(1) Background: P-cadherin (CDH3) is a transmembrane protein that plays a crucial role in maintaining the structural integrity of epithelial tissue and homeostasis. Its role in carcinogenesis remains a subject of debate, as its behavior can vary depending on the molecular context and the specific tumor cell model under study. In this study, we explored the role of P-cadherin in head and neck squamous cell carcinoma (HNSCC) and the mechanism underlying its function. (2) Methods: We analyzed P-cadherin expression in HNSCC patients using The Cancer Genome Atlas (TCGA) database. For in vitro functional analysis, we conducted proliferation, migration, invasion, and western blot assays after either suppressing or overexpressing P-cadherin. For in vivo functional analysis, we utilized mouse xenograft models. (3) Results: P-cadherin was significantly overex-pressed in tumor samples compared to normal samples in the TCGA-HNSCC cohort. P-cadherin knockdown resulted in decreased proliferation, migration, and invasion compared to control cells, while P-cadherin overexpression increased cell proliferation and migration in HNSCC cells. We discovered that c-Met functioned as an upstream regulator of P-cadherin. Surprisingly, we found that P-cadherin knockdown increased the phosphorylation of c-Met and STAT3. Combining P-cadherin siRNA with the c-Met inhibitor SU11274 resulted in a more effective reduction in HNSCC cell growth, both in vitro and in vivo, compared to either treatment alone. (4) Conclusions: Our study uncovered a previously unknown aspect of P-cadherin-mediated c-Met regulation. The enhanced activation of c-Met/STAT3 following P-cadherin inhibition could be responsible for the survival of resistant tumor cells. Therefore, dual inhibition of P-cadherin and c-Met may be a potentially effective approach for treating HNSCC.

Accurate and consistent rainfall observations are vital for climatological studies in support of better planning and decision making. However, estimation of accurate spatial rainfall is limited by sparse rain gauge distributions. Satellite rainfall products can thus potentially play a role in spatial rainfall estimation but their skill and uncertainties need to be under-stood across spatial-time scales. This study aimed at assessing the temporal and spatial performance of seven satellite products (TARCAT (Tropical Applications of Meteorology using SATellite and ground-based observations (TAMSAT) African Rainfall Climatology And Time series), Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), Tropical Rainfall Measuring Mission (TRMM-3B43), Climate Prediction Center (CPC) Morphing (CMORPH), the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks- Climate Data Record (PERSIANN-CDR), CPC Merged Analysis of Precipitation (CMAP) and Global Precipitation Climatology Project (GPCP) using gridded (0.05o) rainfall data over East Africa for 15 years(1998-2012). The products’ error distributions were qualitatively compared with large scale horizontal winds (850 mb) and elevation patterns with respect to corresponding rain gauge data for each month during the ‘long’ (March-May) and ‘short’ (October-December) rainfall seasons. For validation only rainfall means extracted from 284 rain gauge stations were used, from which qualitative analysis using continuous statistics of Root Mean Squared Difference, Standard deviations, Correlations, coefficient of determinations (from scatter plots) were used to evaluate the products’ performance. Results revealed rainfall variability dependence on wind flows and modulated by topographic influences. The products’ errors showed seasonality and dependent on rainfall intensity and topography. Single sensor and coarse resolution products showed lowest performance on high ground areas. All the products showed low skills in retrieving rainfall during ‘short’ rainfall season when orographic processes were dominant. CHIRPS, CMORPH and TRMM performed well, with TRMM showing the best performance in both seasons. There is need to reduce products’ errors before applications.

Antibiotics’ effect on Mycoplasma pneumoniae (MP) infection still remains controversial. A prospective study of 257 children with MP pneumonia during a recent epidemic (2015-2016) was conducted. All MP pneumonia patients were treated with corticosteroids within 24-36 h after admission. Initially, oral prednisolone (1 mg/kg) or intravenous methylprednisolone (IVMP) (1-2 mg/kg) was administered for mild pneumonia patients, and IVMP (5 -10 mg/kg/day) for severe pneumonia patients. If patients showed persistent fever for 36-48 hours or disease progression, additive IVMP (5 mg/kg or 10 mg/kg) was given. Eighty-five patients received only a broad-spectrum antibiotic without macrolide. The mean age and the male:female ratio were 5.6 ± 3.1 years, respectively. Seventy-four percent of patients (190/257) showed immediate defervescence within 24 h, and 95.7% (246/257) of patients showed defervescence within 72 h with improvements in clinical symptoms. Eight patients who received additive IVMP also showed clinical improvement within 48 h without adverse reactions. There were no clinical or laboratory differences between patients treated with a macrolide (n = 172) and without (n = 85). Early corticosteroid therapy might reduce disease morbidity and prevent disease progression in MP pneumonia patients without side effects, and antibiotics may have limited effects on MP infection.

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.

Tailings generated by mining account for the largest proportion of global waste from industrial activities. Copper is relatively uncommon world-wide, with low concentrations in sediments and waters, yet is very elevated around mining sites. On the Keweenaw Peninsula of Michigan, USA, jutting out into Lake Superior, 140 mines extracted native copper from the Portage Lake Volcanic Series, part of an intercontinental rift system. Between 1901-1932, two mills at Gay (Mohawk, Wolverine) sluiced 22.7 million metric tonnes (MMT) of copper-rich tailings (stamp sands) into Grand (Big) Traverse Bay. Here we examine: 1) 3D coastal elevation and reef bathymetry, 2) particle dispersal, 3) copper concentrations and leaching, plus 4) shoreline toxicity. About 10 MMT of tailings created a migrating coastal beach that stretches 7 km from the Gay pile to the Traverse River Seawall. Another 10 MMT are moving underwater on the coastal shelf, threatening Buffalo Reef, an important lake trout and whitefish breeding ground. Aerial photos, ALS (plane) LiDAR, and relatively inexpensive UAS (drone) surveys characterize shoreline structure and aid initial remediation. Because sands (natural beach quartz, stamp sand basalt) are silicates of similar density, particle dispersal is similar and challenging. However, stamp sand beaches contrast greatly with natural sand beaches in both physical profile and chemistry. Dispersing particles retain copper, and release toxic concentrations. Leaching is elevated by exposure to high DOC and low pH waters. Field experiments, shoreline seining, and benthic sampling confirm serious impacts on aquatic biota, supporting tailings removal.

Enveloped viruses represent a significant category of pathogens that cause serious diseases in animals. These viruses express envelope glycoproteins that are singularly important during infection of host cells by mediating fusion between the viral envelope and host cell membranes. Despite low homology at protein levels, three classes of viral fusion proteins have, as of yet, been identified based on structural similarities. Their incorporation into viral particles is dependent upon their proper sub-cellular localization after being expressed and folded properly in the endoplasmic reticulum (ER). However, viral protein expression can cause stress in the ER, and host cells respond to alleviate the ER stress in the form of the unfolded protein response (UPR); the effects of which have been observed potentiating or inhibiting viral infection. One important arm of UPR is to elevate the capacity of the ER-associated protein degradation (ERAD) pathway, which is comprised of host quality control machinery that ensures proper protein folding. In this review, we provide relevant details regarding viral envelope glycoproteins, UPR, ERAD, and their interactions in host cells.

Artisanal and small-scale gold mining (ASGM) has been an important source of income for communities in the Madre de Dios River Basin in Peru for hundreds of years. However, in recent decades, the scale of ASGM activities in the region has increased dramatically, and exposures to a variety of occupational and environmental hazards related to ASGM, including mercury, are becoming more widespread. The aims of our study were to: (1) examine patterns in the total hair mercury level of human participants in several communities in the region and compare these results to the 2.2 µg/g total hair mercury level equivalent to the World Health Organization (WHO) Expert Committee of Food Additives (JECFA)’s Provisional Tolerable Weekly Intake (PTWI); and (2), to measure the mercury levels of paco (Piaractus brachypomus) fish raised in local aquaculture ponds, in order to compare these levels to the EPA Fish Tissue Residue Criterion of 0.3 µg Hg/g fish (wet weight). We collected hair samples from 80 participants in four communities (one control and three where ASGM activities occurred) in the region, and collected 111 samples from fish raised in 24 local aquaculture farms. We then analyzed the samples for total mercury. Total mercury levels in hair were statistically significantly higher in the mining communities than in the control community, and increased with increasing distance away from the Madre de Dios headwaters (as the crow flies), did not differ by sex, and frequently exceeded the reference level. Regression analyses indicated that higher hair mercury levels were associated with residence in ASGM communities. The analysis of paco fish samples found no samples that exceeded the EPA tissue residue criterion. Collectively, these results align with other recent studies showing that ASGM activities are associated with elevated human mercury exposure. The fish farmed through the relatively new process of aquaculture in ASGM areas appeared to have little potential to contribute to human mercury exposure. More research is needed on human health risks associated with ASGM to discern occupational, residential, and nutritional exposure, especially through tracking temporal changes in mercury levels as fish ponds age, and assessing levels in different farmed fish species. Additionally, research is needed to definitively determine that elevated mercury levels in humans and fish result from the elemental mercury from mining, rather than from a different source, such as the mercury released from soil erosion during deforestation events from mining or other activities.

Post-training quantization is pivotal in deploying convolutional neural networks for mobile applications. Block-wise reconstruction with adaptive rounding, as employed in prior works like BrecQ and Qdrop, facilitates acceptable 4-bit quantization accuracy. However, adaptive rounding is time-intensive, and its constraint on weight optimization space curtails the potential for quantization performance. The optimality of block-wise reconstruction hinges on the quantization status of subsequent network blocks. In this investigation, we delve into the theoretical underpinnings of the limitations inherent in adaptive rounding and block-wise reconstruction. Our exploration leads to the development of a post-training quantization methodology, designated as AE-Qdrop. This algorithm operates in two distinct phases: block-wise reconstruction and global fine-tuning. The block-wise reconstruction phase introduces a progressive optimization strategy, superseding adaptive rounding, which not only augments quantization precision but also significantly improves quantization efficiency. To mitigate the risk of overfitting, we introduce a random weighted quantized activation mechanism. During the global fine-tuning phase, we account for interdependencies among quantized network blocks. The weight of each network block will be corrected with logit matching and feature matching. Extensive experiments validate that AE-Qdrop achieves high-precision and efficient quantization. For instance, in the case of 2-bit MobileNetV2, AE-Qdrop outperforms Qdrop by achieving a 6.26% enhancement in quantization accuracy and quintupling the quantization efficiency.

: This study aimed to validate the effects of self-compassion-based forest healing therapy as an intervention for reducing stress and promoting coping resources. Therefore, we investigated the effects of self-compassion-based forest healing therapy on stress, self-compassion, and connectedness to nature. A total of 30 participants were divided into an experimental and control group. Two sessions of forest healing meditation activities were held at the Forest of Healing every two weeks between October and November 2023. As a repeated measures experiment, data were collected before the intervention, after the first intervention, and after the second intervention. Perceived stress, positive and negative affect, and salivary cortisol were measured to assess physiological and psychological stress in participants. Connectedness to nature and self-compassion were measured to evaluate stress-coping resources. The results showed that the forest healing program had significant positive effects on stress and emotional states in the experimental group after the intervention. Further, there was a significant incremental effect on connectedness to nature and self-compassion in the experimental group. Therefore, self-compassion meditation-based forest healing therapy is a feasible and efficient approach for facilitating stress management and coping resource building.

Arthrospira platensis is the widely available source of spirulina and contains distinctive natural pigments including carotenoids and C-phycocyanin (C-PC). In this study, the major carotenoid and C-PC contents were determined in seven commercially available spirulina powder products and laboratory-prepared A. platensis trichomes (AP-1) by an LC-DAD method and a UV-Visible spectrometry, respectively. The correlation of these two pigment content levels with Hunter color coordinates and antioxidant activity was also evaluated. The L* value failed to show a significant correlation with pigment content, but a positive correlation was observed between a* values and the contents of total carotenoid and C-PC. As b* values decreased, the total carotenoid and C-PC contents increased. AP-1 exhibited the highest content of total carotenoids, chlorophyll a and C-PC, and antioxidant activities among the samples. This observation could be related to degradation of these pigments during the mass production process. The carotenoid profiles suggested that the commercial spirulina powders originated from two different sources, A. platensis and A. maxima. Total carotenoid and C-PC content exhibited positive significant correlations with antioxidant activities measured by DPPH and ABTS assays. These results provide a strong scientific foundation for the establishment of standards for the commercial distribution of quality spirulina products.

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 < 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.

The geographical environment, food culture, and dietary habits are substantially different between the southern and northern regions in China. We investigated the associations with dietary patterns and metabolic syndrome between Chinese adult from the southern and northern regions (North: 1249; South: 1849) using data from the Chinese Health and Nutrition 2009 survey. Respectively, four dietary patterns were identified by factor analysis in the two regions. Each dietary pattern of factor score was calculated for three groups by tertile (T1<T2<T3). In the northern region, the association between the Alcohol and Western pattern and the risk of abdominal obesity (OR: 1.31; 95%:1.01, 1.68), hypertriglyceridemia (OR: 1.35; 95%:1.05, 1.74), high fasting blood glucose (OR: 1.37; 95%: 1.05, 1.80), and hypertension (OR: 1.55; 95%: 1.45, 1.99) was increased. In the southern region, the Convenience Food pattern was positively associated with hypertriglyceridemia (OR: 1.53; 95%: 1.03, 2.26), low HDL-cholesterol (OR: 1.96; 95%: 1.12, 3.43), and metabolic syndrome (OR: 1.79; 95%: 1.03, 3.11). The Alcohol dietary pattern was positively associated with high fasting blood glucose (OR: 1.83, 95%: 1.13, 2.97). There are some dietary pattern differences in the two regions. It is necessary to consider the factors of food culture and food intake habits in order to provide nutrition education to Chinese individuals from different regions in the future.

As a representative of Exponential Organizations, MI went from obscurity to the Fortune 500 in just ten years. Mi's success is inextricably linked to its outstanding business model. This paper summarizes the elements of MI's business model from four perspectives: value proposition, value creation, value delivery, and value capture, as well as its measures for developing into an exponential organization. Expecting to provide theoretical references for the transformation and upgrading of manufacturing organizations.

Revolutionizing Lng Plant Construction and its Comprehensive Comparative Analysis And Evaluation Of Modular Design Development Versus Stick-Built Approach For Enhanced Efficiency And Cost-Effectiveness,.Although the utilization of modularization concepts in the LNG industry remains limited, this study focuses on exploring their potential. It is worth noting that modular units typically incur higher costs compared to field erected units due to the additional requirements of structural steel and robustness for transportation purposes.Nevertheless, the increased cost of modularization can often be balanced by conducting the work at the fabrication site instead of on-field construction. This approach reduces the overall project cost by minimizing field construction expenses and shortening the construction schedule. The objective of this paper is to assess and compare LNG modularization options for a newly established LNG facility in comparison to a conventional stick-built plant used as the base case.:The paper delves into various topics related to LNG plant construction, such as the development of modular units, a comprehensive comparison of different options, evaluation of construction schedules and manpower requirements, logistics considerations, and a recommended approach for design and construction. The cost estimates and engineering, procurement, and construction (EPC) schedules are meticulously compared for each option. Additionally, an inshore/near shore gravity base structure (GBS) option is included for further comparison. It is crucial to emphasize that establishing general costs is not possible as each project is distinct and requires individual study and analysis.:Each project has unique characteristics, resulting in varying shapes of cost curves and break-even points. The outcomes of the feasibility evaluation play a crucial role in determining the extent to which the modular approach to construction is advantageous for the specific project at hand. The evaluation takes into consideration multiple factors to determine the potential benefits of adopting a modular construction approach, allowing decision-makers to make informed choices regarding the project's construction methodology

(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.

To ensure the safety in aircraft flying, we aim use of the deep learning methods of nondestructive examination with multiple defect detection paradigms for X-ray image detection posed. The use of the Fast Region-based Convolutional Neural Networks (Fast R-CNN) driven model seeks to augment and improve existing automated Non-Destructive Testing (NDT) diagnosis. Within the context of X-ray screening, limited numbers insufficient types of X-ray aeronautics engine defect data samples can thus pose another problem in training model tackling multiple detections perform accuracy. To overcome this issue, we employ a deep learning paradigm of transfer learning tackling both single and multiple detection. Overall the achieve result get more then 90% accuracy based on the AE-RTISNet retrained with 8 types of defect detection. Caffe structure software to make networks tracking detection over multiples Fast R-CNN. We consider the AE-RTISNet provide best results to the more traditional multiple Fast R-CNN approaches simpler translate to C++ code and installed in the Jetson™ TX2 embedded computer. With the use of LMDB format, all images using input images of size 640 × 480 pixel. The results scope achieves 0.9 mean average precision (mAP) on 8 types of material defect classifiers problem and requires approximately 100 microseconds.

The aim of the study is to assess the loads that are transferred from the main rotor and the tail rotor to the helicopter fuselage. These loads change in the various phases of the transient flight as a result of the variable control of the maneuver and as a result of the variable flow around the blades. The knowledge of the loads allows for the proper selection of the level of excitations that should load the fuselage structure during fatigue and strength tests. The simulation model describing the helicopter flight is discussed. This model takes into account the motion of each blade relative to its hinges. Results are shown for two maneuvers - pullup/pushover and diving. The values of extreme loads transferred to the fuselage were obtained.

This paper presents a piezoresistive pressure sensor with a shield layer for improved stability. Compared with the conventional piezoresistive pressure sensors, p-type piezoresistors are covered by an n-type shield layer, which is formed by ion implantation. The proposed pressure sensors have been successfully fabricated by bulk micromachining techniques. The impact of electrical field on piezoresistors is studied by simulation. The temperature drift of the pressure sensor has been investigated by both simulation and experimental measurement. Characteristics of developed pressure sensors are tested from -40 C to 125 C. A sensitivity of 0.022 mV/V/KPa and a maximum non-linearity of 0.085% FS are measured for the fabricated sensor in a pressure range of 1 MPa. The temperature coefficients of resistance of shielded piezoresistors are found to be smaller than those of un-shielded ones. It is demonstrated that the shield layer is able to reduce the drift caused by electrical field and ambient temperature variation.

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.

Our lives are comprised of moment-to-moment activity experiences. According to the Model of Human Occupation (MOHO), our occupational experiences can be affected by volition, which consists of personal causation, values, and interests. This study investigated how momentary volition affected occupational satisfaction and mind-wandering while performing occupations. This study also examined the relationship between momentary volition and the overall life perspectives of life satisfaction and life balance. Undergraduate students participated in this cross-sectional study. The experience sampling method (ESM) was used to measure students’ momentary states such as activity, volition, occupational satisfaction, and mind-wandering. After conducting the ESM, the participants’ life satisfaction was measured using the Satisfaction With Life Scale (SWLS), and their life balance was measured by the Life Balance Inventory (LBI). Forty-two participants and 1,092 sampling data were included in the analysis. Momentary personal causation, values, and interests contributed to occupational satisfaction. Mind-wandering was predicted negatively by interests but positively by personal causation. Momentary interests were positively correlated with SWLS and LBI scores. This study demonstrated that momentary volition was associated with occupational satisfaction and engagement, as well as life satisfaction and balance, in undergraduate students.

(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.

As the demand for fossil fuels continues to rise and their availability becomes increasingly limited, it is crucial to explore innovative approaches to optimize fuel combustion in existing systems. Among various engines, diesel engines are heavily reliant on fluid motion within the engine cylinder, which plays a critical role in fuel-air mixing. This abstract focuses on the potential of dynamic mathematical model simulation for multi-compartment rotor compressed combustion engines, aiming to revolutionize power generation by enhancing fuel burning efficiency. By leveraging advanced simulation techniques, this research seeks to unlock new insights into fluid dynamics and optimize fuel-air mixing, leading to more efficient and sustainable energy utilization. Through this exploration, we aim to pave the way for groundbreaking advancements in the field of combustion engines, ultimately contributing to a greener and more sustainable future. In the realm of internal combustion engines, the fluid dynamics within the engine cylinder greatly influence the combustion processes and heat transfer. For compression ignition (C.I) engines, both the bulk gas motion and turbulence characteristics play vital roles in engine performance. This study focuses on enhancing the combustibility of the fuel-air mixture in C.I engines by modifying the engine design to induce turbulence through squish and tumble flows. The modification involves creating multiple compartments on the rotor crown, comprising three small chambers spaced 120º apart. By implementing this design, the aim is to optimize the fuel-air mixing and improve the overall combustion efficiency. Through comprehensive analysis and experimentation, we seek to revolutionize C.I engine technology and pave the way for more efficient and environmentally-friendly power generation. In this study, the performance of a compression ignition (C.I) engine with a multiple compartment rotor has been analyzed under motoring conditions using computational fluid dynamics (CFD) simulations with FLUENT software. The obtained results have been compared with those of a base C.I engine. The analysis focused on the effects of the modified engine design on the tumble ratio and squish velocity, which are important parameters for fuel-air mixing and combustion efficiency. The results indicated a significant improvement with the modified engine, with a 35% increase in tumble ratio and a 31% increase in squish velocity compared to the base engine. These findings suggest that the modified engine design has the potential to enhance fuel-air mixing and combustion performance, leading to improved overall engine efficiency. This research presents promising insights into the optimization of C.I engine design and contributes to the development of more efficient and environmentally-friendly power generation technologies..

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.

Air passenger traffic prediction is crucial for the effective operation of civil aviation airports. Despite some progress in this field, the prediction accuracy and methods need further improvement. This paper proposes an integrated approach to the prediction of air passenger index as follows. Firstly, the air passenger index is defined and classified by the K-means clustering method. Based on the mutual information (MI) principle, the information entropy is used to analyze and select the key influencing factors of air passenger travel. By incorporating the MI principle into the support vector regression (SVR) framework, this paper presents an innovative MI-SVR machine learning model used to predict the air passenger index. Finally, the proposed model is validated by passenger throughput data of the Shanghai Pudong International Airport, China. The experimental results prove the model feasibility and effectiveness by comparing them with conventional methods, such as ARIMA, LSTM, and other machine learning models, outperformed by the MI-SVR model. Besides, it is shown that the prediction effect of each model could be improved by introducing influencing factors based on mutual information. The main findings are considered instrumental to the airport operation and air traffic optimization.

Air passenger traffic prediction is crucial for the effective operation of civil aviation airports. Despite some progress in this field, the prediction accuracy and methods need further improvement. This paper proposes an integrated approach to the prediction of air passenger index as follows. Firstly, the air passenger index is defined and classified by the K-means clustering method. Based on the mutual information (MI) principle, the information entropy is used to analyze and select the key influencing factors of air passenger travel. By incorporating the MI principle into the support vector regression (SVR) framework, this paper presents an innovative MI-SVR machine learning model used to predict the air passenger index. Finally, the proposed model is validated by passenger throughput data of the Shanghai Pudong International Airport, China. The experimental results prove the model feasibility and effectiveness by comparing them with conventional methods, such as ARIMA, LSTM, and other machine learning models, outperformed by the MI-SVR model. Besides, it is shown that the prediction effect of each model could be improved by introducing influencing factors based on mutual information. The main findings are considered instrumental to the airport operation and air traffic optimization.

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.

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

Mental wellness can be related to healthier living, the learning process and working environments for people in the university community. A wide range of mental wellness programmes have been explored to provide students with pleasant and satisfying experiences. The purpose of this study is to explore the effects of integrating Zen meditation(禪)and music listening on the mindfulness and happiness levels of university music therapy students. Qualitative methodology was used, and data were collected through surveys and semi-structured interviews. To investigate various aspects of data regarding the role of meditation and music (MM) programme for mindfulness and happiness, this study used thematic analysis within a qualitative research design. The results of this study indicate that the 8-week MM programme is effective in enhancing mindfulness and happiness and has positive responses to daily life stress (e.g., exam anxiety, financial difficulties, and emotional distress during the COVID-19 pandemic). The role of meditation and music in promoting mental health and well-being has long been discussed and the combination of the two has been recognised as a beneficial intervention. This paper could contribute to the support of mental health resources and coping strategies in higher education, as well as expand the potential range of integrating practices involving music and meditation.

This paper investigates the density, phase composition, microstructure and mechanical properties (microhardness, fracture toughness) of binderless WC + SiC ceramics obtained by conventional pressureless sintering (CPS) and Spark Plasma Sintering (SPS). α-WC nanopowders obtained by DC arc plasma chemical synthesis and β-SiC powders have been used as raw materials. The content of SiC particles was 1, 3, 5% wt. Excess graphite (0.3, 0.5% wt.) was added to α-WC nanopowders to decrease the volume fraction of W2C particles that negatively affect the mechanical properties of ceramics. WC + 1% wt. SiC + 0.3% wt. C ceramics are shown to have a homogeneous fine-grained microstructure, high relative density, increased microhardness and Palmquist fracture toughness. The CPS and SPS activation energies of WC + SiC nanopowders at an intensive shrinkage stage are determined using the Young-Cutler model. The effect of carbon and SiC particles on the CPS and SPS activation energies of tungsten carbide nanopowders has been analyzed. The CPS activation energies of WC, WC + C and WC + SiC + C nanopowders are shown to be closer to the carbon diffusion activation energy along α-WC grain boundaries. The SPS activation energies of WC and WC + SiC nanopowders turn out to be lower than the carbon grain boundary diffusion activation energy of α-WC.

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.

We report an agent-based model to compare the effectiveness of simple and complex mobile dating application interfaces in generating matches for virtual users. We define the relative complexity of dating applications as the number of available features and dub this variable, the multiplicity. We replicate some of the most popular mobile dating applications through the generation of a synthetic population endowed with attributes, preferences, and behaviors drawn from literature. We treat our data as a network dataset and use a robust statistical procedure (MRQAP) to issue a valid and reliable comparison between simulated applications. We show how the quadratic assignment procedure can be used to compare network simulations rigorously. As a result, we observe a direct relationship between multiplicity and agent-level experiences and expectations in match generation. We also observe the emergence of divergent matching systems with minor rule changes as well as several expected properties of online dating systems. This work serves as a proof-of-concept in the integration of classical social network analysis methods with agent-based modeling to compare virtual designs and to enhance the policy-generation process of online social networks.

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.

Field cricket (Gryllus bimaculatus) is newly emerged as an edible insect in several countries. Anti-inflammatory effect of glycosaminoglycan derived this cricket was not fully investigated on chronic disease animal model such as diabetic mouse. For potential therapeutic agents, anti-diabetic activities of field cricket glycosaminoglycan (GbG) was evaluated in diabetic mice based on their abilities to reduce glucose, ALT, AST, LDL-cholesterol, and BUN levels, compared with dung beetle (Catharsius molossus) glycosaminoglycan (CaG) as a positive control glycosaminoglycan. Db mice were orally administered for one month according to their groups: Db Hetero (normal), Db Homo (type-2 diabetic), CaG (5 mg/kg), GbG (5 mg/kg), and metformin (10 mg/kg). Blood glucose level was decreased after 1^st week treatment with GbG. It also inhibited LDL-cholesterol and alkaline phosphatase levels. Regarding oxidative damage of diabetic state, levels of hepatocellular biomarkers levels and protein carbonyl content were reduced in db mice treated with GbG. Especially anti-oxidative activities of catalase, superoxide dismutase, and glutathione peroxidase were significantly increased in GbG treated group compared to those in the control. GbG was composed of heparin disaccharides and main N-glycan was identified as Hex₉GlcNAc₂ (m/z 1905.7) of with neutral mono-sugar mainly comprising of hexose, L (+) rhamnose by mass spectroscopy. These results from sero-biochemical, hepatocellular anti-oxidant assay in db mice data suggest cricket (G. bimaculatus) glycosaminoglycan might play a role in its anti-diabetic action.

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.

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.

As human activities of the countries in the East Asia have been remarkably expanding over recent decades, various problems in relation to ships, such as oil spill and many other coastal marine pollution, are continuously occurring in the coastal region. In order to conserve marine resources and prepare for possible ship accidents in advance, the need for efficient ship management is increasing over time. Multi-satellite, multi-sensor, multi-wavelength or multi-frequency observations make it possible to monitor a variety of vessels in the coastal region. This study presents the results of ship detection methodology applied to multi-spectral satellite images in the seas around Korean Peninsula based on optical, hyperspectral, and microwave remote sensing. To detect ships from hyperspectral images with a few hundreds of spectral channels, spectral matching algorithms are used to investigate similarity between the spectra and in-situ measurements. In the case of SAR (Synthetic Aperture Radar) images, the Constant False Alarm Rate (CFAR) algorithm is used to discriminate the vessels from backscattering coefficients of Sentinel-1 SAR and ALOS-2 PALSAR2 images. The present ship detection methods can be extensively utilized for optical, hyperspectral, and SAR images for comprehensive coastal management purposes toward perpetual sustainability in the future.

Factors responsible of species distribution were intensively investigated in the past, including response at different spatial scales. The aim of the present research is to review the most relevant factors explaining chironomid species distribution focusing to factors operating at different spatial scales, such as latitude, longitude, altitude, water temperature, dissolved oxygen, nutrients acting at regional, country, water basin extension. Data including chironomid species abundances from different lentic and lotic waters from Italy and other surrounding countries were analyzed with different multivariate methods: partial canonical correspondence analysis and multiple discriminant analysis. Spatial analysis included univariate Moran’I correlograms, multivariate Mantel correlograms and Moran’s Eigenvectors Maps (MEM) calculation. The results confirmed previous conclusions, that is habitat type including different running waters reaches (kryal, krenal, rhthral, potamal) and different lake types is the most significant factor in separating chironomid assemblages and spatial factors act only as indirect influencers..

Cervi cornu has been extensively used in traditional medicine as an antioxidant and for the treatment of various disorders, including osteoporosis. However, since it is not easy to separate the active ingredient, absorption is not performed well. In this study, we extracted the low molecular weight (843Da) collagen NP-2007 from cervi cornu by enzyme hydrolyzation, and evaluated the therapeutic effect in a monosodium iodoacetate (MIA)-induced rat osteoarthritis model, and identified their molecular mechanisms. NP-2007 was orally administered at 50, 100, and 200 mg/kg for 21 d. Efficacy was evaluated based on serum parameters, inflammatory mediators, and mor-phological and histopathological analyses of knee joints. Production of matrix metalloproteinases, including MMP-2, MMP-3, and MMP-9, in the serum was higher in MIA-treated rats; however, these levels decreased after NP-2007 treatment. Serum levels of tumor necrosis factor-α, interleukin (IL)-1β, IL-6, and prostaglandin E2 were lower in the NP-2007 group than in the MIA group. Furthermore, the administration of NP-2007 resulted in effective preservation of both the synovial membrane and knee cartilage, and significantly decreased the transformation of fibrous tissue. This study indicates that NP-2007 can prevent and alleviate symptoms of osteoarthritis and have applications as a novel arthritis treatment.

The purpose of this study was to investigate the effect that Glycine max hydrolyzed with enzymes from Bacillus velezensis KMU01 has on dextran sulfate sodium (DSS)-induced colitis in mice. Hydrolysis improves functional health through the bioconversion of raw materials and increase in intestinal absorption rate and antioxidants. Therefore, G. max was hydrolyzed in this study using a food-derived microorganism, and its anti-inflammatory effect observed. Enzymatically hydrolyzed G. max (EHG) was orally administered once daily for four weeks before DSS treatment. Colitis was induced in mice through consumption of 5% (w/v) DSS in drinking water for eight days. Results showed that EHG treatment significantly alleviated DSS-induced body weight loss and decreased the disease activity index and colon length. In addition, EHG markedly reduced tumor necrosis factor-a, interleukin (IL)-1b, and IL-6 production, and increased that of IL-10. EHG improved DSS-induced histological changes and intestinal epithelial barrier integrity in mice. Moreover, we found that the abundance of 15 microorganisms changed significantly; that of Proteobacteria and Escherichia coli, which are upregulated in patients with Crohn’s disease and ulcerative colitis, decreased after EHG treatment. These results suggest that EHG has a protective effect against DSS-induced colitis and is a potential candidate for colitis treatment.

Autoantibodies against specific lung cancer-associated antigens have been suggested for lung cancer diagnosis. This study aimed to evaluate the diagnostic performance of anti-gen-autoantibody immune complex (AIC) against its free antigens for CYFRA21-1, ProGRP, NGAL, and NSE in non-small cell lung cancer (NSCLC). In total, 85 patients with NSCLC and 120 healthy controls (HCs) were examined using a 9G DNA chip method. The ratios of AICs to their antigens and combinations of ratios consisting of two to four markers were calculated. The levels of AICs for CYFRA21-1, ProGRP, NGAL, and NSE were higher than their free antigens in all participants. The levels of each free antigen distinguished patients with NSCLC from HCs. The ratios of AIC to its antigen and seven combinations consisting of two to four ratios were significantly higher in patients with NSCLC than those in HCs. Excellent diagnostic performance was observed for all combination ratios (C4-1), with 85.9% sensitivity and 86.7% specificity at cutoff 3.51. Higher sensitivity was observed in the very early stages (0–I) and adenocarcinoma than in stages II–IV and other pathological types. The combination of all ratios of AICs and their antigens for all four markers is useful in the diagnosis of NSCLC.

The purpose of this study is to develop and evaluate the effectiveness of a medical helicopter air transport training program for emergency medical personnel. The program was developed according to Rapid Prototyping Instructional System Design (RPISD) and finalized after content validity and usability evaluation. The effectiveness of the program was evaluated using a single-arm pre-post design to measure the performance of 11 convenience-sampled emergency medical technicians after the program was applied. Data analysis was performed using the SPSS 26.0 Program and Wilcoxon Signed-Rank test. The results of this study are summarized as follows. First, the developed doctor helicopter air transport training program applied RPISD, and the development stage was divided into analysis, design and usability evaluation, and development stages; the final program was derived. Secondly, the developed medical helicopter air transport training program is composed of a blended learning training program that combines online theory lectures and offline simulations for a total of 8 sessions. Third, as a result of applying the developed doctor helicopter air transport training program to 11 emergency medical workers, both pre- and post-air transport subjective job performance and objective job performance were statistically significantly increased. The Dr. Helicopter air transport training program developed in this study was found to be a program that can sufficiently evaluate the job performance of emergency medical personnel in air transport. Through this study, we hope that this training program can directly contribute to improving the survival rate of critically ill patients in the actual air transport field.

The etiological agent of various viral diseases has been identified, and clinical characteristics and complications of each disease are well known. In general, a viral disease appears as acute systemic inflammatory disease, but after acute infection, some patients remain asymptomatic carriers or suffer chronic viral diseases, suggesting that the phenomena are unavoidable processes for viruses’ coexistence with their hosts as virome in microbiota of human species. Although each viral disease has been described as having different pathophysiology, the host's control systems, including immune systems, against the insults from any viral infections, have the same components in previously healthy hosts. Therefore, considering the characteristics of the life cycle of viruses being dependent on the host cell and the same immune components of the host, it is reasonable assumption that there is a common immune mechanism to respond to the insults from all viral diseases. The authors discuss on the characteristics of virus infection and unresolved issues in viral diseases and propose a rationale of early immune modulators for acute insults from viral diseases based on our clinical experiences and the protein-homeostasis-system hypothesis.

Kinases play an important role in regulating various intracellular signaling pathways that control cell proliferation, differentiation, survival and other cellular processes and their deregulation causes more than 400 diseases. Consequently, macrocyclization can be considered a noteworthy approach to develop new therapeutic agents for human diseases. Macrocyclization has emerged as an effective drug discovery strategy over the past decade to improve target selectivity and potency of small molecules. Small compounds with linear structures upon macrocyclization can lead to changes in their physicochemical and biological properties by firmly reducing conformational flexibility. A number of distinct protein kinases exhibit similar binding sites. Comparison of protein binding site provides crucial insights for the drug discovery and development. Binding site similarities are helpful to understand polypharmacology, identifying potential off-targets and repurposing of known drugs. In this review, we focused on comparing binding sites of those kinases for which macrocyclic inhibitors are available/studied so far. Furthermore, we calculated the volume of binding site pocket for each targeted kinase and then compared it with the binding site pocket of the kinase for which only acyclic inhibitors were designed till date. Our review and analysis of several explored kinases might be useful to target new protein kinases for macrocyclic drug discovery.

Through an investigation of recently discovered Incantation of Wish-Fulfillment amulets from the Silla kingdom, this paper reveals that early Korea had more diverse forms of dhāraṇī practices than previously assumed. This paper’s analysis of these amulets from Korea contributes toward filling the gap in our current understanding of the material practice pertaining to the Incantation of Wish-Fulfillment widely practiced in medieval East Asia. Based on an interdisciplinary analysis of the two amulet sheets of the Incantation of Wish-Fulfillment from Silla, this paper explored hitherto unknown aspects of early Korean dhāraṇī practice. Previously, the only material dhāraṇī practice in early Korea was thought to be the enshrinement of textual relics in pagodas based on the Pure Light Incantation, which has little connection to contemporaneous Chinese dhāraṇī practice. However, the newly discovered Incantation of Wish-Fulfillment amulets, whose date this paper inferred to be between the eighth and ninth century, show that the Unified Silla also had a dhāraṇī practice closely linked to the Chinese practice. However, unlike the Chinese Incantation of Wish-Fulfillment amulets that were buried in tombs, the Silla amulets were likely enshrined in one of the pagodas erected on Mount Nam, Gyeongju. At the same time, the Silla epigraph from Myogilsang Pagoda at Haeinsa shows that the Incantation of Wish-Fulfillment was placed in the pagoda so as to wish for good afterlives of the soldiers who died at the battle, suggesting that placing the Incantation of Wish-Fulfillment in a pagoda had a function similar to that of burying the Chinese amulet in the tomb.

Granulomatosis with polyangiitis (GPA) is an autoimmune disease which is a type of anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis that frequently affects the lungs and kidneys. However, GPA limited to a single organ has also been reported. A 73-year-old man was admitted for back pain and fever. We detected elevated levels of inflammatory markers and myeloperoxidase-ANCA. Magnetic resonance imaging indicated diffuse inflammation of the back and psoas muscles. Histology showed degenerated muscle fibers and granulomatosis vasculitis with mixed lymphoplasma cell infiltration. High-dose methylprednisolone therapy improved his symptoms. A final diagnosis of GPA limited to the muscles was made.

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.

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 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.

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.

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.

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.

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.

Exploration practices have proven that over mature shale gas exhibits a feature of carbon isotope reversal. The geochemical statistics indicate that the wetness (C2-C5/C1-C5) of shale gas with carbon isotope reversal is less than 1.8%. In addition, the magnitude of carbon isotope reversal (δ13C1- δ13C2) for the over mature shale gas presents a parabolic variation with decreasing wetness. δ13C1-δ13C2 increases with decreasing wetness within a wetness range of 0.9% ~1.8% and then decreases with decreasing wetness at wetness < 0.9%. The CH4 cracking experiment demonstrates that CH4 polymerization occurring in the early stage of CH4 cracking is an important factor involved in isotope reversal of over mature shale gas. Moreover, δ13C1- δ13C2 decreases with an increase in experimental temperature prior to CH4 substantial cracking. The values of δ13C1 and δ13C2 tend to equalize during CH4 substantial cracking. The δ13C1-δ13C2 of mud gas present at different depths during shale gas drilling in Sichuan Basin increases initially, then decreases with further increase in the depth and finally tends to zero, with only a trace hydrocarbon gas being detectable. Statistical data suggests that the shale gas production in Sichuan Basin decreases with the decreasing δ13C1-δ13C2 value and wetness. Thus, δ13C1-δ13C2 and wetness could potentially serve as useful criteria to screen CH4 cracking degree and to determine the largest depth of natural gas exploration. Great care should be taken during shale gas exploration in deeper layers, with wetness and δ13C1-δ13C2 less than 0.2% and 1%, respectively, since very low wetness (<0.2%) and δ13C1-δ13C2 (<1%) might be indicative of CH4 substantial cracking in a geological setting.

The purpose of this study was to examine the relationships between smartphone addiction of middle school students and smartphone usage types, depression, attention deficit hyperactivity disorder (ADHD), stress, interpersonal problems, and parenting attitude. This study was also performed with the aim of verifying the relationships among depression, ADHD, perceived stress, interpersonal problems, and parenting attitude, which are predictors of smartphone addiction. The subjects of this study were 487 local middle school students (234 males and 253 females). The measurement instruments used were the smartphone addiction scale, depression scale (PHQ-9), ADHD scale (K-ARS), perceived stress scale (PSS), interpersonal problem scale (KIIP-SC), and the parenting attitude scale. This study identified the relationships between the variables with correlation analysis and examined the predictors of smartphone addiction with hierarchical multiple regression analysis. According to the study results, the factors that influenced smartphone addiction were gender, stress, and interpersonal problems. In addition, when the confounding variables of smartphone addiction were controlled to examine the effects of smartphone usage types on smartphone addiction, social media use and music/videos were found to have a positively significant effect on smartphone addiction while study had a negatively significant effect. The order of the usage types with the highest influence on smartphone addiction was enjoying music/videos, social media use, and study. This suggests that selective intervention depending on the main smartphone usage type can be effective.

For better export marketing strategies (EMS), companies mobilize their internal resources, which are managerial commitment, firm experience, and product uniqueness. However, Small businesses with constrained resources cannot be well explained with this view. So, more research on how small business come up with EMS have been called for. To explain how resource-restricted firms which rely heavely on entrepreneur, this study adopted the concept of dynamic managerial capabilities (DMCs) and resource versatility to better explain small business exports. We analyzed small businesses in Mongolia with qualitative research methods, including interviews with entrepreneurs and support organizations, site visits, and group discussions. We suggest international dynamic marketing capabilities (IDMCs), which are entrepreneurial orientation, networking capability, and versatile dynamic capability for small business. Theoretical and managerial implications are discussed.

Cross-border e-commerce is an opportunity for micro, small and medium sized enterprise (MSMEs) in developing countries. Based on a resource-based approach, this research studied how to support resource lacking enterprises with export marketing strategy. It dealt with actual business cases of Mongolian entrepreneurs trying to export Mongolian products to Korean market. Multiple source data including interviews, internal documents, and group discussions, were matched with theories to come up with strategies and validated by supporting organizations in Mongolia and Korea. The research suggests that MSMEs should rely on third party digital platforms rather than setting up their own. For product strtategy of the marketing mix, sellecting competitive product categories and supporting them adjusting to foreign markets and quality assurance is needed. For price strategy, loccally high priced products should use a price penetration strategy with a lower price compared to competing foreign products. For place strategy, supporting organizations should partner with exporters for collective delivery. For promotion strategy, they need to support the capacity of MSMEs enabling them to use digital marketing tools effectivly. These strategies were validated and adopted by supporting organizations in Monglia and Korea.

Erectile dysfunction (ED) is a common and feared complication of radical prostatectomy (RP) for prostate cancer. Recently, tissue engineering is being attempted for post-prostatectomy ED, with controlled interactions between cells, growth factors, and extracellular matrix (ECM) being important for nerve regeneration's structural integrity. In this study, we evaluated the effects of biomechanical ECM patch on human bone marrow-derived mesenchymal stem cells (hBMSCs) morphology and behavior in bilateral cavernous nerve injury (BCNI) rat model. The ECM patch, made of decellularized human fibroblast-derived ECM (hFDM) and a biocompatible polyvinyl alcohol (PVA) hydrogel, was tested with human bone marrow-derived mesenchymal stem cells (hBMSCs) on a bilateral cavernous nerve injury (BCNI) rat model. In vitro analysis showed that the hFDM/PVA + hBMSCs patches significantly increased neural development markers. In vivo experiments demonstrated that the rats treated with the hFDM/PVA patch had higher ICP/MAP ratio, a higher ratio of smooth muscle to collagen, increased content of nNOS, higher levels of eNOS protein expression, and a higher cGMP level compared to the BCNI group. These results indicate that the hFDM/PVA patch is effective in promoting angiogenesis, smooth muscle regeneration, and nitrergic nerve regeneration, which could contribute to improved erectile function in post-prostatectomy ED.

Various vestibuloplasty techniques have been reported to increase the attached mucosa (AM) and vestibular depth around dental implants. However, these surgical methods have disadvantages, such as limitations in manipulation, necessity of suturing, postoperative discomfort, swelling, and pain. This study aimed to evaluate the efficacy of laser-assisted periosteal fenestration (LA-PF) in treating a patient with a shallow vestibule and insufficient AM around dental implants. The LA-PF technique was performed using an Er:YAG laser. First, a partial-thickness apically positioned flap (APF) was performed. Horizontal periosteal fenestration was performed using an Er:YAG laser to expose the bones. Periosteal suturing was not required. After 12 months, sufficient AM and deepened vestibule were obtained and maintained. Thus, the LA-PF technique may be a simple and predictable treatment modality for vestibuloplasty around dental implants.

Greenwater (splashing of water on the deck) loading is a classical problem faced by the designer of ship-shaped vessels, which becomes even worst when the vessel operates at harsh weather conditions for an extended period. Installation of breakwaters on the deck can play a crucial role in minimizing this impact. However, research on the design and optimization of the breakwater is still at its infancy, and this study aims at shedding further light on this area by proposing and analyzing the effectiveness of three breakwater designs on a fixed box-shaped vessel. Commercial CFD software is used for this investigation. However, the design model (without breakwater) was validated at first against experimental results of green water splashing, before performing the actual simulations with proposed breakwater design. A vertical plate is used as the deck structure, and greenwater pressure at several locations on that plate is measured to compare the effectiveness of various breakwater designs. Overall, breakwaters with openings (perforations, grillages etc.) found to be more effective in minimizing the pressure generated by the greenwater. Nevertheless, there are significant rooms for improvement on breakwater designs, and some topics for further research are also suggested in this regard.

Building a new power plant to address the growing demand for power due to population concentration in the metropolitan area is one of the world's major concerns. However, since a large power plant can not be located around the city due to burden of economic cost, building power plant outside metropolitan and cities is necessary. Therefore, new power generation facilities are promoting policies to provide distributed generator(DG) with a small capacity relatively near the metropolitan. When the DG (photovoltaic, wind farm, etc.) is connected with the grid using medium voltage direct current (MVDC) system, voltage sourced converter(VSC) should supply reactive power to the grid, because of fault ride through(FRT) operation in grid fault. If the voltage drop is severe, the converter should be disconnected from the grid immediately without supplying the reactive power, resulting in a considerable economic loss. In general, superconducting fault current limiter(SFCL) is introduced as a measure to enhance FRT capability. In this paper, we use trigger type SFCL which protects superconducting element and reduces low voltage. On the other hand, the active power unbalance of the DC-link and the DC voltage rise due to the reactive power supply of the grid-side converter. The rise of the DC voltage causes the P (active power), Q (reactive power) control of the converter to deviate, causing malfunction and damage of the DC equipment. Therefore, the rise of the DC voltage must be prevented. In this paper, we consider the suppression the DC voltage rising caused by the FRT operation through the active power tracking control (APTC).

Colorectal cancer (CRC) is the third most commonly diagnosed cancer worldwide, and despite advances in treatment, survival rates are still low; therefore, the development of novel drugs is imperative. Acetylcorynoline (ACN) is derived from Corydalis ambigua. The effect of ACN on colon cancer is still unknown. Therefore, we investigated its potential effects. Our data showed that ACN inhibited cell viability and proliferation. Moreover, ACN induced apoptosis and cell cycle arrest by inhibiting cell growth. In the present study, we hypothesized that ACN regulates c-Myc through CNOT2 or MID1IP1. ACN reduced the protein expression of oncogenic genes, decreased c-Myc half-life, and rapidly inhibited the serum stimulation response. Moreover, knockdown of CNOT2 and MID1IP1 with ACN increased apoptosis and further reduced the expression of oncogenes. In addition, ACN exhibited a synergistic effect with low-dose of 5-fluorouracil (5-FU) and doxorubicin (Dox). Collectively, our data demonstrates that ACN inhibited c-Myc expression through CNOT2 and MID1IP1 and induced apoptosis. These findings indicate the potential of ACN as a therapeutic agent against colon cancer.

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.

This study aimed to investigate the effect of potassium poly-γ-glutamate (PGA-K) on mice fed a high-fat diet consisting of 60% of total calories for a duration of 12 weeks. PGA-K administration reduced the increase in body weight, epididymal fat, and liver weight caused by a high-fat diet compared to the obese group. The triglyceride, low-density lipoprotein cholesterol and high-density lipoprotein cholesterol levels, which are blood lipid indicators, were significantly increased in the obese group but were significantly decreased in the PGA-K-treated group. The administration of PGA-K resulted in a significant inhibition of pro-inflammatory cytokines, including tumor necrosis factor α and interleukin 6. Moreover, the levels of leptin and insulin, which are insulin resistance indicators, significantly increased in the obese group but were significantly decreased in the PGA-K-treated group. These results suggest that PGA-K exhibits a protective effect against obesity induced by a high-fat diet, underscoring its potential as a candidate for obesity treatment.

In order to understand the effect of Pb-CuI co-doping on the thermoelectric performance of Bi₂Te₃, n-type Bi₂Te₃ co-doped with x at% CuI and 1/2x at% Pb (x = 0, 0.01, 0.03, 0.05, 0.07, and 0.10) were prepared via high temperature solid state reaction and consolidated using spark plasma sintering. Electron and thermal transport properties, i.e., electrical conductivity, carrier concentration, Hall mobility, Seebeck coefficient, and thermal conductivity, of CuI-Pb co-doped Bi₂Te₃ were measured in the temperature range from 300 K to 523 K and compared to corresponding x% of CuI-doped Bi₂Te₃ and undoped Bi₂Te₃. The addition of a small amount of Pb significantly decreased the carrier concentration, which could be attributed to the holes from Pb atoms, thus the CuI-Pb co-doped samples show a lower electrical conductivity and a higher Seebeck coefficient compared to CuI-doped samples with similar x values. The incorporation of Pb into CuI-doped Bi₂Te₃ rarely changed the power factor because of the trade-off relationship between the electrical conductivity and the Seebeck coefficient. The total thermal conductivity(κ_tot) of co-doped samples (κ_tot ~1.4 W/m∙K at 300 K) is slightly lower than that of 1% CuI-doped Bi₂Te₃ (κ_tot~1.5 W/m∙K at 300 K) and undoped Bi₂Te₃ (κ_tot ~1.6 W/m∙K at 300 K) due to the alloy scattering. The 1% CuI-Pb co-doped Bi₂Te₃ sample shows the highest ZT value of 0.96 at 370 K. All data on electrical and thermal transport properties suggest that the thermoelectric properties of Bi₂Te₃ and its operating temperature can be controlled by co-doping.

In the paper, the authors present unified generalizations for the Bell numbers and polynomials, establish explicit formulas and inversion formulas for these generalizations in terms of the Stirling numbers of the first and second kinds with the help of the Faà di Bruno formula, properties of the Bell polynomials of the second kind, and the inversion theorem connected with the Stirling numbers of the first and second kinds, construct determinantal and product inequalities for these generalizations with aid of properties of the completely monotonic functions, and derive the logarithmic convexity for the sequence of these generalizations.

Background: Capmatinib and savolitinib, selective MET inhibitors, are widely used to treat various MET-positive cancers. In this study, we aimed to determine the effects of these inhibitors on MET-amplified gastric cancer (GC) cells. Methods: After screening 37 GC cell lines, the following cell lines were found to be MET-positive with copy number variation &gt; 10: SNU-620, ESO51, MKN-45, SNU-5, and OE33 cell lines. Nest, we assessed the cytotoxic response of these cell lines to capmatinib or savolitinib alone using cell counting kit-8 and clonogenic cell survival assays. Western blotting was performed to assess the effects of capmatinib and savolitinib on the MET signaling pathway. Xenograft studies were performed to evaluate the in vivo therapeutic efficacy of savolitinib in MKN-45 cells. Results: Savolitinib and capmatinib exerted anti-proliferative effects on MET-amplified GC cell lines in a dose-dependent manner. Savolitinib inhibited the phosphorylation of MET and downstream signaling pathways, such as the protein kinase B (AKT) and extracellular signal-regulated kinase (ERK) pathways, in MET-amplified GC cells. Additionally, savolitinib significantly decreased the number of colonies formed on the soft agar and exerted dose-dependent anti-tumor effects in a MKN-45 GC cell xenograft model. Furthermore, combination of trastuzumab and capmatinib exhibited enhanced inhibition of AKT and ERK activation in human epidermal growth factor receptor-2 (HER2)- and MET-positive OE-33 cells. Conclusions: Therefore, targeting MET with savolitinib and capmatinib efficiently suppressed the growth of MET-amplified GC cells. Moreover, these MET inhibitors exerted synergistic effects with trastuzumab on HER2- and MET-amplified GC cells.

The purpose of this study is to explore conceptual approaches in co-production studies and to examine current research trends of the study. The conceptual paper includes research articles related to co-production in public administration field. By thoroughly scrutinizing 32 research works of co-production, this study highlights major loopholes in the field of the study. The contributions of the study are: (1) identifying two common characteristics of co-production, (2) categorising three types of co-producing by end-users, and (3) finding that goals and success of co-production are more beneficial for service providers though its initial approach is citizen-centric approach. We suggest that future studies should be (1) to focus on reasons for co-production failures or success, (2) to discover further hindrances for co-production in service production, (3) to examine influencing factors on service providers as well as institutional impacts on co-production process, and (4) to include practical assessment in co-production study.

The dopamine D3 receptor is an important CNS target for the treatment of a variety of neurological diseases. Selective dopamine D3 receptor antagonists modulate the improvement of psychostimulant addiction and relapse. In this study, five and six featured pharmacophore models of D3R antagonists were generated and evaluated with the post-hoc score combining two survival scores of active and inactive. Among Top 10 models, APRRR215 and AHPRRR104 were chosen based on the coefficient of determination (APRRR215: R2training = 0.80; AHPRRR104: R2training = 0.82) and predictability (APRRR215: Q2test = 0.73, R2predictive = 0.82; AHPRRR104: Q2test = 0.86, R2predictive = 0.74) of their 3D-quantitative structure–activity relationship models. Pharmacophore-based virtual screening of a large compound library from eMolecules (> 3 million compounds) using two optimal models expedited the search process 100-fold speed increase compared to the docking-based screening (HTVS scoring function in Glide) and identified a series of hit compounds having promising novel scaffolds. After the screening, docking scores, as an adjuvant predictor, were added to two fitness scores (from the pharmacophore models) and predicted Ki (from PLSs of the QSAR models) to improve accuracy. Final selection of the most promising hit compounds were also evaluated for CNS-like properties as well as expected D3R antagonism.

Sustainability is directly linked to firms’ survival in competitive markets. To survive, firms need extra capital, and seasoned equity offerings (SEOs) are one sustainability strategy. Additional resources from SEOs leads to changes in firms’ operational structure, which brings future sustainability. This study investigates whether there is sustainability in firms’ operational structure and the effects of sustainable development on operational performance and market reaction. We measure the operational structure change of firms as three proxies: 1) the rate of increase in the number of operating segments, 2) the Berry–Herfindahl index using the ratio of sales of each operating segment out of total sales, and 3) the size of net investment in plant and equipment. Our results show that operational structure change has a statistically significant and positive correlation with long-term operating performance. In addition, there is no significant stock price response at first, but the operating performance in the next term is perceived as a favorable factor after 3 years. The results show that there are different responses in the stock market toward operational structure change. The empirical results confirm that firms with SEO have sustainable development in operational structure and that markets recognize firms’ sustainability strategy arising from SEOs.

Incident rates of neurodegenerative diseases have steadily increased globally, but there is no therapeutic access available. We newly prescribed medicinal herbal remedy including five different herbal plants called, Chen-Ma-Dan-Sam-Ga-Mi-Bang (CMST), purposed to prove for pharmacological properties and corresponded actions on hippocampus neuronal cell injury by hypoxia-induced mice model. Mice were adapted to normoxia or hypoxia with or without CMST for 5 days. We gathered pharmacological effects of CMST on cell injury by enhancement of dihydroethidium and 4-hydroxynonenal signals which were correlated with abnormal redox status in the protein or gene expression levels (abnormal elevations of nitric oxide, reactive oxygen species, lipid peroxidation and deteriorations of total glutathione, total antioxidant capacity, and activities of superoxide dismutase and catalase) due to hypoxia. CMST also notably exerted to attenuates molecules for neuronal cell injury markers such as p-tau, cleaved caspase-3 due to DNA oxidations (53bp1and phosphor-histone H2AX), inflammatory cytokines, and hemeoxigenase-1. We further figured out the underlying actions of CMST by in vitro experiment through inactivation of microglial cell which can mediate neuronal cell injury. Collectively, CMST prevented from hippocampal neuronal cells via inactivation of microglial cell with normalization of redox status on hypoxia-induced hippocampus neuronal cell injury.

Inflammatory bowel disease (IBD), including ulcerative colitis and Crohn's disease, is a complex gastrointestinal disorder with a multifactorial etiology, including environmental triggers, autoimmune mechanisms, and genetic predisposition. Despite advancements in therapeutic strategies for IBD, its associated mortality rate continues to rise, which is often attributed to unforeseen side effects of conventional treatments. In this context, we explored the potential of Ecklonia cava extract (ECE) derived from an edible marine alga known for its anti-inflammatory and antioxidant properties in mitigating IBD. This study investigated the effectiveness of ECE as a preventive agent in a murine model of dextran sulfate sodium (DSS)-induced colitis. Our findings revealed that pretreatment with ECE significantly ameliorated colitis severity as evidenced by increased colon length, reduced spleen weight, and histological improvements demonstrated by immunohistochemical analysis. Furthermore, ECE significantly attenuated the upregulation of inflammatory cytokines and mediators and the infiltration of immune cells known to be prominent features of colitis in mice. Notably, ECE restored dysbiosis of intestinal microflora and aided in the recovery of damaged intestinal mucosa. Mechanistically, ECE exhibited protective effects against pathogenic colitis by inhibiting the NLRP3/NF-κB pathway known to be pivotal regulators in the inflammatory signaling cascade. These compelling results suggest that ECE holds promise as a potential candidate for IBD prevention. It might be developed into a functional food for promoting gastrointestinal health. This research sheds light on the preventive potential of natural compounds like ECE in the management of IBD, offering a safer and more effective approach to combating this challenging disease.

The plant Allium hookeri, belonging to the Allium genus, has a history of being used both as a common food ingredient and in herbal medicine. It has recently been reported to have anti-oxidant and anti-inflammatory effects. A. hookeri has been also shown to exhibit neuroprotective and anti-neuroinflammatory activities, but the active compounds responsible for these effects have not been identified in previous studies. This study aimed to perform a metabolite profiling using an HRESI-qTOF MS/MS-based molecular networking approach and identify the active compounds from A. hookeri that target senescent cell-associated secretory phenotype (SASP) inhibitory effects, which contribute to neuroprotective activities. As a result, ten compounds, including one new flavonoid (2) and nine known compounds (1 and 3–10), were identified, and their biological activity was tested. The most potent compound was N-trans-feruloyltyramine (7), which inhibited SASP markers and contributed to the senomorphic activities of A. hookeri. These findings suggest that the phenolamides from A. hookeri could be a promising source of bioactive compounds for preventing senescence-associated diseases.

We investigated whether cigarette smoking and dietary acid load (DAL) are associated with the risk of chronic obstructive pulmonary disease (COPD) in middle-aged healthy Korean men. Healthy men without diagnosed chronic disease (40-64 yrs) from the KNHANES-VI (2013–2015) included in the analysis (n=774) were subdivided by smoking status and DAL levels as estimated by the net endogenous acid production (NEAP) quartile. Current smokers tended to have a higher risk of COPD than non-smokers before and after the adjustment. When divided by the DAL quartile, the Q4 tended to have a higher risk of COPD than the Q1. Additionally, current smokers with lower (Q2), modest (Q3), and highest NEAP scores (Q4) showed more than 4-fold higher risks of COPD than the non-smokers with the lowest NEAP scores (Q1). Ex–smokers with higher NEAP scores (Q3 and Q4) showed more than 4-fold higher risks of COPD than the Q1. Interestingly, the risk of COPD was also more than 6-fold higher in non-smokers with the highest NEAP scores compared to the Q1. NEAP scores and smoking status synergistically increased the risk of COPD in middle-aged healthy Korean men. It suggests that DAL levels are an important factor for the prevention and management of COPD.

There has been no significant efficacy in treatment for osteosarcoma (OS) metastasis after nearly four decades of trials. This motivates us to elucidate OS therapies according to their four bidirectional mutation stages. To refresh the OS therapy status quo, the historical developments and clinical advancements are briefly described. However, the main issue of metastasis remains unresolved, accounting for 90% of pulmonary metastasis deaths. Thus, this metastasis problem is related to immune evasion and chemoresistance that are being induced after long-term treatment by the use of immunotherapy for tumorigenesis. Therefore, it is rationale to discuss the relationship cycles of mutation stages including tumorigenesis, metastasis, immune evasion, and chemoresistance. Even though many combinational and targeted therapies have been developed to intensify these mutation treatments, successful clinical translations with higher cure rates are still rare. Through this review, an in-depth understanding of the bidirectional relationship between the four OS mutation stages and their respective therapies is provided. Herein, we summarise the medicines used to treat tumorigenesis, including COLGALT2 inhibitors, Tra2B, and AGAP1, miR-148a and miR-21-5p EVs, and the lncRNA LIFR-AS1. Following the medicines used to treat metastasis are AXL, miR-135a-5p, mRNA BCL6, TGFβ1, Tim-3, SOCS5, CASC15, KLF3-AS1, PDCD4, ATG5, and Rab22a-NeoF1. Then the medicines used to treat immune evasion are N-cadherin, anti-IL-9, USP12 inhibitor, IgG-4+ B-cells, LAP inhibitor, anti-Wnt2 mAb, anti-αvβ8 integrin, HK2-mediated IκBα, IDO inhibitor with NO, and TGF-βRII with anti-IgG1. Finally, the medicines used to treat chemoresistance are DHFR, FPGS, HSP-90AA1, XCT-790, ATKI, and IGF1. As a result, this contribution is expected to serve as a reference and guide for scientists and clinicians.

Antimicrobial peptides (AMPs) have emerged as a promising solution to tackle bacterial infections and combat antibiotic resistance. However, their clinical application has been hindered by their vulnerability to protease degradation and toxicity towards mammalian cells. To overcome these challenges, our study aims to develop a method to enhance the stability and safety of AMPs, applicable to effective drug-device combination products. KR12 antimicrobial peptide was chosen and in order to further enhance its delivery and efficacy, HIV TAT protein-derived cell-penetrating peptide (CPP) was fused to form CPP-KR12. A new product, CPP-KR12@Si, was developed by forming silica nanoparticles with self-entrapped CPP-KR12 peptide using the biomimetic silica precipitability due to its cationic nature. Peptide delivery from CPP-KR12@Si to bacteria and cells was delivered at a slightly delayed rate with improved stability against trypsin treatment and a reduction in cytotoxicity over CPP-KR12. Finally, the antimicrobial potential of CPP-KR12@Si/bone graft substitute (BGS) combination product was demonstrated, which is coated with CPP-KR12 in the form of nanoparticles on the surface of BGS. Self-entrapped AMP in silica nanoparticles is a safe and effective AMP delivery method that will be useful for developing a drug/device combination product for tissue regeneration.

In this study, a basic study was performed to analyze the seasonal temperature status of a research room in the Global Environment Research Building where ceiling-embedded indoor units are installed to study the room temperature status of the building as well as to improve its thermal environment. In addition, a direction for improvement of the indoor thermal environment in the winter was proposed through a CFD (computational fluid dynamics) simulation and was proven by an additional experiment. Through the results of this study, it appeared that if the ceiling-embedded indoor unit was installed in the small indoor space without considering the thermal vulnerability of its perimeter boundary, the air temperature of the upper part was greatly different from that of the bottom part in the winter. Hence, in this study, as a means to improve it, convectors were installed to minimize the effect of the external thermal environment and angle-controllable air flowing fans were installed to mitigate the stratification distribution. With such result, it was intended to present the essential data for improvement of the thermal environment as well as conservation of heating energy in the winter for buildings by reviewing the use of the ceiling-embedded indoor unit in the future.

This study aimed to elucidate the antibacterial efficacy and unique chemical compositions generated from plasma-activated water (PAW) when utilized a novel vaginal cleansing device. We conducted an analysis of antibacterial activity against probiotics and several chemical compositions including ions under various operational parameters of PAW, including electrical power (12 and 24 V), treatment duration (1, 10, and 20 min), and stay duration (immediate, 30 and 60 min). Our findings revealed that as treatment duration increased, hypochlorous acid (HOCl), Ca2+, and Mg2+ concentrations increased and Cl−concentrations decreased. Higher electrical power and longer treatment duration resulted in increased HOCl levels, which acts to prevent the growth of general microorganisms. Notably, PAW exhibited no antibacterial effects against a type of probiotic, Lactobacillus reuteri that produces lactic acid for vaginal health. This result demonstrated the ability of the vaginal cleaning device to generate ions, primarily HOCl and some cations (Ca2+ and Mg2+), thereby providing vaginal mucosa protecting and cleansing effects with the vaginal environment.

Our study provides guidelines on how to build long-term customer relationship in the non-contract mechanism context. More specifically, the findings show that special, social, and core benefits influence calculative commitment, and operational and special benefits influence affective commitment. This study also supports that calculative and affective commitment play a crucial role in understanding multi-channel agencies’ loyalty. In sum, this study revealed that calculative and affective commitment can be considered as partial or full mediators in the relationship between RBs (relational benefits) and loyalty. This study not only contributed to the existing SET (social exchange theory) and RBs paradigm but also provided practical implications for food distribution management.

We aimed to evaluate the feasibility and preliminary efficacy of trauma-focused group psychotherapy in adolescents who experienced traumatic events in Korea. Participants were assigned and recruited from two sites in Korea. Children in Disaster: Evaluation and Recovery (CIDER) V1.0 is a trauma-focused group psychotherapy approach consisting of psychoeducation, normalization, stabilization, and techniques of managing the traumatic memory. The CIDER intervention consists of eight 50-minute-long sessions. The effectiveness of the intervention was evaluated using the Korean version of the Children’s Response to Traumatic Events Scale-Revised (K-CRTES-R), the Beck Depression Inventory (BDI), the State Anxiety Inventory for Children (SAIC), and the Pediatric Quality of Life Inventory (PedQL). Data were analyzed by Wilcoxon signed-rank test. We recruited 22 traumatized adolescents (mean age 16 years; SD 1.43; range 13–18 years old; 71.4% boys) in this pilot study. The K-CRTES-R scores were significantly improved (Z = −2.85, p < 0.01). The BDI demonstrated the effectiveness of the therapy (Z = −2.35, p < 0.05). The assessment of the PedQL supported the effect of CIDER (Z = −3.08, p < 0.01). However, there was no statistically significant differences in the SAIC scores (Z = −1.90, p > 0.05). The results show that there is preliminary evidence that CIDER intervention reduces post-traumatic stress and depressive symptoms and improves quality of life. Our findings indicate that CIDER is feasible for treating adolescents exposed to traumatic events. Larger controlled trials are needed to establish the efficacy of this trauma-focused group psychotherapy and examine its impact on post-traumatic stress disorder.

This study aimed to evaluate the positive effect of autumn olive berries (AOB) extract on aging delay by improving the lipid metabolism of middle-aged C. elegans who became obese due to high glucose (GLU) diet. As a result of investigating the total phenol content and DPPH radical scavenging ability of freeze- or spray-dried AOB, freeze-dried AOB showed better antioxidant potential. Afterward, through HPLC analysis, it was confirmed that catechin was the main compound in the polyphenols of AOB. Therefore, we used freeze-dried AOB in subsequent in vivo experiments. AOB inhibited lipid accumulation in both the young adult and middle-aged groups in a concentration-dependent manner under both normal and 2% GLU conditions. Additionally, AOB inhibited ROS accumulation in a concentration-dependent manner under normal and 2% GLU conditions in the middle-aged worms. In particular, AOB also increased the number of body bending and egg production in middle-aged worms. To confirm the intervention of genetic factors related to lipid metabolism in the effect of AOB, body lipid accumulation was confirmed using worms deficient in the daf-16, atgl-1, aak-1, and akt-1. Regarding the effect of AOB on reducing lipid accumulation, the impact was nullified in daf-16 deficient worms under the 2% GLU condition and nullified in both daf-16 and deficient worms under fasting conditions. This means that AOB regulates lipogenesis and lipolysis by mediating daf-16 and atgl-1 in middle-aged worms. Our results suggest that AOB contributes to the aging delay effect by improving lipid metabolism in metabolic impaired middle-aged worms.

The most common complication of herpes zoster is postherpetic neuralgia (PHN), which is accompanied by severe pain that lowers patients’ quality of life. Although epidural injection of local anesthetics and steroids is effective in controlling neuropathic pain resulting from herpes zoster, few studies report the efficacy and safety of epidural steroid administration in PHN patients. We randomly assigned 42 patients with severe PHN pain (visual analog scale (VAS) score ≥7) to receive continuous epidural infusion of local anesthetics with either a one-time bolus of 5 mg dexamethasone or dexamethasone pulse therapy. VAS scores significantly decreased over time for all patients, but the reduction in VAS scores and likelihood of achieving complete remission were significantly greater among patients who received dexamethasone pulse therapy, without any adverse effects. These results show that continuous epidural infusion of local anesthetics with dexamethasone is effective and safe for reducing PHN pain and promoting complete remission and that more pronounced beneficial effects are associated with more intense epidural steroid administration.

The energy stored in an electric vehicle's battery would be drawn and distributed to the electrical grid to better drive energy consumption within a microgrid that includes a renewable generator(s) managed by a specific energy management strategy. This concept, known as vehicle-to-grid technology: V2G, makes the energy stored in the electric vehicle's battery more beneficial by discharging it to the public grid during periods of high demand. In this study, we will consider a vehicle system connected to a microgrid, which includes a photovoltaic generator reported from the <<PROPRE.MA>> project in the city of Tangier. We will elaborate the study of a strategy of the car connected to this V2G network. This allows electricity to be stored when rates are low (off-peak hours) and then used when prices rise (peak hours). Otherwise, the solar energy will cover the owner's needs, and the surplus will be injected into the distribution network. This strategy will manage the solar power, the load power, the state of charge of the EV battery, the time of day and the driving scenario. Using two driving profiles, we will show the performance of the proposed energy management strategy and the percentage contribution of the photovoltaic array of the <<PROPRE.MA>> project in the city of Tangier.

In 2023, the technological landscape witnessed an unprecedented surge of transformative innovations, including Web 3.0 and machine learning, poised to revolutionize various aspects of our daily lives. At the forefront of this revolution stands artificial intelligence (AI), which has evolved from a concept once confined to science fiction into an indispensable force reshaping industries on a global scale. Notably, recent years have seen remarkable strides in AI functionalities, particularly in machine learning, computer vision, and natural language processing. These advancements have empowered AI to generate diverse interactions and media autonomously. This study ultimately provides invaluable insights into the dynamic intersection of AI and Advertising, con-tributing to a deeper comprehension of this evolving field. This study conducts a comprehensive review of Artificial Intelligence within the advertising domain, employing network analysis. By meticulously examining the evolution of AI through co-occurrences of terms, keywords, and co-authorship analysis, we aim to unveil the relationship of AI & Advertising through the lens of Generative models to identify pivotal trends, core concepts, and seminal studies that have profoundly influenced the industry. The analysis charts the trajectory leading to the emergence of Generative Artificial Intelligence (GenAI), a transformative development poised to revolutionize advertising practices and consumer engagement. In tandem with these objectives, the results highlight vital trends, emphasizing the growing prominence machine learning tools and techniques such as deep learning techniques and advanced natural language processing methods like word2vec, GANs, and more in shaping the future of advertising practices.

Reducing the construction time for large logistics buildings can result in reduced construction management costs and economic gains from early operation. A large logistic building with a heavy load and long spans was constructed as a precast concrete (PC) structure, which requires the use of a sizable crane to lift heavy PC members. A basic analytical approach is employed to resolve potential errors in the planning of PC member erection and to build a systematic erection plan. Calculation techniques for the trajectory distance, which use the crane location, are applied to select an erection plan that minimizes crane work. A crane trajectory distance calculation algorithm for sustainable PC member erection in large logistic buildings with heavy loads and long spans has been developed. The developed model aids in creating simulation and optimization models to ensure minimal usage of cranes in the future and determining cost, construction time, CO2 emissions, and energy use for each erection plan.

The study aims to examine the mediating role of job crafting between inclusive leadership and innovative work behavior. The data were collected from 314 workers employed in China's small and medium-sized industries. The data collection was done through survey design. The data analysis was done through structural equation modeling using Spss 26 and Mplus 8. Inclusive leadership was found to be related to job crafting and innovative work behavior of the employees. Job crafting was found to be mediating between inclusive leadership and innovative work behavior. The study delineated the link mechanism between inclusive leadership and innovative work behavior. Studying inclusive leadership in the context of Chinese culture is a powerful complement to inclusive leadership theory. This paper provides the managers of SMEs with significant managerial insights into how inclusive leadership can effectively motivate employees’ innovative work behaviors.

Lindera obtusiloba Blume has several activities, such as anti-inflammatory, anti-allergic, anti-tumor, anti-wrinkle, and antioxidant activities. Interleukin-6 (IL-6) is a classic pro-inflammatory cytokine that is associated with various functions, such as proliferation, invasion, inflammatory responses and functions within antioxidant defence systems. In this study, we investigated IL-6-induced STAT3 activation of lignan compounds isolated from L. obtusiloba. The structures of the isolated compounds were elucidated via spectroscopic nuclear magnetic resonance (NMR) and electrospray ionization mass spectrometry (ESI-MS). As a result, seven lignans were identified from L. obtusiloba. All the isolated compounds (1-7) were evaluated for their IL-6-induced STAT3 inhibitory effects in Hep3B cells using a luciferase reporter assay. Of the isolates, compounds 1 and 5 showed inhibitory effects against IL-6-stimulated STAT3 activation. Furthermore, the mRNA expression levels of inflammation-related genes such as CRP, IL-1b, and SOCS3 were significantly reduced by exposure to compound 1 and 5. The protein levels of p-STAT3, p-JAK2 in IL-6 induced U266 cells were regulated in the presence of lignans derived from Lindera obtusiloba by western blot assay. Based on the results, this study of L. obtusiloba demonstrates that the species has promise as a bioactive candidate for the treatment of IL-6-induced STAT3-related disease.

Background and objectives: Musculoskeletal (MSK) pain significantly impacts physical activity and quality of life in the elderly, potentially influencing mortality. This study explored the relationship between MSK pain, physical activity, muscle mass, and mortality among older adults. Material and Methods: We studied 1000 participants of the Korean Longitudinal Study on Health and Aging (KLoSHA), a prospective, population-based cohort study of people aged 65 years or older. Survival status was tracked over a 5-year period. Correlations between Low back pain (LBP), knee pain, regular exercise, appendicular skeletal muscle mass (ASM), and other variables were analyzed. Logistic regression analyzes were used to identify independent risk factors for mortality. Results: Of the total participants, 829 (82.9%) survived after a 5-year period. Survivors tended to be younger, had a higher BMI, and were more active in regular exercise. In contrast, non-survivors exhibited a higher prevalence of both LBP and knee pain, along with increased instances of multiple MSK pain. Lower ASM correlated moderately with LBP and knee pain, whereas higher ASM was associated with regular exercise Lower ASM was moderately associated with LBP and knee pain, while higher ASM correlated with engagement in regular exercise. There was a moderate correlation between LBP and knee pain, both of which were associated with a lack of regular exercise. Age, sex, ASM, and regular exercise were significant predictors, even though MSK pain itself did not directly predict all-cause mortality. Conclusions: This study demonstrated the independent association between ASM, regular exercise, and mortality. Although MSK pain did not directly correlate with all-cause mortality, the non-survivor group had higher levels of both single and multiple MSK pain. Recognizing the interplay of MSK pain, physical activity, and muscle mass for older adults, the research underscores the need for holistic strategies to enhance health outcomes in older individuals with MSK pain.

Sulforaphene (SFE), a major isothiocyanate in radish seeds, is a close chemical relative of sulforaphane (SFA) isolated from broccoli seeds and florets. The anti-proliferative mechanisms of SFA against cancer cells have been well investigated, but little is known about the potential anti-proliferative effects of SFE. In this study, we showed that SFE purified from radish seeds inhibited the growth of six cancer cell lines (A549, CHO, HeLa, Hepa1c1c7, HT-29, and LnCaP), with relative half maximal inhibitory concentration (IC50) values ranging from 1.37 to 3.31 g/mL. Among the six cancer cell lines evaluated, SFE showed the greatest growth inhibition against A549 lung cancer cells. In A549 cells, SFE induced apoptosis via changes in the levels of poly (adenosine diphosphate ribose) polymerase and caspase-3, -8, and -9. Our results indicate that SFE from radish seeds may have significant anti-proliferative potency against a broad range of human cancer cells via induction of apoptosis.

The Advanced Meteorological Image (AMI) onboard GEOKOMPSAT 2A (GK-2A) enables the retrieval of dust aerosol optical depth (DAOD) from geostationary satellites using infrared (IR) channels. IR observations allow the retrieval of DAOD and the dust layer altitude (24 hour) over surface properties, particularly over deserts. In this study, dust events in northeast Asia from 2020 to 2021 were investigated using five GK-2A thermal IR bands (8.7, 10.5, 11.4, 12.3, and 13.3 μm). For the dust cloud, the observed brightness temperature differences (BTDs) of 10.5 and 12.3 μm were found to be always negative, while the BTD of 8.7 and 10.5 μm varies relying on the dust intensity. Making the best use of optical properties, a physical approach for DAOD lookup tables (LUTs) was developed using IR channels to retrieve the DAOD. This study simulated the characteristics of thermal radiation transfer using the forward model and dust aerosols can explain by BTD (10.5, 12.3 μm), which is an intrinsic characteristic of dust aerosol. The DAOD and property of dust can be gained from the brightness temperature (BT) of 10.5 μm and the BTD of 10.5, 12.3 μm. Additionally, the cumulative distribution function (CDF) was employed to strengthen the continuity of 24-hour DAOD, which was applied to the algorithm by calculating the conversion value coefficient for the DAOD error correction of the IR with daytime visible aerosol optical depth (VAOD) as the true value. The results show that DAOD product can be successfully used during both daytime and nighttime to continuously monitor the flow of yellow dust from the GK-2A satellite in northeast Asia. In particular, the validation result of IR DAOD was similar to that of the active satellite product (CALIPSO/CALIOP), which showed a tendency similar to that for IR DAOD at night.

The Abnormal increase in the mass of adipose tissue during adipogenesis results in obesity. Obesity is a predominant disorder and its widespread has become a critical concern worldwide. This is due to the burden of its associated co-morbidities like cancer, cardiovascular diseases and diabetes. Over-nutrition and the sedentary lifestyle are considered as the most significant causes of abnormal adipose tissue development. Appropriate lifestyle and behavioural interventions are the corner stones of successful weight loss, but to maintain such a lifestyle is highly challenging. Accordingly, natural products from plants either as crude extracts or purified phytochemicals have shown to have anti-obesogenic properties and are generally non-toxic and cost-effective. In this review, we discuss the comparative analysis of molecular mechanisms involved in adipogenesis and the recently reported anti-obesogenic effects of various plant products. We will provide a common platform for understanding obesity and adipogenesis, and a possible mechanism of action for anti-obesogenic plant products through AMP-activated protein kinase (AMPK), which will support the scientific development of traditional herbal medicine.

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.

Antibody-drug conjugates (ADCs) have provided new therapeutic options and significant promise for patients with cancers, particularly where existing treatments are limited. Substantial effort in ADC development is underway globally, with 13 ADCs currently approved and many more in development [1]. Therapeutic benefits of ADCs leverage the ability to selectively target cancer cells through antibody binding, resultant relative sparing of non-malignant tissues, and the targeted delivery of a cytotoxic payload. Consequently, this drug class has demonstrated activity in multiple malignancies refractory to standard therapeutic options [1-4]. Despite this, limitations exist, including narrow therapeutic windows, unique toxicity profiles, development of therapeutic resistance, and appropriate biomarker selection [5-7]. This review will describe the development of ADCs, their mechanisms of action, pivotal trials, and approved indications and identify common themes. Current challenges and opportunities will be discussed for this drug class in cancer therapeutics at a time when significant developments in antibody therapies, immunotherapy and targeted agents are occurring.