The geometric median, which is applicable to high-dimensional data, can be viewed as a generalization of the univariate median used in 1-dimensional data. It can be used as a robust estimator for identifying the location of multi-dimensional data and has a wide range of applications in real-world scenarios. This paper explores the problem of high-dimensional multivariate analysis of variance (MANOVA) using the geometric median. A maximum-type statistic that relies on the differences between the geometric medians among various groups is introduced. The distribution of the new test statistic is derived under the null hypothesis using Gaussian approximations, and its consistency under the alternative hypothesis is established. To approximate the distribution of the new statistic in high dimensions, a wild bootstrap algorithm is proposed and theoretically justified. Through simulation studies conducted across a variety of dimensions, sample sizes, and data-generating models, we demonstrate the finite-sample performance of our geometric median-based MANOVA method. Additionally, we implement the proposed approach to analyze a breast cancer gene expression dataset.

Based on the signaling and conservation of resources theories, this study aims to identify different strategic organizational profiles related to occupational health and well-being (OHWB). Additionally, this study explores how these various organizational profiles impact employees\' well-being, specifically in relation to absenteeism, emotional exhaustion, work overload, intention to quit, and job satisfaction. Data were collected from 59 organizations and 2828 employees. The first phase of this study presents the latent profile analysis carried out to identify OHWB organizational profiles. This analysis reveals four organizational profiles that are metaphorically named according to the growth stages of plants (i.e., wasteland, sprouting, budding, and blooming OHWB profiles). The second phase of this study investigates the associations between the latent profiles assigned to the organizations with absenteeism, intention to quit, emotional exhaustion, feelings of work overload, and job satisfaction among their employees using MANOVA. The results show that organizational profiles influence employees\' health and well-being. Employees working in organizations with a low OHWB profile, known as the \"wasteland profile\", tend to report more days of absenteeism, higher levels of emotional exhaustion, greater work overload, and lower job satisfaction. Employees are also more likely to express a greater intention to quit their jobs than those working in organizations with a higher OHWB profile (a \"blooming profile\"). This study is useful for organizations and practitioners seeking to understand how investing in a health and well-being strategy can benefit their employees.

The increasing interest in Turkish educational programs has led to the increasing interest in educational migration among the younger Iranian generations. Instructors, as the executive part of educational programs, can also play a key role in satisfying students\' expectations and educational goals. The aim of this study was to identify and compare the Critical Openness (CO), Reflective Skepticism (RS), innovative thinking (IT), external accountability (EA), and internal accountability (IA) for the Iranian and Turkish English as Foreign Language (EFL) instructors through an online survey with Critical Thinking Theory and the 21st century skill consideration lens. To this end, a convenient sample of Iranian (N = 286) and Turkish (N = 281) EFL instructors were invited to take part in the online survey voluntarily. The scales consisted of the Likert scales of Rosenblatt (2017) [1], Semerci (2007) [2], and Sosu (2013) [3], because the conceptual frameworks were also taken from these studies. In the analysis stage, MANOVA was conducted to compare the results of the online survey between Iranian and Turkish EFL instructors in terms of their level of CO, RS, IT, EA, and IA. The analysis of the collected data uncovered that Turkish EFL instructors got higher scores in CO, RS, EA, and IA than Iranian EFL instructors while Iranian EFL instructors received higher scores in the employment of IT. The implications of the results would suggest collaborations between educational policymakers and teacher training course designers.

The objective of the present study was to assess the difference in antimicrobial activity of Satureja kitaibelii Wierzb. ex Heuff. essential oil at three growth stages. In addition, using statistical and chemometric tools, we tried to explain why the essential oil from a certain vegetation stage shows the highest antimicrobial activity. S. kitaibelii essential oils demonstrated minimum inhibitory concentration values from 160 to 10000 μg mL-1 , and minimum microbicidal concentration values from 630 to 20000 μg mL-1 . Geraniol, borneol, limonene and p-cymene are the dominant compounds of S. kitaibelii essential oil. The most abundant compound, geraniol, possesses antimicrobial activity in a range of MIC values from 40 to 5000 μg mL-1 and MMC values from 80 to 10000 μg mL-1 . The highest activity of essential oil for all tested strains of microorganisms was recorded in November. Results of statistical analysis indicate that the percentage of dominant compounds of essential oils does not affect the antibacterial activity of essential oils. Chemometric analyses leads to the conclusion that borneol, spathulenol, caryophyllene oxide and limonene can be the main contributors to the antibacterial activity of essential oil from November and that their mutual ratio is important. These results may represent a new methodological approach for future research on essential oils.

The degree of sexual dimorphism in certain traits between males and females differ from one sample to another. Although trait differences by sex are often reported in bioanthropological research, few studies test for statistical significance or make raw data available. TestDimorph is the first R package dedicated to testing and comparing the degree of sexual dimorphism among different samples by leveraging summary statistics.
We provide two approaches of analysis of inter-sample differences in degree of sexual dimorphism: univariate and multivariate for two or more samples. The methods follow upon publications primarily from the AJBA. Within-sex size variability between samples is compared using one-way ANOVA followed by control for multiple pairwise comparisons. In addition, we compute the overlapping area between the density functions of two normal distributions from the mixture intersection index or the non-overlapping area using the dissimilarity index as well as Hedges\' g with inferential support using the 95% confidence interval. Finally, we use a multivariate analysis of differences in patterning of sexual dimorphism between samples.
We demonstrate various results from applying TestDimorph functions to data supplied with the package.
The package has many features including functionality for working with summary statistics, simulating data from summary statistics, and the extraction of summary statistics from raw data, so that the entire analysis can be performed through the package.

Enrichment of pharmaceutically important vinca alkaloids, vinblastine and vincristine, in the leaves of Madagascar periwinkle (Catharanthus roseus) plants through different pre- or postharvest treatments or cultivation conditions, e.g., exposing the plants to UV-irradiation, has been in focus for decades. Controlled LED environment in the visible light range offers the possibility of monitoring the changes in the concentration of metabolites in the vinca alkaloid-related pathway without involving UV-related abiotic stress. In the frame of our targeted metabolomics approach, 64 vinca alkaloids and metabolites were screened with the help of a UPLC-ESI-QTOF-MS instrumental setup from the leaf extracts of C. roseus plants grown in chambers under control (medium light), low light, and high blue / high red/ high far-red conditions. Out of the 14 metabolites that could be assigned either unambiguously with authentic standards or tentatively with high resolution mass spectrometry-based methods, all three dimer vinca alkaloids, that is, 3\',4\'-anhydrovinblastine, vinblastine and vincristine showed an at least nine-fold enrichment under high blue irradiation when compared with the control conditions: final concentrations of 961 mg kg-1 dry weight, 33.8 mg kg-1 dry weight, and 11.7 mg kg-1 dry weight could be achieved, respectively. As supported by multivariate statistical analysis, the key metabolites of the vinca alkaloid pathway were highly represented among the metabolites that were specifically stimulated by high blue light application.

The present research article provides data about the differences in post-traumatic stress symptoms, and defense mechanisms based on the levels of perceived stress (low, average, high), using a large national sample of 1100 Italian individuals, collected during the first wave of the COVID-19 pandemic. Participants completed an online survey through the Google Form platform, where the Ten-Item Perceived Stress Scale, Impact of Event Scale - Revised, and Forty Item Defense Style Questionnaire were included. First, the cut-offs of the perceived stress scale were calculated by determining the 25th and 75th percentile scores for the sample of this survey. Then, MANOVA analyses were performed, together with ANOVAs and the Bonferroni Post hoc analyses as a follow-up. The dataset (.xlsx) includes the survey scores, while the tables and figures provide the analysed data, where the differences are shown. This data article may provide useful bases for future research on perceived stress and for suggesting associated factors on which focus clinical intervention and preventive programs.

Post-traumatic stress disorder (PTSD) is a pathological condition that may lead to a significant deterioration in the quality of life over time. Therefore, the study of the elements that can characterize the disorder could be considered of great clinical interest and relevance. The aim of the present research was to empirically discriminate the influence of perceived stress, state anxiety, worry, and defense mechanisms (mature, neurotic, and immature) at different levels of post-traumatic stress symptoms. A sample of 1250 participants (69.5% women, 30.5% men; Mage = 34.52, SD = 11.857) completed an online survey including the Impact of Event Scale-Revised, Ten-Item Perceived Stress Scale, Penn State Worry Questionnaire, Forty Item Defense Style Questionnaire, and State-Trait Anxiety Inventory-Form X3. Data were analysed by implementing MANOVA and discriminant analysis. Results showed significant differences in the levels of perceived stress, state anxiety, and worry, as well as neurotic and immature defenses based on the levels of post-traumatic stress symptoms: F(12,2484) = 85.682, p < 0.001; Wilk\'s Λ = 0.430. Furthermore, these variables discriminate significant accuracy between participants who reported a mild psychological impact and those with a probable presence of PTSD, with perceived stress, which was found to be the best predictor. Classification results indicated that the original grouped cases were classified with 86.3% overall accuracy. Such findings may provide useful insight for clinical practice.

UNASSIGNED: In response to the requirement of keeping social distance during the COVID-19 outbreak a lot of employees needed to change from a regular office to a home-office at short notice. The aim of the present study is to explore these employees\' experiences and evaluate changes in their work situation during the pandemic.
UNASSIGNED: A mixed-method design was used with panel data collected twice in an insurance company in Norway. The first dataset was collected in December 2020 (Time 1; N = 558), with a follow up in March 2021 (Time 2; N = 601).
UNASSIGNED: Our study indicated that employees\' main reasons for working from home were to keep social distance, avoid contagion and protect their loved ones. Flexibility, timesaving and more time with family and friends were also motivators. Most employees reported that they had the necessary technical equipment to work from home and wanted more opportunity to use their home office in the future. General Linear Models (GLM) indicated that work-family balance and workload were the same across age, gender, and worksites. Women and employees working from home reported more fear of being infected by COVID-19 at work. Younger employees reported experiencing less social contact with colleagues than normal during the pandemic, compared to the older employees. Overall, employees working at home were more positive toward digital solutions and digital meetings than those at the office. Repeated measures MANOVA showed that the work motivation and digital competence decreased over time for all worksites. Productivity increased for home-office employees but decreased for the hybrid and work-office employees.
UNASSIGNED: This paper contributes to knowledge of employees\' experiences with different worksite solutions, which will be useful for anticipating employees experience in the future with more hybrid work.

Automated and specific picking of selenium-containing molecular entities has not been an obvious option for software tools associated with electrospray high-resolution mass spectrometry (MS). In our study, a comprehensive pattern matching approach based on intra-isotopologue distance and isotopologue ratio data was critically evaluated in terms of reproducibility and selenium isotope selection on three samples, including selenized Torula yeast and the selenium hyperaccumulator plant Cardamine violifolia. Hydrophilic interaction liquid chromatography was applied to provide a one-step separation for water soluble metabolites to put an end to the need for either orthogonal setups or poor retention on reversed phase chromatography. Assistance from inductively coupled plasma-MS was taken only for chromatographic verification purposes, and the involvement of absolute mass defect (MD) data in selenometabolite-specific screening was assessed by multivariate statistical tools. High focus was placed on screening efficiency and on the validation of discovered selenized molecules to avoid reporting of artefacts. From the >1000 molecular entries detected, selenium-containing molecules were picked up with a recovery rate of >88% and a false positive rate of <10%. Isotop(ologu)e pairs of 78Se-80Se and 80Se-82Se proved to be the most performant in the detection. On the basis of accurate mass information and hypothetical deamination processes, elemental composition could be proposed for 72 species out of the 75 selenium species encountered without taking into account selenocompound databases. Absolute MD data were used to significantly differentiate a potentially sample-specific subgroup of false positive molecular entities from non-selenized and selenized entities.