<div> <div> <div> <p>The <em>global yield gap</em> is a concept to assess the difference between the actual yield and the maximum potential yield that could be achieved by applying optimal agricultural techniques such as irrigation. Climate change and socio-economic development, including population growth, call for addressing the yield gap to increase global production and to adapt to climate change as irrigation in many circumstances is a very effective adaptation measure. On the regional level, the irrigation yield gap can thus be interpreted as an indicator linked to adaptive capacity of the agricultural sector to climate change impacts. At the same time, effective deployment of irrigation is linked, among other things, to the socio-economic development including economic capabilities, but also institutional and water governance frameworks.</p> <p>Based on a detailed assessment of the irrigation yield gap, taking into account water availability constraints such as environmental flow requirements, we here establish as sustainable irrigation adaptation index for the agricultural sector. In a next step we link this sustainable irrigation index to socio-economic indicators provided by the framework of Socio- Economic Pathways (SSPs) on the national level. Doing so allows us to project the closure of the yield gap alongside the quantitative SSP narratives of socio-economic developments. We find that even under very optimistic scenarios of socio-economic development, it will take decades to close the irrigation yield gap in many developing countries, while without substantial development improvements our results suggest limited improvement in many tropical countries. Our projections present a first attempt to consistently link future irrigation expansion to socio-economic scenarios used in climate change research. We report a substantial scenario dependence of this expansion that underscores the need to incorporate socio-economic projections into projections of future agricultural impacts.</p> </div> </div> </div>

<p>Heat extremes are among the most pertinent extreme weather hazards. At the same time, adaptation to the impacts of extreme heat can be very effective. The ability of societies to effectively adapt to climate change hazards such as extreme heat, however, critically depends on their level of socio-economic development. Examining the risks posed by future heat extremes to human societies requires to link socio-economic development trajectories with emerging heat extremes. Such an integrated assessment can also provide insights into whether or not it is indeed plausible for societies to &#8220;outgrow&#8221; climate change by increasing adaptive capacity faster than climate impacts emerge - &#160;a narrative that underlies many policy decisions that prioritize economic development over climate action still today.</p><p>&#160;</p><p>Here we provide such an integrated assessment by combining a novel approach to project the continuous emergence of heat extremes over the 21^st century under different concentration pathways and the pace of socio-economic development under the shared socio-economic pathways accounting for continuous autonomous adaptation. We find that even under the most optimistic scenarios of future development, countries may not be able to outpace unmitigated climate change. Only Paris-Agreement compatible concentration pathways allow for human development to keep up with or even outpace the emerging climate change signal in vulnerable countries in the near future. A similar picture emerges when comparing heat day emergence with future evolution of governance as a proxy for adaptive capacity. Our findings underscore the critical importance of achieving the Paris Agreement goals to enable climate-resilient, sustainable development.</p>

<p>The ionosphere is the dominant source of the errors in the Global Navigation Satellite Systems &#160;(GNSS), which causes delays and degradation of the GNSS signal. These errors have an impact on many terrestrial and space applications that rely on GNSS. The key parameter for the study of the ionosphere is the Total Electron Content (TEC). In an effort to eliminate the impact of delayed GNSS signal caused by the ionospheric refraction on the accuracy of GNSS positioning and navigation, the researchers made significant advances and began other ionospheric research. This paper studies the variability of GNSS derived TEC values in the International quiet and disturbed days, but also in periods when three tropical-like cyclones in the Mediterranean developed. However, the term tropical-like cyclone distinguishes tropical cyclones developing outside the tropics (like in the Mediterranean Basin) from those developing inside the tropics. Mediterranean tropical cyclones, known as a Medicane, show no difference to other tropical cyclones and can be developed into a hurricane.</p><p>Hence, the variability of GNSS derived TEC values time series were analyzed during periods when three Medicanes happened in the fall of 2014, 2016, 2017. Data from eight GNSS stations of the European Permanent Network (EPN) were used and TEC calculations were performed using the VShell program. The results demonstrated that the TEC variability is reflected in daily variations within one month, for three different years of consideration. When the state of the ionosphere was disturbed by external influences, such as the space weather storms, the results demonstrated extreme changes in the number of electrons in the ionosphere. Variations of the TEC and parameter VTEC*sigma were analyzed in the weeks before and after three subtropical cyclones in the Mediterranean Sea, recorded in November 2014, November 2016 and November 2017. Special attention was given to the time series analysis of the variable VTEC*sigma for the GNSS stations located nearby the area where the Medicane developed and stations in regions away from the storm.</p><p>The results demonstrated higher VTEC values derived from GNSS stations in the area of the storm on the storm days, as well as the days before and after. Also, the results for the storm in November 2014 showed higher VTEC values compared to the other two tropical-like cyclones. The recorded events of space weather are in correlation with the days when three analyzed Medicanes developed. Therefore, it is difficult to distinguish whether the TEC variability was caused by the space weather storm or the Medicane.</p>

Motivation As multi-region, time-series, and single cell sequencing data become more widely available, it is becoming clear that certain tumors share evolutionary characteristics with others. In the last few years, several computational methods have been developed with the goal of inferring the subclonal composition and evolutionary history of tumors from tumor biopsy sequencing data. However, the phylogenetic trees that they report differ significantly between tumors (even those with similar characteristics). Results In this paper, we present a novel combinatorial optimization method, CONETT, for detection of recurrent tumor evolution trajectories. Our method constructs a consensus tree of conserved evolutionary trajectories based on the information about temporal order of alteration events in a set of tumors. We apply our method to previously published datasets of 100 clear-cell renal cell carcinoma and 99 non-small-cell lung cancer patients and identify both conserved trajectories that were reported in the original studies, as well as new trajectories. Availability CONETT is implemented in C++ and available at https://github.com/ehodzic/CONETT.

<p><strong>Abstract</strong>: Rapid growth of urban population and consequential increasing traffic, construction of buildings, roads, industrial areas, affects urban soils as well as urban environment in general. Urban soils differ from the natural soils by their disturbed structure resulting from waste disposal, construction sites, pollution from atmospheric deposition, traffic and industrial activities. Mismanagement of urban environment can cause severe contamination of green areas in cities, with serious health risk for urban population. To prevail those issues and improve the sustainability of urban green areas, innovative and nature based solutions (NBS) should gain more attention, particularly those easily applied such as tree-based phytoremediation. Unlike traditional remediation techniques that are expensive, very demanding and can cause secondary pollution, tree-based phytoremediation is NBS with wide spectrum of application. It is low-cost technique, based on urban green infrastructure (parks, alleys, community gardens) and has numerous benefits reflected throught sustainable management of urban soils and improvement of general environmental, health, social and economic conditions for urban population. Primarly, urban green infrastructure consist of different tree species capable to mitigate soil contamination, especially contamination with toxic heavy metals (HMs). Regeneration of urban ecosystems based on the role of tree species is connected to ability of trees to retain, uptake and decompose pollutants (including HMs) from contaminated urban soils, enabling their re-use process and turning them into green and environmental friendly areas. Taking into account advantages of phytoremediation technique, the aim of this paper is to present concentration of some HMs (cadmium, lead and zinc) in urban soils of cities accross Bosnia and Herzegovina and look into phytoremediation potential of common urban tree species: horse chestnut (<em>Aesculus</em> <em>hippocastanum</em> L.) and planetree (<em>Platanus</em> &#215; <em>acerifolia</em> (Aiton) Willd.). Results showed high phytoremediation potential of above mentioned tree species, which opens space for further research and introduction of this NBS for remediation of many severely polluted urban soils, drawing attention to better-understood urban sustainability and importance of application of phytoremediation as NBS on local level.</p><p><strong>Key words</strong>: nature-based solutions, phytoremediation, urban soil, trees, heavy metals</p>

<p>Ensemble based data assimilation approaches, such as the Ensemble Kalman Filter (EnKF), have been widely and successfully implemented to combine observations with dynamic models to investigate the evolution of a system&#8217;s state. Such inversions are powerful tools for providing forecasts as well as &#8220;hindcasting&#8221; events such as volcanic eruptions to investigate source parameters and triggering mechanisms. In this study, a high performance computing (HPC) adaptation of the EnKF is used to assimilate ground deformation observations from interferometric synthetic-aperture radar (InSAR) into high-fidelity, multiphysics finite element models to evaluate the prolonged unrest and June 26, 2018 eruption of Sierra Negra volcano, Gal&#225;pagos. The stability of the Sierra Negra magma system is evaluated at each time step by estimating variations in reservoir overpressure, Mohr-Coulomb failure in the host rock, and tensile stress and failure along the reservoir boundary. The deformation of Sierra Negra is tracked over a decade, during which almost 5 meters of surface uplift has been recorded. The EnKF reveals that the evolution of the stress state in the host rock surrounding the Sierra Negra magma reservoir likely controlled the timing of the eruption. While increases in magma reservoir overpressure remained modest (< 10 MPa) throughout the data assimilation time period, significant Mohr-Coulomb failure is indicated in the lead up to the eruption coincident with increased seismicity along both trapdoor faults within Sierra Negra&#8217;s caldera and along the caldera&#8217;s ring faults. During the final stages of pre-eruptive unrest, the EnKF models indicate limited tensile failure, with no tensile failure along the northern portion of the magma system where the eruption commenced. Most strikingly, model calculations of significant through-going Mohr-Coulomb failure correspond in space and time with a Mw 5.4 earthquake recorded in the hours preceding the 2018 eruption. Subsequent stress modeling implicates the Mw 5.4 earthquake along the southern intra-caldera trapdoor fault as the potential catalyst for tensile failure and dike initiation along the reservoir to the north. In conclusion, the volcano EnKF approach successfully tracked the evolving stability of Sierra Negra, indicating great potential for future forecasting efforts.</p>

The shape and location of density anomalies inside the Moon provide insights into processes that produced them and their subsequent evolution. Gravity measurements provide the most complete data set to infer these anomalies on the Moon [1]. However, gravity inversions suffer from inherent non-uniqueness. To circumvent this issue, it is often assumed that the Bouguer gravity anomalies are produced by the relief of the crust-mantle or other internal interface [2]. This approach limits the recovery of 3D density anomalies or any anomaly at different depths. In this work, we develop an algorithm that provides a set of likely three-dimensional models consistent with the observed gravity data with no need to constrain the depth of anomalies a priori.

A proper design of the mooring systems for Wave Energy Converters (WECs) requires an accurate investigation of both operating and extreme wave conditions. A careful analysis of these systems is required to design a mooring configuration that ensures station keeping, reliability, maintainability, and low costs, without affecting the WEC dynamics. In this context, an experimental campaign on a 1:20 scaled prototype of the ISWEC (Inertial Sea Wave Energy Converter), focusing on the influence of the mooring layout on loads in extreme wave conditions, is presented and discussed. Two mooring configurations composed of multiple slack catenaries with sub-surface buoys, with or without clump-weights, have been designed and investigated experimentally. Tests in regular, irregular, and extreme waves for a moored model of the ISWEC device have been performed at the University of Naples Federico II. The aim is to identify a mooring solution that could guarantee both correct operation of the device and load carrying in extreme sea conditions. Pitch motion and loads in the rotational joint have been considered as indicators of the device hydrodynamic behavior and mooring configuration impact on the WEC.

We have read with great interest manuscript by Piccinni et al. in which they demonstrated significant prevalence of liver steatosis in patients with compensated advanced chronic liver disease (cACLD), previously assumed to decrease in advanced fibrosis, as well as very good performance of Controlled attenuation parameter (CAP) in this cohort of patients (1,2).

The generalizability of empirical research depends on the reproduction of findings across settings and populations. Consequently, generalizations demand resources beyond that which is typically available to any one laboratory. With collective interest in the joint Simon effect (JSE)-a phenomenon that suggests people work more effectively with humanlike (as opposed to mechanomorphic) robots -we pursued a multi-institutional research cooperation between robotics researchers, social scientists, and software engineers. To evaluate the robustness of the JSE in dyadic human-robot interactions, we constructed an experimental infrastructure for exact, lab-independent reproduction of robot behavior. Deployment of our infrastructure across three institutions with distinct research orientations (well-resourced versus resource-constrained) provides initial demonstration of the success of our approach and the degree to which it can alleviate technical barriers to HRI reproducibility. Moreover, with the three deployments situated in culturally distinct contexts (Germany, the U.S. Midwest, and the Mexico-U.S. Border), observation of a JSE at each site provides evidence its generalizability across settings and populations. CCS CONCEPTS •Human-centered computing →Empirical studies in HCI. ACM Reference Format: Megan Strait, Florian Lier, Jasmin Bernotat, Sven Wachsmuth, Friederike Eyssel, Robert Goldstone, and Selma Šabanović. 2020. A Three-Site Reproduction of the Joint Simon Effect with the NAO Robot. In Proceedings of the 2020 ACM/IEEE Intemational Conference on Human-Robot Interaction (HRI ’ 20), March 23-26, 2020, Cambridge, United Kingdom. ACM, New York, NY, USA, 9 pages. https://doi.org/10.1145/3319502.3374783

In a rapidly developing IT business environment, quality management practices in various forms are inevitable. Information Technology industry is experiencing the fastest growth in the Bosnian economy over the past five years. Therefore, they are constantly adapting to meet the challenges of digital transformation and to satisfy the expectations of today’s customers. The best way in which an organization undertakes business activities is through quality management practices and organizational learning, which improves product quality and reduce product returns and the cost of servicing dissatisfied customers. This approach ultimately leads to an improvement in the company’s performance. This study proposes a research model based on extensive literature review. This model may serve as a good basis to investigate interrelationships between TQM practices, organizational learning, and organizational performance. It may also help to determine if organizational learning fosters plays a mediating role between TQM practices and performance in IT Sector. Further validation of the model is strongly recommended to future researchers.