Autonomic dysregulation is associated with cardiovascular consequences in obstructive sleep apnea (OSA). This study aimed to investigate the effect of acute continuous positive airway pressure (CPAP) treatment on autonomic activity and to identify factors contributing to the heart rate variability (HRV) changes in OSA. Frequency domain HRV parameters were calculated and compared between the baseline polysomnography and during the CPAP titration in 402 patients with moderate to severe OSA. There were significant reductions in total power, very low-frequency band power, low-frequency band power, and high-frequency band power during the CPAP titration as compared to the baseline polysomnography. This tendency was more pronounced in men than in women, and in patients with severe OSA than those with moderate OSA. Multivariate analysis found that changes in apnea-hypopnea index and oxygen saturation were significantly associated with changes in sympathetic and parasympathetic activity, respectively. This study demonstrated that HRV parameters significantly changed during the CPAP titration, indicating a beneficial effect of CPAP in restoration of sympathetic and parasympathetic hyperactivity in OSA. Prospective longitudinal studies should determine whether long-term CPAP treatment aids in maintaining the long-lasting improvement of the autonomic functions, thereby contributing to the prevention of cardiovascular and cerebrovascular diseases in patients with OSA.

The speech-to-song illusion is a type of auditory illusion that the repetition of a part of a sentence would change people’s perception tendency from speech-like to song-like. The study aims to examine how pace, emotion, and language tonality affect people’s experience of the speech-to-song illusion. It uses a between-subject (Pace: fast, normal, vs. slow) and within-subject (Emotion: positive, negative, vs. neutral; language tonality: tonal language vs. non-tonal language) design. Sixty Hong Kong college students were randomly assigned to one of the three conditions characterized by pace. They listened to 12 audio stimuli, each with repetitions of a short excerpt, and rated their subjective perception of the presented phrase, whether it sounded like a speech or a song, on a five-point Likert-scale. Paired-sample t-tests and repeated measures ANOVAs were used to analyze the data. The findings reveal that a faster speech pace could strengthen the tendency of the speech-to-song illusion. Neither emotion nor language tonality show a statistically significant influence on the speech-to-song illusion. This study suggests that the perception of sound should be in a continuum and facilitates the understanding of song production in which speech can turn into music by having repetitive phrases and to be played in a relatively fast pace.

herein, we have compared the performance of SVM and MLP in emotion recognition using speech and song channels of the RAVDESS dataset. We have undertaken a journey to extract various audio features, identify optimal scaling strategy and hyperparameter for our models. To increase sample size, we have performed audio data augmentation and addressed data imbalance using SMOTE. Our data indicate that optimised SVM outperforms MLP with an accuracy of 82 compared to 75%. Following data augmentation, the performance of both algorithms was identical at ~79%, however, overfitting was evident for the SVM. Our final exploration indicated that the performance of both SVM and MLP were similar in which both resulted in lower accuracy for the speech channel compared to the song channel. Our findings suggest that both SVM and MLP are powerful classifiers for emotion recognition in a vocal-dependent manner.

In order to cope with the limited supply of feed for global animal production, there is a pressing need to explore alternative feed resources. Orange pulp, a by-product of agriculture and industry, has shown potential to positively or neutrally impact pig productive performance when included in their diet. However, there is a lack of research on the effects of fermented navel orange pulp (FNOP) on pig growth and productive performance. This study aimed to investigate the effects of FNOP as a dry matter substitute on pig’s growth performance, carcass characteristics, meat quality, meat nutrition, and serum biochemical indicators. The experiment involved 128 finishing Tibetan pigs, divided into four feed treatment groups, with varying levels (0%, 5%, 10% and 15%) of FNOP replacing dry matter in the basal diet. The results indicated that substituting 5% to 15% FNOP had no adverse effects on pig growth performance. However, at a 15% substitution rate, there was a decrease in serum growth hormone and IGF-1 levels, along with an increase in feed-to-gain ratio. A 10% FNOP replacement notably increased the eye muscle area of pigs. Additionally, 5% and 10% FNOP substitutions reduced the drip loss of pork. The study also found that substituting 5% to 15% FNOP increased unsaturated fatty acids and umami nucleotide contents in pork, as well as raised serum total protein and uric acid (nucleotide metabolism related-product) levels. These findings suggest that moderate FNOP substitution might enhance meat quality and maintain growth and productive performance in Tibetan pigs by improving protein synthesis and nucleotide metabolism, while also reducing feed costs. The optimal substitution ratio identified was 10%.

The guided ultrasonic wave (GUW) is extensively employed in non-destructive testing (NDT) for the purpose of detecting defects in aerospace vehicles, oil pipelines and mechanical equipment. The filtration of GUW signals, which often contain substantial environmental noise, is a crucial procedure in signal processing. This paper presents a novel denoising approach that combines Variational Mode Decomposition (VMD) with an enhanced Singular Value Decomposition (SVD). The VMD method is employed to preprocess the initial signal, thereby segregating the signal component from the noise component. Subsequently, the SampEn-SVD (Sample Entropy-SVD) method is utilized to extract the effective component from the VMD-preprocessed noise component. Finally, the VMD-preprocessed signal component and the SampEn-SVD-processed effective component are combined to yield the resultant signal, which effectively filters out the noise. The efficacy of this integrated denoising approach is substantiated through the examination of experimental signals. Furthermore, a comparative analysis is conducted to evaluate the efficacy of this method in relation to other denoising techniques. The results indicate that the SampEn-SVD method yields a superior signal-to-noise ratio (SNR) when processing the GUW signal transmitted through the steel strand. Moreover, the denoising procedure significantly reduces the discretization of characteristic parameters in the signal waveform, thereby addressing the issue of inadequate reproducibility in testing outcomes. Consequently, the denoised signal exhibits high fidelity and demonstrates a strong correlation between its combined eigenvector and strand stress.

Sea ice extraction and segmentation of remote sensing images is the basis for sea ice monitoring. Machine learning-based image segmentation methods rely on manual sampling and require complex feature extraction. Deep-learning semantic segmentation methods have the advantages of high efficiency, intelligence, and automation. Sea ice segmentation using deep learning methods faces the following problems: in terms of datasets, the high cost of sea ice image label production leads to fewer datasets for sea ice segmentation; in terms of image quality, remote sensing image noise and Severe weather conditions affects image quality, which affects the ac-curacy of sea ice extraction. To address the quantity and quality of the dataset, this study used multiple data augmentation methods for data expansion. To improve the semantic segmentation accuracy, the SC-U2-Net network was constructed using multi-scale inflation convolution and a multi-layer Convolutional Block Attention Module (CBAM) attention mechanism for the U2-Net network. The experiments showed that (1) data augmentation solved the problem of an insuffi-cient number of training samples to a certain extent and improved the accuracy of image seg-mentation. (2) This study designed a multilevel Gaussian noise data augmentation scheme to improve the network's ability to resist noise interference and achieve a more accurate segmenta-tion of images with different degrees of noise pollution. (3) The inclusion of a multi-scale inflation perceptron and multi-layer CBAM attention mechanism improved the ability of U2-Net network feature extraction and enhanced the model accuracy and generalization ability.

The multidrug resistance transporter NorM is an important drug resistance pump and plays a critical role in multidrug resistance in bacteria and mammals. In this study we carried out molecular dynamics simulation to study the mechanism of Na+ binding and dynamical structures of two long loops in the substrate-releasing process in substrate binding NorM. Our simulation study identified several key residues (D41, E261 D377) along the Na+ binding pathway and a multi-state ion-binding mechanism is proposed based on the simulation study. In this proposed model, the transport of Na+ is a multi-stage process with D41 being the first station for binding to Na+, followed by Na+ binding to the second station E262 and finally to the cation-binding site of E262 and D377. During the transport of Na+, the transmembrane components TM1, TM7 and TM2 are rearranged to facilitate the ion transport as well conformational changes of NorM to a closed state. Further, substrate-bound simulation revealed that Loop3-4 and Loop9-10 control the substrate-releasing process.

Abiotic stresses extensively reduce agricultural crop production globally. Traditional breeding approaches have been widely used to mitigate the risks of abiotic stresses. The discovery of gene editing technology for modifying stress-responsive genes and associated molecular networks has paved the foundation for sustainable crop management against environmental stress. Integrated approaches based on functional genomics and transcriptomics are now expanding the opportunities to elucidate the molecular mechanisms underlying abiotic stress responses. This review summarizes some of the features and weblinks of plant genome databases related to abiotic stress genes utilized for crop improvement. Clustered, regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas) based gene-editing tool has revolutionized stress tolerance research due to its simplicity, versatility, adaptability, flexibility, and broader applications. However, off-target and low cleavage efficiency hinder the successful application of CRISPR/Cas systems. Computational tools have been developed for designing highly competent gRNA with better cleavage efficiency. This powerful genome editing tool offers tremendous crop improvement opportunities, overcoming conventional breeding techniques' shortcomings. Furthermore, we also discuss the mechanistic insights of the CRISPR/Cas9-based genome editing technology. This review summarizes the current advances in understanding plant species' abiotic stress response mechanism and applying the CRISPR/Cas system genome editing technology to develop crop resilience against drought, salinity, temperature, heavy metals, and herbicides.

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.

In this study, we investigated the effects of Akebia quinata ethanol extract (AE), Akebia quinata sikhye (AS), and Akebia quinata water extract (AW) on alcohol-induced liver injury in rats. The hepatoprotective, anti-inflammatory, anti-apoptotic, and antioxidant effects of AE, AS, and AW were examined. Experimental animals were randomly divided into five groups: normal, ethanol, AE (10 mL/kg), AS (10 mL/kg), and AW (10 mL/kg). Each group was administered the respective treatment orally once per day for 21 days. CYP2E1 mRNA expression was significantly lower in the AE, AS, and AW groups than that in the ethanol group. Pro-inflammatory cytokines including cyclooxygenase-2, IL-6, and TNF-α increased significantly in the ethanol group but these increases were ameliorated with AE, AS, and AW treatment. Moreover, the expression of the apoptosis-associated proteins Bax, p53, procaspase-3, and PARP decreased after treatment with AE, AS, and AW. The expression of antioxidant enzymes including BCL-2, SOD, and GST slightly decreased in the ethanol group, but AE, AS, and AW treatment augmented their activities. AQ extracts and AS attenuated ethanol-induced increases in the levels of phosphorylated p-AKT, p-ERK, and p-JNK. These results demonstrate that AQ is a competence indicator for inhibiting alcoholic liver injury.

In response to the new concept of the impact of total climate production factors on plant phenology, this study will verify the feasibility of simulating plant phenology and triggering thresholds based on total climatic production factors by using the phenological and meteorological observation data of S. krylovii plant from 1985 to 2018 at the Xilinhot National Climate Observatory of China Meteorological Administration. The results indicate that the total climate production factors influencing plant phenological changes can be well used for phenological simulation and its triggering thresholds. The mutation of cumulative climate production potential based on total climate production factors can effectively indicate the green-up date and the wilting date of S. krylovii plant, and their triggering thresholds depend on the parameters of climate resource change and plant biology, which are (0.085, –5.363) and (0.086, –27.620), respectively. The cumulative climate production potential based on total climate production factors can effectively indicate the heading date of S. krylovii plant, and its triggering thresholds also depends on the parameters of climate resource change and plant biology, which is (394.632，–38026.268). Furthermore, the results support the viewpoint that the climate abrupt changes determine the beginning and the ending of plant growth, while the accumulative climate resources determine the other phenological dates. This study provides new ideas for the study of plant phenology.

A series of ZnO doped nitrogen-carbon materials (xZnO-N-C) with ZnO content of 5-40% are prepared by vacuum curing-carbonization strategy using polyamide-imide as N-C source and zinc nitrate as metal source for propane dehydrogenation (PDH). 20ZnO-N-C exhibits outstanding initial activity (propane conversion of 35.2% and propene yield of 24.6%) and relatively low deactivation rate (0.071 h-1) at 600 ◦C. The detailed characterization results show that small ZnO nanoparticles (5.5 nm) with high dispersion on the catalyst could be obtained by adjusting ZnO loading. Moreover, much more nitrogen-based species especially ZnNx species are formed on 20ZnO-N-C by comparison with 20ZnO-N-C-air prepared by curing-carbonization without vacuum, which may contribute for the higher product selectivity and catalytic stability of 20ZnO-N-C. The probable active sites for PDH reaction on the catalyst system are proposed to be C=O species and Zn2+ species. Moreover, the aggregation of ZnO nanoparticles is the primary reason for the activity loss on this catalyst system. The present finding not only provides the feasible construction strategy for the metal oxide doped nitrogen-carbon materials but also valuable guidance for the design of efficient catalyst in dehydrogenation of light alkane.

Taste determination in small molecules is critical in food chemistry, but traditional experimental methods can be time-consuming. Consequently, computational techniques have emerged as val-uable tools for this task. In this study, we explore taste prediction using various molecular feature representations and assess the performance of different machine learning algorithms on a dataset comprising 2,601 molecules. The results reveal that GNN-based models outperform other ap-proaches in taste prediction. Moreover, consensus models that combine diverse molecular repre-sentations demonstrate improved performance. Among these, molecular fingerprints + GNN con-sensus model emerges as the top performer, highlighting the complementary strengths of GNNs and molecular fingerprints. These findings have significant implications for food chemistry research and related fields. By leveraging these computational approaches, taste prediction can be expedited, leading to advancements in understanding the relationship between molecular structure and taste perception in various food components and related compounds.

This article illuminates the reception and transformation of Ippen一遍(1234-1289)’s religious tenets and practices by Enju Kato加藤円住 (1919-2021) and his temple Shōjōkō-ji清浄光寺. While Enju Kato asserts that his life has been dedicated to adhering and enacting Ippen's concept of "renunci-ation," he has reinterpreted this concept based on his personal experiences and comprehension. Second, Enju Kato and Shōjōkō-ji have inherited some of Ippen's religious practices yet adapted these to align with contemporary settings. This article presents a case study discussing the ac-ceptance and transformation of doctrines and practices of jishū時宗 in contemporary era, which has been overlooked by academia thus far.

Bees (Apoidea), the largest and most crucial radiation of pollinators, play a vital role in ecosystem balance. Transposons are widely distributed in nature and are important drivers of species diversity. However, transposons are rarely reported in important pollinators such as bees. Here, we surveyed 37 genomes in Apoidea, annotated the pogo and Tc1/mariner transposons in the genome of each species and performed a phylogenetic analysis to determine their overall distribution. The pogo and Tc1/mariner families showed high diversity and low abundance in the 37 species, and their proportion was significantly higher in solitary bees than in social bees. DD34D/mariner was found to be distributed in almost all species and was found in Apis mellifera, Apis mellifera carnica, Apis mellifera caucasica and Apis mellifera mellifera and Euglossa dilemma may still be active. Using horizontal transfer analysis, we found that DD30D/Tigger, DD33D/Tigger and DD34D/mariner may have experienced horizontal transfer events. The current study displayed the evolution profiles (including diversity, activity, and abundance) of the pogo and Tc1/mariner transposons across 37 species of Apoidea. Our data revealed their contributions to the genomic variations across these species and facilitated in understanding of the genome evolution of this lineage.

We suppose that a Cooper pair (CP) will experience a damping force exerted by the condensed matter. A Langevin equation of a CP in two dimensional condensed matter is established. Following a method similar to Nelson's stochastic mechanics, generalized Schr\"{o}dinger equation of a CP in condensed matter is derived. If the CPs move with a constant velocity, then the corresponding direct current (DC) electrical conductivity can be calculated. Therefore, a Drude like formula of resistivity of CPs is derived. We suppose that the damping coefficient of CPs in two dimensional cuprate superconductors is a linear function of temperature. Then the resistivity and scattering rate of CPs turn out to be also linear-in-temperature. The origin of linear-in-temperature resistivity and Planckian dissipation in cuprate superconductors may be the linear temperature dependence of the damping coefficient of CPs.

Based on the plate tectonic theory, using seismic, geology, and public literature data, the proto-type basins and lithofacies paleogeography during the main geological periods of the passive continental margin of East Africa are restored, and the architecture characteristics of the basins and the differences in sedimentary fillings are analyzed. Combined with the dissection of discovered oil and gas reservoirs, four types of hydrocarbon accumulation models are established, the favorable hydrocarbon accumulation combinations (plays), and the next exploration directions in this region are explored. The passive continental margin basins in East Africa experienced three proto-type stages: intracontinental aborted rift during the Late Carboniferous-Triassic Karoo period, intracontinental-intercontinental rift during the Jurassic period, and passive continental margin basin since the Cretaceous period. Affected by the difference in sedimentary filling thickness between the rift period and depression period, four types of passive continental margin basins are formed: rifted type, depressed type, faulted depression type, and reformed delta type. The maximum sedimentary thickness of the rifted basins during the rift period is greater than 3500 m, and that during the depression period is less than 4000 m, forming a "single-source structure type" hydrocarbon accumulation model. The exploration of rifted basins should focus on giant structural traps at the top of the rifted sequences. The maximum sedimentary thickness of the depressed basins during the depression period exceeds 4000 m, forming a "single-source fan group type" hydrocarbon accumulation model. The dominant exploration directions of depressed basins are sedimentary sand bodies and structural-lithologic traps during the depression and drift periods. The maximum sedimentary thickness of the faulted depression basins during the rift period is greater than 3500 m, and that during the depression period is greater than 4000 m, forming a "double-source and double-combination type" hydrocarbon accumulation model. The exploration of rifted basins should focus on giant slip-collapse-debris flow sedimentary sand bodies on the upper and middle slopes. In addition to the large sedimentary thickness of the early rift and the central depression, the delta thickness of the reformed delta basins during the late depression period since the Miocene is more than 4000 m, and four structural belts (growth fault, mud diapir, thrust fold, and foredeep gentle slope) were formed from onshore to offshore, forming a "three-source and multi-combination type" hydrocarbon accumulation model. All four structural belts can form giant oil and gas fields.

Background and Objectives: The novel double-pigtail catheter (DPC) has an additional pigtail coiling at the mid-shaft with centripetal multiple side holes. The aim of the present study was to investigate the advantages and efficacy of DPC in overcoming the complications of conventional single-pigtail catheters (SPC) used to drain pleural effusion. Materials and Methods: Between July 2018 and December 2019, 382 pleural effusion drainage procedures were reviewed retrospectively (DPC, n = 156; SPC without multiple side holes, n = 110; SPC with multiple side holes [SPC+M], n = 116). All patients showed shifting pleural effusion in the decubitus view of chest radiography. All catheters were 10.2 Fr in diameter. One interventional radiologist performed all procedures and used the same anchoring technique. Complications (dysfunctional retraction, complete dislodgement, blockage, and atraumatic pneumothorax) were compared among the catheters using chi-square and Fisher’s exact tests. Clinical success was defined as improvement in pleural effusion within 3 days without additional procedures. A survival analysis was performed for calculating the indwelling time. Results: The dysfunctional retraction rate of DPC was significantly lower than that of the other catheters (p < .001). Complete dislodgement did not occur in any of the DPC cases. The clinical success rate of DPC (90.1%) was the highest. The estimated indwelling times were nine (95% confidence interval [CI]: 7.3–10.7), eight (95% CI: 6.6–9.4), and seven (95% CI: 6.3–7.7) days for SPC, SPC+M, and DPC, respectively, with DPC showing a significant difference (p < .05). Conclusions: DPC had a lower dysfunctional retraction rate compared to conventional drainage catheters. Furthermore, DPC were efficient for pleural effusion drainage with a shorter indwelling time.

This study investigated the impact of boron and copper on the microstructure and mechanical properties of Spheroidal graphite Cast Iron (SCI). The addition of boron increased the ferrite content, while copper increased the stability of pearlite. The interaction between boron and copper significantly increased the ferrite content. Differential Scanning Calorimetry (DSC) revealed that boron decreased the enthalpy change of the α + Fe3C -> γ transformation and increased the enthalpy change of the α -> γ transformation. The addition of boron and copper reduced the tensile and yield strength but increased elongation and impact energy. The findings provide valuable insights into the effect of boron and copper on SCI, facilitating the design and development of high-performance SCI materials.

Tenascin C (TNC) is an element of the extracellular matrix (ECM) of various tissues, including the skin, and is involved in modulating ECM integrity and cell physiology. Although skin aging is apparently associated with changes in the ECM, little is known about the role of TNC in skin aging. Here we found that Tnc mRNA level was significantly reduced in the skin tissues of aged mice compared with young mice, consistent with reduced TNC protein expression in aged human skin. TNC-large (TNC-L; 330-kDa) and -small (TNC-S; 240-kDa) polypeptides were observed in conditional media from primary dermal fibroblasts. Both recombinant TNC polypeptides, corresponding to TNC-L and TNC-S, increased the expression of type I collagen and reduced the expression of matrix metalloproteinase-1 in fibroblasts. Treatment of fibroblasts with a recombinant TNC polypeptide, corresponding to TNC-L, induced phosphorylation of SMAD2 and SMAD3. TNC increased the level of TGF-β1 mRNA and upregulated the expression of type I collagen by activating the TGF-β signaling pathway. In addition, TNC also promoted the expression of type I collagen in fibroblasts embedded in a three-dimensional collagen matrix. Our findings suggest that TNC contributes to the integrity of ECM in young skin and to prevention of skin aging.

In this work, a tailored extreme learning machine (ELM) algorithm to enhance the overall robustness of gas analyzer based on the tunable diode laser absorption spectroscopy (TDLAS) method is presented. The ELM model is tailored through activation function selection, input weight and bias searching, and cross validation method to address the analyzer robustness issues for industrial process analysis field application. The two particular issues are the inaccurate gas concentration measurement caused by the process gas background components variation, and the inaccurate spectra shift calculation caused by spectral interference. By using our algorithm, the concentration error is reduced by one order of magnitude over a much larger stream pressure and component range compared with that obtained by classical least square (CLS) fitting methods based on reference curves. Additionally, it is shown that with our algorithm, the wavelength shift accuracy is improved to less than 1 count over 1000 counts spectra length. In order to test the viability of our algorithm, a trace ethylene (C₂H₄) TDLAS analyzer with coexisting methane was implemented, and its experimental measurements support analyzing robustness enhancement effect.

Concrete cracks and local damage can affect the bond performance between concrete and steel bars, thereby reducing the durability of reinforced concrete structures. Compared with general concrete crack repair methods, biomineralization repair not only has effective bonding capabilities but is also particularly environmentally friendly. In view of this, this study aimed to apply biomineralization technology to repair damaged fiber-reinforced lightweight aggregate concrete (LWAC). Two groups of LWAC specimens were prepared. The control group used lightweight aggregates (LWAs) without bacterial spores and nutrient sources, and the experimental group used LWAs containing bacterial spores and nutrient sources. These specimens were first subjected to compression tests and pull-out tests, respectively, and thus were damaged. After the damaged specimen healed itself in different ways for 28 days, secondary compression and pull-out tests were conducted. The self-healing method of the control group involved placing the specimens in an incubator. The experimental group was further divided into experimental group I and experimental group II. The self-healing method of experimental group I was the same as that of the control group. The self-healing method of experimental group II involved soaking the specimen in a mixed solution of urea and calcium acetate for two days, and then taking it out and placing it in an incubator for two days, with a cycle of four days. The test results showed that, compared with the control group specimens, the relative bond strength ratio of the experimental group II specimens increased by 17.9%. Moreover, the EDS and XRD analysis results confirmed that the precipitate formed at the crack was calcium carbonate, which improved the compressive strength and bond strength after self-healing. This indicates that the biomineralization maintenance method used in experimental group II is more effective.

Distributed/semi-distributed models are considered to be sensitive to the spatial resolution of the data input. In this paper, we take a small catchment in high urbanized Yangtze River Delta, Qinhuai catchment as study area, to analyze the impact of spatial resolution of precipitation and the potential evapotranspiration (PET) on the long-term runoff and flood runoff process. The data source includes the TRMM precipitation data, FEWS download PET data, and the interpolated metrological station data. GIS/RS technique was used to collect and pre-process the geographical, precipitation and PET series, which were then served as the input of CREST (Coupled Routing and Excess Storage) model to simulate the runoff process. The results clearly showed that, the CREST model is applicable to the Qinhuai catchment; the spatial resolution of precipitation had strong influence on the modelled runoff results and the metrological precipitation data cannot be substituted by the TRMM data in small catchment; the CREST model was not sensitive to the spatial resolution of the PET data, while the estimation fourmula of the PET data was correlated with the model quality. This paper focused on the small urbanized catchment, suggesting the influential explanatory variables for the model performance, and providing reliable reference for the study in similar area.

Fanconi anemia (FA) develops due to a mutation in one of the FANC genes that are involved in repair of interstrand crosslinks (ICLs). FANCG, a member of the FA core complex, is essential for ICL repair. Previous FANCG-deficient mouse models were generated with drug-based selection cassettes in mixed mice backgrounds, leading to a disparity in interpretation of genotype-related phenotype. To exclude these confounders, we created a Fancg-KO (KO) mouse model using CRISPR/Cas9. The entire Fancg locus was targeted and maintained on the immunological well-characterized C57BL/6J background. Intercrossing of heterozygous mice resulted in sub-Mendelian numbers of homozygous mice, suggesting loss of FANCG can be embryonic lethal. KO mice displayed infertility, hypogonadism but no other developmental problems. Bone marrow analysis revealed a defect in various hematopoietic stem and progenitor subsets with a bias towards myelopoiesis. Cell lines derived from Fancg-KO mice were hypersensitive to crosslinking agents-cisplatin and Mitomycin C, and Fancg-KO mouse embryonic fibroblasts (MEFs) displayed increased γ-H2AX upon cisplatin treatment. Reconstitution of these MEFs with Fancg cDNA corrected for the ICL hypersensitivity. Collectively, this project provides a new, genetically and immunologically well-defined Fancg-KO mouse model for further in vivo and in vitro studies on FANCG and ICL repair.

The object of this study was to discover an alternative therapeutic agent with fewer side effects against acne vulgaris, which is one of the most common skin diseases. Acne vulgaris often associates with acne-related bacteria such as <i>Propionibacterium acnes</i>, <i>Staphylococcus epidermidis</i>, <i>Staphylococcus aureus</i> and <i>Pseudomonas aeruginosa</i>, some of which exhibit a resistant against commercial antibiotics used in the treatment of acne vulgaris (tetracycline, erythromycin, and lincomycin). In the current study, we evaluated <i>in vitro</i> antibacterial activity of chitosan-phytochemical conjugates against acne-related bacteria. Three of chitosan-phytochemical conjugates used in this study showed stronger antibacterial activity than that of chitosan (unmodified control). Chitosan-caffeic acid conjugate (CCA) exhibited the highest antibacterial activity against acne-related bacteria with minimum inhibitory concentration values of 8 μg/mL to 256 μg/mL. In addition, the MICs of antibiotics against antibiotic resistant <i>P. acnes</i> and <i>P. aeruginosa</i> strains were dramatically reduced in the combination with CCA, suggesting that CCA would restore the antibacterial activity of the antibiotics. The analysis of fractional inhibitory concentration indices clearly revealed a synergistic antibacterial effect between CCA and the antibiotics. Thus, the median ∑FIC values against the antibiotic resistant bacterial strains were ranged from 0.375 to 0.533 in the combination mode of CCA and antibiotics.

This study investigates the effects of Zinc (4wt.%) and severe plastic deformation on the mechanical properties of AZ61 magnesium alloy through the stir-casting process. The severe plastic deformation (equal channel angular pressing (ECAP)) has been done followed by T4 heat treatment. The microstructural examinations revealed that the addition of 4wt.%Zn enhances the uniform distribution of β-phase, contributing to a more uniformly corroded surface in corrosive environments. Additionally, dynamic recrystallization (DRX) significantly reduces the grain size of as-cast alloys after undergoing ECAP. The attained mechanical properties demonstrate that after a single ECAP pass, AZ61 + 4wt.%Zn alloy exhibits optimal yield strength (YS), ultimate compression strength (UCS), and hardness. This research highlights the promising potential of AZ61 + 4wt.%Zn alloy for enhanced mechanical and corrosion-resistant properties, offering valuable insights for applications in diverse engineering fields.

The geographical environment, food culture, and dietary habits are substantially different between the southern and northern regions in China. We investigated the associations with dietary patterns and metabolic syndrome between Chinese adult from the southern and northern regions (North: 1249; South: 1849) using data from the Chinese Health and Nutrition 2009 survey. Respectively, four dietary patterns were identified by factor analysis in the two regions. Each dietary pattern of factor score was calculated for three groups by tertile (T1<T2<T3). In the northern region, the association between the Alcohol and Western pattern and the risk of abdominal obesity (OR: 1.31; 95%:1.01, 1.68), hypertriglyceridemia (OR: 1.35; 95%:1.05, 1.74), high fasting blood glucose (OR: 1.37; 95%: 1.05, 1.80), and hypertension (OR: 1.55; 95%: 1.45, 1.99) was increased. In the southern region, the Convenience Food pattern was positively associated with hypertriglyceridemia (OR: 1.53; 95%: 1.03, 2.26), low HDL-cholesterol (OR: 1.96; 95%: 1.12, 3.43), and metabolic syndrome (OR: 1.79; 95%: 1.03, 3.11). The Alcohol dietary pattern was positively associated with high fasting blood glucose (OR: 1.83, 95%: 1.13, 2.97). There are some dietary pattern differences in the two regions. It is necessary to consider the factors of food culture and food intake habits in order to provide nutrition education to Chinese individuals from different regions in the future.

Results showed that mulberry leaves could significantly reduce backfat thickness (P&lt;0.05) and increase intramuscular fat (IMF) content (P&lt;0.05). Lipidomics analysis showed that mulberry leaves improved lipid profile composition and increased the proportion of triglycerides (TG). Interestingly, IMF content was positively correlated with acyl C18:2 and negatively correlated with C18:1 of differential TGs. In addition, cecal microbiological analysis showed that mulberry leaves could increase the abundance of bacteria such as UCG−005, Muribaculaceae_norank, Prevotellaceae_NK3B31_group, Limosilactobacillus, and so on. At the same time improve the L-tyrosine-baton rouge ester, Oleic acid methyl ester, 21-deoxycortisol, N-acetyldihydrosphingosine, Mulberrin relative abundance. In this study, we found that mulberry leaves could extremely significantly increasing the mRNA relative expression of lipoprotein lipase (LPL), fatty acid-binding protein 4 (FABP4) and peroxisome proliferators-activated receptor γ (PPARγ) in muscle (P＜0.01), significantly increasing mRNA relative expression of diacylglycerol acyltransferase 1 (DGAT1) (P＜0.05) and significantly decreasing the mRNA relative expression of acetyl CoA carboxylase (ACC) (P＜0.05), and aignificantly upregulated hormone-sensitive triglyceride lipase (HSL), peroxisome proliferators-activated receptor α (PPARα) mRNA relative expression (P＜0.05) in backfat. In addition mulberry leaves could increased serum leptin and adiponectin (P＜0.01). Ultimately lead to up-regulation of IMF and down-regulation of backfat.

It is desirable to upgrade previous evolutionary theories, which have remained incomplete and controversial for decades. Here we employ the concept of carbon-based entities (CBEs), which include methane, amino acids, proteins, organisms, and other entities containing relatively many carbon atoms. We deduce the driving force, mechanisms, steps, modes, tempos of CBE evolution, through integration of biology, physics, and chemistry using logics for complex issues. We hence establish the Carbon-Based Evolutionary Theory (CBET). The CBET suggests that evolution is the increase in hierarchy, diversity, fitness of CBEs under natural selection and driven by thermodynamics due to the chemical effect of the thermodynamic features of the Earth on CBEs. It provides better explanations for life origin, macroevolution events, natural selection, sympatric speciation, and evolution tempos than previous evolutionary theories. It reveals the evolutionary basis of multiple important social notions, including diversity, collaboration, altruism, obeying rules, and proper increase in freedom. It refutes some wrong notions in thermodynamics, including negative entropy (negentropy) and that biological order is equal to thermodynamic order, which have misled many people. The CBET is supported by its deduction and application. It could be a rare bridge linking laws of thermodynamics, evolution of life, and development of human society, and could have great significance in various sciences.

This article presents multiple novel and compelling arguments to systematically disprove two widely accepted notions: one is that entropy is a measure of disorder, and the other is Schrödinger's notion of negative entropy (negentropy). These two notions have been cited hundreds of times annually in scientific literature for decades. To mathematically describe the second law of thermodynamics, the concept of entropy was created and defined in the 1860s as heat energy divided by thermodynamic temperature, and the entropy of an object increases when it absorbs heat. This is the uncontroversial and fundamental nature of entropy, which is pivotal to current thermodynamics and from which multiple facts are deduced. These facts consistently disprove the above two notions. Some biological facts, such as the one that life orderliness is encoded and provided by inherited genes rather than entropy decline, can also disprove Schrödinger's negentropy notion. Moreover, this article further clarifies the reasoning errors of the two notions. It also shows that the tendency of many natural or social systems to become more disordered over time does not result from the second law of thermodynamics.

Sickle cell disease is characterized by stiff, “sickled” red blood cells that have difficulty moving through the bloodstream and do not efficiently carry oxygen. It is an inherited disease with severely limited treatment options, and is caused by a point mutation. Its prevalence in black and brown communities makes the already limited treatment options even less accessible. Base editing and prime editing are two relatively recent discoveries in the field of genome editing and were developed after the groundbreaking discovery of the CRISPR Cas9 system. While not fully tested, they hold a lot of promise in providing alternative treatment options for sickle cell disease. Both editing systems are able to install individual point mutations in the beta globin gene, which is where the sickle cell mutation occurs, and can thus cure sickle cell disease (in theory). In this paper we outline the mechanisms of CRISPR-Cas9 systems and base and prime editing, and provide insight into how to apply them to treat SCD. Further investigation should be done on specific editing systems and designs to use to ensure optimal treatment of SCD.

In this four-month-long study (from April 1, 2020 to August 1, 2020), we have collected, modeled, and analyzed COVID-19 data from the top five most infected counties per top six most infected states in the United States (30 counties total). More specifically, we collected data on each state’s total COVID-19 cases, deaths, tests conducted, and their counties’ population, density, percentage of seniors, number of hospitals, total COVID-19 cases, and total COVID-19 related deaths. In this study, we have models illustrating the growth of COVID-19 cases and deaths per county, growth of COVID-19 cases and deaths per state (which is really the sum of our chosen five counties), and growth of COVID-19 tests conducted per state. In addition, our study also contains models illustrating the statistics of several variables that might have affected a county’s COVID-19 data, which has been mentioned above: population, density, percentage of seniors, and number of hospitals. An interesting finding we have noticed upon modeling the 30 counties’ density and total COVID-19 cases as an xy scatter plot is that there is a considerably strong relationship between the two variables. Los Angeles County (which was an extreme outlier), in particular, supports the idea that a county’s most populous city can greatly affect its entire county’s COVID-19 cases; if the largest city is extremely dense, it appears that the entire county has a greater total COVID-19 case count.

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.

Earth observation satellites can capture images of specific areas in Earth's orbit based on user requirements. Despite the high demand for satellite imagery, satellites remain a scarce resource. When there are many observation tasks that are large and dense, they may interfere with each other due to satellite mobility. To address this issue, a multi-satellite scheduling algorithm based on a task merging mechanism has been proposed. This paper proposes a two-stage approach to the problem: task merging phase and merging task scheduling phase. The task merging phase introduces two methods based on Mean Shift and Complete Graph to generate the merging task set. In the merging task scheduling phase, a multi-satellite scheduling algorithm based on merging tasks is employed to solve the problem. Finally, certain measurement experiments suggest the effectiveness of the algorithm.

Recently, two respiratory syncytial virus (RSV) vaccines based on the prefusion F (pre-F) antigen were approved in the United States. We developed and validated an enzyme-linked immunosorbent assay (ELISA)-based protocol for the practical and large-scale evaluation of RSV vaccines. Two modified pre-F proteins (DS-Cav1 and SC-TM) were produced by genetic recombination and replication using an adenoviral vector. The protocol was established by optimizing the concentrations of the coating antigen (pre-F proteins), secondary antibodies, and choice of blocking buffer. To validate the protocol, we examined its accuracy, precision, and specificity using serum samples from 150 participants across various age groups and the standard serum provided by the National Institute of Health. In the linear correlation analysis, coating concentrations of 5 and 2.5 μg/mL of DS-Cav1 and SC-TM, respectively, showed high coefficients of determination (r2 = 0.90). Concentrations of secondary antibodies (alkaline phosphatase-conjugated anti-human immunoglobulin G, diluted 1:2000) and blocking reagents (5% skim milk/PBS-T) were optimized to minimize non-specific reactions. High accuracy was observed for DS-Cav1 (r2 = 0.90) and SC-TM (r2 = 0.86). Further, both antigens showed high precision (coefficient of variation &lt; 15%). Inhibition ELISA revealed cross-reactivity of antibodies against DS-Cav1 and SC-TM but not with the attachment protein.

Cerebral ischemic stroke is one of the leading causes of death and disability worldwide. 2’-fucosyllactose (2’-FL), a human milk oligosaccharide, has anti-inflammatory effects and plays a protective role in arterial thrombosis, but its role in ischemic stroke remains unclear. This study aimed to investigate the neuroprotective effects of 2’-FL and its potential mechanisms in a mouse model of ischemic stroke. The administration of 2’-FL led to a reduction in the size of cerebral infarct and reactive oxygen species (ROS)-related products in the brain of MCAO mice. Further, 2’-FL promotes the recovery of neurological deficits and motor function in neurological scores and behavior tests. Biochemical studies showed that 2’-FL reduced upregulated IL-10 and downregu-lated TNF-α. Additionally,2’-FL enhanced M2-type microglial polar2’-FL upregulated IL-10 and downregulated TNF-α ization at 7 days after MCAO, with an increase in IL-4 levels and STAT6 activation at 3 days after MCAO. Our data showed that 2’-FL reduced the neurological symptoms of ischemic stroke and ROS accumulation in the brain through IL-4/STAT6-dependent M2-type mi-croglial polarization in MCAO mice. These results demonstrate that 2’-FL is a potentially effective therapeutic agent for ischemic stroke.

Employing remote sensing techniques to evaluate crop residue cover (CRC) enables rapid mapping of tillage practices over large cropland areas, which has significant practical implications for monitoring the implementation of conservation tillage practices. This research utilized Sentinel-2 MSI and Landsat-8 OLI remotely sensed data, various spectral indices were calculated and the datasets were correlated with the field-measured CRC data. Selected spectral indices, highly significantly correlated, were chosen to build a correlation model between the indices and the CRC. Considering Sentinel-2 MSI and Landsat 8 OLI remotely sensed data variations in spectral and spatial scales, the accuracy of CRC models was evaluated using R2 and RMSE values. From the results, it's evident that all six spectral indices, including STI, NDTI, SRNDR, NDI5, NDI7 and NDSVI, registered correlation coefficients with the CRC exceeded 0.3 in the study area. STI and NDTI showed a stronger correlation to CRC, with coefficients of 0.810 and 0.803, respectively. For the Landsat 8 data, the lowest correlation obtained was for NDSVI with the Landsat 8 data with a correlation coefficient of 0.358. Applying the linear regression technique, STI and NDTI obtained higher accuracy compared to other indices in the Sentinel-2 MSI data. For NDTI and STI, The R2 values were 0.650 and 0.665, respectively, while their corresponding RMSE values were 3.96% and 4.03%. The highest model accuracy was obtained for the STI and NDTI constructed from the Landsat 8 OLI data (R2 values 0.41 and 0.40; RMSE values 5.25% and 5.27%, respectively). The CRC model built using partial least squares regression (PLSR) exhibited greater precision when applied to the Sentinel-2 MSI data (R2 value 0.894; RMSE value 2.18%) in comparison to the Landsat 8 OLI data (R2 value 0.695; RMSE value 3.70%). PLSR has the potential to enhance the precision of the model. In addition, the study area shows that the estimation of the CRC is better in the one-dimensional linear regression model and the PLSR model created with the Sentinel-2 MSI optical data compared to the Landsat 8 OLI optical remotely sensed data. The validation suggests that the CRC estimation in the study area is more precise when using the model relying on Sentinel-2 satellite imagery rather than the Landsat 8 OLI imagery.

Two X chromosomes of female mammals randomly inactivate one of paternal or maternal X chromosome in early embryonic development and all the daughter cells produced from these cells retain the same feature of X chromosome inactivation, which is called X chromosome inactivation (XCI). Studying the mechanisms of XCI is important for understanding epigenetic that plays an important role in age-associated diseases. The previous studies have demonstrated that binding of RNAs and DNAs may play a role in activating gene expression. In this paper, our study aims to explore whether the mechanisms of XCI involve the RNA binding strength to X chromosome DNAs. The bioinformatics analyses based on big data were used to analyze the simulated binding strength of RNAs (RNA binding strength) to 23 chromosomes (including X chromosome and 22 human autosomes) and the characteristics of repetitive sequences in the X-inactivation centre. The results revealed that RNA binding strength of the long arm of the X chromosome that is almost entirely inactivated in XCI was significantly lower than that of all autosomes and the short arm of X chromosome, meanwhile the RNA binding strengths of inactivation regions in X chromosome were significantly lower than that of regions escaping from XCI. Different repetitive sequence clusters within the center of XCI presented a cross distribution characteristic. To further prove whether the repetitive sequences in human X chromosome involve in XCI, we cloned long interspersed element (LINE-1, L1) and short interspersed element (Alu) from human Xq13, the center of XCI, and constructed expression vectors carrying sense-antisense combination repetitive sequences (L1s or Alus). Effects of combined L1 or combined Alu sequences on expression of EGFP reporter gene were examined in stably transfected HeLa cells, which simulates the effects of repetitive sequences located on chromosomes. The results of experiments revealed transcribed L1 repetitive sequences activated EGFP reporter gene expression, so did the Alus. The experiment results suggested repetitive sequences activated genes by interaction of transcribed RNAs and DNAs. Since the binding of RNAs and DNAs can activate gene, so the low RNA binding strength of human X chromosome may be one of reasons of XCI. The cross distribution characteristics of different repetitive sequence clusters leading to a cascade of gene activation or gene inactivation may be the reason of transcriptional silencing one of the X chromosomes in female mammals.

Floods are among the most serious natural disasters worldwide; they cause enormous crop losses every year and threaten world food security. There are many studies focused on flood impact assessments for administrative districts but fewer on postdisaster impact assessments for specific crops. Therefore, this study used remote sensing data, including the normalized difference vegetation index (NDVI), elevation data, slope data, and rainfall data, combined with crop growing season data to construct a crop flood damage assessment index (CFAI). First, an analytic hierarchy process (AHP) was used to assign weights to the impact factors; then, the weighted composite score method was used to calculate the CFAI; and finally, the impact was classified as slight, moderate, or severe based on the magnitude of the CFAI . This method was used for the Missouri River floods of 2019 in the U.S. Due to the lack of measured data, the disaster vegetation damage index (DVDI) was used to validate the results. The combined approach achieved a high degree of consistency in spatial distribution. The CFAI can respond well to the degree of crop impact after flooding, providing new ideas and reference standards for agriculture-related departments.

We suppose that vacuum is filled with a kind of continuously distributed matter which may be called the $\Omega(1)$ substratum, or the electromagnetic aether. Suppose that the time scale of a macroscopic observer is very large compares to the the Maxwelllian relaxation time of the $\Omega(1)$ substratum. Thus, the macroscopic observer concludes that the $\Omega(1)$ substratum behaves like a Newtonian-fluid. Inspired by H. A. Lorentz, we speculate that electric charges may be extremely small hard spherical sources or spherical sinks with finite radii. Based on the spherical source and spherical sink model of electric charges, we derive Coulomb's law of interactions between static electric charges in vacuum. Further, we derive a reduced form of the Lorentz's force law for static electric charges in vacuum.

Intermetallic compounds are increasingly being expected to utilize in tribological environments, but to date the works are hindered by insufficient ductility at low and medium temperature. This paper presents a novel multiphase intermetallic alloy with the chemical composition of Mo-40Ni-13Si (at.%). Microstructure characterization reveals that a certain amount of ductile Mo phases formed during the solidification process of ternary Mo-Ni-Si alloy melt, which is undoubtedly beneficial to the ductility improvement of intermetallic alloy. Tribological properties of the designed alloy, including wear resistance, friction coefficient and metallic tribological compatibility, were evaluated under dry sliding wear test conditions at room temperature. Results suggested that the multiphase alloy possesses an excellent property for room-temperature wear applications, which is attributed to the unique microstructural features and thereby good combination in hardness and ductility. The corresponding wear mechanism is also reported by observing the worn surface, subsurface and wear debris of alloy, which to be found is soft abrasive wear.

Preclinical studies have identified glial cells as pivotal players in the genesis and maintenance of neuropathic pain after nerve injury associated with diabetes, chemotherapy, major surgeries, and virus infections. Satellite glial cells (SGCs) in the dorsal root and trigeminal ganglia of the peripheral nervous system (PNS) and astrocytes in the central nervous system (CNS) express similar molecular markers and are protective under physiological conditions. They also serve similar functions in the genesis and maintenance of neuropathic pain, downregulating some of their homeostatic functions and driving pro-inflammatory neuro-glial interactions in the PNS and CNS, i.e. “gliopathy”. However, the role of SGCs in neuropathic pain is not simply as “peripheral astrocytes”. We delineate how these peripheral and central glia participate in neuropathic pain by producing different mediators, engaging different parts of neurons, and becoming active at different stages following nerve injury. Finally, we highlight the recent findings that SGCs are enriched with proteins related to fatty acid metabolism and signaling such as Apo-E, FABP7, and LPAR1. Targeting SGCs and astrocytes may lead to novel therapeutics for the treatment of neuropathic pain.

Stem cells are undifferentiated cells which can give rise to any types of cells in our body. Hence, they have been utilized for various applications such as drug testing and disease modeling. However, for the successful of those applications, the survival and differentiation of stem cells into specialized lineages should be well controlled. Growth factors and chemical agents are the most common signals to promote the proliferation and differentiation of stem cells. However, those approaches holds several drawbacks such as the negative side effects, degradation or denaturation, and expensive. To address such limitations, nanomaterials have been recently used as a better approach for controlling stem cells behaviors. Graphene oxide is the derivative of graphene, the first 2D materials in the world. Recently, due to its extraordinary properties and great biological effects on stem cells, many scientists around the world have utilized graphene oxide to enhance the differentiation potential of stem cells. In this mini review, we highlight the key advances about the effects of graphene oxide on controlling stem cell growth and various types of stem cell differentiation. We also discuss the possible molecular mechanisms of graphene oxide in controlling stem cell growth and differentiation.

Attribute reduction is a core technique in the rough set domain and an important step in data preprocessing. Researchers have proposed numerous innovative methods to enhance the capability of attribute reduction, such as the emergence of multi-granularity rough set models, which can effectively process distributed and multi-granularity data. However, these innovative methods still have many shortcomings, such as how to deal with complex constraints and how to perform multi-angle effectiveness evaluations. Based on the multi-granularity model, this study proposes a new method of attribute reduction, namely using multi-granularity neighborhood information gain ratio as the measurement criterion. This method combines both supervised and unsupervised perspectives, and by integrating multi-granularity technology with neighborhood rough set theory, constructs a model that can adapt to multi-level data features. This model can select the optimal granularity level or attribute set according to the requirements. Finally, the proposed method is experimented with on 15 UCI datasets against six other attribute reduction algorithms. The experimental outcomes, upon analysis and comparative review, substantiate the reliability and consistency of the attribute reduction approach introduced in this study.

Formal Calculation uses an auxiliary form to calculate various nested sums and provides results in three forms. In addition to computation, it is also a powerful tool for analysis, allowing one to study various numbers in a unified way. This article contains many results of two types of Stirling numbers, associated Stirling numbers, and Eulerian numbers, making a great generalization of Euler polynomials, Wilson's theorem, and Wolstenholme's theorem, showing that they are just special cases. Formal Calculation provides a novel method for obtaining combinatorial identities and analyzing q-binomial.This article has obtained a large number of results in q-analogues, including inversion formulas for q-binomial coefficients. This article also introduces a theorem on symmetry.

This research was conducted to manufacture thermally expandable microspheres (TEMs) for vehicles’ underbody coating and to apply them on an industrial scale. TEMs heat resistance was studied depending on the ratios of a cross-linking agent and an initiator. This research focused on the content of a cross-linking agent and how it affected the results. The TEMs’ outer shell was thickened to solve the problem of the foam expansion ratio’s reduction that occurred due to the shrinkage after the maximum expansion (Tmax) was reached. After foaming, the cross-sectional thickness and surface of the sample with thickened outer shell were observed. The TEMs with the thickened shell showed the least shrinkage, which indicated excellent shrinkage stability, even after prolonged exposure to heat.

This research was conducted to manufacture thermally expandable microspheres (TEMs) for vehicles’ underbody coating and to apply them on an industrial scale. TEMs heat resistance was studied depending on the ratios of a cross-linking agent and an initiator. This research focused on the content of a cross-linking agent and how it affected the results. The TEMs’ outer shell was thickened to solve the problem of the foam expansion ratio’s reduction that occurred due to the shrinkage after the maximum expansion (Tmax) was reached. After foaming, the cross-sectional thickness and surface of the sample with thickened outer shell were observed. The TEMs with the thickened shell showed the least shrinkage, which indicated excellent shrinkage stability, even after prolonged exposure to heat.

The human mandible's cancellous bone, which is characterized by its unique porosity and directional sensitivity to external forces, is crucial for sustaining biting stress. Traditional CAD models fail to fully represent bone's anisotropic structure and thus depend on simple isotropic assumptions. For our research, we use the latest versions of nTopology and Creo Parametric software to make biomimetic Voronoi lattice models that accurately reflect the complex geometry and mechanical properties of trabecular bone. The porosity of human cancellous bone is accurately modeled in this work using biomimetic Voronoi lattice models. The porosities range from 70% to 95%, which can be achieved by changing the pore sizes to 1.0 mm, 1.5 mm, 2.0 mm, and 2.5 mm. Finite element analysis (FEA) was used to examine the displacements, stresses, and strains acting on dental implants with a buttress thread, abutment, retaining screw, and biting load surface. The results show that the Voronoi model accurately depicts the complex anatomy of the trabecular bone in the human jaw, compared to standard solid block models. The ideal pore size for biomimetic Voronoi lattice trabecular bone models is 2 mm, taking into account both the von Mises stress distribution over the dental implant, screw retention, cortical bone, cancellous bone, and micromotions. This pore size displayed balanced performance by successfully matching natural bone's mechanical characteristics. Advanced finite element analysis (FEA) improves biomechanical understanding of how bones and implants interact by creating more accurate models of biological problems and dynamic loading situations. This makes biomechanical engineering better.

This study aimed to learn disturbance information to effectively control multiple small unmanned surface vehicles (USVs) for marine research purposes at sea. The learned disturbance information was used to investigate the control of multiple USV swarms based on the leading–following formation technique. Numerous studies have already been conducted on swarm control using drones in the air; however, there has been a paucity of studies on swarm control in the sea. Contrary to swarm control in aviation, the fluid density of the sea is high, and the environment is constantly changing; thus, a robot system would be significantly affected by disturbances. This ultimately influences the maintenance of swarm formations and the accomplishment of missions [1,2]. Therefore, it is difficult to control numerous moving objects while maintaining a formation at sea by using the existing aerial drone swarm control technology. To solve this problem, we learned a long short-term memory (LSTM) model with time-series marine environmental data to predict maritime disturbances. Thereafter, the model was applied to a mission-based position control algorithm of each USV constituting the swarm to design a marine unmanned floating vessel swarm control system that can be applied to various marine environments. Specifically, to effectively control numerous small USVs for marine research purposes, ocean currents are learned using the LSTM algorithm, and the predicted ocean currents are used to generate a swarm USV control system for USV formations. In this study, a control system model of several small USVs equipped with two rear thrusters and a front lateral thruster was designed. The LSTM algorithm was learned using the previous ocean current data, and the velocity of the following ocean currents was predicted. The predictions were then used as a system disturbance to determine the thrust of the controller. To measure ocean currents in the sea when each USV moves, the velocity, azimuth, and position (latitude, longitude) data from the GPS mounted on the USV were used to measure the velocity and direction of the hull's movement. Further, the flow rate was measured using a flow rate sensor on a small USV. The USV movement and position were controlled using an artificial neural network-PID (ANN-PID) controller. This study entailed a comparative analysis of the designed USV model results and those generated by the simulator, including the behavior control rule of the USV swarm and the path of the actual USV swarm at sea. It was verified that the effectiveness of the USV mathematical model and behavior control rules. By comparing the movement path of the swarm USV with and without the disturbance learning algorithm and ANN-PID control algorithm applied to the designed simulator, the position error and maintenance performance of the swarm formation were analyzed, and the application results were compared.

Effective household and individual disaster preparedness can minimize physical harm and property damage during catastrophic events. To assess the risk and vulnerability of affected areas, it is crucial for relief agencies to understand the level of public preparedness. Traditionally, government agencies have employed nationwide random telephone surveys to gauge the public’s attitudes and actions towards disaster preparedness. However, these surveys may lack generalizability in certain affected locations due to low response rates or areas not covered by the survey. To address this issue and enhance the comprehensiveness of disaster preparedness assessments, we develop a framework that seamlessly integrates machine learning and simulation. Our approach leverages machine learning algorithms to establish relationships between public attitudes towards disaster preparedness and demographic characteristics. Using Monte Carlo simulation, we generate datasets that incorporate demographic information of the affected location based on government-provided demographic distribution data. The generated dataset is then input into the machine learning model to predict the disaster preparedness attitudes of the affected population. We demonstrate the effectiveness of our framework by applying it to Miami-Dade County, where it accurately predicts the level of disaster preparedness. With this innovative approach, relief agencies can have a clearer and more comprehensive understanding of public disaster preparedness.

J. C. Maxwell, B. Riemann and H. Poincar$\acute{e}$ have proposed the idea that all microscopic particles are sink flows in a fluidic aether. Following this research program, a previous theory of gravitation based on a mechanical model of vacuum and a sink flow model of particles is generalized by methods of special relativistic continuum mechanics. In inertial reference frames, we construct a tensorial potential which satisfies the wave equation. Inspired by the equation of motion of a test particle, a definition of a metric tensor of a Riemannian spacetime is introduced. Applying Fock's theorem, generalized Einstein's equations in inertial systems are derived based on some assumptions. These equations reduce to Einstein's equations in case of weak field in harmonic reference frames. There exist some differences between this theory and Einstein's theory of general relativity.

Temperature-responsive separation membranes can significantly change their permeability and separation properties in response to changes in their surrounding temperature, improving efficiency and reducing membrane costs. This study focuses on the modification of commercial polyvinylidene fluoride (PVDF) membranes with amphiphilic temperature-responsive copolymer and inorganic nanoparticles. We prepared an amphiphilic temperature-responsive copolymer which the hydrophilic poly(N-isopropyl acrylamide) (PNIPAAm) was side-linked to a hydrophobic polyvinylidene fluoride (PVDF) skeleton. Subsequently, PVDF-g-NIPAAm polymer and graphene oxide (GO) blended with PVDF to prepare temperature-responsive separation membranes. The results showed that temperature-responsive polymers with different NIPAAm grafting ratios were successfully prepared by adjusting the material ratio of PVDF to NIPAAm. PVDF-g-NIPAAm was blended with PVDF with different grafting ratios to obtain separate membranes with different temperature responses. GO and PVDF-g-NIPAAm formed a relatively stable hydrogen bond network, which improved the internal structure and mechanical properties of the membrane without affecting the temperature response, thus extending the service life of the membrane.

In recent decades, as eutrophication in inland and coastal waters (ICWs) has increased due to anthropogenic activities and global warming, so has the need for timely monitoring. Compared with traditional sampling and laboratory analysis methods, satellite remote sensing technology can provide macro-scale, low-cost, and near real-time water quality monitoring services. The Geostationary Ocean Color Imager (GOCI), integrated onboard the Communication Ocean and Meteorological Satellite (COMS) from the Republic of Korea, was the first geostationary ocean color observation satellite and was operational from April 1, 2011 to March 31, 2021. Over ten years, GOCI has observed oceans, coastal waters, and inland waters within its 2,500 km×2,500 km target area centered on the Korean Peninsula. The most attractive feature of GOCI, compared with other commonly used watercolor sensors, was its high temporal resolution (1h, eight times daily from 0 UTC to 7 UTC), providing the opportunity to monitor the quality of ICWs, where optical properties can change rapidly throughout the day. This systematic review aims to comprehensively review GOCI features and applications in ICWs, analyzing progress in atmospheric correction algorithms and water quality monitoring. Analyzing 123 articles from the Web of Science and China National Knowledge Infrastructure (CNKI) through a bibliometric quantitative approach, we examined GOCI’s strength and performance with different processing methods. These articles reveal that GOCI played an essential role in monitoring the ecological health of ICWs in its observation area in East Asia. GOCI has led the way to a new era of geostationary ocean satellites, providing new technical means for monitoring water quality in oceans, coastal zones, and inland lakes. We also discuss the challenges encountered by geostationary satellites in monitoring water quality and provide suggestions for improvements.

Sexual selection involving female choice or female preference (‘inter-sexual’ selection) or male-male competition (‘intra-sexual’ selection) is one of the key mechanisms for evolutionary diversification and speciation. In particular, sexual selection is recently suggested to be an important mode to drive the evolution of “novel” phenotype (i. e. “evolutionary novelty”). Despite extensive studies performed on sexually selected traits or male-specific ornaments (or weapon-like structures) with respect to their evolutionary origin and history and fitness benefits, relatively little is known about the molecular genetic mechanisms underlying their developmental process. However, with advances of genomic technologies (including whole transcriptome analysis using Next Generation Sequencing [NGS] techniques; RNA-Seq), progresses have been made to unveil the genetic background underpinning diverse sexually selected traits in different animal taxa. In the present review, we compile empirical data on the genes, genetic mechanisms or regulatory pathways underlying various sexually selected traits to explore whether the “common” genetic architectures shape the development and evolution of those traits across evolutionarily distant animal lineages. We show that the recruitment of pre-existing genetic network for a new purpose (i.e. gene network “co-option”) is rather widespread in the development and evolution of sexually selected traits, indicating that particular genes or gene-sets are repeatedly involved in different sexually selected traits. Information of genes or genetic mechanisms regulating the development of sexually selected traits would be an essential piece to complete a whole picture of the origin and evolution of sexually selected traits.

Attention deficit hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder that can diminish the quality of life of both children and adults in academic, occupational, and social contexts. The kynurenine pathway (KP) contains a set of enzymatic reactions involved in tryptophan (TRP) degradation. It is known to be associated with the risk of developing ADHD. This review will address the KP and underlying mechanism of inflammation in ADHD. Potential inflammatory biomarkers reported in the most recent studies are summarized. Although a strong neuroimmunological basis has been established due to advances of recent neurobiological research, the pathophysiology of ADHD remains unclear.

Objective: To use the ancient and modern medical record cloud platform (V2.3.5) to organize and explore the medication patterns of the "Three Causes, Extremity, and One Disease Syndrome Formula" by Chen Wuxuan, and to summarize its therapeutic ideas. Method: Collect and organize the "San Yin Si Tian Fang" in the "San Yin Ji Yi Zheng Fang Lun", and use the modern medical record cloud platform (V2.3.5) to conduct medication frequency statistical analysis, cluster analysis, and complex network analysis. As a result, a total of 16 Chinese herbal medicines were collected in the "Three Causes, Extreme and One Disease Syndrome Formula", involving 75 traditional Chinese medicines. Statistical analysis showed that roasted licorice was the most commonly used, followed by Pinellia ternata, papaya, ginger, and Poria cocos; Medications mainly include warm drugs, sweet and pungent flavors, as well as drugs that promote lung and spleen meridians. Cluster analysis can divide the above-mentioned traditional Chinese medicine into two groups, with specific grouping as follows. Group 1: ginger, white peony, aconite, papaya, and achyranthes bidentata; Group 2: roasted licorice, poria cocos, dried ginger, pinellia ternata, and green peel. Conclusion: The characteristics of the 16 prescriptions are biased towards Xin Gan Wen, emphasizing the regulation of the spleen and stomach, which may be related to the common use of prescription by doctors in the Song Dynasty and the tendency towards warm and dry medication.

This article investigates the impact of the foreign background of women directors on a firm’s corporate social responsibility (CSR) disclosure and performance. Using a dataset on listed firms on Shanghai and Shenzhen stock exchange from 2010 to 2019, we find that corporate boards with a higher proportion of women directors with foreign education experience tend to disclose more CSR information. CSR performance is also improved when there is a greater proportion of women directors with foreign education and work experience on a board. This study provides new insights into integrating stakeholder, social role, and neo-institutional theories to advance the understanding of CSR engagement in emerging economies.

Inspired by Dirac's large number hypothesis (LNH), Zeldovich proposed a relation between the cosmological constant (CC), the mass of a proton, the Planck constant and Newton's gravitational constant. Zeldovich's formula suggests that the substance which is responsible for CC may interact with elementary particles. Since Newton's gravitational constant and the Planck constant appear in Zeldovich's formula, these interactions may be related to gravitational phenomena and quantum phenomena. Following this clue, we propose a liquid droplet model of electron. Applying the Laplace's equation, Zeldovich's formula of CC is derived. Weinberg proposes a relation between the mass of a pion, the Planck constant, the Hubble constant, Newton's gravitational constant and the velocity of light in vacuum when discussing cosmological models with a varying constant of gravitation. Weinberg pointed out that this relation may not merely be regarded as a meaningless random combinations of these fundamental constants in physics. The Weinberg's relation is derived based on the critical mass density formula in the Friedmann model of the universe and Zeldovich's formula.

Safety management assessment systems for national level units’ in South Korea focus on responding capacity to cope with impending accident occurrence and danger occurrence. Since the four stage systems for prevention-preparation-response-recovery, which are core elements of national disaster management, assess the capacities by item such as those of individuals, disaster management departments, institutions, and management networks, there is no assessment function for the organic operation states of the entire systems. Therefore, for efficient disaster management, systematic evaluation indices that will enable active pre-checks in departments in organizations should be developed in place of the existing simply checking methods. In this study, an assessment model that will enable active disaster management centered on practice was developed using resilience engineering techniques. This model consists of disaster management items from the viewpoint of proactive responses instead of prevention. A total of 56 items that constitute four capacities; which are prediction (13 items), monitoring (14 items), proactive response (15 items), and safety learning (14 items) capacities were adopted in this model through Delphi analysis. Institutional capacities for infectious disease disaster management were evaluated based on this model and the resultant scores were prediction 4.41, monitoring 4.63, proactive response 4.69, safety learning 4.56 out of the full score of 5.0 points with an overall average of 4.51. This is an excellent capacity management score comparable to the score 4.57 of diagnosis of similar capacities by the WHO\_JEE (The Joint External Evaluation) in 2017. In fact, in 2015, when infectious disease capacity management was poor, in case of MERS (Middle East Respiratory Syndrome) infectious disease spread in South Korea, 36 patients died and 6,729 patients were isolated. However, through capacity reinforcement, in the case of MERS occurrence in South Korea in September 2018, a management capacity that prevented spread was shown as one confirmed case was completely cured in 10 days and 21 contacts were isolated and tested negative. Therefore, this capacity management assessment model is judged to be usable in enhancing disaster response and management capacities.

(1) Background: The analysis of athletic performance has always aroused great interest from sport scientist. This study utilized machine learning methods to build predictive models using a comprehensive CrossFit (CF) dataset, aiming to reveal valuable insights into the factors influencing performance and emerging trends.; (2) Methods: The study used Random Forest (RF) and Multiple Linear Regression (MLR) models to predict performance in four key weightlifting exercises within CF: clean &amp; jerk, snatch, back squat, and deadlift. Performance was evaluated using R-squared (R2) values and Mean Squared Error (MSE). Feature importance analysis was conducted using RF, XGBoost, and AdaBoost models.; (3) Results: The RF model excelled in deadlift performance prediction (R2 = 0.80), while the MLR model demonstrated remarkable accuracy in clean &amp; jerk (R2 = 0.93). Across exercises, clean &amp; jerk consistently emerged as a crucial predictor. The feature importance analysis revealed intricate relationships among exercises, with gender significantly impacting deadlift performance.; (4) Conclusions: This research advances our understanding of performance prediction in CF through machine learning techniques. It provides actionable insights for practitioners, optimize performance, and demonstrates the potential for future advancements in data-driven sports analytics.

The influences of doped hole transporting layer (HTL) on the performances of perovskite solar cells were studied. The influences of electrostatic and surface roughness effect by solvent additive doping were compared. The electrostatic effect of solvent additive doping was compared by addition of 1,8-diiodooctane and 1,8-dichlorooctane to the HTL layer. The surface roughness effect of solvent additive doping was examined using atomic force microscopy. The perovskite crystallinity by doping HTL was studied by X-ray diffraction. The conductivity of HTL was measured using four probe methods and was higher for doped devices. Enhanced conductivity of PEDOT:PSS film was also proved using fluorescence emission quenching. Long-term stability of the device was enhanced by doping HTL. The device with solvent additive exhibited much enhanced stability, retained over 80% of the initial PCE for 400 hours, while PCE of the device without solvent additive decreased to less than 80% after 200 hours. A very weak power microwave treatment was used for post-annealing of the fully fabricated devices. Post-annealing enhanced the lifetime of the device. Comparing different size of cells, the device lifetime was decreased as the cell area increased and as the size of the cell increased, the extent of lifetime enhancement by doping was increased.

This study presents a novel approach for quantifying the dynamics of monthly hydraulic geometry relationships in the Jingjiang reach of the Yangtze River by integrating leaf area index (LAI) data as an indicator of riparian vegetation. A comprehensive system of ordinary differential equations (ODEs) couples traditional power-law hydraulic geometry equations with LAI, capturing the influence of erosion control on channel morphology. The periodic delayed response theory and automatic differentiation techniques are employed to enhance the modeling framework's capabilities. Calibration and verification demonstrate the models' effectiveness in capturing overall trends in discharge, width, and depth dynamics, outperforming traditional constant-parameter approaches. However, model predictive abilities are limited under extreme climate conditions due to training on normal climate data. Key assumptions, including the periodic delayed response theory's neglect of peak discharges, simplified representation of artificial cut-offs, and reliance on remotely sensed data with limited local validation, introduce uncertainties. The proposed modeling framework shows potential for broader application to other river systems with appropriate adjustments. Future research could incorporate additional environmental factors, integrate models across scales, couple with advanced simulation techniques, and expand stability assessments beyond the riverbed index. By addressing related challenges, this integrated approach lays a foundation for enhancing understanding of river morphodynamics and channel stability.

This narrative review provides a thorough examination of medication-related osteonecrosis of the jaw (MRONJ), encompassing its etiology, the role of drug holidays, and contemporary treatment approaches. By systematically analyzing literature from 2022 to 2023, this paper synthesizes the latest findings and trends in MRONJ research. The study emphasizes the importance of a holistic understanding of MRONJ, beginning with its etiological factors, assessing the therapeutic implications of drug holidays, and evaluating the efficacy of current treatment modalities. This review aims to offer clinicians and researchers a consolidated resource, highlighting the intricacies of MRONJ management and proposing directions for future research. Through this comprehensive approach, the paper seeks to advance the understanding and treatment of MRONJ, ensuring an evidence-based, patient-centric approach in clinical practice.

Background and Objectives: Although there has been growing interest in the association of ADHD with anxiety, depression, suicidal ideation, and self-esteem, there is a lack of consistent results and these associations remain unclear. This study investigated the differential patterns of anxiety, depression, suicidal ideation, and self-esteem with regard to the presence of ADHD. Materials and Methods: The subjects were divided into a patient group and a control group. The patient group included 49 patients diagnosed with ADHD at the department of psychiatry of one university hospital. For the control group, 3,727 students were invited to complete a questionnaire. Of the 1,717 students who responded to the questionnaire, 245 were selected for patient-controlled studies. All the subjects were instructed to complete the Beck Suicide Ideation Scale, Children's Depression Inventory, Beck’s Depression Inventory, State-Trait Anxiety Inventory, and Rosenberg Self-Esteem Scale. Results: ADHD subjects experienced more anxiety, depression, and suicidal ideation as well as lower self-esteem compared to the control group comprising participants without ADHD. Conclusions: These findings suggest that ADHD symptoms may contribute to greater suicidal ideation through experienced depression, anxiety, and low self-esteem in school-aged children. Therefore, appropriate ADHD symptom management is necessary to reduce suicidal ideation among school-aged children with ADHD symptoms.

The Physics-Informed Neural Networks (PINNs) improve the efficiency of data utilization by combining physical principles with neural network algorithms and ensure that the predictions are consistent and stable with the physical laws. PINNs opens up a new approach to address inverse problems in fluid mechanics. Based on the single-relaxation-time lattice Boltzmann method (SRT-LBM) with the Bhatnagar-Gross-Krook (BGK) collision operator, the PINN-SRT-LBM model is proposed in this paper for solving the inverse problem in fluid mechanics. The PINN-SRT-LBM model consists of three components. The first component involves a deep neural network that predicts the equilibrium control equations in different discrete velocity directions within SRT-LBM. The second component employs another deep neural network to predict non-equilibrium control equations, enabling inference of the fluid's non-equilibrium characteristics. The third component, a physics informed function translates the outputs of the first two networks into physical infor-mation. By minimizing the residuals of the physical partial differential equations (PDEs), the physics informed function infers relevant macroscopic quantities of the flow. The model evolves two sub-models applicable to different dimensions, named PINN-SRT-LBM-I and PINN-SRT-LBM-II models according to the construction of the physical informed function. The innovation of this work is the introduction of SRT-LBM and discrete velocity models as physical drivers into the neural network through the interpretation function. Therefore, PINN-SRT-LBM allows the neural network to handle inverse problems of various dimensions and focus on problem-specific solving. Experimental results confirm the accurate prediction of flow infor-mation at different Reynolds numbers within the computational domain. Relying on the PINN-SRT-LBM models, inverse problems in fluid mechanics can be solved efficiently.

Osteoporosis, often linked to increased osteoclast activity due to menopause or aging, was the focus. In this study, the inhibitory effects of Salicornia europaea L. (SE) water extract of desalted SE (WSE) were investigated on osteoclast differentiation and bone loss in ovariectomized mice. The findings revealed that WSE effectively inhibited RANKL-induced osteoclast differentiation, as evidenced by TRAP staining, and also suppressed bone resorption and F-actin ring formation in a dose-dependent manner. Gene expressions related to osteoclast differentiation, including NFATc1, TRAP, cathepsin K, and DC-STAMP, were downregulated by WSE. Oral administration of WSE improved bone density and structural parameters in ovariectomized mice. Dicaffeoyl quinic acids (DCQAs) and saponins in WSE were detected, with 3,4-, 3,5-, and 4,5-DCQA isolated and identified. All tested DCQAs, including the aforementioned types, inhibited osteoclast differentiation, bone resorption, and the expression of osteoclast-related genes. Furthermore, WSE and DCQAs reduced ROS production mediated by RANKL. These results indicate the potential of WSE and its components, DCQA, as preventive or therapeutic agents against osteoporosis and related conditions.

Human monkeypox, caused by monkeypox virus, has spread unprecedentedly to more than 100 countries since May 2022. Here we summarized the epidemiology of monkeypox through a literature review and elucidated the risks and elimination strategies of this outbreak mainly based on the summarized epidemiology. We demonstrated that monkeypox virus became more contagious and less virulent in 2022, which could result from the fact that the virus entered a special transmission network favoring close contacts (i.e., sexual behaviors of men who have sex with men outside Africa) and the possibility that the virus accumulated a few adaptive mutations. We gave the reasons to investigate whether cattle, goats, sheep, and pigs are susceptible to monkeypox virus and whether infection with monkeypox virus could be latent in some primates. We listed six potential scenarios for the future of the outbreak (e.g., the outbreak could lead to endemicity outside Africa with increased transmissibility or virulence). We also listed multiple factors aiding or impeding the elimination of the outbreak. We showed that the control measures strengthened worldwide after the World Health Organization declared the outbreak a public health emergency of international concern (PHEIC) could eliminate the outbreak in 2022. We clarified eight strategies, i.e., publicity and education, case isolation, vaccine stockpiling, risk-based vaccination or ring vaccination, importation quarantine, international collaboration, and laboratory management, for the elimination of the outbreak.

This study examines the negative impacts of dark stores on the urban environment from three perspectives: land use, transportation, and streetscape. It is conducted on B-Mart, a representative dark store in South Korea. First, in terms of land use, we find that dark stores that function as logistics facilities conflict with the surrounding land use. Second, by analyzing the location of dark stores and the hourly traffic volume of delivery vehicles, we find that the impact on the surrounding transportation infrastructure and pedestrian traffic is not as significant as previously claimed. However, during the transportation and loading process of the dark store, several problems such as traffic violations, illegal parking, and illegal loading were observed, posing a risk to nearby vehicles and pedestrians. Third, in terms of streetscapes, the location of dark stores on the ground floor of buildings can harm streetscapes. The current urban planning system in South Korea does not clearly define the status and function of dark stores, making it unclear how to manage them. Therefore, it is necessary to clarify their legal definition and introduce urban planning and design guidelines that are consistent with their appropriate location and appearance.

Social robots may become an innovative means to improve the well-being of individuals. Earlier research showed that people easily self-disclose to a social robot even in cases where that was unintended by the designers. We report on an experiment of self-disclosing in a diary journal or to a social robot after negative mood induction. The off-the-shelf robot was complemented with our inhouse developed AI chatbot and could talk about ‘hot topics’ after having it trained with thousands of entries on a complaint website. We found that people who felt strong negativity after being exposed to shocking video footage benefited the most from talking to our robot rather than writing down their feelings. For people less affected by the treatment, a confidential robot chat or writing a journal page did not differ significantly. We discuss emotion theory in relation to robotics and possibilities for an application in design (the emoji-enriched ‘talking stress ball’). We also underline the importance of - otherwise disregarded - outliers in a data set that is of a therapeutic nature.

A simple design of an ultrathin six-band polarization-insensitive terahertz perfect metamaterial absorber (PMMA) composed of a metal cross-cave-patch resonator (CCPR) placed over a ground plane was proposed and investigated numerically. The numerical simulation results demonstrate that the average absorption peaks are up to 95% at six resonance frequencies with high quality-factors (>65). In addition, the absorption properties can be kept stability for both normal incident transverse magnetic (TM) and transverse electric (TE) waves. The physical mechanism behind the observed high level absorption is illustrated by the electric and power loss density distributions. The different absorption mainly originates from the higher order multipolar and multipolar plasmon resonance of the structure, which are sharp different to the most previous studies of the PMMAs. Furthermore, the resonance absorption of the PMMA can be tunable by varying the geometric parameters of the unit cell.

A simple design of an ultrathin six-band polarization-insensitive terahertz perfect metamaterial absorber (PMMA) composed of a metal cross-cave-patch resonator (CCPR) placed over a ground plane was proposed and investigated numerically. The numerical simulation results demonstrate that the average absorption peaks are up to 95% at six resonance frequencies with high quality-factors (>65). In addition, the absorption properties can be kept stability for both normal incident transverse magnetic (TM) and transverse electric (TE) waves. The physical mechanism behind the observed high level absorption is illustrated by the electric and power loss density distributions. The different absorption mainly originates from the higher order multipolar and multipolar plasmon resonance of the structure, which are sharp different to the most previous studies of the PMMAs. Furthermore, the resonance absorption of the PMMA can be tunable by varying the geometric parameters of the unit cell.

There are two contrary opinions regarding the risk if mainland China (MC) moves away from its zero-COVID policy. Some experts think the risk shall be much lower than influenza as per MC’s own COVID-19 case fatality rate (CFR), while some other experts think the risk shall be much higher than influenza as per the COVID-19 CFRs of other regions. We elucidate here that this and multiple other striking differences in the CFR between various scenarios all support and substantially resulted from the view that good IDM is highly powerful to mitigate COVID-19, where IDM (isolation-disinfection-maintenance) means isolation of COVID-19 cases from other people, disinfection of their living environments, and health maintenance (e.g., rest, nutrition, breathing). The high effect of good IDM is also supported by the theoretic functions of IDM in minimizing co-infections and maintaining body functions, and the fact that all the 505 COVID-19 deaths reported in MC in 2022 before May 5 died directly of severe underlying diseases with COVID-19. Although it is tough for people in poverty to obtain good IDM, good IDM can be feasible at home for the most mild cases and in hospitals for the most severe cases. Therefore, good IDM can be crucial to mitigating COVID-19 worldwide. It also suggests that the risk for China to end its zero-COVID policy depends on China’s control policies or measures. Based on the effect of IDM, the cautious co-existence policy was proposed for COVID-19 control. This policy could reduce the whole death toll in MC because good IDM is non-specific and can reduce deaths of various other diseases. The cautious co-existence policy (non-specific) and the vaccination policy (specific) aid each other to mitigate COVID-19, and they cannot replace each other. Those who are qualified in health for vaccination should be vaccinated against COVID-19 timely.

The digital economy (DE) has become a major force driving the optimization and upgrading of industrial structures (ISOU), and research on the driving mechanism has yet to be verified. To this end, the driving influence of DE on the ISOU is targeted, and the role played by economic resilience (ER) and innovation is explored. Based on the panel data of 31 provinces in China from 2011 to 2020, the driving influence of the DE on the ISOU is analyzed using a two-way fixed-effects model. The empirical study finds that the DE presents a positive driving effect on both industrial structure advancement and rationalization, and the driving effect is still significant after the addition of control variables and the robust-type test with one period of lag; the DE presents regional differences in ISOU, with the driving effect of the DE on industrial structure advancement in the eastern region having a more significant performance than that of the central and western regions, and the driving influence on the rationalization of industrial structure in the eastern and western regions exceeds that in the central region; the impact of DE on the ISOU has a mediating role through innovation, ER has a moderating role in the process, and innovation as a partial mediator also has a threshold effect, and finally countermeasure suggestions are put forward.

Foam concrete is a highly cellularized cementitious material that undergoes extensive plastic deformation when loaded to failure. Under compression, the foam structure gets progressively crushed at a steady stress stage such that a substantial amount of energy is dissipated. Understanding foam concrete crushing behavior is of special importance for its engineering applications such as energy absorber, but the current studies are insufficient to define material properties for design of field applications. This study characterizes the crushing strength and foam modulus of samples with penetration test and resonant frequency test, respectively. A four-phase crushing behavior is observed. The yield strength and plateau strength are identified to characterize the foam crushing. Using the experimental inputs, the modulus-strength constitutive equations are then established. These findings are useful for expanding the knowledge of normal concrete to studies on foam concrete, as well as design of applications.Foam concrete is a highly cellularized cementitious material that undergoes extensive plastic deformation when loaded to failure. Under compression, the foam structure gets progressively crushed at a steady stress stage such that a substantial amount of energy is dissipated. Understanding foam concrete crushing behavior is of special importance for its engineering applications such as energy absorber, but the current studies are insufficient to define material properties for design of field applications. This study characterizes the crushing strength and foam modulus of samples with penetration test and resonant frequency test, respectively. A four-phase crushing behavior is observed. The yield strength and plateau strength are identified to characterize the foam crushing. Using the experimental inputs, the modulus-strength constitutive equations are then established. These findings are useful for expanding the knowledge of normal concrete to studies on foam concrete, as well as design of applications.

Though Moracin D derived from Morus alba was known to have anti-inflammatory and antioxidant activities, the underlying antitumor mechanism of Moracin D was never unveiled so far. Thus, in the recent study, the apoptotic mechanism of Moracin D was elucidated in breast cancer cells. Herein, Moracin D exerted significant cytotoxicity in MDA-MB231 and MCF7 cells. Also, Moracin D increased sub G1 population, cleaved poly (ADP-ribose) polymerase (PARP) and attenuated the expression of pro-cysteine aspartyl-specific protease (procaspase 3), c-Myc, cyclin D1, B-cell lymphoma 2 (Bcl-2),and X-linked inhibitor of apoptosis protein (XIAP) in MDA-MB231 cells. Of note, Moracin D reduced expression of Forkhead box M1 (FOXM1), β-catenin, Wnt3a, and upregulated glycogen synthase kinase 3 beta (GSK 3β) on Tyr216 along with disturbed binding of FOXM1 with β-catenin in MDA-MB-231 cells. Conversely, GSK3β inhibitor SB216763 reversed the apoptotic ability of Moracin D to reduce expression of FOXM1, β-catenin, pro-caspase3 and pro-PARP in MDA-MB-231 cells. Overall, these findings provide novel insight that Moracin D inhibits proliferation and induces apoptosis via suppression of Wnt3a/FOXM1/β-catenin signaling and activation of caspase and GSK3β

In recent years, the taxonomy of the families of Phenuiviridae, Nairoviridae, and Peribunyavidae in Bunyavirales was updated frequently, because many novel viruses in these families have been identified and the species demarcation criteria of these families have been changed. As per these criteria and sequence analysis, we found that the taxonomy of 19 species in these families should be revised. We presented six proposals for optimizing virus species taxonomy using the examples from these families. First, the species demarcation criteria for the same family (e.g., Peribunyavidae) should be unified. Second, the methods and parameters for the taxonomic calculation in the same order (e.g., Bunyavirales) should be unified. Third, virus species taxonomy should be based on phylogenetic relationships, rather than a cutoff value of sequence identities that is a self-contradictory demarcation criterion, although sequence identities aid virus taxonomy greatly. Fourth, virus species taxonomy should be based on the phylogenetic relationship of a key viral gene (e.g., the RdRp gene of Bunyavirales), which is important for the taxonomy of virus recombinants or reassortants. Fifth, a virus can be demarcated without a species before its biomedical significance has been revealed. Sixth, names of all viruses and virus species should be constituted exclusively with common characters (English letters and Arab numbers), to minimize difficulty in spelling and communication. These proposals are rational, flexible, and can accommodate all known viruses. They can also bridge the taxonomy history and the future demands due to their flexibility.

The concept of using special electrical circuit design realize a "cold resistors", that is, an active resistor circuitry with lowered effective noise temperature, was first introduced about 80 years ago. Later on, various kinds of artificial resistors were applied in different research areas, such as gravitational wave detection, photo-amplifiers and quartz oscillators. Their proofs of concepts were experimentally proved. Unfortunately, the complete theory was not found even though several attempts had been published, sometimes with errors. In this paper, we describe a correct and complete circuit theoretical model of a cold resistor system. The results are confirmed by computer simulations. A design tools for this circuit is also shown.

This study analyzes the modeling and dynamics of a novel passive in Multi-Degree-of-Freedom (MDOF) vibration isolation platform which can achieve significant isolation effect. Symmetrical Scissor-Like structures (SLSs) are utilized in the proposed MDOF isolation platform as the supporting and isolation elastic components. Based on the mathematical modeling and theoretical analysis of the MDOF vibration isolation system with SLSs, the effect of structural parameter and joint friction on stiffness and damping properties is investigated. It is shown that due to geometric relations within the SLSs, the natural frequencies can be reduced via adjusting structural parameters of the SLS for different direction vibration isolation. Theoretical and experimental results show that the SLS isolation platform can achieve much better loading capacity and vibration isolation performance simultaneously by only using linear passive components because of the MDOF adjustable stiffness property. Therefore, with low costing and energy consumption, the proposed novel isolation platform can provide the improvement of vibration suppression in various engineering practices.

Gol'denveizer's problem of a torus has been analyzed by Audoly and Pomeau (2002) and Sun (2021). However, all of the investigations of Gol'denveizer's problem of an elastic torus have been linear. In this paper, the finite element method is used to more accurately address this problem. Furthermore, Sun (2021) cannot be solved by nonlinear analysis. We research the nonlinear mechanical properties of Gol'denveizer's problem of circular and elliptic tori, and relevant nephograms are given. We study the buckling of Gol'denveizer's problem of an elastic torus, and propose failure patterns and force-displacement curves of tori in the nonlinear range. Investigations reveal that circular tori have more rich buckling phenomena as the parameter a increases. Gol'denveizer's problem of the buckling of an elliptic torus is analyzed, and we find a new buckling phenomenon called a "skirt." As a/b increases, the collapse load of an elliptic torus of the Gol'denveizer problem is enhanced gradually.

This paper aims to develop a hierarchical risk assessment model using the newly-developed evidential reasoning (ER) rule, which constitutes a generic conjunctive probabilistic reasoning process. In this paper, we first provide a brief introduction to the basics of the ER rule and emphasize the strengths for representing and aggregating uncertain information from multiple experts and sources. Further, we discuss the key steps of developing the hierarchical risk assessment framework systematically, including (1) formulation of risk assessment hierarchy, (2) representation of both qualitative and quantitative information, (3) elicitation of attribute weights and information reliabilities, (4) aggregation of assessment information using the ER rule and (5) quantification and ranking of risks using utility-based transformation. The proposed hierarchical risk assessment framework can potentially be implemented to various complex and uncertain systems. A case study on the fire/explosion risk assessment of marine vessels demonstrates the applicability of the proposed risk assessment model.

Aiming at the problems of high labor intensity and high cost of manual picking, high loss rate of mechanical picking seeds, low mechanization level and difficult to guarantee the quality of picking plates in the process of picking plates of edible sunflower. Based on the principle of manual plate taking, a plate taking control system for sunflower harvesting table was designed. Through the research and analysis of the principle of taking the plate of the edible sunflower harvesting table. According to the actual operation requirements, the overall scheme of the sunflower plate control system is determined, and the control strategy of imitating artificial low loss harvesting is designed. To reduce the grain loss in the process of taking the plate and improve the control accuracy of the system on the movement speed and displacement of the key components in the process of taking the plate, a trapezoidal acceleration and deceleration control algorithm is designed as the control algorithm of taking the plate. To verify the working performance of the plate control system, with the absolute error, relative error and total loss rate of the harvest as objectives. The bench and field verification experiments were both carried out. The bench experiment showed that the speed error of the plate parts was not more than 0.028 m/s. In the bench experiments of the device, the maximum positioning error was 1.25 mm, the average relative error is only 0.94 %, and the grain loss rate was not more than 2.26 %. It result showed that the system algorithm was reliable, the positioning accuracy was high, and the taking plate operation can be completed well. The field verification experiment showed that the forward speed of the unit was in the range of 0.4~0.8 m/s, and the total loss rate of harvest was less than 5 %. When the forward speed is 0.6 m/s, the minimum harvest loss rate is 2.32 %, and which indicated the control system meets the requirements of sunflower harvesting operation.

Management of Australia’s largest river system, the Murray-Darling Basin (MDB) is controversial, addressing conflicting demands from stakeholders, including irrigators, the agriculture industry, indigenous groups, and the environmental lobby. Oversight is concentrated in a single agency, the MDB Authority, but climate change and the water market have contributed to uncertainty over the Basin’s environmental sustainability. This paper reports on preliminary research in South Australia’s Riverland, one of Australia’s most important wine, citrus, nuts, and stone fruit production areas. It focuses on the Renmark Irrigation Trust (RIT), supplying water to irrigators, primarily horticulturalists. It investigates the chief risks perceived and future-plans in face of concerns over variable water flows and economic uncertainty. Using sequential mixed methods, a questionnaire survey supplied information from a sample of irrigators, covering land use, on-farm environmental actions, risks, decision making, recent and proposed changes to farm management, and attitudes to the MDB Plan and the water market. Focus groups and interviews then enabled key topics to be addressed in greater depth. The RIT’s contribution to river restoration is highlighted, with its plans for additional on-farm water stewardship investigated. There are high levels of uncertainty regarding future viability of smallholdings, including unintended consequences from the water market (e.g., increasing areas under water hungry almonds), the role of water brokers, and environmental viability of the river system linked to climate change. More optimistic voices point to increased diversity of production, resilience of the local horticultural industry, and new entrants in the form of hobby and part-time producers.

Discrete Double Hilbert Exponential sums along polynomials. This is preprint version (not peer reviewed) And we now check the proof of (ii) of Lemma 3.2 whether it is really true.

This project focuses on using machine learning classification algorithms to determine whether two people are 6 feet apart or not. Two Raspberry Pis were used simulate smart phones. RSSI values of the Bluetooth beacons transmitted between the Raspberry Pis were collected and recorded to train the classifier. The Gaussian Support Vector Machine Classifer yielded the highest testing accuracy of 79.670 and the Decision Tree Classifier yielded the highest AUC of 0.80.

The advent of deep learning has completely reshaped our world. Now, our daily life is fulfilled with many well-known applications that adopt deep learning techniques, such as self-driving cars and face recognition. Furthermore, robotics developed more forms of technology which share the same principle with face recognition, such as hand pose recognition and fingerprint recognition. Image recognition technology requires a huge database and various learning algorithms, such as convolutional neural network and recurrent neural network, that requires lots of computational power, such as CPUs and GPUs. Thus, clients could not be satisfied with the computational resource of the local machine. The cloud resource platform emerged at a historic moment. Docker containers play a significant role of microservices-based applications in the next generation. However, it could not guarantee the quality of service. From clients’ perspective, they have to balance the budget and quality of experiences (e.g. response time). The budget leans on individual business owners and the required Quality of Experience (QoE) depends on usage scenarios of different applications, for instance, an autonomous vehicle requires real-time response, but, unlocking your smartphone can tolerate delays. Plenty of on-going projects developed user-oriented optimization resource allocation to improve the quality of the service. Considering the users’ specifications, including accelerating the training process and specifying the quality of experience, this thesis proposes two differentiate containers scheduling for deep learning applications: TRADL and DQoES .

Vase life is one of the most important factors that determine the marketability of cut flowers and is greatly affected by the water balance. In recent years, cut hydrangea flowers are increasingly consumed as decorations for various events. However, the vase life of cut hydrangea flowers varies greatly depending on the postharvest solution management. Therefore, this study investigated the vase life, solution uptake, water balance, and relative fresh weight of freshly harvested hydrangea (Hydrangea macrophylla ‘Verena’) according to the three types of holding solutions (tap water, 1% chrysal professional Ⅲ (CPⅢ), 2% sucrose + 250 mg/L 8-hydroxquinoline + 100 mg/L citric acid (SHQC)) and the combination solutions (pretreatment; tap water, 0.1% chrysal RVB (RVB), floralife quickdip (FQ), transport; tap water, CPⅢ, floralife clear (FC), preservatives; CPⅢ, FC) for each distribution stage (pretreatment-transport-consumer). In the preservative comparison experiment, compared with the control, CPⅢ treatment and SHQC treatment significantly increased the vase life in 2019 (0.7 days, 3.4 days) and 2020 (1.4 days, 3.1 days), respectively. In the comparative experiment by solution combination, the group (RVB, FQ) using the pretreatment significantly extended the vase life by 4.6 days and 5.9 days compared to the tap water treatment. It was also determined that the same treatment increased overall solution uptake, maintained water balance longer, and increased relative fresh weight. These results confirm the importance of holding solutions and pretreatments, suggesting that appropriate pretreatments and preservatives should be used to improve the marketability of cut hydrangea flowers.

Sweetpotato is an important miscellaneous grain crop in China, which is threatened by a variety of diseases and insect pests in the process of cultivation and production. sweetpotato stem rot is one of the common sweetpotato diseases, which seriously affects the yield and quality of sweetpotato. However, there are few studies on the mechanism of resistance to stem rot in sweetpotato. In this study, transcriptome sequencing analysis was carried out on the samples at different stages (T1, T2, T3) of stem rot pathogen infecting Xushu 48, and 44839 (T1-VS-T2), 81436 (T1-VS-T2) and 61932 (T2-VS-T3) differentially expressed genes (DEGs) were obtained. The DEGs were mainly concentrated in Alanine, aspartate and glutamate metabolism (ko00250), Carbon fixation in photosynthetic organisms (ko00710) and Amino sugar and nucleotide sugar metabolism (ko00520) and some candidate genes related to plant pathogen infection, such as receptor-like protein kinase (RLK5, RLK7), LRR receptor-like serine/threonine-protein kinase (SERK1), bHLH137, ERF9, MYB73 and NAC053, were screened. The results of this study provide genetic resources for the research on stem rot resistance of sweetpotato and provide theoretical basis for sweetpotato resistance breeding.

This study examined the tourism spatial distribution of nine cities in the Fujian province and assessed the impacts of COVID-19. The modified gravity model found that it was widely dispersed, with uneven and relatively independent tourism development in different cities. The social network analysis showed that tourism connections across cities were significantly reduced after the pandemic. The impacts of brand awareness and transport accessibility on spatial networks were positive in pre-pandemic but became negative during the pandemic. In contrast, tourist volume had negative impacts on spatial networks in pre-pandemic but had positive ones during the pandemic. Tourism resources and market performance had significantly positive impacts in the post-pandemic era. These findings provide advice on tourism recovery and destination management in coping with future critical events. It also contributes to the theoretical gravity framework in tourism and the research scope of the social networks analysis at the city level.

Although global life expectancy has increased over the past 20 years due to improvements in managing infectious diseases, one in five people still succumbs to infections. Humanity is tirelessly working towards developing vaccines and antimicrobial agents in response to this ongoing threat. However, pathogens continue to acquire numerous resistance mechanisms and proliferate. Meanwhile, the COVID-19 pandemic has prompted us to recognize that focusing solely on the killing strategies of immunology and microbiology in complex and multisystemic infectious diseases is insufficient for understanding survival. In essence, there is a need for a treatment approach centered on disease tolerance, capable of alleviating pathology and/or promoting physiological functions in conjunction with the existing strategies of host immune response and pathogen destruction. Against this backdrop, this narrative review comprehends and introduces microbiome therapeutics, which recently garnered attention as next-generation treatments regarding two defense strategies against infectious diseases. First, we delineate the application of existing probiotics and then the microbiome in infectious diseases. Subsequently, we expand this concept to encompass host microbiome crosstalk and present related microbiome therapeutics' current status and direction. Ultimately, the review presents a fresh perspective on understanding microbiome therapeutics in infectious diseases based on a cooperative defense system.

The testing of high-dimensional normality has been an important issue and has been intensively studied in literatures, it depends on the Variance-Covariance matrix of the sample, numerous methods have been proposed to reduce the complex of the Variance-Covariance matrix. The principle component analysis(PCA) was widely used since it can project the high-dimensional data into lower dimensional orthogonal space, and the normality of the reduced data can be evaluated by Jarque-Bera(JB) statistic on each principle direction. We propose two combined statistics, the summation and the maximum of one-way JB statistics, upon the independency of each principle direction, to test the multivariate normality of data in high dimensions. The performance of the proposed methods is illustrated by the empirical power of the simulated data of normal data and non-normal data. Two real examples show the validity of our proposed methods.

Metabolites are essential intermediate products in metabolism, and metabolism dysregulation indicates different types of diseases. Previous studies have shown that cigarette smoke dysregulated metabolites; however, limited information is available with electronic cigarette (E-cig) vaping. We hypothesized that E-cig vaping and cigarette smoking altered systemic metabolites, and we propose to understand the specific metabolic signature between E-cig users and cigarette smokers. Plasma from non-smoker controls, cigarette smokers, and e-cig users were collected, and metabolites were identified by UPLC–MS (Ultraperformance liquid chromatography-mass spectrometer). Nicotine degradation was activated by e-cig vaping and cigarette smoking with increased concentrations of cotinine, cotinine N-oxide, (S)-nicotine, and (R)-6-hydroxynicotine. Additionly, we found significant decreased concentrations in metabolites associated with tricarboxylic acid (TCA) cycle pathways in e-cig users verses cigarette smokers, such as: D-glucose, (2R,3S)-2,3-dimethylmalate, (R)-2-hydroxyglutarate, O-phosphoethanolamine, malathion, D-threo-isocitrate, malic acid, and 4-acetamidobutanoic acid. Cigarette smoking significant up-regulated sphingolipid metabolites, such as D-sphingosine, ceramide, N-(octadecanoyl)-sphing-4-enine, N-(9Z-octadecenoyl)-sphing-4-enine, and N-[(13Z)-docosenoyl]sphingosine, verses e-cig vaping. Overall, e-cig vaping dysregulated TCA cycle realted metabolites while cigarette smoking altered sphingolipid metabolites. Both e-cig and cigarette smoke increased nicotinic metabolites. Therefore, specific metabolic signature altered by e-cig vaping and cigarette smoking could serve as potential systemic biomarkers for early cardiopulmonary diseases.

The purpose of this study is to propose a consecutive manufacturing process system to secure the productivity of excellent STKN540B steel tube in the respect of economy and safety as the supporting material for mega structures such as building, bridge and ship. The components of consecutive manufacturing are press-bending, orbital auto welding and steel tube correction. By using STKN540B a high-strength steel material with low yield point that requires a special manufacturing process unlike other steel materials, an actual tube manufacturing is carried out at each stage in this experimental study. With this, the quality of steel tube and the efficiency of the manufacturing process are analyzed to draw out some points to improve in the future.

This study entailed the design and analysis of a 400 m-class underwater glider operated by a bladder-type buoyancy engine. The underwater glider was designed for high-speed movement with a maximum velocity of 2 knots. The shape of the hull was designed to reduce water resistance using the Myring hull profile equation. The reliability was verified by performing simulations using resistance coefficients. The relationship between the control value of the ballast discharged from the buoyancy engine and the glider's speed according to the path angle was analyzed. Further, the relationship between the optimal glide angle and the design control value of the ballast was derived, and the optimal glider speed was estimated accordingly. Based on the analysis results, a bladder-type buoyancy engine was developed, and the maximum speed of the tested underwater glider was measured via sea trials.

To identify gender- and age-related associations between adult dental checkups and unmet dental care needs, we analyzed data of 14,000 participants, ages ≥ 19, from the 7th Korea National Health and Nutrition Examination Survey (2016–2018) (KNHANES VII). Data was collected via self-report questionnaires and interviews. Complex sample chi-square test and multiple logistic regression analysis indicated 31.7% of participants had unmet dental care needs; in the prior 12months, 67.1% had not utilized dental services, and 43.3% had not received dental checkups. Odds ratios (ORs) for dental checkups and unmet dental needs were 8.87 (CI:7.80–10.09, p < 0.001) for those who used dental services and 1.28 (CI: 1.13–1.44, p < 0.001) for those who had not. Significant age-dependent associations between those not receiving dental checkups and the rate of unmet dental care include men and women aged 50–59 years (OR: 1.77; CI = 1.22–2.58 and OR: 1.43; CI: 1.02–2.02; p = 0.040, respectively) and women ≥ 70 years (OR = 1.79, CI = 1.20–2.66, p = 0.004). Reducing unmet dental care needs requires greater public health promotion and education regarding regular dental checkups; additional practical strategies could enhance dental checkup compliance.

A conjugate compound 5, (E)-6-hydroxy-2-oxo-2H-chromen-7-yl 3-(4-hydroxy-3-methoxyphenyl)acrylate, of 6,7-hydroxycoumarin (esculetin) 3 and (E)-3-(4-hydroxy-3-methoxyphenyl)- acrylic acid (ferulic acid) 1 was prepared in 61% yield by the esterification reaction of a protected ferulic acid 2a with esculetin 3 in the presence of triethylamine in dichloromethane for 3 h, followed by deprotection using 3M HCl. The structure of compound 5 was confirmed by 1H, 13C NMR spectroscopy, mass-spectrometry and elemental analysis.

Lord Kelvin believed that the electromagnetic aether must also generate gravity. Presently, we have no methods to determine the density of the electromagnetic aether, or we say the $\Omega(1)$ substratum. Thus, we also suppose that vacuum is filled with another kind of continuously distributed substance, which may be called the $\Omega(2)$ substratum. Based on a theorem of V. Fock on the mass tensor of a fluid, the contravariant energy-momentum tensors of the $\Omega(1)$ and $\Omega(2)$ substrata are established. Quasi-static solutions of the gravitational field equations in vacuum are obtained. Based on an assumption, relationships between the contravariant energy-momentum tensors of the $\Omega(1)$ and $\Omega(2)$ substrata and the contravariant metric tensor are obtained. Thus, the cosmological constant is calculated theoretically. The $\Omega(1)$ and $\Omega(2)$ substrata may be a possible candidate of the dark energy. According to the theory of vacuum mechanics, only those energy-momentum tensors of discrete or continuously distributed sinks in the $\Omega(0)$ substratum are permitted to act as the source terms in the generalized Einstein's equations. Thus, the zero-point energy of electromagnetic fields is not qualified for a source term in the generalized Einstein's equations. Some people believed that all kinds of energies should act as source terms in the Einstein's equations. It may be this unwarranted belief that leads to the cosmological constant problem. The mass density of the $\Omega(1)$ and $\Omega(2)$ substrata is equivalent to that of around $3$ protons contained in a box with a volume of $1$ cubic metre.

When solving the Einstein's equations for an isolated system of masses, V. Fock introduces harmonic reference frame and obtains an unambiguous solution. Further, he concludes that there exists a harmonic reference frame which is determined uniquely apart from a Lorentz transformation if suitable supplementary conditions are imposed. It is known that wave equations keep the same form under Lorentz transformations. Thus, we speculate that Fock's special harmonic reference frames may have provided us a clue to derive the Einstein's equations in some special class of non-inertial reference frames. Following this clue, generalized Einstein's equations in some special non-inertial reference frames are derived based on the theory of vacuum mechanics. If the field is weak and the reference frame is quasi-inertial, these generalized Einstein's equations reduce to Einstein's equations. Thus, this theory may also explain all the experiments which support the theory of general relativity. There exist some differences between this theory and the theory of general relativity.

Pea shoots is a popular vegetable in certain regions of the world due to their unique taste and abundance of health-promoting phytochemicals. The perishable nature and susceptibility of root rot of pea shoots necessitate a new soilless production system located close to the market. This study compared the growth of pea shoots using various cultivation methods in LED plant factory. The results showed that early topping (4 days after transplanting, ET) promoted early harvest compared to later topping (20 days after transplanting, LT) and increased the number of harvested shoots by extending the harvest time to 2.8 times, ultimately resulting in a substantial yield improvement. Moreover, the yield of ET with lower planting density (72 plants m-2, ET-LD) was 8.7% higher than ET with higher planting density (126 plants m-2, ET-HD). Particularly, the average fresh weight of individual pea shoots under ET-LD exceeded that of ET-HD by 48.9%. It is advisable to consider adopting ET-LD for the cultivation of pea shoots in LED plant factory. Based on ET-LD, the yield, nutritional quality, and light use efficiency of pea shoots were further explored at different stages under three levels of light intensity (50, 100, 150 μmol m-2 s-1). Contrasted against the light intensity of 50 μmol m-2 s-1, the average fresh weight per pea shoots, number of harvested, and total fresh yield under light intensity of 150 μmol m-2 s-1 treatment increased by 60.2%, 62.8%, and 165.1%, respectively. Meanwhile, the fresh weight per pea shoots, photosynthetic capacity, soluble sugar and vitamin C levels in leaves, as well as light use efficiency and photon yield, initially increased and then decreased with the extension of the planting period. Among these, soluble sugar, LUE, and PY started to decrease after reaching the maximum value at 60-70 days after transplanting. In conclusion, light intensity of 150 μmol m-2 s-1 with a photoperiod of 16 h d-1 using LEDs, combined with early topping within a planting period of 60-70 days, proves to be suitable for the hydroponic production of pea shoots in LED plant factory.

Solid waste management in Accra is a major challenge to the Metropolitan Authorities and inhabitants. The rapidly increasing population coupled with poor capacity of the municipal and private waste management companies to management waste effectively has created issues of environmental concern. Due to poor waste managements systems, most household dispose waste indiscriminately leading to floods and health issues. The study showed that about 60% of household waste is organic materials which has the potential to be converted to compost for agriculture purpose. Meanwhile plastics and rubbers which litters the environment as well as blocking major storm drains and gutters hence creating huge environmental hazard is made of 11% of the total component of most household waste generated daily. The study also revealed that among the methods of disposing waste, dumping waste in skip containers located at authorized places was the preferred means of disposing waste by household though others also dispose waste by other means such as burying and burning. Inadequate skip containers per population of household in an area coupled with irregularity of tracks picking these containers makes skip containers dumping site ugly scene, hence creating health issues. Among the constraints that impact negatively on sustainable waste management in Accra Metropolis, economic constraints was perceived as the main challenge which affect efficient waste management. Currently the country is going through serious economic challenges so government does not release money timely to fund projects which waste management is key. Most donor partners that use to support the government with funds have either reduced or redrawn their services as they have no confidence in the state of Ghana economy. Aside the constrains, the study also indicated that factors such as poor public attitude towards waste management, poor enforcement of sanitation by-laws, inadequate and untimely release of government funds were also seen as the main factors affecting waste management.

Objectives: The aim of the study was to evaluate the effects of oral administration of clinical dose of beraprost for feline CKD in healthy cats, and also to examine whether NOS inhibition reversed them. Methods: A placebo-controlled pharmacological sequential design study was carried out to assess plasma aldosterone and renin concentrations, mean blood pressure, heart rate, renal plasma flow, and renal vascular resistance. Results: Beraprost reduced plasma aldosterone when compared to the placebo (P < 0.05); this was reversed when NOS inhibitor NG-nitro-L-arginine methyl ester (L-NAME) was added to beraprost treatment (P < 0.01). No differences in the plasma renin concentration or hemodynamic parameters were detected between beraprost and placebo. The correlation ratios (η2) showed opposite relationships between beraprost and added L-NAME effects on aldosterone concentration, mean blood pressure, heart rate, renal plasma flow, and renal vascular resistance (P < 0.001). Conclusions: In healthy cats, the clinical dose of beraprost suppresses plasma concentration of aldosterone, which can be reversed by inhibition of NOS.