The design, facilities and conditions inside a classroom play a significant role in the teaching and learning experience for both students and lecturers. Prior studies of primary schoolchildren indicate three design principles affecting student learning, namely: naturalness, individualisation and stimulation. The current study extends these investigations to Higher Education through a survey of undergraduate students and university lecturers aimed at determining the most critical factors in undergraduate classroom design. One-to-one interviews were conducted with students and lecturers (n. 31) at the University of Nottingham, Malaysia Campus. Interviewees were encouraged to express their opinions, comments, concerns and suggestions through open-ended questions. The interviews were recorded and then transcribed and coded using NVivo10. Results show a strong desire among lecturers and students for improved classroom equipment, greater flexibility in classroom arrangement, more attractive decoration and for the addition of natural elements to the classroom environment. Of the three design principles, individualisation and naturalness emerged most strongly from the interviews and appear to be more important factors for undergraduates than stimulation. These findings could make a novel and significant contribution to the physical aspects of classroom design in Higher Education settings. Educational institutions are increasingly employing non-traditional classroom designs, which are expected to provide for more flexible, collaborative, and active learning and teaching experiences. Taking into consideration the environmental psychology of teaching and learning, several of the reported design attributes can serve as benchmarks for upgrading current classroom design and facilities in the future, as institutions look to upgrade their physical infrastructures to meet the changing demands of teachers and learners arising from technological innovations and shifts in our understanding of the methods and purposes of Higher Education.

(1) Background: Parents of children with autism spectrum disorders often experience psychological distress, which can affect the quality of childcare they provide. It is crucial to screen for psychiatric symptoms among these parents. The Core Symptom Index (CSI) is a widely used tool for assessing general symptoms such as depression, anxiety, and somatic symptoms, with demonstrated validity and reliability across various populations. However, there is limited research on the validity and reliability of the CSI in the general Chinese population. This study aimed to investigate the psychometric properties of the Chinese version of the CSI among parents of children with autism spectrum disorders using Confirmatory Factor Analysis (CFA). (2) Methods: A total of 794 Chinese parents raising children with autism participated in this study. All completed the CSI, along with the social inhibition subscale of the Interpersonal Problems Inventory and the Couple Satisfaction Index. Factorial validity was assessed using CFA to determine how well the bifactor three-factor model fits the data. Various structural models were compared using model fit indices. Convergent and discriminant validity were examined by exploring correlations with the social inhibition subscale and the Couple Satisfaction Index. Invariance testing of the CSI was conducted across multiple groups based on gender, age, and education using CFA. The reliability of the CSI was evaluated using McDonald’s omega coefficients. (3) Results: The bifactor model emerged as the best-fitting model for the data, suggesting that the total score of the CSI adequately represents overall psychiatric symptoms. The CSI exhibited significant correlations with the social inhibition subscale (r = 0.41, p < 0.01) and smaller correlation coefficients with the Couple Satisfaction Index (r = -0.16, p < 0.05), indicating both convergent and discriminant validity. Invariant tests supported scalar invariance levels based on gender and age but only partial invariance for education. The Chinese version of the CSI demonstrated high consistency, with McDonald's omega coefficients ranging between 0.86 and 0.95. (4) Conclusions: The bifactor model of the Chinese version of the CSI is validated, making it a suitable tool for measuring depression, anxiety, and somatization symptoms among parents of children with autism spectrum disorders. Further research on other Chinese populations is encouraged.

Litsea martabanica root's antioxidant and AChE activity showed promise as a pesticide detoxification agent in our previous study. In addition to roots, its leaves can help mitigate pesticide exposure, although there is limited scientific evidence supporting their efficacy. However, the use of roots in many countries, such as Thailand, could contribute to environmental degradation, as highland communities traditionally cut down whole trees to obtain them. This study aims to evaluate the antioxidant activity and anti-pesticide potential of water extracts from L. martabanica leaves instead of its roots through in vitro and in vivo investigations. The findings showed that L. martabanica water extracts and fractions demonstrated varied antioxidant activity. The water extract, obtained using traditional extraction methods, was chosen for in vivo experiments. Rats received the extract followed by chlorpyrifos exposure for 16 days. Results indicated reduced acetylcholinesterase activity in chlorpyrifos-exposed rats, while treatment with leaf extract led to increased activity, suggesting its potential as a detoxifying agent. Histopathological examination revealed no liver cell necrosis and showed liver cell regeneration, indicating potential protection against free radical-induced liver damage without affecting rat liver weight or biochemical profiles. Utilizing L. martabanica leaves for healthcare purposes holds promise without negative environmental impact.

In the extended malfatti problem, the numbers of circles in the triangle are triangle numbers, because the tangency properties among the internal circles and 3 sides of the triangle have special type of structure. That is, the corner circle tangent to two sides of the triangle and two boundary circles, the boundary circles tangent to one side of the triangle and 4 other circles, and the inner circles always tangent to 6 other circles. The circles we find in extended general Malfatti’s problem has the property that the smallest radius and the largest radius for the circle has big difference. In this paper, we proposed algorithms to solve the problem that the tangency properties among circles and sides of triangle is not fixed, so that the number of circles in the triangle is not necessary a triangle numbers. The purpose of this change is try to find the radii of the circles in the triangle is within a small range.

Limited understanding exists regarding the intricate dynamics between the levels of social inhi-bition exhibited by both wives and husbands concerning their perceived family support and de-pressive symptoms, particularly within couples who are parents of children diagnosed with au-tism spectrum disorder (ASD). This study used the actor-partner, interdependence mediation model to analyze data collected from 397 pairs of Chinese parents with children diagnosed with ASD. The findings of the study revealed significant indirect actor effects, indicating that the levels of social inhibition exhibited by both wives and husbands were associated with their own de-pressive symptoms through their respective perceptions of family support. In general, the study did not find significant partner effects, except for some indirect effect (IE) of wives on their hus-bands' depressive symptoms through the wives' perceived social support. This observation sug-gests that cultural norms and role expectations within the family context may influence these dy-namics. These results underscore the potential importance of interventions aimed at addressing social inhibition and enhancing perceived family support to alleviate depressive symptoms in this population. Additionally, interventions targeting fathers should emphasize the importance of their involvement in parenting and collaboration with their partners in caring for children with ASD. Such collaborative efforts may contribute to improved outcomes for both parents and chil-dren within families affected by ASD.

The modeling of flood-induced bend scour near embankment toes can provide important information for river engineering, embankment safety warnings, and emergency action management. During the rainy seasons, short-term general scour and bend scour are the most common causes for the failure of reinforced concrete embankments in Taiwan. To gain a deeper understanding of the scouring process near levee foundations, this study proposed a straightforward and practical method for bend scour simulation. The proposed simulation method is subdivided into three stages: two-dimensional flow simulation, general scour estimation, and bend scour estimation. A new bend-scour computation equation is proposed and incorporated into a two-dimensional hydraulic finite-volume model for simulating the evolution of bend scour depth around embankment toes. The proposed method is applied to simulate the temporal evolution of bend scouring near the Shuideliaw Embankment on the Cho-Shui River in Taiwan, where serious failure occurred during the June 2012 monsoon. Field data were gathered using the numbered-brick technique at the Shuideliaw Embankment to demonstrate the accuracy of the proposed method. The results of the bend scour simulations compared reasonably well with field measurements, indicating close agreement in terms of water levels and bend scour depths near the Shuideliaw Embankment. The proposed method was found to quickly estimate the maximum short-term general scour and bend scour depths for further enhancement of the safety of the embankment toe.

In China, preschool teachers have a significant influence on the development of young children aged 3-6. It is imperative to understand their mental health and the factors associated with it to inform policies, optimize their mental well-being, and support their job performance. This study aimed to investigate the factors contributing to anxiety symptoms among preschool teachers. A sample of 393 Chinese preschool teachers (279 females, 114 males) aged 21-56 completed online questionnaires collecting their socio-demographic and work-related information and assessing anxiety symptoms, interpersonal difficulties, personality traits, perceived stress, resilience, and inner strength. Pearson correlation and multiple linear regression analyses identified significant predictors of anxiety symptoms. The prevalence of anxiety symptoms among the studied cohort was found to be 12.2%. Statistically significant factors positively correlated with anxiety symptoms included objective work-related stress (B=0.149, p<.001), interpersonal difficulties (B=0.921, p<.001), perceived stress (B=0.108, p=.001), and neuroticism (B=0.071, p=.002). The findings highlight the urgent need for measures to reduce work-related stress and anxiety. However, when negative mental health predictors were included, the effect of positive psychological factors became nullified. Positive mental health might have a moderating role in such a negative mental health outcome as anxiety. Therefore, further research is required to understand the impact of positive mental health factors more clearly.

Tocilizumab against interleukin-6 receptor (IL-6R) has been demonstrated to inhibit the progression of diverse cancers in vitro and in vivo. Nonetheless, evidence regarding the anti-tumor effects of Tocilizumab on human colorectal carcinoma (CRC) corresponding to IL-6R expression levels re-mains scarce. To investigate the influence of IL-6R expression, SW480 and HT-29 cells inoculated subcutaneously into NU/NU mice were used as our human CRC xenograft models with anti-IL-6R antibody (Tocilizumab) therapy. IL-6R expression levels, the histology of CRC growth/ invasiveness and tumor growth-related signaling pathway were estimated by H&E and immunohistochemical staining. SW480 tumor cells with higher IL-6R expression levels exerted better responsiveness in Tocilizumab therapy than the treated HT-29 group. Likewise, therapeutic effects of Tocilizumab on the proliferative ability with mitotic index and Ki-67 expressions, the invasiveness with MMP-9 proteinase expressions, ERK 1/2 and STAT3 signaling transduction in SW480 treatment group were superior to HT-29 treatment group. In light of our results, IL-6R is the key indicator for the efficacy of Tocilizumab treatment in CRC xenografts. From the perspective of precision medicine, tumor response to anti-IL-6R antibody therapy could be predicted on the basis of IL-6R expression levels. In this manner, Tocilizumab may serve as a targeted and promising anti-CRC therapy.

Stallion mules have been used as working equids in several countries. Aggressiveness, under the influence of testosterone, resulted in the necessity for surgical castration before work training. The gonadotropin-releasing hormone (GnRH) vaccine may be an alternative method for immunocastration in mules. The objectives were to evaluate the effect of GnRH vaccine on anti-GnRH antibody production, serum testosterone level, clinical adverse effects, and behavior toward human manipulation. Twenty-five mules were separated into 3 groups: Control-intact, Control-castrated, and Treatment. Treatment was further divided into subgroups according to condition (intact or unilateral cryptorchid) and age. Treatment received 195 µg GnRH vaccine intramuscularly at week 0, 4, and 8. Anti-GnRH antibody increased at week 6 and 10, then gradually decreased to baseline at week 22. Treatment-intact-young had the highest anti-GnRH antibody, resulting in lower serum testosterone levels during week 2-6 and 12-16 compared to Control-intact. Subcutaneous edema adjacent to the injection site was detected only in Treatment-intact after booster vaccination. During week 6-22, the behavioral scores of Treatment significantly changed toward at ease with human contact compared to a score before vaccination. In conclusion, mules responded to GnRH vaccine, which could temporarily suppress testosterone for up to 16 weeks.

.Maize cultivation in Thailand faces challenges owing to climate change and soil organic carbon (SOC) loss. This highlights the importance of comparing maize soil with paddy soil in terms of the role of dissolved organic carbon (DOC) and nutrient availability, as they influence SOC content. Soil samples from Chiang Mai province, primarily Fluvisol, were collected for the cultivation of paddy rice and maize, analysed for carbon fractions and chemical properties, and categorised into layers. Comparative analysis revealed that maize soils had lower levels of labile carbon components and organic carbon than paddy soils (P

Ultramafic rocks become promising candidates for carbon sequestration by enhanced carbon dioxide (CO2) mineralization strategies due to their highly CO2-reactive mineral composition and its abundant availability. This study reports a mineralogy and microtextures of a representative ultramafic rock from the Ma-Hin Creek in northern Thailand and observes evidence of CO2 mineralization occurring through the interaction between CO2 and the rock with the existence of water under ambient conditions. After sample collection, rock description was determined by optical petrographic analysis. The rock petrography reveals a cumulated wehrlite comprising over 50% olivine and minor amounts of clinopyroxene, plagioclase, and chromian spinel. Approximately 25% of the wehrlite has altered to serpentine and chlorite. A series of CO2 batch experiments were conducted on six different rock sizes at a temperature of 40°C and pressure of 1 atm over five consecutive days. The post-experimental products were dried, weighed, and geochemically analyzed to detect changes in mineral species. Experimental results showed that product weight and the presence of calcite increased with reducing grain size. Additionally, the modal mineralogy of the wehrlite theoretically suggests a potential CO2 uptake of up to 53%, which is higher than the average uptake values of mafic rocks. These findings support the suitable rock investigation approach and the preliminary assessment of carbon mineralization potential, contributing to enhanced rock weathering techniques for CO2 removal that could be adopted by mining and rock supplier industries.

Cancer patients, susceptible to severe COVID-19 outcomes, exhibit varied vaccine responses, particularly those who are receiving chemotherapy. This prospective cohort study enrolled 115 cancer patients, and data from 91 patients who received two doses of COVID-19 vaccines were analyzed. Blood was drawn at baseline, day 28, and 6 months post-second dose for neutralizing antibody analysis. The primary outcome was seroconversion rate against wild type and Omicron at day 28. Secondary outcomes included seroconversion at 6 months, factors associated with seroconversion, and safety. Of the 157 cancer patients screened, 91 were enrolled, with 45% receiving chemotherapy. Seroconversion rates at day 28 were 77% for the wild type and 62% for Omicron. Chemotherapy did not affect seroconversion (p=0.789 for wild type, p=0.597 for Omicron). Vaccine type positively correlated with seroconversion, with an adjusted ORR of 25.86 (p=0.029) for the wild type and 17.38 (p<0.001) for Omicron with the primary heterologous vaccine. Adverse events were grade 1 in 34.0% and grade 2 in 19.7% of participants. Despite lower seroconversion against Omicron, no difference was noted between chemotherapy and non-chemotherapy groups. COVID-19 vaccinations demonstrated good tolerability. This data underscores vaccine efficacy considerations in cancer patients, informing tailored strategies for this vulnerable population.

Mistreatment can adversely affect students’ academic performance and mental health. This study aimed to investigate the prevalence of mistreatment and its association with academic motivation among Thai medical students in clinical years. A cross-sectional study was conducted among medical students throughout Thailand using the Composite Questionnaire of Mistreatment and Academic Motivation Scale (AMS). Descriptive statistics, chi-square tests, correlations, and regression analyses were conducted. A p-value &lt; 0.05 was considered statistically significant. The sample included 399 students, with mean age of 23 ± 1.29 years old, and 61.5% were female. A total of 81% of participants experienced mistreatment. Twenty-nine percents of students thought that mistreatment occurred because the maltreaters did not consider mistreatment as inappropriate or serious. Students who experienced mistreatment exhibited lower AMS (B = -9.16, 95% CI: -15.37 to -2.95, p-value = 0.004) than those who did not. Moreover, students who experienced academic mistreatment exhibited a higher amotivation score (B = 1.50, 95% CI: 0.16 to 2.85, p-value = 0.029) than those who did not. The prevalence of mistreatment was unexpectedly high, and it associated with students' motivation to study. Educational institutions should prioritize addressing this issue and developing strategies to provide assistance, including the enhancement of reporting systems.

In recent years, growing attention has been directed towards the potential of plant extracts as great therapeutic agents in controlling oxidative stress and inflammation. Gymnema inodorum (Lour.) Decne, an indigenous plant locally grown in Northern Thailand, is known for its anti-diabetic activity. This study aims to explore the antioxidant properties and phenolic profile of column chromatographic fractionated G. inodorum leaf extract. The ethanolic-reflux extracts of G. inodorum leaves were subjected to column chromatography for the isolation of bioactive molecules. Total phenolic and flavonoid content were assessed using Folin–Ciocalteu and aluminium chloride colorimetric methods, respectively. Total antioxidant activity was evaluated by employing different antioxidant assays, including 2,2-diphenyl-1-picrylhydrazyl (DPPH), 2,2′-azino-bis-(3-ethylbenzothiazoline-6-sulfonic)acid (ABTS) scavenging assay and ferric reducing antioxidant power (FRAP) assay. High-Performance Liquid Chromatography (HPLC) with a C18 column was employed to determine the level of gymnemic acid, while Liquid Chromatography Quadrupole Time-of-Flight/Mass Spectrometry (LC-QTOF/MS) was used to identify potential phenolic compounds. The three separated fractions indicating A, B, and C, exhibited remarkable antioxidant activity, with total phenolic content of 0.294 ± 0.056, 0.085 ± 0.039, and 0.227 ± 0.041 mg QE/mL, and total flavonoid content of 0.274 ± 0.050, 0.309 ± 0.110, and 0.384 ± 0.007 mg QE/mL, respectively. Fraction A exhibited the highest DPPH and ABTS scavenging activity, while fraction C demonstrated significantly higher ferric-reducing power. HPLC analysis revealed a highest concentration of gymnemic acid in fraction C (0.393 ± 0.003 mg/g) compared to fraction A (0.159 ± 0.003 mg/g) and fraction B (0.142 ± 0.000 mg/g). The LC-QTOF/MS phenolic screening showed seven potential phenolic compounds in fraction A, seven compounds in fraction B, and four compounds in Fraction C. A significant relationship is found between antioxidant potential and total phenolic content, suggesting that phenolic compounds are the major contributors to the antioxidant activity of G. inodorum.

Sign language recognition technology can help people with hearing impairments to communicate with those who are hearing impaired. At present, with the rapid development of society, deep learning technology also provided certain technical support for sign language recognition work. In sign language recognition tasks, the use of traditional convolutional neural networks to extract spatio-temporal features from sign language videos suffers from insufficient feature extraction, resulting in low recognition rates. Nevertheless, video-based sign language datasets are very large and require a lot of computational resources for training and generalisation must be ensured, which poses a challenge for recognition. In this paper, we have presented a video-based sign language recognition method based on resnet and lstm. As the number of network layers increases, the ResNet network can effectively solve the granularity explosion problem and obtain better time series features. We use the Resnet convolutional network as the backbone model. At the initialisation stage, we obtain sign language features using ResNet; then, the learned feature space is used as the input of LSTM network to obtain long sequence features. The experimental results show that the accuracy of the above model is better than the mainstream model, and it can effectively extract the spatio-temporal features in sign language videos and improve the recognition rate of sign language actions.

Difficult-to-cut materials are being increasingly used in many industries because of their superior properties, including high corrosion resistance, heat resistance and specific strength. However, these same properties make the materials difficult to machine using conventional machining techniques. Laser-assisted milling (LAM) is one of the effective methods for machining difficult-to-cut materials. In laser-assisted milling machining occur after the workpiece is locally preheated using a laser heat source. Laser assisted machining has been studied by many researchers on flat workpiece or micro end-milling. However, there is no research on the curved shape using laser assisted milling. This study investigated the use of laser assisted milling to machine a three-dimensional curved shape workpiece based on NURBS. A machining experiment was performed on Inconel 718 using different tool paths (ramping, contouring) under various machining conditions. Finite elements analysis was conducted to determine the depth of cut. Cutting force, specific cutting energy and surface roughness characteristics were measured, analyzed and compared for conventional and LAM machining. LAM significantly improved these machining characteristics, compared to conventional machining. There results can be applied to the laser-assisted machining of various three-dimensional shapes.

Early stroke diagnosis remains a big challenge in healthcare partly due to the lack of reliable diagnostic blood biomarkers, which in turn leads to increased rates of mortality and disability. Current screening methods are optimised to identify patients with a high risk of cardio-vascular disease, especially among the elderly. However, in young adults and children, these methods suffer low sensitivity and specificity and contribute to further delays in their triage and diagnosis. Accordingly, there is an urgent need to develop reliable blood biomarkers for triaging patients suspected of stroke in all age groups, especially children and young adults. This review explores some of the existing blood biomarkers, as single biomarkers, or biomarker panels, and examine their sensitivity and specificity for predicting stroke. A review was performed on PubMed and Web of Science for journal articles published in English during the period 2001 to 2021 which contained information regarding biomarkers of stroke. In this review article, we provide comparative information on the availability, clinical usefulness, and time-window periods of eight single blood biomarkers and six biomarker panels that have been used for predicting stroke in emergency situations. The outcomes of this review can be used in future research for developing more effective stroke biomarkers.

This study was conducted to evaluate the feasibility of applying a two-step biological treatment process, solid-state anaerobic digestion (SSAD) and black soldier fly larvae (BSFL) composting, for treating dairy cattle manure. Biogas from SSAD of dairy cattle manure, and the digestate of SSAD was fed to BSFL. In turn, BSFL can be fed to animals as a protein supplement. Adjustment of pH and 30% inoculation ratio (IR₃₀) during SSAD produced the highest theoretical methane yield, 626.1±28.7 L CH₄/kg VS_des, with an ultimate methane yield of 96.81±2.0 L CH₄/kg VS_load. For BSFL composting, the groups with a feeding rate of 75 and 100 mg/day/larvae had the highest body weight change, which was 969.6±28.4 and 984.1±177.6%, respectively. The combination process of SSAD and BSFL composting increases the incentive for dairy cattle manure treatment enabled higher waste removal efficiency, and produced more valuable products.

Large quantities of clothing are routinely discarded, ending up in landfills that contribute to the environmental crisis; hence, it is worthwhile investigating how to dispose of this waste in a sustainable way. This study considered environmental values and prosocial behavior from a behaviorism theory. The aim was to set up an environmental protection model for the sustainable disposal of consumer clothing. A structural equation modeling analysis of 407 undergraduate and postgraduate consumer data in Taiwan revealed that consumers’ choice to donate clothing was influenced by environmental values and prosocial behaviors. Clothing resale was influenced by the factor of prosocial behavior. However, prosocial consumers used other disposal patterns instead of resale. Clothing reuse was not influenced by either environmental values or prosocial behavior. The results indicated that environmental values and prosocial behavior did in fact influence consumers’ choices regarding clothing donation. However, prosocial consumers used other disposal patterns instead of resale. Behaviorism theory model is effective in analyzing the factors influencing sustainable clothing disposal. To face clothing waste issues, one can intensify traditional values of industriousness and thriftiness, of compassion and sympathy to others, to accelerate the promotion of the sustainable disposal of clothing.

In northern Thailand, the problem of small particulate matter happens every year, with the pri-mary source being agricultural weed burning and wildfire. The tourism industry is strongly impacted and has been the spotlight for the past few years. Thus, the study aims to investigate the effect of small particulate matter on tourism and related SMEs in Chiang Mai, Thailand. The data was collected from 286 entrepreneurs in the tourism and related SMEs sectors. The data was analyzed using data mining and association rule techniques. The study revealed that small particulate matter has a considerable impact on customer factors, especially the number of customers has decreased. Operational factors and prod-uct/service factors are also affected by the dust in the form of adjustments to keep the business running and the protection of the health of employees and customers. Certainly, financial factors are affected by the small particulate matter situation, both lower revenues and higher costs.

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

Aberrant neutrophil extracellular trap (NET) formation and the loss of barrier integrity in inflamed intestinal tissues have long been associated with inflammatory bowel disease (IBD). However, whether NETs alter intestinal epithelium permeability during colitis remains elusive. Here, we demonstrated that NETs promote the breakdown in intestinal barrier function for the pathogenesis of intestinal inflammation in mouse models of colitis. NETs were abundant in the colon of mice with colitis experimentally induced by dextran sulfate sodium (DSS) or 2,4,6-trinitrobenzene sulfonic acid (TNBS). Analysis of the intestinal barrier integrity revealed that NETs impaired gut permeability, enabling the initiation of luminal bacterial translocation and inflammation. Furthermore, NETs induced the apoptosis of epithelial cells and disrupted the integrity of tight junctions and adherens junctions. Intravenous administration of DNase I, an enzyme that dissolves the web-like DNA filaments of NETs, during colitis restored the mucosal barrier integrity which reduced the dissemination of luminal bacteria, and attenuated intestinal inflammation in both DSS and TNBS models. We conclude that NETs serve a detrimental factor in the gut epithelial barrier function leading to the pathogenesis of mucosal inflammation during acute colitis.

Adlay (Coix lachryma-jobi L. var. ma-yuen Stapf) contains various phytonutrients for treating many diseases in Asia. To investigate whether orally administered of adlay bran oil (ABO) can cause drug interactions, the effects of ABO on the pharmacokinetics of five cytochrome P450 (CYP) probe drugs were evaluated. Rats were given a single oral dose (2.5 mL/kg BW) of ABO 1 h before administration of a drug cocktail either orally or intravenously, and blood was collected at various time points. A single oral dose of ABO administration did not affect the pharmacokinetics of five probe drugs when given as a drug cocktail intravenously. However, ABO increased plasma theophylline, dextromethorphan, and diltiazem when co-administered an oral drug cocktail. After 7-days of feeding with an ABO-containing diet, plasma concentrations of theophylline and chlorzoxazone were increased after oral administration of drug cocktail. The major CYP enzyme activities in liver and intestinal were not affected by ABO treatment. Results from this study indicate that a single oral dose or short-term administration of ABO may increase plasma drug concentrations when ABO is given concomitantly with drugs. ABO is likely to enhance intestinal drug absorption. Therefore, caution is needed to avoid food-drug interactions between ABO and co-administered drugs.

Various colors of clothing originating from synthetic dyes are presently causing serious environmental pollution problems, whereas natural dyes extracted from natural indigo plants help reduce the harm to the environment and extend the sustainable use of clothing. This study focuses on the relation between indigo dyeing colors and the environment on the basis of sustainable design. The results reveal that light colors are considered to conform to the sustainable spirit more than dark colors in different indigo colors. In fact, the recyclable light-colored indigo dyeing t-shirt is beneficial in its reuse. Indigo dyeing fabric can be decomposed by a variety of microorganisms; however, the light-colored indigo dyeing takes a short time. Light colored indigo dyeing is more resource-saving when considering dye, water and electricity costs. The results of colors and environmental protection provide scheme references to consumers or industry for clothing collocation of different indigo dyeing colors for a series of blue clothing and carry out the ideal of the sustainability and co-existence between clothing and natural resources.

In South Korea, demolition waste (DW) management has become increasingly significant owing to the rising number of old buildings. Effective DW management requires an efficient approach that accurately quantifies and predicts the generation of DW (DWG) of various types, which necessitates access to the required information or technology capable of achieving this. Hence, we developed an artificial intelligence-based model that predicts the generation of ten DW types, specifically from buildings in redevelopment areas. We used an artificial neural network algorithm with < 10 neurons in the hidden layer to derive individual input variables and optimal hyperparameters for each DW type. All DWG prediction models achieved an average validation and test prediction performance (R²) of 0.970 and 0.952, respectively, with their ratios of percent deviation ≥ 2.5, ver-ifying them as excellent models. Moreover, a Shapley additive explanations analysis revealed that DWG was most impacted by the floor area for all the DW types, with a positive correlation with DWG. Conversely, other factors showed either a positive or negative correlation with DWG de-pending on the DW type. The study findings will enable demolition companies and local gov-ernments in making informed decisions for efficient DW management and resource allocation by accurately predicting the generation of various types of DW.

This study investigated the relationship of acrosome reactions and fatty acid composition on fertility in boar sperm. The acrosome reaction of sperm was induced via methyl-beta-cyclodextrin (MBCD), and acrosome reaction, plasma membrane integrity, and fertility were analyzed. The fatty acid composition of the excess acrosome reacted sperm was determined via gas chromatography. The results showed that the acrosome reaction in sperm was induced over 85% of the time by 60 mM MBCD treatment, and the plasma membrane integrity was significantly decreased and was dependent on the MBCD level. The acrosome reacted sperm resulted in significantly higher saturated fatty acids (SFAs) and lower unsaturated fatty acids (PUFAs) than the non-acrosome reaction group. Moreover, the acrosome reacted sperm from 60 mM MBCD significantly decreased in vitro fertility and blastocyst formation relative to non-acrosome reacted sperm, and the acrosome reaction was positively correlated with SFAs and negatively correlated with PUFAs. Of these fatty acids, C22:5n-6 (docosapentaenoic acid [DPA]) and C22:6n-3 (docosahexaenoic acid [DHA]) were directly negatively correlated with the acrosome reaction (r = -0.982 and -0.947, respectively). In conclusion, the excessive acrosome reactions may occur by reducing the PUFAs, which may then dramatically decrease sperm fertility in pigs.

This study aims to construct simple devices to ascertain the concentrations of ammonium (NH4+) and nitrate (NO3-). The device structure comprises a visible and near-infrared absorption meas-urement room, along with an RGB (red, green, and blue) absorption measurement room, con-stituting the two measuring rooms. Both the measurement rooms are equipped with light sources and detectors configured to operate in opposed or thru-beam modes. A tiny processor is utilized for processing the measurements, with an algorithm implemented within its memory. During the algorithm development phase, ranges for measuring the quantity of nutrients were categorized using a discriminant analysis approach. Thirty percent of the soil sample data were utilized as verification data, while the remaining 70 percent served as training data. Nutrient content values from reliable measuring instruments were incorporated into all datasets. Discriminant analysis was employed to classify the amount of NH4+ into five ranges based on the test results. When tested with soil samples, the accuracy was 66.13% compared to the reference value of a reliable measuring device. Similarly, NO3- was classified into four ranges with an accuracy of 81% com-pared to the reference value of a reliable measuring device.

This study used the sol–gel method to synthesize a non-halogenated hyperbranched flame retardant containing nitrogen, phosphorus and silicon, HBNPSi, which was then added to a polyurethane (PU) matrix to form an organic–inorganic hybrid material. Using 29Si nuclear magnetic resonance, energy-dispersive X-ray spectroscopy of P- and Si-mapping, scanning electron microscopy, and X-ray photoelectron spectroscopy, this study determined the organic and inorganic dispersity, morphology, and flame retardance mechanism of the hybrid material. The condensation density of the hybrid material PU/HBNPSi was found to be 74.4%. High condensation density indicates a dense network structure of the material. The P- and Si-mapping showed that adding inorganic additives in quantities of either 20% or 40% results in homogeneous dispersion of the inorganic fillers in the polymer matrix without agglomeration, indicating that the organic and inorganic phases had excellent compatibility. In the burning test, adding HBNPSi to PU resulted in the material passing the UL-94 standard at the V2 level, unlike the pristine PU, which did not meet the standard. The results demonstrated that after non-halogenated flame retardant was added to PU, the material’s flammability and dripping were lower, thereby proving that flame retardants containing elements such as nitrogen, phosphorus, and silicon exert an excellent flame retardant synergistic effect.

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.

The NCO functional group of 3-isocyanatoproply triethoxysilane (IPTS) and the OH functional group of DOPO-BQ were used to conduct an addition reaction. Following completion of the reaction, triglycidyl isocyanurate (TGIC) was introduced to conduct a ring-opening reaction. Subsequently, a sol-gel method was used to take place a hydrolysis- condensation reaction on TGIC-IPTS-DOPO-BQ to form a hyperbranched nitrogen–phosphorous–silicon (HBNPSi) flame retardant. This flame retardant was incorporated into a polyurethane (PU) matrix to prepare a hybrid material. Fourier-transform infrared spectroscopy (FT-IR), thermogravimetric analysis (TGA), limiting oxygen index (LOI), UV-VIS spectrophotometry, and Raman analysis were conducted to structure characterization and analyzed transparency, thermal stability, flame retardancy, and residual char to understand the flame retardant mechanism of prepared hybrid materials. After the flame retardant was added, the maximum degradation rate decreased from −36 wt%/min to −17 wt%/min, the integral procedure decomposition temperature (IPDT) increased from 348 ℃ to 488 ℃, and the char yield increased from 0.7 to 8.1 wt%. The aforementioned results verified that thermal stability of PU can be improved after adding HBNPSi. The LOI analysis indicated that the pristine PU was flammable because the LOI of pristine PU was only 19. When the content of added HBNPSi was 40%, the LOI value was 26; thus the PU hybrid became nonflammable.

Fall armyworm Spodoptera frugiperda (J.E. Smith, 1797) is a major pest of corn, rice, and sorghum among other crops usually controlled using synthetic or biological insecticides. Currently, the new invention of nanotechnology is taking root in the agricultural industry as an alternative source of pest management that is target-specific, safe, and efficient. This study sought to determine the efficacy of commercial Zinc Oxide (ZnO) nanoparticles (NPs) towards S. frugiperda under labora-tory conditions. ZnO NPs were diluted into different concentrations (100- 500ppm), where the baby corn used to feed the S. frugiperda larvae was dipped. The development of the insect feeding on food dipped in ZnO solution was significantly (p<0.05) affected, and the number of days that the insect took to complete its life cycle had a significant difference compared to the control. There was a significant difference in the adults’ emergence at all the concentrations of ZnO NPs compared to the control, with over 90% of the eggs successfully going through the cycle until adult emergence. Additionally, several malformations were observed throughout the lifecycle of the insect. Also, the fecundity of the females was greatly affected. The findings of this study suggest the possibility of exploitation of ZnO nanoparticles not only to eradicate S. frugiperda but to significantly reduce their population in the ecosystem through deformations, reduced fecundity, reduced oviposition, and hatchability of eggs. It will be a valuable tool in integrated pest management regimens.

One of the most important sources of energy is the sun. Taiwan is located at north 22-25° latitude. Due to its proximity to the equator, it experiences only a small angle of sunlight incidence. Its unique geographical location which can obtain sustainable and stable solar resources. This study takes research on the forecast of solar radiation to maximize the benefits of solar power generation, and develops methods that can predict the future solar radiation pattern to help reduce the costs of solar power generation. This study builds supervised machine learning models, known as deep neural network (DNN) and long short-term memory neural network (LSTM). The hybrid supervised and unsupervised model, namely cluster-based artificial neural network (k-means clustering and fuzzy C-means clustering-based models), was developed. After establishing these models, the study evaluated their prediction results. For different prediction periods, the study selected the best-performing model based on the results and proposed combining them to establish a real-time updated solar radiation forecast system capable of predicting the next 12 hours. The study area covered Kaohsiung, Hualien, and Penghu in Taiwan. Data from ground stations of the Central Weather Administration, collected between 1993 and 2021, as well as the solar angle parameters of each station, were used as input data for the model. The results of this study show that different models have their advantages and disadvantages in predicting different future times. Therefore, the hybrid prediction system can predict future solar radiation more accurately than a single model.

Globally, road traffic collisions cause over a million deaths annually, with pedestrians accounting for nearly one-quarter (23%) of these fatalities. This casualty proportion highlights the critical importance of adhering to traffic regulations. This study analyzes the factors influencing driver yielding behavior at midblock crosswalk improvements, comparing (1) a typical zebra crossing (C1) and (2) an intelligent signalized crosswalk (C2). The study used video-based observational data to investigate driver behaviors and factors influencing driver behaviors. The study applied multinomial logistic regression to formulate yielding behavior models. The results indicate that the number of traffic lanes, width of the traffic lanes, width and length of the crosswalk, vulnerable group, the number of pedestrian crossings, pedestrian crossing time, the number of vehicles approaching a crosswalk, speed of vehicle, headway, the post-encroachment time (PET) between vehicles and pedestrian, and roadside parking are the significant factors influence yielding behavior. These findings provide a better understanding of the factors influencing driver yielding behavior and propose measures to set proper physical improvements (e.g., curb extensions, raised pedestrian platforms, and pedestrian fencing), enforcement (e.g., parking restriction, speed violation detection), public awareness campaigns, and education initiatives.

Health services research is a multidisciplinary discipline that aims to improve population health by studying healthcare services' organization, delivery, and financing. Over time, the field has worked to define its boundaries and establish a set of core research topics and methods addressing population wellbeing, access, quality, and cost. Although the influence of health technology is significant, our literature survey on health services research showed that SCs in general—containing their management, cost, and policy—had received little attention. Importantly, our assessment also showed that the system’s readiness to handle supply policy and supply device deficiencies like those encountered during pandemic was hardly ever mentioned. Reduced open areas and water bodies, deteriorating infrastructure, and changes in the biological morphology all affect cities’ uncontrollable and unplanned growth. Urban amenities, facilities, and healthcare services were unevenly distributed due to this unchecked urban population development. In light of this, this research suggests two reliable models for site selection issues for one of Hong Kong’s main hospitals. Levels of uncertainty, infeasibility tolerance, and reliability are taken into consideration. Then, two categories of uncertainty—symmetric and bound-ed—were examined. As a result, the challenge of scheduling in uncertainty has been considered, and potential solutions have been presented using a specified probability distribution function. The paper concludes by introducing the specific justice and health problems and outlining four typical strategies. In order to ensure that medications and other healthcare supplies are produced, distributed, and given to patients, a vast network of systems, components, and procedures must be effectively managed. This research contributes in this regard. Also, its grantee fairness in health systems and the populations health locally, nationally, and globally. It highlights health inequity, advances the measurement of health inequity, and promotes public dialogues on health inequity.

The mystery phenomenon of fungal bioluminescence has always captivated human curiosity, although more attempts need to be made, particularly to bring the new species to the surface. In this study, we devoted considerable space to the taxonomy of these fungi while discussing their biogeography, evolution, bioluminescence mechanism, and potential ecological roles. We provide a detailed explanation of how these fungi produce light, including the role of the enzyme luciferase and luciferin. We also discussed their applications. Here, we presented an updated list of 122 bioluminescent fungi identified from five distinct evolutionary lineages viz. Armillaria, Eoscyphella, Lucentipes, Mycenoid, and Omphalotus worldwide, mainly in tropical and subtropical areas. The bioluminescent fungi descended from the last common ancestor of the mycenoid and the marasmioid clades of Agaricales, which have been maintained for at least 160 million years of evolution. We highlighted the need for further research to understand the ecological role of bioluminescent fungi. Applying bioluminescent fungi in various areas (e.g., environmental and medicinal) demonstrates their validity.

The spatial heterogeneity in hydrologic simulations is a key difference between lumped and distributed models. Not all distributed models benefit from pedo-transfer functions based on soil properties and crop-vegetation dynamics. Mostly coarse scale meteorological forcing is used to estimate water balance at the catchment outlet only. Mesoscale hydrologic model (mHM) is one of the rare models that incorporates remote sensing data i.e. leaf area index (LAI) and aspect to improve actual evapotranspiration (AET) simulations and water balance together. The user can select either LAI or aspect to scale PET. However, herein we introduced a new weighting parameter “alphax” that allows user to incorporate both LAI and aspect together for PET scaling. With this mHM code enhancement, the modeler has an also option of using raw PET with no scaling. In this study, streamflow, and AET are simulated using the mesoscale Hydrological Model (mHM) in Main (Germany) basin for the period of 2002-2014. The additional value of PET scaling with LAI and aspect for model performance is investigated using Moderate Resolution Imaging Spectroradiometer (MODIS) AET and LAI products. From 69 mHM parameters, 26 parameters are selected for calibration using Optimization Software Toolkit (OSTRICH). For calibration and evaluation, KGE metric is used for water balance and SPAEF metric is used for evaluating spatial patterns of AET. Our results show that AET performance of the mHM is highest when using both LAI and aspect indicating that LAI and aspect contain valuable spatial heterogeneity information from topography and canopy (e.g., forests, grasslands, and croplands) that should be preserved during modeling. The additional “alphax” parameter makes the model physically more flexible and robust as the model can decide the weights according to the study domain.

This study explores the use of satellite-based LULC (Land Use / Land Cover) data while simultaneously correcting potential evapotranspiration (PET) input with Leaf Area Index (LAI) to increase the performance of a physically distributed hydrologic model. The mesoscale hydrologic model (mHM) was selected for this purpose due to its unique features. Since LAI input informs the model about vegetation dynamics, we incorporated the LAI based PET correction option together with multi-year LULC data. The Globcover land cover data was selected for the single land cover cases, and hybrid of CORINE (coordination of information on the environment) and MODIS (Moderate Resolution Imaging Spectroradiometer) land cover datasets were chosen for the cases with multiple land cover datasets. These two datasets complement each other since MODIS has no separate forest class but more frequent (yearly) observations than CORINE. Calibration period spans from 1990 to 2006 and corresponding NSE (Nash-Sutcliffe Efficiency) values varies between 0.23 and 0.42, while the validation period spans from 2007 to 2010 and corresponding NSE values are between 0.13 and 0.39. The results revealed that the best performance is obtained when multiple land cover datasets are provided to the model and LAI data is used to correct PET, instead of default aspect-based PET correction in mHM. This study suggests that to minimize errors due to parameter uncertainties in physically distributed hydrologic models, adequate information can be supplied to the model with care taken to avoid over-parameterizing the model.

Mitral valve disease is a common heart disease in dogs. The aim of this study was to describe the cases of dogs who underwent mitral valve repair using a v-clamp device and to provide their long-term follow-up data on cardiac function after mitral valve repair. Four dogs with mitral valve regurgitation who experienced coughing and dyspnea underwent surgical mitral valve repair between December 2023 and June 2024. The patients were evaluated by transthoracic and transesophageal echocardiography. Echocardiography revealed mitral valve leaflet regurgitation. Mitral valve repair was performed under general anesthesia using a v-clamp device introduced through an introducer wire guide. Echocardiography was conducted at baseline and the 6-month follow-up. Blood analysis results after surgical repair were normal. Follow-up echocardiography revealed no complications related to the procedure, with all dogs demonstrating improved respiratory signs and quality of life after repair. No adverse reactions were reported after surgery. A v-clamp device was used to repair mitral valve regurgitation in four dogs. Mitral valve repair using a v-clamp device is another treatment option for mitral valve disease in dogs.

In the wake of increasing digital fraud, this paper introduces an innovative application of Artificial Intelligence (AI) in detecting fraudulent activities across finance, healthcare, and e-commerce sectors. It presents a detailed analysis of machine learning methodologies, specifically focusing on the advantages of supervised, unsupervised, and deep learning techniques. The paper addresses the challenges such as data imbalance, model interpretability, and ethical implications in AI-based fraud detection. It also discusses the necessity of high-quality datasets and advocates for the integration of traditional and advanced machine learning methods to enhance accuracy and adaptability in fraud identification. However, it acknowledges the limitations including computational demands and overfitting risks. The study underscores the importance of collaborative efforts between AI experts and industry professionals to develop ethical, efficient, and reliable AI solutions for fraud detection.

The application of smartphone-based color evaluation of passive sampling devices for gases has only been sparsely reported. The present review aims to compile available publications with respect to the configuration of the passive samplers, conditions of smartphone photographing, analytical procedure for color detection and quantification (including calibration processes), and their application to different target gases. The performance of the methods - whenever available - is presented regarding the analytical specifications selectivity, sensitivity, and limit of detection in comparison with other color evaluation methods of passive samplers. Practical aspects like requirements of instrumentation and ease of use will be outlined in view of the potential employment in education and citizen science projects. In one section of the review the inconsistent terminology of passive and diffusive sampling is discussed in order to clarify the distinction of information obtained from the uptake of the passive samplers between gas-phase concentration and the accumulated deposition flux of gaseous analytes. Colorimetric gas sensors are included in the review when applied in passive sampling configurations and evaluation is performed with smartphone-based color evaluation. Differences in the analytical procedures employed after the passive sampling step and prior to the detection of the colored compounds are also presented.

Music therapy has served as complementary and alternative medicine for various neurological disorders. Five Phases Music Therapy (FPMT) employs the theory of five phases and five music scales or tones (宫Gong (do), 商Shang (ri), 角Jue (mi), 徵Zhi (so) and 羽Yu (la)) to analyze and treat mind-body illness. In Chinese Medicine (CM), the five music scales are used to connect the human body and the universe, interpret personalities and constitution and analyze the influences of climatic changes on health. FPMT has a self-contained theory and routine of practice application. Large amounts of clinical and fundamental reports have been available and clinical benefits have been obtained. However more systemic clinic research esp. evidence-based and random controlled trials must be performed to validate and optimize its routines and biological and neurological mechanism must be further explored. It’s reasonable to believe that the effective music therapy will attract more attention from the world outside China with the introduction of FPMT.

Construction productivity entails a wide range of work combinations. When human resources are scarce, it is critical to replace manpower with machinery, and calculating machinery productivity is crucial. Traditional labor productivity methods, however, cannot address dredging complex multi-attribute decision-making (MADM) problems. Aiming to address the limitations of the traditional labor productivity method, this paper extends the data envelopment analysis (DEA) and proposes a new dredging productivity evaluation method. The proposed method can solve the problem of evaluating various combinations of factors (single-input, multiple-input, sin-gle-output, and multiple-output) and the problem suggesting that the efficiency of the DEA method'scalculation results is equal to 1. The effectiveness of the proposed method was verified using reservoir dredging examples. The simulation results show that the proposed method has broad applicability, can accurately evaluate the related dredging performance issues, and provide directions for construction managers to improve labor productivity.

In this paper, a buck DC-DC converter with the proposed twin frequency control scheme (TFCS) and accurate load current sensing (ALCS) have been designed and implemented with 0.18µm CMOS technology for a supply voltage ranging from 2.0-3.0V which is compatible with state-of-the-art batteries (NiCd/NiMH: 1.1-2V, Li-Ion: 2.5-4.2V). The proposed converter yields a peak efficiency of about 92.7% with a load current of 30mA. Furthermore, it only occupies a silicon area of 1.3mm2. The proposed buck converter is dedicated for smartphone applications whereby it spends most of its time in idle, low load conditions.

No research to date has explored the possibility of context-specific, within-relationship fluctuation in attachment security. In this present article, two cross-sectional studies were designed (1) to develop and validate context-specific attachment scales in Traditional-Chinese, and (2) to explore fluctuations in within-parent attachment security between the contexts of sport and academics, in relation to global attachment patterns and indicators of psychological wellbeing. Results indicated that youth can and do perceive within-parent attachment patterns differently depending upon context but that the relationship of such differences to context-specific outcomes is complex. Of particular interest was that the degree of within-parent attachment variability between contexts was clearly and negatively related to indices of psychological wellbeing. This suggests that contextual variation may be a meaningful and useful way to explore within-parent attachment fluctuation.

Iron overnutrition has been implicated with higher risk of developing metabolic and cardiovascular diseases, including metabolic syndrome (MetS), while iron deficiency anemia exacerbates many underlying chronic conditions. Hemoglobin (Hb) concentration in the blood, which reflects a major functional iron (i.e., heme iron) in the body, may serve as a surrogate of iron nutrition status. We conducted sex-specific observational association studies where we carefully titrated the association between Hb deciles and MetS and its components among the Taiwanese Han Chinese (HC) from the Taiwan Biobank and Europeans of White ancestry from the UK Biobank, representing two large ethnicities. Our data show that at higher-than-normal levels of Hb, increasing deciles of Hb concentration were significantly associated with MetS across all sex subgroups in both ethnicities, with the highest deciles resulting in up to three times greater risks than the reference group [Taiwanese HC: OR=3.17 (95% CI, 2.75-3.67) for Hb >16.5 g/dL in men, OR=3.11 (2.78-3.47) for Hb >14.5 g/dL in women; European Whites: OR=1.89 (1.80-1.98) for Hb >16.24 g/dL in men, OR=2.35 (2.24-2.47) for Hb >14.68 g/dL in women]. The association between stronger risks and increasing Hb deciles was similarly observed with all metabolic components except diabetes. Here we found that both the highest Hb decile groups and contrarily the lowest ones, with respect to the reference, were associated with higher odds of diabetes in both ethnic groups [e.g., Taiwanese HC men: OR=1.64 (1.33-2.02) for Hb >16.5 g/dL, OR=1.71 (1.39-2.10) for Hb <13.5 g/dL; European Whites women: OR=1.39 (1.26-1.45) for Hb >14.68 g/dL, OR=1.81 (1.63-2.01) for Hb <12.39 g/dL]. These findings confirm that elevated Hb concentrations, a potential indicator of iron overnutrition, may play a role in the pathophysiology of MetS and metabolic components.

Change orders have received considerable attention from researchers thus far, but none have considered pricing strategies of change orders through the interaction between general contractors and subcontractors. Previous studies found that contractors’ opportunistic bidding considering beyond-contractual reward (BCR) in the execution stage can be reduced by improving the construction management system and strengthening the supervision of contractors’ performance. However, the BCR remains in ecology of construction engineering. This study proposes an integrated evolutionary game theory-system dynamics model (ET-SD model) and simulates the pricing strategy of change orders between general contractors and subcontractors to explore the root cause of BCR phenomenon. Sensitivity analysis on the evolutionary dynamics of payoff is explored. Results reveal that change orders with BCR maintain Nash equilibrium and evolutionary stable strategy (ESS) unless changing the payoff structure between general and subcontractors’ pricing strategies. This study presents important managerial insights from the evolutionary game perspectives, nature of change orders, and payoff of the alternative.

Quantitative determination of the critical size of inclined coal pillar in old goaf water affected area is of great significance for water damage prevention and safe mining. The critical size of inclined waterproof coal pillar is derived by using theoretical analysis, numerical calculation and field engineering practice for the stability of the waterproof coal pillar in old goaf water affected area of 1303 working face of Dananhu I mine in Xinjiang region. Firstly, a force model of inclined waterproof coal pillar was established to reveal the law that the critical size of the coal pillar increases with the increase of coal seam inclination under the action of asymmetric load. Then, numerical simulation was applied to reveal the dynamic evolution process of plastic deformation-destabilization-destruction of section coal pillar under the influence of mining and single-side water pressure, and the critical size of waterproof coal pillar in study area was determined to be 19.09m. Finally, measures such as pumping and pressure relief and slurry reinforcement were adopted to reduce the deformation rate of the roadway on side of waterproof coal pillar, which ensured the stability of the coal pillar and roadway and the safe recovery of the working face.

For many decades, X-ray diffraction (XRD) has been used for material characterization. With the recent development in material science understanding and technology, various new materials are being developed, which requires upgrading the existing analytical techniques such that intricate problems can be solved. Although, XRD is a well-established non-destructive technique, it still requires further improvements in its characterization capabilities, especially when dealing with complex mineral structures. The present review conducts comprehensive discussions on atomic crystal structure, XRD principle, its applications, uncertainty during XRD analysis, and required safety precautions, all in one place. It further discusses the future research directions, especially the use of artificial intelligence and machine learning tools for improving the effectiveness and accuracy of XRD technique for mineral characterization. It has been focused that how XRD patterns can be utilized for a thorough understanding of the crystalline structure, size, and orientation, dislocation density, phase identification, quantification, and transformation, information about lattice parameters, residual stress, and strain, and thermal expansion coefficient of materials. All these important discussions on XRD for mineral characterization are compiled in this short yet comprehensive review that would benefit specialists and engineers in the chemical, mining, iron, metallurgy, and steel industries.

Plants are immobile, and, to overcome harsh environmental conditions, such as drought, salt, and cold, they have evolved complex signaling pathways. Abscisic acid (ABA), an isoprenoid phytohormone, is a critical signaling mediator that regulates diverse biological processes in various organisms. Significant progress has been made in the determination and characterization of key ABA-mediated molecular factors involved in different stress responses, including stomatal closure and developmental processes, such as seed germination and bud dormancy. Since ABA-signaling is a complex signaling network that integrates with other signaling pathways, the dissection of its intricate regulatory network is necessary to understand the function of essential regulatory genes involved in ABA signaling. In the present review, we focus on two aspects of ABA signaling. First, the perception of the stress signal (abiotic and biotic) and the response network of ABA-signaling components that transduce the signal to the downstream pathway to respond to stress tolerance, regulation of stomata, and ABA signaling component ubiquitination. Second, ABA-signaling in plant development processes, such as lateral root growth regulation, seed germination, and flowering time regulation. Examining such diverse signal integration dynamics could enhance our understanding of the underlying genetic, biochemical, and molecular mechanisms of ABA signaling networks in plants.

Polydimethylsiloxane with hydroxy groups was functionalized to form functionalized polydimethylsiloxane, which subsequently underwent an addition reaction with isophorone diisocyanate to form the prepolymer. Next, 3-aminopropyltriethoxysilane (APTS) reacted with 3-glycidoxypropyltrimethoxysilane (GPTS) to produce bridged polysilsesquioxanes, and the sol–gel technology was employed to form hyperbranched polysiloxane nanoparticles with hydroxy groups, which was used as the additive. The hyperbranched polysiloxane and the prepolymer containing NCO functional groups then underwent an addition reaction to produce the hybrid materials. Fourier-transform infrared spectroscopy and 29Si nuclear magnetic resonance were used to characterize the structure of the polyurethane hybrid. Regarding thermal stability, after the hyperbranched polysiloxane nanoparticles was introduced, the integral procedural decomposition temperature increased from 348 ºC for polyurethane matrix to 859 ºC for the hybrid material. The results revealed that the thermal stability of the hybrid material substantially increased by approximately 247%.

Fibrillin (FBN) is a plastid lipid-associated protein found in photosynthetic organisms from cyanobacteria to plants. In this study, 10 CsaFBN genes were identified in genomic DNA sequences of cucumber (Chinese long and Gy14) through database searches using the conserved domain of FBN and the 14 FBN genes of Arabidopsis. Phylogenetic analysis of CsaFBN protein sequences showed that there was no counterpart of Arabidopsis and rice FBN5 in the cucumber genome. FBN5 is essential for growth in Arabidopsis and rice; its absence in cucumber may be because of incomplete genome sequences or that another FBN carries out its functions. Among the 10 CsaFBN genes, CsaFBN1 and CsaFBN9 were the most divergent in terms of nucleotide sequences. Most of the CsaFBN genes were expressed in the leaf, stem, and fruit. CsaFBN4 showed the highest mRNA expression levels in various tissues, followed by CsaFBN6, CsaFBN1, and CsaFBN9. High-light stress combined with low temperature decreased photosynthetic efficiency and highly induced transcript levels of CsaFBN1, CsaFBN6, and CsaFBN11, which decreased after 24 h treatment. Transcript levels of the other seven genes were changed only slightly. This result suggests that CsaFBN1, CsaFBN6, and CsaFBN11 may be involved in photoprotection under high-light conditions at low temperature.

A common spinal condition, spondylolisthesis is the presence of a relative back or forth displacement between the upper and lower vertebra due to one vertebra being oriented away from the smooth curvature of a normal spine. Aging-related illnesses such as degenerative spondylolisthesis are especially burdensome on social welfare and health-care systems in an aging society, especially radiologists and clinical physicians. Therefore, we proposed a computer aided diagnosis algorithm, named LumbarNet, for vertebral slippage detection on clinical X-ray images. Collaborating with i) a P-grade, ii) a piecewise slope detection scheme, and iii) a dynamic shift detection routine, LumbarNet was thus specialized for analyzing complex structural patterns in lumbar spine X-ray images and outcompeted other U-Net based methods. Extensive experiments on lumbar spine X-ray images in standard clinical practices showed that LumbarNet achieved a mean intersection over union value of 0.88 in vertebral region detection and an accuracy of 88.83% in vertebral slippage detection.

Postoperative adhesive arachnoiditis is an inflammatory response of the spinal leptomeninges that occurs after surgery, resulting in scar formation in the avascular nature of the arachnoid layer. Clinical manifestations of this condition include pain, sensory deficits, motor dysfunction, reflex abnormalities, and bladder/bowel impairments. In MRI scans, the signs of postoperative adhesive arachnoiditis can vary, but some specific indicators can assist surgeons in locating the lesion and planning surgical interventions more accurately. In this report, we reported a 37-year-old man with postoperative adhesive arachnoiditis after two surgeries for Chiari I malformation, demonstrating that the gradually-forming the delta cord sign with sequential syringomyelia. During the intraoperative examination, we identified the presence of the delta cord sign, which was formed by an arachnoid scar that was tethering the dorsal spinal cord to the dura. This discovery allowed us to precisely pinpoint the location of the arachnoid scar, thereby providing valuable guidance to avoid any unnecessary exploration of innocent structures during the procedure. Other localization signs were also reviewed.

Biocompatible and biodegradable poly(butylene succinate-co-adipate) (PBSA)/hexadecylamine-modified PPZn (m-PPZn) nanocomposites were prepared using a melt mixing process. Experimental results of wide-angle X-ray diffraction and transmission electron microscopy revealed that the stacking layers of the m-PPZn were partially intercalated and partially exfoliated into the PBSA polymer matrix. The isothermal crystallization kinetics of PBSA/m-PPZn nanocomposites were studied at the temperature range of 62−70 °C and the half-time for crystallization of 3 wt % PBSA/m-PPZn nanocomposite was reduced by 27−35% compared with that of pure PBSA. This finding suggests that the incorporation of m-PPZn might cause the heterogeneous nucleation and the subsequent crystallization growth, which enhances the isothermal crystallization rate of PBSA/m-PPZn nanocomposite. The biodegradation rates of PBSA using Lipase from Pseudomonas sp. increase as the contents of m-PPZn increase. The degradation behavior of the neat PBSA investigated using the change of weight-average molecular weight belongs to exo-type hydrolysis activity. It is necessary to point out that the change of degree of crystallinity and degradation rate are almost linearly proportional to the loading of hexadecylamine-modified PPZn. This finding would provide an important information for the manufacturing biodegradable PBSA nanocomposites.

A suitable waste management strategy is crucial for a sustainable and efficient circular economy in the construction sector, and requires precise data on the volume of demolition waste (DW) gen-erated. Therefore, we developed an optimal machine learning (ML) model to forecast the quantity of recycling and landfill waste based on the characteristics of DW. A dataset comprising infor-mation on the characteristics of 150 buildings, demolition equipment utilized, and volume of five waste types generated (i.e., recyclable mineral, recyclable combustible, landfill specified, and landfill mix waste, and recyclable minerals) was constructed. ML models were developed to predict the quantities of such waste. Artificial neural network, decision tree, gradient boosting machine, k-nearest neighbors, linear regression, random forest (RF), and support vector regression were applied, and optimal models were derived via hyperparameter tuning. The RF model demonstrated superior performance. In both validation and test phases, the “recyclable mineral waste” and “recyclable combustible waste” models achieved accuracies of of 0.987 and 0.972, re-spectively. The “recyclable metals” and “landfill specified waste” models achieved accuracies of 0.953 and 0.858 or higher, respectively. Moreover, the “landfill mix waste” model exhibited an accuracy of 0.984 or higher. SHapley Additive exPlanations analysis highlighted floor area as the primary input variable influencing model performance. The type of equipment employed in demolition emerged as another crucial input variable impacting the volume of recycling and landfill wastes generated. The developed model can provide precise data on waste management, thereby facilitating the decision-making process for industry professionals.

Curcumin, a natural polyphenolic compound isolated from the plant Curcuma longa, is known to induce autophagy in various cancer cells, including lung cancer. In the present study, we also confirmed by LC3 immunofluorescence and immunoblotting analyses that curcumin triggers autophagy in human lung adenocarcinoma A549 cell line. In parallel with autophagy induction, gene expression of human GD3 synthase (hST8Sia I) responsible for ganglioside GD3 synthesis was markedly elevated in response to curcumin in A549 cells. To investigate transcriptional activation of hST8Sia I associated with autophagy formation in curcumin-treated A549 cells, functional characterization of the 5’-flanking region of the hST8Sia I gene was carried out using luciferase reporter assay system. Deletion analysis demonstrated that the -1146 to -646 region, which includes putative c-Ets-1, CREB, AP-1 and NF-κB binding sites, functions as the curcumin-responsive promoter of hST8Sia I in A549 cells. Site-directed mutagenesis and chromatin immunoprecipitation assay demonstrated that the NF-κB binding site at -731 to -722 was indispensable for the curcumin-induced hST8Sia I gene expression in A549 cells. Moreover, the transcriptional activation of hST8Sia I by curcumin A549 cells was strongly inhibited by compound C, an inhibitor of AMP-activated protein kinase (AMPK). These results suggest that curcumin controls hST8Sia I gene expression via AMPK signal pathway in A549 cells.

Polluted rivers are a primary problem in Changhua County, Taiwan, due to rapid and massive developments in agriculture and industry. In this study, samples consisted of water influent from the Yangzi-Cuo River, Ci-Tong Jiao, Changhua County. Ecology technology, a combination of gravel contact oxidation and surface flow constructed wetlands, was employed to enhance the water quality. Ecology technology is a useful and ordinary process that focuses on original treatment of pollution through chemical, physical, and biological procedures based on the mediums of soil, plant, water, and microorganisms from pure environments. Moreover, this study aimed to minimize the river pollution index (RPI) of the Yangzi-Cuo River by using combinations of gravel contact oxidation and surface flow constructed wetlands. The inflow volume of the water samples in situ was found to be 1534–2261 cubic meters per day (CMD). The pollution in the water sample mostly involved suspended solid (SS), ammoniacal nitrogen (NH₃–N), total phosphorus (TP), total nitrogen (TN), and biochemical oxygen demand (BOD), and the values of the above indexes were found to be 10.0–26.7 mg/L, 0.9–14.0 mg/L, 1.2–14.1 mg/L, 11.1–18.2 mg/L, and 0.5–3.6 mg/L, respectively. Efficiencies of pollution elimination in SS, NH₃–N, TP, TN, and BOD were found to be 24.2–93.1%, 58.3–86.2%, 5.2–85.0%, 59.4–77.2%, and 46.3–76.4%, correspondingly, after purification treatment via ecology technology. Thus, ecology technology is a valid means of purification treatment for polluted rivers.

Conventional methods of crop mapping need ground truth information to train the classifier. Thanks to the frequent acquisition allowed by recent satellite missions (Sentinel 2), we can identify temporal patterns that depend on both phenology and crop management. Some of these patterns are specific to a given crop and thus can be used to map it. Thus, we can substitute ground truth information used in conventional methods with agronomic knowledge. This approach was applied to identify irrigated permanent grasslands (IPG) in the Crau area (Southern France) which play a crucial role in groundwater recharge. The grassland is managed by making three mows during the May-October period which leads to a specific temporal pattern of leaf area index (LAI). The mowing detection algorithm was designed using the temporal LAI signal derived from Sentinel 2 observations. The algorithm includes some filtering to remove noise in the signal that might lead to false mowing detection. A pixel is considered a grassland if the number of detected mows is greater than 1. A data set covering five years (2016-2020) was used. The detection mowing number was done at the pixel level and then results are aggregated at the plot level. A validation data set including 780 plots was used to assess the performances of the classification. We obtained a Kappa index ranging between 0.94-0.99 according to the year. These results were better than other supervised classification methods that include training data sets. The analysis of land-use changes shows that misclassified plots concern grasslands managed less intensively with strong intra-parcel heterogeneity due to irrigation defects or year-round grazing. Time series analysis, therefore, allows us to understand different management practices. Real land-use change in use can be observed, but long time series are needed to confirm the change and remove ambiguities with heterogeneous grasslands.

Solid state sensors having timing capabilities are becoming an absolute need in particle tracking techniques of future experiments at colliders. In this sense, silicon sensors having 3D structure are becoming an interesting solution, due to their intrinsic speed and radiation resistance. A characteristics of such devices is the strict dependence of their performance on their geometric structure, which can be widely optimised by design, thus requiring suitable tools for an accurate modeling of their behaviour. This paper illustrates the development, performance and use of the TCoDe simulator, specifically dedicated to the fast simulation of carrier transportation phenomena in solid state sensors. Some examples of its effectiveness in the design and analysis of 3D sensors is also given.

Artificial sweeteners are widely used food ingredients in beverages and drinks to lower calorie intake which in turn prevent lifestyle diseases such as obesity. Epidemiological evidences suggest that an overdose of artificial sweeteners could result to adverse effects after consumption. Thus, our study aims to systematically explore the potential adverse effects of eight commercial artificial sweeteners, including acesulfame-K, alitame, aspartame, sodium cyclamate, dulcin, neotame, saccharin and sucralose on cardiac performances of zebrafish (Danio rerio) and Daphnia as model animals. Embryonic zebrafish and Daphnia were exposed to eight artificial sweeteners at 100 ppb concentrations and their cardiac performance (heart rate, ejection fraction, fractional shortening, stroke volume, cardiac output and heartbeat regularity) were measured and compared. Saccharin significantly increased the heart rate of zebrafish larvae while a significant decrease was observed in Daphnia. Significant increase was also noted in zebrafish heart rate variability after incubation in acesulfame K, dulcin, sodium cyclamate, and sucralose. However, a significant increase in Daphnia was only observed after incubation in dulcin. Based on Principal Component Analysis (PCA) and hierarchical clustering results, several artificial sweetener samples were species-specific to zebrafish and Daphnia. Our study demonstrates the potential adverse physiological effects of artificial sweeteners in cardiovascular systems of zebrafish larvae and Daphnia.

Arid- and semi-arid Central Asia is particularly sensitive to climate change. The changes in extreme precipitation in Central Asia stemming from climate warming are the subject of intense debate within the scientific community. This study employed a Morlet wavelet analysis to examine the annual occurrence number of extreme precipitation in Central Asia from May to September during the period of 1951–2005. Their modulating planetary-scale climate modes were identified by using a linear regression analysis. Two major scales of the temporal variability were derived: 2–3.9 yr and 4–6 yr. The dominant variability was 2–3.9-yr scale and was associated with the negative phase of the Polar/Eurasia (POL) pattern. The 4–6-yr scale provided a secondary contribution and was closely linked to the negative phase of the North Atlantic Oscillation (NAO). These planetary climate modes acted as precursors of extreme precipitation over Central Asia. The negative phase of POL directly contributed to a negative height anomaly over Central Asia, which was intimately related to extreme precipitation. In contrast, the negative NAO phase possibly manifested as a Rossby wave source, which was subsequently exported to Central Asia through a negative–positive–negative Rossby wave train.

Background: Neurological disorders are the leading cause disability in Australia and the world. Combating the perceived difficulty of neurology or “neurophobia” and improving physician education is a key component in addressing this problem. We aim to conduct the first study to identify whether neurophobia exists in medical students and junior doctors in an Australian population and try to identify factors that may contribute to this in this population. Methods: A 24 question online validated survey was distributed via email broadcast to all medical students and junior doctors at a metropolitan tertiary care centre in Australia. Responses were collected over 6 weeks with weekly reminder emails for 4 weeks after the initial invitation email. Results: 114 medical students and junior doctors participated in the study. Participants perceived neurology as the most difficult medical speciality compared to 10 other medical specialties (p=0.001). The top three factors contributing to this perceived difficulty were: a lack of understanding of neuroanatomy, lack of diagnostic certainty and lack of clinical exposure. 65% of the participants stated that they had too little planned teaching in neurology with only 36% of the participants having performed a neurology rotation during medical school. Conclusion: The prevalence of neurophobia in this Australian cohort of medical students and junior doctors is consistent with previous findings from around the world. This concerning finding requires further examination into the contributing factors in order to created trials of targeted interventions in order to resolve this.

People with sickle cell disease (SCD) are at greater risk of severe illness and death from respiratory infections, including COVID-19 than people without SCD (Centers for Disease Control and Prevention, USA). Vaso-occlusive crises (VOC) in SCD and severe SARS-CoV-2 infection are both characterized by thrombo-inflammation mediated by endothelial injury, complement activation, inflammatory lipid storm, platelet activation, platelet-leukocyte adhesion, and activation of the coagulation cascade. Notably, lipid mediators, including thromboxane A2, significantly increase in severe COVID-19 and SCD. In addition, the release of thromboxane A2 from endothelial cells and macrophages stimulates platelets to release microvesicles which are harbingers of multicellular adhesion and thrombo-inflammation. Currently, there are limited therapeutic strategies targeting platelet-neutrophil activation and thrombo-inflammation in either SCD or COVID-19 during acute crisis. However, due to many similarities between the pathobiology of thrombo-inflammation in SCD and COVID-19, therapies targeting one disease may likely be effective in the other. Therefore, the preclinical and clinical research spurred by the COVID-19 pandemic, including clinical trials of anti-thrombotic agents, are potentially applicable to VOC. Here, we first outline the parallels between SCD and COVID-19; second, review the role of lipid mediators in the pathogenesis of these diseases and lastly, examine the therapeutic targets and potential treatments for the two diseases.

Confronting the dual challenges of rapid urbanization and climate change, although extensive research has investigated the influencing factors and practical strategies of urban carbon emissions and urban vibrancy, respectively, the unclear mutual nexus between them and the development strategy of collaborative optimization requires further in-depth analysis. This study explores the delicate balance between urban vibrancy and low-carbon sustainability within the confines of Beijing’s Fifth Ring Road. By integrating OpenStreetMap, land use, population, and building carbon emission data, we have developed a reproducible method to estimate total carbon emission and emission intensity per capita. Furthermore, we have introduced vibrancy index data to distinguish the vibrancy evaluation of residential and non-residential land and applied cross-combinational classification technology to dissect the spatial correlation between urban carbon emissions and urban vibrancy. The results reveal that the four combination typologies show more significant differences and regularity in residential land. Based on the discovery of spatial correlation, this study puts forward corresponding development strategy suggestions for each typology based on geographical location and the requirements of urban development policies of these four combination typologies. In conclusion, our study highlights the importance of integrating carbon emissions and urban vibrancy comprehensively in sustainable urban planning and proposes that various land use combinations need targeted development strategies to achieve this goal, which need to consider population, energy, service facilities, and other diverse aspects.

Bowlby’s (1969/1982) attachment theory has been employed as a broad and integrative framework to explore human wellness across a range of disciplines. Attachment theory has even been labelled one of the last surviving “grand theories” not to have been completely dismissed, replaced, or extensively reworked (e.g., Carr, 2012; Mercer, 2011). However, despite the ubiquitous nature of some of the theory’s fundamental tenets, there are always possibilities for new conceptual development, extension, and revision. In this paper, we critically explore the idea of “context-specific” attachment within parent-child relationships. We briefly outline critical assumptions and key areas of attachment and articulate potential rationale, conceptualisation, and relevance of contextual attachment.

The present study examined and compared the effects of high- and low-molecular weight (MW) chitosan, a nutraceutical, on intestinal and liver lipid metabolism in rats fed with high-fat diet. Both high- and low-MW chitosan decreased liver weight, elongated small intestine, improved the dysregulation of blood lipids and liver fat accumulation, and increased fecal lipid excretion in high-fat diet-fed rats. Supplementation of both high- and low-MW chitosan significantly inhibited the decreased phosphorylated AMP-activated protein kinase (AMPK)α and peroxisome proliferator-activated receptor (PPAR)α protein expressions and the increased lipogenesis/cholesterogenesis-associated protein expressions (sterol regulatory element binding protein (SREBP)1c, SREBP2, and PPARγ) and the decreased apolipoprotein (Apo)E and microsomal triglyceride transfer protein (MTTP) protein expressions in the livers of high-fat diet-fed rats. Both high and low-MW chitosan supplementation could also suppress the increased MTTP protein expression and the decreased angiopoietin-like protein (Angptl)4 protein expression in the intestines of high-fat diet-fed rats. Comparison between high and low-MW chitosan, high-MW chitosan has a higher efficiency than low-MW chitosan on the inhibition of intestinal lipid absorption and the increase of hepatic fatty acid oxidation, which can improve liver lipid biosynthesis and accumulation.

Early debridement and stabilization for pyogenic spondylodiscitis allow early mobilization of the patient and prevent subsequent spinal deformity. Tantalum (Ta) trabecular metal (TM) components have several potential advantages over conventional implant materials, such as its uniformity and structural continuity, strength, low stiffness, high porosity, high coefficient of friction and tantalum trabecular metal enhances the host defense mechanism by increasing leukocyte chemotaxis, phagocytosis, and the bacterial killing rate. A single-stage surgery with a tantalum trabecular metal cage combining two different approaches is sufficient to maintain vertebral stability. This retrospective cohort study included 57 patients, 31 (54%) patients were treated with single-stage debridement and reconstruction with trabecular metal cages, and 26 (45.6%) patients received spine surgery without trabecular metal cages received surgery between January 2018 and March 2021 in our tertiary academic teaching hospital. The CRP values dropped borderline significantly in the TM cage group compared with the non-TM cage group postoperatively. In patients with spondylodiscitis, it is advisable to perform single-stage debridement and reconstruction with a trabecular metal cage, which allows abscess drainage and rapid mobilization, prevents deformity.

It is a truism that whole energy system models underpin the development of policies for energy system decarbonisation. But recent reviews have thrown doubt on the appropriateness of such models for addressing the multiple goals for future energy systems, in the face of emergent real-world complexity and the evolution of stakeholder’s priorities. Without an understanding of the changing priorities of policy makers and expectations of stakeholders for future systems, system objectives and constraints are likely to be ill-defined, and there is a risk that models may be inadvertently instrumentalised. Adopting a system architecture perspective, the authors have undertaken a three-year programme of research to explore strategies for decarbonising heat in the UK, with interaction with and elicitation of needs from stakeholders at its heart. This paper presents the procedure, methods, and results of an exercise in which experts from stakeholder organisations across the energy system were interviewed. Analysis of interview data reveals two broad approaches to heat decarbonisation which can be broadly defined as either adaptive or transformative. Specific insights gained from these interviews enabled our modelling teams to refocus their work for exploration with a wider circle of stakeholders. Results suggests that this iterative approach to formalising model-policy interaction could improve the transparency and legitimacy of modelling and enhance its impact on policy making.

In recent years, the demand for coffee has increased tremendously. During the production process, green coffee beans are traditionally screened manually for defective beans before they are packed into coffee bean packages; however, this method is not only time-consuming but also increases the rate of human error due to fatigue. Therefore, this paper proposed a lightweight deep convolutional neural network (LDCNN) for the quality detection system of green coffee beans, which combined depthwise separable convolution (DSC), squeeze-and-excite block (SE block), skip block, and other frameworks. To avoid the influence of low parameters of the lightweight model caused by the model training process, rectified Adam (RA), lookahead (LA), and gradient centralization (GC) were included to improve efficiency; the model was also put into the embedded system. Finally, the local interpretable model-agnostic explanations (LIME) model was employed to explain the predictions of the model. The experimental results indicated that the accuracy rate of the model could reach up to 98.38% and the F1 score could be as high as 98.24% when detecting the quality of green coffee beans. Hence, it can obtain higher accuracy, lower computing time, and lower parameters. Moreover, the interpretable model verified that the lightweight model in this work is reliable, providing the basis for screening personnel to understand the judgment through its interpretability, thereby improving the classification and prediction of the model.

Synthetic cathinones, derived from cathinone found in the plant Catha edulis, represent the second-largest and most frequently seized group of new psychoactive substances. They are considered as β-keto analogs of amphetamine, sharing pharmacological effects with amphetamine and cocaine. This review describes the neurotoxic properties of synthetic cathinones, encompassing their capacity to induce neuroinflammation, dysregulate neurotransmitter systems, and alter in monoamine transporters and receptors. Additionally, it discusses the rewarding and abuse potential of synthetic cathinones drawing from findings obtained through various preclinical animal models, contextualized with other classical psychostimulants. The review also offers an overview of current abuse trends of synthetic cathinones on the illicit drug market, specifying the aspects covered, and underscores the risks they pose to public health.

Due to the rapid development and popularity of the Internet, cloud computing has become an indispensable application service. However, how to assign various tasks to the appropriate service nodes is an important issue. Based on the reason above, an efficient scheduling algorithm is necessary to enhance the performance of system. Therefore, a Three-Layer Cloud Dispatching (TLCD) architecture is proposed to enhance the performance of task scheduling. In first layer, the tasks need to be distinguished to different types by their characters. Subsequently, the Cluster Selection Algorithm is proposed to dispatch the task to appropriately service cluster in the secondly layer. Besides, a new scheduling algorithm is proposed to dispatch the task to a suitable server in a server cluster to improve the dispatching efficiency in the thirdly layer. Basically, the TLCD architecture can obtain better task completion time than previous works. Besides, our algorithm and can achieve load-balancing and reliability in cloud computing network.

The International Health Regulations (2005) promote national capacity in core institutions so countries can better detect, respond to and recover from public health emergencies. In accordance with the ‘all hazards’ approach to public health risk, this systematic review examines poisoning and toxic exposures in Myanmar. A systematic literature search was undertaken to find articles pertaining to poisoning in Myanmar published between 1998 and 2020. A number of poisoning risks are identified in this review including snakebites, heavy metals, drugs of abuse, agro-chemicals and traditional medicine. Patterns of poisoning presented in the literature diverge from poisoning priorities reported in other lower-middle income countries in the region. The expe-rience of professionals working in a Yangon-based poison treatment unit indicates that frequently observed poisoning as a result of substances including pharmaceuticals, methanol, and petroleum products were absent from the literature. Other notable gaps in the available research include assessments of the public health burden of poisoning through self-harm, household exposures to chemicals, paediatric risk and women’s occupational risk of poisoning. There is a limited amount of research available on poisoning outcomes and routes of exposure in Myanmar. Further inves-tigation and research is warranted to provide a more complete assessment of poisoning risk and incidence.

This paper shares our work in developing and implementing an immersive gamification training platform for students who undergo manufacturing shopfloor training at the School of Engineering, Nanyang Polytechnic, Singapore. In this gamification training platform, we developed a virtual manufacturing shopfloor that is identical to the actual shopfloor located in the school. Students have the freedom to learn the manufacturing shopfloor operations and safety acts through the various game scenarios and training tasks which include workshop safety, CNC machine introduction, CNC machining dynamics, MES, etc. In addition, the assessment feature with immediate feedback were embedded within the gamification platform, which aim to help students to assess their level of understanding and help teachers to monitor the learning progress of their students. To investigate the impact of this gamification training platform on students’ learning outcome and motivation in manufacturing shopfloor technologies and safety acts, a pilot study was conducted in AY2018 semester 2 for a total 134 students from 4 classes of digital & precision engineering diploma. It is found that gamification can be integrated effectively into manufacturing education to motivate students and enhance their learning effectiveness. Based on the collected data from the technical quizzes and satisfactory survey, the results showed that the integration of gamification into the classroom learning not only added a stimulating and captivating game-like layer to the learning experience of the students, but also provided a safe environment for students to learn without fear of making errors. Challenges faced in implementing this gamification training platform will also be discussed in this paper.

Bright morning light (BML) entrains the body clock, modulates circadian rhythm, and improves sleep-wake disturbances. However, its impact on the autonomic nervous system (ANS) at night remains unclear. Hence, we investigated the effects of BML exposure on activities of the parasympathetic nervous system (PSNS) and sympathetic nervous system (SNS) at night. This non-randomized controlled pilot study included participants ≥60 years, diagnosed with a type of dementia or cognitive disorder. We excluded participants with pacemakers. The treatment group received 2500 lx BML, whereas the control group received approximately 200 lx of general lighting. We measured the heart rate variability to quantify ANS activity. The treatment group displayed significantly increased high-frequency (HF) power (Roy's largest root=2.44; P<.01) and insignificantly decreased normalized low-frequency (LF%) power. The corresponding low-frequency/high-frequency ratio (LF/HF), insignificant decrease, and cognitive function were correlated with PSNS activity (Roy's largest root=3.92; P<.01), which is effective for moderate dementia. BML exposure reduced SNS activity and enhanced PSNS activity at night, which consequently affected cognitive function. Furthermore, the light washout intervention markedly increased SNS activity at night. BML therapy may be a useful clinical tool for alleviating the deterioration of cognitive function.

This study focuses on the analyses of nano-twinned Copper (Cu) films deposited through magnetron sputtering on Silicon Carbide (SiC) chips. The investigation encompasses the utilization of Chromium (Cr) adhesive layer coupled with varying voltage bias conditions. The goal is to comprehensively examine the influence of adhesive layer and negative bias voltages, contributing to an enhanced understanding of materials engineering and bonding technologies for advanced applications. The formation of a nanotwinned structure and (111) surface orientation can be properly controlled by applied substrate bias. High density nanotwinned structures were introduced into Cu films sputtered on SiC substrates with 82.3% of (111)-orientation proportion at -150 V much higher than the Cu film sputtered with another substrate bias. It is concluded that the sputtered Cu nanotwinned film formed with -150 V bias voltage has the potential to be employed as the interlayer for low temperature direct bonding.

In this study, a composite flame retardant was created by combining fish scale (FS), fishery waste, and ammonium polyphosphate (APP), a commercially available flame retardant. The composite flame retardant was added to epoxy resin (EP) to form an EP/APP/FS composite that prevents burns and is environmentally friendly. The use of FS conforms to the concept of circular economy and lowers costs by reducing the consumption of APP. Thermogravimetric analysis (TGA), integral procedural decomposition temperature (IPDT), pyrolysis kinetics, limiting oxygen index (LOI), the Underwriters Laboratories 94 (UL94) flammability test, scanning election microscopy, Raman spectroscopy, and energy-dispersive X-ray spectroscopy were used to determine the thermal properties, flame retardant properties, flame retardant mechanism, char morphology, and composition of the composites. The TGA results indicated that the addition of 40% flame retardant raised the char residue from 16.45 wt% (pure EP) to 36.07 wt%, IPDT from 685.6 °C (pure EP) to 1143.1°C, LOI from 21% (pure EP) to 30%, and UL94 classification from fail (pure EP) to V-0. These results suggest an increase in char residue, which indicates better protection of the polymer matrix material. The improvements in IPDT, LOI, and UL94 classification, which indicate greater thermal stability, lower flammability (from flammable to fireproof), and higher flammability rating (from fail to V-0), respectively, suggest that the composite material has favorable thermal properties and is less inflammable.

This research presents a novel approach for estimating soil organic carbon (SOC) content in agricultural soils using a photocatalytic Chemical Oxygen Demand (PeCOD) analyzer integrated with Geographic Information System (GIS) technology for spatial analysis. The PeCOD method, which relies on photochemical oxidation of organic carbon, demonstrated an uncanny correlation between its values and SOC content, making it a quick and accurate way to estimate SOC levels. Finer materials, such as clayey soils, demonstrated higher SOC content compared to coarser ones and decreased with increasing soil depth. GIS georeferencing enabled precise mapping of SOC distribution and identification of hotspot areas with high SOC content. This study highlights the significance of soil texture and depth on SOC distribution and emphasizes its significance within geological context when studying soil properties. Research results have practical ramifications for sustainable agriculture, climate change mitigation and soil health management - providing farmers and land managers with strategies that increase carbon sequestration while simultaneously improving soil health. Integrating PeCOD analyzer technology with GIS technology offers promising avenues for advanced soil carbon monitoring practices that promote climate-smart agricultural practices.

Novel genetic and epigenetic factors involved in the development and prognosis of idiopathic pulmonary fibrosis (IPF) have been identified. We previously observed that EPB41L3 increased in the lung fibroblasts of IPF patients. Thus, we investigated the role of EPB41L3 in IPF by comparing EPB41L3 mRNA and protein expression of lung fibroblast between patients with IPF and controls. We also investigated the regulation of the epithelial-mesenchymal transition (EMT) in an epithelial cell line (A549), and the fibroblast-to-myofibroblast transition (FMT) in a fibroblast cell line (MRC5), by overexpressing and silencing EPB41L3. EPB41L3 mRNA and protein levels, as measured by RT-PCR, real-time PCR, and western blot, were significantly higher in fibroblasts derived from 14 IPF patients than in those from 10 controls. The mRNA and protein expression of EPB41L3 was upregulated during transforming growth factor-β-induced EMT and FMT. Overexpression of EPB41L3 in A549 cells using lenti-EPB41L3 transfection suppressed the mRNA and protein expression of N-cadherin and COL1A1. Treatment with EPB41L3 siRNA upregulated mRNA and protein expression of N-cadherin. Overexpression of EPB41L3 in MRC5 cells using lenti-EPB41L3 transfection suppressed mRNA and protein expression of fibronectin and α-SMA. Finally, treatment with EPB41L3 siRNA upregulated mRNA and protein expression of FN1, COL1A1, and VIM. Overall, these data strongly support an inhibitory effect of EPB41L3 on the process of fibrosis and suggest therapeutic potential of EPB41L3 as an anti-fibrotic mediator.

New antimicrobial approaches are essential to counter antimicrobial resistance. The drug development pipeline is exhausted with emergence of resistance resulting in unsuccessful trials. The lack of an effective drug developed from the conventional drug portfolio has mandated the introspection into the list of potentially effective unconventional alternate antimicrobial molecules. Alternate therapies, that are clinically explicable forms include monoclonal antibodies, antimicrobial peptides, aptamers and phages. Clinical diagnostics optimizes the drug delivery. In the era of diagnostic-based applications, it is logical to draw diagnostic based treatment for infectious diseases. Selection criteria of alternate therapeutics in infectious disease include detection, monitoring of response and resistance mechanism identification. Integrating these diagnostic applications is disruptive to the traditional therapeutic development. The challenges and mitigation methods need to be noted. Applying the goals of clinical pharmacokinetics that include enhancing efficacy and decreasing toxicity of drug therapy this review analyses the strong correlation of alternate antimicrobial therapeutics in infectious diseases. The relationship between drug concentration and the resulting effect defined by the pharmacodynamic parameters are also analyzed. This review analyzes the perspectives of aligning diagnostic initiatives into the use of alternate therapeutics with a particular focus on companion diagnostic applications in infectious diseases.

Early diagnosis of paroxysmal atrial fibrillation (PAF) could suggest patients to receive timely interventions in clinical practice. Various PAF onset prediction algorithms might benefit from accurate heart rate variability (HRV) analysis and machine learning classification but to be challenged in real-time monitoring scenarios. The aim of this study is to present an end-to-end deep learning based PAFNet model that integrates a sliding window technique on raw R-R interval of electrocardiogram (ECG) segments to achieve a real-time prediction of PAF onsets. This integration enable the deep convolutional neural network (CNN) to be customized as a light-weight architecture that accommodates the size of sliding windows simply by altering the input layer, specifically its effectiveness in making a new prediction with each new heartbeat. Catering to potential influence of input sizes, three CNN models were trained using 50, 100, and 200 R-R intervals, respectively. For each model, the performance of automated algorithms was evaluated for PAF prediction using a ten-fold cross-validation. As a results, a total of 56,381 PAFN-type and 56,900 N-type R-R interval segments was collected from publicly accessible ECG databases, and a promising prediction performance of the automated algorithm with a 100 R-R intervals was achieved in terms of the sensitivity of 97.12%, the specificity of 97.77%, and the accuracy of 97.45%, respectively. Importantly, the automated algorithm with a sliding windows step of 1 could process one sample in only 23.1 milliseconds and identify the onset of PAF at least 45 minutes in advance. The present results suggest that the sliding window technique on raw R-R interval sequences along by deep learning based algorithms may offers the possibility of providing an accurate, real-time, and end-to-end clinical tool for mass monitoring of PAF.

The once-held wisdom of the supreme efficiency of one-way streets has been gradually sup-planted by the perceived sustainability of two-way streets in the design of livable cities that prioritizes the safety of pedestrians and thriving of local businesses. However, it is rarely dis-cussed on whether one-way street conversions have truly improved the long-term traffic effi-ciencies on urban street networks, as conflating socioeconomic factors such as vehicular popula-tion growth and induced travel demand may render empirical analysis inconclusive. In this study, microscopic traffic simulations implemented on SUMO platform was performed to ana-lyze the effect of street conversion in Downtown Brickfields, Kuala Lumpur. This approach can control and standardize travel demand in both one-way and two-way street networks, and would therefore give a fairer evaluation by precluding all socioeconomic factors. It was found that one-way streets do not necessarily improve the traffic efficiency of the network, as it is very dependent on the traffic scenario evolution over time. One-way streets perform better at the on-set of traffic congestion due to its higher capacity, but on average, the 4-fold longer travel times that made it harder to clear traffic by getting vehicles to their destinations compared to two-way streets. As time progresses, congestion in one-way streets may become twice as worse compared to two-way streets. This study may contribute to a more holistic assessment of traffic circulation plan designed for smart and livable cities

Blood testing is a crucial medical application. In this study, we applied Raman spectroscopy to test blood samples and obtained complete biological information, including the main components and compositions in these samples. Short-wavelength (532-nm green light) Raman scattering spectroscopy was conducted on samples of normal blood, abnormal blood in 3 types of preparation including whole blood, plasma, and serum, and the underlying information reflected by the biological characteristics detected in each sample type were analyzed. Raman spectroscopy results indicated that normal blood had high hemoglobin content, which suggests that hemoglobin is a major component of blood. Hemoglobin affects blood oxygen level. The characteristic peaks of hemoglobin were observed at 690, 989, 1015, 1182, 1233, 1315, and 1562–1649 cm−1. Analysis of plasma and serum samples indicated the presence of β-carotene, which exhibited characteristic peaks at 1013, 1172, and 1526 cm−1. In addition, surface-enhanced Raman spectroscopy was used to collect biological signals that are difficult to obtain in conventional Raman spectroscopy, including those of small molecules such as hormones, antibodies, and enzymes. Changes in biological information collected in this manner can be used as a basis for potentially diagnosing clinical diseases.

The digital revolution has significantly impacted many Chinese Time-Honored businesses, particularly those slow to adapt to environmental changes, resulting in challenges related to long-term marketing capabilities and declining performance. This study explores the relationship between ambidextrous marketing capabilities and corporate performance. Utilizing a survey involving 91.8% of middle and upper-level managers across 47 Chinese time-honored firms, we construct a research model that demonstrates how the application of ambidextrous marketing capabilities can foster the development of Sustainable marketing capability, which in turn positively influence corporate performance. Sustainable marketing capability mediate the effect of ambidextrous marketing capabilities on corporate performance. Additionally, enhancements in market conditions or legislation may further amplify the impact of Sustainable marketing capability on business performance. In the context of Chinese time-honored firms, these findings offer managerial insights into building Sustainable marketing capability, enhancing performance, and achieving competitive advantages.

Digital dentistry, including CAD/CAM dentistry, is perhaps the most disruptive innovation in dentistry to date. The rapid development of digital dentistry technologies over the past several decades has enabled clinicians to improve patient care by significantly reducing the time necessary for the restorative phase of treatment. Advancements in intra-oral scanning and computer-aided design and manufacturing (CAD/CAM), in conjunction with new dental CAD/CAM ceramic materials, have simplified patient care and made same-day dentistry a reality. This review aims to present the most recent advancements described in current literature as well as to document the successful implementation of digital dentistry into a predoctoral program. The overall process of CAD/CAM same-day dentistry and the accompanying advancements in software and materials were presented and discussed. Implementation of technology and personnel requirements were reviewed. CAD/CAM dentistry has been influential in shaping and improving dental practice and education, and this influence will only continue with time.

Lymphoma diagnoses in the U.S. are substantial, with an estimated 89,380 new cases in 2023, necessitating innovative treatment approaches. Phase 1 clinical trials play a pivotal role in this context. We developed a binary predictive model to assess trial adherence to expected average durations, analyzing 1,089 completed Phase 1 lymphoma trials from clinicaltrials.gov. Using machine learning, the Random Forest model demonstrated high efficacy with an accuracy of 0.7248 and ROC-AUC of 0.7701 for lymphoma trials. Importantly, this model maintained an accuracy of 0.7405 when applied to lung cancer trials, showcasing its versatility. A key insight is the correlation between higher predicted probabilities and extended trial durations, offering nuanced insights beyond binary predictions. Our research contributes to enhanced clinical research planning and potential improvements in patient outcomes in oncology.

A human eye has about 120 million rod cells and 6 million cone cells. This huge number of light sensing cells inside a human eye will continuously produce a huge quantity of visual signals which flow into a human brain for daily processing. However, the real-time processing of these visual signals does not cause any fatigue to a human brain. This fact tells us the truth which is to say that human-like vision processes do not rely on complicated formulas to compute depth, displacement, and colors, etc. On the other hand, a human eye is like a PTZ camera. Here, PTZ stands for pan, tilt and zoom. We all know that in computer vision, each set of PTZ parameters (i.e., coefficients of pan, tilt and zoom) requires a dedicated calibration to determine a camera’s projection matrix. Since there is an infinite number of PTZ parameters which could be produced by a human eye, it is unlikely that a human brain stores an infinite number of calibration matrices for each human eye. Therefore, it is an interesting question for us to answer, which is to say whether simpler formulas of computing depth and displacement exist or not. Moreover, these formulas must be calibration friendly (i.e., easy process on the fly or on the go). In this paper, we disclose an important discovery of a new solution to 3D projection in a human-like binocular vision system. The purpose of doing 3D projection in binocular vision is to undertake forward and inverse transformations (or mappings) between coordinates in 2D digital images and coordinates in a 3D analogue scene. The formulas underlying the new solution are accurate, easily computable, easily tunable (i.e., to be calibrated on the fly or on the go) and could be easily implemented by a neural system (i.e., a network of neurons). Experimental results have validated the discovered formulas.

Visual signals are the upmost important source for robots, vehicles or machines to achieve human-like intelligence. Human beings heavily depend on binocular vision to understand the dynamically changing world. Similarly, intelligent robots or machines must also have the innate capabilities of perceiving knowledge from visual signals. Until today, one of the biggest challenges faced by intelligent robots or machines is the matching in stereovision. In this paper, we present the details of a new principle toward achieving a robust matching solution which leverages on the use and integration of top-down image sampling strategy, hybrid feature extraction, and RCE neural network for incremental learning (i.e., cognition) as well as robust match-maker (i.e., recognition). A preliminary version of the proposed solution has been implemented and tested with data from Maritime RobotX Challenge (www.robotx.org). The contribution of this paper is to attract more research interest and effort toward this new direction which may eventually lead to the development of robust solutions expected by future stereovision systems in intelligent robots, vehicles and machines.

Additive manufacturing (AM) has revolutionized the field of biopolymers by providing a range of opportunities to create complex and intricate structures. Here we provide an overview of developments in biopolymer AM, first in the context of how natural systems have impacted the synthetic processes of AM, and secondly in the context of how synthetically derived structures can be used for biomedical applications. In particular, we explore the range of biopolymers developed for AM, AM techniques for biopolymers, and potential biocompatible medical applications with a focus on four categories of tissue in the human body: skin, bone, heart, and nerve. Despite the current challenges of the technology, exciting results in tissue regeneration, synthetic replacements for natural grafts, and complex dynamic organoids have already come to pass - with many more possible in the future.

One of the key issues in sustainable tourism research is the gap between tourists' expressed friendly attitudes towards sustainable behaviors and their actual behaviors. Although many "low-carbon" themed restaurants have emerged during the low-carbon transformation of the Chinese tourism industry, low-carbon food services have not been significantly improved. This study takes food as the entry point to explore tourists' behavior and attitudes towards low-carbon tourism in relation to food. We conducted two interviews. The first interview was a semi-structured contextual interview with 120 tourists who had experiences in food streets, aim-ing to identify the core user group: low-carbon attitude-friendly tourists with high-carbon food behaviors. The second interviews was an in-depth interview based on grounded theory with 29 core users, analyzing the four main reasons for their high-carbon food behaviors and their re-quirements for low-carbon food services in tourism. Based on this, we extracted four design ele-ments for low-carbon tourism food services: low-carbon information show service, low-carbon service product attractiveness improvement, low-carbon food environment atmosphere creation, and service providers' low-carbon behaviors. Through these four service elements, we constructed a low-carbon tourism food service design framework based on the core users' needs, discussed the mechanism of service elements, and provided service design suggestions accordingly. The re-search results serve tourism providers, low-carbon tourism researchers, and designers.

Microbial populations involved in forming the distinctive precipitates of the S, Fe, Mn, and Ca cycles in the San Diego River watershed reflect an interplay between mineralogy of the rocks in the watershed, sparse rainfall, ground- and surface-water anoxia, and runoff of high sulfate, treated imported water. In the less developed headwaters, Temescal Creek tributary emerges from pyrite-bearing metamorphic rocks, and thus exhibits both an oxidized Fe and reduced S cycle. In the middle reaches, the river moves through developed land where treated, imported high sulfate Colorado River water enters from urban runoff. Mast Park surrounded by caliche-bearing sedimentary rocks is a site where marl is precipitating. Cobbles in riffles in the river are coated black with Mn oxide. When the river encounters deep-seated volcanic bedrock, it wells up to precipitate both Fe and Mn oxides at Old Mission Dam. Then, directly flowing through caliche-laced sedimentary rocks, Birchcreek tributary precipitates tufa. Further downstream, at a site that periodically receives full sunlight, a sulfuretum sets up during the summer when the river is deoxygenated. Such a rich geochemistry results in activity of iron and manganese oxidizing bacteria, sulfur oxidizers and reducers, and cyanobacteria precipitating calcareous marl and tufa.

Coastal wave modeling and forecasting are essential in oceanography, sustainable marine energy, and ocean engineering. Precise forecasting of wave speed and direction are crucial for offshore operations, marine energy, risk management, environmental management, coastal and sustainable maritime management. The coastline of Brunei Darussalam can generate between 15 and 126 Giga Watt of wave energy. In this experimental research, we used two numerical approaches, the finite difference, and spectral element methods, to model and simulate wave speed and direction. We calculated the mean error between numerical and analytical solutions. We proposed a novel, promising, univariate time series forecasting model by combining the Long Short-Term (LSTM) with KerasTuner hyperparameters tuning and optimization techniques. This method helps us to improve the accuracy and efficiency of time-series forecasting.. The experimental data was computed from high-precision Acoustic Doppler Current Profiler (ADCP) sensor data. This research is part of the preliminary feasibility analysis of wave energy production in Brunei Darussalam and net zero commitment for a sustainable environment. Seven independent forecast experiments were performed for wave speed and direction in degree and radian units for 1, 3, 6, 8, 10, 12, and 24 hours. Mean squared error (MSE) was adopted as a metric for both training and testing. The experimental results reveal that the wave speed forecast has the lowest MSE compared to direction, regardless of the unit of measure, but has a longer duration. In addition, the direction forecast in the degree unit has the lowest errors compared to the unit of radians; the latter has a longer running time than the former. The model has delivered optimal results throughout the experiments with minor training and test errors. We conducted a thorough evaluations on two benchmark time series datasets, which include the study dataset and air quality index dataset, to validate the performance of the proposed model with other models. The proposed model outperforms cutting-edge forecasting models, such as the conventional LSTM, ARIMA, and Prophet. The model has the slightest forecast error compared to the existing literature’s result.

Currently, drug screening is primarily based on human cell culture for initial high-throughput screening, and subsequently, rodent model to confirm the biological effects. However, the mammalian system is known for time-consuming and highly-cost to be difficult to perform high-throughput drug screening, which exists a critical gap between in vitro cell-based models and the in vivo mammalian models. Therefore, the zebrafish could bridge this gap in preclinical toxicity screening along the drug development pipeline because of its efficiency. We aimed to develop an in vivo zebrafish platform for rapid drug screening. Zebrafish, due to its high genomic conservation with mammals and rapid development and differentiation, it has many advantages, such as short life span, large number of offspring and low cost, easy manipulation for generating transgenic species, to serve as animal model for disease-based research. In 96-well microplates, zebrafish embryos were incubated with small molecular compounds that affected bone mineralization. The level of osteogenic mineralization was evaluated by fluorescent dye staining and quantified by image analysis software. Quantitative real time-PCR (qRT-PCR) was performed to evaluate the biological pathways involved in bone metabolism at the molecular level. The system was validated by demonstrating that response to alendronate and Dorsomorphin in zebrafish. In our study, we screened for 24 compounds within the CYCU-1120~1152 chemical library and identified 3 compounds, pentamidine (CYCU-1140), BML-267 (CYCU-1147), and alendronate (CYCU-1152), increased embryonic mineralization; while 6 compounds, RWJ-60475 (CYCU-1126), levamisole HCL (CYCU-1128), tetramisole HCL (CYCU-1129), fenvalerate (CYCU-1132), NSC-663284 (CYCU-1138), and BML-267ester (CYCU-1148), were inhibitory to bone mineralization. We also found that alendronate enhanced the level of bone mineralization by inhibiting osteoclast-related genes. To sum up, our research showed that zebrafish may have potential to be a drug-screening and mechanism-analysis platform for bone mineralization.

Introduction: Treating elbow fracture-dislocation is a challenge, especially in the situation of basal-coronoid trans-ulnar fracture. The study ams to explain whether or not the minimal invasive surgery (MIS) would be feasible in elbow dislocation with coronoid fracture. Materials & Methods: At Taipei Veterans General Hospital, patients who had elbow dislocations with coronoid process fractures underwent single one surgeon’s MIS techniques which included the fluoroscopy-guided ulnar anteromedial (FGUAM) approach in the stage of reducing coronoid process. When there is a proximal ulnar fracture, the posterior incision should be necessary, followed by the incision over the lateral or medial elbow in treating radial fractures or ligament injuries. Results: The Flow Diagram about approach recommendation was established in base of defining MIS as not to do cross-plane dissection. Anteriorly rigid fixation for the coronoid process was also emphasized. Conclusions: MIS can be achieved by multiple limited surgical incisions. However, if there is an unstable ulnar metaphysis or ligament avulsion fracture, the posterior approach has to be extended and the so-called MIS fails to be established.

Inherited retinal diseases (IRD) comprise a heterogeneous set of clinical and genetic disorders that lead to blindness. Given the emerging opportunities in precision medicine and gene thera-py, it has become increasingly important to determine whether DNA variants with uncertain significance (VUS) are responsible for the patients’ IRD. This research was performed to assess the functional consequence of six VUS identified in patients with IRD. Clinical assessments in-cluded an ophthalmic examination, best corrected visual acuity, and kinetic perimetry. Imaging was acquired with the Optos ultra-widefield camera and spectral-domain optical coherence to-mography (SD-OCT). Genetic testing was performed by Molecular Vision Laboratories. VUS that were predicted to alter splicing were analyzed with a minigene assay which revealed that VUS in the genes OPA1, CNGB1, and CLUAP1 altered spicing mechanisms. Due to the emerging gene and cell therapies, these results expand the genotype-phenotype correlations for patients diag-nosed with an IRD.

A number of epidemiological studies have implicated elevated iron levels with higher risks of cardiometabolic diseases, including the metabolic syndrome (MetS). MetS is a pathologic clustering of metabolic derangements characterized by central obesity, insulin resistance, hypertension, and dyslipidemia, which can all lead to increased cardiovascular disease morbidity and mortality. However, it remains unclear whether a causal association exists between higher iron status and MetS and its associated risk components. Using the data from the Taiwan Biobank (TWB) (19,012 males; 42,340 females) and of the European Whites from the UK Biobank (UKB) (128,549 males; 142,817 females), we first constructed ethnic- and sex-specific hemoglobin-polygenic risk scores (Hb-PRS) as instrumental variable (IV) for iron status with the Hb-associated SNPs we previously identified from genome-wide association studies (GWAS). We then conducted Mendelian randomization (MR) analyses to elucidate the causal role of elevated iron (either Hb-PRS quintiles or continuous Hb-PRS) on various metabolic components. MR-Egger regressions determined the potential pleiotropic effects of the constructed Hb-PRSs, while the causal relationship of Hb-PRS with anemia served as a control in the analyses. The mean Hb concentration range corresponding to the Hb-PRS quintiles is relatively narrow in both UKB (14.91-15.21 g/dL for males and 13.39-13.71 g/dL for females) and TWB (14.79-15.28 g/dL for males and 12.78-13.21 g/dL for females). In these windows of Hb-PRSs, we found differential associations of Hb-PRS with diabetes (T2D) or hyperglycemia (HGY) as compared to other MetS components. The highest quintiles of Hb-PRSs were causally associated with greater risks of hypertension (HTN) and hypertriglyceridemia (DLP) (i.e., [Taiwanese HC males: Q5 vs. Q1 ORHTN = 1.10 (1.00–1.21), p = 0.0473, Q4 vs. Q1 ORDLP = 1.10 (1.00–1.22), p = 0.0485; European White males: ORHTN = 1.05 (1.01–1.09), p = 0.0194, ORDLP = 1.04 (1.00–1.08), p = 0.0468]). Interestingly, we obtained a consistent negative causal association between increasing Hb-PRS quintiles and T2D or HGY risk across all sex subgroups (i.e., [Taiwanese HC females: ORHGY = 0.89 (0.84–0.95), 0.88 (0.83–0.94), 0.87 (0.82–0.93), 0.86 (0.81–0.92) from Q2 to Q5; European White females: ORHGY = 0.92 (0.87–0.98), 0.91 (0.86–0.97), 0.93 (0.87–0.98), 0.87 (0.82–0.93) from Q2 to Q5; all p &lt; 0.05]. The positive causal relationships between Hb-PRSs and diastolic blood pressure (DBP) and triglycerides (TG) but inverse causal association with glucose (GLU) and glycated hemoglobin (HbA1c) further corroborated such findings. There is, however, a lack of causal association with central obesity (CO), while a U-shaped type of causality was observed for gout (GT) or hyperuricemia (HUA). Sensitivity analyses, which excluded subjects based on self-reports of health conditions or medications and hospital episode statistics data, revealed similar results. Our MR studies confirm a modest causal relationship between propensity of elevated iron status and increased risk of HTN and DLP. We have further observed that modestly lower iron levels causally contribute to the development of T2D. Further validation and elucidation of the underlying biological mechanisms are highly warranted.

Dravet syndrome (DS), also known as severe myoclonic epilepsy of infancy, is a rare and drug-resistant form of developmental and epileptic encephalopathies, which is both debilitating and challenging to manage, typically arising during the first year of life, with seizures often triggered by fever, infections, or vaccinations. It is characterized by frequent and prolonged seizures, developmental delays, and various other neurological and behavioral impairments. Most cases result from pathogenic mutations in the sodium voltage-gated channel alpha subunit 1 (SCN1A) gene, which encodes a critical voltage-gated sodium channel subunit involved in neuronal excitability. Precision medicine offers significant potential for improving DS diagnosis and treatment. Early genetic testing enables timely and accurate diagnosis. Advances in our understanding of DS's underlying genetic mechanisms and neurobiology have enabled the development of targeted therapies, such as gene therapy, offering more effective and less invasive treatment options for patients with DS. Targeted and gene therapies provide hope for more effective and personalized treatments. However, research into novel approaches remains in its early stages, and their clinical application remains to be seen. This review addresses the current understanding of clinical DS features, genetic involvement in DS development, and outcomes of novel DS therapies.

The application of 16S rRNA gene pyrosequencing has expanded our knowledge about the respiratory tract microbiome originally obtained using conventional, culture-based methods. In this study, we employed DNA-based molecular techniques for examining the sputum microbiome in bronchiectasis patients in relation to disease severity. Of 63 study subjects, 42 had mild and 21 had moderate or severe bronchiectasis, which was classified by calculating the FACED score based on FEV₁ (forced expiratory volume in 1 s, %) (F, 0–2 points), age (A, 0–2 points), chronic colonization by Pseudomonas aeruginosa (C, 0-1 point), radiographic extension (E, 0–1 point), and dyspnoea (D, 0–1 point). Bronchiectasis was defined as mild at 0–2 points, moderate at 3–4 points, and severe at 5–7 points. The mean age was 68.0 ± 9.3 years; 33 patients were women. Haemophilus (p=0.005) and Rothia (p=0.043) were significantly more abundant in the mild bronchiectasis group, whereas Pseudomonas (p=0.031) was significantly more abundant in the moderate or severe group. However, the alpha or beta diversity did not significantly differ among sputum microbiota, i.e. the same dominating genera were found in all samples. Further large-scale studies are needed to investigate the sputum microbiome in bronchiectasis.

Large structures such as wind turbines are subject to environmental factors and varying operational loads which may result in structural damage, making components of these large structures prone to performance and mechanical degradation. The use of high-definition optical vision sensors in digital image correlation (DIC) allow for the application of a non-destructive image registration technique in which it measures finite three-dimensional deformations on surfaces through correlations of a unique pattern or set of unique localized patterns. However, the physical placement of an artificial marker such as a unique speckled pattern on the surface of the structure is time-consuming and often impractical for large structures. Therefore, we propose a novel auto-mated methodology that searches and segments salient and unique regions of an image as well as for all subsequent images to assist in performing efficient displacement measurements for vibrational study and structural health monitoring purposes. Our algorithm is validated on a con-trolled set of images, as well as on a small structure and large real-world wind turbine, which suggests the algorithm’s efficacy without the use of artificial markers for large structural health monitoring.

Despite extensively investigating the impact of social media on fashion products’ marketing, little evidence is available on how the platforms influence sales prediction. Focusing on Lolita fashion, this study investigates the impact of social media marketing on the sales volume prediction of fashion products. Essentially, we analyzed marketing data, including comments, likes, and shares from the Weibo social platform, to forecast future sales, examine how to enhance profit performance, and make production decisions. Using a quantitative approach, we tested three different prediction models, including multiple regression, decision tree, and XGBoost. The results revealed that increasing comments and decreasing the number of likes could significantly improve the sales volumes of Lolita products. In contrast, shares exerted a less significant impact on sales. Regarding prediction models, XGBoost was found to be the best method. In the fashion industry, social media is a useful tool for forecasting market trend. A limitation of this study is that only one social media platform was used to extract data, which might limit the generalization of the findings.

Objective: There are currently no known treatment methods for ensuring complete recovery from facial nerve damage. Thus, various basic and clinical studies continue to be conducted to achieve this end. As part of this research, autophagy is being investigated for its role in nerve regeneration. Here, we review the existing literature regarding the involvement and signifi-cance of autophagy in facial nerve injury and regeneration. Methods: A comprehensive litera-ture review was conducted to assess the induction and role of autophagy in facial nerve injury and subsequent regeneration. Results: Studies conducted on rats and mice have demonstrated activation of autophagy and expression of related factors in facial and sciatic nerves. Among the most studied of these factors in relation to degeneration and regeneration of facial and sciatic nerves are LC3II/I, PI3K, mTOR, Beclin-1, ATG3, ATG5, ATG7, ATG9, and ATG12. Conclusion: This analysis indicates that autophagy is involved in the process of nerve regeneration follow-ing facial and sciatic nerve damage. Inadequate autophagy induction or failure of autophagy re-sponses can result in regeneration issues after facial or sciatic nerve damage. Animal studies suggest that autophagy plays an important role in facial and sciatic nerve degeneration and re-generation.