Drivers of Spatial Heterogeneity in the Russian Forest Sector: A Multiple Factor Analysis

This study explored the regional differences in the forest industry and management via a Multiple Factor Analysis approach. The dataset used comprises all Russian regions and 34 variables that comprehensively describe the situation in the sector. Based on the Multiple Factor Analysis, the variables contributing most to the spatial heterogeneity in Russian forestry were divided into industrial and forestry factors. The regions leading in the development of the timber industry are mainly located in the Northwestern and Southeastern parts of Russia. They show similarities in high logging volumes, investment attractiveness, and competitiveness in foreign markets. However, a divergence was found between the Northwestern regions and the Siberian and the Far East territories in terms of forest management factors. The Western part of Russia benefits from the density of the population and infrastructure, and proximity to the national financial centers and European markets. By comparison, Asian Russia suffers from labor shortages caused by negative demographic trends and the negative consequences of climate change, resulting in an increase in forest losses and a lack of control, finance, and transport accessibility due to the vast territory. To alleviate regional inequalities, we propose the introduction of private ownership of forests, support for investment projects, and human capital development.

Chemical Composition and Sensory Evaluation of Saffron

The quality and economic value of saffron, one of the most counterfeited spices, are based on three key substances that are relatively easy to measure: crocines (colour); picrocrocines (bitter); safranal (odour impact). Despite being well-known, as their concentration is correlated to sensory intensity, a detailed sensory evaluation, performed by a trained panel, supported by advanced analytical approaches, may better show the relationships between saffron composition and sensory perception. Three saffron samples of different Italian origins (Sardinia and Tuscany) were evaluated by a trained sensory panel and their chemical composition was determined by HPLC (High Performance Liquid Chromatography) and spectrophotometry. Safranal concentration and the perceived odour intensity were positively correlated while relationships between picrocrocine and bitter perception were more complex to detect. By correlating (Multiple Factor Analysis) saffron sensorial and chemical profiles, this work aims at improving saffron characterisation while providing better information on the quality of this valuable spice.

Modelling Cabernet-Sauvignon wine sensory traits from spectrofluorometric data

Understanding how wine compositional traits can be related to sensory profiles is an important and ongoing challenge. Enhancing knowledge in this area could assist producers to select practices that deliver wines of the desired style and sensory specifications. This work reports the use of spectrofluorometry in conjunction with chemometrics for prediction, correlation, and classification based on sensory descriptors obtained using a rate-all-that-apply sensory assessment of Cabernet-Sauvignon wines (n = 26). Sensory results were first subjected to agglomerative hierarchical cluster analysis, which separated the wines into five clusters represented by different sensory profiles. The clusters were modelled in conjunction with excitation-emission matrix (EEM) data from fluorescence measurements using extreme gradient boosting discriminant analysis. This machine learning technique was able to classify the wines into the pre-defined sensory clusters with 100 % accuracy. Parallel factor analysis of the EEMs identified four main fluorophore components that were tentatively assigned as catechins, phenolic aldehydes, anthocyanins, and resveratrol (C1, C2, C3, and C4, respectively). Association of these four components with different sensory descriptors was possible through multiple factor analysis, with C1 relating to ‘dark fruits’ and ‘savoury’, C2 with ‘barnyard’, C3 with ‘cooked vegetables’ and ‘vanilla/chocolate’, and C4 with ‘barnyard’ and a lack of C1 descriptors. Partial least squares regression modelling was undertaken with EEM data and sensory results, with a model for perceived astringency being able to predict the panel scores with 68.1 % accuracy. These encouraging outcomes pave the way for further studies that relate sensory traits to fluorescence data and move research closer to the ultimate goal of predicting wine sensory expression from a small number of compositional factors.

Global Food Security, Economic and Health Risk Assessment of the COVID-19 Epidemic

This study addresses the complexity of global pandemic (COVID) exposures and explores how sustainable development relates to economic and health risks and food security. Multiple factor analysis (MFA) is applied to compute the links among blocks of variables, and results are validated by random sampling with bootstrapping, exhaustive and split-half techniques, and analysis of variance (ANOVA) to test the differences of the MFA factors within the different stages of competitiveness. Comparing the MFA factors suggests that higher competitiveness is correlated with better food security and natural resilience and the tremendous economic downturn; the most competitive countries have lower exposures to health risks. In addition, the risk of pandemics appears to be lower with well-established public health care (HC) system services and good health for the population. The study also underlines that the economic and health systems are unfortunately inadequate to deal with a crisis of this magnitude. Although the countries least affected by the epidemic are the most competitive, they cannot protect people and the economy effectively. Formulating appropriate global responses is a challenge, but the results may lead to more nuanced findings regarding treatment policies that can be addressed at the country level.

Does It Matter Where Design Teams Come From in Design Studies?

Professionals need to collaborate with multiple stakeholders in product development to stay competitive and to innovate. Through their values and mission, companies develop a specific working environment that can lead to the development of design methods and tools. In this article, we study design team dynamics of professional engineers working in two different organizations. We aim at identifying differences in team behaviors between teams drawn from two different organizations. The goal is twofold. At a theoretical level, we aim at gaining a better understanding of the effect of work culture on design team behaviors. At a methodological level, we explore whether grouping teams from different organizations into a single larger sample to obtain better reliability is relevant. To do this, we compared two cohorts of teams based on which company engineers worked at. Both companies are international organizations employing more than 50,000 collaborators worldwide. Teams of three engineers worked on designing a next-generation personal assistant and entertainment system for the year 2025. We analyzed each team’s design interactions and behaviors using quantitative tools (Multiple Factor Analysis and Correspondence Analysis). Results from this exploratory analysis highlight different behaviors between cohorts as well as a common overall approach to team design thinking.

A unified framework for the integration of multiple hierarchical clusterings or networks from multi-source data

Background Integrating data from different sources is a recurring question in computational biology. Much effort has been devoted to the integration of data sets of the same type, typically multiple numerical data tables. However, data types are generally heterogeneous: it is a common place to gather data in the form of trees, networks or factorial maps, as these representations all have an appealing visual interpretation that helps to study grouping patterns and interactions between entities. The question we aim to answer in this paper is that of the integration of such representations. Results To this end, we provide a simple procedure to compare data with various types, in particular trees or networks, that relies essentially on two steps: the first step projects the representations into a common coordinate system; the second step then uses a multi-table integration approach to compare the projected data. We rely on efficient and well-known methodologies for each step: the projection step is achieved by retrieving a distance matrix for each representation form and then applying multidimensional scaling to provide a new set of coordinates from all the pairwise distances. The integration step is then achieved by applying a multiple factor analysis to the multiple tables of the new coordinates. This procedure provides tools to integrate and compare data available, for instance, as tree or network structures. Our approach is complementary to kernel methods, traditionally used to answer the same question. Conclusion Our approach is evaluated on simulation and used to analyze two real-world data sets: first, we compare several clusterings for different cell-types obtained from a transcriptomics single-cell data set in mouse embryos; second, we use our procedure to aggregate a multi-table data set from the TCGA breast cancer database, in order to compare several protein networks inferred for different breast cancer subtypes.

Study on the Lamb Meat Consumer Behavior in Brazil

In Brazil, the sheep market, including lamb meat consumption, is regionalized, and the consumption of lamb meat is higher in production areas; yet, consumption of lamb still remains below that of other meat livestock. The aim of this study was to identify the profile of Brazilian lamb meat consumers in order to understand their behavior in relation to food in general and on the consumption of this species. Therefore, a survey on consumer habits and preferences regarding food buying and consumption habits, their preferences in relation to the quality attributes of lamb meat, and sociodemographic characterization was performed. Data collected were analyzed by nonlinear canonic relationship analysis and categorical principal component analysis, followed by multiple factor analysis. Three consumer profiles were identified: traditional, interested, and disinterested, and a fourth group was considered independent but could not be described. Among lamb meat consumers, men with higher income seemed to be more frequent consumers than the others, and the intrinsic characteristics of meat quality, especially color and freshness, were the most important at the time of purchase. Thus, the results could be important to the industry in order to guide marketing strategies to certain niche markets.

Symptomatic DVT One Month After TKA Was Associated With Tourniquet Reuse During Operation

Background: DVT (Deep vein thrombosis) was one of the most common and sever complications after TKA (total knee arthroplasty). When tourniquet use and sometime the reuse was performed for surgery convenient of TKA. There was not sure if tourniquet use or reuse during operation would increase DVT after TKA.Methods: A retrospective study was performed about primarily TKA in our institute continuous 5 years. Univariate analysis was performed and potential intervention variables (P ≤ 0.1) were included in multiple factor analysis to certain the independent risk factors.Results: 807 patients (431 females and 376 males) were included with mean age was 65 years old. 3.84% (31 patients) were occurred sym-DVT (symptomatic DVT) one month after TKA with median time of diagnosis was 17 days. Incidence of sym-DVT after tourniquet reuse was significant high than once use and no use (7.25% versus 2.54% and 1.86%, P = 0.014 and 0.072), mean time of tourniquet use was 90.46 ± 14.28 mins in once and 106.58 ± 16.13 mins in reuse (P = 0.045). After multiple analysis, independent risk factors were revealed as history of tumor (P = 0.021), history of DVT (P < 0.001) and tourniquet reuse (P = 0.005).Conclusions: Tourniquet reuse was associated with highly incidence of sym-DVT other than history of tumor and DVT. There should be once use of tourniquet for prevent sym-DVT.

On the Appropriateness of Using the Concept of «Competitiveness»

Changes happening in the internal and external business environment in the 21st century intensify the need for improving approaches to the evaluation of effectiveness of economic entities on different levels of economic analysis: micro, meso and macro. Although there is a significant theoretical background, the most common category for an assessment of the condition of an economic entity in the economic theory is «competitiveness», which was proposed by Adam Smith. Starting from the second half of the 20th century, specialists have been using this term for characterizing efficiency of individuals, cities, industries, regions and countries. Today, academics have developed unique ideas about the content of this category: methods of assessment of the reached level; factors which influence the category on different levels of economic analysis. However, the paradox is that the theoretical foundation cannot solve practical problems and answer relevant questions. In the article, the authors try to show that making the term «competitiveness» unified is unreasonable, it is based on factual material and opinions of national and foreign researchers. The authors formulate a hypothesis about the necessity of terminological disintegration while making multiple factor analysis: identifying independent groups of phenomena all of which are responsible for a specific condition type of a subject / object.

2018 Survey of antimicrobial drug use and stewardship practices in adult cows on California dairies: post-Senate Bill 27

Background A survey of California (CA) dairies was performed in spring 2018 to characterize antimicrobial stewardship practices, antimicrobial drug (AMD) use, and health management of adult cows on CA dairies since the implementation of the Veterinary Feed Directive (VFD) and the CA Senate Bill 27 (SB 27). Effective January 1, 2017, the U.S. Food and Drug Administration (FDA) implemented regulatory changes requiring veterinary oversight for therapeutic uses of medically-important antimicrobial drugs (MIADs) administered in feed (VFD) and water (veterinary prescription). Similarly, effective January 1, 2018, the CA legislature enacted California Food and Agricultural Code (FAC) 14400–14408, formerly known as Senate Bill 27 (SB 27) requiring veterinary prescriptions for all other dosage forms of MIADs. Methods The questionnaire consisted of 43 questions partitioned into three sections to assess herd information, management practices, and AMD use and perspectives. The questionnaire was mailed to 1,282 grade A licensed dairies in CA and 149 responses (11.6%) were collected from 19 counties across the three defined regions of CA: Northern CA (NCA), Northern San Joaquin Valley (NSJV), and Greater Southern CA (GSCA). Results Most dairies reported treating all dry cows with intramammary AMD and/or teat sealant at the end of a lactation (87.2%). In 92.3% of dairies, producers relied on the veterinarian for information about AMD used to treat cows. Treatment duration for cows treated with AMD was based on the drug manufacturer’s label and veterinarian’s instructions in most dairies (98.6%). Most respondents to the survey confirmed having a valid veterinarian-client-patient-relationship (VCPR) for their dairies (91.7%), participated in animal welfare audit programs (81.8%) and dairy quality assurance programs (52.9%). Approximately 98.6% respondents were aware that all uses of MIADs in livestock required a veterinary feed directive (VFD) or prescription and are no longer sold over-the-counter (OTC) in CA since January 1, 2018. Multiple factor analysis (MFA) was performed and identified seven components composed of 21 variables (questions) that explained 99.7% of the total variance in the data. Hierarchical cluster analysis on the principal coordinates of the MFA based on conventional dairy survey responses identified two clusters characterized as large conventional dairies (median herd size: 1,265 cows) and mid-sized conventional dairies (median herd size: 715 cows) mostly in GSCA and NSJV. The organic dairies grouped into a single cluster of median herd size of 325 cows mostly in NCA. Conclusions The survey results contribute to the knowledge of AMD use and antimicrobial stewardship practices on CA dairies since the implementation of the SB 27 and VFD laws and provide useful information for future evaluation of resistance-related risk in adult cows.