It is time-consuming for acquiring complete data by fully phase encoding in two orthogonal directions along with one frequency encoding direction. Undersampling in the 3D k-space is promising in accelerating such 3D MRI process. Though 3D undersampling can be conducted according to predefined probability density, the density based method is not optimal. Because of the large amount of 3D data and computational cost, it is challenging to perform data-driven and learning-based 3D undersampling and subsequent 3D reconstruction. To tackle this challenge, this paper proposes a deep neural network called EEUR-Net, realized by optimizing specific undersampling patterns for the fully-sampled 3D k-space data. Innovatively, our undersampling algorithm employs an end-to-end deep learning approach to optimize phase encoding patterns and uses a 3D U-Net for image reconstruction of undersampled data. Through end-to-end training, we obtain an optimized 3D undersampling pattern, which significantly enhances the quality of the reconstructed image under the same acceleration factor. A series of experiments on a knee MRI dataset demonstrated that, in comparison to standard random uniform, radial, Poisson and equispaced Cartesian undersampling schemes, our end-to-end learned undersampling pattern considerably improves the reconstruction quality of undersampled MRI images.

In this study, a motion control problem for the vessels towed by tugboats or towing ships on the sea is considered. The towed vessels including barge ships are need to have assistance of tugboats. Combining two vessels, some work purposes in the sea or harbor area can be completed. In this study, the authors give newly developed mathematical model and control system strategy. Especially, the system model fully presenting the physical characteristics of two vessels are derived. For controlling the system effectively, it is considered that the towed vessel has no power propulsion system but the rudder is activated to improve the maneuverability. Considering the strong nonlinearities included in the vessel dynamics, the modelled system is presented by nonlinear system without linearization of nonlinear parameters. Thus, the control system for the towed vessel is designed based on the nonlinear control scheme. Exactly, the back-stepping control method is applied to its motion control. Also, the PID control method is applied for comparing with the proposed control strategy.

Ultraviolet (UV) radiation has both harmful and beneficial effects on human health. It can cause skin damage and cancer, but also provides the primary source of vitamin D. Additionally, UV radiation affects energy metabolism in mice with metabolic diseases and has protective effects on hypertension and cardiovascular diseases.Metabolic Syndrome is a collection of metabolic dysfunctions such as dyslipidemia, hypertension, hyperglycemia, abdominal/central obesity, and insulin resistance. Chronic UVR exposure suppressed obesity and type 2 diabetes in high-fat diet-fed mice, while vitamin D supplementation did not replicate these effects. On the other hand, topical application of nitric oxide (NO) donors replicated UV effects on mice, and NO scavengers prevented the positive impact of UV. UVR may prevent the development of obesity and metabolic syndrome through mechanisms that depend on UVR-induced NO, not vitamin D. Exposure to sunshine has a protective impact on blood pressure and cardiovascular disease. Although lower vitamin D concentration is linked to increased hypertension and the incidence of CVD, oral vitamin D supplementation does not decrease blood pressure or the risk of CVD, indicating that vitamin D may not mediate the beneficial effects of sun exposure. Instead, NO plays a crucial role as an endogenous vasodilator, produced by the vascular endothelium. Solar UVA may release nitrogen oxides from skin storage into the bloodstream, lowering blood pressure and cardiovascular mortality.In conclusion, UVR exposure could be a promising non-pharmacological intervention for metabolic syndrome, hypertension, and CVD prevention, and NO may play a crucial role in mediating these effects. Further research is needed to explore the precise mechanisms and identify the optimal doses and exposure times of UVR.

Vip3 proteins are increasingly used in insect control in transgenic crops. To shed light on the structure of these proteins, we used the approach of trypsin fragmentation of mutants altering the conformation of the Vip3Af protein. From an alanine scanning on Vip3Af, we selected mutants with an altered proteolytic pattern. Based on the protease digestion patterns, their effect on oligomer formation, and theoretical cleavage sites, we generated a map of the Vip3Af protein with five domains, which match some of the domains proposed independently by two in silico models. Domain I ranges from aa12-198, domain II from aa199-313, domain III from aa314-526, domain IV from aa527-668 and domain V from aa669-788. The effect of some of the mutations on the ability to form a tetrameric molecule revealed that domains I-III are required for tetramerization, while domain V is not. The involvement of domain IV in the tetramer formation is not clear. Some mutations distributed from near the end of domain I up to the end of domain II affect the stability of the first three domains of the protein and negatively impact oligomerization upon trypsin treatment. Because of the high sequence similarity among Vip3 proteins, we propose that our domain map can be extended to many other members of the Vip3 family of proteins.

In this paper, the sol−gel method was used to synthesize powders of LaMnO3 (LMO), La0.85Ca0.15MnO3 (LCM), and La0.85Sr0.15MnO3 (LSM). We investigated the impact of substituting Ca and Sr at the A−site on the perovskite crystal structure and electrochemical capabilities of LMO. LCM retained its orthogonal structure in comparison to the parent LMO components, whereas LSM transitioned to a rhombic structure. At 0.5 A/g, the specific capacitance of LCM and LSM electrodes is 185.5 F/g and 248 F/g, respectively.The specific capacitance of LCM was more three times than that of the LMO electrode. Among the three samples (LMO, 22.25 m2 g−1; LSM, 31.56 m2 g−1), the LCM sample exhibited the highest specific surface area of 38.79 m2 g−1. The charge transfer resistances of the LMO, LCM, and LSM are 0.48 Ω, 0.36 Ω, and 0.38 Ω, correspondingly. The LCM electrode exhibits the greatest capacitance performance due to its more refined morphology, increased concentration of oxygen vacancy, and more complete utilization of the perovskite bulk structure. The above results demonstrate that Ca or Sr substitution of A−site compounds has great potential for supercapacitor applications.

China promotes nature-based solutions (NbS) as key approaches to addressing climate change, ecosystem damage, and biodiversity loss. However, indigenous and local knowledge (ILK), which is recognized by international scholars as an essential element of successful NbS, has not been thoroughly studied in the Chinese context. By conducting a comprehensive review of Chinese central governmental policies and semi-structured interviews with typical cases, this study finds out diversified sources of ILK and five pathways of ILK integration, including education, supervision, participation, knowledge preservation, and knowledge adoption. An increasing emphasis on community engagement has been driven by central policies such as the ecological civilization, carbon peaking and carbon neutrality goals. From a practical perspective, consistent core ideas of ILK exist in selected typical Chinese cases and studies in other countries, namely co-existence and reciprocity with nature. While supportive central policies can set the scene, ILK integration could not be realized without local governmental endorsement, context-based implementation, and long-term multi-stakeholder participation. Furthermore, this study also figures out a potential deficiency in terms of realizing effective ILK integration in mainstream and conventional practices, which can be further investigated by future studies.

We investigated the response of leaf photosynthetic capacity to climate warming and its variation among provenances of Larix gmelinii (Dahurian larch). Seedlings of 11 L. gmelinii provenances were transplanted into two common gardens with different climate conditions (control and warming climate). We measured the leaf photosynthetic capacity and explored its influencing factors. The warming treatment significantly increased the maximum net photosynthetic rate (Pmax-a), photosynthetic nitrogen use efficiency (PNUE), maximum carboxylation rate (Vcmax), maximum electron transport rate (Jmax), triose phosphate utilization rate (TPU), mesophyll conductance (gm), leaf nitrogen content (Narea), and chlorophyll content (Chlm). The Pmax-a was significantly positively associated with Vcmax, Jmax, TPU, gm, and Narea, and the slope of the correlations between Pmax-a and Vcmax, Jmax, and TPU was steeper in the warming treatment. The responses of Pmax-a, PNUE, Vcmax, Jmax, TPU, Narea, and Chlm to warming differed among provenances. The effects of warming on Pmax-a, Vcmax, Jmax, and TPU increased and then decreased as the aridity index of the original site increased. Overall, the warming treatment improved the photosynthetic capacity of L. gmelinii, but the extent of the improvement varied among provenances. These findings provide insights into the mechanisms underlying the responses of L. gmelinii to climate warming.

A complete MAPLE procedure is designed to implement effectively an algorithm for approximating the trigonometric functions. The algorithm gives a piecewise polynomial approximation on an arbitrary interval, presenting a special partition that we can get its parts, subintervals with ending points of finite rational numbers, together with corresponding approximate polynomials. The procedure takes a sequence of pairs of interval-polynomial as its output that we can easily explore in some useful ways. Examples on calculating approximate values of the sine function with arbitrary accuracy for both of rational and irrational arguments as well as drawing the graph of the piecewise approximate functions will be presented. Moreover, from the approximate integration of integrands of the form $x^m\sin x$ on $[a,b]$, another MAPLE procedure is proposed to find the desired polynomial estimates in norm for the best $L^2$-approximation of the sine function in the vector space $\mathcal{P}_{\ell}$ of polynomials of degree at most $\ell$, a subspace of $L^2(a,b)$.

In order to solve the problem of the poor oil displacement effect of high molecular weight alkali/surfactant/polymer (ASP) solution in low permeability reservoirs, Daqing Oilfield uses a partial quality tool to improve the oil displacement effect in low permeability reservoirs. Without changing the oil displacement capability of high molecular weight ASP solution in high permeability oil layers, the ASP solution is actively sheared in low permeability oil layers by using a partial quality tool to increase the injection capability of the solution and improve the overall oil recovery. In order to study the ability of the partial quality tool to improve the oil displacement effect, firstly, the matching degree of high molecular weight ASP solution to low permeability cores is studied, and the ability of quality control tools to change the molecular weight is studied. Then, experimental research on the pressure and oil displacement effect of high molecular weight ASP solution before and after the actions of the partial quality tool is carried out. The results show that ASP solutions with molecular weights of 1900 × 104 and 2500 × 104 have a poor oil displacement effect in low permeability reservoirs. After the action of the partial quality tool, the injection pressure is reduced by 5.22 MPa, and the oil recovery is increased by 7.79%. The injection pressure of the ASP solution after shearing by the partial quality tool is lower than that of the ASP solution with the same molecular weight and concentration without shearing, but the oil recovery is lower. On the whole, the use of the partial quality tool can obviously improve the oil displacement effect in low permeability reservoirs.

Traditional 3D reconstruction models have consistently encountered a challenge: attaining high recall of object edges while preserving precision. In this paper, we introduce a post-processing method Multi-Head Attention Refiner (MA-R) aimed at tackling this challenge by integrating a multi-head attention mechanism within the U-Net style refiner module. The 3D reconstruction model applying this method demonstrates excellence in parsing intricate image details, resulting in significant enhancement of boundary predictions and increased recall rates. In our experiments, our method significantly enhances the reconstruction performance of Pix2Vox++ when multiple images are utilized as input. Specifically, it achieves an enhanced Intersection Over Union score of approximately 1.1% compared to the original Pix2Vox++ model when 16-view images are employed.

This paper aims to build up a preference function to evaluate the public benefits of the type of agricultural farming, biodiversity, water provisions, land use type, ecotourism modes, and a monetary attribute (environmental trust fund and willingness to contribute) associated with an ecosystem service and land use program in a forest park. This study used the choice experiments to build a random utility model, analyze the average preference for the above land use attributes based on the conditional logit and used a latent class model to test the resident’s heterogeneous preferences for land use planning in the forest park. We also estimated the welfare derived from various land use programs. The empirical result had shown that: (1) increasing organic farming area, maintaining the status quo of species biodiversity, increasing the surface water provision, increasing the area of custom flora, increasing the wetland area, and setting up an integrated framework for ecotourism increase the public’s preference for the land use program; (2) we found that farmer and non-farmer haven’t the same land use preferences; (3) the ecotourism development program incorporating biodiversity, organic farming, ethnobotany, and wetland area with integrated ecotourism are more preferred than other land use program scenarios.

Recent prolonged dry periods and lack of irrigation water have severely affected the productivity of coffee farms’ in the Central Highlands of Vietnam. This paper analyzes the efficiency of irrigation water use for Robusta coffee (Coffea canephora) in Lam Dong province, Highlands, Vietnam. A Cobb-Douglas production function was used to determine coffee productivity’s response to the application of irrigation water and other production factors using data collected from 194 farmers while the Technical Efficiency (TE) and Irrigation Water Use Efficiency (IWUE) were analyzed using a Data Envelopment Analysis (DEA) model. The correlation of different factors to IWUE was determined using the Tobit model. The production function analysis using Cobb-Douglas shows that the volume of irrigation water, amount of working capital, labor and farm size significantly influence coffee productivity. It also shows that indigenous farmers are more efficient in utilizing irrigation water than the (mostly Kinh) migrant farmers. The Tobit result, on the other hand. indicates that farmers’ experience, education level, distance of farm to water source, security of access to water source, extension contact and credit access significantly affect IWUE. The study findings further suggest that mitigating water shortages in coffee farms require sub-regional and national policy support such as better access to credit and extension services, training, land management and household-level effort to improve farming practices, through the application of appropriate technologies and traditional knowledge.

Leaf color mutants (LCMs) are important resources for studying diverse metabolic processes such as chloroplast biogenesis and differentiation, pigments’ biosynthesis and accumulation, and photosynthesis. However, in Dendrobium officinale, LCMs are yet to be fully studied and exploited due to the unavailability of reliable RGs (reference genes) for qRT-PCR (quantitative real-time reverse transcription PCR) normalization. Hence, this study took advantage of previously released transcriptome data to select and evaluate the suitability of ten candidate RGs, including Actin (Actin), polyubiquitin (UBQ), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), elongation factor 1-α (EF1α), β-tubulin (β-TUB), α-tubulin (α-TUB), 60S ribosomal protein L13-1 (RPL13AD), aquaporin PIP1-2 (PIP1-2), Intima protein (ALB3) and Cyclin (CYCB1-2) for normalizing leaf color-related genes’ expression levels via qRT-PCR. Stability rankings analysis via common software Best-Keeper, GeNorm, and NormFinder disclosed that both ten genes met the requirements of RGs. Of them, EF1α exhibited the highest stability and was selected as the most reliable. The reliability and accuracy of EF1α were confirmed through qRT-PCR analysis of fifteen chlorophyll pathway-related genes. The expression patterns of these genes via EF1α normalization were consistent with the results by RNA-Seq. Our results will pave the way for molecular dissection of leaf color mutations in D. officinale.

Study Objectives: To (1) investigate the prevalence of sleep disorder symptoms in caregivers of children with autism spectrum disorder (ASD) and (2) the relationships between caregiver sleep problems and their health-related quality of life and family quality of life. Methods: Descriptive cross-sectional study of caregivers (N=62) of children ages 6 to 11 years old diagnosed with ASD receiving care at a regional autism research and resource center. Measurements and Results: Participants completed the Sleep Habits Questionnaire (SHQ), the Medical Outcomes Study (MOS) SF-12, and the Beach Center Family Quality of Life Scale (FQOL). Caregivers with longer sleep duration reported better mental health and better family quality of life. Caregivers who reported insomnia symptoms, non-restorative sleep, and insufficient sleep were more likely to report poorer mental health than caregivers who did not report these sleep disorder symptoms. Caregivers with obstructive sleep apnea and restless legs syndrome experienced worse physical quality of life. Conclusions: The physical and mental health of the primary caregiver is essential to the support of the child with ASD and to the functioning of the family. The study findings point to the importance of future research and interventions to enhance sleep health in order to improve quality of life for caregivers of children with ASD.

JIS SUJ2 is most widely used in bearing steels. The advantages are good hardenability, excellent fatigue, wear resistance and comprehensive mechanical properties. For wear resistance and fatigue resistance of the steel are getting more and more attention, the residual stress state and its distribution on the surface of the heat affect zone are critical factors affecting the fatigue life and wear resistance of the parts. In this study, using the SUJ2 as the material to talk about the surface residual stress and retained austenite distribution. Doing the quenching and tempering treatment to obtain different microstructures, using the induction method to re-quench the case region. After the heat treatment, measuring the residual stress and retained austenite volume on the surface by X-ray diffraction, observing the microstructure and comparing the hardness. The results show that the microstructure after heat treatment contains unsolidified carbides, tempered martensite and retained austenite. The residual stress on the surface is the tensile state. In the re-hardened area after induction quenching, the residual stress is all compressive, and the values are more than -800 MPa. In conclusion, in the same output power condition can be observed that the microstructure of the specimens before induction hardening has a significant impact on the effective case depth. The surface residual stress has changed from a tensile to a compressive state. In the re-hardened area, the maximum of the residual compressive stress increased with the austenitized temperature increase.

In the overall context of national eco-conservation civilization development and considering the hills in the Beijing-Tianjin-Hebei-Shanxi region, the local forest coverage rate is gradually on the rise, and so is the risk of forest fire. Every year, satellites can monitor and detect hundreds of fire spots on average. In recent years, serious fire took place for several times, leading to loss of life and personal injury. Then the fire-fighting work consumed huge amount of labor and material resources, exerting negative social impacts in many ways. Thus, the analysis of fire climate background in this region and the forecast based on fire weather indexes constitute an important part in the forest fire risk management. Located in the tropical monsoon climate zone, four provinces and municipalities of Beijing, Tianjin, Hebei and Shanxi are similar in terms of climate characteristics. This study tries to analyze the characteristics about fire spots under satellite monitoring, fire climate and fire weather index. The probability distribution analysis of weather index about fire spots in history and key meteorological observation stations as well as the weather index analysis in the early stage of typical fire indicate that the Fine Fuel Moisture Content (FFMC) and the Initial Spread Index (ISI) in the Fire Weather Index (FWI) system is applicable to the fire risk analysis in the Beijing-Tianjin-Hebei-Shanxi region, which can also effectively indicate the fuel moisture and spread conditions. As regards to the average level in Beijing-Tianjin-Hebei-Shanxi, when the FFMC is smaller than 93.5 and the ISI is also smaller than 5.0, there is a low risk of fire; when the FFMC is above 94 and the ISI is larger than 10.0, there is a high risk of fire; and the fire risk will be extremely high if the FFMC is over 96 and the ISI is above 13.0. In the practical fire-fighting management, the fire danger class can be released in reference to the ISI classes and threshold values of key meteorological observation stations under analysis provided by this study.

The biomimetic design of engineering structures is based on biological structures with excellent mechanical properties, which are the result of billions of years of evolution. However, current biomimetic structures, such as ordered lattice materials, are still inferior to many biological materials in terms of structural complexity and mechanical properties. For example, the structure of \textit{Euplectella aspergillum}, a type of deep-sea glass sponge, is an eye-catching source of inspiration for biomimetic design; however, guided by scientific theory, how to engineer structures surpassing the mechanical properties of \textit{E. aspergillum} remains an unsolved problem. The lattice structure of the skeleton of \textit{E. aspergillum} consists of vertically, horizontally, and diagonally oriented struts, which provide superior strength and flexural resistance compared with the conventional square lattice structure. Herein, the structure of \textit{E. aspergillum} was investigated in detail, and by using the theory of elasticity, a lattice structure inspired by the bionic structure was proposed. The mechanical properties of the sponge-inspired lattice structure surpassed the sponge structure under a variety of loading conditions, and the excellent performance of this configuration was verified experimentally. The proposed lattice structure can greatly improve the mechanical properties of engineering structures, and it improves strength without much redundancy of material. This study achieved the first surpassing of the mechanical properties of an existing sponge-mimicking design. This design can be applied to lattice structures, truss systems, and metamaterial cells.

One new cassane diterpene possessing an unusual N bridge between C-19 and C-20 named caesalsappanin R (1), as well as another new diterpene caesalsappanin S (2), were isolated from the seeds of Caesalpinia sappan with methanol extract. Their structures were determined by spectroscopic analysis and examined alongside existing data from prior studies. Their biological activities were profiled by their antiplasmodial activity.

In the field of computer vision, large-scale image classification tasks are both important and highly challenging. With the ongoing advances in deep learning and optical character recognition (OCR) technologies, neural networks designed to perform large-scale classification play an essential role in facilitating OCR systems. In this study, we developed an automatic OCR system designed to identify up to 13,070 large-scale printed Chinese characters by using deep learning neural networks and fine-tuning techniques. The proposed framework comprises four components, including training dataset synthesis and background simulation, image preprocessing and data augmentation, the process of training the model, and transfer learning. The training data synthesis procedure is composed of a character font generation step and a background simulation process. Three background models are proposed to simulate the factors of the background noise and anti-counterfeiting patterns on ID cards. To expand the diversity of the synthesized training dataset, rotation and zooming data augmentation are applied. A massive dataset comprising more than 19.6 million images was thus created to accommodate the variations in the input images and improve the learning capacity of the CNN model. Subsequently, we modified the GoogLeNet neural architecture by replacing the FC layer with a global average pooling layer to avoid overfitting caused by a massive amount of training data. Consequently, the number of model parameters was reduced. Finally, we employed the transfer learning technique to further refine the CNN model using a small number of real data samples. Experimental results show that the overall recognition performance of the proposed approach is significantly better than that of prior methods and thus demonstrate the effectiveness of proposed framework, which exhibited a recognition accuracy as high as 99.39% on the constructed real ID card dataset.

On 17 October 1947, Niels Bohr was made a knight of the Order of the Elephant by the King of Denmark in view of his outstanding achievements and contributions to science. Bohr designed his own coat of arms that featured a pattern of Yin and Yang (Tai Chi symbol) to symbolize the wave-particle complementarity. However, Bohr’s Yin-Yang diagram (YYD) was neither drawn based on the principles of quantum mechanics, nor did it originate from the traditional Taoist YYD. Scientists still have doubts about the legitimacy of using YYD as the icon of the wave-particle complementarity, because the YYD belonging to quantum mechanics itself is unknown so far. This article reports the YYDs existing in quantum mechanics and justifies the role of YYD in the wave-particle duality by showing that any system, whether classical or quantum, has an ideal YYD as long as it satisfies Bohr’s principle of complementarity (BPC). The deviation of a deformed YYD from the ideal YYD indicates the extent to which a real system satisfies BPC. This article constructs the quantum YYD by the complex quantum trajectory of a particle tunneling via a step barrier, which displays the continuous transition between the wave behavior and the particle behavior. It appears that the YYD designed by Bohr in his coat of arms resembles the YYD generated by tunneling motion, not only in appearance but also in the governing equation.

Although crop conversion from annual to perennial crops has been considered as one path towards climate-smart and resource-efficient agriculture, the effects of this conversion on soil multifunctionality and biomass yields remain unclear. Here, we investigated the effects of one annual and three perennial crops (a grass (Lolium perenne), a legume (Medicago sativa), and their mixture) on soil multifunctionality and biomass yield on the Yellow River floodplain. Soil multifunctionality was assessed by the capacity of water regulation and the multifunctionality of carbon (C), nitrogen (N), and phosphorus (P) cycles. Results showed that perennial crops enhanced soil multifunctionality by 207% for L. perenne, 311% for M. sativa, and 438% for L. perenne + M. sativa, compared with annual winter wheat (Triticum aestivum). The effect of perennial crops on soil multifunctionality increased with infiltration rate, dissolved organic C, microbial biomass C, and extracellular enzymatic activities for both C and N acquisition. However, we observed that perennial crops had lower biomass yield than annual crop. Therefore, the transition of agricultural landscapes to perennials needs to take into account the balance between environmental protection and food security, as well as environmental heterogeneity, to promote sustainable agricultural development.

Quantitative analysis of human gait is critical for early discovery, progressive tracking, and rehabilitation of neurological and musculoskeletal disorders, such as Parkinson’s Disease, stroke, and Cerebral Palsy. Gait analysis typically involves estimating gait characteristics, such as spatio-temporal gait parameters and gait health indicators (e.g., step time, length, symmetry, and balance). Traditional methods of gait analysis involve the use of cameras, wearables, and force plates, but are limited in operational requirements when applied in daily life - such as direct line-of-sight, carrying devices, and dense deployment. This paper introduces a novel approach for gait analysis by passively sensing footstep-induced floor vibrations during walking using vibration sensors mounted on the floor surface. Our approach is non-intrusive, scalable, and perceived as more privacy-friendly, making it suitable for continuous gait health monitoring in daily life. We developed a floor vibration-based gait analysis framework to estimate various gait parameters that are used as standard metrics in medical practices, including temporal parameters (step, stride, stance, swing, double-support, single-support time) and spatial parameters (step length, width, angle, stride length), and extracts gait health indicators (cadence/walking speed, left-right symmetry, gait balance, initial contact types). The main challenge is that floor vibrations are distinct across different floor types. To address this challenge, our approach develops floor-adaptive algorithms to extract floor-specific features and is designed to be generalizable to various settings, including homes, hospitals, and eldercare facilities. We evaluate our approach through real-world walking experiments with 20 adults with 12,231 labeled gait cycles across concrete and wooden floors. Our results show 90.5% (RMSE 0.08s), 71.3% (RMSE 0.38m), and 92.3% (RMSPE 7.7%) accuracy in estimating temporal, spatial parameters, and gait health indicators, respectively.

The time’s arrow of macroscopic physical phenomenon is reflected by irreversible physical process, which essentially occurs from small probability state to high probability state. In this paper, simplified models are proposed to understand the macroscopic physical process. In order to describe the information of a physical system, we defined the full self-information as "information height" to describe the complexity or difficulty of a macrostate of physical system. In this way, the direction of macroscopic physical process is from high information height to low information height. We can judge the direction of physical process by the information height. If we want the macroscopic physical process to evolve from the low information height state to the high information height state, the system need to add extra information and corresponding energy to increase the information height.

Objective: This study aimed to demonstrate the availability of portable devices for nasal FeNO measurement, which could replace exhaled NO measurement based on the continuous aspiration of multiple flow measurement systems. Methods: A descriptive cross-sectional study. The healthy subjects without rhinosinusis disorders (control group) and those with diagnosed allergic rhinitis (AR group) were enrolled in the study. They underwent nasal and bronchial FeNO measurements by both fixed flow NObreath® connected to nasal mask and multiple flows HypAir FeNO®. Results: A total of 153 people were recruited including 63 healthy subjects and 90 subjects with AR. There were no statistically significant differences in anthropometric characteristics between the two groups (P > 0.05). There were a significant increase in FeNO values in the AR group compared to the control group; concentrations of nasal and bronchial FeNO mearsured by NObreath® were 76.0 ± 50.7 ppb (vs 36.0 ± 28.1 ppb, P < 0.01) and 32.3 ± 15.4 ppb (vs 9.2 ± 5.6 ppb, P < 0.001), and those mearsured by NObreath® Hypair FeNO® were 1796.9 ± 523.3 ppb (vs 400.2 ± 123.1 ppb, P < 0.001) and 37.3 ± 23.0 ppb (vs 17.4 ± 18.3 ppb, P < 0.01). A weak correlation between the values measured by NObreath® and Hypair FeNO® devices was observed (r = 0.023 and r = 0.089, respectively; p < 0.05). Conclusions: The handheld NObreath® device is effective in measuring FeNO concentrations in both normal subjects and AR patients. The advantages in price and size, creating a compact, low-cost device that is convenient for use and research.

Background: Educating college students about the importance of good sleep habits could lead to the adoption of healthier sleep routines, including sufficient sleep duration and sleep quality. The current pre-post study examines the impact of completing a sleep education program called “Sleep 101” on (1) sleep hygiene practices, (2) sleep quality, and (3) weekday and weekend sleep behaviors among college students. “Sleep 101” is an interactive online course developed to educate college students about the importance of sleep by addressing basic sleep physiology, the impact of sleep on mood, academic and physical performance, the interactions between sleep and various substances, and common sleep disorders. Methods: 338 college students were recruited from a midsized public university in the US and invited to participate in “Sleep 101”, of which 25 participants completed the baseline and post-intervention questionnaire. The Sleep Hygiene Index (SHI) was utilized to evaluate sleep hygiene practices, while standard questions were employed to assess weekday and weekend sleep behaviors and overall sleep quality. Results: Those who completed the study demonstrated a significant increase in weekday sleep duration and were less likely to engage in negative prior bedtime activities. In addition, 40% of those who completed baseline and post-intervention assessments noticed improvements in their sleep quality. Conclusion: These findings suggest that a brief online program is beneficial in improving sleep behaviors among college and could be a scalable approach to addressing current sleep issues and preventing future sleep problems in college students.

Semi-solid feedstock of AZ80 magnesium alloy modified by minor rare-earth Y element (0, 0.2, 0.4, 0.8 wt.%) were fabricated by strain induces melting activated (SIMA) in the form of extrusion and partial remelting. The effect of Y addition on the microstructure evolution of extruded and isothermal treated alloy was observed by optical microscope (OM), scanning electron microscope (SEM), X-ray diffraction (XRD) and quantitative analysis. The results show that the Y addition can refine the microstructure and make the β-Mg17Al12 phases agglomerating. During the subsequent isothermal treatment at 570℃, the average solid grain size, shape factor and liquid fractions increased with prolonged soaking time. Smaller spheroidal solid grains and the larger shape factor were obtained due to Y addition. The coalescence and Ostwald ripening of solid grains operated the coarsening process simultaneously. The coarsening rate constants of AZ80M1 (0.2 wt.% Y addition) of 164.22 μm3s-1 was approximately four times less than the un-modified AZ80 alloy of 689.44 μm3s-1. In contrast, the desirable semi-solid structure featured by fine, well globular solid grains and appropriate liquid fractions and shape factor was achieved in AZ80M1 alloy treated at 570℃ for 20-30 min.

A large amount of raw data collected by satellites is processed by the production chain to obtain a large amount of product data, of which the secure exchange and storage is of interest to researchers in the field of remote sensing information science. Authentic, secure data is a critical foundation for data analysis and decision-making. And traditional centralized cloud computing systems are vulnerable to attacks, and once the central server is successfully attacked, all data will be lost. Distributed Ledger Technology (DLT) is an innovative computer technology that can ensure information security, traceability and tamper-proof, and can be applied to the field of remote sensing. Although there are many advantages to using DLT in remote sensing applications, there are some obstacles and limitations to its application. Remote sensing data has the characteristics of large data volume, spatiotemporal nature, global and so on, and it is difficult to store and interconnect remote sensing data in the blockchain. To address these issues, this paper proposes a trustworthy and decentralized system using blockchain. The novelty of this paper is to propose a multi-level blockchain architecture in which the system collects remote sensing data and stores it in the Interplanetary File System (IPFS) network, after generating the IPFS hash, the network rehashes the value again and uploads it on the Ethereum chain for public query. Distributed data storage improves data security, supports the secure exchange of information, and improves the efficiency of data management.

(1) Background : When placing implants in the maxillary posterior region with insufficient alveolar bone, a maxillary sinus elevation is necessary. Autogenous bone, though biologically ideal, poses risks and discomfort due to donor site harvesting. Block-type autogenous tooth bone graft material, made from the patient’s own extracted tooth, offers similar biological stability without these drawbacks; (2) Methods : This study observed the progress of 19 implant patients who were treated with maxillary sinus elevation procedures using block-type autogenous tooth bone graft material at the Daegu Catholic University Medical Center. Extracted teeth were processed into demineralized tooth block bone. After elevating the sinus membrane, implants and the tooth bone graft material were placed in the space, and the bony window was repositioned. Postoperative evaluations through clinical observation and radiographic imaging assessed sinus membrane elevation, alveolar bone height increase, and implant osseointegration; (3) Results : Results showed proportional increases in alveolar bone height to the graft material size, with long-term stability. No postoperative complications occurred, even with sinus membrane perforation, and implants remained stable; (4) Conclusions : The study concludes that maxillary sinus lifts using block-type autogenous tooth bone graft material provide excellent bone induction and biocompatibility, making it a highly beneficial method for both dentists and patients.

Green innovation has become the mainstream of the era, and New Urbanization is an inevitable choice in the process of urbanization in China. Focusing on the topics of green innovation and new urbanization, much work has been done to find their factors respectively while the relationship between the two remains to be explored. Hence, in this article, representative indicators of new urbanization and green innovation are selected to study the Yangtze River Delta City Group from the perspective of both the entire urban agglomeration and a single city, in terms of time and space, using the entropy method and the coupling model. The results show that (1). Green innovation promotes the new urbanization development and there is a synergistic effect between the two systems. (2). The level of economic development is an important factor that affects the degree of coupling degree and coordination degree between the two interactions, and its influence is better than the spatial effect. (3). Green innovation and new urbanization have positive spatial autocorrelation and regional agglomeration (there are High-High, Low-Low, and High-Low collections).

The Range–Doppler (R-D) model is extensively employed for the geometric processing of Synthetic Aperture Radar (SAR) images. Refining the sensor motion state and imaging parameters is the most common method for achieving high-precision geometric processing using the R-D model, comprising a process that involves numerous parameters and complex computations. In this study, we introduce a novel approach to improve the positioning accuracy of the R-D model, implementing a low-order polynomial to compensate for the original imaging errors without altering the initial positioning parameters. We also design low-order polynomial compensation models with different parameters. The models are evaluated on various SAR images from different platforms and bands, including spaceborne TerraSAR-X and GF3-C images, manned airborne SAR-X images, and unmanned aerial vehicle-mounted miniSAR-Ku images. Furthermore, image positioning experiments involving the use of different polynomial compensation models and various numbers and distributions of Ground Control Points (GCPs) are conducted. The experimental results demonstrate that geometric processing accuracy comparable to that of the classical rigorous positioning method can be achieved even when applying only an affine transformation model to the images. Compared to classical refinement models, however, the proposed image-compensated R-D model is much simpler and easy to implement. Thus, this study provides a convenient, robust, and widely applicable method for the geometric positioning processing of SAR images, offering a potential approach for the joint-positioning processing of multi-source SAR images.

In-depth insights into the profound impacts of climate change and human activities on water resources are garnered through the dynamic changes in surface water, a crucial aspect of effective water resource management and the preservation of aquatic ecosystems. This paper introduces an innovative approach employing the random forest algorithm for the systematic extraction and monitoring of surface water at large regional or national scales. This method integrates spectral bands, spectral indices, and digital elevation model data, offering a novel perspective on this critical task. A data filling model is proposed to mitigate the impact of missing data due to cloud cover. Leveraging the capabilities of the Google Earth Engine (GEE), detailed information on surface water dynamics during the rainy and dry seasons in the Yangtze River Basin (YRB) from 1991 to 2021 is extracted using Landsat time series imagery. The analysis encompasses spatial-temporal variation characteristics and trends, with a specific focus on the intricate interplay between the areal extent of surface water and hydro-meteorological factors in each sub-basin of the YRB. Importantly, this includes considerations of potential groundwater contributions to surface water. Key findings from our research include: (1) Achieving a remarkable overall accuracy of 0.96 ± 0.03 in obtaining reliable surface water datasets with the support of GEE. (2) Identifying significant trends, such as a noteworthy increase in rainy season surface water bodies (+248.0 km2·yr−1) and a concerning decrease in surface ice/snow cover during both rainy and dry seasons, with change rates of −39.7 km2·yr−1 and −651.3 km2·yr−1, respectively. (3) Uncovering the driving mechanisms behind these changes, revealing positive correlations between the areal extent of rainy season surface water bodies and precipitation, as well as negative correlations between surface ice/snow cover area and average surface skin temperature. It is crucial to note that these driving factors exhibit variation among secondary river systems, underscoring the complexity of surface water dynamics. Furthermore, comparative analyses with existing surface water products are conducted, contributing to a deeper understanding of the advantages and uncertainties inherent in our proposed extraction method. The proposed method for large-scale surface water extraction not only enhances the monitoring of spatio-temporal surface water dynamics in the YRB but also provides valuable insights for the sustainable utilization and protection of water resources, considering the potential role of groundwater in supplementing surface water.

In recent years, due to the low energy utilization of the whole life-cycle of buildings and the di-minished indoor and outdoor comfort of buildings and the impact on the surrounding environ-ment caused by the carbon emissions of the building life-cycle, the establishment of a whole life- cycle carbon emission model for buildings to improve their energy utilization at all stages of their life-cycle has received unprecedented attention. In China, the construction industry has become a major carbon emitter, and traditional houses, as a green development building type, are an effec-tive way to achieve carbon neutrality in buildings, but the existing green building evaluation system lacks quantitative indicators of carbon emissions in the building life-cycle. The exclusive evaluation indexes for regional and characteristic buildings, such as traditional houses, are ne-glected; This study explored the formula for calculating the life-cycle carbon emissions model of traditional residential houses under a carbon emission intervention and used real measurements of the physical environment and comparative analysis of the limitations of existing local stand-ards; The results showed that the carbon emission calculation formulas for each stage of the life-cycle of traditional residential houses must be established by combining the selection of local building materials, and the materials for sustainable energy and carbon sinks of green systems. Based on the results of indoor and outdoor heat and humidity environmental tests of residential houses and an analysis of the limitations of existing evaluation indexes due to locality, four im-portant factors affecting locality green buildings in terms of energy utilization, site ecology and landscape, land saving and material saving were extracted; on this basis, the whole life-cycle carbon emission model of traditional residential houses is constructed by combining the existing green building evaluation standards with the carbon emission indexes of the life-cycle of tradi-tional residential houses.

Recently, federated learning (FL) has been receiving great attention as an effective machine learning method to avoid the security issue in raw data collection as well as to distribute the computing load to edge devices. However, even though wireless communications is a essential part for implementing FL in edge networks, there have been a few works that analyze the effect of wireless networks on FL. In this paper, we investigate FL in small-cell networks where multiple base stations (BSs) and users are located according to homogeneous Poisson point process (PPP) with different densities. We comprehensively analyze the effects of geographic node deployment on the model aggregation in FL on the basis of stochastic geometry-based analysis. We derive the closed-form expressions of coverage probability with tractable approximations and discuss the minimum required BS density for achieving a target model aggregation rate in small-cell networks. Our analysis and simulation results provide insightful information for understanding the behaviors of FL in small-cell networks, and it can be exploited as a guideline for designing the network facilitating the wireless FL.

This paper draws upon the theory of turbulence in physics to explore the similarities and differences between volatility in financial markets and turbulent phenomena at a statistical physics level. By analogizing the dynamics of financial markets with fluid turbulence, we have developed an innovative analytical framework aimed at deepening the understanding of the complexity inherent in financial markets. Our research methodology includes a comparative analysis of simulated time series data for the Standard & Poor's 500 Index and fully developed turbulent velocity time series. We focus on the similarities in key statistical physical properties, including probability distributions, correlation structures, and power spectral densities. Furthermore, we have established a model of capital flow in financial markets and proposed corresponding solutions. Through computational simulations and data analysis, we find that while financial market volatility shares some statistical characteristics with turbulent phenomena, significant differences exist in the shapes of probability distributions and the temporal scales of correlations. This suggests that although financial markets exhibit patterns akin to turbulence, the behavior of this complex, multi-variable driven system does not completely correspond to natural turbulence, highlighting the limitations of directly applying turbulence theory to financial market analysis. Our study offers a new perspective for the theories of financial markets and the field of econophysics, providing fresh insights into the complexity of financial markets and contributing to the prevention and management of financial risk.

The determination of the non-loading condition of the rail cable shifting (RCS) system, which consists of main cables, hangers and rail cables, is the premise of the girder erection for the long-span suspension bridges. An analytical form-finding analysis model of shifting system is established according to the basic assumptions of flexible cable structures. Herein, the rail cable is discretized into segmental linear cable elements and the main cable is discretized into segmental catenary elements. Moreover, the calculation and analysis equation of each member and their iterative solutions are derived by taking the elastic elongation of the sling into account. In addition, by taking the girder construction of Aizhai suspension bridge as engineering background, a global scale model of the RCS system is designed and manufactured; also the test system and working conditions are established. The comparison between the test results and analytical results shows the presented analytical method is correct and effective. The process is simplified in the analytical method, and the computational results and precision can satisfy the practical engineering requirements. In addition, the proposed method is suitable to apply to the computation analysis of similar structures.

This study assesses the biomethane (CH4) generation and greenhouse gas (GHG) emissions resulting from municipal solid waste landfilling in Phnom Penh, Cambodia, with a focus on the impact of fugitive CH4 emissions and operation processes in four landfilling scenarios: simple dumping (S1), improved management with leachate treatment (S2), engineered landfill with flaring (S3), and engineered landfill with energy recovery (S4). The study also considered the environmental benefits of carbon sequestration and landfill gas utilization. The LandGEM and IPCC FOD models were used to calculate CH4 generation over the period of 2009-2022, and it was found that approximately 18 and 21 M kg/year of CH4 are released, respectively. The energy potential from CH4 recovery was 51–61 GWh/year. Overall GHG emissions in S2 were the highest, amounting to 409–509 M kg CO2-eq/year, while S1 had lower emissions at 397–496 M kg CO2-eq/year. Flaring captured CH4 in S3 could reduce GHG emissions by at least 55%, and using captured CH4 for electricity production in S4 could mitigate at least 83% of GHG emissions. Electricity recovery (S4) could avoid significant amounts of GHG emissions (˗104.5 kg CO2-eq/tMSW). The study suggests that landfill gas-to-energy could significantly reduce GHG emissions.

This study aimed to assess the prevalence and identify risk factors for schistosomiasis among school-aged children in low- and middle-income communities. A retrospective cross-sectional study was conducted, involving the examination of 24 034 children for Schistosoma haematobium ova. Data were analyzed using IBM Statistical Package for the Social Sciences (SPSS) version 27. Logistic regression was employed to determine the factors associated with schistosomiasis. The overall prevalence of schistosomiasis in the study population was 75%, with higher rates observed in rural-dominated areas, particularly Bushbuckridge (73%) and Nkomazi (51%). Age, a history of bilharzia, and the presence of blood in urine were significantly associated with schistosomiasis, while being a female child was found to be a protective factor. This study underscores the importance of implementing robust screening procedures and the necessity for health education to mitigate the high prevalence of schistosomiasis and prevent its further spread.

Inverse optimal control is a method for recovering the cost function used in an optimal control problem in expert demonstrations. Most studies on inverse optimal control have focused on building the unknown cost function through the linear combination of given features with unknown cost weights, which are generally considered to be constant. However, in many real-world applications, the cost weights may vary over time. In this study, we propose an adaptive online inverse optimal control approach based on a neural-network approximation to address the challenge of recovering time-varying cost weights. We conduct a well-posedness analysis of the problem and suggest a condition for the adaptive goal, under which the weights of the neural network generated to achieve this adaptive goal are unique to the corresponding inverse optimal control problem. Furthermore, we propose an updating law for the weights of the neural network to ensure the stability of the convergence of the solutions. Finally, simulation results for an example linear system are presented to demonstrate the effectiveness of the proposed strategy. The proposed method is applicable to a wide range of problems requiring real-time inverse optimal control calculations

The two-stage direct thermal contact (2sDTC) process is a rapid dewatering approach for fluid fine tailings (FFT) that is integrated into an oil sands bitumen extraction plant to reduce tailings pond storage and freshwater usage. In the first stage, combustion gas directly contacts atomized FFT, vaporizing water and yielding dry solids and steam-rich hot gas. The second stage involves pond effluent water directly contacting the steam-rich hot gas, recovering heat and condensing moisture. Case studies confirm the technical feasibility of the integration. Benefits include producing a dry discharge, reducing tailings water discharge and conserving an equivalent to 0.2 barrels of freshwater per barrel of oil produced. Most importantly, these benefits incur no additional energy cost to the plant as the integration eliminates the energy penalty and CO2 emissions associated with FFT dewatering. Further capacity enhancement can be achieved by using centrifuge-concentrated FFT. The study reveals that FFT concentrated to ~50 wt% solids could still maintain its pump-ability and be accommodated by the 2sDTC process, leading to an integration which could dewater more FFT annually and conserve more freshwater ( 0.58 barrels per barrel of oil produced), with the sole energy requirement being the power to drive the centrifuge machinery.

We investigate and discuss in detail the structure of the restricted singular value decomposition for a tensor triplet under t-product (T-RSVD). The algorithm is provided with a numerical example illustrating the main result. For applications, we consider color image watermarking processing with T-RSVD.

Several types of guided bone regeneration materials are available with various properties and clinical indications. Among them, dentin-derived matrix from extracted teeth is an excellent alternative to traditional graft materials, such as allografts and xenografts. Different clinical preparation protocols exist: block form versus powder form, demineralized versus non-demineralized form. Out of these methods, demineralization protocols for dentin-derived matrix from extracted teeth have been noted for a wide range of successful clinical outcomes. The purpose of this animal study was to find out the most effective method of demineralizing dentin-derived matrix to result in the highest regenerative ability in the bone graft material in rabbit calvaria. The study conducted a comparative histomorphometric analysis of four groups in distinguished matrix conditions: a control group without graft placement, a non-demineralized dentin-derived matrix graft placement group, a 15-minute demineralized dentin-derived matrix graft placement group, and a 30-minute demineralized dentin-derived matrix graft placement group. Regenerative processes were evaluated three times at 2, 4, and 8 weeks post-graft placement. These groups of rabbits were evaluated randomly in a blinded setting to prevent bias. Among the four groups compared, the group with a 15-minute demineralized dentin-derived matrix graft showed the most efficient bone regeneration in the histomorphometric analysis. Based on this animal study, it was apparent that a 15-minute demineralization of dentin-derived matrix is the preferred preparation protocol to maximize the regenerative potential in the matrix.

The inhibition of alpha-glucosidase and alpha-amylase is one of clinic strategies for remedy the type II diabetes. Herbal medicines are reported to alleviate hyperglycemia. However, the constituents from those sources whether are targeted to the alpha-glucosidase and alpha-amylase still unexplored. This study attempted to select the compounds for efficacy of hypoglycemia via cellular and mouse levels. The results illustrated that the cytotoxicity in all tested compounds at various concentrations except the concentration of 16-hydroxy-cleroda-3,13-dine-16,15-olide (HCD) at 30 µM were not significant difference (p > 0.05) when compared with the untreated control. Acarbose (reference drug), Antroquinonol, Catechin, Quercetin, Actinodaphnine, Curcumin, HCD, Docosanol, Tetracosanol, Berberine, and Rutin could effectively inhibit the alpha-glucosidase activity of Caco-2 cells when compared with the control (maltose). The compounds (Curcumin, HCD, Tetracosanol, Antroquinonol, Berberine, Catechin, Actinodaphnine, and Rutin) could reduce blood sugar level at 30 min in tested mice. The effects of tested compounds on area under curve (AUC) were significant (p < 0.05) among Acarbose, Tetracosanol, Antroquinonol, Catechin, Actinodaphnine, and Rutin along with Berberine and Quercetin. In in vitro (alpha-glucosidase) with in vivo (alpha-amylase) experiments suggest that bioactive compounds can be a potential inhibitor candidate of alpha-glucosidase and alpha-amylase for the alleviation of type II diabetes.

Tourism Geographers in Anglo-American geographical departments migrate to teach and research tourism in applied schools and departments such as business, resource and environment, and even cultural and creative industry. Under national research assessment and funding pressures, tourism geographers are not encouraged to keep on undertaking serious theoretical researches related to their mother discipline and transferred to research applied researches and publish in hybrid journals. Such changes in tourism geographers` research behavior have not been tested and reported in Asian academic contexts, especially Taiwan while frequently being discussed internationally. This research aims to investigate the differences in the research behavior of tourism geographers between those who are staffed in geography departments and those who migrate to applies departments such as tourism and recreation, resource and environment, and others in terms of publishing journals, paradigmatic approaches, research types(qualitative, quantitative, and mixed), research methods and geographical scales conducted based on content analysis of articles published by tourism geographers in geography and tourism and recreation departments. This study revealed that there are significant differences in the research behavior of tourism geographers between different department. Finally, this paper explains the differences in terms of Taiwan changing social and economic conditions, academic traditions and politics of geography and applied departments, research habits and preferences of tourism geographers among departments and other aspects. This study can help international tourism geography academic circles to understand the complexity and diversity of tourism geography academic landscape of the Chinese language.

Nanosystems-based antifungal agents have emerged as an effective strategy to address issues related to drug resistance, drug release, and toxicity. Among the different materials used for drug delivery, multifunctional polymers have proven to be ideal due to their versatility. This review provides an overview of the various types of nanoparticles used in antifungal drug delivery systems, with a particular emphasis on the types of polymers used. The review focuses on the application of drug delivery systems and the release behavior of these systems. Furthermore, the review summa-rizes the critical physical properties and relevant information utilized in antifungal polymer nanomedicine delivery systems, and briefly discusses the application prospects of these systems.

Background: Endotheliopathy is common pathologic findings in patients with acute and long COVID-19. It may be associated with disease severity and predispose to long-term complications. Plasma levels of a proteoglycan syndecan-1 are found to be significantly elevated in patients with COVID-19, but its roles in assessing the disease severity and predicting long-term outcome are not fully understood. Methods: 124 consecutive hospitalized patients with SARS-CoV2 infection were prospectively enrolled and blood samples were collected on admission (T1), 3-4 days following treatment (T2), and 1-2 days prior to discharge or death (T3). Plasma levels of syndecan-1 were determined using an immunosorbent assay; various statistical analyses were performed to determine the association between plasma syndecan-1 levels and disease severity or the 60-day mortality rate. Results: Compared with those in the healthy controls, plasma levels of syndecan-1 in patients with critical COVID-19 were significantly higher (p<0.0001). However, there was no statistically significant difference among patients with different disease severity (p>0.05), resulting from large individual variability. Longitudinal analysis demonstrated that while the levels fluctuated during hospitalization in all patients, plasma syndecan-1 levels were persistently elevated from baseline in critical COVID19 patients. Cox proportional hazard regression analyses revealed that elevated plasma levels of syndecan-1 (>260 ng/mL at T1, >1018 ng/mL at T2, and >461 ng/mL at T3) were significantly associated with the 60-day mortality rate. Conclusions: Endotheliopathy, marked by glycocalyx degradation and elevated plasma syndecan-1, occurs in nearly all hospitalized patients with SARS-CoV2 infection; the elevated plasma syndecan-1 is associated with increased mortality in COVID-19 patients.

A novel catechol (CA) biosensor was developed by the immobilization of tyrosinase (Tyr) onto in situ electrochemical reduction graphene (EGR) on choline functionalized gold nanoparticals (AuNPs–Ch) film. The results of UV–visible spectra indicated that Tyr retained its original structure in the film. And electrochemical investigation of the biosensor showed a pair of well–defined, quasi–reversible redox peaks with E_pa= –0.0744V and E_pc= –0.114 V (vs. SCE) in 0.1 M, pH 7.0 sodium phosphate buffered saline at the scan rate of 100 mV/s. The transfer rate constant k_s was 0.66 s^–1. The Tyr–EGR/AuNPs–Ch showed a good electrochemical catalytic response for the reduction of CA, with the linear range from 0.2 to 270 μM and a detection limit of 0.1 μM (S/N= 3). The apparent Michaelis–Menten constant was estimated to be 109 μM.

We still do not have satisfactory answers about the inflationary and accelerating expansions of the universe, the missing mass problem, and the origins of the four fundamental forces and the quantum phenomena. Here, we introduce a new model of matter and space and a postulate on a constant of motion, and then show that an equation of motion derived from the constant of motion could provide new understandings of the above problems. For example, we show that there is a natural inflation scenario and that the co-moving distance to the closest accelerating supernova is clearly given as $c/(\sqrt{3} H)$ ($\sim$8.1 billion ly). In addition, we show that, in a system including a proton and an electron, the equation of motion has eight acceleration terms, some of which are suspected to be responsible for the four fundamental forces and the galaxy rotation anomaly. From further discussion, we conjecture that in order to understand the gravitational and strong interactions and the quantum phenomena, it is necessary to consider the expansion of the universe. The lensing mass distribution is explained, based on another postulate on a method of representing superposition.

Here, satellite images from 2006 to 2022 were collected to assess changes in the sandbar topography of the Nakdong River Estuary region, southeast of South Korea. The employed method of satellite image acquisition involves capturing images at the same time each year to facilitate a comparison of topographical changes over time. The shorelines of the islands in the study area, including Jinwoo Island, Shinja Island, and Doyo Sandbar, were analyzed. Shoreline analysis was performed using the digital shoreline analysis system (DSAS) package in ArcGIS. The results indicate that Jinwoo Island is expanding at 6.46 m/year in the direction of Nulcha Island. The western side of Shinja Island is expanding at 4.76 m/year, whereas the eastern side is retreating at a rate of 24.41 m/year. In the case of the Doyo Sandbar, the southern shoreline is retreating at a rate of 14.69 m/year; however, the speed is gradually decreasing. Marked topographical changes are evident in the Nakdong River Estuary, and the interlinked barrier islands undergo deposition and erosion, leading to alterations in the shoreline. These findings serve as foundational data for predicting and addressing environmental and social issues arising in the Nakdong River Estuary region due to climate change.

This study utilises NaOH to treat composite cementitious materials containing aeolian sand and zeolite powders, which were used to replace 50% of the cement in aeolian-sand concrete (ASC). The mechanical properties of treated ASC considerably improved, especially when the NaOH dosage was 4% by mass. After curing this sample (denoted as AAZC-4) for 28 d, its compressive strength improved by 17.2% and its split tensile was increased by 16.3%. Potassium feldspar and montmorillonite in zeolite powder and SiO2 in the sand were decomposed by OH− and combined with other elements to generate various silicate gels and A-type potassium zeolite crystals inside the concrete. Microscopic examination showed that the gels and crystals intertwined to fill the pores, decreasing (increasing) the percentage of large (small) pores, thus optimising the pore structure. This substantially improved the mechanical properties of ASC. Freeze–thaw salt-intrusion tests showed that the extent of mass loss, degree of damage and loss of compressive strength of AAZC-4 were similar to those of ordinary concrete but were reduced by 36.8%, 19% and 52.1%, respectively, compared with those of ASC. Therefore, AAZC-4 has sustainable working performance in the chloride ion permeable environment in cold and arid areas.

The estimation of ecological service system value of water resources in Tarim river basin is of great significance for resource allocation management and ecological protection. However, there is still no unified and complete evaluation method for ecological service system value of inland river in China. Based on the perspective of the whole value chain, the study classifies its ecological service functions, and divides 11 sub-categories into 4 categories (supply, regulation, culture and support) as evaluation indicators to carry out quantitative evaluation. The results showed that the total value of ecological service system in Tarim river basin in 2018 was 4156.5247×108 Yuan, and the value of regulating function, cultural function, supporting function and supply function were successively from high to low, which were as follows: 2565.6825×108 Yuan, 1009.5471×108 Yuan, 884.0770×108 Yuan, 20.3350×108 Yuan, among which the value of regulation function is dominant.

This article utilized electrodeposition technology to fabricate Zn and Zn-Y₂O₃-Al₂O₃ composite coatings on Q235 steel plates. The composite coatings were obtained by adding Y₂O₃/Al₂O₃ nanoparticles (0, 5, 10, and 15 g/L) to acidic chloride solutions. This study then examined the impact of these nanoparticles on the microstructure, morphology, microhardness, hydrophobicity, and corrosion resistance of the composite coatings. The results indicate that the addition of the nanoparticles increased the nucleation sites on the surface of the coating, thereby refining the grain size and reducing the roughness of the coating surface. When 10g/L of Y₂O₃ and 10g/L of Al₂O₃ nanoparticles were added, the hardness of the composite coating (369 Hv) was 2.49 times higher than that of the pure Zn coating (148 Hv), which was attributed to the dispersion strengthening and grain refinement effects of the nanoparticles. The corrosion resistance of the Zn and Zn-Y₂O₃-Al₂O₃ composite coatings was studied using linear sweep voltammetry and AC impedance spectroscopy. The addition of the nanoparticles improved the corrosion resistance of the composite coating, and the composite coating prepared in an electrolyte containing 10 g/L of Y₂O₃ and 10 g/L of Al₂O₃ nanoparticles exhibited the best corrosion resistance. Meanwhile, the composite coating exhibited good hydrophobicity, with a contact angle of 120.9°, 1.94 times that of the pure Zn coating (62.2°). The Zn-Y₂O₃-Al₂O₃ nanocomposite coating material has significant potential advantages in the field of steel corrosion.

High dimensional statistical analysis for the yield of large-scale circuits is quite difficult due to expensive simulations, especially for the memory circuits with high sigma requirement (e.g., SRAM). In this paper, we developed an efficient sparse additive model to substitute simulations. To fit high sigma region accurately, the modeling center is moved to near failure boundary searched by scaling the shape of sampling function. To solve the model efficiently, the process variables are grouped by standard cells so that the model can be solved by our developed blockwise greedy algorithm. The experiments on the 28nm memory circuits validate that our method achieves high accuracy and efficiency compared with other state-of-art works.

Novel 1,2,3-triazole compounds 3–4 were synthesised via the regioselective addition and cyclization reaction of 1,1-enediamines (EDAMs) 1 with p-methylbenzenesulfonyl azide (TsN₃) 2 in 1,4-dioxane at refluxing for 5 hours. As a result, 1,2,3-triazoles 3–4 can be easily and efficiently obtained via catalyst-free click chemistry. The reactions have some advantages such as metal-free catalyst, excellent yield, inexpensive raw materials, and convenient final treatment.

The nonlinear dynamics exhibited by aircraft flying at high angle of attack (AOA) pose great challenges to the design of flight control. The control design based on nonlinear dynamic inversion (NDI) is to reversely find the required control input based on the current nonlinear dynamics of the aircraft and the control objectives to be achieved. Since it is derived from the nonlinear dynamics of the aircraft, a single NDI controller can cover the entire flight envelope without the need for controller switching or gain scheduling. This paper employs the layered structure of the flight control loop to implement the NDI controller through the combination of aerodynamic control and thrust vectoring control (TVC). The resulting NDI controller is applied to an experimental F-16 installed with TVC to verify its high AOA maneuverability in the post-stall region. The verification simulation shows that the experimental F-16 under the NDI control can effectively track the high AOA command and successfully demonstrate the Herbst maneuver by performing the heading reversal with 70° AOA.

Functional connectivity (FC) is a potential candidate that can increase the performance of brain-computer interfaces (BCIs) in the elderly because of its compensatory role in neural circuits. However, it is difficult to decode FC by current machine learning techniques because of a lack of its physiological understanding. To investigate the suitability of FC in BCI for the elderly, we propose the decoding of lower- and higher-order FCs using a convolutional neural network (CNN) in six cognitive-motor tasks. The layer-wise relevance propagation (LRP) method describes how age-related changes in FCs impact BCI applications for the elderly compared to younger adults. Seventeen younger (24.5±2.7 years) and twelve older (72.5±3.2 years) adults were recruited to perform tasks related to hand-force control with or without mental calculation. CNN yielded a six-class classification accuracy of 75.3% in the elderly, exceeding the 70.7% accuracy for the younger adults. In the elderly, the proposed method increases the classification accuracy by 88.3% compared to the filter-bank common spatial pattern (FBCSP). LRP results revealed that both lower- and higher-order FCs were dominantly overactivated in the prefrontal lobe depending on task type. These findings suggest a promising application of multi-order FC with deep learning on BCI systems for the elderly.

Tsallis entropy has been widely used in image thresholding because of its non-extensive properties. The non-extensive parameter q contained in this entropy plays an important role in various adaptive algorithms and has been successfully applied in bi-level image thresholding. In this paper, the relationships between parameter q and pixels’ long-range correlations have been further studied within multi-threshold image segmentation. It is found that the pixels’ correlations are remarkable and stable for images generated by a known physical principle, such as infrared images and medical CT images. And the corresponding non-extensive parameter q can be evaluated by using self-adaptive Tsallis entropy algorithm. The results of this algorithm are compared with those of Shannon entropy algorithm and the original Tsallis entropy algorithm, in terms of quantitative image quality evaluation metrics PSNR (Peak Signal-to-Noise Ratio) and SSIM (Structural Similarity). Furthermore, we observed that for image series with the same background, the q values determined by the adaptive algorithm are consistently kept in a narrow range. Therefore, similar or identical scenes during imaging would produce similar strength of long-range correlations, which provides potential applications for unsupervised image processing.

Star image registration is the most important step in the application of astronomical image differencing, stacking and mosaicking, which requires high robustness, accuracy and real--time of the algorithm, but there is no high--performance registration algorithm in this field. In this paper, we propose a star image registration algorithm that relies only on radial module features (RMF) and rotation angle features (RAF), which has excellent robustness, high accuracy, and good real--time performance. The test results on a large amount of simulated and real data show that the comprehensive performance of the proposed algorithm is significantly better than the four classical baseline algorithms in the presence of rotation, insufficient overlapping area, false stars, position deviation, magnitude deviation and complex sky background, which is a more ideal star image registration algorithm.

Abstract:The objects of fine-grained image categories(e.g., bird species) are various subclass under different categories. Because the differences between subclass are very subtle and most of them are concentrated in multiple local areas, the task of fine-grained image recognition is very challenging. At the same time, some fine-grained networks tend to focus on a certain region when judging the target category, resulting in the lack of other auxiliary regional features. To this end, Inception V3 is used as the backbone network, and an enhanced and complementary fine-grained image classification network is designed. While adopting the method of reinforcement learning to obtain more detailed fine grain image features, the complementary network can obtain the complementary discriminant area of the target through the method of attention erasure to increase the network's perception of the overall target. Finally, experiments are conducted on CUB-200-2011, FGVC Aircraft and Stanford dogs three open datasets. The experimental results show that the proposed model has better performance.

Objectives: To examine the long term impact of COVID-19 on sleep patterns and development of sleep disorders. Methods: Using the centralized Massachusetts General Brigham (MGB) Research Patient Data Registry (RPDR), SARS-CoV2 positive patients were surveyed about their sleep patterns before and after the viral infection. Information related to co-morbid conditions and medications were obtained through chart review. Results: Two hundred and forty five completed surverys were analysed. Average age was 53.3 ± 16.3 years, and participants were predominantly Non-Hispanic White (84.1%) and female (74.3%). Average BMI (kg/m2) was 29.9 ± 6.9, and a greater proportion was non-smokers (63.2%). After COVID-19, there was an increase in the percentage of participants reporting difficulty initiating (31 ± 46% vs. 39 ± 49%, P=0.01), and maintaining sleep (43 ± 49% vs. 57 ± 49%, P<0.001), and use of sleep aids (24 ± 43% vs. 30 ± 45% P=0.003) with an incidence rate of 24.3%, 37.4%, and 12.3% respectively. In addition, there was an increase in daytime fatigue and the need for napping (58 ± 49% vs. 36 ± 48%, P <0.0001) with an incidence of 8% and 23% respectively. The sleep symptoms persisted beyond 12 months among 28% of the participants and were predominantly seen among women. Conclusions: Infection with SARS-CoV2 has negative effects on sleep, and a significant proportion of adults experience insomnia and daytime sleepiness beyond 12 months after recovering from the initial infection.

：An effective technology for predicting the end-point phosphorous content of basic oxygen furnace (BOF) can provide theoretical instruction to improve the quality of steel via controlling the hardness and toughness. Given the slightly inadequate prediction accuracy in the existing prediction model, a novel hybrid method was suggested to more accurately predict the end-point phosphorus content by integrating an enhanced sparrow search algorithm (ESSA) and a multi-strategy with a deep extreme learning machine (DELM) as ESSA-DELM in this study. To begin with, the input weights and hidden biases of DELM were randomly selected, resulting in that DELM inevitably had a set of non-optimal or unnecessary weights and biases. Therefore, the ESSA was used to optimize the DELM in this work. For the ESSA, the Trigonometric substitution mechanism and Cauchy mutation were introduced to avoid trapping in local optima and improve the global exploration capacity in SSA. Finally, to evaluate the prediction efficiency of ESSSA-DELM, the proposed model was tested on process data of the converter from the Baogang steel plant. The efficacy of ESSA-DELM was more superior to that of other DELM-based hybrid prediction models and conventional models. The result demonstrated that the hit rate of end-point phosphorus content within ±0.003%, ±0.002%, and ±0.001% was 91.67%, 83.33%, and 63.55%, respectively. The proposed ESSA-DELM model could possess better prediction accuracy compared with other models, which could guide field operations.

A high-performance Lead-free Piezoelectric Energy Harvester (LPEH) based on a Ba0.85Ca0.15Ti0.90Zr0.10O3 + CuO 0.3 wt% (BCTZC0.3) composite was fabricated by sintering at 1450℃. The BCTZC0.3 composite, which has an enhanced high-energy-conversion constant (〖d_33×g〗_33), shows improved piezoelectric power-generation performance when compared with conventional piezoelectric energy harvesters. The BCTZC0.3-based LPEH produces instantaneous maximum power of 8.2 mW and an energy density of 107.9 mW/cm3 in a weak magnetic field of 250 μT. This energy harvester can be used to charge a capacitor and operate a wireless sensor network (WSN) system to provide temperature sensing and radio-frequency (RF) transmission in a 250 μT magnetic field. The proposed LPEH is a promising green-energy device for potentially self-powering WSN systems when applied.

With the development of deep learning, several Graph Neural Networks (GNN)-based approaches have been utilized for text classification. However, GNNs encounter challenges in capturing contextual text information within a document sequence. To address this, a novel text classification model RB-GAT is proposed by combining RoBERTa-BiGRU embedding and a multi-head Graph ATtention Network (GAT). First, the pre-trained RoBERTa model is exploited to learn word and text embeddings in different contexts. Second, the Bidirectional Gated Recurrent Unit (BiGRU) is employed to capture long-term dependencies and bidirectional sentence information from the text context. Next, the multi-head graph attention network is applied to analyze this information, which serves as a node feature for the document. Finally, the classification results are generated through a Softmax layer. Experimental results on three benchmark datasets demonstrate that our method can achieve an accuracy of 71.48%, 98.45%, and 80.32% on Ohsumed, R8, and MR, which is superior to the existing nine text classification approaches.

The iron roughneck is an automated equipment utilized for the connection and removal of drilling tools. This paper presents the design of an integrated iron roughneck, providing a detailed introduction to its clamp body structure, along with an analysis of its structural characteristics and performance requirements. The study delves into the integration mode and working characteristics of the clamping mechanism and spin buckle mechanism for the integrated upper clamp body structure of the iron roughneck. Additionally, this paper conducts an in-depth theoretical study on the spin buckle mechanism. Firstly, it analyzes the actual working condition of the spin buckle roller from two perspectives: contact theory and rolling friction theory, determining the structural form of the spin buckle roller. Secondly, it investigates the relative displacement between the spin buckle mechanism and the drilling tool, proposing a design method for the floating device mounted on the spin buckle roller and establishing the kinematic equation of the spin buckle roller under the influence of the floating device. Furthermore, the kinematic equations of the spin buckle roller under the influence of the floating device are established. Finally, a dynamics simulation experiment is performed to simulate the working process of the spin buckle mechanism under actual working conditions, analyzing the dynamics and kinematics of the spin buckle mechanism and obtaining the relevant parameter curves of the spin buckle mechanism and drilling tools. Through data comparison and analysis, the correctness of the theoretical analysis results and the rationality of the performance and structure of the spin buckle mechanism are verified.

Currently, peptic ulcers are widely studied as an infectious disease caused by Helicobacter pylori primarily due to 3 supporting evidences, and this etiology may explain the other 3 observations, but cannot confront the challenges of the 15 major characteristics and the other 75 observations/phenomena of peptic ulcers. To address the challenges, a recently published Complex Causal Relationship with its accompanying methodologies was applied to analyze existing data. Peptic ulcers are identified as a psychosomatic disease triggered by psychological stress, where Helicobacter pylori plays a secondary role in only the late phase of ulceration. This new etiology elucidated all the 15 major characteristics and 81 observations/phenomena of peptic ulcers in a series of 6 articles. This sixth article focuses exclusively on the controversies surrounding the role of Helicobacter pylori in peptic ulcers. In-depth analyses find that all the 3 evidences supporting “peptic ulcers are an infectious disease caused by Helicobacter pylori” are deceiving, and 2 of the 3 explainable observations may have been misinterpreted. Meanwhile, the definitions of ‘etiological factor’ and ‘causality’ do not support ‘H. pylori infection is an etiological factor of peptic ulcers’, and existing literatures have presented a controversial view on the role of Helicobacter pylori in peptic ulcers. Interestingly, if “peptic ulcers are an infectious disease caused by Helicobacter pylori” is considered an illusion, all the characteristics of the disease, along with all the clinical, epidemiological, and laboratory observations/phenomena, can be fully understood. This illusion has misguided peptic ulcer research over the past 36 years with little progress in the field, and that may represent a widespread situation in modern medical research, resulting in a direct interference with the true understanding of disease. Evidently, keeping the concept “illusion” in mind may help remove a huge obstacle that impedes medical advance, thereby facilitating the in-depth study of disease.

This study examines the Willingness-To-Pay (WTP) of consumers and the determinants of eco-labeling for the organic cocoa powder produced in the Dong Nai UNESCO Biosphere Reserve (DNBR), Southern Vietnam. Eco-labels are designed according to Tiers of eco-labeling for biosphere reserves (BR) introduced by UNESCO include BR Destination (Tier 1), BR Quality Label (Tier 2), and Professional Certification Label (Tier 3). Questionnaires are delivered to 203 customers in the DNBR and nearby places, such as Dong Nai and HCMC. This study employs a hybrid approach using descriptive statistics, ANOVA test, and Partial Least Squares Structural Equation Model (PLS-SEM). The results indicate that gender and educational level have a positive effect on consumers' preferences. Customers are willing to pay more for cocoa powder with an eco-label than one with an organic label. Perceived food safety and product knowledge lower customers’ WTP, whereas agricultural environment and pricing concerns increase it. Tier 2 is suggested for labeling cocoa powder in the DNBR. The DNBR Management Board, together with the federal and provincial governments, should all follow a similar certification process. Increased eco-label awareness is crucial for the future of environmentally responsible shopping and responsible business practices.

The power converter is the significant device in a wind power system. Wind turbine will be shut down and off grid immediately with the occurrence of the IGBT module open-circuit fault of power converter, which will seriously impact the stability of grid and even threaten personal safety. However, in the existing diagnosis strategies of power converter, there are few single and double IGBT modules open-circuit fault diagnosis methods producing negative results including erroneous judgment, omissive judgment and low accuracy. In this paper, a novel method to diagnose the single and double IGBT modules open-circuit faults of the permanent magnet synchronous generator (PMSG) wind turbine grid-side converter (GSC) is proposed. Above all, collecting the three-phase current varying with wind speed of 22 failure states including a normal state of PMSG wind turbine GSC as the original signal data. Afterward, the original signal data are decomposed by using variational mode decomposition (VMD) to obtain the mode coefficient series, which are analyzed by the proposed method base on fault trend feature for extracting the trend feature vectors. Finally, the trend feature vectors are used as the input of deep belief network (DBN) for decision-making and obtaining the classification results. The simulation and experimental results show that the proposed method can diagnose the single and double IGBT modules open-circuit faults of GSC, and the accuracy is higher than the benchmark models.

This work presented the design and fabrication of blood vessel and breast tumor detection device (BKA-06) based on optical energy spectroscopy. The BKA-06 device uses red-to-near-infrared light-emitting diodes that allow physicians or physicians to visualize blood vessels and surface structures such as breast tumors with the naked eye. The device consisted of built-in current control circuit to have the appropriate brightness (maximum illuminance of 98592 lux) for the examination of superficial tumors deep under the skin, with a scan time of 3-5 minutes. The device BKA-06 could facilely observe each layer of blood vessels at the depth of the skin. For breast tumors, the location, size and invasive areas around the tumor can also be visualized with the naked eye using the BKA-06 sensor. The results show that the BKA-06 sensor can provide clear breast tumor and vascular images with a penetration of up to 15 cm in the skin and tissue layers of the breast. The breast tumor scanning tests with the BKA-06 sensor gave patients quick results and compared them through cell biopsy and MRI respectively. The device has the advantage of being simple, easy to use, providing potential practical applications in the medical field, reducing costs for patients when taking MRI or CT scans. Therefore, the BKA-06 device is expected to help doctors and medical staff overcome difficulties in infusion as well as identify breast tumors to support early breast cancer diagnosis and treatment.

Objective: The objective of this study is to determine the epidemic dynamics and clinical features of COVID-19 in southern Hainan Island, China, and provide experience for other tropical areas of the world. Methods: This retrospective study included confirmed cases of COVID-19 in southern Hainan. All enrolled patients were treated in Sanya, and data on epidemiological and clinical features of the disease and infection prevention and control measures adopted by the local government during the epidemic were collected. Results: Of the 74 cases, 71 (95.95%) were imported from Wuhan, Hubei Province (47, 63.51%), other cities in Hubei Province (11, 14.86%), or provinces other than Hubei and Hainan (13, 17.57%). Three (4.06%) patients were infected in southern Hainan, including one autochthonous case in Sanya. Fifty-four cases (72.97%) were detected in Sanya, and 27 cases (27.03%) were diagnosed in other cities. The rate of severe or critical cases was 28.38% (21/74), and mortality was 2.7% (2/74). The serum lactate levels and base excess of severe-critical patients were higher than those of patients with mild-moderate disease. Multivariate logistic regression analysis showed that chronic conditions were risk factors for severe and critical COVID-19. Seventy-four patients were diagnosed with COVID-19 over a 22-day period in Sanya, and the epidemic period in the city was 48 days. The outbreak was controlled rapidly because the local government adopted strict infection prevention and control measures. Conclusions: The clinical characteristics of COVID-19 in Hainan Island were similar to those reported in other regions. In Sanya, the rate of severe and very severe cases was higher than in other regions; however, most cases were imported, and there was only one autochthonous case. The rapid control of the outbreak in Sanya may be related to the tropical climate, adoption of strict infection prevention and control measures, daily reporting of new cases, increased public awareness about the epidemic, and other emergency actions implemented by the local government.

: This study focuses on optimizing chlorophyll extraction techniques and strategically placing leaf disks to enhance chlorophyll concentration in sesame (Sesamum indicum L.) leaves. Thirty sesame genotypes, categorized into light green (LG), middle green (MG), and deep green (DG) pigment groups based on leaf coloration, were selected from a larger pool of field-grown accessions. The investigation involved determining optimal SPAD value index measurements, quantifying pigment concentrations, exploring extraction solvents, and selecting suitable leaf disk positions. Significant variations in chlorophyll content were observed across genotypes, greenness categories, and leaf disk positions. The categorization of genotypes into DG, MG, and LG groups revealed a correlation between leaf appearance and chlorophyll content. The study highlighted a consistent relationship between carotenoids and chlorophyll, indicating their role in adaptation to warm environments. Examination of leaf disk positions revealed a significant chlorophyll gradient along the leaf blade, emphasizing the need for standardized protocols. Chlorophyll extraction experiments identified DMSO and 96% ethanol, particularly the later incubated for 10 minutes at 85°C, as effective choices. This recommendation considers factors like cost-effectiveness, time efficiency, safety, and environmental regulations, ensuring consistent and simplified extraction processes. For higher chlorophyll extraction, focusing on leaf tips and the 75% position along the sesame leaf blade is suggested, consistently yielding higher chlorophyll content. Our findings therefore, underscores insightful knowledge on chlorophyll gradients and encouraging for standardized protocols, that enabling researchers to refine experimental designs for precise and comparable chlorophyll measurements. Recommended solvent choices ensure reliable outcomes in plant physiology, ecology, and environmental studies.

An experiment was conducted to investigate the role of single nucleotide polymorphisms of the gene RNF34 3′UTR-588 G>A and RNF128 I1-2380C>T with carcass and meat quality traits of Chinese Simmental-cross steers. METHOD: We performed sequencing and restriction enzyme digestion to detect genotypes of RNF34 3′UTR-588 G>A and RNF128 I1-2380C>T. Then, we analyzed the association of novel single nucleotide polymorphisms in intron regions of the RNF128 gene and in the 3′UTR region of RNF34 and meat quality traits of Chinese Simmental-cross steers. RESULTS: Statistical analyses revealed that SNP of RNF128 (I1-2380C>T) was significantly associated with dressed weight, forepaw weight, carcass depth, carcass brisket depth, hind legs length (P<0.05), etc. And RNF34 (3′UTR-588 G>A) were significantly associated with testis weight, kidney weight, tare weight (P<0.05), etc. CONCLUSION: Our findings suggest that polymorphisms in RNF34 and RNF128 might be important genetic factors that influence carcass and meat quality in beef cattle. Thus, they might be useful markers for meat quality traits in future marker-assisted selection programs in beef cattle breeding and production.

The drinking water temperature is expected to increase in the Netherlands due to climate change and the installation of district heating networks as part of the energy transition. To determine effective measures to prevent undesirable temperature increase of the drinking water a model is developed. This model describes the temperature in the drinking water distribution network as a result of the transfer of heat from the climate, above and underground heat sources through the soil. The model consists of two coupled applications. The extended soil temperature model (STM+) describes the soil temperatures, in a two-dimensional finite element method that includes a drinking water pipe and two hot water pipes, coupled to a micro meteorology model. The extended water temperature model (WTM+) describes the drinking water temperature as a function of the surrounding soil temperature (the boundary temperature, resulting from the STM+), thermal sphere of influence where the drinking water temperature influences the soil temperature, and the hydraulics in the drinking water network. Both models are validated with field measurements. This paper describes the WTM+. Previous models did not consider the cooling effect of the drinking water on the surrounding soil, which led to an overestimation of the boundary temperature, and to an overestimation of how quickly the drinking water temperature reaches this boundary temperature. The field measurements show the improved accuracy of the WTM+ when considering one to two times the radius of the drinking water pipe as the thermal sphere of influence around the pipe.

The presence of phase diffusion can lead to the loss of the advantages of quantum measurements. Squeezing is considered to be an effective method to reduce the detrimental effect of phase diffusion on the measurement. The Mach-Zehnder (MZ) interferometer has been exploited as a generic tool for precise phase measurement. Describing the reduction in quantum advantage caused by phase diffusion in an MZ interferometer that can be mitigated by squeezing is not easy to handle analytically, because the input state will change from a pure state to a mixed state after experiencing the diffusion noise in the MZ interferometer. We introduce a truncated MZ interferometer that can achieve the same potential phase sensitivity as the conventional MZ interferometer. This scheme can theoretically explain how phase diffusion reduces phase estimation and why squeezing counteracts in the presence of phase diffusion. Using the Gaussian property of the input state and the characteristic of Gaussian operation in the squeezing, the two orthogonal field quantities of the quantum state are squeezed and anti-squeezed to different degrees, and the analytic results are obtained. The truncated MZ interferometer is simpler to build and operate than the conventional MZ interferometer, and also mitigates the phase diffusion noise by the squeezing operation, thus making it useful for applications in precision metrology.

The application of movement-detection sensors is crucial for understanding surface movement and tectonic activities. The development of modern sensors has been instrumental in earthquake monitoring, prediction, early warning, emergency commanding and communication, search and rescue, and life detection. There are numerous sensors currently being utilized in earthquake engineering and science. It is essential to review their mechanisms and working principles thoroughly. Hence, we have attempted to review the development and application of these sensors by classifying them based on the timeline of earthquakes, physical or chemical mechanisms of sensors, and location of sensor platforms. In this study, we analyzed all available sensor platforms that have been widely used in recent years, with satellites and UAVs being among the most used. The findings of our study will be useful for future earthquake response and relief efforts, as well as research aimed at reducing earthquake disaster risks.

A overview on application of CO2 in the ironmaking and steelmaking process is presented. Study on resource utilization of CO2 is significant for the reduction of CO2 emissions and the coping with global warming. The paper introduces the research progress of CO2 utilization in the sintering, Blast Furnace, Converter, secondary refining, Continuous Casting and smelting process of stainless steel in recent years in China. According to the foreign and domestic research and application status, the paper analyzes the feasibility and metallurgical effects of the CO2 utilization in the ferrous metallurgy process. The paper mainly introduces such new techniques as 1) flue gas circulating sintering, 2) blowing CO2 through Blast Furnace tuyere and CO2 as a pulverized coal carrier gas, 3) top and bottom blowing CO2 in the converter, 4) Ladle Furnace and Electric Arc Furnace bottom blowing CO2, 5) CO2 as Continuous Casting shielding gas, 6) CO2 for stainless steel smelting, and 7) CO2 circulation combustion. CO2 has a very wide application prospect in ferrous metallurgy process and the quantity of CO2 utilization is expected to be 100kg per ton of steel. It will effectively facilitate the progress of metallurgical technology and strongly promote the energy conservation of metallurgical industry.

When overhead lines are impacted by lightning, the traveling wave of the fault contains a wealth of fault information. The accurate extraction of feature quantities from transient components and their classification is fundamental to the identification of lightning faults. The extraction process may involve modal aliasing, optimal wavelet base issues, and inconsistencies between the lightning strike distance and the fault point, which have the potential to impact the effectiveness of recognition. This paper presents a method for identifying lightning strike faults by utilizing Kullback-Leibler (KL) divergence enhanced Variational Mode Decomposition (VMD) and Symmetric Geometry Mode Decomposition (SGMD) improved with Permutation Entropy (PE) to address the aforementioned issues. A model of a 220 kV overhead line is constructed using real faults to replicate scenarios of winding strike, counterstrike, and short-circuit. The three-phase voltage is chosen and then sub-jected to Karenbaren decoupling in order to transform it into zero mode, line mode 1, and line mode 2. The zero mode voltage is decomposed using KL-VMD and PE-SGMD methods, and lightning identification criteria are developed based on various transient energy ratios. The research findings demonstrate that the criteria effectively differentiate between winding strike, counterstrike, and short-circuit faults, thus confirming the accuracy and efficacy of the lightning fault identification criteria utilizing KL-VMD and PE-SGMD.

Brain metastasis (BrM), involving the spread of cells from a primary tumor through the blood circulation system to the brain microvasculature, eventually progresses despite multiple treatments and remains a substantial contributor to major mortality in patients with advanced- stage cancer. Molecular signatures and immune cellular components of the tumor microenvironment (TME) are emerging as essential regulators involved in establishing an organ-specific metastasis (colonization) and therapeutic response. A comprehensive understanding of detailed characterization and the immune landscape in context of process of BrM formation will greatly expand the horizon of treatments available to target these deadly diseases. In this review, we provide a comprehensive picture of the complex interactions between tumor cells and immune cellular components participated in the BrM process. Based on this knowledge, we will discuss opportunities and challenges for therapeutic strategies against BrM.

Flux-switching permanent magnet (FSPM) motors have gained increasing attention in the electric vehicles (EVs) applications due to the advantages of high power density, high efficiency. However, the heat sources of both permanent magnet (PM) and armature winding are located on the limited stator space in the FSPM motors, which may result in the PM overheated and irreversible demagnetization caused by temperature rise and it is often ignored in the conventional thermal analysis. In this paper, a new electrical-thermal two-way coupling design method is proposed to analyze the electromagnetic performances, where the change of PM material characteristics under different temperatures is taken into consideration. Firstly, the motor topology and design equations are introduced. Secondly, the demagnetization curves of PM materials under different temperatures are modeled due to PM materials are sensitive to the temperature. And based on the electrical-thermal two-way coupling method, the motor performances are evaluated in details, such as the load PM flux linkage and output torque. Then, the motor is optimized, and the electromagnetic performances between initial and improved motors are compared. Finally, a prototype motor is manufactured, and the results are validated by experimental measurements.

Convolutional Neural Networks (CNNs) are largely hand-crafted, which leads to inefficiency in the constructed network. Various other algorithms have been proposed to address this issue, but the inefficiencies resulting from human intervention have not been addressed. Our proposed EvolveNet algorithm is a task-agnostic evolutionary search algorithm that can find optimal depth and width scales automatically in an efficient way. The optimal configurations are not found using grid search, instead evolved from an existing network. This eliminates inefficiencies that emanate from hand-crafting, thus reducing the drop in accuracy. The proposed algorithm is a framework to search through a large search space of subnetworks until a suitable configuration is found. Extensive experiments on the ImageNet dataset demonstrate the superiority of the proposed method by outperforming the state-of-the-art methods.

Displacement mapping is a computer graphics technique that enables the design of components with regularly or randomly textured surfaces that can be quickly materialized on a three-dimensional (3D) printer when needed. This approach is in principle more flexible, faster and more economical compared to conventional texturing methods, but the accuracy of the texture depends heavily on the parameters used. The purpose of this study is to demonstrate how to produce a surface-textured part using polygonal (mesh) modeling software and a photopolymerizable resin, and to develop a universal methodology to predict the dimensional accuracy of the model file log combined with a resin 3D printer. The printed components were characterized on a scanning confocal microscope. In the setup used in this study, the mesh size had to be reduced to 10% of the smallest feature size and the textured layer had to be heavily (x4) overexposed to achieve the desired accuracy. As a practical application, two functional stamps with a regular (honeycomb) and a random texture, respectively, were successfully manufactured. The insights gained will be of great benefit in quickly and cost-effectively producing components with innovative patterns and textures for a variety of hobby, industrial and biomedical applications.

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

Background: Plasma levels of von Willebrand factor (VWF) are significantly elevated in patients with COVID-19. However, the dynamic changes and prognostic value of this biomarker in hospitalized patients with COVID-19 are not determined. Methods: 124 patients infected with SARS-CoV2 were prospectively recruited for the study. Serial blood samples were obtained at the time of admission (D1), 3-4 days following standard of care treatments (D2), and 1-2 days prior to discharge or death (D3). Plasma VWF antigen, ADAMTS13 antigen and activity, as well as the ratio of VWF/ADAMTS13 were determined, followed by statistical analyses. Results:While admission plasma levels of VWF in COVID-19 patients were significantly elevated, no statistical significance was detected among patients of different disease severity. Plasma ADAMTS13 activity, but not its antigen levels, were significantly lower in patients with severe or critical COVID-19 compared with other groups. Interestingly, the ratios of plasma VWF antigen to ADAMTS13 antigen were significantly higher in patients with severe or critical COVID-19 than in those with mild to moderate disease. More importantly, plasma levels of VWF and VWF/ADAMTS13 ratios were persistently elevated in patients with COVID-19 during hospitalization. Kaplan-Meier and Cox proportional hazard regression analysis revealed that an increased plasma VWF or ratio of VWF/ADAMTS13 at D2 and D3 associated with an increased mortality rate. Conclusions: Persistent endotheliopathy, marked by an elevated level of plasma VWF or an increased VWF/ADAMTS13 ratio, is present in all hospitalized patients following SARS-CoV2 infection and strongly associated with mortality.

The purpose of this study is to examine the relationship between the institutional investors which can affect financial performance for corporate sustainability on the income smoothing. Therefore, this study focus on the connection between the nature of stock rights and income smoothing in China. For this study, hypotheses were established on the relationship each state-controlled companies, income smoothing, and information equilibrium of individual investors, and empirical analysis was conducted through related variables. The analysis results are summarized in three categories as follows. First, this research finds that state-controlled firms (CONTs) prefer income smoothing activities compared to non-state-controlled firms for the long-term sustainable development of firms using data from 2011 to 2019. Second, this study found out that Institutional investors support the behavior of CONTs to smooth their earnings because this behavior is seen as an attempt by CONTs to convey valuable private information to other investors. Third, we was able to discover that institutional investors' monitoring effect is predominantly driven by pressure-resistant institutional investors. This research complements the lack of empirical research on income smoothing and enable to give a guideline that the type of stock rights is a critical key determinant of participation in income smoothing activities for stable growth and sustainability in the future.

The majority of existing numerical simulations of the effect of bridge piers on water movement are based on a limited number of bridge piers at a laboratory scale. Furthermore, some 2D numerical simulations for actual bridge projects have deficiencies, including the use of overly large mesh sizes and an inadequate treatment of bridge piers. In this study, we compare three methods of structural mesh encryption, suspension mesh, and nonstructural mesh based on Delft3D, and apply the optimization scheme to a real bridge project. It is demonstrated that optimal results can be achieved by utilising a grid size comparable to the pier diameter (Dp) in the region away from the piers. In the vicinity of the piers, the grid cell size should be no larger than 1/9 Dp. The suspended grid technique (DD Boundary) can yield results consistent with those obtained using a full-area high-resolution grid, provided that the total number of grids can be reduced and the computational time is considerably reduced. In this study, the unstructured mesh (Deflt3D Flexible Mesh) scheme was unable to capture the oscillations of the wake flow behind the bridge piers. However, the application of the optimized scheme in bridge engineering has demonstrated its practical value. The findings of this study on mesh resolution and suspension mesh scheme can be applied to the Delft3D software and are also useful for other numerical simulation work.

This paper proposed a three-layer distributed simulation network architecture: 1. Distributed virtual simulation network, 2. Perception and control sub-network, and 3. Collaborative communication service network. This simulation architecture runs on a distributed platform. The platform can provide a unique virtual scenario and several simulation services to verify the individual robot system's basic perception, control, and planning algorithms and the distributed collaborative algorithms of heterogeneous multi-robot systems. Furthermore, we designed a simulation experiment scenario for classical heterogeneous robot systems such as unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs). At last, We gave a rough estimation model of the bandwidth.

At the end of the dry season in early March to early April each year, extensive agricultural biomass waste burnings occur throughout insular mainland Southeast Asia. During this biomass burnings period, smoke aerosols blanket the whole regions and were transported and dispersed by predominant westerly and south westerly winds to southern China, Taiwan and as far southern Japan and the Philippines. The extensive and intense burnings coincided with some wildfires in the forests due to high temperature making the region one of the global hot spots of biomass fires. In this study, we focus on the effect of pollutants emitted from biomass burnings in March 2019 at the height of the burnings period to the exposed population and their health impact. The Weather Research Forecast- Chemistry (WRF-Chem) model was used to predict the PM2.5 concentration over the simulating domain and health impacts are then assessed on the exposed population in the four countries of Southeast Asia, namely Thailand, Laos, Cambodia and Vietnam. Using the health impact based on log-linear concentration response function and Integrated Exposure Response (IER), the results show that at the peak period of the burnings from 13 to 20 March 2019, Thailand experienced the highest impact, with an estimated 2170 premature deaths. Laos, Vietnam, and Cambodia followed, with estimated mortalities of 277, 565, and 314 deaths respectively. However, when considering the impact per head of population, Laos exhibited the highest impact, followed by Thailand, Cambodia, and Vietnam. The results highlight the significant health impact and associated economic cost of agricultural waste burnings in Southeast Asia at the end of the dry season. And hence policy makers should take these into account to design measures to reduce the negative impact of widespread burnings on exposed population in the region.

Amid escalating urbanization, devising rational commercial space layouts is a critical challenge. Leveraging machine learning, this study uses a Back-propagation (BP) neural network to optimize commercial spaces in Weinan City's central urban area. The results indicate an increased number of commercial facilities with a trend of multi-centered agglomeration and outward expansion. Based on these findings, we propose a strategic framework for rational commercial space development emphasizing aggregation centers, development axes, and spatial guidelines. This strategy provides valuable insights for urban planners in small and medium-sized cities in the Yellow River Basin and metropolitan areas, ultimately showcasing the power of machine learning in enhancing urban planning.

Detecting cracks in structural health monitoring is crucial for ensuring infrastructure safety and longevity. Using drones to obtain crack images and automate processing can improve the efficiency of crack detection. To address the challenges posed by the limited computing resources of edge devices in practical applications, we propose CrackScopeNet, a lightweight segmentation network model that simultaneously considers local and global crack features, suitable for deployment on drone platforms with limited computational power and memory. CrackScopeNet features a multi-scale branch to improve sensitivity to cracks of varying sizes without substantial computational overhead and a stripe-wise context attention mechanism to enhance the capture of long-range contextual information, mitigating the interference from complex backgrounds. Experimental results on CrackSeg9k dataset demonstrate that CrackScopeNet leads to a significant improvement in prediction performance, with the highest mean intersection over union (mIoU) scores reaching 82.12%, while maintaining a lightweight architecture with only 1.05M parameters and 1.58G floating point operations (FLOPs). Besides, CrackScopeNet excels in inference speed on edge devices without GPU because of its low FLOPs. CrackScopeNet contributes to the development of efficient and effective crack segmentation networks, suitable for practical structural health monitoring applications using drone platforms.

This article summarizes Chinese framework for regulating artificial intelligence and integrates evolutionary game theory with cost-benefit analysis to establish a model and simulation. This framework is employed to analyze the behavioral trends among three distinct entities: governmental bodies, third-party independent institutions, and AI companies within the context of regulatory relationship. The findings indicate that: (1) The cost-benefit dynamics within the regulatory legal nexus significantly influence the behaviors of these entities; (2) Under the condition of normalized government regulation approaching full enforcement, the behavioral choices of third-party independent institutions and AI companies exhibit cyclical fluctuations.The paper draws two principal conclusions: (1) The regulatory framework need to be tailored to the specific risks presented by AI and the relative costs and benefits of legal enforcement in different jurisdictions. (2) From a cost-benefit standpoint, government intervention in AI regulation ought to be circumscribed, with government regulation focusing on critical legal risks. Other aspects of regulatory control should be delegated to cooperative legal framework that allows the participation of the independent third-party institution,which brings a nuanced and specialized approach to the governance of AI.

Classical enzyme kinetics are summarized and linked with modern discoveries here. The time course of sequential catalytic events by biological macromolecular enzyme is analyzed at the molecular level; the relationships between catalytic efficiency (turnover number), catalytic rate/velocity, the amount of time taken and physical/biochemical conditions of the system are discussed. This writing tries to connect the microscopic molecular behavior of enzyme to kinetic data obtained in experiment, and the hypothesis proposed here provide an interpretation to previous experimental observations and can be testified by future experiments.

With the rapid development of MEMS (Micro-electro-mechanical Systems) fabrication technologies, manifolds microelectrodes with various structures and functions have been designed and fabricated for applications in biomedical research, diagnosis and treatment through electrical stimulation and electrophysiological signal recording. The flexible MEMS microelectrodes exhibit multi-aspect excellent characteristics beyond stiff microelectrodes based on silicon or SU-8, which comprising: lighter weight, smaller volume, better conforming to neural tissue and lower fabrication cost. In this paper, we mainly reviewed key technologies on flexible MEMS microelectrodes for neural interface in recent years, including: design and fabrication technology, flexible MEMS microelectrodes with fluidic channels and electrode-tissue interface modification technology for performance improvement. Furthermore, the future directions of flexible MEMS microelectrodes for neural interface were described including transparent and stretchable microelectrodes integrated with multi-aspect functions and next-generation electrode-tissue interface modifications facilitated electrode efficacy and safety during implantation. Finally, the combinations among micro fabrication techniques with biomedical engineering and nanotechnology represented by flexible MEMS microelectrodes for neural interface will open a new gate to human lives and understanding of the world.

To address the problems of lining cracking and spalling of tunnel structures in coastal areas under the influence of special geologic conditions, environmental loading, and the coupling effect of chemical erosion effects, hybrid fibers were introduced to fly ash concrete in this study. The working performance, compressive strength, split tensile strength, and flexural strength of the hybrid fiber fly ash concrete were tested.The NEL chloride diffusion coefficient under steady-state conditions and the durability test for resistance to sulfate corrosion were carried out. Thus, in-depth analyses of the comprehensive performance of the hybrid fiber fly ash concrete used for tunnel lining were carried out and the damage mechanism were explored. The results showed that the hybrid fiber fly ash concrete exhibited higher strength compared to the control group concrete. However, when the fibers exceeded a certain dosage, the reduction in the working properties of the concrete structure led to the creation of larger pores in the matrix structure, which in turn affected the mechanical properties of the concrete. The most significant reduction in NEL chloride diffusion coefficient was observed when both steel fibers and coconut fibers were added at 1.0 % volumetric parameter, compared to the control group. The apparent state and compressive strength after sulfate corrosion were also minimally affected. This study ensured that the mechanical properties of the concrete were improved and also substantially improved the corrosion resistance of the matrix, providing a scientific basis for the performance improvement of tunnel lining concrete, confirming that steel-coconut fibers hybrid fiber fly ash concrete has a great potential to improve the structural load bearing capacity and durability, and may provide theoretical support for the continued use of tunneling projects and construction processes.

The quantified residence time distribution (RTD) provides a numerical characterization of mixing in the continue casting tundish, thus allowing the engineer to better understand the metallurgical performance of the reactor. This paper describes a computational fluid dynamic (CFD) modelling study for analyzing the flow pattern and the residence time distribution in a five-strand tundish. Two passive scalar transport equations are applied to separately calculate the E-curve and F-curve in the tundish. The numerical modelling results are compared to the water modelling results for the validation of the mathematical model. The volume fraction of different flow regions (plug, mixed and dead) and the intermixing time during the ladle changeover are calculated to study the effects of the flow control device (FCD) on the tundish performance. The result shows that a combination of the U-baffle with deflector holes and the turbulence inhibitor has three major effects on the flow characteristics in the tundish: i) reduce the extent of the dead volume; ii) evenly distribute the liquid streams to each strand and iii) shorten the intermixing time during the ladle changeover operation.

According to the characteristics of the sustainable development of subway traffic, the establishment process of an evaluation index system is determined, and the evaluation method and basis are defined. The evaluation index system is established from the aspects of subway traffic sustainability, economic sustainability and urban coordination sustainability. The comprehensive evaluation method of the analytic hierarchy process (AHP) model is used to calculate the weights of comprehensive evaluation indexes at each level. Finally, the sustainable development model of Shijiazhuang subway traffic is evaluated. The results show that the proposed evaluation system and model reflect the degree of sustainable development of subway traffic and can be used for reference in the evaluation of regional subway traffic sustainable development.

State transition in the multiple-levels system has the great potential applications in the quantum technology. In this article we employ a deterministic approach in complex space to analyze the dynamics of the 1s-2p electron transition in the hydrogen atom. The electron’s spin motion is embodied in the framework of quantum Hamilton mechanics that allows us to examine the transition dynamics more precisely. The transition is driven by an oscillating electric field in the z-direction. The electron’s transition process can be visualized by monitoring its motion in the complex space. The quantum potential and the total energy proposed in this paper provide new indices to observe the dynamic changes of electrons in the transition process.

Mucosal vaccines can target specific mucosal surfaces, such as the respiratory, genital, or intestinal mucosa. Conventional systemic immunization, such as intramuscular injections, do not provide mucosal immunity, including IgA, nor do they prevent pathogens from entering the mucous membranes. Nasal immunization protects mucosal membranes, but nasal antigen presentation appears to entail adjuvant to stimulate immunogenicity. Current treatments for mucosal diseases such as inflammatory bowel disease (IBD) and allergic dermatitis only aimed to temporarily relieve symptoms. Moreover, these treatments not only have drug resistance or side effects, but the disease can recur, leading to switching to other treatments. Therefore, there is a need to develop safe and effective treatments that provide better long-term outcomes to reduce the risk of recurrence. Regulatory T (Treg) cells have been used to suppress inflammation. To find advances in mucosal treatment, we investigated the therapeutic effects of intranasal pep27 mutant immunization. Here, a new method of Treg induction through intranasal immunization without adjuvant has been developed to potentially overcome allergies and mucosal inflammation of the lung-gut axis in animal models. The implementation of the pep27 mutant for these therapies should be preceded by studies of Treg resilience through clinical translational studies of dietary changes.

The rampant misuse of drones poses a serious threat to national security and human life. Currently, the CNN method has been widely used in drone detection. However, there is a challenge that traditional CNN cannot cope with, which is small drone targets often have reduced amplitude or even lost features in infrared images. This paper proposes a Progressive Feature Fusion Network (PFFNet) that gradually increases the response amplitude of the target in the deep network. The Feature Selection Model (FSM) is designed to improve the utilisation of the output coding graph and enhance the feature representation of the target in the network. A lightweight segmentation head is also designed to achieve progressive feature fusion with multi-layer outputs. Experimental results show that the proposed algorithm can achieve low duration and high accuracy in drone target detection. On the public dataset, the IoU is improved by 2.53% and the detection time is reduced by 81.03%.

Fe-(9, 19, 28, 37)wt.% Cr alloys were corroded at 700 and 800 ^oC for 70 h under 1 atm of N₂, 1 atm of N₂/3.2%H₂O-mixed gas, and 1 atm of N₂/3.1%H₂O/2.42%H₂S-mixed gas. The corrosion rate of Fe-9Cr alloy increased with the addition of H₂O, and furthermore with the addition of H₂S in N₂ gas. Fe-9Cr alloy was always nonprotective. In contrast, Fe-(19, 28, 37) wt.%Cr alloys were protective in N₂ and N₂/H₂O-mixed gas because of formation of the Cr₂O₃ layer. They were, however, nonprotective in N₂/H₂O/H₂S-mixed gas because sulfidation dominated to form the outer FeS layer and the inner Cr₂S₃ layer containing some FeCr₂S₄.

Aging is associated with muscle atrophy and fatty infiltration of skeletal muscle. The multifidus muscle stabilizes the lumbar spine and undergoes adipose accumulation with age, leading to functional decline in the elderly. Therefore, quantitative assessment of the multifidus muscle can be beneficial for the elderly when formulating treatment strategies and reducing future complications. Fifty-seven patients (mean age, 73.89 ± 6.09; 23 male patients) who underwent lumbar Magnetic resonance imaging (MRI) were prospectively recruited. The cross-sectional area (CSA) of the multifidus from the L2-S1 level and the CSA of the L4-5 level psoas muscle were measured. The functional CSA (fCSA) of the multifidus muscle was measured by excluding the fat infiltration area from the multifidus CSA. The CSA to fCSA ratio was obtained by multiplying 100 by the value obtained by dividing CSA by the fCSA. Pfrrmann classification was used to evaluate the degree of disc degeneration. The functional disability measurements were the Short Physical Performance Battery (SPPB), Berg Balance Scale (BBS), grip strength, and functional reach test (FRT). Pearson's correlation analysis was used to examine the relationship between the functional disability measurements and the multifidus muscle. The CSA to fCSA ratio value was relatively constant at each spine level and showed a significant correlation with the SPPB, grip strength, FRT, and psoas index (p&lt;0.05). However, degree of disc and multifidus muscle degeneration were not statistically significant. So, age-related changes play a significant role in developing back muscle fatty infiltration than disc dgeneration. Moreover, Grip strength showed a stronger relationship with the quality of the multifidus muscle than other functional disability measurements.

A new design scheme is proposed for twisting the walls of a microchannel, and its performance is demonstrated numerically. The numerical study was carried out for a T-shaped microchannel with twist angles in the range of 0 to 34π. The Reynolds number range was 0.15 to 6. The T-shaped microchannel consists of two inlet branches and an outlet branch. The mixing performance was analyzed in terms of the degree of mixing and relative mixing cost. All numerical results show that the twisting scheme is an effective way to enhance the mixing in a T-shaped microchannel. The mixing enhancement is realized by the swirling of two fluids in the cross section and is more prominent as the Reynolds number decreases. The twist angle was optimized to maximize the DOM, which increases with the length of the outlet branch. The twist angle was also optimized in terms of the relative mixing. The two optimum twisting angles are generally not coincident. The optimum twist angle shows a dependence on the length of the outlet branch but it is not affected much by the Reynolds number.

This study aimed to select the most effective metabolites for controlling honey bee nosemosis using culture extracts from 342 entomopathogenic fungi of 24 species from 18 genera. The germination inhibitory activity of the fungal culture extract against Nosema ceranae spores was evaluated using an in vitro germination assay method. Among 89 fungal culture extracts showing germination inhibitory activity of approximately 80% or more, 44 culture extracts that maintained their inhibitory activity even at a concentration of 1% were selected. Finally, the honey bee nosemosis inhibitory activity was evaluated using the cultured extracts of 5 fungal isolates having a Nosema inhibitory activity of approximately 60% or more even when the extract was removed after treatment. As a result, the proliferation of Nosema spores was reduced by all fungal culture extract treatments. However, only the treatment of the culture extracts from Paecilomyces marquandii 364 and Pochonia bulbillosa 60 showed a reduction in honey bee mortality due to nosemosis. In particular, the extracts of these two fungal isolates also increased the survival of honey bees.