In this paper, the performance of Cu-(In,Ga)-S2 (CIGS2) solar cells with adjusting composite CGI-ratio absorber is explored and compared through an improved three-stage co-evaporation technique. For co-evaporating CIGS2 absorber as a less toxic alternative to Cd-containing film, we analyse the effect of the CGI-ratio stoichiometry and crystallinity, and explore its opto-electric sensing characteristic of individual solar cell. The results of this research signify the potential of high-performance CIGS2-absorption solar cells for photovoltaic (PV)-module industrial applications. For the optimal CIGS2-absorption film (CGI=0.95), the Raman main-phase signal (A1) falls at 291 cm-1, which is excited by the 532-nm line of Ar+-laser. Using photo-luminescence (PL) spectroscopy, the corresponding main-peak bandgaps measured is 1.59 eV at the same CGI-ratio film. Meanwhile, the best conversion efficiency (=3.212%) and the average external quantum efficiency (EQE=51.1% in the visible-wavelength region) of photo-electric properties were achieved for the developed CIGS2-solar cells (CGI=0.95). The discoveries of this CIGS2-absorption PV research provide a new scientific understanding of solar cells. Moreover, this research undeniably contributes to a major advancement towards practical PV-module applications and can help more to build an eco-friendly community.

In laser-assisted milling, higher temperature in shear zone softens the material potentially resulting in a shift of mean residual stress, which significantly affects the damage tolerance and fatigue performance of product. In order to guide the selection of laser and cutting parameters based on the preferred mean residual stress, inverse analysis is conducted by predicting residual stress based on guessed process parameters, which is defined as the forward problem, and applying iterative gradient search to find process parameters for next iteration, which is defined as the inverse problem. An analytical inverse analysis is therefore proposed for the mean residual stress in laser-assisted milling. The forward problem is solved by analytical prediction of mean residual stress after laser-assisted milling. The residual stress profile is predicted through the calculation of thermal stress, by treating laser beam as heat source, and plastic stress by first assuming pure elastic stress in loading process, then obtaining true stress with kinematic hardening followed by the stress relaxation. The variance-based recursive method is applied to solve inverse problem by updating process parameters to match the measured mean residual stress. Three cutting parameters including depth of cut, feed per tooth, and cutting speed, and two laser parameters including laser-tool distance and laser power, are updated with respected to the minimization of resulting residual stress and measurement in each iteration. Experimental measurements are referred on the laser-assisted milling of Ti-6Al-4V grade 5 and ELI. The percentage difference between experiments and predictions is less than 5% for both materials, and the selection is completed within 50 loops.

Our study optimized MET ex14 skipping mutation detection by analyzing 223 Oncomine Focus Assay (OFA)-positive cases using Pan Lung Cancer PCR Panel (AmoyDx) and reverse transcription (RT)-PCR. Among the 11 MET ex14 skipping mutation-positive cases (average read counts: 1,390), two with OFA read counts of 2540 and 10177 were positive on all platforms. Those with OFA read counts ranging from 179–612 tested negative elsewhere. Specimens with low ratios (average ratio: 0.12% for nine cases) may yield false-positive results. Our results suggested monitoring read counts and ratios, and validating results with RT-PCR, is crucial to prevent false positives.

Oriental lacquer, a natural and renewable polymeric coating, comes from the sap produced by lacquer trees. For practical application, oriental lacquer must be refined to reduce excess water and enhance its quality. In this study, drying oils were blended with oriental lacquer during the refining process to prepare an oil-modified refined lacquer (OMRL). The type and adding amount (0, 10, and 20% by wt.) of drying oils for wood coatings utilization were evaluated. Rhus succedanea oriental lacquer is composed of 54.1% urushiols, 34.3% water, 7.2% plant gum, and 4.4% nitrogenous compounds, and drying oils, including tung oil (TO), linseed oil (LO), and dehydrated castor oil (DCO) were used as materials in this study. The results show that the drying oil acts as a diluent, which reduces the viscosity and enhances the workability and could shorten the touch-free drying time and speed up the hardened drying of the OMRL. The results also indicate that the hardness, mass retention, Tg, tensile strength, abrasion resistance, and lightfastness of OMRL films decrease as more drying oils are blended. Conversely, the bending resistance, elongation at break, impact resistance increase, and particularly, the gloss, is greatly improved through the blending of more drying oils. In conclusion, the LO-modified refined lacquer (RL) has the highest film gloss and the DCO-modified RL has the shortest drying time for coating; otherwise, the film properties are similar among the three types of drying oil.

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

This study mainly explores the effect of policy formalism, equipment insufficiency, covid-19 fear and job insecurity on construction workers’ insomnia during the epidemic. The main contribution of this article is to introduce policy formalism into the exploration of the causes of insomnia among construction site workers during the epidemic. This study collected 733 valid samples of construction site workers. We tested the established hypotheses using confirmatory factor analysis and structural equation modeling. The research results found that equipment insufficiency positively affects Covid-19 fear. Policy formalism and Covid-19 fear positively affect job burnout. Social support negatively affects job burnout. Job burnout and job insecurity positively affect insomnia.

Helicobacter pylori (H. pylori) is known to play a significant role in the development of peptic ulcer diseases and gastric cancer. Previous studies have reported the existence of polymorphism in the ureC gene of H. pylori. However, the relationship between genetic sequence variations in ureC and the pathogenesis of peptic ulcer diseases remains unclear. We aimed to investigate the associations between ureC sequence variations and the development of gastric ulcer and gastric cancer. PCR amplification and DNA sequencing to analyze ureC sequences, and conducted phylogenetic analysis using MEGA X software. Samples from Taiwanese patients with gastric ulcer and gastric cancer were included in this study. PCR was used to amplify the ureC gene from these samples, followed by DNA sequencing. The obtained sequences were then subjected to phylogenetic analysis using MEGA X software. In addition, ureC sequences from different geographical regions, including China and other countries, were included in the analysis for comparison. Analysis of the ureC se-quences from Taiwanese samples revealed that 6 out of 7 gastric ulcer samples clustered together in one group, while the sequences from 7 out of 8 gastric cancer samples were distributed across other groups. Phylogenetic analysis incorporating ureC sequences from different geographical regions showed that Taiwanese ureC sequences could be divided into two distinct groups, although the bootstrap values supporting this separation were low. Notably, the ureC sequences from China formed a distinct group with a high bootstrap value, separate from sequences from all other countries. There are two genotypes of ureC sequences present in Taiwanese samples, with one genotype showing a closer association with gastric cancer. Additionally, the ureC sequences from China appear to be unique and separate from those obtained from other countries, indicating the presence of genetic diversity in ureC sequences among H. pylori strains from different regions, potentially contributing to differences in disease outcomes. Further research is needed to elucidate the specific mechanisms by which ureC sequence variations may influence the pathogenesis of peptic ulcer diseases and gastric cancer.

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.

This study aims to develop an elderly care system for improving the interpersonal relationship of the elderly with mild cognitive impairment (MCI) by employing the speaker recognition technique and association functionality of social network platforms. Firstly, the speaker recognition units based on the Gaussian Mixture Model (GMM) and Gaussian Mixture Model-Universal Background Model (GMM-UBM) are implemented to identify the visitor via individual input utterance. After the visitor is identified, the proposed system will be linked to the private database and social network platforms to extract the associated message of two parties. Experimental results indicate that the speaker recognition unit based on GMM-UBM achieves the best performance. Finally, five elderly persons are invited to measure the usability of the proposed system. A questionnaire is used to survey the five elderly persons, and the result indicates that the proposed system is highly potentially applicable in improving the interpersonal relationship of the elderly with MCI.

Force reduction is one of the most important benefit of applying ultrasonic vibration on milling. However, most of studies so far are limited to experimental investigation. In the current study, an analytical predictive model on cutting forces in ultrasonic vibration-assisted milling is proposed. The three types of tool-workpiece criteria are considered based on the instantaneous position and velocity of tool center. Type I criterion indicates that there is no contact if the instantaneous velocity is opposite to tool rotation direction. Type II criterion checks whether the vibration displacement is larger than the instantaneous uncut chip thickness. Type III criterion considers the overlaps between current and previous tool paths due to vibration. If none of these criteria is satisfied, milling forces are nonzero. Then the calculation is performed by transforming milling and tool geometry configuration to orthogonal cutting at each instant. The orthogonal cutting forces are predicted through the exhaustive search of shear angle and calculation of shear flow stress on tool-chip interface. The axial force is then calculated based on tool geometry, and the milling forces in feed, cutting, and axial directions are calculated after coordinate transformation. The proposed predictive force model in ultrasonic vibration-assisted milling is validated through comparison to experimental measurements on Aluminum alloy 2A12. The predicted values are able to match the measured milling forces with high accuracy of average difference of 13.6% in feed direction and 13.8% in cutting direction.

With the rise of the Internet of Things (IOT), mobile devices and Location-Based Social Network (LBSN), an abundant amount of trajectory data has made research on location prediction more popular. The check-in data shared through LBSN hides information related to life patterns, obtaining this information is helpful for location prediction. However, the trajectory data recorded by mobile devices is different from check-in data that has semantic information. In order to obtain the user’s semantic, relevant studies match the stay point to the nearest Point of Interest (POI), but location error may lead to wrong semantic matching. Therefore, we propose A Self-Attention for Next Location Prediction based on Semantic Mining to predict the next location. When calculating the semantic feature of a stay point, the first step is to search for the k nearest POI, then use the reciprocal of the distance from the stay point to the k nearest POI and the number of categories as weights. Finally, we use the probability to express semantic without losing other important semantic information. Furthermore, this research combined with sequential pattern mining can bring richer semantic features. In order to better perceive the trajectory, temporal features learn periodicity of time series by sine function. In terms of location features, we build a directed weighted graph and regard the frequency of users visiting locations as the weight, so the location features are rich in contextual information. We then adopt the Self-Attention model to capture long-term dependencies in long trajectory sequences. Experiments in Geolife show that the semantic matching of this study improved by 45.78% in TOP@1 compared with the closest distance search for POI. Compared with the baseline, the model proposed in this study improved by 2.5% in TOP@1.

This study evaluates the incidence and characteristics of adverse events (AEs) following the second COVID-19 booster dose, leveraging Taiwan's distinctive approach of extending booster vaccinations to all citizens, unlike the targeted high-risk group strategies in other countries. Utilizing data from Taipei Veterans General Hospital's Vaccine Adverse Event Reporting System (VAERS) from October 27, 2022, to January 19, 2023, the research examines AEs in 441 out of 1711 second booster recipients, considering factors like age, vaccine brands, and booster combinations. The findings reveal incidence rates (IR) of 25.6% (95% CI: 21.1-30.8) after the first booster and 24.9% (95% CI: 20.5-30.0) after the second, mostly non-serious, with those having AEs post-first booster 5 times more likely to report them again (Incidence rat rato, 5.02, P<0.001). Significantly, switching from the mRNA1273 vaccine to another brand reduced AE risk by 18%. The study underscores that AEs are more repetitive than cumulative with additional booster doses, advocating for personalized vaccination strategies based on individual medical histories and previous vaccine reactions. These insights are valuable for healthcare providers in discussing potential AEs with patients, thereby improving vaccine compliance and public trust, and for policymakers in planning future booster vaccination strategies.

The outbreak of novel coronavirus (COVID-19) infections in 2019 is in dire need of finding potential therapeutic agents. In this study, we used molecular docking to repurpose HIV protease inhibitors and nucleoside analogues for COVID-19, with evaluations based on docking scores calculated by AutoDock Vina and RosettaCommons. Our results suggest that Indinavir and Remdesivir possess the best docking scores, and comparison of the docking sites of the two drugs reveal a near perfect dock in the overlapping region of the protein pockets. After further investigation of the functional regions inferred from the proteins of SARS coronavirus, we discovered that Indinavir does not dock on any active sites of the protease, which may give rise to concern in regards to the efficacy of Indinavir. On the other hand, the docking site of Remdesivir is not compatible with any known functional regions, including template binding motifs, polymerization motifs and nucleoside triphosphate (NTP) binding motifs. However, when we tested the active form (CHEMBL2016761) of Remdesivir, the docking site revealed a perfect dock in the overlapping region of the NTP binding motif. This result suggests that Remdesivir could be a potential therapeutic agent. Clinical trials still must be done in order to confirm the curative effect of these drugs.

Due to the highly nonlinear, multi-stage, and strongly time-varying marine lysozyme fermentation process, it is difficult to assure the stability and prediction accuracy of the traditional single global soft sensor model on a global scale. This study innovatively proposed a soft sensor model based on an improved seagull optimization algorithm (ISOA) combined with Gaussian process regression (GPR) weighted ensemble learning. First, the sample data set is divided into multiple local sample subsets by the improved density peak clustering algorithm (ADPC). Second, the Gaussian process regression model is optimally altered with an improved seagull optimization algorithm for the purpose of establishing the corresponding sub-prediction model. Finally, the prediction model's fusion strategy is ultimately determined depending on the degree of connection between the test samples and a subset of local pieces. Simulation results show that the proposed soft sensor model, which searches GPR based on ISOA and combines various sub-models, can predict the key biochemical parameters of the marine lysozyme fermentation process better with less prediction error under the condition of fewer training data, and it can be expanded to the soft sensor models of general nonlinear systems, according to simulation results.

Patients with Peripheral-artery-disease (PAD) are prone to risks of major-adverse-limb-events (MALE), and major-adverse-cardiovascular-events (MACE). CHA2DS2-VASc is a prognostic score for Atrial fibrillation stroke risk, however, no study exists that evaluated its predictability for MALE and MACE in PAD patients. In this study, patients with PAD were stratified into four risk groups based on CHA2DS2-VASc score. Cox-proportional hazards models,10-fold cross-validation and Receiver operating characteristic (ROC) analyses were utilized to evaluate the predictability of CHA2DS2-VASc for predicting MALE, MACE, and MALE+MACE. Kaplan-Meier analysis estimated the survival-probability of risk-groups. CHA2DS2-VASc was found to be a significant predictor of MACE (hazard ratio (95% confidence interval; P) = 3.47 (0.99 - 12.18; 0.052), 4.12 (1.19 - 14.14; 0.024), and 5.06 (1.48 – 17.28; 0.009), for moderate-, high- and very-high-risk groups, respectively, while for MALE and MALE+MACE significance was achieved only for high-risk group. MACE demonstrated AUC > 0.8, good-discrimination (c-index > 0.8) and good-calibration. However, MALE and MALE+MACE models failed to achieve good performances. Based on all findings, CHA2DS2-VASc could potentially serve as a risk stratification score for predicting MACE in patients with PAD but failed to qualify as a good predictor for MALE.

Objectives. Invasive fungal spondylodiscitis (IFSD) is rare and could be lethal in certain circumstances. Previous literature revealed limited data concerning the outcomes. This study aimed to establish a risk-scoring system. Methods. A total of 53 patients were included in the study from a multi-centered database in Taiwan. All the clinicopathological and laboratory data were retrospectively analyzed. Variables strongly related to 1-year mortality were identified using a multivariate Cox proportional hazards model. A receiver operating characteristic curve was used to express the performance of our IFSD scoring model. Results. Five strong predictors were included in the IFSD score: predisposing immunocompromised state, the initial presentation of either radiculopathy or myelopathy, initial laboratory findings of WBC > 12.0 or < 0.4 103/uL, hemoglobin < 8 g/dL, and evidence of candidemia. 1-year mortality rates for patients with IFSD Scores of 0, 1, 2, 3, and 4 were 0%, 16.7%, 56.3%, 72.7%, and 100%, respectively. The area under the curve of the receiver operating characteristic curve was 0.823. Conclusions. We developed a practical scoring model with easily obtained demographic, clinical, and laboratory parameters to predict the probability of 1-year mortality in patients with IFSD. However, more large-scale and international validations would be necessary before this scoring model is commonly used.

The United Nations' sustainable development goals have underscored the importance of enhancing supply chain sustainability while appropriately distributing orders. This study proposes a novel framework involving Z-number, game theory, indifference threshold-based attribute ratio analysis (ITARA), and combined compromise solution method (CoCoSo) to evaluate the sustainability of suppliers and order allocations. To better reflect the decision makers’ current choices for the sustainability of assessed suppliers and order allocations; enhance the comprehensiveness of decision-making, the importance parameter of the supplier is obtained through game theory objectively for transforming supplier performance into order allocation performance. The Z-numbers are involved in ITARA (so-called ZITARA) and CoCoSo (so-called ZCoCoSo) to overcome the issue of information uncertainty in the process of expert evaluation. ZITARA and ZCoCoSo are applied to assess the objective weight of criteria and the ranking of assessed order allocations, respectively. Afterwards, a case study of China’s company is illustrated the utility of the proposed framework and inform their decision-making process regarding the orders to be assigned to the assessed suppliers.

Concrete cracks and local damage can affect the bond performance between concrete and steel bars, thereby reducing the durability of reinforced concrete structures. Compared with general concrete crack repair methods, biomineralization repair not only has effective bonding capabilities but is also particularly environmentally friendly. In view of this, this study aimed to apply biomineralization technology to repair damaged fiber-reinforced lightweight aggregate concrete (LWAC). Two groups of LWAC specimens were prepared. The control group used lightweight aggregates (LWAs) without bacterial spores and nutrient sources, and the experimental group used LWAs containing bacterial spores and nutrient sources. These specimens were first subjected to compression tests and pull-out tests, respectively, and thus were damaged. After the damaged specimen healed itself in different ways for 28 days, secondary compression and pull-out tests were conducted. The self-healing method of the control group involved placing the specimens in an incubator. The experimental group was further divided into experimental group I and experimental group II. The self-healing method of experimental group I was the same as that of the control group. The self-healing method of experimental group II involved soaking the specimen in a mixed solution of urea and calcium acetate for two days, and then taking it out and placing it in an incubator for two days, with a cycle of four days. The test results showed that, compared with the control group specimens, the relative bond strength ratio of the experimental group II specimens increased by 17.9%. Moreover, the EDS and XRD analysis results confirmed that the precipitate formed at the crack was calcium carbonate, which improved the compressive strength and bond strength after self-healing. This indicates that the biomineralization maintenance method used in experimental group II is more effective.

Exercise training influences the risk of vascular thrombosis in patients with peripheral arterial disease (PAD). Mitochondrial functionalities in platelets involve the cellular bioenergetics and thrombogenesis. This study aimed to elucidate the effect of cycling exercise training (CET) on platelet mitochondrial bioenergetics in PAD patients. Forty randomly selected patients with PAD engaged in general rehabilitation (GR) with CET (i.e., cycling exercise at ventilation threshold for 30 min/day, 3 days/week) (GR+CET, n=20) or to a control group that only received GR course (n=20) for 12 weeks. Systemic aerobic capacity and platelet mitochondrial bioenergetics that included oxidative phosphorylation (OXPHOS) and electron transport system (ETS) were measured using automatic gas analysis and high-resolution respirometry, respectively. The experimental results demonstrated that GR+CET for 12 weeks significantly (i) elevated VO2peak and lowered VE-VCO2 slope, (ii) raised resting ankle-brachial index and enhanced cardiac output response to exercise, (iii) increased the distance in 6-minute walk test and raised the Short Form-36 physical/mental component scores, and (iv) enhanced capacities of mitochondrial OXPHOS and ETS in platelets by activating FADH2 (Complex II)-dependent pathway. Moreover, changes in VO2peak levels were positively associated with changes in platelet OXPHOS and ETS capacities. However, no significant changes in systemic aerobic capacity, platelet mitochondrial bioenergetics, and health-related quality of life (HRQoL) occurred following GR alone. Hence, we conclude that CET effectively increases the capacities of platelet mitochondrial bioenergetics by enhancing Complex II activity in patients with PAD. Moreover, the exercise regimen also enhanced functional exercise capacity, consequently improving HRQoL in PAD patients.

The previous studies on the diversion pipe of pumped storage power stations (PSPS) primarily focused on numerical simulations of pulsating pressure propagation within the pipe and its inducing factors. However, there was a lack of field monitoring and analysis of measured data to support surface ambient vibration, resulting in insufficient credibility and practicality of the numerical results. Based on ambient monitoring and data analysis, this paper examines the factors contributing to the ambient vibration of the water diversion pipeline in Changlongshan (CLS) PSPS. It is concluded that: (1) The primary source of vibration originates from units operation-induced ambient vibrations; (2) Vibration during pumping conditions exceeds that during power generation conditions; (3) The ground measuring point's vibration acceleration primarily depends on the distance from the vibration source; (4) Different types of units have varying effects on water diversion pipeline vibrations.

A multiscale model that enables quantitative understanding and prediction of the size effect on scattering properties of micro- and nanostructures is crucial for the design of LED surface textures optimized for high light extraction efficiency (LEE). In this paper, a hybrid process for combining full-wave finite-difference time-domain simulation and a ray-tracing technique based on a bidirectional scattering distribution function model is proposed. We apply this method to study the influence of different pattern sizes of a patterned sapphire substrate on GaN-based LED light extraction from the microscale to the nanoscale. The results show that near-wavelength–scaled patterns with strong diffraction are not expected to enhance LEE. By contrast, microscaled patterns with optical diffusion behavior have the highest LEE at a specific aspect ratio, and subwavelength-scaled patterns that have antireflection properties show marked enhancement of LEE for a wide range of aspect ratios.

Skeletal muscle is a specialized tissue consisting of nondividing and multinucleated muscle fibers. Skeletal muscle-specific myostatin (MSTN) is a secreted protein that acts as a negative regulator of muscle mass by inhibiting proliferation and differentiation of myoblasts. In this study, we established a screening platform to monitor myostatin promoter activity in rat L8 myoblasts. Extract of Glycyrrhiza uralensis (GUE), an oriental herbal medicine, was identified through this screening platform and, the active fractions of GUE were identified by process-scale liquid column chromatography system. For in vivo study, the GUE as a feed additive was investigated in growth-finishing pigs. The results showed that GUE significantly increased body weight, carcass weight and lean content in pigs. Microbiota analysis indicated that GUE did not affect the composition of gut microbiota in pigs. In summary, this established rodent myoblast screening platform was used to identify a myogenesis-related phytogenic, GUE, and further demonstrated that the active fractions inhibited MSTN expression. These finding suggest a novel application for GUE in growth performance enhancement through modulation of MSTN expression. Furthermore, this established screening platform has great potential for identification and evaluation of a wide variety of phytogenics involving in myogenesis.

In our previous study, a novel barrier processing on a porous low-dielectric constant (low-k) film was developed: an ultrathin Mn oxide on a nitrogen-stuffed porous carbon-doped organosilica film (p-SiOCH(N)) as a barrier of the Cu film was fabricated. To form a better barrier Mn₂O_3-xN film, an additional annealing at 450°C was implemented. In this study, the electrical characteristics and reliability of this integrated Cu/Mn₂O_3-xN/p-SiOCH(N)/Si structure is investigated. The proposed Cu/Mn₂O_3-xN/p-SiOCH(N)/Si capacitors exhibited poor dielectric breakdown characteristics in the as-fabricted stage, although, less degradation was found after thermal stress. Moreover, its time-dependence-dielectric-breakdown electric-field acceleration factor slightly increased after thermal stress, leading to a larger dielectric lifetime in a low electric-field as compared to other MIS capacitors. Furthermore, its Cu barrier ability under electrical or thermal stress was improved. As a consequent, the proposed Cu/Mn₂O_3-xN/p-SiCOH(N) scheme is a promising integrity for back-end-of-line interconnects.

A single-crystal of ytterbium-doped “mixed” yttrium-lutetium aluminium garnet with a stoichiometric composition of (Y0.601Lu0.233Yb0.166)3Al5O12 was grown by the Czochralski method and its structure, vibronic, spectroscopic and laser properties were studied. The stimulated-emission cross-section for Yb3+ ions was maximized to 2.53×10-20 cm2 at 1031 nm, the emission bandwidth is ~8 nm and the reabsorption-free luminescence lifetime of the 2F5/2 state is 1.063 ms. Pumped at 941 nm, the Yb-laser generated a maximum output power of 1.04 W at 1.03 and 1.05 μm with a high slope efficiency of 76.4% and a laser threshold of 76 mW. A continuous wavelength tuning over a range of 51.6 nm (1026.4 - 1078.0 nm) was also achieved. Power scaling is achieved using a 969 nm-diode pumped microchip cavity. A maximum output power of ~9 W is obtained at 1.05 μm with a slope efficiency of 76% and with an almost circular laser beam profile.

With the rapid growth of large language models (LLMs), there is increasing demand for memory and computation in LLMs. Recent efforts on post-training pruning of LLMs aim to reduce the model size and computation requirements, yet the performance is still sub-optimal. In this paper, we present a plug-and-play solution for post-training pruning of LLMs. The proposed solution has two innovative components: 1) Relative Importance and Activations (RIA), a new pruning metric that jointly considers the weight and activations efficiently on LLMs; and 2) Channel Permutation, a new approach to maximally preserve important weights under N:M sparsity. The two proposed components can be readily combined to further enhance the N:M semi-structured pruning of LLMs. Our empirical experiments show that RIA alone can already surpass all existing post-training pruning methods on prevalent LLMs, e.g., LLaMA ranging from 7B to 65B. Furthermore, N:M semi-structured pruning with channel permutation can even outperform the original LLaMA2-70B on zero-shot tasks, together with practical speed-up on specific hardware. Our code is available at: https://github.com/biomedical-cybernetics/Relative-importance-and-activation-pruning

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/.

In recent years, exterior-rotor brushless DC motors have become increasingly popular in robotics applications due to their compact shape and high torque density. However, these motors were originally used for continuous operation in drones. For applications such as exoskeletons, prostheses, or legged robots, short bursts of high power are often required. Unfortunately, vendors do not typically provide data on the motors' performance under these conditions. This paper presents experimental data on the torque-speed relationship, efficiency, and thermal responses of one of the most widely used outrunner-type brushless motors across its full operating range, including high-power, short-duration operation. The results of this study can inform the selection and design of actuators for a range of robotics applications, particularly those that require high power output for brief periods of time.

As in glaucoma and other optic neuropathies cellular dysfunction often precedes cell death, sensitive assessment of retinal ganglion cell (RGC) function represents a key outcome measure for neuroprotective strategies aimed at targeting distressed but still viable cells. Here we offer a conceptual framework to identify progressive stages of RGC dysfunction leading to cell death in mouse models of glaucoma and other optic neuropathies based on non-invasive pattern electroretinogram (PERG), to differentiate phenotypic and altered RGC response dynamics, to assess susceptibility to stressors and to assess reversible dysfunction.

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

Epigallocatechin-3-gallate (EGCG) is the most abundant polyphenol in green tea. In this study, the effects of dietary EGCG on oxidative stress and the metabolism and toxicity of acetaminophen in liver were investigated. Rats were fed the diets with (0.54 %) or without EGCG supplementation for four weeks and were then intraperitoneally injected with acetaminophen (1g/kg). Results showed EGCG lowered hepatic oxidative stress and cytochrome P450 (CYP) 1A2, 2E1, and 3A, and UDP-glucurosyltransferase activities prior to acetaminophen injection. After acetaminophen challenge, the elevations in plasma alanine aminotransferase activity and histological changes in liver were ameliorated by EGCG treatment. EGCG reduced acetaminophen-induced apoptosis by increasing the Bax/Bcl2 ratio in liver. EGCG mildly increased autophagy by increasing the LC3B II/I ratio. Lower hepatic acetaminophen-glutathione and acetaminophen-protein adducts contents were observed after EGCG treatment. EGCG increased glutathione peroxidase and NAD(P)H quinone 1 oxidoreductase activities and reduced organic anion-transporting polypeptides 1a1 expression in liver after acetaminophen treatment. Our results indicate that EGCG may lower oxidative stress and reduce the metabolism and toxicity of acetaminophen. The reductions in CYP-mediated acetaminophen bioactivation and uptake transporter, as well as enhanced antioxidant enzyme activity, may limit the accumulation of toxic products in liver and thus lower hepatotoxicity

The aim of this study was to examine oxidative stress and low level of alpha-1-antitrypsin (A1AT) in primary Sjögren's syndrome (pSS), and evaluate the associated autoreactivity against unmodified and their 4-hydroxy-2-nonenal (HNE)-modified peptides with pSS. Two differentially expressed proteins, alpha-1-acid glycoprotein 1 (A1AG1) and A1AT, exhibited 2-fold differences, and their HNE modifications were identified by depleted-albumin and immunoglobulin G (IgG) serum protein, in-solution digestion, in-gel digestion, and nano-LC-MS/MS from pSS patients and age-matched healthy controls (HCs). Furthermore, levels of proteins, confirmation of HNE modifications, HNE-protein adducts and autoreactivity against unmodified and their HNE-modified peptides were further validated. Levels of the HNE-protein adduct and A1AG1 were significantly higher in pSS patients than HCs, but levels of A1AT were significantly lower in pSS patients compared to HCs. Only the HNE modification of A1AT was confirmed. Further, concentrations of anti-A1AT^50-63 IgG and anti-A1AT^50-63 HNE IgA were significantly lower in pSS patients than HCs. Our study suggests that elevated HNE-protein adduct, oxidative stress, level [odds ratio (OR) 4.877, p = 0.003], lowered A1AT level (OR 3.910, p = 0.010) and a decreased level of anti-A1AT^50-63 IgG (OR 3.360, p = 0.010) showed an increased risk in pSS patients compared to HCs, respectively.

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

Product innovation is a crucial factor in enterprise survival. Even though there are sources from strategic theory that guides the clear comprehension towards appreciating the nexus between these two variables (product innovation and enterprise survival), there are still many lacunas that should be addressed and filled. Consequently, the need for additional empirical corroboration or support is pertinent. This study aimed at verifying the nexus between product innovation and enterprise survival, and how they are affected by the existence of antecedent variables such as competitive intensity and competitive advantage. In the methodology, this study adopts the conduct of explanatory and cross-sectional investigations through the use of structural equation modelling (SEM) to a sample of selected food and beverages enterprises in Lagos, Nigeria. Regarding the food and beverage enterprises in Lagos, Nigeria, this study discovered that competitive intensity has huge positive implication on product innovation at (0.39; t = 5.69, p < 0.05). This gives numerical evidence that, in the face of more market competition, enterprises will be pressured to adopt the model of costs reduction on products which will enhance the reduction of product prices, and will have significant impact on profit. However, the findings reveal that there is no significance between competitive advantage and product innovation at (0.002; t = 0.203, p > 0.05), and there is no significance between product innovation and enterprise survival at (-0.035; t = -1.583, p > .05). As a result, the food and beverage enterprises should concentrate more on product innovation so that they will be able to stand the intensity of competition. The results emanated from the study is germane as it make significant contribution to literature and the body of knowledge and on strategic management by enlightening that competitive intensity is a necessary inducement for product innovation.

(1) Background: Breast cancer is the second leading cause of cancer death among women. The accurate prediction of survival intervals will help physicians make informed decisions on treatment strategies or the use of palliative care for patients; (2) Methods: The gene expression is predictive and correlates to patient prognosis. To establish a reliable prediction tool, we collected the RNA-seq data of breast cancer patients, a total of 1187 RNA-seq data (median age 58 years), in FPKM format from the TCGA database. Among them, 144 RNA-seq data with date of death information was selected to establish the SaBrcada-AD dataset. We first normalized the SaBrcada-AD dataset to transcripts per million (TPM) to build survival prediction model SaBrcada. After normalization and dimension raising, the differential gene expression data were used for testing eight different deep learning architectures. Among them, GoogLeNet performed the best. Considering the effect of age on prognosis, we examined all ages between the lower and upper quartiles of patient age for a stratified random sampling test; (3) Results: Stratifying by age based on a cut-off of 61 years of age improved the accuracy of SaBrcada compared to previous findings, resulting in an accuracy of 0.798. We also built a free website tool to provide 5 kinds of predicted survival period information for clinician reference; (4) Conclusions: We established a breast cancer survival analysis prediction model, SaBrcada, and a website tool with the same name. Through this highly reliable survival analysis model and website tool, information on survival intervals will be provided for clinicians as part of precision medicine.

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%.

Molecular hydrogen (H2) has been shown to have antioxidant and anti-inflammatory activities that may reduce the development and progression of many diseases. In this study, Hydrogen-rich water (HRW) was obtained by reacting hybrid magnesium-carbon hydrogen storage materials with water. Then the effects of intake of HRW on the activities of xenobiotic-metabolizing enzymes, membrane transporters, and oxidative stress in rats were investigated. Rats were given HRW ad libitum for 4 weeks. Results showed that intake of HRW had no significant effect on the activities of various cytochrome P450 (CYP) enzymes (CYP1A1, 1A2, 2B, 2C, 2D, 2E1, 3A, 4A), glutathione-S-transferase and UDP-glucuronosyltransferase. Except for a slight lower plasma glucose concentration, intake of HRW had no effect on other plasma biochemical parameters in rats. P-Glycoprotein and multidrug resistance-associated protein (Mrp)2 protein expressions in liver were elevated after intake of HRW. However, HRW had no significant effects on glutathione, glutathione peroxidase, or lipid peroxidation in liver. Results from this study suggest that consumption of HRW may not affect xenobiotic metabolism or oxidative stress in liver. However, intake of HRW may increase the efflux of xenobiotics or toxic substances from the liver into bile by enhancing the expression of p-glycoprotein and Mrp2 protein.

Water electrolysis is a compelling technology for the production of environmentally-friendly hydrogen, minimizing carbon emissions. The electrolysis process of water heavily relies on the effective and steady oxygen evolution reaction (OER) taking place at the anode. Herein, we in-troduce a highly promising catalyst for OER called CoSe2@NiFeOOH arrays, which are supported on a nickel foam. This catalyst, referred to as CoSe2@NiFeOOH/NF, is fabricated through a two-step process involving the selenidation of a Co-based porous metal organic framework and subsequent electrochemical deposition on a nickel foam. The CoSe2@NiFeOOH/NF catalyst demonstrates outstanding activity for the OER in an alkaline electrolyte. It exhibits a low over-potential (η) of 254 mV at 100 mA cm−2, a small Tafel slope of 73 mV dec−1, and excellent high stability. The high performance of CoSe2@NiFeOOH/NF can be attributed to the combination of the high conductivity of the inner layer and the synergistic effect between CoSe2 and NiFeOOH. This study offers an effective method for the fabrication of highly efficient catalysts for the OER.

Inflammation has been reported as a facilitator in cervical oncogenesis, but the correlation between inflammation and cytology abnormality including Cervical Intraepithelial Neoplasia (CIN) remains uncertain. The aim of this study was to investigate the correlation between them with ThinPrep cytological test (TCT) as a screening tool for cervical cancer and CIN, which can identify abnormal morphology of cervical mucosa epithelium and inflammation degrees. A retrospective analysis of clinical data from 48101 women undergoing TCT in the affiliated hospitals of Sun Yat-Sen University (SYSU) revealed that among the 8.87% (4102 cases) total positive rate of ASC, LSIL and HSIL, 67.7% (2777/4102) of TCT positive samples had inflammatory infection. The rate of severe inflammation was significantly higher in cytological abnormality group than the control group (15.1% vs. 2%, P=0.000). Our results showed that severe inflammation significantly increased incidence of cytological abnormality by 12.59 times and elevated the risk of HSIL by 756.47 times. In conclusion, severe inflammation increased the risk of cytological abnormality, and should be viewed as an important risk of HISL. These results of our study remind clinicians to be more watchful for women with severe cervical inflammation in TCT reports for earlier prevention of the HSIL.

Mercury (Hg) is a toxic element impacting on biological systems and ecosystems. Because the toxicity of Hg species is highly dependent on concentration levels and chemical forms, sensitive identification of chemical forms for Hg, i.e., Hg speciation, is of major significance in providing meaningful information about the source of Hg exposure. In this study, a microfluidic-based device made of high clarity poly(methyl methacrylate) (PMMA) was fabricated. Then titanium dioxide nanoparticles (nano-TiO2) were attached to the treated channel interior with the aid of poly(diallyldimethylammonium chloride) (PDADMAC). After coupling the nano-TiO2-coated microfluidic-based photocatalyst-assisted reduction device (the nano-TiO2-coated microfluid-ic-based PCARD) with high-performance liquid chromatography (HPLC) and inductively coupled plasma-mass spectrometry (ICP-MS), a selective and sensitive hyphenated system for Hg specia-tion was established. Validation procedures demonstrated that the method could be satisfactorily applied to the determination of mercuric ion (Hg2+) and methylmercury ion (CH3Hg+) in both human urine and water samples. Remarkably, the zeta potential measured clearly indicated the PDADMAC-capped nano-TiO2 with predominance of positive charges indeed provided steady force for firm attachment to the negatively charged device channel. The cause for the durability of the nano-TiO2-coated microfluidic-based PCARD was clarified thus.

In China's mountainous coastal terrain, the storm badly damaged low-rise buildings. At present, it is not clear how the relative position of buildings and mountains affects the surface of a low-rise building’s fluctuating coefficient. The study compared these results with the wind pressure distribution without the surrounding environment. The primary objective of this study is to examine the fluctuating coefficient variation rule based on the spacing between hillsides and buildings under 0° wind angle. Additionally, the study analyzes the fluctuating wind pressure coefficient across wind angles between 0°~90°. The distribution of wind pressure in different common hillside landforms was examined through a wind tunnel experiment, which also compared with the distribution in an open environment. The study examined the fluctuating coefficient as the distance between the building and the hillside changed, specifically for wind blowing at a 0° angle. Next, an analysis is conducted on the changing pattern of the fluctuating coefficient for low-rise buildings ranging from a wind angle of 0° to 90°. Simultaneously, the investigation examined the power spectrum and wind pressure’s probability distribution, while considering the proximity of the building to an adjacent hill. The findings indicated that the changing wind pressure factor on the surface of the structure differed based on the relative location of the hillside and the building. The roof's wind pressure coefficient fluctuated and gradually increased until it reached its peak, unaffected by the surroundings. The low-frequency energy decreased in windward eaves, while the high-frequency energy progressively rose as the distance between the hillside and the building increased. The wind pressure on the leeward side exhibited Gaussian characteristics in its probability distribution.

Background: This retrospective study evaluates the survival effects of metronomic maintenance therapy with fluoropyrimidine in patients with stage III colorectal cancer (CRC) according to epidermal growth factor receptor (EGFR) expression. Methods: We enrolled 197 patients with stage III CRC who had undergone radical resection and FOLFOX regimen adjuvant chemotherapy. The clinicopathological features and effects of metronomic maintenance therapy on survival according to treatment group and EGFR expression were analyzed. By conducting an in vitro cell line study and in vivo study through knockdout of EGFR gene, we analyzed the capacities of cell proliferation and migration. Results: Postoperative relapse and mortality were significantly more common in the FOLFOX group. Metronomic maintenance therapy was a significantly independent predictive factor of postoperative relapse and mortality, as well as a prognostic factor of disease-free survival and overall survival. The significant differences of survival between the two groups were only observed in patients with positive EGFR expression. Conclusions: The present study suggested EGFR expression as the prognostic factor in patients with stage III CRC receiving metronomic maintenance therapy. By analyzing EGFR expression, we can identify the potential candidates with optimal survival benefit from metronomic maintenance therapy in patients with stage III CRC.

Prostate-specific membrane antigen (PSMA) is a well validated prostate cancer marker, but reported PSMA-targeted tracers derived from the Lys-urea-Glu pharmacophore including the clinically validated [99mTc]Tc-EDDA/HYNIC-iPSMA have high off-target uptake in kidneys, spleen and salivary glands. In this study, we synthesized and evaluated three novel 99mTc-labeled PSMA-targeted tracers and investigated if the tracers derived from the Lys-urea-Aad pharmacophore could have minimized uptake in off-target organs/tissues. In vitro competition binding assays showed that compared with HYNIC-iPSMA, the three novel ligands had slightly weaker PSMA binding affinity (average Ki = 3.11 vs 8.96 - 11.6 nM). Imaging and ex vivo biodistribution studies in LNCaP tumor-bearing mice showed that [99mTc]Tc-EDDA/HYNIC-iPSMA and the three novel tracers successfully visualized LNCaP tumor xenografts in SPECT images and were excreted mainly via the renal pathway. The average tumor uptake at 1 h post-injection varied from 5.40 to 18.8 %ID/g, and the tracers derived from the Lys-urea-Aad pharmacophore had much lower uptake in spleen and salivary glands. Compared with the clinical tracer [99mTc]Tc-EDDA/HYNIC-iPSMA, the Lys-urea-Aad derived [99mTc]Tc-EDDA-KL01127 had lower background uptake and superior tumor-to-background contrast ratios, and is therefore promising for clinical translation to detect prostate cancer lesions with SPECT.

The thermal decomposition of brominated butyl rubber under air atmosphere was investigated by thermogravimetry (TG) and derivative thermogravimetry (DTG) at various heating rates. The kinetic parameters were evaluated by TG and the isoconversional method developed by Ozawa. One prominent decomposition stage was observed in the DTG curves at high heating rates while an additional small peak was observed at low heating rates. The apparent activation energy determined using the TG method ranged from 219.31–228.13 kJ·mol-1 at various heating rates. The non-isothermal degradation was found to be a first order reaction, and the activation energy, as determined by the isoconversional method, increased with an increase in mass loss. The kinetic data suggested that brominated butyl rubber had excellent thermal stability. This study will indirectly aid in improving rubber pyrolysis methods and in enhancing the heat resistance of materials.

Heat dissipation from Li-ion batteries is a potential safety issue for large-scale energy storage applications. Maintaining low and uniform temperature distribution, and low energy consumption of the battery storage is very important. We studied the fluid dynamics and heat transfer phenomena of a single cell, 16-cell modules, battery packs, and cabinet through computer simulations and experimental measurements. The results show that the temperature distribution of single cell is relatively uniform when the cell is facing the air flow. In a module, very high air flow rate and large gap between the cells can reduce the cell temperature. A pack with a good thermally conductive case is very important to ensure good heat dissipation of the battery module. Due to limited space in the cabinet, additional air inlets and outlets can be opened outside of the cabinet to slightly lower the pack temperature. Installing fins outside the cabinet can also slightly reduce the temperature inside the cabinet. Liquid cooling medium, such as water, is much better than the air-cooling medium.

Compared to the southern Tibetan Plateau, the northern part has been regarded as relatively lacking geothermal resources. However, there is no lack of natural hot springs exposed in beads along large-scale fracture systems, and research on them is currently limited to individual hot springs or geothermal systems. This paper focuses on the Wahongshan-Wenquan Fracture Zone (WWFZ), analyzes the formation of five hydrothermal activity zones along the fracture zone in terms of differences in the hydrochemical and isotopic composition of the hot water, and then explores the hydrothermal control of hot springs in the zone by the fracture. The results show that the main Fractures of WWFZ is the regional heat-control structures, and the fracture system formed by a small number of near-north-south and near-east-west fractures transversal to it provides a favorable channel for deep hydrothermal convective circulation. Ice and snow melt water from the Ngola Shan Mountains, with an average elevation of more than 4,500 meters above sea level, infiltrates along the fractures and is heated by deep circulation to form deep geothermal reservoirs. There is no detectable contribution of mantle source heat to the hot spring gases, and the heat source is mainly natural heat conduction warming, but the "Low-Velocity body (LVB)" in the middle and lower crust of the area may be the primary heat source of the high geothermal background in the area. The hydrochemical components of the hot springs in the area show a certain regularity, and the main ionic components, TDS and water temperature, tend to increase away from the main rupture, reflecting the controlling effect of the WWF on the hydrothermal transport in the area. In the future, the geothermal work in this area should focus on the hydrothermal control properties of different levels, the nature of fractures in the area, and the thermal contribution of LVB in the middle and lower crust.

This study delves into the impact of artificial intelligence on students’ learning.The paper pioneers the use of kmeans classification to reduce the dimensionality of features before the classification process, which minimizes redundant information and computational overhead. This step is not commonly found in prior research.Firstly, a random forest model is established with “whether AI assistance was used to complete the paper” as the output, and various features as inputs. The analysis of the predictive accuracy when changing input features reveals the degree of influence of each feature on using AI to complete the paper. After feature selection, the remaining 6 features can still effectively predict the use of AI to complete the paper, indicating the representativeness of the extracted indicators. Subsequently, the PCA-K-means algorithm is employed to classify the use of artificial intelligence. PCA algorithm is used for dimensionality reduction of the extracted features to better characterize students’ use of AI. Three representative variables are selected, and the contribution of each feature is computed based on the factor loading matrix. Finally, the K-means algorithm is used to classify students based on the three dimensional features, showing that students can be effectively classified into 2 categories. The results indicate that the majority of students support the use of AI technology to enhance their abilities, although some students may only intend to use AI to cope with exams and similar tasks.

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.

This study investigated the roles of low-molecular-weight fucoidan (LMWF) in enhancing the anti-cancer effects of fluoropyrimidine-based chemotherapy. HCT116 and Caco-2 cells were treated with LMWF and 5-FU. Cell viability, cell cycle, apoptosis, and migration were analyzed in both cell types. Potential mechanisms underlying how LMWF enhances the anti-cancer effects of fluoropyrimidine-based chemotherapy were also explored. The cell viability of HCT116 and Caco-2 cells was significantly reduced after treatment with a LMWF-5-FU combination. In HCT116 cells, LMWF enhanced the suppressive effects of 5-FU on cell viability through the 1) induction of cell cycle arrest in the S phase and 2) late apoptosis mediated by the Jun-N-terminal kinase (JNK) signaling pathway. In Caco-2 cells, LMWF enhanced the suppressive effects of 5-FU on cell viability through both c-mesenchymal–epithelial transition (MET)/ Kirsten Rat Sarcoma virus (KRAS)/ extracellular signal-regulated kinase (ERK) and c-MET/ phosphatidyl-inositol 3-kinases (PI3K)/ protein kinase B (AKT) signaling pathways. Moreover, LMWF enhanced the suppressive effects of 5-FU on tumor cell migration through the c-MET/ matrix metalloproteinase (MMP)-2 signaling pathway in both HCT116 and Caco-2 cells. Our results demonstrated that LMWF is a potential complementary therapy for enhancing the efficacies of fluoropyrimidine-based chemotherapy in colorectal cancers (CRCs) with the wild-type or mutated KRAS gene through different mechanisms. However, in vivo studies and in clinical trials are required to validate the results of the present study.

Enterovirus 71 (EV71) is an etiological agent of hand foot and mouth disease and can also cause neurological complications in young children. However, there are no approved drugs to treat EV71 infections. In this study, we conducted an antiviral drug screening by using a Food and Drug Administration (FDA)-approved drug library. We identified five drugs that showed dose-dependent inhibition of viral replication. Sertraline was further characterized because it exhibited the most potent antiviral activity with the highest selectivity index among the five hits. The antiviral activity of sertraline was noted for other EV serotypes. The drug’s antiviral effect is not likely associated with its approved indications as an antidepressant and its mode-of-action as a selective serotonin reuptake inhibitor. The time-of-addition assay revealed that sertraline inhibited an EV71 infection at the entry stage. We also showed that sertraline partitioned into acidic compartments, such as endolysosomes, to neutralize the low pH levels. In agreement with the findings, the antiviral effect of sertraline could be relieved greatly by exposing virus-infected cells to extracellular low-pH culture media. Together, we have identified an FDA-approved antidepressant with the new indication for the broad-spectrum EV inhibition by blocking viral entry through the alkalization of the endolysosomal route.

Performance of the overhead squat may affect golf swing mechanics associated with golf-related low back pain. This study investigates the difference in lumbar kinematics and joint loads during the golf downswing between golfers with different overhead squat abilities. Based on the per-formance of the overhead squat test, 21 golfers aged 18 to 30 years were divided into the highest-scoring group (HS, N=10, 1.61 ± 0.05 cm, and 68.06 ± 13.67 kg) and lowest-scoring group (LS, N=11, 1.68 ± 0.10 cm, and 75.00 ± 14.37 kg). Data collection used a motion analysis system, two force plates, and TrackMan. OpenSim software was used to simulate the joint loads for each lum-bar joint. An independent t-test was used for statistical analysis. Compared to golfers demonstrat-ing limitations in the overhead squat test, golfers with better performance in the overhead squat test demonstrated significantly greater angular extension displacement on the sagittal plane, smaller lumbar extension angular velocity, and smaller L4-S1 joint shear force. Consequently, the overhead squat test is found to be a useful index to reflect lumbar kinematics and joint loading patterns during the downswing, and provides a good training guide reference for reducing the risk of a golf-related low back injury

This study aims to develop novel automated computer vision algorithms and systems for component replacement inspection for Printed Circuit Boards (PCBs). The proposed algorithms are able to identify locations as well as sizes of different components. They are object detection algorithms based on keypoints of the target components. The algorithms can be implemented as neural networks consisting of two portions: frontend networks and backend networks. The frontend networks are used for the feature extractions of input images. The backend networks are adopted for producing component inspection results. Each component class can has its own frontend and backend networks. In this way, the neural model for the component class can be effectively reused for different PCBs. To reduce the computation time for the inference of the networks, different component classes can share the same frontend networks. A two-stage training process is proposed for effectively exploring features of different components for accurate component inspection. The proposed algorithm has the advantages of the simplicity for training data collection, high accuracy for defect detection, and high reusability and flexibility for online inspection. The algorithm is an effective alternative for the automated inspection in smart factory with growing demand for product quality and diversification.

In this study, a simple, easy and convenient fluorescent sensing system for detection of vascular endothelial growth factor (VEGF) based on VEGF aptamers, aptamer-complementary fluorescence-labeled probe and streptavidin magnetic beads was developed in only one single tube. The VEGF is the most important biomarker in cancer angiogenesis, and is investigated that serum VEGF level was various according to the different type and course of cancers. Hence, efficient quantification of VEGF is able to improve the accuracy of cancer diagnosis and precision of disease surveillance. In this research, the VEGF aptamer was designed to be able to bind with the VEGF by forming G-quadruplex secondary structures, and then the magnetic beads would capture the none-binding aptamers due to none steric interference, and finally, the fluorescence-labeled probes were hybridized with the aptamers captured by the magnetic beads. Therefore, the fluorescent intensity in the supernatant would specifically reflect the present of VEGF. After an overall optimization, the optimal conditions for detection of VEGF were as followed, KCl, 50 μM; pH 7.0; aptamer, 0.1 μM and magnetic beads, 10 μL (4 μg/μL). The VEGF could be well quantified within a range of 0.2-2.0 ng/ml in plasma, and the calibration curve possessed a good linearity (y = 1.0391x + 0.5471, r = 0.998). The detection limit (LOD) was calculated to be 0.0445 ng/mL according to the formula (LOD = 3.3×σ/S). The specificity of this method was also investigated under the appearance of many other serum proteins, and the data showed the good specificity in this aptasensor-based magnetic sensing system. This strategy provided a simple, sensitive and selective biosensing platform for detection of serum VEGF. Finally, it was expected that this detection technique can be promoted to more clinical applications.

Numerous cases and a shortage of resources usually limit wild animal rescue. New technology implemented might save these severely injured wild animals from the situation of euthanasia by easing the requirement of intensive medication. Three-dimensional (3D) technologies provide precise and accurate results that improve the quality of the medical application. These 3D tools have become relatively low-cost and accessible in the past years. In the medical field of exotic animal, turtle shell defect is highly challenging because of inevitable water immersion. This report is the first attempt to apply the combination of 3D scanning, computer-aid design (CAD), and 3D printing to make a protective device that frees the wound from exposure to water or infection sources. The presenting techniques successfully extricate a wild freshwater turtle from an extensive shell defect within a short period. Integration of multiple sciences to 3D technology can provide a facile model for veterinary medical applications.

Despite huge effort has been devoted to the design of the initiators and reaction conditions, it remains challenging to synthesize high molecular weight polypeptides with conventional solution phase synthesis. In this work, surface-initiated vapor deposition polymerization (SI-VDP) was utilized to graft synthetic polypeptides poly (γ-benzyl L-glutamate) (PBLG) from polystyrene (PS) resin beads by ring-opening polymerization of N-carboxyanhydrides (NCAs). It was demonstrated for the first time that high molecular weight bulk PBLG (> 500,000) could be readily obtained within one hour via solvent-free synthetic method which paves the way for the synthesis of copolypeptides with high molecular weight.

Steam Generator Level Control System (SGLCS) is one of the key instrumentations and control subsystems to ensure the safe operation of nuclear power plants. It is highly recommended to perform reliability analysis for SGLCS for making better maintenance strategy. SGLCS is a digital control system with complex redundant configuration and failure\self-diagnosis\repair action, traditional fault tree is not applicable due to its static property, Markov model is not a good choice too because of heavy burden of creating state transition graph for even medium-size system. Boolean Logic Driven Markov Process (BDMP) can describe complex failure-repair state transition via ‘trigger link’ and three kinds of leaf nodes, as well as keep compact and easy-read struct like fault tree. So BDMP is adopted to analysis reliability of SGLCS. Graphical BDMP modeling environment KB3 and Monte Carlo simulator YAMS is used for BDMP modeling and quantitative analysis respectively, and unavailability of SGLCS is obtained. The contribution of three parts of SGLCS to the unavailability of the system is also evaluated, and it is found that the water supply flow control part contributes the most to the failure of SGLCS.

We aimed to evaluate the protective effects of acetyl-xylogalactan on the activity of RAW264.7 macrophages against heat stress. To this end, we assessed cell survival, phagocytic activity, in-tracellular Ca2+ level, mitochondria potential exchange, apoptotic assay findings, galactosidase activity and the RNA-seq by NGS and real-time polymerase chain reaction (PCR) expression. In our evaluation of macrophage morphology at 37°C and 41°C, the macrophages showed an oval shape at 41°C , unlike the spindle shape at 37°C. Therefore, 41°C was chosen as the heat stress condition. Subsequently, we designed an experiment to evaluate changes in the RAW264.7 macrophages after acetyl-xylogalactan treatment under heat stress. The survival of RAW264.7 macrophages treated with acetyl-xylogalactan was higher than that of controls that were not treated with acetyl-xylogalactan. Moreover, on the basis of the results of the annexin-V detection assay, the apoptotic activity of macrophages appeared to have reduced after treatment with ac-etyl-xylogalactan. Moreover, treatment with acetyl-xylogalactan resulted in a stronger recovery trend in the intracellular Ca2+ and mitochondrial membrane potential after heat stress. RNA sequencing and real-time polymerase chain reaction (PCR) illustrated that Sarcodia suieae acetyl-xylogalactan could upregulate the expression of the anti-apoptosis Cflar gene and down-regulate the expression of the apoptosis factors Ddit3, and Hyou1 to protect macrophages under heat stress.

Background: This retrospective study evaluate the survival effects of metronomic maintenance therapy with fluoropyrimidine in patients with stage III colorectal cancer (CRC) according to epidermal growth factor receptor (EGFR) expression. Methods: We enrolled 197 patients with stage III CRC who had undergone radical resection and FOLFOX regimen adjuvant chemotherapy. The clinicopathological features and effects of metronomic maintenance therapy on survival according to treatment group and EGFR expression were analyzed. By conducting an in vitro cell line study and in vivo study through knockdout of EGFR gene, we analyzed the capacities of cell proliferation and migration. Results: Postoperative relapse and mortality were significantly more common in the FOLFOX group. Metronomic maintenance therapy was a significantly independent predictive factor of postoperative relapse and mortality, as well as a prognostic factor of disease-free survival and overall survival. We also demonstrated that EGFR-knockout Caco2 cells are more sensitive to the inhibition effect of fluoropyrimidine than the control those. Conclusions: The present study suggested EGFR expression as the prognostic factor in patients with stage III CRC receiving metronomic maintenance therapy. By analyzing EGFR expression and treatment strategies, we can identify the potential candidates with optimal survival benefit from metronomic maintenance therapy in patients with stage III CRC.

Abstract. Graphene family (GF)-Calcium phosphate (CaP) composites, holds great potential as components of bone regeneration materials. GF nanomaterials can be modified physically as well as chemically, which are to be biomimetic, mechanically to be hard due to their capability to support exceptional mechanical, thermal and electronic properties. These biocompatible GF composites coated on the calcium phosphate can enhance and tolerate stem cell growth and differentiation, proliferation into various lineages or interact with bioorganisms. The development in CF-CaP materials and their physicochemical/biointeractions and strategies towards osteoblasts is a great concern to promote faster healing and reconstructions of large bone imperfections or defects. In this review, we explain the influence of the CF-CaP and summarize recent developments on designing CF-CaP architectures as multifunctional bone regeneration platforms. We have also explored the typical biological applications concerning these CF-CaP based bioactive nanocomposites. Furthermore, the future viewpoints and evolving challenges will also be emphasized. Due to the shortage of full-length reviews in this emerging research field, this review would be caught great attention and encourage various new chances across a wider range of disciplines.

Supramolecular solvent (SUPRAS) has received increasing interest as an innovative, efficient, and green solvent for the effective extraction and separation of bioactive compounds from natural resources. However, studies on the use of SUPRAS for the extraction of phenolic components from plants, which are highly valued in food products due to their excellent antioxidant capacity, are still lacking. The present study developed a green ultrasound-assisted and efficient SU-PRAS method to simultaneously determine three phenolic acids in Prunella vulgaris by high-performance liquid chromatography (HPLC) and the experimental parameters were optimized in detail. The efficiency and antioxidant properties of the phenolic compounds obtained by different extraction methods were also compared. Under the optimal conditions, the extraction efficiency of SUPRAS, prepared with octanoic acid reverse micelles dispersed in ethanol-water, was substantially higher than conventional organic reagents. Moreover, this SUPRAS method also showed more significant antioxidant capacities. The confocal laser scanning microscopy (CLSM) images presented the spherical droplet structure of SUPRAS (A well-defined circle), which coincided with the position of the fluorescence position of phenolic acids. The phenolic acids were encapsulated in the vesicles by the SUPRAS droplets, which indicated the efficient extraction capacities of SUPRAS for the target compounds. Finally, combined with the CLSM method, the mechanism of the proposed method was further clarified, and the superior extraction performance of SUPRAS was theoretically demonstrated through molecular dynamics simulations. In comparison with conventional methods, the higher extraction efficiency of SUPRAS can be illustrated by the larger solvent contact surface area, more types of hydrogen bonds between extractants and supramolecular solvents, and stronger and more stable interaction forces. The results of the theoretical studies are in rational agreement with the experimental outcome.

In order to understand the response mechanism between plant stress, physiological indicators and hyperspectral indices, pot experiments were conducted on Suaeda salsa seedlings collected from a coastal wetland area to reveal the effects of salt stress on the physiological indicators and reflectance spectra of Suaeda salsa at the canopy and leaf level. The Suaeda salsa seedlings were exposed to seven salt treatments of different concentrations (0 mmol/L (control), 50 mmol/L, 100 mmol/L, 200 mmol/L, 300 mmol/L, 400 mmol/L, and 600 mmol/L) in natural conditions. The physiological indicators of plant height, fresh weight, dry weight, leaf succulence, chlorophyll content, and carotenoid content were measured, in addition to the reflectance spectra of Suaeda salsa at both the canopy and leaf level. Firstly, the effects of salt stress on the physiological indicators and reflectance spectra were analyzed by the qualitative and quantitative methods. Then, physiological indicators sensitive to salt stress were further retrieved. Afterwards hyperspectral indices such as a/b and ((a-b)/(a+b) ) sensitive to salt stress were also extracted by one-way analysis of variance (ANOVA) and Student-Newman-Keuls (S-N-K) comparison test. Our results showed that plant height, root length, leaf succulence, biomass, Chl-a, and Chl-b were sensitive to salt stress, while carotenoids (Car) and relative water content on the root were not significantly affected by salt stress. At the salt concentration of 200 mmol/L, plant height, biomass, relative water content, leaf succulence peaked. With enhanced salt stress, physiological indicators decreased. The first-order derivative spectral reflectance has the highest correlation with salt stress, compared to the control. The spectral index most sensitive to the salt stress at the canopy level is (D₉₀₃−D₈₅₁)/(D₉₀₃+D₈₅₁), for which the multiple determination coefficient (r²) is 0.9216. While the most sensitive spectral index to the salt stress is (D₄₄₂−D₆₆₇)/(D₄₄₂+D₆₆₇) at the leaf level, for which the r² is −0.898. In summary, the results indicated that there exists the quantitative relationship between the physiological indicators and spectra reflectance under salt stress and hyperspectral plant indices can effectively estimate the degree of salt stress. The inconsistency between the diagnostic hyperspectral plant indices at the canopy and leaf levels may be caused by the observation conditions, canopy structure.

Lithium-sulfur (Li-S) battery has been regarded as an important candidate for the next-generation energy storage system due to its high theoretical capacity (1675 mAh g-1) and high energy density (2600 Wh kg-1). However, the shuttle effect of polysulfide seriously affects the cycling stability of the Li-S battery. Here, a novel Fe3C decorated folic acid-derived graphene-like N-doped carbon sheet (Fe3C@N-CS) was successfully prepared as the polysulfide catalyst to modify the separator of Li-S battery. The porous layered structures can successfully capture polysulfide as a physical barrier, and the encapsulated Fe3C catalyst can effectively trap and catalyze the conversion of polysulfide, thus accelerating the redox reaction kinetics. Together with the highly conductive networks, the cell with Fe3C@N-CS modified separator evinces superior cycling stability with 0.06% capacity decay per cycle at 1 C rate over 500 cycles and excellent specific capacity with an initial capacity of 1260 mAh g-1 at 0.2 C. Besides, at a high sulfur loading of 4.0 mg cm-2, the batteries also express superb cycle stability and rate performance.

The most recent National Research Council Nutrient Requirements for Sheep and Goats was published in 2007, one of the most consequential nutrient requirement recommendations for sheep and goats in the world. It is pertinent to continue the refinement and discussion of nutrient utilization and requirements for the purposes of enhancing the efficiency of production systems, maximizing resource economy, and minimizing the carbon footprint, among others. Progress has been made in the estimation of energy and protein requirements in sheep and goats, mainly utilizing empirical feeding experimentation, comparative slaughter technique and minimum endogenous loss method. In sheep, newer estimates of energy and protein requirements for maintenance and growth and partial efficiencies had been reported since 2007. There were suggestions that energy and protein requirements could have been affected by breed, wool growth, gender and size; with these reported values being similar or lower than the recommended values in international feeding systems such as NRC, ARC, INRA and AFRC. In goats, energy and protein requirements for growing goats were reported to be either higher or lower than the established recommendations, depending upon meat or dairy breeds. Effect of gender on energy requirement appeared to be related to the stage of growth or degree of maturity. Newer data also suggested that the guidelines of the major feeding systems for the entire growth phase may not be adequate for non-pregnant and non-lactating pubertal females. In multiparous pregnant goats, energy and protein requirements for maintenance did not appear to be affected by days of pregnancy, but efficiencies of metabolizable energy and metabolizable protein utilization for pregnancy were. There were suggestions that that metabolizable protein synthesis in the rumen can be predicted from energy intake using combined equations that encompass both sheep and goats, but more data on goats were called for to account for specific differences in nutrition. In addition to sulfur, there has been progress made on the estimation of maintenance and growth requirements of calcium, phosphorus, potassium and magnesium in goats, with suggestions on the consideration of gender and breed differences. Species, level of Intake, genotype, mature size, age, gender, body composition, use of tissue energy, activity, season, and acclimatization continue to be important considerations for the estimation of nutrient requirements in sheep and goats, with emerging factors such as climate change, heat stress, parasitism and secondary plant compounds. Model equations and partial efficiencies used by NRC to predict energy and protein requirements for maintenance, growth, lactation, and fiber have been highlighted and discussed for the purpose of a more focus discussion and refinement for the future. Potential and limitation of both traditional and emerging methodologies in determining the nutrient requirements in sheep and goats were discussed. To justify the research investment, emerging methodologies such as nutrigenomics will have to be linked more directly to the improvement of production efficiency via more precise prediction of nutrient requirement.

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.

Soarinho Alkaline Intrusion, southeastern Brazil, makes part of the Serra do Mar Igneous Province, and it is composed of alkali feldspar syenite, alkali feldspar trachyte, quartz syenite, and mon-zonite. Geochemical and geochronological analysis of the Soarinho were compared with data from its neighbors Rio Bonito and Tanguá. Zircon U-Pb Laser Ablation ages show that Soarinho is youngest than Rio Bonito and Tanguá. Ages obtained from the monzonite (60 ± 2 Ma), alkali feldspar syenite (58 ± 2 Ma), and quartz syenite (58 ± 2 Ma) are indistinguishable within error. Petrographic and geochemical data show a clear contrast among Soarinho, Rio Bonito, Tanguá, and Lu-Hf isotopic data for the three alkaline intrusions (all negative), point to some similarities in their sources. The data suggest an enriched mantle source for Soarinho; however, an older con-tinental crust contribution cannot be discarded.

Background: Pleurotus ostreutus is one of the world’s most commonly consumed mushrooms. Cultivation of mushrooms using wood resources usually results in environmental issues of deforestation. Juncao grass Pennisetum sp, Arundo Donax, and Methodology: Miscanthus are the culture mediums used in this research which offered a composting system most particularly for a simple formulation, cheap and feasible for small farms in cultivating oyster mushrooms. Results: The present study assessed the different junco grass as a substrate for growing Pleurotus ostreatus given the enzyme activities, growth, and yields. In addition, on the other hand, Lignin peroxidase (LiP) was the most active enzyme in each culture material among the other enzyme activities expressed differently between substrate and growing stages. Fruiting bodies harvested on giant grass,Arundo donax,and miscanthus,substrate weighed 159.2g/bag,132g/bag, and 65.1g/bag on average respectively. The biological efficiency of pleurotus cultivated in three different substrates was 75.2%, 63.4%, and 28.7%, respectively. Lignin peroxidase (LiP) was the most active enzyme followed by Laccase in each substrate. At the same time, other enzyme activities were differently expressed between substrate and different developmental stages. Nutrient analysis revealed significant variations, with differences in polysaccharides, proteins, and amino acids among substrates as well as the presence of heavy metals as arsenic, lead, mercury, and cadmium content in all samples was within safe limits. Conclusion: Findings from this study will serve as a solid foundation for future studies aimed at characterizing different substrate responses on enzyme activity. This research provides a sustainable footprint for subsequent research promoting eco-friendly mushroom production. The obtained results indicate that Arundo donax should be a good substrate in place of giant grass, using miscanthus is not productive based on the results obtained in this research the juncao grasses offer a sustainable approach that reduces reliance on wood-based substrates and enhances environmental sustainability.

This study analyses regional development in one of the poorest provinces in China, Guizhou Province, between 2000 and 2012 using a multiscale and multi-mechanism framework. In general, regional inequality has been declining since 2000. In addition, economic development in Guizhou Province presented spatial agglomeration and club convergence, which shows how the development pattern of one core area, two-wing areas and a contiguous area at the edge of the province have been developed between 2006 and 2012. Multilevel regression analysis revealed that industrialization and investment level were the primary driving forces of regional economic disparity in Guizhou Province. The influences of marketization and decentralization on regional economic disparity were relatively weak. Investment level reinforced regional economic disparity and the development of core-periphery structure in the province. However, investment level actually weakened the regional economic disparity in Guizhou Province when the variable of time was considered. In addition, both the topography and urban–rural differentiation were the two main reasons for forming a core-periphery structure in Guizhou Province.

This work is devoted to physical vapor deposition synthesis, and characterisation of bismuth and lutetium-substituted ferrite-garnet thin-film materials for magneto-optic (MO) applications. The properties of garnet thin films sputtered using a target of nominal composition type Bi_0.9Lu_1.85Y_0.25Fe_4.0Ga₁O₁₂ are studied. By measuring the optical transmission spectra at room temperature, the optical constants and the accurate film thicknesses can be evaluated using Swanepoel’s envelope method. The refractive index data are found to be matching very closely to these derived from Cauchy’s dispersion formula for the entire spectral range between 300-2500 nm. The optical absorption coefficient and the extinction coefficient data are studied for both the as-deposited and annealed garnet thin-film samples. A new approach is applied for accurately deriving the optical constants data simultaneously with the physical layer thickness, using a combination approach employing custom-built spectrum-fitting software in conjunction with Swanepoel’s envelope method. MO properties, such as specific Faraday rotation, MO figure of merit and MO swing factor are also investigated for several annealed garnet-phase films.

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

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.

In the recent decade, Building Information Modelling (BIM) has widely been adopted in the Architecture, Engineering and Construction (AEC) industry and completely upended the way we build. While BIM continues gain momentum in the industry, it has also attracted increasing attentions from researchers. However, most of the current study focuses on reviewing BIM for management, BIM for green building, BIM for infrastructure and BIM for Facilities Management (FM). There are few studies about Global BIM review and to discuss their complex inter-connections. In this study, we adopted a scientometric analysis method to review global BIM research from 2004-2019. A total of 1455 scholarly bibliographic records obtained from Web of Science Core Collection databased were established for the analysis. This study has identified the top productive and influential researchers, research institutes, regions/countries, subject categories and journals in the BIM field. In addition, 11 clusters of Global BIM research were also identified including construction project, green BIM, construction safety planning, automated IFC-based workflow and so on. Authors distinguished 11 clusters of global BIM research into 3 stages, namely formulating stage, accelerating stage and transforming stage. Furthermore, authors reviewed the BIM policy of Singapore and observed there is a co-production relationship between evolution of BIM policy and global BIM research. These findings provide valuable information for researchers, practitioners and policy makers by visualizing the current progress in the research field of BIM and highlighting future research needs.

Background: In recent years, computational aesthetics and neuroaesthetics have provided novel insights into understanding beauty. Building upon the findings of traditional aesthetics, this study aims to combine these two research methods to explore an interdisciplinary approach to studying aesthetics; Method: Abstract artworks were used as experimental materials. Based on traditional aesthetics and in combination, features of composition, tone, and texture were selected. Computational aesthetic methods were then employed to correspond these features to physical quantities: blank space, gray histogram, GLCM, LBP, and Gabor filters. An EEG experiment was carried out, in which participants conducted aesthetic evaluations of the experimental materials in different contexts (genuine, fake), and their EEG data was recorded to analyze the impact of various feature classes in the aesthetic evaluation process. Finally, a SVM was utilized to model the feature data, EEG data, context data, and subjective aesthetic evaluation data; Result: Behavioral data revealed that higher aesthetic ratings in the genuine context. EEG data indicated that genuine contexts elicited more negative deflections in the prefrontal lobes between 200-1000ms. Class II compositions demonstrated more positive deflections in the parietal lobes at 50-120ms, while Class I tones evoked more positive amplitudes in the occipital lobes at 200-300ms. Gabor features showed significant variations in the parieto-occipital area at an early stage. Class II LBP elicited a prefrontal negative wave with a larger amplitude. The results of the SVM models indicated that the model incorporating aesthetic subject and context data (ACC=0.76866) outperforms the model using only parameters of the aesthetic object (ACC=0.68657); Conclusion: A positive context tends to provide participants with a more positive aesthetic experience, but abstract artworks may not respond to this positivity. During aesthetic evaluation, the ERP data activated by different features show a trend from global to local. The SVM model based on multimodal data fusion effectively predicts aesthetics, further demonstrating the feasibility of the combined research approach of computational aesthetics and neuroaesthetics.

Background: Symmetry is a special kind of balance. This study aims to systematically explore and apply the role of balanced composition in aesthetic judgments by focusing on balanced composition features and employing research methods from computational aesthetics and Neuroaesthetics. Methods: First, experimental materials were classified by quantifying balanced composition using several indices, including symmetry, center of gravity, and negative space. An EEG experiment was conducted with 18 participants, who were asked to respond dichotomously to the same stimuli under different judgment tasks (balance and aesthetics), with both behavioral and EEG data being recorded and analyzed. Subsequently, participants' data were combined with balanced composition indices to construct and analyze various SVM classification models. Results: Participants largely used balanced composition as a criterion for aesthetic evaluation. ERP data indicated that from 300-500ms post-stimulus, brain activation was more significant in the aesthetic task, with unbeautiful and imbalanced stimuli eliciting larger frontal negative waves and occipital positive waves. From 600-1000ms, beautiful stimuli caused smaller negative waves in the PZ channel. The results of the SVM models indicated that the model incorporating aesthetic subject data (ACC=0.9989) outperforms the model using only balanced composition parameters of the aesthetic object (ACC=0.7074). Conclusions: Balanced composition is a crucial indicator in aesthetics, with similar early processing stages in both balance and aesthetic judgments. Multimodal data models validated the advantage of including human factors in aesthetic evaluation systems. This interdisciplinary approach not only enhances our understanding of the cognitive and emotional processes involved in aesthetic judgments but also enables the construction of more reasonable machine learning models to simulate and predict human aesthetic preferences.

This study proposed a spatially and temporally improving methodology adopting the Regional Frequency Analysis with L-moments approach to estimate rainfall quantiles from 22787 grids of radar rainfall in Taiwan for a 24-hour duration. Due to limited radar coverage in the eastern region, significant discordant grids were found in the coastal area of the eastern region. A K-means cluster analysis using scaled at-site characteristics was used to group the QPESUMS grids in Taiwan into 22 clusters/sub-regions based on their characteristics. Spatially, homogeneous subregions with QPESUMS data produce more detailed homogeneous subregions with clear and continuous boundaries, especially in the mountain range area where the number of rain stations is still very limited. According to the results of z-values and L-moment ratio diagrams, the Wakeby (WAK), Generalized Extreme Value (GEV), and Generalized Pareto (GPA) distributions of rainfall extremes fitted well for the majority of subregions. The Wakeby distribution was the dominant best-fitted distribution, especially in the central and eastern regions. The east of the northern part and southern part of Taiwan had the highest extreme rainfall for each return period. Both areas were frequently struck by typhoons. By using grid-based (at-site) as the basis for assessing regional frequency analysis, the results show that the regional approach in determining extreme rainfall is very suitable for large-scale applications and even better for smaller scales such as watershed areas. The spatial investigation was performed by establishing regions of interest in small subregions across the northern part. It showed that regionalization was correct and consistent.

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

Expansion tube is ideal energy absorber which dissipates kinetic energy through plastic deformation and friction. There is an urgent need to understand the influence of key parameter, e.g. semi angle, tube material, and friction coefficient, on the mechanical response and energy absorption characteristics of expansion tube. In the present work, the material properties of the tubes were tested under quasi-static loading condition, and the numerical simulations were carried out by using commercial software ABAQUS. Based on the validated finite element simulation, all the semi angle, tube material, and friction have significant effects on the energy absorption capacity of expansion tube. The expansion tube with high tensile stress of parent material have high energy absorption capacity, while the specific energy absorption is linear with the tensile stress/density of tube material. This work would give a guidance to the structural design and parent materials selection for expansion tubes.

Small peptides (SPs), ranging from 5 to 100 amino acids, play integral roles in plants due to their diverse functions. Despite their low abundance and small molecular weight, SPs intricately regulate critical aspects of plant life, including cell division, growth, differentiation, flowering, fruiting, maturation, and stress responses. As vital mediators of intercellular signaling, SPs have garnered significant attention in plant biology research. This comprehensive review delves into SPs' structure, classification, and identification, providing a detailed understanding of their significance. Additionally, we summarize recent findings on the biological functions and signaling pathways of prominent SPs that regulate plant growth and development. The review also offers a forward-looking perspective on future research directions in peptide signaling pathways.

Consumption of refined foods and beverages high in sugar make the teeth susceptible to the formation of biofilm, and lead to dental caries and diseases of the oral cavity such as periodontitis and periodontal disease. The aim of the present study was to determine the ability of selected probiotics to inhibit growth and biofilm formation by the cariogenic bacterium Streptococcus mutans in vitro. We screened strains of latic acid bacteria (LAB) (n=120) from the Bioresources Collection and Research Center (BCRC), saliva of healthy adults and infant stool. The antimicrobial activity of LAB in vitro was evaluated by agar spot culture and co-culture of the S. mutans strains. We determined the effect of heating and dilution factors (2- and 4-fold) on the antagonistic activity of LAB. Antagonistic substances in the spent culture suspensions (SCS) of LAB were precipitated by extraction with ammonium sulphate and chloroform to characterise the protein and lipophilic fractions. Results of co-culturing show that the SCS of the three LAB strains (Lactobacillus pentosus 13-1, 13-4 and Lactobacillus crispatus BCRC 14618) subjected to heat treatment showed significantly high antimicrobial activity. We found that substances produced by L. pentosus 13-4 which have the potential to exhibit antimicrobial properties might be lipophilic proteins. Additionally, we infer that the mechanism of reducing biofilm formation by Lactobacillus strains is associated with sucrose-dependent cell–cell adhesion and the gtfC level of glucosyltransferases (Gtfs) in the biofilm. Native LAB strains screened in our study may be used in chewing gums and other processed foods for preventing tooth decay.

The Pearl River Delta (PRD) has undergone complex geological development within a multi-island faulted basin, shaped by the interplay of regional tectonic movements, Quaternary sea-level fluctuations, and fluvial-marine interactions. Despite a great number of studies on the Holocene sedimentary sequences and spatial difference of lithofacies and environments, scant attention has been paid to the overarching human influence on deltaic evolution and coastline modifications since the Neolithic epoch. To further elucidate the spatial variation in Holocene sedimentation and its underlying basement topography shaped during the Last Glacial Maximum (LGM), we compiled a comprehensive dataset incorporating borehole data from over 2,800 cores within the PRD. Subsequently, high-resolution isobath maps of Quaternary deltaic deposits were generated, offering unprecedented insights into sediment distribution. This dataset facilitated a nuanced reconstruction of pre-Holocene topography, revealing a zone characterized by elongated, deep-incised valleys governed by NW-SE fault orientations. Further, we delineated coastline shifts since the period of maximum marine transgression (~7000 years BP), contributing to an enhanced understanding of the formation and evolutionary patterns of the delta and the river network oscillations. Our findings illuminate increasing anthropogenic impact on the rate of fluvial sedimentation and land growth, particularly accentuated over the last two millennia, favoring deltaic accretion. The current study has considerable implications for understanding the dynamic interplay between land-sea interactions and anthropogenic activities in shaping the delta, and stands to significantly inform land and resource management strategies, as well as future urban planning within the delta's bay areas.

While considering the sensitivity over the parameter optimization, it is essential to determine which parameters have the most significant implications on model performance. This study focuses on the baseflow recession constant as one of the independent basin parameters to forecast low flows, perform hydrograph analysis, and calibrate rainfall-runoff models for significant improvement. Prior studies examined that the optimization of data adjustment parameters can improve the hydrological model performance and determine the minimum acceptable data length for data scarce regions using the Xinanjaing model. However, it is essential to pay special attention to the sensitivity of the recession constant, which can also impact the model performance during the data scarcity. Therefore, this study extends the research to comprehend the recession constant sensitivity over data adjustment parameters in the shorter datasets leading to more reliable parameter estimation. In terms of that, this study explores how recession constant affects hydrological parameter estimation on annual scale while keeping data adjustment parameters constant in continuous hydrological modeling, employing the Xinanjiang (XAJ) model as a case study. This study considered two approaches of recession constant (cg); (i) assessing the relationship between cg and the data adjustment parameter (Cep), for the 28-year datasets, (ii) investigating the significant impacts of the sensitivity of cg over Cep in shorter datasets which can affect the estimation of the acceptable minimum data length in the data scarce basins. The study underscores the importance of the recession constant sensitivity for reliable continuous hydrological model predictions, especially in data-scared areas. The study’s outcomes enhance the understanding of the importance of parameter sensitivity and its relationship in conceptual hydrological modeling during the data limitations.

Background: Previous in vitro and in vivo studies have demonstrated that storage of cooked rice at 4 °C for 24 h and reheating to 65 °C significantly reduced starch digestibility and postprandial glycaemic responses. Moreover, the effect was greater for parboiled rice compared to other rice varieties commonly consumed in New Zealand. This study aimed to evaluate consumer preferences of related sensory attributes and consumer acceptability of several rice varieties freshly cooked or reheated. Method: Sixty-four consumers volunteered and recorded on Visual Analoge Scales their preference and acceptability of freshly prepared or cold-stored and reheated medium grain white, medium grain brown and parboiled rice. Results: All six rice samples were accepted by participants (average 54%). Reheated parboiled rice and reheated medium grain brown rice were both accepted by participants as a preferred staple meal compared to other rice samples. Among all rice samples, the sweetness and the flavour of freshly cooked warm medium-grain white rice were less preferred (scored 42.1% and 45.0% respectively) compared with other samples (P = 0.05). Participants who prepared and consumed brown rice at home regularly (more than 10 times per month), preferred the reheated brown rice (73.8% (67.4, 80.2)) and reheated parboiled rice (74.3% (67.9, 80.7)) (P < 0.001). Conclusions: It is suggested that reheated parboiled rice, with the lowest starch digestibility and glycaemic impact (both in vitro glucose release and in vivo glucose response) could be accepted as a healthier alternative for the daily staple meal.

Liquid-liquid phase separation (LLPS) of proteins has been found ubiquitously in eukaryotic cells, critical in the controlling of many biological processes through forming a temporary condensed phase with different bimolecular components. TDP-43 is recruited to stress granules in cells and is the main component of TDP-43 granules and proteinaceous amyloid inclusions in patients with amyotrophic lateral sclerosis (ALS). TDP-43 low complexity domain (LCD) is able to demix in solution forming the protein condensed droplets. The molecular interactions regulating its LLPS were investigated at the protein fusion equilibrium stage, where the droplets stopped growing. We found the molecules in the droplet were still liquid-like but with enhanced intermolecular helix-helix interaction in the LCD. The protein would start to aggregate after about 200 minutes of lag time and aggregate slower than at the condition when the protein does not phase separate or the molecules have a reduced intermolecular helical interaction. A structural transition intermediate towards protein aggregation was also discovered involving a decrease of the intermolecular helix-helix interaction and a reduction in the helicity. Therefore, LLPS and the intermolecular helical interaction could help maintain the stability of TDP-43 LCD.

Agricultural activities are the second largest source of greenhouse gas emissions, and carbon emissions from agricultural land use (CEALU) have become a hot issue across the world. However, few scholars explored the impact of agricultural land policies on carbon emissions, such as the High-standard farmland construction(HSFC) in China.Thus，by relying on provincial panel data for China for the period 2005-2017, the effect of the high-standard basic farmland construction policy on carbon emissions from agricultural land use per unit area and its regional differences were quantitatively analyzed using the difference-in-difference (DID) model. The results showed that: 1) China's CEALU per unit area presented a fluctuating upward trend during the period 2005-2017, from 392.58 kg/ha to 457.72 kg/ha, with an average annual growth rate of 1.31%. 2) The high-standard farmland construction(HSFC) policy produced a significant carbon emission reduction effect in agricultural land use, and reduced the CEALU per unit area by 10.80% on average. With the promotion of this policy, its carbon emission reduction effect in agricultural land use presented an overall increasing trend. 3) The carbon emission reduction effect of the high-standard farmland construction policy in agricultural land use was significant in central China, but non-significant in eastern China and western China.

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.

The accompanying mechanical behavior during the flow of ore-rock dispersion is an important factor leading to the instability and failure of the orepass in the ore storage section. It is of great significance to accurately understand the instability characteristics of the well wall in the ore section, during the ore drawing process by understanding the flow characteristics and internal mechanical transfer mechanism of ore-rock dispersion. Using the discrete element method to analyze the flow characteristics, contact compactness, stress distribution characteristics and contact force probability distribution of the ore-rock dispersion, it realizes the quantitative characterization of the damage degree of ore-rock flow, and reveals the damage mechanism of mine storage wall. The results show that: (1) The friction between ore-rock particles, between ore-rock and well wall is an important reason for the change of the macroscopic flow form of ore-rock from “one” to “V” type. (2) The compactness and stress concentration of ores are increasing with the increase of storage depth, which is shown that with the increase of storage depth, the greater the probability of well wall instability. (3) The probability distribution of contact force strength between particles decreases exponentially in the whole process of ore drawing, in which the strong chain plays a major role in the stability of the dispersion system. (4) The number of overpressure and the overpressure coefficient can be used to quantitatively characterize the wall damage degree under the action of ore-rock flow. The dynamic side pressure decreases periodically in the form of exponential fluctuations, and the dynamic load formed by the ore-rock flow mainly played a role in the lower area of the ore storage section.

On the basis of the force and safety factor analysis of traditional retaining wall, a new analytical method of force and displacement of slope is suggested, the numerical theoretical solution of the stress distribution of the sliding body can be obtained under the conditions, which the stresses distribution are satisfied with the differential equilibrium equations, the boundary conditions, the compatibility equation and the macroscopic equilibrium equations. The interface stresses between the sliding body and the retaining wall are continuous, the theoretical solution of retaining wall stress distributions can be gotten, while the stress differential equilibrium equation, the compatibility equation, macroscopic force and moment balance equations are satisfied. The strain and displacement solutions can be obtained by using Duncan Chang and Hooke constitutive equations for the slope and the retaining wall respectively. The transfer station of landfill in the Guandukou Town of Badong County is taken as an example, the results of the sliding body and retaining wall analysis show: The stress and strain solutions of a slope and a retaining wall can be obtained by the proposed method, the forces between the retaining wall and the sliding body include shear stress and normal stress, and the stress distributions change with the deformation of the sliding body, the shape and material of retaining wall can be optimized according to the calculation results，it is feasible for the proposed analysis method of slope with retaining wall design to be run many years.

The broad emission bump in the electromagnetic spectra observed following the detection of gravitational waves created during the kilonova event of merger of two neutron stars in August 2017, GW170817, has been linked to the heavy elements of lanthanides (Z=57-71), and a new understanding of creation of heavy elements in the r-process. The initial spectral emission bump has a wavelength range of 3000 - 7000 \AA, thus covering the region of ultraviolet (UV) to optical (O) wavelengths, and is similar to those seen for lanthanides. Most lanthanides have large number of closely lying energy levels which introduce extensive sets of radiative transitions which often form broad region of lines of significant strength. The current study explores these broad features through photoabsorption spectroscopy of 25 lanthanides ions, Ho I-III, Er I-IV, Tm I-V, Yb I-VI and Lu I-VII. With excitations only to a few orbitals up beyond the ground configurations, we find most of these ions cover large number of bound levels with open $4f$ orbital and produce tens to about hundred thousands lines that may form one or multiple broad features in X-ray to UV, O, and infrared (IR) regions. Spectrum of each of 25 ions is presented indicating presence, shape and wavelength region of the features. Accuracy of atomic data to interpret the merger spectra has been a outstanding problem. The present study aims at providing improved atomic data for energies and transition parameters obtained using relativistic Breit-Pauli approximation implemented in the atomic structure code SUPERSTRUCTURE. The present data have been benchmarked with available experimental data for energies and transition parameters. The study finds that number of ions under the present study are possible contributors of the emission bump of GW170817. All atomic data will be made available online at NORAD-Atomic-Data database.

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.

We study the Gaudin models with gl(1|1) symmetry that are twisted by a diagonal matrix and defined on tensor products of polynomial evaluation gl(1|1)[t]-modules, extending all the results of to the twisted case. Namely, we give an explicit description of the algebra of Hamiltonians (Gaudin Hamiltonians) acting on tensor products of polynomial evaluation gl(1|1)[t]-modules and show that there exists a bijection between common eigenvectors (up to proportionality) of the algebra of Hamiltonians and monic divisors of an explicit polynomial written in terms of the highest weights and evaluation parameters. In particular, our result implies that each common eigenspace of the algebra of Hamiltonians has dimension one. We also give dimensions of the generalized eigenspaces.

Background: Globally, hot cooked refined rice is consumed in large quantities and is a major contributor to dietary glycaemic load. This study aimed to compare the glycaemic potency of hot and cold stored parboiled rice to widely available medium grain white rice. Method: Twenty-eight healthy volunteers participated in a three treatment experiment where postprandial blood glucose was measured over 120 minutes after consumption of 140g of rice. Three rice samples were freshly cooked medium-grain white rice, freshly cooked parboiled rice, and parboiled rice stored overnight at 4 ºC. All rice was served warm at 65 ºC. Chewing time was recorded. Results: The 24-hours cold-stored and reheated parboiled rice resulted in a 42% and 12% lower blood glucose concentration trajectory than freshly cooked medium-grain white rice and freshly cooked parboiled rice. Chewing time for 10g cold stored parboiled rice was 6 seconds (25%) longer and was considered more palatable, visually appealing and better tasting than freshly cooked medium grain (all P<0.05). Conclusions:. For regular consumers of rice reheating cooked rice after cold storage would lower the dietary glycaemic load and long term may reduce risk for type 2 and gestational diabetes. More trials are needed to identify the significance.

Silicon carbide single crystal (SiC) has been widely used in the field of power devices, while it is difficult to fabricate ultra-flat surface by traditional manufacturing technologies due to its difficult-to-machine property. This paper investigates the interaction process during femtosecond laser ablation of crystalline silicon carbide based on the two-temperature model simulation and experimental study. The findings reveal that parameters such as laser pulse energy, scanning interval, and defocus amount exert significant influence on ablation depth, roughness, and surface morphology. The femtosecond laser proves effective in removing surface defects from cut SiC substrates, albeit resulting in increased surface roughness. However, subsequent polishing treatment of the laser-ablated silicon carbide surface can mitigate this roughness, underscoring the feasibility of laser surface ablation for silicon carbide single crystals.

As a vital component of the terrestrial ecosystem, grassland accounts for one-third of the global vegetation system. Grassland degradation has been exacerbated due to extreme overgrazing in China's Inner Mongolia Autonomous Region (IMAR). While conservation was carried out as the Ecological Subsidy and Award Program (ESAP) to mitigate grassland degradation, little is known about its effectiveness in improving the biophysical conditions of grassland. This paper integrates the conceptual frameworks of total socio-environmental systems to assess how ecological systems respond to ESAP, investigate spatial heterogeneity of ESAP, and explore the meddling effects of socio-environmental interactions on ESAP. We integrate ecological, climate, and socioeconomic data and developed several hierarchical linear mixed models (HLMM) to investigate how these factors interact with ESAP in IMAR. Our findings prove that the above-ground biomass between 2011 and 2015 responds significantly to variations in socioeconomic conditions and ecological communities. Available land resources, hospital and medical facilities, and net farmer and herdsman income are the most critical factors contributing to grassland productivity. Primary industries like mining, total consumer retail value, farming, forestry, animal husbandry, fishery productions, and GDP are the most damaging factors affecting biomass. Our study recommends a regionally or locally tailored ecological recovery policy, instead of a generalized one, in the future effort to conserve grassland.

People have always hoped to be able to fill an entire plane with ``single unit cells'' without periodicity. This wish was realized after the mathematician discovered a 13-sided ``single unit cell'' named `einstein'. These non-periodic tessellations generally exhibit anisotropic properties, making them superior in terms of mechanical performance compared to periodic structures. From the perspective of information entropy, the reason behind the improved mechanical properties of these structures is the higher entropy associated with non-periodic configurations. To quantify the disorder of non-periodic structures, we propose an entropy expression for the `einstein' metamaterial. To demonstrate the mechanical properties of these high-entropy structures, we fabricate specimens using 3D printing and conducte mechanical experiments. For comparative analysis, we also use ABAQUS to perform finite element analysis of the problem. The research results reveal that the mechanical properties of high-entropy structures created by the non-periodic stacking of cells are significantly improved compared to those of low-entropy structures created by periodic stacking. The conclusions drawn from the study of individual issues are generalizable and may be of assistance in future material and structural design.

With increasing research focus on industrial anomaly detection, numerous methods have emerged in this domain. Notably, memory bank-based approaches, coupled with kNN distance metrics, have demonstrated remarkable performance in anomaly detection (AD) and anomaly segmentation (AS). However, upon examination of the Back to the Feature (BTF) method applied to the Mvtec-3D AD dataset, it was observed that while it exhibited exceptional segmentation performance, its detection performance was lacking. To address this discrepancy, this study base improves the implementation of BTF, especially the improvement of the anomaly score metric. It posits that different "clusters" necessitate distinct k values in kNN distance metrics. For simplify, this assumption is distilled into the proposition that AD and AS tasks impose differing requirements on the k value in kNN distance metrics. Consequently, the paper introduces the BTM method, which utilizes distinct distance metrics for AD and AS tasks. This innovative approach yields superior AD and AS performance (I-AUROC 93.0%, AURPO 96.9%, P-AUROC 99.5%), representing a substantial enhancement over the BTF method (I-AUROC 5.7% ↑, AURPO 0.5% ↑, P-AUROC 0.2% ↑).

Abstract: Bacillus subtilis fmb60, which has broad-spectrum antimicrobial activities was isolated from plant straw compost. A hybrid NRPS/PKS cluster was screened from the genome. Sixteen secondary metabolites produced by the gene cluster were isolated and identified using LC-HRMS and NMR. Three lipoamides D–F (1-3) and two amicoumacin derivatives, amicoumacins D, E (4, 5), were identified, and are reported here for the first time. Lipoamides D–F exhibited strong antibacterial activities against harmful foodborne bacteria, with the MIC ranging from 6.25 to 25 µg/mL. Amicoumacin E scavenged 38.8% of ABTS+ radicals at 1 mg/mL. Direct cloning and heterologous expression of the NRPS/PKS and ace gene cluster identified its importance for the biosynthesis of amicoumacins. This study demonstrated that there is a high potential for biocontrol utilization of B. subtilis fmb60, and genome mining for clusters of secondary metabolites of B. subtilis fmb60 has revealed a greater biosynthetic potential for the production of novel natural products than previously anticipated.

This paper proposes an approach for image data extraction and driving behavior analysis using geographic information and driving data. Information derived from geographic and global positioning systems was used for image data extraction. In addition, we used an onboard diagnostic II and a controller area network bus logger to record driving data for driving behavior analysis. Driving behavior was analyzed using sparse automatic encoders and data exploration to detect abnormal and aggressive behavior. A regression analysis was used to derive the relationship between aggressive driving behavior and road facilities. Several traffic improvements were proposed for specific intersections and roads. The results indicate that lane ratios without lane markings and with straight lane markings are important features that affect aggressive driving behaviors.

Imitation learning, also known as programming by demonstration, has been shown to be a promising paradigm for intuitive robot programming by non-expert users. However, the classical kinesthetic approach with physical hand guidance suffers from generalizability across different robot types and is impractical for demonstrating tasks with long horizons. Visual imitation learning enables the recording of multi-step tasks as a single continuous video, allowing non-experts to demonstrate tasks naturally. Existing approaches typically require a large amount of data to develop end-to-end deep learning models that map raw pixels to robot actions. This paper explores the application of visual imitation learning from one-shot demonstration, significantly reducing the data requirements and simplifying the programming process. To achieve this target, a framework is proposed to map hand trajectories to the robot end-effector, consisting of four essential components: hand detection; object detection; segmentation of the trajectories into elemental skills; and learning the skills. Methods are developed for each component and evaluated on recorded videos to demonstrate the effectiveness of the proposed framework.

This research focuses on the Hopf bifurcation occurring at a singular point with high-order degeneracy in a class of three-dimensional systems. Based on center manifold theorem, by expanding the technique for determining singular point values of degenerate singularities in two-dimensional systems, the formal series method to determine the singular point values at the high-order degenerate critical point is discussed. Furthermore, a class of specific three-dimensional differential systems with high-order degenerate singularities is explored. By computing the singular point values and determining center conditions, we proved that a minimum of 5 small-amplitude limit cycles in the vicinity of the origin. This research provides new perspectives on the center problem and limit cycle bifurcation in high-dimensional systems with high-order degenerate singular points.

According to many research groups, high glucose induces over production of superoxide anions, and reactive oxygen species (ROS) in general is the link between high glucose levels and the toxicities seen at cellular levels. Respiratory complex anomalies could lead to the production of ROS. Calcium [Ca2+], at physiological levels serves as a second messenger in many physiological functions. Accordingly, mitochondrial calcium [Ca2+]m overload leads to ROS production which could be lethal to the mitochondria through various mechanisms. The F1F0-ATPase (ATP syn-thase or complex V) is the enzyme that is responsible for catalyzing the final step of oxidative phosphorylation. It does so by coupling the translocation of protons in the mitochondrial in-termembrane space and shuttling them to the mitochondrial matrix for ATP synthesis to take place. Mitochondrial complex V T8993G mutation specifically blocks the translocation of protons across the intermembrane space thereby blocking ATP synthesis leading to Neuropathy, Ataxia and Retinitis Pigmentosa Syndromes (NARP). This study seeks to explore the possibility of [Ca2+]m overload mediating the pathological roles of high glucose in defective respiratory chain mediated mitochondrial stress. The NARP cybrids are the in vitro experimental models for the cells with F1FO-ATPase defects, these cells harbor 98% of mtDNA T8993G mutation. Their coun-terparts 143B osteosarcoma cell lines are the parental cell lines used for comparisons. We uncov-ered that, NARP cells mediated and enhanced the death of the cells (apoptosis) when incubated with hydrogen peroxide (H2O2) and high glucose respectively as depicted by the MTT assay of cell viability. Furthermore, using the fluorescence probe-coupled laser scanning confocal imag-ing microscopy, NARP cells significantly enabled mitochondrial reactive oxygen species (mROS) formation and enhanced the depolarization of the mitochondrial membrane potential (ΔΨm). Elucidating the mechanisms of sugar enhanced toxicity on mitochondria would help in the fu-ture to alleviate the symptoms of patients associated with (NARP) syndromes.

Interpore hydrates are the main occurrence forms of marine gas hydrates. Pore characteristics are a vital factor affecting the thermodynamic properties of hydrates and their distribution in sediments. Currently, the characterization of the pore system for hydrate-bearing reservoirs are little reported. Therefore this paper focus on the Krishna-Godavari Basin, via varies methods to characterize the hydrate-bearing sediments in the region. The results showed that X-ray Diffraction(XRD) combined with Scanning Electron Microscope (SEM)and Cast Thin Section (CTS) can better characterize the mineral composition in the reservoir, High Pressure Mercury Injection (HPMI) focused on the contribution of pore size to permeability, Constant Rate Mercury Injection(CRMI) had the advantage of distinguishing between pore space and pore throat, and Nuclear Magnetic Resonance Cryoporometry (NMRC) technique can not only obtain the pore size distribution of nanopores with a characterization range greater than Nitrogen Gas Adsorption (N2GA), but also quantitatively describe the trend of fluids in the pore system with temperature. As for pore system, Samples 58 and 68 all developed nanopores, the mineral distribution was relatively scattered, and they were rich in paleontological shells such as foraminifera, among which Sample 68 had more pyrite content, and abundant pyrite framboid was observed, which made the intergranular pore develop and provide more nanopores. Sample 58 has a high concentration of pore and throat, high pore connectivity, low pore curvature, and pores with a diameter of 10μm contributing to the main permeability, with an average pore radius of 2.495μm, whereas Sample 68 has poor pore connectivity, high curvature, and pores with a diameter of 1μm contributing to the main permeability, with an average pore diameter of 60 nm, which explains the obvious difference in permeability between the two samples.

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