The diversity and inclusion discussion permeates many sectors of society. Within this dialogue, science and scientists are acutely aware of the value of diversity and the need for inclusion. While demographic diversity in science has received considerable recent attention, very little research and understanding exists on inclusion. Our study presents empirical data on the meaning of inclusion using a crowdsourcing approach that sought responses to the question “What does inclusion mean to you?”. The most prominent concepts were those of empathy, warmth, support, love, acceptance and curiosity; diverse perspectives; and participation. We clustered conceptual elements of inclusion into four themes: access and participation, embracing diverse perspectives, a welcome environment, and team belonging. On the basis of these data, we theorize a conceptual framework model from which inclusion may be put into practice. Our model suggests a dynamic process of inclusion operating from principal structural elements of 1) a foundation that involves place, access and participation, and space; 2) reciprocal engagement as an engine for inclusion; and 3) expression of inclusion as culture. The framework model demonstrates a means by which the practice of diversity can be more than shifts in demographic statistics, and instead promote the full expression of benefits derived when the many dimensions of diversity are truly included.

The management of shoulder instability in children and adolescents is a challenging field of orthopaedics. There are several complicating factors which originate from the variable underlying cause that is often a unique combination of traumatic factors, ligamentous laxity, and the pattern of muscle contractility. As the cause is often multifactorial, this makes interpretation of the literature difficult as nomenclature is variable. The purpose of this review is to shed light on the nuances of paediatric and adolescent shoulder instability.

Some time ago, Kobayashi et al. experimentally studied the so-called Lee-Naughton-Lebed's (LNL) angular effect in strong electric fields [K. Kobayashi, M. Saito, E. Omichi, and T. Osada, Phys. Rev. Lett. \textbf{96}, 126601 (2006)]. They found that strong electric fields split the LNL conductivity maxima in $\alpha$-(ET)$_2$-based organic conductor and hypothetically introduced the corresponding equation for conductivity. In this Letter, for the first time we suggest quantum mechanical theory of the LNL angular oscillations in moderately strong electric fields. In particular, we demonstrate that the obtained by us approximate theoretical formula coincides with the hypothetical one and well describes the above mentioned experiments.

Background: Endometriosis affects between 1% to 10% of women worldwide; it is associated with a significant burden on the woman, her relationships, productivity, mental health, family and society. Aim:To contribute to the current understanding of the impact of endometriosis on women’s lives by integrating qualitative research findings to explore the illness experiences of women living with endometriosis. Study design:Synthesis of qualitative data using Britten’s meta-ethnography.Methods:Six bibliographic databases (Medline, Embase, CINAHL, Web of Science, Scopus and PsycINFO) and Google Scholar were searched for peer-reviewed papers published in English language from inception of until August 6th 2021. Results: Fifteen studies were included in the data synthesis. The review included a total of 354 women from fourteen countries (including South Africa, Iran, England, Australia and United States of America), of age range 16-78 years. Subjects represented diverse ethnicities, cultures and native languages distributed across socioeconomic classes. Representation of all stages of endometriosis was included.Findings incorporate the following nine categories into a conceptual model: disease symptoms; health services experience; isolation and limited social participation; limited physical functioning; a coterie of emotions; sex and intimate relationships; infertility; work life and education; coping strategies and support. Diagnostic delays, persistent symptoms, healthcare costs and inadequate education to patients about the disease; all intersect into a web of struggles and incoherence for patients. Conclusion:Women with endometriosis living in various countries report similar illness experiences; although gender roles, culture and socio-economic status may act as mediating factors that shape an individual’s illness experience.

For development and successful application of any material, a clear understanding of their mechanical behavior is one of the most important things, but when it comes to nanofibers networks it become a challenge due to, their high porosity, many scales in their structure, and characteristics non-linear. Therefore, an experimental methodology in conjunction with a theoretical model that can fully consider their characteristics is still needed. In this work we proposed a model that incorporates the propagation of the elastic waves in two-phase media to determine the effective elastic modulus of electrospun membranes of PLA/gelatin given the mechanical properties of nanofibers, shape, distribution and concentration. The model was verified via laser ultrasonic testing. It was found that the values predicted for the effective modulus by the model were higher than the values obtained from experimental results. One explanation is due to the experimental density. As a result, the P-Wave velocity from the model best fit to experimental results and it has the same behavior, decrees as the concentration of gelatin in the solution. These results indicate the model and experimental methodology can assist in the dressing of nanofibers networks and electrospun materials.

The work proposes a backtesting analysis in comparison between the Lee-Carter and the Cairns-Blake-Dowd mortality models, employing Italian data. The mortality data come from the Italian National Statistics Institute (ISTAT) database and span the period 1975-2014, over which we computed back-projections evaluating the performances of the models in comparisons with real data. We propose three different backtest approaches, evaluating the goodness of short-run forecast versus medium-length ones. We find that both models were not able to capture the improving shock on the mortality observed for the male population on the analyzed period. Moreover, the results suggest that CBD forecast are reliable prevalently for ages above 75, and that LC forecast are basically more accurate for this data.

The North-Marchean Apennines (central Italy) host an extraordinary geological and geomor-phological heritage, significant for its richness, diversity, rarity, scientific interest, aesthetic ap-peal, naturalistic, cultural, and educational values. The area, which covers 600 square kilometres and includes numerous spectacular geosites, embraces 18 municipalities in the provinces of Pesaro-Urbino and Ancona. These municipalities are distributed along the ridge that includes the peaks of Mts. Strega, Catria, Acuto, Petrano, Tenetra and Nerone and covers the parallel ridge of Mts. Paganuccio-Pietralata, together with the spectacular Furlo Gorge. It is a real geological museum outdoors, which, with its continuous stratigraphic succession of 200 million years, its geosites, and a vast system of karstic caves, is distinctive for geologists all over the world. This study aims to analyse the environmental heritage of the North-Marchean Apennines through the integrated study and description of the geo-environmental aspects of 7 geosites, se-lected from a list of 44, presented here and localized. These 7 geosites were chosen as being par-ticularly significant from a scientific, naturalistic as well as aesthetic, and cultural point of view. The richness of its geological and geomorphological heritage and the great wealth of its naturalistic, historical, and cultural aspects make it an area with high educational, tourist and recreational potential.

Real-time multi-axis distributed tactile sensing is a critical capability if robots are to perform stable gripping and dexterous manipulation, as it provides crucial information about the sensor-object interface. In this paper, we present an optical-based 6-axis tactile sensor designed in a fingertip shape for robotic dexterous manipulation. The distributed sensor can precisely estimate local XYZ force and displacement at ten distinct locations, and provide global XYZ force and torque measurements. Its compact size, comparable to that of a human thumb, and minimal thickness allow seamless integration onto existing robotic fingers, eliminating the need for complex modifications to the gripper. The proposed sensor design uses a simple, low-cost fabrication method. Moreover, the optical transduction approach uses light angle and intensity sensing to infer force and displacement from deformations of individual sensing units that form the overall sensor, providing distributed 6-axis sensing. The local force precision at each sensing unit in the X, Y, and Z axes is 20.89 mN, 19.19 mN, and 43.22 mN, respectively, over an local force range of approximately ±1.5 N in X and Y and 0 to -2 N in Z. The local displacement precision in the X, Y and Z axes is 56.70 μm, 50.18 μm and 13.83 μm, respectively, over a local displacement range of ±2 mm in the XY directions and 0 to -1.5mm in Z (i.e., compression). Additionally, the sensor can measure global torques, Tx, Ty and Tz, with a precision of of 1.90 N-mm, 1.54 N-mm and 1.26 N-mm, respectively. The fabricated design is showcased by integrating it with an OnRobot RG2 gripper and illustrating real-time measurements during in simple demonstration task which generate changing global forces and torques.

Research on alternatives to rectal thermometry in canine and feline patients has focused on equipment and measurement location but not procedure duration. In a cross-over designed clinical scenario, we evaluated the time prior to and after (Pre-TempT and Post-TempT) rectal and axillary thermometry in canine (n = 114) and feline (n = 72) patients. Equipment duration was controlled for to determine a presumptive total time (TTime) associated with each thermometry method. Pre-TempT and TTime was significantly shorter in axillary thermometry trials for both canine and feline pets (P < 0.001). There was no difference in Post-TempT between thermometry methods in canine patients (P = 0.887) however, the Post-TempT was longer in felines after axillary thermometry (P = 0.004). Reductions in Pre-TempT and TTime were not significant in Scottish Fold breed cats and within the feline rectal trials, the TTime of domestic-long hair breeds was significantly longer than domestic-short hair breeds (P = 0.019). No other tested parameter played a significant role in these results. Axillary thermometry was faster than rectal thermometry in both canine and felines pets due primarily to the time associated with animal approach and restraint (Pre-TempT). These results have implications when optimizing clinic workflow, appointment durations and patient handling time.

Electrochemical Impedance Spectroscopy techniques were applied in this work to 9 lead-acid battery prototypes fabricated industrially, divided on three type/technology packages. Frequency dependent impedance changes were interpreted during successive charge/discharge cycles on two distinct stages: 1) immediately after fabrication; and 2) after a controlled aging procedure to 50% Depth of Discharge, following industrial standards. By investigating their State of Health behaviour vs electrical response, three methods were employed, namely the (Q-Q0) total charge analysis, the decay values of Constant Phase Element in the equivalent Randles circuits, and the resonance frequency of the circuit. A direct correlation has been found for prediction of the best performant batteries in each package, thus allowing a qualitative analysis capable to provide the decay of the battery State of Health. We emphasized which parameters are directly connected with their lifetime performance in both stages, and by consequence, which type/technology battery prototype emphasize the best performance. Based on this methodology, the industrial producers can further establish the quality of the novel batteries in terms of performance vs lifespan, allowing them to validate the novel technological innovations implemented in the current prototypes.

This study investigated whether reciprocal collaborative pedagogy significantly impacts Indonesian electrical engineering polytechnic students in reducing reading anxiety and improving self-efficacy in ESP reading comprehension skills. Fifty Polytechnic students were equally assigned to two groups. Control groups learned in the traditional reciprocal teaching method individually. Experimental group engaged in reciprocal collaborative pedagogy. Each group received a 6-week reading strategy training. E-learning platforms were used in this study as a complementary tool to distribute ESP reading materials, announcements, and the experiment details being taught. The quantitative and qualitative results demonstrated that the tasks in reciprocal collaborative pedagogy positively affects Indonesian electrical engineering polytechnic students' learning experience and outcomes. This pedagogy promotes a productive learning environment through peer interaction, active engagement, and peer group discussions of the whole learning activities, reducing feelings of anxiety and building confidence in ESP-specialized text.

This research investigates the economic resilience of small and medium enterprises (SMEs) during financial crises, focusing on the factors that enable these businesses to survive and recover from economic downturns. Employing a qualitative methodology, the study examines various aspects of SME operations, including financial management, innovation, leadership, government support, geographical location, social capital, and contingency planning. The findings reveal that effective financial management—encompassing cash flow management, debt restructuring, and diversified funding sources—is crucial for maintaining stability during financial crises. Innovation and adaptability also play significant roles, with SMEs that embraced new technologies and market strategies demonstrating greater resilience. Leadership emerged as a critical factor, with leaders who communicated effectively and managed stress contributing to their organization's ability to navigate crises. Government support provided essential relief, although its impact varied depending on accessibility and timeliness. Geographical location influenced resilience, with urban SMEs having better access to resources, while rural SMEs benefited from strong community networks. Social capital, including relationships with suppliers and customers, was vital for providing stability and support. Contingency planning and risk management were identified as essential for preparing for and responding to disruptions. The research highlights that resilience is a multifaceted attribute resulting from the interplay of financial prudence, adaptability, effective leadership, supportive policies, geographic factors, and strong social networks. These insights offer valuable lessons for SME owners, policymakers, and support organizations, emphasizing the need for a comprehensive approach to building and sustaining resilience in the face of economic challenges.

The ancient Duchy of Urbino (Marche and Emilia-Romagna Regions, Italy) is known for its spectacular landscapes linked to a unique geological history. This area owns an unexpected cultural resource, which concerns using its landscapes in art. Some great Renaissance artists, including Piero della Francesca, Raphael, and Leonardo, were so impressed by the landscapes that they reproduced them in their most famous paintings. This paper summarizes research concerned with their identification, employing a multidisciplinary method that has enabled the recognition of many morphologies. This contribution provides the scientific community with information on the methodology and regional and national projects developed in this area to enhance its cultural landscapes. Starting from the geological description of the territory, the research focuses on famous works by three great Renaissance artists, providing evidence and morphological details related to the recognition of places: “Nativity” by Piero della Francesca, “Madonna Litta” by Leonardo da Vinci and “Knight’s Dream” by Raphael. Finally, it is proposed to make these landscapes a timeless resource through their inclusion in UNESCO’s cultural heritage. This contribution is addressed to representatives of the administration, conservation, and enhancement of artistic and landscape heritage to stimulate new perspectives for research, education, and tourism within the cultural heritage of this area.

Depressive disorder in childhood and adolescence is a highly prevalent mood disorder that tends to recur throughout life. Untreated mood disorders can adversely impact a patient's quality of life and cause socioeconomic loss. Thus, an accurate diagnosis and appropriate treatment is crucial. However, until now, diagnoses and treatments are conducted according to clinical symptoms. Objective and biological validation are lacking. This may result in a poor outcome for patients with depressive disorder. Research has been conducted to identify the biomarkers that are related to depressive disorder. Cumulative evidence has revealed that certain immunologic biomarkers in-cluding brain-derived neurotrophic factor (BDNF) and cytokines, gastrointestinal biomarkers, hormones, oxidative stress, and certain hypothalamus-pituitary axis biomarkers are associated with depressive disorder. This article reviews the biomarkers related to the diagnosis and treatment of pediatric depressive disorders. To date, clinical biomarker tests are not yet available for diagnosis or for the prediction of treatment prognosis. However, cytokines such as Interleukin-2, interfer-on-gamma, tumor necrosis factor-alpha, and BDNF have shown significant results in previous studies of pediatric depressive disorder. These biomarkers have the potential to be used for diagnosis, prognostic assessment, and group screening for those at high risk.

As air traffic demand grows, robust, data-driven anomaly detection methods are required to ensure that aviation systems become safer and more efficient. The terminal airspace is identified as the most critical airspace for both individual flight-level and system-level safety and efficiency. As such, developing data-driven anomaly detection methods to analyze terminal airspace operations is paramount. With the expansion of ADS-B technology, open-source flight tracking data has become more readily available to enable larger-scale analyses of aircraft operations. This paper makes a distinction between spatial metrics in ADS-B trajectory data and energy metrics derived from ADS-B trajectory data. Motivated by the limited number of approaches that simultaneously consider both spatial and energy metrics, this paper introduces the concepts of spatial anomalies and energy anomalies. In particular, it proposes a novel, unified framework for detection of spatial and energy anomalies in ADS-B trajectory data (and associated derived metrics). The framework consists of three main parts - a data processing procedure, a spatial anomaly detection method, and an energy anomaly detection method. The framework is demonstrated utilizing four months of ADS-B trajectory data associated with arrivals at San Francisco International Airport, and the relationship between the spatial and energy anomalies in this terminal airspace is explored. The results that stem from the implementation of this framework indicate that if an aircraft is spatially not conforming to an identified set of air traffic flows representing standard spatial operations, then this aircraft is more likely to experience non-conformance to standard operations in its energy metrics. Aviation operators, such as air traffic controllers, may benefit from this observation, as it may factor into decision-making in instances where there is the potential to instruct an aircraft to spatially deviate from standard operations. Additionally, this research revealed underlying differences between trajectories that are spatially nominal yet energy-anomalous and those trajectories that are spatially anomalous and energy-anomalous. Focusing solely on energy anomaly detection does not provide insight into potential spatial-related decisions that may have been made to result in off-nominal energy behavior.

(1) Background: There are links between tension-type headache and/or migraine with dysfunctions of the cervical and masticatory muscles and with psychosocial factors. The study aims to highlight the connections between primary headaches, bruxism and psychosocial issues, the effectiveness of a multidisciplinary approach in decreasing the intensity and frequency of the headache episodes and bruxism. (2) Methods: 67 patients with primary headache and bruxism were divided into two equal groups. The subjects attended manual therapy sessions twice a week and a weekly counselling session for three months. (3) Results: an overall comparison before and after three months show a significant decrease of the qualitative variables (tension-type headache, migraine, awake bruxism, limited jaw opening, anxiety and stress) after 3 months. Comparing the efficiency of the procedures after 3 months between the two groups, awake bruxism and perceived stress are significantly different. (4) Conclusions: Although the differences are not radical when comparing MT with MT+C at three months, the patients who received either manual therapy or this treatment combination showed an improvement in pain relief, in the frequency and complexity of their symptoms, a reduction in functional disability and an overall improvement of the quality of their lives after three months of treatment.

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

This study proposes and validates a novel combustion control system for Oil-Fired Boilers aimed at reducing air pollutant emissions through flame image prediction. The proposed system is easily applicable to existing ships. Traditional proportional combustion control systems supply fuel and air at fixed ratios according to the set steam load, without considering the emission of air pollutants. To address this, a stable and immediate control system is proposed, which adjusts the air supply to modify the combustion state. The combustion control system utilizes oxygen concentration predictions from flame images via SEF+SVM as control inputs, and applies Internal Model Control (IMC)-based Proportional-Integral (PI) control for real-time combustion control. Due to the complexity of modeling the image-based system, IMC parameter tuning through experimentation is essential for achieving effective control performance. Experiments conducted on a 3000 kg/h marine oil-fired boiler in actual operation optimized the controller parameters for stability and responsiveness, and validated their effectiveness. The results demonstrate the potential of the proposed system to improve combustion efficiency and reduce emissions of air pollutants. This study provides a feasible and effective solution for enhancing the environmental performance of marine oil-fired boilers. Given its ease of application to existing ships, it is expected to contribute to sustainable air pollution reduction across the maritime environment.

The exploration and understanding of sentiments and emotions through textual analysis are foundational to advancements in natural language processing (NLP). While sentiment analysis, which involves discerning the polarity of text, has been extensively explored, the nuanced detection of complex emotions within textual content is still an emerging area of study. In this paper, we introduce EmoLeverage, a model leveraging Transformer architecture and enhanced with a novel Fusion Adapter module. This model aims to deepen emotion detection capabilities by drawing insights from fundamental sentiment analysis tasks, focusing exclusively on textual data. EmoLeverage sets a new standard in the field by demonstrating that deep, nuanced understanding of emotions is achievable through text alone, challenging and surpassing existing methodologies in emotion identification on key datasets. This is a significant step forward, considering the complexity of human emotions and the subtleties involved in their expression through language. By concentrating on textual input, EmoLeverage offers a promising avenue for applications where audio or visual data is not available, highlighting the versatility and potential of text-based emotional analysis. Our approach illustrates the untapped potential of leveraging sophisticated NLP techniques to enhance the detection and comprehension of a wide array of emotions from text. The success of EmoLeverage in outperforming conventional models in emotion recognition tasks underscores the model's effectiveness in parsing and understanding the intricate expressions of human emotions through linguistic cues alone. This achievement paves the way for more accurate, efficient, and nuanced emotion detection tools, potentially transforming various sectors by providing deeper insights into human emotional states through text.

This paper offers a comprehensive examination of the process involved in developing and automating supervised end-to-end machine learning workflows for forecasting and classification purposes. It offers a complete overview of the components (i.e. feature engineering, model selection, etc), principles (i.e. bias-variance decomposition, model complexity, overfitting, model sensitivity to feature assumptions and scaling, output interpretability, etc), models (i.e. neural networks, regression models, etc), methods (i.e. Cross-Validation, data augmentation, etc), metrics (i.e. Mean Squared Error, F1-score, etc) and tools that rule most supervised learning applications with numerical and categorical data, as well as their integration, automation, and deployment. The end goal and contribution of this paper is the education and guidance of the non-AI expert academic community over complete and rigorous machine learning pipelines and data science practices, from problem scoping to design and state-of-the-art automation tools, including basic principles and reasoning in the choice of methods. The paper delves into the critical stages of supervised machine learning workflow development, many of which are often omitted by researchers due to brevity, and covers foundational concepts essential for understanding and optimizing a functional machine learning workflow, thereby offering a holistic view of task-specific application development for applied researchers who are not AI experts.

The United States is plagued with the highest rates of preventable metabolic diseases it has ever seen, and while poor nutrition is increasingly recognized as a critical contributing factor, good nutrition has been shown to be a potent factor in prevention and management of these illnesses. Notably, nutrition is inextricably intertwined with farming practices and the stewardship of our environment – particularly its soil. In this proposal, we propose a method to expose medical students to basic agricultural and environmental knowledge regarding the production of food, as well as educate them in practical nutrition education within the interactive, case-based, and longitudinal preclinical curriculum at Case Western Reserve University School of Medicine (CWRU SOM). We propose a two-part approach; first: integrating relevant topics in nutrition, culinary medicine, and farming practices into the preclinical blocks through Official Learning Objectives, and second: an optional 8-week, zero credit elective for students interested in pursuing a deeper understanding of these topics. Through these interventions, we believe courses like this will support a generation of physicians able to understand health from soil to plate with a consideration for the environment in addition to exemplifying healthful lifestyles themselves. We believe these kinds of future physicians will be the most effective in treating (and ideally reversing) the chronic disease epidemic.

The livestock sector can be a major contributor to the mitigation of greenhouse (GHG) emissions. Within the sector, beef production produces the largest proportion of the livestock sector’s direct emissions. The objective of this study was to assess the on-farm GHG emissions in semi-arid rangelands in Argentina and to identify the relationships between emissions and current farm management practices. A survey recorded detailed information on farm management and characteristics. Assessments of GHG emissions were based on the IPCC Tier 2 protocols [1]. The relationships between farm management and GHG emissions were identified using General Linear Models. Cluster analysis was used to identify groups of farms that differed from others in emissions and farm characteristics. Emissions per product sold were low on farms that had improved livestock care management, rotational grazing, received technical advice, and had high animal and land productivities. Emissions per hectare of farmland were low on farms that had low stocking rates, low number of grazing paddocks, little or no land dedicated to improved pastures and forage crops, and low land productivity. Our results suggest that the implementation of realistic, relatively easy-to-adopt farming management practices has considerable potential for mitigating GHG emissions in semi-arid rangelands of central Argentina.

In this work, we investigate by ab initio calculations and optical experiments the sensitiv- ity of graphene quantum dots in their use as devices to measure the presence, and concentration, of heavy metals in water. We demonstrate that the quenching or enhancement in the optical response (absorption, emission) depends on the metallic ion considered. In particular, two test cases of opposite behaviour are considered: Cd 2+ , where we observe an increase in the optical response for increasing concentration, and Pb 2 whose emission spectra are quenched along the concentration rise. We envisage that quantum dots of graphene may be routinely used as cheap detectors to measure the degree of poisoning ions in water

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

Abstract Increasing awareness of the potential health risks associated with microplastics (MPs) presence in the environment has led to significant rise in research focused on these particles over the past few years. This review focuses on research on MPs presence and spread, pathways of exposure and toxicological effects on human health and legal framework related to MP challenges. Several research projects have aimed to assess their potential harm to human health. Toxicological effects have been noticed at high concentrations of MPs, specifically polystyrene, the most widespread typical MP, but only short-term effects have been mostly studied. Significant quantities of consumed MP have been discovered to have diverse detrimental effects, posing a threat to human welfare. The exact concentrations of microplastics that are inhaled and swallowed and then build up in the human body are still not known. Further investigation is necessary to evaluate the impact of MP contamination at minimal concentrations and for prolonged durations.

There are many species of endemic plants from Mexico, without food or commercial use, but with different applications in traditional medicine and valuable for their content of secondary metabolites. In this sense, we found two species of Cucurbitacea family plants natives of southeast and gulf of México, with traditionally use how soap and laundry agent, control of some pests, and it has also been used how infusion for the treatment of different types of dermatitis and stomachache. In the present work, we evaluate the antiproliferative activity in vitro, of six crude organic extracts, tested against six human tumor cell lines, A549 (lung), HBL-100 (breast), HeLa (cervix), SW1573 (lung), T-47D (breast) and WiDr (colon), the results indicated that at least three extracts from both species presents an interesting antiproliferative activity on five tumor cell lines.

With the increasing use of data-driven modeling methods new approaches to complex problems in the field of wind energy can be addressed. Topics reviewed through literature include wake modeling, performance monitoring and controls applications, condition monitoring and fault detection, and other data-driven research. Literature shows the advantages of data-driven methods reduce computational expense or complexity, particularly in the cases of wake modeling and controls, as well as various data-driven methodologies’ aptitude for predictive modeling and classification, as in the cases of fault detection and diagnosis. Significant work exists for fault detection while less work is found for controls applications. A methodology for creating data-driven wind turbine models for arbitrary performance parameters is proposed. Results are presented utilizing the methodology to create wind turbine models relating active adaptive twist to steady-state rotor thrust as a performance parameter of interest. Resulting models are evaluated by comparing root-mean-square-error (RMSE) on both the training and validation data sets, with Gaussian Process Regression (GPR), deemed an accurate model for this application. The resulting model undergoes particle swarm optimization to determine the optimal aerostructure twist shape at a given wind speed with respect to the modeled performance parameter, aerodynamic thrust load. The optimization process shows an improvement of 3.15% in thrust loading for the 10 MW reference turbine, and 2.66% for the 15 MW reference turbine.

This article presents a unique set of voltage and current data from a public building and acquired using a hybrid measurement solution that combines Python and Grafana. The transversal purpose consists of contributing to the community with a vision of the quality of the supply more oriented to the monitoring of the state of the network, providing a more realistic vision, which allows a better understanding, and the adoption of the best decisions to achieve the efficient energy management and thus optimize the operation and maintenance of power systems. The work focuses on higher order statistical estimators that, combined with exploratory data analysis techniques, improve the characterization of the shape of the stress signal. These techniques and data, together with the acquisition and monitoring system, present a unique combination in the line of low-cost measurement solutions. It also incorporates the underlying benefit of the contribution to industrial benchmarking. The paper also includes a computational comparison between Python and LabVIEW to elicit the performance of the measurement solution.

Background: Underreporting of Visceral Leishmaniasis (VL) in India remains a problem to public health controls. Effective and reliable surveillance systems are critical for monitoring disease outbreaks and public health control programs. However, in India, government surveillance systems are affected by levels of scarcity in resources and therefore, uncertainty surrounds the true incidence of asymptomatic and clinical cases, affecting morbidity and mortality rates. The State of Bihar alone contributes up to the 40\% of the worldwide VL cases. The inefficiency of surveillance systems occurs because of multiple reasons including delay in seeking health care, accessing non-authentic health care clinics, and existence of significant asymptomatic self healing infectious cases. This results in a failure of the system to adequately report true transmission rates and number of symptomatic cases that have sought medical advice (thus, high underreporting of cases). Objectives and Methods: There are several methods to estimate the extent of underreporting in the surveillance system. In this research, we use a mathematical dynamic model and two different types of data sets, namely, monthly incidence for 2003-2005 and yearly incidence from 2006-2012 from the Bihar's 21 most VL affected districts out of its 38 districts. The goals of the study are to estimate critical metrics to measure level of transmission and to evaluate the estimation process between the two data sets and 21 districts. In particularly, our focus is on (i) estimating infection transmission potential, underreporting level in incidence and proportion of self-healing cases, (ii) quantifying reproduction number of the$R_0$, and (iii) comparing underreporting incidence levels and proportion of self-healing cases between the two periods 2003-2005 and 2006-2012 and between 21 districts. Results: Our research suggests that the number of asymptomatic individuals in the population who eventually self-heal may have a significant effect on the dynamics of VL spread. The estimated mean self-healing proportion (out of all infected) is found to be $\sim 0.6$ with only 7 out of 21 affected districts having self-healing proportion less than $0.5$ for both data sets. The estimated mean underreporting level is at least $64$\% for the state of Bihar. The estimates of the basic reproduction numbers obtained are similar in magnitude for most of the districts, being in the range of (0.88, 2.79) and (0.98, 1.01) for 2003-2005 and 2006-2012, respectively. Conclusions: The estimates for the two types (monthly and yearly) of temporal data suggest that monthly data are better for estimation if less number of data points are available, however, in general, using such data set results in larger variances in parameters as compared to estimates obtained through aggregated yearly data. Estimated values of transmission related metrics are lower than those obtained from earlier analyses in the literature, and the implications of this for VL control are discussed. The spatial heterogeneity in these control metrics increases the risk of epidemics and makes the control strategies more complex.

Epithelial ovarian cancer is an aggressive disease of the female reproductive system and a leading cause of cancer death in women. Standard of care includes surgery and platinum-based chemotherapy yet patients continue to experience a high rate of recurrence and metastasis. Hyperthermic intraperitoneal chemotherapy (HIPEC) treatment in highly selective patients extends overall survival by nearly 12 months. The clinical studies are highly supportive of the use of HIPEC in the treatment of ovarian cancer though the therapeutic approach is limited to academic medical centers. The mechanism underlying HIPEC benefit remains unknown. The efficacy of HIPEC therapy is impacted by several procedural and patient/tumor factors including the timing of surgery, platinum sensitivity, and molecular profiling such as homologous recombination deficiency. The present review aims to provide insight into the mechanistic benefit of HIPEC treatment with a focus on how hyperthermia activates the immune response, induces DNA damage and impairs DNA damage repair pathways, and has a synergistic effect with chemotherapy, with the ultimate outcome of increasing chemosensitivity. Identifying the points of fragility unmasked by HIPEC may provide the key pathways that could be the basis of new therapeutic strategies for ovarian cancer patients.

Sperm during the freezing and thawing process is damaged by oxidative stress. Thus, its antioxidant scavenger is essential for sperm survival and death in frozen-thawed semen. We used melatonin and silymarin in experiments. Our study aimed to identify the effect of melatonin and silymarin on the motility and viability of sperm, reactive oxygen species (ROS), and nitric oxide (NO) production in frozen-thawed boar semen. Melatonin and silymarin were treated alone and co-treated in the fresh boar semen. Boar semen was collected using the gloved-hand method from ten crossbred pigs, and the age of the experimental ten male pigs was 28.7 ± 3.2 months. We evaluated sperm viability using SYBR-14 and PI kit, and ROS and NO production were detected by DCF-DA and DAF-2, respectively. The sperm motility was not significantly different between non-treatment and treatment. ROS and NO production in frozen-thawed sperm were decreased by melatonin and silymarin (P < 0.05). Moreover, silymarin significantly reduced NO production more than melatonin (P < 0.05). Melatonin (46.37 ± 1.10) and silymarin (46.13 ± 0.80) enhanced the viability of sperm (P < 0.05). We suggest that melatonin and silymarin are essential antioxidants in semen cryopreservation for protecting sperm damage and maintaining sperm viability. Melatonin and silymarin may be useful antioxidants in freezing boar sperm.

This research investigates the potential application of generative language models, especially ChatGPT, in aviation safety analysis as a means to enhance the efficiency of safety analyses and accelerate the time it takes to process incident reports. In particular, ChatGPT was leveraged to generate incident synopses from narratives, which were subsequently compared with ground truth synopses from the Aviation Safety Reporting System (ASRS) dataset. The comparison was facilitated by using embeddings from Large Language Models (LLMs), with aeroBERT demonstrating the highest similarity due to its aerospace-specific fine-tuning. A positive correlation was observed between synopsis length and their cosine similarity. In a subsequent phase, human factor issues involved in incidents as identified by ChatGPT were compared to human factor issues identified by safety analysts. A concurrence rate of 61% was found, with ChatGPT demonstrating a cautious approach towards attributing human factor issues. Finally, the model was used to attribute incidents to relevant parties. As no dedicated ground truth column existed for this task, a manual evaluation was conducted. ChatGPT attributed the majority of incidents to the Flight Crew, ATC, Ground Personnel, and Maintenance. This study opens new avenues for leveraging AI in aviation safety analysis.

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

Although sarcopenia is known to be a risk factor for non-alcoholic fatty liver disease (NAFLD), whether NAFLD is a risk factor for the development of sarcopenia is not clear. We investigated bidirectional relationships between NAFLD and low skeletal muscle mass index (LSMI) using three different datasets. Participants were classified into LSMI and normal groups. LSMI was defined as a body mass index (BMI)-adjusted appendicular skeletal muscle mass &lt;0.789 in men and &lt;0.512 in women or as the sex-specific lowest quintile of BMI-adjusted total skeletal muscle mass. NAFLD was determined according to NAFLD liver fat score or abdominal ultrasonography. The NAFLD groups showed a higher hazard ratios (HRs) with 95% confidence intervals (CIs) for LSMI than the normal groups (HRs=1.213, 95% CIs=1.050–1.402). The LSMI groups also showed a higher HRs with 95% CIs for NAFLD than normal groups (HRs=1.564, 95% CIs=1.378–1.775). Participants with NAFLD had consistently less skeletal muscle mass over 12 years of follow-up. In conclusion, LSMI and NAFLD showed a bidirectional relationship. Maintaining muscle mass should be emphasized in the management of NAFLD.

This paper addresses the analysis for the nonlinear vibration response of a rectangular tube with a flexible end and non-rigid acoustic boundaries. This is a further work of the linear structural acoustic problem in a well-known acoustic book. In fact, the acoustic boundaries of an enclosed space sometimes are non-rigid and the structural vibration responses are nonlinear. These two points are the focuses of this paper. The multi-level residue harmonic balance method is applied to this nonlinear structural acoustic problem. The results obtained from the multi-level residue harmonic balance method and numerical method are generally in good agreement. The effects of excitation magnitude, tube length, and phase shift parameter etc. are examined.

Background Patients with severe dysphagia are usually fed using a nasogastric tube (NGT). Many patients who receive long-term NGT feeding are unable to obtain sufficient nutrients orally immediately after NGT removal. Thus, a transitional period involving oral diet training is required to transition from NGT feeding to exclusive oral feeding. We aimed to investigate the therapeutic effect of oral diet training in indwelling NGT patients with prolonged dysphagia. Methods A total of 175 patients who were fed using an NGT for more than 4 weeks were enrolled. Their swallowing function was evaluated by a videofluoroscopic swallowing study (VFSS). During the VFSS, patients received thick and thin barium while the NGT was insulted. Then, the patients underwent a VFSS without an NGT thirty minutes after NGT removal. If a patient had no aspiration with NGT inserted during the VFSS, oral diet training combined with NGT feeding was recommended. Results Of the 49 indwelling NGT patients who were recommended to receive oral diet training, 39 (79.6%) transitioned to exclusive oral feeding. A transition period of 2-8 weeks was required for them to achieve full oral feeding. Patients who were eligible for oral feeding trials showed no significant aspiration during the VFSS with an NGT inserted and had sufficient cough function. Patients who required prolonged NGT feeding and who could not complete oral trials showed significant aspiration during the VFSS when an NGT was inserted. Conclusion This study demonstrated that oral diet training combined with NGT feeding was safe in patients with prolonged dysphagia who had sufficient cough function and no aspiration during VFSS. We suggest that if the patient is a proper candidate for NGT removal, direct oral feeding training with an NGT inserted could be a useful therapeutic strategy during the transitional period from long-term NGT feeding to successful oral feeding.

Magnetic Particle Imaging (MPI) is a new imaging modality that sensitively and specifically detects superparamagnetic iron oxide nanoparticles (SPIONs). Many labs have been developing cellular magnetic resonance imaging (MRI) tools using both SPIONs and fluorine-19 (19F)-based contrast agents for numerous important applications, including tracking of immune and stem cells used for cellular therapies. SPION-based MRI cell tracking has very high sensitivity, but low specificity. SPIONs produce negative contrast in MRI, or signal voids. SPIO is not directly detected by MRI, but indirectly through its relaxation effects on protons, therefore, it is not possible to reliably quantify the local tissue concentration of SPION particles and cell number cannot be determined. 19F based cell tracking uses perfluorocarbons (PFC) to label cells. The number of 19F atoms can be directly measured from 19F MR images and related to cell number. 19F MRI has high specificity, but low sensitivity. MPI cell tracking displays great potential for overcoming the challenges of MRI-based cell tracking allowing for both high cellular sensitivity and high specificity and quantification of SPIO labeled cell number. In this paper we describe nanoparticle and MPI system factors that influence MPI sensitivity and resolution, quantification methods and give our perspective on testing and applying MPI for cell tracking.

Radiator reliability is crucial in environments characterized by high temperatures and friction, where prompt interventions are often required to prevent system failures. This study introduces a proactive approach to radiator fault diagnosis, leveraging the integration of Gaussian Mixture Model (GMM) and Long-Short Term Memory (LSTM) autoencoders. Vibration signals from radiators were systematically collected through randomized durability vibration bench tests, resulting in four operating states—two normal, one unknown, and one faulty. Time-domain statistical features of these signals were extracted and subjected to Principal Component Analysis (PCA) to facilitate efficient data interpretation. Subsequently, this study discusses the comparative effectiveness of GMM and LSTM in fault detection. GMMs are deployed for initial fault classification, leveraging their clustering capabilities, while LSTM autoencoders excel in capturing time-dependent sequences, facilitating advanced anomaly detection for previously unencountered faults. This alignment offers a potent and adaptable solution for radiator fault diagnosis, particularly in challenging high-temperature or high-friction environments. Consequently, the proposed methodology not only provides a robust framework for early-stage fault diagnosis but also effectively balances diagnostic capabilities during operation. Additionally, this study presents the foundation for advancing reliability life assessment in accelerated life testing, achieved through dynamic threshold adjustments using both the absolute log-likelihood distribution of the GMM and the reconstruction error distribution of the LSTM autoencoder model.

Many drastic actions are taken by cocaine users for the sake of experiencing high dopamine levels, which depends on iron for its synthesis. Dopamine depletion and iron deficiency are also involved in the symptoms of restless leg syndrome (RLS). The intersecting biochemical pathways of cocaine use, iron deficiency, and RLS have not been adequately investigated. This case report reveals the successful treatment of a patient with these conditions. A 63-year-old male with a history of cocaine use disorder, insomnia, and RLS sought emergency care for suicidality. Upon admission, he was also found to be iron-deficient. He revealed that his RLS worsened when he attempted to abstain from cocaine. He also used alcohol to sustain the effects of cocaine when the cost of cocaine was too high. During hospitalization, his mood, cravings, and RLS were resolved with adjunctive iron supplementation as well as 300 mg of Wellbutrin. If iron-deficient, replenishment of adequate dopaminergic receptor density and function via supplementation may play an essential role in the prevention of cocaine use and cessation of cocaine withdrawal. Further research is warranted to validate these findings and understand the implications of iron supplementation in addiction medicine.

Requirements are predominantly written in Natural Language (NL), which makes them accessible to stakeholders with varying degrees of experience, as compared to a model-based language which requires special training. However, despite its benefits, NL can introduce ambiguities and inconsistencies in requirements, which may eventually result in system quality degradation and system failure altogether. The system complexity that characterizes current systems warrants an integrated and comprehensive approach to system design and development. This need has brought about a paradigm shift towards Model-Based Systems Engineering (MBSE) approaches to system design and a departure from traditional document-centric methods. While, MBSE shows great promise, the ambiguities and inconsistencies present in NL requirements hinder their conversion to models directly. The field of Natural Language Processing (NLP) has demonstrated great potential in facilitating the conversion of NL requirements into a semi-machine-readable format that enables their standardization and use in a model-based environment. A first step towards standardizing requirements consists of classifying them according to the ``type'' (design, functional, performance, etc.) they represent. To that end, a language model capable of classifying requirements needs to be fine-tuned on labeled aerospace requirements. This paper presents the development of an annotated aerospace requirements corpus and its use to fine-tune BERT$_\text{BASE-UNCASED}$ to obtain aeroBERT-Classifier: a new language model for classifying aerospace requirements into design, functional, or performance requirements. A comparison between aeroBERT-Classifier and bart-large-mnli (zero-shot text classification) showcased the superior performance of aeroBERT-Classifier on classifying aerospace requirements despite being fine-tuned on a small labeled dataset.

The cooperation between humans and robots is becoming increasingly important in our society. Consequently, there is a growing interest in the development of models that can enhance the interaction between humans and robots. A key challenge in the Human-Robot Interaction (HRI) field is to provide robots with cognitive and affective capabilities, developing architectures that let them establish empathetic relationships with users. Several models have been proposed in recent years to solve this open-challenge. This work provides a survey of the most relevant attempts/works. In details, it offers an overview of the architectures present in literature focusing on three specific aspects of HRI: the development of adaptive behavioural models, the design of cognitive architectures, and the ability to establish empathy with the user. The research was conducted within two databases: Scopus and Web of Science. Accurate exclusion criteria were applied to screen the 1007 articles found (at the end 30 articles were selected). For each work, an evaluation of the model is made. Pros and cons of each work are detailed by analysing the aspects that can be improved so that an enjoyable interaction between robots and users can be established.

Effective teamwork is essential to the success of sport and athletic organizations. Interprofessional Collaboration (IPC) and team-based care has also been identified as a priority for health and social care organizations.(World Health Organization, 2010) The Interprofessional Education Collaborative (IPEC) Core Competencies of (1) Values and Ethics; (2) Roles and Responsibilities; (3) Communication; and (4) Teams and Teamwork provide a guiding framework for IPC. (Interprofessional Education Collaborative, 2023). Student-athlete well-being is a key objective for individuals working with or for university athletic departments, with high levels of well-being being correlated with sport, academic, and personal improvements (Navarro et al., 2020). Due to the multifaceted factors that influence student-athlete well-being (e.g., cultural factors, coaches, academic pressure, family stress, etc.), there is an increasing need for an interdisciplinary/interprofessional approach to well-being (Lemelin et al., 2022, Navarro et al., 2020; Ulrich et al., 2022) However, significant barriers exist in implementing IPC into university athletic departments and little research exists on how to overcome roadblocks to integrating IPC in university athletic departments for enhancing student-athlete wellness. This paper will describe how a university athletic department used a team approach to enhance student-athlete health and well-being. The Interprofessional Wellness Team (IWT) included a clinical sport psychology doctoral student, a licensed mental health professional, athletic trainer, and sport dietitian. A case vignette is used to demonstrate how IPEC core competencies are operationalized by the team to address athlete health and well-being through IPC. Recommendations on the further implementation of IPC centered around student-athlete well-being will be provided.

A multiscale model that enables quantitative understanding and prediction of the size effect on scattering properties of micro- and nanostructures is crucial for the design of LED surface textures optimized for high light extraction efficiency (LEE). In this paper, a hybrid process for combining full-wave finite-difference time-domain simulation and a ray-tracing technique based on a bidirectional scattering distribution function model is proposed. We apply this method to study the influence of different pattern sizes of a patterned sapphire substrate on GaN-based LED light extraction from the microscale to the nanoscale. The results show that near-wavelength–scaled patterns with strong diffraction are not expected to enhance LEE. By contrast, microscaled patterns with optical diffusion behavior have the highest LEE at a specific aspect ratio, and subwavelength-scaled patterns that have antireflection properties show marked enhancement of LEE for a wide range of aspect ratios.

Several types of guided bone regeneration materials are available with various properties and clinical indications. Among them, dentin-derived matrix from extracted teeth is an excellent alternative to traditional graft materials, such as allografts and xenografts. Different clinical preparation protocols exist: block form versus powder form, demineralized versus non-demineralized form. Out of these methods, demineralization protocols for dentin-derived matrix from extracted teeth have been noted for a wide range of successful clinical outcomes. The purpose of this animal study was to find out the most effective method of demineralizing dentin-derived matrix to result in the highest regenerative ability in the bone graft material in rabbit calvaria. The study conducted a comparative histomorphometric analysis of four groups in distinguished matrix conditions: a control group without graft placement, a non-demineralized dentin-derived matrix graft placement group, a 15-minute demineralized dentin-derived matrix graft placement group, and a 30-minute demineralized dentin-derived matrix graft placement group. Regenerative processes were evaluated three times at 2, 4, and 8 weeks post-graft placement. These groups of rabbits were evaluated randomly in a blinded setting to prevent bias. Among the four groups compared, the group with a 15-minute demineralized dentin-derived matrix graft showed the most efficient bone regeneration in the histomorphometric analysis. Based on this animal study, it was apparent that a 15-minute demineralization of dentin-derived matrix is the preferred preparation protocol to maximize the regenerative potential in the matrix.

Although 4Ce4YSZ has high corrosion resistance, it faces challenges concerning sinterability and ionic conductivity. Therefore, we studied destabilization behavior caused by corrosion and oxygen vacancy ordering according to ZnO doping. The powders of (4Ce4YSZ)1-x(ZnO)x (x=0.5, 1, 2, 4 mol%) were synthesized through the sol-gel method. With the addition of ZnO, the cubic phase increased, and secondary phases were not observed. The (111) peak showed a higher angle shift in ZnO-doped 4Ce4YSZ compared to 4Ce4YSZ, and TEM-SAED revealed a reduction in the spacing of the (011)t plane, suggesting lattice contraction due to the substitution of the smaller Zn2+ (60 Å) for Zr4+ (84 Å) in the lattice. The local atomic structure analysis was conducted using EXAFS to investigate the oxygen vacancy ordering behavior. Zr K-edge Fourier-transform data revealed a decrease in the Zr-O1 peak intensity with an increasing amount o ZnO doping, indicating an increase in oxygen vacancies. The Zr-O1 peak position shifted to the right, leading to an increase in the Zr-O1 interatomic distance. In the Y K-edge Fourier-transform data, the Y-O1 peak intensity did not decrease, and there was little variation in the Y-O1 interatomic distance. These results suggest that the oxygen vacancies formed due to ZnO doping are located in the neighboring oxygen shell of Zn, rather than in the neighboring oxygen shells of Y and Zr. Impedance measurements were conducted to measure the conductivity, and as the amount of ZnO doping increased, the total conductivity increased, while the activation energy decreased. The increase in oxygen vacancies by ZnO doping contributed to the enhancement of conductivity and it is considered that these created oxygen vacancies did not interact with Zn2+ and did not form defect associations. Fluoride-based molten salts were introduced to the specimens to assess corrosion behavior in a molten salt environment. Yttrium depletion layers (YDLs) were formed on the surfaces of all specimens due to the leaching of yttrium. However, Ce remained relatively stable at the interface according to EDS line scans, suggesting a reduction in the phase transformation (cubic, tetragonal to monoclinic) typically associated with yttrium leaching in YSZ.

This article proposes a measurement solution designed to monitor instantaneous frequency in power systems. It uses a data acquisition module and a GPS receiver for time stamping. A program in Python takes care of receiving the data, calculating the frequency, and finally transferring the measurement results to a database. The frequency is calculated with two different methods, which are compared in the article. The stored data is visualized using the Grafana platform, thus demonstrating its potential for comparing scientific data. The system as a whole constitutes an efficient low cost solution as a data acquisition system.

This study examined ways to prevent failures in the front-end of forklifts by addressing the center of gravity of heavy objects carried by forklifts, predicting the remaining useful lifetime (RUL), and the fault diagnosis based on alarm rules. In the research process, acceleration signals were acquired from the outer beam of the front-end of the forklift. A one-second window was applied to extract the time-domain statistical features, which were then set as variables. An exponentially weighted moving average was used to smooth the noise in the feature data set. The AWGN and LSTM autoencoders were used for data augmentation. Based on them, random forest and lightGBM models were used to develop classification models for the weight center of heavy objects carried by a forklift. In addition, contextual diagnosis performed by applying exponentially weighted moving averages to the classification probabilities of the machine learning models showed that random forest achieved an accuracy of 0.9563 and lightGBM achieved an accuracy of 0.9566. In addition, the acceleration data were collected through experiments to predict forklift failure and RUL because of the repeated forklift use when the center of heavy objects carried by the forklift was skewed to the right. The time-domain statistical features of the acceleration signals were extracted and set as variables by applying a 20-second window. Subsequently, logistic regression and random forest models were used to classify the failure stages of the forklifts. The f1-score (macro) obtained were 0.9790 and 0.9220 for logistic regression and random forest, respectively. In addition, the random forest probabilities for each stage were combined and averaged to generate a degradation curve and derive the failure threshold. The coefficient of the exponential function was calculated using the least squares method on the degradation curve, and the RUL prediction model was developed to predict the failure point. In addition, the SHAP algorithm was used to identify the significant features in classifying the stage. The alarm rule-based fault diagnosis was performed using the threshold of the normal stage distribution of the significant features.

The present study was conducted to investigate the comparative effects of organic and inorganic forms of sulfur, methyl sulfonyl methane (MSM) and sodium sulfate (SS), on laying performance, egg quality, ileal morphology, ileal volatile fatty acids, and antioxidant and stress markers in various biological samples in aged laying hens. A total of 144, 73-week-old Lohman Brown-Lite laying hens were randomly assigned to one of three experimental diets: basal diet (CONT), CONT + 0.2% MSM (MSM), and CONT + 0.3% SS (SS). The trial lasted for 12 weeks. MSM and SS groups contained 0.07% of sulfur, either organic or inorganic. Dietary MSM did not affect egg production and feed conversion ratio at 12 weeks compared with the CONT group. Dietary sulfur did not affect egg quality except for Haugh unit at 4 weeks which was lowered (P &lt; 0.05) in the SS group. Compared with the CONT group, higher (P &lt; 0.05) villus height and crypt depth ratio was observed in the SS group. None of dietary sulfur affected the percentages of short-chain fatty acids in the ileum. Total antioxidant capacity of liver increased (P &lt; 0.05) in laying hens fed MSM- and SS-added diets compared with the CONT group. The MSM and SS groups lowered (P &lt; 0.05) malondialdehyde (MDA) concentration in serum samples compared with the CONT. Finally, dietary MSM had the lowest (P &lt; 0.05) MDA concentrations in yolk samples. Taken together, our study showed that dietary organic and inorganic sulfur have positive effects on ileal morphology and antioxidant capacity in laying hens. However, SS-mediated inhibition in laying performance needs to be clarified.

This study identified the effects of substituting fishmeal (FM) with soy protein concentrate (SPC) supplemented with lysine and methionine in the olive flounder (Paralichthys olivaceus) diet on the expression of genes related to growth, stress, immunity, and digestion. Three experimental diets were prepared; the control diet (Con) contained 60% FM, and 25% (SPC25) and 50% (SPC50) FM were replaced by SPC. After the 140-day feeding period, weight gain, specific growth rate, feed availability, biological indices and chemical composition of the muscle were not significantly affected by the dietary treatments. The gene expression levels of growth-related genes (IGF, GFB-3), immune-related genes (IL-8 and caspase), stress-related genes (SOD, GPX, PRX, TRX) were higher in Con fish than in those fed the SPC25 and SPC50 diets. Chymo-TRY2, TRY2 and TRY3 in the stomach of fish fed the SPC25 diet were higher than fish fed the Con or SPC50 diets. TRY2 and lipase of fish fed the SPC25 diet were higher than those of fish fed the other diets but TRY3 was not significantly affected by the treatments in the intestine. In conclusion, substituting 25% FM with SPC was the most effective for the expression of growth, immune, stress, and digestive enzyme genes.

Abstract: This study investigates the transition to sustainable shipping industry within the framework of the IMO's 2050 carbon neutrality objective, focusing on socio-technical systems analysis. The research delves into the sustainable paradigm shift towards alternative marine fuels such as LNG, methanol, ammonia, and hydrogen from a socio-technical transition perspective, analyzing the multi-level per-spective challenges and opportunities. Specifically, it scrutinizes the implications of adopting these al-ternative fuels for global shipping, identifying technical uncertainties, financial constraints, and infra-structure needs. Through a comprehensive review of existing literature on ship emissions and alterna-tive fuels, coupled with socio-technical transition theory, the study addresses the multifaceted chal-lenges and opportunities in meeting the IMO's environmental objectives. It emphasizes the necessity of collaborative governance, innovative niche strategies, and a holistic approach to leverage the current window of opportunity in facilitating the maritime industry's transition to sustainable fuel options. Fi-nally, this research enhances our understanding of the intricate interplay between technological, social, industrial, and cultural dynamics in the greening of shipping and offers insights into the strategic adop-tion of environmentally friendly marine fuels for a sustainable future.

Cisplatin is a widely used anticancer drug for treating solid tumors, but it is associated with severe side effects, including nephrotoxicity. Various studies have suggested that the nephrotoxicity of cisplatin could be overcome; nonetheless, an effective adjuvant drug has not yet been established. Oleanolic acid acetate (OAA), a triterpenoid isolated from Vigna angularis, is commonly used to treat inflammatory and allergic diseases. This study aimed to investigate the protective effects of OAA against cisplatin-induced apoptosis and necroptosis using TCMK-1 cells and a mouse model. In cisplatin-treated TCMK-1 cells, OAA treatment significantly reduced Bax and cleaved-caspase3 expression, whereas increased Bcl-2 expression. Moreover, in cisplatin-induced kidney injury mouse model, OAA treatment alleviated weight loss in the body and major organs and also relieved cisplatin-induced nephrotoxicity symptoms. RNA sequencing analysis of kidney tissues identified lipocalin-2 as the most upregulated gene by cisplatin. Additionally, necroptosis-related genes such as receptor interacting protein kinase (RIPK) and mixed lineage kinase domain like (MLKL) were identified. In vitro study, the phosphorylation of RIPKs and MLKL was reduced by OAA pretreatment in both cisplatin-treated cells and cells boosted by co-treatment with z-VAD-FMK. In conclusion, OAA could protect the kidney from cisplatin-induced nephrotoxicity and may serve as an anticancer adjuvant.

In the development of the safety-critical systems, it is important to perform Failure Modes and Effects Analysis (FMEA) process to identify potential failures. However, traditional FMEA activities tend to be considered difficult and time-consuming tasks. To compensate for the difficulty of the FMEA task, various types of tools are used to increase the quality and the effectiveness of the FMEA reports. This paper explains an Automatic FMEA tool which integrates the Model-based Design (MBD), FMEA, and Simulated Fault Injection techniques in a single environment. The Automatic FMEA tool has the following advantages compared to the existing FMEA analysis tool. First, the Automatic FMEA tool automatically generates FMEA reports compared to the traditional spreadsheet-based FMEA tools. Second, the Automatic FMEA tool analyzes the causality between the failure modes and the failure effects by performing model-based fault injection simulation. In order to demonstrate the applicability of the Automatic FMEA, we used the electronic fuel injection system (EFI) Simulink model. The results of the Automatic FMEA were compared to that of the legacy FMEA.

Objective: This systematic review investigates the diagnostic, prognostic, and therapeutic implications of immunohistochemical markers in dentigerous cysts (DC) and odontogenic keratocysts (OKC) associated with impacted third molars. Materials and Methods: A comprehensive search strategy was employed across major databases including MEDLINE/PubMed, EMBASE, and Web of Science, from the inception of the databases to March 2024. Keywords and Medical Subject Heading (MeSH) terms such as "dentigerous cysts," "odontogenic kerato-cysts," "immunohistochemistry," "Ki-67," and "p53" were used. The PRISMA 2020 guidelines were followed to ensure methodological rigor. Inclusion criteria encompassed studies on humans and animals providing de-finitive diagnoses or specific signs and symptoms related to DC and OKC, with results on protein expression derived from immunohistochemistry, immune antibody, proteomics, or protein expression methods. Results: Of the 159 studies initially identified, 138 met the inclusion criteria. Our analysis highlighted sig-nificantly higher expressions of Ki-67 (22.1% ± 4.7 vs. 10.5% ± 3.2, p < 0.001), p53 (15.3% ± 3.6 vs. 5.2% ± 1.9, p < 0.001), and Bcl-2 (18.4% ± 3.2 vs. 8.7% ± 2.4, p < 0.001) in OKCs compared to DCs, indicating a higher proliferative index, increased cellular stress, and enhanced anti-apoptotic mechanisms in OKCs. Ad-ditionally, PCNA levels were higher in OKCs (25.6% ± 4.5 vs. 12.3% ± 3.1, p < 0.001). Genetic mutations, particularly in the PTCH1 gene, were frequently observed in OKCs, underscoring their aggressive behavior and potential malignancy. Conclusion: The findings emphasize the significant role of immunohistochemical markers in distinguishing between DCs and OKCs, with elevated levels of Ki-67, p53, Bcl-2, and PCNA in OKCs suggesting a higher potential for growth and recurrence. Genetic insights, including PTCH1 mutations, further support the need for personalized treatment approaches. These markers enhance diagnostic accuracy and inform targeted thera-peutic strategies, potentially transforming patient management in oral and maxillofacial surgery.

Transition metal complexes have historically played a pivotal role in creating vibrant pigments utilized across artistic mediums such as ceramics, paintings, and glass mosaics. Despite their extensive historical use, our understanding of the mechanisms governing transition metal complex behavior has predominantly emerged in recent times, leaving numerous aspects of this process ripe for exploration. These complexes exhibit striking color variations under diverse conditions when employed in pigment formulations. This review utilizes a bottom-up scientific approach, spanning from microscopic to macroscopic scales, to unravel the molecular origins of the colors generated by transition metal complexes in pigments and ceramic glazes. Advanced spectroscopy techniques and computational chemistry play pivotal roles in this endeavor, highlighting the significance of understanding and utilizing analytical data effectively, with careful consideration of each technique's specific application. Furthermore, the review investigates the influence of processing conditions on color variations, providing valuable insights for artists and manufacturers aiming to enhance the precision and quality of their creations while mitigating environmental impact.

One of the challenges posed by renewable energies is the stabilization of parameters related to the quality of electrical energy. This study demonstrates the existence of a relationship between input blocks of hydropower and the variation of the fundamental frequency of the electricity grid. By mapping production data provided by Spanish Electric Network with frequency measured in the laboratory, it is shown that gradients of hydropower are correlated with frequency fluctuations for certain characteristic times. Considering hourly instances of energy input, the study compares two methods for calculating hydropower gradients (linear regression and pseudo-linear regression); and two methods for calculating local frequency extremes (the "specular inertia" method and analysis by comparison with the moving average), in order to corroborate the results.

During the progression from ductal carcinoma in situ (DCIS) to invasive breast cancer (IBC), cells have to overcome the physically restraining basement membrane (BM) which compartmentalizes the epithelium from the stroma. Since the extracellular matrix (ECM) of the epithelial and stromal compartment is biochemically and physically distinct from one another, the progression demands a certain degree of cellular plasticity being essentially required for a primary tumor to become invasive. The Epithelial-to-Mesenchymal Transition depicts such a cell program equipping cancer cells with features allowing for dissemination from the epithelial entity and stromal invasion on the single-cell level. Here, we investigated the reciprocal interference between an altering tumor microenvironment and the EMT-phenotype in vitro. BM-typical collagen IV and stroma-typical collagen I coatings were applied as provisional 2-D matrices. Pro-inflammatory growth factors were introduced to improve tissue mimicry. Whereas the growth on coated surfaces did only slightly affect the EMT-phenotype, the combinatorial action of collagen with growth factor TGF-β1 induced prominent phenotypic changes. However, the EMT-induction was independent of the collagen type and cellular accessibility for EMT-like changes was strongly cell line dependent. Summarizing the entire body of data, we computed an EMT-phenotyping model that was used to decide on cellular EMT-status and estimate EMT-like changes. We confirmed that miR200c-mediated reversion of mesenchymal MDA-MB-231 cells is reflected by our EMT-phenotype model emphasizing its potential to predict the therapeutic efficacy of EMT-targeting drugs in the future.

Levels of synthetic musk fragrances (SMFs) and various personal care products (PCPs) were measured in the Han River and its tributaries in Seoul, Korea. The most abundant SMF in all river and PCP samples was 4,6,6,7,8,8-hexamethyl-1,3,4,7-tetrahydrocyclopenta[g]isochromene (HHCB), followed by 1-(3,5,5,6,8,8-hexamethyl-6,7-dihydronaphthalen-2-yl)ethanone (AHTN), musk ketone (MK), and 1,1,2,3,3-pentamethyl-2,5,6,7-tetrahydroinden-4-one (DPMI). There was a significant correlation between the SMF concentration in the PCPs and the Han River samples. Moving from upstream to downstream in the Han River, the median SMF concentration was 6.756, 2.945, 0.304, and 0.141 μg/L in the sewage treatment plant (STP) influent, effluent, tributaries, and mainstream, respectively, implying that effective SMF removal was achieved during the sewage treatment process, followed by dilution in the receiving water. Four STPs using advanced biological treatment processes had removal efficiencies of 55.8%, 50.6%, 43.3% for HHCB, AHTN, and MK, respectively. The highest SMF concentrations in the tributaries were observed at locations close to the STPs. Our study confirmed that the main source of SMFs in the receiving water were sewage effluent containing untreated SMFs, which are largely originated from household PCPs, especially hair care products (e.g., shampoo) and perfumes.

Background The Delta Neutrophil Index (DNI), a prodiagnostic marker for sepsis, utilizes leukocyte count. Platelet activation, similar to leukocytes, plays a crucial role in host defence against pathogens and may serve as a predictor of sepsis outcome. However, the combined evaluation of Mean Platelet Component (MPC) and DNI in assessing sepsis has been rarely used. Methods To assess the prodiagnostic validity of simultaneous utilization of DNI and MPC in cases of human febrile sepsis, we conducted measurements of cellular indices, including DNI and MPC, as well as molecular biomarkers such as procalcitonin (PCT) and C-reactive protein (CRP). This study was carried out on patients admitted to the emergency department with suspected sepsis. Results Using a cutoff value of 2.65%, the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of DNI in sepsis were found to be 69%, 73.9%, 77.9%, and 64.1%, respectively. Furthermore, significant differences in DNI and MPC levels were observed between the sepsis and non-sepsis groups (6.7±7.8% versus 2.1±2.2%, P=0.000 and 26.0±1.9 g/dl versus 26.8±1.4 g/dl, P=0.002), respectively. Notably, there was a negative correlation between DNI and MPC, with the strength of the correlation varying based on the cause of sepsis. By setting the cutoff value for DNI at 6.2%, the sensitivity, specificity, and NPV improved to 100%, 80.3%, and 100%, respectively, although the PPV remained at 10.6%. Importantly, the DNI≥6.2 group exhibited a higher incidence of death (10.9%, 5/46) and multiorgan failure (19.6%, 9/46) compared to the DNI<6.2 group (0.0%, 0/46 and 0.0%, 0/167, respectively) (P=0.000 and P=0.000, respectively). Conclusions In our study, DNI demonstrates superior effectiveness compared to other molecular biomarkers such as CRP and procalcitonin in distinguishing febrile septic patients from febrile nonseptic patients and predicting prognosis. Additionally, there exists a negative correlation between MPC and DNI, making MPC a valuable marker for differentiating the etiology of sepsis. These findings hold significant clinical implications as DNI/MPC is a cost-effective and readily applicable approach in various impending sepsis scenarios. Notably, this study represents the first examination of the prodiagnostic validity of simultaneously employing DNI and MPC in human cases of febrile sepsis.

Regardless of country and age, the importance of history education is always being emphasized. Although the importance of history education is being emphasized in Korea, there are many difficulties in getting students to understand history properly through school classes alone, and it is also difficult to attract students to participate in classes. The effectiveness of education using games has been proven 20 years ago, and the demand for game-based education is gradually increasing in the current education world, which is becoming more open. In this paper, based on the effects proven through research on the existing game-based education, the improvement of historical thinking ability, experiential history learning, and the problems of game-based education introduced in the ESN report and the discomfort of teachers who participated in the education were improved. A plan was suggested to select and use games suitable for basic education. In this thesis, we selected a history game with a clear historical and periodic background and without distortion of history, and experimented with teaching using games focusing on historical thinking and empirical history learning. The learning achievement of textbook-based education was compared.

Regardless of country and age, the importance of history education is always being emphasized. Although the importance of history education is being emphasized in Korea, there are many difficulties in getting students to understand history properly through school classes alone, and it is also difficult to attract students to participate in classes. The effectiveness of education using games has been proven 20 years ago, and the demand for game-based education is gradually increasing in the current education world, which is becoming more open. In this paper, based on the effects proven through research on the existing game-based education, the improvement of historical thinking ability, experiential history learning, and the problems of game-based education introduced in the ESN report and the discomfort of teachers who participated in the education were improved. A plan was suggested to select and use games suitable for basic education. In this thesis, we selected a history game with a clear historical and periodic background and without distortion of history, and experimented with teaching using games focusing on historical thinking and empirical history learning. The learning achievement of textbook-based education was compared.

This study aims to investigate the effects of cement kiln dust (CKD) on the hydration reactions and mechanical properties of cement and to evaluate its potential for use as a supplementary cementitious material (SCM). The key variables are the CKD type and incorporation rate. Cement paste and mortar specimens containing CKD were prepared to examine their effects on the cement hydration and mechanical properties. The impact on hydration was assessed using setting time measurements, heat of hydration tests, and thermogravimetric analysis (TG). In addition, compressive strength tests were conducted to evaluate the effect of CKD on the mechanical properties of the cement. The results indicated that CKD promoted early cement hydration and enhanced the early age mechanical properties. However, owing to its lack of pozzolanic reactivity, it did not significantly affect long-term hydration. Given that the effects of CKD vary slightly depending on its chemical composition, careful consideration of CKD's properties suggests that its potential use as a SCM is promising.

This paper aims to build up a preference function to evaluate the public benefits of the type of agricultural farming, biodiversity, water provisions, land use type, ecotourism modes, and a monetary attribute (environmental trust fund and willingness to contribute) associated with an ecosystem service and land use program in a forest park. This study used the choice experiments to build a random utility model, analyze the average preference for the above land use attributes based on the conditional logit and used a latent class model to test the resident’s heterogeneous preferences for land use planning in the forest park. We also estimated the welfare derived from various land use programs. The empirical result had shown that: (1) increasing organic farming area, maintaining the status quo of species biodiversity, increasing the surface water provision, increasing the area of custom flora, increasing the wetland area, and setting up an integrated framework for ecotourism increase the public’s preference for the land use program; (2) we found that farmer and non-farmer haven’t the same land use preferences; (3) the ecotourism development program incorporating biodiversity, organic farming, ethnobotany, and wetland area with integrated ecotourism are more preferred than other land use program scenarios.

In Los Angeles, at one point, the Covid-19 testing positivity rate was 6.25%, or one in sixteen. This translates to, on average, one in sixteen specimens testing positive and the vast majority testing negative. Usually, we run sixteen tests on sixteen specimens to identify the positive one(s). This process can be time consuming and expensive. Since a group of negative specimens pooled together for testing will produce a negative result, one single test could potentially eliminate many specimens. Only when the pooled specimen tests positive do we need further testing to identify the positive one(s). Based on this concept, we designed a strategy that will identify the positive specimen(s) efficiently. Assuming one in sixteen specimens is positive, we find that only four tests are needed. Furthermore, we can run them simultaneously, saving both resources and time. Although, in the real world, we cannot make the assumption of only one positive specimen, the same strategy works with slight modification and proves to be much more efficient than the conventional testing. Our strategy returns an answer 48% of the time in four tests and one time cycle. Overall, the average number of tests is seven or eight depending on the follow-up testing, and the average time cycle is about one and a half.

Aim: To improve risk stratification in early-stage endometrial cancer (EC), we performed mo-lecular classification, and L1CAM immunohistochemistry (IHC) for additional risk assessment. Method: We analyzed archival tumor tissue from 247 early-stage EC patients. POLE mutations were detected using a Droplet digital polymerase chain reaction assay and Sanger sequencing, while the mismatch repair (MMR) status was determined by MMR protein IHC and MSI test. Additionally, we conducted IHC of p53 and L1CAM. Results: The 247 ECs were categorized into four subgroups: POLE-mutated (13.0%), MMR-deficient (27.9%), p53-abnormal (8.5%), and non-specific molecular profile (NSMP, 50.6%). We further subcategorized NSMP subgroup into NSMP-L1CAMneg (44.9%) and NSMP-L1CAMpos (5.7%), which we refer to as the molecu-lar-L1CAM classification. The molecular-L1CAM classification was an independent prognostic factor for recurrence-free survival (RFS) and overall survival (OS) (p <0.001, each). Similarly, the simplified L1CAM-p53 categorization, for practical use, remained an independent prognostic factor for RFS and OS (p <0.001, p =0.003, respectively). Conclusion: Integrating the molecu-lar-L1CAM classification or the simplified L1CAM/p53 categorization can enhance risk stratifi-cation in early-stage EC, providing valuable prognostic information to guide treatment deci-sions and improve patient outcomes.

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.

This study surveyed the variation in Perfluorinated Compounds (PFCs) concentration entering urban wastewater treatment plants and proposed an optimal PFCS treatment method. The PFCS concentration in influent was shown to be affected by the types of industries and operating rate. The concentration of PFCs in the wastewater treatment effluent was slightly lower than that of influent. Thus, PFCs were considered to have barely been removed by the existing biological treatments. The pilot test result showed that about 10% of PFCs were removed by coagulation and precipitation, and the ozone and chlorine test also showed that few PFCs were removed regardless of the amount of injection. The activated carbon adsorption test showed that the removal was significantly increased by the empty bed contact time, with about a 60% removal in five minutes and over a 90% removal in 15 minutes. Therefore it is determined that a more stable and higher PFCs removal would result from the continuous oxidation processes such as ozone and adsorption processes such as activated carbon rather than a single biological treatment.

The increased complexity of modern systems is calling for an integrated and comprehensive approach to system design and development and in particular, a shift towards Model-Based Systems Engineering (MBSE) approaches for system design. The requirements that serve as the foundation for these intricate systems are still primarily expressed in Natural Language (NL), which can contain ambiguities and inconsistencies that hinder their direct translation into models. The colossal developments in the field of Natural Language Processing (NLP) in general and Large Language Models (LLMs) in particular can serve as an enabler for the conversion of NL requirements into semi-machine-readable requirements. This is expected to facilitate their standardization and use in a model-based environment. This paper discusses a two-fold strategy for converting NL requirements into semi-machine-readable requirements using language models. The first approach involves creating a requirements table by extracting information from free-form NL requirements. The second approach is an agile methodology that facilitates the identification of boilerplate templates for different types of requirements based on observed linguistic patterns. For this study, three different LLMs were utilized. Two of these models were fine-tuned versions of Bidirectional Encoder Representations from Transformers (BERT), specifically aeroBERT-NER and aeroBERT-Classifier, which were trained on annotated aerospace corpora. Another LLM, called flair/chunk-english, was utilized to identify sentence chunks present in NL requirements. All three language models were utilized together to achieve the standardization of requirements. To demonstrate the effectiveness of the methodologies, requirements from Parts 23 and 25 of Title 14 Code of Federal Regulations (CFRs) were employed, and a total of two, five, and three boilerplate templates were identified for design, functional, and performance requirements, respectively.

Glioblastoma (GBM) is the most common primary brain tumor. Due to high resistance to treatment, local invasion, and high risk of recurrence, GBM patient prognoses are often dismal, with median survival around 15 months. The current standard of care is threefold: surgery, radiation therapy and chemotherapy with temozolomide (TMZ). However, patient survival has only marginally improved. Radioimmunotherapy (RIT) is a fourth modality under clinical trials and aims at combining immunotherapeutic agents with radiotherapy. Here, we develop in vitro assays for rapid evaluation of RIT strategies. Using a standard cell irradiator and an Electric Cell Impedance Sensor, we quantify cell migration following the combination of radiotherapy and chemotherapy with TMZ and RIT with durvalumab, a PD-L1 immune checkpoint inhibitor. We measure cell survival using a cloud-based clonogenic assay. Irradiated T98G and U87 GBM cells migrate significantly (p < 0.05) more than untreated cells in the first 20-40 hours post-treatment. Addition of TMZ increased migration rates for T98G at the 20 Gy (p < 0.01). Neither TMZ nor durvalumab significantly changed cell survival in 21 days post-treatment. Interestingly, durvalumab abolished the enhanced migration effect, indicating possible potency against local invasion. These results provide parameters for rapid supplementary evaluation of RIT against brain tumors.

Mate choice that is based on behavioural traits is a common feature in the animal kingdom. Using the Trinidadian guppy, a species with mutual mate choice, we investigated whether males use female swimming activity – a behavioural trait known to differ consistently among individuals in many species – as a trait relevant for their mate choice. In a first experiment, we assessed male and female activity in an open field test alone (two repeated measures) and afterwards in heterosexual pairs (two repeated measures). In these pairs, we simultaneously assessed males’ mating efforts by counting number of sexual behaviours (courtship displays and copulation). Male and female guppies showed consistent individual differences in their swimming activity when tested both alone and in a pair, and these differences were maintained across both test situations. When controlling for male swimming behaviour and both male and female body size, males performed more courtship displays towards females with higher swimming activity. In a second experiment, we tested for a directional male preference for swimming activity by presenting males video animations of low and high active females in a dichotomous choice test. In congruence with experiment 1, we found males to spend significantly more time in association with the high active female stimulus. Both experiments thus point towards a directional male preference for higher activity levels in females. We discuss the adaptive significance of this preference as activity patterns might indicate individual female quality, health or reproductive state while, mechanistically, females that are more active might be more detectable to males as well.

Multiple sclerosis (MS) is a heterogeneous disease of the central nervous system that is governed by neural tissue loss and dystrophy during its progressive phase, with complex reactive pathological cellular changes. The immune-mediated mechanisms that promulgate the demyelinating lesions during the relapses of acute episodes are not characteristic of chronic lesions during progressive MS. This has limited our capacity to target the disease effectively as it evolves within the central nervous system white and gray matter, thereby leaving neurologists without effective options to manage individuals as they transition to a secondary progressive phase. The current review highlights the molecular and cellular sequelae that have been identified to cooperate and/or contribute to neurodegeneration that identifies individuals with progressive forms of MS. We emphasize the need for appropriate monitoring via known and novel molecular and imaging biomarkers that can accurately detect and predict progression for the purposes of newly designed clinical trials that may demonstrate efficacy of neuroprotection and potentially neurorepair. To achieve neurorepair, we focus on the modifications required in the reactive cellular and extracellular milieu, in order to enable endogenous cell growth as well as transplanted cells that can integrate and/or renew the degenerative MS plaque.

This study was conducted to investigate the effect of supplementing different types of methionine (L and D-type) and its precursor (HMBi) on milk protein synthesis using immortalized bovine mammary epithelial cell line (MAC-T Cell); D-methionine (D-Met), L-methionine (L-met) and 2-hydroxy-4-methylthiobutanoic acid I (HMBi), an isopropyl ester of the hydroxy analogue precursor of methionine. The underlying mechanism of milk protein synthesis by adding D- and L-type amino acid as well as HMBi was elucidated through omics analysis to verify the metabolism pathway. Results showed that HMBi group showed the highest beta casein mRNA expression levels compared to D- and L-Met groups and highest medium protein although not different with the L-Met treatment. The observed upregulated (>2 protein expression vs. control) and downregulated (<0.5 protein expression vs. control) proteins in L-Met, D-Met and HMBi treated groups were: 39, 77; 46, 68; and 40, 78, respectively. Interestingly, based on protein pathway analysis, L-Met treated group stimulated the ATP synthesis, PI3 kinase and pyruvate metabolism. On the other hand, the D-Met group stimulated fructose-galactose metabolism, glycolysis pathway, PI3 kinase and pyruvate metabolism. And lastly HMBi-treated group stimulated pentose phosphate pathway and glycolysis pathway. Metabolite analysis revealed that L-Met treated group resulted in the increase in 11 metabolites. On the other hand, D-Met treated group showed increase in 7 metabolites and decreased of uridine monophosphate (UMP). HMBi supplementation caused increases of 3 metabolites and decreased of UMP and N-acetyl-L-glutamate Addition of different isoforms of Met stimulated the production of intermediate metabolites for energy production. Addition of L-Met stimulated the production of energy metabolites such as pyruvate, malate, and fumarate, well-known as intermediates of Krebs cycle. On the other hand, HMBi supplementation resulted in increases of energy metabolite glucose 1-phosphate and 6-phosphogluconate. Results showed that HMBi-treated group exhibited highest expression of β-casein mRNA expression by stimulating proteins and metabolites as well as protein and metabolic pathways involved in protein and energy synthesis. As a result, HMBi-treated group resulted in highest protein concentration but not significantly different with L-Met. Both the D- and L-isoforms has considerably the same medium protein concentration and β-casein mRNA expression higher than the control. So, D- and L-Met isoforms can be used alternatively without any significant change in protein synthesis efficiency in bovine mammary epithelial cells.

This paper proposes a metaphysical framework for distinguishing between human and machine intelligence. It posits two identical deterministic worlds -- one comprising a human agent and the other a machine agent. These agents exhibit different information processing mechanisms despite their apparent sameness in a causal sense. Providing a conceptual modeling of their difference, this paper resolves what it calls “the vantage point problem” – namely, how to justify an omniscient perspective through which a determinist asserts determinism from within the supposedly deterministic universe.

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

Cost-effective community engagement is needed to address causes of mental illness related to social issues (i.e. isolation, stigma and lack of purpose) that are typically outside the scope of healthcare. This pilot study evaluated the relationship between clinical healthcare resources and a community-based social engagement organization in a medium-sized community in the midwestern US. Analyses were based on a retrospective longitudinal comparison of clinical visit frequency from two cohorts that joined the Momentum Center for Social Engagement (MC) and either frequently participated (Engaged; n = 9) or had extenuating circumstances limiting participation (Non-engaged; n = 3). The frequency of >1800 visits to the member’s primary mental healthcare provider were compared during the period from November 2016 - May 2021. Engaged MC members reduced frequency of regular visits to their primary mental healthcare provider by 50%, while Non-engaged MC members maintained clinical visit frequency. The financial value of reduced healthcare visits and associated wellbeing improvements was estimated to be $1.0 million, 95% CI: [$0.6-1.4 million], or roughly four times the budget received by the MC from the healthcare provider. Thus, the MC appears to be a valuable approach to improving mental health in conjunction with existing community healthcare services. Clinical implications include considering the unique MC-style community-based support as a component of practice.

AI-driven tools can identify nursing students' strengths and weaknesses, thus enabling the development of customized learning plans that target specific areas for improvement. This targeted approach can enhance knowledge retention and skill development, resulting in better prepared healthcare professionals. Nursing students are required to overcome their own psychological stress during their internship in order to understand sick children’s emotional reactions, as well as to be able to interact and communicate with such children. The application of AI picture-based teaching e-books helps nursing students to understand how to use therapeutic games to improve communication with sick children. A comparison of the differences between nursing teachers’ self-efficacy scores and nursing students’ application of AI picture-based teaching e-books (experimental group) and narrative handouts (control group) was achieved via therapeutic games to deal with sick children’s fear of medical examinations and treatments. In addition, a comparison was also conducted on the differences between the impact of the self-efficacy of the experimental group and that of the control group in dealing with sick children’s behavioral responses with respect to fears of medical examinations and treatments. This study is a quasi-experimental study, in which the self-efficacy scores of 30 nursing students were collected and analyzed in both the experimental group and the control group before and after intervention in dealing with sick children’s behavioral responses to fears of medical examinations and treatments. It was found that the self-efficacy score of the experimental group was higher than that of the control group (β coefficient is 0.356) when assessing the self-efficacy scores and behavior of the experimental and control groups in dealing with sick children’s fears of medical examinations and treatments through one-way analysis of covariance (one-way ANCOVA), moreover, a statistically significant difference (p < 0.05) was observed. The experimental group’s score of behavioral responses to the fears of sick children to examinations and treatments was lower than that of the control group (β coefficient was -1.540), wherein a statistically significant difference (p < 0.05) was shown. The self-efficacy of the experimental group in dealing with sick children’s fears of medical examinations and treatments had a statistically significant impact on the sick children’s behavioral responses to the fear of medical examinations and treatments (p < 0.05). In addition, the higher the self-efficacy scores of the experimental group in dealing with sick children’s fear of medical examinations and treatments, the lower the sick children’s behavioral responses to fears of medical examinations and treatments (the β coefficient was -0.914), the control group’s self-efficacy scores in dealing with sick children’s fears of medical examinations and treatments did not have a statistically significant impact on the sick children’s behavioral responses to fears of medical examinations and treatments (p > 0.05). This study proves that the application of AI picture-based teaching e-books by nursing teachers is more effective than narrative handouts in improving nursing students’ self-efficacy when using therapeutic games to deal with, as well as reduce, sick children’s fears of medical examinations and treatments.

Bangladeshi medicinal plants (BMP) have been used as traditional medicinal plants to treat chronic inflammatory diseases, but the antioxidant and anti-inflammatory effects of the bark of BMP are not yet known. The objective of this study was to determine antioxidant and anti-inflammatory activities using methanolic extracts of bark obtained from 15 medicinal spices of Bangladesh plants. The bark methanol extracts of BMP evaluated the total antioxidant activity and anti-inflammatory effect of lipopolysaccharide (LPS)-induced inflammation in RAW 264.7 macrophages. Among the 15 bark extracts of BMP, Albizia odoratissima (A. odoratissima), Engelhardia spicata (E. spicata), and Shorea robusta (S. robusta) showed the highest total phenolic contents and total antioxidant capacity by reducing free radicals scavenging activity. In particular, the three bark extracts significantly reduced the mRNA expression of LPS-induced inflammatory cytokines and inflammation-inducible enzymes in macrophages. Also, the mRNA expression of NADPH oxidase 2 was significantly suppressed by three bark extracts in LPS-induced RAW 264.7 macrophages. The results suggest that among the 15 bark extracts obtained from medicinal plant in Bangladesh, three bark extracts of A. odoratissima, E. spicata, and S. robusta exert total antioxidant capacity by reducing free radicals scavenging activity and inhibitory effects on LPS-stimulated inflammation in macrophages.

Background: Overweight and obese adults seek effective exercise interventions to reduce accumulated fat, but the effectiveness of these interventions vary across studies. The purpose of this meta-analysis was to investigate the effectiveness of exercise interventions in overweight and obese adults based on measurement of accumulated fat distributions. (2) Methods: Databases were used to select eligible studies for this meta-analysis. Randomized controlled trials with a control and experimental group were included. Degrees of effectiveness of exercise interventions were computed to assess the benefits on reducing weight and subcutaneous, visceral, and ectopic fat accumulation. (3) Results: A total of twenty-one studies were included in this meta-analysis. Participation in exercise interventions showed beneficial effects in reducing weight and subcutaneous and visceral fat. The effectiveness of exercise interventions on ectopic fat accumulation could not be assessed due to the limited number of studies measuring ectopic fat. Additionally, effectiveness of exercise interventions that depended on measurements of accumulated fat varied. The average exercise intervention for overweight and obese individuals was moderate to vigorous intensity, 4 times per week, 50 minutes per session, and 22 weeks duration. (4) Conclusions: Participating in exercise interventions has favorable effects on reducing weight and accumulation of subcutaneous and visceral fat.

Accumulating reports have suggested that an inability to clear dead cells is a cause of inflammation and cancer and that the fascia is associated with cancer metastasis. Novel corpuscle-connected filiform structures (CCFSs) entangled on the fascia of the internal organs of rats were selectively visualized with high repeatability (93%) under vital staining with Janus Green B (JGB). Serial sections of CCFSs stained with haematoxylin and eosin and with Mattson Trichrome were microscopically examined. In parallel, the immunohistochemistry with CD31, Lyve 1, scanning electron microscopy, and transmission electron microscopy (TEM) were also used to investigate the novel properties of the CCFSs. All of the CCFSs enclosed JGB-stained granules, which was verified by the impromptu coupling of stereo and light microscopes and fluorescence-activated cell sorting. The functions of the CCFSs were discovered under fluorescence microscopy and confocal laser scanning microscopy to be implicated in cell death: fragmented DNAs and f-actins with extracellular DNAs. The dead cells in the CCFSs were verified by using terminal deoxynucleotidyl transferase dUTP nick end labelling and TEM. Moreover, the CCFS had a relatively-high concentration of calcium, a main element for cell death in tissue, which was measured in 2-dimensionally images using time-of-flight secondary ion mass spectrometry. Taken these results, we report for the first time that novel reticular CCFSs are widely entangled on the fascia of the internal organs of rats with the implication for cell death.

The study was done to determine the effect of supplementing different forms of L-methionine (L-Met) and acetate on protein synthesis in immortalized bovine mammary epithelial cell line (MAC-T Cell): Control, L-Met, conjugated L-Met and acetate (CMA), and non-conjugated L-Met and Acetate (NMA). Protein synthesis mechanism was determined by omics method. NMA group had the highest protein content in the media and β-casein mRNA expression levels (P < 0.05). The number of upregulated and downregulated proteins observed were 77 and 62 in CMA group and 50 and 81 in NMA group from 448 proteins, respectively (P < 0.05). NMA and CMA treatments stimulated pathways related to protein and energy metabolism (P < 0.05). Metabolomic analysis also revealed CMA and NMA treatments resulted in increases of several metabolites (P < 0.05). In conclusion, NMA treatment increased protein concentration and expression level of β-casein mRNA in MAC-T cells compared to CMA.

(1) Background: The COVID-19 pandemic has affected healthcare utilization rates on a global scale. This study aimed to analyze whether the COVID-19 pandemic affected the characteristics of first-visit patients with peripheral facial palsy visiting a Korean Medicine hospital and to observe characteristics changes in them. (2) Methods: This study analyzed the electronic medical records of 2,310 first-visit patients with peripheral facial palsy who visited the Facial Palsy Center, Korean Medicine Hospital, Kyung Hee University Medical Center from January 1, 2019 to December 31, 2021 in terms of demographic characteristics, disease phase, residence locations, hospital visit route, and patient care type. (3) Results: There were significant relationships between the presence of the COVID-19 pandemic (i.e., before and during) and the number of patients by disease phase (p=0.043), residence locations (p=0.003), residence locations in Seoul (p=0.003), and patient care types (p=0.003). (4) Conclusions: There were several differences in characteristics of first-visit patients with peripheral facial palsy visiting a Korean Medicine hospital during COVID-19 pandemic in terms of demographic characteristics, disease phase, residence locations, residence locations in Seoul, and patient care types.

Whole blood viscosity, a hemorheological factor, is currently used for diagnosis, as it is correlated with various vascular diseases that are difficult to diagnose early with a general blood test. It was determined that it was necessary to set reference intervals for further studies and utilization of whole blood viscosity in cats, a representative companion animal, and this study was conducted. 50 healthy cats were recruited for the study and whole blood viscosity, complete blood count, and serum chemistry tests were performed. The reference intervals of whole blood viscosity were 15.169 to 43.684 cP at a shear rate of 1 s-1 reflecting diastole, and 3.524 to 5.544 cP at a shear rate of 300 s-1 reflecting systole. Red blood cells, hematocrit, hemoglobin, white blood cells, and neutrophils in the complete blood count, and total protein, albumin, globulin, and cholesterol in the serum chemistry were significantly correlated with whole blood viscosity. The results of this study set reference intervals of whole blood viscosity for healthy cats in a wide shear rate range that has not yet been fully established and investigated its correlation with other blood indicators.

The carotid body is a major peripheral chemoreceptor that senses changes in arterial blood oxygen, carbon dioxide, and pH, what is important for regulation of breathing and cardiovascular function. The mechanisms by which the carotid body senses O2 and CO2 are well known; conversely, the mechanisms by which it senses pH variations are almost unknown. Here we used immunohistochemistry to investigate how the human carotid body contributes to the detection acidosis analyzing whether it expresses acid-sensing ion channels (ASIC) ion channels, and to know if these channels are in the cells chemosensory glomic cells or in the afferent nerves. ASIC1, ASIC2 and ASIC3, and to a much lesser extent ASIC4, immunoreactivity was detected in subpopulations of type I glomus cells, as well as in the nerves of the carotid body. In addition, immunoreactivity was found for all ASIC subunits in neurons of the petrosal and superior cervical sympathetic ganglia, where afferent and efferent neurons are located, respectively, innervating the carotid body. This study reports for the fist time the occurrence of ASIC proteins in the human carotid body, demonstrating that they are present in glomus chemosensory cells (ASIC1 &lt; ASIC2 &gt; ASIC3 &gt; ASIC4) and nerves, presumably both afferent an efferent supplying the organ. These results suggest that the detection of acidosis by the carotid body can be mediated by ASIC ion channels present in the type I glomus cells or directly by sensory nerve fibers.

We aimed to test the hypothesis that serum 25-hydroxyvitamin D3 [25(OH)D] concentration is associated with mental health and life stress measures in young adults, and investigate sex and racial disparities in these associations. This study comprised 327 black and white participants. Depression, trait anxiety, perceived stress, and hostility were measured by validated instruments: Beck Depression Inventory (BDI), State-Trait Anxiety Inventory (STAI), Perceived Stress Scale (PSS), and Cook-Medley Hostility Scale (CMHS). Linear regression was used to estimate correlations between serum 25(OH)D concentration and mental health measurements in total population and in subgroups stratified by sex and race. In this sample (28.2 ± 3.1 years, 48% male, 53% black), serum 25(OH)D concentration was negatively related to BDI, STAI, PSS, total CMHS score and the majority of CMHS subscale scores (p-values < 0.05). Stratified by sex, most of these associations remained significant only in women (p-values < 0.05). Stratified by race, higher 25(OH)D concentrations in the whites were significantly related to lower BDI, STAI, PSS, and CMHS-cynicism subscale (p-values < 0.05); 25(OH)D concentrations in the blacks were only inversely associated with CMHS and most CMHS subscales (p-values < 0.05), but not with BDI, STAI and PSS. We present novel findings of consistent inverse relationships between serum 25(OH)D concentration and various measures of mental health and life stress. Long-term interventional studies are warranted to investigate the roles of vitamin D supplementation in prevention and mitigation of depression, anxiety and psychological stress in young adults.

We used a mixed-method single-case experimental research design to examine the effect of modelling (peer versus non-peer) on exercise self-efficacy in stroke survivors who participated in a community-based exercise program. Quantitative data were obtained using a ABCA design: (A1) no model/baseline 1 (3 weeks); (B) peer model (6 weeks); (C) non-peer model (6 weeks); and (A2) no model/baseline 2 (3 weeks). Four participants completed self-efficacy questionnaires after each weekly session. Qualitative data were obtained using researcher diaries and two semi-structured interviews: after B and A2. Based on quantitative and qualitative results, participants reported higher exercise self-efficacy in the model conditions, with ratings appearing highest for the non-peer model. This finding could be due to a lack of full integration of the peer model and low feelings of similarity. Modelling in general could help people recovering from a stroke increase their exercise self-efficacy, but non-peer models may not be most advantageous.

Health information and communication are key elements that allow patients and family members to make decisions about end-of-life process and guarantee a death with dignity. Objective: To understand carers’ experiences regarding health information and communication during the illness and death of family members. Methods: This qualitative study was conducted in Andalusia based on the paradigm of hermeneutic phenomenology. Participants were carers who had accompanied a family member at the end of life for over 2 months and less than 2 years. Five nominal groups and 5 discussion groups were established, and 41 in-depth interviews with 123 participants were conducted. Atlas.ti 7.0 software was used to analyse the discourses. Results: Four dimensions of the dying process emerged: differences in carers’ perceptions of information and communication, a conspiracy of silence, consequences of the absence or presence of information, and the need for a culture change. Conclusions: Poor management of health information and communication at the end of life suffering and discomfort patients and their families. The culture of denying and avoiding death is still present today. A change in education about death would better enable health professionals to care for patients at the end of life.

Bioremediation of crude oil-contaminated soil in Kuwait was evaluated using the biowashing pilot reactor system, whose components included 3 biowashing reactors; an oil separator, a hydrocyclone, and a dissolved air flotation. The biowashing pilot reactor system was fed with hemoglobin, a cheap and rich nutrient source containing carbon and nitrogen for bacterial growth. The initial total petroleum hydrocarbons (TPH) concentration was about 84,000 mg/kg soil. The initial TPH concentration decreased to 38,000 mg/kg soil on day 1. The degradation extents of TPH were 55%, 91%, and 96% on days 1, 3, and 5. The first-order rate constant for TPH degradation rate was 0.6820.0004/day. The initial unresolved complex mixture (UCM) concentration was 78,000 mg/kg soil. The degradation extents of UCM were 53%, 91%, and 98% on days 1, 3, and 5. Then, the degradation extents of individual components of total polycyclic aromatic hydrocarbons (PAH), alkylated PAH, and n-alkanes were measured for 5 days. 16S rRNA gene copy number was measured during 5 days for bacterial population estimation. Although there was a day delay in the accretion of the number of copies, the number increased from day 2 to day 5. The present study suggests that the biowashing pilot reactor system with a capacity of 200 L is efficient for TPH degradation.

Numerous innovative advancements in dressing technology for wound healing have emerged. Among the various types of wound dressings available, hydrogel dressings, structured with a three-dimensional network and composed of predominantly hydrophilic components, are widely used for wound care due to their remarkable capacity to absorb abundant wound exudate, maintain a moisture environment, provide soothing and cooling effects, and mimic the extracellular matrix. Composite hydrogel dressings, one of the evolved dressings, address the limitations of traditional hydrogel dressings by incorporating additional components, including particles, fibers, fabrics, or foams, within the hydrogels, effectively promoting wound treatment and healing. The added elements enhance the features or add specific functionalities of the dressings, such as sensitivity to external factors, adhesiveness, mechanical strength, control over the release of therapeutic agents, antioxidant and antimicrobial properties, and tissue regeneration behavior. They can be categorized as natural or synthetic based on the origin of the main components of the hydrogel network. This review focuses on recent research on developing natural polysaccharide-based composite hydrogel wound dressings. Their preparation and composition, the reinforcement materials integrated into hydrogels, and therapeutic agents are also explored. Furthermore, their features and the specific types of wounds where applied are discussed as well.

Affective computing has emerged as a prominent technology in recent years, driven by the increasing demand for machines capable of understanding and interpreting emotions. The COVID-19 pandemic has intensified this need by reducing physical interactions and increasing reliance on digital communication, which often involves complex emotional exchanges. To enhance social interactions by identifying and addressing negative emotions, an interactive emotion-perception system based on multi-sensing interfaces and affective computing has been proposed. Integration of gesture, voice, and brainwave sensors is employed to provide users with a rich sensory experience and immersive environment. Design principles and system development processes are derived from the affinity diagram method and prototype development approach. The proposed system was constructed, and experiments were conducted with 60 participants. Interpersonal interaction scenarios were explored to understand emotional transmission mechanisms, aiming to enhance user satisfaction and positive interpersonal experiences. Data were collected through indirect observation and questionnaires, followed by evaluation and statistical analysis. Findings include: (1) The emotion-perception system enhances positive interpersonal interactions by identifying 36 distinct emotions, with overall user emotions being positive but exhibiting notable individual variations; (2) The system effectively stimulates positive emotions and strengthens interpersonal interactions, with affective computing technology fostering enjoyable emotional resonance and high-quality relationships; (3) A positive correlation was observed between semantic analysis and brainwave metrics of relaxation and concentration, showing increased concentration and enhanced positive emotional interactions during message transitions; and (4) The multi-sensing and affective computing technology provides a pleasant and relaxing emotional journey, with interactions shifting from enthusiasm to comfort, demonstrating the system’s capacity for a satisfying and enjoyable experience.

Day-ahead forecasting of electricity prices is important in deregulated electricity markets for all the stakeholders: energy wholesalers, traders, retailers, and consumers. Electricity price forecasting is an inherently difficult problem due to its special characteristic of dynamicity and non-stationarity. In this paper, we present a robust price forecasting mechanism that shows resilience towards aggregate demand response effect and provides highly accurate forecasted electricity prices to the stakeholders in a dynamic environment. We employ an ensemble prediction model in which a group of different algorithms participate in predicting the price for each hour of a day. We propose two different strategies, namely, Fixed Weight Method (FWM) and Varying Weight Method (VWM), for selecting each hour's expert algorithm from the set of participating algorithms. In addition, we utilize a carefully engineered set of features selected from a pool of features derived from information such as past electricity price data, weather data, and calendar data. The proposed ensemble model offers better results than both the Pattern Sequence-based Forecasting (PSF) method and our own previous work using Artificial Neural Networks (ANN) alone do on the datasets for New York, Australian, and Spanish electricity markets.

This study investigated the physical properties of section-restoration mortar with calcium nitrite and carbon dioxide (CO2) nanobubble mixing water to develop materials and methods for the repair and reinforcement of cracks in reinforced concrete (RC) structures. As the calcium nitrite content increased, the generation rate and generated amount of nitrite-based hydration products increased, owing to the rapid reaction between NO2- ions in calcium nitrite and C3A(Al2O3). Further, the reaction with C3S and C2S was accelerated, thereby increasing the generation rates of Ca(OH)2 and C-S-H. Further, the large amount of Ca2+ ions in these hydration products reacted with CO32- ions in CO2 nanobubble water, thereby increasing the generation of calcite-based CaCO3 in the cement matrix. This appears to have affected the strength development and durability improvement via the densification of the structure. These results suggest that the performance of polymer cement mortar for repairing concrete structures can be improved if calcium nitrite and CO2 nanobubble water are properly combined and applied.

The violation of data integrity in automotive Cyber-Physical Systems (CPS) may lead to dangerous situations for drivers and pedestrians in terms of safety. In particular, cyber-attacks on the sensor could easily degrade data accuracy and consistency over any other attack, we investigate attack detection and identification based on a deep learning technology on wheel speed sensors of automotive CPS. For faster recovery of a physical system with detection of the cyber-attacks, estimation of a specific value is conducted to substitute false data. To the best of our knowledge, there has not been a case of joining sensor attack detection and vehicle speed estimation in existing literatures. In this work, we design a novel method to combine attack detection and identification, vehicle speed estimation of wheel speed sensors to improve the safety of CPS even under the attacks. First, we define states of the sensors based on the cases of attacks that can occur in the sensors. Second, Recurrent Neural Network (RNN) is applied to detect and identify wheel speed sensor attacks. Third, in order to estimate the vehicle speeds accurately, we employ Weighted Average (WA), as one of the fusion algorithms, in order to assign a different weight to each sensor. Since environment uncertainty while driving has an impact on different characteristics of vehicles and cause performance degradation, the recovery mechanism needs the ability adaptive to changing environments. Therefore, we estimate the vehicle speeds after assigning a different weight to each sensor depending on driving situations classified by analyzing driving data. Experiments including training, validation, and test are carried out with actual measurements obtained while driving on the real road. In case of the fault detection and identification, classification accuracy is evaluated. Mean Squared Error (MSE) is calculated to verify that the speed is estimated accurately. The classification accuracy about test additive attack data is 99.4978%. MSE of our proposed speed estimation algorithm is 1.7786. It is about 0.2 lower than MSEs of other algorithms. We demonstrate that our system maintains data integrity well and is safe relatively in comparison with systems which apply other algorithms.

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

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

Buruli ulcer is a chronic ulcerative disease of skin and subcutaneous tissues caused by infection with Mycobacterium ulcerans. Although Australian possums are known to be susceptible to Buruli ulcer, many aspects of the disease in possums, including welfare impacts, remain largely unreported. Severe clinical Buruli ulcer was identified in four common ringtail possums (Pseudocheirus peregrinus) from Melbourne, Victoria. All four possums were euthanised due to welfare concerns and poor prognosis, based on the presence of deep ulcerative lesions to paws, some of which exposed carpal or tarsal bones. These lesions were considered likely to cause partial or complete loss of limb function, which would severely affect the welfare and survival of these wild arboreal animals. Histologically, there was severe ulcerative necrotising pyogranulomatous dermatitis, panniculitis, and myositis, with intralesional acid-fast bacteria. M. ulcerans was detected by real-time PCR in all swabs and biological tissues collected from all four cases. Buruli ulcer may be an important and under-recognised cause of poor possum welfare in endemic areas. In addition to severe cutaneous lesions, infection extends to underlying bones and joints, and the systemic distribution of M. ulcerans throughout all major tissues and internal organs, as observed in these four cases, may further impact the health and fitness of infected possums. Further research is needed to investigate the epidemiology, pathogenesis and impacts of Buruli ulcer in possums, and to inform the design of interventions that may protect the health and welfare of possums and other affected animal species.

Background: Despite advances in the treatment of hepatocellular carcinoma (HCC) over the last few decades, treatment opportunities for patients with HCC remain limited. HCC is the most common form of liver cancer, accounting for approximately 90% of all cases worldwide. Moreover, apart from the current pharmacological interventions, hepatic resection and liver transplantation are the mainstay curative approaches for patients with HCC. Methods: This systematic review included phase I, II, III, and IV clinical trials (CTs) and randomized controlled trials (RCTs) on current treatments for patients with HCC in an Asian population (2013–2023). A total of 427 articles were screened, and 184 non-duplicate publications were identified. After screening titles and abstracts, 96 publications were excluded, and another 28 were excluded after full-text screening. The remaining 60 eligible RCTs/CTs were finally included. Results: Sixty clinical trials fulfilled our inclusion criteria and screened 36 drugs as monotherapy or combination therapy for HCC. Most studies used sorafenib alone or in combination with any of the treatment regimens. Lenvatinib or atezolizumab with bevacizumab was used for HCC after initial sorafenib treatment. Eighteen studies compared the efficacy of sorafenib with that of other drugs, including lenvatinib, cabozantinib, tepotinib, tigatuzumab, linifanib, erlotinib, resminostat, brivanib, tislelizumab, selumetinib, and refametinib. Conclusion: This study provides comprehensive insights into effective treatment interventions for HCC in Asian populations. The overall assessment indicated that sorafenib alone or in combination with atezolizumab and bevacizumab has been the first treatment choice in the past decade to achieve better outcomes in patients with HCC in an Asian population

Residential segregation refers to the phenomenon where people of different socioeconomic backgrounds live in spatially separated areas. It is essential to ensure equitable access to urban amenities for all residents in pursuit of the normative values in urban planning. To achieve this planning goal, the disparity in accessibility to urban amenities needs to be appropriately diagnosed. Private apartments and public rental apartments are representative types of residences where residential segregation is likely to occur in the context of South Korea, since these two types show considerable differences in the education, income, and occupations. The objective of this study is to develop an analysis framework for diagnosing the difference in accessibility to urban amenities between the two residential types, and to empirically demonstrate their utility in the planning process. The empirical analysis conducted on Seoul revealed that not only were there significant local variations in accessibility between the two segregated residential areas, but the overall differences across the entire area were also pronounced. The proposed framework is useful in supporting decision-making processes for locating new public facilities or identifying regional priorities for guiding the placement of private amenities, with the aim of mitigating differences between segregated residential areas.

This review focuses on the regulation and modulation of human DNA polymerase δ (Pol δ). The emphasis is on mechanisms that regulate the activity and properties of Pol δ in DNA repair and replication. The areas covered are the degradation of the p12 subunit of Pol δ, which converts it from a heterotetramer (Pol δ4) to a heterotrimer (Pol δ3), in response to DNA damage and also during the cell cycle. The biochemical mechanisms that lead to degradation of p12 are reviewed, as well as the properties of Pol δ4 and Pol δ3 that provide insights into their functions in DNA replication and repair. The second focus of the review involves the functions of two Pol δ binding proteins, PDIP46 and PDIP38, both of which are multi-functional proteins. PDIP46 is a novel activator of Pol δ4, and the impact of this function is discussed in relation to its potential roles in DNA replication. Several new models for the roles of Pol δ3 and Pol δ4 in leading and lagging strand DNA synthesis that integrate a role for PDIP46 are presented. PDIP38 has multiple cellular localizations including the mitochondria, the splicesosomes and the nucleus. It has been implicated in a number of cellular functions, including the regulation of specialized DNA polymerases, mitosis, the DNA damage response, Mdm2 alternative splicing and the regulation of the Nox4 NADPH oxidase.

The corpus luteum is a temporary endocrine gland formed in the ovary after ovulation, and it plays a critical role in reproductive processes. Tumors rely on the development of an adequate blood supply to ensure the delivery of nutrients and oxygen and the removal of waste products. While angiogenesis occurs in various physiological and pathological contexts, the corpus luteum and tumors share similarities in the signaling pathways that promote angiogenesis. In the corpus luteum and tumors, apoptosis plays a crucial role in controlling cell numbers and ensuring proper tissue development and function. Interestingly, there are similarities in the apoptotic-regulated signaling pathways involved in apoptosis between the corpus luteum and tumors. However, the regulation of apoptosis can differ due to their distinct physiological and pathological characteristics. Thus, we reviewed the biological events of the corpus luteum and tumors in similar microenvironments of angiogenesis and apoptosis for studying novel research methods.

The oil spilled from the Gulf war caused land pollution and various petroleum compounds. Among petroleum compounds, polycyclic aromatic hydrocarbons (PAHs) are known for toxicity, and have been designated as carcinogenic, mutagenic, and endocrine disrupting substances by the United States Environmental Protection Agency (USEPA). According to the USEPA, toxic equivalents quotient (TEQ), and mutagenic equivalents quotient (MEQ) can be calculated by multiplying the toxic equivalency factor (TEF) and mutagenic equivalency factor (MEF) by the concentration of PAHs. The USEPA calculates the relative TEF for other PAHs by setting the TEF value of benzo(a)pyrene, which is highly toxic, to 1. Relative MEF is also calculated in the same way. In this study, the TPH concentrations of crude oil-contaminated soils collected from the Burgan in Kuwait were measured to be 5, 8, and 20% and TEQ and MEQ of the soils were calculated by multiplying the 16 PAHs concentrations measured for each sample by TEF and MEF, respectively. When the TPH concentration was increased by 4 times from 5% to 20%, the TEQ was increased by about 9 times and the MEQ was increased by about 10 times. Therefore, it was concluded that as the TPH concentration increases, the carcinogenicity and mutation rate increase greatly. In addition, ecotoxicity assessment was performed using luminescent bacteria to compare the relationship between the calculated TEQ and MEQ and actual ecotoxicity, and benzo(a)pyrene among 16 PAHs showed a coefficient of determination of 0.95. In this study, ecotoxicity in PAHs-contaminated environment can be estimated by analyzing benzo(a)pyrene as a representative substance.

In this paper, we present a full coverage path planning (CPP) algorithm for the marine surveys conducted in the convex polygon shaped search area. The survey is supposed to carry out by torpedo-type AUVs (autonomous underwater vehicles). Due to their nonholonomic mechanical characteristics, these vehicles have nonzero minimum turning radius. For any given polygon shaped search area, it can always be partitioned into one or more convex polygons. With this in mind, this paper proposes a novel search algorithm called CbSPSA (Calculation based Shortest Path Search Algorithm) for full coverage of any given convex polygon shaped search area. By aligning the search inter-tracks alongside the edge with the minimum height, we can guarantee the minimum number of the vehicle’s turns. In addition, the proposed method can guarantee the planned path is strictly located inside the polygon area without overlapped or crossed path lines, and also has the total path length as short as possible. Considering the vehicle’s nonzero minimum turning radius, we also propose a sort of smoothing algorithm to smooth the waypoint path searched by CbSPSA so as for the vehicle to exactly follow it. The smoothed path is also guaranteed to be strictly located inside the polygon. Numerical simulation analyses are also carried out to verify the effectiveness of the proposed schemes.