Search

We examined the state of "enchantment" as a consumer motivator, especially in the context of social and travel restrictions during COVID-19. An online purposive sample (n = 104) provided narrative data and ratings of past experiences versus future expectations of enchantment. Linguistic cluster analysis revealed five categories of these experiences termed Escapade, Nostalgia, Catharsis, Communion, and Attachment. These categories strongly align to hospitality-tourism offerings, but businesses must help consumers to overcome certain stated barriers (COVID and economic concerns) to future experiences of enchantment. Moreover, people often intend to relive their past experiences of enchantment but will opt for "escapades" when novelty is desired or repeats are unworkable. [ABSTRACT FROM AUTHOR]

Plant stoichiometry and nutrient allocation can reflect a plant's adaptation to environmental nutrient changes. However, the allocation strategies of carbon (C), nitrogen (N), and phosphorus (P) between leaf and fine root in response to wildfire have been poorly studied. Our primary objective was to elucidate the trade-off of elemental allocation between above- and belowground parts in response to the soil nutrient changes after a wildfire. We explored the allocation sloping exponents of C, N, and P between leaf and fine root at the species and community levels at four recovery periods (year 2, 10, 20, and 30) after moderately severe wildfire and one unburned treatment in boreal forests in Great Xing'an Mountains, northeast China. Compared with the unburned treatment, leaf C concentration decreased and fine root C increased at year 2 after recovery. The leaf N concentration at year 10 after recovery was higher than that of unburned treatment. Plant growth tended to be limited by P concentration at year 10 after recovery. Nutrient allocation between leaf and fine root differed between species and community levels, especially in the early recovery periods (i.e., 2 and 10 years). At the community level, the nutrient concentrations of the leaf changed more as compared to that of the fine root at year 2 after recovery when the fine root nutrients changed more than those of the leaf. The different C, N, and P allocation strategies advanced the understanding of plant adaptation to soil nutrient changes during the postfire ecosystem restoration. [ABSTRACT FROM AUTHOR]

Plant stoichiometry and nutrient allocation can reflect a plant’s adaptation to environmental nutrient changes. However, the allocation strategies of carbon (C), nitrogen (N), and phosphorus (P) between leaf and fine root in response to wildfire have been poorly studied. Our primary objective was to elucidate the trade-off of elemental allocation between above- and belowground parts in response to the soil nutrient changes after a wildfire. We explored the allocation sloping exponents of C, N, and P between leaf and fine root at the species and community levels at four recovery periods (year 2, 10, 20, and 30) after moderately severe wildfire and one unburned treatment in boreal forests in Great Xing’an Mountains, northeast China. Compared with the unburned treatment, leaf C concentration decreased and fine root C increased at year 2 after recovery. The leaf N concentration at year 10 after recovery was higher than that of unburned treatment. Plant growth tended to be limited by P concentration at year 10 after recovery. Nutrient allocation between leaf and fine root differed between species and community levels, especially in the early recovery periods (i.e., 2 and 10 years). At the community level, the nutrient concentrations of the leaf changed more as compared to that of the fine root at year 2 after recovery when the fine root nutrients changed more than those of the leaf. The different C, N, and P allocation strategies advanced the understanding of plant adaptation to soil nutrient changes during the postfire ecosystem restoration.

Background: High-intensity interval training (HIIT) is a well-established training modality to improve aerobic and anaerobic capacity. However, sex-specific aspects of different HIIT protocols are incompletely understood. This study aimed to compare two HIIT protocols with different recovery periods in moderately trained females and males and to investigate whether sex affects high-intensity running speed and speed decrement.Methods: Fifty moderately trained participants (30 females and 20 males) performed an exercise field test and were randomized by lactate threshold (LT) to one of two time- and workload-matched training groups. Participants performed a 4-week HIIT intervention with two exercise sessions/week: Group 1 (4 × 30,180 HIIT), 30-s all-out runs, 180-s active recovery and Group 2 (4 × 30,30 HIIT), 30-s all-out runs, 30-s active recovery. High-intensity runs were recorded, and speed per running bout, average speed per session, and speed decrement were determined. Blood lactate measurements were performed at baseline and follow-up at rest and immediately post-exercise.Results: Females and males differed in running speed at LT and maximal running speed determined during exercise field test (speed at LT, females: 10.65 ± 0.84 km h−1, males: 12.41 ± 0.98 km h−1, p < 0.0001; maximal speed, females: 14.55 ± 1.05 km h−1, males: 17.41 ± 0.68 km h−1, p < 0.0001). Estimated maximal oxygen uptake was ~52.5 ml kg−1 min−1 for females and 62.6 ml kg−1 min−1 for males (p < 0.0001). Analysis of HIIT protocols revealed an effect of sex on change in speed decrement (baseline vs. follow-up) in that females showed significant improvements only in the 4 × 30:30 HIIT group (p = 0.0038). Moreover, females performing the 4 × 30:30 protocol presented increased speed per bout and average speed per session at follow-up (all p ≤ 0.0204), while no effect was detected for females performing the 4 × 30:180 protocol. Peak blood lactate levels increased in all HIIT groups (all p < 0.05, baseline vs. follow-up), but males performing the 4 × 30:180 protocol showed no difference in lactate levels.Conclusions: If not matched for physical performance, females, but not males, performing a 4 × 30 HIIT protocol with shorter recovery periods (30 s) present increased average high-intensity running speed and reduced speed decrement compared to longer recovery periods (180 s). We conclude that female- and male-specific HIIT protocols should be established since anthropometric and physiological differences across sexes may affect training performance in real-world settings.

Background: High-intensity interval training (HIIT) is a well-established training modality to improve aerobic and anaerobic capacity. However, sex-specific aspects of different HIIT protocols are incompletely understood. This study aimed to compare two HIIT protocols with different recovery periods in moderately trained females and males and to investigate whether sex affects high-intensity running speed and speed decrement. Methods: Fifty moderately trained participants (30 females and 20 males) performed an exercise field test and were randomized by lactate threshold (LT) to one of two time- and workload-matched training groups. Participants performed a 4-week HIIT intervention with two exercise sessions/week: Group 1 (4 × 30,180 HIIT), 30-s all-out runs, 180-s active recovery and Group 2 (4 × 30,30 HIIT), 30-s all-out runs, 30-s active recovery. High-intensity runs were recorded, and speed per running bout, average speed per session, and speed decrement were determined. Blood lactate measurements were performed at baseline and follow-up at rest and immediately post-exercise. Results: Females and males differed in running speed at LT and maximal running speed determined during exercise field test (speed at LT, females: 10.65 ± 0.84 km h−1, males: 12.41 ± 0.98 km h−1, p < 0.0001; maximal speed, females: 14.55 ± 1.05 km h−1, males: 17.41 ± 0.68 km h−1, p < 0.0001). Estimated maximal oxygen uptake was ~52.5 ml kg−1 min−1 for females and 62.6 ml kg−1 min−1 for males (p < 0.0001). Analysis of HIIT protocols revealed an effect of sex on change in speed decrement (baseline vs. follow-up) in that females showed significant improvements only in the 4 × 30:30 HIIT group (p = 0.0038). Moreover, females performing the 4 × 30:30 protocol presented increased speed per bout and average speed per session at follow-up (all p ≤ 0.0204), while no effect was detected for females performing the 4 × 30:180 protocol. Peak blood lactate levels increased in all HIIT groups (all p < 0.05, baseline vs. follow-up), but males performing the 4 × 30:180 protocol showed no difference in lactate levels. Conclusions: If not matched for physical performance, females, but not males, performing a 4 × 30 HIIT protocol with shorter recovery periods (30 s) present increased average high-intensity running speed and reduced speed decrement compared to longer recovery periods (180 s). We conclude that female- and male-specific HIIT protocols should be established since anthropometric and physiological differences across sexes may affect training performance in real-world settings. [ABSTRACT FROM AUTHOR]

Upon continuous stress exposure, plants display attenuated metabolic stress responses due to regulatory feedback loops. Here, we have tested the hypothesis that pulsed stress exposure with intervening recovery periods should affect these feedback loops, thereby causing increased accumulation of stress‐induced metabolites. The response of Arabidopsis plantlets to continuous UV‐B exposure (Cuv) was compared with that of pulsed UV‐B exposure (Puv). The differential responses to Puv versus Cuv were monitored at the level of gene expression and metabolite accumulation, using wild type (WT) and different mutant lines. In comparison with Cuv, Puv increased sinapyl and flavonol (S + F) content, whereas adaptive growth attenuation was reduced. Furthermore, in a myb4 mutant (AtMYB4, repressor‐type R2R3‐MYB transcription factor), the S + F content was increased only for Cuv, but not beyond the level for Puv observed in WT. These observations and the ability of AtMYB4 to repress AtMYB12/AtMYB111‐mediated activation of target gene promoters (pCHS and pFLS) indicate that the increase of S + F content after Puv observed in WT plants results from reduced feedback inhibition by AtMYB4. The results support the notion that stress‐induced metabolic changes not necessarily cause a growth penalty. Furthermore, the observed Puv‐induced increase in flavonol accumulation may stimulate reevaluation of commercial plant production practices. Attenuation of plant secondary metabolite accumulation in response to continuous stress exposure is thought to depend on regulatory feedback loops. This study explores to what extent intervening stress‐free recovery periods can dampen these negative feedback loops. Treatment of Arabidopsis seedlings to UV‐B light revealed that pulsed stress exposure results in increased flavonol accumulation as compared with continuous exposure. Analysis of various mutant lines indicates that this phenomenon is due to a modified action of the transcriptional repressor AtMYB4. [ABSTRACT FROM AUTHOR]

Biausque, M. and Senechal, N., 2020. Analysis of two contrasting seasonal recovery periods of an open sandy beach, using high frequency DGPS surveys. In: Malvárez, G. and Navas, F. (eds.), Global Coastal Issues of 2020. Journal of Coastal Research, Special Issue No. 95, pp. 377-381. Coconut Creek (Florida), ISSN 0749-0208. High frequency DGPS surveys were undertaken for 2.5 years (November 2015 until April 2018) on an open sandy double barred beach in the SW of France (Biscarrosse Beach) covering three winter and two summer periods. On those latitudes, summers are usually described as seasonal recovery periods. The morphological response of the beach during two consecutive summer periods (2016 and 2017) has been analyzed to identify processes involved in seasonal recovery. Analysis of alongshore mean profiles indicates that the summer 2016 is marked by a progressive berm reconstruction, manly driven by cross-shore sediment transport. The beach recovery in 2016 can be characterized as complete with a stable berm through the summer season associated with steady beach cusps, and a seaward dune foot migration. During this summer the variations in volume of each section of the beach (intertidal/supratidal beach and dune) show sediment transport firstly orientated from the intertidal beach toward the supratidal one, and, later, driven from the supratidal beach to the dune. This cycle is coherent with recent observations described by Philips (2017). In contrast, the summer 2017 is characterized by an incomplete recovery, an unstable berm and so, a much more complex dynamic: the berm, rapidly rebuild (by the end of June), started to erode in July. Six sequences of cross-shore sediment exchanges are measurable along the season between the intertidal and the supratidal beach, inducing successive erosion/ accretion of both sections of the beach. Thus, according to those results summers 2016 and 2017 present variable spatial and temporal dynamics. Moreover, analysis of hydrodynamic and environmental factors indicate that recovery periods not only depend on hydrodynamic conditions, such as wave energy and tide, but also on winter/summer morphological coupling, and sandbar/beach coupling. [ABSTRACT FROM AUTHOR]

The performance of preclinical studies requires team work, thorough discussion prior to study start and careful monitoring during the course of the study. Many variables may influence the study outcome. Often they may be foreseeable and can be limited or even avoided, eg: study design such as insufficient duration, absence or insufficient duration of recovery period, insufficient group size, continuous versus cyclic administration, incorrect dose selection and omission of data from protein binding and similar testing; incorrect positive or negative control treatments; selection of inappropriate metabolising species, unhealthy strains, irrelevant sex, inappropriate age; misinformation or no information on the nature of the test item by sponsor leading to inadequate basic knowledge of test item-related lesions; poor knowledge of test system; analytical errors or development of inadequate methods; selection of established vs. new vehicles or inadequate knowledge on possible hazard by known vehicles. Others may occur accidentally during the study, eg: technical errors and artifacts; Independently, the report design and conclusions taken from the results obtained from the study may be a source of variability, eg ‘shopping lists’ instead of summaries or conclusions, use of different nomenclature during the execution of a number of studies with the same test item, misinformation and miscommunication. [ABSTRACT FROM AUTHOR]