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.

This paper discusses the computer-aided (CAD) classification between Hepatocellular Carcinoma (HCC), i.e., the most common type of liver cancer, and Liver Abscess, based on ultrasound image texture features and Support Vector Machine (SVM) classifier. Among 79 cases of liver diseases, with 44 cases of HCC and 35 cases of liver abscess, this research extracts 96 features of Gray-Level Co-occurrence Matrix (GLCM) and Gray-Level Run-Length Matrix (GLRLM) from the region of interests (ROIs) in ultrasound images. Three feature selection models, i) Sequential Forward Selection, ii) Sequential Backward Selection, and iii) F-score, are adopted to determine the identification of these liver diseases. Finally, the developed system can classify HCC and liver abscess by SVM with the accuracy of 88.875%. The proposed methods can provide diagnostic assistance while distinguishing two kinds of liver diseases by using a CAD system.

It is well established that the reaction cycles involving some halogenated alkanes (so-called ozone-depleting substances, ODS) contribute to the depletion of ozone in the stratosphere, thus causing the Montreal Protocol (initially signed in 1987) and later amendments. The Protocol called for the scheduled phase-out of ODS, including chlorofluorocarbons (CFC), hydrochloro-fluorocarbons (HCFC), carbon tetrachloride (CCl4), halon, methyl chloroform (CH3CCl3), me-thyl chloride (CH3Cl), and even hydrofluorocarbons (HFCs). In view of the urgent importance of ozone layer protection to the globally ecological environment, the Taiwan government took regulatory actions on reducing ODS consumption since 1993 by the joint-venture of the central competent authorities. Under the regulatory requirements and the industry’s efforts by adopt-ing the alternatives to ODS and abatement technologies, the phase-out of some ODS (i.e., CFC, CCl4, halon, and CH3CCl3) have been achieved prior to 2010. The consumptions of HCFCs and methyl chloride have been significantly declined over the past three decades (1993-2022). However, HFC emission indicated a V-type variation during the period. Due to the local pro-duction and extensive use of HFC in Taiwan, its emissions increased from 663 kilotons of carbon dioxide equivalents (CO2eq) in 1993 to 2,330 kilotons of CO2eq in 2001, and then decreased to 373 kilotons of CO2eq in 2011. Since then, the emissions of HFC largely used as the alternatives to ODS showed an upward trend, increasing to 1,555 kilotons of CO2eq in 2022. To be in compliance with the Kigali Amendment (KA-2015) to the Montreal Protocol for mitigating global warming, the Taiwan government has taken regulatory actions in reducing the consumption of some HFC substances with high global warming potential (GWP) under the authorization of the Climate Change Response Act in 2023, aiming at the baseline consumption in 2024 by 80 % reduction by 2045.

In this paper we perform numerous numerical studies for the problem of low-rank matrix completion. We compare the Bayesian approaches and a recently introduced de-biased estimator which provides a useful way to build confidence intervals of interest. From a theoretical viewpoint, the de-biased estimator comes with a sharp minimax-optimal rate of estimation error whereas the Bayesian approach reaches this rate with an additional logarithmic factor. Our simulation studies show originally interesting results that the de-biased estimator is just as good as the Bayesian estimators. Moreover, Bayesian approaches are much more stable and can outperform the de-biased estimator in the case of small samples. However, we also find that the length of the confidence intervals revealed by the de-biased estimator for an entry is absolutely shorter than the length of the considered credible interval. These suggest further theoretical studies on the estimation error and the concentration for Bayesian methods as they are being quite limited up to present.

We derive some Quantum Central Limit Theorems for expectation values of macroscopically coarse-grained observables, which are functions of coarse-grained hermitean operators consisting of non-commuting variables. Thanks to the hermicity constraints, we obtain positive-definite dis- tribution for the expectation values of observables. These probability distributions open some pathway for an emergence of classical behaviours in the limit of innitely large number of identical and non-interacting quantum constituents. This is in contradistinction to other mechanisms of classicality emergence due to environmental decoherence and consistent histories. The probabil- ity distributions so derived also enable us to evaluate the nontrivial time-dependence of certain differential entropies.

Flood records of the Kunmalik River in Chinese Tien Shan mountains have showed that glacier- dammed lake outburst floods (GLOF) had occurred almost every year since 1956 from the glaci-er-dammed Lake Merzbacher. However, GLOF in cold season is seldomly studied. The defense and management of the flood need further observation and study. The maximum peak discharge of 825 m3/s occurred on 5th December 1996 with the maximum flood volume of 2.875×108 m3, which was 18 times larger than that of the mean daily discharge in winter over the past six decades. The drainage of the Merzbacher lake is not a mechanical breaking up of the glacier dam, but the release of pressurized water along a subglacial tunnel triggered by quickly surge of the Northern Glacier, the subglacial tunnels are enlarged by both ice melting and frictional heat in the flooding water and heat under the glaciated dam and the lake in winter. There is no correlation between the GLOF size and air temperature of cold season. The floods in cold season have become bigger since 1996 than that before, and the flood duration has been extended from winter to spring. Once the cold GLOF starts, its discharge can be forecasted day by day to extrapolate the monitoring hydrograph as a linear curve.

Bisphenol A (BPA) has been identified as one of endocrine disrupting chemicals (EDCs). Due to its massive production (over 700,000 tons per year) and the extensive use of BPA-based plastics (i.e., polycarbonate and epoxy resin) in Taiwan, it was thus included into a toxic substance by the Ministry of Environment. This work surveyed the updated information about the production of BPA and its environmental distributions in Taiwan over the past decade. Furthermore, the regulatory strategies and countermeasures for managing the environmental risks of BPA by the Taiwan government were summarized to show the cross-ministerial efforts under the relevant acts, including the Toxic and Concerned Chemical Substances Control Act (TCCSCA), the Food Sanitation Management Act (FSMA) and the Commodity Inspection Act (CIA). The findings showed that most of the monitoring data showed far below the acceptable risks. However, the people may pose an adverse threat to the aquatic environment and human health via ecological and food chains. In addition, some countermeasures were further recommended to echo the international actions on environmental endocrine disruptors in recent years.

The recent market and pandemic, with their complex nature and unpredictable developments, have had a great impact on coffee chains. The recovery factor in today's fiercely competitive coffee market is also derived from customer satisfaction, and the product's perceived value and ever with businesses' capabilities and recovery strategies. The research is based on the Customer and Service Recovery Performance model. Therefore, this study aims to investigate the impact of the Customer Satisfaction premise on the service recovery of the coffee chain and some other effects. After collecting surveys from 300 customers who have used beverages at famous coffee chains in Vietnam and performing data analysis via SEM-PLS, the results show that customer satisfaction positively influences customer loyalty. Customer loyalty mediates between customer satisfaction, and price fairness affects the resilience of the coffee chain. In addition, the two factors, Flexibility, and Adoption, also positively affect service recovery performance. Therefore, for coffee chains, customers are an important factor, and they need to maintain customer loyalty. In addition, seek ways to increase flexibility and apply technology at stores so that the company has enough experience and capacity to respond promptly to difficult market conditions, natural disasters and epidemics. This study presents insights into how coffee chains can adapt to the dynamic business environment during the current difficult business environment.

Osteoclasts (OCs) are the multinucleated, bone-resorbing giant cells originally differentiated from a monocyte/macrophage lineage. OC differentiation and maturation, also called osteoclastogenesis, are strictly regulated by a variety of signaling pathways primarily induced by the interactions of two prerequisite cytokines, macrophage colony-stimulating factor (M-CSF) and the receptor activator of nuclear factor-κB ligand (RANKL) to their respective surface receptors, c-fms and RANK, in OC precursors (pre-OCs). Rab11 has emerged as the spatiotemporal regulators of intracellular vesicular transport in the endosomal recycling system; however, how it regulates osteoclastogenesis is incompletely understood. OC-triggered bone resorption is best characterized to be immensely dependent upon lysosomal function, the intracellular acidic organelles containing more than 50 acid hydrolases secreted into bone matrix microenvironment (BME). On the contrary, it is little known about the lysosomal function on modulating the turnover of c-fms and RANK surface receptors via Rab GTPase-mediated vesicular transport, thereby dictating osteoclastogenesis. In this review, I briefly describe the mechanism underlying lysosome-induced osteoclastogenesis via the Rab11-mediated modulation of the surface receptors in OCs.

Due to their excellent physicochemical properties, fluorinated greenhouse gases (F-gases), including hydrofluorocarbons (HFCs), perfluorocarbons (PFCs), sulfur hexafluoride (SF6), and nitrogen trifluoride (NF3), are used in a variety of applications, but they are potent greenhouse gases. Therefore, they have been blanketed into the list of phase-out under the international protocols or treaties. In this work, the updated statistics of the Taiwan’s national inventory report (NIR) were used to analyze the trends of F-gases (i.e., HFCs, PFCs, SF6 and NF3) emissions during the period of 2000-2020. Furthermore, the regulatory strategies and measures for reducing the emissions of the four F-gases will be summarized to be in accordance with the national and international regulations. With the progressive efforts by the regulatory requirements and the industry’s voluntary reduction, the total F-gases emissions indicated a significant increase from 2,462 kilotons of carbon dioxide equivalents (CO2eq) in 2000 to the peak value (i.e., 12,643 kilotons) of CO2eq in 2004, but sharply decreased from 10,284 kilotons of CO2eq in 2005 to 3,906 kilotons of CO2eq in 2020. It was also found that the most commonly used method for controlling the emissions of F-gases from the semiconductor and optoelectronic industries was based on the thermal destruction-local scrubbing technology.

The aim of this study is to investigate the impact of delegated monitoring by the group leader and peer monitoring by group members on loan defaults in a group-based lending program in Vietnam. Data used in the study were collected from a questionnaire survey of 675 participants involved in group-based lending program in the Mekong River Delta, Vietnam. The group-based lending program employs a unique monitoring system that involves hiring the group leader to supervise the group and encouraging group members to monitor each other. The empirical findings derived from the Probit model indicated that delegated monitoring significantly reduces loan defaults, but there was no evidence supporting the effectiveness of peer monitoring within the group. Additionally, under the delegated monitoring scheme, group size plays an important role in decreasing loan defaults.

The paper presents the prediction of hydrodynamic characteristics of different rudder -plane configurations behind a submarine in deep water through the Reynolds-Averaged Navier-Stokes method in Ansys Fluent Solver. The hydrodynamic force and moment acting on the Cross-plane, X-plane, and Y-plane rudder configurations are analyzed for estimating hydrodynamic coefficientsfor predicting the advantages of each configuration to control the ship. The obtained results show that X-force of the X-plane rudder configuration is larger than the force acting on the Cross-plane rudder and Y-plane rudder configurations. However, Y-force, and Z-force of the X-plane rudder configuration are significantly greater than the Y-force of the left configurations. The same tendency can be seen in the moment of the X-plane rudder about the y-axis and z-axis. The roll moment induced by the Y-plane and Cross-plane rudder configurations is significantly larger than the case of the X-plane rudder configuration.

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.

The purpose of this study is to elucidate the factors influencing the voluntary adoption of IFRS by examining, analyzing, and synthesizing findings from empirical studies conducted worldwide. The research scrutinizes 185 relevant studies on the voluntary adoption of IFRS published before August 2023. Our assessment reveals that, in prior research, the factors influencing the voluntary adoption of IFRS are categorized into seven main factors, including corporate operations, capital structure, ownership structure, internationalization, financial performance, corporate governance, and several other factors. These studies employ various methodologies, including data surveys, and cross-sectional data, to estimate the relationships between these factors and the voluntary adoption of IFRS. In addition to providing an evaluation of the research in this field, this study can serve as a framework for future researchers to link and compare the results of different studies. We anticipate that this research will be beneficial for future scholars interested in the factors influencing the voluntary adoption of IFRS. Furthermore, the study proposes essential guidance for future research considerations.

Purpose: We evaluated the outcomes of fluid-gas exchange (FGE) for long-term flap closure of idiopathic macular hole (MH) after the inverted internal limiting (ILM) flap technique. Methods: We included eyes showed flap closure without complete MH closure, connection of the apart macular tissue, 1 month postoperatively after the inverted ILM flap technique. The eyes stayed at flap closure at 2 months postoperatively further underwent in-office FGE with 16% C3F8. Results: Among 10 eyes, 5 eyes (50%) showed flap closure at 2 months postoperatively further underwent FGE for complete MH closure while the remaining 5 eyes (50%) progressed directly at 2 months postoperatively. The improvement in vision of all flap closure from baseline was significant (p=0.015), with the mean baseline vision was 1.19 [Snellen equivalent (SE), 20/307] ± 0.52 logMAR and the mean final vision being 0.63 (SE, 20/85) ± 0.38 logMAR. The group that underwent FGE showed a better final vision of 0.45 (SE, 20/75) ± 0.23 logMAR than the group that didn’t undergo FGE (0.81 [SE, 20/128] ±0.44 logMAR). All eyes achieved complete MH closure, including the eyes that underwent FGE in a mean period of 5.60 months (range 3-10 months) after the inverted ILM flap technique. The eyes that underwent FGE achieved higher rate of foveal restoration [complete external limiting membrane (ELM): 80%; complete ellipsoid zone (EZ): 60%] than those that didn’t receive FGE (complete ELM: 40%; complete EZ: 10%). Conclusions: Eyes that underwent FGE accelerated complete MH closure and showed better final vision and fovea l restoration.

Entrepreneurship has been viewed as an opportunity for economic development and changing economic scenarios in global markets. Women are viewed as a reservoir of entrepreneurial talent, so they can be growth engines in novel markets. Previous studies have considered entrepreneurship as the most effective way towards the economic empowerment of women. Female students engaged in entrepreneurial education have been addressed persistently, while what transforms them in an education process is still unclear. Considering the transforming global economy and its influence on higher education, this study aims to detect female students transforming entrepreneurial competency, mindset, and intention into sustainable entrepreneurship. Using a self-compiled survey, we targeted 752 female students to investigate their entrepreneurial competency, mindset, and intention. SPSS and AMOS were used to transform the data for interpretation. We assumed that the impact of female students’ entrepreneurial competency could be modified by an entrepreneurial mindset and result in entrepreneurial intention. To detect this causal relationship, this study employed reliability, factor, structural equation modeling (SEM), and bootstrap-ping analyses to verify the evidence. The result of the SEM confirms that female students’ entrepreneurial competency will, through their entrepreneurial mindset, impact entrepreneurial intention. With bootstrapping, 5000 samples were collected, and it was demonstrated that the measure constructs were still reliable in the model. This study found that there is a mediation effect between entrepreneurial competency and entrepreneurial intention. The entrepreneurial mindset plays a crucial role in the transformation process. Without an entrepreneurial mindset, entrepreneurial competency cannot exert a significant effect on entrepreneurial intention. The findings can help reinvent related entrepreneurial education in higher education.

In this study, an experiment was conducted on hoop pine (Araucaria cunninghamii), which is a common tree species in Taiwan. Holes with diameters of 4, 5, 7, 10, 12, and 14 cm were drilled in dry hoop pine timber with a diameter of 39 cm and a height of 57 cm, and an 800 MHz Ground Penetrating Radar (GPR) antenna were used to determine the minimum image resolution and the size of the holes in the wood. GPR images of the timber were subjected to a filtering process to obtain characteristic reflection curves of the damage to the timber. Curves with clear waveforms were observed in the GPR profiles of eccentric holes with a diameter of 4 cm. Profiles of the damage were obtained and profile images with the trunk radius at the centre were transformed into polar coordinate images. From these polar coordinate images, the location, size and diameter of the eccentric holes in the wood were identified, and the reflection curves were characterised by waveforms and irregular fluctuations. The risk levels of tree trunks were determined on the basis of their t/R (minimum normal wall thickness of the cross-section of the trunk/radius of the trunk) values and hole area ratios. A comparison between the GPR-based results and the actual diameters of the holes revealed that the filtered GPR profiles could be used for the efficient and accurate assessment of damage to hoop pine timber (average error rate ≤ 4%).

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.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is pandemic. Prevention and control strategies require an improved understanding of SARS-CoV-2 dynamics. We did a rapid review of the literature on SARS-CoV-2 viral dynamics with a focus on infective dose. We sought comparisons of SARS-CoV-2 with other respiratory viruses including SARS-CoV-1 and MERS-CoV. We examined laboratory animal, and human studies. The literature on infective dose, transmission, and routes of exposure was limited specially in humans, and varying endpoints were used for measurement of infection. We propose the minimum infective dose of COVID-19 in humans, is higher than 100 particles, possibly slightly lower than the 700 particles estimated for H1N1 influenza. Despite variability in animal studies, there was some evidence that increased dose at exposure correlated with higher viral load clinically, and severer symptoms. Higher viral load measures did not reflect COVID-19 severity. Aerosol transmission seemed to raise the risk of more severe respiratory complications in animals. An accurate quantitative estimate of the infective dose of SARS-CoV-2 in humans is not currently feasible and needs further research. Further work is also required on the relationship between routes of transmission, infective dose, co-infection, and outcomes.

Ensuring equal access to affordable higher education for women and men has become a crucial target of UNESCO’s SDG4-Education 2030. Currently, about one-third of the world's college-age population participates in higher education, while the gender disparity persists in various systems. This study employed GDP per capita, gross enrollment ratio (GER), and the gender parity index (GPI) to demonstrate how the education systems have expanded resulting in the transformation of gender parity. We selected Japan, Korea, Taiwan, and the UK as research targets using a cross-correlation function and trend analysis to detect concurrent relationships and future trends with GDP per capita, GER, and GPI. The findings suggest Japan, Korea, and the UK continue to show gender disparity and need to respond to this issue in their policy intervention for SDG4-Education 2030. The results reveal a potential problem in the UK when GPI growth might become unlimited with females dominated. This study suggests the higher education expansion phenomenon and gender diversity in mass and universal systems can be detected by the trend analysis with GDP per capita, GER, and GPI in different settings. The design of the study provides an example to explore the gender diversity patterns in higher education systems for sustainable development.

Opioids are highly addictive substances with a relapse rate of over 90%. While preclinical models of chronic opioid exposure exist for studying opioid dependence, none recapitulate the relapses observed in human opioid addiction. The mechanisms associated with opioid dependence, the accompanying withdrawal symptoms and the relapses that are often observed months or years after opioid dependence are poorly understood. Therefore, we developed a novel model of chronic opioid exposure whereby the level of administration is self-directed with periods of behavior acquisition, maintenance and then extinction alternating with reinstatement. This profile arguably mirrors that seen in humans, with initial opioid use followed by alternating periods of abstinence and relapse. Recent evidence suggests that dietary interventions that reduce inflammation, including omega-3 fatty acids such as docosahexaenoic acid (DHA), may reduce substance misuse liability. Using the self-directed intake model, we characterize the observed profile of opioid use and demonstrate that a diet enriched in polyunsaturated fat acids (PUFAs) ameliorates oxycodone-seeking behaviors in the absence of drug availability and reduces anxiety. Guided by the major role gut microbiota have on brain function, neuropathology, and anxiety, we profile the microbiome composition and the effects of chronic opioid exposure and DHA supplementation. We demonstrate that withdrawal of opioids led to a significant depletion in specific microbiota genera whereas DHA supplementation increased microbial richness, phylogenetic diversity, and evenness. Lastly, we examined the activation state of microglia in the striatum and found that DHA supplementation reduced the basal activation state of microglia. These preclinical data suggest that a diet enriched in PUFAs could be used as a treatment to alleviate anxiety induced opioid-seeking behavior and relapse in human opioid addiction.

This paper reviews the requirements for the production, quality, and quality assurance of solid recovered fuels (SRF) that are increasingly used for the substitution of fossil fuels in the indus-trial utilities. The economical, technological and environmental aspects should be considered before using SRF as an alternative fuel. In general, the most important factors determining the commercial production of SRF referred to the calorific values and their available amounts adopted in the starting materials. Furthermore, the low-melting impurities and undesired constituents/elements, including chlorine, sulfur, potassium and sodium, may pose negative impacts on air pollutant emission and slagging & fouling in the process utilities. In this regard, the vent emitted from the industrial utilities must comply with the effluent standards of station-ary sources like particulate, sulfur oxides, nitrogen oxides, heavy metals (e.g., lead, cadmium, and mercury) and dioxins. For these reasons, this work will summarize the legal or regulatory requirements under development in Asian countries (i.e., Japan, South Korea, and Taiwan) and European Union (EU). Finally, the outlook of solid recovered fuel (SRF) in the waste manage-ment and industrial sectors will be addressed to echo the sustainable development goals (SDGs).

Lateral vehicle control is a high importance in automated vehicles as it directly influences the vehicle’s performance and safety during operation. The Linear Quadratic Regulator (LQR) controller stands out due to its high-performance characteristics and is used in the open source for self driving functions. However, a notable limitation of the current approach is the manual calibration of LQR controllers based on the experience and intuition of the designers, leading to empirical uncertainties. To address this issue and enhance the lateral control performance, this paper concentrates on refining the LQR by employing three optimization algorithms: Artificial Bee Colony Optimization (ABC), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO). These algorithms aim to overcome the reliance on empirical methods and enable a data-driven approach to LQR calibration. By comparing the outcomes of these optimization algorithms to the manual LQR controller within an offline multibody simulation as testing platform, the study highlights the superiority of the best-performing optimization approach. Following this, the optimal algorithm is implemented on a real-time system for the full vehicle level, revealing the Model-in-the-Loop and the Hardware-in-the-Loop gap up to 78,89% with lateral velocity when we use Relative Error Criterion (REC) method to validate and 2.35m with lateral displacement when considering by maximum absolute value method.

Power quality is a major concern in electrical power systems. The power quality disturbances such as sags, swells, harmonic distortion and other interruptions have impact on the electrical devices and machines and in severe cases can cause serious damages. Therefore it is required to recognize and compensate all types of disturbances at an earliest to ensure normal and efficient operation of the power system. To solve these problems, many types of power devices are used. At the present time, one of those devices, Dynamic Voltage Restorer (DVR) is the most efficient and effective device used in power distribution system. In this paper, design and modeling of a new structure of multifunctional DVR for voltage correction is presented. The performance of the device under different conditions such as voltage swell, voltage sag due to symmetrical and unsymmetrical short circuit, starting of motors, and voltage distortion are described. Simulation result shows the superior capability of proposed DVR to improve power quality under different operating conditions. The proposed new DVR controller is able to detect the voltage disturbances and control the converter to inject appropriate voltages independently for each phase and compensate to load voltage through three single- phase transformers.

Here, we present a staged approach for an innovative repurposing of a portable infant humidicrib into a live cell growth, observation, and imaging system. Furthmore, humidicrib can support different variations of “umbilical” bioreactors, and can be used to conduct electrophysiology experiments and in situ immunohistochemistry. Modifications incorporate a closed loop carbon dioxide (CO₂) concentration control system with umbilical CO₂ and heating support for tailored bioreactors. The repurposing cost is inexpensive and allows for the continued observation and imaging of cells. This prototype unit has been used to continuously observe and image live primary neurons for up to 21 days. This demonstrates the repurposed units’ suitability for use in tissue culture based research, particularly where modifications to microscopes are required or where sensitive manipulation outside of a standard incubator is needed.

This study developed a three-dimensional kinematic and dynamic model of a center-driven linkage system (CDLS). Force analysis was conducted to determine the required driving torque to ensure that the input link of the CDLS rotates at a constant speed with a certain angular velocity, even in the presence of frictional resistance torque. The primary objective was to optimize the maximum angular acceleration of the output links to reduce wiper noise. This optimization can enhance the stability of the linkage system while maintaining its operational functionality. In the adopted methodology, the frames of the fixed links are assumed to remain unchanged, and the input link is considered to operate at a constant angular speed and have a constant length. To meet standard vehicle windshield wiper requirements, 10 constraints were imposed on the optimization problem, which was solved using the differential evolution method. The lengths of both output links were reduced by over 10% after optimization.

This article aims to identify the current development of cross-border tourism between Vietnam and China. The paper analyzes the perception and strategy of cross-border tourism development in the two countries, especially in the context of China’s implementation of the “Belt and Road Initiative” (BRI). The article emphasizes that Vietnam and China have recently made efforts to promote cross-border tourism development. At the same time, Vietnam and China see cross-border tourism development as a significant part of comprehensive border cooperation between the two countries. However, the development plans for cross-border tourism between the two countries are still mainly on the desk, not yet implemented effectively. Thus, its achievements are relatively modest. Besides, the article emphasizes that the interests of the people living in the border area, especially the Vietnam side, are almost “forgotten” in the development of cross-border travel between the two countries. Besides, the article also analyzes the challenges that the two sides are facing, especially the Vietnam side, in promoting the development of cross-border tourism between the two countries.

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.

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.

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.

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.

Ce³⁺ and Dy³⁺ ions doped Ca₂Al₂SiO₇ (CAS) phosphors were prepared by the solid-state reaction at 12800C for 1h. X-ray diffraction patterns confirmed a tetragonal crystalline structure. The luminescent spectra of CAS: Ce³⁺, Dy³⁺ phosphors consist a board band with peaking at 420 nm corresponding to the luminescence of Ce³⁺ ions and narrow lines of Dy³⁺ ions. The energy transfer from Ce³⁺ ion to Dy³⁺ ion is presented and discussed

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.

(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.

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.

Background: Few studies have investigated the longitudinal association between cervical spondylosis (CS) and migraine by using a nationwide population-based database. Methods: We conducted a retrospective cohort study from 2000 to 2011 identifying 27,930 cases of cervical spondylosis and 111,720 control subjects (those without cervical spondylosis) from a single database. The subjects were frequency-matched on the basis of sex, age, and diagnosis date. The non- cervical spondylosis cohort was four times the size of the cervical spondylosis cohort. To quantify the effects of cervical spondylosis on the risk of migraine, univariate and multivariate Cox proportional hazard regression analyses were used to calculate the hazard ratio (HR) and 95% confidence interval (CI). Results: After a 10-year follow-up controlling for potential confounding factors, overall migraine incidence was higher in the cervical spondylosis cohort than in the non- cervical spondylosis cohort (5.16 and 2.09 per 1,000 people per year, respectively; crude hazard ratio = 2.48, 95% confidence interval = 2.28–2.69) with an adjusted hazard ratio of 2.03 (95% confidence interval = 1.86–2.22) after accounting for sex, age, comorbidities, and medication. Individuals with myelopathy in the cervical spondylosis cohort had a 2.19 times (95% confidence interval = 1.80–2.66) higher incidence of migraine compared than did those in the non- cervical spondylosis cohort. Conclusion: Individuals with cervical spondylosis exhibited a higher risk of migraine than those without cervical spondylosis. The migraine incidence rate was even higher among individuals with cervical spondylotic myelopathy.

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.

With the continuous increase in ship size combined with the generally slower increase in the size of waterways, the need for the prediction of ship maneuvering in shallow waterways continues to attract attention from the international scientific community. Ship behavior in shallow water is relevant in seabed effects that result in changing the hydrodynamic forces acting on the ship. In this study, the maneuvering characteristics of container ship with four degrees of freedom in shallow water are analyzed. The Reynolds-averaged Navier Stokes approach in Ansys Fluent code is used to produce the maneuvering coefficients through the simulations of forward running, static drift, static heel, circular motion, the combined motions, and the pure roll motion of the Kriso container ship. The maneuvering characteristics of the ship are estimated for evaluating the ship behaviors in shallow water condition. The obtained results show that the roll has a significant decrease and the ship’s turning diameter has a significant increase when the ship operates in the shallow waterway. The prediction of maneuvering characteristics of the ship are in good agreement with those of free running model tests, indicating that the numerical simulation based on the Computational Fluid Dynamics method has compromising capability to predict the maneuvering derivatives and the 4-DOF ship maneuvering motion in shallow water as well.

Background: During pregnancy, major physiological changes occur in every system. Understanding the hemodynamic changes in different stages of pregnancy can help to identify abnormal states during pregnancy. Harmonic analysis could be a useful tool in monitoring the state of the ventricular-arterial system during pregnancy. The aim of this study was to investigate the specific statistical relationships between changes in harmonic indices during different stages of pregnancy. Methods: A Total of 380 women (190 pregnant women and 190 age-matched non-pregnant women), with ages ranging from 20 to 45, were enrolled in the study. The visit measured the subject’s hemodynamic parameters including heart rate, systolic blood pressure (SBP), diastolic blood pressure (DBP) and photoplethysmography (PPG). SBP and DBP were evaluated by an automatic blood pressure monitor. PPG signal were continuously recorded for 12-seconds using a PPG sensor. Spectrum analysis of the PPG signal was performed to evaluate the first five harmonic components (C1 – C5) and harmonic phases (P1 – P5). Result: A comparison between pregnant women and non-pregnant women showed that the non-pregnant women had lower DBP, C3, C5 and P5 (p<0.05). Waist Circumference, Heart rate, C2, C4 and P2 were higher in pregnant women. Logistic regression analysis was used to determine the associations between pregnancy and harmonics indices. C2, C4 and P3 were positively and P1 and P4 were negatively associated with pregnancy after controlling age, BMI, waist circumference, heart rate, SBP and DBP. Conclusion: The results of this study provide information on the changes in the harmonic frequency components during various stages of pregnancy. The harmonic components of the PPG signal have independent predictive value for changes in a woman's physiology during pregnancy. Since non-invasive PPG measurements can be performed frequently and easily, in the future, it is possible that the hemodynamic changes from some pregnancy-related disorders could be studied by harmonic analysis.

In this study, we conducted experiments to assess the forecasting capabilities for the tropical cyclone (TC) genesis over the South China Sea using the ensemble-based data assimilation system (EPS-DA) by WRF-LETKF. These experiments covered forecast lead times of up to 5 days and spanned a period from 2012 to 2019, involving a total of 45 TC formation events. The evaluation involved forecast probability assessments and positional and timing error analysis. Results indicated that successful forecasting depends on lead time and initial condition quality. For TC formation from an embryo vortex to tropical depression intensity, the EPS-DA system demonstrated improved accuracy as the forecast cycle approached the actual formation time. TC centers converged toward observed locations, highlighting the potential of assimilation up to 5 days before formation. We examined statistical variations in dynamic and thermodynamic variables relevant to TC processes, offering an objective system assessment. Our study emphasized early warnings of TC development appear linked to formation-time environmental conditions, particularly strong vorticity and enhanced moisture processes.

The undoped and tungsten (W)-doped vanadium dioxide (VO₂) thin films were prepared by electron beam evaporation associated with ion-beam assisted deposition (IAD). The influence of different W-doped contents (3%-5%) on the optical, electrical, structural, and thermos-mechanical properties of VO₂ thin films was investigated experimentally. Spectral transmittance results showed that with the increase of W-doped contents, the transmittance in the visible light range (400-750 nm) decreases from 60.2% to 53.9%, and the transmittance in the infrared wavelength range (2.5 μm to 5.5 μm) drops from 55.8% to 15.4%. As the W-doped content increases, the residual stress in the VO₂ thin film decreases from -0.276 GPa to -0.238 GPa, but the surface roughness increases. For temperature-dependent spectroscopic measurements, heating the VO2 thin films from 30°C to 100°C showed the most significant change in transmittance for the 5% W-doped VO₂ thin film. When the heating temperature exceeds 55°C, the optical transmittance drops significantly, and the visible light transmittance drops by about 11%. Finally, X-ray Diffraction (XRD) and scanning electron microscope (SEM) were used to evaluate the microstructure characteristics of VO₂ thin films.

This work emphasizes to use silver decorative method to enhance the antibacterial activity of TiO₂ and ZnO nanoparticles. These silver decorated nanoparticles (hybrid nanoparticles) were synthesized by using sodium borohydride as a reducing agent, with the weight ratio of Ag precursors: oxide nanoparticles = 1: 30. The morphology and optical property of these hybrid nanoparticles were investigated using transmission electron microscopy (TEM) and UV–vis spectroscopy. The agar-well diffusion method was used to evaluate their antibacterial activity against both Staphylococcus aureus and Escherichia coli bacteria, with or without light irradiation. The TEM images indicated clearly that silver nanoparticles (AgNPs, 5-10 nm) were well deposited on the surface of nano-TiO₂ particles (30-60 nm). Besides, smaller AgNPs (< 2 nm) were dispersed on the surface of nano-ZnO particles (20-50 nm). UV-vis spectra confirmed that the hybridization of Ag and oxide nanoparticles led to shift the absorption edge of oxide nanoparticles to the lower energy region (visible region). The antibacterial tests indicated that both oxide pure nanoparticles did not exhibit inhibitory against bacteria, with or without light irradiation. However, the presence of AgNPs in their hybrids, even at low content (< 40 mg/mL) leads to a good antibacterial activity and the higher inhibition zones under light irradiation as compared to that in dark was observed.

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.

Osteoarthritis (OA) is the degeneration of cartilage in joints that results in bones rubbing against each other, it causes uncomfortable symptoms such as pain, swelling, stiffness, and can lead to disability. It usually occurs in the elderly and causes a large medical burden. The aim of this study is to evaluate cost-effectiveness between the standard treatment for osteoarthritis and the standard treatment with added crystalline glucosamine sulfate at various stages. The Markov analysis modelling was applied to evaluate the effect of both adding glucosamine compared to standard treatment from a societal perspective during whole patients’ lifetimes. Data input was collected by review in previous studies. The outcome was measured in quality-adjusted life years (QALYs), and the incremental cost-effectiveness ratio (ICER) from a societal perspective was ap-plied with 3%-discounted for all cost and outcome. One-way analysis via Tornado diagram was performed to investigate the change of factors in model. In general, the adding glucosamine into the standard treatment proved to be more cost-effectiveness compared to the standard treatment. Particularly, early stage adding glucosamine in the treatment was cost-effectiveness then post-stage adding glucosamine. The addition of supplementing crystalline glucosamine sulfate to whole regimen at any stage was cost-effectiveness at willingness-to-pay (WTP) threshold

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.

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

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.

Recent preclinical studies have shown the potential benefits of short-term calorie reduction (SCR) on cancer treatment. In this integrative review, we aimed to identify and synthesize current evidence regarding the feasibility, process, and effects of SCR in cancer patients receiving chemotherapy. PubMed, Cumulative Index to Nursing and Allied Health Literature, Ovid Medline, PsychINFO, and Embase were searched for original research articles using various combinations of Medical Subject Heading terms. Among the 311 articles identified, seven studies met the inclusion criteria. The majority of the reviewed studies was small randomized controlled trials or cohort study with fair quality. The results suggest that SCR is safe and feasible. SCR is typically arranged around the chemotherapy with the duration ranging from 24 to 96 hours. Most studies examined the protective effects of SCR on normal cells during chemotherapy. The evidence supports that SCR had the potential to enhance both physical and psychological wellbeing of patients during chemotherapy. SCR is a cost-effective intervention with great potential. Future well-controlled studies with sufficient sample sizes are needed to examine the full and long-term effects of SCR and its mechanism of action.

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.

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 proposes a novel hybrid machine learning approach for modeling of rainfall-induced shallow landslides. The proposed approach is a combination of an instance-based learning algorithm (k-NN) and Rotation Forest (RF), state of the art machine techniques that have seldom explored for landslide modeling. The Lang Son city area (Vietnam) is selected as a case study. For this purpose, a spatial database for the study area was constructed, and then, was used to build and evaluate the hybrid model. Performance of the model was assessed using Receiver Operating Characteristic (ROC), area under the ROC curve (AUC), success rate and prediction rate, and several statistical evaluation metrics. The results showed that the model has high performance with both the training data (AUC = 0.948) and the validation data (AUC = 0.848). The results were compared with those obtained from soft computing techniques i.e. Random Forest, J48 Decision Trees, and Multilayer Perceptron Neural Networks. Overall, the performance of the proposed model is better than those obtained from the above methods. Therefore, the proposed model is a promising tool for landslide modeling. The research result can be highly useful for land use planning and management in landslide prone areas.

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.

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.

2-Methylquinazolin-4(3H)-one was prepared by reaction of anthranilic acid, acetic anhydride and ammonium acetate. The reaction of 2-methylquinazolin-4(3H)-one with N-aryl-2-chloroacetamides in acetone in the presence of potassium carbonate gave nine N-aryl-2-(2-methyl-4-oxoquinazolin-3(4H)-yl)acetamide compounds. The structures of these compounds were elucidated on the basis of their IR, 1H-NMR, 13C-NMR and HR-MS spectral data. These synthesized compounds containing the 2-methyl-3,4-dihydroquinazolin-4-one moiety exhibited excellent activity against Aedes aegypti mosquito larvae with LC50 values in the range of 2.085-4.201 μg/mL after 72 h exposure. Interestingly, these compounds did not exhibit toxicity to the non-target organism Diplonychus rusticus. In silico molecular docking revealed acetylcholine binding protein (AChBP) and acetylcholinesterase (AChE) to be potential molecular targets. These data indicated the larvicidal potential and environmental friendliness of these N-aryl-2-(2-methyl-4-oxoquinazolin-3(4H)-yl)acetamide derivatives.

The increasing prevalence of obesity and sedentary lifestyles has led to an increased incidence of metabolic syndrome (MetS) worldwide. In Taiwan, middle-aged women are at a greater risk of MetS, type 2 diabetes, and cardiovascular disease than men are because they have more subcutaneous fat and larger waist circumferences compared to men with equal visceral fat levels. This study investigated the effects of calorie restriction supplemented with fish oil (CRF) in middle-aged women with MetS. For 12 weeks, 75 eligible participants were randomly assigned either calorie restriction (CR) or CRF. Both dietary intervention groups were further divided into two age groups: ≤45 and >45 years. The changes in MetS severity, inflammatory status, iron status, and red blood cell fatty acid profile were evaluated. Seventy-one participants completed the trial. Both dietary interventions significantly ameliorated MetS and improved the participants’ inflammatory status. CR significantly increased total iron binding capacity, whereas CRF increased hepcidin levels. Furthermore, CRF significantly increased the n-6/n-3 and arachidonic acid/docosahexaenoic acid ratios. In conclusion, CR and CRF improved the anthropometric and MetS characteristics of early-middle aged women, including body weight, blood glucose levels, triglyceride levels, as well as the scores for the homeostasis model assessment of insulin resistance and quantitative insulin sensitivity cheque index. Dietary intervention was more effective in >45-year-old women than ≤45-year-old women.

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.

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.

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 effects of anisotropic properties (wettability and roughness) on microgroove surfaces in pool boiling heat transfer using Novec-7100 as a working fluid were experimentally investigated. The idea of introducing the concept of anisotropic wettability in boiling experiments draws inspiration from biphilic surfaces. The investigation is also motivated by two-phase immersion cooling, which involves phase-change heat transfer by using dielectric liquid as a working fluid. Very few studies have focused on the effects of surfaces with anisotropic properties on boiling performance. Thus, this study aims to examine the pool boiling heat transfer performance on surfaces with microgroove-induced anisotropic properties under the saturation condition. A femtosecond laser–texturing method was employed to create microgroove surfaces with different groove spacing. The results indicated that anisotropic properties affected the heat transfer coefficient and critical heat flux. Relative to the plain surface, microgroove surfaces enhanced the heat transfer performance due to the increased number of bubble nucleation sites and higher bubble detachment frequency. An analysis of bubble dynamics under different surface conditions was conducted with the assistance of high-speed images. The microgroove surface with groove spacing of 100 μm maximally increased the BHTC by 37% compared to the plain surface. Finally, the CHF results derived from experiments were compared with related empirical correlations. Good agreement was achieved between the results and the prediction correlation.

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.

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.

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.

: 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.

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.

This study proposed a regression model for predicting fatigue properties based on crucial weld geometry factors in lap-welded joints with gaps using statistical analysis. Welding conditions were varied to build various weld geometries in joints configured in a lap from with gaps of 0, 0.2, 0.5, and 1.0 mm, and 87 S-N curves for the lap-welded joints were derived. As input variables, 17 weld geometry factors (7 lengths, 7 angles, and 3 area factors) were selected. The slope of the S-N curve using Basquin model from the S-N curve and the safe fatigue strength were selected as output variables for prediction to develop the regression model. Multiple linear regression models, multiple non-linear regression models, and second-order polynomial regression models were proposed to predict fatigue properties. Backward elimination was applied to simplify the models and reduce overfitting. Among the three proposed regression models, the multiple non-linear regression model had a coefficient of determination greater than 0.86. In lap-welded joints with gaps, the weld geometry factors representing fatigue properties were identified through standardized regression coefficients, and four weld geometry factors related to stress concentration were proposed.

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.

Emerging evidence demonstrated that using a new manufacturing technology to produce γ-aminobutyric acid (GABA)-fortified oolong (GO) tea could relieve human stress and exert versatile physiological benefits. The purpose of this human research aims to investigate therapeutic effects of daily GO tea consumption on the improvement of blood pressure, relaxation-related brain waves and quality of life (QOL) during a period of 28 consecutive days. Total polyphenols, major catechins and free amino acids were analyzed via HPLC assay. Changes of heart rate, blood pressure, α-brain wave (index of relaxation) and eight-item QOL score were investigated on day 0, 7, 14, 21 and 28, respectively. The chemical analysis results showed that GO tea contained the most abundant amino acids and GABA, contributing to the relaxation activity. Among all study participants, daily drinking GO tea could reduce systolic blood pressure on day 21 and diastolic blood pressure on day 28 (p &lt; 0.05, respectively). For participants with pre-hypertension, GO tea could effectively reduce heart rate, systolic and diastolic blood pressure on day 28 (p &lt; 0.05). At the end of the study, incremental changes in alpha-brain wave and QOL scores were also demonstrated (p &lt; 0.05, respectively). This study recommended that GO tea might potentially serve as a natural source of alternative therapy to benefit blood pressure, stress-relief and QOL.

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.

Novel multifunctional fluorescent chemosensors composed of electrospun (ES) nanofibers with high sensitivity toward pH, mercury ions (Hg²⁺), and temperature were prepared from poly(N-Isopropylacrylamide-co-N-methylolacrylamide-co-rhodamine derivative) (poly(NIPAAm-co-NMA-co-RhBN2AM)) by employing electrospinning process. NIPAAm and NMA moieties provide hydrophilic and thermo-responsive properties (absorption of Hg²⁺ in aqueous solutions), and chemical cross-linking sites (stabilization of the fibrous structure in aqueous solutions), respectively. The fluorescent probe, RhBN2AM is highly sensitive toward pH and Hg²⁺. Synthesis of poly(NIPAAm-co-NMA-co-RhBN2AM) with different compositions were carried on via free-radical polymerization. ES nanofibers prepared from sensory copolymers with a 71.1:28.4:0.5 NIPAAm: NMA: RhBN2AM ratio (P3 ES nanofibers) exhibited significant color change from nonfluorescent to red fluorescence while sensing pH or Hg²⁺, and high reversibility of on/off switchable fluorescence emission when Hg²⁺ and ethylenediaminetetraacetic acid (EDTA) were sequentially added. The P3 ES nanofibrous membranes had a higher surface-to-volume ratio to enhance their performance than did the corresponding thin films. In addition, the fluorescence emission of P3 ES nanofibrous membranes exhibited second enhancement above the lower critical solution temperature. Thus, the ES nanofibrous membranes prepared from P3 with on/off switchable capacity and thermo-responsive characteristics can be used as multifunctional sensory devise for specific heavy transition metal (HTM) in aqueous solutions.

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.

In industry 4.0 era, video applications such as surveillance visual systems, video conferencing, or video broadcasting have been playing a vital role. In these applications, for manipulating and tracking objects in decoded video, the quality of decoded video should be consistent because it largely affects to the performance of the machine analysis. To cope with this problem, we propose a novel perceptual video coding (PVC) solution in which a full reference quality metric named Video Multimethod Assessment Fusion (VMAF) is employed together with a deep convolutional neural network (CNN) to obtain the consistent quality while still achieving the high compression performance. First of all, to achieve the consistent quality requirement, we propose a CNN model with an expected VMAF as input to adaptively adjust the quantization parameters (QP) for each coding block. Afterwards, to increase the compression performance, a Lagrange coefficient of Rate-Distortion optimization (RDO) mechanism is adaptively computed under Rate-QP and Quality-QP models. Experimental results show that the proposed PVC has achieved two targets simultaneously: the quality of video sequence is kept consistently with an expected quality level and the bit rate saving of the proposed method is higher than traditional video coding standards and relevant benchmark, notably with around 10% bitrate saving in average.

In an age of market liberalization, globalization, and expanding agribusiness, there is a danger that small-scale farmers will find difficulty in fully participating in the market economy. One of the solutions to solve the above situation is to strengthen linkages between farmers and firms through contract farming. The purpose of this study is to assess the factors affecting the level of linkages between businesses and farmers in crop development in Thai Binh province, Vietnam. The two main research methods used were exploratory factor analysis (EFA) and regression analysis with survey data which was conducted from 300 farmers, 10 firms, and 15 factors related to contract-farming. The results indicated that there are 5 factors that significantly affect the level of participation of farmers in the linking process, the order of impacts from strong to weak is as follows: (1) Commitment and sharing of benefits and risks between farmers and firms in the linking process, (2) Issues related to management skills and enterprises capacity of link firms, (3) Price issues that farmers are interested in in the process of implementing links with firms, (4) Policy environment - Institutions related to farmer contracts between firms and farmers, (5) Household awareness about the benefits brought about by farmer contracts with firms. Based on results, a number of specific solutions have been proposed to enhance the efficiency of farming contracts between firms and farmers in cultivation production.

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.

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.

Probiotics, known for regulating gut microbiota, may aid those with overweight or obesity, but their mechanisms require more research. This study involved 75 overweight or obese young adults, randomly assigned to either a Bifidobacterium brevis BBr60 group or a placebo group. Both groups received diet guidance and took either BBr60 (1×1010 CFU/day) or a placebo for 12 weeks. Re-searchers analyzed body composition, serum glucose, lipids, liver and kidney function, comprehensive metabolome, and intestinal homeostasis before and after the intervention. After 12 weeks, BBr60 significantly reduced weight and BMI compared to pre-treatment levels and outperformed the placebo. The BBr60 group also showed improved blood biochemistry, with notably lower fasting blood glucose (FBG) levels than the placebo group (p < 0.05). Additionally, BBr60 influenced vital serum and fecal metabolites related to three amino acid metabolic pathways and regulated the bacteria Dialister, Klebsiella, and Bacteroides, which correlated strongly with serum metabolites. These findings indicate that BBr60 can safely and effectively regulating BMI, body weight, serum glucose, lipids, and liver function markers, which may involve BBr60's impact on key gut bacteria, which influence metabolites related to the valine, leucine, and isoleucine biosynthesis; glycine, serine, and threonine metabolism; and alanine, aspartate, and glutamate metabolism.

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.

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.

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.

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.

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.

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.

Cell division control 37 (CDC37) increases the stability of HSP90 client proteins and is thus essential for numerous intracellular oncogenic signaling pathways, playing a key role in prostate oncogenesis. Notably, elevated expression of CDC37 was found in prostate cancer cells, although the regulatory mechanisms through which CDC37 expression becomes increased are unknown. Here we show both positive and negative regulation of CDC37 gene transcription by two members of the SCAN transcription factor family- MZF1 and SCAND1, respectively. Consensus DNA-binding motifs for myeloid zinc finger 1 (MZF1 / ZSCAN6) were abundant in the CDC37 promoter region. MZF1 became bound to these regulatory sites and trans-activated the CDC37 gene whereas MZF1 depletion decreased CDC37 transcription and reduced tumorigenesis of prostate cancer cells. On the other hand, SCAND1, a zinc-fingerless SCAN box protein that potentially inhibits MZF1, accumulated at MZF1-binding sites in CDC37 gene, negatively regulated CDC37 gene and inhibited tumorigenesis. SCAND1 was abundantly expressed in normal prostate cells but was reduced in prostate cancer cells, suggesting a potential tumor suppressor role of SCAND1 in prostate cancer. These findings indicate that CDC37, a crucial protein in prostate cancer progression, is regulated reciprocally by MZF1 and SCAND1.

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.

Recently, there has been considerable research on deepfake detection. However, most existing methods face challenges in adapting to the advancements in new generative models within unknown domains. In addition, the emergence of new generative models capable of producing and editing high-quality images, such as Diffusion, Consistency, and LCM, poses a challenge for traditional deepfake training models. These advancements highlight the need for adapting and evolving existing deepfake detection techniques to effectively counter the threats posed by sophisticated image manipulation technologies. In this paper, our objective is to detect deepfake videos in unknown domains using unlabeled data. Specifically, our proposed approach employs Meta Pseudo Labels (MPL) with Supervised Contrastive Learning, so-called SupCon-MPL, allowing the model to be trained on unlabeled images. MPL involves the simultaneous training of both a Teacher model and a Student model, where the Teacher model generates Pseudo Labels utilized to train the Student model. This method aims to enhance the adaptability and robustness of deepfake detection systems against emerging unknown domains. Supervised Contrastive Learning utilizes labels to compare samples within similar classes more intensively, while encouraging greater distinction from samples in dissimilar classes. This facilitates the learning of features in a diverse set of deepfake images by the model, consequently contributing to the performance of deepfake detection in unknown domains. When utilizing the ResNet50 model as the backbone, SupCon-MPL exhibited an improvement of 1.58% in accuracy compared to traditional MPL in known domain detection. Moreover, in the same generation of unknown domain detection, there was a 1.32% accuracy enhancement, while in the detection of post-generation unknown domains, there was an 8.74% increase in accuracy.

Tumor cells exhibit a resistance-associated secretory phenotype involving extracellular vesicles (EVs) and heat shock proteins (HSPs). This response occurs in response to cell stress and cancer therapeutics. HSPs are stress-responsive molecular chaperones promoting proper protein folding, while also being released from cells with EVs as well as in free form as alarmins. We have here investigated the secretory phenotype of castration-resistant prostate cancer (CRPC) cells using proteome analysis. We have also examined the roles of the key co-chaperone CDC37 in stressome release, epithelial-to-mesenchymal transition (EMT), and tumor progression. A number of HSP family members and their common receptor CD91/LRP1 were enriched at high levels in CRPC cell-derived EVs among over 700 other protein species. The small EVs (30 to 200 nm in size, potentially exosomes) were released even in a non-heated condition from the prostate cancer cells, whereas EMT-coupled release of EVs (200 to 500 nm, likely ectosomes) with associated HSP90α was increased after heat shock stress (HSS). Lactate dehydrogenase, a marker of membrane leakage/damage of cells, was also released upon HSS from the prostate cancer cells. During this stress response, intracellular CDC37 was also transcriptionally inducible by heat shock factor 1, and knockdown of CDC37 decreased EMT-coupled release of EVs. Triple knockdown of CDC37, HSP90α, and HSP90β was required for efficient reduction of the chaperone trio and to reduce tumorigenicity of the CRPC cells in vivo. Taken together, the data indicated that CDC37 and HSP90 are essential for stressome release and for tumorigenesis in resistant cancer.

This study aimed to investigate the effects of jet-milling on lutein extraction contents of spinach powder (SP) and pulsed electric fields as a non-thermal pasteurization technology on spinach juice (SJ) to preserve lutein contents. SP particles were divided into SP-coarse (Dv50 = 315.2 μm), SP-fine (Dv50 = 125.20 μm), and SP-superfine (Dv50 = 5.59 μm) fractions and SP-superfine was added to SJ due to the highest contents of lutein extract. The PEF and thermal treatment were applied to evaluate the effects of preserving the lutein content of PEF during storage (25 days). The juice after being designated to untreated (no pasteurization), PEF1,2 (SJ treated with PEF 20 kV/cm 110 kJ/L, 150 kJ/L), Thermal1,2 (SJ treated with 90 ℃, 10 min and 121 ℃, 15 min). The sizes and surface shapes of superfine SP particles were more homogeneous and smoother than the other samples. SJ made with SP-superfine and treated by PEF had the highest lutein content and antioxidant activities among the group. Complex of jet-milling and PEF pasteurization could be great potential technologies to improve the lutein contents of lutein-enriched juice in the food industry.

Background: The seasonal variation of peptic ulcers is a rhythmic phenomenon reported worldwide, exhibiting diverse patterns and controversies. Unfortunately, it has remained an unresolved mystery for more than 90 years. Numerous studies have found that this phenomenon was closely associated with multiple environmental factors, but the underlying mechanism has never been elucidated. Objectives: This study aims to elucidate the seasonal variation of peptic ulcers and identify the role of environmental factors in the disease. Methods: Based on a recently identified etiology of peptic ulcers, two inverse operations in calculus, differentiation and integration, are iterated to analyze the existing data. First, the fluctuation curve in the seasonal variation is differentiated twice into the monthly incidences caused by multiple individual environmental factors, and the fluctuation curve due to each individual environmental factor is generated separately. Second, the monthly incidences caused by the individual environmental factors are integrated twice to reproduce the fluctuation curves in the seasonal variation of peptic ulcers. Results: The differentiations of the fluctuation curves in the season variation reveal a parallel relationship between the psychological impacts of each individual environmental factor and the monthly incidences of peptic ulcers. The integrations of the monthly incidences caused by 3 environmental factors reproduce the fluctuation curves in 3 representative seasonal patterns of peptic ulcers but make the parallel relationships invisible. Discussion: The parallel relationships revealed a causal role of environmental factors in peptic ulcers, whereas the reproduction of the fluctuation curves elucidated that multiple environmental factors cause the seasonal variation of peptic ulcers by Superposition Mechanism. The regional differences in environmental factors result in the diverse patterns, as well as the controversy questioning the seasonality of peptic ulcers. Significantly, the data analyses exemplify the application of a new concept, Superposition Mechanism, which might be an indispensable methodological complement to life science and medicine.

Background: In 1962, Susser and Stein observed that the mortality rates of peptic ulcers in England and Wales increased markedly in the 1910s, maintained at a high level during the 1910s-1940s, and began to decline steadily since the early 1950s. They termed this epidemic pattern a birth-cohort phenomenon, but its mechanism has never been elucidated. Susser and Stein speculated that the occurrences of extraordinary social environmental factors roughly fit the fluctuations, but the role of environmental factors in peptic ulcers has never been identified. Objectives: This study aims to elucidate the mechanism of the birth-cohort phenomenon of peptic ulcers and identify the role of environmental factors in the disease. Methods: Starting from an etiology identified recently, this study uses the two inverse operations in calculus, differentiation, and integration, to analyze the existing data. First, a fluctuation curve in the birth-cohort phenomenon is differentiated into multiple annual mortality rates caused by individual environmental factors. Second, these annual mortality rates are integrated to reproduce the fluctuation curve in the birth-cohort phenomenon. Results: The differentiation reveals a parallel relationship between the psychological impacts of environmental factors and the mortality rates of peptic ulcers, whereas the integration reproduces a representative fluctuation curve in the birth-cohort phenomenon. The successive occurrences of multiple social environmental factors from the 1910s to 1940s maintained the increase in mortality rates, while the sustained improvements in living environments explained the steady decline of the mortality rates from the early 1950s. Conclusion: The parallel relationship suggests a causal role of environmental factors in peptic ulcers, whereas the reproduction of a representative fluctuation curve indicates that multiple environmental factors caused the birth-cohort phenomenon by Superposition Mechanism. Significantly, this study challenges the current reductionist approach used to study disease in modern medicine by demonstrating the effectiveness of an opposite methodological concept focused on integration.

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.

Recently, methods to detect DoS and spoofing attacks that occur on in-vehicle networks using CAN Protocol are being studied through deep learning models such as CNN, RNN, and LSTM. These studies have produced significant results in the field of In-Vehicle Network attack detection using deep learning models. In addition, significant results are being achieved through research on applying time series-based deep learning models such as LSTM to detect DoS attacks and replay attacks occurring in in-drone networks by expanding them to drones using the UAVCAN protocol. In this paper, we conducted an experiment to detect in-drone network attacks through non-time series analysis using machine learning models and deep learning models, and through appropriate learning for each attack type, it can also be analyzed through non-time series analysis. The results showed that it was possible to detect attacks.

Let BT4l denotes a subclass of bounded turning functions connected with a four-leaf-type domain. The goal of the study is to probe into coefficients of |b6|, |b7|, |b8|, the bounds of the logarithmic coefficients and the third-order determinants of H3,1, H3,2, H3,3 for functions in this class.

Aquaporins (AQPs) are a family of integral membrane proteins that selectively transport water and glycerol across the cell membrane. Because AQPs are involved in a wide range of physiological functions and pathophysiological conditions, AQP-based therapeutics may have broad potential for clinical utility, including disorders of water and energy balance. However, AQP modulators have not yet been developed as suitable candidates for clinical applications. In this study, to identify potential modulators of AQPs, we screened 32 natural products by measuring the water and glycerol permeability of mouse erythrocyte membranes using a stopped-flow light scattering method. None of the tested natural compounds substantially affected osmotic water permeability. However, several compounds considerably affected glycerol permeability. Stichoposide C increased the glycerol permeability of mouse erythrocyte membranes, whereas rhizochalin decreased it at nanomolar concentrations. Immunohistochemistry revealed that AQP7 was the main aquaglyceroporin in mouse erythrocyte membranes. We further verified the effects of stichoposide C and rhizochalin on aquaglyceroporins using human AQP3 expressing keratinocyte cells. Stichoposide C, but not stichoposide D, increased AQP3-mediated transepithelial glycerol transport, whereas the peracetyl aglycon of rhizochalin was the most potent inhibitor of glycerol transport among the tested rhizochalin derivatives. Collectively, stichoposide C and the peracetyl aglycon of rhizochalin might function as modulators of AQP3 and AQP7, and suggest the possibility of these natural products as potential drug candidates for aquaglyceroporin modulators

G protein-coupled receptor 15 (GPR15, also known as BOB) is an extensively studied orphan GPCR involving HIV infection, colonic inflammation and smoking-related diseases. Recently, GPR15 was deorphanized and its corresponding natural ligand demonstrated an ability of inhibiting cancer cell growth. However, no study reported the potential role of GPR15 in a pan-cancer manner. Using large-scale publicly available data from the Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) databases, we found that GPR15 expression is significantly lower in colon adenocarcinoma (COAD) than in normal tissues. And among 33 cancer types, GPR15 expression is significantly correlated with the prognoses of COAD, neck squamous carcinoma (HNSC), lung adenocarcinoma (LUAD) positively and stomach adenocarcinoma (STAD) negatively. This study also revealed that commonly upregulated gene set in the high GPR15 expression group (stratified via median) of COAD, HNSC, LUAD and STAD are enriched in immune systems, indicating that GPR15 might be considered as a potential target for cancer immunotherapy. Furthermore, we modelled the 3D structure of GPR15 and conducted the structure-based virtual screening. The top 8 hits compounds were screened and then subjected to molecular dynamics (MD) simulation for stability analysis. Our study provided novel insights into the role of GPR15 in a pan-cancer manner and discovered a potential hit compound for GPR15 antagonists.

The construction of reinforced concrete (RC) structures inevitably consumes an excessive number of rebars, leading to significant cutting waste and carbon emissions. Extensive research has been conducted to minimize this issue and its consequences; however, these methods consistently consume a substantial number of rebars. This includes a previous study that utilizes the lap splice position optimization and special-length rebar concept without considering the lapping zone regulation. Moreover, conventional lap splices pose inherent drawbacks that could jeopardize the structural integrity of RC members. In contrast, mechanical couplers eliminate the need for rebar lapping, effectively reducing rebar consumption. This research aims to evaluate the impact of an integrated mechanical coupler and special-length-priority minimization algorithm on the reduction in rebar consumption and cutting waste in RC columns, achieving near-zero cutting waste. To validate the effectiveness of the proposed algorithm, it was applied to the column rebars of an RC building. The results revealed a significant reduction in ordered rebar consumption by 18.25%, accompanied by substantial reductions in cutting waste (8.93%), carbon emissions (12.99%), and total costs (10.81%) compared with a previous study. The outcomes provide the industry with insights into further reducing rebar consumption and its related consequences. Applying the proposed algorithm to various construction projects will further amplify the corresponding benefits.