Babeș-Bolyai University

Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. Atmospheric emissions and concentrations of CH4 continue to increase, making CH4 the second most important human-influenced greenhouse gas in terms of climate forcing, after carbon dioxide (CO2). The relative importance of CH4 compared to CO2 depends on its shorter atmospheric\nlifetime, stronger warming potential, and variations in atmospheric growth rate over the past decade, the causes of which are still debated. Two major challenges in reducing uncertainties in the atmospheric growth rate arise from the variety of geographically overlapping CH4 sources and from the destruction of CH4 by short-lived hydroxyl radicals (OH). To address these challenges, we have established a consortium of multidisciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate new research aimed at improving and regularly updating the global methane budget. Following Saunois et al. (2016), we present here the second version of the living review paper dedicated to the decadal methane budget, integrating results of top-down studies (atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up estimates (including process-based models for estimating land surface emissions and atmospheric chemistry, inventories of anthropogenic emissions, and data-driven extrapolations).\nFor the 2008–2017 decade, global methane emissions are estimated by atmospheric inversions (a top-down approach) to be 576 TgCH4 yr-1 (range 550–594, corresponding to the minimum and maximum estimates of the model ensemble). Of this total, 359 TgCH4 yr-1 or 60% is attributed to anthropogenic sources, that is emissions caused by direct human activity (i.e. anthropogenic emissions; range 336–376 TgCH4 yr-1 or 50 %–65 %). The mean annual total emission for the new decade (2008–2017) is 29 TgCH4 yr-1 larger than our estimate for the previous decade (2000–2009), and 24 TgCH4 yr-1 larger than the one reported in the previous budget for 2003–2012 (Saunois et al., 2016). Since 2012, global CH4 emissions have been tracking the warmest scenarios assessed by the Intergovernmental Panel on Climate Change. Bottom-up methods suggest almost 30% larger global emissions (737 TgCH4 yr-1, range 594–881) than top-down inversion methods. Indeed, bottom-up estimates for natural sources such as natural wetlands, other inland water systems, and geological sources are higher than top-down estimates. The atmospheric constraints on the top-down budget suggest that at least some of these bottom-up emissions are overestimated. The latitudinal distribution of atmospheric observation-based emissions indicates a predominance of tropical emissions (∼65% of the global budget, <30◦N) compared to mid-latitudes (∼30 %, 30–60◦ N) and high northern latitudes (∼4 %, 60–90◦N). The most important source of uncertainty in the methane budget is attributable to natural emissions, especially those from wetlands and other inland waters.\nSome of our global source estimates are smaller than those in previously published budgets (Saunois et al., 2016; Kirschke et al., 2013). In particular wetland emissions are about 35 TgCH4 yr-1 lower due to improved partition wetlands and other inland waters. Emissions from geological sources and wild animals are also found to be smaller by 7 TgCH4 yr-1 by 8 TgCH4 yr-1, respectively. However, the overall discrepancy between bottom-up and top-down estimates has been reduced by only 5% compared to Saunois et al. (2016), due to a higher estimate of emissions from inland waters, highlighting the need for more detailed research on emissions factors. Priorities for improving the methane budget include (i) a global, high-resolution map of water-saturated soils and inundated areas emitting methane based on a robust classification of different types of emitting habitats; (ii) further development of process-based models for inland-water emissions; (iii) intensification of methane observations at local scales (e.g., FLUXNET-CH4 measurements) and urban-scale monitoring to constrain bottom-up land surface models, and at regional scales (surface networks and satellites) to constrain atmospheric inversions; (iv) improvements of transport models and the representation of photochemical sinks in top-down inversions; and (v) development of a 3D variational inversion system using isotopic and/or co-emitted species such as ethane to improve source partitioning.\nThe data presented here can be downloaded from https://doi.org/10.18160/GCP-CH4-2019 (Saunois et al.,\n2020) and from the Global Carbon Project

This study of the international partner selection of firms from emerging (Mexico, Poland, and Romania) and developed (Canada, France, and the United States) markets supports resource-based and organizational learning explanations of such partner selection, a critical factor for success with international strategic alliances. Emerging market firms emphasized financial assets, technical capabilities, intangible assets, and willingness to share expertise in selection of partners more than developed market firms. In contrast, developed market firms tried to leverage their resources through partner selection. In particular, they emphasized unique competencies and local market knowledge and access in their partner selection more than emerging market firms.

Climate change affects human health; however, there have been no large-scale, systematic efforts to quantify the heat-related human health impacts that have already occurred due to climate change. Here, we use empirical data from 732 locations in 43 countries to estimate the mortality burdens associated with the additional heat exposure that has resulted from recent human-induced warming, during the period 1991–2018. Across all study countries, we find that 37.0% (range 20.5–76.3%) of warm-season heat-related deaths can be attributed to anthropogenic climate change and that increased mortality is evident on every continent. Burdens varied geographically but were of the order of dozens to hundreds of deaths per year in many locations. Our findings support the urgent need for more ambitious mitigation and adaptation strategies to minimize the public health impacts of climate change. Current and future climate change is expected to impact human health, both indirectly and directly, through increasing temperatures. Climate change has already had an impact and is responsible for 37% of warm-season heat-related deaths between 1991 and 2018, with increases in mortality observed globally.

A very effective and simple way to produce silver colloids for surface-enhanced Raman scattering (SERS) is reported. Reduction of silver nitrate with hydroxylamine hydrochloride at alkaline pH and at room temperature yields highly sensitive SERS colloids within a short time. The so-produced colloids can be used for SERS spectroscopy immediately after preparation. The overall procedure is fast, simple, and characterized by a high preparation success rate. Changing the mixing order and rate of the two involved solutions, silver nitrate and hydroxylamine hydrochloride containing sodium hydroxide, one can control the size and dispersion of the produced colloids. The obtained colloids have been characterized by UV−vis spectroscopy, transmission electron microscopy, and SERS using a 1064 nm laser line on a Fourier transform and a 785 nm laser line on a dispersive Raman spectrometer. The SERS enhancement factor of the hydroxylamine-reduced silver colloids was tested using crystal violet, rhodamine 6G, methylene blue, and 9-aminoacridine. It was found that for both excitation lines sensitivities comparable to those achievable with a Lee−Meisel silver colloid were obtained thus rendering the new colloid advantageous because of its significantly simpler and faster synthesis.

Partial least squares structural equation modeling (PLS-SEM) has become a standard tool for analyzing complex inter-relationships between observed and latent variables in tourism and numerous other fields of scientific inquiry. Along with the recent surge in the method’s use, research has contributed several complementary methods for assessing the robustness of PLS-SEM results. Although these improvements are documented in extant literature, research on tourism has been slow to adopt the relevant complementary methods. This article illustrates the use of recent advances in PLS-SEM, designed to ensure structural model results’ robustness in terms of nonlinear effects, endogeneity, and unobserved heterogeneity in a PLS-SEM framework. Our overarching aim is to encourage the routine use of these complementary methods to increase methodological rigor in the field.

Abstract Structural equation modeling is a multivariate data analysis method for analyzing complex relationships among constructs and indicators. To estimate structural equation models, researchers generally draw on two methods: covariance-based SEM (CB-SEM) and partial least squares SEM (PLS-SEM). Whereas CB-SEM is primarily used to confirm theories, PLS represents a causal–predictive approach to SEM that emphasizes prediction in estimating models, whose structures are designed to provide causal explanations. PLS-SEM is also useful for confirming measurement models. This chapter offers a concise overview of PLS-SEM’s key characteristics and discusses the main differences compared to CB-SEM. The chapter also describes considerations when using PLS-SEM and highlights situations that favor its use compared to CB-SEM.

Purpose Partial least squares structural equation modeling (PLS-SEM) has attracted much attention from both methodological and applied researchers in various disciplines – also in hospitality management research. As PLS-SEM is relatively new compared to other multivariate analysis techniques, there are still numerous open questions and uncertainties in its application. This study aims to address this important issue by offering guidance regarding its use in contexts with which researchers struggle. Design/methodology/approach The authors examine the most prominent questions and answers posed in a well-known PLS-SEM discussion forum. The authors do so by using a text analysis technique to identify the most salient topics. Findings The data analysis identifies three salient PLS-SEM topics (i.e. bootstrapping and significance testing, higher-order constructs and moderation). Research limitations/implications The results allow us to address the PLS-SEM community’s main methodological issues. The authors discuss each area separately and provide explanations and guidelines. Practical implications The guidelines on the most important PLS-SEM topics provide decision-making and application aids. In this way, the authors make a decisive contribution to clarifying ambiguities when applying the PLS-SEM method in hospitality management research and other disciplines. Originality/value There has as yet been no systematic analysis of this kind in the field of PLS-SEM; the authors, therefore, present the first research results. The findings and recommendations provide guidance for PLS-SEM applications in hospitality research and practice.

Abstract Partial least squares structural equation modeling (PLS‐SEM) is an essential element of marketing researchers' methodological toolbox. During the last decade, the PLS‐SEM field has undergone massive developments, raising the question of whether the method's users are following the most recent best practice guidelines. Extending prior research in the field, this paper presents the results of a new analysis of PLS‐SEM use in marketing research, focusing on articles published between 2011 and 2020 in the top 30 marketing journals. While researchers were more aware of the when's and how's of PLS‐SEM use during the period studied, we find that there continues to be some delay in the adoption of model evaluation's best practices. Based on our review results, we provide recommendations for future PLS‐SEM use, offer guidelines for the method's application, and identify areas of further research interest.

Polydopamine (PDA) formed by the oxidation of dopamine is an important polymer, in particular, for coating various surfaces. It is composed of dihydroxyindole, indoledione, and dopamine units, which are assumed to be covalently linked. Although PDA has been applied in a manifold way, its structure is still under discussion. Similarities have been observed in melanins/eumelanins as naturally occurring, deeply colored polymer pigments derived from L-DOPA. Recently, an alternative structure was proposed for PDA wherein dihydroxyindoline, indolinedione, and eventually dopamine units are not covalently linked to each other but are held together by hydrogen bonding between oxygen atoms or π stacking. In this study, we show that this structural proposal is very unlikely to occur taking into account unambiguous results obtained by different analytical methods, among them (13)C CPPI MAS NMR (cross-polarization polarization-inversion magic angle spinning NMR), (1)H MAS NMR (magic angle spinning NMR), and ES-HRMS (electrospray ionization high-resolution mass spectrometry) for the first time in addition to XPS (X-ray photoelectron spectroscopy) and FTIR spectroscopy. The results give rise to a verified structural assignment of PDA wherein dihydroxyindole and indoledione units with different degrees of (un)saturation are covalently linked by C-C bonds between their benzene rings. Furthermore, proof of open-chain (dopamine) monomer units in PDA is provided. Advanced DFT calculations imply the arrangements of several PDA chains preferably by quinone-hydroquinone-type interactions in a parallel or antiparallel manner. From all of these results, a number of hypotheses published before could be experimentally supported or were found to be contradictory, thus leading to a better understanding of the PDA structure.

Retrograde tracer injections in 29 of the 91 areas of the macaque cerebral cortex revealed 1,615 interareal pathways, a third of which have not previously been reported. A weight index (extrinsic fraction of labeled neurons [FLNe]) was determined for each area-to-area pathway. Newly found projections were weaker on average compared with the known projections; nevertheless, the 2 sets of pathways had extensively overlapping weight distributions. Repeat injections across individuals revealed modest FLNe variability given the range of FLNe values (standard deviation <1 log unit, range 5 log units). The connectivity profile for each area conformed to a lognormal distribution, where a majority of projections are moderate or weak in strength. In the G29 × 29 interareal subgraph, two-thirds of the connections that can exist do exist. Analysis of the smallest set of areas that collects links from all 91 nodes of the G29 × 91 subgraph (dominating set analysis) confirms the dense (66%) structure of the cortical matrix. The G29 × 29 subgraph suggests an unexpectedly high incidence of unidirectional links. The directed and weighted G29 × 91 connectivity matrix for the macaque will be valuable for comparison with connectivity analyses in other species, including humans. It will also inform future modeling studies that explore the regularities of cortical networks.

In mountainous regions, climate warming is expected to shift species' ranges to higher altitudes. Evidence for such shifts is still mostly from revisitations of historical sites. We present recent (2001 to 2008) changes in vascular plant species richness observed in a standardized monitoring network across Europe's major mountain ranges. Species have moved upslope on average. However, these shifts had opposite effects on the summit floras' species richness in boreal-temperate mountain regions (+3.9 species on average) and Mediterranean mountain regions (-1.4 species), probably because recent climatic trends have decreased the availability of water in the European south. Because Mediterranean mountains are particularly rich in endemic species, a continuation of these trends might shrink the European mountain flora, despite an average increase in summit species richness across the region.

Here, palaeobotanical and genetic data for common beech (Fagus sylvatica) in Europe are used to evaluate the genetic consequences of long-term survival in refuge areas and postglacial spread. Four large datasets are presented, including over 400 fossil-pollen sites, 80 plant-macrofossil sites, and 450 and 600 modern beech populations for chloroplast and nuclear markers, respectively. The largely complementary palaeobotanical and genetic data indicate that: (i) beech survived the last glacial period in multiple refuge areas; (ii) the central European refugia were separated from the Mediterranean refugia; (iii) the Mediterranean refuges did not contribute to the colonization of central and northern Europe; (iv) some populations expanded considerably during the postglacial period, while others experienced only a limited expansion; (v) the mountain chains were not geographical barriers for beech but rather facilitated its diffusion; and (vi) the modern genetic diversity was shaped over multiple glacial-interglacial cycles. This scenario differs from many recent treatments of tree phylogeography in Europe that largely focus on the last ice age and the postglacial period to interpret genetic structure and argue that the southern peninsulas (Iberian, Italian and Balkan) were the main source areas for trees in central and northern Europe.

BACKGROUND: Exposure to cold or hot temperatures is associated with premature deaths. We aimed to evaluate the global, regional, and national mortality burden associated with non-optimal ambient temperatures. METHODS: In this modelling study, we collected time-series data on mortality and ambient temperatures from 750 locations in 43 countries and five meta-predictors at a grid size of 0·5° × 0·5° across the globe. A three-stage analysis strategy was used. First, the temperature-mortality association was fitted for each location by use of a time-series regression. Second, a multivariate meta-regression model was built between location-specific estimates and meta-predictors. Finally, the grid-specific temperature-mortality association between 2000 and 2019 was predicted by use of the fitted meta-regression and the grid-specific meta-predictors. Excess deaths due to non-optimal temperatures, the ratio between annual excess deaths and all deaths of a year (the excess death ratio), and the death rate per 100 000 residents were then calculated for each grid across the world. Grids were divided according to regional groupings of the UN Statistics Division. FINDINGS: Globally, 5 083 173 deaths (95% empirical CI [eCI] 4 087 967-5 965 520) were associated with non-optimal temperatures per year, accounting for 9·43% (95% eCI 7·58-11·07) of all deaths (8·52% [6·19-10·47] were cold-related and 0·91% [0·56-1·36] were heat-related). There were 74 temperature-related excess deaths per 100 000 residents (95% eCI 60-87). The mortality burden varied geographically. Of all excess deaths, 2 617 322 (51·49%) occurred in Asia. Eastern Europe had the highest heat-related excess death rate and Sub-Saharan Africa had the highest cold-related excess death rate. From 2000-03 to 2016-19, the global cold-related excess death ratio changed by -0·51 percentage points (95% eCI -0·61 to -0·42) and the global heat-related excess death ratio increased by 0·21 percentage points (0·13-0·31), leading to a net reduction in the overall ratio. The largest decline in overall excess death ratio occurred in South-eastern Asia, whereas excess death ratio fluctuated in Southern Asia and Europe. INTERPRETATION: Non-optimal temperatures are associated with a substantial mortality burden, which varies spatiotemporally. Our findings will benefit international, national, and local communities in developing preparedness and prevention strategies to reduce weather-related impacts immediately and under climate change scenarios. FUNDING: Australian Research Council and the Australian National Health and Medical Research Council.

Abstract We present here the results of pollen analysis of two sequences of about 8.06 m and 11.90 m length, originating from two adjacent peat bogs in the southern part of Transylvania province, Romania (155 and 122 pollen spectra). The vegetation record, which is supported by 17 14 C dates, begins in the Late Glacial interstadial when forest recolonisation began with the development of Pinus , without a pioneer Betula phase. Picea began to expand from regional refuges. After a well‐defined Younger Dryas, the Holocene opens with the expansion of Betula , Ulmus and Picea , followed, at about 10 400 cal. yr BP, by Fraxinus , Quercus and Tilia . The Corylus optimum is correlated with the Atlantic chronozone (after 8600 cal. yr BP). The local establishment of Carpinus occurred at about 6500 cal. yr BP, with a maximum at about 5700 cal. yr BP. Fagus pollen is regularly recorded after 8200 cal. yr BP. This taxon became dominant at about 3700 cal. yr BP. The first indications of human activities appear at around 7200 cal. yr BP. Copyright © 2005 John Wiley &amp; Sons, Ltd.

A summary of the most important technological applications employing reduced graphene oxide.

Genetic diversity provides the basic substrate for evolution, yet few studies assess the impacts of global climate change (GCC) on intraspecific genetic variation. In this review, we highlight the importance of incorporating neutral and non-neutral genetic diversity when assessing the impacts of GCC, for example, in studies that aim to predict the future distribution and fate of a species or ecological community. Specifically, we address the following questions: Why study the effects of GCC on intraspecific genetic diversity? How does GCC affect genetic diversity? How is the effect of GCC on genetic diversity currently studied? Where is potential for future research? For each of these questions, we provide a general background and highlight case studies across the animal, plant and microbial kingdoms. We further discuss how cryptic diversity can affect GCC assessments, how genetic diversity can be integrated into studies that aim to predict species' responses on GCC and how conservation efforts related to GCC can incorporate and profit from inclusion of genetic diversity assessments. We argue that studying the fate of intraspecifc genetic diversity is an indispensable and logical venture if we are to fully understand the consequences of GCC on biodiversity on all levels.

This perspective article on using partial least squares structural equation modelling (PLS-SEM) is intended as a guide for authors who wish to publish datasets that can be analysed with this method as stand-alone data articles. Stand-alone data articles are different from supporting data articles in that they are not linked to a full research article published in another journal. Nevertheless, authors of stand-alone data articles will be required to clearly demonstrate and justify the usefulness of their dataset. This perspective article offers actionable recommendations regarding the conceptualisation phase, the types of data suitable for PLS-SEM and quality criteria to report, which are generally applicable to studies using PLS-SEM. We also present adjusted versions of the HTMT metric for discriminant validity testing that broaden its applicability. Further, we highlight the benefit of linking data articles to already published research papers that employ the PLS-SEM method.

Small-world networks provide an appealing description of cortical architecture owing to their capacity for integration and segregation combined with an economy of connectivity. Previous reports of low-density interareal graphs and apparent small-world properties are challenged by data that reveal high-density cortical graphs in which economy of connections is achieved by weight heterogeneity and distance-weight correlations. These properties define a model that predicts many binary and weighted features of the cortical network including a core-periphery, a typical feature of self-organizing information processing systems. Feedback and feedforward pathways between areas exhibit a dual counterstream organization, and their integration into local circuits constrains cortical computation. Here, we propose a bow-tie representation of interareal architecture derived from the hierarchical laminar weights of pathways between the high-efficiency dense core and periphery.

The growing presence of social media influencers (SMIs) is increasingly modulating consumer behaviour in the travel industry. Trust is a vitally important topic in influencer and tourism marketing and is responsible for creating and maintaining successful long-term relationships between organizations and consumers. This study uses customer journey theory to explain the impact of SMI trust on customer travel decision-making and focuses on evaluating the role of customer journey constructs (including desire, information search, evaluating alternatives, purchase decisions, satisfaction and experience sharing) in mediating the interrelation between SMI trust and the dimensions of customer journeys. Using Smart PLS to analyze the data collected, the results indicate that consumer trust in SMIs has a positive effect on each phase of travel decision-making. Moreover, each step of the decision-making journey mediates the trust effect on the next step, having a spillover effect on the whole journey, implying continuous SMI input. Tourism marketers are advised to use SMIs to increase and stimulate the desire to travel as clearly, a means by which consumers search for information about their next journey. Besides SMIs as a marketing tool, their trustworthiness serves as a highly important aspect to successfully influence tourists’ destination decision making.

Virtual reality exposure therapy (VRET) is a promising intervention for the treatment of the anxiety disorders. The main objective of this meta-analysis is to compare the efficacy of VRET, used in a behavioral or cognitive-behavioral framework, with that of the classical evidence-based treatments, in anxiety disorders. A comprehensive search of the literature identified 23 studies (n = 608) that were included in the final analysis. The results show that in the case of anxiety disorders, (1) VRET does far better than the waitlist control; (2) the post-treatment results show similar efficacy between the behavioral and the cognitive behavioral interventions incorporating a virtual reality exposure component and the classical evidence-based interventions, with no virtual reality exposure component; (3) VRET has a powerful real-life impact, similar to that of the classical evidence-based treatments; (4) VRET has a good stability of results over time, similar to that of the classical evidence-based treatments; (5) there is a dose-response relationship for VRET; and (6) there is no difference in the dropout rate between the virtual reality exposure and the in vivo exposure. Implications are discussed.