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

Thalassemia is a heterogeneous congenital hemoglobinopathy common in the Mediterranean region, Middle East, Indian subcontinent, and Southeast Asia with increasing incidence in Northern Europe and North America due to immigration. Iron overloading is one of the major long-term complications in patients with thalassemia and can lead to organ damage and carcin-ogenesis. Hepatocellular carcinoma (HCC) is one of the most common malignancies in both transfusion-dependent thalassemia (TDT) and non-transfusion-dependent thalassemia (NTDT). The incidence of HCC in patients with thalassemia has increased over time, as better chelation therapy confers a sufficiently long lifespan for the development of HCC. The mechanisms of iron overloading-associated HCC development include the increased　reactive oxygen species (ROS), inflammation cytokines, dysregulated hepcidin, and ferroportin metabolism. The treat-ment of HCC in patients with thalassemia was basically similar to those in general population. However, due to the younger age of HCC onset in thalassemia, regular surveillance for HCC development is mandatory in TDT and NTDT. Other supplemental therapy and experience of novel treatment for HCC in thalassemia population were also reviewed in this article.

The objective of this study is to investigate the use of excavation behavior prediction and analysis software in the field of civil en-gineering. PLAXIS and SoilWorks, widely used in the engineering and academic communities, were employed as research tools for analyzing gravel layers and deriving appropriate ranges of soil elastic modulus for different software programs. By collecting excavation cases in the Xindian area of New Taipei City, Taiwan, and conducting deep excavation analysis using the displacement of retaining walls, this study provides recommended ranges for localized selection of soil elastic modulus. The suggested range for PLAXIS is 7,840 N/m² to 9,800 N/m², while Soil-Works suggests a range of 2,450 N/m² to 3,430 N/m². These ranges allow for reasonable estimation of maximum deformations during the final excavation stage. Based on the research findings, it is recommended that engineers refer to the provided ranges when selecting soil elastic modulus for excavation analysis in gravel layers using different soft-ware programs in the Xindian area of Taiwan to improve the accuracy of deformation predictions during the final excavation stage. These results serve as important references for engineers and contribute to the effective prediction and management of excavation behavior in civil engineering projects.

This paper proposes a single-stage asymmetrical half-bridge fly-back (AHBF) converter with resonant mode using dual-mode control. The presented converter has an integrated boost converter and asymmetrical half-bridge fly-back converter and operates in resonant mode. The boost-cell always operates in discontinuous conduction mode (DCM) to achieve high power factor. The presented converter operates simultaneously using a variable-frequency-controller (VFC) and pulse-width-modulation (PWM) controller. Unlike the conventional single-stage design, the intermediate bus voltage of this controller can be regulated depending on the main power switch duty ratio. The asymmetrical half-bridge fly-back converter utilizes a variable switching frequency controller to achieve the output voltage regulation. The asymmetrical half-bridge fly-back converter can achieve zero-voltage-switching (ZVS) operation and significantly reduce the switching losses. Detailed analysis and design of this single-stage asymmetrical half-bridge fly-back converter with resonant mode is described. A wide AC input voltage ranging from 90 to 264 Vrms and output 19 V/ 120 W prototype converter was built to verify the theoretical analysis and performance of the presented converter.

Dry eye syndrome (DES) has become increasingly prevalent due to the prolonged use of digital devices in modern society. Individual supplementation with lutein or docosahexaenoic acid (DHA) demonstrated potential benefits for eye health. This study aimed to investigate the effects of lutein plus DHA complex supplementation on DES, visual function, and memory in healthy individuals. Thirty-four participants, aged 40~60 years, received lutein/DHA complex supplements (containing 10 mg free-form lutein, 200 mg DHA, 30 mg red algae extract (astaxanthin), phosphatidylserine, and vitamin A) for 12 weeks. Ophthalmological examinations and memory tests were carried out, and a questionnaire was administered at weeks 0, 6, and 12 of the study. After 12 weeks of the intervention, the tear break-up time had significantly increased, and intraocular pressure (IOP) had significantly decreased. This suggests that lutein/DHA complex supplementation may reduce the IOP and offer potential benefits for DES, as indicated by improved tear stability.

Recently, generative adversarial networks (GANs) can be used to generate the photo-realistic image from a low-dimension random noise. It is very dangerous that the synthesized or generated image is used on inappropriate contents in social media network. In order to successfully detect such fake image, an effective and efficient image forgery detector is desired. However, conventional image forgery detectors are failed to recognize the synthesized or generated images by using GAN-based generator since they are all generated but manipulation from the source. Therefore, we propose a deep learning-based approach to detect the fake image by combining the contrastive loss. First, several state-of-the-art GANs will be collected to generate the fake-real image pairs. Then, the contrastive will be used on the proposed common fake feature network (CFFN)to learn the discriminative feature between the fake image and real image (i.e., paired information). Finally, a smaller network will be concatenated to the CFFN to determine whether the feature of the input image is fake or real. Experimental results demonstrated that the proposed method significantly outperforms other state-of-the-art fake image detectors.

Aging and obesity make humans more prone to cardiovascular and metabolic syndrome diseases, leading to several serious health conditions, including dyslipidemia, high blood pressure, and sleep disturbance. Hyperlipidemia means elevated blood lipid levels, including cholesterol and triglycerides. This study aimed to explore the hypolipidemic effect of fermented citrus lemon juice using a hyperlipidemic hamster model. Sugar-free lemon juice’s fermentation was optimized, and the characteristics of fresh and fermented lemon juice (FLJ) were evaluated and compared. In addition, tests were conducted to determine the appropriate hamster feed for the functional animal tests. Then, experiments were conducted to evaluate the hypolipidemic effect of the FLJ, which contained polyphenols and superoxide dismutase-like activity, on a hyperlipidemic hamster model. This study’s pre-fermentation efficiency evaluation found that 21–30 days of bacterial DMS32004 and DMS32005 fermentation of fresh lemon juice provided the best fermentation benefits. In addition, the fermentation evaluation showed that a sugar-free fermentation method provided FLJ with the best benefits. Results showed that the absorption and utilization efficiency of FLJ was higher compared with the unfermented lemon juice. After six weeks of feeding, the total cholesterol and triglyceride values in the blood and liver of the FLJ treatment groups were de-creased compared with the high-fat diet (HFD) group. In addition, the blood low-density lipoprotein cholesterol levels were significantly reduced in the FLJ treatment groups compared with the HFD group. In contrast, the blood high-density lipoprotein to low-density lipoprotein cholesterol ratio increased considerably in the FLJ treatment groups, and the total to high-density lipoprotein ratio was significantly lower than in the HFD group. Compared with the HFD group, the total cholesterol content in the FLJ treatment groups’ feces increased significantly. This study demonstrated that the sugar-free fermentation method and fermentation cycle management provided FLJ with the potential to regulate blood lipids. Further research and verification will be carried out to isolate specific substances from the FLJ and identify their mechanisms of action.

Excessive body fat is a major contributor to obesity, which is related to high blood, total cholesterol and triglycerides. Lemons (Citrus limon) are renowned for their antioxidant and lipid-lowering properties. First, Sugar-free fermentation demonstrated better results lower sugar content and was identified as the preferred fermentation method. Next, the effect of two doses of sugar-free fermented lemon peel juice (SF-FLPJ) on obesity was investigated. Sprague Dawley (male rats) were randomly divided into 4 groups and fed a standard feed or high-fat diet (HFD) to induce fatness for eight weeks. The two groups of rats fed an HFD were administered SF-FLPJ at 0.45 or 0.9 g/kg body weight daily for eight weeks. The obese rats administered 0.9 g/kg (body weight/day) of SF-FLPJ exhibited significant reductions in body fat mass and percentage; they also had lower blood cholesterol and triglyceride levels than the other groups. Additionally, the rats displayed diminished liver fat accumulation. The results suggest that SF-FLPJ can be a supplement in managing body fat, contributing positively to addressing obesity within the context of health management, and reduce obesity-associated issues.

Vascular calcification (VC) is associated with increased cardiovascular risks in patients with chronic kidney disease (CKD). Sodium-glucose cotransporter 2 inhibitors, like empagliflozin, can improve cardiovascular and renal outcomes. We assessed the expression of Runt-related transcription factor 2 (Runx2), interleukin (IL)-1β, IL-6, AMP-activated protein kinase (AMPK), nuclear factor erythroid-2-related factor (Nrf2), and heme oxygenase 1 (HO-1) in inorganic phosphate–induced VC in mouse VSMCs to investigate the mechanisms underlying empagliflozin’s therapeutic effects. We evaluated biochemical parameters, mean artery pressure (MAP), pulse wave velocity (PWV), transcutaneous glomerular filtration rate (GFR), and histology in an in vivo mouse model with VC induced by an oral high-phosphorus diet following a 5/6 nephrectomy in ApoE−/− mice. Compared to the control group, empagliflozin-treated mice showed significant reductions in blood glucose, MAP, PWV, and calcification, as well as increased calcium and GFR levels. Empagliflozin inhibited osteogenic trans-differentiation by decreasing inflammatory cytokine expression and increasing AMPK, Nrf2, and HO-1 levels. Empagliflozin mitigates high phosphate–induced calcification in mouse VSMCs through the Nrf2/HO-1 anti-inflammatory pathway by activating AMPK. Animal experiments suggested that empagliflozin reduces VC in CKD ApoE−/− mice on a high-phosphate diet.

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.

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

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

Pain is unpleasant sensory and emotional experience accompanied by tissue injury. Often an indi-vidual experience, it can be influenced by different physiological, psychological, and social factors. Fibromyalgia, one of the most difficult-to-treat types of pain, is characterized by general muscle pain accompanied by obesity, fatigue, sleep, and memory and psychological concerns. Fibromyal-gia has increased nociceptive sensations via central sensitization in the brain and spinal cord level. We used intermittent cold stress to create a mouse fibromyalgia pain model (Day 0: 3.69  0.14 g; Day 5: 2.13  0.12 g). Mechanical pain could be reversed by eicosapentaenoic acid (EPA) admin-istration (Day 0: 3.72  0.14 g; Day 5: 3.69  0.13 g). A similar trend could be also observed for thermal hyperalgesia. The levels of elements in the transient receptor potential V1 (TRPV1) sig-naling pathway were increased in the ascending pain pathway, including the thalamus, medial prefrontal cortex, somatosensory cortex, anterior cingulate cortex, and cerebellum. EPA intake significantly attenuated this overexpression. Novel chemogenetics method was used to indeed in-hibit SSC to ACC activity presented an analgesic effect through TRPV1 downstream pathway. The present results provide insights as to the role of TRPV1 signaling pathway as in fibromyalgia and its potential as a clinical target.

Neuropathic pain is initiated by a malfunction of the somatosensory cortex system. Acupuncture had been shown to have therapeutic effects for neuropathic pain, although with uncertain mechanisms. We used electroacupuncture (EA) to treat mice spared nerve injury (SNI) model and explore the underlying molecular mechanisms through novel chemogenetic techniques. Both me-chanical and thermal pain were found in SNI mice till four weeks (mechanical: 3.23 ± 0.29 g; thermal: 4.9 ± 0.14 s). Hyperalgesia was attenuated by 2 Hz EA (mechanical: 4.05 ± 0.19 g; ther-mal: 6.22 ± 0.26 s) but not with sham EA (mechanical: 3.13 ± 0.23 g; thermal: 4.58 ± 0.37 s), sug-gesting EA’s specificity. In addition, animals with transient receptor potential V1 (Trpv1) deletion showed no significant induction of neuropathic pain (mechanical: 4.43 ± 0.26 g; thermal: 6.24 ± 0.09 s). Moreover, we found increased levels of inflammatory factors such as interleukin-1 beta (IL1-β), IL-3, IL-6, IL-12, IL-17, tumor necrosis factor alpha, and interferon gamma after SNI modeling, which decreased in EA and Trpv1-/- group rather than sham group. Western blot and immunofluorescence analysis showed similar tendency in the dorsal root ganglion, spinal cord dorsal horn, somatosensory cortex (SSC), and anterior cingulate cortex (ACC). In addition, a novel chemogenetics method was used to precisely inhibit SSC to ACC activity showed an analgesic effect through TRPV1 pathway. In summary, our findings indicate a novel mechanism underlying neuropathic pain as beneficial targets for neuropathic pain.

The development of cost-effective methods for estimating hydraulic conductivity profiles has been an ongoing effort in the field of engineering practice, which can be used to increase availability to clarify the hydrogeological complexity of fractured rock aquifers for the aid of solving groundwater-related problems. A methodology is presented, which combines electrical well logs, fluid conductivity logs, double packer hydraulic tests, Archie’s law, and the Kozeny-Carman-Bear equation to investigate relations between formation factor and hydraulic conductivity. This method was applied to develop hydraulic conductivity profiles based on the data collected from 88 boreholes in Taiwan's mountainous areas. The investigation results include: (1) Well logging signals were suggested to be categorized by rock types to establish effective relationships with hydraulic conductivity. (2) Removing the mud-bearing section data with two proposed data clustering techniques could effectively enhance the correlation between the formation factor and hydraulic conductivity. (3) The predictive models for estimating hydraulic conductivity have been developed for sandstone, schist, and slate. (4) The prevalence of clay content in most of Taiwan's mountainous rock formations has been found, which implies that careful consideration of clay-related issues in complex geologic formations is essential while applying Archie's law theory.

Dry eye disease (DED) most commonly caused by evaporative subtypes and mainly induced by meibomian gland dysfunction (MGD). Intense pulsed light (IPL) combined with meibomian gland expression (MGX) is noninvasive treatment for improvement of ocular discomfort symptoms and MGD. In this prospective study between November 2020 and May 2022, the patients met the criteria of both ocular surface disease index (OSDI) ≥13 scores and standardized patient evaluation of eye dryness (SPEED)≥ 8 scores were enrolled in Kaohsiung Veteran General Hospital. Three separate treatment sessions of IPL therapy combined with MGX administered to the lower lids with an interval of 28 days. Further tear film assessment included lipid layer thickness (LLT), tear meniscus height (TMH), non-invasive tear break-up time (NIBUT), meibomian gland loss (MGL) either beforeor after 1st and 3rd IPL therapy combined with MGX. Besides, lissamine green staining and pain scores were also recorded. We totally enrolled 37 patients of 74 eyes. Men accounted for 18.92% (7/37). The mean age was 54.51 ± 11.72 years. The mean OSDI scores were 58.12 ± 22, while the SPEED scores were 17.03 ± 5.98. The mean Schirmer’s test was 3.66 ± 2.43 mm. After three sessions IPL treatment with MGX, the OSDI, SPEED, LLT, TMH, MGL, MGXS and pain scores were significantly improved. For the MGX scores (MGXS) ≤20 group, MGL and lissamine green scores showed significant improvements. For the MGXS >20 group, TMH and dry spot rate revealed statistically improvement. Noninvasive IPL therapy with MGX statistically improved not only dry eye symptoms but also tear film assessments.

The standard treatment for early-stage lung cancer is complete tumor excision by limited resection of the lung. Pre-operative localization is used before video-assisted thoracoscopic surgery (VATS) to improve the accuracy of pulmonary nodule excision. However, lung atelectasis and hypoxia resulting from controlling apnea during the localization procedure may affect the localization accuracy. Pre-procedural pulmonary recruitment may improve respiratory mechanics and oxygenation during localization. In this study, we investigated the potential benefits of pre-localization pulmonary recruitment prior to pulmonary ground-glass nodule localization in a hybrid operating room. We hypothesized that pre-localization pulmonary recruitment would increase localization accuracy, improve oxygenation, and prevent the need for re-inflation during the localization procedure. We retrospectively enrolled patients with multiple pulmonary nodule localizations before surgical intervention in our hybrid operating room. We compared localization accuracies between patients who had undergone pre-procedure pulmonary recruitment and patients who had not. Saturation, re-inflation rate, apnea time, procedure-related pneumothorax, and procedure time were also recorded as secondary outcomes. Patients who had undergone pre-procedure recruitment had better saturation, shorter procedure time, and higher localization accuracy. The pre-procedure pulmonary recruitment maneuver was effective in increasing regional lung ventilation, leading to improved oxygenation and localization accuracy.

Identifying locations of landslide slip surfaces provides critical information for understanding the volume of landslides and the scale of disasters, which is essential for formulating disaster preparedness and mitigation strategies. Based on hydrogeological survey data from 24 deep-seated landslide-prone sites in Taiwan's mountainous regions, this study first developed the hydraulic conductivity potential index (HCPI) using principal component analysis to quantify hydraulic properties of disturbed rock formation with six geological factors. Then, The regression analysis was performed to construct a permeability estimation model for the geological environment of landslides. Finally, the established model was utilized to develop an identification method for potential slip depths in landslide-prone sites. Results indicated a strong relation between HCPI and hydraulic conductivity with a determination coefficient of 0.895. The relation equation confirmed that its generated data concerning the depths of significant changes in hydraulic conductivity could be used to identify potential slip surfaces. Additionally, this study successfully establishes a rule for identifying potential slip zones by summarizing data concerning the generated hydraulic conductivity profiles, stratigraphic lithology, existing inclinometer slip depth records, and groundwater level of landslide sites. This identification method was then applied to predict potential slip depths for ten landslide sites where slip surfaces have not yet occurred. These findings offer a new alternative to having early information on potential sliding depths for timely disaster management and control implementation.

The early detection of cognitive decline and timely non-pharmacological management or drug therapy are extremely important in providing care for Parkinson’s disease with dementia (PDD). In this study, we first conducted a discovery study to identify six plasma microRNAs that may allow for the differentiation of PD with or without mild cognitive impairment via NGS. A total of 120 participants were further recruited in a validation cohort and divided into four subgroups, namely, normal controls (HC), PD with no dementia (PDND), PD with mild cognitive impairment (PD-MCI) and PDD. Among the six candidates, miR-203a-3p was successfully detected in the plasma of the validation cohort using droplet digital PCR (ddPCR). Our results show that the ratio of miR-203a-3p/miR-16-5p observed in PDD was significantly increased compared to in PD-MCI (p < 0.001) and PDND (p = 0.041). Moreover, the ratio of miR-203a-3p/miR-16-5p showed a significant correlation with MoCA scores (r = -0.237, p = 0.024) in patients with PD (PwP). The ROC curve of the logistic regression model, consisting of the variables of age, the ratio of miR-203a-3p/miR-16-5p and the UPDRS III score, also demonstrated an average AUC of 0.883 via 5-fold cross-validation. In conclusion, the ratio of miR-203a-3p/miR-16-5p may serve as a potential biomarker for distinguishing cognitive dysfunction from PwP.

Guided ultrasonic waves are suitable for use in the context of structural health monitoring of thin-walled, plate-like structures. Hence, observing the wave propagation in the plates can provide an indication of whether damage has occurred in the structure. In this work, the wave propagation in fiber metal laminate consisting of thin steel foils and layers of carbon fiber-reinforced polymer is studied, focusing on the main propagation characteristics like dispersion diagrams and displacement fields. For this purpose, the dispersion diagrams derived from the analytical framework and numerical simulations are first determined and compared to each other. Next, the displacement fields are computed using the global matrix method for two excitation frequencies. The results derived from the analytical framework is used to validate numerically determined displacement fields based on a 2D and a 3D modeling approach. For both investigations the results of the analytical treatment and the numerical simulation show good agreement. Furthermore, the displacement field reveals the typical and well-known characteristics of the propagation of guided waves in thin-walled structures. Since the use of full 3D models involves a very high computational cost, this work also successfully investigates the possibility for model order reduction to decrease the computational time and costs of the simulation without the loss of accuracy.

High-strength low-alloy steels (HSLAs) are widely used in the structural body components of many domestic motor vehicles owing to their better mechanical properties and greater resistance. The real production process of HSLA steelmaking can be regarded as a model that builds on the relationship between process parameters and product quality attributes. A surrogate modeling method is used, and the resulting production process model can be applied to predict the optimal manufacturing process parameters. We used different methods in this paper to build such a surrogate model, including linear regression, random forests, support vector regression, multilayer perception, and a simplified VGG model. We then applied three bio-inspired search algorithms, namely particle swarm optimization, the artificial bee colony algorithm, and the firefly algorithm, to search for the optimal controllable manufacturing process parameters. Through experiments on 9,000 test samples used for building the surrogate model, and 299 test samples for making the optimal process parameter selection, we found that the combination of a simplified VGG model and the firefly algorithm was the most successful at reaching a success rate of 100%—in other words, when the product quality attributes of all test samples satisfy the mechanical requirements of the end products.

Cholangiocarcinoma is the most common primary malignant tumor of the bile duct. The current standard first-line treatment for advanced or metastatic cholangiocarcinoma is gemcitabine and cisplatin. However, few effective treatment choices exist for refractory cholangiocarcinoma, and additional therapeutic drugs are urgently required. Our previous work demonstrated that the ALDH isoform 1A3 plays a vital role in the malignant behavior of cholangiocarcinoma and may serve as a new therapeutic target. In this study, we found a positive correlation between ALDH1A3 protein expression levels and cell migration abilities of three cholangiocarcinoma cell lines, which was verified using ALDH1A3-overexpressing and ALDH1A3-knockdown clones. We also used ALDH1A3-high and ALDH1A3-low populations of cholangiocarcinoma cell lines from the Library of Integrated Network-based Cellular Signatures (LINCS) program and assessed the effects of ruxolitinib, a commercially available JAK2 inhibitor. Ruxolitinib had a higher cytotoxic effect when combined with gemcitabine. Furthermore, the nuclear translocation STAT1 and STAT3 heterodimers were markedly diminished by ruxolitinib treatment, possibly resulting in decreased ALDH1A3 activation. Notably, ruxolitinib alone or combined with gemcitabine led to significantly reduced tumor size and weight. Collectively, our studies suggest that ruxolitinib might suppress the ALDH1A3 activation through the JAK2/STAT1/3 pathway in cholangiocarcinoma, and trials should be undertaken to evaluate its efficacy in clinical therapy.

Lamb waves occur in thin-walled structures in two wave modes, the symmetric and antisymmetric mode. Their oscillation on the structures‘ surfaces is either in phase (symmetric) or shifted by a phase angle of π (antisymmetric). In this work, a method is developed to compare the surfaces‘ oscillation phase relation. It is based on the evaluation of time signals regarding the instantaneous phase angle using the continuous wavelet transformation and as a comparative method the short-time Fourier transformation. For this purpose, numerical simulations utilizing the finite element method provide time signals from the top and bottom surface of different thin-walled structures. They differ with respect to their material settings and laminate configurations. The numerically obtained time signals are evaluated by the developed methods. The occurring oscillation phase differences on the top and bottom surface are studied and both methods are compared. Subsequently, the oscillation phase is evaluated experimentally for the wave propagation in a fiber metal laminate. It is shown that the method based on the continuous wavelet transformation is suitable for the evaluation of oscillation phase relations in time signals. Additionally, it is proven that fiber metal laminates show only two phase relations which indicates the occurrence of Lamb waves.

This paper focuses on parametric model order reduction (PMOR) of guided ultrasonic wave propagation and its interaction with damage in a fiber metal laminate (FML). Structural health monitoring in FML seeks to detect, localize and characterize the damage with high accuracy and minimal use of sensors. This can be achieved by the inverse problem analysis approach which employs the signal measurement data recorded by the embedded sensors in the structure. The inverse analysis requires to solve the forward simulation of the underlying system several thousand times. These simulations are often exorbitantly expensive and triggered the need for improving their computational efficiency. A PMOR approach hinged on the proper orthogonal decomposition method is presented in this paper. An adaptive parameter sampling technique is established with the aid of a surrogate model to efficiently update the reduced-order basis in a greedy fashion. A numerical experiment is conducted to illustrate the parametric training of the reduced-order model. The results show that the reduced-order solution based on the PMOR approach is accurately complying with that of the high fidelity solution.

There is a potential for synergy effects in utilizing CO2 for both enhanced gas recovery (EGR) and geothermal energy extraction (CO2-plume geothermal, CPG) from natural gas reservoirs. This “combined CO2-EGR–CPG system” has been introduced as a feasible approach that constitutes a CO2 Capture double-Utilization and Storage (CCUUS) system. In this study, we carry out reservoir simulations, using TOUGH2, to evaluate the sensitivity of the natural gas recovery, pressure buildup, and geothermal power generation performance of the combined system to various key reservoir and operational parameters. The reservoir parameters include horizontal permeability, permeability anisotropy, reservoir temperature, and pore-size-distribution index; while the operational parameters include wellbore diameter and ambient surface temperature. Using an example of a natural gas reservoir model, we also investigate the effects of different strategies of transitioning from the CO2-EGR stage to the CPG stage on the energy-recovery performance metrics and on the two-phase fluid-flow regime in the production well. The simulation results show that overlapping the CO2-EGR and CPG stages and having a relatively brief period of CO2 injection but no production (which we call the CO2-plume establishment stage) achieves the best overall energy (natural gas and geothermal) recovery performance. Permeability anisotropy and reservoir temperature are the parameters the natural gas recovery performance of the combined system is most sensitive to. The geothermal power generation performance is most sensitive to the reservoir temperature and the production wellbore diameter. The results of this study pave the way for future CPG-based geothermal power-generation optimization studies. For a CO2-EGR–CPG project, the results can be a guide regarding the required accuracy of the reservoir parameters during exploration and data acquisition.

Surface-enhanced Raman spectroscopy (SERS) is commonly used for super-selective analysis through nanostructured silver layers in the environment, food quality, biomedicine, and materials science. To fabricate a high-sensitivity but more accessible device of SERS, dc magnetron sputtering technology was used to realize high sensitivity, low cost, stable deposition rate, and rapid mass production. This study investigated various thicknesses of a silver film ranging from 3.0 to 12.1 nm by field-emission-scanning-electron microscope, X-ray diffraction, and X-ray photoelectron spectroscopy. In the rhodamine 6G (R6G) testing irradiated by a He-Ne laser beam, the analytical enhancement factor (AEF) of 9.35x108, the limit of detection (LOD) of 10-8 M, and the relative standard deviation (RSD) of 1.61% were better than other SERS substrates fabricated by the same dc sputtering process because the results show that the 6 nm thickness silver layer has the highest sensitivity, stability, and lifetime. The paraquat and acetylcholine analytes were further investigated and high sensitivity was also achievable. The proposed SERS samples were evaluated and stored in a low humidity environment for up to forty weeks, and no spectrum attenuation could be detected. Soon, the proposed technology to fabricate high sensitivity, repeatability, and robust SERS substrate will be an optimized process technology in multiple applications.

Current methodologies for developing patient-derived xenografts (PDX) in humanized mice in preclinical trials to test response to immune-based therapies are limited by graft versus host disease. Here we compared two approaches for establishing PDX tumors in humanized mice: 1) PDX are first established in immune-deficient mice; 2) PDX are initially established in humanized mice, before transplanting established PDX’s to a larger cohort of humanized mice for preclinical trials. With the first approach, there was rapid wasting of PDX-bearing humanized mice with high levels of activated T cells in the circulation and organs, indicating immune-mediated toxicity. In contrast, with the second approach, toxicity was less of an issue and long-term human melanoma tumor growth and maintenance of human chimerism was achieved. Pre-clinical trials from the second approach revealed that rigosertib, but not anti-PD-1, increased CD8/CD4 T cell ratios in spleen and blood and inhibited PDX tumor growth. Resistance to anti-PD-1 was associated with limited infiltration of CD8+ T cell into the tumor. Our findings suggest that it is essential to carefully manage immune editing by first establishing PDX tumors in the presence of human immune cells before expanding PDX tumors into a larger cohort of humanized mice to evaluate therapy response.

In the clock network design, the trade-off between power consumption and timing closure is an important and difficult issue. To achieve this target, a hybrid clock network architecture that combines both clock tree and clock mesh seems to be a promising solution. In this paper, we propose a novel clock mesh architecture – cross-mesh, with the average dispersion of the overall driving force, our methodology creates small non-zero skew clock trees. In addition, we integrate clock gating and register clustering techniques to further reduce dynamic power consumption. The proposed algorithms have four stages: cross-mesh planning, register clustering, mesh line connecting, and load balancing. Experimental results show that our methodology and algorithms get feasible solution effectively and improve both power consumption and clock skew simultaneously.

This study centers on childcare facilities catering to children with moderate cerebral palsy, exploring a four-phase process: (1) cultivating an understanding and acceptance, (2) integrating specialized resources, (3) developing strategic plans, and (4) establishing stable collaboration. The case study demonstrates the profound impact of well-rounded support systems. Children with cerebral palsy showed marked improvements in development and emotional stability. Concurrently, their peers developed greater empathy and cooperative skills, smoothly adjusting to the inclusive setting. Additionally, the childcare staff refined their methods and attitudes, enhancing their ability to meet each child's specific needs and thus elevating the standard of integrated care.Concluding with three strategic recommendations, the paper proposes measures to augment the quality of care for children with special needs. These include defining clearer guidelines and policies for special needs care in childcare environments, emphasizing professional development and the amalgamation of diverse resources to cultivate a more skilled caregiving workforce, and encouraging robust partnerships between parents and childcare facilities. These recommendations are expected to significantly influence the domain of inclusive education, providing crucial insights for those engaged in early childhood care and education..

For the numerical simulation of components made of short fiber-reinforced composites the correct prediction of the deformation including the elastic and plastic behavior and its spatial distribution is essential. When using purely deterministic modeling approaches the information of the probabilistic microstructure is not included in the simulation process. One possible approach for the integration of stochastic information is the use of random fields. In this study numerical simulations of tensile test specimens are conducted utilizing a finite deformation elastic-ideal plastic material model. A selection of the material parameters covering the elastic and plastic domain are represented by cross-correlated second-order Gaussian random fields to incorporate the probabilistic nature of the material parameters. To validate the modeling approach tensile tests until failure are carried out experimentally, that confirm the assumption of spatially distributed material behavior in both the elastic and plastic domain. Since the correlation lengths of the random fields cannot be determined by pure analytic treatments, additionally numerical simulations are performed for different values of the correlation length. The numerical simulations endorse the influence of the correlation length on the overall behavior. For a correlation length of 5mm a good conformity with the experimental results is obtained. Therefore, it is concluded, that the presented modeling approach is suitable to predict the elastic and plastic deformation of a set of tensile test specimens made of short fiber-reinforced composite sufficiently.

Holistic information integrity for managing wicked problems, developing equity is getting attention. Artifitial intelligence based topologies, dual sensor-information nodes, are prototyped to offer more availability, reliability, maintainability for operating healthy urbanism. Bipartite spider-webs, cube-connected cycles are aimed in ‘the radial-ring urban-building skeleton’ and ‘wetlands and sparsely populated areas’, respectively. Furthermore, honeycomb tori, mathematical HT(m), m≥2, for tasks related to wireless communications, are found having two mutually independent Hamiltonian paths (MIHP). This parallelism creates dual cipher-coding, supports logistic privacy, and help prevent information loss, electromagnetic interference, unexpected changes caused by such as clogged water.

This is a survey study that dialysis patients were randomly sampled from a medical center in northern Taiwan, and those who gave their consent to participate were included in this study. The purpose of this study was to explore the correlation between depression, hope, and quality of life of dialysis patients. All subjects agreed to take "Beck’s Depression Inventory", " The Chinese version of Herth Hope Index" and " The Chinese version of Kidney Disease Quality of Life" (KDQOL-SFTM). Data were processed using SPSS for descriptive and inferential statistics. The results showed that patients were 12.45±SD 9.03, which was mild depression, the mean score of hope was 34.25, which was equivalent to 72.60%, and was at the middle level. In KDQOL-SFTM, the score in mental composite (M=42.65, SD=8.81) was higher than in physical composite (M=37.38, SD=9.28), and the score was at the intermediate quality of life, and hope and depression were significantly and negatively correlated. This study suggests that dialysis case managers provide nursing guidance to help dialysis patients learn comfortable care methods and support the resilience they need.

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

Embracing innovative digital technologies within educational systems is essential for overcoming challenges in modern learning environments, especially in the post-COVID-19 era. Teaching sustainability management in higher education institutions with innovative digital tools plays a fundamental role in the transition toward sustainable societies. Suitable game design elements play a significant role in facilitating sustainable learning. This study explored the effectiveness of incorporating business simulation games with project-based learning (PBL) in a flipped classroom setting. This approach was adopted within the context of a university cross-border e-commerce course to prepare students for acquiring 21st -century skills as higher-order thinking skills in a rapidly changing educational landscape. A quasi-experimental method was employed, involving a total of 60 university students from China's Zhejiang Province. Participants completed an online questionnaire designed to assess their learning engagement across three dimensions (cognitive, emotional, and behavioral) as well as their higher-order thinking skills (problem-solving, critical thinking, and creativity). The results show that the business simulation games combined with flipped classroom learning had a significantly positive impact on students’ learning outcomes, enhancing their problem-solving, critical thinking, and creative capabilities. Importantly, this approach also improved student engagement and promoted sustainable practices by applying real-life scenarios in an interactive environment. We conclude that business simulation games integrated with project-based learning (PBL) in flipped classroom settings represent a valuable educational approach. This approach not only enhances learning engagement but also fosters the development of higher-order thinking skills, encouraging students to adopt sustainable learning practices.

In all areas of medicine, especially in radiology, computers are increasing year by year. Filmless radiology, speech recognition software, electronic application forms, and teleradiology are recent developments that have greatly improved radiologists' performance. This research explores radiology software trends, predictions, and the challenges posed by informatics and historical trend analysis. The rationale behind this research is that information technology (IT) is overgrowing almost every day. We must continuously seek new ways to apply IT to make more use of resources. Consequently, IT becomes increasingly crucial to radiology organizations' innovative thinking, workflow, and business models. This study aimed to analyze all radiology software publications in the Science Citation Index (SCI). From 1991 to July 2021, SCI was used to search for publications systematically. We have also widely used this historical method in radiology software research. The findings and discussions are base on an assessment of trends, predictions, contributions, and challenges in radiology software, and we are exploring radiology software with six evolutionary stages. The gift of this research is that radiology managers realize that the use of new information technologies is closely related to survival in a competitive environment. Radiology companies can review these new technologies to develop more innovative business models and services to improve operational deficiencies.

This work investigates how integrated polyimide inlays with applied sensor bodies influence the guided ultrasonic wave propagation in narrow glass fiber-reinforced polymer specimens. Preliminary numerical simulations indicate that in a damping-free specimen, the inlays show reflections for the S0-mode propagation. Hence, an air-coupled ultrasonic technique and a 3D laser Doppler vibrometer measurement are used to measure different parts of the propagating waves’ displacement field after burst excitation at different frequencies. No significant reflections on the inlay can be seen in the experiments. However, it is shown that the reflections from the strip specimen’s narrow width cause periodical reflections that superimpose with the excited wave fronts. A continuous wavelet transformation in the time-frequency domain filters discontinuities from the measurement signal and is used for reconstruction of the time signals. The reconstructed signals are used in a spatial continuous wavelet transformation to identify the occurring wavelengths and hence to prove the assumption of reflections from the narrow edges. Since the amplitude of the reflections identified in the numerical data at the polyimide inlays are an order of magnitude smaller than the excited wave packages, it is concluded that material damping of the epoxy resin matrix extincts possible reflections from the inlays.

Various vaccines have been developed in response to the SARS-CoV-2 pandemic, and the safety of vaccines has become an important issue. COVID-19 vaccines-related central nervous system inflammatory demyelinating diseases (CNS IDDs) have been reported recently. We present one case of AstraZeneca vaccine-related myelin oligodendrocyte glycoprotein (MOG) antibody-associated disease and literature review another 78 patients published from January 2020 to October 2022. Patients were divided into three vaccine groups (viral vector, mRNA and inactivated vaccines) for further analyses. Among 79 patients with COVID-19 vaccines-related CNS IDDs, 49 (62%) cases received viral vector vaccines, 20 (25.3%) received mRNA vaccines and 10 (12.7%) received inactivated vaccines. Twenty-seven cases (34.2%) were confirmed with autoantibodies, including 15 patients (19%) with anti-MOG, 11 (13.9%) with anti-aquaporin 4 (AQP4), and one (1.3%) with both antibodies. Significantly, more males developed CNS IDDs post viral vector vaccines compared to mRNA and inactivated vaccines. Patients receiving mRNA vaccines were older than other groups. Furthermore, mRNA and inactivated vaccines correlated more with anti-AQP4 antibodies, while viral vector vaccines showed higher MOG positivity. The research suggests potential associations between COVID-19 vaccines-related CNS IDDs and gender, age, and autoantibodies, contingent on vaccine types. Protein sequence analysis implies similarities between the S protein and AQP4/MOG. Further studies may elucidate the mechanisms of CNS IDDs, aiding vaccine selection for specific groups.

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.

Static standing postural stability has been measured by multiscale entropy (MSE), which is used to measure complexity. In this study, we used the average entropy (AE) to measure the static standing postural stability, as AE is a good measure of disorder. The center of pressure (COP) trajectories were collected from 11 subjects under four kinds of balance situation, from stable to unstable: bipedal with open eyes, bipedal with closed eyes, unipedal with open eyes, and unipedal with closed eyes. The AE, entropy of entropy (EoE), and MSE methods were used to analyze these COP data, and EoE was found to be a good measure of complexity. The AE of the 11 subjects sequentially increased by 100%as the balance situations progressed from stable to unstable, but the results of EoE and MSE did not follow this trend. Therefore, AE, rather than EoE or MSE, is a good measure of static standing postural stability. Furthermore, the comparison of EoE and AE plots exhibited an inverted U curve, which is another example of a complexity versus disorder inverted U curve.

ABSTRACT Introduction: Traditional penile venous surgery and enhancement have been controversial. Based on De Novo penile fibrovascular assembly, we report on penile venous stripping (PVS) and factual penile girth enhancement (FPGE). Methods: From 2013 to 2023, 18 men underwent PVS and FPGE, all confirmed with veno-occlusive dysfunction (VOD). PVS involves the stripping of erection-related veins. FPGE was performed along the tunica albuginea bilaterally; then, the two tunic defects were repaired with a 70.0x30.0 mm venous stripe and covered with either autologous venous walls (AVW, n=10) or Surgiform (SF, n=8). The penile girth was measured, and radio-opaque contrast was used. The abridged 5-item version of the International Index of Erectile Function (IIEF-5) score and the Erection Hardness Scale (EHS) were used yearly during follow-up via the Internet. Results: The follow-up period was 5.3±1.5 years. Radiopacity was consistently enhanced. Although there was indifference between AVW and SF, there was a significant improvement (both P＜0.01) in IIEF-5 and EHS scores (9.7±2.8 vs. 20.8±2.3; 1.7±0.6 vs. 3.2±0.2, respectively). Both the diameters of the glans and penile shaft increased (28.0±2.3mm and 28.3±2.1mm vs 35.3±2.2mm and 36.3±2.1mm respectively). The satisfaction rate was 81.3% (13/16). Conclusions: This novel combination of PVS and FPGE is promising, although a larger sample size is needed for further validation.

Wind energy is a kind of renewable energy with great potential for development. This study mainly investigated the application of shock waves generated by high-pressure gases (wind energy) for generating energy. In this study, we designed a new supersonic shock wave generator that can be reused without disassembling and assembling bolts and developed a supersonic shock wave monitoring system. This system monitored the velocity of the generated shock waves, which was Mach 3-5, and the output pressure was more than 100 times higher than the input pressure of the shock wave generator tank.Then, we developed a power generation system driven by supersonic shock waves based on the characteristics of the new shock wave generator, which can generate high-pressure and high-speed blast waves and can be reused. The shock wave generator can repeatedly generate high-pressure waves to drive the Tesla turbine and then the magnetic energy generator for power generation. We established a complete control process for power generation driven by shock waves by controlling the valve stem. The system can detect the tank pressure, output pressure, gas flow, rotation speed, voltage, and current during the control process for the performance analysis of power generation.

Our results demonstrated that SWT stimulates osteoblastogenesis and increase the cell number of osteoblasts, suggesting positive regulatory effects on osteoblast differentiation. However, the effect of SWT on bone formation need further examination, since the expression of alp gene is downregulated. On the other hand, SWT appears to negatively regulate osteoclast differentiation and bone resorption, as number of osteoclasts and the expression of critical bone resorptive genes are all downregulated. Collectively, SWT might change the equilibrium of bone remodeling and increase the bone mass. Our data provided supportive evidences that this medicine formulation can be applied to treat osteoporosis or bone destructive diseases.

The movement of liquid droplets on the energy gradient surface has attracted extensive attention. Inspired by biological features in nature, such as the periodic spindle-shaped nodes in spider silks and conical-like barbs of cacti, the structure-property-function relationship of multifunctional gradient surfaces. In this study, a series of specific patterns are fabricated by 3D printing technology, followed by modification via the atmospheric pressure plasma treatment and liquid phase chemical deposition, resulting in enhancing the ability of water droplets of 5μL to travel 18.47mm on a horizontal plane and 22.75mm against gravity up to 20° tilting angle. Additionally, analysis techniques have been employed including contact angle analyzer, ESCA and laser confocal microscope to evaluate the sample performance. This work could further be applied to many applications related to microfluidic devices, drug delivery and water/fog collection.

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

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

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.

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

To enhance industrial competitiveness and increase productivity, every country has strived to create a smart factory by introducing technologies such as Internet of Things, big data and artificial intelligence into production line and build cyber-physical system for the purpose of promoting manufacturing efficiency. For mission assignment, production line management or manufacturing field analysis, the location information of employee, machine and material is very essential. To promote manufacturing efficiency, of course, the location information became more important. A Bluetooth low energy (BLE) positioning system for the manufacturing is developed in this research. A "Tag tracking" mechanism is addressed and adopted, which uses Beacon to catch the location information and a BLE receiver is also used to receive the broadcasting information from Beacon. The position information from the BLE receiver will be compared with the data in the database for calculating the location of the target. The status of the target may also be obtained by using the data from the BLE receiver. Comparing with the mobile device, this method can reduce energy consumption and make the maintenance simple and easy. In the real applications, the target may not be limited to human. The "Regional label positioning technology" is also investigated in this research. Defining a suitable zone location and arranging BLE receiver location, and positioning analysis theory are the key factors included in this developed technology. The developed system will be tested for real industry applications. The test results show that the feasibility of this technology.

Background: People with Down syndrome (DS) have a trisomy of chromosome 21 and marked deficits in verbal memory but relatively preserved visuospatial perception. Verbal memories are related to semantic knowledge. Little is known about the organization of semantic knowledge in people with DS, which was the aim of this study. Aims: The extent of false memory in people with DS was examined. Possible differences in the number of false memories induced by nominal and verbal themes were examined. Methods and Procedures: In the study phase, ten word lists with semantically related associates were presented. In the recognition phase, participants made judgments on whether each word had been represented previously as semantically related lures, old words, and semantically unrelated new words. Outcomes and Results: Differences in the processing of nominal and verbal theme-related lures were observed among people with DS. When processing nominal theme-related lures, people with DS showed delayed false positives. When processing verbal theme-related lures, people with DS showed no differences compared to controls. Similar patterns have been observed in people with DS when processing nominal theme-related associates and verbal theme-related associates. People with DS have delayed recognition of associates. When processing unrelated words, they showed significantly higher false positives than controls for both nominal and verbal eliciting themes. Further analyses of the themes revealed differences in false positives across syntactic categories among groups. Conclusions and Implications: People with DS showed a delayed recognition of associates and deviance in recognizing unrelated words in the nominal and verbal theme categories. People with DS were delayed in terms of nouns, but deviated with verbs in associated and unrelated words. Additionally, people with DS showed distinct patterns in processing five nominal lures and three verbal lures, suggesting that they formed false memories differently based on distinct syntactic categories. Thus, it was concluded that people with DS develop a deviant semantic structure. Category-based interventions for people with DS should be implemented in order to improve their semantic knowledge through lexical connections.

Floating Offshore Wind Turbine (FOWT) is an innovative technology with little industry guidance for its hull design. Various FOWT floaters with different hull shapes claim to support the same turbines. Structural integrity and material expense analyses of different pontoon shapes were conducted, and it was found that some configurations, such as those with every two columns connected by both pontoon and bracing, have advantages over others. However, it is important to note that the choice of pontoon shape should be based on the wave loading conditions the floater will be exposed to. While a T-shaped pontoon provides a cost-effective solution under certain wave loading scenarios, it may not be the best option for all conditions. Specifically, ring pontoon designs with full bracing were found to be necessary for withstanding certain wave loads. Therefore, it is important to consider different Dominant Load Parameters (DLP) and ensure that a FOWT floater can withstand all applicable DLPs. An uneven hexahedral column shape, which combines the best attributes of square and round shapes, is proposed as a better alternative to cylindrical columns. It offers ease of manufacture and reasonably low drag. Bracing is found to be necessary for withstanding the wind turbine’s incurred moment and forces. The conclusion is that platform design should prioritize manufacturing costs and strength over maximizing hydrodynamic performance.

In a single-center, retrospective study, 22 cases were enrolled and divided into two groups: those who underwent surgical wide excision (group A) and those who did not (group B). The study included 13 cases in group A and 9 cases in group B. In group A, 6 cases solely underwent surgical wide excision, while 7 cases received additional treatments like radiotherapy or chemotherapy. Conversely, in group B, 4 cases received chemotherapy, 4 cases received radiotherapy, and 1 case was managed through observation alone. The mean follow-up time was 60.15 months in group A and 43.44 months in group B, with no significant difference observed. In group A, 9 cases resulted in mortality, whereas 6 cases died within the follow-up period in group B. Lesion-free intervals post-operation were observed predominantly in group A, while 7 cases in group B never experienced freedom from skin lesions. Kaplan-Meier survival curve analysis demonstrated a significant difference between the survival curves of the two groups (P = 0.046). Among non-HIV Kaposi’s sarcoma patients, surgical wide excision appears to have a role in treatment. Patients in group A exhibit a more favorable outcome in the survival curve analysis.

Aluminum alloy (Al6061) sheet micro-hole processing is extensively used in smartphones, tablet PC, and smart wearable devices. The micro-hole processing is commonly performed using laser, micro drilling, microstamping, micro discharge, and chemical etching technologies. Micro-stamping technology is characterized by precision and rapid processing, but the precision positioning of the punch head and lower die is one of the major difficulties in micro-hole stamping, especially in manufacturing array micro-holes. This study used stamping without die technology. This technology uses an array punch head to punch the lower die holes on the base, then performs array micro-hole stamping. The experimental results show that a micro-hole array with 37 micro-holes were successfully manufactured and can be reproduced many times. Tapered array micro-holes with a high aspect ratio can be manufactured using this stamping without die technology; the micro-hole depth can be 260μm, the inlet diameter is 116μm, and the outlet diameter is 25μm. This study has successfully developed the feasibility of array micro-hole stamping technology.

A novel flexible humidity sensor, incorporating gold nanoparticles (Au NPs) and a trifunctional organosilica compound, has been developed through the integration of sol-gel processing, free radical polymerization, and self-assembly techniques. The trifunctional organosilica was initially synthesized by modifying (3-mercaptopropyl)trimethoxysilane (thiol-MPTMS) with 3-(trimethoxysilyl)propyl methacrylate (vinyl-TMSPMA). Subsequently, a hydrophilic polyelectrolyte, [3(methacryloylamino)propyl]trimethyl ammonium chloride (MAPTAC), was grafted onto the MPTMS-TMSPMA gel. The Au NPs were assembled onto the thiol groups present in the MPTMS-TMSPMA-MAPTAC gel network. The compositional and microstructural properties of the Au NPs/MPTMS-TMSPMA-MAPTAC composite film were investigated utilizing Fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM). The presence of thiol groups and mesoporous silica skeletons ensured the stability of the humidity-sensing film on the substrate under highly humid conditions, while the hydrophilic groups functioned as humidity-sensitive sites. This innovative humidity sensor demonstrated high sensitivity, acceptable linearity, minimal hysteresis, and rapid response time across a broad range of working humidity levels. Based on the complex impedance spectra analysis, hydronium ions (H₃O⁺) were determined to govern the conductance process of the flexible humidity sensor.

Background: People with Williams syndrome (WS) are characterized with hypersociability, fluency in languages, and advantageous face-processing skills, leading to the proposal of a social module. Previous studies on the mentalizing abilities of people with WS using two-dimensional pictures and mindreading from eyes, including normal-like, delayed, and deviant behaviors, have yielded mixed results. This study thus examined the mentalizing ability of people with WS through structured computerized animations of false belief tasks to investigate whether inferences about other people’s minds can be improved in this population. Method: Participants were shown animations with unexpected location and content changes. After viewing each animation, participants had to answer four types of questions: character identification, reality, memory, and false belief. Their responses were recorded and analyzed. Results: Comprehension of false belief was observed in 4-year-old healthy children, whereas children with WS showed unsuccessful comprehension of false belief (until they attained a mental age of 5.3 years), suggesting an improvement in theory of mind resulting from viewing structured computerized animations. This age is earlier than that reported by previous studies for using theory of mind to pass false belief tests (8.5 years old), even challenging the age at which individuals failed to pass the tests (12.10 years old). Conclusions: Structured computerized animations enhanced the mentalizing ability of people with WS to a certain extent. Compared to the typically developing controls, people with WS presented with a lower developmental level in processing false belief tasks. The educational implication of this study is to develop computerized social skills interventions for people with WS.

Because imbalanced power will cause the loss of the propulsion motor of the railway vehicle, and the increase in temperature will shorten the service life of the electric vehicle. Not only this, but also increase the cost of electricity and maintenance. In the past, the industry only focused on methods to improve power quality such as load capacity, relay setting, and harmonic resolution. Now, the consider of three-phase unbalance rate (TPUR) must be applied. I propose special transformers wiring (STW) to improve the three unbalance rates and provide different transformer wiring methods. According to the IEEE Committee, in the future, power companies will need to install balanced relay stations to improve three-phase unbalance rate. the internal regulations of Taipower must be less than 4.5% (voltage unbalance rate (NPSUR)of 2.5% and motor temperature rise of 12.5%). the derivation of the transformer "three-phase unbalance rate" model is the focus of the railway system. This research is based on the model derivation of different wiring methods to improve the hot problem caused by the three-phase imbalance and improve the service life of the train. And pointed out that Scott, Le-Blanc, Modified-Woodbridge three wiring methods can be applied to future railway system routes to improve the three-phase unbalance rate, in line with the IEEE standard of less than 2%.

Taiwan's bed and breakfast (B&B) development has been more than 25 years ago, from the first generation of retirement to the B&B industry, serving tourists from all over the world accom-modation, providing breakfast and accommodation mode to the present, after the change of employees from the second generation, more and more attention is paid to the cultivation and cultivation of business ability. With the advent of the era of AI technology networking, the ca-pabilities required for B&B operation are more focused on all aspects of service, and the good marketing ability of B&B can promote a green chimney-free tourism economy, which is also a favorite industry of various governments and the public. This study explores the basic vocational competency indicators required for running a B&B, with (1)EQ emotion management skills, (2)Financial management ability, (3)(SK) technical skills, and (4)Marketing and promotion management capabilities. Through the study method, the K-S Z test was determined by the con-sensus conclusion of expert reliability and validity p value

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

Chimeric antigen receptor (CAR) T-cell therapy has greatly improved outcomes for patients with relapsed or refractory hematological malignancies. However, challenges such as treatment resistance, relapse, and severe toxicity still hinder its widespread clinical application. Traditional transcriptome analysis has provided limited insights into the complex transcriptional landscape of both leukemia cells and engineered CAR-T cells, as well as their interactions within the tumor microenvironment. However, with the advent of single-cell sequencing techniques, a paradigm shift has occurred, providing robust tools to unravel the complexities of these factors. These techniques enable unbiased analysis of cellular heterogeneity and molecular patterns. These insights are invaluable for precise receptor design, guiding gene-based T cell modification, and optimizing manufacturing conditions. Consequently, this review utilizes modern single-cell sequencing techniques to clarify the transcriptional intricacies of leukemia cells and CAR-Ts. The aim of this manuscript is to discuss the potential mechanisms that contribute to the clinical failures of CAR-T immunotherapy. We will examine the biological characteristics of CAR-Ts, the mechanisms that govern clinical responses, and the intricacies of adverse events. By exploring these aspects, we hope to gain a deeper understanding of CAR-T therapy, which will ultimately lead to improved clinical outcomes and broader therapeutic applications.

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.

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

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

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

This paper reassesses the detrimental effect on fatigue performance due to thicker sections based on extensive fatigue strength test database, taken from research program worldwide over the past half of a century in offshore oil &amp; gas and renewable industry. The data entries in the database have been evaluated to ensure its data integrity. Statistical analyses on these S-N data are performed with or without the thickness correction at different exposure level to corrosive environment, in order to re-evaluate the suitability of current standards in regard to the thickness effect. The study has concentrated on T-joint, transverse butt welded joint and tubular joint as these are the most commonly used joint types in the offshore wind industry. The analysis indicates general agreement of fatigue strength with the thickness effects in current standard for in air conditions but great conservatism for corrosive environment.

The concept of Design Fatigue Factors (DFFs) was introduced for providing desired level of safety in structural fatigue design, often associated with damage calculated from S-N curves. Calculation of fatigue damage from S-N curves can be affected by multiple factors, e.g. types of weld class, corrosion condition, loading conditions, stress concentration on different geometries etc. Each of them can be subject to different level of uncertainties. This study intends to recalibrate the DFFs from a detailed reliability analysis by investigating the probabilistic models derived from the database of S-N curves that has been most frequently used in offshore wind industry. The results of such study indicate that the DFFs can be reduced substantially for the corrosive environmental fatigue models from current standards to the same level of target reliability.

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

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.

Hepatocellular carcinoma (HCC) is the fifth most common type of cancer, and is the third leading cause of cancer-related deaths each year. It involves a multi-step progression and is strongly associated with chronic inflammation induced by the intake of environmental toxins and/or viral infections (i.e., hepatitis B and C viruses). Although several genetic dysregulations are considered to be involved in disease progression, the detailed regulatory mechanisms are not well defined. Homeobox (Hox) genes that encode transcription factors with homeodomains control cell growth, differentiation, and morphogenesis in embryonic development. Recently, more aberrant expressions of Hox genes were found in a wide variety of human cancer, including HCC. In this review, we summarize the currently available evidence related to the role of Hox genes in the development of HCC. The objective is to determine the roles of this conserved transcription factor family and its potential use as a therapeutic target in future investigations.

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

Background: Auriculotherapy is a widely used approach for alleviating discomfort in patients experiencing pain, itchiness, sleep disturbances, and heightened anxiety. This method is also applicable to patients dealing with significant burn scars, who often encounter similar symptoms. Employed as an adjuvant therapy, auriculotherapy demonstrates potential in mitigating these clinical manifestations among individuals with major burn scars. These symptoms are known to be influenced by the autonomic nervous system. Objectives: Despite the absence of current data elucidating the impact of auriculotherapy on the autonomic nervous system, we embarked on an analysis of our heart rate variability (HRV) data to evaluate autonomic system functionality before and after the administration of auriculotherapy. Methods: Paired-samples t-tests and linear regression analysis of HRV variables and correlations with TBSA before and after auriculotherapy of a cohort of 31 survivors from 2016 Formosa Color Dust Explosion was carried out. Results: Significant change of specific HRV variables were found before and after auriculotherapy, and significantly negative correlations was revealed between TBSA and pre-SD prior to auriculotherapy. Conclusion: Our study showed that auriculotherapy may, at least in part, restore the equilibrium of autonomic nervous system and improve HRV parameters.

Visual-inertial integrated navigation system (VINS) has been extensively studied over the past decades to provide accurate and low-cost positioning solutions for autonomous systems. Satisfactory performance can be obtained in an ideal scenario with sufficient and static environment features. However, there are usually numerous dynamic objects in deep urban areas, and these moving objects can severely distort the feature tracking process which is fatal to the feature-based VINS. The well-known method mitigates the effects of dynamic objects is to detect the vehicles using deep neural networks and remove the features belongs to the surrounding vehicle. However, excessive exclusion of features can severely distort the geometry of feature distribution, leading to limited visual measurements. Instead of directly eliminating the features from dynamic objects, this paper proposes to adopt the visual measurement model based on the quality of feature tracking to improve the performance of VINS. Firstly, a self-tuning covariance estimation approach is proposed to model the uncertainty of each feature measurements by integrating two parts: 1) the geometry of feature distribution (GFD), 2) the quality of feature tracking. Secondly, an adaptive M-estimator is proposed to correct the measurement residual model to further mitigate the impacts of outlier measurements, such as the dynamic features. Different from the conventional M-estimator, the proposed method effectively alleviates the reliance of excessive parameterization of M-estimator. Experiments are conducted in a typical urban area of Hong Kong with numerous dynamic objects, and the results show that the proposed method could effectively mitigate the effects of dynamic objects and improved accuracy of VINS is obtained when compared with the conventional method.

Objective: To use the ancient and modern medical record cloud platform (V2.3.5) to organize and explore the medication patterns of the "Three Causes, Extremity, and One Disease Syndrome Formula" by Chen Wuxuan, and to summarize its therapeutic ideas. Method: Collect and organize the "San Yin Si Tian Fang" in the "San Yin Ji Yi Zheng Fang Lun", and use the modern medical record cloud platform (V2.3.5) to conduct medication frequency statistical analysis, cluster analysis, and complex network analysis. As a result, a total of 16 Chinese herbal medicines were collected in the "Three Causes, Extreme and One Disease Syndrome Formula", involving 75 traditional Chinese medicines. Statistical analysis showed that roasted licorice was the most commonly used, followed by Pinellia ternata, papaya, ginger, and Poria cocos; Medications mainly include warm drugs, sweet and pungent flavors, as well as drugs that promote lung and spleen meridians. Cluster analysis can divide the above-mentioned traditional Chinese medicine into two groups, with specific grouping as follows. Group 1: ginger, white peony, aconite, papaya, and achyranthes bidentata; Group 2: roasted licorice, poria cocos, dried ginger, pinellia ternata, and green peel. Conclusion: The characteristics of the 16 prescriptions are biased towards Xin Gan Wen, emphasizing the regulation of the spleen and stomach, which may be related to the common use of prescription by doctors in the Song Dynasty and the tendency towards warm and dry medication.

Caring for dolphins is a delicate process that requires experienced caretakers to pay close attention to their behavioral characteristics. However, caretakers may sometimes lack experience or not be able to give their full attention, which can lead to misjudgment or oversight. To address these issues, a dolphin behavior analysis system has been designed to assist caretakers in making accurate assessments. The study utilized image preprocessing techniques to reduce sunlight reflection in the pool and enhance the outline of dolphins, making it easier to analyze their movements. The dolphins were divided into 11 keypoints using an open-source tool called DeepLabCut, which helped accurately mark various body parts for skeletal detection. The AquaAI Dolphin Decoder (ADD) was then used to analyze six dolphin behaviors. To improve behavior recognition accuracy, the Long Short-Term Memory (LSTM) neural network was introduced. The ADD and LSTM models were integrated to form the ADD-LSTM system. Several classification models, including unidirectional and bidirectional LSTM, GRU, and SVM, were compared. The results showed that the ADD module combined with a double-layer bidirectional LSTM method achieved high accuracy in dolphin behavior analysis. The accuracy rates for each behavior were over 90%.

Copper-based nanoparticles were synthesized using the glycine–nitrate process (GNP) by using copper nitrate trihydrate [Cu(NO₃)₂‧3H₂O] as the main starting material and glycine [C₂H₅NO₂] as the complexing and incendiary agent. The as-prepared powders were characterized through X-ray diffraction (XRD), Brunauer–Emmett–Teller (BET) analysis, X-ray photoelectron spectroscopy, and scanning electron microscopy. Using Cu(NO₃)₂.3H₂O as the oxidizer (N) and glycine as fuel (G), we obtained CuO, mixed-valence copper oxides (CuO + Cu₂O, G/N = 0.3–0.5), and metallic Cu (G/N = 0.7). The XRD and BET results indicated that increasing the glycine concentration (G/N = 0.7) and reducing particle surface area increased the yield of metallic Cu. The effects of varying reaction parameters such as catalyst activity, catalyst dose, and H₂O₂ concentration on nonylphenol-9-polyethoxylate (NP9EO) degradation were assessed. With a copper‐based catalyst in a heterogeneous system, the NP9EO and total organic carbon removal efficiencies were 83.1% and 70.6%, respectively, under optimum operating conditions (pH, 6.0; catalyst dose, 0.3 g/L; H₂O₂ concentration, 0.05 mM). The results suggested that removal efficiency increased with an increase in H₂O₂ concentration but decreased when the H₂O₂ concentration exceeded 0.0.5 mM. Furthermore, the trend of photocatalytic activity was as follows: G/N = 0.5 > G/N = 0.7 > G/N = 0.3. The G/N = 0.5 catalysts showed the highest photocatalytic activity and resulted in 94.6% NP9EO degradation in 600 min.

This study evaluated the mechanical strengths of three types of orthodontic micro-implants by analyzing their structural configurations. Thirty micro-implants of three types (diameter 1.5 mm, Types A, B, C) were assessed. All micro-implants were manually driven into artificial bones at an 8-mm depth. The insertion torque (IT), pullout strength (PS), and gripping volume (GV) of each type were measured. Intergroup comparisons and intragroup correlation were investigated by statistical analysis. Type B had the greatest inner–outer diameter ratio (0.67), and Type A had the smallest (0.53). The IT of Type A (5.26 Ncm) was significantly (p = 0.038) lower than that of Type C (8.8 Ncm). There was no significant difference in the pullout strength (p = 0.868). The GV of Type A (9.7 mm3) was significant (p < 0.01) greater than Type C (8.4 mm3). Type C was significant (p < 0.01) greater than Type B (7.2 mm3). Spearman’s rho rank correlation test showed that PS of Type B was correlated significantly with GV. In conclusion, the design of thread and its GV were the important factors on the mechanical strengths of micro-implant.

Age-related sarcopenia meaningfully increases the risks of functional limitations and mortality in the elderly. Although circulating microRNAs (c-miRNAs) are associated with aging-related cellular senescence and inflammation, the relationships between c-miRNAs and sarcopenia in the elderly remain unclear. This study investigates whether circulating myo-miRNAs and inflammation-related miRNAs are associated with sarcopenia in the elderly. This study recruited 77 eligible subjects (41 males and 36 females) from 597 community-dwelling older adults, and then divided into normal (n=24), dynapenic (loss of muscular function without mass, n=35), and sarcopenic groups (loss of muscular function with mass, n=18). Moreover, myo-miRNAs (c-miRNA-133a and c-miRNA-486), inflammation-related miRNAs (c-miRNA-21 and c-miRNA-146a), and inflammatory-related cytokine levels in plasma were determined using quantitative polymerase chain reaction and ELISA, respectively. The results demonstrated that sarcopenic group exhibited lesser skeletal muscle mass index (SMI), handgrip strength, and gait speed, as well as, lower c-miR-486 and c-miR-146a levels, compared to those of normal and dynapenic groups. Moreover, c-miR-486 level was positively related to SMI (r=0.334, P=0.003), whereas c-miR-146a level was positively associated with SMI (r=0.240, P=0.035) and handgrip strength (r=0.253, P=0.027). In the receiver operating characteristic analysis for predicting sarcopenia, the area under the curve in c-miR-486 was 0.708 (95% confidence interval: 0.561-0.855, P=0.008) and c-miR-146a was 0.676 (95% CI: 0.551-0.801, P=0.024). However, no significant relationships were observed between SMI/ handgrip strength/gait speed and plasma myeloperoxidase/interleukin-1?/interleukin-6 levels. In conclusion, myo-miRNA (c-miR-486) and inflammation-related miRNA (c-miR-146a) are superior to inflammatory peroxide/cytokines in plasma for serving as critical biomarkers of age-related sarcopenia.

This study aims to determine the protective effects of red seaweed Eucheuma cottonii (EC) ethanol extract on acute colitis disease in mice. Male BALB/c mice used for acute colitis disease model by induced 2.5% (w/v) of dextran sulfate sodium (DSS) for 7 days for all groups, except control group. The DSS-induced mice then treated by three different doses of EC extracts (0.35, 0.70, 1.75 g/kg body weight), curcumin (as a positive control, 0.10 g/kg), and a group was orally only by water. In 8^th day, the mice sacrificed and collected the blood, then measured the body weight, colon weight, and colon length. Disease activity index (DAI), pro-inflammatory such as tumor necrosis factor (TNF)-α, interleukin (IL)-1β, and IL-6, as well as IL-10 as anti-inflammatory were measured. The results showed that after treatment for 7 days, EC extract protected the weight loss and decreased the colon weight per length ratio. In addition, EC extract also decreased the pro-inflammatory cytokines expression in serum and increased the IL-10. Moreover, EC extract protected the colonic tissue damage. According to this results, the EC ethanol extract might be can used for the treatment of colitis disease.

3D-mapping-aided (3DMA) global navigation satellite system (GNSS) positioning that improves positioning performance in dense urban areas has been under development in the recent years, but it still faces many challenges. This paper details a new algorithm that explores the potential of using building boundary for positioning. Rather than applying complex simulations to analyze and correct signal reflections by buildings, the approach utilizes a convolutional neural network to differentiate between the sky and building in a sky-pointing fisheye image. A new skymask matching algorithm is then proposed to match the segmented fisheye images with skymasks generated from a 3D building model. Each matched skymask holds a latitude and longitude coordinate to determine the precise location of the fisheye image. The results are then compared with the conventional GNSS and advanced 3DMA GNSS positioning methods. The aims of the proposed algorithm are to increase positioning and heading accuracy in a rich urban environment.

Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer and is highly invasive and easily recurs. For HCC, chemotherapy shows a limited effect. The gold standard for HCC treatment includes curative surgical resection or liver transplantation. However, the recur-rence rate at 5 years after liver resection is estimated at approximately 70% and even at 5 years after liver transplantation, it is 20%. Therefore, improving survival outcomes after curative surgi-cal resection of liver cancer is crucial. This review highlights the importance of identifying risk factors for HCC recurrence following radical surgical resection and adjuvant therapy options that may reduce the recurrence risk and improve overall survival, including local adjuvant therapy (e.g., transcatheter arterial chemoembolization and radiotherapy), adjuvant systemic therapy (e.g., small molecule targeted therapy and immunotherapy), and other adjuvant therapies (e.g., chem-otherapy). However, further research is needed to refine the use of these therapies and optimize their effectiveness in preventing HCC recurrence.

This paper designed a new type of generator, transgenerator, that integrates the wind turbine and flywheel into one system, aiming to make the flywheel distributed energy storage (FDES) more modular and scalable than the conventional FDES. The transgenerator is a three-member dual-mechanical-port (DMP) machine with two rotating members (inner and outer rotors) and one stationary member (stator). The transgenerator-flywheel system is introduced with the system configuration, transgenerator overview, flywheel operation principle and power management strategies, and control system. Simulations are performed in MATLAB/ Simulink to verify the system viability, including control system verification and the flywheel storage performance evaluation. Results show that the inner and outer rotors can be controlled independently with accurate and fast control response, and the grid-side control works properly. The flywheel performs well with considerable charging power and storage capacity.

In recent years, with the increasing research and development of the LED industry which contains GaN, it is expected that there will be a large amount of related wastes in the future. Especially the gallium has extremely high value of economic, therefore, it is necessary to establish the recycling system of the GaN waste. However, GaN is a direct-gap semiconductor and with high energy gap, high hardness, and high melting point make it difficult to recycle. Therefore, this study will analyze the physical characteristics of LED wastes containing GaN and carry out various leaching method to leach the valuable metals from the waste optimally. Different acids are used to find out the best reagent for leaching the gallium. Different experimental parameters are discussed such as the effect of the different acid agents , concentration, pressure, solid-liquid mass ratio, temperature, and time which influence the leaching efficiency of the gallium. In this study, various leaching methods which effect the leaching efficiency of the gallium are compared and the advantages and disadvantages are discussed. Finally, pressurized acid leaching method is preferred to leach the GaN waste, and hydrochloric acid is used as the leaching solution because of its better leaching efficiency of gallium. Eventually, the leaching efficiency of the gallium can reach to 98%.

In this study, the resource blocks (RB) are allocated to user equipment (UE) according to the evolutional algorithms for long term evolution (LTE) systems. Particle Swarm Optimization (PSO) algorithm is one of the evolutionary algorithms, based on the imitation of a flock of birds foraging behavior through learning and grouping the best experience. In previous work, the Simple Particle Swarm Optimization (SPSO) algorithm was proposed for RB allocation to enhance the throughput of Device-to-Device (D2D) communications and improve the system capacity performance. In simulation results, with less population size of M = 10, the SPSO can perform quickly convergence to sub-optimal solution in the 100^th generation and obtained sub-optimum performance with more 2 UEs than the Rand method. Genetic algorithm (GA) is one of the evolutionary algorithms, based on Darwinian models of natural selection and evolution. Therefore, we further proposed a Refined PSO (RPSO) and a novel GA to enhance the throughput of UEs and to improve the system capacity performance. Simulation results show that the proposed GA with 100 populations, in 200 generations can converge to suboptimal solutions. Therefore, with comparing with the SPSO algorithm the proposed GA and RPSO can improve system capacity performance with 1.8 and 0.4 UEs, respectively.

Inflammasomes are multiprotein complexes that activate inflammatory responses by inducing pyroptosis and secretion of pro-inflammatory cytokines. Along with many previous studies on inflammatory responses and diseases induced by canonical inflammasomes, an increasing number of studies have demonstrated that non-canonical inflammasomes, such as mouse caspase-11 and human caspase-4 inflammasomes, are emerging key players in inflammatory responses and various diseases. Flavonoids are natural bioactive compounds found in plants, fruits, vegetables, and teas and have pharmacological properties in a wide range of human diseases. Many studies have successfully demonstrated that flavonoids play an anti-inflammatory role and ameliorate many inflammatory diseases by inhibiting canonical inflammasomes. Others have demonstrated the anti-inflammatory roles of flavonoids in inflammatory responses and various diseases, with a new mechanism by which flavonoids inhibit non-canonical inflammasomes. This review discusses recent studies that have investigated the anti-inflammatory roles and pharmacological properties of flavonoids in inflammatory responses and diseases induced by non-canonical inflammasomes and further provides insight into developing flavonoid-based therapeutics as potential nutraceuticals against human inflammatory diseases.

Precipitation downscaling is widely employed for enhancing the resolution and accuracy of precipitation products from general circulation models (GCMs). In this study, we propose a novel statistical downscaling method to foster GCMs’ precipitation prediction resolution and accuracy for monsoon region. We develop a deep neural network composed of convolution and Long Short Term Memory (LSTM) recurrent module to estimate precipitation based on well-resolved atmospheric dynamical fields. The proposed model is compared against GCM precipitation product and classical downscaling methods in the Xiangjiang River Basin in South China. Results show considerable improvement compared to the ECMWF-Interim reanalysis precipitation. Also, the model outperforms benchmark downscaling approaches, including 1) quantile mapping, 2) support vector machine, and 3) convolutional neural network. To test the robustness of the model and its applicability in practical forecast, we apply the trained network for precipitation prediction forced by retrospective forecasts from ECMWF model. Compared to ECMWF precipitation forecast, our model makes better use of the resolved dynamical field for more accurate precipitation prediction at lead time from 1 day up to 2 weeks. This superiority decreases along forecast lead time, as GCM’s skill in predicting atmospheric dynamics being diminished by the chaotic effect. At last, we build a distributed hydrological model and force it with different sources of precipitation inputs. Hydrological simulation forced with the neural network precipitation estimation shows significant advantage over simulation forced with the original ERA-Interim precipitation (with NSE value increases from 0.06 to 0.64), and the performance is just slightly worse than the observed precipitation forced simulation (NSE=0.82). This further proves the value of the proposed downscaling method, and suggests its potential for hydrological forecasts.

Health issues of children with intellectual disabilities (ID) have gained significant attention as a key focus of China health goals. This study aimed to compare the differences in displacement skills and problem behaviors among children with varying degrees and types of ID, while also exploring their relationship. The study included 90 participants who were children with ID and had completed TGMD-2 displacement skills and Strengths and Difficulties Questionnaire (SDQ) assessments. Covariance, partial correlation, and multiple linear regression analyses were conducted to examine the differences and correlations between these factors. The findings revealed that higher severity of intellectual disability was associated with lower scores in locomotor skills and increased manifestation of problem behaviors. Notably, there were significant variations in locomotor skills and problem behaviors among children with different types of intellectual disabilities. There is a positive correlation between locomotor skills and problem behaviors in children with intellectual disabilities, where locomotor skills can predict the occurrence of problem behaviors. In Conclusion, the research confirms that the development of locomotor skills can have a positive impact on the accompanying problem behaviors of children with developmental disabilities.

Accurate and reliable mid-long runoff prediction (MLTRP) is of great importance in water re-sources management. However the MLTRP is not suitable in each basin and how to evaluate the applicability of MLTRP is still a question. Therefore, the total mutual information (TMI) index is developed in this study based on the predictor selection method using mutual information (MI) and partial MI (PMI). The relationship between the TMI and the predictive performance of five models is analyzed by applying five models in 222 forecasting scenarios in Australia. The results over 222 forecasting scenarios demonstrate that, compared with the MI, the developed TMI index can better represent the available information in the predictors, and has more significant negative correlation with the RRMSE with the correlation coefficient between -0.62 and -0.85. This means the model's predictive performance will become better along with the increase of TMI, and there-fore the developed TMI index can be used to evaluate the applicability of MLTRP. When TMI is more than 0.1, the available information in the predictors can support the construction of MLTRP models. In addition, the TMI is used to partly explain the difference of predictive performance among five models. In general, the complex models, which can better utilize the contained infor-mation, are more sensitive to the TMI, and have more significant improvement in terms of predic-tive performance along with the increase of TMI. This research can provide support for the study of MLTRP.

People with aphantasia exhibit the inability to voluntarily generate or form mental imagery in their minds. Since the term “aphantasia” was proposed by Zeman et al. in 2015 to describe this, it has gained increasing attention from psychiatrists, neuroscientists, and clinicians. Previous studies have mainly focused on definition, prevalence, and measurement, its impacts on individuals’ cognitive and emotional processing, and theoretical frameworks synthesizing existing findings, which have contributed greatly to our understanding of aphantasia. However, there are still some debates regarding the conclusions derived from existing research and the theories that were constructed from various sources of evidence. Building upon existing endeavors, the current systematic review emphasizes that future research is much needed to refine definition and diagnosis of aphantasia, strengthen empirical investigations at behavioral and neural levels, and more importantly, develop or update theories. These multiple lines of efforts could lead to a deeper understanding of aphantasia and further guide researchers in future research directions.

In autonomous driving systems, high-speed and real-time image processing, along with object recognition, are crucial technologies. This paper builds upon the research achievements in in-dustrial item sorting systems and proposes an object recognition and sorting system for auton-omous driving. In industrial sorting lines, goods sorting robots often need to work at high speeds to efficiently sort large volumes of items. This poses a challenge to the robot's real-time vision and sorting capabilities, making it both practical and economically viable to implement a real-time and low-cost sorting system in a real-world industrial sorting line. Existing sorting systems have limitations such as high cost, high computing resource consumption, and high power consump-tion. These issues lead to the fact that existing sorting systems are typically used only in large industrial plants. In this paper, we design a high-speed, low-cost, low-resource-consumption FPGA (Field-Programmable Gate Array) based item sorting system that achieves similar perfor-mance to current mainstream sorting systems at a lower cost and consumption than existing sorting systems. The recognition part employs a morphological recognition method, which segments the image using a frame difference algorithm and then extracts the color and shape features of the items. To handle sorting, a six-degree-of-freedom robotic arm is introduced in the sorting segment. The improved cubic B-spline interpolation algorithm is employed to plan the motion trajectory and consequently control the robotic arm to execute the corresponding actions. Through a series of experiments, this system achieves an average recognition delay of 25.26ms, ensures smooth operation of the gripping motion trajectory, minimizes resource consumption, and reduces implementation costs.

Metabolic disorders have become among the most serious threats to human health, leading to severe chronic diseases such as obesity, type 2 diabetes, non-alcoholic fatty liver disease, as well as cardiovascular diseases. Interestingly, despite the fact that each of these maladies has different physiological and clinical symptoms, they appear to share certain pathological traits such as intracellular stress and inflammation induced by metabolic derangements stemmed from over nutrition frequently aggravated by modern sedentary life style. These modern ways of living inundate cells and organs with saturating levels of sugar and fat, leading to glycotoxicity and lipotoxicity that induce intracellular stress signaling ranging from oxidative to ER stress response to cope with the metabolic insults [1]. In this review, we discuss the roles played by cellular stress and its responses in shaping metabolic disorders. We have summarized here current mechanistic insights explaining the pathogenesis of these disorders. These are followed by a discussion of the latest therapies targeting the stress response pathways.

In recent decades, with the ever-growing scale of video data, near-duplicate videos continue to emerge. Data quality issue caused by near-duplicate videos is becoming more and more prominent, which has affected the application of normal videos. Although current studies on near-duplicate video detection can be helpful to uncover data quality issues for videos, they still lack a process of automatic merging for the video data represented by high-dimensional features, which are difficult to automatically clean the near-duplicate videos to improve data quality for video datasets. At present, there are few studies on near-duplicate video data cleaning. The existing studies have the sensitive problems of video data orderliness and clustering initial center under a condition that prior distribution is unknown, which seriously affect the accuracy of near-duplicate video data cleaning. To address the above issues, an automatic near-duplicate video data cleaning method based on a consistent feature hash ring is proposed in this paper. First, a residual network with convolutional block attention modules, a long short-term memory deep network, and an attention model are integrated to construct an RCLA deep network with the multi-headed attention mechanism to extract spatiotemporal features of video data. Then, a consistent feature hash ring is constructed, which can effectively alleviate the sensitivity of video data orderliness while providing a condition of near-duplicate video merging. To reduce the sensitivity of the initial cluster centers to results of near-duplicate video cleansing, an optimized feature distance-means clustering algorithm is constructed by utilizing a mountain peak function on a consistent feature hash ring, which can implement automatic cleaning of near-duplicate video data. Finally, experiments are conducted based on a commonly used dataset named CC_WEB_VIDEO and a coal mining video dataset. Compared with some existing works, simulation results demonstrate that the performance of the proposed method.

Amid the swift progression of the global automobile industry, the aspiration for lightweight vehicle design has surfaced as a crucial approach to boost fuel efficiency and curtail environmental impact. The objective of this study revolves around achieving holistic optimization of vehicle structure via detailed scrutiny of vehicle process characteristics, amalgamated with a Back Propagation neural network (BPNN) optimized by a genetic algorithm (GA) and a topology optimization (TO) method.The process initiates with an examination of the vehicle's technical characteristics, succeeded by an optimization protocol that couples GA with BPNN. This exhaustive optimization procedure derives the best-fit values of design parameters and identifies the globally optimal lightweight design approach. Subsequently, a comprehensive structural optimization is actualized by modifying the topological distribution of the structure.A simulation experiment of the conceptual car body beam skeleton is conducted as a conclusive step, and the anti-collision capacity of the car body beam skeleton is assessed by measuring deformation intrusion. The findings reveal that in the vehicle topology optimization, a comparative analysis of pre and post-optimization results indicates an improved topological density across diverse sections. The topological density of the vehicle's frontal structure escalates from 0.75 to 0.8. Following optimization, the stiffness assessment records a marginal increase (within the range of 0.02–0.05), implying that the lightweight design does not compromise the general rigidity of the structure.The optimized body structure manifests superior crashworthiness in the crash test: the deformation intrusion diminishes by 27% in front-end collisions. In side impacts, the deformation and intrusion at critical points are reduced by 13.15% to 10% respectively. The comprehensive method proposed herein proves to be an efficient strategy to actualize the lightweight design of vehicles.

In coastal areas around the world, seagrass meadows play a crucial ecological and economic role. A large amount of seagrass beds dominates primary production and contributes to the high secondary productivity of this ecosystem. The microbial loop (consuming bacterial biomass by grazers and using seagrass-derived detritus by bacteria) may be an important mechanism for transferring seagrass-derived organic matter to the aquatic food chain. This study aims to improve our understanding of how bacterial growth and mortality (grazing and viral lysis rates) differ in seagrass and adjacent unvegetated meadow habitats. We found that viral lysis and grazing caused similar mortality rates of bacteria in a seagrass environment during the summer. It has been found, however, that bacterial production is controlled by the availability of resources (bottom-up control) and is cycled within the bacteria-virus-DOC loop in adjacent unvegetated waters. Our study region may be affected by this shift in organic matter fate and cycling.

Much has been explored in the individual health issue, and most of them adopt the objective data such as laboratory tests or health services utilization to analyze individual health assessment. However, the factors influencing individuals in self‐assessed health is still unclean. The study considers that self‐assessed health is viewed as catalyst in health management and explores various dimensions associated with self‐assessed health. Totally, 800 participants who were randomly sampled from the citizen of Porter County, Indiana completed the Needs Assessment Citizen Survey in 2007.After adjustment for age, gender, education, income, and health coverage, life quality (β=1.5538, sdandard erro of β=0.8404), and Medicaid assistance (β= -0.7715, sdandard erro of β= 0.3958) are the main determinants of individuals’ self‐assessed health. The results suggest that public health officials should consider improving citizens’ self-assessed health by providing good living and socio-economic environment.

In this study, we test the performance of a compact gas chromatograph with photoionization detector (GC-PID) and optimize the configuration to detect ambient (sub-ppb) levels of benzene, toluene, ethylbenzene, and xylene isomers (BTEX). The GC-PID system was designed to serve as a relatively inexpensive (~$10k) and field-deployable air toxic screening tool alternative to conventional benchtop GCs. The instrument uses ambient air as a carrier gas, and consists of a Tenax-GR trap preconcentrator, a gas sample valve, two capillary columns, and a photoionization detector (PID) with a small footprint and low power requirement. The performance of the GC-PID has been evaluated in terms of system linearity and sensitivity in field conditions. The BTEX-GC system demonstrated the capacity to detect BTEX at levels as high as 500 ppb with a linear calibration range of 0-100 ppb. A detection limit lower than 1 ppb was found for all BTEX compounds with a sampling volume of 1 L. No significant drift in the instrument was observed. A time-varying calibration technique was established that requires minimal equipment for field operations and optimizes the sampling procedure for field measurements. With an analysis time of less than 15 minutes, the compact GC-PID is ideal for field deployment of background and polluted atmospheres for near-real time measurements of BTEX. The results highlight the application of the compact and portable GC-PID for community monitoring and screening of air toxics.

Dysregulation of cartilage homeostasis and the changes in the density and the architecture of the subchondral bone were postulated as a potent mechanically pathological activity contributing to osteoarthritis (OA) pathogenesis. Extracorporeal shockwave therapy (ESWT) is a new, none invasive and effective method in the treatment of animal OA model. In the current study, we demonstrated that shockwave induced the expression of protein-disulfide isomerase-associated 3 (Pdia-3) which is a multifunctional protein hypothesized to be a significant mediator for 1α,25-Dihydroxyvitamin D3 (1α,25(OH)₂D₃) signaling pathway using two-dimensional electrophoresis. Histological analysis and quantitative polymerase chain reaction (qPCR) were verified and observed that the expression of Pdia-3 at 2 weeks was significantly higher than that of any other group at 4 weeks, 8 weeks, and 12 weeks post-shockwave treatment in early OA knee of rat. The other factors of the 1α,25(OH)₂D₃ rapid membrane signaling pathway including extracellular signal-regulated protein kinases 1 (ERK1), osteopontin (OPG), alkaline phosphatase (ALP), and matrix metallopeptidase 13 (MMP13) were measured and significantly increased by qPCR at 2 weeks post-shockwave treatment in early OA knee. Our proteomic data revealed significant Pdia-3 expression in microenvironments of joint tissue that could be actively responded to ESWT, which may potentially regulate biological function of chondrocytes and osteoblasts in the treatment of OA knee.

The pursuit of materials that offer both wear comfort and protection for functional and protective clothing has led to the exploration of weft-knitted spacer structures. Traditional cushioning materials such as spacer fabrics and laminated foam often suffer from deformation under compression stresses, thus compromising their protective properties. This study investigates the enhancement of the force absorption, stress-strain and thermal properties of weft-knitted spacer fabrics with inlays. Surface yarns with optimal stretchability and thermal properties are used and combined with elastic yarns in various patterns to fabricate nine different inlay samples. The mechanical and thermal properties of these samples are systematically analyzed, including their compression, stretchability, thermal comfort and surface properties. The results show that the inlay spacer fabric exhibits superior compression properties and thermal conductivity compared to traditional laminated foam and spacer fabrics, while maintaining stretchability, thus providing a better performance than traditional fabrics for protective clothing and wearable cushioning products. This study further confirms that the type of inlay yarn and inlay structure are crucial factors that significantly influence the thermal, tensile and compressive properties of fabric. This research provides valuable insights into the design and development of advanced textile structures to improve wear comfort and protection in functional garment applications.

Water quality forecasting is increasingly significant for agricultural management and environmental protection. Enormous amounts of water quality data are increasingly being collected by advanced sensors, which leads to an interest in using data-driven models for predicting trends in water quality. However, the unpredictable background noises introduced during water quality monitoring seriously degrade the performance of those models. Meanwhile, artificial neural networks (ANN) with feed-forward architecture lack the capability of maintaining and utilizing the accumulated temporal information, which leads to biased predictions in processing time series data. Hence, we propose a water quality predictive model based on a combination of Kernal Principal Component Analysis (kPCA) and Recurrent Neural Network (RNN) to forecast the trend of dissolved oxygen. Water quality variables are reconstructed based on kPCA method, which aims to reduce the noise from the raw sensory data and preserve actionable information. With the RNN's recurrent connections, our model can make use of the previous information in predicting the trend in the future. Data collected from Burnett River, Australia was applied to evaluate our kPCA-RNN model. The kPCA-RNN model achieved R2 scores up to 0.908, 0.823 and 0.671 for predicting the concentration of dissolved oxygen in the upcoming 1, 2 and 3 hours, respectively. Compared to current data-driven methods like ANN and SVR, the predictive accuracy of the kPCA-RNN model was at least 8 %, 17 % and 21 % better than the comparative models in these 3 cases. The study demonstrates the effectiveness of the kPAC-RNN modeling technique in predicting water quality variables with noisy sensory data.

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

Federated learning trains a neural network model using the client's data to maintain the benefits of centralized model training, while maintaining the privacy. However, if the client data are not independently and identically distributed (non-IID) because of different environments, the accuracy of the model may suffer from client drift during training owing to discrepancies in each client's data. This study proposes a personalized federated learning algorithm based on the concept of multitask learning to divide each client model into two layers: a feature extraction layer and a category prediction layer. The feature extraction layer maps the input data to a low-dimensional feature vector space. Furthermore, the parameters of the neural network are aggregated with those of other clients using an adaptive method. The category prediction layer maps low-dimensional feature vectors to the label sample space, with its parameters remaining unaffected by other clients to maintain client uniqueness. The proposed personalized federated learning method produces faster learning model convergence rates and higher accuracy rates for the non-IID datasets in our experiments.

Multi-chiplet technique is expected to be a promising solution to achieve high-density system integration with low power consumption and high usage ratio. This technique can be integrated with glass interposer to accomplish a competitive low fabrication cost compared with the silicon-based interposer architecture. In this study, process-oriented stress simulation is performed by the element activation and de activation technique in finite element analysis architecture. Submodeling technique is also utilized to mainly conquer the scale mismatch and difficulty in mesh gridding design. It is used as well to analyze the thermomechanical responses of glass interposer with chiplet arrangement and capped epoxy molding compound (EMC) during curing. A three-factor, three-level full factorial design is applied using the analysis of variance method to explore the significance of various structural design parameters on stress generation. Analytic results reveal that the maximum first principal stresses of 130.75 and 17.18 MPa are introduced on the sidewall of Cu-filled via and the bottom of glass interposer, respectively. Moreover, the EMC thickness and through glass via pitch are the dominant factors in the adopted vehicle. They significantly influence the stress magnitude during heating and cooling.

The study provides a comprehensive and detailed analysis of the existing key policies and considerations in Taiwan's Other Effective Area-Based Conservation Measures (OECMs), with the objective of providing useful evidence-based insights for formulating new effective environmental-friendly policies and promoting the existing policies. The study adopts a mixed research methodology that entails the combination of qualitative and quantitative research methodological frameworks. The primary source of the quantitative data for the study is the World Database on Protected Areas (WDPA) which provides variable data on OECMs and a component of databases of the Protected Planet Initiative (PPI) which is the joint product of UNEP and IUCN, managed by UNEP-WCMC and the IUCN working with governments, communities and collaborating partners. The qualitative methodological framework for the research adopted a technical systematic review approach based on the three-step framework for systematic reviews that involved planning, conducting and reporting the review. The review was based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The sources that were included in the review included scientific research materials that focused on the policies related to OECMs. Taiwan has a total of 92 individual areas that are designated as national protected areas (PAs) and OECMs and formally recognized by the World Database on Protected Areas (WDPA). Out of the 92 designated areas, only seven are managed by the Construction and Planning Agency while the remaining 85 areas are managed by the Forestry Bureau. In terms of designation, 37 areas are designated as major wildlife habitats, 21 areas are designated as nature reserves, 20 areas are designated as wildlife refuges, eight areas are designated as national parks and six areas are designated as forest reserves. The primary themes that were identified were associated with marine spatial planning, environmental impact assessment (EIA) and marine scientific research and included biodiversity, protected area consideration, geographically defined areas, coastal resources and marine ecosystems. Other Effective Area-Based Conservation Measures (OECMs) have not been widely implemented yet, but most countries, including Taiwan, are increasingly aligning their existing policies with the strategies outlined in the OECMs policies to achieve large area-based conservation targets and reduce biodiversity loss.