Previous studies to recognize negative emotions (e.g. disgust, fear, sadness) for mental health care have used heavy equipment directly attaching electroencephalogram (EEG) electrodes to the head, making it difficult to use in daily life, and they have proposed binary classification methods to determine whether negative emotion or not. To tackle this problem, we propose a negative emotion recognition system to collect multimodal biosignal data such as five EEG signals in an EEG headset and heart rate, galvanic skin response, and skin temperature in a smart band for classifying multiple negative emotions. It consists of android Internet of Things (IoT) application, an oneM2M-compliant IoT server, and a machine learning server. The android IoT application upload the biosignal data to the IoT server. By using the biosignal data stored in the IoT server, the machine learning server recognizes the negative emotions of disgust, fear, and sadness using a multi-class support vector machine (SVM) model with a radial basis function kernel (RBF). The experimental results showed that the multi-class SVM model achieved 93% accuracy when considering all the multimodal biosignal data. Moreover, when considering only data in the smart band, it could achieve 98% accuracy by optimizing the hyper-parameter of the RBF kernel.

Background The prognostic value of estimated pulse wave velocity (ePWV) has been infrequently explored in high-risk patient groups. Our study aimed to evaluate the prognostic significance of ePWV among patients undergoing percutaneous coronary intervention (PCI) with drug-eluting stent (DES). Methods A total of 4,119 consecutive subjects who underwent PCI with DES (mean age, 67.1 ± 11.6 years and 33.1% were female) were retrospectively analyzed. ePWV was calculated based on the patient’s age and mean blood pressure. Major adverse cardiovascular event (MACE), including cardiac death, non-fatal myocardial infarction, coronary revascularization, and ischemic stroke, were evaluated. Reults During a median follow-up duration of 3.51 years (interquartile range, 1.35 ~ 6.37 years), there were 746 MACE (18.1%). Multivariable analysis showed that higher ePWV was associated with higher MACE incidence (middle tertile vs. the lowest tertile: hazard ratio [HR], 2.49; 95% confidence interval [CI], 1.81-3.42; P < 0.001; the highest tertile vs. the lowest tertile: HR, 6.18; 95% CI, 4.33-8.80; P < 0.001) The inclusion of ePWV data significantly increased the global chi-square values when added to the clinical information (from 96 to 128; P < 0.001). Conclusion ePWV demonstrated a significant association with MACE in patients who underwent DES implantation. Given its relative simplicity to calculate, ePWV could potentially serve as a valuable instrument for stratifying cardiovascular risk within this high-risk patient population.

This paper presents a study on the thermal efficiency improvement of the user equipment room in the district heating system based on reinforcement learning [1], and suggests a general method of constructing a learning network(DQN)[2] using deep Q learning[3], which is a reinforcement learning algorithm that does not specify a model. In addition, we introduce the big data platform system and the integrated heat management system for the energy field in the massive data processing from the IoT sensor installed in large number of thermal energy control facilities.

In a power plant that uses seawater as a coolant, a debris filter is required to remove foreign substances from the seawater, and differential pressure leads to a decrease in the coolant flow rate, leading to a decrease in power generation efficiency. In this study, analysis was performed under different initial flow velocity conditions of 1.5m/s, 2.0m/s, and 2.5m/s for a debris filter used in a power plant to understand flow characteristics in CTCS. The flow and differential pressure characteristics of a CTCS with an installed debris filter were considered in a comparative analysis of velocity, pressure, and turbulent kinetic energy distribution. The results confirmed that a vortex was generated in the pipe with the debris filter, apparently due to the collision of the flow with the bracket of the debris filter. As the flow rate increased, the range of the vortex increased, causing a loss in flow.

Hashimoto’s thyroiditis (HT) is a common autoimmune disease, with its prevalence rapidly increasing. Both genetic and environmental risk factors contribute to the development of HT. Recently, viral infection has been suggested to act as a trigger of HT by eliciting the host immune response and subsequent autoreactivity. We analyzed features of HT through bioinformatics analysis so as to identify markers of HT development. We accessed public microarray data of HT patients from the Gene Expression Omnibus (GEO) and obtained differentially expressed genes (DEGs) under HT. Gene Ontology (GO) and KEGG pathway enrichment analyses were performed for functional clustering of our protein-protein interaction (PPI) network. Utilizing ranked gene lists, we performed Gene Set Enrichment Analysis (GSEA) using the clusterprofiler R package. By comparing the expression signatures of the huge perturbation database with the queried rank-ordered gene list, connectivity map (CMap) analysis was performed to screen potential therapeutic targets and agents. The gene expression profile of the HT group was in line with general characteristics of HT. Biological processes related to the immune response and viral infection pathways were obtained for the upregulated DEGs. GSEA results revealed activation of autoimmune disease-related pathways and several viral infection pathways. Autoimmune disease and viral infection pathways were highly interconnected by common genes, while the HLA genes which are shared by both were significantly upregulated. CMap analysis suggested that perturbagens, including SRRM1, NLK, and CCDC92, have the potential to reverse the HT expression profile. Several lines of evidence suggested that viral infection and the host immune response are activated during HT. Viral infection is suspected to act as a key trigger of HT by causing autoimmunity. SRRM1, an alternative splicing factor, which responds to viral activity, might serve as potential marker of HT.

Among the electrochemical energy storage (EES) technologies, rechargeable batteries (RBs) and supercapacitors (SCs) are the two most desired candidates for powering a range of electrical and electronic devices. The RB operates on Faradaic processes, whereas the underlying mechanisms of the SC vary as non-Faradaic in the electrical double layer capacitors (EDLCs), Faradaic at the surface of the electrodes in the pseudo capacitors (PCs), and a combination of both non-Faradaic and Faradaic in the hybrid capacitors. The EDLCs offer high power density but low energy density. The hybrid capacitors take advantage of the Faradaic process without compromising their capacitive nature. Unlike batteries, supercapacitors provide high power density and numerous charge-discharge cycles; however, their energy density lags that of batteries. Here, we review recently published critically selected articles on supercapatteries, a generic term that refers to EES devices that can combine the merits of EDLCs and RBs. Also discussed are the properties, design strategies, and future perspectives of supercapatteries.

Recently, cobalt iron boron (CoFeB) thin films have been widely investigated to apply to magnetic sensors, due to their high magnetic moment, anisotropy, and stability. However, most of these studies are conducted on rigid silicon substrates. For more diverse applications of magnetic sensors and angle sensors, it is important to explore the properties of ferromagnetic thin films grown on non-rigid deformable substrates. Here, using representative deformable substrates such as polyimide (PI), polyethylene naphthalate (PEN) and polydimethylsiloxane (PDMS) that can be bent or stretched, we report experimental comparison of in-plane magnetic field angle-dependent properties of the amorphous Ta/CoFeB/MgO/Ta thin film which is grown on those deformable substrates. We investigate effects of substrate roughness, tensile stress, characteristics of deformable substrates, and sputtering process on the change of magnetic properties like coercive field (Hc), remanence over saturation magnetization (Mr/Ms), and their biaxial characteristics. This work presents unconventional foundations for exploring deformable magnetic sensors capable of detecting magnetic field angle.

This study investigated mortality discrepancies in Korea, 2000-2020, with a focus on age, gender, and preventable causes of death, and their impact on life expectancy at birth. The study utilized data from Korean Standard Classification of Diseases and OECD/Eurostat lists of preventable and treatable causes of death and employed Arriaga's method. Noteworthy findings revealed gender disparities in life expectancy increases, with male gaining an advantage over females from 2000-2020 (8.142 years for males versus 6.806 years for females). The most significant increase in life expectancy was found to be in males aged 70-74 and females aged 75-79. The gender gap in LEB is narrowing and that the main age group contributing to the gender gap are getting older. Reduced gains in life expectancy at birth resulted from avoidable mortality, contributing 57.3% to the increase. Cerebrovascular disease and transport accidents were positive contributors, whereas suicide and certain cancers were negative contributors. The changes in mortality for individuals aged 65 and over had an impact of 45.44% (males) and 71.01% (females) on life expectancy gains. This study offers a novel approach in evaluating avoidable mortality and life expectancy, having the potential to improve international health indicators and inform health policies.

Alginate, a biopolymer promising in food, biomedical, pharmaceutical, and electronic materials industries, is characterized by its biodegradability, biocompatibility, low toxicity, and gel-forming properties. It is most abundantly found in brown algae. However, conventional dilute acid and alkali extraction methods face limitations in commercialization due to their long processing time, low throughput, and high solvent requirements. In this study, a microwave-assisted extraction (MAE) process for sodium alginate was designed to improve extraction efficiency. Solid/liquid ratio, extraction temperature, and extraction solvent concentration were major variables affecting sodium alginate extraction from Undaria pinnatifida(sea mustard). They were then statistically optimized using response surface methodology. Under optimal conditions (13.27 g/L, 91.86 ℃, 2.51 %(w/v), and 15 min), the yield was 38.41 %, which was 93.43 % of the theoretical content of sodium alginate in Undaria pinnatifida. Our work has confirmed the productivity and industrial feasibility of efficient extraction of sodium alginate from marine biomass, and we hope that it will serve as an encouraging case for the application of biopolymers as one of the desirable options for alternative petrochemicals to construct a sustainable society.

Microbial production is a promising method that can overcome major limitations in conventional methods of lycopene production, such as low yields and variations in product quality. Significant efforts have been made to improve lycopene production by engineering either the 2-C-methyl-D-erythritol 4-phosphate (MEP) pathway or mevalonate (MVA) pathway in microorganisms. To further improve lycopene production, it is critical to utilize metabolic enzymes with high specific activities. Two enzymes, 1-deoxy-D-xylulose-5-phosphate synthase (Dxs) and farnesyl diphosphate synthase (IspA), are required in lycopene production using MEP pathway. Here, we evaluated the activities of Dxs and IspA of Vibrio sp. dhg, a newly isolated and fast-growing microorganism. Considering that the MEP pathway is closely related to the cell membrane and electron transport chain, the activities of the two enzymes of Vibrio sp. dhg were expected to be higher than the enzymes of E. coli. We found that Dxs and IspA in Vibrio sp. dhg exhibited 1.08-fold and 1.38-fold higher catalytic efficiencies, respectively. Consequently, the heterologous overexpression improved the specific lycopene production by 1.88-fold. Our findings could be widely utilized to enhance production of lycopene and other carotenoids.

Background/Aims: Conflicting results have been reported regarding the interaction between proton pump inhibitors (PPIs) and clopidogrel. We investigated whether concomitant PPI use influenced the risk of recurrence in patients with stroke and myocardial infarction (MI). Methods: This study used two databases for different designs, the Korean National Health Insurance Service (NHIS) database for a self-controlled case series design, and the national sample cohort of the NHIS database converted to the Observational Medical Outcomes Partnership-Common Data Model version for a cohort study. Results: In the PPI co-prescription group, recurrent hospitalization with stroke occurred in 17.6% of the 8,201 patients with history of stroke, and recurrent MI occurred in 17.1% of the 1,216 patients with history of MI during 1 year. According to the self-controlled case series, the overall relative risk (RR) of recurrent stroke was 2.09 [95% confidence interval (CI); 1.83-2.38], and the RR showed an increasing trend with PPI duration. In the cohort study, there was a higher incidence of recurrent stroke in the PPI co-prescription group [Hazard ratio (HR): 1.34, 95% CI: 1.01-1.76, P=0.04]. The overall RR of recurrent MI was 1.47 (95% CI; 1.02-2.11) in the self-controlled case series; however, there was no statistically significant difference in recurrent MI in the cohort study (HR:1.42, 95% CI:0.79-2.49, P=0.23). The impact of individual PPIs on stroke and MI showed different patterns. Conclusions: PPI co-prescription with clopidogrel was associated with recurrent stroke; however, its association with recurrent MI remains inconclusive. The influence of individual PPIs should be clarified in the future.

Recently, “mature” silkworms (MS) of Bombix mori have been considered as a potential nutraceutical, with a number of health benefits reported for steamed and lyophilized MS powder (SMSP). However, no obesity-related effects have been reported for SMSP. In the present study, anti-obesity effects of SMSP were investigated in adult mice in vivo, aged 12 weeks at the onset of drug administration, fed normal diet (ND) and high-fat diet (HFD), respectively, for 12 weeks. SMSP significantly suppressed body weight gain, intra-abdominal adipose tissue, and food efficiency in both ND-fed and HFD-fed adult mice. In addition, SMSP significantly decreased food intake and liver weight in HFD-fed mice, indicating that SMSP suppressed appetite and simultaneously reduced the conversion of feed into body weight in HFD-fed mice. SMSP also significantly lowered serum levels of glucose, triglyceride, total cholesterol, low-density lipoprotein cholesterol, asparagine transaminase, alanine transaminase, and alkaline phosphatase. However, SMSP had no significant effect on the weights of kidney, spleen, and thymus and serum levels of blood urea nitrogen and creatinine. Taken together, the above results suggest that SMSP has potent anti-obesity effects and is safe for long-term use as a potential therapeutic and/or nutraceutical in both obese patients and non-obese individuals.

Excessive alcohol consumption is one of the significant causes of morbidity and mortality worldwide. Alcohol is oxidized to toxic and carcinogenic acetaldehyde by alcohol dehydrogenase (ADH) and further oxidized to a non-toxic acetate by aldehyde dehydrogenase (ALDH). Emerging evidence shows that Lactobacillus and Bifidobacterium species encode alcohol dehydrogenase (ADH) and acetaldehyde dehydrogenase (ALDH) mediate alcohol and acetaldehyde metabolism, respectively. This study involves supplementation of Lactobacillus and Bifidobacterium probiotic mixture in humans and assessed their effects on alcohol and acetaldehyde metabolism. Here, twenty-seven wild types (ALDH2*1/*1) and the same number ofheterozygotes (ALDH2*2/*1) were recruited for the study. The enrolled participants were randomly divided into either the probiotic (Duolac ProAP4) or the placebo group. Each group received a probiotic or placebo capsule for 15 days with subsequent crossover. Primary outcomes were measurement of alcohol and acetaldehyde in the blood after the alcohol intake. Blood levels of alcohol and acetaldehyde in the ALDH2 heterozygote group were significantly downregulated in the probiotic-supplemented group with no changes in hangover score symptoms than the placebo group. No clinically significant changes were observed in safety parameters. These results suggest that probiotic has a potential to downregulate the alcohol and acetaldehyde concentrations, and their effects depend on the presence or absence of polymorphism on the ALDH2 gene.

A fern, Polypodium aureum, possesses a specialized spore-releasing mechanism like a catapult induced by quick expansion of vaporized bubbles. This study introduces lipid-coated perfluorocarbon droplets to enable repeatable vaporization-condensation cycles, inspired by the repeatable vaporization of Polypodium aureum. Lipid-perfluorocarbon droplets have been considered not to exhibit repeatable oscillations due to bubble collapse by low surface tension of lipid layers. However, a single lipid-dodecafluoropentane droplet with a diameter of 9.17 µm shows expansion-contraction oscillations over 4,000 cycles by changing lipid composition and applying low power of 1.7 MHz ultrasound to induce partial vaporization of droplets. The optimal combinations of shell composition, droplet fabrication, and acoustic conditions can minimize damage on shell structure and quick recovery of damaged shell layers. The highly-expanding oscillatory microbubbles provide a new direction for fuel-free micro or nanobots as well as biomedical applications of contrast agents and drug delivery.

In this study, we propose a solution process for realizing color glass for building integrated pho-tovoltaic (BIPV) systems by spin coating a color solution composed of a pearlescent pigment mixed in a norland optical adhesive (NOA) matrix. Color solutions are made from mixing pearlescent pigments in NOA63. Compared to a physical vapor deposition process, color coatings are achieved by spin coating in a relatively simple and inexpensive process at room temperature. The optical properties can be easily controlled by adjusting the spin coating speed and the concentra-tion of the pearlescent pigments. The produced color glasses achieved a high transmittance of 85% or more in the visible wavelength range, except the wavelength spectrum exhibiting the maxi-mum reflectance. In addition, we propose a one-step lamination process of color glass on a solar cell by leveraging on the adhesive property of the NOA matrix. This eliminates the cost and pro-cess of additional ethylene vinyl acetate (EVA) layer or other materials used in the conventional lamination process. The color glass produced through this study has stability that does not change its properties over time. Therefore, it is expected to be applied to the BIPV solar module market where aesthetics and energy efficiency are required.

Smartphone-based point-of-care testing (POCT) is rapidly emerging as an alternative to traditional screening and laboratory testing, particularly in resource-limited settings. In this proof-of-concept study, we present a smartphone- and cloud-based artificial intelligence quantitative analysis system (SCAISY) for relative quantification of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-specific IgG antibody lateral flow assays that enables rapid and accurate evaluation of test strips. By capturing an image with a smartphone camera, SCAISY quantitatively analyzes antibody levels and provides results to the user. We analyzed changes in antibody levels over time in over 248 individuals, including vaccine type, number of doses, and infection status, with a standard deviation of less than 10%. We also tracked antibody levels in six participants before and after SARS-CoV-2 infection. Finally, we examined the effects of lighting conditions, camera angle, and smartphone type to ensure consistency and reproducibility. This study suggests that SCAISY is a simple and powerful tool for real-time public health surveillance, enabling the acceleration of quantifying SARS-CoV-2-specific antibodies generated by either vaccination or infection and tracking of personal immunity levels.

Lipofibromatous hamartoma, first reported in 1953, is a rare, slowly-progressive soft tissue tumor, characteristics of which include enlargement of the affected nerve by epineurial and perineurial proliferation of adipose and fibrous tissues. Out of previously reported 200 cases of lipofibromatous hamartoma of the median nerve, there have been approximately 40 pediatric cases under the age of 18. Herein, we report a case of lipofibromatous hamatoma of the median nerve in a 3-year-old female patient, who was surgically decompressed by carpal tunnel release only and histologically confirmed. The patient was followed-up on outpatient clinic basis annually along with ultrasonography, and the postoperative 10th year follow-up did not show recurrence or any deficits in motor and sensory functions

We investigated layered titanium nitride (TiN) and aluminum nitride (AlN) for color glasses in Building Integrated Photovoltaic (BIPV) systems. AlN and TiN are among suitable and cost-effective optical materials to be used as thin multilayer films, owing to the significant difference in their refractive index. To fabricate the structure, we used radio frequency magnetron deposition method to achieve the target thickness uniformly. A simple, fast, and cheap fabrication method is achieved by depositing the multilayer films in a single sputtering chamber. It is demonstrated that a multilayer stack that allows light to move from a low refractive index layer to a high refractive index layer or vice-versa can effectively create various distinct color reflections for different film thicknesses and multilayer structures. It is investigated from simulation based on wave optics that, TiN/AlN multilayer offers better color design freedom and cheaper fabrication process as compared to AlN/TiN multilayer films. Blue, green, and yellow color glasses with optical transmittance of more than 80% was achieved by ITO coated glass/TiN/AlN multilayer films. This technology exhibits good potential in commercial BIPV system applications.

Vase life is one of the most important factors that determine the marketability of cut flowers and is greatly affected by the water balance. In recent years, cut hydrangea flowers are increasingly consumed as decorations for various events. However, the vase life of cut hydrangea flowers varies greatly depending on the postharvest solution management. Therefore, this study investigated the vase life, solution uptake, water balance, and relative fresh weight of freshly harvested hydrangea (Hydrangea macrophylla ‘Verena’) according to the three types of holding solutions (tap water, 1% chrysal professional Ⅲ (CPⅢ), 2% sucrose + 250 mg/L 8-hydroxquinoline + 100 mg/L citric acid (SHQC)) and the combination solutions (pretreatment; tap water, 0.1% chrysal RVB (RVB), floralife quickdip (FQ), transport; tap water, CPⅢ, floralife clear (FC), preservatives; CPⅢ, FC) for each distribution stage (pretreatment-transport-consumer). In the preservative comparison experiment, compared with the control, CPⅢ treatment and SHQC treatment significantly increased the vase life in 2019 (0.7 days, 3.4 days) and 2020 (1.4 days, 3.1 days), respectively. In the comparative experiment by solution combination, the group (RVB, FQ) using the pretreatment significantly extended the vase life by 4.6 days and 5.9 days compared to the tap water treatment. It was also determined that the same treatment increased overall solution uptake, maintained water balance longer, and increased relative fresh weight. These results confirm the importance of holding solutions and pretreatments, suggesting that appropriate pretreatments and preservatives should be used to improve the marketability of cut hydrangea flowers.

Background: Schizophrenia is a severe psychiatric disorder that has a large impact on patients’ lives. In addition to Western medicine, the use of additional treatments, such as acupuncture, in treating the positive, negative, and cognitive symptoms is increasing. Methods: We conducted a systematic review on the use of acupuncture as an add-on treatment for patients with schizophrenia that are in regular care, with a special focus on the treatment of the often accompanying co-morbid sleep disorders. In this study, we searched the Medline, ScienceDirect, Cochrane Library, Scopus, and ERIC databases with a cut-off date of December 31, 2017, thereby following the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) protocol. Results: Our search resulted in 26 eligible studies. Most studies showed limited evidence for the use of acupuncture as add-on therapy in the treatment of clinical symptoms, but beneficial effects have been reported in the treatment of co-morbid sleep disorders. Conclusions: Limited evidence was found for the use of acupuncture as add-on therapy in the treatment of patients with schizophrenia; however, positive results were found in the treatment of sleep disorders, but this result needs to be confirmed in large, randomized, controlled trials.

Sphingosine 1-phosphate (S1P) is a signaling lipid molecule involved in various cellular processes. It is important to develop a quantitative method for S1P to determine endogenous levels and to investigate its functions. Especially since S1P is a tiny lipid component of most biological samples, highly sensitive analysis by LC-MS/MS is required. The main challenge in S1P analysis by chromatography is peak broadening due to the presence of a polar phosphate and zwitterion formation in S1P. In this study, we used hydrogen fluoride (HF) to efficiently remove a phosphate and then analyzed the surrogate, sphingosine, as a sharp peak by LC-ESI-MS/MS. We optimized the dephosphorylation reaction in terms of reaction time, temperature, and HF concentration. Multiple reaction monitoring (MRM) for dephosphorylated form of S1P and C17-S1P as internal standard at m/z transition 300.4&gt;282.4 (quantification ion), 300.4&gt;262.4 (qualification ion), 286.3&gt;268.2 (internal standard). This method was validated by essential parameters such as specificity, linearity, range, LOQ, LOD, accuracy, precision, and repeatability. To confirm this new method, we quantified S1P levels in various serum products (100.02 ~ 284.38 nM). To apply the method in vivo, we analyzed S1P in plasma and kidney tissues obtained from a chronic kidney disease (CKD) mouse model. S1P levels were increased only in CKD kidney tissue but not in plasma. In conclusion, by applying the dephosphorylation step with HF, we established a new sensitive LC-MS/MS quantitative method for S1P that can be applied to biological samples.

Recently, the mapping industry has been focusing on the possibility of large-scale mapping from unmanned aerial vehicles (UAVs) owing to advantages such as easy operation and cost reduction. In order to produce large-scale maps from UAV images, it is important to obtain precise orientation parameters. For this, various techniques have been developed and are included in most of the commercial UAV image processing software. For mapping, it is equally important to select images that can cover a region of interest (ROI) with the fewest possible images. Otherwise, to map the ROI, one may have to handle too many images, and commercial software does not provide information needed to select images, nor does it explicitly explain how to select images for mapping. For these reasons, stereo mapping of UAV images in particular is time consuming and costly. In order to solve these problems, this study proposes a method to select images intelligently. We can select a minimum number of image pairs to cover the ROI with the fewest possible images. We can also select optimal image pairs to cover the ROI with the most accurate stereo pairs. We group images by strips, and generate the initial image pairs. We then apply an intelligent scheme to iteratively select optimal image pairs from the start to the end of an image strip. According to the results of the experiment, the number of images selected is greatly reduced by applying the proposed optimal image–composition algorithm. The selected image pairs produce a dense 3D point cloud over the ROI without any holes. For stereoscopic plotting, the selected image pairs were map the ROI successfully on a digital photogrammetric workstation (DPW), and a digital map covering the ROI is generated. The proposed method should contribute to time and cost reductions in UAV mapping.

The objective of this study is to investigate the effect of the premixed ethanol ratio based on the same total heating value in-cylinder on the equivalence ratio distributions and the injected fuel droplet behavior in the cylinder of the RCCI engine. The spray simulation was conducted by dividing two-part. First, the spray validation simulations progressed to find the spray-influenced factor of the test injector. Next, the engine simulations were performed with the spray-influenced factor obtained from spray validation simulations to investigate the effect of the premixed ethanol ratio based on the same total heating value in-cylinder on the injected fuel atomization and the equivalence ratio distributions. The introduced total heating value was fixed at 595J based on the lower heating value of diesel 14mg. The heating value of the premixed ethanol ratio varied from 0% to 40% based on the same total heating value in-cylinder in steps of 10%. It was revealed that when the premixed ethanol ratio based on the same total heating value in-cylinder was increased, the spray tip penetration value was reduced from the time after 4deg of diesel injection start because of the short injection duration by the small amount of diesel fuel. The SMD value was also more enormous up to 32.58% with increasing the premixed ethanol ratio because of the low kinetic energy of the injected fuel by the short injection duration and the slow evaporation of the injected fuel by the low cylinder temperature.

To address the challenges of climate change and food security, the establishment of smart farm complexes is necessary. While there have been numerous studies on the productivity and environmental control of individual greenhouses, research on greenhouse complexes is considerably limited. Conducting environmental studies during the design phase of these complexes poses financial constraints and practical limitations in terms of on-site experiments. To identify potential issues that may arise when developing large-scale greenhouse complexes, it is possible to utilize modeling techniques using Computational Fluid Dynamics (CFD) to assess environmental concerns and location issues before constructing the facilities. Consequently, simulating large-scale CFD models that incorporate multiple greenhouses and atmospheric conditions simultaneously presents significant numerical challenges. The objective of this study was to develop a guideline for verifying CFD models for a large-scale Venlo greenhouse, where acquiring field data before construction is not feasible for designing a greenhouse complex. The verification processes of the CFD models were conducted using 2D and 3D iterative simulations of a 2-hectare greenhouse model, using the improved Grid Independence Test (GIT) and wall Y+ approaches. Subsequently, the aerodynamic characteristics were analyzed in a 3D greenhouse model to access its performance when the wind direction was 90° in summer season. The findings revealed that a grid resolution of 0.8 meters and a first layer height of 0.04 meters were suitable for developing large-scale greenhouse models, resulting in a low Root Mean Square Error (RMSE) of 3.9% and a high coefficient of determination (R2) of 0.968. This process led to a significant reduction of 38% in the number of grid cells. These results will serve as design standards for large-scale greenhouses.

Cell-penetrating peptides (CPPs), a group of small peptides capable of promoting the transport of molecular cargo across the plasma membrane, have become important tools in promoting the cellular uptake of exogenously delivered macromolecules. GV1001, a peptide derived from a reverse-transcriptase subunit of telomerase (hTERT) and developed as a vaccine against various cancers, reportedly has unexpected CPP properties. Unlike typical CPPs, such as the HIV-1 TAT peptide, GV1001 enabled the cytosolic delivery of macromolecules such as proteins, DNA and siRNA via extracellular heat shock protein 90 (eHSP90) and 70 (eHSP70) complexes. The eHSP-GV1001 interaction may have biological effects in addition to its cytosolic delivery function. GV1001 was originally designed as a MHC class II-binding cancer epitope, but its CPP properties may contribute to its strong anti-cancer immune response relative to other telomerase peptide-based vaccines. Cell signaling via eHSP-GV1001 binding may lead to unexpected biological effects, such as direct anticancer or antiviral effects. In this review, we focus on the CPP effects of GV1001 bound to eHSP90 and ehsp70.

Trans-arterial radioembolization (TARE) is a form of radiation therapy performed for hepatocellular carcinoma (HCC) via selective intra-arterial injection of Yttrium-90 loaded microspheres. This was a multicenter retrospective study of consecutive patients with HCC who underwent TARE between July 2009 and May 2019. Using pre-treatment computed tomography imaging, the total cross-sectional area (cm2) of the abdominal skeletal muscle at the third lumbar vertebra was measured. The skeletal muscle index (SMI) was calculated by normalizing the muscle area to patient height. In total, 347 patients (median age, 65 years; 284 male) were included in the study. A total of 108 (31.1%) patients had portal vein tumor thrombus (PVTT) and 126 (36.3%) were classified as sarcopenic. The median overall survival (OS) was 28.1 months (95% CI, 24.8-35.7) and median progression-free survival was 8.0 months (95% CI, 6.4-9.4). Multivariate Cox regression analysis revealed that sarcopenia (hazard ratio [HR], 1.36; 95% CI, 1.00-1.85, p = 0.05), PVTT (HR, 1.82; 95% CI, 1.33-2.49, p &lt; 0.01), alpha-fetoprotein (AFP) (≥200 ng/mL) (HR 1.41; 95% CI, 1.04-1.92, p = 0.03), and albumin-bilirubin grade (2-3) (HR 1.74; 95% CI, 1.24-2.43, p &lt; 0.01) were independently associated with poor OS. TARE provided favorable long-term outcomes for patients with advanced HCC. Pre-treatment sarcopenia independently associated with survival, suggesting its utility as a surrogate biomarker for identifying TARE candidates.

In this paper, a 100CMM regenerative thermal oxidizer (RTO) system based on a high heating device for low-emission combustion is implemented at a volatile organic compound (VOCs) gas generation workplace. Existing RTO has a structure that repeats the inflow and discharge of VOCs gas into a cylindrical drum-type rotating disk and has excellent energy efficiency with a heat recovery rate of 95% or more. However, when used for a long time, there is a problem that rotation stops or explodes due to the discharge of pollutants due to dust and thermal expansion due to high temperature of 800℃. To overcome this, a RTO based on a high heating device was developed to reduce low-emission combustion emissions and energy use. Through 177 hours of demonstration time, the oxidation efficiency of VOCs was 97.87%; the waste heat recovery rate was reduced by 95.78%, the fuel consumption was reduced by 21.95%, and the nitrogen oxide concentration was 3.9 ppm

In order to reduce the large damage caused by train derailment, protective facilities of various shapes and conditions can be installed on railroad tracks. These protective facilities are referred to as derailment containment provisions (DCPs) and three different types are used worldwide. However, there are no clear standards for DCPs design such as installation location, size, and design load, and performance verification of DCPs installed in the actual railway field is not sufficiently performed. In this paper, the functionality of DCPs is analyzed through the full-scale derailment test. In order to propose a method for estimating the collision load acting on the DCP type I after derailment, the experimental results and simulation results are compared. The function of DCP type I according to the change of the vehicle's center of gravity is identified through comparative analysis of the post derailment behavior.

Exposure to air pollution have detrimental effects on the elderly, women, people with pre-existing medical conditions, people living in poverty and children. The aim of the study was to investigate the extent of community awareness and knowledge on the health risks associated with exposure to air pollution. A cross-sectional study design was used for the study, using self-administered questionnaires. A simple random sampling technique was used to select 376 respondents. Systematic sampling method was applied to select the households. SPSS version 26 was used to analyze data. Of 376 respondents, 221 were males and 154 females. 113 were aged between 23-47years and 353 were aware that if they don’t protect themselves against polluted air, they may get sick, with age and educational status associated with their awareness (p &lt; 0.05). About 361 knew what air pollution is and 188 think the air they breathe in Annadale is moderate. A total number of 278 said they feel sick/uncomfortable when the quality of air is bad. About 293 knew that people are exposed to air pollution by breathing contaminated air and 237 identified sewage smell as the main cause of air pollution. Respondents who identified internet and television as the main source of information were 199 and 177 respectively. Those who were not aware of actions implemented to reduce air pollution were 180. Based on the results of the study, respondents are aware of the dangers of exposure to polluted air, and it is necessary that air pollution risk communication strategies be implemented to empower residents.

Porcine parvovirus (PPV) 1 is a major causative pathogen of reproductive failure, and porcine circovirus (PCV) 2 is an etiological pathogen causing PCV-associated and PCV diseases worldwide. PPV2–6 and PCV3 were recently identified as newly emerging viruses with unknown pathogeneses. However, little is known of PPV1–6 and PCV3 effects or their co-infections with PCV2. In this study, we examined 926 samples (272 aborted pig fetuses and 654 pig lung tissues) from domestic pig farms for the presence of PPV1–6 or PCV3 and for PCV2 co-infection with these seven viruses. The prevalence of PPV and PCV was significantly greater in lung tissue samples than aborted pig fetus samples. PPV3–6 were detected for the first time in Korean domestic pigs. Co-infection rates with PCV2 and other viruses were significantly higher in abattoir samples than that in aborted pig fetus samples. Concurrent infections are more common than single infection in pig population and nu-merous infectious pathogens such as PPV and PCV2 can impact the respiratory diseases. Fur-thermore, Korean PPV1 strain (PPV1-82) was identical to the virulent PPV-27a strain in this respect. Our results describe, for the first time the prevalence of PPV1–6 and PCV3 infections and their co-infection rates with PCV2 in Korean domestic pigs.

As broiler farming facilities have become larger and more concentrated in response to external environmental changes, there is a possibility of increased concentrations of fine dust and aerosols inside these facilities due to enclosure. In particular, workers are exposed to high concentrations of organic particulate matter and harmful gases while performing their tasks, and as they age, they become more vulnerable to respiratory diseases. It is essential to directly monitor the concen-trations to which workers are exposed, along with the spatial distribution of aerosols inside broiler house. In this study, we analyzed the regional aerosol concentrations using passive samplers in commercial tunnel-ventilated broiler farms. Simultaneously, we employed active samplers at the height of the workers' breathing zones to monitor real-time aerosol concentrations by particle size along their work routes. Spatial aerosol concentrations generally increased from the inlet to the exhaust in the breathing zone. The average aerosol concentrations were TSP -1,042 µg/m³, PM-10 718 µg/m³, and PM-2.5 137 µg/m³. To analyze the workers' exposure environments, we categorized the tasks in the barn into Static work period (SWP) and Moving work period (MWP) based on video analysis. The results showed that during MWP, fine dust concentrations exceeded the standards by up to 214%. Particularly, during MWP, the concentrations were 1.74 times higher for TSP, 1.40 times higher for PM-10, and 1.22 times higher for PM-2.5 compared to SWP. It was observed that during the movement of workers, physical generation of particles around 10 µm, such as feces, feed, and bedding, occurred due to the movement of chicken, which influenced the aerosol concentration.

Many farms utilize closed-type livestock systems to enhance productivity and facilitate effective environmental management. However, the confined nature of these closed spaces poses an increased risk of exposure to harmful gases and organic dust for both workers and livestock. Additionally, the introduction of outside air through ventilation systems can lead to temperature fluctuations within the breeding environment, resulting in potential productivity issues. This research paper employs computational fluid dynamics (CFD) to develop ventilation operation management plans that address both the working environment and the breeding environment simultaneously. The proposed plans are designed to be easily implemented in practical farm settings. The findings of this study, based on simulation analysis, indicate that while ventilation is effective in reducing harmful gases and improving the working environment, its efficiency decreases after the initial 3 minutes of operation. Furthermore, uncontrolled ventilation can cause sudden temperature changes, which may adversely affect the well-being of the livestock. However, when upgraded ventilation structures are implemented, significant improvements in the working environment (an average of 27.3% improvement) can be achieved while maintaining temperature stability for the livestock. These results highlight the importance of referring to the provided ventilation operation management table before commencing work, as it enables workers to improve the working environment while minimizing the potential impact of ventilation on the breeding environment.

The inter-subspecific crossing between indica and japonica subspecies in rice have been utilized to improve the yield potential of temperate rice. In this study, a comparative study of the genomic regions in the eight high-yielding varieties (HYVs) was conducted with those of the four non-HYVs. The Next-Generation Sequencing (NGS) mapping on the Nipponbare reference genome identified a total of 14 common genomic regions of japonica-originated alleles. Interestingly, the HYVs shared japonica-originated genomic regions on nine chromosomes, although they were developed through different breeding programs. A panel of 94 varieties was classified into four varietal groups with 38 single nucleotide polymorphism (SNP) markers from 38 genes residing in the japonica-originated genomic regions and 16 additional trait-specific SNPs. As expected, the japonica-originated genomic regions were only present in the japonica (JAP) and HYV groups, except for Chr4-1 and Chr4-2. The Wx gene, located within Chr6-1, was present in the HYV and JAP variety groups, while the yield-related genes were conserved as indica alleles in HYVs. The japonica-originated genomic regions and alleles shared by HYVs can be employed in molecular breeding programs to further develop the HYVs in temperate rice.

(1) Background: The aim of the present study was to evaluate the effect of ETS homologous factor (EHF) in malignant breast cancer cells. (2) Methods: Overexpression and knockdown of the EHF gene in human and mouse breast cancer cells were performed, and the TCGA dataset and Q-omics were analyzed. (3) Results: We found that the tumor suppressor NDRG2 is correlated with EHF gene expression in triple-negative breast cancer cells, that EHF overexpression results in reduced cell proliferation and that apoptosis is promoted by chemotherapeutic reagent treatment of EHF-overexpressing cells. By EHF overexpression, senescence-associated β-galactosidase activity and p21WAF1/CIP1 expression were increased, suggesting that EHF may induce cellular senescence. In addition, overexpression of EHF reduced the migratory ability and inhibited epithelial-mesenchymal transition (EMT). Furthermore, EHF inhibited the phosphorylation of STAT3. Overexpression of EHF also reduced tumor size, and lung metastasis in vivo. At the tumor site, β-galactosidase activity was increased by EHF. Finally, Kaplan-Meier-plotter analysis showed that TNBC patients with high expression of EHF had a longer relapse-free survival rate. (4) Conclusions: Our findings demonstrated that EHF inhibits breast tumor progression by inducing senescence and regulating EMT in TNBC cells.

Obesity is a global health concern. Recent research has suggested that the development of anti-obesity ingredients and functional foods should focus on natural products without side effects. We investigated the anti-obesity efficacy and mechanisms of action of Brassica juncea extract (BJE) using in vitro and in vivo obesity models. In in vitro experiments, BJE treatment downregulated adipogenic-related proteins CCAAT/enhancer-binding protein-α (C/EBP-α), peroxisome proliferator-activated receptor-γ (PPAR-γ), adipocyte protein 2 (aP2), and lipid synthesis-related protein acetyl-CoA carboxylase (ACC). It also upregulated the heat generation protein peroxisome proliferator-activated receptor gamma coactivator-1α (PGC-1α) and fatty acid oxidation protein carnitine palmitoyltransferase-1 (CPT-1). Oral administration of BJE decreased body weight, alleviated liver damage, and inhibited lipid accumulation in high-fat diet (HFD)-induced obese mice. Inhibition of lipid accumulation by BJE in vivo was associated with decreased expression of adipogenic and lipid synthesis proteins and increased expression of heat generation and fatty acid oxidation proteins. BJE administration improved obesity by decreasing adipogenesis and activating heat generation and fatty acid oxidation in 3T3-L1 cells and in HFD-induced obese C57BL/6J mice. These findings indicate that BJE is a promising natural means of preventing obesity-related metabolic diseases.

Coxsackievirus A6 (CV-A6) has emerged as the predominant causative agent of hand, foot, and mouth disease (HFMD) in young children. Since the declaration of coronavirus disease 2019 (COVID-19) as a global pandemic, the incidence of infectious diseases, including HFMD, has decreased markedly. When social mitigation was relaxed during the COVID-19 pandemic in 2022, re-emergence of HFMD was observed in Gwangju, South Korea, and seasonal characteristics of the disease appeared to have changed. To investigate the molecular characteristics of enterovirus (EV) associated with HFMD during 2022, 277 specimens were collected. Children aged under 5 years accounted for the majority of affected individuals. EV detection and genotyping were performed using real-time RT-PCR and nested RT-PCR followed by sequence analysis. EV detection rate was found to be 82.3%, and the main genotype identified was CV-A6. Sixteen CV-A6 samples were selected for whole genome sequencing. According to phylogenetic analysis, all CV-A6 strains from this study belonged to the sub-genotype D3 clade based on VP1 sequences. Analysis of 3D polymerase phylogeny showed that only the recombinant RF-A group was identified. In conclusion, circulating EV types should be continuously monitored to understand pathogen emergence and evolution during the post-pandemic era.

Recently, two respiratory syncytial virus (RSV) vaccines based on the prefusion F (pre-F) antigen were approved in the United States. We developed and validated an enzyme-linked immunosorbent assay (ELISA)-based protocol for the practical and large-scale evaluation of RSV vaccines. Two modified pre-F proteins (DS-Cav1 and SC-TM) were produced by genetic recombination and replication using an adenoviral vector. The protocol was established by optimizing the concentrations of the coating antigen (pre-F proteins), secondary antibodies, and choice of blocking buffer. To validate the protocol, we examined its accuracy, precision, and specificity using serum samples from 150 participants across various age groups and the standard serum provided by the National Institute of Health. In the linear correlation analysis, coating concentrations of 5 and 2.5 μg/mL of DS-Cav1 and SC-TM, respectively, showed high coefficients of determination (r2 = 0.90). Concentrations of secondary antibodies (alkaline phosphatase-conjugated anti-human immunoglobulin G, diluted 1:2000) and blocking reagents (5% skim milk/PBS-T) were optimized to minimize non-specific reactions. High accuracy was observed for DS-Cav1 (r2 = 0.90) and SC-TM (r2 = 0.86). Further, both antigens showed high precision (coefficient of variation &lt; 15%). Inhibition ELISA revealed cross-reactivity of antibodies against DS-Cav1 and SC-TM but not with the attachment protein.

Histone demethylases, enzymes responsible for removing methyl groups from histone proteins, have emerged as critical players in regulating gene expression and chromatin dynamics, thereby influencing various cellular processes. LSD2 and LSD1 have attracted considerable interest among these demethylases because of their associations with cancer. However, while LSD1 has received significant attention, LSD2 has not been recognized to the same extent. In this study, we conduct a comprehensive comparison between LSD2 and LSD1, with a focus on exploring LSD2's implications. While both share structural similarities, LSD2 possesses unique features. Functionally, LSD2 shows diverse roles, particularly in cancer, with tissue-dependent roles. Additionally, LSD2 extends beyond histone demethylation, impacting DNA methylation and DNA damage repair pathways. This study underscores the distinct roles of LSD2, providing insights into their contributions to cancer and other cellular processes.

Although global life expectancy has increased over the past 20 years due to improvements in managing infectious diseases, one in five people still succumbs to infections. Humanity is tirelessly working towards developing vaccines and antimicrobial agents in response to this ongoing threat. However, pathogens continue to acquire numerous resistance mechanisms and proliferate. Meanwhile, the COVID-19 pandemic has prompted us to recognize that focusing solely on the killing strategies of immunology and microbiology in complex and multisystemic infectious diseases is insufficient for understanding survival. In essence, there is a need for a treatment approach centered on disease tolerance, capable of alleviating pathology and/or promoting physiological functions in conjunction with the existing strategies of host immune response and pathogen destruction. Against this backdrop, this narrative review comprehends and introduces microbiome therapeutics, which recently garnered attention as next-generation treatments regarding two defense strategies against infectious diseases. First, we delineate the application of existing probiotics and then the microbiome in infectious diseases. Subsequently, we expand this concept to encompass host microbiome crosstalk and present related microbiome therapeutics' current status and direction. Ultimately, the review presents a fresh perspective on understanding microbiome therapeutics in infectious diseases based on a cooperative defense system.

As climate changes, our daily life has been much influenced by abnormal meteorological phenomena such as heavy rainfall, heat wave, heavy snowfall, and fine dust. Atmospheric air quality is worsening day by day and indoor air quality is also affected by interconnected daily activities throughout the inside and outside of buildings and houses. Nowadays, pollutants from various sources are emitted, transformed by sunlight, vapor, and ozone and transported into the city from country to country. Due to these reasons, there have been high demands to monitor the transportation of particulate matters and improve air quality. Monitoring of pollutants and identification of type and its concentration enables us to track and control its generation and consequently find out the solution. However, monitoring of pollutants, especially, particulate matter generation and its transportation is still not fully operated in atmospheric air due to its open nature and meteorological factors. Even though indoor air is relatively easy to monitor and control than outdoor in the aspect of specific volume and contaminant source, but it still needs to consider the meteorological parameters because indoor air is not fully separated from the outdoor air flow and contaminants transportation. In this study, optical approach using spectral sensor was attempted to reveal the feasibility of wavelength and chromaticity values of reflected light from specific particles. From the analysis of reflected light of various particulate matters according to different liquid additives, parameter studies were performed to investigate which experimental conditions can contribute to the enhanced selective sensing of particulate matters. Five different particulate matters such as household dust, soil, talc powder, gypsum powder and yellow pine tree pollen were utilized and observed to elucidate the relationship between property of particulate matter and detected light spectrum. Applicable approaches to assist current particle matter sensors and improve the selective sensing were suggested.

Background: Relatively little is known and inconclusive about social inequality in human papillomavirus (HPV) vaccination among teenagers in the United States. This study aims to investigate whether there is a social disparity in HPV vaccination among teenagers and if so, whether it can differ by the source of teen vaccination information (parental reports and provider records). 
Methods: We used the data from the 2019 National Immunization Survey-Teen (NIS-Teen; 42,668 teenagers, aged 13-17) including parental reported vaccination status. Among them, 18,877 teenagers had adequate provider reported vaccination records. Two socioeconomic status (SES) measures were used: mother’s education and annual family income. Multivariate logistic analyses were conducted. 
Results: False negatives of parental reports against provider records were more than two times higher (p < 0.001) in low SES teens than in high SES teens. In both SES measures, the proportion of HPV unvaccinated teenagers were lowest in the highest SES level in analyses with parental reports. However, it was the opposite in analyses with provider records. Interestingly, regardless of vaccination information source, the HPV unvaccinated rate was highest in the middle SES teens (>12 years, non-college graduates; and above poverty level, but not > $75K). 
Conclusion: A significant social inequality in HPV vaccination among teenagers exists in the United States. The pattern of social inequality in HPV vaccination can be distorted when only parent reported vaccination information is used.

A novel chemically cross-linked hydrogel was prepared through the utilization of the nor-bornene (Nb)-methyl tetrazine (mTz) click reaction, derived from carboxymethyl cellulose (CMC) and alginate (Alg). The hydrogel was designed to generate reactive oxygen species (ROS) from NIR-dye, indocyanine green (ICG) for a combined photothermal and photodynamic ther-apy (PTT/PDT). The cross-linking of Nb and mTz moieties occurred via an inverse elec-tron-demand Diels-Alder reaction under physiological conditions avoiding the need for a cata-lyst. The resulting hydrogels exhibited viscoelastic properties (G′ ~ 492-270 Pa) and high porosi-ty. The hydrogels were found to be injectable with tunable mechanical characteristics. The ICG encapsulated hydrogels demonstrated ROS generation ability under NIR exposure. The ROS production was investigated through DPBF assays to access photodynamic effect (with NIR irra-diation at 1-2W for 5-15 min). The temperature of the ICG-loaded hydrogels was also raised up-on the NIR irradiation to eradicate tumor cells photothermally. In vitro cytocompatibility as-sessments revealed the non-toxic nature of CMC-Nb and Alg-mTz towards HEK-293 cells. Fur-thermore, the ICG-loaded hydrogels effectively inhibited the metabolic activity of Hela cells following NIR exposure. This innovative hydrogel system holds promise for applications in combined PTT and PDT.

Various therapeutic approaches have been developed for neglect. Many studies have demonstrated the effect of Digital therapeutics(DTx) on neglect. By contrast, only a few studies have reported on the effects of DTx on egocentric and allocentric neglect. In this article, seven studies on DTx of egocentric and allocentric neglect were reviewed. DTx, which was employed in these studies, could be classified as follows: 1) software adaptation in traditional treatment, 2) VR game using the head-mount display as treatment, and 3) development of new digital program like ReMoVES. In addition, more studies and effective results were reported on egocentric neglect than allocentric neglect. In future studies, each effect on egocentric and allocentric neglect should be identified in detail through the appropriate use of differential evaluation and long-term application of independent digital therapeutics.

Recently, research on ultra-high-performance concrete (UHPC) with the characteristics of ultra-high strength, high toughness, and high durability has been actively conducted from materials to actual structural applications. However, research on experimental methods that reflect the unique characteristics of UHPC, which are different from those of normal concrete, is insufficient. To solve the difficulties in applying the compressive creep test method for normal concrete to UHPC and to verify the validity of the recently proposed ASTM C 1856 standard test method, this study performed compressive creep tests on UHPC with variables of specimen size, sustained load intensity, fiber length, and strain measuring method. Two types of cylindrical specimens of ϕ100 × 200 mm and ϕ75 × 150 mm were used for a specimen size variable. The sustained load intensities of 10% to 40% based on the specified compressive strength of 150 MPa were applied. Two types of steel fiber lengths of 13 mm and 19.5 mm in the UHPC mix were used as a variable, and three strain measuring methods of the embedded strain gauge method, the attached strain gauge method, and the strain meter with stud measured the change in length of the UHPC specimens. The experimental results showed that the strain meter method using the standard rod had limitations due to the error in the verification process using the standard rod and the observation error of the measurer, and the sustained load intensity is preferable to 15% to 40% of the actual compressive strength. It was found that it is possible to perform a compressive creep test for UHPC using a specimen with a size of ϕ75 mm or more, and the fiber length did not affect the creep behavior of UHPC up to 19.5 mm. As a result of comparing the UHPC creep test results with the creep prediction model, the B3 model was found to most accurately predict the UHPC creep behavior. The creep coefficient pattern of the B3 model was very similar to the measured results, and well reflected the effects of the mixing ratio and compressive strength of UHPC.

Close to half (45.4%) of 2.3 million breast cancers (BC) diagnosed in 2020 were from Asia. While the burden of breast cancer has been examined on the level of broad geographic regions, literature on more in-depth coverage of the individual countries and subregions of the Asian continent is lacking. This review examines the breast cancer burden in 47 Asian countries. Breast cancer screening guidelines and risk-based screening initiatives are discussed.

Recently, doubts were raised about the existence of the bilingual advantage in cognitive control. The aim of the present review was to investigate the bilingual advantage and its modulating factors. We searched the Medline, ScienceDirect, Scopus, and ERIC databases for all original data and reviewed studies on bilingualism and cognitive control, with a cut-off date of October 31, 2018, thereby following the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) protocol. The results of the 46 original studies show that, indeed, the majority, 54.3%, reported beneficial effects of bilingualism on cognitive control tasks; however, 28.3% found mixed results, and 17.4% found evidence against its existence. Methodological differences seem to explain these mixed results: particularly, the varying selection of the bilingual participants, the use of non-standardized tests, and the fact that individual differences were often neglected, and that longitudinal designs were rare. Therefore, a serious risk for bias exists in both directions (i.e., in favor of and against the bilingual advantage). To conclude, we found some evidence for a bilingual advantage in cognitive control; however, if significant progress is to be made, better study designs, bigger data, and more longitudinal studies are needed.

Rice, as a staple crop feeding billions, faces constant threats from various diseases jeopardizing global food security. Precise understanding of disease resistance mechanisms is crucial for developing resilient rice varieties. Traditional genetic mapping methods, such as QTL mapping, provide valuable insights into the genetic basis of diseases. However, the complex nature of rice diseases demands a holistic approach to gain accurate knowledge of it. Omics technologies, including genomics, transcriptomics, proteomics, and metabolomics, enable a comprehensive analysis of biological molecules, uncovering intricate molecular interactions within the rice plant. Integration of various mapping techniques using multi-omics data has revolutionized our understanding of rice disease resistance. By overlaying genetic maps with high-throughput omics datasets, researchers can pinpoint specific genes, proteins, or metabolites associated with disease resistance. This integration enhances the precision of disease-related biomarkers with better understanding of their functional roles in disease resistance. Improvement of rice breeding for disease resistance through this integration represents a significant stride in agricultural science because better understanding of the molecular intricacies and interactions underlying disease resistance architecture leads to more precise and efficient development of resilient and productive rice varieties. In this review, we explore how the integration of mapping and omics data can give a transformative impact on rice breeding for enhancing disease resistance.

(1) Background: The analysis of athletic performance has always aroused great interest from sport scientist. This study utilized machine learning methods to build predictive models using a comprehensive CrossFit (CF) dataset, aiming to reveal valuable insights into the factors influencing performance and emerging trends.; (2) Methods: The study used Random Forest (RF) and Multiple Linear Regression (MLR) models to predict performance in four key weightlifting exercises within CF: clean &amp; jerk, snatch, back squat, and deadlift. Performance was evaluated using R-squared (R2) values and Mean Squared Error (MSE). Feature importance analysis was conducted using RF, XGBoost, and AdaBoost models.; (3) Results: The RF model excelled in deadlift performance prediction (R2 = 0.80), while the MLR model demonstrated remarkable accuracy in clean &amp; jerk (R2 = 0.93). Across exercises, clean &amp; jerk consistently emerged as a crucial predictor. The feature importance analysis revealed intricate relationships among exercises, with gender significantly impacting deadlift performance.; (4) Conclusions: This research advances our understanding of performance prediction in CF through machine learning techniques. It provides actionable insights for practitioners, optimize performance, and demonstrates the potential for future advancements in data-driven sports analytics.

We propose that the high energy Cosmic Ray particles around the spectral turn-down commonly called the {\it knee} and up to the upturn, commonly called the {\it ankle}, mostly come from Blue Super Giant star explosions. At the upturn, i.e. the {\it ankle}, Cosmic Rays probably switch to another source class, most likely extragalactic sources. To show this we recently compiled a set of Radio Supernova data to list the magnetic field, shock speed and radius scale (Biermann et al. 2018) \cite{Biermann18}. Using particle acceleration theory at shocks, those numbers can be transformed into characteristic {\it knee} and {\it ankle} energies. Without adjusting any free parameters both of these observed energies are directly indicated by the supernova data. We now proceed to the next step in the argument, and use the Supernova Remnant data of the starburst galaxy M82. Assuming that they are Blue Supergiant star explosions, the shock will race to their outer edge with a magnetic field that follows ${B (r) \, r \, \sim \, const.}$. We argue that the shock runs through the entire magnetic plasma wind region at full speed all the way out to the wind-shell, which is of order parsec scale. The speed is observed to be $\sim \, 0.1 \, c$ at about ${10^{16} \, {\rm cm}}$ radius in the plasma wind. This demonstrates how Blue Supergiant star explosions can provide the Cosmic Ray particles across the {\it knee} and up to the {\it ankle} energy range. The data from the CREAM (Cosmic Ray Energetics and Mass Experiment) mission will test this cosmic ray concept which is reasonably well grounded in two independent radio supernova data sets. The next step in developing our understanding is to obtain accurate Cosmic Ray data near to the {\it knee}, and use unstable isotopes of Cosmic Ray nuclei at high energy to probe the "piston" driving the explosion. We plan to combine these data with the physics of the budding black hole which is probably forming in each of these stars to learn more.

The comparative efficacy and safety between lenvatinib and hepatic artery infusion chemotherapy (HAIC) in patients with unresectable hepatocellular carcinoma (HCC) are still unclear. This multicenter historical cohort study enrolled 244 patients who were treated with HAIC (n = 173) or lenvatinib (n = 71) between 2012 and 2020. Propensity score matching (PSM) was performed, and 52 patients were selected per group. Clinical outcomes and safety were compared. Objective response rate (ORR) was not different between the two groups (26.0% vs. 23.1%, P = 0.736). Before PSM, HAIC group had a higher proportion of Child-Pugh B and portal vein tumor, whereas lenvatinib group had more patients with extrahepatic metastases, which was adjusted after PSM. There were no differences in progression-free survival (PFS) and overall survival (OS) after PSM (HAIC vs. lenvatinib, median PFS, 3.6 vs. 4.0 months, P = 0.706; median OS 10.8 vs. 7.9 months, P = 0.106). Multivariate Cox-regression showed that alpha-fetoprotein ≤ 1000 ng/mL was only associated factor for OS after PSM in all patients (hazard ratio = 0.421, P = 0.011). Subgroup analysis for patients with high tumor burden beyond the REFLECT eligibility criteria revealed that HAIC group (n = 29) had a significantly longer OS than did lenvatinib group (n = 30) (10.0 vs. 5.4 months, P=0.004). More patients in HAIC group achieved better liver function than those in lenvatinib group at the time of best responses. There was no difference in the incidence of grade 3 and 4 adverse events between the two groups. Therefore, lenvatinib is comparable to HAIC in terms of ORR and OS in unresectable HCC meeting REFLECT eligibility criteria.

In the paper, the authors survey integral representations (including the Lévy--Khintchine representations) and applications of some bivariate means (including the logarithmic mean, the identric mean, Stolarsky's mean, the harmonic mean, the (weighted) geometric means and their reciprocals, and the Toader--Qi mean) and the multivariate (weighted) geometric means and their reciprocals, derive integral representations of bivariate complex geometric mean and its reciprocal, and apply these newly-derived integral representations to establish integral representations of Heronian mean of power 2 and its reciprocal.

Visual inertial odometry (VIO) has recently received much attention for efficient and accurate ego-motion estimation of unmanned aerial vehicle systems (UAVs). Recent studies have shown that optimization-based algorithms achieve typically high accuracy when given enough amount of information, but occasionally suffer from divergence when solving highly non-linear problems. Further, their performance significantly depends on the accuracy of the initialization of inertial measurement unit (IMU) parameters. In this paper, we propose a novel VIO algorithm of estimating the motional state of UAVs with high accuracy. The main technical contributions are the fusion of visual information and pre-integrated inertial measurements in a joint optimization framework, and the stable initialization of scale and gravity using relative pose constraints. To count for ambiguity and uncertainty of VIO initialization, a local scale parameter is adopted in the online optimization. Quantitative comparisons with the state-of-the-art algorithms on the EuRoC dataset verify the efficacy and accuracy of the proposed method.

Despite good intentions, the increasing number of plastic bag bans aimed at alleviating marine plastic pollution saw a correlated increase in the number of unintended consequences that emerged alongside the bans, suggesting that human behavior towards plastic bag consumption have not changed, but merely shifted, and are feeding into other major international environmental catastrophes. Nudge theory, which helps people make better choices for themselves without inhibiting their free will, is a potential solution that has been shown to play a subtle but important role in providing options under circumstances where complex information needs to be streamlined for the wider community, avoiding any unintended consequences and behavioural shifts that might arise from instruments that diminishes autonomy. It is therefore timely to look into the insights of nudge theory to encourage a positive behavioural change to reduce plastic bag consumption. Here we apply a systematic literature review to show how successful applications of nudges in supermarkets can be leveraged to reduce plastic bag consumption. We find that the current applications of nudges in various industries worldwide, including supermarkets have produced positive and encouraging results, as well as producing lasting behavioural change among the wider community. Supermarkets are identified as a powerful deployment site of these nudges due to their positioning as a dominant provider of plastic bags to the wider community, as well as being the largest and leading provider of daily food needs. Finally, we synthesise our findings to produce a coherent and testable framework of actionable interventions that supermarkets can employ to nudge customers towards reduced plastic bag reliance, accompanied with a visual timeline of a customer shopping in a supermarket experiencing these nudges.

During the 2008 Great Recession, many families with children relied on cash assistance from Temporary Assistance for Needy Families (TANF) program. The present study applied Exploratory Spatial Data Analysis (ESDA) tools to analyze geographically varying spatial clusters of states’ unemployment rates, TANF caseload growth rates, TANF policy choices such as benefit levels and TANF responsiveness rates to the recession. We analyzed 45 contiguous states and Washington D.C. A standardized TANF responsiveness index was developed to compare states’ TANF growth rates relative to their labor market conditions. The western states were found to be very responsive to the recession with ratios greater than one. In contrast, Texas and Arizona, with ratios below 1, were unresponsive to the recession. The presence of strong spatial clusters in unemployment rate and TANF maximum aid were found. In the case of maximum aid, there was a strong presence of Low-Low spatial clusters in Southern States and High-High clusters in Northeastern States. The findings suggest that several neighboring states in the northeast and some in the south had similar levels of financial commitment during the 2008 recessionary as the ones found by earlier research conducted during non-recessionary periods. The findings have implications for future federal actions and for state level collaboration.

The increasing prevalence of methicillin-resistant S. aureus (MRSA) in the dairy industry has become a fundamental concern. Endolysins are bacteriophage-derived peptidoglycan hydrolases that induce the rapid lysis of host bacteria. We investigated endolysin candidates with lytic activity against MRSA and evaluated the lytic activity of the endolysin candidate against S. aureus and MRSA. To identify endolysins, we used the following bioinformatic strategy: (1) retrieval of genetic information, (2) annotation, (3) selection of MRSA, (4) selection of endolysin candidates, and (5) evaluation of protein solubility. We then characterized the endolysin candidate under various conditions. Approximately 67% of S. aureus was detected as MRSA and a total of 114 putative endolysins were found. The 114 putative endolysins were divided into three groups based on their combination of conserved domains. Considering the protein solubility, we selected putative endolysins 177 and 117. Putative endolysin 117 was successfully overexpressed and renamed LyJH1892. LyJH1892 lysed approximately 85% of S. aureus. LyJH1892 showed more potent lytic activity against MRSA than normal S. aureus (relative lytic activity &gt; 125%). LyJH1892 showed broad lytic activity against coagulase-negative Staphylococci (CNS). In conclusion, These findings provide a rapid and useful strategy for the development of specific endolysins against antibiotic-resistant bacterial strains.

A detection system, modeled in a graph, uses "detectors" on a subset of vertices to uniquely identify an "intruder" at any vertex. We consider two types of detection systems: open-locating-dominating (OLD) sets and identifying codes (ICs). An OLD set gives each vertex a unique, non-empty open neighborhood of detectors, while an IC provides a unique, non-empty closed neighborhood of detectors. We explore their fault-tolerant variants: redundant OLD (RED:OLD) sets and redundant ICs (RED:ICs), which ensure that removing/disabling at most one detector guarantees the properties of OLD sets and ICs, respectively. This paper focuses on constructing optimal RED:OLD sets and RED:ICs on the infinite king's grid, and presents the proof for the bounds on their minimum densities; [3/10, 1/3] for RED:OLD sets and [3/11, 1/3] for RED:ICs.

While previous research has shown the use of attachable air-caps on windows to efficiently reduce a building’s energy consumption, the air-caps considered had to be attached to the entire window’s surface, thus limiting the occupants’ view and creating the inconvenience of needing to detach and attach the air-caps. In this study, a window-mounted air-cap roller module using Velcro tape that may be easily attached, detached, and rolled up or down was developed and performance tested in a full-scale test bed. It was found that as the area of the air-caps attached on a window increased, the required indoor lighting energy increased. However, the window insulation improved, thus reducing the cooling and heating energy needed. Attaching the air-caps to the entire window surface effectively reduced the building’s energy consumption, but views through the window may be disturbed. Thus, the developed window-mounted air-caps enable an occupant to reduce the building energy consumption and maintain their view according to their need. The findings of this study may contribute to a reduction in building energy consumption without sacrificing a pleasant indoor environment. Further studies may be needed to verify their efficacy under varying indoor and outdoor conditions.

Sarcopenia is associated with clinical complications, which increase mortality. Effective sarcopenia risk screening in the elderly should be grounded in a comprehensive assessment, encompassing both nutritional status and medication use. Current screening tools, while emphasizing muscular per-formance, exhibit limited sensitivity in identifying elderly individuals at risk of sarcopenia. This cross-sectional study aimed to develop a sarcopenia risk screening tool, named Sarc-Global, with enhanced sensitivity, incorporating factors pertinent to the overall health of the elderly. Utilizing the criteria established by EWGSOP2 for diagnosing sarcopenia, we evaluated 395 communi-ty-dwelling elderly individuals. This evaluation served as a reference for assessing the efficacy of two validated questionnaires, Sarc-F and Sarc-CalF, and our newly developed Sarc-Global. Con-structed through multiple logistic regression, Sarc-Global integrates variables such as sex, age, medication use, body mass index, arm circumference, and handgrip strength – all significantly associated with sarcopenia (p

Submucosal invasion is a critical step in gastric cancer (GC) progression, which greatly enhances metastasis risk. Cancer stem cells are responsible for invasion, metastasis, and tumor growth. To identify stem cell-related markers associated with submucosal invasion in GCs, we investigated the expression of candidate cancer stem cell (CSC) markers (CD133, CD44, and ALDH1A) and intestinal stem cell (ISC) markers (EPHB2, OLFM4, and LGR5) in early GCs with submucosal invasion. Remarkably, expression of all ISC markers and CD133 was frequently confined to the basal area of the lamina propria (basal pattern) in mucosal cancer. The proportion of stem cell marker-positive cells substantially increased during submucosal invasion. Given that ISC markers are restricted to the crypt base of the normal intestinal mucosa, these findings suggest that many early GCs may retain hierarchical characteristics. CD44 expression showed a focal pattern, ALDH1A was predominantly expressed diffusely, and there was no expansion of CD44 or ALDH1A expression in the submucosal cancer cells. RSPO2 from muscularis mucosa seem to be partly responsible for the increased expression of ISC markers in GC cells at the basal areas. We also found that ISC markers were correlated with CDX2 expression in GCs, indicating that ISC markers are involved in the intestinal differentiation in GCs. Interestingly, ISC markers (EPHB2 and OLFM4) and CD133 showed a positive impact on clinical outcomes. In particular, the prognostic value of EPHB2 was significant for intestinal-type GCs in a multivariate analysis. In summary, ISC markers and CD133 showed a basal distribution pattern along with enhanced expression in submucosal invading cells in early GCs. EPHB2 was an independent prognostic marker in intestinal-type GCs.

Major depressive disorder (MDD) and generalized anxiety disorder (GAD) exert significant burdens on individuals and society, underscoring the importance of accurate predictions using advanced machine learning (ML) algorithms. Leveraging electronic health records (EHRs) and survey data, these algorithms offer potential in forecasting such mental health conditions. Yet, the precision of these predictions can be compromised by biases or inaccuracies inherent in subjective survey responses. In this research, we assess the reliability of four prominent ML algorithms—Random Forest, XGBoost, Logistic Regression, and Naïve Bayesian—in predicting MDD and GAD. Our dataset encompasses a rich array of information, from biomedical metrics and demographic details to self-reported survey insights. A focal point of our investigation is the algorithms' performance under scenarios with varying degrees of subjective response inaccuracies, such as memory recall biases or subjective interpretation. Our findings reveal that while all algorithms exhibit commendable accuracy with pristine survey data, their performance diverges when faced with erroneous or biased responses. Notably, XGBoost remains stable and excels in identifying true positive cases, even in the presence of such noise. These observations underscore the criticality of algorithmic resilience in mental health prediction, especially when relying on subjective data. The robustness of certain algorithms to noisy inputs positions them as more reliable choices for predicting mental health conditions based on self-reported data, emphasizing the need for careful algorithm selection in such contexts.

In this study, the microbial community during the barley yeast fermentation of stevia leaves and its correlation with antioxidant, antiobesity, and anti-inflammatory properties, as well as metabolites, were investigated using UPLC-Q-TOF-MS. Stevia was fermented using commercial TSB media (TSB 1, TSB 2, and TSB 3) and sucrose (Sucrose 1, Sucrose 3, and Sucrose 3) for 1, 3, and 5 days, respectively. Stevia ferments showed higher DPPH and ABTS radical scavenging capacity compared to samples incubated with sucrose for 5 days, and all six ferments inhibited nitric oxide production in a concentration-dependent manner in LPS-induced mouse macrophages. Furthermore, UPLC-QTOF-MS analysis identified 23 related substances, including 10 terpenoids, including rubusoside, steviolbioside, and rebadioside derivatives; dulcoside A; and phlomisoside II, which are indicators of stevia, as well as five flavonoids, four phenolic acids, and four fatty acids. We also identified the microbial community during fermentation via the next-generation sequencing of the 16S rRNA gene for bacteria and the internal transcribed spacer (ITS) gene for fungi. The results showed that TSB 1 and Sucrose 1 ferments were dominated by the pathogens Enterococcus hirae (58.93%) and Cronobacter sakazakii (80.92%), while samples fermented for more than 3 days were pathogen-free and dominated by lactic acid bacteria such as Pediococcus stilesii (73.37%). Microbial community analysis using the ITS region showed that Saccharomycopsis fibuligera, classified as a yeast rather than a mold, dominated the stevia fermentation regardless of the fermentation duration. In particular, the microbial community of the fermentation with a sugar solution was dominated by S. fibuligera by more than 99% throughout the fermentation periods of 1, 3, and 5 days. Finally, to apply the stevia ferments topically to human skin, skin irritation tests were performed on 30 volunteers. The results showed that the highly concentrated extracts (1 mg/mL) of all six stevia ferments were hypoallergenic. Taken together, these findings suggest that brewer's yeast fermented from stevia leaves with a sugar solution offers promise as a natural ingredient for use in functional foods and cosmetics.

Metal oxide based electrodes play a crucial role in various as a transparent conductive oxide (TCO). One of the metal oxides, nickel oxide is a promising electrical conductive material. Here, we display that incorporation of vanadium in NiO lattice significantly improve both electrical conductivity and hole extraction. Also, vanadium doped nickel oxide exhibits a lower crystalline size compared to pristine nickel oxide, which maintains the reduction of surface roughness. These results indicating that the vanadium is an excellent dopant for NiO.

Mitochondria are highly dynamic organelles that continuously change their shape. Their main function is ATP production; however, they are additionally involved in a variety of cellular phenomena, such as apoptosis, cell cycle, proliferation, differentiation, reprogramming, and aging. The change in mitochondrial morphology is closely related to the functionality of mitochondria. Normal mitochondrial dynamics are critical for cellular function, embryonic development, and tissue formation. Thus, defect in proteins involved in mitochondrial dynamics that control mitochondrial fusion and fission can affect cellular differentiation, proliferation, cellular reprogramming, and aging. Here we review the processes and proteins involved in mitochondrial dynamics and its various associated cellular phenomena.

In this work, we report the electric energy storage properties of (1-x)Bi0.5(Na0.8K0.2)0.5TiO3-xBi0.2Sr0.7TiO3 (BNKT-BST; x = 0.15-0.50) relaxor ferroelectric ceramics enhanced via a domain engineering method. A rhombohedral–tetragonal phase, the formation of highly dynamic PNRs, and a dense microstructure are confirmed from XRD, Raman vibrational spectra, and microscopic investigations. The relative dielectric permittivity (2664 at 1 kHz) and loss factor (0.058) were gradually improved with BST (x=0.45). The incorporation of BST into BNKT can disturb the long-range ferroelectric order, lowering the dielectric maximum temperature Tm and inducing the formation of highly dynamic polar nano-regions. In addition, the Tm shifts toward high temperature with frequency and a diffuse phase transition, indicating relaxor ferroelectric characteristics of BNKT-BST ceramics, which is confirmed by the modified Curie Weiss law (γ=1.83). The rhombohedral–tetragonal phase, fine grain size, and lowered Tm with relaxor properties synergistically contribute to a high recoverable energy density Wrec of 0.81 J/cm3 and a high energy efficiency η of 86.95% at 90 kV/cm for x = 0.45.

The objective of this study was to evaluate the effects of dietary supplementation with bacteriophage and β-mannanase on health and growth performance in calves. Thirty-six pre-weaning male Holstein calves were randomly allocated to one of four dietary treatments: no supplementation, 0.1% β-mannanase, 0.1% bacteriophage, and both 0.1% bacteriophage and β-mannanase supplementation in a starter. The experiment lasted from 2 weeks before weaning to 8 weeks after weaning. Twenty-two calves survived to the end of the experiment. No interaction was observed between the two methods of supplementation. A 1-kg increase in initial BW resulted in a 1.41-fold increase in the odds ratio of survival (p < 0.01). The bacteriophage supplementation tended to increase the odds ratio of survival (p = 0.09). The number of Escherichia coli in feces significantly decreased one week after weaning. β-mannanase supplementation increased the concentrates intake (p < 0.01) and tended to increase the final BW (p = 0.08). Analysis of repeated measures indicated β-mannanase supplementation increased weekly body weight gain (p = 0.018). We conclude that bacteriophage supplementation may have a positive effect on calf survival rate, while β-mannanase supplementation may increase the growth rate and intake of a starter in calves.

Liver fibrosis is a critical health issue with limited treatment options. This study investigates the potential of PGC-Sec, a secretome derived from PGC-1α-overexpressing adipose-derived stem cells (ASCs), as a novel therapeutic strategy for liver fibrosis. Upon achieving a cellular confluence of 70-80%, ASCs were transfected with pcDNA-PGC-1α. PGC-Sec, obtained through concentration of conditioned media using ultrafiltration units with a 3-kDa cutoff, was assessed through in vitro assays and in vivo mouse models. In vitro, PGC-Sec significantly reduced LX2 human hepatic stellate cell proliferation and mitigated mitochondrial oxidative stress compared to control-secretome (Ctrl-Sec). In an in vivo mouse model, PGC-Sec treatment led to notable reductions in hepatic enzyme activity, serum pro-inflammatory cytokine concentrations, and fibrosis-related marker expression. Histological analysis demonstrated improved liver histology and reduced fibrosis severity in PGC-Sec-treated mice. Immunohistochemical staining confirmed enhanced expression of PGC-1α, OPA1 (a mitochondrial function marker), and PPARα (an anti-fibrogenic marker) in the PGC-Sec-treated group, along with reduced Collagen 1A expression (a pro-fibrogenic marker). These findings highlight the therapeutic potential of PGC-Sec in combating liver fibrosis by enhancing mitochondrial biogenesis and function, and promoting antifibrotic processes. PGC-Sec holds promise as a novel treatment strategy for liver fibrosis.

The objective of this study is to evaluate the effect of constitutive equations on the prediction accuracy for springback in cold stamping with various deformation modes. In this study, two types of yield functions—Hill’48 and Yld2000-2d—were considered to describe yield behavior. Isotropic and kinematic hardening models based on the Yoshida–Uemori model were also adopted to describe hardening behavior. Various material tests (such as uniaxial tension, tension- compression, loading-unloading, and hydraulic bulging tests) were carried out to determine the material parameters of the models. The obtained parameters were implemented in the finite element (FE) simulation to predict springback, and the results were compared with experimental data. U-bending and T-shape drawing were employed to evaluate the springback prediction accuracy. Obviously, the springback prediction accuracy was greatly influenced by constitutive equations. Therefore, it is important to choose appropriate constitutive equations for accurate description of material behaviors in FE simulation.

This research is focused on two key areas. The first is mapping the 2022 flood in the Red River of the North near Grafton, North Dakota, US, and the second is evaluating the scour potential of the Grafton Bridge. Local scour of bridge piers can cause hydraulic structures such as bridge piers and abutments to fail during floods, making it a crucial area of investigation. To collect bathymetry and discharge data during low and high flow conditions, including a flood event with a 16.5-year return period in 2022, an Autonomous Surface Vehicle (ASV) incorporated with LiDAR DEM (Digital Elevation Model) data obtained from the US Geological Survey (USGS) National Map was used. Flood mapping and evaluation of local scour around the bridge pier were conducted using the HEC-RAS 6.0.0 software, which utilizes the Colorado State University method as a default equation. This research demonstrates the potential of ASVs in collecting critical data and LiDAR DEM data is an efficient method for flood mapping and determining scour potential, as it integrates bathymetry, flow velocity, and flood prediction.

During the high-speed flight of a vehicle in the atmosphere, surface friction with the air generates aerodynamic heating. The aerodynamic heating phenomenon can create extremely high temperatures near the surface. These high temperatures impact material properties and the structure of the aircraft, so thermal deformation measurement is essential in aerospace engineering. This paper revisits high-temperature deformation measurement using the digital image correlation (DIC) technique under high-intensity blackbody radiation with a precise speckle pattern fabrication and a heat haze reduction method. The effect of speckle pattern on the DIC measurement has been thoroughly studied at room temperature, but high-temperature measurement studies have not reported such effects so far. We found that the commonly used methods to reduce the heat haze effect could produce incorrect results. Hence, we propose a new method to mitigate heat haze effects. An infrared radiation heater was employed to make an experimental setup that could heat a specimen up to 950 ℃. First, we mitigated image saturation using a short-wavelength bandpass filter with blue light illumination, a standard procedure for high-temperature DIC deformation measurement. Second, we studied how to determine the proper size of the speckle pattern under a high-temperature environment. Third, we devised a reduction method for the heat haze effect. As proof of the effectiveness of our developed experimental method, we successfully measured the deformation of stainless steel 304 specimens from 25 ℃ to 800 ℃. The results confirmed that this method can be applied to the research and development of thermal protection systems in the aerospace field.

Detection of formaldehyde is very important in terms of life protection, as it can cause serious injury to eyes, skin, mouth and gastrointestinal function if indirectly inhaled and hence researchers are putting effort in developing novel and sensitive device. In this work, we have fabricated an electro-chemical sensor in the form of a field effect transistor (FET) to detect formaldehyde over wide range (10 nM to 1 mM). For this, ZnO nanosheets (NS) were first synthesized by hydrothermal method with in-situ deposition on cleaned SiO₂ coated Si (100) substrate. The synthesized materials were characterized for morphology and purity and surface area (31.718 m²/g). The developed device was tested for formaldehyde detection at room temperature that resulted in a linear response with concentration (96%), sensitivity value of 0.27 mA/M/cm² and a low detection limit of 210 nM, and a high 0.93194 return.

Alzheimer's disease (AD) is the most common form of dementia and neurogenerative diseases (NDDs), which is one of the leading causes of death worldwide. The number of AD patients is over 55 million according to 2020 Alzheimer's Disease International (ADI) and the number is increasing drastically without any effective cure. In this review, we discuss and analyze the potential role of anthocyanins (ACNs) against AD with understanding the molecular mechanisms. ACNs have been reported as having neuroprotective effects by mitigating cognitive impairments, apoptotic markers, neuroinflammation, aberrant amyloidogenesis, and tauopathy. Taken together, ACNs could be the therapeutic agent for combating or delaying the onset of AD.

The order Mucorales, the largest in number of species within the Mucoromycotina, comprises typically fast-growing saprotrophic fungi. During a study of the fungal diversity of undiscovered taxa in Korea, two novel mucoralean strains, CNUFC-GWD3-9 and CNUFC-EGF1-4, were isolated from specific habitats including freshwater and fecal samples, respectively, in Korea. On the basis of their morphological characteristics and sequence analyses of internal transcribed spacer (ITS) and large subunit (LSU) of 28S ribosomal DNA regions, the CNUFC-GWD3-9 and CNUFC-EGF1-4 isolates were confirmed to be Gilbertella persicaria and Pilobolus crystallinus, respectively. It is ecologically, pathologically and mycologically significant to find such rare zygomycetous fungi in such specific habitats.

Licochalcone H (LCH), a regioisomer of licochalcone C derived from the root of Glycyrrhiza inflata. CRC treatment has always been challenged by the development of resistance. We investigated the antiproliferative activity of LCH in oxaliplatin (Ox)-sensitive and -resistant CRC cells. LCH significantly inhibited cell viability and colony growth in both Ox-sensitive and Ox-resistant CRC cells. We found that LCH decreased epidermal growth factor receptor (EGFR) and AKT kinase activities and related activating signaling proteins including phospho (p)-EGFR and pAKT. A computational docking model indicated that LCH may interact with EGFR, AKT1, and AKT2 at the ATP-binding sites. LCH induced ROS generation, as verified by N-acetyl-L-cysteine (NAC) treatment, and increased the expression of the ER stress markers. LCH treatment of CRC cells induced depolarization of MMP and increased. Multi-caspase activity was induced by LCH treatment and confirmed by Z-VAD-FMK treatment. LCH increased the number of subG1 cells and arrested the cell cycle at the G1 phase. LCH inhibits the growth of Ox-sensitive and Ox-resistant CRC cells by targeting EGFR and AKT, and inducing ROS generation and ER stress-mediated apoptosis. Therefore, LCH could be a potential therapeutic agent for improving not only Ox-sensitive but also Ox-resistant CRC treatment.

Displacement mapping is a computer graphics technique that enables the design of components with regularly or randomly textured surfaces that can be quickly materialized on a three-dimensional (3D) printer when needed. This approach is in principle more flexible, faster and more economical compared to conventional texturing methods, but the accuracy of the texture depends heavily on the parameters used. The purpose of this study is to demonstrate how to produce a surface-textured part using polygonal (mesh) modeling software and a photopolymerizable resin, and to develop a universal methodology to predict the dimensional accuracy of the model file log combined with a resin 3D printer. The printed components were characterized on a scanning confocal microscope. In the setup used in this study, the mesh size had to be reduced to 10% of the smallest feature size and the textured layer had to be heavily (x4) overexposed to achieve the desired accuracy. As a practical application, two functional stamps with a regular (honeycomb) and a random texture, respectively, were successfully manufactured. The insights gained will be of great benefit in quickly and cost-effectively producing components with innovative patterns and textures for a variety of hobby, industrial and biomedical applications.

An ultraviolet (UV) nanosecond pulsed laser with a wavelength of 355 nm was applied to anneal amorphous indium-gallium-zinc oxide (a-IGZO) thin-film transistors (TFT) at various laser beam powers ranging from 0 to 280 mW. Laser irradiation was selectively carried out on the a-IGZO channel area using the beam scanning method after the a-IGZO TFT was formed through indium-tin oxide (ITO) electrode patterning and a subsequent lift-off process. After laser annealing, negative shifts in the threshold voltages and enhanced on-currents were observed at laser-beam powers ranging from 54 to 120 mW. No meaningful parameters were investigated for laser beams higher than 200 mW. By extracting the energy band gap and work function of a-IGZO from the transmittance and ultraviolet photoelectron spectroscopy (UPS) results, the ITO electrode/a-IGZO channel energy band structures were established under different laser annealing conditions, and the electron injection mechanism from the ITO to the a-IGZO channel was analyzed and optimized at a laser beam power of 120 mW. The results show that the electrical characteristics of the a-IGZO TFTs can be improved without any heat damage to the substrate because of the selective annealing process.

This study compared condylar volume, length, and articular eminence (AE) characteristics in normal individuals and those with unilateral and bilateral juvenile idiopathic osteoarthritis (JOA). The 116 patients were divided into four groups: control (n=16), affected condyle of unilateral JOA (Aff-Uni) (n=36), non-affected condyle of JOA (NonAff-uni) (n=36), and bilateral JOA (Bi-JOA) (n=28). Volume and length differences in the condyle and AE were analyzed using ANOVA and Bonferroni post hoc tests. The results showed that Bi-JOA had significantly different condylar volume, especially in the condylar head (p&lt;0.01), specifically the middle, anterior, and medial parts (p&lt;0.05). Condylar length also differed among the groups, with differences observed between the control group and the other three groups, as well as between the bilateral group and the other three groups (p&lt;0.01). AE total volume differed between the control group and Aff-Uni. In the detailed comparison, Aff-Uni and NonAff-Uni were smaller than the control group in the posterior, lateral, and medial sections (p&lt;0.05). In conclusion, depending on the involvement of unilateral or bilateral JOA, there were differences in condylar volume and AE compared to the normal control group. Therefore, prognosis should be evaluated by distinguishing between patients with unilateral and bilateral JOA.

Numerous structures at the nano- and microscale manifest distinctive properties with far-reaching implications across diverse fields, including electronics, electricity, medicine, and surface engi-neering. Established methods such as nanoimprint lithography, photolithography, and self-assembly play crucial roles in the fabrication of nano- and microstructures; however, they exhibit limitations in generating high-aspect-ratio structures when utilizing high-viscosity pho-tocurable resins. In response to this inherent challenge, we propose a highly cost-effective ap-proach facilitating the direct replication of high-aspect-ratio structures, specifically nanowires, through the utilization of anodized aluminum substrates. This study elucidates the streamlined fabrication process for multiscale porous surfaces achieved through the evaporation-induced in-tegration of solid nanowires printed with high-viscosity photocurable resin.

In the paper, the authors establish two identities, which can be regarded as nonlinear differential equations, for the generating function of Eulerian polynomials, find two identities for the Stirling numbers of the second kind, and present two identities for Eulerian polynomials and higher order Eulerian polynomials, pose two open problems about summability of two finite sums involving the Stirling numbers of the second kind. Some of these conclusions meaningfully and significantly simplify several known results.

Polypyrrole (PPy)-capped caped silver nanowire (Ag NW) nanomaterials (core–shell rod-shaped Ag NW@PPy) were synthesized suing a one–port suspension polymerization technique. The thickness of PPy layer on the 50-nm-thickness/15-μm-length Ag NW was effectively controlled to 10, 40, 50, and 60 nm. Thin films cast from one-dimensional conductive Ag NW@PPy formed a three-dimensional (3-D) conductive porous network structure and provided excellent electrochemical performance. The 3-D Ag NW@PPy network can significantly reduce the internal resistance of the electrode and maintain structural stability. As a result, a high specific capacitance of 625 F/g at a scan rate of 1 mV/s was obtained from the 3-D porous Ag NW@PPy composite film. The cycling performance over a long period exceeding 10,000 cycles was also evaluated. We expect that our core–shell-structured Ag NW@PPy composites and their 3-D porous structure network films can be applied as electrochemical materials for the design and manufacture of supercapacitors and other energy storage devices.

Irrational belief is a product of complex personality traits and Machiavellianism Intelligence. The present study is conducted to trace the significance of predictive nature of personality characteristics and Machiavellianism Intelligence (Mach Intelligence) on irrational beliefs among chronically ill older people. The research method is cross-sectional with correlational design, purposive sampling with a total of 200 chronically ill older people aged between 40–60 years with disease type such as Systemic lupus erythematosus, Complicated Diabetes, Glomerulonephritis and Chronic Heart Failure. The analysis revealed that personality characteristics and irrational belief subscales such as worrying, rigidity, problem avoidance and Mach Intelligence are significantly positively correlated; however, Emotional irresponsibility has significant negative correlation with personality characteristics and Mach Intelligence. Gender differences revealed that males are high on all the subscales of personality characteristics, irrational beliefs (except emotional irresponsibility) and Mach Intelligence as com-pared to female chronically ill older people. Predictive analysis also revealed that overall personality characteristics explained a total of 67% variance in irrational beliefs. Moreover, Mach Intelligence predicts irrational beliefs. Future health related recommendations should be planned accordingly.

This research presents a comprehensive framework for efficiently generating forest fire datasets from Google Earth Engine data sources. The primary contribution of this work lies in providing a methodology to swiftly extract forest fire factors without the need for permissions or access to private datasets, rendering the dataset openly accessible and shared without barriers. Furthermore, given that the remote sensing data used is a global dataset, it can be applied in any region without restrictions. In this study, Peninsular Malaysia is chosen as a case study to demonstrate the framework's effectiveness. The generated dataset includes essential variables including the climate and environment, landcover, topography, and anthropogenic factors facilitating the analysis of fire occurrences. The methodology empowers data scientists, enabling them to leverage their analytical skills on the extracted dataset without requiring specialized remote sensing knowledge. Additionally, this study also showcases the adoption of large language models, specifically GPT-4 with the Noteable plugin, as a tool for conducting preliminary analyses on the generated dataset. Sample analyses reveal that several key features, including the KBDI, LST, PDSI, climate water deficit, and precipitation, significantly impact forest fire occurrences in Peninsular Malaysia. Despite the successful application of the GPT-4 with Noteable plugin, certain limitations and challenges are identified, highlighting the necessity for further validation of the tool's applicability and limitations. This study encourages future research to (1) adopt the proposed framework in other regions, (2) explore more detailed analyses encompassing all variables, and (3) leverage machine learning for advanced forecasting.

Diabetes mellitus is associated with cardiovascular, ophthalmic, and renal comorbidities. Among these, diabetic cardiomyopathy (DCM) causes the most severe symptoms and is considered to be a major health problem worldwide. Exercise is widely known as an effective strategy for the prevention and treatment of many chronic diseases. Importantly, the onset of complications arising from diabetes can be delayed or even prevented by exercise. Regular exercise is reported to have positive effects on diabetes mellitus and the development of DCM. The protective effects of exercise include the prevention of cardiac apoptosis, fibrosis, oxidative stress, and microvascular diseases, as well as improvement in cardiac mitochondrial function, and calcium regulation. The present review summarizes the recent findings to describe the potential mechanisms by which exercise may prevent DCM and heart failure.

In this paper, we examined the temperature variations of key constituents during the operational cycle of a custom-built electric vehicle. The vehicle was made employing a motor of 10kW, a KLS7275D controller, and a lithium-ion battery. Temperature sensors for monitoring was affixed to the motor, controller, and battery, facilitating a comprehensive analysis of thermal behaviors. A controlled 20 minute driving tests encompassing both high and low speeds were executed to scrutinize temperature variations. Our findings reveal that the controller exhibited the most substantial temperature fluctuation compared to the battery and motor. Results shows the importance of thermal management strategies for components to ensure optimal driving performance and component reliability in electric vehicles.

Clinical trials for Alzheimer’s disease (AD) face multiple challenges, such as the high screen failure rate and even allocation of heterogeneous participants. Artificial intelligence (AI), which has become a potent tool of modern science with the expansion in the volume, variety, and velocity of biological data, offers promising potential to address these issues in AD clinical trials. In this review, we introduce the current status of AD clinical trials and topic of machine learning. Then, a comprehensive review is focused on the potential applications of AI in the steps of AD clinical trials, including the prediction of AD biomarkers and differential diagnosis of AD in the prescreen during eligibility assessment and the likelihood stratification of patients who will progress to AD dementia and fast cognitive decline group from the slow decline group in randomization. Finally, this review provides challenges, developments and the future outlook on the integration of AI into AD clinical trials.

Due to its built-up chemoresistance after prolonged usage, the demand for replacing platinum in metal-based drugs (MBD) is rising. The first MBD approved by the FDA for cancer therapy was cisplatin in 1978. Even after nearly four and a half decades of trials, there has been no significant improvement in osteosarcoma (OS) therapy. In fact, many MBD have been developed, but the chemoresistance problem raised by platinum remains unresolved. This motivates us to elucidate the possibilities of the copper and zinc (CuZn) combination to replace platinum in MBD. Thus, the anti-chemoresistance properties of CuZn and their physiological functions for OS therapy are highlighted. Herein, we summarise their chelators, main organic solvents, and ligand functions in their structures that are involved in anti-chemoresistance properties. Through this review, it is rational to discuss their ligands’ roles as biosensors in drug delivery systems. Hereafter, an in-depth understanding of their redox and photoactive function relationships is provided. The disadvantage is that the other functions of biosensors cannot be elaborated on here. As a result, this review is being developed, which is expected to intensify OS drugs with higher cure rates. Nonetheless, this advancement intends to solve the major chemoresistance obstacle towards clinical efficacy.

Hydrogen energy is regarded as an auspicious future substitute to replace fossil fuels, because of its environmentally friendly characteristics and high energy density. In the pursuit of clean hydrogen production, there has been a significant focus on the advancement of effective electrocatalysts for the process of water splitting. Although noble metals like Pt, Ru, Pd and Ir are superb electrocatalysts for the hydrogen evolution reaction (HER), they have limitations for large-scale applications, mainly high cost and low abundance. As a result, non-precious transition metals have emerged as promising candidates to replace their more expensive counterparts in various applications. This review focuses on recently developed transition metal phosphides (TMPs) electrocatalysts for the HER in alkaline media due to the cooperative effect between the phosphorus and transition metals. Finally, we discuss the challenges of TMPs for HER.

Thanks to rapid development of artificial intelligence technology in recent years, the current artificial intelligence technology is contributing to many part of society. Education, environment, medical care, military, tourism, economy, politics, etc. are having a very large impact on society as a whole. For example, in the field of education, there is an artificial intelligence tutoring system that automatically assigns tutors based on student's level. In the field of economics, there are quantitative investment methods that automatically analyze large amounts of data to find investment laws to create investment models or predict changes in financial markets. As such, artificial intelligence technology is being used in various fields. So, it is very important to know exactly what factors have an important influence on each field of artificial intelligence technology and how the relationship between each field is connected. Therefore, it is necessary to analyze artificial intelligence technology in each field. In this paper, we analyze patent documents related to artificial intelligence technology. We propose a method for keyword analysis within factors using artificial intelligence patent data sets for artificial intelligence technology analysis. This is a model that relies on feature engineering based on deep learning model named KeyBERT, and using vector space model. A case study of collecting and analyzing artificial intelligence patent data was conducted to show how the proposed model can be applied to real-world problems.

In this study, reinforcement learning (RL) was used in factory simulation to optimize storage devices for use in Industry 4.0 and digital twins. First, we defined an RL environment, modeled it, and validated its ability to simulate a real physical system. Subsequently, we introduced a method to calculate reward signals and apply them to the environment to ensure the alignment of the behavior of the RL agent with the task objective. The stocker simulation model was used to validate the effectiveness of RL. The model is a storage device that simulates logistics in a manufacturing production area. The results revealed that RL is a useful tool for automating and optimizing complex logistics systems and increase the applicability of RL in logistics. We proposed a novel method for creating an agent through learning using the proximal policy optimization algorithm, and the agent was optimized by configuring various learning options. The application of reinforcement learning resulted in an effectiveness of 30% to 100%, and methods can be expanded to other fields.

Within financial technology, Blockchain is a topic that is receiving a lot of attention and discussion. There has been a meteoric rise in engagement and recent studies on this technology. The mainframe, personal computers, the Internet, and mobile applications follow the breakthrough in the history of computing. In qualitative research, the investigation was synthesized utilizing the documentary approach, including content analysis for a review article. The results reveal that Blockchain Technology is getting a foothold not only in the financial industries but is also likely to disrupt other areas like healthcare, real estate, the legal industry, security, government, education, rentals and ride-sharing, charities and aid organizations, and politics. Currently, several projects are researching the possibility of implementing the Blockchain as a structure to support them; as a result, we will soon see that it truly becomes the technology of the future. Furthermore, qualitative interviews or focus group discussions could give more insight into details. In addition, a quantitative approach for further research could provide a generalized explanation.

In this study, the multi-relaxation-time lattice Boltzmann method is applied to investigate the oscillatory instability of lid-driven flows in two-dimensional semi-elliptical cavities with different vertical to horizontal aspect ratios K in the range of 1.0--3.0. The program implemented in this study is parallelized using CUDA (compute unified device architecture), a parallel computing platform, and computations are carried out on NVIDIA Tesla K40c GPU. To carry out precise calculations, the CUDA algorithm is extensively investigated, and its parallel efficiency indicates that the maximum speedup is 47.6 times faster. Furthermore, the steady--oscillatory Reynolds numbers are predicted by implementing the CUDA-based programs. The amplitude coefficient is defined to quantify the time-dependent oscillation of the velocity magnitude at the monitoring point. The simulation results indicate that the transition Reynolds numbers correlate negatively with the aspect ratio of the semi-elliptical cavity, and are smaller than those of the rectangular cavity at the same aspect ratio. In addition, the detailed vortex structures of the semi-elliptical cavity within a single period are also investigated when the Reynolds number is larger than the steady--oscillatory value to determine the effects of periodic oscillation of the velocity magnitude.

Three-dimensional (3D) cell culture is considered more clinically relevant in mimicking the structural and physiological conditions of tumors in vivo compared to two-dimensional cell cultures. In recent years, high-throughput screening (HTS) in 3D cell arrays has been extensively used for drug discovery because of its usability and applicability. Herein, we developed a microfluidic spheroid culture device (μFSCD) with a concentration gradient generator (CGG) that enabled cells to form spheroids and grow in the presence of cancer drug gradients. The device is composed of concave microwells with several serpentine micro-channels which generate a concentration gradient. Once the colon cancer cells (HCT116) formed a single spheroid (approximately 120 μm in diameter) in each microwell, spheroids were perfused in the presence of the cancer drug gradient irinotecan for 3 days. The number of spheroids, roundness, and cell viability, were inversely proportional to the drug concentration. These results suggest that the μFSCD with a CGG has the potential to become an HTS platform for screening the efficacy of cancer drugs.

Attention deficit hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder that can diminish the quality of life of both children and adults in academic, occupational, and social contexts. The kynurenine pathway (KP) contains a set of enzymatic reactions involved in tryptophan (TRP) degradation. It is known to be associated with the risk of developing ADHD. This review will address the KP and underlying mechanism of inflammation in ADHD. Potential inflammatory biomarkers reported in the most recent studies are summarized. Although a strong neuroimmunological basis has been established due to advances of recent neurobiological research, the pathophysiology of ADHD remains unclear.

This study emphasizes the necessity of introducing a blockchain-based joint logistics system to strengthen the competency of medical supply chain management (SCM) and tries to develop a healthcare supply chain management (HSCM) competency measurement item through an analytic hierarchy process. The variables needed for using blockchain-based joint logistics are the performance expectations, effort expectations, promotion conditions, and social impact of the UTAUT model, and the HSCM competency results in increased reliability and transparency, enhanced SCM, and enhanced scalability. Word cloud results, analyzing the most important considerations to realize work efficiency among medical industry-related agencies, mentioned numerous words, including sudden situations, delivery, technology trust, information sharing, effectiveness, urgency, etc. This might imply the need to establish a system that can respond immediately to emergency situations during holidays. It could also suggest the importance of real-time information sharing to increase the efficiency of inventory management. Therefore, there is a need of a business model that can increase the visibility of real-time medical SCM through big data analysis. By analyzing the importance of securing reliability based on the blockchain technology in the establishment of a supply chain network for HSCM competency, we reveal that joint logistics can be achieved and synergistic effects can be created by implementing the integrated database to secure HSCM competency. Strengthening partnerships, such as joint logistics, will eventually lead to HSCM competency. In particular, HSCM should seek ways to upgrade its competitive capabilities through big data analysis based on the establishment of a joint logistics system.

Collagen type I production decreases with aging, leading to wrinkles and impaired skin function. Prostaglandin E2 (PGE2), a lipid-derived signaling molecule produced from arachidonic acid by cyclo-oxygenase, inhibits collagen production and induces matrix metallopeptidase 1 (MMP1) expression by fibroblasts in vitro. PGE2-induced collagen expression inhibition and MMP1 promotion are aging mechanisms. This study investigated the role of E-prostanoid 1 (EP1) in PGE2 signaling in normal human dermal fibroblasts (NHDFs). When EP1 expression was inhibited by EP1 small interfering RNA (siRNA), there were no significant changes in messenger RNA (mRNA) levels of collagen, type I, alpha 1 (COL1A1)/MMP1 between siRNA-transfected NHDFs and siRNA-transfected NHDFs with PGE2. This result showed that EP1 is a PGE2 receptor. Extracellular signal-regulated kinase 1/2 (ERK1/2) phosphorylation after PGE2 treatment significantly increased by ~2.5 times. In addition, PGE2 treatment increased the intracellular Ca²⁺ concentration in NHDFs. These results indicated that PGE2 is directly associated with EP1 pathway–regulated ERK1/2 and inositol trisphosphate (IP₃) signaling in NHDFs.

Various peptides or non-structural amino acids are recognized by their specific target proteins and perform biological role in various pathways in vivo. Understanding the interactions between target protein and peptides (or non-structural amino acids) provides key information on the molecular interactions, which can be potentially translated to the development of novel drugs. However, it is experimentally challenging to determine the crystal structure of protein-peptide complexes. To obtain structural information on substrate recognition of peptide-recognizing enzyme, X-ray crystallographic studies were performed using triglycine (Gly-Gly-Gly) as main-chain of peptide. The crystal structure of Parengyodontium album Proteinase K in complex with triglcyine was determined at 1.4 Å resolution. Two different bound conformations of triglycine were observed at the substrate recognition site. The triglycine backbone forms stable interactions with β5-α4 and α5-β6 loops of main-chain. One of the triglycine-binding conformations was identical with the binding mode of a peptide-based inhibitor from a previously reported crystal structure of Proteinase K. Triglycine has potential application X-ray crystallography to identify substrate recognition sites in peptide binding enzymes.

Energy demand and consumption in recent times have witnessed a rapid proliferation influenced by technological developments, increased population and economic growth. This has fuelled research trends in the domain of energy management employing tri-generation systems such as the combined cooling, heating and power (CCHP) systems. Furthermore, the incorporation of renewable energy, especially solar energy, to complement the thermal input by fossil fuels has facilitated the effectiveness and sustainability of CCHP systems. This study proposes a new approach to improve the overall efficiency of CCHP systems and compute the optimal design parameters in order to assist decision makers to identify the best geometrical configuration. A multi-objective optimization formulation of a solar-assisted CCHP system was adopted to maximize the net power, the exergy efficiency and minimize the CO2 emission using the greywolf optimization technique. In addition, the effects of the decision variables on the objective functions were analysed. The proposed optimization approach yielded 100 set of Pareto optimal solutions which would serve as options to the decision maker to make a selection in order to improve the performance of a solar-assisted CCHP system. This study demonstrates that the proposed approach is potentially suitable for the optimization of a solar-assisted CCHP system.

Cardiomyopathies are diseases of heart muscle, a significant percentage of which are genetic in origin. Cardiomyopathies can be classified as dilated, hypertrophic, restrictive, arrhythmogenic right ventricular or left ventricular non-compaction, although mixed morphologies are possible. A subset of neuromuscular disorders, notably Duchenne and Becker muscular dystrophies, are also characterized by cardiomyopathy aside from skeletal myopathy. The global burden of cardiomyopathies is certainly high, necessitating further research and novel therapies. Genome editing tools, which include zinc finger nucleases (ZFNs), transcription activator-like effector nucleases (TALENs) and clustered regularly interspaced short palindromic repeats (CRISPR) systems have emerged as increasingly important technologies in studying this group of cardiovascular disorders. In this review, we discuss the applications of genome editing in the understanding and treatment of cardiomyopathy. We also describe recent advances in genome editing that may help improve these applications, and some future prospects for genome editing in cardiomyopathy treatment.

Manual interpretation of these huge amounts of image volumes are susceptible to inter-reader variability and human error. Thus, accurate automated CAD scheme is highly desirable in clinical pathological diagnosis. In this research, plethora of machine learning paradigms (e.g. feature extraction, dimensionality reduction and supervised classification methods) were explored, evaluated, compared and analyzed to identify the optimal pathway for brain MR images (normal vs neoplastic) binary classification task. External validation dataset was used to test the generalizability of the optimal predictive models implemented. Relevant and informative features were selected to construct cross-validated decision tree and eventually simple rule set was built based on the decision tree. The experimental results show that almost all pattern recognition paradigms achieve high accuracy with careful selection of number of attributes. LDA+ELM with 55 features are the optimal pipelines which achieve perfect classification when training and test data are of same source; and achieving (accuracy=97.5%, AUC=0.989, sensitivity=95% and specificity=100%) under balanced test dataset; (accuracy=99.5%, AUC=0.988, sensitivity=95% and specificity=100%). Cross-validated decision tree model also shows comparable performance: accuracy=98.8%, AUC=99.1%, sensitivity=99.6% and specificity=98.2%. Three highly relevant and robust attributes are visualized and selected for construction of decision tree models and finally a rule sets are read directly off the decision tree. This rule sets can potentially serve as fast and accurate classification algorithm.

We introduce the lower chaos grade of a real-valued function F defined on the Markov triple (E,μ,Γ), where μ is a probability measure and Γ is the carré du champ operator. As an application of this concept, we obtain the better estimate of the four moments theorem for Markov diffusion generators worked by Bourguin et al (2019). For our purpose, we need to find the largest number except zero in the set of eigenvalues corresponding to its eigenfunction in the case where the square of a random variable F, coming from a Markov triple structure, can be expressed as a sum of eigenfunctions, We give some examples of eigenfunctions of the diffusion generators such as Ornstein-Uhlenbeck, Jacobi and Romanovski-Routh. In particular, two bounds, called the four moments theorem and fourth moment theorem respectively, will be provided for the normal approximation of the case where a random variable F comes from eigenfunctions of a Jacobi generator.

The aim of this work was to classify the business incubators in Spain according to the four phases of startups incubation. Taking into account that the graduation rate implies greater survival and business success of the incubated companies, they have been identified at each stage of the incubation (spread of entrepreneurship, pre-incubation, advanced incubation, and graduation). The activities that present higher impacts on the success of the incubated companies and the activities carried out by the incubator that have a greater relevance on the graduation of the companies have concretely been considered. Principal component (PC) cluster analysis have been applied. All the incubation variables were used simultaneously, reducing their number, and grouping them into factors, finally the cases were grouped according to these latent variables. Principal components analysis reduced dimensionality to 8 factors with a 74 % of explained variance. Factor 1 was positively related to pre-incubation variables, factor 2 was linked to training and collaboration variables within the entrepreneurship diffusion phase. Factor 3 called activity monitoring and control and was related to phase 3 or basic incubation variables. Clusters analysis facilitates the grouping of incubators into three clusters: Group 1 (16 % of the total), incubators with strong deficits in incubation phases 1, 2 and 3. They are small Business Incubators, often located in rural areas or cities and low graduation rate. Group 2 (30 %), business incubators with very high graduation rate, and strongly positive values in factor 1 and 2. Factor 3 although positive is susceptible to improvement. They are the largest incubators and usually located in industrial and technological parks. Group 3 (54 %) is the majority, with values close to cluster 2 and 3.