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

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

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

To mitigate pyrethroid resistance in mosquito vectors of emerging and re-emerging human pathogens, there is an urgent need to discover insecticides with novel modes of action. Natural alternatives, such as extracts derived from plants, may serve as substitutes for traditional synthetic insecticides if they prove to be sustainable, cost-effective, and safe for non-target organisms. Hemp (Cannabis sativa) is a sustainable plant known to produce various secondary metabolites with insecticidal properties, including terpenoids and flavonoids. The goal of this study was to assess the larvicidal activity of hemp leaf extract on 1st instar mosquito larvae from both pyrethroid-susceptible (PS) and pyrethroid-resistant (PR) strains of Aedes aegypti Another goal was to identify which components of the extracts were responsible for any observed larvicidal activity. We found that methanol extract of hemp leaves induced similar concentration-dependent larvicidal activity against PS (LC50: 4.4 ppm) and PR (LC50: 4.3 ppm) strains within 48 hours. Partitioning of the dried leaf extract between methanol and revealed that full larvicidal activity was restricted to the methanol fraction. Analysis of this fraction by gas chromatography-mass spectrometry and nuclear magnetic resonance showed it to be dominated by cannabidiol (CBD). Larvicidal assays using authentic CBD confirmed this compound was primarily responsible for the toxicity of hemp leaf extract against both strains. We conclude that hemp leaf extracts and CBD have the potential to serve as viable sources for the development of novel mosquito larvicides.

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

Drug resistance in melanoma is a major hindrance in cancer therapy. Growth hormone (GH) plays a pivotal role in contributing to resistance to chemotherapy. Knocking down or blocking the GH receptor has been shown to sensitize the tumor cells to chemotherapy. Extensive studies have demonstrated that exosomes, a subset of extracellular vesicles, play an important role in drug resistance by transferring key factors to sensitize cancer cells to chemotherapy. In this study, we explore how GH modulates exosomal cargoes from melanoma cells and their role in drug resistance. We treated the melanoma cells with GH, doxorubicin, and GHR antagonist, pegvisomant, and analyzed the exosomes released. Additionally, we administered these exosomes to recipient cells. The GH-treated melanoma cells released exosomes with elevated levels of ABC transporters (ABCC1 and ABCB1), N-cadherin and MMP2, enhancing drug resistance and migration in recipient cells. GHR antagonism reduced these exosomal levels, restoring drug sensitivity and attenuating migration. Overall, our findings highlight a novel role of GH in modulating exosomal cargoes that drive chemoresistance and metastasis in melanoma. This understanding provides insights to the mechanisms of GH in melanoma chemoresistance and suggests GHR antagonism as a potential therapy to overcome chemoresistance in melanoma treatment.

Zinc cobalt oxide-zinc hydroxide (ZnCo2O4-Zn(OH)2) microspheres were successfully fabricated on carbon cloth via a sample hydrothermal method. The surface morphology of these microspheres and their efficacy in degrading methyl violet were further modulated by varying the thermal annealing temperatures. The manipulation of thermal annealing temperatures was pivotal in adjusting the porosity of ZnCo2O4-Zn(OH)2 microspheres to amplify their photocatalytic performance. Various analytical techniques were utilized to evaluate the physical and chemical properties of the ZnCo2O4-Zn(OH)2 microspheres, including field-emission scanning electron microscopy, energy-dispersive spectroscopy, X-ray diffraction, field-emission transmission electron microscopy, X-ray photoelectron spectroscopy, and UV-vis spectroscopy. Compared to untreated ZnCo2O4-Zn(OH)2 microspheres, those subjected to thermal annealing exhibited increased specific surface area and light absorption capacity, rendering them highly effective photocatalysts under UVC light exposure. Subsequent studies have confirmed the superior performance of ZnCo2O4-Zn(OH)2 microspheres as a reusable photocatalyst for degrading methyl violet and tetracycline. Additionally, trapping experiments during the photodegradation process involving ZnCo2O4-Zn(OH)2 microspheres have identified hydroxyl radicals (·OH) and superoxide radicals (·O2–) as the primary reactive species.

In Cameroon, Aedes mosquitoes transmit various arboviruses, posing significant health risks. We aimed to characterize the Aedes virome in southwestern Cameroon and identify potential core viruses which might be associated with vector competence. A total of 398 Aedes mosquitoes were collected from four locations (Bafoussam, Buea, Edea and Yaounde). Aedes albopictus dominated all sites except for Bafoussam where Aedes africanus prevailed. Metagenomic analyses of mosquitoes grouped per species into 54 pools revealed notable differences in eukaryotic viromes between Ae. africanus and Ae. albopictus, with the former exhibiting greater richness and diversity. Thirty-seven eukaryotic virus species from 16 families were identified, including six novel viruses with near complete genome sequences. Seven viruses were further quantified in individual mosquitoes via qRT-PCR. Although none of them could be identified as core viruses, Guangzhou sobemo-like virus and Bafoussam mosquito solemovirus virus were highly prevalent regionally in Ae. albopictus and Ae. africanus, respectively. This study highlights the diverse eukaryotic virome of Aedes species in southwestern Cameroon. Despite their shared Genus, Aedes species exhibit limited viral sharing, with varying viral abundance and prevalence across locations. Ae. africanus, an understudied vector, harbors a rich and diverse virome, suggesting potential implications for arbovirus vector competence.

The NCO functional group of 3-isocyanatoproply triethoxysilane (IPTS) and the OH functional group of DOPO-BQ were used to conduct an addition reaction. Following completion of the reaction, triglycidyl isocyanurate (TGIC) was introduced to conduct a ring-opening reaction. Subsequently, a sol-gel method was used to take place a hydrolysis- condensation reaction on TGIC-IPTS-DOPO-BQ to form a hyperbranched nitrogen–phosphorous–silicon (HBNPSi) flame retardant. This flame retardant was incorporated into a polyurethane (PU) matrix to prepare a hybrid material. Fourier-transform infrared spectroscopy (FT-IR), thermogravimetric analysis (TGA), limiting oxygen index (LOI), UV-VIS spectrophotometry, and Raman analysis were conducted to structure characterization and analyzed transparency, thermal stability, flame retardancy, and residual char to understand the flame retardant mechanism of prepared hybrid materials. After the flame retardant was added, the maximum degradation rate decreased from −36 wt%/min to −17 wt%/min, the integral procedure decomposition temperature (IPDT) increased from 348 ℃ to 488 ℃, and the char yield increased from 0.7 to 8.1 wt%. The aforementioned results verified that thermal stability of PU can be improved after adding HBNPSi. The LOI analysis indicated that the pristine PU was flammable because the LOI of pristine PU was only 19. When the content of added HBNPSi was 40%, the LOI value was 26; thus the PU hybrid became nonflammable.

Delivering effective messages is critical to creating a more sustainable and resilient culture. The explosion of social media has enhanced information access but has often reinforced and polar-ized pre-existing viewpoints and norms. In contrast, digital signs are an “in your face in your space” technology that has the potential to deliver common content to a diverse local audience. Environmental Dashboard (ED) is a communications platform and set of content applications that combines information on current environmental conditions, real-time resource consumption, positive actions being taken by community members, and a community calendar. We conducted a longitudinal study to assess whether ED content delivered via digital signs in public locations would result in desirable psychological changes within a community. Participants completed surveys in six designated signage locations prior to installation (N = 174) and following two years of continuous exposure (N = 133). We observed: increases in pro-environmental social norms among people of color (a demographic emphasized); enhanced awareness of and sense of connection with the local community and ecology; increased self-reported electricity conservation; and increased perception of youth engagement (another demographic emphasized). Changes were mediated by exposure to digital signage. These findings support the hypothesis that content delivered through digital signs can strengthen pro-environmental and pro-social culture within communities.

3D printing is a non-traditional additive manufacturing process. It is different from the traditional subtractive manufacturing process. It offers exceptional rapid prototyping capabilities and results that traditional subtractive manufacturing methods cannot attain, especially in applications involving curved or intricately shaped components. Despite its advantages, metal 3D printing will face porosity, warpage, and surface roughness issues. These issues will affect the future practical application of the parts indirectly, for example, the structural strength and the parts assembly ca-pability. Therefore, this study compares the qualities of the warpage, weight, and surface rough-ness after milling and grinding processes under the same materials (316L stainless steel) between general rolled steel and 3D additive steel. Experimental results show that 3D printing parts are approximately 13% to 14% lighter than the general rolled steel. The surface roughness performance of 3D printing steel is better than general rolled steel under the same material after milling or grinding processing. The hardness of the 3D printing steel is better than that of the gen-eral rolled steel. The research verifies that 3D additive manufacturing can use surface processing to optimize surface performance and achieve the functions of lightness and hardness.

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

Environmental estrogen pollution and estrogen effects on the female reproduction system are well-recognized scientifically. Among the estrogens, 17 β-estradiol is a priority in environmental estrogen pollution, and it is also a major contributor to estrogen which regulates the female reproduction system. 17 β-estradiol is carcinogen and has a tumor promotion effect relating to breast cancer, lung cancer and others. It also affects the psychological well-being such as depression, fatigue and others. Thus, a simple method of detection of 17 β-estradiol will be important for both environmental estrogen pollution and women’s health care. This study demonstrates a simple-use, cost effective 17 β-estradiol biosensor system which can be used for both environment and women’s health care applications. The bio-recognition mechanism is based on the influence of the redox couple, K₃Fe (CN) ₆/K₄Fe (CN) ₆ by the interaction between 17 β-estradiol antigen and its α-receptor (ER- α; α-estrogen antibody). The transduction mechanism is an electrochemical analytical technique, differential pulse voltammetry (DPV). The levels of 17 β-estradiol antigen studied was between 2.25 pg/mL to 2,250 pg/mL, Phosphate buffered saline (PBS), tap water from the Cleveland regional water district, and simulate urine were used as the test media covering the potential application areas for 17 β-estradiol detection. An interference study by testosterone which has a similar chemical structure and molecular weight as those of 17 β-estradiol was carried out, and this 17 β-estradiol biosensor showed excellent specificity without any interference by similar chemicals.

In individuals with spinal cord injury (SCI), rapid skeletal muscle atrophy and metabolic dysfunction pose profound rehabilitation challenges, often resulting in substantial loss of muscle mass and function. This study evaluates the effect of combined neuromuscular electrical stimulation (Comb-NMES) on skeletal muscle cross-sectional area (CSA) and inflammatory signaling within the acute phase of SCI. We applied a novel Comb-NMES regimen, integrating both high-frequency resistance and low-frequency aerobic protocols on the vastus lateralis muscle, to participants early post-SCI. Muscle biopsies were analyzed for CSA and inflammatory markers pre-and post-intervention. The results revealed a preservation of muscle CSA in the Comb-NMES group compared to a control group receiving transcutaneous electrical nerve stimulation and passive movements. Inflammatory signaling proteins such as TLR4 and Atrogin-1 were downregulated, whereas markers associated with muscle repair and growth were modulated beneficially in the Comb-NMES group. The study's findings suggest that early application of Comb-NMES post-SCI can attenuate inflammatory pathways linked to muscle atrophy and potentially promote muscle repair, advocating for its inclusion in early rehabilitation efforts. However, the small sample size and variability in injury characteristics emphasize the need for further research to corroborate these results across a more diverse and extensive SCI population.

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

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

In fuzzy decision problems, the ordering of fuzzy numbers is the basic problem. Among which, the fuzzy preference relation is the reasonable one to represent preference relation by a fuzzy membership function. This paper studies the Nakamura’s and Kołodziejczyk’s preference relations. Eight cases of representing different level of overlapping between two triangular fuzzy numbers are considered. We analyze the ranking behaviors of all possible combinations of decomposition and intersection of two fuzzy numbers for the Nakamura’s and Kołodziejczyk’s preference relations of these test cases. The results indicate that the decomposition and intersection can affect the fuzzy preference relations, thereby the final total order relation of fuzzy numbers.

Smart farm is a technology that greatly helps improve the productivity and quality of crops and is being actively introduced into indoor environments such as green houses. However, it has not yet been distributed to field-grown crops. The main reason is that, unlike indoor environments, it is very difficult to collect sensor data for monitoring the growth environment of crops in open fields where weather conditions change significantly and power supply is difficult. Additionally, because various sensors are used, the data formats of the devices are different, making it difficult to process. This paper presents a field crop growth environment monitoring and big data analysis system. The proposed system first solves power supply and data communication problems using solar power generation and LPWA technology. Additionally, based on the oneM2M architecture, data from various sensors is transmitted to the server using standardized technology. The transmitted data is stored and managed on the server as big data, and can be used to predict the production and quality of field-grown crops and take appropriate measures. The proposed system is expected to create an environment optimized for the growth of field crops and help prevent and manage diseases.

In manufacturing chatter is an unwanted phenomenon that can lead to product quality reduction and tool wear. Real time chatter detection is key to preventing these issues and improving overall machining efficiency. In this paper we propose an unsupervised chatter detection method using autoencoders (AE) and Density-Based Spatial Clustering of Applications with Noise (DBSCAN) clustering algorithm that uses internal signals of Computer Numerical Control (CNC) machines. The proposed method starts by using an AE to extract features from raw internal signals collected from CNC machines. This step reduces the dimensionality of the data and captures the underlying patterns of chatter. Then the extracted features are fed into DBSCAN clustering algorithm which is a density based algorithm that groups similar data points and identifies outliers. We tested the proposed method with real world data collected from various CNC machines. The results show that our unsupervised chatter detection method has high accuracy, precision and recall, can detect chatter and distinguish it from normal machining. Also the method is robust to noise and can adapt to dynamic machining conditions. In summary our work presents an unsupervised chatter detection method using AE and DBSCAN clustering that uses internal signals of CNC machines. This method is a reliable and efficient solution for real time chatter detection so manufacturers can improve product quality, optimize machining process and reduce tool wear during machining.

We investigate the structural correlation of non-covalent crown ether/H+/L-tryptophan (CR/TrpH+) host-guest complexes in the solution phase with those in the gas phase generated through electrospray ionization/mass spectrometry (ESI/MS) techniques. We perform quantum chemical calculations to determine their structures, relative Gibbs free energies, and infrared spectra. We compare the calculated infrared (IR) spectra with the IR multiphoton dissociation (IRMPD) spectra observed for the 18-Crown-6/TrpH+ complex by Polfer and co-workers [J. Phys. Chem. A 2013, 117, 1181−1188] for assigning the IR bands. We observe that the carboxyl group remains ‘naked’, lacking hydrogen bonding with the CR unit in the gas phase, and that this most stable conformer originates from the corresponding lowest Gibbs free energy structure in solution. Based on these findings, we propose that gas phase host-guest complexes directly correlate with those in solution, reinforcing the possibility of obtaining invaluable information about host-guest-solvent interactions in solution from the structure of the host-guest pair in the gas phase.

Nanofiber (NF) products exhibit outstanding performances in the materials science, textile, and medical fields, which cannot be realized using conventional technologies. However, the safety of such products is debated because of the potential risk of nanomaterials and lack of standardized guidelines for safely evaluating NF products. The global safety evaluations of nanomaterials focused on evaluating the cytotoxicity of zero-dimensional materials including nanoparticles and nanotubes based on OECD criteria. The NFs are one-dimensional materials with nanometer diameters and considerable lengths. Many fibers are applied in a densely woven web-like form, and therefore, assessing cellular penetration and fiber toxicity using the same methods is inappropriate. This study verifies the safety of polyurethane (PU) and polyvinylidene fluoride (PVDF) polymers, which are currently applied in filters and masks. To this end, polymer NFs were collected from each product, and the NFs were compared with reference samples considering their physical properties using FT-IR and Raman spectroscopy. For the safety evaluation, DMSO stocks of varying concentrations of PVDF and PU NFs (at 0.5, 1, 5, and 10 μg/mL) were prepared, and the cytotoxicity and inhibitory effects on nitric oxide production and protein expression obtained via Western blot were identified.

Equality and incomparability multi-label ranking have not been introduced to learning before. This paper proposes new native ranker neural network to address the problem of multi-label ranking including incomparable preference orders using a new activation and error functions and new architecture. Preference Neural Network PNN solves the multi-label ranking problem, where labels may have indifference preference orders or subgroups which are equally ranked. PNN is a nondeep, multiple-value neuron, single middle layer and one or more output layers network. PNN uses a novel positive smooth staircase (PSS) or smooth staircase (SS) activation function and represents preference orders and Spearman ranking correlation as objective functions. It is introduced in two types, Type A is traditional NN architecture and Type B uses expanding architecture by introducing new type of hidden neuron has multiple activation function in middle layer and duplicated output layers to reinforce the ranking by increasing the number of weights. PNN accepts single data instance as inputs and output neurons represent the number of labels and output value represents the preference value. PNN is evaluated using a new preference mining data set that contains repeated label values which have not experimented on before. SS and PS speed-up the learning and PNN outperforms five previously proposed methods for strict label ranking in terms of accurate results with high computational efficiency.

Accuracy and computational cost are the main challenges of deep neural networks in image recognition. This paper proposes an efficient ranking reduction to binary classification approach using a new feed-forward network and feature selection based on ranking the image pixels. Preference net (PN) is a novel deep ranking learning approach based on Preference Neural Network (PNN), which uses new ranking objective function and positive smooth staircase (PSS) activation function to accelerate the image pixels’ ranking. PN has a new type of weighted kernel based on spearman ranking correlation instead of convolution to build the features matrix. The PN employs multiple kernels that have different sizes to partial rank image pixels’ in order to find the best features sequence. PN consists of multiple PNNs’ have shared output layer. Each ranker kernel has a separate PNN. The output results are converted to classification accuracy using the score function. PN has promising results comparing to the latest deep learning (DL) networks using the weighted average ensemble of each PN models for each kernel on CFAR-10 and Mnist-Fashion datasets in terms of accuracy and less computational cost.

Objective: Studies in Sports Psychology and Sociology have validated causality in team-sport athletes by using emotional intelligence as a variable. This study aimed to examine the causal relationship between the types of autonomy support coaching, emotional intelligence, and interruption intention as psychosocial variables among current taekwondo athletes in Korea.Methods: In this study, 217 adult or university athletes registered in the Korea Taekwondo Association in 2020 were evaluated for the type of autonomy support coaching, emotional intelligence, and interruption intention. Results: Autonomy support coaching recognized by taekwondo athletes has a negative and positive effect on interruption intention and emotional intelligence, respectively. Moreover, emotional intelligence has a negative effect on interruption intention. which revealed that autonomy support coaching has a negative effect on interruption intention through emotional intelligence.Conclusions: Such outcomes can serve as a foundation for athletes to have the opportunity to participate in sports in a mature manner and promote positive changes in sports culture. In other words, the sensibility of the athletes can be harmoniously symmetry.

Objective: Studies in Sports Psychology and Sociology have validated causality in team-sport athletes by using emotional intelligence as a variable. This study aimed to examine the causal relationship between the types of autonomy support coaching, emotional intelligence, and interruption intention as psychosocial variables among current taekwondo athletes in Korea. Methods: In this study, 217 adult or university athletes registered in the Korea Taekwondo Association in 2020 were evaluated for the type of autonomy support coaching, emotional intelligence, and interruption intention. Results: Autonomy support coaching recognized by taekwondo athletes has a negative and positive effect on interruption intention and emotional intelligence, respectively. Moreover, emotional intelligence has a negative effect on interruption intention. which revealed that autonomy support coaching has a negative effect on interruption intention through emotional intelligence. Conclusions: Such outcomes can serve as a foundation for athletes to have the opportunity to participate in sports in a mature manner and promote positive changes in sports culture. In other words, the sensibility of the athletes can be harmoniously symmetry.

This paper presents the design of a robust speed controller for brushless DC motors (BLDCM) under field-oriented control (FOC). The proposed robust controller integrates extension theory (ET) and sliding mode theory (SMT) to achieve robustness. First, the speed difference between the speed command and the actual speed of the BLDCM, along with the rate of change of the speed difference, are divided into 20 interval categories. Then, the feedback speed difference and the rate of change of the speed difference are calculated for their extension correlation with each of the 20 interval categories. The interval category with the highest correlation is used to determine the appropriate control gain for the sliding mode speed controller. This gain adjustment tunes the parameters of the sliding surface in the SMT, thereby suppressing the overshoot of the motor speed. Because the sliding surface reaching law of the sliding mode controller (SMC) adopts the exponential approach law, the system's speed response can quickly follow the speed command in any state and exhibit excellent load regulation response. The simplicity of this robust control method, which requires minimal training data, facilitates easy implementation. Finally, the speed control of the BLDCM is simulated using Matlab/Simulink software, and the results are compared with those of the SMC using the constant speed approach law. The simulation results demonstrate that the proposed robust controller exhibits superior speed command tracking and load regulation response compared to the traditional SMC.

Relativistic shocks are one of the most plausible sites of the emission of strongly variable, polarized multi-wavelength emission from relativistic jet sources such as blazars, via diffusive shock acceleration (DSA) of relativistic particles. This paper summarizes recent results on a self-consistent coupling of diffusive shock acceleration and radiation transfer in blazar jets. We demonstrate that the observed spectral energy distributions (SEDs) of blazars strongly constrain the nature of hydromagnetic turbulence responsible for pitch-angle scattering by requiring a strongly energy-dependent pitch-angle mean free path. The prominent soft X-ray excess (``Big Blue Bump'') in the SED of the BL Lac object AO 0235+164 can be modelled as the signature of bulk Compton scattering of external radiation fields by the thermal electron population, which places additional constraints on the level of hydromagnetic turbulence. It has further been demonstrated that internal shocks propagating in a jet pervaded by a helical magnetic field naturally produce polarization-angle swings by 180$^o$, in tandem with multi-wavelength flaring activity, without requiring any helical motion paths or other asymmetric jet structures. The specific application of this model to 3C279 presents the first consistent, simultaneous modeling of snap-shot SEDs, multi-wavelength light curves and time-dependent polarization signatures of a blazar during a polarization-angle (PA) rotation. This model has recently been generalized to a lepto-hadronic model, in which the high-energy emission is dominated by proton synchrotron radiation. It is shown that in this case, the high-energy (X-ray and $\gamma$-ray) polarization signatures are expected to be significantly more stable (not showing PA rotations) than the low-energy (electron-synchrotron) signatures.

Hypertrophic Cardiomyopathy (HCM) is a common inherited disorder characterized by unexplained left ventricular hypertrophy, with or without left ventricular outflow tract (LVOT) obstruction. Single nuclei RNA-sequencing (snRNA-seq) of both obstructive and nonobstructive HCM patient samples have revealed alterations in communication between various cell types but a direct and integrated comparison between the two HCM phenotypes has not been reported. We performed a bioinformatic analysis of HCM snRNA-seq datasets from obstructive and nonobstructive patient samples to identify differentially expressed genes and distinctive patterns of intercellular communication. Differential gene expression analysis revealed 37 differentially expressed genes, predominantly in cardiomyocytes but also in other cell types, relevant to aging, muscle contraction, cell motility and the extracellular matrix. Intercellular communication was generally reduced in HCM, affecting the extracellular matrix, growth factor binding, integrin binding, PDGF binding and SMAD binding, but with increases in adenylate cyclase binding, calcium channel inhibitor activity, and serine-threonine kinase activity in nonobstructive HCM. Increases in neuron to leukocyte and dendritic cell communication, in fibroblast to leukocyte and dendritic cell communication and in endothelial cell communication to other cell types, largely through changes in expression of integrin-b1 and its cognate ligands, were also noted. These findings indicate both common and distinct physiological mechanisms affecting the pathogenesis of obstructive and nonobstructive HCM and provide opportunities for personalized management of different HCM phenotypes.

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

Ecosystem physical structure, defined by the quantity and spatial distribution of biomass, influences a range of ecosystem functions. Remote sensing tools permit the non-destructive characterization of canopy and root features, potentially providing opportunities to link above- and belowground structure at fine spatial resolution in functionally meaningful ways. To test this possibility, we employed ground-based portable canopy lidar (PCL) and ground penetrating radar (GPR) along co-located transects in forested sites spanning multiple stages of ecosystem development and, consequently, of structural complexity. We examined canopy and root structural data for coherence at multiple spatial scales ≤ 10 m within each site using wavelet analysis. Forest sites varied substantially in vertical canopy and root structure, with leaf area index and root mass more evenly distributed by height and depth, respectively, as forests aged. In all sites, above- and belowground structure, characterized as mean maximum canopy height and root mass, exhibited significant coherence at a scale of 3.5-4 meters, and results suggest that the scale of coherence may increase with stand age. Our findings demonstrate that canopy and root structure are linked at characteristic spatial scales, which provides the basis to optimize scales of observation. Our study highlights the potential, and limitations, for fusing lidar and radar technologies to quantitatively couple above- and belowground ecosystem structure.

Herein, we developed a highly sensitive and specific bimolecular fluorescence complementation (BiFC)-based influenza A virus (IAV) sensing system created by combining a galactose/glucose-binding protein (GGBP) with an N-terminal large domain (YN1-172) and a C-terminal small domain (YC173-239) of enhanced yellow fluorescence protein (eYFP). The GGBP-based BiFC reporter exhibits the fluorescence reconstitution as a result of conformational changes in GGBP when lactose, derived from 6’-silalyllactose used as a substrate for neuraminidase (NA), binds to GGBP in the presence of IAV. The system showed a linear dynamic range from 1 x 100 TCID50/mL to 1 x 107 TCID50/mL, with a detection limit of 4 x 101 TCID50/mL for IAV (H1N1), demonstrating ultra-high sensitivity. Our system exhibited fluorescence intensity enhancements in the presence of IAV, while displaying weak fluorescence signals when exposed to NA-deficient viruses such as RSV A, RSV B, adenovirus and rhinovirus, thereby indicating selective responses for IAV detection. Taken together, our system provides a simple, highly sensitive and specific IAV detection platform based on BiFC capable of detecting the ligand-induced protein conformational changes, obviating the need for virus culture or RNA extraction processes.

The recycling, incineration, and final disposal rate of municipal solid waste (MSW) are calculated based on the total amount of waste input to each facility in many countries. These statistic data have serious limitation in setting the national goal and policy for effective waste management because it is not considering the amount of foreign objectives in the process of each life-cycle stage. This case study is to estimate the actual rates of recycling, incineration, and final disposal by material flow analysis (MFA) after the collection of MSW in Korea. The actual rates of recycling, incineration and final disposal for MSW in 2016 were 49.9%, 32.9% and 23.1% respectively, indicating that the recycling rate was lower by 10.1%, while the incineration and final disposal rates were raised by 7.6% and 8.4% respectively, compared with the statistics for current MSW. In addition, the changed actual rates of recycling, incineration treatment, and final landfill, and variation of waste treatment charge according to treated amounts per treatment method was analyzed. This results of this study will contribute to establish national level of plan on effective waste management.

Simulating the non-perturbative and non-Markovian dynamics of open quantum systems is a very challenging many body problem, due to the need to evolve both the system and its environments on an equal footing. Tensor network and matrix product states (MPS) have emerged as powerful tools for open system models, but the numerical resources required to treat finite temperature environments grow extremely rapidly and limit their applications. In this study we use time-dependent variational evolution of MPS to expore the striking theory of Tamescelli et al. that shows how finite temperture open dyanmics can be obtained from zero temperature, i.e. pure wave function, simulations. Using this approach, we produce a benchmark data set for the dynamics of the Ohmic spin-boson model across a wide range of coupling and temperatures, and also present detailed analysis of the numerical costs of simulating non-equilibrium steady states, such as those emerging from the non-perturbative coupling of a qubit to baths at different temperatures. Despite ever growing resource requirements, we find that converged non-perturbative results can be obtained, and we discuss a number of recent ideas and numerical techniques that should allow wide application of MPS to complex open quantum systems.

The study investigated the relationships between sarcopenia, frailty, and related factors in hemodialysis patients with chronic kidney disease. A prospective cross-sectional study with convenience sampling was conducted between August 2021 and February 2022 at a hospital-affiliated hemodialysis center. Ninety-six hemodialysis patients participated in the study. Quantitative data were collected with structured interviews. Sarcopenia was determined with a rapid screening tool. Frailty was determined with the Rockwood clinical frailty score. Descriptive analysis, Person Correlations, and Linear regression analysis were used to evaluate the associations between frailty, sarcopenia, and health-related factors in hemodialysis patients. The mean age of the participants was 65.4 11.5 years, with an average of 95.0 77.5 months of hemodialysis. The most common comorbidity was hypertension (72.9%), followed by diabetes mellitus (39.6%) and cardiovascular health problems (35.4%). A significant difference in frailty between sarcopenia patients and a healthy population (X2 =9.51, p <.001) was identified. There was a strong negative correlation (r= −.853, p<.001) between sarcopenia and frailty, while moderate correlations between sarcopenia and frailty in sarcopenia patients (r= −.66, p<.001) and a healthy population (r= −.58, p<.001) were observed. Age, body weight before dialysis, and hand grip strength were found to be potential predictors of sarcopenia and frailty. Left calf circumference was significantly associated with sarcopenia (ß= −.128, p = .049). Age, body weight before dialysis, and hand grip strength are potential predictors of sarcopenia and frailty in hemodialysis patients with chronic kidney disease. Comorbidities, which may be preventable, are common in this population.

In electric circuits, energy is delivered by electromagnetic fields through the space, as suggested by Kraus and Carver. They provide insights by showing electric/magnetic fields and Poynting vector directions around a DC circuit. In this work, the energy flow mechanism by Kraus and Carver is further studied theoretically for arbitrary terminal potentials of a DC power source.

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

It is postulated in this research that the paradox of “advances in technology and management not keeping pace with the ever-increasing urban problems” is due to the poor understanding of person-focused governance of societal, environmental and economic entities. Therefore, the objective of this paper is to present an adaptive institutional model of person-driven effectiveness and ineffectiveness. The model proposes that human, ecologic and economic outcomes are heavily influenced by a complex system of systems, spanning from individually unique “non-physical influencers” to a broader set of social and environmental influencers that have a common impact on the larger society-environment-economy (SEE) system. At the heart of the model is an analytic formulation that explains the phenomena of non-physical blocker, enhancer and indifferent that are responsible for the adaptation and maladaptation of social agents, and accordingly for the sustainability and unsustainability of SEE systems. Examples are provided to illustrate the model applications: (a) the non-physical and maladaptive syndromes as antecedents of multi-morbidity and (b) the broadened and narrowed minds as sources of sustainability and unsustainability at the SEE system level within the context of emerging technologies such as engineered nanomaterials.

This study aimed to evaluate the safety and tolerability of STP1, a combination of ibudilast and bumetanide, tailored for the treatment of a specific subgroup of patients with Autism Spectrum Disorder (ASD), namely ASD Phenotype 1 (ASD-Phen1). We conducted a randomized, double-blind, placebo-controlled, parallel-group phase 1b study with two 14-day treatment phases (registered at clinicaltrials.gov as NCT04644003). Nine ASD-Phen1 patients were administered STP1, while three received a placebo. We assessed safety and tolerability, along with electrophysiological markers, such as EEG, Auditory Habituation, and Auditory Chirp Synchronization, to better understand STP1's mechanism of action. Additionally, we used several clinical scales to measure treatment outcomes. The results showed that STP1 was safe and well-tolerated, with electrophysiological markers indicating a significant and dose-related reduction of gamma power in the whole brain and in brain areas associated with executive function and memory. Treatment with STP1 also increased alpha 2 power in frontal and occipital regions and improved habituation and neural synchronization to auditory chirps. Although numerical improvements were observed in several clinical scales, they did not reach statistical significance. Overall, this study suggests that STP1 is safe and well-tolerated in ASD-Phen1 patients and shows indirect target engagement in ASD brain regions of interest.

Previous research has paid little attention to the relationship between corporate governance and brand equity in the tourism industry. This study aims to investigate the moderating effect of corporate governance (CG) on the relationship between brand equity (BE) and corporate profit-ability (CP) with ten control variables including five company characteristics and five macroeconomic variables. Financial data is retrieved from the Taiwan Economics Journal Database (TEJ), covering a total of 196 records from 32 listed companies for 16 years. Results indicate that BE has a significantly positive impact on CP in Taiwanese-listed tourism companies, and that CG moderates the relationship between BE and CP. These findings could help management executives enhance profitability by deepening BE and CG in the tourism industry. Managerial implications are also discussed.

Fibromyalgia (FM) is a chronic central sensitivity syndrome characterized by augmented pain processing at diffuse body sites and presents as a multimorbid clinical condition. Long COVID (LC) is a heterogenous clinical syndrome that affects 10-20% of individuals following COVID-19 infection. FM and LC shares similarities with regards to the pain and other clinical symptoms experienced, thereby posing a challenge for accurate diagnosis. This research explores the feasibility of using surface enhanced Raman spectroscopy (SERS) combined with soft independent modelling of class analogies (SIMCA) to develop classification models differentiating LC and FM. Venous blood samples were collected using two supports, dried bloodspot cards (DBS, n= 48 FM and n= 46 LC) and volumetric absorptive micro sampling tips (VAMS, n= 39 FM and n= 39 LC). A semi-permeable membrane (10 kDa) was used to extract low molecular fraction (LMF) from the blood samples, and Raman spectra was acquired using SERS with gold nanoparticles (AuNPs). Soft Independent Modelling of Class Analogy (SIMCA) models developed with spectral data of blood samples collected in VAMS tips showed superior performance with a validation performance of 100% accuracy, sensitivity, and specificity achieving an excellent classification accuracy of 0.86 area under the curve (AUC). Amide groups, aromatic and acidic amino acids were responsible for the discrimination patterns among FM and LC syndromes, emphasizing the findings from our previous studies. Overall, our results demonstrate the ability of AuNPs SERS to identify unique metabolites that can be potentially used as spectral biomarkers to differentiate FM and LC.

Functional health literacy is the ability to read, write, and speak about health. Functional health literacy events can nudge the development of children’s health identity when using valid and reliable reading materials that portray the “what, where, when, why, and with whom” to eat nutritious foods and be physically active. Children who lack social role models for healthy eating and physical activity may also lack development in language and motor skills. Therefore, literacy-rich environments are needed when developing cognitive-motor language skills with children. Children with obesogenic body frames can gain from the production of childcentric health narratives that draw upon the Habits of Mind and Habits of Health© Model to produce Electronic Texts for Health Literacy©. When health professionals plan and implement functional health literacy events so children can read, write, and speak about their own health, new behavioral patterns and routines emerge into performances of understanding. Constructivist pedagogical approaches can help children to create health narratives using multimodal language while practicing health literacy skills as a foundational impetus to health behaviors. Children who struggle with obesity can also gain social agency when writing with peer partners who serve as supportive collaborators when developing interactive health literacy.

Phage, which is often used therapeutically, has begun to receive interest as an alternative to antibiotic growth promoters (AGPs) to enhance chicken growth. Another option that has been extensively studied as a growth promoter in chicken is probiotics. However, there are no studies using phages and probiotics as prospective feed additives for broiler chickens. Therefore, this study demonstrated the effects of phage cocktail, probiotics and their combinations on growth performance and gut microbiota of broiler chickens. A total of 288 one-day-old male Cobb 500 broilers were randomly allotted to 1 of 6 treatments in a completely randomised design. The treatments were: (i) C (basal diet (BD) only), (ii) 1ɸ (BD + 0.1% phage cocktail), (iii) 2ɸ (BD + 0.2% phage cocktail), (iv) P (BD + 0.1% probiotic), (v) 1ɸP (BD + 0.1% phage cocktail + 0.1% probiotic), (vi) 2ɸP (BD + 0.2% phage cocktail + 0.1% probiotic). The 1ɸP treatment had significantly (P < 0.05) better BW (35 d), BWG (22 – 35 d, 1 – 35d), and FCR (1-21 d. 22-35 d, 1-35 d) compared to C. Unique gut microbiota diversity was also found between the ɸP (1ɸP and 2ɸP) and non-ɸP groups (C, 1ɸ, 2ɸ and P) in ilea, particularly in the 35 d chickens. Microorganisms associated with short-chain fatty acid (SCFA) producers were significantly (P <0.05) present in the ɸP group than in the non- ɸP group. The carbohydrate and amino acid metabolism predicted genes were significantly upregulated in ɸP groups compared to non- ɸP groups. These genes were involved in the digestion and absorption of nutrients as well as the production of energy. Our findings showed that 1ɸP treatment could be a potential alternative to AGPs for poultry where growth performance was enhanced, and gut microbiota was positively modulated.

Recently, smart mobility intelligent traffic services have become a critical task in Intelligent Transportation Systems (ITS). This involves not only the use of advanced sensors and controllers but also the ability to respond to real-time traffic situations at intersections, alleviate congestion, and generate policies to prevent traffic jams. DRL (Deep Reinforcement Learning) provides a natural framework for processing tasks. In DRL, each intersection can control itself and coordinate with neighbors to achieve optimal network-wide policies. However, comparing approaches remains a challenging task due to the existence of numerous possible configurations. This research performs a critical comparison of various traffic controllers found in the literature. It demonstrates that using a nonlinear approximator for coordination mechanisms and enhancing observability at each intersection are key performance drivers.

Interrelationships between traditional dental variables are becoming more evident in far reaching aspects of life such as psychosocial interaction, self-esteem, overall health and even occupational performance. This study compares quality of life (QoL) in postmenopausal women (PMW) with poor oral health (POH) with QoL in PMW with good oral health. 200 randomly recruited PMW received a dental evaluation and completed Utian Quality of Life Survey. The participants were divided into POH and healthy groups based on dental exam. Mean scores were calculated for each QoL item, domain and the overall summary score. For each of the four parameters for periodontitis diagnosis, periodontitis patients’ QoL outcomes were compared to those of healthy patients using T-test with threshold of significance at p<0.05. QoL in all fields measured were significantly poorer in the POH compared to the healthy patients, occupational (19.95±5.35vs. 27.56±6.13), health (18.02±8.23 vs. 26.59 ±6.45), emotional (15.68±10.22vs. 21.15±9.15), sexual (6.2±5.98vs. 10.02±5.35), and total score (60.21±25.85 vs. 84.26±22.35). This study finds that PMW with POH, report significantly poorer quality of life. Clinicians caring for PMW should be aware of that oral health impacts QoL and make appropriate referral decisions for patients’ dental care. Keywords: Quality of Life, Oral Health, Post-menopause, Women

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

For the elimination of radio-frequency interference (RFI) in a passive microwave radiometer, the threshold level is generally calculated from the mean value and standard deviation. However, a serious problem that can arise is an error in the retrieved brightness temperature from a higher threshold level owing to the presence of RFI. In this paper, we propose a method to detect and mitigate RFI contamination using the threshold level from statistical criteria based on a spectrogram technique. Mean and skewness spectrograms are created from a brightness temperature spectrogram by shifting the 2-D window to discriminate the form of the symmetric distribution as a natural thermal emission signal. From the remaining bins of the mean spectrogram eliminated by RFI-flagged bins in the skewness spectrogram for data captured at 0.1-s intervals, two distribution sides are identically created from the left side of the distribution by changing the standard position of the distribution. Simultaneously, kurtosis calculations from these bins for each symmetric distribution are repeatedly performed to determine the retrieved brightness temperature corresponding to the closest kurtosis value of three. The performance is evaluated using experimental data, and the error in the retrieved brightness temperature is observed to be less than approximately 3 K from a window with a size of 100 × 100 time-frequency bins according to the RFI levels and cases.

Introduction: Transforming growth factor beta receptor 2 (Tgfbr2) signaling regulates odontoblast differentiation, dentin mineralization, and the paracrine signaling that guides sensory innervation in developing mouse molars. We hypothesized that Tgfbr2 also regulates the neuro-pulpal responses to injury to activate axon sprouting and tertiary dentin secretion. Methods: We per-formed a timed deletion of Tgfbr2 using tetracycline-responsive Osterix-Cre;Tgfbr2f/f (Tgfbr2^cko) mice, which allowed them to develop normally. At 3 months, we drilled a shallow hole on the mesial side of the first mandibular molar (M1) in both control and Tgfbr2^cko mice. Hemi-mandibles were collected 4, 8, 21, and 56 days post-injury (dpi). In situ hybridization (ISH) for Sp7 was performed to confirm Osterix-Cre transcription. Microcomputed tomography (micro-CT) imaging and histology were used to examine the tertiary dentin, and immunofluorescence was used to visualize CGRP+ axons following the injury. Results: Tgfbr2 deletion was inferred by Sp7 ISH. Micro-CT and histology indicated a lower dentin volume in 21 dpi Tgfbr2^cko M1s compared to WT M1s, but the volume was comparable by 56 dpi. The duration of axon sprouting was longer in injured Tgfbr2^cko M1s compared to WT M1s. Conclusions: These results suggest that sensory afferents may support dentin repair in Tgfbr2-deficient odontoblasts.

This narrative review provides a thorough examination of medication-related osteonecrosis of the jaw (MRONJ), encompassing its etiology, the role of drug holidays, and contemporary treatment approaches. By systematically analyzing literature from 2022 to 2023, this paper synthesizes the latest findings and trends in MRONJ research. The study emphasizes the importance of a holistic understanding of MRONJ, beginning with its etiological factors, assessing the therapeutic implications of drug holidays, and evaluating the efficacy of current treatment modalities. This review aims to offer clinicians and researchers a consolidated resource, highlighting the intricacies of MRONJ management and proposing directions for future research. Through this comprehensive approach, the paper seeks to advance the understanding and treatment of MRONJ, ensuring an evidence-based, patient-centric approach in clinical practice.

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.

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

This study investigates the asymmetric impacts of oil price changes on inflation in Algeria, Angola, Libya and Nigeria. Three different oil price data were applied in this study; the specific spot oil price of individual countries, the OPEC reference basket oil price and an average of the Brent, WTI and Dubai oil price. The dynamic panels ARDL were used to estimate the short and the long-run impacts. Also, this study partitioned the oil price into positive and negative changes to capture asymmetric impacts and found both positive and negative oil price changes positively influenced inflation. However, the impact was found to be more significant when oil prices dropped. The results from the study also found that money supply, the exchange rate and GDP are positively related to inflation while food production is negatively related to inflation. Accordingly, policymakers should be cautious in formulating policies between the positive and negative changes in oil prices as it was shown that inflation increased when the oil price dropped. Additionally, the use of contractionary monetary policy would help to reduce the inflation rate, and lastly, it is proposed that the government should encourage domestic food production both in quantity and quality to reduce inflation.

By using 0.35-um CMOS process, this work achieves a design of analogous band-gap reference voltage circuit with low temperature coefficient. The proposed circuit operates at 3V and generates a reference current of 44 uA. The HSPICE simulation results show the temperature coefficient of this circuit is 23 ppm/℃ at range of -10 ℃ to 100 ℃, and the line regulation (the ratio of output current variation to supply voltage variation) is estimated as 1.95 uA/V from supply voltage variation of 3 V to 5 V. The experimental chip is fabricated and measured. The circuit provides adjustable capability for output voltage among temperature variation of -10 - 100 ℃. The chip area is 534 × 695 um^2. In this new design, the operational amplifier is not necessary. The chip design effort can be great reduced.

Environmental deterioration factors are constantly increasing, causing unwanted aesthetic changes to stone artworks due to exposure to various physical and chemical deterioration factors. Inorganic nanoparticle-filled polymer composites have extended their multiple functionalities to various applications, including cultural heritage conservation. Therefore, this study has examined the effects of clay, SiO2, Ca(OH)2 and CaCO3 nanomaterials in the enhancement of the physicomechanical properties of limestone monuments, the aim of the present work being to evaluate comparatively the effectiveness of nanoparticles as consolidation and protection material for limestone artworks. The nanoparticles were added to an acrylic-based copolymer (polyethylmethacrylate (EMA)/methylacrylate (MA) (70/30), in order to improve its physiochemical and mechanical properties, and produced a significant improvement in the ability of the polymers to consolidate and protect the stone. The synthesis process of nanoparticles/polymer nanocomposite has been prepared by an in situ emulsion polymerization system. The nanocomposites contained poly (EMA/MA) with a solid content of 3% [poly (EMA/MA)] in the absence and presence of 5% nanoparticles (0.15 g nanoparticles). Samples were subjected to artificial aging by relative humidity/temperature and acid/salt crystallization weathering to show the optimum conditions of durability and the effectiveness of the nano-mixture in improving the physical and mechanical properties of the stone material. To ensure that the treatment had no negative effects on the physical characteristics of the limestone, the properties of the treated limestone samples were evaluated comparatively before and after artificial aging by the conduct of microstructural (phase morphology studied by means of scanning electron microscopy) and aesthetic (colour and lightness measured by spectrophotometry) analyses. Also used were measurement of static contact angle of water droplets on the surface of the samples, total immersion water absorption, compressive strength, and abrasion resistance test. Results demonstrated that the addition of nanoparticles to an acrylic-based polymer enhanced its capability to consolidate and protect the limestone samples.

Dental anxiety (DA) negatively affects patients’ oral and overall health. This study explored attitudes and clinical practices of licensed Ohio general dentists who treat patients with DA. Methods: An anonymous self-administered mail survey was sent to 500 general dentists licensed and practicing in Ohio. Responses to 21 pre-coded questions were analyzed. Frequencies were examined; cross-tabs, Chi-Square, and Fischer’s Exact Test were calculated for statements according to dentists’ gender. Alpha was set at p = 0.05. Results: Nearly all respondents treated anxious patients; males were more likely to find it challenging than females. Dentists were most familiar with distraction, although half found nitrous oxide to be an effective tool. Female dentists were more likely than males to be familiar with anxiolytics and find them effective. Conclusion: Overall, Ohio general dentists are most familiar with using distraction and nitrous oxide during appointments for anxious patients. Gender differences exist in attitudes towards anxiolytic use for patients with DA. Practice Implications: By identifying techniques that are comfortable for patient and practitioner, oral health disparities associated with DA may be reduced.

Hypertrophic cardiomyopathy (HCM) is a common inherited heart disorder complicated by left ventricle outflow tract (LVOT) obstruction, which can be treated with surgical myectomy. To date, no reliable biomarkers for LVOT obstruction exist. To determine whether metabolomic biomarkers for obstruction can be identified, we conducted metabolomic profiling on plasma samples of 18 HCM patients before and after undergoing surgical myectomy to measure changes in the plasma metabolome in the postoperative state. Plasma was collected approximately 4 weeks before surgery at the preoperative visit and approximately 3 months after the surgery at the postoperative visit. We found that 215 metabolites were altered in the postoperative state (p-value &lt; 0.05). Identified metabolites that were significantly reduced post-myectomy included metabolites of heme, such as bilirubin, and phenylacetylglutamine, a biomarker of urea cycle disorders, which suggests that liver and kidney function are improved in the postoperative state. Markers of arginine metabolism such as homoarginine and dimethylarginine are also decreased in the postoperative state, suggestive of reduction in nitric oxide production, inflammation and heart failure after surgery. 3-hydroxybutyrate (BHBA) was also decreased, suggesting possible increased fatty acid utilization and a return to normal heart function. 12 of these metabolites were notably significant after adjusting for multiple comparisons (q-value &lt; 0.05), including bilirubin, PFOS, PFOA, 3,5-dichloro-2,6-dihydroxybenzoic acid, 2-hydroxylaurate, trigonelline and 6 unidentified compounds, which support improved kidney and liver function and increased lean soft tissue mass. These findings suggest improved organ metabolic function after surgical relief of LVOT obstruction in HCM and further underscore the beneficial systemic effects of surgical myectomy.

Acute myeloid leukemia (AML) is the second common hematologic malignancy in children. The incidence of childhood AML is much lower than acute lymphoblastic leukemia (ALL), which makes the childhood AML a rare disease in children. The role of genetic abnormalities in AML classification, management and prognosis prediction is much more important than before. The WHO classification of myeloid neoplasms and the European LeukemiaNet (ELN) classification were both revised in 2022. The application of the new information in childhood AML will be upcoming in the next few years. The frequency of each genetic abnormality in adult and childhood AML is different, therefore, in this review we emphasize in well-known genetic subtypes in childhood AML, including Core-binding factor AML (CBF AML), KMT2Ar (KMT2A/11q23 rearrangement) AML, normal karyotypes AML with somatic mutations, unbalanced cytogenetic abnormalities AML, NUP98 11p15/NUP09 rearrangement AML and acute promyelocytic leukemia (APL). Current risk group classification, management algorithm in childhood AML and novel treatment modalities, such as targeted therapy, immune therapy, chimeric antigen receptor (CAR) T-cell therapy are reviewed. Finally, the indications of hematopoietic stem cell transplantation (HSCT) in AML are discussed.

Background: The receptor activator of the nuclear factor-kB (RANK)/RANK ligand (RANKL)/osteoprotegerin (OPG) pathway is a determining pathway in the balance between bone formation and resorption; disruptions in this complex can affect bone metabolism. Methods: This study analyzed the changes in RANKL, OPG and 25(OH)D levels, the RANKL/OPG ratio, and other bone turnover markers (BTM) from diagnosis to complete remission in children with acute lym-phoblastic leukemia (ALL). This is a prospective observational cohort study. This study was carried out in the Instituto Mexicano del Seguro Social in Mexico City. Thirty-three patients (4-17 years) with newly diagnosed B-cell ALL were included. The patients were treated with the HP09 chemotherapy protocol. Children who had previously been treated with corticosteroids were excluded. A pe-ripheral blood sample at diagnosis and remission was collected to determine the 25(OH)D and BTM concentrations. Results: Increased RANKL (p=0.001) and osteocalcin (p

In the present work, we designed a mild strategy to make Cu₂(OH)PO₄ (CHP) nanoparticles on cotton fabrics (CFs) to achieve multi-functionalities. The phytic acid (IP6) assisted method was employed to synthesize nanoparticles (CHP-IP6). Under Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), scanning electron microscopy (SEM), energy-dispersive X-ray (EDX), transmission electron microscope (TEM), X-ray photoelectron spectroscopy (XPS) as well as thermogravimetric analysis (TGA), we characterized the coated cotton fabrics. The CHP-IP6 treated fabrics showed prominent photocatalytic activity, excellent photocatalytic stability and thorough discoloration of methylene blue (MB) stain under sunlight irradiation.

This study introduces a hardware accelerator to support various Post-Quantum Cryptosystem (PQC) schemes, addressing the quantum computing threat to cryptographic security. PQCs, while more secure, also bring significant computational demands, especially problematic for lightweight devices. Previous hardware accelerators are typically scheme-specific, which is inefficient given the National Institute of Standards and Technology (NIST)'s multiple finalists. Our approach focuses on the shared operations among these schemes, allowing a single design to accelerate multiple candidate PQCs at the same time. This is further enhanced by allocating resources according to performance profiling results. Our compact, scalable hardware accelerator supports four of NIST PQC finalists, achieving an area efficiency of up to 81.85\% compared to the current state-of-the-art multi-scheme accelerator while supporting twice as many schemes. The design demonstrates average throughput improvements ranging from 0.97$\times$ to 35.97$\times$ across the four schemes and their main operations, offering an efficient solution for implementing multiple PQC schemes within constrained hardware environments.

Excessive production, consumption and indiscriminate disposal of plastic waste cause an increasing plastic pollution with detrimental impacts on environment and human health. This study aimed to assess the level of knowledge, attitude, and practices (KAP) towards plastic pollution among Malaysians and evaluate the variation of plastic pollution related KAP among various socio-demographics. An online survey was conducted, and 294 valid responses was obtained. Descriptive statistics, KAP scoring and cross tabulation of responses were estimated. One-way analysis of variance, paired t-test and binary logistic regressions were carried out. Results showed that respondents had poor knowledge (mean 7.41 ± 1.80) and practice score (3.81 ± 1.39) across all socio-demographics. Compared to younger (18-30 years) respondents, older ones (>46 years) had higher knowledge (odds ratio, OR 4.304; p<0.01). However, middle aged (31-45 years) respondents reported significantly (p<0.01) higher attitude (OR 4.019) and practice (OR 4.056; p <0.05). Respondents with environmental related university education had showed higher odds about plastic pollution related knowledge (OR 10.343; p<0.01). Suggestions are made to undertake interventions such as environmental awareness creation, incorporating plastic pollution topics in formal and informal education, and providing recycling facilities nearby the localities for encouraging good practices towards minimizing plastic uses and pollution.

Molecular transport and quantum tunneling of H2 and H2O molecules through nanoporous gra-phene is studied using computational modeling and first principles density functional theory. It is demonstrated that molecules with sufficiently high kinetic energies can tunnel through the na-nopores. It is also demonstrated that molecules can be trapped in front of the nanopore or behind it. These investigations help us learn the behavior of molecules in and around nanopores of gra-phene. They also help us learn fundamentals of molecular tunneling. We believe, nanoporous gra-phene can play important roles for gas separation and nanofiltration.

Alpha-B-Crystallin, a member of the small heat shock family of proteins, has been implicated in a variety of cardiomyopathies and in normal cardiac homeostasis. It is known to function as a molecular chaperone, particularly for desmin, but also interacts with a wide variety of additional proteins. The molecular chaperone function is also enhanced by signal-dependent phosphorylation at specific residues under stress conditions. Naturally occurring mutations in CRYAB, the gene that encodes alpha-B-crystallin, have been suggested to alter ionic intermolecular interactions that affect dimerization and affect chaperone function. These mutations have been associated with myofibrillar myopathy, restrictive cardiomyopathy, and hypertrophic cardiomyopathy, and promote pathological hypertrophy through different mechanisms such as desmin aggregation, increased reductive stress or activation of calcineurin-NFAT signaling. This review will discuss the known mechanisms by which alpha-B-crystallin functions in cardiac homeostasis and the pathogenesis of cardiomyopathies and provide insight into potential future areas of exploration.

Prevalence of antimicrobial-resistant bacteria has become a major challenge worldwide. Methicillin-resistant Staphylococcus aureus (MRSA)—a leading cause of infections—forms biofilms on polymeric medical devices and implants, increasing their resistance to antibiotics. Antibiotic administration before biofilm formation is crucial. Raman spectroscopy was used to assess MRSA biofilm development on solid culture media from 0 to 48 h. Biofilm formation was monitored by measuring DNA/RNA-associated Raman peaks and protein/lipid-associated peaks. The search for an antimicrobial agent against MRSA biofilm revealed that Eugenol was a promising candidate as it showed significant potential for breaking down the biofilm. Eugenol was applied at different times to test the optimal time for inhibiting MRSA biofilms, and the Raman spectrum showed that the first 5 h of biofilm formation was the most antibiotic-sensitive time. This study investigated the performance of Raman spectroscopy coupled with Principal Component Analysis (PCA) to identify planktonic bacteria from biofilm conglomerates. Raman analysis, microscopic observation, and quantification of the biofilm growth curve indicated early adhesion from 5 to 10 h of incubation time. Therefore, Raman spectroscopy can help in monitoring biofilm formation on a solid culture medium and performing rapid antibiofilm assessments with new antibiotics during the early stages of the procedure.

Hypertrophic cardiomyopathy (HCM) is the most common inherited cardiovascular disorder affecting 1 in 500 people in the general population. Although characterized by asymmetric left ventricular hypertrophy, cardiomyocyte disarray and cardiac fibrosis, HCM is in fact a highly complex disease with heterogenous clinical presentation, onset and complications. While HCM is generally accepted as a disease of the sarcomere, variable penetrance in families with identical genetic mutations challenges the monogenic origin of HCM and instead implies a multifactorial cause. Furthermore, large scale genome sequencing studies revealed that many genes previously reported as causative of HCM in fact have little or no evidence of disease association. These findings thus call for a re-evaluation of the sarcomere-centered view of HCM pathogenesis. Here, we summarize our current understanding of sarcomere-independent mechanisms of cardiomyocyte hypertrophy, highlight the role of extracellular signals in cardiac fibrosis, and propose an alternative but integrated model of HCM pathogenesis.

In this paper, an extendable fuzzy robust speed controller suitable for induction motor drive system was proposed. Firstly, the two-degrees-of-freedom (2DOF) robust control technology with feedforward control and disturbance elimination method was adopted. Upon parameter variation and load disturbance, the motor drive system could utilize a robust controller to generate compensation signals and reduce the impact on controlling performance of the motor drive system. The magnitude of the compensation signal was adjusted via the weighting factor. However, should a fixed weighting factor be adopted, system instability might be generated easily when time delay and saturation of control force occur. Based on the above, the smart method of extendable fuzzy theory (EFT) was adopted in this paper to adjust adequate weighting factors, where the controlling performance of the induction motor drive system could be improved accordingly. The method divided the speed difference between motor speed command and actual speed of the induction motor, and the variation rate for such speed difference into 20 regional categories. The correlation degree between the speed difference of actual feedback, variation rate for speed difference and each regional category was then calculated, where more suitable weighting factor was selected. Therefore, the proposed extendable fuzzy robust 2DOF controller with variable weighting factor designed will allow better performance for response in speed tracking and load regulation. Lastly, the simulation software Matlab/Simulink was applied to simulate the utilization of the controlling method proposed for the induction motor drive system. For both the response in speed tracking and load regulation, the simulation results proved that the extendable fuzzy robust speed controller proposed provided better controlling performance than the conventional robust controller.

Currently, most plastic waste stems from packaging materials, with a large proportion of this waste either discarded or used to derive fuel. Accordingly, there is growing interest in the use of pyrolysis in the context of chemically recycling non-recyclable (i.e., via mechanical means) plastic waste into petrochemical feedstock. The aim of this study is to use kinetic analyses to elucidate the pyrolytic properties of solid recovered fuel (SRF) produced using two types of reactors, namely, fixed bed and fluidized bed reactors. From the kinetic analysis, the activation energy corresponding to the rate of pyrolysis reaction conversion was obtained. In conclusion, we found that the pyrolysis occurs more vigorously in fluidized bed reactors compared to fixed bed reactors.

A number of studies have been conducted to improve the accessibility of images using touchscreen devices for screen reader users. In this study, we conducted a systematic review of 33 papers to get a holistic understanding of existing approaches and to suggest a research road map given identified gaps. As a result, we identified types of images, visual information, input device and feedback modalities that were studied for improving image accessibility using touchscreen devices. Findings also revealed that little has studied how to automate the generation of image-related information, and that screen reader users play important roles during the evaluation but the design process. Then we introduce two of our recent studies on the accessibility of artwork and comics, AccessArt and AccessComics respectively. Based on the identified key challenges, we suggest a research agenda for improving image accessibility for screen reader users.

This paper examines the Business Model (BM) from a socioeconomic system perspective to discern key factors, and understand its interactions resulting in the Scaling of Social Impact (SSI) in Social Entrepreneurship (SE). Previously, studies have explained the importance of BM in relation to SE. However, there is a lack of empirical studies on how BM’s transitions through participation of various actors result in SSI. This research applies qualitative analysis on a single case study of a Japanese social startup, “mymizu”, the first water refill application platform in Japan. The findings show that collaboration amongst different stakeholders on the initial phase of the BM could increase awareness of responsible consumption, convert into actual users for sustainability, and change their behavior. Secondly, members of the society could take on dual roles, both as users and collaborators in the BM, which results in an exponential scaling effect of the social impact. This paper contributes towards adding a participatory stakeholder (PS) to the ecosystem of SSI and building a “regenerative” BM that is relevant in SE towards sustainability.

This paper presents a novel algorithm, the multi-objective nonlinear interval PageRank (MONIPR) Algorithm. This algorithm extends the conventional PageRank (PR) algorithm, integrating nonlinear interval computation and multi-objective considerations into the computation process. The MONIPR algorithm bridges a research gap in integrating nonlinear interval approaches and multi-objective problems into the PR algorithm, which were traditionally treated separately. In addition, this research adopts the constrained interval arithmetic proposed to address the limitations of the conventional PR algorithm, which tends to overlook uncertainties and results in deterministic outcomes. In addition, we use a numerical example to demonstrate the proposed algorithm, contrasting it with the conventional approaches. A numerical example demonstrates the algorithm's performance by comparing the rank intervals obtained with the traditional crisp Markov chain and PR algorithm. The results highlight the ability of the proposed algorithm to provide a range of possible rank intervals, considering both uncertainty and multi-objectives. The findings suggest potential applications in decision-making, uncertainty quantification, and systems analysis.

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

(1) Background: Due to the high proportion of disadvantaged students in a rural school in Taiwan and the gap between students’ concepts and practices of environmental protection and sustainable energy, four science and mathematics teachers in this school planned an engineering-centered PjBL of sustainable energy curriculum in a Makers Club to enhance students’ creativity, engineering skills, practices of environmental protection and sustainable energy, and learning attitudes; (2) Methods: This study is four-year action research. Teachers and students initiated the idea from rebuilding an old fan in a classroom; (3) Results: The students in the Makers Club improved their engineering skills and created various green-power generation devices (evolved from ventilation ball generator, hydropower, ocean current power generators to tiny, 3D-printing wind power generators). They turned environmental protection and sustainable energy concepts into actions during practices and won awards from science and engineering fairs every year. This creative and supportive atmosphere spread from the club to the whole school and improved the students’ practices of environmental protection and learning attitudes after long-term implementation; (4) Conclusions: The design principles of the engineering-centered PjBL of sustainable energy curriculum played a critical role and were outlined at the end of the study.

This paper analyzes the representation behaviors of a comparison measure between two compared fuzzy sets. Three types of restrictions on two fuzzy sets are considered in this paper: the two disjoint union fuzzy sets, the two disjoint fuzzy sets and the two general fuzzy sets. Differences exist among the numbers of possible representations of a comparison measure for the three types of fuzzy sets restrictions. The value of comparison measure is constant for the two disjoint union fuzzy sets. There are 42 candidate representations of a comparison measure for the two disjoint fuzzy sets. Of which 13 candidate representations with one or two terms can be used to easily calculate and compare a comparison measure.

In fuzzy group decision making problems and fuzzy shortest path problems, the addition and subtraction are the basic problems. For the mixed normal fuzzy numbers and trapezoidal fuzzy numbers, the addition and subtraction operations are approximated by the normal fuzzy numbers in this paper. The behaviors of approximated normal fuzzy numbers are the same as those of the normal distributions from the viewpoint of probability. An application of the addition and subtraction operations of mixed fuzzy numbers to the fuzzy sample mean is also proposed.

This article develops algorithms for the characterization and the visualization of micro-scale features by using a small number of sample points, and with a goal to mitigate for the measurement shortcomings which are often destructive or time consuming. We implement the algorithms to rapidly examine the microscopic features of a Microelectromechanical System (MEMS) surface. Such images are highly dense; therefore, traditional image processing techniques might be computationally expensive. The contribution of this research include first, we develop local and global algorithm based on modified Thin Plate Spline (TPS) model to reconstruct high resolution images of the micro-surface’s topography, and its derivatives by using low resolution images. Second, we obtain a bending energy algorithm from our modified TPS model, and use it to filter out image defects. Finally, we develop a computationally efficient Windowing technique, which combines TPS and Linear Sequential Estimation (LSE), to enhance the visualization of images. The Windowing technique allows rapid image reconstruction based on the reduction of inverse problem.

In recent years, the demand for coffee has increased tremendously. During the production process, green coffee beans are traditionally screened manually for defective beans before they are packed into coffee bean packages; however, this method is not only time-consuming but also increases the rate of human error due to fatigue. Therefore, this paper proposed a lightweight deep convolutional neural network (LDCNN) for the quality detection system of green coffee beans, which combined depthwise separable convolution (DSC), squeeze-and-excite block (SE block), skip block, and other frameworks. To avoid the influence of low parameters of the lightweight model caused by the model training process, rectified Adam (RA), lookahead (LA), and gradient centralization (GC) were included to improve efficiency; the model was also put into the embedded system. Finally, the local interpretable model-agnostic explanations (LIME) model was employed to explain the predictions of the model. The experimental results indicated that the accuracy rate of the model could reach up to 98.38% and the F1 score could be as high as 98.24% when detecting the quality of green coffee beans. Hence, it can obtain higher accuracy, lower computing time, and lower parameters. Moreover, the interpretable model verified that the lightweight model in this work is reliable, providing the basis for screening personnel to understand the judgment through its interpretability, thereby improving the classification and prediction of the model.

This work communicates line strength data and associated scripts for computation and spectroscopic fitting of selected transitions of the diatomic molecules AlO, C2, CN, OH, N2+, NO, and TiO. For ease of use, the scripts for data analysis are designed for inclusion in various software packages or program languages. The accuracy of the data is of the order of less than one picometer, suitable for analysis of laser-induced fluorescence and laser-plasma spectra. Selected results demonstrate the applicability of the program for data analysis in laser-induced optical breakdown spectroscopy primarily at The University of Tennessee Space Institute, Center for Laser Applications. Representative spectra are calculated and referenced to measured data records.

Crystalline β-cobalt hydroxide (β-Co(OH)₂) of different morphologies have been successfully synthesized with the addition of sodium hydroxide to cobalt nitrate solution and aging in the mother liquor. The rate of NaOH addition, ranging from 0.1 mL/min to 10 mL/min, influences the surface morphology with the obtained storage capability of the respective electrode. Characterization of the β-Co(OH)₂ was fully developed, including X-ray diffraction, scanning and transmission electron microscopy, and BET analyses. At a lower rate of NaOH addition, particles are like platelets, while for a higher rate (≥2 mL/min) grains are fused together forming a larger crystallite size. This result is supported by the X-ray diffraction structural analysis, where the phase evolution of (002) plane becomes distinct for the higher rate of NaOH addition. Lithium cobalt oxide (LiCoO₂) was synthesized through oxidation from the as-prepared β-Co(OH)₂ and LiOH. The electrochemical performance of as obtained LiCoO₂ is investigated using charge-discharge and cyclic voltammetric studies. The precursor β-Co(OH)₂ prepared at a lower rate of 0.1 mL/min in LiCoO₂ demonstrated the best electrochemical performance of 155 mAh/g. After 50 cycles, the capacity retention rate was 67% compared with the first cycle. Finally, we have attempted to correlate the amount of the available OH^- ions with the formation of platelets and the discharge capacity. This work has developed a methodology for the synthesis of LiCoO₂ using β-Co(OH)₂ in a facile chemical solution process.

In this study, Li-Al-OH layered double hydroxide (LDH), which was prepared by solvent-free one-step mechanochemical reaction of LiOH and Al(OH)₃, was applied to remove boron from aqueous solution. Dry-grinding for 3 h at a rotational speed of 500 rpm, Li/Al molar 1/2 was the optimum condition to prepare highly crystalline of Li-Al LDH phase with no evident impure phases. Two milling products with Li/Al molar ratio at 1/2 and 2/2 were evaluated for boron adsorption. The results confirmed that Li/Al molar ratio 2/2 sample showed high boron adsorption capacity due to the physical adsorption of Li-Al-OH LDH and chemical synergism of phase gel Al(OH)₃. The adsorption isotherms, described by the Langmuir model, indicated maximum monolayer boron uptake capacity 45.45 mg/g, implying competitive adsorption capacity of the material in our experiment.

In this paper, a mathematical and physical interpretation of the length and the angle of the catenary curve made by the anchor chains was implemented, and the safety of an anchored vessel was reviewed. So far, holding force has been calculated approximately when the angle of the catenary curve of the anchor chain to the seafloor is 0°. In this study, the holding force equation was strictly derived for the case of anchor dragging. In addition, the equations for the angle and length of the catenary curve were mathematically derived when the anchor dragging occurs. The holding force equation derived in this paper are expected to help provide guidelines in vessel design or increase the safety of anchoring.

This study compares the performance of existing studies on multimodal emotion recognition, and proposes a model that fuses two modalities with the speaker's text and voice signals as input values and detects depression. Based on the DAIC-WOZ dataset, voice features were extracted using CNN, text features were extracted using Transformers, and two modalities were fused through a tensor fusion network. We also build a model to detect whether the speaker is depressed or not using LSTM in the final layer. This study suggests the possibility of increasing access to mental illness diagnosis by enabling patients to detect depression on their own in daily conversations. If the model proposed in this study is developed and the voice conversation system is connected, it will be easier for patients who cannot visit the hospital periodically or who are reluctant to visit the hospital to check their condition and seek recovery. Furthermore, it can be expanded to multi-label classification for various mental diseases and used as a simple self-mental disease diagnosis tool.

The mobile payment has been emerging as an alternative to cash and credit cards and is rapidly evolving around the world. This study integrated the general model of innovation diffusion theory (IDT) with the technology acceptance model (TAM) to examine the impact of near-field-communication (NFC) mobile payment environment on the restaurant operating performance (ROP). This paper used convenience sampling to distribute questionnaires to restaurant owners and managers in order to investigate the impact of NFC mobile payment environment on ROP. A total of 279 valid questionnaires were collected. The empirical results show that sales growth, cost saving, flexibility, accessibility and trust &amp; safety had significantly positive impacts on ROP. After considering the restaurant size as a moderator for analysis, there are only two constructs- accessibility and trust &amp; safety had significant impacts on ROP. This empirical finding could provide restaurateurs with a reference to improve ROP by increasing the mobile payment environment.

This paper aims to quantify the effect of the deadly novel coronavirus (COVID-19) pandemic outbreak on Chinese stock market performance. Shanghai Stock Exchange Composite Index and its component sector indices are examined in this study. The pandemic is represented by a lockdown dummy, new COVID-19 cases and a dummy for 3 February 2020. First, descriptive analysis is performed on these indices to compare their performances before and during the lockdown period. Next, regression analysis with Exponential Generalized Autoregressive Conditional Heteroscedasticity specification is estimated to quantify the pandemic effect on the Chinese stock market. This paper finds that health care, information technology and telecommunication services sectors were relatively more pandemic-resistant, while other sectors were more severely hurt by the pandemic outbreak. The extent to which each sector was affected by pandemic and sentiments in other financial and commodity markets were reported in details in this paper. The findings of this paper are resourceful for investors to avoid huge loss amid pandemic outburst and the China Securities Regulatory Commission in handling future pandemic occurrence to cool down excessive market sentiments.

Background and Objectives: There is a need to effectively manage the healthy aging of the rapidly increasing number of elderly people in an ultra-elderly society. The purpose of this study was to analyze the mediating effects of social networks and wisdom on the relationship between lifestyle habits and healthy aging in older adults with chronic diseases. Materials and Methods: Participants were 120 community-dwelling older adults aged 65 and older with at least one chronic disease. Data were collected from elderly people who met the criteria by visiting nursing care worker training centers, senior centers, social gatherings, and home welfare centers in D, G, and S cities from May 24 to June 23, 2023, with a questionnaire consisting of lifestyle habits, social networks, wisdom and healthy aging, and general characteristics. Results: The degree of healthy aging of the subjects was 3.56 out of 5, and there were differences in the degree of healthy aging according to age (F=3.76, p=0.026), spousal relationship (t=3.11, p=0.002), education (F=9.08, p&lt;0.001), number of diseases (F=8.65, p&lt;0.001), and economic level (t=-2.45, p=0.016). The most common diseases among the subjects were hypertension, hyperlipidemia, joint diseases and diabetes mellitus. Healthy aging was highly correlated with lifestyle habits (r=0.63, p&lt;0.001), social networks (r=0.65, p&lt;0.001), and wisdom (r=0.73, p&lt;0.001). Social networks (β=0.46, p&lt;0.001) and wisdom (β=0.55, p&lt;0.001) had partial mediating effects (z=4.15, p&lt;0.001; z=5.11, p&lt;0.001) on the relationship between subjects' lifestyle habits and healthy aging. Conclusions: In order to increase the degree of healthy aging of the subjects, it is necessary to establish a mediating intervention program that manages to have a good lifestyle habits in daily life, increase social networks, and become wise.

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

Using the World Bank Global Findex Database for 91 countries in 2014, 2017, and 2021, we examine whether fintech levels influence bank performance and whether fintech’s interaction with GDP per capita causes differential effects on bank performance globally. Since fintech levels were already very high for rich countries when the World Bank started providing fintech development statistics in 2014, we estimate AbFintech by regressing fintech levels on GDP per capita by year. AbFintech is the difference between the fintech level and its fitted values. Then, using multiple regression analyses, we investigate the impact of AbFintech on bank performance worldwide, focusing on the differential effects of AbFintech and GDP levels on bank performance. We find AbFintech significantly increases bank performance, primarily in less developed countries. Specifically, AbFintech increases banks’ ROA in the least developed countries and net interest margin in the 75th percentile countries. Also, AbFintech decreases the cost-to-income ratio in the 75th percentile countries, while it increases the ratio in the most developed countries. AbFintech does not affect the ratio of noninterest income to total income, regardless of the level of economic development.

Carbazole is one of the typical heterocyclic aromatic compounds (NSO-HETs) observed in pol-luted urban atmosphere, which has become a serious environmental concern. The most im-portant atmospheric loss process of carbazole is the reaction with OH radical. The present work investigated the mechanism of OH-initiated atmospheric oxidation degradation of carbazole by using density functional theory (DFT) calculations at the M06-2X/6-311++G(3df,2p)//M06-2X/6-311+G(d,p) level. The rate constants were determined by the Rice-Ramsperger-Kassel-Marcus (RRKM) theory. The lifetime of carbazole determined by OH was compared with other typical NSO-HETs. The theoretical results show that the degradation of carbazole initiated by OH radical includes four types of reactions: OH additions to “bend” C atoms, OH additions to “benzene ring” C atoms, H abstractions from C-H bonds and the H ab-straction from N-H bond. The OH addition to C1 atom and the H abstraction from N-H bond are energetically favorable. The main oxidation products are hydroxycarbazole, dialdehyde, carba-zolequinone, carbazole-ol, hydroxy-carbazole-one and hydroperoxyl-carbazole-one. The calcu-lated overall rate constant of carbazole oxidation by OH radical is 6.52 × 10−12 cm3 molecule−1 s−1 and the atmospheric lifetime is 43.92 h under the condition of 298 K and 1 atm. The lifetime of carbazole determined by OH radical is similar with that of dibenzothiophene oxidation but longer than those of pyrrole, indole, dibenzofuran and fluorene. This work provides a better understanding of the reactivity of carbazole in the atmospheric environment, the formation of secondary organic aerosols, and the chemical degradation and removal of carbazole in the at-mospheric environment.

The addition of active seed for increasing the precipitation rate leads to the formation of fine Al(OH)3 particles that complicates separation of solid from the mother liquor. In this study, the enhanced precipitation of coarse Al(OH)3 from sodium aluminate solution using active agglomerated seed was investigated. Aluminum salt (Al2(SO4)3) were used for active agglomerated seed precipitation at the initial of the process. About 50% of precipitation rate was obtained when these agglomerates were used as a seed in the amount of 20 g L–1 at 25 °C within 10 h. The agglomerated active seed and precipitate samples were characterized using X-ray diffraction (XRD), scanning electron microscopy (SEM) and Fourier-transform infrared spectroscopy (FTIR). SEM images showed that agglomerates consist of flake-like particles that can be stick together by bayerite (β-Al(OH)3) acting as a binder. The precipitation temperature above 35 °C and the high concentration of free alkali (αk &gt; 3) lead to the agglomerates refinement that can be associated with the bayerite dissolution.

Our previous study demonstrated that mesenchymal stem/stromal cells (MSCs) induced the differentiation of myeloid-derived suppressor cells (MDSCs) in the bone marrow (BM) under inflammatory conditions. In the present study, we aimed to explore the signaling pathway in BM cells responsible for MDSC generation. RNA-seq revealed that the mitogen-activated protein kinase (MAPK) pathways, among biochemical pathways, exhibited the highest number of differentially expressed genes in BM cells with MSC coculture relative to those without. Western blot confirmed strong phosphorylation of c-Jun N-terminal kinase (JNK) in BM cells cocultured with MSCs under GM-CSF stimulation, whereas p38 kinase activation remained unaltered by MSCs. Inhibition of JNK by SP600125 significantly abolished the expression of Arg1 and Nos2, the hallmark genes of MDSCs, as well as Hif1α, a molecule mediating monocyte functional re-programming into suppressive phenotype, in MSC-cocultured BM cells, while increasing TNF-α in response to lipopolysaccharides stimulation. Furthermore, JNK inhibition markedly abrogated the effect of MSCs on the production of TGF-β1, TGF-β2 and IL-10 in BM cells. These results suggest that MSCs induce MDSC differentiation in BM during inflammation, at least in part, through the activation of the JNK MAPK signaling pathway.

Let ${\mathcal{SR}}^*$ be the class of starlike functions with real coefficients, i.e., the class of analytic functions $f$ which satisfy the condition $f(0)=0=f'(0)-1$, Re{z f'(z) / f (z)} > 0, for $z\in\mathbb{D}:=\{z\in\mathbb{C}:|z|<1 \}$ and $a_n:=f^{(n)}(0)/n!$ is real for all $n\in\mathbb{N}$. In the present paper, the sharp estimates of the third Hankel determinant $H_{3,1}$ over the class ${\mathcal{SR}}^*$ are computed.

Although wireless capsule endoscopy (WCE) detects small bowel diseases effectively, it has some limitations. For example, the reading process can be time-consuming due to the numerous images generated per case, and lesion detection accuracy may rely on the operators' skills and experiences. Hence, many researchers have recently developed deep learning-based methods to address these limitations. However, they tend to select only a portion of the images from a given WCE video and analyze each image individually. In this study, we note that more information can be extracted from the unused frames and temporal relations of sequential frames. Specifically, to increase the accuracy of lesion detection without depending on experts' frame selection skills, we suggest using whole video frames as the input to the deep-learning system. Thus, we propose a new Transformer-based neural encoder that takes the entire video as the input, exploiting the power of the Transformer to extract long-term global correlation within and between the input frames. Subsequently, we can capture the temporal context of the input frames and the attentional features within a frame. Tests on benchmark datasets of four WCE videos showed 95.1% sensitivity and 83.4% sensitivity. These results may significantly advance automated lesion detection techniques for WCE images. Our code is available at https://github.com/syupoh/VWCE-Net.git.

In this study, we used statistical models to analyze nonlinear behavior links with atmospheric teleconnections between hydrometeorological variables and Indian Ocean Dipole (IOD) mode over the East Asia (EA) region. The analysis of atmospheric teleconnections was conducted using principal component analysis and singular spectrum analysis techniques. Moreover, the nonlinear lag-time correlations between climate indices and hydrological variables were calculated using mutual information (MI) techniques. The teleconnection-based nonlinear correlation coefficients (CCs) were higher than the linear CCs in each lag time. Additionally, we documented that the IOD has a direct influence on hydro-meteorological variables, such as precipitation within the Korean Peninsula (KP). Moreover, during the warm season (June to September) the variation of hydro-meteorological variables in the KP demonstrated significantly decreasing patterns during positive IOD years and they have neutral conditions during negative IOD years in comparison with long-term normal conditions. Finally, the revealed relationship between climate indices and hydro-meteorological variables and their possible changes will allow better understanding of stakeholder decision-making regarding to manage of freshwater management over the EA region. It can also provide useful data for long-range water resources prediction, to minimize hydrological uncertainties in a changing climate.

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

This research develops the Osteoporosis Knowledge, Attitude, and Behaviors Questionnaire (OKABQ) with the intent to evaluate levels of osteoporosis knowledge, attitude and behavior change. The aims of the study were to develop and validate the OKABQ; and to establish a mediation model of the research. A quantitative, descriptive, and instrumental study was conducted in two phases: Phase I—development of the scale through Delphi Method by osteoporosis experts; Phase II—evaluation of the validity and reliability of the scale and construction of a mediation model using SmartPLS. In Phase I, the content validity index (CVI) of the questionnaire was higher than 0.96 and the inter-rater reliability (IRR) kappa was 1.00. In Phase II, exploratory factor analysis showed that two predominating factors of attitude as a mediation were addressed by the 26-item OKABQ. The indirect effect results from the estimated model indicates that attitude mediates the relationship between knowledge and behaviors (β = 0.114, t = 2.627, p < 0.001), which is positive and statistically significant. We concluded that the OKABQ is a valid measure of osteoporosis knowledge, attitude and behaviors for women with osteoporosis. These assessment results could assist healthcare providers in mitigating insufficiency on health education.

Nonhost disease resistance is the most common type of plant defense mechanism against potential pathogens. In this study, the metabolic enzyme formate dehydrogenase (FDH1) was identified to be involved in nonhost disease resistance in Nicotiana benthamiana and Arabidopsis thaliana. In Arabidopsis, AtFDH1 was highly upregulated in response to both host and nonhost bacterial pathogens. Arabidopsis Atfdh1 mutants were compromised in nonhost resistance, basal resistance, and gene-for-gene resistance. The expression patterns of salicylic acid (SA) and jasmonic acid (JA) marker genes after pathogen infections in Atfdh1 mutant indicated that SA is most likely involved in the FDH1-mediated plant defense response to both host and nonhost bacterial pathogens. Previous studies reported that FDH1 localizes to only mitochondria, or both mitochondria and chloroplasts. Our results showed that the AtFDH1 localized to mitochondria and the amount of FDH1 localized to mitochondria increased upon infection with host or nonhost pathogens. Interestingly, the subcellular localization of FDH1 was observed in both mitochondria and chloroplasts after infection with a nonhost pathogen in Arabidopsis. We speculate that FDH1 plays a role in cellular signaling networks between mitochondria and chloroplasts to produce coordinated defense responses such as SA-induced reactive oxygen species (ROS) generation and hypersensitive response (HR)-induced cell death against nonhost bacterial pathogens.

As e-commerce services and Internet technology have rapidly developed in recent years, many services and applications integrating these technologies can now be completed online. These commercial activities include online auctions, online ticketing and online payments. The client shops from the store online, andthe store delivers the goods to the client. The goods can be divided into digital products without entities, as well as actual entities. If it is a physical product, the store will deliver the package to the client through itslogistics. However, there have been many cases of switched goods purchased by clients in recent years. Earlier, some scholars proposed a security mechanism with a subliminal channel for E-cash and digital content. Only the sender and the receiver would know that the secret information was hidden in the signature. So the privacy of this subliminal message couldbe ensured. We apply this concept to the logistics environment to design secure logistics architecture with subliminal messages. The client can check the subliminal message of the received package, and know whether the package has been switched by malicious people. In addition, the proposed scheme also applies sensor technology;the client can check the GPS location, the temperature and humidity at any time during the delivery process. So intelligent logisticswouldthereby be achieved. This paper proposes an intelligent and secure package sensoring logistics system based on a subliminal channel. The proposed architecture uses the related mechanisms tosolve the problems of a logistics system, including how to achieve mutual authentication, data integrity, anti-switch package, package location and status tracing, resisting replay attacks, forward and backward secrecy, and non-repudiation issues.

The classic, chronic Philadelphia chromosome-negative (Ph-) myeloproliferative neoplasms (MPN)- mainly essential thrombocythemia (ET), polycythemia vera (PV), and myelofibrosis (MF)— represent a heterogeneous group of stem cell disorders characterized by clonal proliferation of one or more hematopoietic cell lineages with organomegaly and constitutional symptoms. Several studies have shown that the presence of chronic inflammation and a dysregulated immune system play indisputable roles in the pathogenesis of these diseases. Lately, the treatment of cancer including hematological malignancy has progressed on the agents targeting the immune system, cytokine milieu, immunomodulatory agents, and targeted immune therapy. Immune checkpoints are the molecules that regulate T cells function in the tumor microenvironment (TME). The fully unraveled primary immune checkpoints are programmed cell death-1 (PD-1)/programmed cell death ligand-1 (PD-L1), and cytotoxic T-lymphocyte antigen-4 (CTLA-4). Immune checkpoint inhibitor therapy (ICIT) is based on blocking the inhibitory pathways in T cells to promote anti-tumor immune responses and has revolutionized cancer treatment paradigms. Despite the impressive clinical success of ICIT, tumor intrinsic resistance remains a daunting challenge for oncologists leading to a low response rate in solid tumors and hematological malignancies. A phase II trial on Nivolumab for patients with Primary Myelofibrosis, post-Essential thrombocythemia myelofibrosis, or post- Polycythemia myelofibrosis has been performed (ClinicalTrials.gov Identifier: NCT02421354). This clinical trial, on the efficacy of PD-1 blockade using the monoclonal antibody Nivolumab, was prematurely terminated due to a lack of efficacy and adverse events. A multicenter, open-label, phase 2, single-arm study was conducted including pembrolizumab in patients with Dynamic International Prognostic Scoring System category of intermediate-2 or greater primary, post-essential thrombocythemia or post-polycythemia vera myelofibrosis that were ineligible for or were previously treated with Ruxolitinib. Pembrolizumab treatment was well tolerated, but there were no objective clinical responses, so the study closed after the first stage was completed. To permit more patients to benefit from immunotherapy, the focus has changed to targeting alternative novel immune checkpoints in the tumor microenvironment such as lymphocyte activation gene-3 (LAG-3), T cell immunoglobulin, and mucin domain 3 (TIM-3), V-domain immunoglobulin-containing suppressor of T-cell activation (VISTA), T cell immunoglobulin and ITIM domain (TIGIT) and human endogenous retrovirus-H long terminal repeat-associating protein 2 (HHLA2) forming the basis of next-generation ICIT. Our article aims at emphasizing and discovering the role of next-generation ICIT in MPN as targeted immunotherapy involving monoclonal antibodies, checkpoint inhibitors, or therapeutic vaccines against selected MPN epitopes that could further enhance tumor-specific immune responses. Immunotherapeutic approaches are expanding and hopefully will extend the therapeutic armamentarium in patients with myeloproliferative neoplasms. Preliminary studies from our laboratory showed over-expressed MDSC and over-expressed VISTA in MDSC, and in progenitor and immune cells directing the need for more clinical trials using next-generation ICI in the treatment of MPN.

This work reports the first nanocrystalline SnON (7.6 % Nitrogen content) n-type nanosheet Field-Effect Transistor (nFET) with transistor’s effective mobility (µeff) as high as 357 and 325 cm2/V-s at electron density (Qe) of 5×1012 cm-2 and ultra-thin body thickness (Tbody) of 7 and 5 nm, respectively. At the same Tbody and Qe, these µeff values are significantly higher than single crystalline Si, InGaAs, thin-body Si-on-Insulator (SOI), two-dimensional (2D) MoS2 and WS2. New discovery of slower µeff decay rate at high Qe than SiO2/bulk-Si universal curve was found, owing to one order of magnitude lower effective field (Eeff) by more than 10 times higher dielectric constant () in channel material, which keeps the electron wave-function away from the gate-oxide/semiconductor interface and lowers the gate-oxide surface scattering. In addition, the high µeff is also due to the overlapped large radius s-orbitals, low 0.29 mo effective mass (me*) and low polar optical phonon scattering. SnON nFETs with record-breaking µeff and quasi-2D thickness enable potential monolithic three-dimensional (3D) integrated circuit (IC) and embedded memory for 3D biological brain-mimicking structures.

With an aging population, the prevalence of geriatric diseases is increasing, especially among older individuals who live alone. This study investigates the potential of using TV viewing patterns to detect these diseases by analyzing variables such as daily average viewing time, peak viewing hours, and channel-switching behaviors. Significant correlations between TV viewing patterns and early indicators of geriatric diseases (depression, activities of daily living (ADL) performance, and cognitive function) were found. The correlations between the Korean form of the Geriatric Depression Scale (KGDS) and daily average viewing time and excessive channel switching were 0.320 and 0.308, respectively. The Korean version of the Modified Barthel Index (KMBI) showed correlations of -0.313 with daily average viewing time and -0.352 with excessive channel switching. Participants were divided into groups based on scores, and significant differences in peak viewing hours were observed among the different groups. The Korean version of the Mini-Mental State Examination (MMSE-K) groups showed significant differences at 3, 4, and 5 PM. The KGDS and KMBI groups showed significant differences at 8 PM and midnight and 1 AM and 2 AM, respectively. These findings suggest that TV viewing patterns can serve as effective early diagnostic indicators for geriatric diseases.

Hydroa vacciniforme (HV) is a rare form of photosensitivity disorders in children and is frequently associated with Epstein-Barr virus (EBV) infection, whereas HV-like lymphoproliferative disorders (HVLPD) describe a spectrum of EBV-associated T-cell or NK-cell lymphoproliferations with HV-like cutaneous manifestations, including EBV-positive HV, atypical HV, and HV-like lymphoma. Classic HV occurs in childhood with vesiculopapules on sun-exposed areas, which is usually induced by sunlight and ultraviolet irradiation, and mostly resolves by early adult life. Unlike classic HV, atypical or severe HV manifests itself as recurrent papulovesicular eruptions in sun-exposed and sun-protected areas associated occasionally with facial edema, fever, lymphadenopathy, oculomucosal lesions, gastrointestinal involvement, and hepatosplenomegaly. Notably, atypical or severe HV may progress to EBV-associated systemic T-cell or natural killer (NK)-cell lymphoma after a chronic course. Although rare in the United States and Europe, atypical or severe HV and HV-like lymphoma are predominantly reported in children from Asia and Latin America with high EBV DNA levels, low numbers of NK cells, and T cell clones in the blood. In comparison with the conservative treatment used for patients with classic HV, systemic therapy such as immunomodulatory therapy is recommended as the first-line therapy for patients with atypical or severe HV. This review aims to provide an integrated, overview of current evidence and knowledge of HV and HVLPD to elucidate the pathophysiology, practical issues, environmental factors, and the impact of EBV infection.

If an AI entity is conscious, then it deserves moral status and to have its welfare protected. Society has granted certain animals moral status and has legislation to protect animal welfare because these kinds of animals have been deemed to be sentient. This paper shows that for any entity that can be determined to be conscious, that entity deserves the same status and protection as sentient entities. The paper further develops a framework for how an AI entity's welfare can be protected, based on the Five Freedoms of Animal Welfare. The extant Five Freedoms are translated into terms more suitable for artificial entities, encompassing discomfort and harms, constraints on inherent functions, fear and distress, malfunction and degradation, and resource depletion. Each of the new Five Freedoms are justified using formalised arguments and supported using evidence from animal welfare literature. The paper concludes by presenting three formalised case studies to highlight the potential stressors conscious AI entities may face and how this ethical framework can work to protect the welfare of AI entities.