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.

Historical maps constitute unique sources of retrospective geographic information. Recently, several map archives containing map series covering large spatial and temporal extents have been systematically scanned and made available to the public. The geographic information contained in such data archives allows extending geospatial analysis retrospectively beyond the era of digital cartography. However, given the large data volumes of such archives and the low graphical quality of older map sheets, the processes to extract geographic information need to be automated to the highest degree possible. In order to understand the salient characteristics, data quality variation, and potential challenges in large-scale information extraction tasks, preparatory analytical steps are required to efficiently assess spatio-temporal coverage, approximate map content, and spatial accuracy of such georeferenced map archives across different cartographic scales. Such preparatory steps are often neglected or ignored in the map processing literature but represent highly critical phases that lay the foundation for any subsequent computational analysis and recognition. In this contribution we demonstrate how such preparatory analyses can be conducted using classical analytical and cartographic techniques as well as visual-analytical data mining tools originating from machine learning and data science, exemplified for the United States Geological Survey topographic map and Sanborn fire insurance map archives.

Abstract: Spatially explicit, fine-grained datasets describing historical urban extents are rarely available prior to the era of operational remote sensing. However, such data are necessary to better understand long-term urbanization and land development processes and for the assessment of coupled nature-human systems, e.g., the dynamics of the wildland-urban interface. Herein, we propose a framework that jointly uses remote sensing derived human settlement data (i.e., the Global Human Settlement Layer, GHSL) and scanned, georeferenced historical maps to automatically generate historical urban extents for the early 20th century. By applying unsupervised color segmentation to the historical maps, spatially constrained to the urban extents derived from the GHSL, our approach generates historical settlement extents for seamless integration with the multi-temporal GHSL. We apply our method to study areas in countries across four continents, and evaluate our approach for two U.S. study sites against historical settlement extents derived from the Historical Settlement Data Compilation for the US, HISDAC-US, achieving Area-under-the-Curve values >0.9. Our results are largely in agreement with model-based urban areas from the HYDE database, and demonstrate that the integration of remote sensing derived observations and historical cartographic data sources opens up new, promising avenues for assessing urbanization, and long-term land cover change in countries where historical maps are available.

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.

A new power receiving unit (PRU) is proposed in this paper for the resonant wireless power transfer (WPT), which is characterized by the capability of attracting high power from the power transmitting unit (PTU). The resonant WPT is designed for delivering the electrical power to the PRU attached on an electrical vehicle (EV) chassis 50cm away from a PTU installed on the ground. The proposed PRU uses only the passive elements such as inductors, diodes and the capacitors, which needs no initial power from the EV. It is then applicable for charging a battery to several hundred volts for even a first-time charging battery. At a switching frequency of the resonant WPT in the experiment being 4MHz, the proposed PRU behaves itself as a negative impedance converter (NIC) in the subharmonics of 4MHz. The NIC effect plus the subharmonic oscillation causes an instability current charging the battery connected to the PRU. In this paper, we simulated the PRU and performed the experiment. The experiment demonstrates a battery charging of 150W from 50cm away using three D-mode GaN HEMT transistors via the instability current ramp. The power transfer efficiency (PTE) improved as the power delivered to load (PDL) goes higher. The best power transfer efficiency (PTE) is 65% in the present findings. The simulation analysis shows that the circuit allows itself be used to much higher power transfer when it is implemented with more GaN HEMT transistors connected in parallel. The theoretical derivation of the PRU circuit is also used to support both the experimental and simulation results.

(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.

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.

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.

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.

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.

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.

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.

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.

Carbapenemase-producing organisms (CPOs) present a major threat to public health, demanding precise diagnostic techniques their detection. Discrepancies among CPO tests have raised concerns, partly due to limitations in detecting bacterial diversity within host/specimen. We explored the impact of unbiased colony selection on carbapenemase testing and assessed its relevance on various tests. Based on "FirstAll" for unbiased colony selection to reduce bias, we compared modified carbapenem inactivation method/EDTA-modified carbapenem inactivation method (mCIM/eCIM), Carba5, the CPO panel, and multiplex PCR (M-PCR). Initially, we compared FirstAll to conventional colony selection for mCIM. Second, we used M-PCR as a reference, to evaluate test performance across seven CPO species. The results revealed that FirstAll selection improved carbapenemase detection, revising false-negative in 10.5% of K. pneumoniae isolates. In addition, 12.4% of CPOs tested positive for multiple carbapenemase genes. Both the Carba5 test and CPO panel showed suboptimal performance (sensitivity/specificity: Carba5 75.5%/89.0%, CPO panel 78.1%/74.0%). Carba5 test provided specific carbapenemase class assignments but CPO panel failed in 20.3% of cases. Carba5 test and the CPO panel results correlated well with ceftazidime-avibactam minimal inhibitory concentrations (MICs). Concordance for class A/D with MICs was 88.3% for Carba5 and 92.0% for the CPO panel; whereas for class B, it was 86.5% for Carba5 and 76.2% for the CPO panel. In conclusion, FirstAll as the unbiased colony selection impacted carbapenemase testing. With FirstAll, the diagnostic performance of either Carba5 or the CPO panel was compromised. The utilization of ceftazidime-avibactam guided by either the CPO panel or Carba5 was appropriate.

Excretory-secretory products (ESPs) are the main research targets for investigating the hosts and helminths interaction. Parasitic worms can migrate to parasitic sites and avoid the host immune response by secreting this product. Angiostrongylus cantonensisis an important food-borne zoonotic parasite that causes severe neuropathological damage and symptoms, including eosinophilic meningitis or meningoencephalitis in humans. Benzaldehydes are organic compounds composed of a benzene ring and formyl substituents. This compound has anti-inflammatory and antioxidation properties. Previous studies showed that 3-hydroxybenzaldehyde (3-HBA) and 4-hydroxybenzaldehyde (4-HBA) can reduce apoptosis in A. cantonensis ESPs treated astrocytes. These results on the protective effect underlying benzaldehyde have primarily focused on cell survival. The study was designed to investigate the molecular mechanisms of endoplasmic reticulum stress (ER stress) and oxidative stress in astrocytes in A. cantonensis ESPs treated astrocytes and to evaluate the therapeutic consequent of 3-HBA and 4-HBA. First, we initially established the RNA-seq dataset in each group, including Normal, ESPs, ESPs+3-HBA, and ESPs+4-HBA. We also found that benzaldehyde (3-HBA and 4-HBA) can stimulate astrocytes to express ER stress-related molecules after ESP treatment. The level of oxidative stress could also be decreased in astrocytes by elevating antioxidant activity and reducing ROS generation. These results suggested that benzaldehyde may be a potential therapeutic compound for human angiostrongyliasis to support brain cell survival by inducing the expression levels of ER stress- and oxidative stress-related pathway.

This work aims to develop an integrated fault location and restoration approach for microgrids (MGs). This work contains two parts. Part I presents the fault location algorithm, and Part II shows the restoration algorithm. The proposed algorithms are implemented by particle swarm optimization (PSO). The fault location algorithm is based on network connection matrices, which are the modifications of bus-injection to branch-current and branch-current to bus-voltage (BCBV) matrices, to form the new system topology. The backward/forward sweep approach is used for the prefault power flow analysis. After the occurrence of fault, the voltage variation at each bus is calculated by using the Zbus modification algorithm to modify Zbus. Subsequently, the voltage error matrix is computed to search for the fault section by using PSO. After the allocation of the fault section, the multi-objective function is implemented by PSO for optimal restoration with its constraints. Finally, the IEEE 37-bus test system connected to distributed generations is utilized as the sample system for a series simulation and analysis. The outcomes demonstrated that the proposed optimal algorithm can effectively solve the fault location and restoration problem in MGs.

.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

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.

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.

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.

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.

This research focuses on optimization of coupled solar production and battery storage system to achieve Nearly Zero-Energy Building (nZEBs) based on building load behavior patterns. Moni-toring data from an office building with 120kW peak and 40kW average load consumption equipped with a 160kW solar photovoltaic (PV) system and a 50kW-45kWh energy storage system (ESS). The primary objective is to the primary objective is to analyze collected data from existing system and setup guideline to optimize ESS capacity to maximize clean energy consumption and thus minimize excess production losses, progressing the building toward Nearly ZEB Level 1 status (87.5%-100% energy usage). The study outcome has identified parameter impacts and demonstrates additional optimized cases with various PV and ESS installed capacity. Further analysis is performed based on working day load profile and appliance patterns. This ap-proach aims to learn the usage HVAC, lighting, and electronics, enabling the optimization scheme to be applied to buildings with different load patterns. Additionally, the analysis predicts other building behavior patterns and optimized clean energy system. The findings are then validated against actual data and the results demonstrate good model accuracy, especially daytime predic-tion. These insights also provide guidelines and strategies for further interventions on HVAC operations and adjusting concerned schedules to achieve desired ZEB level.

Background and Objectives: Fifty percent of individuals with borderline personality disorder (BPD) experience Non-Suicidal Self-Injury (NSSI). One of the crucial factors related to NSSI is the feeling of emptiness. Although some inner strengths, such as five precepts, meditation, and equanimity, have been identified as potential buffers against negative mental health outcomes in BPD, their role in mediating the relationship between emptiness and NSSI is not well-documented. This study aimed to explore how these inner strengths mediate the relationship between feelings of emptiness and NSSI in individuals with BPD symptoms. Materials and Methods: A total of 302 participants with BPD symptoms completed several assessments: the SCID-II Personality Disorder (Borderline PD) to assess feelings of emptiness and NSSI, the Inner-Strength-Based Inventory (i-SBI) to evaluate five precepts, meditation, and equanimity, and the Outcome Inventory Depression (OI-Dep) to assess depression. Mediation analysis was performed using IBM SPSS and AMOS, with NSSI as the outcome variable, feelings of emptiness as the predictor, and the inner strengths as mediators. Results: The participants had a mean age of 36.56, with 65.4% being female. The analysis showed that five precepts, meditation, and equanimity significantly mediated the relationship between feelings of emptiness and NSSI, with a standardized coefficient of β = 0.534 (95% CI = 0.417 to 0.647, p &lt; 0.001). The indirect effect of emptiness through these inner strengths was significant (β = 0.034, 95% CI = 0.009 to 0.075, p = 0.005). The mediation model explained 38% of the variance in NSSI with a 3% increase, albeit small but significant. Conclusions: The study highlights a negative mediating role of inner strengths in the relationship between feelings of emptiness and NSSI meaning that as these inner strengths increase, the direct impact of feelings of emptiness on NSSI decreases. This suggests that these inner strengths act as protective factors, reducing the likelihood that someone with feelings of emptiness will resort to NSSI as a coping mechanism. These findings suggest that targeting these inner strengths could be a valuable strategy in developing interventions aimed at reducing NSSI by addressing the underlying emotional challenges associated with BPD.

Osteoporosis is a common problem in orthopedic medicine, and it has become an important medical issue in orthopedics as Taiwan is gradually becoming an aging society. In the diagnosis of osteoporosis, the bone mineral density (BMD) derived from dual-energy X-ray absorptiometry (DXA) is the main criterion for orthopedic diagnosis of osteoporosis, but due to the high cost of this equipment and the lower penetration rate of the equipment compared to the X-ray images, the problem of osteoporosis has not been effectively solved for many people who suffer from osteoporosis, however, at present, in clinical diagnosis, doctors are not yet able to accurately interpret X-ray images for osteoporosis manually, and must rely on the data obtained from DXA. In recent years, with the continuous development of artificial intelligence, especially in machine learning and deep learning, significant progress has been made in image recognition. Therefore, it is worthwhile to revisit whether it is possible to use a convolutional neural network model to read a hip X-ray image and then predict the patient's BMD. In this study, we proposed a hip X-ray image segmentation model and a hip X-ray image recognition classification model. First, we used the U-Net model as a framework to segment the femoral neck, greater trochanter, wards triangle, and the total hip in the hip X-ray images. We then performed image matting and data augmentation. Finally, we constructed a predictive model for osteoporosis using deep learning algorithms. In the segmentation experiments, we used intersection over union (IoU) as the evaluation metric for image segmentation, and both the U-Net and U-Net++ models achieved segmentation results greater than or equal to 0.5. In the classification experiments, using the T-score as the classification basis, the total hip using the DenseNet121 model has the highest accuracy of 74%.

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.

Patients with lean NAFLD make up an increasing subset of liver diseases. The association between lean NAFLD and feutin-A, which serves as a hepatokine and adipokine, has never been examined. Our study aimed to explore the association of serum fetuin-A among lean and nonlean patients. The study comprised 606 adults from the community, stratified into lean or nonlean (BMI </≥ 24 kg/m2) and NAFLD or non-NAFLD (scoring of ultrasonographic fatty liver indicator, US-FLI ≥ 2/<2). Multivariate logistic regression analyses were performed to estimate the odds ratio of having NAFLD among the tertiles of fetuin-A after adjustment. The least square means were computed by general linear models to estimate marginal means of the serum fetuin-A concentrations in relation to the NAFLD groups. The OR of having NAFLD for the highest versus the lowest tertile of fetuin-A was 2.62 (95% CI: 1.72-3.98; P for trend<0.001). Stratifying by BMI, the OR of having lean NAFLD for the highest versus the lowest tertile of fetuin-A was 2.09 (95% CI: 1.09-3.98; P for trend 0.026), while nonlean NAFLD had no significant association with the fetuin-A gradient after adjustments. Fetuin-A was positively associated with lean NAFLD after adjusting for central obesity and insulin resistance.

3D printing is a non-traditional additive manufacturing process. It is different from the traditional subtractive manufacturing process. It offers exceptional rapid prototyping capabilities and results that traditional subtractive manufacturing methods cannot attain, especially in applications involving curved or intricately shaped components. Despite its advantages, metal 3D printing will face porosity, warpage, and surface roughness issues. These issues will affect the future practical application of the parts indirectly, for example, the structural strength and the parts assembly ca-pability. Therefore, this study compares the qualities of the warpage, weight, and surface rough-ness after milling and grinding processes under the same materials (316L stainless steel) between general rolled steel and 3D additive steel. Experimental results show that 3D printing parts are approximately 13% to 14% lighter than the general rolled steel. The surface roughness performance of 3D printing steel is better than general rolled steel under the same material after milling or grinding processing. The hardness of the 3D printing steel is better than that of the gen-eral rolled steel. The research verifies that 3D additive manufacturing can use surface processing to optimize surface performance and achieve the functions of lightness and hardness.

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.

Agriculture is an industry that heavily relies on the environment. The increasing frequency of ex-treme disasters attributable to climate change has adversely affected agricultural land and dis-rupted the stability of the supply of agricultural products. Therefore, we implemented a research program focused on current strategies for adapting to agricultural meteorological disasters. The primary goal was to actively promote disaster prevention information and techniques through information platforms and applications and to provide refined forecasting and an early warning system to enhance preparedness for and recovery from agricultural disasters. This initiative can transform passive mitigation into dynamic action by disseminating crucial information to farmers. We integrated meteorological data and crop characteristics to develop disaster prevention strate-gies for the predisaster, during-disaster, and postdisaster stages to empower farmers to implement autonomous disaster prevention, ensuring their profitability and minimizing the impact of disas-ters. This paper presents an agricultural disaster prevention system involving cross-disciplinary collaboration to establish an early warning system for crop disasters. However, the effectiveness of the early warning system relies on the availability of complete meteorological and crop infor-mation, necessitating high-density agricultural meteorological stations, refined weather forecast services, historical crop damage data, and ongoing research and development on disaster preven-tion technology. In the system, a diversified social media interface is used to provide local farmers with weather forecast information. When impending disasters are identified, the platform acti-vates disaster prevention measures to reduce agricultural losses. This article paper introduces Taiwan’s agricultural disaster prevention system as a complete disaster prevention strategy.

Background Diabetic patients have an increased risk of infections; however, the association between type 2 diabetes and hospital outcomes of sepsis remains controversial when the diabetes severity is not considered. We examined this association using nationwide and hospital-based databases concomitantly. Methods The first part of this study was conducted using 2 nationwide databases: the Longitudinal Cohort of Diabetes Patients and the Longitudinal Health Insurance Database 2000. The diabetic complication burden was evaluated using the adapted Diabetes Complications Severity Index score (aDCSI score). In the second part, we used the hospital-based database with laboratory data, such as initial blood glucose and HbA1c levels, to make comparisons between surviving and dead patients with type 2 diabetes and sepsis. Results The nationwide study included 19,719 type 2 diabetic sepsis patients and an equal number of non-diabetic patients. The diabetic sepsis patients had an increased odds ratio (OR) of 1.14 (95% CI 1.1-1.19) for hospital mortality. The OR for mortality increased as the complication burden increased (diabetic sepsis patients with aDCSI scores of 0, 1, 2, 3, 4, and ≥5 had ORs of 0.91, 0.87, 1.14, 1.25, 1.56, and 1.77 for mortality, respectively (all P<0.001 and P for trend <0.001)). A total of 1,054 diabetic sepsis patients were included from the hospital-based database. Initial blood glucose levels in the surviving and dead diabetic sepsis patients did not differ significantly: 273.9 ± 180.3 versus 266.1 ± 200.2 (mg/dL) (P=0.095). Moreover, the surviving diabetic sepsis patients did not have a lower HbA1c (%): 8.4 ± 2.6 versus 8.0 ± 2.5 (P=0.078). Conclusions In the case of type 2 diabetic sepsis patients, the diabetes-related complication burden is the major determinant of hospital mortality rather than the diabetes itself. Contrary to popular belief, initial blood glucose and HbA1c levels may not be as important as previously thought.

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.

Nerve hydrodissection (HD), a technique used when treating nerve entrapments, involves using an anesthetic or solution such as saline or 5% dextrose solution to separate the nerve from the surrounding tissue, fascia, or adjacent structures. This technique aims to treat neuropathic pain, or pain caused by the nerve. Ultrasound-guided HD of peripheral nerves has gained significant attention in the medical profession and pain management fields in recent years. This is due to a number of high impact publications of randomized control trials demonstrating the efficacy and safety of this technique for the treatment of carpal tunnel syndrome. Even the 20th edition of Harrison’s Principles of Internal Medicine textbook lists injection of 5% dextrose as an alternative local treatment that does not have the side effects of corticosteroids. At present, there is no review of the current literature on this technique. This manuscript will summarize and discuss the following: 1) the different approaches to doing ultrasound-guided HD of nervous structures, 2) its usages in different clinical situations, 3) its clinical pearls, 4) the solution used, and 5) the postulated mechanisms of action.

The increased global incidence of myopia requires the establishment of therapeutic approaches. Previous studies have suggested that inflammation plays an important role in the development and progression of myopia. We used human retinal pigment epithelial cell to study the molecular mechanisms on how FJE and PVE lowering the inflammation of the eye. The effect of FJE and PVE in MFD induced hamster model and explore the role of inflammation cytokines in myopia. Expression levels of IL-6, IL-8, and TNF-α were upregulated in retinal pigment epithelium (RPE) cells treated with IL-6 and TNF-α. FJ extract (FJE) + PV extract (PVE) reduced IL-6, IL-8, and TNF-α expression in RPE cells. Furthermore, FJE and PVE inhibited inflammation by attenuating the phosphorylation of protein kinase B (AKT), and nuclear factor kappa-light-chain-enhancer of activated B (NF-κB) pathway. In addition, we report two resveratrol + ursolic acid compounds from FJ and PV and their inhibitory activities against IL-6, IL-8, and TNF-α expression levels in RPE cells treated with IL-6 and TNF-α. FJE, PVE, and FJE + PVE were applied to MFD hamsters and their axial length was measured after 21 days. The axial length showed statistically significant differences between phosphate-buffered saline- and FJE-, PVE-, and FJE + PVE-treated MFD eyes. FJE + PVE suppressed expressions of IL-6, IL-8, and TNF-α. They also inhibited myopia-related transforming growth factor-beta (TGF)-β1, matrix metalloproteinase (MMP)-2, and NF-κB expression while increasing type Ⅰ collagen expression. Overall, these results suggest that FJE + PVE may have a therapeutic effect on myopia and be used as a potential treatment option.

Notch signaling is a highly conserved pathway which occurs between adjacent cells to distinguish them. The Notch signaling cascade operates in a simple mechanism, yet Notch plays remarkably diverse roles in development to regulate cell fate determination, organ growth and tissue patterning. Originally isolated and characterized in the model insect Drosophila melanogaster, recent studies in various insect species have revealed that Notch signaling is broadly involved in the construction of insect tissues. This review focuses on providing a molecular mechanistic and developmental picture regarding the roles of Notch pathway in insects. The functions of Notch in the formation and patterning of insect embryo, wing, leg, ovary and several specific structures as well as in stress responses are summarized. These results are discussed in developmental context with an eye toward understanding the functionality of Notch signaling pathway in different insect species.

This paper presents a compact wideband circularly polarized cross dipole antenna with low-pass filter response. It consists of two pairs of folded crossed dipole arms printed separately on both sides of the top substrate, and the two dipole arms on the same surface are connected by an annular phase-shifting delay line to generate circular polarization. A bent metal square ring and four small metal square rings around the cross dipoles are employed to introduce new resonant frequencies, effectively extending the impedance and axial ratio bandwidth. Four square patches printed on the middle substrate are connected to the ground plane by the vertical metal plates, in order to reduce the antenna height. Thus, a compact wideband circularly polarized antenna is realized. In addition, a transmission zero can be introduced at the upper frequency stopband by the bent metal square rings, without using extra filter circuits. For verification, the proposed model is implemented and tested. The overall size of the model is 90mm×90mm×33mm(0.37λ0×0.37λ0×0.14λ0, λ0 denotes the center operating frequency). The measured impedance bandwidth and 3 dB axial ratio bandwidth are 53.3% and 41%, respectively. More than 15 dB upper-band radiation suppression level is realized, indicating a good low-pass filter response.

The Koka gold deposit is located in the Elababu shear zone between the Nakfa terrane and the Adobha Abiy terrane, NW Eritrea. Based on the paragenetic study two main stages of gold mineralization were identified in the Koka gold deposit: 1) an early stage of pyrite-chalcopyrite-sphalerite-galena-gold-quartz vein; and 2) a second stage of pyrite-quartz veins. NaCl-aqueous inclusions, CO2-rich inclusions, and three-phase CO₂-H₂O inclusions occur in the quartz veins at Koka. The ore-bearing quartz veins formed at 268℃, from NaCl-CO₂-H₂O(-CH₄) fluids averaging 5 wt% NaCl eq. The ore-forming mechanisms include fluid immiscibility during stage I, and mixing with meteoric water during stage II. Oxygen, hydrogen and carbon isotopes suggest that the ore-forming fluids originated as mixtures of metamorphic water, meteoric water and magmatic water, whereas sulfur isotope suggest an igneous origin. Features of geology and ore-forming fluid at Koka deposit are similar to those of orogenic gold deposits, suggesting the Koka deposit might be an orogenic gold deposit related to granite.

Patients receiving hemodialysis are at risk of vascular access infections (VAIs) and particularly vulnerable to the opportunistic pathogen Staphylococcus aureus. Hemodialysis patients were also at increased risk of infection during the COVID-19 pandemic. Therefore, this study determined the change in the molecular and antibiotic resistance profiles of S. aureus isolates from VAIs during the pandemic compared with before. 102 S. aureus isolates were collected from VAIs between November 2013 and December 2021. Before the pandemic, 69 isolates were collected, 58%, 39.1%, and 2.9% from arteriovenous grafts (AVGs), tunneled cuffed catheters (TCCs), and arteriovenous fistulas (AVFs), respectively. The prevalence of AVG and TCC isolates changed to 39.4% and 60.6%, respectively, of 33 isolates during the pandemic. Sequence type (ST)59 was the predominant clone in TCC-methicillin-resistant S. aureus (MRSA) and AVG-MRSA before the pandemic, whereas the predominant clone was ST8 in AVG-MRSA during the pandemic. ST59 carrying the ermB gene was resistant to clindamycin and erythromycin. By contrast, ST8 carrying the msrA gene was exclusively resistant to erythromycin. The ST distribution for different VAIs changed from before to during the pandemic. The change in antibiotic resistance rate for different VAIs was closely related to the distribution of specific STs.

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.

The advancement of mass spectrometry technologies has revolutionised plant metabolomics research by enabling the acquisition of raw metabolomics data. However, the identification, analysis, and visualisation of these data require specialised tools. Existing solutions lack a dedicated plant-specific metabolite database and pose usability challenges. To address these limitations, we developed PlantMetSuite, a web-based tool for comprehensive metabolomics analysis and visualisation. PlantMetSuite encompasses interactive bioinformatics tools and databases specifically tailored for plant metabolomics data, facilitating upstream-to-downstream analysis in metabolomics and supporting integrative multi-omics investigations. PlantMetSuite can be accessed directly through a user's browser without the need for installation or programming skills. The tool is freely available at https://plantmetsuite.verygenome.com/ and will undergo regular updates and expansions to incorporate additional libraries and newly published metabolomics analysis methods. The tool's significance lies in empowering researchers with an accessible and customisable platform for unlocking plant metabolomics insights.

Background Coronary artery disease (CAD) is a widely recognized cardiovascular disease that is considered the leading cause of death worldwide, affecting people on a global scale. Percutaneous coronary intervention (PCI), which involves procedures such as balloon angioplasty or stenting, plays an important role in opening blocked arteries and minimizing damage to the cardiac muscle. While the use of drug-eluting stents (DESs) has significantly reduced the occurrence of coronary restenosis, the problem of in-stent restenosis (ISR) continues to pose a significant clinical challenge. Gaining a deeper understanding of the clinical predictors associated with ISR is vital for early detection and appropriate treatment. Hence, this study aimed to evaluate the clinical predictors of ISR specifically in Taiwanese patients. Methods We conducted a single-center, retrospective case-control study, enrolling 517 CAD patients undergoing previous coronary stenting and stable angina with positive stress test or acute coronary syndrome (ACS) during follow-up between January 2019 and December 2022 at National Taiwan University Hospital. The patients were categorized into two groups: the ISR group, consisting of individuals who received drug-coated balloon (DCB) treatment (n=177), and the non-ISR group, comprising patients who did not receive DCB treatment (n=340). To gather relevant data, we meticulously reviewed the medical records and analyzed the findings from coronary angiography to assess the clinical characteristics of the patients. Results Patients with three-vessel disease (3VD) exhibited a higher prevalence of underlying diseases and were more likely to be taking aspirin and clopidogrel. Moreover, our analysis revealed that age (adjusted odds ratio [aOR] 1.02, 95% confidence interval [CI] 1.00 - 1.04, p = 0.037) and the presence of 3VD (adjusted odds ratio [aOR] 2.15, 95% confidence interval [CI] 1.03 - 4.46, p = 0.039) were significantly associated with an increased risk of coronary ISR. Conclusions Older age and 3VD were the independent predictors of coronary ISR in CAD patients receiving coronary stent implantation.

The formula Chong-Lou-Yao-Fang (CLYF) is an herbal medicinal formulation developed by the indigenous Naxi people for treating liver cancer. This study is to reveal the biological activity, potential targets, and molecular mechanisms of CLYF for cancer treatment through network pharmacology, molecular docking and in vitro experiments. 35 key compounds were screened from 176 active ingredients in CLYF, which played a vital role in the treatment of cancer, 20 core targets were filtered through protein–protein interaction (PPI) network analysis. The enrichment analysis of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) indicated that PI3K-Akt, MAPK, hepatitis B, hepatitis C might be effective in liver cancer treatment. Mo-lecular docking revealed stable binding between EGFR, TP53, and AKT1 with active ingredients. Experiments with cell cultures confirmed that CLYF-A suppressed the proliferation of HepG2 cells, which is consistent with the network pharmacology approach undertaken and the predictions of molecular docking. CLYF-A also induced significant apoptosis and cell cycle arrest in HepG2 cells, which was associated with the loss of mitochondrial membrane potential. This study explored the biological activity, potential targets, and molecular mechanisms of CLYF for cancer treatment. Our results may provide a scientific basis for the clinical use of CLYF for cancer treatment and have important implications for developing pharmaceutical preparations, which also need more phar-macological experiments.

In this study, based on frost formation data provided by Harbin Meteorological Bureau, combined with geographical factors, temperature and population density, linear fitting, Mann-Kendall mutation test, pettitt method and sliding T test were used to analyze the spatio-temporal variation characteristics of frost date in Harbin Municipality and the effects of geographical factors, temperature and population density on frost regularity. The results showed that (1) The earliest year of FSD appeared was 1966 and 1967, on the 255th, i.e., August 18th, and the latest was 283 days, i.e., October 10th, 2006. The earliest year in which the FED appeared was April 24th of 2015, the 114th day of that year, and the latest was April 21st of 1974, the 141st day of that year. The year with the most frost was 2012, with 161 days, and the year with the shortest was 1966, with 123 days. (2) Throughout the study period, FSD increased by 7.8 days at a rate of -1.27d/10a, FED increased by 10.9 days at a rate of 1.77d/10a, and FFS increased by 18.9 days at a rate of 3.05d/10a. The tendency rate of FSD and FFS at each site in Harbin showed an increasing trend. For FED, the tendency rate of some sites showed an increasing trend. In general, FSD showed a delayed trend, FED showed an advanced trend, and FFS showed a prolonged trend. Using the method of unary linear regression, FSD of each site showed an increasing trend, FFS showed an increasing trend, and FED showed a decreasing trend in general. (3) Throughout the study period, FSD was mutated in 2000, and the arrival time of it in the study area averaged the 265th, i.e., September 22nd, and after that, the arrival time of it changed to the 272nd, i.e., September 29th of that year. FED was mutated in 2006, and the arrival time of it in the study area averaged 128th, i.e., April 8th. After the mutation, the arrival time of FED changed to 121st, i.e., April 1st of that year. FFS was mutated in 2004. Before the mutation, with an average arrival time of 137days in the study area .But after that, the time changed to 150 days.(4) FSD and FFS in Harbin Municipality were negatively correlated with latitude and positively correlated with temperature, while FED was positively correlated with latitude and negatively correlated with temperature. The FSD, FED and FFS in the central part of Harbin Municipality were the earliest, the latest and the longest, respectively, so the Pearson correlation coefficient method and the influence of longitude could not be reflected in the multiple regression. Several factors were judged by grey correlation analysis method. The longitude is significantly related to FSD, FED and FFS.

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.

Globally, the use of whole-cell matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) in clinical microbiology laboratories has increased considerably. With the rapid growth of artificial intelligence technology, there is an increasing number of areas devoted to solving problems by implementing machine learning-based methods. Applying the use of artificial intelligence to the analysis of the massive amount of information obtained in the mass spectrum derived from MALDI-TOF MS should be a breakthrough in clinical microbiology. Specifically, it would facilitate a more rapid and accurate strain typing or antibiotic susceptibility test (AST) based on whole-cell MALDI-TOF MS spectra, and hence, it is a promising solution. Even though the reproducibility of peaks could result in some critical problems, computational methods have been developed to address this issue. Therefore, clinical microbiologists are able to perform strain typing or an AST as smoothly and easily as identifying species by using MALDI-TOF MS and artificial intelligence.

In this study, we demonstrate a high luminous efficacy of 118 lm/W and high reliability through 450°C thermal aging of white LEDs (WLEDs) utilizing four-inch YAG: Ce3+ phosphor-in-glass (PiG) plates designed for vehicle headlights. The sintering process of mixing glass and phosphor typically generates pores, which can scatter light and reduce the luminous efficacy of the fabricated PiG. In this study, we produced four-inch PiG plates under four different fabrication conditions to evaluate their luminous efficacy. Our results revealed that the PiG plate with a thin thickness of 0.08 mm exhibited a 16.83% increase in luminous efficacy compared to the 0.15 mm plate, attributed to reduced light interaction with the pores. Unlike silicone-based phosphor WLEDs, which offer high performance but lower reliability due to the silicone resin's low transition temperature (150°C), our novel thin PiG plate achieves high performance and reliability. This advancement suggests that the proposed thin PiG plate could replace traditional silicone-based phosphors, enabling the development of high-quality WLEDs for vehicle headlights in automotive applications.

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.

In view of the limitations of the existing eccentricity error separation method of the rotary table, an eccentricity error separation method based on the phase feature of the moiré signal of single reading head is proposed herein. A grating pair transmission model is established based on the analysis of the principle of the rotary table, thereby the influence of eccentricity error on the phase feature of the moiré signal in the rotation course of the rotary table is clarified, and the corresponding model between the phase feature spectral components and the eccentricity error is established. The verification experiments of the proposed method are carried out based on the laboratory-made circuit system. After verifying the accuracy of the data acquisition of the laboratory-made circuit board, the verification experiments of the eccentricity error separation effect of the proposed method are carried out. The experimental data are compared with those of the traditional method and the results show that the error between the two methods is 2.34μm and the relative error is 2.3%.

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.

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

Concussion, also known as mild traumatic brain injury (mTBI), commonly causes transient neurocognitive symptoms, but in some cases, it causes cognitive impairment, including working memory (WM) deficit, which can be long-lasting and impede a patient’s return to work. The predictors of long-term cognitive outcomes following mTBI remain unclear because abnormality is often absent in structural imaging findings. The purpose of the study was to determine whether machine learning-based models using functional magnetic resonance imaging (fMRI) biomarkers and demographic or neuropsychological measures at baseline could effectively predict 1-year cognitive outcomes of concussion. We conducted a prospective, observational study of patients with mTBI who were compared with demographically-matched healthy controls enrolled between September 2015 to August 2020. Baseline assessments were collected within the first week of injury, and follow-ups were conducted at 6 weeks, 3 months, 6 months, and 1 year. Potential demographic, neuropsychological, and fMRI features were selected according to the significance of correlation with the estimated changes in WM ability. The support vector machine classifier was trained using these potential features and estimated changes in WM between the predefined time periods. Patients demonstrated significant cognitive recovery at the third month, followed by worsened performance after 6 months, which persisted until 1 year after concussion. Approximately half of the patients experienced prolonged cognitive impairment at 1-year follow up. Satisfactory predictions were achieved for patients whose WM function did not recover at 3 months (accuracy=87.5%), 6 months (accuracy=83.3%), 1 year (accuracy=83.3%), and performed worse at 1-year follow-up compared to baseline assessment (accuracy=83.3%). This study demonstrated the feasibility of personalized prediction for long-term postconcussive WM outcomes based on baseline fMRI and demographic features, opening a new avenue for early rehabilitation intervention in selected individuals with possible poor long-term cognitive outcomes.

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.

In this paper, we investigate a class of hierarchical variational inequalities (HVIPs, i.e., strongly monotone variational inequality problems defined on the solution set of multiple-set split common fixed point problems) with quasi-pseudocontractive mappings in real Hilbert spaces, which special cases can be found in many important engineering practical applications such as image recognizing, signal processing and machine learning. In order to solve HVIPs of potential application value, inspired by the primal-dual algorithm, we propose a novel accelerated cyclic iterative algorithm that combines the inertial method with a correction term and a self-adaptive step-size technique. Our approach eliminates the need for prior knowledge of the bounded linear operator norm. Under appropriate assumptions, we establish strong convergence of the algorithm. Finally, we apply our novel iterative approximation to solve multiple-set split feasibility problems and verify the effectiveness of the proposed iterative algorithm through numerical results.

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.

A novel five-surface phosphor-in-glass (FS-PiG) for high illumination and excellent color uniformity in larger-scale LEDs for sensor light source application is demonstrated. YAG phosphor (Y3Al5O12:Ce3+) was uniformly mixed with ceramic and sintered at 680°C to form a phosphor wafer. A sophisticated laser engraving was employed on the phosphor wafer to form a saddle-shaped large-scale FS-PiG LEDs. The performance of the FS-PiG LEDs exhibited the illumination of 401lm, average color temperature (CCT) of 5488K±110K, and color coordinates (CIE) of (0.3179±0.003, 0.3352±0.003). In contrast to convention single-surface phosphor-in-glass (SS-PiG) LEDs, the performance exhibited the illumination of 380lm, average CCT of 5830K±758K, and CIE of (0.3083±0.07, 0.3172±0.07). These indicated that the performance of the FS-PiG LEDs was higher than the SS-PiG LEDs for illumination, CCT, and CIE of 1.7, 7, and 23 times, respectively. Furthermore, the FS-PiG LEDs demonstrate lower lumen loss of 2% and less chromaticity shift of 5.4x10-3 under accelerated aging at 350°C for 1008 hours, owing to the high ceramic melting temperature of up to 510°C. In this study, the proposed FS-PiG larger-scale LEDs having excellent optical performance and high reliability may be the promising candidates to replace the convention phosphor-in-organic silicone material used in high-power LEDs for the next generation of sensor light sources, display, and headlight applications.

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.

Physical inactivity is a well-known risk factor for various non-communicable diseases (NCDs). Sufficient physical activity (PA) is essential for the prevention of NCDs and thus it is imperative to study the current status of PA and its influencing factors among rural residents in China. A population-based survey was conducted in rural areas of Shandong, Shanxi and Yunnan Provinces using a stratified random sampling method. The International Physical Activity Questionnaire Short Form (IPAQ-S) was used to collect the data on PA. A total of 3780 rural residents participated in the survey. The result showed that 22.2% of rural residents were physical inactivity. The proportion of rural residents reporting practice of physical exercise was 54.4%. The most frequently performed physical exercise was walking/brisk walking(78.3%).Binary logistic regression analyses showed that being female, people at age between 15 to 34 years or 60 years old and above, employees of governmental departments/retirees, school students, the unemployed, people with NCDs were risk factors of PA and ethnic minority groups,smoking and alcohol consumption were risk factors of physical exercise. Health promotion programme aiming at increasing people’s PA in rural China is needed and it should focus on the populations groups of the female, people at age 60 years and above ,school students, the unemployed, and people with NCDs.

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.

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.

Cancer immunotherapy reaches a remarkable achievement in various cancer types and brings new possibilities to improve cancer patients’ long-term survival. However, outcomes vary from case to case, and the present protocol benefits a small fraction of patients. One notable factor is the tumor microenvironment, especially the immune cell components, that may reflect the immune response's status quo on site. Thus, understanding the content of infiltrating immune cells in tumors is not only for research interesting but also a crucial subject toward precision medicine. We implement an algorithm for resolving relative proportions of twenty-one immune cell subclasses from a human tissue profiled transcriptome by microarray technology to reach the goal above. By selecting gene features and then adopting ?-Support Vector Regression, we can construct a deconvolution model and resolve the immune cell context. The excellent consistency between the estimated values and the correct immune-cell composition further demonstrates this approach provides a more natural alternative to revealing samples' immune cell content and reliable results like recent single-cell technologies. Based on this algorithm, the web-based deconvolution tool implemented named mySORT provides a user-friendly interface for estimating the immune cell content by uploading gene expression profiling. We also present comprehensive visualization 2D/3D plots in mySORT so that users can easily make a comparison between different samples. Finally, we synthesized pseudo-bulk expression data from single-cell transcriptomic datasets of 17 melanoma and 16 head and neck cancer patients. The deconvolution results of microarray-based data in the previous study and synthetic pseudo-bulk data all proved the excellent performance of mySORT. We believe that mySORT can help researchers in all fields easily understand complex immune microenvironment. The website of mySORT is freely accessible on https://symbiosis.iis.sinica.edu.tw/mySORT/.

Background: Most sepsis patients died during their first episode and the long-term survival post discharge was low. Major adverse cardiovascular events and repeated infections were regarded as the major causes in such conditions. No definite medications were proven to effectively improve the long-term outcome. We aimed to examine the benefit of statins on the long-term outcome of survived sepsis patients. Methods: Between 1999 and 2013, a total of 220,082 patients with the first episode of sepsis hospitalization were included and 134,448 ones (61.09%) survived to discharge. The survived patients who subsequently had statins use of >30 cumulative defined daily doses (cDDDs) post discharge were defined as the statin users. After propensity score matching of 1:5, a total of 7,356 and 36,780 survived patients were retrieved as the study (statin-users) and comparison cohort (non-statin users), respectively. The main outcome was the long term survival post discharge. HR with 95% CI was calculated using the Cox regression model to evaluate the effectiveness of statins with further stratification analyses according to cDDDs. Results: The study cohort, that is, the statin users had an adjusted HR of 0.29 (95% CI, 0.27-0.31) in long term mortality rate compared with the comparison cohort. For statin users with the cDDDs of 30–180, 180–365, and >365, the adjusted HRs were 0.32, 0.22, and 0.16, respectively, (95% CI, 0.30-0.34, 0.19-0.26, and 0.12-0.23, respectively) compared with the non-statin users (defined as statins use <30 cDDDs post discharge), and the P for trend <.0001. In the sensitivity analysis, after excluding the survived patients who died within three and six months post discharge, the adjusted HR of statins use remained significant (0.35, 95% CI 0.32-0.37 and 0.42, 95% CI 0.39-0.45, respectively). Conclusions: Statins decreased the long-term mortality post sepsis. Further randomized control trial deserved to be conducted to confirm this observation.

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.

Artificial intelligence (AI) is revolutionizing the textile industry by improving the prediction of fabric properties and handfeel, which are essential for assessing textile quality and performance. However, the practical application and translation of AI-predicted results into real-world textile production remain unclear, posing challenges for widespread adoption. This paper systematically reviews AI-driven techniques for predicting these characteristics by focusing on model mechanisms, dataset diversity, and prediction accuracy. Among 811 papers initially identified, 26 were selected for in-depth analysis through both bibliometric and content analysis. The review categorizes and evaluates various AI approaches, including machine learning, deep learning, and hybrid models, across different types of fabric. Despite significant advances, challenges remain, such as ensuring model generalization and managing complex fabric behavior. Future research should focus on developing more robust models, integrating sustainability, and refining feature extraction techniques. This review highlights the critical gaps in the literature and provides practical insights to enhance AI-driven prediction of fabric properties, thus guiding future textile innovations.

We study the electron tunneling (ET) and local Andreev reflection (AR) processes in a quantum dot (QD) coupled to the left and right ferromagnetic leads with noncollinear ferromagnetisms. In particular, we consider that the QD is also side-coupled to a nanowire hosting Majorana bound states (MBSs) at its ends. Our results show that when one mode of the MBSs is coupled simultaneously to both spin-up and spin-down electrons on the QD, the height of the central peak is quite different from that if the MBS is coupled to only one spin component electrons. The ET and AR conductances which are mediated by the dot-MBS hybridization strongly depend on the angle between the left and right magnetic moments in the leads, which result in sign change of the angle-dependent tunnel magnetic resistance. This result is very different from case when the QD is coupled to regular fermonic mode, and can be used for detecting the existence of MBSs, a current challenge in condensed matter physics under extensive investigations.

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.

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.

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%.

Flower color is an important ornamental feature, often modulated by the contents of flavonoid. Chalcone synthase is the first key enzyme in the biosynthesis of flavonoid, but little is known about the role of R. delavayi CHS in flavonoid biosynthesis. In this paper, three CHS genes (RdCHS1-3) were successfully cloned from R. delavayi flowers. According to multiple sequence alignment and phylogenetic analysis, only RdCHS1 contained all the highly conserved and important residues, and classified into the cluster of bona fide CHSs. Thus RdCHS1 was then subjected for further functional analysis. Real-Time PCR analysis revealed that transcripts of RdCHS1 was the highest in leaves and lowest in root, did not match the anthocyanin accumulation patterns during flower development. Biochemical characterization displayed that RdCHS1 could catalyze p-coumaroyl-CoA and malonyl-CoA molecules to produce naringenin chalcone. Physiological function of RdCHS1 was checked in Arabidopsis mutant and tobacco, the results showed RdCHS1 transgenes could recover the color phenotypes of tt4 mutant and made tobacco flower color from pink to dark pink through modulating the expression of endogenous structural and regulatory genes in tobacco. All these results demonstrated that RdCHS1 is a bona fide CHS and contribute to flavonoid biosynthesis in R. delavayi.

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.

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.

There is no doubt that seagrass beds constitute one of the most productive ecosystems in shallow coastal waters. Despite this, picoplankton in seagrass ecosystems has received relatively little attention. The purpose of this study was to compare picoplankton growth and mortality rates between seagrass and unvegetated habitats using chamber incubations. We tested two main hypotheses: (i) incubation with seagrass would result in higher bacterial growth rates due to increased DOM release from seagrass photosynthesis, and (ii) Synechococcus spp. would be lower in the presence of seagrass due to competition for inorganic nutrients. Our results showed bacterial growth rates of 2.31 and 2.44 d–1 without and with seagrass, respectively. In seagrass chambers, bacterial growth was higher than that in non-seagrass chambers, suggesting that organic carbon coming from the seagrass community may support bacterial production. Furthermore, we observed a negative Synechococcus spp. growth rate (-0.9 d–1) in the seagrass treatment, likely reflecting nutrient competition with the seagrass. Small-scale chambers proved to be a useful tool for studying the factors controlling spatial and temporal patterns of picoplankton across different habitats. Furthermore, future studies should examine picoplankton growth over a wider range of spatial scales in seagrass beds and adjacent unvegetated sediment.

Chemical investigation of the Chinese soft coral Lobophytum sp. has resulted in the isolation of six new compounds, namely lobosteroids A–F (1–6), along with four known compounds. Their structures were determined by extensive spectroscopic analysis and comparison with the spectral data reported in the literature. Among them, the absolute configuration of 1 was determined by X-ray diffraction analysis. These steroids characterized by either the presence of an α,β-αꞌ,βꞌ-unsaturated carbonyl or an α,β-unsaturated carbonyl moiety in ring A, or the existence of a 5α,8α-epidioxy system in ring B, as well as diverse oxidation sites of side chains. The prelimi-nary antibacterial bioassay showed all compounds exhibited significant antibacterial activities against the fish pathogenic bacteria Streptococcus parauberis FP KSP28 and Phoyobacterium damselae FP2244 with all inhibition rates more than 90% at the concentration of 150 µM. And at the same concentration, compounds 2, 6–10 also displayed potent inhibitory effects against vancomy-cin-resistant Enterococcus faecium bacteria G7 with all inhibition rates more than 90%.

Combining Matrix-Assisted Laser Desorption/Ionization Time-of-Flight (MALDI-TOF) spectra data and artificial intelligence (AI) has been introduced for rapid prediction on antibiotic susceptibility test (AST) of S. aureus. Based on the AI predictive probability, the cases with probabilities between low and high cut-offs are defined as “grey zone”. We aimed to investigate the underlying reasons of unconfident (grey zone) or wrong predictive AST. A total 479 S. aureus isolates were collected, analyzed by MALDI-TOF, and AST prediction, standard AST were obtained in a tertiary medical center. The predictions were categorized into the correct prediction group, wrong prediction group, and grey zone group. We analyzed the association between the predictive results and the demographic data, spectral data, and strain types. For MRSA, larger cefoxitin zone size was found in the wrong prediction group. MLST of the MRSA isolates in the grey zone group revealed that uncommon strain types composed 80%. Amid MSSA isolates in the grey zone group, the majority (60%) was composed of over 10 different strain types. In predicting AST based on MALDI-TOF AI, uncommon strains and high diversity would contribute to suboptimal predictive performance.

Based on the minimum conduction band edge caused by the minimum channel potential resulting from the quasi-3D scaling theory and the 3D density of state (DOS) accompanied by the Fermi-Dirac distribution function on the source and drain sides, a unified semiconductor-device-physics-based ballistic model is developed for the threshold voltage of modern multiple-gate (MG) transistors, including FinFET, W-gate MOSFET, and Nanosheet (NS) MOSFET. It is shown that the thin silicon, thin gate oxide, and high work function will alleviate the ballistic effects and resist the threshold voltage degradation. Besides, as the device dimension is further reduced to give rise to the 2D/1D DOS, the lowest conduction band edge is hence increased to resist the threshold voltage degradation. The nanosheet MOSFET exhibits the largest threshold voltage among the three transistors due to the smallest minimum conduction band edge caused by the quasi-3D minimum channel potential. Compared to P-type MOSFET (P-FET), the N-FET shows more threshold voltage because the electron has a more effective mass than the hole

Semi-continuous data are very common in the social science and economics. In this paper, a Bayesian variable selection procedure is developed to assess the influence of exogenous factors including observed and unobserved on the semi-continuous data. Our formulation is based on the two-part latent variable model with polytomous response. We consider two schemes for the penalties of regression coefficients and factor loadings: the Bayesian spike and slab bimodal prior and the Bayesian lasso prior. Within the Bayesian framework, we implement Markov Chains Monte Carlo sampling method to conduct posterior inference. To facilitate posterior sampling, we recast the logistic model in part one as the norm-like mixture model. Gibbs sampler is designed to draw observations from the posterior. Our empirical results show that with suitable hyper-parameters, the spike and slab bimodal method slightly outperforms the Bayesian lasso in the current analysis. Finally, a real example related to the China household finance survey is analyzed to illustrate the application of the methodology.. .

In mesoscale eddies, chemical properties and biological composition are different from those in surrounding water, due to their unique physical processes. It is unclear how physical-biological coupling occurs in warm-core eddies, particularly since no study has examined the relationship between bacteria and viruses. The purpose of the present study was to examine the influence of anticyclonic warm eddy on the relationship between bacterial and viral abundances as well as viral activity (viral production) in different depths. In the core of warm eddy, bacterial abundance (0.48 to 2.82 ×105 cells mL−1) fluctuated less than that of the outside eddy (1.12 to 7.03×105 cells mL−1). In particular, there was four-folds higher of viral-bacterial abundance ratio (VBR) estimated within the eddy below DCM than the outside eddy. We suggest that prevailing physical forces with downwelling at the center of the anticyclonic warm eddy, viruses can also be transmitted into the deep ocean directly through adsorption on particulate organic matter during sinking. Overall, our findings provide valuable insights into the interaction between bacterial and viral communities and their ecological mechanism within the warm eddy.

(1) Background: in the context of sustainable development goals (SDGs), this work explores the repair direction of future cultivated land protection policies based on the Smith policy implementation model from the historical evolution to ensure that the cultivated land protection policy does not deviate during the implementation process. (2) Methods: this paper uses literature research and inductive deduction methods to sort out the evolution process of Chinese cultivated land protection policy, summarize the successful experience of transferring the focus of cultivated land protection in chronological order, and conclude the repair direction of Chinese cultivated land protection. (3) Results: although the Chinese cultivated land protection policy in the historical evolution has through three significant phases, there are still certain issues in the development trend of Chinese cultivated land protection policy based on regional division of labor for grain transportation and sales. (4) Conclusion: directly utilizing feedback from farmers as stakeholders will contribute to the maturity and improvement of cultivated land protection policies in the specific implementation of cultivated land protection policies.

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.

The quality of healthcare services is a very important indicator of social welfare in developed and emerging countries. Good quality levels are critical to ensuring patient safety, improving health outcomes, increasing patient satisfaction, optimizing resource utilization, and meeting regulatory requirements. The stable and sustainable operation of medical institutions urgently requires the establishment of a reliable and effective medical quality performance evaluation platform. However, the complexity of the evaluation process, involving numerous evaluators and the consideration of different subjective and objective criteria, poses significant challenges and essentially constitutes a group multi-criteria decision-making problem. This article uses the overall medical environment of the institution, medical service attitude, medical security, administrative service measures, etc. as measurement standards to deal with this challenge. It proposes a medical service quality measurement model suitable for both qualitative and quantitative analysis. In view of the heterogeneity of information, the two-tuple fuzzy language calculation method is introduced to enable evaluators to skillfully manage diverse information and effectively avoid potential information omission problems in the subjective evaluation integration process. The effectiveness and feasibility of the model were demonstrated by applying it to the operational framework of a medical institution in central Taiwan.

A real-time two-way direct load control (TWDLC) of central air-conditioning chillers in wide area is proposed to provide demand response. The proposed TWDLC scheme is designed to optimize the load shedding ratio of every customer under control to ensure the target load to be shed is met at every scheduling period. In order to overcome the load reduction uncertainties of TWDLC, an innovative solution is proposed by applying a certain degree of loosening on the constraint of the actual shed load. Fuzzy linear programming is utilized to solve the optimization problem with fuzzy constraints. The proposed fuzzy linear programming problem is solved by delicately transforming it into a regular liner programming problem. A selection scheme used to obtain the feasible candidates set for load shedding at every sampling interval of TWDLC is also designed along with the fuzzy linear programming.

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.

To further investigate the immune response of Macrobrachium rosenbergii against Aeromonas veronii, comparative transcriptomic analyses of the M. rosenbergii hepatopancreas were conducted on challenge and control groups at 6, 12, and 24 h post-infection (hpi), independently. A total of 51,707 high-quality unigenes were collected from the RNA-seq data, and 8,060 differentially expressed genes (DEGs) were discovered through paired comparisons. Among three comparison groups, KEGG pathway enrichment analysis showed that 173 immune-related DEGs were considerably clustered into 28 immune-related pathways, including the lysosome and phagosome, etc. Moreover, the expression levels of the four key immune-related genes (TOLL, PAK1, GSK3β, and IKKα) were evaluated at various stages following post-infection in the hepatopancreas, hemolymph, and gill. Both PAK1 and GSK3β genes were highly upregulated in all three tissues at 6 hpi with A. veronii; TOLL was up-regulated in the hepatopancreas and hemolymph but down-regulated in the gill at 6 hpi; and IKKα was up-regulated in hemolymph and gill, but down-regulated in the hepatopancreas at 6 hpi. These findings lay the groundwork for understanding the immune mechanism of M. rosenbergii after contracting A. veronii.

Major depressive disorder (MDD) is one of the most prevalent and disabling mental disorders worldwide. Among the symptoms of MDD, sleep disturbance such as insomnia is prominent and the first reason patients may seek professional help. However, the underlying pathophysiology of this comorbidity is still elusive. Recently, genome-wide association studies (GWAS) have begun to unveil the genetic background of several psychiatric disorders, including MDD and insomnia. Identifying the shared genomic risk loci between comorbid psychiatric disorders could be a valuable strategy to understand their comorbidity. This study seeks to identify the shared genes and biological pathways between MDD and insomnia based on their shared genetic variants. First, we performed a meta-analysis based on the GWAS summary statistics of MDD and insomnia obtained from Psychiatric Genomics Consortium and UK Biobank, respectively. Next, we associated shared genetic variants to genes using two gene mapping strategies: (a) positional mapping based on genomic proximity and (b) expression quantitative trait loci (eQTL) mapping based on gene expression linkage across multiple tissues. As a result, a total of 719 shared genes were identified. Over half (51%) of them are protein-coding genes. Functional enrichment analysis shows that the most enriched biological pathways are related to epigenetic modification, sensory perception, and immunologic signatures. We also identified druggable targets using a network approach. Together these results may provide insights into understanding the genetic predisposition and underlying biological pathways of comorbid MDD and insomnia symptoms.

Aluminum wire is a common material for wire bonding due to its resistance to oxidation and low price. It does not melt when becoming a free air ball (FAB) during the electronic flame-off (EFO) process with wettability, and is applied by wedge bonding. This study used 20μm Zn-Coated Al-0.5wt.%Si (ZAS) wires to improve the FAB shape after the EFO process, while maintaining stability of the mechanical properties, including the interface bonding strength and hardness. In order to test circuit stability after ball bonding, the current-tensile test was performed. During the experiment, it was found that 80nm ZAS with wire bonding has lower resistance and higher fusing current. For the bias tensile test, the thicker Zn film diffused into the Al-Si matrix easily, after which the strength was reduced. The ball-bond interfaces had no change in their condition before and after the bias. Accordingly, ZAS could be a promising candidate for ball bonding in the future.

Colonization of distant organs by tumor cells is a critical step of cancer progression. The initial avascular stage of this process (micrometastasis) remains almost inaccessible to study due to the lack of relevant experimental approaches. Here, we introduce an in vitro/in vivo model of organ-specific micrometastases of triple-negative breast cancer (TNBC) that is fully implemented in a cost-efficient chick embryo (CE) experimental platform. The model is built as three-dimensional (3D) tissue engineering constructs (TECs) combining human MDA-MB-231 cells and decellular-ized CE organ-specific scaffolds. TNBC cells colonized CE organ-specific scaffolds in 2-3 weeks, forming tissue-like structures. The feasibility of this methodology for basic cancer research, drug development and nanomedicine was demonstrated on a model of hepatic micrometastasis of TNBC. We revealed that MDA-MB-231 differentially colonize parenchymal and stromal com-partments of the liver-specific extracellular matrix (LS-ECM) and become more resistant to the treatment with molecular Doxorubicin (Dox) and Dox-loaded mesoporous silica nanoparticles than in monolayer cultures. When grafted on CE chorioallantoic membrane, LS-ECM-based TECs induced angiogenic switch. These findings may have important implications for the diag-nosis and treatment of TNBC. The methodology established here is scalable and adaptable for pharmacological testing and cancer biology research of various metastatic and primary tumors.

Reconstructing 3D indoor scenes from 2D images has always been an important task in computer vision and graphics applications. For indoor scenes, traditional 3D reconstruction methods suffer from the lack of surface details, poor reconstruction of large flat surface textures and areas with uneven lighting, and many falsely reconstructed floating debris noises in the reconstructed models. We add adaptive normal priors to the neural implicit reconstruction process to optimize the network, and improve the accuracy of volume density prediction by adding regularization terms to the neural radiation field to constrain the volume density obtained by weight distribution, and learn a smooth SDF surface from the network to obtain an explicit mesh model. Experiments show that the method proposed in this paper outperforms the state-of-the-art methods on ScanNet, Hypersim, and Replica datasets.

Multi-wire saw machining (MWSM) used for slicing hard-brittle materials in semiconductor, is an important material removal process that uses free abrasives. Cutting model of single-wire saw machining (SWSM) is the basis of MWSM, and the material removal mechanism of SWSM can better understand than MWSM. Mathematical model (includes brittle fracture and plastic deformation) is presented in this paper for SWSM ceramic with abrasives. This paper determines the effect of various machining parameters on the removal of hard-brittle materials. For brittle fracture of SWSM ceramics, the minimum of the strain energy density is used as a fracture criterion. The material removed of SWSM ceramics due to plastic deformation is calculated using the equations of motion. Actual wire-sawing experiments are conducted to verify the results from the developed mathematical model. Theoretical results agree with experimental data and practical experience. The developed mathematical model shows that brittle fracture plays a major concern role in material removed of SWSM ceramics. Wire speed and working load have positively correlated with material removed of SWSM ceramics. The coefficient of friction is low, a lateral crack, which propagates almost parallel to the working surface, leads to more brittle fracture and material removed is increased on SWSM ceramics.

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.

Transforaminal lumbar interbody fusion (TLIF) is a commonly used technique for treating lumbar degenerative diseases. Here, we developed a fully computer-supported pipeline to predict the cage height and the degree of lumbar lordosis subtraction from the pelvic incidence (PI-LL) after TLIF surgery through preoperative X-ray images. The automated pipeline included two primary stages. First, a deep learning model was used to extract essential features from X-ray images. Second, five machine learning algorithms were trained to identify the optimal models to predict the interbody cage height and postoperative PI-LL. Lasso regression and support vector regression exhibited superior performance for predicting the interbody cage height and postoperative PI-LL, respectively. For cage height prediction, the root mean square error (RMSE) was calculated as 1.01, and the model achieved the highest accuracy at a height of 12 mm, with exact prediction achieved in 54.43% (43/79) of cases. In most of the remaining cases, the prediction error of the model was within 1 mm. In addition, the model demonstrated adequate performance for predicting PI-LL, with an RMSE of 5.19 and an accuracy of 0.81 for PI-LL stratification. In conclusion, the interbody cage height and postoperative PI-LL can be reliably predicted using artificial intelligence and ML models.

A novel five-surface phosphor-in-ceramic (FS-PiC) for high illumination and excellent color uniformity in larger-scale LEDs for sensor light source application is demonstrated. YAG phosphor (Y3Al5O12:Ce3+) was uniformly mixed with ceramic and sintered at 680°C to form a phosphor wafer. A sophisticated laser engraving was employed on the phosphor wafer to form a saddle-shaped large-scale FS-PiC LEDs. The performance of the FS-PiC LEDs exhibited the illumination of 401lm, average color temperature (CCT) of 5488K±110K, and color coordinates (CIE) of (0.3179±0.003, 0.3352±0.003). In contrast to convention single-surface phosphor-in-ceramic (SS-PiC) LEDs, the performance exhibited the illumination of 380lm, average CCT of 5830K±758K, and CIE of (0.3083±0.07, 0.3172±0.07). These indicated that the performance of the FS-PiC LEDs was higher than the SS-PiC LEDs for illumination, CCT, and CIE of 1.1, 7, and 23 times, respectively. Furthermore, the FS-PiC LEDs demonstrate lower lumen loss of 2% and less chromaticity shift of 5.4x10-3 under accelerated aging at 350°C for 1008 hours, owing to the high ceramic melting temperature of up to 510°C. In this study, the proposed FS-PiC larger-scale LEDs having excellent optical performance and high reliability may be the promising candidates to replace the convention phosphor-in-organic silicone material used in high-power LEDs for the next generation of sensor light sources, display, and headlight applications.

IoT is a computational perception that defines a situation, where smart objects are interconnected to the internet/ network. In the last few years, IoT objects have increased in all sectors/ fields and use in all domains of our lives. As the number of devices increases, the privacy of data becomes an important issue. To deal with this issue different techniques have been used by researchers in this field. Unfortunately, these methods have less traceability, privacy of data, and accountability. This paper aims to design a blockchain-based network architecture for Traceability, Data privacy, and Accountability (TDA). Technologies of blockchain are known as a distributed ledger of transactions record, which record the life span information with a timestamp. The major features of blockchain are persistency, decentralization, and audibility. These features help to decrease the budget and increase efficiency. Moreover, to strengthen the TDA architecture, this paper also discusses the performance of the proposed architecture.

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.

Tefluthrin (Tef) is categorized as a type-I pyrethroid insecticide, telmisartan (Tel) functions as an angiotensin II receptor blocker, and KB-R7943 was identified as an inhibitor of Na+-Ca2+ exchange process. However, the influence of these compounds on the amplitude and gating properties of voltage-gated Na+ current (INa) in neurons associated with pain signaling remains unclear. In cultured dorsal root ganglion (DRG) neurons, whole-cell current recordings revealed that Tef or Tel increased the peak amplitude of INa, concomitant with an elevation in the time constant of INa inactivation, particularly in the slow component. Conversely, exposure to KB-R7943 resulted in a depression in INa, coupled with a decrease in the slow component of the inactivation time constant of INa. Theoretical simulations and bifurcation analyses were performed on a modeled interneuron in the spinal dorsal horn. The occurrence of INa inactivation accentuated the subthreshold oscillations (SO) in the membrane potential. With an increase in applied current, SO became more pronounced, accompanied by the emergence of high-frequency spiking (HF) with a frequency of approximately 150 Hz. Moreover, an elevation in INa conductance further intensified both SO and HF. Consequently, through experimental and in silico studies, this work reflects that Tef, Tel, or KB-R7943 significantly impacts the magnitude and gating properties of INa in neurons associated with pain signaling. The alterations in INa magnitude and gating in these neurons suggest a close relationship with pain transmission.

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.

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.

With the development of social economy, the quality of national life has been rapidly improved, along with the accelerated aging of the population and the continued prevalence of metabolic risk factors. Cardiometabolic diseases (CMDs) have become a major disease burden for both urban and rural residents in China, and most of them are related to lifestyle changes in modern society, especially circadian rhythm disorders. Circadian rhythm regulating the activity of metabolism, such as carbohydrates, lipids, and other nutrients, is the most important pathway modulating the health. Nowadays, studies have shown that the interaction between circadian rhythmicity and gut microbiota counts for the homeostasis of metabolic health, while circadian rhythm disruption is associated with gut microbiota dysbiosis and metabolic diseases. However, there is a lack of research on the topic of gut microbiota mechanisms regulating circadian rhythm disruption leading to CMDs. With increased burden of CMDs prevention and treatment, as well as the demand of healthcare resource allocation, it prompts us to put forward a new strategy to solve this problem. This review focuses on the interactions between circadian rhythm and gut microbiota to elucidate the potential mechanisms of circadian rhythm disruption induced CMDs, providing a solid support for further prevention and treatment.

Thyroid nodules (TNs) are common thyroid lesions in older population. Few studies focused on the prevalence of TNs and its relationship to lifestyle characteristics and dietary habits in centenarians. The current study aimed to determine the prevalence of TNs in Chinese centenarians using high-resolution ultrasound equipment and investigate its relationship to lifestyles and dietary habits. The current study was part of China Hainan Centenarian Cohort Study (CHCCS) which conducted in Hainan, an iodine sufficient region in China. A total of 874 permanent residents aged 100 years or older (mean age, 102.8 ± 2.8 years) without any missing data were included in the analysis. Among the participants, 649 of them were detected at least one thyroid nodule under the ultrasound examinations. The overall prevalence rate of TNs was 74.3%. The prevalence of TNs was higher in participants who were females, hypertension, diabetes, and underweight than their counterparts. Multivariate logistic regression analyses showed that being female, hypertension, diabetes, betel quid consumption, red meat consumption were independent risk factors, while being underweight, and nut consumption were independent protective factors for TNs. Our findings indicate that the presence of thyroid nodules was highly prevalent in Chinese centenarians, particularly in females. In addition to gender, hypertension, diabetes, and underweight, the presence of TNs was independently associated with betel quid, red meat, and nut consumptions. Further prospective studies are warranted to verify these associations in population from different age strata, races, cultures, and iodine backgrounds.

With the gradual improvement of coal mining efficiency, the disturbance of groundwater system caused by the high-intensity mining mode also increases, which is a more severe challenge to the prevention of mine safety and the protection of water resources in mining areas. How to accurately describe the dynamic changes of the groundwater system under mining and quantitatively predict mine water inflow is a major problem in the current research. Based on the full analysis of the response characteristics of groundwater system to the extraction disturbance, this paper forms a kind of method to establish a mine hydrogeological conceptual model that can accurately represent the water inrush process, and uses the MODFLOW non-structural division grid to accurately characterize the formation structure, and finally make accurate water inflow prediction. Taking the Caojiatan Coal Mine in Shaanxi Province, China as an example, a numerical model of unstructured mine water inrush was established for the first time, and the changes of water inflow source and water inflow intensity were quantitatively evaluated. Compared with the traditional water inflow prediction method, it is found that the prediction accuracy is improved by 12%~17% by detailing the response characteristics of complex groundwater system under high-strength coal seam mining conditions. The method is of great significance and promotion value for the comprehensive understanding of the disturbance characteristics of human underground engineering activities, such as coal mining, on the groundwater system, and for accurately predicting water inflow.

Color image binarization plays a pivotal role in image preprocessing work, significantly impacting subsequent tasks, particularly in text recognition. This paper concentrates on Document Image Binarization (DIB), aiming to separate a image into foreground (text) and background (non-text content). Through a thorough analysis of conventional and deep learning-based approaches, we conclude that prevailing DIB methods leverage deep learning technology. Furthermore, we explore the receptive fields pre- and post-network training to underscore the Transformer model's advantages. Subsequently, we introduce a lightweight model based on the U-Net structure, enhanced with the Mobile ViT module to better capture global information features in document images. Given its adeptness at learning both local and global features, our proposed model exhibits superior performance on two standard datasets (DIBCO2012 and DIBCO2017) compared to state-of-the-art methods. Notably, our proposed DIB method presents a straightforward end-to-end model devoid of additional image preprocessing or post-processing. Moreover, its parameter count is less than a quarter of the HIP'23 model, which achives best results on three datasets(DIBCO2012, DIBCO2017 and DIBCO2018). Finally, two sets of ablation experiments were conducted to verify the effectiveness of the proposed binarization model.