changes of silicon nanoparticles, shorten the transmission distance of lithium ions (Li+) and electrons, and make the electrode have good conductivity and stability in mechanical properties. In addition, compared with the Si@N-doped rGO and Si/rGO/CNF composite electrode, the Si@N-doped rGO/CNF composite electrode shows good cycle performance and rate capability, and its reversible specific capacity can reach 1418.8 mAh/g. The capacity retention rate is 64.7%, and the coulomb efficiency is 95%.

Major emergencies can have a devastating impact on society, becoming a catalyst for social disorder and unrest and a trigger for social or political change. In today's world of frequent emergencies, the emergency management capacity of local governments is key to promoting safe operations and maintaining stability in cities and towns. Aiming to explore the direction and focus of local government emergency management capacity building, this paper establishes a local government emergency capacity evaluation system based on the emergency management process and combines Gray-Dematel, a gray decision laboratory analysis method, and AISM, an adversarial explanatory agency model, to derive the importance and intrinsic relationship among emergency capacity indicators. The algorithm describes the importance degree of each indicator in the system and also helps better understand the intrinsic relationship among the indicators. The outcomes of this research can be used to outline directional suggestions for the development of local government emergency response capacity and provide a new theoretical basis for more effective construction of local government emergency response capacity.

In this study, we explore the potential of using a straightforward neural network inspired by the retina model to efficiently restore low-light images. The retina model imitates the neurophysiological principles and dynamics of various optical neurons. Our proposed neural network model reduces the computational overhead compared to traditional signal-processing models while achieving results similar to complex deep learning models from a subjective perceptual perspective. By directly simulating retinal neuron functionalities with neural networks, we not only avoid manual parameter optimization but also lay the groundwork for constructing artificial versions of specific neurobiological organizations.