The leaf area index (LAI) is a crucial parameter for climate change research, agricultural management, and ecosystem monitoring. Despite extensive use of remote sensing data to estimate the LAI, comprehensive evaluations of product consistency and uncertainty remain limited. This study evaluated the uncertainties of four LAI products—GLASS, MCD15A2H, VNP15A2H, and CLMS—across diverse land cover types in the Heihe River Basin through two triple collocation approaches, innovatively. Each approach, respectively, focused on achieving more precise temporal characteristics and spatial characteristics of product uncertainties. The results indicate that all products generally met the Global Climate Observing System’s precision requirement (±0.5) for most biomes during the growing season. When comparing monthly uncertainties within grid cells, GLASS demonstrates superior performance, particularly in grasslands and croplands, whereas CLMS exhibits a slightly weaker ability to represent the spatial distribution of the LAI, especially in regions with high LAI values. When time series data are used to analyze the seasonal uncertainties of the products, MCD15A2H and VNP15A2H show more pronounced distortions, indicating their limited capability in capturing the temporal dynamics of the LAI. Correlation analyses revealed strong product agreement in regions with a low LAI, but discrepancies increased during the growing season and in heterogeneous land covers like croplands. These findings provide critical insights into the reliability of LAI products, offering a robust reference for validating their performance and ensuring their alignment with user requirements across diverse applications. The study highlights the importance of addressing spatial and temporal variability in uncertainties to improve the practical utility of LAI datasets in ecological and climate-related research.
Rhaphidophoridae, also called cave crickets, is a globally distributed insect group belonging to the katydids and allies (Orthoptera: Ensifera: Tettigoniidea). Rhaphidophorids are restricted to humid microhabitats such as caves and wet forests, but the group’s true diversity is poorly known. In Australia, 27 species are described from nine genera in the subfamily Macropathinae, with the highest diversity concentrated in the mesic island state of Tasmania. Micropathus Richards, 1964 is the most widespread genus on the island and contains five species largely restricted to subterranean habitats. Micropathus is reliant on pockets of relictual wet forest, placing species at risk of decline due to climate and land use change, and one species is listed as Critically Endangered. A recent molecular phylogeny for Macropathinae identified two additional, putatively undescribed species of Micropathus, neither of which can be adequately conserved without formal scientific names. Integrating morphological evidence alongside this phylogenetic framework, we describe Micropathus ditto Beasley-Hall sp. nov., previously thought to be a subpopulation of Micropathus tasmaniensis, and Micropathus zubat Beasley-Hall sp. nov., currently known only from the remote Forest Hills karst system. We also provide a key to Micropathus and redescribe its existing members to better reflect intraspecific morphological variation in the genus.
<p style="text-align: left;"><strong>Abstract:</strong></p>
<p style="text-align: left;">Increasing organizational productivity by focusing on effectiveness along with the satisfaction of service recipients of service organizations is an inevitable necessity. The present study is an attempt to investigate the impact of knowledge management dimensions on organizational effectiveness in the field of police crime prevention, considering the mediating role of employees' spiritual intelligence. This study is quantitative in terms of data, applied in terms of objective, and correlational in nature. The statistical population of this research consisted of level one and two managers of Strategic Studies Center, Police Science Research Institute, Amin University and Prevention Police in 2022. Based on stratified and simple random sampling, the sample size included 103 participants. The collected data were analyzed by structural equation method using SPSS and Lisrel software. The findings of the research show that knowledge management dimensions have a direct effect of 67% and indirect effect of 48% through the spiritual intelligence of employees on organizational effectiveness. The direct effect of employees' spiritual intelligence on organizational effectiveness is 56%. Also, the dimensions of knowledge management predict 73% of changes in employees' spiritual intelligence. As a result, strengthening the variables of creation, distribution and application of knowledge in the direction of organizational effectiveness should be given serious attention. In addition, the spiritual intelligence of employees as a mediating variable should be strengthened since by strengthening the indicators of spiritual intelligence, the indirect effect of knowledge management dimensions on the organizational effectiveness of the police in the field of crime prevention can be increased.</p>
<p style="text-align: left;"><strong>Key Words:</strong> organizational effectiveness, organizational knowledge, police organization, spiritual intelligence</p>
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<p style="text-align: left;"><strong>1.Introduction</strong></p>
<p style="text-align: left;">Understanding the implications of the dimensions and indicators of knowledge management and spiritual intelligence on organizational effectiveness can be valuable for officials and managers who seek to improve and strengthen performance. However, the necessity of investigating the knowledge management, spiritual intelligence and organizational effectiveness of the police, especially in the field of crime prevention, can be seen as a response to the current environmental conditions and the needs of managers and commanders. On the other hand, increasing the effectiveness of the organization in order to improve the performance of the employees requires nobility and understanding of the direct and indirect effect of the knowledge management and spiritual intelligence components and indicators on the effectiveness of the organization. In fact, by improving the knowledge management and spiritual intelligence indicators, the organizational effectiveness of the police can be improved. In order to achieve organizational goals, including crime prevention, the present research tries to determine the dimensions of the direct and indirect effect of knowledge management through spiritual intelligence as a mediator on the organizational effectiveness of the police in crime prevention.</p>
<ol style="text-align: left;" start="2">
<li><strong>Literature Review</strong></li>
</ol>
<p style="text-align: left;">The present research, which is conducted with the aim of knowing the impact of knowledge management dimensions on organizational effectiveness in the police crime prevention with the mediating role of employees' spiritual intelligence, is based on the dimensions of knowledge management, defined by Bhatt (2001) who considers knowledge management as the process of creating, presenting, distributing and applying knowledge, and spiritual intelligence of Wellman who emphasizes the seven dimensions of spiritual intelligence, including mastery, mindfulness, extrasensory perception, unity, intelligence, trauma, and childhood spirituality, as well as the effectiveness of Robbins (2008) including quality, education development, motivation and flexibility.</p>
<p style="text-align: left;"><strong>3.Methodology</strong></p>
<p style="text-align: left;">This study is quantitative in terms of data, applied in terms of objective, and correlational in nature. The statistical population of this research consisted of level one and two managers of the Strategic Studies Center, Research Institute of Police Sciences and Social Order, Amin University of Police Sciences and Prevention Police in 2022, including 140 participants. The sampling method was based on stratified and simple random sampling method. According to the formula for determining the sample size, 103 participants constituted the sample of the study. Hypotheses testing was conducted using mean tests to analyze the data and calculate the population mean and standard deviation. Additionally, a structural equation model was employed in order to perform multivariate regression, factor analysis, path analysis, and to assess the causal relationship among variables. Also, to measure hidden variables measurable and obvious indicators were used. The data was analyzed using SPSS and Lisrel software.</p>
<p style="text-align: left;"><strong>4.Result</strong></p>
<p style="text-align: left;">The research data and the results obtained through path analysis show that the dimensions of knowledge management not only have a significant direct effect on organizational effectiveness, but also have a greater and stronger effect on spiritual intelligence and that investing through spiritual intelligence has a double effect of 88% directly and indirectly on organizational effectiveness. For this reason, the third and fourth hypotheses of the research were also confirmed.</p>
<p style="text-align: left;"><strong>5.Conclusion</strong></p>
<p style="text-align: left;">The significant effect of knowledge management dimensions on organizational effectiveness has been confirmed in the conducted research. Also, in this research, the effect of knowledge management on organizational effectiveness in crime prevention, and more importantly, the significant large effect of organizational structure on spiritual intelligence have been confirmed. Furthermore, the indirect effect of knowledge management through spiritual intelligence on organizational effectiveness shows that the mediating variable, in addition to the direct effect on organizational effectiveness in the field of crime prevention, also indirectly affects the dimensions which in turn facilitates the management of organizational effectiveness knowledge. Therefore, it is possible to restore and develop the indicators of creation, presentation, distribution and use throughout the organization, especially within the executive layers of the police, and at the same time, consider the indicators of spiritual intelligence including mastery, concern, extrasensory perception and unity which is derived from the nature of humans, in order to increase the intensity of the direct and indirect effect of knowledge management on organizational effectiveness. It should be mentioned that, based on the the findings of the present research, organizational knowledge helps to strengthen spiritual intelligence.</p>
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The article explores the revitalization of Italy's "inner areas" - —fragile territories facing challenges such as depopulation, abandonment, and a lack of essential services, primarily due to limited mobility. The enhancement of secondary and disused railways is proposed as a tool for territorial rebalancing, to be achieved through multilevel governance that integrates spatial planning, interinstitutional cooperation, and the strategic allocation of financial and economic resources. This approach aims to move beyond sectoral perspectives on infrastructure networks.
The Axis Contract is introduced as an integrated framework linking urban planning and mobility, centered on the right to mobility and the empowerment of local communities.
The article is structured into three parts: the first examines the relationship between territory, mobility, and infrastructure policies; the second analyzes the French Contrat d’axe model and its applicability in Italy; and the third presents the results of an interdisciplinary study on the reactivation of the Civitavecchia -Capranica - Orte railway line.
The findings confirm that the Axis Contract is an effective tool for integrating urban and mobility planning, addressing accessibility needs, and promoting the sustainable rebalancing of territories.
Transportation engineering, Urbanization. City and country
Sara Mobsite, Renaud Hostache, Laure Berti Equille
et al.
Supervised deep learning for land cover semantic segmentation (LCS) relies on labeled satellite data. However, most existing Sentinel-2 datasets are cloud-free, which limits their usefulness in tropical regions where clouds are common. To properly evaluate the extent of this problem, we developed a cloud injection algorithm that simulates realistic cloud cover, allowing us to test how Sentinel-1 radar data can fill in the gaps caused by cloud-obstructed optical imagery. We also tackle the issue of losing spatial and/or spectral details during encoder downsampling in deep networks. To mitigate this loss, we propose a lightweight method that injects Normalized Difference Indices (NDIs) into the final decoding layers, enabling the model to retain key spatial features with minimal additional computation. Injecting NDIs enhanced land cover segmentation performance on the DFC2020 dataset, yielding improvements of 1.99% for U-Net and 2.78% for DeepLabV3 on cloud-free imagery. Under cloud-covered conditions, incorporating Sentinel-1 data led to significant performance gains across all models compared to using optical data alone, highlighting the effectiveness of radar-optical fusion in challenging atmospheric scenarios.
Accurate and reliable aircraft landing time prediction is essential for effective resource allocation in air traffic management. However, the inherent uncertainty of aircraft trajectories and traffic flows poses significant challenges to both prediction accuracy and trustworthiness. Therefore, prediction models should not only provide point estimates of aircraft landing times but also the uncertainties associated with these predictions. Furthermore, aircraft trajectories are frequently influenced by the presence of nearby aircraft through air traffic control interventions such as radar vectoring. Consequently, landing time prediction models must account for multi-agent interactions in the airspace. In this work, we propose a probabilistic multi-agent aircraft landing time prediction framework that provides the landing times of multiple aircraft as distributions. We evaluate the proposed framework using an air traffic surveillance dataset collected from the terminal airspace of the Incheon International Airport in South Korea. The results demonstrate that the proposed model achieves higher prediction accuracy than the baselines and quantifies the associated uncertainties of its outcomes. In addition, the model uncovered underlying patterns in air traffic control through its attention scores, thereby enhancing explainability.
We show that, after a simple power-transform reparameterization of the (vector) exponential family, the solutions to the likelihood equations coincide with moment-type estimating equations. This equivalence enables a unified route to closed-form point estimators for multi-parameter models that typically lack explicit maximum likelihood (ML) solutions. Within this framework we (i) recover, as special cases, several recent closed-form estimators from the literature; (ii) derive new families of estimators indexed by monotone transformations $g$; and (iii) establish strong consistency and asymptotic normality under mild regularity, including a dominated differentiation condition. As a detailed illustration, we derive closed-form estimators for parameters that index the beta distribution. A Monte Carlo simulation study is carried out to evaluate and compare the performance of proposed and existing estimators. Finally, we illustrate the approach with a novel municipal data set regarding proportions of land used for farming in Roraima (Brazil), which, to the best of our knowledge, has not been analyzed in the literature before, demonstrating the method's practical usefulness.
Jumping constitutes an essential component of quadruped robots' locomotion capabilities, which includes dynamic take-off and adaptive landing. Existing quadrupedal jumping studies mainly focused on the stance and flight phase by assuming a flat landing ground, which is impractical in many real world cases. This work proposes a safe landing framework that achieves adaptive landing on rough terrains by combining Trajectory Optimization (TO) and Reinforcement Learning (RL) together. The RL agent learns to track the reference motion generated by TO in the environments with rough terrains. To enable the learning of compliant landing skills on challenging terrains, a reward relaxation strategy is synthesized to encourage exploration during landing recovery period. Extensive experiments validate the accurate tracking and safe landing skills benefiting from our proposed method in various scenarios.
The Lunar landing has drawn great interest in lunar exploration in recent years, and autonomous lunar landing navigation is fundamental to this task. AI is expected to play a critical role in autonomous and intelligent space missions, yet human experts question the reliability of AI solutions. Thus, the \gls{xai} for vision-based lunar landing is studied in this paper, aiming at providing transparent and understandable predictions for intelligent lunar landing. Attention-based Darknet53 is proposed as the feature extraction structure. For crater detection and navigation tasks, attention-based YOLOv3 and attention-Darknet53-LSTM are presented respectively. The experimental results show that the offered networks provide competitive performance on relative crater detection and pose estimation during the lunar landing. The explainability of the provided networks is achieved by introducing an attention mechanism into the network during model building. Moreover, the PCC is utilised to quantitively evaluate the explainability of the proposed networks, with the findings showing the functions of various convolutional layers in the network.
Remote sensing observations and Mars rover missions have recorded the presence of beaches, salt lakes, and wind erosion landforms in Martian sediments. All these observations indicate that Mars was hydrated in its early history. There used to be oceans on Mars, but they have now dried up. Therefore, signs of previous life on Mars could be preserved in the evaporites formed during this process. The study of evaporite regions has thus become a priority area for Mars' life exploration. This study proposes a method for training similarity metrics from surface land image data of Earth and Mars, which can be used for recognition or validation applications. The method will be applied in simulating tasks to select Mars landing sites using a selecting small-scale area of the Mars analaogue the evaporite region of Qaidam Basin, Qinghai-Tibet Plateau. This learning process minimizes discriminative loss function, which makes the similarity measure smaller for images from the same location and larger for images from different locations. This study selected a Convolutional Neural Networks (CNN) based model, which has been trained to explain various changes in image appearance and identify different landforms in Mars. By identifying different landforms, priority landing sites on Mars can be selected.
Daisy Damando, B. Gérard Josias Yaméogo, Hermine Zimé-Diawara
et al.
La résistance des moustiques aux insecticides chimiques conventionnels demeure une préoccupation majeure pour les programmes de lutte anti-vectorielle. Les recherches s’orientent actuellement vers l’utilisation d’alternatives naturelles, les bio insecticides. L’activité insecticide de certaines plantes comme le Calotropis procera (Ait.) R.br (Apocynaceae) pourrait avoir un grand intérêt dans ce domaine. Dans cette étude, nous avons effectués un criblage des extraits de feuilles de C. procera (aqueux, hydro- éthanolique, méthanolique et éthanolique) par HPTLC, puis mesurer leur teneur en stérol, triterpène et en cardénolides. Nous avons étudié également l’activité larvicide des extraits aqueux et hydro- éthanolique contre le vecteur de la dengue Aedes aegypti selon la méthodologie décrite par l’OMS.
Le profil chimique des différents extraits montre la présence de flavonoïdes, tanins, stérols et triterpènes, coumarines, alcaloïdes et cardénolides. La plus grande activité larvicide a été obtenue avec l’extrait hydro-éthanolique provenant de feuilles récoltées en saison sèche dans la localité de Kombissiri (partie Centre Sud du Burkina) avec une DL50 de (1,58 mg/ml ± 1,51 ; 1,66 mg/ml)
Les résultats obtenus indiquent que l’extrait hydro-éthanolique de C. procera pourrait servir à la formulation d’un bio-insecticide écologique et peu coûteux pour lutter contre les larves d'Aedes aegypti.
This interview highlights the extensive research project African Water Cities by architectural studio NLÉ, which explores intersections of rapid urbanization and climate change in the African context. NLÉ proposes new strategies for addressing water, culture and heritage management in Africa as Sub-Saharan Africa experiences the second-fastest rates of urbanization and population growth in the world. The discussion also addresses whether and how these strategies fit within the scope of the UN SDGs.
To reduce the heat island effect brought by conventional asphalt roofing products with high solar absorption, we propose a category of self-cleaning and self-cooling composited roofing tile (CRT) made of old corrugated containers (OCC) and tung oil inspired by traditional Chinese oil-paper umbrellas, which can be fabricated at scale and easily recycled for roofing applications. Compared with asphalt shingles, CRTs can improve the solar reflection due to the randomized structure of the cellulose microfibers, contributing to a significant temperature difference of ∼13.2 °C. In addition, they have a high thermal emissivity of 0.93 in the atmospheric window, radiating great amounts of heat into the cold outer space (∼ 3 K). The top layer tung oil film smeared on the OCC pulp fibers transforms the roofing tile from a waterabsorbing to a waterproofing state and significantly enhances the mechanical strength, contributing to a stable thermal performance in outdoor applications. Furthermore, dyed CRTs can selectively reflect visible light for desired colors and effectively reflect near-infrared light to reduce solar heating, which synchronously achieves roof cooling and aesthetic variety. These cheap, eco-friendly, and multifunctional roofing tiles can provide a value-added path for OCC recycling, which may inspire more radiative cooling composites purely from recycling waste towards an energy-saving and sustainable society.
Energy industries. Energy policy. Fuel trade, Renewable energy sources