This chapter addresses the concepts and methods to assess quantitative indicators of Climate-Smart Forestry (CSF) at stand and management unit levels. First, the basic concepts for developing a framework for assessing CSF were reviewed. The suitable properties of indicators and methods for normalization, weighting, and aggregation were summarized. The proposed conceptual approach considers the CSF assessment as an adaptive learning process, which integrates scientific knowledge and participatory approaches. Then, climate smart indicators were applied on long-term experimental plots to assess CSF of spruce-fir-beech mixed mountain forest. Redundancy and trade-offs between indicators, as well as their sensitivity to management regimes, were analyzed with the aim of improving the practicability of indicators. At the management unit level, the roles of indicators in the different phases of forest management planning were reviewed. A set of 56 indicators were used to assess their importance for management planning in four European countries. The results indicated that the most relevant indicators differed from the set of Pan-European indicators of sustainable forest management. Finally, we discussed results obtained and future challenges, including the following: (i) how to strengthen indicator selections and CSF assessment at stand level, (ii) the potential integration of CSF indicators into silvicultural guidelines, and (iii) the main challenges for integrating indicators into climate-smart forest planning.

Understanding tree and stand growth dynamics in the frame of climate change calls for large-scale analyses. For analysing growth patterns in mountain forests across Europe, the CLIMO consortium compiled a network of observational plots across European mountain regions. Here, we describe the design and efficacy of this network of plots in monospecific European beech and mixed-species stands of Norway spruce, European beech, and silver fir.First, we sketch the state of the art of existing monitoring and observational approaches for assessing the growth of mountain forests. Second, we introduce the design, measurement protocols, as well as site and stand characteristics, and we stress the innovation of the newly compiled network. Third, we give an overview of the growth and yield data at stand and tree level, sketch the growth characteristics along elevation gradients, and introduce the methods of statistical evaluation. Fourth, we report additional measurements of soil, genetic resources, and climate smartness indicators and criteria, which were available for statistical evaluation and testing hypotheses. Fifth, we present the ESFONET (European Smart Forest Network) approach of data and knowledge dissemination. The discussion is focussed on the novelty and relevance of the database, its potential for monitoring, understanding and management of mountain forests toward climate smartness, and the requirements for future assessments and inventories.In this chapter, we describe the design and efficacy of this network of plots in monospecific European beech and mixed-species stands of Norway spruce, European beech, and silver fir. We present how to acquire and evaluate data from individual trees and the whole stand to quantify and understand the growth of mountain forests in Europe under climate change. It will provide concepts, models, and practical hints for analogous trans-geographic projects that may be based on the existing and newly recorded data on forests.

von Willebrand factor (VWF) and factor VIII (FVIII) circulate in a noncovalent complex in blood and promote primary hemostasis and clotting, respectively. A new VWF A1-domain binding aptamer, BT200, demonstrated good subcutaneous bioavailability and a long half-life in non-human primates. This first-in-human, randomized, placebo-controlled, double-blind trial tested the hypothesis that BT200 is well tolerated and has favorable pharmacokinetic and pharmacodynamic effects in 112 volunteers. Participants received one of the following: a single ascending dose of BT200 (0.18-48 mg) subcutaneously, an intravenous dose, BT200 with concomitant desmopressin or multiple doses. Pharmacokinetics were characterized, and the pharmacodynamic effects were measured by VWF levels, FVIII clotting activity, ristocetin-induced aggregation, platelet function under high shear rates, and thrombin generation. The mean half-lives ranged from 7-12 days and subcutaneous bioavailability increased dose-dependently exceeding 55% for doses of 6-48 mg. By blocking free A1 domains, BT200 dose-dependently decreased ristocetin-induced aggregation, and prolonged collagen-adenosine diphosphate and shear-induced platelet plug formation times. However, BT200 also increased VWF antigen and FVIII levels 4-fold (P<0.001), without increasing VWF propeptide levels, indicating decreased VWF/FVIII clearance. This, in turn, increased thrombin generation and accelerated clotting. Desmopressin-induced VWF/FVIII release had additive effects on a background of BT200. Tolerability and safety were generally good, but exaggerated pharmacology was seen at saturating doses. This trial identified a novel mechanism of action for BT200: BT200 dose-dependently increases VWF/FVIII by prolonging half-life at doses well below those which inhibit VWF-mediated platelet function. This novel property can be exploited therapeutically to enhance hemostasis in congenital bleeding disorders.

Models to predict the effects of different silvicultural treatments on future forest development are the best available tools to demonstrate and test possible climate-smart pathways of mountain forestry. This chapter reviews the state of the art in modelling approaches to predict the future growth of European mountain forests under changing environmental and management conditions. Growth models, both mechanistic and empirical, which are currently available to predict forest growth are reviewed. The chapter also discusses the potential of integrating the effects of genetic origin, species mixture and new silvicultural prescriptions on biomass production into the growth models. The potential of growth simulations to quantify indicators of climate-smart forestry (CSF) is evaluated as well. We conclude that available forest growth models largely differ from each other in many ways, and so they provide a large range of future growth estimates. However, the fast development of computing capacity allows and will allow a wide range of growth simulations and multi-model averaging to produce robust estimates. Still, great attention is required to evaluate the performance of the models. Remote sensing measurements will allow the use of growth models across ecological gradients.

Mountain forests in Europe have to face recently speeding-up phenomena related to climate change, reflected not only by the increases in the mean global temperature but also by frequent extreme events, that can cause a lot of various damages threatening forest stability. The crucial task of management is to adapt forests to environmental uncertainties using various strategies that should be undertaken to enhance forest resistance and resilience, as well as to maintain forest biodiversity and provision of ecosystem services at requested levels. Forests can play an important role in the mitigation of climate change. The stand features that increase forest climate smartness could be improved by applying appropriate silvicultural measures, which are powerful tools to modify forests. The chapter provides information on the importance of selected stand features in the face of climate change and silvicultural prescriptions on stand level focusing to achieve the required level of climate smartness. The selection of silvicultural prescriptions should be also supported by the application of simulation models. The sets of the various treatments and management alternatives should be an inherent part of adaptive forest management that is a leading approach in changing environmental conditions.

Considering the fact that water is a basic need of every living being, it is important to ensure its safety. In this work, the data on the presence of the opportunistic pathogen P. aeruginosa in drinking water (n = 4171) as well as in pool water (n = 5059) in Primorje-Gorski Kotar County in Croatia in the five-year period (2016–2020) were analysed. In addition, the national criteria were compared with those of neighboring countries and worldwide. The proportion of P. aeruginosa-positive samples was similar for drinking water (3.9%) and pool water (4.6%). The prevalence of this bacterium was most pronounced in the warmer season. P. aeruginosa-positive drinking water samples were mostly collected during building commissioning, while pool samples were from entertainment and spa/hydromassage pools. Outdoor pools showed a higher percentage of positive samples than indoor pools, as well as the pools filled with freshwater rather than seawater. The highest P. aeruginosa load was found in rehabilitation pools. Croatia, Serbia and Montenegro are countries that have included P. aeruginosa in their national regulations as an indicator of the safety of water for human consumption as well as for bottled water, while Slovenia and Bosnia and Herzegovina have limited this requirement to bottled water only. In the case of swimming pool water, this parameter is mandatory in all countries considered in this study.

Soil samples were collected in an industrial area (Banja Luka, Bosnia and Herzegovina) and analyzed the concentration of 16 polycyclic aromatic hydrocarbons (PAHs). The total concentration of 16 PAHs in surface soil varied within the range of 0.599-2.848 mg/kg and in deeper layer soil samples 0.041-0.320 mg/kg. Two basic sources of PAHs at this location are: pyrogenic and petrogenic sources. Benzo(a)pyrene toxic equivalency factors (TEFs) were used to calculate BaPeq in order to evaluate carcinogenic risk of soil contamination with PAHs. The total BaPeq of seven carcinogenic PAHs in surface soil and deeper soil layer were in the range 23.270-368.63 µg/kg (mean of 151.223 µg/kg), and 15.71-80.24 µg/kg, (mean of 48.08 µg/kg), respectively. These indicated that PAHs in this industrial soil presented relatively high toxicity potential. This study identifies the concentration and estimation of the potential cancer risk caused by contact with soils for adults, adolescents and children. In accordance with the estimated values of incremental life cancer risks (ILCRs), the cancer risk resulting from contact with the contaminated surface soil should be considered high (total ILCR>10 -3 ). The results suggest that current PAHs concentration highly carcinogenic and may hold a serious health risk for local residents and employees.

The COVID-19 pandemic has altered the way business is conducted. The widespread closure of commercial organizations presents opportunities to reset the way business activities are conducted. Regardless of the organization’s size or its status as a domestic or international firm, due diligence is required to find solutions that will allow firms to sustain their business activities in uncertain times. This study addresses this issue and attempts to identify issues that require urgent attention so that organizations can be effective and efficient in their global operations. In this context, the study proposes three imperatives for global/international businesses to sustain their operations in the long term. These imperatives include having a strong reserve fund, access to a local mutual fund, and networking to form alliances in host countries. Other implications are discussed, and we identify areas for future research.

AIM To identify the top 100 most-cited case reports and case series published in Endodontic journals and to analyse their bibliometric characteristics. METHODOLOGY The Clarivate Analytics' Web of Science (WoS), Scopus, and PubMed databases were used to identify the top 100 most-cited case reports and case series in Endodontic journals. Complete bibliographic records of the selected case reports and case series were exported in plain text or BibTeX format and imported into the R environment for statistical computing and graphics. The following parameters were then analysed: names and affiliations of the authors, title, year of publication, journal of publication, first author, corresponding author, literature cited within reports, language, citation counts, impact factor of the journal, keywords, Keywords Plus, and research topic. RESULTS In total, 88 case reports and 12 case series published in English between 1977 and 2016 were identified as the most-cited reports in the field of Endodontics. The terms 'case report(s)' or 'case series' were not included in the title of 57 articles. The number of authors per report ranged from one to seven, with the average number of co-authors per report being 3.14. The most cited author was M Trope (University of Pennsylvania, USA). The University of Washington and Private Practice, Cetraro, Italy were the most productive institutions. The country whose case reports received the largest total number of citations was the USA. The largest number of the most-cited reports appeared in 2002, 2004, and 2007 (n=7, respectively). According to the WoS database, the total number of citations ranged from 42 to 453, with the average number of citations per report being 79.97. The majority of the top 100 most-cited articles were published in the Journal of Endodontics and the International Endodontic Journal. The most frequently used author keywords were revascularization and mineral trioxide aggregate. The majority of the case reports and case series dealt with topics related to pulp regeneration. CONCLUSION This bibliometric study provides a comprehensive overview on the progress, trends and current directions in clinical practice within the field of Endodontics.

Wearable devices and smartphone applications have allowed for the utilization of different at-home treatments. Biofeedback is a mind-body technique that enables users to self-regulate the responses of the autonomic nervous system. This paper has conducted a proof-of-concept study to test multimodal biofeedback treatment with smartphone application and custom-made wearable sensor. While contact-based measurements included skin temperature and skin conductance from the sensor, the smartphone's front camera recorded the patient's face to estimate cardiovascular parameters such as heart rate and heart rate variability. The tested individual completed five biofeedback treatments at home, with activation stress exercises before and after a 5-day experiment. The obtained results show increased finger's skin temperature and heart rate variability during biofeedback sessions, indicating the successful biofeedback treatment.

The paper proposes a novel computing and net-working framework that can be implemented for the realization of different disaster management applications or real-time surveillance. The framework is based on networks of unmanned aerial vehicles (UAVs) equipped with different sensors including cameras. The framework represents a holistic approach that exploits the distributed architecture of clusters of UAVs and cloud computing resources located on the ground. The proposed framework is characterized by the hierarchical organization among framework elements. In such a framework, each UAV is assumed to be fully autonomous and locally implements a state-of-the-art deep learning algorithms for real-time route planning, obstacle avoidance and object detection on aerial images. The main operating modules of the proposed framework have been presented, with the emphasis on the improvements which the proposed framework can bring in terms of event detection time and accuracy, energy consumption and reliability of application in disaster management systems. The proposed framework can serve as the foundation for the development of more reliable, faster in terms of disaster event detection and energy-efficient disaster management systems based on UAV networks.

Positive energy districts (PEDs) are seen as a promising pathway to facilitating energy transition. PEDs are urban areas composed of different buildings and public spaces with local energy production, where the total annual energy balance must be positive. Urban areas consist of a mix of different buildings, such as households and service sector consumers (offices, restaurants, shops, cafes, supermarkets), which have a different annual energy demand and production, as well as a different consumption profile. This paper presents a data modeling approach to estimating the annual energy balance of different types of consumer categories in urban areas and proposes a methodology to extrapolate energy demands from specific building types to the aggregated level of an urban area and vice versa. By dividing an urban area into clusters of different consumer categories, depending on parameters such as surface area, building type and energy interventions, energy demands are estimated. The presented modeling approach is used to model and calculate the energy balance and CO2 emissions in two PED areas of the City of Groningen (The Netherlands) proposed in the Smart City H2020 MAKING CITY project.