Additional Variables Research Articles

Psychological Factors Affecting Drive-by-Lane Behavior at Lane Offset Intersections: Analysis Based on Extended Theory of Planned Behavior in a Chinese Sample

Traffic conflict commonly occurs in intersections with offset lane lines because of mismatched choices of entrance and exit lanes. This conflict drives down overall traffic efficiency and can cause crashes. At such intersections, the driver’s lane choice behavior seriously affects the traffic system. The theory of planned behavior (TPB) was used in this study to excavate the impact mechanism of drive-by-lane behavior at offset intersections. A scale incorporating TPB constructs and additional variables (risk perception [RP], traffic environment [TE], optimization measures [OM], and driving style [DS]) was developed to collect empirical data with 557 valid samples in China. A structural equation model of drivers’ drive-by-lane behavior was established to explore the causal relationship between behavior and influencing factors, as well as the interrelationships between TPB variables. TE, behavior intention (BI), subjective norms (SN), and RP show the most significant effects on drive-by-lane behavior. DS, perceived behavior control, attitude (ATT), and OM have little impact on drive-by-lane behavior. BI, TE, RP, and DS have significant, direct effects on drive-by-lane behavior. The TE, OM, and DS variables significantly affect drive-by-lane behavior through mediators. RP, BI, and ATT mediate the influence of other variables as well as affecting drive-by-lane behavior. We put forward suggestions to improve driving behavior at offset intersections including changing external factors, education, and training. The direct and indirect relationships between the influencing factors and drive-by-lane behavior are discussed in this paper to provide technical and reference support for future research on managing irregular urban traffic intersections.

A simple and realistic aerosol emission approach for use in the Thompson–Eidhammer microphysics scheme in the NOAA UFS Weather Model (version GSL global-24Feb2022)

Abstract. A physics suite under development at NOAA's Global Systems Laboratory (GSL) includes the aerosol-aware double-moment Thompson–Eidhammer microphysics (TH-E MP) scheme. This microphysics scheme uses two aerosol variables (concentrations of water-friendly aerosol (WFA) and ice-friendly aerosol (IFA) numbers) to include interactions with some of the physical processes. In the original implementation, WFA and IFA depended on emissions derived from climatologies. In our approach, using the Common Community Physics Package (CCPP), we embedded modules of sea-salt emissions, dust emissions, and biomass-burning emissions, as well as of anthropogenic aerosol emissions, into the Unified Forecast System (UFS) to provide realistic aerosol emissions for these two variables. This represents a very simple approach with no additional tracer variables and therefore very limited additional computing cost. We then evaluated a comparison of simulations using the original TH-E MP approach, which derives the two aerosol variables using empirical emission formulas from climatologies (CTL) and simulations that use the online emissions (EXP). Aerosol optical depth (AOD) was derived from the two variables and appears quite realistic in the runs with online emissions when compared to analyzed fields. We found less resolved precipitation over Europe and North America from the EXP run, which represents an improvement compared to observations. Also interesting are moderately increased aerosol concentrations over the Southern Ocean from the EXP run, which invigorate the development of cloud water and enhance the resolved precipitation in those areas. This study shows that a more realistic representation of aerosol emissions may be useful when using double-moment microphysics schemes.

Motivation and attitude of English language learning among nursing students

Background: Proficiency in speaking English is an individual's ability to convey thoughts and desires verbally to anyone. However, it can be challenging to develop this skill without continuous self-training. One effective approach is through peer or classmate interactions, as well as guidance from English language instructors. Numerous factors influence the success of students in learning English, and motivation and attitude are crucial aspects needed by nursing students to master the language.Purpose: To identify the description of motivation and attitude among nursing students in learning English, providing input for learning achievement targets for English courses and the most suitable learning methods to enhance the language skills of nursing students at Murni Teguh University.Method: A quantitative research method with a descriptive design was employed. The total sampling technique was used, and 157 respondents willingly filled out the questionnaire from a total population of 167 individuals. Instruments for measuring motivation and attitude were adopted from previous studies with established validity. Data analysis utilized Univariate data analysis.Results: Instrumental motivation among respondents (90.5%) was higher than integrative motivation (88.9%). The majority of respondents had high motivation at 89.6%. Meanwhile, most respondents exhibited good attitudes at 41.2%, followed by fairly good attitudes at 36.4%, and poor attitudes at 22.4%.Conclusion: Nursing students at Murni Teguh University demonstrate high motivation and positive attitudes toward learning English. However, this does not align with the English language proficiency of the respondents.Suggestion: It is highly recommended for future researchers to include additional variables such as interest in learning, self-concept, self-efficacy, the cause-and-effect correlation between each researched variable in English language learning, and the use of effective English teaching methods to enhance the English language proficiency of nursing students.

Understanding consumers’ adoption of e-pharmacy in Qatar: applying the unified theory of acceptance and use of technology

Purpose This study aims to investigate the factors influencing the adoption of online pharmacies in Qatar using the unified theory of acceptance and use of technology-2 (UTAUT-2) framework. Specifically, this study examines the impact of performance expectancy, effort expectancy, social influence, hedonic motivation, habit, technology trust, perceived risk and users’ level of awareness of behavioral intention, which in turn affects the adoption of online pharmacies. Furthermore, this study explores the moderating role of word-of-mouth (WOM) recommendations on the relationship between behavioral intention and online pharmacy adaptation. Design/methodology/approach This study adopted a descriptive, quantitative approach to investigate the UTAUT-2 model in the context of consumers’ adoption of e-pharmacy in Qatar. Through convenience sampling, 455 responses were collected from regular customers accessing online pharmacy services. The data were analyzed using Smart-PLS 3.2 software to examine the hypothesized relationships. Findings The results showed that WOM recommendations significantly enhanced the relationship between behavioral intention and adopting online pharmacies in Qatar. This study identified the factors that may hinder or enable the adoption of online pharmacies, including performance expectancy, effort expectancy, social influence, hedonic motivation, habit, technology trust, perceived risk and users’ level of awareness. Research limitations/implications This study contributes to the existing literature on technology acceptance by extending the UTAUT-2 model and recognizing three additional variables (perceived risk, technology trust and technology awareness). These need to be investigated against UTAUT-2 variables to detect the significance of their impact on adapting the e-health concept in Qatar. The potential for cultural change to accelerate the adoption of online pharmacies is highlighted. Future research should explore the role of moral and cultural factors in technology adoption. Practical implications The results underscore the economic and social significance of e-pharmacy adoption, particularly within the context of a developing country. Considering the positive intentions expressed by individuals toward e-pharmacy, it becomes crucial for managers and decision-makers to make strategic choices to address any challenges that may arise. Policymakers are encouraged to enhance their services and implement various development initiatives to expand e-pharmacy accessibility and availability. Originality/value This study builds upon previous research on e-commerce in the pharmaceutical industry and provides a comprehensive understanding of customers in developing countries. Extending the UTAUT-2 model and identifying additional variables contributes to the knowledge of e-health concepts in Qatar. The findings have practical implications for developing strategies to promote online pharmacy adoption in Qatar and other countries.

Understanding the effects of socialness and color complexity in listing images on crowdfunding behavior

PurposeColor psychology theory reveals that complex images with very varied palettes and many different colors are likely to be considered unattractive by individuals. Notwithstanding, web content containing social signals may be more attractive via the initiation of a social connection. This research investigates a predictive model blending variables from these theoretical perspectives to determine crowdfunding success.Design/methodology/approachThe research is based on data from 176,614 Kickstarter projects. A number of machine learning and artificial intelligence techniques were employed to analyze the listing images for color complexity and the presence of people, while specific language features, including socialness, were measured in the listing text. Logistic regression was applied, controlling for several additional variables and predictive model was developed.FindingsThe findings supported the color complexity and socialness effects on crowdfunding success. The model achieves notable predictive value explaining 56.4% of variance. Listing images containing fewer colors and that have more similar colors are more likely to be crowdfunded successfully. Listings that convey greater socialness have a greater likelihood of being funded.Originality/valueThis investigation contributes a unique understanding of the effect of features of both socialness and color complexity on the success of crowdfunding ventures. A second contribution comes from the process and methods employed in the study, which provides a clear blueprint for the processing of large-scale analysis of soft information (images and text) in order to use them as variables in the scientific testing of theory.

P743 A personalised algorithm predicting the risk of intravenous corticosteroid failure in acute ulcerative colitis

Abstract Background An episode of acute ulcerative colitis (UC) represents an important watershed moment in a patient’s disease course. Foreknowledge of a patient's likely response to intravenous corticosteroid therapy has significant clinical utility. Using a large prospectively collected acute UC patient database and machine learning-based techniques we aimed to derive and validate a personalised algorithm for identifying patients at high risk of corticosteroid therapy failure from variables available at hospital presentation. Methods A prospectively collected database of 600 consecutive presentations of acute UC was collated at a single referral centre between 1996 and 2022. An AIC-based Elastic Net model was used to select variables on the 419 earliest presentations of acute UC (1996-2017). Two risk-scoring algorithms, with and without utilising additional endoscopic variables, were constructed using logistic regression models. These risk scores were then validated on a separate cohort of 181 acute UC presentations (2018-2022). Results The partial risk of rescue (ROR) score included the admission indices of oral corticosteroid treatment; bowel frequency ≥6/24 hours; albumin; CRP ≥12mg/ml and log10CRP. The full ROR score incorporates the same variables with the addition of the Mayo endoscopic subscore and disease extent. The ROC AUCs in the validation cohort were 0.76 (95% CI: 0.69-0.83) and 0.78 (95% CI: 0.71-0.85) for the partial and full ROR scores, respectively. When incomplete cases were excluded, the full ROR score validation cohort ROC AUC increased from 0.78 to 0.80. Conclusion These pragmatic personalised risk scores (available at www.severecolitis.com) have comparably strong performance characteristics and usability enabling the identification of individuals at high risk of corticosteroid treatment failure before or after endoscopic assessment. These patients may be suitable for consideration of early treatment escalation or screening for participation in clinical trials.

Localized management of distributed flexible energy resources

The integration of distributed energy resources continues to be a challenge for the traditional electricity grid. Aside from additional variability in the net power demand, there is often a temporal discrepancy between generation and consumption schedules which can exacerbate demand peaks and troughs, leading to system overloading, voltage violations, and a low system load factor. This study proposes a control system approach to unify the management of the different types of flexible energy resources through Localized Demand Control. In this system, all flexible energy resources are coordinated using a power line carrier frequency signal to follow a preferred demand curve at the distribution transformer level. The system’s functionality has been confirmed in an actual 5-house microgrid without adverse effects on end-user comfort. Meanwhile, scaled-up simulation studies have shown improvements in the system load factor by as much as 189%, and increased hosting capacity by 40% for electric vehicles and 16% for solar photovoltaic panels.

Assessing the intention to accept inquiry-based teaching pedagogy among Chinese university students: an extension of technology acceptance model.

Due to the limitations of traditional didactic teaching, inquiry-based teaching has attracted increasing attention and has become an important content of curriculum teaching reform in college education. Nevertheless, it is vital to investigate students' subjective acceptance of inquiry-based instruction and its influencing factors before inquiry-based teaching methods are widely implemented. In light of this, taking into account the psychological factors of students, an acceptance model of inquiry-based teaching pedagogy was established based on the extended technology acceptance model (TAM). Three additional variables, namely self-efficacy, implementation quality, and risk perception, were incorporated into the TAM. Firstly, subjective evaluation data of the influencing factors of inquiry teaching acceptance were obtained through a network questionnaire survey from university students in Guangdong, China, using snowball sampling and convenient sampling. A total of 485 valid questionnaires were retrieved, with an effective response rate of 88.2%. Then, internal consistency and reliability, convergent validity and discriminant validity of the model and its hypothesis were tested with reliability and validity tests. Finally, path analysis was used to examine key determinants of students' acceptance of inquiry teaching and moderators. Results indicated that the constructed model can explain the acceptability of inquiry teaching for college students by 88.6%; Attitude has a positive significant impact on behavioral intention; Perceived ease of use indirectly affects behavioral intention through perceived usefulness, while perceived usefulness indirectly affects behavioral intention through attitude; self-efficacy not only directly affects behavioral intention but also indirectly affects behavioral intention through implementation quality; implementation quality indirectly affects behavioral intention through perceived usefulness and attitude; students' risk perception of inquiry-based teaching has no negative impact on behavioral intention. Overall, this study has implications for policymakers, teachers or learners in terms of the implementation and promotion of inquiry-based teaching in college classroom.

Genome-wide association study for stayability at different calvings in Nellore beef cattle

BackgroundingStayability, which may be defined as the probability of a cow remaining in the herd until a reference age or at a specific number of calvings, is usually measured late in the animal’s life. Thus, if used as selection criteria, it will increase the generation interval and consequently might decrease the annual genetic gain. Measuring stayability at an earlier age could be a reasonable strategy to avoid this problem. In this sense, a better understanding of the genetic architecture of this trait at different ages and/or at different calvings is important. This study was conducted to identify possible regions with major effects on stayability measured considering different numbers of calvings in Nellore cattle as well as pathways that can be involved in its expression throughout the female’s productive life.ResultsThe top 10 most important SNP windows explained, on average, 17.60% of the genetic additive variance for stayability, varying between 13.70% (at the eighth calving) and 21% (at the fifth calving). These SNP windows were located on 17 chromosomes (1, 2, 4, 6, 7, 8, 9, 10, 11, 12, 13, 14, 18, 19, 20, 27, and 28), and they harbored a total of 176 annotated genes. The functional analyses of these genes, in general, indicate that the expression of stayability from the second to the sixth calving is mainly affected by genetic factors related to reproductive performance, and nervous and immune systems. At the seventh and eighth calvings, genes and pathways related to animal health, such as density bone and cancer, might be more relevant.ConclusionOur results indicate that part of the target genomic regions in selecting for stayability at earlier ages (from the 2th to the 6th calving) would be different than selecting for this trait at later ages (7th and 8th calvings). While the expression of stayability at earlier ages appeared to be more influenced by genetic factors linked to reproductive performance together with an overall health/immunity, at later ages genetic factors related to an overall animal health gain relevance. These results support that selecting for stayability at earlier ages (perhaps at the second calving) could be applied, having practical implications in breeding programs since it could drastically reduce the generation interval, accelerating the genetic progress.

An efficient penalty function method for scenario-based uncertainty quantification problems

This paper proposes an efficient penalty function method to transform constrained optimization problems into unconstrained ones without introducing Lagrange multipliers or slack variables. The method designs new activation and loss penalty functions for inequality and equality functional models and establishes a non-Lagrangian-constrained optimization method. A novel optimality condition independent of any additional variables and equivalent to the Karush–Kuhn–Tucker (KKT) condition is introduced. Additionally, a scenario constraint handling method that does not rely on slack variables is proposed. Compared to soft constraint optimization methods, the proposed method can easily handle numerous scenario constraints. Two examples are used to compare the results with those in the literature, verifying the effectiveness and reliability of the proposed method. Finally, the method is applied to three scenario-based uncertainty quantification problems, including a trigonometric function affected by a noise term, the dynamic performance of a black-box system controller, and the frequency response of a damaged suspension arm. The results demonstrate that the proposed penalty function method can effectively solve scenario-based uncertainty quantification problems with many constraints and improve computational efficiency, providing a new method and means for addressing uncertainty quantification optimization problems in engineering.

Greening the path to carbon neutrality in the post-COP26 era: Embracing green energy, green innovation, and green human capital

The COP26 Glasgow conference stressed the importance of all nations committing to more ambitious targets for reducing emissions to keep global temperatures from rising more than 1.5 ​°C above pre-industrial levels. This is crucial since any temperature greater than that will have grave and irreversible climatic repercussions. This research, utilizing data from Ghana from 1980 to 2018, investigates the role of green innovation, green energy consumption, and green human capital in mitigating carbon dioxide (CO2) emissions to achieve carbon neutrality within the environmental Kuznets curve (EKC) framework while using natural resources and industrialization as additional variables in the study model. Current econometric techniques are employed for accurate and reliable analyses, and the findings reveal the study variables as stationary and co-integrated in the long run. The novel quantile-on-quantile regression is adopted, and the empirical discoveries reveal that green energy consumption, green innovation, and green human capital mitigate CO2 emissions. However, the findings indicate that natural resources and industrialization escalate CO2 emissions in the country. The findings also validate the N-shape EKC hypothesis between economic growth and CO2 emissions in Ghana. Policy recommendations are offered based on these insights.

Greek primary school students’ moral judgments and motives about sustainable food consumption

Modern dietary habits pose large threats to the global vision for a sustainable food system transition, intensifying discussions around the urgency for educational initiatives that can promote more sustainable food consumption practices. However, research has not sufficiently studied food consumers' moral background, despite its strong influence on food choices, while relevant research on school-aged consumers is even scarcer. This study focuses on two individual ethical decision-making processes regarding food sustainability: moral judgments and moral motives. Data was selected using non-probability, opportunity sampling from 587 students attending the last two grades of primary school in the Region of Western Macedonia, Greece. Participants completed a Likert-scale questionnaire, which adopted a holistic approach towards food sustainability, incorporating the following 12 variables associated with all three domains of sustainability (environmental, societal, economic): Biodiversity, Carbon footprint, Soil, water and air conservation, (Food) loss and waste, Water footprint, Nutrition and health, Animal welfare, Workers' rights and safety, Cultural traditions, Food supply, Tax revenues and Profits, Jobs/incomes. In the moral motives scale, additional variables associated with non-moral considerations were also assessed: Sensory Appeal, Mood, Promotion, Social influence, Convenience and Familiarity. For the moral judgments scale, findings revealed low to medium scores for all the domains and among the variables associated with a sustainable food system, the lowest mean scores being recorded in those linked to the social dimension of sustainability. Regarding food consumption motives, results indicate that non-moral considerations prevail remarkably over moral ones and are linked to all three domains of sustainability. Statistical testing identified grade level, gender, place of residence and participation in environmental, health or food education school programs as factors influencing certain aspects of students’ moral thinking at a statistically significant level. Insights gained from this study can contribute to educational and other agendas aiming to promote sustainable food consumption.

Opposite Responses of Native and Nonnative Birds to Socioeconomics in a Latin American City.

Due to the massive increase of the urban population, a global target is to achieve sustainable cities that are sensitive to nature and environmentally just for urban dwellers. To accomplish this, it is important to understand the responses of native and nonnative birds, identify the environmental variables that promote native species and limit nonnative species, and understand how they vary among socioeconomic groups. Although many cities in the Global South exhibit strong social and environmental segregation, few studies have investigated the relationship between socioeconomics and biodiversity. Therefore, to help promote ecological justice and biodiversity conservation in the developing world, we investigated the influence of socioeconomic level and woody cover on bird species richness and abundance in the city of Santiago de Chile. We also investigated whether bird response changes with species provenance-it is important to understand the response of native birds separately from nonnative birds because they imply opposite management strategies (e.g., conservation vs. species control/eradication). Thus, we surveyed 120 sites located in residential areas of high, medium, and low socioeconomic levels across the city and fit generalized linear (mixed) models that described bird species richness and abundance for total, native, and nonnative birds according to socioeconomic level and woody vegetation cover. We found that both socioeconomic level and woody vegetation cover influenced the bird community, but their effects changed with bird species origin, having opposite effects on native and nonnative birds. Residential areas where wealthier people live supported greater species richness and abundance of native birds than residential areas where people of lower socioeconomic status live. In contrast, residential areas where vulnerable people live had greater bird abundance that was mainly composed of nonnative birds. Therefore, affluent neighborhoods provide more opportunities to encounter native birds and experience nature close to home than poorer neighborhoods. Due to woody cover having positive effects on native birds and a negative influence on nonnative birds, increasing tree and shrub cover will contribute to supporting more native birds in residential areas deprived of woody vegetation, which are commonly low socioeconomic areas. Additional variables that can explain bird response among residential areas of different socioeconomic levels need to be investigated to better understand the factors influencing the distribution of birds in cities and promote a more biodiverse and environmentally just city.

The Effect of Islamic Financial Inclusion, Urbanization, Inflation, and GDP on Poverty in Indonesia

This research aims to assess the influence of Islamic financial inclusion, urbanization, inflation, and GDP on the alleviation of poverty in Indonesia. The methodology employed is quantitative, utilizing secondary data in a panel data format spanning the period from 2018 to 2022. A total of 165 samples were gathered, and the data underwent processing through Eviews 10. The findings indicate that individually, the Sharia Financial Inclusion Index (IIKS), inflation, and GDP do not exhibit a significant impact on poverty reduction in Indonesia. Conversely, urbanization has a noteworthy and negative effect on poverty reduction in Indonesia. When considered collectively, the IIKS, urbanization, inflation, and GDP variables jointly exert a substantial influence on poverty reduction in Indonesia, reflected in an Adjusted R-squared value of 98%, while the remaining 2% is attributed to other unexplored factors in this study. For future research endeavors, it is advisable to introduce additional variables for a more comprehensive and profound exploration of this subject.

Prevalence of radiographic findings in chronic osteomyelitis

BackgroundSimple radiography in conjunction with pertinent medical history and a comprehensive physical examination is typically adequate for diagnosing chronic osteomyelitis (CO). However, radiographic manifestations of CO lack specificity; therefore, the concordance among specialists in this regard has not been systematically assessed. This study aimed to compare and evaluate the proficiency of orthopedic surgeons and radiologists in identifying radiographic indicators present in simple radiographs for diagnosing CO.MethodsThis cross-sectional study was a correlational investigation utilizing plain radiographs obtained from a cohort of 60 patients diagnosed with CO. Comprehensive assessments of the demographic and clinical characteristics, comorbidities, and microbiological parameters were conducted. Additional variables included the anatomical location of the CO, existence of fistulas, disease duration, and presence of pseudoarthrosis. This study meticulously documented the presence or absence of six specific findings: bone destruction, which incorporates erosion and radiolucencies around implants; bone sclerosis; cortical thinning concomitant with erosion; cortical thickening; sequestrum formation; and soft-tissue swelling.ResultsMost patients were men (75%), with a mean age of 45.1 years. Hematogenous etiology of CO represented 23%. Bone sclerosis (71.3%) and cortical thickening (67.7%) were the most common radiographic findings, followed by soft-tissue swelling (51.3%), sequestration (47.3%), bone destruction (33.3%), and cortical erosion (30.3%). The mean agreement was 74.2%, showing a marked disagreement rate of 25.8% among all radiographic findings. The presence or absence of soft tissue edema, a prominent radiographic finding that was more important than the other findings, showed the greatest disagreement.ConclusionsRadiographic findings in CO were universally observed in all patients, demonstrating a high degree of concordance among specialists, with the exception of soft tissue swelling.

Association between Oxidative Stress with Psychological and Biochemical Variables in a Sample of Healthy Mexican People: A Cross-Sectional Study.

Oxidative stress (OS) has been linked to cell damage and chronic disease development; however, the study of psychological factors related with OS has been limited, as has its relationship with biochemical and personal variables. Therefore, the aim of this study was to evaluate the association between a wide variety of personal, psychological, and biochemical factors with OS in a sample of healthy Mexican people. A total of 134 participants, from which 70 (52%) were women, without known chronic conditions were included in the study, and the molecule 8-hydroxy-2'-deoxyguanosine (8-OHdG) was also measured as a marker of OS. We observed in the multivariate analysis of the whole sample that depressive symptoms (measured with CES-D scale) were the only psychological variable significantly associated (positively) with 8-OHdG. In addition, the following sociodemographic variables were associated with 8-OHdG: age, schooling (positively correlated), and the frequency of vitamins/antioxidant consumption (negatively correlated). The biochemical variables of erythrocytes in urine and amylase were positively correlated with 8-OHdG, while glucose was negatively correlated with it. Additional biochemical variables were associated in the multivariate analysis of each sex, including the positive correlation of LDL-cholesterol, LDH enzyme, lymphocytes, and the negative correlation of phosphorus and eosinophils in women's samples, as well as the positive correlation of potassium, uric acid, and leucocytes in urine and the negative correlation of erythrocytes and lipase in the men's samples. In conclusion, depression was the only psychological variable positively correlated with 8-OHdG after adjusting for confounders, and new associations with biochemical variables were found with some differences between sexes.

Comparing the Effect of Scientific Background on University Students’ Environmental Views

Creating an environmentally aware society is not an easy task and requires knowledge about what affects the formation of environmental views. At the same time, to contribute to environmental protection, individuals with different educational backgrounds need to have environmental awareness, because their decisions as future professionals may affect the environment. The problem, however, is that there is not adequate research on the association between educational background and environmental views. To address this gap, the aim of this study is to investigate whether scientific background affects environmental views and attitudes. Specific objectives are to examine whether scientific background affects university students’ views on environmental issues as well as their attitudes towards the solution to environmental problems. To achieve this aim, a comparative study was performed on two student groups: students attending environmental studies and students attending classical studies. The results showed that non-environmental students were less willing to change their habits to protect the environment and to participate in environmental actions compared to environmental students who expressed a pronounced willingness to do so. However, both student groups did not acknowledge their personal environmental responsibility. Categorical regression revealed that students’ certain sociodemographic variables affected their willingness to change habits. However, other additional variables are recommended to be analyzed in future studies. The results from this study provide support for making changes in the curricula of non-environmental departments and for carrying out actions to reinforce the participation of students in initiatives aimed at raising environmental awareness.

Frontloading visual field tests detect earlier mean deviation progression when applied to real-world-derived early-stage glaucoma data.

To examine the diagnostic accuracy of performing two (frontloaded) versus one (clinical standard) visual field (VF) test per visit for detecting the progression of early glaucoma in data derived from clinical populations. A computer simulation model was used to follow the VFs of 10,000 glaucoma patients (derived from two cohorts: Heijl etal., Swedish cohort; and Chauhan etal., Canadian Glaucoma Study [CGS]) over a 10-year period to identify patients whose mean deviation (MD) progression was detected. Core data (baseline MD and progression rates) were extracted from two studies in clinical cohorts of glaucoma, which were modulated using SITA-Faster variability characteristics from previous work. Additional variables included follow-up intervals (six-monthly or yearly) and rates of perimetric data loss for any reason (0%, 15% and 30%). The main outcome measures were the proportions of progressors detected. When the Swedish cohort was reviewed six-monthly, the frontloaded strategy detected more progressors compared to the non-frontloaded method up to years 8, 9 and 10 of follow-up for 0%, 15% and 30% data loss conditions. The time required to detect 50% of cases was 1.0-1.5 years less for frontloading compared to non-frontloading. At 4 years, frontloading increased detection by 26.7%, 28.7% and 32.4% for 0%, 15% and 30% data loss conditions, respectively. Where both techniques detected progression, frontloading detected progressors earlier compared to the non-frontloaded strategy (78.5%-81.5% and by 1.0-1.3 years when reviewed six-monthly; 81%-82.9% and by 1.2-2.1 years when reviewed yearly). Accordingly, these patients had less severe MD scores (six-monthly review: 0.63-1.67 dB 'saved'; yearly review: 1.10-2.87 dB). The differences increased with higher rates of data loss. Similar tendencies were noted when applied to the CGS cohort. Frontloaded VFs applied to clinical distributions of MD and progression led to earlier detection of early glaucoma progression.

Temporal signed gestures segmentation in an image sequence using deep reinforcement learning

Continuous sign language recognition is challenging due to coarticulatory distortions, which occur at the beginning and end of each gesture. These distortions depend on the temporal context and introduce additional intraclass variability. To address this issue, a new approach is proposed that extracts segments from the image sequence corresponding to undistorted parts of gestures. This should simplify the task by reducing it to the easier problem of isolated gestures recognition. The proposed approach uses deep reinforcement learning for segmentation and a novel image sequence processing scheme to extract gradient changes over time. A dataset recorded by deaf people and annotated according to the proposed approach, was prepared to evaluate the method. The proposed deep learning architectures achieved leave-one-subject-out recognition accuracies in the range of 0.70 to 0.76. Considering the inability to compare with other works, the authors also proposed other evaluation protocols to thoroughly examine the employed approach. This work will be developed, and the main aspiration of the authors will be to create an integrated framework that converts the raw form of RGB video into a string of words representing the Sign Language user’s intentions.

Estimand for non-inferiority influenza vaccine immunogenicity trials

According to recent regulatory guidance, clinical trial objectives should be translated into estimands, i.e., precise descriptions of that what is to be estimated. Hence, estimands are to be formulated for influenza vaccine immunogenicity (IVI) trials, notably for one of the most popular immunogenicity trials, the non-inferiority trial. In this paper an estimand for this trial design is proposed.An estimand should state how intercurrent events are handled. Intercurrent events are events that occur after the start of the trial and that affect the endpoint’s measurement or interpretation or prevent its observation. In IVI trials the intercurrent events of interest are immunological intercurrent events (IIEs). Major IIEs are identified, i.e., protocol deviations occurring during the trial that affect immunogenicity endpoints, and the consequences for the trial data collection are discussed.In the statistical analysis endpoint values that are missing or excluded from the analysis due to IIEs are to be substituted by plausible values, by means of multiple imputing. Replacing values are based on predictors of the endpoint. A distinction is made between mandatory and non-mandatory predictors. Mandatory predictors are predictors necessary to prevent biased prediction. Non-mandatory predictors are predictors that limit the additional variance due to the imputing. The four steps of the multiple imputing are explained, and available software is listed.