Miracle-dz/UniFAR-FTUs huggingface dataset:
Recovery of Neglected Species with Cloud Water Micro Condense Capacity as a Response to Climate Change: The Case of Sclerophyllous Boxwoods of Buxus balearica Lam. in the Southern Spanish Mediterranean

Understanding the survival needs of neglected or underutilized species (NUS) in agroforestry can offer valuable insights to mitigate climate change and biodiversity loss. This paper analyses the habitat heterogeneity of Buxus balearica populations (palaeorelict of the Mediterranean Basin) using a methodology that integrates four approaches: ecological profiling, multivariate analysis, and the clustering of populations according to environmental variables and suitability. The habitat analysis was conducted on 240 occurrence points, integrating open-source databases and germplasm collection field work. Results reveal that the distribution of B. balearica in the south of the Iberian Peninsula is mainly conditioned by thermal variations, the humidity regime, and microtopography, which makes it very vulnerable to current and future climate change scenarios. The analysis of habitat heterogeneity demonstrates its capacity to estimate genetic diversity, which provides a solid basis for future research and conservation actions. The rapid extinction process of these boxwoods is evident by comparing the suitability model under different climate scenarios. There is an urgent need to improve the current status of the species and associated landscapes, considering B. balearica as an underutilized species, and establishing a sound management plan to reinforce its populations and protect its natural habitat.
Influence of irrigation on root zone storage capacity estimation

Vegetation plays a crucial role in regulating the water cycle through transpiration, which is the water flux from the subsurface to the atmosphere via vegetation roots. The amount and timing of transpiration is controlled by the interplay of seasonal energy and water supply. The latter strongly depends on the size of the root zone storage capacity ( S r ) which represents the maximum accessible volume of water that vegetation can use for transpiration. S r is primarily influenced by hydro-climatic conditions as vegetation optimizes its root system in a way it can guarantee water uptake and overcome dry 5 periods. S r estimates are commonly derived from root zone water deficits that result from the phase shift between the seasonal signals of root zone water inflow (i.e., precipitation) and outflow (i.e., evaporation). In irrigated croplands, irrigation water serves as an additional input into the root zone. However, this aspect has been ignored in many studies, and the extent to which irrigation influences S r estimates was never comprehensively quantified. In this study, our objective is to quantify the influence of irrigation on S r and identify the regional differences therein. To this aim, we integrated two irrigation methods, based on 10 irrigation water use and irrigated area fractions, respectively, into the S r estimation. We evaluated the effects in comparison to S r estimates that do not consider irrigation for a sample of 4511 catchments globally with varying degrees of irrigation activities. Our results show that S r consistently decreased when considering irrigation with a larger effect in catchments with a larger irrigated area. For catchments with an irrigated area fraction exceeding 10 %, the median decrease of S r was 17 mm and 22 mm for the two methods, corresponding to 12 % and 17 %, respectively. S r decreased the most for catchments in tropical 15 climates. However, the relative decrease was the largest in catchments in temperate climates. Our results demonstrate, for the first time, that irrigation has a considerable influence on S r estimates over irrigated croplands. This effect is as strong as the effects of snow melt that were previously documented in catchments that have a considerable amount of precipitation falling as snow.
University of Memphis Digital Commons University of Memphis Digital Commons

Abstract Every agent aspiring to human level intelligence, every AGI agent, must be capable of a theory of mind. That is, it must be able to attribute mental states, including intentions, to other agents, and must use such attributions in its action selection process. The LIDA conceptual and computational model of cognition offers an explanation of how theory of mind is accomplished in humans and some other animals, and suggests how this explanation could be implemented computationally. Here we describe how the LIDA version of theory of mind is accomplished, and illustrate it with an example taken from an experiment with monkeys, chosen for simplicity
Attentional Capture by Irrelevant Transients Leads to Perceptual Errors in a Competitive Change Detection Task

Theories on visual change detection imply that attention is a necessary but not sufficient prerequisite for aware perception. Misguidance of attention due to salient irrelevant distractors can therefore lead to severe deficits in change detection. The present study investigates the mechanisms behind such perceptual errors and their relation to error processing on higher cognitive levels. Participants had to detect a luminance change that occasionally occurred simultaneously with an irrelevant orientation change in the opposite hemi-field (conflict condition). By analyzing event-related potentials in the EEG separately in those error prone conflict trials for correct and erroneous change detection, we demonstrate that only correct change detection was associated with the allocation of attention to the relevant luminance change. Erroneous change detection was associated with an initial capture of attention toward the irrelevant orientation change in the N1 time window and a lack of subsequent target selection processes (N2pc). Errors were additionally accompanied by an increase of the fronto-central N2 and a kind of error negativity (Ne or ERN), which, however, peaked prior to the response. These results suggest that a strong perceptual conflict by salient distractors can disrupt the further processing of relevant information and thus affect its aware perception. Yet, it does not impair higher cognitive processes for conflict and error detection, indicating that these processes are independent from awareness.
The Land of Britain, 1930-1990: a comparative study of Field Mapping and Remote Sensing Techniques

Over fifty years after the Land Utilization Survey, directed by the geographer Dudley Stamp, the first Land Cover Map of Great Britain, derived in digital form from satellite sensor imagery, has been launched. This paper discusses in turn the procedures, logistics and results of the two surveys, and their wider relevance to the recording of landscape changes.
Domestic Credit to the Private Sector and Economic Growth in Cameroon

The indispensability of a strong private sector to economic growth and development has been proven severally in empirical research. Nevertheless, different finance theories have assigned varied degrees of importance to private sector performance measures like credit provision and capital accumulation among on economic growth and development. This paper examines the relationship between domestic credit to the private sector by commercial banks, and
Improving maintenance of community-based knowledge graphs

Data quality is crucial for the effective utilization of knowledge graphs, ensuring it is challenging due to the need for continuous monitoring and maintenance. This research proposal focuses on data quality in open knowledge graphs, with an emphasis on Wikidata. Wiki-data, one of the largest collaborative knowledge graphs, has its own approach for data consistency, deviating from regular OWL ontologies or SHACL, the W3C recommendation. The proposal aims to comprehend and formalize Wikidata’s approaches for assessing and resolving data inconsistencies. By formalizing constraints, refinement operations, and repair strategies, this research aims to improve the quality of Wikidata and other knowledge graphs also developed based on Wikibase. As one of the contributions, our research proposes a semi-automatic refinement pipeline to empower the Wikidata user community by recommending repairs of constraint violations, combining distance-based refinement approaches and ranking heuristics. Establishing a comprehensive framework and engaging users in knowledge graph maintenance enhances the reliability and usability of open knowledge graphs.
Beneficial effects of physical exercise on the osteo-renal Klotho-FGF-23 axis in Chronic Kidney Disease: A systematic review with meta-analysis

The aim of this study was to investigate the efficacy of physical exercise in chronic kidney disease, describing its impact on the Klotho-FGF23 axis. PubMed, Web of Science and Scopus databases, updated to January 2023, were searched. The present study employed mean difference and a 95% confidence interval (CI) to examine the efficacy of the intervention. Heterogeneity was assessed through inconsistency statistics (I2). Out of the 299 studies identified, a total of 4 randomized controlled trials (RCTs), comprising 272 participants, met the eligibility criteria. Compared with the control group, physical exercise significantly decreased the concentrations of FGF23 (MD: -102.07 Pg/mL, 95% CI: -176.23.47, -27.91 I2= 97%, p = 0.001), and a significantly increased the concentrations of Klotho protein: (MD: 158.82 Pg/mL, 95% CI: 123.33, -194.31, I2 = 0%, p = 0.001). The results of our study indicated that the exercise has a direct relationship with Klotho-FGF23 axis. We can conclude that physical exercise in patients with CKD produces beneficial effects on the pathophysiological components related to this disease, including cardiorespiratory fitness and vascular functions. As observed, both endurance and aerobic physical exercise increase Klotho production and decrease FGF23 levels. Evidence indicates that exercise attenuates the progression of CKD, improves uremic parameters and down-regulates inflammation-related markers.
Test-retest reliability of the ABILHAND Questionnaire in persons with chronic stroke

• Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal Take down policy If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim.
Identi ﬁ cation of quantitative trait loci associated with sorghum susceptibility to Asian stem borer damage

Sorghum ( Sorghum bicolor (L.) Moench) is an important crop originated in Africa that shows susceptibility to herbivores. In this study, we identi ﬁ ed two sorghum genotypes with highly contrasting levels of stem damage caused by the caterpillars of Asian stem borer ( Ostrinia furnacalis Guenée). Recombinant inbred lines (RILs) from genetic cross between resistant (BTx623) and susceptible (NOG) sorghum were used to perform a quantitative trait locus (QTL) analysis in the ﬁ eld. Two major QTLs responsible for higher NOG infestation by stem borer in three independent ﬁ eld seasons were detected on chromosomes 7 and 9, interestingly in positions that overlapped with two major QTLs for plant height. As plant height and stem borer damage were highly correlated, we propose that sorghum height-associated morphological or physiological traits could be important for stem borer establishment and/or damage in sorghum
Predictive model of solar potential on building façades with the sky view factor as shading indicator

Building façades represent a considerable part of the urban surface and the solar energy they receive can significantly contribute to the whole urban solar potential. Extending the use of building facades to produce more renewable energy can help address the challenges of climate change, promote energy independence, and create economic benefits. A major challenge in harnessing solar energy from vertical surfaces is the variation of solar availability on urban facades, which can be affected by orientation, neighboring buildings or vegetation. An easy, reliable and robust method for evaluating the solar potential of facades since the strategical stage of the building development can assist experts in designing façades where building integrated photovoltaics (BIPV) can be efficiently implemented. This study aims to identify a relationship between the variation of the sky view factor (SVF), a measure of the amount of sky that is visible from a given position, and the corresponding reduction of solar irradiation due to shading. This can then be used to predict the solar potential at each point on the façade on a monthly basis only depending on orientation, SVF value and geographical coordinates, drastically reducing the complexity of analysis and without requiring time-consuming tools.
Optimization of a ventilation system integrated into a window frame using CFD simulations

A decentralized ventilation system has the potential to decrease the pressure drop in a ventilation system and consequently, increase the efficiency of the system and building skin. Including a decentralized ventilation system in a window cavity allows independent regulation of the fresh air quality in each room and can be easily installed without any additional brickwork. In this study, a novel ventilation system integrated into a window-frame is examined and the most critical region regarding pressure drop is identified using computational fluid dynamic (CFD) simulations. The entire fresh air channel including the optimized section is compared with the original volume regarding system resistance and satisfaction of the required airflow according to Swiss standards. The results suggest a relocation of the restricting control unit and an increased cross-section to decrease the air velocity and the pressure drop. The simulations predicted that the required airflow for sufficient indoor air quality is exceeded using the optimized geometry.
Impacts of energy saving measures on IEQ, task performance and COVID-19 contagion risk in public buildings: analysis of a case-study in Bozen-Bolzano, Italy

The recent 2022 energy crisis has pushed several Italian public administrations to adopt solutions to reduce energy demand for space heating in public buildings. Reduction of HVAC system operation time, decrease of heating setpoint and changes to ventilation schedules are some examples of typically implemented measures. However, some of them are in direct competition with those adopted so far to limit the risk of COVID-19 contagion, such as higher ventilation rates. Furthermore, limited operation time and lower setpoints can lead to suboptimal thermal comfort conditions for workers in public buildings, with subsequent decrease of their task performances. In this framework, to assess the global efficacy of the most recent energy saving policies in public buildings, this research focuses not only on the quantification of energy savings but also on the analysis of increased COVID-19 contagion risk, as well as performance loss due to suboptimal building operation conditions. To investigate the impact of new building operation policies for energy savings, an intermediate storey of a public office building in Bolzano, Italy, was selected as a case-study.
Challenges with onboard strain measurements on a model Francis turbine runner

As the world transitions towards more renewable energy sources, as a step to reduce the emissions of CO2, intermittent and non-dispatchable sources like solar and wind will take up a larger proportion of the energy production. With more unregulated power in the energy mix, a higher demand is put on the rest of the energy production system. Hydropower is in a unique position as it is both renewable and a highly flexible energy source. The increased use of flexible operation of Francis turbines especially, puts a higher dynamic load on the runner components which as a consequence leads to a reduced lifetime. In this paper we present the experimental setup and results from a measurement campaign performed on a model of a low specific speed Francis runner. Onboard measurements with strain gauges at the trailing edge of two runner blades were performed. The experiments were conducted as a part of the HydroFlex project with the goal of validating numerical simulations and to gain a better understanding of the reduction of lifetime on Francis turbines due to higher fatigue loading from more flexible operation. The results shows that there were a significant drift of the mean strain over time during the measurement campaign, and a lower measured strain at BEP than expected when compared to numerical simulations. In this paper, the experimental setup, results and challenges encountered are presented.
Estimating perceived indoor air quality and environmental satisfaction using a camera

Although indoor environmental monitoring data are increasingly available, they often fail to accurately capture personal environmental perception, comfort, and satisfaction. This disconnection has led to a growing interest in using real-time feedback from building users to improve the control of heating, ventilation, and air-conditioning systems and reduce energy waste. However, traditional questionnaire-based surveys only provide a snapshot at the time of investigation and suffer from a variety of bias sources. To address this, this paper proposes a novel camera-based method for estimating perceived indoor air quality and environmental satisfaction by analysing facial expressions. We conducted indoor air pollution exposure experiments on 24 healthy adults in twin environmental chambers. Their changes in facial expressions were compared between different exposure conditions and the potential correlation between facial expressions and perceived air quality, environmental satisfaction, and self-reported sick building syndrome symptoms was explored. Preliminary results indicate that a common RGB camera can repeatably detect facial expressions from the same subject. Also, results from a subset of five subjects suggest moderate differences in concentration, calmness, contemplation, and tiredness expressions between the two air quality conditions.
Comparison of different deep neural networks for system identification of thermal building behavior

Having accurate information available about future thermal building behavior can help to make good decisions in various heating control tasks. However, creating precise mathematical models for many different buildings is a complex and time-consuming task, owing to the heterogeneity of the building stock and the behavior of its occupants. In this paper, we propose a DNN-based system identification approach for predicting the room temperature inside a building based on past information and future weather forecasts. We evaluate various state-of-the-art and custom-built DNN architectures for TSF. Besides prediction performance, storage space and inference speed as measures for the respective model’s complexity are also taken into account. Our main contribution is demonstrating the effectiveness of these models in predicting the room temperature for differently parameterized simulated buildings. By using several distinct buildings for training, validation and testing, we additionally show that these models are capable to generalize in a way such that the room temperature for different buildings can be predicted by a single model, without any changes or adaptions.
Inspiration from animal’s collective behavior for home energy demand management

An interdisciplinary approach towards managing energy demand through users’ behavior is discussed, drawing on knowledge from studies on collective behavior in nature. Studies on home energy demand management have focused mainly on social, technical and, more recently, socio-technical aspects that are considered largely at the individual levels only. However, emerging trends in social studies call for explorations across different social and spatial scales beyond the individual levels. This work distinguishes several principles and mechanisms of collective foraging decision-making from nature that respond to demand, including aspects of self-organization and stigmergy. The scoping of potential biological systems and behavioral aspects emulation aims to provide a foundation for agent-based modelling (ABM). Collective behavior emerges from local interactions of the individuals within a group, and nonlinear interactions between individuals and their environment enable them to accomplish tasks, such as structural construction, without the involvement of centralized control systems. Response to demand in nature is significantly influenced by information flow, processing, perception, and communication and coordination patterns between individuals, groups, and their environment. By studying these interactions and adapting their principles to the context of home energy management, we can develop new, more efficient, sustainable, and resilient approaches.
Comparison of two deep reinforcement learning algorithms towards an optimal policy for smart building thermal control

Heating, Ventilation, and Air Conditioning (HVAC) systems are the main providers of occupant comfort, and at the same time, they represent a significant source of energy consumption. Improving their efficiency is essential for reducing the environmental impact of buildings. However, traditional rule-based and model-based strategies are often inefficient in real-world applications due to the complex building thermal dynamics and the influence of heterogeneous disturbances, such as unpredictable occupant behavior. In order to address this issue, the performance of two state-of-the-art model-free Deep Reinforcement Learning (DRL) algorithms, Proximal Policy Optimization (PPO) and Soft Actor-Critic (SAC), has been compared when the percentage valve opening is managed in a thermally activated building system, modeled in a simulated environment from data collected in an existing office building in Switzerland. Results show that PPO reduced energy costs by 18% and decreased temperature violations by 33%, while SAC achieved a 14% reduction in energy costs and 64% fewer temperature violations compared to the onsite Rule-Based Controller (RBC).
The resilience of buildings to climate change: the role of mobile passive systems

Climate change indicates that we are heading towards higher temperatures worldwide and greater temperature variations. To face this challenge, we need to adapt to coming conditions and minimize negative impacts on people and the environment. In this paper, we aim to generate evidence to inform decision-making when designing buildings in Switzerland by considering possible future climatic conditions and maximizing the time when buildings do not require neither heating nor cooling systems. We compare two cases, a static scenario where passive systems are permanent (wall and roof thermal insulation), and an adaptable scenario that accounts for movable passive systems (interior shutters, cross ventilation, and solar protection). The results show that the adaptable scenario returns over 1000 hours of free-running conditions more than the static case, both for 2050 and 2070. In the static scenario, the free-running period represents 25% of the year, while in the adaptable scenario it represents around 40%. Thus, passive strategies with movable devices can be a suitable approach to adapt buildings to future climate conditions, which would provide larger periods of free-running conditions, lower energy demand, and lower costs on permanent thermal insulation.