There is a high iron content in the nickel slag that mainly exists in fayalite phase. Basic Oxide can destroy the stable structure of fayalite which is beneficial to the treatment and comprehensive utilization of nickel slag. The reseach was based on the composition of the raw nickel slag, taking CaO-SiO₂-FeO-MgO system as the object and CaO as a modifier. The effect of basicity on the melting characteristics, viscosity and structure of CaO-SiO₂-FeO-MgO system was studied. The relationship between the viscosity and structure of CaO-SiO₂-FeO-MgO system was also explored. The results show as follows. (1) When the basicity is 0.38~0.90, the phase of primary crystal is olivine at argon atmosphere, while it is monoxide at the basicity of 0.90~1.50. The liquidus temperature, softening temperature, hemispherical temperature, and flow temperature all reach the lowest value at the basicity of 0.90. (2) With the increase of basicity, critical viscosity temperature of CaO-SiO₂-FeO-MgO system decreases first and then increases. Critical viscosity temperature is the lowest at the basicity of 0.90, which is 1263 ℃. (3) When the slag system is heterogeneous, the viscosity of the molten slag increase rapidity because of the type and quantity of solid phase precipitated from CaO-SiO₂-FeO-MgO system. And critical viscosity temperature of the slag system is also significantly affected. (4) When the slag system is in a homogeneous liquid phase, the molar fraction of O0 decreases with the increase of basicity and the mole fraction of O^- and O^2- increases continuously at the basicity of 0.38~1.50. The silicate network structure is gradually depolymerized into simple monomers, resulting in the degree of polymerization is reduced and the viscosity is reduced, too.

Using agronomic measures to remediate heavy metals on farmland is the main measure to achieve the safe utilization of crops. Investigating the effects of applying different fertilizers on the uptake, and translocation of Chromium (Cr) in maize and on the effectiveness of Cr in soil under Cr contamination of farmland is of great theoretical and practical significance to achieve the safe utilization of arable land and safe production of agricultural products. Under field trial conditions, different fertilizer types were set up, including ammonium sulfite, calcium-magnesium phosphate, and diammonium phosphate. locally formulated fertilizers (urea-ammonium phosphate-potassium chloride) serving as the control, with Biochar and conditioner PX5B were chosen to compare the impacts of each. To study the effects of different fertilizer types on maize yield, Cr content in the plant, bioconcentration factor, translocation factor and available content of Cr in the soil. The results showed that Compared with the formulated fertilizer, all treatments could improve pH, soil organic matter (SOM） and reduce the effective state of Cr content in the soil by 15.05% to 42.66%. While the Cr content of maize grains treated with biochar and conditioner PX5B was 0.80 mg·kg-1 and 0.88 mg·kg-1 with reduction rates of 39.95% and 33.83%, respectively. The Cr content of maize grains treated with various fertilizer treatments ranged from 0.82 to 1.32 mg·kg-1 with reduction rates of 0.75% to 38.19%. The Cr content of maize grains could be brought down to below the national food safety standards of China(1.0 mg·kg-1) using urea – calcium magnesium phosphate - potassium chloride, urea - diammonium phosphate - potassium chloride, ammonium sulfite – calcium magnesium phosphate - potassium chloride and ammonium sulfite, urea – calcium magnesium phosphate - potassium chloride and the two conditioner treatments. Among the different fertilizer treatments, the best fertilizer treatment for reducing the effective state Cr content of soil and the Cr content of maize grains was ammonium sulfite-calcium-magnesium-phosphate fertilizer-potassium chloride, which could achieve similar reductions as the two conditioners, while it also had a certain reduction effect on the Cr content in maize roots and straws and on the aboveground bioconcentration factor（BCF） and the root-to-straw translocation factor（PTF） of maize for Cr. Therefore, the combination of ammonium sulfite and calcium magnesium phosphate is the best fertilizer combination to block the absorption of Cr by maize and has some implications for the fertilization of farmland under acidic soil conditions of Cr contamination.

Keywords: mHealth; peritoneal dialysis; functionality; usability

Depressive disorder in childhood and adolescence is a highly prevalent mood disorder that tends to recur throughout life. Untreated mood disorders can adversely impact a patient's quality of life and cause socioeconomic loss. Thus, an accurate diagnosis and appropriate treatment is crucial. However, until now, diagnoses and treatments are conducted according to clinical symptoms. Objective and biological validation are lacking. This may result in a poor outcome for patients with depressive disorder. Research has been conducted to identify the biomarkers that are related to depressive disorder. Cumulative evidence has revealed that certain immunologic biomarkers in-cluding brain-derived neurotrophic factor (BDNF) and cytokines, gastrointestinal biomarkers, hormones, oxidative stress, and certain hypothalamus-pituitary axis biomarkers are associated with depressive disorder. This article reviews the biomarkers related to the diagnosis and treatment of pediatric depressive disorders. To date, clinical biomarker tests are not yet available for diagnosis or for the prediction of treatment prognosis. However, cytokines such as Interleukin-2, interfer-on-gamma, tumor necrosis factor-alpha, and BDNF have shown significant results in previous studies of pediatric depressive disorder. These biomarkers have the potential to be used for diagnosis, prognostic assessment, and group screening for those at high risk.

We study the generalized χ and η cross helicities for non-ideal non-barotropic magnetohydrodynamics (MHD). χ and η, the additional label translation symmetry group, have been used to generalize the cross helicity in ideal flows. Both new helicities are additional topological invariants of ideal MHD. To study there behaviour in non-ideal MHD, we derive the time derivative of both helicities using the non-ideal MHD equations taking viscosity, finite resistivity and heat conduction into account. Physical variables are divided into ideal and non-ideal quantities separately during the mathematical analysis for simplification. The analytical results indicate that χ and η cross helicities are not strict constant of motion in the non-ideal MHD and show the rate of dissipation which is compared to the dissipation of other topological constants of motion.

Emerging evidence has shown that microRNAs play pivotal roles in wound healing. MicroRNA-21 (miR-21) was previously found to upregulate in order to fulfill an anti-inflammation role for wounds. Exosomal miRNAs have been identified and explored as essential markers for diagnostic medicine. However, the role of exosomal miR-21 in wounds has yet to be well studied. In order to facilitate the early management of poorly healing wounds, we developed an easy-to-use, rapid, paper-based microfluidic-exosomal miR-21 extraction device to determine wound prognosis in a timely manner. We isolated and then quantitatively examined exosomal miR-21 in wound fluids from normal tissues, acute and chronic wounds. Eight improving wounds displayed lower levels of exosomal miR-21 expression after wound debridement. However, four instances of increased exosomal miR-21 expression levels were notably associated with patients with poor healing wounds despite aggressive wound debridement, indicating a predictive role of tissue exosomal miR-21 for wound outcome. Paper-based nucleic acid extraction device provides a rapid and user-friendly approach for evaluating exosomal miR-21 in wound fluids as a means of monitoring wounds. Our data suggest that tissue exosomal miR-21 is a reliable marker for determining current wound status.

In urban area, one of the great problem is the rise of temperature, which leads to form the urban heat island effect. This paper refers to the trend of the urban surface temperature extracted from the Landsat images from which to consider changes in the formation of surface urban heat island for the north of Ho Chi Minh city in period 1995-2015. Research has identified land surface temperature from thermal infrared band, according to the ability of the surface emission based on characteristics of normalized difference vegetation index NDVI. The results showed that temperature fluctuated over the city with a growing trend and the gradual expansion of the area of the high-temperature zone towards the suburbs. Within 20 years, the trend of the formation of surface urban heat island with two typical locations showed a clear difference between the surface temperature of urban areas and rural areas with space expansion of heat island in 4 times in 2015 compared to 1995. An extreme heat island located in the inner city has an area of approximately 18% compared to the total area of the region. Since then, the solution to reduce the impact of urban heat island has been proposed, in order to protect the urban environment and the lives of residents in Ho Chi Minh City becoming better

The morphological and compositional complexities of keratinized components make feathers ingenious skin appendages adapted to diverse ecological needs. Frizzling feathers, characterized by their distinct curling phenotypes, offer a unique model to explore the intricate morphogenesis in developing a keratin-based bioarchitecture over a wide range of morphospace. Here, we investigated the heterogeneous allocation of α- and β-keratins in flight feather shafts of homozygous and heterozygous frizzle chickens by analyzing the medulla-cortex integrations using quantitative morphology characterizations across scales. Our results reveal intriguing construction of frizzling feather shaft through modified medulla development, leading to a perturbed balance of the internal biomechanics and, therefore, introducing the inherent natural frizzling compared to those from wild-type chickens. We elucidate how the localized developmental suppression of the α-keratin in the medulla interferes with the growth of the hierarchical keratin organization by changing the internal stress in the frizzling feather shaft. This research not only offers insights into the morphogenetic origin of the inherent bending of frizzling feathers but also facilitates our in-depth understanding of the developmental strategies toward the diverse integuments adapted for ecological needs.

As an essential synthetic material used in continuous casting of steels, mold fluxes improve the surface quality of steel slabs. In this study, a CaO-SiO₂-Na₂O based low-fluorine mold flux was solidified by an improved water-cooled copper probe with different temperatures of molten flux and different probe immersion times. The heat flux through solid films and the film structures were calculated and inspected, respectively. The results indicate: large internal cracks (formed in the glassy layer of films during solidification) were observed, the formation and evolution of those cracks contributed to the the unstable heat flux density. The roughness of the surface in contacted with the water-cooled copper probe formed as films were still glassy and the roughness have no causal relationship with crystallization or devitrification. Combeite with columnar and faceted dendritic shapes is the main crystal in the film.

During the coronavirus disease 2019 (COVID-19) pandemic, individuals with immune-mediated inflammatory diseases (IMIDs), such as systemic lupus erythematosus and rheumatoid arthritis, face a heightened risk of infection and severe outcomes due to immunological alterations resulting from their underlying conditions and immunosuppressive treatments. Even as the pandemic has transitioned to an endemic state, it remains crucial to recognize that these patients continue to be at risk. In this narrative review, we analyzed existing literature to explore the impact of IMIDs, clinical risk factors, and the influence of immunosuppressive therapies on COVID-19-related risks and outcomes. Notably, certain disease-modifying antirheumatic drugs (DMARDs), like rituximab, are associated with worse COVID-19 outcomes, and rituximab-treated patients show impaired immune responses to COVID-19 vaccination. Additionally, we outline the diverse effects of glucocorticoids on COVID-19 outcomes and management. To highlight real-life challenges faced by clinicians caring for patients with IMIDs, we present an illustrative scenario that underscores the importance of effective vaccination, timely boosting, and additional mitigation strategies against COVID-19. Given the clinical heterogeneity and diverse disease states within IMIDs, it is crucial to understand the ongoing implications and risks associated with COVID-19 in these patients, to guide the implementation of appropriate measures and optimize care and outcomes in the current endemic era.

In this study, the impact of the addition of high-aspect-ratio nano-ettringite to photocurable epoxy acrylate resin was explored, with a specific focus on the changes observed in viscosity, shrinkage, tensile strength, and elongation at the break of composites formed. Herein, the nano-ettringite samples were modified using KH-570. The 3 wt% or 6 wt% KH-570-modified and unmodified nano-ettringite were dispersed into the resin by ultrasonic treatment in conjunction with mechanical stirring. The grafting effects of nano-ettringite onto KH-570 were analyzed through scanning electron microscopy (SEM), X-ray diffraction (XRD), thermogravimetric (TG) analysis, and Fourier transform infrared spectroscopy (FTIR). The results demonstrate that increased dosages of unmodified and modified nano-ettringite led to increased viscosity of the composite while reducing shrinkage. At the same dosage, the photocurable resin with modified nano-ettringite demonstrated a lower shrinkage and a higher tensile strength. Notably, when the amount of modified nano-ettringite was 3 wt%, the highest tensile strength of the composite was 64.61 MPa, presenting a 72.57% increase compared to the blank sample. Furthermore, the incorporation of modified nano-ettringite as a filler provides a new perspective for improving the performance of photocurable epoxy acrylate resin composites.

In recent years, governments applied intelligent transportation system (ITS) technique to provide several convenience services (e.g., garbage truck app) for residents. This study proposes a garbage truck fleet management system (GTFMS) and data feature selection and data clustering methods for travel time prediction. A GTFMS includes mobile devices (MD), on-board units, fleet management server, and data analysis server (DAS). When user uses MD to request the arrival time of garbage truck, DAS can perform the procedure of data feature selection and data clustering methods to analyses travel time of garbage truck. The proposed methods can cluster the records of travel time and reduce variation for the improvement of travel time prediction. After predicting travel time and arrival time, the predicted information can be sent to user’s MD. In experimental environment, the results showed that the accuracies of previous method and proposed method are 16.73% and 85.97%, respectively. Therefore, the proposed data feature selection and data clustering methods can be used to predict stop-to-stop travel time of garbage truck.

Ho Chi Minh City (HCMC), the most crowded city and economic hub of Viet Nam, has been experiencing land subsidence over the past decades. This effort aims to contribute the spatial distribution of subsidence in HCMC in its horizontal and vertical components using synthetic aperture radar interferometry (InSAR) time series. To this purpose, an advanced Persistent Scatterers and Distributed Scatterers (PSDS) InSAR technique was applied to two European Space Agency (ESA) Sentinel-1 datasets consisting of 96 ascending and 202 descending images, acquired from 2014 to 2020 over the HCMC area. A time series of 33 COSMO-SkyMed ascending images was also used for comparison. The combination of ascending and descending satellite passes is used to decompose the light of sight velocities into horizontal east-west and vertical components. Taking into account the presence of east-west horizontal motion, our findings indicate that the accuracy of the decomposed vertical velocity can be improved by up to 3 mm/year for Sentinel-1 data. The obtained results revealed that subsidence is most pronounced in the areas along the Sai Gon River, in the northwest-southeast axis, and in the southwest of the city, with a maximum value of 80 mm/yr, which is in accordance with the findings of the literature. The amplitude of east-west horizontal velocities is relatively small and large-scale eastward movement can be observed in the west of the city at a rate of 3-5 mm/yr. This confirmed that the displacement in Ho Chi Minh City area is mainly vertical downward. Together, these results reinforced the remarkable suitability of ESA's SAR Sentinel-1 for subsidence applications, even for non-European countries such as Vietnam and Southeast Asia.

Bonfire night is a worldwide phenomenon given to numerous annual celebrations characterised by bonfires and fireworks. Since Thailand has no national ambient air quality standards for metal particulates, it is important to investigate the impacts of particulate injections on elevations of air pollutants and ecological health impacts resulting from firework displays. In this investigation, Pb and Ba were considered potential firework tracers because their concentrations were significantly higher during the episode and lower than/comparable with minimum detection limits during other periods, indicating that their elevated concentrations were principally due to pyrotechnic displays. Pb/Ca, Pb/Al, Pb/Mg, and Pb/Cu can be used to pin-point emissions from firework displays. Air mass backward trajectories (72 h) from the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model indicated that areas east and north-east of the study site were the main sources for the air transportation. Although the combined risk associated with levels of Pb, Cr, Co, Ni, Zn, As, Cd, V, and Mn was far below the standards mentioned in international guidelines, the lifetime cancer risks associated with As and Cr levels exceeded US-EPA guidelines, and may expose inhabitants of surrounding areas of Bangkok to elevated cancer risk.

Characterization of cancer cells and neural stem cells indicates that tumorigenicity and pluripotency are coupled cell properties determined by neural stemness, and tumorigenesis represents a process of progressive loss of original cell identity and gain of neural stemness. This reminds of a most fundamental process required for the development of the nervous system and body axis during embryogenesis, i.e., embryonic neural induction. Neural induction is that, in response to extracellular signals that are secreted by the Spemann-Mangold organizer in amphibians or the node in mammals and inhibit epidermal fate in ectoderm, the ectodermal cells lose their epidermal fate and assume the neural default fate and consequently, turn into neuroectodermal cells. They further differentiate into the nervous system and also some non-neural cells via interaction with adjacent tissues. Failure in neural induction leads to failure of embryogenesis, and ectopic neural induction due to ectopic organizer or node activity or activation of embryonic neural genes causes a formation of secondary body axis or a conjoined twin. During tumorigenesis, cells progressively lose their original cell identity and gain of neural stemness, and consequently, gain of tumorigenicity and pluripotency, due to various intra-/extracellular insults in cells of a postnatal animal. Tumorigenic cells can be induced to differentiation into normal cells and integrate into normal embryonic development within an embryo. However, they form tumors and cannot integrate into animal tissues/organs in a postnatal animal because of lack of embryonic inducing signals. Combination of studies of developmental and cancer biology indicates that neural induction drives embryogenesis in gastrulating embryos but a similar process drives tumorigenesis in a postnatal animal. Tumorigenicity is the manifestation of aberrant occurrence of pluripotent state in a postnatal animal. Pluripotency and tumorigenicity are both but different manifestations of neural stemness in pre- and postnatal stage, respectively, of animal life. The unique property of neural stemness is derived from the evolutionary advantage of neural genes and the neural-biased state of the last common unicellular ancestors of metazoan. Based on these findings, I discuss about some confusion in cancer research, propose to distinguish the causality and associations and discriminate causal and supporting factors involved in tumorigenesis, and suggest revisiting the focus of cancer research.

Recognizing highly occluded objects is believed to arises from the interaction between the brain's vision and cognition controlling areas, although supporting neuroimaging data is currently limited. To explore the neural mechanism during this activity, we conducted an occlusion object recognition experiment using functional magnetic resonance imaging (fMRI). During magnet resonance examinations, 66 subjects engaged in object recognition tasks with three different occlusion degrees. Generalized linear model (GLM) analysis showed that the activation degree of occipital lobe (inferior occipital gyrus, middle occipital gyrus, and occipital fusiform gyrus) and dorsal anterior cingulate cortex (dACC) was related to the occlusion degree of the objects. Multivariate pattern analysis (MVPA) further unearthed a considerable surge in classification precision when dACC activation was incorporated as a feature. This suggested the combined role of dACC and occipital lobe in occluded object recognition tasks. Moreover, psychophysiological interaction (PPI) analysis disclosed that functional connectivity (FC) between the dACC and the occipital lobe was enhanced with increased occlusion, highlighting the necessity of FC between these two brain regions in effectively identifying exceedingly occluded objects. In conclusion, these findings contribute to understanding the neural mechanisms of highly occluded objects recognition, augmenting our appreciation of how the brain manages incomplete visual data.

Predictions of crop production in the Chi basin are of major importance for decision support tools in countries such as Thailand, which aim to increase domestic income and global food security by implementing the appropriate policies. This research aims to establish a predictive model for predicting crop production for an internal crop growth season prior of harvest at the province scale for fourteen provinces in Thailand's Chi basin between 2011 and 2019. We provide approaches for reducing redundant variables and multicollinearity in remotely sensed (RS) and meteorological data to avoid overfitting models using correlation analysis (CA) and variance inflation factor (VIF). Temperature condition index (TCI), normalized difference vegetation index (NDVI), land surface temperature (LSTnight), and mean temperature (Tmean) were the resulting variables in the prediction model with a p-value < 0.05 and a VIF < 5. The baseline data (2011–2017: June to November) were used to train four regression models, which revealed that eXtreme Gradient Boosting (XGBoost), random forest (RF), and XGBoost achieved R2 values of 0.95, 0.94, and 0.93, respectively. In addition, the testing dataset (2018–2019) displayed a minimum root mean square error (RMSE) of 0.18 ton/ha for the optimal solution by integrating variables and applying the XGBoost model. Accordingly, it is estimated that between 2020 and 2022, the total crop production in the Chi basin region would be 7.88, 7.64, and 7.72 million tons, respectively. The results demonstrated that the proposed model is proficient at greatly improving crop yield prediction accuracy when compared to a conventional regression method and that it may be deployed in different regions to assist farmers and policymakers in making more informed decisions about agricultural practices and resource allocation.

Regulatory T cells are key immune cells to initiate tolerable immune responses. TGFβ is the key cytokine of regulatory T cells. TGFβ is also the master cytokine to stimulate tissue fibrosis. Systemic sclerosis is an autoimmune disease related to overt organ fibrosis. Thus, systemic sclerosis is a disease related to regulatory T cell over-representation. Besides, many end stage organ failures including heart failure, liver cirrhosis, uremia, and pulmonary fibrosis also related to tissue fibrosis. Thus, TGFβ producing regulatory T cells are also involved in the pathogenesis of these end stage organ failure. Once we know the significance of TGFβ and it induced tolerable immune reactions in the pathophysiology of end organ failure, we can develop better prevention or therapeutic strategies to combat these detrimental disorders.

Background: The link between nocturia and aging male symptoms (AMS) has not been scientifically established. This study aimed to measure the degree of severity of AMS that impact on the health-related quality-of-life (HRQoL) in adult males living with nocturia, and to determine the predictive values of nocturnal factors on AMS. Methods: It is an extended analysis of new data collected by using the Hong Kong Traditional AMS (HK-AMS) scale and Cantonese version of the Pittsburgh Sleep Quality Index (PSQI) in a recently published cross-sectional population-based survey. Results: Of the 781 respondents that have completed the set of questionnaires, 68% and 61% of men living with nocturia reported clinically significant (at moderate-to-severe levels) somato-vegetative and sexual AMS, whereas the prevalence and severity were increased with advancing nighttime voiding frequency. The nocturia-specific QoL (NQoL) score and nocturnal frequency were found to be significant predictive factors for composite, somato-vegetative and sexual AMS, in addition to age, global OSQI score, and certain metabolic diseases. Conclusions: Current findings suggested the inclusion of nocturia when measuring the male-specific HRQoL related to aging.

A simple bounded stochastic motion is employed for modelling equity price dynamics under shocks, where the prices are constrained to lie between two positive bounds. While the stochastic process has an inaccessible boundary, the other boundary is quasi-bounded, implying that the boundary can be breached if the probability leakage condition is met. The quasi-boundedness of the process at the boundary can thus provide an indicator of possible risk of equities under price shocks. Empirical calibration of model parameters of the proposed process for equities can be performed easily due to the availability of an analytically tractable probability density function which generates fat-tailed distributions consistent with empirical observations. The volatility and mean-reversion of the S&P500 dynamics calibrated by the process is positively and negatively co-integrated respectively with the VIX index representing the level of market distress. The process captures the high likelihood of Hertz’s default about two months earlier, using only information until that point, and before the firm filed for Chapter 11 bankruptcy in May 2020 as a result of the Covid-19 pandemic. Empirical calibration of the process for GameStop’s stock price shows that the short squeeze of the stock occurred when the condition for breaching an upper boundary was met on 14 January 2021, i.e., about two weeks before major short sellers closed out their positions with significant losses. The trading volume of the stock was positively co-integrated with the probability leakage ratio.

The purpose of this study is to apply the convergence-confinement method (CCM) based on the assumption of hydrostatic stress to the surrounding rock excavated in a circular tunnel whose rock mass characteristics meet the requirements of the non-linear Hoek-Brown failure criterion. Based on a consistent and rigorous method of theoretical analysis, a closed-form analytical solution for the stress/displacement of the ground reaction induced by the advancing excavation of the tunnel, especially in the elastic and plastic regions, is derived and investigated under the condition of an isotropic stress state. By taking the value of a confinement loss as an explicit analysis process in an incremental manner, not only is the computationally executable analytical solution achieved, but it can also be performed using a simple spreadsheet. The validity of the analytical solution implemented by the incremental procedure was examined with published data to study the effect of nonlinear failure criteria on the ground reaction curve; in particular the mechanical behavior at the intrados of the tunnel, and the distribution of stress/displacement on the cross-section of the tunnel. A comparison between the published results and the solution proposed in this study, which interprets the closed-form by the incremental procedure, shows consistent and favorable trends.

A better understanding of high temperature processes in slags contributes to facilitate knowledge based design of the solidified product. Here, a slag analogue with a nominal composition of 17 wt% LiMnO2 and 83 wt% Ca2SiO4 was synthesized encountering fairly high cooling rates. The Mn species from 1223 K to 1773 K was simulated using a thermodynamic model assuming a homogeneous melt. The micro-composition including the Mn species of the solidified slag was determined experimentally and was used as basis for molecular dynamics (MD) simulation. The MD simulation provides information on structure and viscosity at high temperatures, otherwise difficult to access. These parameters significantly influence oxidation state of redox-active elements and the solidified product. The micro-composition analyzed by electron probe micro analysis (EPMA) and synchrotron based micro-X-ray fluorescence (micro-XRF) showed that Mn-rich and Ca-Si-rich phases are separated. While the Mn-O phases did not contain noticeable Ca, the Ca2SiO4 phase had incorporated 0.6 wt% of Mn. The slag solidified into round shaped and droplet shaped grains of a Li-Mn-oxide, some Mn3O4 and Ca2SiO4. The powder X-ray diffraction (PXRD) confirmed the formation of larnite, the identity of the Li-Mn-oxide however remained inconclusive. The Mn oxidation state (OS) was identified using synchrotron based micro-X-ray absorption near edge spectroscopy (micro-XANES). The Mn-O grains, matched well with Li-Mn-oxides and a Mn OS: +3 e.g. LiMn3+O2. Small areas matching Hausmannite (Mn2+Mn23+O4) were also identified. The OS of Mn in the silicate phase could not be identified. For comparison a slowly cooled slag analogue with similar composition however higher Si content, was also subjected to micro-XANES. The slowly cooled slag formed long Mn-rich needles in a matrix of large calcium silicate crystals. The Mn-rich crystals matched well with the XANES spectrum of a Mn3+ Li-oxide like LiMn3+O2. At the rim of the needles the Mn-spectra matched well the Hausmannite (Mn2+Mn23+O4) reference. In the silicate phases Mn had a OS: +2, unambiguously. The melt structure at different temperatures of two compositions i.e. LiMn3+O2 and Ca2SiO4 was simulated using molecular dynamics (MD). They serve as model compositions assuming a heterogeneous melt. The results show significant different degrees of polymerization and viscosity. Information from MD simulations can support the identification of potentially different oxygen permeability and with that prediction of oxidation states. The bulk composition was identified by inductively coupled plasma optical emission spectrometry (ICP-OES), bulk structure by PXRD and bulk species by lab-XANES. The synchrotron micro analysis including micro-XRD were performed at the microfocus beamline I18 at the Diamond Light Source. Pure reference compounds were prepared and characterized with the same multi-modal approach.

Resilience governance provides a new governance model for emergency management in higher education institutions facing major public crises. Higher education resilience governance, while achieving short-term objectives such as mitigating external impacts and maintaining core functions, enhances the enduring adaptability of higher education institutions to the increasingly changing natural and social environments. This transformation shifts the emergency management mode in higher education from reactive responses to proactive governance. In terms of value logic, resilience governance upholds the mission of higher education as the primary nurturing ground, ensuring fairness, quality, and sustainability in education. In terms of organizational logic, it emphasizes collaborative cooperation among higher education institutions, government, society, and the market, as well as the integration of functions within higher education institutions and relatively close connections among their personnel. In terms of institutional logic, it relies on both top-down institutional supply and bottom-up institutional demand to support effective participation, resulting in authoritative and complementary behavioral rules. In terms of action logic, it combines vertical coordination mechanisms and horizontal community collaboration to enhance the effectiveness of cooperative governance. Therefore, the highest value should be placed on the safety of faculty and students, and education planning should be imbued with resilience. It starts with organizational adaptability to develop resilient institutions, focuses on orderly transitions to enhance the emergency management system in higher education, and centers on proactivity and collaboration to build a community of action for emergency governance in higher education.

Tumorigenesis is a complex biological phenomenon that includes extensive genetic and phenotypic heterogeneities and complicated regulatory mechanisms. In the recent few years, our studies demonstrate that tumor-initiating cells are similar to neural stem/progenitor cells in regulatory networks, tumorigenicity and pluripotent differentiation potential. In the review, I will make further discussion on these observations and propose a rule of cell biology by integrating these findings with evidence from developmental biology, tumor biology and evolution, which suggests that neural stemness underlies two coupled cell properties, tumorigenicity and pluripotent differentiation potential. Tumorigenicity and phenotypic heterogeneity in tumor is a result of acquirement of neural stemness in cells. The neural stemness property of tumor-initiating cells can hopefully integrate different concepts/hypotheses underlying tumorigenesis. Neural stem cells/neural progenitors and tumor-initiating cells share regulatory networks; both exhibit neural stemness, tumorigenicity and differentiation potential; both are dependent on expression or activation of ancestral genes (the atavistic effect); both rely primarily on aerobic glycolytic metabolism; both can differentiate into various cells or tissues that are derived from three germ layers, resembling severely disorganized or more severely degenerated process of embryonic development; both are enriched in long genes with more splice variants that provide more plastic scaffolds for cell differentiation, etc. The property of neural stemness might be a key point to understand tumorigenesis and pluripotent differentiation potential, and possibly explain certain pathological observations in tumors that have been inexplicable. Therefore, behind the complexity of tumorigenesis might be a general rule of cell biology, i.e., neural stemness represents the ground state of cell tumorigenicity and pluripotent differentiation potential.

The mechanism of immune activation and de-activation is very important. Host should trigger effective immunity against pathogen infection. And, host cannot trigger immunity against self-antigens that will lead to detrimental autoimmune disorders. Spleen and liver have opposite roles in mediating immune responses. Spleen is the organ involving in immune activation, and liver is the organ involving in immune de-activation. Sympathetic nerve system and parasympathetic nerve system have opposite roles in mediating immune responses. Sympathetic nerve system is involving in pro-inflammatory, and parasympathetic nerve system is involving in anti-inflammatory. ACTH and glucocorticosteroid have opposite roles in mediating immune responses. ACTH is involving in activating adaptive immunity with inhibiting innate immunity, and glucocorticosteroid is involving in activating innate immunity with inhibiting adaptive immunity. The molecular chaperons, heat shock proteins, which are induced by fever, have the vital roles in immune activation. On the contrary, IgD B cells and gamma-delta T cells are causing immune de-activation via the mechanism of clonal anergy. These mechanism can help us the know the work of immunological pathways better for better control of infectious diseases and autoimmune disorders.

To study the influence of Latin dance and Tai Chi on knee joint proprioception and balance. Method: All experiments were performed in the Beijing Normal University School of Physical Education and Sport Biomechanics Laboratory. An isokinetic test system (Biodex system 4, BS4) and a balance testing system (Biodex Balance System, BBS)from the United States Biodex medical system were used to test related indexes. Results: In the LOS test, the overall score of Latin group is much better than sedentary group. In the ASL test, Latin group have a better balance ability in anterior and posterior direction and overall score than sedentary group(p＜0.05); TAI CHI group have a better balance ability than sedentary group in anterior and posterior direction(p＜0.05)and right and left direction (p＜0.01). When the knee joint was at 15, 30, and 45degree positions, the Tai Chi exercise group was much better than sedentary group (P < 0.05), and the 45 degree position in the Tai Chi group was much better than that in the Latin dance group (P < 0.01).When the knee joint was at the 30 degree position, the quadriceps force sense was significantly better in the Tai Chi group than in the Latin dance and sedentary groups. In a test of the four angles, the hamstring force sense in the Tai Chi exercise group was obviously better than that in the sedentary group (P < 0.05); at the 15 degree position, the Tai Chi group was significantly better than the Latin group (P < 0.05); and at 30 degree position, the hamstring force sense of the Latin group was obviously better than that of the sedentary group (P < 0.05).

Multicellular organisms organize themselves according to two principles; first, the equilibrium between the driving force of unstable state cells and apoptosis or senescence; and second, the mutual equilibrium between the functional requirements of different types of cells. For the first principle, we deduce that stem cells at different levels have their own growth limits, which are determined by two factors: the ability of the stem cells to enter an unstable state (specifically, the ability of cells to divide and differentiate); and the rate of cellular senescence, loss of function, and finally, apoptosis. The superposition of stem cell limits at different levels over each other can amplify small differences at the genetic level. Moreover, the growth limits of different organs are different, which lead to different individuals having completely different appearances. The second principle is that the sum of the specific output functions of an organ must be equal to the overall demand for the function to be provided by the organ. If negative entropy input can meet this equilibrium, defects in certain genes will cause these defective individuals to become larger or develop other morphology.

This paper comprehensively reviews sensors and sensing devices developed or/and proposed so far utilizing two smart materials: electrorheological fluids (ERFs) and magnetorheological materials (MRMs) whose rheological characteristics such as stiffness and damping can be controlled by external stimuli, an electrical voltage for ERFs and a magnetic field for MRMs, respectively. In this review article, the MRMs are classified into magnetorheological fluid (MRF), magnetorheological elastomer (MRE) and magnetorheological plastomer (MRP). To easily understand the history of sensing research using the two smart materials, the order of this review article is organized in a chronological manner of ERF sensors, MRF sensors, MRE sensors and MRP sensors. Among many sensors fabricated from each smart material, one or two sensors or sensing devices are adopted to discuss on the sensing configuration, working principle and specifications such as accuracy and sensitivity. Some sensors adopted in this article include force sensor, tactile device, strain sensor, wearable bending sensor, magnetometer, display device and flux measurement sensor. After briefly describing what have been reviewed in a conclusion, several challenging future works, which should be done for practical applications as sensors or sensing devices, are remarked in terms of new technologies such as artificial intelligence neural network in which several parameters affecting the sensor signals can be precisely tuned or controlled. It is sure that this review article is very helpful to make creative sensors using not only the proposed smart materials but also several different types of smart materials including shape memory alloys and active polymers.

Rose (Rosa spp.), especially R. hybrida, is one of the most popular ornamental plants in the world and the third largest cut flower crop in Taiwan. Rose mosaic disease (RMD), showing mosaic, line patterns and ringspots on leaves, is a common rose disease caused by complex infection of various viruses. Due to pests and diseases, the rose planting area in Taiwan has been decreasing since 2008; however, no rose virus disease has been reported in the past five decades. In the spring of 2020, rose samples showing RMD-like symptoms were observed at an organic farm in Chiayi, central Taiwan. The virome in the farm was analyzed by RNA-seq. Rose genomic sequences were filtered from the obtained reads. The remaining reads were de novo assembled to generate 294 contigs, 50 of which were annotated as viral sequences corresponding to 10 viruses. Through reverse transcription-polymerase chain reaction validation, a total of seven viruses were detected, including six known rose viruses, namely apple mosaic virus, prunus necrotic ringspot virus, rose partitivirus, apple stem grooving virus, rose spring dwarf-associated virus and rose cryptic virus 1, and a novel ilarvirus. After completing the whole genome sequencing and sequence analysis, the unknown ilarvirus was demonstrated as a new species, tentatively named rose ilarvirus 2. This is the first report of the rose viruses in Taiwan.

Biocompatibility of ceramic materials in CaO-P2O5 system was investigated using different methods, including in vitro and in vivo tests. Ceramics based on calcium pyrophosphate Ca2P2O7 were obtained by annealing cement-salt stone from highly concentrated hardening suspensions (HCHS). Cement-salt stone was prepared using powder mixtures of calcium citrate tetrahydrate Ca3(C6H5O7)2·4H2O and monocalcium phosphate monohydrate (MCPM) Ca(H2PO4)2·H2O. These salts were mixed with each other in such a way that calcium pyrophosphate and calcium polyphosphate were present in the final ceramic product in the following weight ratios: Ca(PO3)2/Ca2P2O7 = 0/100; 5/95; 10/90 and 20/80. Distilled water was added to a homogenized powder mixtures of Ca3(C6H5O7)2·4H2O and Ca(H2PO4)2·H2O by a water/solid ratio of 0,5 by weight. The obtained suspensions were shaped using silicon molds and left to dry in air for a week. The phase composition of the obtained samples of cement-salt stone was represented by brushite CaHPO4·2H2O, monetite CaHPO4, calcium citrate tetrahydrate Ca3(C6H5O7)2·4H2O and monocalcium phosphate monohydrate Ca(H2PO4)2·H2O. According to the XRD data, the phase composition of ceramic materials after annealing in the temperature range of 800-1000 0C was mainly represented by the β-Ca2P2O7 phase. In vivo tests shown that obtained ceramic materials can be recommended for regenerative treatments for bone defects.

In this work, a series of compounds in the CaO-½Er2O3-CoOz ternary oxide system were synthesized in air at 885℃ using high temperature solid-phase synthesis method. Phase boundary of each solid solution region in the CaO-½Er2O3-CoOz system was determined by X-ray powder diffraction technique. The phase diagram of the CaO-½Er2O3-CoOz system at 885℃ includes three series of ternary oxide solid solutions : (Ca3-xErx)Co4O9-z (0≤x≤0.9), (Ca3-xErx)Co2O6-z (0≤x≤1.25) and (Er1-xCax)CoO3-z (0≤x≤0.33). Four three-phase regions and five solid solution tie-line regions were obtained. The structure of perovskite solid solution (Ca3-xErx)Co2O6-z has been analyzed by Rietveld refinements. With the increase of Er content, the cell parameters of (Ca3-xErx)Co2O6-z exhibit an decreasing trend in a and b directions and an increasing trend in c direction.

Insulated Gate Bipolar Transistor (IGBT) may convey high current and sustain high breakdown voltages; it may provide high power control. In a sense, how IGBT demonstrates the capability of power control was not specifically described, and the equivalent bipolar junction transistors (BJT) activated by an applied bias to the insulated gate is intriguing. As seen in Figure 1, IGBT shows an equivalent circuit structure containing two types of BJT, (NPN-type Bipolar transistor and PNP-type Bipolar transistor), which can be modeled as diode-associated transistor. Apparently, as a bias applies to the controlling gate, the channel beneath the gate oxide gets strongly inversed and turns out to be conductive just like what happens on metal-oxide-silicon field effect transistor (MOSFET), which provides necessary igniting currents to both BJTs and thus causes high current gain flowing through them-selves from the bottom. A proposed and renewed formula provides addressing the above scenario and successfully fitting the measured data that forms the characteristic curves. Some parameters in the proposed formula, which includes size and mobility associated constant, threshold voltage, and Early-Voltage-related lambda for MOSFET, explain and explore the underlying physics. IGBT thus enjoy high input impedance and high current gain due to MOSFET (Insulated Gate) and BJT, respectively. This formula combines both merits of MOSFET and BJT in order to fit the measured data. Indeed, the formula intimately fits IGBT electrical characteristic curves, and thus may be qualified and served as a model. The new model is then advisable for designing power integrated circuit to exactly achieve power saving, power control, and power efficiency.

Current stock market forecasting methods encompass fundamental, technical, emotional, and bargaining factors. Predominantly, price prediction hinges on order volume and price, although correlating these two within existing models proves challenging. This study employs Cycle Generative Adversarial Network (Cycle GAN) to unravel the intricate price-volume relationship, combining it with Bollinger Bands for trading signal analysis, overcoming hurdles in short-term forecasting prevalent in numerical analysis and AI. Focusing on TSMC (2330.TW) stock price, the research leverages Cycle GAN in deep learning to master the price-volume nexus, juxtaposed with LSTM and RNN. Historical TSMC closing prices and transaction counts are model inputs, scrutinizing their interconnectedness for predictions. This innovative approach aligns stock price, volume, market value, taxes, and prior changes via system engineering. By intertwining Bollinger Bands with stock price forecasts, trading signals are distilled, factoring in extended index %b for a comprehensive market picture.

This paper presents a piezoresistive pressure sensor with a shield layer for improved stability. Compared with the conventional piezoresistive pressure sensors, p-type piezoresistors are covered by an n-type shield layer, which is formed by ion implantation. The proposed pressure sensors have been successfully fabricated by bulk micromachining techniques. The impact of electrical field on piezoresistors is studied by simulation. The temperature drift of the pressure sensor has been investigated by both simulation and experimental measurement. Characteristics of developed pressure sensors are tested from -40 C to 125 C. A sensitivity of 0.022 mV/V/KPa and a maximum non-linearity of 0.085% FS are measured for the fabricated sensor in a pressure range of 1 MPa. The temperature coefficients of resistance of shielded piezoresistors are found to be smaller than those of un-shielded ones. It is demonstrated that the shield layer is able to reduce the drift caused by electrical field and ambient temperature variation.

The Vu Gia - Thu Bon River Basin (VG-TB) is confronting numerous challenges related to water security (WS), particularly in the face of the impacts of climate change. These challenges manifest in salinity intrusion, altered rainfall patterns, and reduced water supply in downstream areas. To assess the current state of water security in the basin, the study employed statistical analysis methods, Process Analysis Method (PAM), SMART, and Analytic Hierarchy Process (AHP) to develop a comprehensive Assessment Framework for Water Security (AFWS) in the VG-TB. The AFWS encompasses five key dimensions, 17 indicators, and 28 variables, aligning with the UN-Water definition of water security and addressing the Sustainable Development Goal 6 (SDG6) criteria for global water sustainability. It also adheres to the Asian Development Bank's (ADB) approach to water security assessment as outlined in the Asian Water Development Outlook (AWDO) reports. This allows for the computation of a comprehensive Water Security Index (WSI) for specific regions, serving as a foundation for decision-making and policy formulation aimed at enhancing water security in the context of climate change and facilitating sustainable basin development in the future.

Molecular modeling is widely utilized in subjects including but not limited to physics, chemistry, biology, materials science and engineering. Impressive progress has been made in development of theories, algorithms and software packages. To divide and conquer, and to cache intermediate results have been long standing principles in development of algorithms. Not surprisingly, Most of important methodological advancements in more than half century of molecule modeling are various implementations of these two fundamental principles. In the mainstream classical computational molecular science based on force fields parameterization by coarse graining, tremendous efforts have been invested on two lines of algorithm development. The first is coarse graining, which is to represent multiple basic particles in higher resolution modeling as a single larger and softer particle in lower resolution counterpart, with resulting force fields of partial transferability at the expense of some information loss. The second is enhanced sampling, which realizes "dividing and conquering" and/or "caching" in configurational space with focus either on reaction coordinates and collective variables as in metadynamics and related algorithms, or on the transition matrix and state discretization as in Markov state models. For this line of algorithms, spatial resolution is maintained but no transferability is available. Deep learning has been utilized to realize more efficient and accurate ways of "dividing and conquering" and "caching" along these two lines of algorithmic research. We proposed and demonstrated the local free energy landscape approach, a new framework for classical computational molecular science and a third class of algorithm that facilitates molecular modeling through partially transferable in resolution "caching" of distributions for local clusters of molecular degrees of freedom. Differences, connections and potential interactions among these three algorithmic directions are discussed, with the hope to stimulate development of more elegant, efficient and reliable formulations and algorithms for "dividing and conquering" and "caching" in complex molecular systems.

As governments in various countries and regions issue tourism-friendly policies in the post-pandemic period, the voices for tourism consumption recovery and innovative transformation have attracted great attention. Many scholars, experts and industry professionals in the field of festivals are actively exploring efficient solutions for festival marketing and sustainability. It is worth rethinking tourists’ consumption psychology and perceived image toward exiting festival products as well as the antecedents that affect festival loyalty. The Qingdao International Beer Festival, as one of the most influential festivals in China, was selected as the research case for this study. The main goal of this study was to investigate festival consumption promotion mechanism by proposing a conceptual framework in which the associations from destination familiarity and product familiarity to loyal intentions (re-patronage and recommendation) were examined, with mediators of overall festival image, perceived value and overall satisfaction. Furthermore, the moderating role of visitor involvement in the proposed framework was also adequately demonstrated. The research findings are expected to provide a significant reference for the recovery and competitiveness improvement of the entire festival industry.

Systemic lupus erythematosus (SLE) is a prevalent autoimmune condition, yet its alignment with a specific host immunological pathway remains unclear. The THαβ host immunological pathway, recognized for its defense against viruses and prions, has recently emerged as a response to DNA, RNA, and protein pathogens. SLE patients often produce anti-double strand DNA antibodies and anti-nuclear antibodies, suggesting a potential association with the THαβ host immune reaction. Throughout the course of SLE, elevated levels of type 1 interferons, type 3 interferons, interleukin-10, IgG1, and IgA1 are commonly observed. These cytokines and antibody isotypes are indicative of the THαβ host immunological pathway. Similarly, Myasthenia gravis, Grave’s disease, Graft versus host disease, autoimmune hemolytic anemia, immune thrombocytopenia, dermatomyositis, and Sjogren’s syndrome are also linked to THαβ-related type 2 hypersensitivities. Considering the potential association of these diseases with dysregulated THαβ immune responses, therapeutic strategies such as anti-interleukin-10 or anti-interferons α/β could be explored to manage these disorders effectively.

Ensuring optimal performance and reliability in rotor-bearing systems is crucial for industrial applications. Imbalance and shaft bow in these systems can lead to decreased efficiency and increased vibrations. Early detection and mitigation of a rotor’s faults are essential, and model-based fault identification has gained much attention in the manufacturing industry for years. Over the past two decades, however, the development of fault diagnosis rules with data-driven and artificial intelligence (AI) has become a trend, and in the foreseeable future, AI combined with big data will become mainstream. Nevertheless, the critical role of rotating machinery in manufacturing introduces a challenge, as the availability of fault data is often insufficient. This limitation renders the establishment of diagnostic rules using data-driven methods and AI technologies impractical. In light of these challenges, this study proposes a novel hybrid approach, that combines a physical model with machine learning (ML) techniques for the diagnosis of multi-faults (imbalance and shaft-bow demonstrated) in a Jeffcott rotor. To overcome the lack of real-world faulted, labeled datasets, a physics-based Jeffcott rotor model is first derived and then used to generate abundant fault datasets for ML. Subsequently, simulated data are employed for the training of an artificial neural network (ANN), enabling the network to learn from and analyze the vast array of generated data. The results prove that a well-trained feed-forward neural network (FNN) can accurately isolate and diagnose the imbalance and shaft-bow faults using the simulated data and the real data from the Jeffcott rotor experiment. These physics-based and ML approaches prove effective particularly for multi-fault, offering new possibilities for advanced rotor system monitoring and maintenance strategies in industrial applications.

Many theoretical models of iron-based superconductors have been proposed but Tc calculations based on the models are usually missing. We have chosen two models of iron-based superconductors in the literature and then compute the Tc values accordingly: Recently two models have been announced which suggest that superconducting electron concentration involved in the pairing mechanism of iron-based superconductors may have been underestimated, and that the antiferromagnetism and the induced xy potential may even have a dramatic amplification effect on electron-phonon coupling. We use bulk FeSe, LiFeAs and NaFeAs data to calculate the Tc based on these models and test if the combined model can predict the superconducting transition temperature (Tc) of the nanostructured FeSe monolayer well. To substantiate the recently announced xy potential in the literature, we create a two-channel model to separately superimpose the dynamics of the electron in the upper and lower tetrahedral plane. The results of our two-channel model support the literature data. While scientists are still searching for a universal DFT functional that can describe the pairing mechanism of all iron-based superconductors, we base on the ARPES data to propose an empirical combination of DFT functional for revising the electron-phonon scattering matrix in the superconducting state, which ensures that all electrons involved in iron-based superconductivity are included in the computation. Our computational model takes into account this amplifying effect of antiferromagnetism and the correction of the electron-phonon scattering matrix together with the abnormal soft out-of-plane lattice vibration of the layered structure, which allows us to calculate theoretical Tc values of LiFeAs, NaFeAs and FeSe as a function of pressure that correspond reasonably well to the experimental values. More importantly, by taking into account the interfacial effect between an FeSe monolayer and its SrTiO3 substrate as an additional gain factor, our calculated Tc value is up to 91 K high, and provides evidence that the strong Tc enhancement recently observed in such monolayers with Tc reaching 100 K may be contributed from the electrons within the ARPES range.

Three new secoiridoid constituents Gonocarin A-C (1-3) and a new derivative Gonocarin A monoacetate (4), along with two known lignins pinoresinol (5) and paulownin (6) were isolated from the seed of Gonocaryum calleryanum (Baill.) Becc. The structures of the new metabolites were determined on the basis of extensive spectroscopic analysis, particularly mass spectroscopy and 2D NMR (1H–1H COSY, HMQC, HMBC, and NOESY) spectroscopy. When mouse macrophages RAW264.7 were treated with compounds 1-6 together with LPS -stimulated, a concentration-dependent inhibition of nitric oxide (NO) and tumor necrosis factor (TNF-α) productions were detected. The results confirmed that the Gonocaryum calleryanumrrg could be a potential anti-inflammatory agent.

In Taiwan, colorectal cancer is ranked second and third in terms of mortality and cancer incidence, respectively. In addition, medical expenditures related to colorectal cancer are considered to be the third highest. While advances in treatment strategies have provided cancer patients with longer survival, potentially harmful second primary cancers can occur. Therefore, second primary colorectal cancer analysis is an important issue with regard to clinical management. In this study, a novel predictive scheme was developed for predicting the risk factors associated with second colorectal cancer in patients with colorectal cancer by integrating five data mining classification techniques, including support vector machine, random forest, multivariate adaptive regression splines, extreme learning machine, and extreme gradient boosting. In total, 4,287 patients in the datasets provided by three hospital tumor registries were used. Our empirical results revealed that this proposed predictive scheme provided promising classification results and the identification of important risk factors for predicting second colorectal cancer based on accuracy, sensitivity, specificity, and area under the curve metrics. Collectively, our clinical findings suggested that the most important risk factors were the combined stage, age at diagnosis, BMI, surgical margins of the primary site, tumor size, sex, regional lymph nodes positive, grade/differentiation, primary site, and drinking behavior. Accordingly, these risk factors should be monitored for the early detection of second primary tumors in order to improve treatment and intervention strategies.

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.

Blockchain technology can achieve decentralization, multi-party verification, anti-tampering, anonymity, traceability of transactions, and the application of distributed ledger. Countries around the world continue to seek the blockchain business models, technologies and applications, and have different visions and policies for the development of blockchain. This study conducts a comparative policy framework of theoretical analysis of the blockchain technology between the USA and China. Using the innovative policy tools proposed by Rothwell and Zegveld, the above mentioned governments are analyzed from the viewpoint of twelve policy tools. The results show that the USA and China all prefer to use “Environmental-side” policy. The USA has paid more attention to “Legal and regulatory”, “Public services” and “Procurement”. China has the highest proportion of policies in “Political tools”, followed by “Legal & regulatory”, while “Scientific and technical”, “Education” and “Overseas agent” come in third . The blockchain technology has developed vigorously among industries and its applications have gradually diversified. The results are provided to various stakeholders as a reference for policy planning.

In Taiwan, farmers often apply excess compost to ensure adequate crop yield in highly frequent tillage, highly weathered, and lower fertility soils. The potential of biochar (BC) for diminishing soil C mineralization, and improving soil nutrient availability in compost over-fertilized soil is promising, but the study is still under-examined. To test the hypothesis, 434 days in vitro C mineralization kinetics of incubation experiment were conducted. Woody BC 0%, 0.5%, 1.0% and 2.0% (w/w) made of lead tree (Leucaena leucocephala (Lam.) de. Wit) were added to an Oxisols, and two Inceptisols of Taiwan. In each treatment, 5% swine manure compost (2 times recommended amount) was added and served as the over-fertilized soil. The results indicated that soil type strongly influenced the impact of BC addition on soil carbon mineralization potential. Respiration per unit of total organic carbon (total mineralization coefficient, TMC) of three studied soils significantly decreased with BC addition increased. Principal component analysis (PCA) suggested that for retaining more plant nutrients in addition to the effects of carbon sequestration, it is recommended that farmer could use locally produced biochars and composts in highly weathered and highly frequent tillage soil. Adding 0.5%-1% woody BC in soil should be reasonable and appropriate.

In Taiwan, farmers often apply excess compost to ensure adequate crop yield in highly frequent tillage, highly weathered, and lower fertility soils. The potential of biochar (BC) for diminishing soil C mineralization, and improving soil nutrient availability in compost over-fertilized soil is promising, but the study is still under-examined. To test the hypothesis, 434 days in vitro C mineralization kinetics of incubation experiment were conducted. Woody BC 0%, 0.5%, 1.0% and 2.0% (w/w) made of lead tree (Leucaena leucocephala (Lam.) de. Wit) were added to an Oxisols, and two Inceptisols of Taiwan. In each treatment, 5% swine manure compost (2 times recommended amount) was added and served as the over-fertilized soil. The results indicated that soil type strongly influenced the impact of BC addition on soil carbon mineralization potential. Respiration per unit of total organic carbon (total mineralization coefficient, TMC) of three studied soils significantly decreased with BC addition increased. Principal component analysis (PCA) suggested that for retaining more plant nutrients in addition to the effects of carbon sequestration, it is recommended that farmer could use locally produced biochars and composts in highly weathered and highly frequent tillage soil. Adding 0.5%-1% woody BC in soil should be reasonable and appropriate.

Demand response flexible loads can provide fast regulation and ancillary services as reserve capacity in power systems. This paper proposes a joint optimization dispatch control strategy for source-load system with stochastic renewable power injection and flexible thermostatically controlled loads (TCLs) and plug-in electric vehicles (PEVs). Specifically, the optimization model is characterized by a chance constraint look-ahead programming to maximal the social welfare of both units and load agents. By solving the chance constraint optimization with sample average approximation (SAA) method, the optimal power scheduling for units and TCL/PEV agents can be obtained. Secondly, two demand response control algorithms for TCLs and PEVs are proposed respectively based on the aggregate control models of the load agents. The TCLs are controlled by its temperature setpoints and PEVs are controlled by its charging power such that the DR control objective can be fulfilled. The effectiveness of the proposed dispatch and control algorithm has been demonstrated by the simulation studies on a modified IEEE 39 bus system with a wind farm, a photovoltaic power station, two TCL agents and two PEV agents.

Background: Most prevalence surveys on nocturia have focused on older populations. This study aimed to measure the nocturia prevalence across the full spectrum of male adults living in Hong Kong, where severity and associated quality-of-life (QoL) were also explored. Methods: A cross-sectional population-based survey was conducted in men aged 18 or above using the ICIQ-NQoL Questionnaire. Results: With 1,239 respondents at age ranged 18-99, the overall nocturia prevalence were found to be 63.0% (ranged 41.6-84.6% at different age groups) and 31.2% (ranged 13.0-56.3% at different age groups), for ≥1 and ≥2 bedtime voiding episodes, respectively. The chance of nocturia was dramatically increased at age 60 or above while both prevalence and voiding frequency were increased with advancing age. About 83% of the nocturia men experienced 1-2 voiding episodes per night, but many of them had self-rated their QoL poor or very poor and indicated moderate-to-high bothersome. Younger men at age 18-39 were found to have high prevalence as 41.6% and almost 30% of them rated poor or very poor QoL. Conclusions: Nocturia was not only affecting the older populations but also caused significant bothersome and negative impacts on QoL in younger males.

This work investigated the isothermal holding time dependence of the densification, microstructure, weight loss and tensile properties of Fe-Mn-Si powder compacts. Elemental Fe, Mn and Si powder mixtures with a nominal composition of Fe-28Mn-3Si (in weight percent) were ball milled for 5h and subsequently pressed under a uniaxial pressure of 400 MPa. The compacted Fe-Mn-Si powder mixtures were sintered at 1200 ℃ for 0, 1, 2 and 3 h, respectively. In general, the density, weight loss and tensile properties increased with the increase of isothermal holding time. A significant increase in density, weight loss and tensile properties occurred in the compacts isothermally holding for 1 h, as compared to those with no isothermal holding. However, further extension of isothermal holding time (2 and 3 h) only played a limited role in promoting the density and tensile properties. The weight loss of the sintered compacts was mianly caused by the sublimation of Mn in Mn depletion region on the surface layer of the sintered Fe-Mn-Si compacts. The length of the Mn depletion region increased as isothermal holding time increased. A single α-Fe phase was detected on the surface of all the sintered compacts, and the locations beyond the Mn depletion region were comprised of a dual dominant γ-austenite and minor ε-martensite.

Previous studies implied the different behavioral intention formation of a specific object for individuals in different age groups, but few research to Chinese consumers’ sustainable fast fashion behaviour were found considering the enormous amount of consumption and waste of fast fashion products in China. Meanwhile, as a fast developing country, it might be insufficient to conduct research ignoring the consequences of different education level and growing environment among different generations. Thus, to generate in-depth and heuristic Chinese consumers information, this study developed proposed theoretical framework (TORA) based on research by Fishbein and Ajzen (1975), while the validity among Chinese consumers was tested as well. Following the TORA model, this study aims to investigate if consumers’ age will moderate the relationship between attitude and intention, and the relationship between subjective norms to behavioral intention. Through structural equation modelling in AMOS, it was found that the model has a well fit to large sample of Chinese consumers, while the moderation effect of age was not significant in the whole sample. Further hierarchical regression analysis conducted in SPSS and Process was able to locate the moderation effect of if divide the consumers into groups by age. Which is, age is significantly and positively moderating the path subjective norms to intention in younger generation (18-25), but significantly positive moderating attitude to intention in consumers aged 26-39. Implications in marketing and to policy makers are discussed at the end of this research.

Considering the spectrum shortage problem of IoT devices, we introduce a collaborative spectrum sensing (CSS) framework in this paper to identify available spectrum resources, so that IoT devices can access it and meanwhile avoid causing harmful interference to the normal communication of the primary user (PU). However, in the process of the PU’s signal detection in IoT devices, the issue about the stopping time and decision cost arises. To this end, we propose a distributed cognitive IoT model, which includes two IoT devices independently using sequential decision rules to detect the PU. On this basis, we define the stopping time and cost function for IoT devices, and formulate an average cost optimization problem in CSS. To solve this problem, we further regard the optimal stopping time problem as a finite horizon problem, and solve the threshold of the optimal decision rule by dynamic programming. At last, numerical simulation results demonstrate the correctness of our proposal in terms of the global false alarm and miss detection probability, and it always achieves minimal average cost under various cost of each observation taken and thresholds.

Despite the fact that SMA restrainers exhibit a superelastic strain capacity of 7%, this capacity appears inadequate for isolated bridges due to the typically greater than 20cm relative dis-placements between girders during intense seismic events. In order to perform such a stroke, a SMA restrainer of greater than 3 metres in length might be required. In order to reduce the length of restrainers, a novel honeycomb damper constructed from superelastic shape memory alloy (SMA) is proposed. The proposed device, denoted as the superelastic SMA honeycomb damper (SHD), is comprised of steel plates to prevent the SMA plane from collapsing and superelastic SMA honeycomb to provide self-centering capability. By incorporating the large strain capacity of SMA and the geometrically nonlinear deformation of honeycomb structures, SHD has been developed to satisfy the requirements of bridge restrainers with large strokes. It is capable of functioning as a restrainer and energy dissipation device when subjected to dynamic tension and compression loads. The SHD was initially investigated from a theoretical perspective. Following this, a mul-ti-cell SHD specimen was manufactured. The specimen underwent axial tensile and compressive experiments in order to examine the mechanical properties of SHDs. Finally, experimental results were investigated through numerical simulation analyses of the SHDs using a three-dimensional high-fidelity finite element model. Additionally, a method for enhancing SHD was proposed. The findings indicate that SHD is capable of exhibiting superior self-centering capability and sta-ble hysteretic responses when subjected to earthquakes.

Digital wellbeing concerns the balance and health we may experience in digital use, and the existing studies have focused on adolescents and adults. However, young children are more vulnerable to digital overuse and addiction than adults; thus, their digital wellbeing deserves empirical exploration. This scoping review synthesized and evaluated 35 collected studies on young children’s digital use and their wellbeing that were published until October of 2022 to understand the definitions, measurements, contributors, and interventions. The synthesis of evidence revealed that: (1) there was no consensus about its definition; (2) there were no effective measurements of young children’s digital wellbeing; (3) both child factors (duration and place of digital use, child demographic characteristics) and parent factors (digital use, parental perception, and mediation) contribute to young children’s wellbeing; and (4) there were some effective applications and interventions. This review contributes to the theoretical development by mapping the existing work on young children's digital wellbeing, proposing a model, and identifying the research gaps for future studies.

Gossypol is a complex plant polyphenol reported to be cytotoxic and anti-inflammatory, but little was known about its effect on gene expression in macrophages. The objective was to explore gossypol’s toxicity and its effect on gene expression involved in inflammatory responses, glucose transport and insulin signaling pathway in mouse macrophages. Mouse RAW264.7 macrophages were treated with multiple concentrations of gossypol for 2-24 h. Gossypol toxicity was estimated by MTT assay and soluble protein content. qPCR analyzed the expression of anti-inflammatory tristetraprolin family (TTP/ZFP36), proinflammatory cytokine, glucose transporter (GLUT) and insulin signaling genes. Cell viability was greatly reduced by gossypol, accompanied with dra-matic reduction of soluble protein content in the cells. Gossypol treatment resulted in an increase of TTP mRNA level 6-20 fold and increased ZFP36L1, ZFP36L2 and ZFP36L3 mRNA levels by 26-69 fold. Gossypol increased proinflammatory cytokine TNF, COX2, GM-CSF, INFγ and IL12b mRNA levels up to 39-458 fold. Gossypol treatment upregulated mRNA levels of GLUT1, GLUT3 and GLUT4 genes as well as INSR, AKT1, PIK3R1 and LEPR but not APP genes. This study demonstrated that gossypol induced macrophage death and reduced soluble protein content that was accom-panied with massive stimulation of anti-inflammatory TTP family and proinflammatory cytokine gene expression as well as elevation of gene expression involved in glucose transport and insulin signaling pathway in mouse macrophages.

This study is the first to investigate the asymmetric effects of oil price volatility on stock returns for the Ho Chi Minh Stock Exchange (HOSE). We utilized weekly series of VN30-Index, WTI crude oil prices, geopolitical risks (GPR) index and gold prices spanning from 6 February 2012 to 31 December 2023 as data sources. Using a nonlinear Autoregressive Distributed Lag (NARDL) bounds testing approach, we found that in the short-term, oil price volatility has negative asymmetric effects on the market returns. Specifically, in the short-term, a one percent increase in oil price volatility immediately leads to a 2,6868 percent decrease in the market returns while a similar magnitude decrease in oil price volatility is associated with 6.3180 percent increase in the market returns. In addition, the results obtained from the NARDL model indicated that, in the long-term, the negative and positive changes of oil price volatility have significantly negative effects on the market returns. Finally, the findings derived from the error correction model (ECM) show that 98.21 percent of the disequilibria from the previous week are converged and corrected back to the long-term equilibrium in the current week.

A sensitive electrochemical sensor based on AuPtPd trimetallic nanoparticles functionalized multi-walled carbon nanotubes coupled with chitosan modified glassy carbon electrode (GCE/CS/MWCNTs-AuPtPd) for the rapid detection of bisphenol A (BPA) was proposed. AuPtPd trimetallic nanoparticles were first assembled on MWCNTs to obtain MWCNTs-AuPtPd nanocomposite. Then the MWCNTs-AuPtPd was further dispersed on the surface of chitosan modified electrode surface to fabricate the GCE/CS/MWCNTs-AuPtPd sensor. Due to the superior catalytic properties of MWCNTs-AuPtPd and the good film formation of chitosan, the constructed sensor displayed good performances for BPA detection. The structural morphology of CS/MWCNTs-AuPtPd was characterized by many methods, such as SEM, UV-vis and TEM. Under the optimal conditions, the designed sensor showed a linear range from 0.05 to 100 µM for BPA detecting with a low detection limit of 1.4 nM. The designed sensor was further used to realize the determination of BPA in real samples and the recoveries ranged from 94.4% to 103.6%. The results demonstrated that the electrochemical sensor designed by CS/MWCNTs-AuPtPd nanocomposites was reliable and could be a useful tool for the monitoring of food safety.

Chinese divination of I Ching has a history of thousands of years. The six lines changes in 64 hexagrams have exceeded one billion scenarios, and the inherent laws among them have not been well revealed to this day. By using big data's technology and coin toss method, this paper simulates the change of 64 hexagrams, and explores the probability and proportion of each hexagram during the change from the perspective of quantification, as well as the maximum and minimum conversion rate of hexagram change. This paper summarizes the basic characteristics and the basic law of hexagram change, and accordingly constructs the spatial form of hexagram change, and reveals the hidden secrets of the ancient Book of changes (I Ching). To achieve this goal, we randomly toss three coins 600 million times to generate 100 million hexagrams. According to the basic rules of hexagram divination, we calculate the hexagram changes. The results showed that: (1) Changes of things are mostly simple changes. The probability of 1 billion randomly generated hexagrams from one to three dynamic lines is close to 80%. (2) About 17% of the 64 hexagrams have no dynamic lines, which means that a significant proportion of the 64 hexagrams are invariant. (3) Small probability changing hexagram certainty and large probability changing hexagram uncertainty. (4) After generating one billion hexagrams at random, the topographic map with the probability of changing hexagrams has axial symmetry and fractal geometric characteristics, and the fractal characteristics are mainly manifested in that the changes on both sides of the symmetry are presented based on the triangle background. These results reflect the obvious characteristics and internal regularity of the changes in the 64 hexagrams of the I Ching. This article provides new ideas for scientific exploration of the internal laws of the 64 hexagrams in the I Ching.

Green consumption has become a crucial academic and practical topic with the increasing environmental-protection awareness of scholars, industries and consumers. However, the growth in green purchasing may not reflect the concerns. This study aims to synthesize recent research, and points several causes of low purchases to green products in the consumer perspective, and provide a comprehensive understanding to the realistic consumer decision-making process. Through the scope of Consumer Buying Process framework, this study systematically reviewed 73 credible articles on green purchase behaviour published from 2010 to 2022. Main constructs and theories applied in selected literature is further discussed in each sector of the CBP framework. The study results showed the green purchase process may have a ‘loop tendency’ that falls into the circulation of construction of evaluation and adoption of those evaluation. Moreover, purchasing behaviour which performed by minority of the consumers may not be strong enough to form a valid social norm, and the current available still lacked power to fulfil consumer needs. The lack of research to impulsive purchasing behaviour, or the emotions of consumers are under-researched, thus how the emotional appraisals affect consumer green purchasing may require more research. With the modified consumer buying process framework, this study highlights the importance of creating memorable experience and build strong emotional communications with consumers. In addition, triggering the collective empathy is recommended to be an effective way of constructing consistent social norms thus enhance the green purchasing intention of consumers.

The ever-burgeoning growth of autonomous unmanned aerial vehicles (UAVs) has demonstrated a promising platform for utilization in real-world applications. In particular, UAV equipped with a vision system could be leveraged for surveillance applications. This paper proposes a learning-based UAV system for achieving autonomous surveillance, in which the UAV can be of assistance in autonomously detecting, tracking, and following a target object without human intervention. Specifically, we adopted the YOLOv4-Tiny algorithm for semantic object detection and then consolidated it with a 3D object pose estimation method and Kalman Filter to enhance the perception performance. In addition, a back-end UAV path planning for surveillance maneuver is integrated to complete the fully autonomous system. The perception module is assessed on a quadrotor UAV, while the whole system is validated through flight experiments. The experiment results verified the robustness, effectiveness, and reliability of the autonomous object tracking UAV system in performing surveillance tasks. The source code is released to the research community for future reference.

Paraphrase generation is an important yet challenging task in NLP. Neural network-based approaches have achieved remarkable success in sequence-to-sequence(seq2seq) learning. Previous paraphrase generation work generally ignores syntactic information regardless of its availability, with the assumption that neural nets could learn such linguistic knowledge implicitly. In this work we make an endeavor to probe into the efficacy of explicit syntactic information for the task of paraphrase generation. Syntactic information can appear in the form of dependency trees which could be easily acquired from off-the-shelf syntactic parsers. Such tree structures could be conveniently encoded via graph convolutional networks(GCNs) to obtain more meaningful sentence representations, which could improve generated paraphrases. Through extensive experiments on four paraphrase datasets with different sizes and genres, we demonstrate the utility of syntactic information in neural paraphrase generation under the framework of seq2seq modeling. Specifically, our GCN-enhanced models consistently outperform their syntax-agnostic counterparts in multiple evaluation metrics.

The potential adverse effects of coronavirus disease 2019 (COVID-19) vaccinations raise public concerns. Data from Taiwan’s Vaccine Injury Compensation Program (VICP) can provide valuable insights. This study analyzed preliminary application data for COVID-19 vaccine compensation in Taiwan’s VICP, focusing on applicants receiving vaccines between March 2021 and June 2022. Among the 2941 adverse events, 113 cases (3.8%) were deemed causally associated with vaccination, 313 (10.6%) were indeterminate, and 2515 (85.5%) had no causal association. Nearly half (47.6%) of applicants were over 60 years old, and 76.6% had a history of preexisting chronic dis-eases. Among the 426 vaccine-associated or indeterminate cases, the most common causes were hematological diseases and thrombosis. There were 920 mortality cases reported, and 97.4% were unassociated with vaccination. Only five deaths were judged to be associated with the COVID-19 vaccination, all involving the adenovirus vector vaccine and thrombosis with thrombocytopenia syndrome. In conclusion, most compensation applications were not causally linked to vaccination. Compared to other countries, the number of applications in Taiwan’s VICP is relatively high. These findings may indicate a need to adjust the application requirements for compensation in Taiwan’s program.

Miniature sensors are key components for the applications in the Internet of Things (IoT), wireless sensor networks, autonomous vehicles, smart cities and smart manufacturing. As a miniature and self-powered magnetic sensor, Wiegand sensor possesses the advantageous traits including changing-rate-independent output, low cost, and remarkable repeatability and reliability. Typical Wiegand sensor requires hard magnetic pole pieces that provide external fields for triggering voltage outputs that are called Wiegand pulses. However, the wire-shaped sensing element of Wiegand sensor is the critical issue that limits the design, selection, and adoption of the external triggering magnets. Currently, the widely used pole piece materials are rare-earth magnets. However, adopting rare-earth magnets brings strong stray fields, causing electromagnetic interference (EMI) problem. In this study, patterned CoNiP hard magnets were electrodeposited on flexible substrates through microfabrication. Origami magnetization was utilized to control the resultant stray fields, and hence the pole piece of CoNiP magnets can successfully trigger the output of Wiegand pulse. In comparison, the output voltage of the triggered pulse acquired through the patterned CoNiP magnets is comparable to that by using the rare-earth magnets. Furthermore, both the volume (meanwhile the weight) of the Wiegand sensor and the EMI issue can be significantly reduced and mitigated by the CoNiP magnets.

High-methoxyl apple pectin (AP) derived from apple was employed as the main ingredient facilitating rheological modification features for developing dysphagia-friendly fluidized alimentary matrices. Xanthan gum (XG) was also included as a composite counterpart to modify the viscoelastic properties of the thickened system under different thermal processes. The results indicate that AP is extremely sensitive to thermal processing, and the viscosity is greatly depleted under a neutral pH level. Moreover, the inclusion of calcium ions echoed a modification effect on the rheological properties of AP, and both the elastic property and viscosity value are promoted after thermal processing. The modification effect of viscoelastic properties (Gʹ and Gʹʹ) is observed while XG is incorporated into the composite formula. By promoting the XG ratio from 7: 3 to 6: 4 (AP: XG), it triggers the rheological transformation from a liquid-like form to a solid-like state, and the viscosity value shows that the AP-XG composite system exhibits better thermal stability after thermal processing. The ambient modifiers of pH (pH &lt; 4) and calcium chloride concentration (7.5%) with an optimal AP-XG ratio of 7:3 lead to weak-gel-like behavior (Gʹʹ &lt; Gʹ), helping to maintain the texture properties of dysphagia-friendly features similar to those prior to the thermal processing.

A fast and effective determination method of different species of vegetable seeds oil is vital in the plant oil industry. The near-infrared reflectance spectroscopy (NIRS) method was developed in this study to massively analyze the oil and moisture contents of Camellia gauchowensis Chang and C. semiserrata Chi seeds kernels. In the prediction models of NIRS, the levels of accuracy obtained were sufficient for C. gauchowensis Chang and C. semiserrata Chi, the correlation coefficient of which oil were 0.983 and 0.962, respectively, while which of moisture were 0.937 and 0.907, respectively. The near infrared spectrum of crush seeds kernels was more precise compared to intact kernels. Based on the calibration models of the two Camellia species, the NIRS predictive oil contents of C. gauchowensis Chang and C. semiserrata Chi seeds kernels were 48.71 ± 8.94% and 31.71 ± 7.39%, respectively, and the NIRS predictive moisture contents were 4.39 ± 1.08% and 3.49 ± 0.71%, respectively. Compared with the traditional chemical measurement, the rapid, precise measurement of oil and moisture of C. gauchowensis Chang and C. semiserrata Chi seeds kernels can be actualized by NIRS method.

Taiwan developing offshore wind power to promote green energy and self-electricity production. In this study, a Light Detection and Ranging (Lidar) was set up at Chang-Hua development zone one on the sea and 10km away from the seashore. At Lidar location, WRF (3.33km & 2km grid lengths) model and WAsP were used to simulate the wind speed at various elevations. Three days mean wind speed of simulated results were compared with Lidar data. From the four wind data sets, developed five different comparisons to find an error% and R-Squared values. Comparison between WAsP and Floating Lidar was shown good consistency. Lukang meteorological station 10 years wind observations at 5m height were used for wind farm energy predictions. The yearly variation of energy predictions of traditional and TGC wind farm layouts are compared under purely neutral and stable condition. The one-year cycle average surface heat flux over the Taiwan Strait is negative (-72.5 (W/m2) and 157.13 STD), which represents stable condition. At stable condition TGC (92.39%) and 600(92.44%), wind farms were shown higher efficiency. The Fuhai met mast wind data was used to estimate roughness length and power law exponent. The average roughness lengths are very small and unstable atmosphere.

Studying hydro-meteorological factors variations and its links to large-scale atmospheric circulation systems can facilitate the understanding of the hydrological processes and sustainable water resources management in the source region of the Yangtze River (SRYR). Currently, researches mostly focused on the temporal and spatial variation characteristics in hydro-meteorological factors; however, researches on the hydro-meteorological variations and its links to large-scale atmospheric circulation systems in the SRYR are scarce. Based on long-term hydro-meteorological and reanalysis data, this research investigated multiscale variations of hydro-meteorological factors and its links to large-scale atmospheric circulation characteristic indices during 1957~2012 in the SRYR. The results showed that the amounts of streamflows and precipitation in the SRYR declined during the 1990s. Since the 2000s, the amounts of streamflows and precipitation had increased significantly climate in the SRYR. The change trends of precipitation and streamflows in the SRYR are synergetic at annual and seasonal scales, and have three significant periods, namely 3~5 years, 15–20 years and 30–40 years. The South Asia monsoon (SAM) plays a relatively more important role in the hydro-meteorological factors changes in the SRYR. The relative contributions of SAM to streamflows and precipitation changes were 83.6% and 78%, respectively. During the driest (wettest) year, the SAM is relatively weak (strong), and brings less (more) southwest airflow into the SRYR, less (more) precipitation and streamflows will be generated in the SRYR.

The essence of cross-modal generation and retrieval modeling for image-text interactions lies in semantic consistency. Among these, cross-modal representation alignment serves as the foundational requirement for achieving cross-modal semantic consistency. The crux of our proposed method entails the collaborative training of an image captioning model(referred to as the ’captioner’) and a pair of contrastive encoders for image-text matching(referred to as the ’concoder’). This synergistic approach yields concurrent enhancements in concoder’s performance, captioner’s proficiency, and cross-modal semantic coherence. We coin the proposed method as ‘ReCap’. To begin, we initialize the concoder through knowledge distillation from a pre-trained model. During the training process, we use the output of the initialized concoder as input to a residual attention network, jointly training it with the captioner to achieve semantic consistency. Subsequently, we iteratively update the concoder during the image-text momentum encoding phase using the residual attention network, creating a closed-loop for semantic consistency resolution. Upon completion of training, the concoder and captioner modules can be used independently to perform tasks related to cross-modal retrieval and cross-modal generation of text and images. In order to substantiate the efficacy of our proposed method, we initially conducted empirical experiments encompassing image-text retrieval and image captioning tasks, employing a widely recognized benchmark dataset, MSCOCO. Subsequently, we assessed the fine-grained cross-modal alignment performance of the concoder through an image classification task on the iNaturalist 2018 dataset. The achieved performance metrics notably surpassed those achieved by several incumbent state-of-the-art models, thus validating the proficiency of our method. Finally, motivated by the practical requirements of handling the nature conservation image data, we performed caption annotation for the iNaturalist 2018 dataset. Subsequently, we trained the ReCap on this annotated data. Experimental results demonstrate that our proposed method can maintain semantic consistency between cross-modal retrieval and image caption generation for species with similar visual features but distinct semantics. This achievement signifies a meaningful exploration in the field of cross-modal semantic consistency representation, holding significant practical value in the domain of biological research.

In the contemporary era, youthful and healthy skin is a pivotal determinant of beauty. Choices pertaining to one's dietary and lifestyle practices wield substantial influence over skin health. Currently, the focal point of attention lies in strategies to delay skin aging and maintain skin quality. Remarkably, the skin, the body's largest organ, serves as the primary defense barrier against external elements. Skin aging encompasses intrinsic and extrinsic categories, both susceptible to genetic, lifestyle, and environmental factors. Given the strides in science and technology, the pursuit of effective and safe interventions for skin aging assumes paramount importance. Thus, this review delves into the intricate relationship between diet, lifestyle, and skin aging, culminating in an exploration of the crucial role played by excess iron in this intricate nexus. Understanding these dynamics holds promise for advancing our knowledge of skincare and the quest for timeless vitality.

A recent study found that a 3ppb increase in O₃ ambient concentration was associated with an increased progression of 0.18 percentage points in percent emphysema and that such increase was equal to smoking 20 cigarettes per day for 29 years. A simple estimation of population attributable fraction shows that COPD diagnoses due to smoking are actually 30 times more than those attributed to a 3 ppb increment in O₃ concentration. Labelling ozone pollution as the new smoking may distort perception of the risks and hinder proper response to real life threatening risk such as smoking.

Wearable sensors for human physiological monitoring have attracted tremendous interest from researchers in recent years. However, most of the research was only done in simple trials without any significant analytical algorithms. This study provides a way of recognizing human motion by combining textile stretch sensors based on single-walled carbon nanotubes (SWCNTs) and spandex fabric (PET/SP) and machine learning algorithms in a realistic applications. In the study, the performance of the system will be evaluated by identification rate and accuracy of the motion standardized. This research aims to provide a realistic motion sensing wearable products without unnecessary heavy and uncomfortable electronic devices.

Climate and land use changes are major factors affecting runoff in regional basins. Understanding variation by considering interactions among hydrological components is an important process for water resource management. This study aimed to assess the variation of future runoff in the Upper Chi Basin, Northeastern Thailand. QSWAT hydrological model was integrated to 3 CMIP6 GCMs including ACCESS-CM2, MIROC6, and MPI-ESM1-2-LR under SSP245 and SSP585 scenarios during 2023 – 2100. Land Change Modeler (LCM) was also used for future land use simulation. The results revealed that future average of long-term precipitation and temperature tended to increase while forest land tended to decrease and be replaced by sugarcane plantations. The accuracy assessment of baseline year runoff calculation by QSWAT during 1997 – 2022 showed acceptable result as can be seen from R2, NSE, RSR, and PBIAS indices. This result could lead to temporal and spatial simulation of future runoff. Likewise, runoff of 2 SSPs scenarios tended to increase consecutively, especially in SSP585 scenario. In addition, in case of long-term spatial changes in the subbasins scale, over 90% of the area, from upstream to outlet point, tended to get higher due to 2 major factors including future increased precipitation and changes in cultivation, which would be influential to groundwater and interflow components respectively. Methodology and result of this study can be useful to stakeholders in understanding changes in hydrological system so that they can apply it to develop a strategy for water resource management and handling factors affecting different dimensions properly and sustainably.

COS production is carried out enzymatically using chitosanase, but this process is expensive. Production costs can be reduced by using crude enzyme chitosanase, and the resulting COS has depolymerization &lt; 20 and molecular weight &lt; 3900 Da. Sources of crude enzyme chitosanase come from the soil, sediment, and fishery waste. Chitosanase is produced from bacteria and molds isolated from the source or direct isolation process for extracellular enzymes, especially from fishery waste. Microorganisms in the soil produce chitosanase as a biocontrol and self-defense agent. Bacteria and molds have been isolated, including Bacillus cereus, Bacillus mycoides, Paenibacillus sp., and Penicillium janthinellum. Fishery waste, especially parts of the digestive tract, is a source of chitosanase because of its relation to its nature and food, such as small fish, frogs, and several types of crustaceans. In addition, fishery waste can be used as a carbon and nitrogen source (C/N) in microorganism culture media. The chitin content becomes a stimulant for the synthesis of chitosanase by microorganisms. Crude enzyme chitosanase has an active site that hydrolyzes chitosan by breaking glycosidic bonds and producing glucosamine units (GlcN) and N-acetyl glucosamine (GlcNAc). This mechanism can take place through two events, namely inverting and retaining. Crude enzyme chitosanase can break glycosidic bonds, especially with the same groups, for example, bonds between glucosamine or N-acetyl glucosamine. The COS produced is of the partially acetylated COS (paCOS) type, which still contains an acetyl group. The degree of deacetylation is a significant factor in the resulting COS product, COS with the fully deacetylated COS (fdCOS) type of chitosan with a high degree of deacetylation. Other factors to consider are the raw material of chitosan, the incubation time, the screening process, and the production of microorganism cultures.

Let a,b,c be positive integers such that a²+b²=c², 2|b,gcd(a,b)=1. In 1956, Jesmanowicz conjectured that for any positive integer w, the only solution of (aw)^x+(bw)^y=(cw)^z in positive integers is (x, y, z) = (2, 2, 2). In this paper, based on Gaussian integer ring, we show that Je$\acute{s}$manowicz' conjecture is true for any positive integer

Epithelial–mesenchymal transition (EMT) is defined as a cellular process during which epithelial cells acquire mesenchymal phenotypes and behavior following the downregulation of epithelial features. EMT and its reversed process, the mesenchymal-epithelial transition (MET), and the special form of EMT, the endothelial-mesenchymal transition (EndMT), have been thought as a universal dogma controlling developmental and pathological processes. More than half a century of EMT study has made it a large research field and a mainstream concept. However, discrepancies and disputes over EMT and EMT research have also grown over time. Particularly, neither the epithelial and mesenchymal states/properties nor their regulatory networks nor specific markers have been defined, rendering the EMT, MET and EndMT concepts groundless. Moreover, EMT and MET effects should not be a cause, but rather a consequence of or an accompanying effect during developmental and pathological processes. EMT and MET represented by the change in cell shapes or adhesiveness or symbolized by EMT factors are biased interpretation of the overall change in cellular property and regulatory networks during development and cancer progression. The true meaning of EMT effects in some developmental and pathological processes, such as fibrosis, needs re-evaluation. But the core EMT factors are actually a few components of the regulatory networks of neural stemness, which determines tumorigenicity and pluripotency. The EMT effects in cancer progression and neural crest formation are wrong attribution of the role of neural stemness during cancer progression and the cell-intrinsic property of neural crest cells to the unknown mesenchymal state. It is time to reassess the significance of EMT and its related concepts in scientific research.

There is a noticeable absence of health education among college students. This study aimed to evaluate the extent of general nutrition knowledge among Chinese university students and explore its association with eating attitudes. Data were collected from a group of 273 students in Spring of 2023, using a valid and reliable research instrument consisting of three sections: demographic variables, the General Nutrition Knowledge Questionnaire (GNKQ), and the Eating Attitudes Test (EAT-26). The results were analyzed using SPSS, with correlations and t-tests to examine the relationships between nutritional knowledge and dietary attitudes. Furthermore, the present study employed the Random Forest (RF) algorithm, a machine learning technique, utilizing the Mean Decrease Impurity (MDI) method to investigate the influence of various features on participants' eating attitudes. The findings revealed that Chinese university students had an average accuracy of over 60% in their nutritional knowledge, but their understanding of the relationship between diet and disease still needs improvement. Moreover, male students had significantly lower nutritional knowledge than female students, and there was a positive correlation between nutritional knowledge and parents’ income. The study also found a significant correlation between the level of nutritional knowledge and eating attitudes. RF results indicated that family income level exhibited the most substantial impact on the eating attitudes of the participants. The study highlights the need for nutrition education curriculum developers to focus more on improving students' nutritional knowledge, with particular attention given to male students, low-income individuals, and those with an abnormal BMI.

Suitable soil structure and nutrient security are important for plant growth and development, characteristics of soil fractal dimension and distribution of physical and chemical properties and their interactions play an important role in studying the stability of soil structure and water and fertilizer cycles. As a sustainable management model, intercropping has positive benefits for erosion control, spatial optimization of resources, as well as improving system productivity. The effects of four intercropping methods on soil fractal dimension and physicochemical properties were investigated by intercropping Salvia miltiorrhiza with forage and S. miltiorrhiza with forest under typical karst rock desertification habitats in Guizhou. The results showed that soil nutrient content of intercropping was significantly higher than that of monoculture, the organic carbon content of soil grown under forest is higher than other treatments, and there was a non-significant change in soil water content of intercropping compared with monoculture. The soil fine-grained matter of intercropping was significantly higher than that of monoculture, while the soil fractal dimension showed a tendency to become larger with the increase of fine-grained matter. The intercropping planting, due to its component types and spatial and temporal configurations, leads to differences in soil water and fertilizer interactions, which can be combined with other ecological restoration measures to optimize the composite model and jointly promote the restoration and development of ecologically fragile areas.

This study explores the public library service evaluation domain through user-generated content on Google Maps, highlighting digital feedback's significant yet underexplored potential in understanding public library patronage across Taiwan's six major cities. Utilizing a mixed-methods research design, this study integrates Google Maps review content analysis with Social Network Analysis to delineate public perceptions and identify areas for service enhancement in public libraries. It innovatively leverages personal experiences extracted from over 60,000 Google Maps reviews to evaluate public library services in cities such as Taipei, New Taipei, Taoyuan, Taichung, Tainan, and Kaohsiung. The research taps into the National Library of Taiwan's National Library Statistics System to provide a robust analysis of library performance and user satisfaction, offering a novel perspective by emphasizing user-centric feedback from Google Maps as a primary data source. This approach provides quantitative data on library usage and geographic distribution and enriches our understanding of the qualitative experiences of library users. In analyzing the keywords from Google Maps reviews of public libraries, we categorize and interpret these under the three core LibQUAL+ dimensions—Affect of Service, Information Control, and Library as Place. The findings expose variances in perceived service quality among the cities, with Kaohsiung and Taichung receiving the highest accolades for service satisfaction. Simultaneously, the study identifies potential areas for improvement, particularly in cities with lower satisfaction ratings like Taipei. This personalized feedback illustrates the intimate relationship between public libraries and their communities, offering invaluable insights for policymakers and library management to enhance service delivery and user experience.

Current-voltage characteristics curves of NFinFET are presented and are fitted with the modi-fied current-voltage (I-V) formulas, where the modified term in the triode region is demon-strated to be indispensable. In the as-known I-V formula, important parameters need determin-ing to make both the measured data and the fitting data as close as possible. Those parameters include kN (associated with the sizes of the transistor and mobility), (associated with Early Voltage), and Vth (the threshold voltage). The differences between the measured data and the fit-ting data vary as the applied source-drain bias, proving that the mobility of the carriers is not consistently constant. On the other hand, a modified formula, called kink effect factor, is nega-tively or positively added simulating solitary heat waves, which disturb the propagation of car-riers and thus influence the Source-Drain current (IDS). The new statistical standard deviations () are then found to be effectively suppressed as the kink effect is taken into account.

Building sustainable campuses has become a priority for various higher education institutes (HEIs). Internalization is one of the important tasks in the progress. Therefore, attracting and maintaining international faculty has converted to action for various internationalized campuses. During the COVID-19 pandemic, it has impacted most of the citizens’ life, while the international faculty members’ life might be tight during this period. The purpose of this study is to explore the perspectives of international faculty members on their life in higher education institutes by using partial least square structural equation modeling (PLS-SEM). Using a self-compiled online survey, we invited 80 international faculty members of HEIs in Taiwan to investigate this issue. The survey covers career and professional status, teaching and research status, and demographics of the faculty. This study proposes a novel conceptual framework for addressing international faculty’s campus life, the design will examine the relationships among working conditions, views of institutions, views of government’s measures, and levels of satisfaction through PLS-SEM. The demographic profile of the participants revealed (a) most international faculty are employed full-time as lecturers or assistant professors in most public universities; (b) most international faculty members earned their first degree outside of Taiwan; however, 66% of them earned their post-doctoral degrees in Taiwan. The results of PLS-SEM suggest that the international faculty perspective of government is more directly related to their current work satisfaction and overall satisfaction. The designed model has shown work well to assess this issue. This can be extended to other higher education settings to tackle similar issues.

In order to better plan new or update sewer pipe condition assessment protocols, this paper presents systematic comparisons of four most widely-used sewer condition assessment protocols, including the fourth edition of Sewer Rehabilitation Manual (SRM-4) in UK, Pipeline Assessment and Certification Program (PACP) in America, Sewer Physical Condition Grading Protocols (SPCCM) in Canada, and Technical Specification for Inspection and Evaluation of Urban Sewer (TSIEUR) in China. In qualitative comparison, the defects, deduct values and assessment methods of the four protocols were analyzed; in quantitative comparison, protocols were used to evaluate the same 182 sewer pipe segments based on field data and the assessment results were compared. It was found that SRM-4 are the most optimistic with 59% pipes being Grade 1 and Grade 2, while SPCCM gives the most pessimistic results with 62% pipes being Grade 3 and Grade 4. Assessment results by PACP and TSIEUR are in the middle. The main reasons for the different evaluation results were due to the different weight of defect and evaluation methods used.

In this paper, a semi-empirical model of air waves induced by falling rock is described. The model is composed of a uniform motion phase (velocity close to 0 m·s^-1) and an acceleration movement phase. The uniform motion phase was determined based on experimentally and the acceleration movement phase was derived by theoretical analysis. A series of experiments were performed to verify the semi-empirical model and elucidated the law of the uniform motion phase. The acceleration movement phase accounted for a larger portion with a greater height of the falling rock. Experimental results of different falling heights of the goaf showed close agreement with theoretical analysis values. The semi-empirical model could accurately and conveniently estimate the velocity of air wave induced by falling rock. Thus, the semi-empirical model can provide a reference and basis for estimating the speed of air waves and designing protective measures in mines.

Abiotic stress is a significant factor restricting the normal growth and development of plants. Under abiotic stress, plants maintain their life and continuous growth by reconfiguring transcriptional regulation and metabolic networks. In recent years, with the development of sequencing technology and mass spectrometry technology, transcriptomics and metabolomics have emerged as new disciplines following genomics and proteomics, which are conducive to identifying metabolites and regulatory genes in plants under abiotic stress. In this review, we mainly analyzes the technical characteristics, advantages, and disadvantages of transcriptomics and metabolomics, focusing on reviewing the research progress in the field of plant responses to abiotic stress (temperature stress, salt stress, water stress, and heavy metal stress) using transcriptomics and metabolomics both domestically and internationally in recent years. It also provides a prospective view on current issues, which helps accelerate the understanding of the mechanisms of plant responses to abiotic stress and provides new ideas for breeding stress-resistant varieties in the future.

The pharmacological effects of the fruiting body of Ophiocordyceps sinensis (Os) exerted antioxidant, anti-virus, and immunomodulatory, whereas the anti-inflammatory effects and active components of Os mycelial submerged culture (OMSC) are not known. This study aimed to investigate the active compounds in the fermented liquid (FLOS), hot water (WEOS), and 50-95% (EEOS-50, EEOS-95) ethanol extracts of OMSC and their anti-inflammatory effects and potential mechanisms in LPS-stimulated microglial BV2 cells. The results demonstrated that all of the OMSC extracts could inhibit NO production in BV2 cells. EEOS-95 exhibited the strongest inhibitory effects (41 % inhibitory ability at 500 µg/mL), and its ergosterol, GABA, total phenolic, and total flavonoid contents were significantly higher than those of the other extracts (18.60, 18.60, 2.28, and 2.14 mg/g, p &lt; 0.05, respectively). EEOS-95 also has a strong inhibitory ability against IL-6, IL-1β and TNF-α with IC50 of 617, 277 and 507 µg/mL, respectively, which is higher than that of 1 mM melatonin. The anti-inflammatory mechanism of EEOS-95 seems to be associated with up-regulation of PPAR-γ/Nrf-2/HO-1 antioxidant-related expression and down-regulation of NF-κB/COX-2/iNOS pro-inflammatory expression signaling. Therefore, we hypothesized that EEOS-95 can prevent neurodegenerative diseases, but the effect on the application in vivo should be further investigated.

Timely and accurate information on tree species is crucial for the sustainable management of natural resources, forest inventory, biodiversity detection, and carbon stock calculation. The advancement of remote sensing technology and artificial intelligence has facilitated the acquisition and analysis of remote sensing data, resulting in more precise and effective classification of tree species. Multimodal remote sensing data and deep learning seem to be the current tree species classification research mainstream, whether or not. The current review on the remote sensing data and deep learning tree species classification methods perspectives to analyze the unimodal and multimodal remote sensing data and classification methods in this realm is missing. To bridge the gap, we search for major trends in the remote sensing data and tree species classification methods, provide a detailed overview of classic deep learning-based methods for tree species classification, and discuss the limitations.

Despite several decades’ effort to detect and identify phytoplasmas (Tenericutes: Mollicutes) using PCR and Sanger sequencing focusing on diseased plants, knowledge of phytoplasma biodiversity and vector associations remains highly incomplete. To improve protocols for documenting phyto-plasma diversity and ecology, we used DNA extracted from phloem-feeding insects and com-pared traditional Sanger sequencing with a next-generation sequencing method, Anchored Hy-brid Enrichment (AHE) for detecting and characterizing phytoplasmas. Among 22 of 180 leaf-hopper samples that initially tested positive for phytoplasmas using qPCR, AHE yielded phyto-plasma 16Sr sequences for 20 (19 complete and 1 partial sequence) while Sanger sequencing yield-ed sequences for 16 (11 complete and 5 partial). AHE yielded phytoplasma sequences for an addi-tional 7 samples (3 complete and 4 partial) that did not meet the qPCR threshold for phytoplasma positivity or yielded non-phytoplasma sequences using Sanger sequencing. This suggests that AHE is more efficient for obtaining phytoplasma sequences. Twenty-three samples with sufficient data were classified into eight 16Sr subgroups (16SrI-B, I-F, I-AO, III-U, V-C, IX-J, XI-C, XXXVII-A), three new subgroups (designated as 16SrVI-L, XV-D, XI-G) and three possible new groups. Our results suggest that screening phloem-feeding insects using qPCR and AHE sequencing may be the most efficient method for discovering new phytoplasmas.

This study explores the significance of active suspension systems for vehicles with lower chassis compared to conventional ones, aiming at the development of future automobiles. Conventional linear MR (Magneto-Rheological) dampers were found inadequate in ensuring sufficient vibration control because the vehicle's chassis becomes lowered in the unmanned vehicles or purposed based vehicles. As an alternative, a rotary type of MR damper is proposed in this work. The proposed damper is designed based on pre-specified design parameters through mathematical modeling and magnetic field analyses. Subsequently, a prototype of the rotary MR damper identical to the design is fabricated, and effectiveness is shown through experimental investigations. In configuring the experiments, a proportional-integral (PI) controller is employed for current control to reduce the response time of the damper. The results presented in this work provides useful guidelines to develop a new type of MR damper applicable to various types of future vehicles’ suspension systems with low distance from the tire to the body floor.

The aim of the experiment was to determine the effect of strontium oxide addition on zirconium silicate recrystallization when adding strontium oxide to the glaze composition. Zirconia glazes (4 different contents) were prepared to which strontium oxide was added in amounts of 0, 1, 3, 6, and 12 mass%. SrO. The characteristic temperatures of the raw glazes were measured, based on which the maximum firing temperatures were determined. The fired glazes were subjected to study of the phase composition and observation of the microstructure. Analysis of the characteristic temperatures showed a fluxing effect, but it was not as strong for all glazes. Differences in the amount of the crystalline phase of zirconium silicate obtained in fired glazes and the partial transition of zirconium silicate to the amorphous phase were observed. Observations of the microstructure clearly indicated an increase in the homogeneity of the distribution of zirconium silicate.

The development of innovative materials is one of the most important focuses of research in heritage conservation. Eligible materials can not only protect the physical and chemical integrity of artworks, but also preserve their artistic and aesthetic features. Recently, as one of the hot research topics in materials science, biomimetic superhydrophobic materials have gradually attracted the attention of conservation scientists due to their unique properties. In fact, ultra-repellent materials are particularly suitable for hydrophobization treatments on outdoor artworks. Owing to their excellent hydrophobicity, superhydrophobic materials can effectively prevent the absorption, penetration of liquid water as well as the condensation of water vapor, thus greatly relieving water-induced decay phenomena. Moreover, in presence of liquid water, the superhydrophobic surfaces equipped with self-cleaning property can clean the dirt, dust deposited spontaneously, thereby restoring the artistic features simultaneously. In the present paper, besides the basic principles of wetting on solid surfaces, materials and methods reported for preparing bioinspired ultra-repellent materials, the recently proposed materials for art conservation are also introduced and critically reviewed. Lastly, the current status and the problems encountered in practical application are also pointed out, and the focus of future research is prospected as well.

Predators are dependent on the capture of prey to meet their energetic and nutritive requirements, imposing a regime of predation risk. Consequently, prey experience both consumptive and non-consumptive effects. Non-consumptive effects may manifest through altered growth and ontogenetic trajectories of prey species, a dynamic modulated by olfactory or other sensory cues from predators. Bactrocera dorsalis Hendel represents a great invasive threat to global horticulture. While earlier research has primarily centered on the consumptive interactions between B. dorsalis and its natural enemies, the potential consequences of non-consumptive interactions on the development of B. dorsalis have been overlooked. In this study, we investigated the impact of predation risk effects, induced by both visual exposure to the predatory mantis Hierodula patellifera Serville and its associated odor, on the life history traits of B. dorsalis. Female B. dorsalis demonstrated reduced development time in the presence of isolated H. patellifera or H. patellifera odor, yet evidenced significantly increased fecundity. Conversely, males displayed no significant change in development time. Additionally, neither female nor male body weight at death was significantly influenced by predation risk from isolated predators or predator odor. These results indicated adaptive developmental strategies of B. dorsalis when faced with risks from predators and highlight the important role of predator odor, which has the potential to lay the groundwork for improving biological control efforts and innovative approaches within pest control.

Dynamical manipulation of plasmon-induced transparency (PIT) in graphene metasurfaces is promising for optoelectronic devices such as optical switching and modulating, however, previous design approaches are limited within one or two bright/dark modes, and the realization of dual PIT windows through triple bright modes in graphene metasurfaces is rare and urgently needed. Here we demonstrate that dual PIT can be realized through a symmetry-engineered graphene metasurface, which consists the graphene central cross (GCC) and graphene rectangular ring (GRR) arrays. The GCC supports a bright mode from electric dipole (ED), the GRR supports two nondegenerate bright modes from ED and electric quadrupole (EQ) due to the C2v symmetry breaking, and the resonant coupling of these three bright modes induces the dual PIT windows. A triple coupled-oscillator model (TCM) is proposed to evaluate the transmission performances of the dual PIT phenomenon, and the results are in good agreement with the finite-difference time-domain (FDTD) method. In addition, the dual PIT windows are robust to the variation of the structural parameters of the graphene metasurface except the y-directioned length of the GRR. By changing the carrier mobility of graphene, the amplitudes of the two PIT windows can be effectively tuned. The alteration of the Fermi level of graphene enables the dynamic modulation of the dual PIT with good performances for both modulation degree (MD) and insertion loss (IL).

The divination function of China's Yijing has led to its circulation for thousands of years. In our exploration of Yijing's characteristics using big data, we have discovered variations in results between the coin toss method and the ancient yarrow-stalk method of divination, known as "the number for the great expansion method of divination(大衍之数)". The yarrow-stalk method serves as the fundamental method of divination in Yijing and continues to hold significance in studying the essential characteristics of Yijing. Despite the complexity of yarrow calculations, advancements in computer technology and big data have simplified its application. By employing the yarrow-stalk method, we simulated changes in the 64 hexagrams, calculated probabilities and proportions of hexagram alterations, and derived fundamental characteristics and patterns of hexagrams. Additionally, we constructed the spatial representation of lines and hexagrams. Through a binary system rearrangement, we created a 64x64 matrix illustrating hexagram transformations. Subsequently, we generated 100 million random hexagrams and analyzed line and hexagram changes accordingly. Our findings indicate the following:(1) Big data analysis reveals evident asymmetry in the hexagrams obtained through the yarrow-stalk method, with a triangular fractal characteristic forming the background.(2) Each of the 64 hexagrams exhibits a distinct probability distribution when transforming into other hexagrams, which can be categorized into five types.(3)The occurrence probabilities of Laoyang, Laoyin, Shaoyang, and Shaoyin are 18.61%, 6.387%, 31.38%, and 43.62% respectively. The probabilities of Yin and Yang occurrences are nearly equal, each close to 50%. However, the probability of Laoyang is approximately three times higher than that of Laoyin.(4) Visualized and analyzed the characteristics of hexagram changes greater than 100000 times using 3D statistical maps and Sankey diagram.These results demonstrate that the yarrow-stalk method effectively unveils the characteristics and underlying patterns of the 64 hexagrams. This study provides a novel approach for scientifically exploring the internal laws governing the 64 hexagrams in Yijing.

There has been a growing awareness of the need to implement environmentally friendly operations in the hotel industry, but most studies focus on guest behaviors. Only a few studies investigate employees’ willingness to comply with hotels’ green practices. This study seeks to further the investigation from the human resource perspective. Using alumni from a tourism and hospitality programs, this study collected 233 responses. The study hypothesizes that the employees’ green ability consisting of environmental awareness, environmental knowledge, and environmental skill creates a positive impact on hotels’ green ability. The results indicate that employees contribute approximately a fifth of hotels’ ability to implement greener practices.

This paper takes the VR animation display of the Ming Xiao Mausoleum General stone statue life as an example to study the advantages of VR animation in the display of material heritage. Combined with literature and pictures, the digital restoration of the Ming Xiao Mausoleum stone statue is carried out in MAYA and Z brush, and the construction of the scene and the output of the final effect are realized in UE4.

Automated machine classifications of galaxies are necessary because the size of upcoming surveys will overwhelm human volunteers. We improve upon existing machine classification methods by adding the output of SpArcFiRe to the inputs of a machine learning model. We use the human classifications from Galaxy Zoo 1 (GZ1) to train a random forest of decision trees to reproduce the human vote distributions of the Spiral class. We prefer the random forest model over other black box models like neural networks because it allows us to trace post hoc the precise reasoning behind the classification of each galaxy. We find that, across a sample of 470,000 Sloan galaxies that are large enough that details could be seen if they were there, the combination of SpArcFiRe outputs with existing SDSS features provides a better machine classification than either one alone on comparison to Galaxy Zoo 1. We suggest that adding SpArcFiRe outputs as features to any machine learning algorithm will likely improve its performance.

Recently, various applications of indoor location-based services using Wi-Fi fingerprint data have been studied. However, since fingerprint data collected at a specific location does not have continuous information between signals and correlation information between signals, path data cannot exist in principle. Therefore, most indoor positioning technologies are based on predicting the position of a stationary positioner at a specific location based on signal data collected at a specific location in the indoor space. Due to the discontinuous nature of these signals, they are unable to account for user movement. Therefore, there is a need for techniques to improve the accuracy of indoor positioning in moving situations. This paper proposes a method for enriching all data points with relevant information to obtain improved indoor positioning results and an improved technique for generating movement path data. The proposed technique generates relevant information with continuity by expressing data points as Bounding Boxes (BB) and subsequently clustering them using grid cells. Through the proposed method, we represented and expanded the indoor location data, which consists of data points, as BB. However, data points represented by BB do not have any adjacency information with each other, and as a result, it is not possible to create a movement path between neighboring BB. To solve the problem, we used clustering, a machine learning technique that categorizes data points into groups, to group BBs. This was done by constructing a YOLO (You Only Look Once) grid cell that included all BBs and clustered them into grid cells that were divided into specific regions through the suggestion phase. The clustering results align with the indoor structure of the building, indicating that the data points have been appropriately clustered. BBs inside a grid cell are contained within a moveable area and have related information. We also generated association information between neighboring grid cells through the proposal technique, and then generated path information that can be traveled between grid cells. In this paper, we use the movement path information generated from a dataset as training data for machine learning, and through this, we propose an enhanced indoor positioning technology.

Abstract: Objectives: To establish the expression profile of N6-methyladenosine(m6A) modifications in the hippocampus of mice with diabetic cognitive impairment (DCI) and elucidate the potential regulatory mechanism. Methods: A DCI model was established by feeding a high-fat diet to C57BL/6J mice. m6A and RNA sequencing was conducted to profile the m6A-tagged transcripts in the hippocampus. Results: Methylated RNA immunoprecipitation with next-generation sequencing and RNA sequencing analyses yielded differentially m6A-modified and expressed genes in the hippocampus of DCI mice, which were enriched in pathways involving synaptic transmission and axonal guidance. Mechanistic analyses revealed a remarkable change in m6A modification levels through alteration of the mRNA expression of m6A methyltransferases (METTL3 and METTL14) and demethylase (FTO) in the hippocampus of DCI mice. Conclusions: We identified a co-mediated specific RNA regulatory strategy that broadens the epigenetic regulatory mechanism of RNA-induced neurodegenerative disorders associated with metabolic and endocrine diseases.

Aiming at the limitations of single-functionality, limited applicability, and complex designs prevalent in current metasurfaces, we propose a terahertz multifunctional and multiband tunable metasurface utilizing a VO2-metal hybrid structure. This metasurface structure comprises a top VO2-metal resonance layer, a middle polyimide dielectric layer, and a gold film reflective layer at the bottom. This metasurface exhibits multifunctionality, operating independently of polarization and incident angle. The varying conductivity states of the VO2 layers, enable the metasurface to achieve various terahertz functionalities, including single-band absorption, broadband THz absorption, and multiband perfect polarization conversion for linear (LP) and circularly polarized (CP) incident waves. Finally, we believe that the functional adaptability of the proposed metasurface expands the repertoire of options available for future terahertz device designs.

An oceanic radar altimeter such as TOPEX/Poseidon (T/P) is typically for observing elevation changes over the open oceans or large inland lakes/rivers, with limited applications over solid earth due to its large footprint and susceptibility to waveform contamination and slope effect. Here we demonstrate that it is possible to construct a long-term time series of glacier elevation change from T/P-series radar altimeters over two flat surfaces near a glacier terminus and an icefield (Sites A and B, with slopes of 2° and 0.8°) in Mt. Tanggula, Tibet, at elevations over 5400 m. We retracked radar waveforms using the subwaveform threshold algorithm, selected quality altimeter data (1/4 of the original) with nearly the same slope and adjusted the original elevations by fitting with a time-varying, 2nd order surface. The glacier elevation changes at the two sites from T/P (1993–2002) show seasonal elevation oscillations with linear rates at about −3 m/year and abnormal seasonal changes around the 1997–98 El Niño. Site A is over a deep valley in southern Tanggula. Its elevation dropped about 30 m over 1993–2002 (from T/P) and the glacier almost disappeared by 2016 (from altimeters and satellite images). Despite the sporadic Jason-2 and Jason-3 altimeter data, we also derived long-term rates of glacier elevation change over 1993–2017. Landsat-derived glacier area and elevation changes near the two sites confirm the rapid glacier thinning from the altimeters. The glacier meltwater near Site A supplied increasing source water to Chibuzhang Co west of Mt. Tanggula, contributing partially to its accelerated rising lake level. The glacier thinning at Site B (icefield) was correlated with the increased discharge of the Tuotuo River in eastern Mt. Tanggula, a source region of the Yangtze River. The successful detection of glacier thinning at the two sites shows that T/P-series altimeters can serve as a virtual station at a flat glacier spot to monitor long-term glacier elevation changes in connection to climate change. This virtual station concept is particularly useful for inaccessible glaciers, but its implementation faces two challenging issues: increasing the volume of quality altimeter data and improving the ranging accuracy over a targeted mountain glacier spot.

This study was to identify clinical cancer biomarkers for recurrent gastric cancer survivors using artificial intel-ligence. From a hospital-based cancer registry database in Taiwan, the datasets of the incidence of recurrence and clinical risk features were included in 2476 gastric cancer survivors. We benchmarked Random forest with MLP, C4.5, AdaBoost, and Bagging algorithms on metrics and leveraged synthetic minority oversampling technique (SMOTE) for imbalanced dataset issues, cost-sensitive learning for risk assessment, and SHapley Additive ex-Planations (SHAP) for feature importance analysis in this study. Our proposed Random forest outperformed the other models with an accuracy of 87.9%, a recall rate of 90.5%, an accuracy rate of 86% and F1 of 88.2% on re-current category by a 10-fold cross-validation in a balanced dataset. We identified clinical features of recurrent gastric cancer, which are the top five features, stage, number of regional lymph node involvement, Helicobacter pylori, BMI(body mass index), and gender, which significantly affect the prediction model's output, are worth paying attention to in the following causal effect analysis. Using an artificial intelligence model, the risk factors for recurrent gastric cancer could be identified and cost-effectively ranked according to their feature importance. In addition, they should be crucial clinical features to provide physicians with the knowledge to screen high-risk patients in gastric cancer survivors as well.

Metachrony is defined as coordinated asynchronous movement throughout multiple appendages, such as the cilia of cells and swimmerets of crustaceans. We investigate the process of metachronal propulsion, notably used by species of crustaceans and microscopic cells to move through fluid. A rigid crustacean model with paddles moving in symmetric strokes was created to simulate metachronal movement. Coupled with the surrounding fluid domain, we employ the immersed boundary method to analyze fluid-structure interactions. To explore the effect of nonlinear morphology on the efficiency of metachronal propulsion, we generate and simulate a range of crustacean body shapes, from upward curves to downwards curves. We found that the highest propulsion velocity is achieved when the crustacean model morphology follows a downwards curve, specifically a parabola of leading coefficient k=−0.4. This curved morphology results in 4.5% higher velocity compared to the linear model. As k deviates from −0.4, the propulsion velocity decreases with increasing magnitude, forming a concave downward trend. The impact of body shape on propulsion velocity is shown by how the optimal velocity with k=−0.4 is 71.5% larger than the velocity at k=1. Overall, this study suggests that morphology has a significant impact on metachronal propulsion.