Food Purchase Behavior during The First Wave of COVID-19: The Case of Hungary

Coronavirus disease (SARSCoV-2) appeared in 2019 was confirmed as pandemic by the WHO on 11 March 2020. Stay-at-home order had an impact on consumers’ food purchase habits, as people around the world were able to leave their homes solely in extremely severe or urgent cases. In our research, we delve into the impact of COVID-19 pandemic on consumers’ food purchase habits. The research involved 3000 consumers during the first wave of coronavirus. The sample represents the Hungarian population by gender and age. To achieve the research goals, we applied multivariate statistical tools. The findings suggest that the pandemic could not change consumer attitude significantly, but the order of factors influencing purchases changed. Consumer motivation factors were organized into four well-distinguished factors: Healthy, domestic, and environmentally friendly choice; Usual taste and quality; Reasonable price; Shelf life. Due to the lack of outstanding data during segmentation, we developed four segments by hierarchical cluster analysis: Health- and environment-conscious women; Price sensitive young people; Taste-oriented men; Quality-oriented intellectuals. The results confirm that food manufacturers and traders need to be prepared for further restrictions in the future.

Insights into Magma Storage Beneath a Frequently Erupting Arc Volcano (Villarrica, Chile) from Unsupervised Machine Learning Analysis of Mineral Compositions

A key method to investigate magma dynamics is the analysis of the crystal cargoes carried by erupted magmas. These cargoes may comprise crystals that crystallize in different parts of the magmatic system (throughout the crust) and/or different times. While an individual eruption likely provides a partial view of the sub-volcanic plumbing system, compiling data from multiple eruptions builds a picture of the whole magmatic system. In this study we use machine learning techniques to analyze a large (>2000) compilation of mineral compositions from a highly active arc volcano: Villarrica, Chile. Villarrica's post-glacial eruptive activity (14 ka–present) displays large variation in eruptive style (mafic ignimbrites to Hawaiian effusive eruptions) yet its eruptive products have a near constant basalt-basaltic andesite bulk-rock composition. What, therefore, is driving explosive eruptions at Villarrica and can differences in storage dynamics be related to eruptive style? We used hierarchical cluster analysis to detect previously undetected structure in olivine, plagioclase and clinopyroxene compositions, revealing the presence of compositionally distinct clusters. Using rhyolite-MELTS thermodynamic modeling we related these clusters to intensive magmatic variables: temperature, pressure, water content and oxygen fugacity. Our results provide evidence for the existence of multiple discrete (spatial and temporal) magma reservoirs beneath Villarrica where melts differentiate and mix with incoming more primitive magma. The compositional diversity of an erupted crystal cargo strongly correlates with eruptive intensity, and we postulate that mixing between primitive and differentiated magma drives explosive activity at Villarrica.

Multi-Block Data Integration Analysis for Identifying and Validating Targeted N-Glycans as Biomarkers for Type II Diabetes Mellitus

Plasma N-glycan profiles have been shown to be defective in type II diabetes Mellitus (T2DM) and holds a promise to discovering biomarkers. The study comprised 232 T2DM patients and 219 healthy individuals. N-glycans were analysed by high-performance liquid chromatography. Principal component analysis (PCA), discriminatory analysis and agglomerative hierarchical cluster analysis (HCA) were performed. N-glycan groups (GPs 34, 32, 26, 31, 36 and 30) were significantly expressed in T2DM in component 1 and GPs 38 and 20 were related to T2DM in component 2. Four clusters based on the correlation of the expressive signatures of the 39 N-glycans across T2DM and controls. Cluster A, B, C and D had 16, 16, 4 and 3 N-glycans respectively, of which 11, 8, 1 and 1 were found to express differently between controls and T2DM in a univariate analysis P. Multi-block analysis revealed that trigalactosylated (G3), triantennary (TRIA), high branching (HB) and trisialylated (S3) expressed significantly highly in T2DM than healthy controls. A bipartite relevance network revealed that HB, monogalactosylated (G1) and G3 were central in the network and observed more connections, highlighting their importance in discriminating between T2DM and healthy controls. Investigation of these N-glycans can enhance the understanding of T2DM.

Hydrochemical and Stable Isotope Analyses Show Limited Interactions Between Groundwater and Lake Water in the Lake Bosomtwi Impact Crater, Ghana.

The relationship between groundwater and surface water in the Lake Bosumtwi impact crater has been assessed using hydrochemical data and stable water isotopes of δ18O and δD. This study aimed to define likely groundwater flow and recharge zones, estimate the rate of evaporation, and examine the relationship between the lake and groundwater in the study area. The results of Q-Mode hierarchical cluster analysis (HCA) clearly differentiate the lake water from the groundwater based on their spatial relationship. These preliminary results indicated that groundwater recharge occurs on the hilltops of the crater, where it is slightly acidic with low levels of dissolved minerals, characterized by short residence time and rapid unrestricted vertical infiltration and recharge. The groundwater becomes more mineralized with longer contact times and deeper circulation with the host rock, while it flows from the recharge areas towards the lake at lower elevations. Analyses of stable water isotopes of δ18O and δD showed a high evaporation rate on the lake surface, of ~90% with a relatively significant evaporative enrichment, whereas groundwater showed a relatively lower evaporation rate ranging between 54-60%. Both reservoirs do not appear to be hydraulically connected, and where such a connection exists, it is expected to favour the lake.

TYPOLOGY OF PRIVATE CAR USERS DURING COVID-19 PANDEMIC IN KAYURINGIN JAYA

<p>The Covid-19 Pandemic was indicated in March 2020, which has changed people's daily activities patterns. Implementing the restricting regulation imposed by the government made some of the people's daily activities diverted to an online system. As a result, community mobility has decreased, especially on private car usage. However, there is a shift in vehicle usage which many people are starting to switch their mode to the private car in daily travel. This condition was predicted would continue even after the Pandemic ends. The increase in private car usage will worsen the congestion than before the Covid-19 Pandemic appropriate steps and handling are needed to prevent the increase in congestion. One of them is by knowing the characteristics and journeys of private car users during the Covid-19 Pandemic. This research is a typology of private car users during the Covid-19 Pandemic to identify the similarities and differences in the characteristics possessed by each private car user through the typological groups formed. Through this research, it can be seen the movement patterns and characteristics of the people who use private cars. This study uses the Hierarchical Cluster Analysis method. The analysis is based on several variables such as private car usage frequency variables, socioeconomic characteristics variables, demographic variables, household variables, and household travel patterns object of this research is 107 households which are owners and use of private cars for further analysis and form clusters of private car users that have the same characteristics of each cluster. The typology of private car users is compiled based on the unique characteristics possessed by each cluster that is formed. The results of this study are 8 typologies of private car users, which are divided from intensive users to irregular users. Typology 1 has the largest number of respondents and dominates the frequency of trips by private car users. The benefit of this research for the government is as input in the formulation of policies to regulate the use of private cars so that the policies taken by the government can be right on target</p>

Comparative Study of the Petal Structure and Fragrance Components of the Nymphaea hybrid, a Precious Water Lily

Nymphaea hybrid, a precious water lily, is a widely-cultivated aquatic flower with high ornamental, economic, medicinal, and ecological value; it blooms recurrently and emits a strong fragrance. In the present study, in order to understand the volatile components of N. hybrid and its relationship with petals structure characteristics, the morphologies and anatomical structures of the flower petals of N. hybrid were investigated, and volatile compounds emitted from the petals were identified. Scanning and transmission electron microscopy were used to describe petal structures, and the volatile constituents were collected using headspace solid-phase microextraction (HS-SPME) fibers and analyzed using gas chromatography coupled with mass spectrometry (GC-MS). The results indicated that the density and degree of protrusion and the number of plastids and osmiophilic matrix granules in the petals play key roles in emitting the fragrance. There were distinct differences in the components and relative contents of volatile compounds among the different strains of N. hybrid. In total, 29, 34, 39, and 43 volatile compounds were detected in the cut flower petals of the blue-purple type (Nh-1), pink type (Nh-2), yellow type (Nh-3) and white type (Nh-4) of N. hybrid at the flowering stage, with total relative contents of 96.78%, 97.64%, 98.56%, and 96.15%, respectively. Analyses of these volatile components indicated that alkenes, alcohols, and alkanes were the three major types of volatile components in the flower petals of N. hybrid. The predominant volatile compounds were benzyl alcohol, pentadecane, trans-α-bergamotene, (E)-β-farnesene, and (6E,9E)-6,9-heptadecadiene, and some of these volatile compounds were terpenes, which varied among the different strains. Moreover, on the basis of hierarchical cluster analysis (HCA) and principal component analysis (PCA), the N. hybrid samples were divided into four groups: alcohols were the most important volatile compounds for Nh-4 samples; esters and aldehydes were the predominant volatiles in Nh-3 samples; and ketones and alkenes were important for Nh-2 samples. These compounds contribute to the unique flavors and aromas of the four strains of N. hybrid.

HS-SPME-GC–MS Volatile Profile Characterization of Peach (Prunus persica L. Batsch) Varieties Grown in the Eastern Balkan Peninsula

The volatile compounds of eight peach varieties (Prunus persica L.)—“Filina”, “Gergana”, “Ufo-4”, “July lady”, “Laskava”, “Flat Queen”, “Evmolpiya”, and “Morsiani 90”—growing in Bulgaria were analyzed for the first time. Gas chromatography–mass spectrometry (GC–MS) analysis and the HS-SPME technique revealed the presence of 65 volatile compounds; the main identified components were aldehydes, esters, and fatty acids. According to the provided principal component analysis (PCA) and hierarchical cluster analysis (HCA), the relative quantities of the identified volatile compounds depended on the studied peach variety. The results obtained could be successfully applied for the metabolic chemotaxonomy of peaches.

Analytical and Chemometric Characterization of Fino and Amontillado Sherries during Aging in Criaderas y Solera System

Fino and Amontillado are Sherry wines, produced in Marco de Jerez area (southern Spain), and aged in Criaderas y Solera system. Fino Sherry wine follows a biological aging process, under a veil of flor yeasts, while Amontillado Sherry wine shares the same biological aging firstly, followed by oxidative aging, which gives them special features. Organic acids, esters, higher alcohols, phenolic compounds and total dry extract of Sherries evolve during aging due to evaporation processes, physical-chemical reactions, wood contributions and microbiological activity. During aging, Sherry wines improve their organoleptic profile, as could be proved in the tasting sessions. Hierarchical Cluster Analysis and Factor Analysis with factor extraction using Principal Components of Sherry wines studied were carried out and natural groupings of the wines according to the type of aging and their age were observed. A strong correlation between the parameters analyzed and the aging of each wine has been seen in the Multiple Linear Regression studies, establishing two different models, one for each type of Sherry wine, that, with only four of all the variables studied estimated the wine age with more than 99% of confidence. This constitutes a useful tool to control the age of these Sherry wines in the winery.

The complex syndrome of functional neurological disorder

Background Patients with functional neurological disorders (FND) often present with multiple motor, sensory, psychological and cognitive symptoms. In order to explore the relationship between these common symptoms, we performed a detailed clinical assessment of motor, non-motor symptoms, health-related quality of life (HRQoL) and disability in a large cohort of patients with motor FND. To understand the clinical heterogeneity, cluster analysis was used to search for subgroups within the cohort. Methods One hundred fifty-two patients with a clinically established diagnosis of motor FND were assessed for motor symptom severity using the Simplified Functional Movement Disorder Rating Scale (S-FMDRS), the number of different motor phenotypes (i.e. tremor, dystonia, gait disorder, myoclonus, and weakness), gait severity and postural instability. All patients then evaluated each motor symptom type severity on a Likert scale and completed questionnaires for depression, anxiety, pain, fatigue, cognitive complaints and HRQoL. Results Significant correlations were found among the self-reported and all objective motor symptoms severity measures. All self-reported measures including HRQoL correlated strongly with each other. S-FMDRS weakly correlated with HRQoL. Hierarchical cluster analysis supplemented with gap statistics revealed a homogenous patient sample which could not be separated into subgroups. Conclusions We interpret the lack of evidence of clusters along with a high degree of correlation between all self-reported and objective measures of motor or non-motor symptoms and HRQoL within current neurobiological models as evidence to support a unified pathophysiology of ‘functional’ symptoms. Our results support the unification of functional and somatic syndromes in classification schemes and for future mechanistic and therapeutic research.