Building on the Sustainable Happiness Model, this study examined how congruency between ideal self-image and brand image influence a sense of happiness. The findings show that when ideal self-image and ideal social self-image are congruent with brand image a sense of happiness can be enhanced through brand identification and positive emotions. This study contributes to literature as it reveals the mechanism of how congruency between ideal self-image and brand image positively affect happiness.

Evaluating soil quality across various altitudinal gradients, both with and without vegetative cover, is crucial for the proper functioning of soil and optimal crop growth, thereby contributing to the sustainability of agroecosystems. Although the altitudinal gradient significantly influences soil quality, the ability to predict this quality, expressed through an index, in soils with and without vegetative cover, is still insufficiently explored. This study aimed to assess soil quality in the Jun Jun micro-watershed, located in the Tungurahua region, Ecuador. To achieve this objective, three categories of altitudinal gradients were selected: less than 2800 meters above sea level (masl), between 2800 and 2900 masl, and greater than 2900 masl. A total of 24 soil samples were collected in the mentioned gradients, considering both areas with and without vegetative cover. The indicators used included chemical and biological parameters such as soil organic carbon (OC), earthworm density (WD), earthworm biomass (WB), organic matter (OM), pH, total nitrogen (TN), and organic carbon (OC). The results revealed that in areas with altitudinal gradients below 2800 masl, soil quality index values were higher compared to other altitudes. In vegetated areas, a decrease in index values was observed as the altitudinal gradient increased, indicating a deterioration in soil quality with altitude. These findings are significant in providing a quantitative assessment of the effects of altitudinal gradient and vegetative cover influence on soil quality.

Information security plays a major role in the dynamics of today’s interconnected world. Despite the successful implementation and effectiveness of modern cryptographic techniques, their inherent limitations can be exploited by quantum computers. In this article we discuss Grover’s quantum searching algorithm and its impact on the security of modern symmetric ciphers. More specifically, we present its formal description and give an implementation of the algorithm using IBM’s Qiskit framework, which allows us to simulate and run the program on a real device. The developed program is modular and scalable, managing to properly run on any input state. We compare the performance of the algorithm running on the local simulator against its execution on a quantum processor from IBM’s lineup, noting the discrepancies between the results due to physical characteristics of the chip.

The current recommendation to avoid non-steroidal anti-inflammatory drugs (NSAIDs) in management of dengue virus disease is, as it was adopted earlier in COVID-19, scientifically considered of very low to low certainty. In this perspective I argue, for the first time globally, basing on real-life practice that NSAIDs might be lifesaving in early management of dengue virus disease as I originally argued and proved rightful in COVID-19. Moreover, I also argue that the Egyptian immune-modulatory Kelleni’s protocol, including nitazoxanide as an integral component, can be safely and effectively used to early manage COVID-19, human metapneumovirus, dengue virus disease, Zika virus separate or co-infections similar to what has already been experienced and published with separate or conjoined infections with SARS CoV-2, influenza, RSV and Norwalk viruses without the need of prior serological or molecular investigations to determine the causative agent.

Chat generative pre-trained transformer (ChatGPT) is a developed language model and a subgroup of artificial intelligence (AI) which has demonstrated noticeable innovation in interactions between computer models and human studies. The release of ChatGPT in November 2022 attracted over 100 million users in a short time. It has unlimited applications in different fields of studies such as technology and science. ChatGPT utilizes deep learning and internet text to produce responses that resemble human language, although their accuracy is not always guaranteed. ChatGPT and GPT-4 can make a huge revolution in biology, medical, dental research, and health care. However, it's important to acknowledge the limitations of ChatGPT such as limitation in accessing the latest data. ChatGPT has generated both excitement and concern regarding its potential misuse. Its utilization in scientific publications has sparked debates and prompted the development of policies to govern the use of it. Although ChatGPT has certain limitations, it could impact on many different fields of study. There are challenges associated with using ChatGPT in the field of laboratory medicine and biology, particularly in the interpretation of test results. In this article, we review some of the applications of ChatGPT and GPT-4 in biology, dental and medical studies, and concerns about ChatGPT. Despite ChatGPT's conversational abilities are impressive, there are important considerations regarding its use in different fields of research and academic public.

This perspective discusses the ongoing real-world practice using nitazxoanide, NSAIDs and/or azithromycin (Kelleni’s protocol) to manage the evolving manifestations of SARS CoV-2 Omicron EG.5.1, its descendant HV.1 as well as BA.2.86 and its descendant JN.1 subvariants in Egypt. These subvariants are well-known for their highly evolved immune-evasive properties and the manifestations include some peculiar manifestations as persistent cough besides high fever in young children as well as high fever, persistent severe cough, change of voice, loss of taste and smell, epigastric pain, nausea, vomiting, diarrhea, generalized malaise and marked bone aches in adults including the high risk groups. It’s suggested that the ongoing SARS CoV-2 evolution is continuing to mostly affect the high risk groups of patients, to some of whom we’ve also successfully prescribed nitazoxanide and/or NSAIDs for post-exposure prophylaxis of all household contacts. We also continue to recommend starting the immune-modulatory antiviral Kelleni’s protocol as soon as possible in the course of infection and adjusting it in a personalized manner to be more aggressive from the beginning for the high risk patients, at least until the currently encountered surge of infections subsides.

Azithromycin has been shown to have a clinical efficacy against severe acute respiratory syndrome coronavirus 2 (SARS CoV-2); ivermectin has also demonstrated a remarkable experimental efficacy with a potential to be used for Coronavirus disease 2019 (COVID-19). Further, BCG vaccination is being considered for clinical trials aiming to test its potential for lowering COVID-19 morbidity and mortality. This article illustrates some structural and functional relationships that may gather these drugs and the author, basing on a combined pathophysiological and pharmacological approach, recommends the FDA-approved antidiarrhea drug; nitazoxanide, which has been previously suggested but unfortunately ignored, to be tested in combination with azithromycin for their potential activity against SARS CoV-2 soonest. The author recommends testing their combined administration as early during the clinical course of COVID-19 as possible. Further, basing on the same represented concept, the author recommends more trials for interferons to be tested against SARS CoV-2 especially in severe and critical cases.

The Geostationary Environment Monitoring Spectrometer (GEMS) onboard the Geostationary Korean Multi-Purpose Satellite 2B was successfully launched in February 2020. GEMS is a hyperspectral spectrometer measuring solar irradiance and Earth radiance in the range of 300 to 500 nm. This paper introduces the spectral calibration algorithm for GEMS, which uses a nonlinear least-squares approach. To assess the performance of the algorithm, sensitivity tests for a series of spectral parameters such as shift, spectral range for fitting, signal-to-noise ratio, spectral response function (SRF), and reference spectrum have been conducted. To improve the assessment, a synthetic GEMS spectrum using the prelaunch GEMS SRF is adopted here. The test results show that the required accuracy (0.002 nm) is achievable for the expected uncertainties of the parameters except for the SRF and the choice of high-resolution reference spectrum, which degrade the algorithm performance by an order magnitude. To mitigate the sensitivity to SRF, retrieval of in-orbit SRF using an analytic function is suggested. Finally, a few candidates for the high-resolution solar reference spectrum are prepared for testing by the instrument during in-orbit tests.

In recent years, the nanoparticles applications have been well recognized in various fields. It is known that nanoparticles as an active ingredient in sunscreens are widely used. Zinc oxide and titanium oxide nanoparticles are common nanoparticles utilized in sunscreens. In this study, we aimed to suggest new nanoparticles for this purpose. Cerium oxide nanoparticles (CeO2-NPs) were synthesized by using Musa sapientum fruit peel extract. Synthesized nanoparticles were identified through Raman, Powder X-ray Diffraction (PXRD), Fourier Transform Infrared spectroscopy (FT-IR), Field Energy Scanning Electron Microscopy (FESEM) and Energy-Dispersive Spectroscopy (EDX). The results showed that size of synthesized nanoparticles are in range 4-13 nm. The cytotoxic activity of synthesized nanoparticles on lung (A549) cancer cell line was performed through MTT assay. The results showed that synthesized nanoparticles are non-toxicity against A549 cell line to below 500 μg/mL of nanoparticles concentration. The Sun protection factor (SPF) was estimated ~ 40 for synthesized CeO2-NPs. So, synthesized nanoparticles can be a good option for use in the cosmetics industry.

SOX proteins are transcription factors which play a role in regulating the development of pro-genitor cells and tissue differentiation. Twenty members are known, clustered in eight groups named A to H, and sharing a common DNA-binding domain called the HMG (high-mobility-group) box. Eleven of the SOX genes have been associated with genetic disorders so far, covering a broad spectrum of developmental diseases. SOX4 is a single-exon gene and belongs to the SOXC group together with SOX11 and SOX12. SOX4 variants were recently described to cause a highly penetrant but heterogeneous disorder, with a phenotypic spectrum ranging from mild developmental delay and learning difficulties to intellectual disability with congenital anomalies. Nineteen pathogenic variants were reported to date, generally de novo, heterozygous, and inactivating, either stop-gain or missense, the latter ones primarily targeting the HMG domain. Further, a bi-allelic variant was reported in a single consanguineous family. Copy number variants, leading to whole gene deletion or duplication, are rare and not clearly associated with a neurodevelopmental disorder. Many open questions remain, regarding the definition of variants of unknown significance, a possible role of missense variants outside the HMG domain, genotype-phenotype correlation, the range of phenotypic spectrum and modifying factors, and treatment options.

In this paper, the tensile behavior of unidirectional carbon/epoxy prepreg is experimentally analyzed at varying loads and temperatures, focusing on the considerable nonlinearity at the beginning of the stress-strain curve. The high viscosity of this material presented difficulties in securely holding specimens during tensile testing. As a result, modifications were made to the conventional gripping method to enable the acquisition of reliable test data. Additionally, a longer gauge length was chosen to minimize the impact of slippage on the elastic modulus measurement. To support the experiment, a micromechanical model of a prepreg tow with fiber waviness is proposed. An RVE model of periodically distributed unidirectional waved cylindrical fibers embedded within the matrix is developed to predict the effective material stiffness parameters. Numerical results are presented for different amplitude-to-wavelength ratios which indicate the fiber waviness reduces the tensile modulus of the composite. The simulation results are in good agreement with the uniaxial tensile test of the prepreg tow.

: Soil free living nematodes community composition was compared for five agro-management systems in a basaltic soil. The sites differed in their long-term management system and were designated as organic farming (OM), conventional (MI), natural pasture (NP), foliage farming (FF) and open field (OF). The effect of five diverse land use types in vineyard growth in basaltic soils on soil free living nematodes, density, diversity, and functionality in the plant rhizosphere was examined. We found 22 families, 42 genera of which only 14 genera were present in all soil samples, three bacteria feeders, 4 fungi feeders, 3 omnivores-predators and 4 plant parasites, in the soil collected from the five sampling sites. The organic and conventional managements were found to influence soil free living nematode community and its trophic composition. The higher abundance of bacteria feeders included the Cephalobidae and Panagrolaimidae families. The fungi feeders included the Anguinidae and Aphelenchidae families. Ominvores-predators included the Aprocelaimidae and Qudsianematidae, and the plant parasites included the Anguinidae (genus Anguina), Nothotylenchidae and Tylenchidae families. The changes in plant parasite nematodes were one of the main pests in the below-ground rhizosphere biome. Promoting the bacterial community could be a beneficial and promising way for a considerable increase in organic management.

Transient receptor potential melastatin-8 (TRPM8) is a cation channel that is activated by cold and “cooling agents” such as menthol and icilin, which induce a cold sensation. Stimulation of TRPM8 activates an intracellular signaling cascade that ultimately leads to a change in the gene expression pattern of the cells. Here, we investigated the TRPM8-induced signaling pathway that links TRPM8 channel activation to gene transcription. Using a pharmacological approach, we show that inhibition of phosphatidylinositol 4-phosphate 5 kinase alpha (PIP5K), an enzyme essential for the biosynthesis of phosphatidylinositol 4,5-bisphosphate, attenuated TRPM8-induced gene transcription. Analyzing the link between TRPM8 and Gq proteins, we show that pharmacological inhibition of the beta gamma subunits impairs TRPM8 signaling. In addition, genetic studies showed that TRPM8 requires an activated Galpha subunit for signaling. In the nucleus, the TRPM8-induced signaling cascade triggers an activation of the transcription factor AP-1, a complex consisting of a dimer of basic region leucine zipper (bZIP) transcription factors. Here, we identified the bZIP protein c-Jun as an essential component of AP-1 within the TRPM8-induced signling cscade. In summary, with PIP5K, Gq subunits and c-Jun we have identified key molecules in the TRPM8-induced signaling from the plasma membrane to the nucleus.

Human Papillomavirus (HPV) self-sampling has the potential to increase cervical cancer screening (CCS) and reduce the cervical cancer burden in Medically Underserved Women (MUW). However, interventions promoting self-sampling are limited. We examined the effectiveness of an intervention study in increasing CCS among MUW. We conducted a quasi-experimental intervention study. Face-to-face verbal approach was to recruit MUW (n=85, mean age 48.57±11.02) living in a small city in the US. Behavioral intervention based on reframing, reprioritizing, and reforming (3R model) was used to educate the women about CCS in a group format. The women completed pre-and post-intervention assessments and followed-up interviews. The primary outcome was CCS uptake. Mixed methods analyses were conducted using a t-test for the primary outcome, PROCESS for mediation analysis, and NVivo for interview data. Majority of women (75%) completed self-testing. High-risk HPV prevalent among the women was 11%, and of those, 57% followed-up with physicians for care. We found that the significant increase in the women’s post-intervention screening behaviors was mediated by the increase in knowledge (Indirect Effect [IE] = .1314; 95% CI, .0104, .4079) and attitude (IE = .2167; 95% CI, .0291, .6050) scores, (p<0.001). Interview analyses offered further explanations (see the explanations in parenthesis) why MUW found the intervention messages acceptable (encourages proactive behavior), feasible (simple and easy to understand), and appropriate (helpful and informative). Barriers including lack of trust and fear of results were identified. The findings suggest that an intervention that combines the 3R model and self-sampling may increase CCS among MUW.

Housing is always crucial for the sustainable development of communities, specifically in urban areas, due to the population density of cities. The present study constructs its own structure on the basis of the recent papers investigating various sustainability factors for the urban housing sector. By doing a comprehensive systematic literature review, one of the most extensive lists of urban housing sustainability factors is gathered from 118 recent related papers. The factors are prioritized by their frequency of investigation and categorized by their scale(s) and sector(s) of influence. According to the results, the top three significant factors affecting urban housing sustainability are “natural resource or energy consumption/efficiency of the building/equipment (during the construction, operation, etc.)”, “materials performance (durability, cost, thermal capacity, permeability, ability to re-use, recycled, eco-friendly materials)”, and “access to public services/infrastructure: availability/quality of services and/or distance/time of travel time to the services (public transport, education/health/shopping/leisure facilities, parks, etc.)”. By analyzing the results with an integrative approach, it is understood that environmental factors are the most considered ones (more considered than the factors with influence on all sustainability sectors) where institutional factors received the least attention. Also, the most significant measures are the ones that have impacts on both ‘building’ and ‘neighborhood/community’ scales. It should be noticed that the neighborhood/community scale indicators are seen, almost, as important as the measures that affect the building itself. The results of this study can be helpful in establishing future housing-related policies, and also in having more efficient housing sustainability assessment tools.

Software engineering is a comprehensive process that requires developers and team members to collaborate across multiple tasks. In software testing, bug triaging is a tedious and time-consuming process. Assigning bugs to the appropriate developers can save time and maintain their motivation. However, without knowledge about a bug's class, triaging is difficult. Motivated by this challenge, this paper focuses on the problem of assigning the suitable developer to new bug by analyzing the history of developers’ profiles and analyzing history of bugs for all developers using machine learning-based recommender systems. Explainable AI (XAI) is AI that humans can understand. It contrasts with "black box" AI, which even its designers can't explain. By providing appropriate explanations for results, users can better comprehend the underlying insight behind the outcomes, boosting the recommender system's effectiveness, transparency, and confidence. In this paper, we propose two explainable models for recommendation. The first one is an explainable recommender model for personalized developers generated from bug history to know what the preferred type of bug is for each developer. The second model is an explainable recommender model based on bugs to generate the best developer for each bug from bug history.

The continuing development of industrialization and increasing population density has led to the emergence of noise as an increasingly common problem, requiring various types of sound absorption and insulation methods to address it. Meanwhile, the recycling of resources to ensure a sustainable future for the planet and mankind is also required. Therefore, this study investigates the potential of corrugated cardboard as a resource for noise reduction. The sound absorption and insulation performance of non-perforated corrugated cardboard (NPCC) were measured, and modified corrugated boards were fabricated by drilling holes either through the surface of the corrugated board alone or through the corrugated board in its entirety. The sound absorption/insulation performance both of perforated corrugated cardboard (PCC), and perforated corrugated cardboard with multi frequency resonators (PCCM) were measured using the transfer function method and the transmission matrix method. To determine the effectiveness of NPCC, PCC, and PCCM in noise reduction, the sound pressure level was analyzed by applying it to a home blender. The results showed PCCM’s sound absorption and insulation performance to be excellent. On the basis of these findings, we propose the use of PMMC as an eco-friendly noise reduction material.

When we were working on improving the resistance to deep abrasion of porcelain stoneware tiles, several tiles which had a very high resistance to abrasion were found in the market. The abraded volume of these tiles, measured via ISO 10545-6 method, was conspicuously less than 75 mm³. These values were well below the standard limit (<175 mm³) and reported values in the literature (>110 mm³). We determined the chemical, physical and microstructural characteristics of these tiles and other commercially available ones to find the relationship between the abrasion resistance and the technical specifications. We also characterized the samples by Vickers microhardness (VH), X-ray diffraction (XRD), mercury intrusion porosimetry (MIP) and scanning electron microscopy (SEM). It was observed that the high resistance to abrasion could be due to the presence of an adequate glassy phase capable of wetting all the hard crystalline phases in the matrix such as quartz and mullite. Therefore, the resistance to deep abrasion could be improved by increasing the amount of “vitreous” matrix, without altering the content of "hard" phases considerably well-bonded to the matrix.

Pyracantha angustifolia has been used in traditional medicine to treat a range of diseases of the stomach and improve digestion, blood circulation, diarrhea, dysentery, and hemostasis. This study evaluated bioactivity-guided fractionation as a means to identify therapeutic phytochemicals from P. angustifolia that can attenuate melanogenesis and oxidation. Seven compounds with inhibitory effects on melanin production and tyrosinase (TYR) activity, as well as ABTS and DPPH radical scavenging activities, and have not been reported as whitening materials, were isolated from the n-butanol fraction from P. angustifolia leaves (PAL). Among the seven compounds, p-hydroxybenzoic acid beta-d-glucosylester (HG), and cimidahurinine (CD) had strong inhibitory effects of melanin production, TYR activity, and ABTS and DPPH radical scavenging activities. Western blot analysis showed that HG and CD suppressed tyrosinase-related protein (TYRP)-1 and TYRP-2 expression. These results suggest that P. angustifolia containing active compounds, such as HG and CH, is a potent therapeutic candidate for the development of hypopigmenting agents.

The greatly diversified flowering plants (angiosperms) are the dominating and defining group in the current earth ecosystem. However, from which group by what way the flowers, especially their gynoecia (key characteristics of angiosperms), are derived have been the questions in botany unanswered over centuries. Such an embarrassing situation can be attributed to the lack of plants with partially enclosed ovules, which are supposed to be a post between gymnosperms and angi-osperms. Here we report a fossil plant that has an apparent coniferous vegetative and reproduc-tive morphologies but has a single seed partially wrapped by the subtending bract. Such a mor-phology suggests that the carpels in angiosperms may be equivalent to bracts enclosing their axil-lary seed(s). Such a non-traditional interpretation of the homology of angiosperm carpels is com-patible with various new progresses made in botany and is in line with Tomlinson’s recent hy-pothesis. Together with other fossil evidence reported recently, it appears that gynoecia in angio-sperms are derived in multiple ways.

Fighting corruption and enhancing tax compliance through digital public services represent key factors for increasing sustainable development in Romania. We argue that fighting corruption may increase the level of sustainable development, through digital pubic services. Using digital public services leads to the increase of the level of tax compliance, because entrepreneurs will feel more confident and responsible and they will decide to better comply. Tax regulations can affect the level of tax compliance through the additional costs they generate. The discussion is based on the consideration of the costs generated by compliant behavior and we explain how such costs influence the entrepreneurs’ decision in the fiscal environment. If the costs are higher, entrepreneurs will take evasive initiatives and will refuse to comply. Among the numerous tools developed to fight corruption, the use of communication technologies has recently been researched and there is still need for further research in the Romanian economic environment. The use of digital public services reduces costs for entrepreneurs and increases their confidence in state institutions due to higher levels of transparency. We argue for increasing sustainable development in Romania through digital public services, thus fighting corruption and enhancing tax compliance.

As one of GEO-constellation for environmental monitoring in the next decade, Geostationary Environment Monitoring Spectrometer (GEMS) is designed to observe the Asia Pacific region to provide the information on the atmospheric chemicals, aerosol and cloud properties. For the continuous monitoring of the sensor performance after its launch in early 2020, here we suggest deep convective clouds (DCCs) as a possible target for the vicarious calibration of GEMS, the first UV/VIS hyperspectral sensor onboard a geostationary satellite. Tropospheric Monitoring Instrument (TROPOMI) and Ozone Monitoring Instrument (OMI) are used as a proxy of GEMS, and a conventional DCC detection approach applying the thermal threshold test is used for the DCC detection based on the collocations with Advance Himawari-8 Imager (AHI) onboard Himawari-8 geostationary satellite. DCCs are frequently detected over the GEMS observation area on average over 200 pixels in a single observation scene. Considering the spatial resolution of GEMS, 3.5 km×7 km which is similar to TROPOMI, and its temporal resolution (8 times a day), availability of DCCs for vicarious calibration of GEMS is expected to be sufficient. Inspection of the DCC reflectivity spectra estimated from the OMI and TROPOMI data also shows a promising result. Even though, their observation geometry and sensor characteristics are quite a different, the estimated DCC spectra agree quite a well within a known uncertainty range with comparable spectral features. When the DCC detection is further improved by applying both visible and infrared tests, the variability of DCC reflectivity from the TROPOMI data is reduced by half, from 10% to 5%. This is mainly due to the efficient screening of cold thin cirrus with the visible test and of bright warm clouds with the infrared test. The precise DCC detection is also expected to contribute to the accurate characterization of the cloud reflectivity, which will be further investigated.

Amidst the escalating demands for efficient Intelligent Transportation Systems (ITS) management, the significance of accurate Origin-Destination (OD) data prediction has emerged as a paramount concern, given its indispensable role in the ITS domain. This paper introduces a groundbreaking integrated model, creatively fusing the unique strengths of Graph Convolutional Network (GCN), Residual Neural Network (ResNet), and Long Short-Term Memory Network (LSTM) into a single architecture, which we name GraphResLSTM, to exploit road segment average speed data for OD prediction. Compared with conventional road segment traffic volume data, average speed data is more readily available, significantly reducing the data accessibility barrier for OD prediction. We underscore the critical role of selection of key road segments and employs a combination of Entropy Weight Method and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to identify 41 representative road segments from the experimental road network. In the experimental phase, we simulate 86400000 seconds of traffic conditions, generating a total of 1440000 data records. Utilizing these simulated data, we design and conduct comparative experiments between models as well as data types. The results demonstrate that both the GraphResLSTM model and road segment average speed data outperform other models and data types notably in OD prediction tasks.

This study presents an in–depth analysis and strategic planning techniques for approaching a situation or achieving progress related to information technology services of Nueva Ecija University of Science and Technology, particularly the San Isidro Campus. As an educational organization and one in the region excellence providers in education, the University has so much vital information to manage and services to offer to provide the student's needs through the Management Information System department, application of IT services as a competing instrument to combat tedious tasks such as online admission, grade release, enrollment information, and online learning, university announcement, and possible students’ internship. The objective of this study is to determine the influence of information technology in day–to–day activities of the organization and strategy applied to streamline processes more conveniently. The researchers develop a conceptual model that would analyze the IT services' impact by identifying its strengths, weaknesses, opportunities, and threats and cleverly act on it using the TOWS Matrix in generating strategic decisions. The overall results were beneficial to the University and MIS as a basis for formulating competitive strategies and integrating it in an extended development plan.

System-of-systems (SoS) evolution is a complex and unpredictable process. Although various principles to facilitate collaborative SoS evolution have been proposed, there is a lack of experimental data validating their effectiveness. To address these issues, we present an Agent-Based Model (ABM) for SoS evolution in the Internet of Vehicles (IoV) , serving as a quantitative analysis tool for SoS research. By integrating multiple complex and rational behaviors of individuals, we aim to simulate real-world scenarios as accurately as possible. To simulate the SoS evolution process, our model employs multiple agents with autonomous interactions and incorporates external environmental variables. Furthermore, we propose three evaluation metrics: evolutionary time, degree of variation, and evolutionary cost, to assess the performance of SoS evolution. Our study demonstrates that enhanced information transparency significantly improves the evolutionary performance of distributed SoS. Conversely, the adoption of uniform standards only brings limited performance enhancement to distributed SoSs. Although our proposed model has limitations, it stands out from other approaches that utilize Agent-Based Modeling to analyze SoS theories. Our model focuses on realistic problem contexts and simulates realistic interaction behaviors. This study enhances the comprehension of SoS evolution processes and provides valuable insights for the formulation of effective evolutionary strategies.

To define and evaluate the areas of consideration concerning in identifying the critical factors that top universities in Nueva Ecija, Philippines can be used for triangulating the courses of actions that can be applied to improve the current practices of universities towards its combat to the COVID–19 disease is the primary objective of this study. The researchers used a descriptive design of methodology by using questionnaire–checklist to scientifically describe the situation, problems, phenomenon, or program, or provide information about certain issues related to the virus outbreak. The respondents of the study were faculty and staff of five established universities in Nueva Ecija, Philippines wherein the researchers employed a non–probability sampling technique to be logically assumed as the representative of the entire population. The results of the study shown that the top universities in Nueva Ecija have made efforts to ensure the safety of university workers by complying with the Inter–Agency Task Force (IATF) protocols. It can be inferred, in reality, that there are some areas that must be improved especially when it comes to ensuring the welfare of the personnel who are still reporting to work even in this time of the pandemic. The researchers suggested an enhancement plan that can be adapted by these universities to resolve the concerns of the faculty and staff especially in reducing the spread of the virus without sacrificing the day–to–day transactions of the academic institutions.

A new lateral force-resisting wall panel is presented for applications in mid-rise prefabricated lightweight steel construction in seismic prone regions. This panelised system is composed of a hot-rolled frame and cold-formed studs and tracks, which works as a lateral force resisting system in lightweight steel framing. The proposed hybrid panel system exhibits proper ductility and energy dissipation behaviour. The hysteretic responses of full-scale panel experiments demonstrate that the system can safely resist high cyclic loads. The hot-rolled steel part, on the other hand, can significantly improve the initial lateral stiffness of the total system that will control the maximum allowable drift of multi-story buildings. Finally, in a case study, by applying the proposed system to the design of a mid-rise building in a high seismic area, the performance of the hybrid panels, are compared with those of fully hot-rolled systems (moment resisting frames) and fully cold formed systems. The findings indicate that applying hybrid panels will result in lower weights and better performance in seismic prone regions.

Introdução: Os fatores de risco vasculares são decisivos na evolução da doença aterosclerótica e a ecografia Doppler carotídea e vertebral permite acompanhar o seu aparecimento e evolução. A medida do espessamento da parede arterial permite o diagnóstico precoce da doença potencializando seu tratamento e controle dos fatores de risco vasculares. Objetivo: Analisar a presença de doença ateromatosa em indivíduos com idade > 65 anos e compreender sua transformação com fatores de risco vascular. Materiais e Métodos: Estudo observacional transversal, em indivíduos com idade > 65 anos manifestados ao ecoDoppler carotídeo entre 1º de janeiro de 2012 e 31 de dezembro de 2021. Foi calculado o índice médio-intimal, a presença de placas ateromatosas, sua repercussão hemodinâmica e fatores de risco vascular foram registrados. Resultados: Obteve-se uma amostra de 5885 indivíduos, sendo 41,8% do sexo feminino e 58,2% do sexo masculino. A média de idade foi de 76,59 anos, variando entre 65 e 98 anos (+6,69). A hipertensão arterial foi a mais prevalente 81,3%. Houve relação positiva significativa entre índice médio-intimal, idade e história pessoal de doenças cardiovasculares e cerebrovasculares (p=0,001). Na presença de placas, sexo masculino, hipertensão arterial, diabetes, dislipidemia, tabagismo e história pessoal de doenças cardiovasculares e cerebrovasculares apresentadas de forma positiva. Conclusões: Nesta amostra, fatores de risco vascular não modificáveis ​​parecem ser determinantes na presença de aumento da espessura da parede arterial. Na presença de sinais de um estágio mais avançado da doença aterosclerótica, os fatores de risco vascular modificáveis ​​​​são decisivos,

Gas flaring is commonly used by industrial plants for processing oil and natural gases in the atmosphere, and hence is an important anthropogenic source for various pollutants including CO₂, CO, and aerosols. This study evaluates the feasibility of using satellite data to characterize gas flaring form space by focusing on the Khanty Mansiysk Autonomous Okrug in Russia, a region that is well known for its dominatingly gas flaring activities. Multiple satellite-based thermal anomaly data products at night are inter-compared and analyzed, including MODIS (Moderate Resolution Imaging Spectroradiometer) Terra level-2 Thermal Anomalies product (MOD14), MODIS Aqua level-2 Thermal Anomalies product (MYD14), VIIRS (Visible Infrared Imaging Radiometer Suite) Active Fires Applications Related Product (VAFP), and VIIRS level-2 data based Nightfire product (VNF). The analysis compares and contrasts the efficacy of these sensor products in detecting small, hot sources like flares on the ground in extremely cold environments such as Russia. We found that the VNF algorithm recently launched by NOAA has the unprecedented accuracy and efficiency in characterizing gas flares in the region owing primarily to the use of Shortwave Infrared (SWIR) bands. Reconciliation of VNF’s differences and similarities with other nighttime fire products is also conducted, indicating that MOD14/MYD14 and VAFP data are only effective in detecting those gas flaring pixels that are among the hottest in the region. Validation of VNF product of gas flaring location with Google Earth images are made. It is shown that that VNF’s estimates of gas flaring area (the area of gas flaming) agree well the counterparts from Google images with a linear correlation of 0.91, highlighting its potential use for routinely monitoring emissions of gas flaring from space.

Water pollution, intensified by the release of hard-to-degrade pollutants, poses severe threats to ecosystems, human health, and economic development. The existing advanced oxidation processes often involve high operational costs and may result in secondary pollution, highlighting the necessity for innovative and more sustainable solutions. To address these challenges, our study introduces a cost-effective and eco-friendly corona discharge barrier plasma discharger for wastewater treatment. Through the central composite design/response surface methodology, a high decolorization rate of 98% of methylene blue (MB) within 10 minutes was achieved by optimizing parameters such as pH and voltage. Furthermore, the mechanisms of the generation of reactive oxygen species via this device was discussed in detail and the degradation pathways of MB were described. Moreover, this device is also very energy-efficient, with a low energy density and electrical energy per order of 0.15 watt/mL and 5.79 kWh/m³/order, respectively. In conclusion, the plasma discharger developed in this study provides a cost-effective and environmentally sustainable solution for dye wastewater treatment. This research contributes significantly to the advancement of sustainable dye wastewater management practices, offering an innovative method that meets both environmental and economic objectives.

The soil and groundwater of Bhagobangola I block of Murshidabad district, West Bengal, India is severely arsenic contaminated. A bacterium was isolated from the garden soil of Mahishasthali village, which could tolerate 36.49 mM arsenic (III), 280.44 mM arsenic (V) and 63 mM chromium (III), which makes it arsenic (III & V) and chromium (III) hyper-tolerant bacterium. The growth pattern of this bacterium does not show much alteration in presence of 10 mM arsenic (III) and chromium (III), emphasizing its resistance to these heavy metals. Scanning electron microscopy depicted the size of this bacterium to be ~1.45 µm. 16S rDNA sequencing followed by subsequent phylogenetic analysis established the identity of this bacterium as Microbacterium paraoxydans. The bacterium is capable of bioremediation of arsenic and showed 30.8% & 22.6%, and 35.2% and 30.5% of bioremediation over a period of 24 and 48 hours in 1 mM and 4 mM arsenite, respectively. Microbacterium paraoxydans also exhibit plant growth promoting properties like nitrogen fixation, phosphate solubilization, indole-3-acetic acid production and production of siderophores. Therefore, the heavy metal resistance, bioremediation potential and plant growth promoting potential of the bacterium could be utilized not only for reduction of arsenic toxicity in soil and groundwater but also for plant growth promotion by using it as a biofertilizer.

Large epidemiological studies show U-shaped relationships between high-density lipoprotein cholesterol (HDL-C) levels and all-cause mortality in individuals without atherosclerotic cardiovascular diseases (ASCVD). Association in those with ASCVD by sex is unclear. We examined the association between HDL-C levels and 10-year all-cause mortality in subjects (≥40 years of age) with ASCVD using the 2010 National Health Insurance Service and the National Death Registry of Korea. We categorized HDL-C levels into three groups (low: <40 mg/dL for males, <50 mg/dL for females; high: 40-90 mg/dL for males, 50-90 mg/dL for females; extremely high: >90 mg/dL) and 10 mg/dL intervals. We conducted a sex-stratified and adjusted Cox proportional hazards analysis. Out of 1,711,548 individuals (54% female, mean age 61.4 years), 10-year mortality was observed in 218,252 (12.8%). Males had a higher mortality rate than females (16.2% vs 9.8%; P<0.001). When adjusting for age, body mass index, LDL-cholesterol, triglycerides, hypertension, diabetes, smoking, and alcohol consumption, the low and extremely high HDL-C groups had significantly higher hazard ratios for 10-year mortality compared to the high HDL-C group in males [1.183 (1.166-1.199), 1.359 (1.288-1.434)] and in females [1.153 (1.138-1.169), 1.095 (1.029-1.167)]. The frequency distribution bars for the 10-year mortality rate showed sex-specific nadirs of 50-59 mg/dL in males and 70-79 mg/dL in females. In this ASCVD cohort, the extremely high HDL-C (>90 mg/dL) group had 35.9% and 9.5% higher 10-year mortality risk than the high HDL-C group for males and females, respectively. There was a slightly U-shaped relationship between baseline HDL-C levels and 10-year mortality rate, with earlier inflection in males than in females.

Polarimetric Synthetic Aperture Radar (PolSAR) images encompass valuable information that can facilitate extensive land cover interpretation and generate diverse output products. Extracting meaningful features from PolSAR data poses challenges distinct from those encountered in optical imagery. Deep Learning (DL) methods offer effective solutions for overcoming these challenges in PolSAR feature extraction. Convolutional Neural Networks (CNNs) play a crucial role in capturing PolSAR image characteristics by leveraging kernel capabilities to consider local information and the complex-valued nature of PolSAR data. In this study, a novel three-branch fusion of complex-valued CNN named Shallow to Deep Feature Fusion Network (SDF2Net) is proposed for PolSAR image classification. To validate the performance of the proposed method, classification results are compared against multiple state-of-the-art approaches using the Airborne Synthetic Aperture Radar (AIRSAR) datasets of Flevoland, San Francisco, and ESAR Oberpfaffenhofen dataset. The results indicate that the proposed approach demonstrates improvements in OA, with 1.3% and 0.8% enhancement for the AIRSAR datasets and 0.5% improvement for the ESAR dataset. The analyses conducted on the Flevoland data underscore the effectiveness of the SDF2Net model, revealing a promising OA of 96.01% even with only 1% sampling ratio.

Ocean surface waves have been utilized as fundamental information in various fields of oceanic research. In this paper, we suggest a simulation and modelling technique for generating an ocean surface wave using an inverse Fast Fourier Transform (iFFT), and we subsequently verify the wave’s accuracy. The conventional method, linear superposition, requires recursive calculation because of the double summation and the time variable; to circumvent this issue, the new algorithm is presented. The Joint North Sea Wave Project (JONSWAP) spectrum is utilized for the ocean surface wave simulation example, and the parameters are the significant wave height (HS) and the zero-crossing wave period (TZ). A coordinate transform for the wavenumber domain was used to apply the inverse FFT algorithm. To verify the accuracy of the simulation result, the relative error between the input condition and the analysis result was calculated. The result for TZ is below 4% relative error, and the maximum relative error for HS is 7%. To avoid the Nyquist frequency for wave-field analysis and simulation, the minimum grid size was calculated by twice applying the maximum wavenumber.

With the rapid evolution of SARS-CoV-2, the emergence of new strains is an intriguing question. This paper presents an evolutionary theory to analyze the mutations of the virus and identify the conditions that lead to the generation of new strains. We represent the virus variants using a 4-letter sequence based on amino acid mutations on the spike protein and employ an n-distance algorithm to derive a variant phylogenetic tree. We show that the theoretically-derived tree aligns with experimental data on virus evolution. Additionally, we propose an A-X model, utilizing the set of existing mutation sites (A) and a set of randomly generated sites (X), to calculate the emergence of new strains. Our findings demonstrate that a sufficient number of random iterations can predict the generation of new macro-lineages when the number of sites in X is large enough. These results provide a crucial theoretical basis for understanding the evolution of SARS-CoV-2.

Excess salt and inadequate potassium intakes are associated with high cardiovascular disease (CVD). In Montenegro, CVD is the leading cause of death and disability. There is no survey that has directly measured salt and potassium consumption in Montenegro. The aim is to estimate population salt and potassium intakes and explore knowledge, attitudes and behaviour (KAB), amongst the adult population of Podgorica. Random samples of adults were obtained from primary care centres. Participants attended a screening including demographic, anthropometric and physical measurements. Dietary salt and potassium intakes were assessed by 24h urinary sodium (UNa) and potassium (UK) excretions. Creatinine was measured. KAB was collected by questionnaire. Six hundred and thirty-nine (285 men, 25-65 years) were included in the analysis (response rate 63%). Mean UNa was 186.5 (SD 90.3) mmol/day, equivalent to 11.6g of salt/day, and potassium excretion 62.5 (26.2) mmol/day, equivalent to 3.2g/day. Only 7% of them had a salt intake below the WHO recommended target of 5g/day, and 13% ate enough potassium (>90 mmol/day). The majority (86%) knew that high salt causes ill-health. However, only 44% thought it would be useful to reduce consumption. Salt consumption is high, and potassium consumption is low, in men and women living in Podgorica.

Despite recent advances in optimizing reliever, controller and maintenance therapy in asthma, a large subgroup of asthmatic patients continues to suffer from severe asthma, affecting their psychosociological status, their quality of life and even their life expectancy. Identifying and recognizing the specific phenotypic and endotypic characteristics in asthma has provided the medical community to drive the development of targeted therapies that are proved to benefit patients in terms of symptom control, exacerbation rate, quality of life and lung function. Adopting a more tailored and targeted approach is proving to be the key factor in reforming severe asthma treatment, minimizing the patients’ burden, as well as the socioeconomical impact worldwide. In this review, we are going to describe the different phenotypes and endotypes of asthma, the currently approved targeted therapies in severe asthma as imprinted in Global Initiative for Asthma (GINA) 2023, as well as other potential pharmacological agents and strategies investigated or currently under investigation for the treatment of severe asthma.

The emergence of new type of viral pneumonia cases in China, on December 31, 2019; identified as the cause of human coronavirus, labeled as "COVID-19," took a heavy toll of death and reported cases of infected people all over the world, with the potential to spread widely and rapidly, achieved worldwide prominence but arose without the procurement guidance. There is an immediate need for active intervention and fast drug discovery against the 2019-nCoV outbreak. Herein, the study provides numerous candidates of drugs (either alone or integrated with another drugs) which could prove to be effective against 2019-nCoV, are under different stages of clinical trials. This review will offer rapid identification of a number of repurposable drugs and potential drug combinations targeting 2019-nCoV and preferentially allow the international research community to evaluate the findings, to validate the efficacy of the proposed drugs in prospective trials and to lead potential clinical practices.

Recent advances in single-atom catalysis resulted in readily accessible materials whose application in most catalytic reactions mediated by conventional nanoparticle-based catalysts often results in higher activity and selectivity. Can we expect catalysis by atomically dispersed atoms to find practical applications? Which are the hurdles to be overcome prior to widespread uptake of atomically dispersed metals in industrial synthetic processes and in hydrogen fuel cells?

Tack is one of the most important factors affecting the operability of prepregs, but it is still very difficult to obtain the change of prepreg tack with time at different temperatures. In this paper, a newly designed T-peel device is used to test the tack decay rate of prepregs at different temperatures. The obtained decay rate deviates less than 8.9% from the manufacturer's data. The maximum deviation of the ratio of tack decay speeds calculated by the Arrhenius equation from the experiments is not higher than -9.7%. It is proved that the present method can obtain the decay rate of tack of prepregs at different temperatures. This method is also applicable to the other two types of prepregs. The article proposes the handling life unit, an operational life measurement unit for prepregs, and establishes that the relationship between tack and remaining shelf life reduces prepreg management costs.

Saikosaponin (SS) a is a compound with various pharmacological properties and easily degraded into SSb1 and SSg in acid condition. In present work another two new degradation products of SSa formed under acid hydrolytic condition were detected and isolated by analytical and semi-preparative liquid chromatography technology, furthermore their structures were characterized as hydroxyl-saikosaponin a and SSb2 by spectral analysis, which is not only essential in stability-indicating method development and validation but also could be used as a worst case to assess the analytical method performance of SSa. Moreover their structural transformation pathways were also proposed.

This study explored the incidence of metaphorical virtual classrooms and interactive learning objects in the interaction of students in online mode. The main objective was to analyze how these digital tools, driven by a set of strategies to promote their use, affect the interaction of students in the virtual classroom system and their derived effects. To this end, the latest version of Moodle was implemented in conjunction with gamification plugins and interactive tools in the higher education institution used as a case study. The methodology consisted of data collection through ordinal instruments applied to the teachers and student performance metrics gathered using a plugin developed to extract accurate metrics of each student's usage and performance through direct queries to the Moodle database and its processing through a neural network. This facilitated the collection of standardized data on the actual metrics of each virtual classroom at the end of the teaching of each subject from both the previous LMS and the newly implemented one. This data was then analyzed using advanced statistical techniques, including Mahalanobis distances, confirmatory factor analysis, and the Wilcoxon signed-rank test. These methods provided a compelling comparison between the old and new systems, revealing significant improvements in the metrics and factors evaluated. The results showed a significant improvement in teachers' perceptions of the usability of the virtual classroom system and an increase in students' academic performance, interaction, progress, and time spent learning in virtual contexts. These results provide solid empirical evidence of the added value of these educational tools as effective strategies for improving student interaction, performance, and motivation in online education.

Resection of malignant lesions in the oral and maxillofacial area causes functional and morphological defects. To recover from these defects, reconstruction surgery is needed such as a primary closure or a flap. There are advantages and disadvantages to the method of using the primary closure and the flap, and the choice of procedure is entirely up to a surgeon. The purpose of this study is to evaluate availability of primary closure in patients. For 10 years from January 2010 to May 2020, patients who recovered using flaps after removing malignant lesions from the oral cavity and those who closed the lesion using primary closure were investigated. The investigation was conducted by searching the database of the hospital. There were 85 patients who removed malignant lesions in the oral and maxillofacial area, and among them 16 patients closed the soft tissue defects using primary closure. Operation time, histologic types, stages, wound status, and period of hospitalization according to the patients' medical records were investigated retrospectively. Between the staging and the primary closure, statistically significant differences were observed between stage I and stage II patients in 13 patients using the primary closure. (P=0.046). Statistically significant differences were identified between operation time and primary closure, with an average of 4.02 hours (P=0.015). The average period of hospitality for patients who underwent primary closure was 13.4 days, compared to 26.7 days for those who underwent flap surgery. This difference was statistically significant (P=0.0003). This study evaluated the use of primary closure in patients who underwent resection of malignant lesions in the oral and maxillofacial area. Although the majority of patients underwent reconstruction with flaps, our results showed that primary closure can be a viable option for certain patients with early-stage lesions. Therefore, oral and maxillofacial surgeons should carefully consider various evaluation criteria and select appropriate reconstruction methods to optimize functional and aesthetic outcomes for each patient.

A robust guaranteed cost preview repetitive controller is proposed for a class of polytopic uncertain discrete-time systems. In order to improve the tracking performance, the repetitive controller combined with preview compensator is inserted in the forward channel. By using the L-order forward difference operator, an augmented dynamic system is constructed. Then, the guaranteed cost preview repetitive control problem is transformed into the guaranteed cost control problem for the augmented dynamic system. For given performance index, the sufficient condition of asymptotic stability for the closed-loop system is derived by combining parameter-dependent Lyapunov function method with linear matrix inequality (LMI) techniques. By incorporating the controller obtained into the original system, the guaranteed-cost preview repetitive controller is derived. A numerical example is also included to show the effectiveness of the proposed method.

The objective of this study was to analyze the effects of a pulmonary telerehabilitation (TR) program in young adults with post-COVID-19 syndrome. The information of sixteen students' medical files were analyzed and allocated to one of two groups (control=CG/experimental=EG). Twelve TR sessions were performed distantly and asynchronously at the EG patients' homes during 4-weeks. The program included diaphragmatic pattern breathing and aerobic exercises. The parameters: i) vital signs (oxygen saturation "SpO2", heart rate "HR", respiratory rate "RR" and blood pressure "BP"; ii) physical capacity “Sit-to-stand test”; iii) cardiorespiratory capacity “6-Minute Walk Test”; and iv) perceived effort "Borg scale" were assessed in both groups. The statistical analyses showed a significant decrease of RR and HR (p < 0.012) accompanied by a significant increase in SpO2 (p < 0.042), physical (p < 0.012) and respiratory (p < 0.028) capacity. The perceived effort decreased significantly in both groups (CG: p < 0.006; EG p < 0.001) only for physical but not for cardiorespiratory capacity (p < 0.106). There were no statistical changes registered in BP (p > 0.05). The current study suggests that a TR program that involves breathing and aerobics exercises is feasible and effective in treating post-COVID-19 syndrome in young patients.

Blood image intensity has been used to detect erythrocyte sedimentation rate (ESR). However, it does not give an information on biophysical properties of blood sample under continuous ESR. In this study, three physical properties, including, τ₀, ESR_τ, and AI_I, are suggested to quantify mechanical variations of blood under continuous ESR. To demonstrate the proposed method, blood sample is loaded into a driving syringe. The blood flow rate is set in a periodic on–off pattern. Blood sample is then supplied into a capillary chip, and microscopic blood images are captured at specific intervals. Blood shear stress is quantified from the interface of blood stream in the coflowing channel. Both τ₀ and ESR_τ are then obtained by analyzing the blood shear stress. Simultaneously, the AI_I is evaluated by analyzing the image intensity of blood flow. According to the experimental results, the τ₀ exhibits consistent trends with respect to hematocrit as well as diluent. The ESR_τ and AI_I showed a reciprocal relationship each other. Three suggested properties represented substantial differences for suspended blood samples (i.e., hardened red blood cells, different concentration of dextran solution and fibrinogen). In conclusion, the present method can detect variations of blood sample under continuous ESR effectively.

Searching over a sorted list is a classical problem in computer science. Binary Search takes at most log2n+1 tries to find an item in a sorted list of size n. Interpolation Search achieves an average time complexity of Ο(loglogn) for uniformly distributed data. Hybrids of Binary Search and Interpolation Search are also available to handle data with unknown distributions. This paper analyzes the computation cost of these methods and shows that interpolation can significantly affect their performance — accordingly, a new method, Interpolation Once Binary Search (IOBS), is proposed. The experimental results show that IOBS outperforms the hybrids of Binary Search and Interpolation Search for nonuniformly distributed data.

The hybrid method proposed in the study, ANFIS-GWO, combines the Adaptive Neuro-Fuzzy Inference System (ANFIS) with Grey Wolf Optimization (GWO) for the diagnosis of liver disorders. ANFIS is a powerful tool that combines the advantages of neural networks and fuzzy logic to create a hybrid model capable of handling complex and uncertain data. GWO is a metaheuristic optimization algorithm inspired by the social behaviour of grey wolves. In the ANFIS-GWO method, the hyperparameters of ANFIS are optimized using GWO. This optimization process aims to fine-tune the ANFIS model based on the available dataset, which consists of 7 characteristic attributes and 354 samples related to liver diseases. By adopting the hyper-parameters, the ANFIS-GWO method enhances the overall performance and accuracy of the diagnostic system. To evaluate the effectiveness of the ANFIS-GWO intelligent medical system, the study employs classification accuracy, sensitivity, and specificity analysis. Classification accuracy measures the overall correctness of the system in predicting liver disease cases. Sensitivity refers to the system’s ability to correctly identify individuals with liver disorders, while specificity measures its ability to correctly identify those without liver disorders. Experimental results demonstrate that the performance of the ANFIS-GWO method surpasses that of traditional Fuzzy Inference Systems (FIS) and ANFIS models that do not undergo an optimization phase. This suggests that the integration of GWO optimization significantly improves the diagnostic accuracy of the ANFIS model for liver disease diagnosis.

The surface velocity of the Amery Ice Shelf (AIS) is vital to assessing its stability and mass balance. Previous studies have shown that the AIS basin has a stable multi-year average surface velocity. However, spatiotemporal variations in the surface velocity of the AIS and the underlying physical mechanism remain poorly understood. This study combined offset tracking and DInSAR methods to extract the monthly average surface velocity of the AIS and obtained the inter-annual surface velocity from the ITS_LIVE product. An uneven spatial distribution in inter-annual variation of the surface velocity was observed between 2000–2022, although the magnitude of variation was small at less than 20.5 m/yr. The increase and decrease in surface velocity on the eastern and western-central sides of the AIS, respectively, could be attributed to the change in the thickness of the AIS. There was clear seasonal variation in monthly average surface velocity at the eastern side of the AIS between 2017–2021, which could be attributed to variations in the area and thickness of fast-ice and also to variations in ocean temperature. This study suggested that changes in fast-ice and ocean temperature are the main factors driving spatiotemporal variation in the surface velocity of the AIS.

In February 2004, the Food and Drug Administration (FDA) was the first to approve the combination of cisplatin (CDDP) and pemetrexed (PEM) as standard first-line chemotherapy for untreated, unresectable malignant pleural mesothelioma (MPM). However, after that approval, no progress was made in the standard first-line treatment of MPM for almost 15 years. Positive results from a phase 3 study (Mesothelioma Avastin Cisplatin Pemetrexed Study: MAPS) verifying the effect of bevacizumab, an anti-angiogenesis agent added to CDDP/PEM for unresectable MPM, were published in The Lancet in December 2015; however, this did not lead to approval by national drug regulatory agencies. Furthermore, no second-line treatment was established for cases refractory to CDDP/PEM. In August 2018, the Pharmaceuticals and Medical Devices Agency of Japan was the first in the world to approve monotherapy with nivolumab, an immune checkpoint inhibitor (ICI), for previously unresectable, advanced, or recurrent MPM. Following Japan, in October 2020, the FDA approved the combination of nivolumab and ipilimumab for the treatment of previously untreated, unresectable MPM. In this article, we review the transition of drug treatment for MPM, in light of the historical background, focusing on the benefits of ICIs.

The multidrug resistance transporter NorM is an important drug resistance pump and plays a critical role in multidrug resistance in bacteria and mammals. In this study we carried out molecular dynamics simulation to study the mechanism of Na+ binding and dynamical structures of two long loops in the substrate-releasing process in substrate binding NorM. Our simulation study identified several key residues (D41, E261 D377) along the Na+ binding pathway and a multi-state ion-binding mechanism is proposed based on the simulation study. In this proposed model, the transport of Na+ is a multi-stage process with D41 being the first station for binding to Na+, followed by Na+ binding to the second station E262 and finally to the cation-binding site of E262 and D377. During the transport of Na+, the transmembrane components TM1, TM7 and TM2 are rearranged to facilitate the ion transport as well conformational changes of NorM to a closed state. Further, substrate-bound simulation revealed that Loop3-4 and Loop9-10 control the substrate-releasing process.

Flap surgery is a common method used to cover defects following tumor ablation, trauma, or infection. However, insufficient vascularity in the transferred flap can lead to flap necrosis and failure. Proper postoperative monitoring is essential to prevent these complications. Recently, research has explored the use of infrared thermal imaging in plastic surgery, leading to its clinical application. This study investigates the use of a forward-looking infrared (FLIR) camera to monitor blood flow in flaps. In the study, 28 rats underwent reverse McFarlane flap surgery, and their flaps were analyzed using a FLIR thermal imaging camera seven days post-surgery. Additionally, thermal images of flaps were taken on postoperative days 0, 1, 2, 3, and 7 in 22 patients. The study focused on temperature differences between normal skin and the perforator compared to the average flap temperature. Results showed that the temperature difference was higher in the necrosis group and increased over time in cases of total necrosis. A lower perforator temperature compared to the flap's average indicated vascular compromise, potentially leading to flap failure. The FLIR camera, being contact-free and convenient, shows promise for understanding and inferring the clinical progression of flaps in postoperative monitoring.

Background: Smart transport plays a crucial role in urban planning and the transition from traditional to smart cities in developing countries with sustainability requirements.Traditional cities in developing countries often suffer from traffic congestion,air pollution, and inadequate public transportation systems,which can impede economic growth and negatively impact the quality of life for residents. Smart transport solutions can address these challenges by providing more efficient, sustainable.Here is a possible business model for an ITS system in a high-potential city in Iran,Based on IoT analysis, Mashhad city in Iran selected as a high-potential city to be changed to a smart city in the transportation sector.In the localization business model,the Uber smart transportation business model as a successful world experience is considered the base model. Methods: Based on the literature review,various criteria and sub-criteria were identified and determined in designing a new localized transportation business model.A questionnaire was prepared and filled with the help of 11 experts,method IAHP technique; Results:The present study showed the possibility of monthly payments for customers,software development, and the addition of luxury cars are among the most important sub-criteria with high weights;Conclusions: Working with transport companies,schools and universities as key partners solves reaching a strong and sustainable smart transportation system.

Flexible implementations of Monte Carlo Tree Search (MCTS), combined with domain specific knowledge and hybridization with other search algorithms, can be a very powerful for the solution of problems in complex planning. We introduce mctreesearch4j, a standard MCTS implementation written as a standard JVM library following key design principles of object oriented programming. We define key class abstractions allowing the MCTS library to flexibly adapt to any well defined Markov Decision Process or turn-based adversarial game. Furthermore, our library is designed to be modular and extensible, utilizing class inheritance and generic typing to standardize custom algorithm definitions. We demon- strate that the design of the MCTS implementation provides ease of adaptation for unique heuristics and customization across varying Markov Decision Process (MDP) domains. In addition, the implementation is reasonably performant and accurate for standard MDP’s. In addition, via the implementation of mctreesearch4j, the nuances of different types of MCTS algorithms are discussed.

Oleuropein, glycosylated secoiridoid present in olive leaves is known to be an important antioxidant phenolic compound. We studied the antioxidant effect of low doses of oleuropein aglycone (3,4-DHPEA-EA) and oleuropein aglycone peracetylated (3,4-DHPEA-EA(P)) in murine C2C12 myocytes treated with hydrogen peroxide (H2O2). Both compounds were used at a concentration of 10 μM and were able to inhibit cell death induced by the H2O2 treatment, with 3,4-DHPEA-EA(P) being more. Under our experimental conditions, H2O2 efficiently induced the phosphorylated-active form of JNK and of its downstream target c-Jun. We demonstrated, by Western blot analysis, that 3,4-DHPEA-EA(P) was efficient in inhibiting the phospho-active form of JNK. This data suggests that the growth arrest and cell death of C2C12 proceeds via the JNK/c-Jun pathway. Moreover, we demonstrated that 3,4-DHPEA-EA(P) affects the myogenesis of C2C12 cells; because MyoD mRNA levels and the differentiation process are restored with 3,4-DHPEA-EA(P) after treatment. Overall, the results indicate that 3,4-DHPEA-EA(P) prevents ROS-mediated degenerative process in a genomic and epigenomic manner by functioning as an efficient antioxidant.

Oleuropein, glycosylated secoiridoid present in olive leaves is known to be an important antioxidant phenolic compound. We studied the antioxidant effect of low doses of oleuropein aglycone (3,4-DHPEA-EA) and oleuropein aglycone peracetylated (3,4-DHPEA-EA(P)) in murine C2C12 myocytes treated with hydrogen peroxide (H2O2). Both compounds were used at a concentration of 10 μM and were able to inhibit cell death induced by the H2O2 treatment, with 3,4-DHPEA-EA(P) being more. Under our experimental conditions, H2O2 efficiently induced the phosphorylated-active form of JNK and of its downstream target c-Jun. We demonstrated, by Western blot analysis, that 3,4-DHPEA-EA(P) was efficient in inhibiting the phospho-active form of JNK. This data suggests that the growth arrest and cell death of C2C12 proceeds via the JNK/c-Jun pathway. Moreover, we demonstrated that 3,4-DHPEA-EA(P) affects the myogenesis of C2C12 cells; because MyoD mRNA levels and the differentiation process are restored with 3,4-DHPEA-EA(P) after treatment. Overall, the results indicate that 3,4-DHPEA-EA(P) prevents ROS-mediated degenerative process in a genomic and epigenomic manner by functioning as an efficient antioxidant.

Over recent decades, therapeutic proteins have had widespread success in treating a myriad of diseases. Glycosylation, a near universal feature of this class of drugs, is a critical quality attribute that significantly influences the physical properties, safety profile and biological activity of therapeutic proteins. Optimizing protein glycosylation, therefore, offers an important avenue to developing more efficacious therapies. In this review, we discuss specific examples of how variations in glycan structure and glycoengineering impacts the stability, safety, and clinical efficacy of protein-based drugs that are already in the market as well as those that are still in preclinical development. We also highlight the impact of glycosylation on next generation biologics such as T cell-based cancer therapy and gene therapy.

Insulated Gate Bipolar Transistor (IGBT) may convey high current and sustain high breakdown voltages; it may provide high power control. In a sense, how IGBT demonstrates the capability of power control was not specifically described, and the equivalent bipolar junction transistors (BJT) activated by an applied bias to the insulated gate is intriguing. As seen in Figure 1, IGBT shows an equivalent circuit structure containing two types of BJT, (NPN-type Bipolar transistor and PNP-type Bipolar transistor), which can be modeled as diode-associated transistor. Apparently, as a bias applies to the controlling gate, the channel beneath the gate oxide gets strongly inversed and turns out to be conductive just like what happens on metal-oxide-silicon field effect transistor (MOSFET), which provides necessary igniting currents to both BJTs and thus causes high current gain flowing through them-selves from the bottom. A proposed and renewed formula provides addressing the above scenario and successfully fitting the measured data that forms the characteristic curves. Some parameters in the proposed formula, which includes size and mobility associated constant, threshold voltage, and Early-Voltage-related lambda for MOSFET, explain and explore the underlying physics. IGBT thus enjoy high input impedance and high current gain due to MOSFET (Insulated Gate) and BJT, respectively. This formula combines both merits of MOSFET and BJT in order to fit the measured data. Indeed, the formula intimately fits IGBT electrical characteristic curves, and thus may be qualified and served as a model. The new model is then advisable for designing power integrated circuit to exactly achieve power saving, power control, and power efficiency.

Scaffold guided breast tissue regeneration (SGBTR) can both transform reconstructive and cosmetic breast surgery. Implant-based surgery is the most common method. However, there are inherent limitations as there is replacement of tissue rather than regeneration. Regenerating autologous soft tissue has the potential to provide a more like-for-like reconstruction with minimal morbidity. Our SGBTR approach regenerates soft tissue by implanting additively manufactured bioresorbable scaffolds filled with autologous fat graft. A pre-clinical large animal study was conducted implanting 100 ml breast scaffolds (n=55) made from medical-grade polycaprolactone in 11 minipigs for 12 months. Various treatment groups were investigated where immediate or delayed autologous fat graft, as well as platelet rich plasma were added to scaffolds. Computed Tomography and Magnetic Resonance Imaging was performed on explanted scaffolds to determine volume and distribution of regenerated tissue. Histological analysis was performed to confirm tissue type. At 12 months we were able to regenerate and sustain a mean soft tissue volume of 60.9 4.5 ml (95% CI) across all treatment groups. There was no evidence of capsule formation. There were no immediate or long-term post-operative complications. In conclusion, we were able to regenerate clinically relevant soft tissue volumes utilizing SGBTR in a pre-clinical large animal model.

In order to better realize rural revitalization, this paper analyzes the spatial and temporal char-acteristics and influencing factors of agricultural surface source pollution in the Yangtze River Economic Belt from the three perspectives of government, enterprise and agriculture by using the spatial Durbin model and the dynamic GMM method in the period of 2006-2021, and further re-searches the threshold characteristics of the distortion of the factor market on the agricultural surface source pollution under the different strengths of environmental regulation. The results show that there is a positive spatial correlation between agricultural surface pollution in the Yangtze River Economic Belt, and government environmental regulation, input factor market distortion and labor force transfer all have a significant impact on agricultural surface pollution. Among them, factor market distortion has a significant spatial spillover effect on agricultural surface pollution in the Yangtze River Economic Zone, and has a significant single-threshold ef-fect on environmental regulation. Accordingly, the government should strengthen environmental regulation, continuously improve the agricultural factor market mechanism, and pay attention to the construction of talents to provide support for rural revitalization.

The high prevalence of human papillomavirus (HPV) infection in oropharyngeal squamous cell carcinoma (OPSCC) is well-established, with p16 expression being a strong predictor. HPV-related tumors exhibit unique mechanisms targeting p16 and p53 proteins. However, re-search on HPV prevalence and the combined predictive value of p16 and p53 expression in head and neck cutaneous squamous cell carcinomas (HNCSCC), especially in Asian populations, is limited. This retrospective study surveyed 62 HNCSCC patients (2011–2020), excluding those with facial warts or other skin cancers. All patients underwent wide excision and biopsy. Immuno-histochemical staining for HPV, p16, and p53 yielded both positive and negative results. The relevance of each marker was investigated by categorizing the tumor locations into high-risk (Area H) and mid-risk (Area M) zones based on recurrence frequency. Of the 62 patients, 20 (32.26%) were male, with an average age of 82.27 years (26–103). Area H included 19 cases (30.65%), with the eyelid and lip being the most common sites (five cases, 8.06%). Area M in-cluded 43 cases (69.35%), with the cheek being the most common site (29 cases, 46.77%). p16 ex-pression was positive in 24 patients (38.71%), p53 expression in 42 patients (72.58%), and HPV in five patients (8.06%). No significant association was found between p16 expression and HPV presence (p > 0.99), with a positive predictive value of 8.33%. This indicates that p16, a surrogate marker of HPV in OPSCC, is not a reliable marker for HPV in HNCSCC. This study enhances our understanding of the relationship between HPV, p53, and p16 in HNCSCC in Asian populations and offers valuable insights for further research.

Although promoting healthy eating is a policy objective, the controllability of dietary habits remains uncertain. The personal dietary patterns reflect many factors, of which some are relatively controllable for individual, and others are not. In this article, assuming that some sort of information about controllability of dietary habits is contained in the observed pattern of food consumptions, we focused on dietary pattern on its own. We introduced a statistical descriptive model for data on food frequency questionnaire, estimated strength of pairwise linkage between foodstuffs, and grouped foodstuffs by applying community detection to the networks of the estimated inter-food linkages. Those linkages represent co-movement of pairs of foods consumption. Furthermore, we demonstrated an analysis on the relationship between health of mind and dietary habits considering the aspect of controllability of dietary habits. Using an observational study in Japan, we obtained the following results: 115 foodstuffs were divided into 3 groups for both of genders, but the compositions were different by gender; in the analysis of mental health, some stress response items were associated with the dependence on some of those food groupings. As the grouping of foodstuffs based on our estimation depicted the internal structure of dietary habit that a healthy eating policy should regard as constraint, it follows that we should design the policy along the line with that grouping.

Evans' Syndrome (ES) is a rare autoimmune disorder characterized by the simultaneous occurrence of immune thrombocytopenia (ITP) and autoimmune hemolytic anemia (AIHA). Thrombotic complications in ES patients are uncommon, particularly involving Buerger's Disease (BD). We report a case of a 49-year-old male with ES and a history of diabetes and heavy smoking, presenting with a necrotic wound on his right great toe. Diagnostic evaluations revealed severe stenosis and thrombosis in the lower limb arteries, diagnosed as BD. The patient underwent successful popliteal-tibioperoneal artery bypass surgery and subsequent disarticulation and revision of the distal phalanx, followed by the application of an acellular dermal matrix (ADM) to promote healing. Post-surgery, the patient showed significant improvement in blood flow and complete epithelialization without complications. This case highlights the importance of a multidisciplinary approach in managing complex wounds in ES patients, suggesting potential treatment pathways for future cases involving BD

Oleuropein, glycosylated secoiridoid present in the olive leaves, is known as an important antioxidant phenolic compound. We studied the antioxidant effect of low dose of oleuropein aglycone (3,4-DHPEA-EA) and oleuropein aglycone peracetylated (3,4-DHPEA-EA(P)) in murine C2C12 myocytes treated with hydrogen peroxide (H2O2). Both compounds were used at a concentration of 10 μM and were able to inhibit cell death induced by H2O2 treatment, with 3,4-DHPEA-EA(P) being more. Under our experimental conditions H2O2 efficiently induced the phosphorylated-active form of JNK and of its downstream target c-Jun. We demonstrated, by Western blot analysis, that 3,4-DHPEA-EA(P) was efficient in inhibiting the phospho-active form of JNK. This data suggest that growth arrest and cell dead of C2C12 proceeds via the JNK/c-Jun pathway. Moreover, we demonstrated that 3,4-DHPEA-EA(P) affects myogenesis of C2C12 cells; because the MyoD mRNA levels and the differentiation process are restored after treatment with 3,4-DHPEA-EA(P). Overall, the results indicate that 3,4-DHPEA-EA(P) prevents ROS-mediated degenerative process by functioning as an efficient antioxidant.

The purpose of this study is to examine the relationship between the institutional investors which can affect financial performance for corporate sustainability on the income smoothing. Therefore, this study focus on the connection between the nature of stock rights and income smoothing in China. For this study, hypotheses were established on the relationship each state-controlled companies, income smoothing, and information equilibrium of individual investors, and empirical analysis was conducted through related variables. The analysis results are summarized in three categories as follows. First, this research finds that state-controlled firms (CONTs) prefer income smoothing activities compared to non-state-controlled firms for the long-term sustainable development of firms using data from 2011 to 2019. Second, this study found out that Institutional investors support the behavior of CONTs to smooth their earnings because this behavior is seen as an attempt by CONTs to convey valuable private information to other investors. Third, we was able to discover that institutional investors' monitoring effect is predominantly driven by pressure-resistant institutional investors. This research complements the lack of empirical research on income smoothing and enable to give a guideline that the type of stock rights is a critical key determinant of participation in income smoothing activities for stable growth and sustainability in the future.

Considering the spectrum shortage problem of IoT devices, we introduce a collaborative spectrum sensing (CSS) framework in this paper to identify available spectrum resources, so that IoT devices can access it and meanwhile avoid causing harmful interference to the normal communication of the primary user (PU). However, in the process of the PU’s signal detection in IoT devices, the issue about the stopping time and decision cost arises. To this end, we propose a distributed cognitive IoT model, which includes two IoT devices independently using sequential decision rules to detect the PU. On this basis, we define the stopping time and cost function for IoT devices, and formulate an average cost optimization problem in CSS. To solve this problem, we further regard the optimal stopping time problem as a finite horizon problem, and solve the threshold of the optimal decision rule by dynamic programming. At last, numerical simulation results demonstrate the correctness of our proposal in terms of the global false alarm and miss detection probability, and it always achieves minimal average cost under various cost of each observation taken and thresholds.

Acute intense exercise causes significant oxidative stress and consequently an increase in total antioxidant capacity; however, the mechanisms and combined effects of intense exercise and smoking on oxidative stress among active and non-active smokers are not clear. The aim of this study was to investigate the effect of acute intense exercise on antioxidant enzyme activity responses in active and non-active individuals exposed to cigarette smoke. The study included 40 subjects who were equally classified as: smokers that did exercise (SE), smokers that did not do exercise (SnE), non-smokers that did exercise (NSE), and non-smokers that did not do exercise (NSnE). The adjusted Astrand test was used to exhaust the subjects. Salivary enzymes of peroxidase (POX), catalase (CAT), and superoxide dismutase (SOD) were measured, by spectrophotometry methods, at 3 different time points: pre-test (TP1), post-test (TP2), and one hour after finishing the test (TP3). Significant (p<0.05) group x time interactions were found for the three enzymes. Salivary POX, CAT and SOD increased in all groups from TP1 to TP2 and decreased from TP2 to TP3. Only the NSE showed a significant difference between TP1 to TP3 in POX and SOD by +0.011 ± 0.007 and +0.075 ± 0.02 (U/ml), respectively. The NSE showed significantly higher levels of POX, CAT and SOD in TP2 compared to the other groups. Furthermore, NSE and NSnE had higher levels of POX, CAT and SOD in TP1 and TP3 (p<0.05) compared with SE and SnE. Only in the NSnE, were no differences observed in CAT compared with SE and SnE in TP3. These results showed that the antioxidant level at rest and in the recovery time after the acute intense exercise was lower in SE and SnE compared with NSE and NSnE, suggesting that smoking habit may reduce the ameliorating effect of regular physical activity on acute exercise-induced oxidative stress.

The dilatometer curves of continuous cooling transformation of 12Mn steel were measured with Formastor-FⅡthermal mechanical simulator．The steel's undercooled austenite phase continuous cooling transformation curves ( CCT curves) were established by means of the dilatometer method and the metallographic-hardness measurement method． The effect of cooling rate on microstructure and hardness of the steel was studied． CCT curve of test steel was simulated by JMatPro. The results show that the Ac1 and Ac3 of the experimental steel are 692 ℃ and 855 ℃ ; the microstructure obtained is made of ferrite，pearlite and bainite．The ferrite transformation and pearlite transformation occur at a slower cooling rate，in which the ferrite is dominant. When the cooling rate is greater than 4.25 ℃ / s bainite transformation happens．As the cooling rate increases，microstructure or grains become finer．The hardness of the tested steel with increasing cooling rate shows a trend of first fast increase and soon decrease．The simulation results are consistent with the measured CCT law. The high temperature mechanical properties of 12mn steel round billet were tested by gleeble-1500d thermal / mechanical simulator. The tensile strength, reduction of area and stress-strain curves of the billet were obtained in the range of 600-1300 ℃.

Our understanding of pull-apart basins and their fault systems has been enhanced by analog experiments and simulations. However, there has been no opportunity to compare the faults that constitute pull-apart basins with surface ruptures during earthquakes. In this study, we investigated the effects of a 2018 earthquake (Mw 7.5) on a pull-apart basin in the Palu-Koro fault system, Sulawesi Island, Indonesia, using geomorphic observations in digital elevation models, optical correlation with pre- and post-earthquake satellite images. A comparison of active fault traces determined by geomorphology with the locations of surface ruptures from the 2018 earthquake shows that some of the boundary faults of the basin are inactive and that active faulting has shifted to basin-shortcut faults and relay ramps. We also report evidence of lateral spreading, in which alluvial fan materials moved around the end of the alluvial fan. These phenomena may provide insights for anticipating the location of future surface ruptures in pull-apart basins.

Building Information Modeling (BIM) has been one of the overwhelming trends in the worldwide. In Korea, from 2012, BIM application to the public construction projects worth more than $40 million was mandated. However, despite the policy, many public owners have hesitated to apply BIM to their projects. They generally view BIM very complex to manage and difficult to understand. While there have been diverse BIM guides as a reference, most of them have developed from BIM suppliers’ perspective involving certain deficiency in meeting the public owners’ taste. The public owners have addressed the necessity for developing an owner-oriented BIM guide on which they can understand the overall BIM procurement process thereby efficiently preparing their BIM service contracts. The main objective of this study is to develop the structure and contents guidance of the new guide to be developed that follows the public business process and mitigates the deficiency. To meet the research objective, a number of domestic and international BIM guides were analyzed and workshops were operated twice with the 12 BIM experts from the Korean construction industry. As a result of the study, a four-staged guide structure was developed consisting of the BIM service Scoping, Tendering, Executing, and Wrapping-up (STEW) guides.

Hydrogel-based wearable electrochemical biosensors (HWEBs) are emerging biomedical devices that have recently received immense interest. The exceptional properties of HWEBs include excellent biocompatibility with hydrophilic nature, high porosity, tailorable permeability, the capability of reliable and accurate detection of disease biomarkers, suitable device-human interface, facile adjustability, and stimuli-responsive to the nanofiller materials. Although the biomimetic three-dimensional hydrogels can immobilize bioreceptors, such as enzymes and aptamers, without any loss in their activities. However, most HWEBs suffer from low mechanical strength and electrical conductivity. Many studies have been performed on emerging electroactive nanofillers, including biomacromolecules, carbon-based materials, and inorganic and organic nanomaterials, to tackle these issues. Non-conductive hydrogels and even conductive hydrogels may be modified by nanofillers as well as redox species. All these modifications have led to the design and development of efficient nanocomposites as electrochemical biosensors. In this review, both conductive-based and non-conductive-based hydrogels derived from natural and synthetic polymers are systematically reviewed. The main synthesis methods and characterization techniques are addressed. The mechanical properties and electrochemical behavior of HWEBs are discussed in detail. Finally, the prospects and potential applications of HWEBs in biosensing, healthcare monitoring, and clinical diagnostics are highlighted.

Technology development changes society and society demands new and innovative technology development. We analyze technology to understand society and technology itself. Many researches have been introduced in various fields. Most of them were about patent analysis. This is because detailed and accurate results of research and development are patented. In this paper, we study on new patent analysis method based on count data model and Bayesian regression analysis. Using count data model, we analyze the technological keywords extracted from the collected patent documents. We use the posterior distribution of Bayesian statistics to reflect the experience and knowledge of the relevant technological experts in the analysis model. Moreover, we apply the proposed model to finding sustainable technologies. Finding and developing sustainable technologies is an important activity for companies and research institutes to maintain their technological competitiveness. To illustrate how our modeling could be applied to real domain, we carry out a case study using the patent documents related to artificial intelligence.

The electroencephalogram (EEG) is a record of brain activity. Brain Computer Interface (BCI) technology formed by the EEG signal has become one of the hotspots at present. How to extract the feature signal of EEG is the most basic research of BCI technology. In this paper, A new method of recognizing fatigue, conscious, concentrated state of human brain is proposed by the combination of discrete wavelet transform and the neural network based on EEG signal. First of all, the law signal is preprocessed by the wavelet denoising method because the law EEG signal contains a large number of high frequency noise, which is decomposed into multi-layer high frequency signal and low frequency signal. thus, δ wave, θ wave, α wave, β wave are obtained by the wavelet transform. And then, frequency band energy of the different wave is regards as the feature signal of EEG. In the experiment, the feature signal is classified by radial basic function (RBF) and annealed chaotic competitive learning network (ACCLN). RBF and ACCLN networks are trained with 500 sets of sample data and are tested by 100 sets of samples in different mental states. The experimental results show that the average accuracy of RBF network under three conditions are 88.75%, 88.25%, 88.5%, respectively, and the correct rate of ACCLN network is 97%, 98%, 98%, respectively.

Flammability was evaluated and the results showed the values of critical flux at extinguishment (CFE) as 49.5kW/㎡ on average, total heat release (Qt) as 0.21MJ on average, and peak heat release rate (Qp) as 0.66kW on average, which satisfied all of the thresholds presented by the IMO. Therefore, flame-retardant plywood, of which the flame-retardant performance was evaluated, was determined to be an applicable finishing material that satisfies fire safety standards.

With the rapid developments that have been made in computer vision and computer technology, semantic segmentation of high-resolution images has emerged as a mainstream and challenging task. The, segmentation of water areas remains a complex task due to the similar features between water areas or between water areas and other land objects. Meanwhile, since coastlines and riverbanks are typically presented in irregular shapes, it is difficult to obtain the categories of pixels at boundaries. This paper proposed the use of a Water-Land Boundary Attention Network (WLBANet) to improve the accuracy of pixels at boundaries between water and land. This network also reinforced the performance of contextual information extraction into distinguishing between water areas and other land objects. To prove the validity of this proposed network, WLBANet was performed on the Water Land Dataset (WLD), which is also by this paper, and which contains water areas and other land objects categories. The results demonstrates that the proposed method has significant effectiveness.

This study analyzes the influence of CEO types on corporate governance, focusing on de facto (substantial) CEOs. We examine how substantial CEOs impact ESG activities (Hypothesis 1) and corporate value (Hypothesis 2). Data were collected from KIS-VALUE and DART (Electronic Disclosure System) of the Financial Supervisory Service, defining substantial CEOs as highest remuneration recipients exceeding the representative director of the company pay. Results sup-port Hypothesis 1, showing companies with substantial CEOs are more engaged in ESG activities, potentially to improve public image while concealing self-serving behaviors. Hypothesis 2 is validated, indicating lower corporate value in companies with substantial CEOs due to prioritizing personal interests over long-term profit maximization. Despite limitations in exploring governance relationships beyond remuneration data, the study offers key contributions. It expands research on corporate governance and ESG activities by identifying substantial CEOs through objective remuneration data. It highlights the importance of an independent board for transparent governance and positive corporate value. Lastly, empirical evidence shows the negative impact of misdirected ESG activities on corporate value. By using remuneration as an indicator, this study illuminates substantial CEOs' influence on corporate value and ESG activities, providing insights for future research in corporate governance and ESG.

Synthesis of natural products with complicated architecture often requires segments having the functional groups that can be structurally transformed with the desired stereogenic centers. Bicyclic ?-lactones have a great potential for a suitable segment for natural product synthesis. However, the stereoselective construction of such functionalized bicyclic ?-lactones is not as straightforward as one might expect. On the other hand, the Lewis acid template-mediated Diels-Alder reaction is one of the most powerful and versatile methods for providing bicyclic ?-lactones with high regioselectivity and stereoselectivity. In this reaction, the Lewis acid template activates the dienophile as well as linking the diene and dienophile by a temporary tether. Therefore, Diels-Alder reaction smoothly proceeds in a stereocontrolled manner, allowing a simple access to bicyclic ?-lactone as a valuable building block for the synthesis of complicated natural products. In this review, some highlights of the Lewis acid-mediated Diels-Alder reaction, along with its application to the synthesis of biologically active compounds are discussed.

Background and Objectives: Cancer as the second leading cause of death in the United States poses a huge healthcare burden. Barriers to access to advanced therapies influence the outcome of cancer treatment. In this study, we examined whether insurance types affect the quality of cancer clinical care regarding access to an important monoclonal antibody, ramucirumab. Materials and Methods: Data for 13,340 cancer patients with Purchased or Medicaid insurance from the All of Us Database were collected for this study. The Chi-square test of proportions was employed to determine the significance of patient cohort characteristics and ramucirumab usage between Purchased and Medicaid insurance groups. The independent t-test was utilized to assess the influences of other determinants on insurance types. Results: Cancer patients who are African American, with lower socioeconomic status, or with lower educational attainment are more likely to be insured by Medicaid. Analysis of survey questions demonstrated the relationship between income and education level with insurance type as Medicaid cancer patients were less likely to receive primary care and specialist physician access and more likely to request lower cost medications. In addition, those with Medicaid insurance were identified to have poorer access to expensive therapeutics like ramucirumab compared to those with Purchased insurance.  Conclusions: The inequities of the US healthcare system are observed for cancer patient care; access to physicians and therapeutics are highly varied and dependent on insurance types. Socioeconomic status determines insurance type, which unfortunately generates a significant impact on cancer treatment and disease outcome.

The low relative humidity (RH) levels in a greenhouse during the daytime in a strawberry (Fragaria × ananassa Duch) cultivation period negatively affect the growth of strawberry related to photo-physiology. Therefore, this study was conducted to confirm an efficient RH management method by analyzing the phenotypic characteristics related to photo-physiology by controlling the RH in a greenhouse during the daytime with a fog system. Strawberry plants were grown respectively in a greenhouse affected by natural RH changes (control) and in a greenhouse with 40% ~ 50% RH adjusted during the daytime using a fog system. In the greenhouse, with controlled RH, the temperature decreased, and the RH was higher in the initial growth stage of strawberry planting than the control. It was observed a significant increase in the survival rate of the strawberry plant, as well as the incidence of powdery mildew, was lowered. In addition, the photosynthetic rate and OJIP chlorophyll a fluorescence transients related to photosystem II efficiency of strawberry leaves were significantly higher in the fog treatment than in the control. In winter, during the day, the number of days on which the temperature dropped below 20℃ has increased, the greenhouse temperature with controlled RH was lower due to the fog system. When the yield per strawberry plant in January and February was investigated, the control was higher than the RH treatment. Therefore, RH management using a fog system must be controlled at a level where a temperature range is adequate for plant growth, in which the efficient control of these parameters increases strawberry productivity.

In history, theta function identities have been studied extensively and deeply. In this paper, applying the residue theorem of an elliptic function, we obtain a parameterized theta function identity. Then, by selecting the appropriate parameter, we derive some famous Jacobi identities, as well as other relatively simple theta function identities.

The present paper deals with a class of even entire functions of order $\rho =1$ and genus $\vartheta =0$ of the polynomials form, \[ \sum\limits_{m=0}^\infty {\frac{\left( {-1} \right)^m\Phi ^{\left( {2m} \right)}\left( 0 \right)}{\Gamma \left( {2m+1} \right)}x^{2m}} =\Phi \left( 0 \right)\prod\limits_{k=1}^\infty {\left( {1-\frac{x}{\ell _k }} \right)} , \] where $\Phi\left( 0 \right)\ne 0$, real numbers $x$, nonnegative integers $m$, and $\ell _k \ne 0$ are all of the nonzero roots with $\sum\limits_{k=1}^\infty {1/\left| {\ell _k } \right|} <\infty $ and natural numbers $k$. We provide an efficient criterion for the polynomials with only real zeros. We also prove that the conjecture of Jensen is our special case.

In this paper we address some variants for the products of Hadamard and Patterson. We prove that all zeros of the Riemann $\Xi$--function are real. We also prove that the Riemann hypothesis is true. The equivalence theorems associated with the Riemann zeta--function are obtained in detail.

In this article we propose the integral, series and product representations for the Ramanujan zeta-function. We suggest a variant for the Conrey-Ghosh product for the entire Ramanujan zeta-function. We present some variants for the product for the Ramanujan $\Xi$-function. We prove that all of its zeros are real. Along the way we obtain the truth of the Riemann-Hardy conjecture.

This paper addresses a variant of the product for the Dirichlet $L$--functions. We propose a completely detailed proof for the truth of the generalized Riemann conjecture for the Dirichlet $L$--functions, which states that the real part of the nontrivial zeros is $1/2$. The Wang and Hardy--Littlewood theorems are also discussed with removing the need for it. The results are applicable to show the truth of the Goldbach's conjecture.

It is due to Littlewood that the truth of the Riemann theorem implies that of the Lindel\"{o}f conjecture. This paper aims to use the idea of Littlewood to prove the Lindel\"{o}f conjecture for the Riemann zeta function. The Lindel\"{o}f $\mu $ function at the critical line is zero, with use of the Riemann theorem for the entire Riemann zeta function, proved based on the work of Heath-Brown. Our result is given to show that the Lindel\"{o}f conjecture, connected with the proof of the moment conjecture, is true.

This paper presents a wideband dual-polarized dipole antenna structure operating at 1.7-3.8 GHz (76.4%). For a traditional 4G dipole antenna which covers the band 1.71 GHz- 2.69 GHz, it’s difficult to maintain the satisfactory impedance matching and normal stable radiation patterns within the 5G sub-6 GHz band 3.3-3.8 GHz, which mainly due to the fixed antenna height is no longer a quarter-wavelength. To solve this, a connected-ring-shaped metasurface structure is proposed and deployed to operate as an artificial magnetic conductor (AMC). As a result, stable antenna radiation patterns are obtained within the whole band 1.7-3.8 GHz. For verification, this wideband dipole antenna using AMC is implemented and tested. The measured results show that the proposed antenna has an impedance bandwidth of 80.7% (1.7-4.0 GHz). It has an average measured in-band realized gain of 7.0±1.0 dBi and a stable 70∘±5∘ half power beam width (HPBW) within the 4G/5G-sub 6GHz bands 1710-2690 MHz and 3300-3800 MHz.

The impact of the agriculture net carbon effect is crucial for climate change mitigation, yet research on this topic in China is currently insufficient. In this study, the carbon balance ratio (CBR) is used to characterise the net carbon effect of agriculture, and the spatial Durbin model and threshold regression model were used to empirically analyse the CBR with a sample of 30 provincial-level regions in China from 2004 to 2019. The aim was to investigate the mechanism of the influence of the land management scale (SCALE) of farming on the CBR. The results of the study indicate that national farming generally has a net sink effect, with large changes in interannual fluctuations; the expansion of SCALE has an obvious role in increasing sinks and reducing emissions, and has a positive spatial spillover effect on CBR, with significant spatial heterogeneity. Furthermore, as the SCALE expands, the direction of the influence of rural residents’ income and education level on CBR changes in the opposite direction, showing a significant non-linear relationship characteristic. However, in most areas, the SCALE threshold has not yet been reached, suggesting that the improvement in education levels can still offset the negative impact of economic income growth in the short term. The study recommends paying attention to the role of farmers’ human capital, changing production methods, and implementing carbon peaking and carbon neutrality goals to enhance the net sink effect of the farming industry, which would be achieved by increasing land management scale.

In order to overcome the limitation of the traditional adaptive Unscented Kalman Filtering (UKF) algorithm in noise covariance estimation for statement and measurement, we propose a hybrid adaptive UKF algorithm based on combining Maximum a posteriori (MAP) criterion and Maximum likelihood (ML) criterion, in this paper. First, to prevent the actual noise covariance deviating from the true value which can lead to the state estimation error and arouse the filtering divergence, a real-time covariance matrices estimation algorithm based on hybrid MAP and ML is proposed for obtaining the statement and measurement noises covariance, respectively; and then, a balance equation the two kinds of covariance matrix is structured in this proposed to minimize the statement estimation error. Compared with the UFK based MAP and based ML, the proposed algorithm provides better convergence and stability.

Complex modeling has received significant attention in recent years and is increasingly used to explain the statistical phenomenon with increasing and decreasing fluctuations such as the similarity or difference of spike protein charge patterns of coronaviruses. Different from the existing covariance or correlation coefficient methods in traditional integer dimension construction, this study proposes a simplified novel fractional dimension derivation with the exact Excel tool algorithm. It involves the fractional center moment extension to covariance, which ends up a complex covariance coefficient that is better than the Pearson correlation coefficient, in the sense that the nonlinearity relationship can be further depicted. The spike protein sequences of coronaviruses were obtained from the GenBank and GISAID database, including the coronaviruses from pangolin, bat, canine, swine (three variants), feline, tiger, SARS-CoV-1, MERS, and SARS-CoV-2 (including the strains of Wuhan, Beijing, New York, German, and UK variant B.1.1.7) were used as the representative examples in this study. By examining the values above and below the average/mean based on the positive and negative charge patterns of the amino acid residues of the spike proteins from coronaviruses, the proposed algorithm provides deep insights into the nonlinear evolving trends of spike proteins for understanding the viral evolution and identifying the protein characteristics associated with viral fatality. The calculation results demonstrate that the complex covariance coefficient analyzed by this algorithm is capable of distinguishing the subtle nonlinear differences in the spike protein charge patterns with reference to Wuhan strain SARS-CoV-2 for which the Pearson correlation coefficient may overlook. Our analysis reveals the unique convergent (positive correlative) to divergent (negative correlative) domain center positions of each virus. The convergent or conserved region may be critical to the viral stability or viability; while the divergent region is highly variable between coronaviruses suggesting high frequency of mutations in this region. The analyses show that the conserved center region of SARS-CoV-1 spike protein is located at amino acid residues 900, but shifted to the amino acid residues 700 in MERS spike protein, and then to amino acid residues 600 in SARS-COV-2 spike protein, indicating the evolvement of the coronaviruses. Interestingly, the conserved center region of the spike protein in SARS-COV-2 variant B.1.1.7 shifted back to amino acid residues 700, suggesting this variant is more virulent than the original SARS-COV-2 strain. Another important characteristic our study reveals is that the distance between the divergent mean and the maximal divergent point in each of the viruses (MERS>SARS-CoV-1>SARS-CoV-2) is proportional to viral fatality rate. This algorithm may help to understand and analyze the evolving trends and critical characteristics of SARS-COV-2 variants, other coronaviral proteins and viruses.

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

Aborycin is a type I lasso peptide with a stable interlocked structure, offering a favorable framework for drug development. The aborycin biosynthetic gene cluster gul from marine sponge-associated Streptomyces sp. HNS054 was cloned and integrated into the chromosome of S. coelicolor hosts with different copies. The 3-copy gul-integration strains S. coelicolor M1346::3gul showed better production than one-copy or 2-copy gul-integration strains, and the total titer reached approximately 10.4 mg/L, i.e., 2.1 times that of the native strain. Then, five regulatory genes, phoU (SCO4228), wblA (SCO3579), SCO1712, orrA (SCO3008) and gntR (SCO1678), which were reported to have negative effects on secondary metabolism, were further knocked out from the M1346::3gul genome by CRISPR/Cas9 technology. While the ΔSCO1712 mutant showed a significant decrease (4.6 mg/L) and the ΔphoU mutant showed no significant improvement (12.1 mg/L) in aborycin production, the ΔwblA, ΔorrA and ΔgntR mutations significantly improved the aborycin titers to approximately 23.6 mg/L, 56.3 mg/L and 48.2 mg/L, respectively, which were among the highest heterologous yields for lasso peptides in both Escherichia coli systems and Streptomyces systems. Thus, this study provided important clues for future studies on enhancing antibiotic production in Streptomyces systems.

Acoustic emission (AE) is caused by the sudden release of energy by a material as a result of material degradation related to deformation, crack, or fault within a solid. The same situation also occurs in leaks caused by turbulence in the fluid around the leak. In this study, analytical modeling for AE due to leakage through a circular pinhole in a gas storage cylinder was performed. The displacement fields responsible for AE, excited by the concentrated force (CF) associated with the turbulent flow though the pinhole, were derived by solving the Navier-Lamé equation. The CF as an excitation source was formulated in terms of a fluctuating Reynolds stress (FRS) and spatial Green’s function. In particular, a series of experiments were conducted under different operating conditions to explore the characteristics of the AE signals due to leak in a gas cylinder. Finally, the simulation and experimental results were compared to verify the accuracy of the simulation results.

: Cnidium officinale Makino, a perennial crop in the Umbeliperae family, is harvested in the summer for medicinal purposes. The average temperature in Korea has recently increased, and consequently, the area used to cultivate C. officinale has been reduced, and plant disease and soil sickness have increased. In this study, rhizosphere bacteria were isolated from C. officinale, and their antagonistic activity evaluated against Fusarium solani, which is a major issue during repeated cultivation. Twenty-eight strains were isolated from the root and rhizosphere soil, of which seven showed antagonistic activity against F. solani and were further investigated. An in planta test found that the dead rate of shoots was significantly lower in the group inoculated with PT1 isolated from the root tissue and that the fresh and dry weights were also higher, when compared with the other groups. PT1 was thus considered to have antagonistic activity against F. solani. The 16S rRNA analysis identified the PT1 as Leclercia adecarboxylata, and downstream studies confirmed the production of enzymes related to antagonism, such as siderophore and N-acetyl-β-glucosaminidase. The phosphorous solubilizing ability and secretion of related enzymes were also confirmed. The results indicate that PT1 could be utilized as a PGPR to help control fusarium wilt.

Polyglycolic acid (PGA) is a promising polymer in the packaging field owing to excellent hydrolysis, heat resistance and gas barrier properties, but there are limited in application due to poor toughness. For this reason, a covalently bonded chain extender is introduced to increase compatibility with flexible polymers. However, covalent bonds are unfavorable for application to degradable plastics because of require a lot of energy for reverse reactions. Therefore, it is intended to effectively control the ductility of blending plastics by using a novel ionic chain extender having a relatively weaker non-covalent bond than the existing covalent bond. Polycaprolactone (PCL), which has biodegradability and flexibility, was selected as a blending polymer. For comparison, a covalently reactive chain extender (G-CE) and a non-covalently ionic chain extender (D-CE) were synthesized and compounded to blending plastics. Each chain extenders were improved the compatibility between PGA and PCL, and the ductility of the PGA/PCL blending plastics were greatly enhanced with non-covalently bonding D-CE than with covalently bonding G-CE. At this time, the ductility of PGA/PCL blending plastic without CE is 7.2%, the ductility of 10D with D-CE is 26.6%, and the ductility of 10G with G-CE is 18.45%. Therefore, it was confirmed that the novel ionic chain extender inducing non-covalent bonds improves the compatibility between PGA and PCL and is more advantageous in enhancing ductility through a reversible reaction.

In this study, the coating order of two monomers in the shell polymerization process of core–shell nanoparticles was altered to facilitate easy coating and optimize the properties of the coated surface to simplify the additional coating formulation process. To obtain a glass transition temperature suitable for coating, a core was synthesized by the copolymerization of an acryl monomer. A perfluoro monomer and silane monomer were additionally added to synthesize nanoparticles exhibiting both water–oil repellency and anchoring properties. In order to realize various surface properties, the nanoparticles underwent surface modification and cellulose fiber was introduced. Through the various data described in this text, the surface properties improved with the order of introduction of the two monomers.

Electrochemical Impedance Spectroscopy (EIS) is a powerful non-invasive technique used to characterize Lithium-ion cells. Its application allows to identify and track the evolutions of cell degradation processes within a short testing time. This review collects all the available works which have used EIS spectra either to characterize Li-ion cell degradation or to develop Electric Circuit Models (ECMs). The objectives of this work are: (i) to highlight the influence of different aging test conditions on the EIS spectra; (ii) to find the correlations between EIS spectra variations and the underlying degradation mechanisms and (iii) to list the available options to formulate ECMs from EIS spectra of aged cells. After an exhaustive analysis of the state-of-the-art, a critical review is presented to discuss the existing links between degradation mechanisms and the most reliable solutions to model them.

This research analyzed the impact of quality of service as perceived by Hapkido students on their exercise continuation and recommendation intentions. It also identified the measures to reduce the rate of student dropout, strengthen competitiveness, and create more efficient marketing strategies for consumer patterns that are rapidly diversifying Hapkido. A questionnaire survey method was conducted with 300 middle and high school students aged 14–19 years having Hapkido training of three months to two years in Incheon and Bucheon during March–April 2019. Frequency, factor, reliability, correlation, and standard multiple regression analyses were conducted on the surveyed data. The conclusions are as follows. First, considering the impact of service quality on exercise continuation intention, service quality positively affects reliability, personification, and perceptual openness; in terms of possibility, it positively affects typicality, personification, and perceptual openness; and in terms of reinforcement, it positively affects reliability and perceptual openness. Second, examining the impact of service quality on recommendation intention positively affects reliability, personification, and perceptual openness. Third, exercise continuation intention positively affects recommendation intention.

The traffic light detection and recognition are crucial for enhancing the security of unmanned systems. This study proposes a YOLOv5-based traffic light detection algorithm to tackle the challenges posed by small targets and complex urban backgrounds. Initially, the mosaic-9 method is employed to enhance the training dataset, thereby boosting the network’s ability to generalize and adapt to real-world scenarios. Furthermore, the network incorporates the Squeezed-and-Excitation (SE) attention mechanism to improve. Moreover, the YOLOv5 algorithm’s loss function has been optimized by substituting it with EIoU_loss, which addresses issues like missed detection and false alarms. Experimental results demonstrate that the model , trained with this enhanced network, achieves a 99.4% mAP on a custom dataset, which is 6.3% higher than the original YOLOv5, while maintaining a detection speed of 74 f/s. Therefore, this algorithm offers higher detection accuracy and effectively meets real-time operational requirements.

Determining accurate PM2.5 pollution concentrations and understanding their dynamic patterns is crucial for scientifically informed air pollution control strategies. Traditional reliance on linear correlation coefficients for ascertaining PM2.5 related factors only uncovers superficial relationships. Moreover, the invariance of conventional prediction models restricts their accuracy. To enhance the precision of PM2.5 concentration prediction, this study introduces a novel integrated model that leverages feature selection and a clustering algorithm. Comprising three components - feature selection, clustering, and integrated prediction, the model first employs the non-dominated sorting Genetic Algorithm (NSGA-III) to identify the most impactful features affecting PM2.5 concentration within air pollutants and meteorological factors. This step offers more valuable feature data for subsequent modules. The model then adopts a two-layer clustering method (SOM+K-means) to analyze the multifaceted irregularity within the dataset. Finally, the model establishes the Extreme Learning Machine (ELM) weak learner for each classification, integrating multiple weak learners using the Adaboost algorithm to obtain a comprehensive prediction model. Through feature correlation enhancement, data irregularity exploration, and model adaptability improvement, the proposed model significantly enhances the overall prediction performance. Data sourced from 12 Beijing-based monitoring sites in 2016 were utilized for an empirical study, and the model's results compared with five other predictive models. The outcomes demonstrate that the proposed model significantly heightens prediction accuracy, offering useful insights and potential for broadened application to multifactor correlation concentration prediction methodologies for other pollutants.

In this study, UAV (Unmanned Aerial Vehicle) photogrammetry was used to monitor the ground displacement on the slope below a coal waste-rock stockyard, and to investigate the role of rainfall on this displacement. The study area is a mountainous region in Korea, where coal mining continues, and coal waste-rock is stored on the slopes of the mountain. In this area, ma-terial removal work was undertaken to reduce the steepness of the slope and driving forces in order to prevent disasters, but the strategy requires continuous monitoring to confirm the stabilization of the slope. For slope monitoring, a total of six UAV photogrammetry campaigns were conducted between April 2019 and August 2020. As a result of data processing, an orthoimage and DSM (Digital Surface Model) were generated. The ground displacement was estimated through four ways: slope extraction, displacement area evaluation, horizontal displacement, and vertical displacement analysis. During the study period, the maximum vertical displacement was 3.3 m and the maxi-mum horizontal displacement was 3.5 m. The horizontal displacement was effectively evaluated through the measurement of the movement of the drainage system using orthoimages that captured with a periodic survey. The effects of rainfall on ground displacement were also investigated. A very clear linear relationship between rainfall intensity higher than 20mm/d and ground displacement was identified. Accumulated amount of rainfall also showed good correlation with slope movement, but the frequency of rainfall intensity below 20 mm/d showed relatively low correlation with ground dis-placements.