CASBEE-City tool determines the city’s Built Environment Efficiency (BEE) by calculating the improvement of Quality of Life (Q) over human activities’ Environmental Load (L) within the city’s hypothetical boundary. A total of 58 variables (57 Q indicators and one variable for L) are used in the worldwide version of CASBEE-City which were grounded using ISO 37120:2014 Sustainable Development of Communities and 17 Sustainable Development Goals (SDGs) by the United Nations (UN). This paper examines the application of CASBEE-City for Malaysian cities using the case of Johor Bahru City and identifies assessment indicators which are customised based on the data availability, reliability and suitability through focus group discussions (FGDs) which involved 36 respondents (researchers, urban planners and stakeholders). This paper reveals Johor Bahru with moderate score B+ in 2010 and 2025. Consensus were also achieved from the 36 FGD respondents for the practicability and future potential of CASBEE-City and BEE framework in Johor Bahru.

The UK Government is committed to reducing greenhouse gas (GHG) emissions by 80% by 2050. Buildings are responsible for 37% of the total GHG emissions in the UK and the need to reduce their emissions has resulted in more stringent building regulations in the recent past. The regulations, energy rating systems and voluntary guidelines — all are primarily aimed at reducing the need for heating and associated energy use by increasing insulation and air-tightness. However, future climates are projected to be warmer than the present day. Internal gains dominated non-domestic buildings will likely overheat, the adaptation to which will require energy-intensive cooling solutions, thus defeating the purpose of heating-focused regulations. This research investigated the effects of warming climate on overheating, and energy use and resulting emissions in representative urban office spaces in London in the present-day and future climates using hourly dynamic thermal simulations. Findings suggest that more airtight and highly—insulated office buildings designed for heating—dominated temperate UK climate will overheat in the 2050s. Heating demand reduces but electricity consumption increases by 121% when hybrid cooling is adopted to ameliorate overheating. Despite the rise, adopting a mixed-mode ventilation strategy was one of the ways of achieving overall energy efficiency while meeting benchmark overheating and carbon emissions target in present and future climatic contradictions. Current heating-focused legislations need to be urgently re-evaluated to account for the effects of climatic variability and overheating risks.

Timely and accurate identification of change detection for areas depicted on nautical charts constitutes a key task for marine cartographic agencies in supporting maritime safety. Such a task is usually achieved through manual or semi-automated processes, based on best practices developed over the years requiring a substantial level of human commitment (i.e., to visually compare the chart with the new collected data or to analyze the result of intermediate products). This work describes an algorithm that aims to largely automate the change identification process as well as to reduce its subjective component. Through the selective derivation of a set of depth points from a nautical chart, a triangulated irregular network is created to apply a preliminary tilted-triangle test to all the input survey soundings. Given the complexity of a modern nautical chart, a set of feature-specific, point-in-polygon tests are then performed. As output, the algorithm provides danger-to-navigation candidates, chart discrepancies, and a subset of features that requires human evaluation. The algorithm has been successfully tested with real-world electronic navigational charts and survey datasets. In parallel to the research development, a prototype application implementing the algorithm was created and made publicly available.

Most of the phase change materials (PCMs) have been limited to use as functional additions or sealed in containers, and extra auxiliary equipment or supporting matrix is needed. The emergence of 3D printing technique has dramatically advanced the developments of materials and simplified production processes. This study focuses on a novel strategy to model thermal energy storage crystalline gels with three-dimensional architecture directly from liquid resin without supporting materials through light-induced polymerization 3D printing technique. A mask-projection stereolithography printer was used to measure the 3D printing test, and the printable characters of crystalline thermal energy storage P(SA-DMAA) gels with different molar ratios were evaluated. For the P(SA-DMMA) gels with small fraction of SA, the 3D fabrication was realized with higher printing precision both on mili- and micro-meter scales. As a comparison of 3D printed samples, P(SA-DMAA) gels made by other two methods, post-UV curing treatment after 3D printing and UV curing using conventional mold, were prepared. The 3D printed P(SA-DMAA) gels shown high crystallinity. Post–UV curing treatment was beneficial to full curing of 3D printed gels, but did not lead to the further improvement of crystal structure to get higher crystallinity. The P(SA-DMAA) crystalline gel having the highest energy storage enthalpy that reached 69.6 J·g⁻¹ was developed. Its good thermoregulation property in the temperature range from 25 to 40 °C was proved. The P(SA-DMAA) gels are feasible for practical applications as one kind of 3D printing material with thermal energy storage and thermoregulation functionality.

The optimization of photovoltaic (PV) systems is vital for enhancing efficiency and economic viability, especially under Partial Shading Conditions (PSCs). This study focuses on the development and comparison of traditional and advanced algorithms, including Perturb and Observe (P&O), Incremental Conductance (IC), Fuzzy Logic Control (FLC), Grey Wolf Optimization (GWO), Particle Swarm Optimization (PSO), and Artificial Neural Networks (ANN), for efficient Maximum Power Point Tracking (MPPT). Simulations conducted in MATLAB/SIMULINK evaluated these algorithms’ performance under various shading scenarios. The results indicate that while traditional methods like P&O and IC are effective under uniform conditions, advanced techniques, particularly ANN-based MPPT, exhibit superior efficiency and faster convergence under PSCs. The study concludes that integrating AI and ML into MPPT algorithms significantly enhances the reliability and efficiency of PV systems, paving the way for broader adoption of solar energy technologies in diverse environmental conditions. These findings contribute to advancing renewable energy technology and support the green energy transition.

Many ailments can be diagnosed while they are asymptomatic, meaning that the patient has no signs or symptoms of a progressing disease. If caught in their initial stage of formation, these maladies can be effectively treated, leading to successful outcomes; curative therapies can halt illnesses from advancing, thus improving the quality of life, and long-term survival of the patient. Still cutting-edge upgrades in precision technologies are necessary for early, reliable, affordable, and rapid disease detection, but also are vital for the well-being of people and the future of global public health. The emerging role and utility of non-invasive and repeatable diagnostic test approaches for detection of health conditions has been liquid biopsies based on genomic biomarkers. As such, biological fluids permit any measurable molecular indicator or signature (e.g., proteins), to provide valuable information on individual’s wellness and/or disease. Among the bodily secretions used for non-invasive diagnostics is sputum, a complex viscous gel-like biopolymeric network, that has gained growing recognition as a rich source of biomarkers of airway infections, pulmonary diseases, and serves as a determinant to reveal other illnesses. As per the World Health Organization, the burden of respiratory conditions is exacerbated by factors, ranging from considerable subjection to air pollution and occupational contaminants, to tobacco smoking and second-hand smoke, in addition to poor socio-economic status. Due to the likely increase of these determinants, respiratory tract ailments are on the rise, affecting the health of many individuals, in addition to putting stress on healthcare facilities and services worldwide. We therefore highlight the need to use expectorated or induced sputum specimens as a routine sample source for testing valuable protein biomarkers to diagnose these chronic maladies, to predict inflammation and disease progression, as well as monitor the effectiveness of treatments. Further, we discuss the urgency for fast and reliable point-of-care methods to detect and quantify crucial protein biomarkers in sputum specimens, and limitations faced when dealing with their complex matrices.

This article introduces a novel approach, termed the Asymmetric Probabilistic Tsetlin (APT) Machine, which incorporates the Stochastic Point Location (SPL) algorithm with the Asymmetric Steps technique into the Tsetlin Machine (TM). APT introduces stochasticity into the state transitions of Tsetlin Automata (TA) by leveraging the SPL algorithm, thereby enhancing pattern recognition capabilities. To enhance random search processes, we introduced a decaying normal distribution into the procedure. Meanwhile, the Asymmetric Steps approach biases state transition probabilities towards specific input patterns, further elevating operational efficiency. The efficacy of the proposed approach is assessed across diverse benchmark datasets for classification tasks. The performance of APT is compared with traditional machine learning algorithms and other Tsetlin Machine models, including the Asymmetric Tsetlin (AT) Machine, characterized by deterministic rules for Asymmetric transitions, and the Classical Tsetlin (CT) Machine, employing deterministic rules for symmetric transitions. Strikingly, the introduced APT methodology demonstrates highly competitive outcomes compared to established machine learning methods. Notably, both APT and AT exhibit state-of-the-art performance, surpassing the Classical Tsetlin Machine, emphasizing the efficacy of asymmetric models for achieving superior outcomes. Remarkably, APT exhibits even better performance than AT, particularly in handling complex datasets.

In Germany, as in many developed countries, over 60% of buildings were constructed before 1978, where most are in critical condition, requiring either demolition with plans for redevelopment or renovation and rehabilitation. Given the urgency of climate action and relevant sustainable development goals set by the United Nations, more attention must be shifted toward the various sustainability aspects when deciding on the strategy for renovation or redevelopment of existing buildings. To this end, this study focused on developing a smart decision support framework for aging buildings based on lifecycle sustainability considerations. The framework integrated digital technological advancements, such as building information modeling (BIM), point clouds processing with field information modeling (FIM)®, and structural optimization, together with life-cycle assessment to evaluate and rate the environmental impact of different solutions. Three sustainability aspects, namely, cost, energy consumption, and carbon emissions, were quantitatively evaluated and compared in two scenarios, namely, renovation, and demolition or deconstruction combined with redevelopment. A real building constructed in 1961 was the subject of the experiments to validate the framework. The result outlined the limitations and advantages of each method in terms of economics and environmental impact. It was further observed that optimizing the building design with the goal to reduce embodied energy and carbon in compliance with modern energy standards, was crucial to improve overall energy performance. This work demonstrated that the developed BIM-based framework to assess the environmental impact of rehabilitation work in aging buildings can provide effective ratings to guide decision-making in real-world projects.

Purpose: This research compared the dissociated phoria at near and distance fixation in free space using three techniques: the Howell test, alternate Cover test, and Thorington test. Methods: 220 healthy Mexican children (age 5.06-17.11) participated in this study. Phorias were quantified at both distances using each test, from the least to the most disruptive. The stereopsis degree and near point of convergence (break/recovery) were analyzed to understand their role on the visual system's sensorimotor balance. Results: For the exophoria/esophoria at near, the alternate Cover and Thorington tests showed similar values. The exophoria at distance, was similar with the alternate Cover and Howell tests, while esophoria, with the alternate Cover and Thorington tests. The break value and near exophoria relates to each other and affect the stereopsis degree, whereas age is associated with the stereopsis degree and break value. Conclusions: The analysis revealed that alternate Cover and Thorington tests can substitute one another, but not with the Howell test. The test's specific dissociation method may explain these results. Analyzing the binocular visual system provides information about its sensorimotor balance and fragility when faced to the technique’s degree of dissociation.

I show how the quantum paradoxes occurring when we adopt a standard realist framework (or a framework in which the collapse implies a physical change of the state of the system) vanish if we abandon the idea that a measurement is related (directly or indirectly) to a physical change of state. In Convivial Solipsism, similarly to Everett’s interpretation, there is no collapse of the wave function. But contrary to Everett’s interpretation, there is only one world. This allows also to get rid of any non-locality and to provide a solution to the Wigner’s friend problem and its more recent versions.

Mortality and readmission rates for decompensated acute heart failure (AHF) is overall increasing and risk stratification might be challenging. We sought to evaluate the prognostic role of systemic venous ultraso-nography in patients hospitalized for AHF. We prospectively recruited 74 AHF patients with a NT-proBNP level above 500 pg/mL. Then, a multiorgan ultrasound assessment (lung, inferior vena cava, Doppler of hepatic, portal, intrarenal and femoral veins) were performed at admission, discharge, and follow-up (for 90 days). An intrarenal monophasic pattern (AUC 0.923, Sn 90%, Sp 81%, PPV 43%, NPV 98%), a portal pulsatility >50% (AUC 0.749, Sn 80%, Sp 69%, PPV 30%, NPV 96%) and a VExUS score of 3 (AUC 0.885, sensitivity 80%, specificity 75%, PPV 33%, NPV 96%) predicted death during hospitalization. An IVC above 2 cm (AUC 0.758, Sn 93.l% and Sp 58.3) and the presence of an intrarenal monophasic pattern (AUC 0. 834, sensitivity 0.917, specificity 67.4%) in the follow-up visit predicted AHF related readmission. Addi-tional scans during hospitalization or calculate a VExUS score probably adds unnecessary complexity to the assessment of AHF patients. In conclusion, VExUS score does not contribute to guide therapy or the predic-tion of complications, compared to the presence of an inferior vena cava greater than 2 cm, a venous mo-nophasic intrarenal pattern or a pulsatility > 50% of the portal vein in AHF patients. Early and multidisci-plinary follow-up visit remains necessary to improve prognosis of this highly prevalent disease.

This article analyzes and compares the integration of two different maximum power point tracking (MPPT) control methods, which are tested under partial shading and fast ramp conditions. These MPPT methods are designed by Improved Particle Swarm Optimization (IPSO) and a combination technique between Neural Network and Perturb & Observe method (NN_P&O). These two methods are implemented and simulated for photovoltaic systems (PV), where various system responses, such as: voltage and power are obtained. The MPPT techniques were simulated using Matlab/Simulink environment. A comparison of the performance of IPSO and NN_P&O algorithms is carried out to confirm the best accomplishment of the two methods in terms of speed, accuracy and simplicity.

Current clinical treatment options for symptomatic, partial-thickness rotator cuff tear (sPTRCT) offer only limited potential for true tissue healing and improvement of clinical results. In animal models, injections of adult stem cells isolated from adipose tissue into tendon injuries evidenced histological regeneration of tendon tissue. However, it is unclear whether such beneficial effects could also be observed in a human tendon treated with fresh, uncultured, autologous, adipose derived regenerative cells (UA-ADRCs). A specific challenge in this regard is that UA-ADRCs cannot be labeled and, thus, not unequivocally identified in the host tissue. Therefore, histological regeneration of injured human tendons after injection of UA-ADRCs must be assessed using comprehensive, immunohistochemical and microscopic analysis of biopsies taken from the treated tendon a few weeks after injection of UA-ADRCs.

The article obtains large deviation asymptotic for sub-critical communication networks modelled as signal-interference-noise-ratio(SINR) random networks. To achieve this, we define the empirical power measure and the empirical connectivity measure, as well as prove joint large deviation principles(LDPs) for the two empirical measures on two different scales. Using the joint LDPs, we prove an Asymptotic equipartition property(AEP) for wireless telecommunication Networks modelled as the subcritical SINR random networks. Further, we prove a Local Large deviation principle(LLDP) for the sub-critical SINR random network. From the LLDPs, we prove the large deviation principle, and a classical McMillan Theorem for the stochastic SINR model processes. Note that, the LDPs for the empirical measures of this stochastic SINR random network model were derived on spaces of measures equipped with the $\tau-$ topology, and the LLDPs were deduced in the space of SINR model process without any topological limitations. We motivate the study by describing a possible anomaly detection test for SINR random networks.

Repeat-Induced Point mutations (RIP) serves as a genome defence mechanism that impedes the deleterious consequences of repeated motifs such as transposable elements in fungi. Genomic regions with RIP are biased for adenosine and thymine transitions and the cumulative influence of RIP is thought to have a considerable impact on genome composition. We investigated the impact of RIP on localized genomic regions and whole-genome sequences for representatives of the pine pathogen, Fusarium circinatum. We set out to determine the intraspecific variation in acquired RIP and the role of RIP in the development of diverse F. circinatum sub-genomic compartments. The results of the study show that the AT-enriched sub-genomic compartment accounts for ca. 97% of the calculated RIP and was further prominent in both core and accessory genomic regions. However, more extensive RIP was observed in the accessory sub-compartment and more variable regions of the genome. Regions with RIP indicated increased intrinsic curvature of the DNA which may influence DNA-protein interactions and may promote constitutive heterochromatin formation. The results show that RIP is an important source of functional novelty and genome variation. RIP contributes to the evolution of the genetic landscape and differentiation of diverse sub-genomic compartments of this important fungal pathogen.

Computation of Common Middle Point seismic sections and their subsequent time migration and diffraction imaging provides very important knowledge about the internal structure of 3D heterogeneous geological media and are key elements for successive geological interpretation. Full-scale numerical simulation, that computes all single shot seismograms, provides a full understanding of how the features of the image reflect the properties of the subsurface prototype. Unfortunately, this kind of simulations of 3D seismic surveys for realistic geological media needs huge computer resources, especially for simulation of seismic waves’ propagation through multiscale media like cavernous fractured reservoirs. In order to significantly reduce the query of computer resources we propose to model these 3D seismic cubes directly rather than the shot-by-shot simulation with subsequent CMP stacking. To do that we modify the well known "exploding reflectors principle" for 3D heterogeneous multiscale media by use of the finite-difference technique on the base of grids locally refined in time and space. To be able to simulate realistic models and acquisition we develop scalable parallel software, which needs reasonable computational costs. Numerical results for simulation of Common Middle Points sections and their time migration are presented and discussed.

This paper introduces a model-free, "on-the-fly" learning control strategy for arrays of energy converters with adjustable generator damping. The devices are arranged so that they are affected simultaneously by the energy medium. Each device uses a different control strategy, of which at least one has to be the machine learning approach presented in this paper. During operation all energy converters record the absorbed power and control output; the machine learning device gets the data from the converter with the highest power absorption and so learns the best performing control strategy for each state. Consequently, the overall network has a better overall performance than each individual strategy. This concept is evaluated for wave energy converter (WEC) with numerical simulations and experiments with physical scale models in a wave tank. In the first of two numerical simulations, the learnable WEC works in an array with four WECs applying a constant damping factor. In the second simulation, two learnable WECs were learning with each other. It showed that in the first test the WEC was able to absorb as much as the best constant damping WEC, while in the second run it could absorb even slightly more. During the physical model test, the ANN showed its ability to select the better of two possible damping coefficients based on real world input data.

This contribution considers an improved control scheme for three-phase two-stage grid-tied photovoltaic (PV) power system based on integral sliding mode control (ISMC) theory. The proposed control scheme consists of maximum power point tracking (MPPT), DC-Link voltage regulation and grid currents synchronization. A modified voltage-oriented maximum power point tracking (VO-MPPT) method based on ISMC theory is proposed for design of an enhanced MPPT under irradiation changes. Moreover, a novel DC-Link voltage control based on ISMC theory is proposed in order to achieve good regulation of DC-Link voltage over its reference. To inject the generated PV power into the grid with high quality, a voltage oriented control based on space vector modulation (SVM) and ISMC (VOC-ISMC-SVM) has been developed to control the grid currents synchronization. Numerical simulations are performed in Matlab/SimulinkTM environment in order to evaluate the proposed control strategy. In comparison with conventional control scheme, the developed control strategy provides an accurate MPP tracking with less power oscillation as well as a fast and an accurate DC-Link regulation under climatic conditions variations. Moreover, the transfer of the extracted power into the grid is achieved with high quality.

Demographic studies have revealed a strong association between exposure to high ambient temperatures during pregnancy and increased risks of preterm birth (PTB). The mechanism underlying this association is unclear, but it is plausible that altered placental function may contribute. In this study, we conducted differential gene expression analysis, gene set enrichment analysis (GSEA), and gene ontology (GO) analysis on bulk RNA-seq data from human placentas delivered at term and preterm during the warmer months compared to placentas delivered at term and preterm during the colder months in the UK. We detected 48 differentially expressed genes in preterm placentas delivered during the warmer months compared to preterm placentas delivered during the colder months, the majority of which were inflammatory cytokines and chemokines, including SERPINA1, IL1B, CCL3, CCL3L3, CCL4, CCL4L2, CCL20, and CXCL8. The GSEA positively enriched 17 signalling pathways, including the NF-κB, IL17, toll-like receptor, and chemokine signalling pathways, in warm-exposed preterm placentas, which were not observed in warm-exposed term placentas. The GO analysis revealed several biological processes, including neutrophil, granulocyte, monocyte, and lymphocyte chemotaxis, as well as inflammatory and humoral immune responses in warm-exposed preterm placentas, but not in warm-exposed term placentas. We conclude that maternal exposure to warm environmental temperatures during pregnancy alters the placental transcriptome towards inflammation and immune regulation, potentially leading to PTB.

This research provides an in-depth analysis of drought impacts in West Pokot, Kenya, utilizing both remote sensing surveys and focus group discussions. The study commenced by assessing the impact of drought on vegetation health via spatial sensors. It then utilized surveys and focus group discussions (FGDs) to engage farmers from the most drought-affected areas in Kacheliba and Sigor sub-counties. The analysis of remote sensing data from 1990 to 2022 highlighted that Sigor and Kacheliba experienced significant drought events during the years 1995, 2000, 2002, 2005, and 2009, and 1991, 1995, 2000, 2005, and 2019, respectively. This study delves into both the meteorological and socio-economic effects on local communities. Using the Multinomial Logistic Regression (MLR) model with the glm function, the research uncovered the impacts of so-cio-economic factors and agricultural practices on household livestock production. Additionally, the study employed Multiple Correspondence Analysis (MCA) to explore the dynamics between livestock production, community resilience, and crop production. The findings underscore the urgent need for tailored interventions to enhance community resilience in the face of increasing climatic extremes, serving as a blueprint for similar arid and semi-arid regions worldwide.

Landraces are considered a crucial component of biodiversity conservation, serving as a reservoir of genetic diversity. Consequently, the collection, cultivation and detailed characterization of such landraces constitute an inherent aspect of the world’s natural resource heritage. This effort holds promise for the development of elite varieties capable of thriving amidst continuous global climate fluctuations. In this context, we conducted a comprehensive assessment of the main agronomic attributes, physico-chemical properties, and functional quality traits of the major hot pepper landraces adapted to diverse climatic conditions in Tunisia. These landraces include ‘Dhirat’, ‘Semmane’, ‘Beldi’, ‘Nabeul’, ‘Jerid’, ‘Mahdia’, ‘Cayenne’, ‘Kairouan’ and ‘Baklouti’. Most of the pepper landraces exhibited satisfactory yields, ranging from 1163.25 to 1841.67 g plant-1 in ‘Jerid’ and ‘Kairouan’, respectively, indicating robust productivity, especially under prevailing climatic changes and high temperatures. Landraces such as ‘Baklouti’, ‘Beldi’, ‘Nabeul’, ‘Semmane’, ‘Kairouan’ and ‘Mahdia’ appear suitable for both fresh consumption and processing, owing to their favorable average fruit weight and soluble solids content. Functional quality and the levels of antioxidants, as well as radical scavenging activity, emerged as key discriminating factors among pepper landraces. Irrespective of genotype, capsaicin and dihydrocapsaicin constituted the major capsaicinoids, accounting for at least 87% of the total. Total capsaicinoids ranged from 1.81 µg g−1 to 193.71 µg g−1, with ‘Baklouti’ and ‘Jerid’ identified as the most pungent landraces. Total carotenoids ranged from 45.94 µg g−1 to 174.52 µg g−1 with ‘Semmane and ‘Jerid’ exhibiting the highest levels. Considerable variation was observed in β-carotene content, spanning from 3% to 24% of the total carotenoids. α-Tocopherol content ranged from 19.03 µg g-1 fw in ‘Kair-ouan’ to 30.93 µg g-1 fw in ‘Beldi’, exerting a notable influence on the overall tocopherol content. Conversely, the other isomers were detected at very low concentrations. The total vitamin C content ranged from 132 mg 100g-1 fw in ‘Mahdia’ to 200 mg 100 g-1 fw in ‘Nabeul’, indicating relatively low genetic variability. However, large variability was detected in total phenolics content, ranging from 168.58 mg GAE kg-1 fw in ‘Beldi ‘to 302.98 mg GAE kg-1 fw in ‘Cayenne’. Among the pepper landraces tested, ‘Cayenne’ achieved the highest value of radical scavenging activity in both hydrophilic and lipophilic fractions (RSAHF and RSALF), with variations rang-ing from 59% to 120% for RSAHF and from 4% to 64% for RSALF. This study aims to: 1) preserve and enhance the value of local genetic resources, 2) identify desiderable traits for incorporation into breeding programs, and 3) develop high-quality, high-yielding cultivars capable of with-standing climate variations.

In the global carbon cycle, atmospheric carbon emissions, both ‘natural’ and anthropogenic, are balanced by carbon uptake (i.e. sequestration) that mostly occurs via photosynthesis, plus a much smaller proportion via geological processes. Since the formation of the Earth about 4.54 billion years ago the ratio between emitted and sequestered carbon has varied considerably with atmospheric CO₂ levels ranging from 100,000 ppm to a mere 100 ppm. Over this time, a huge amount of carbon has been sequestered due to photosynthesis and essentially removed from the cycle, being buried as fossil deposits of coal, oil and gas. Relatively low atmospheric CO₂ levels were the norm for the past 10 million years, and during the past million years they averaged about 220 ppm. More recently, the Holocene epoch, starting ~11,700 years ago, has been a period of unusual climatic stability with relatively warm, moist conditions and low atmospheric CO₂ levels of between 260 and 280 ppm. During the Holocene, stable conditions facilitated a social revolution with domestication of crops and livestock leading to urbanisation and development of complex technologies. As part of the latter process, immense quantities of sequestered fossil carbon have recently been used as energy sources, resulting in a particularly rapid increase in CO₂ emissions after 1950 CE to the current value of 424 ppm, with further rises to >800 ppm predicted by 2100. This is already perturbing the previously stable Holocene climate and threatening future food production and social stability. Today, the global carbon cycle has been shifted such that carbon sequestration is no longer keeping up with recent anthropogenic emissions. In order to address this imbalance it is important to understand the roles of high-capacity carbon sequestration systems, such as natural forests and tropical croplands, and to devise strategies to facilitate net CO₂ uptake.

Sri Lanka's vulnerability to climate change-induced natural disasters, particularly floods, under-scores the urgent need for an integrated approach to disaster risk management (DRM) that ad-dresses the interconnected challenges within the water-food-land-energy nexus. The Deduru Oya basin, located in the north-western region, exemplifies this vulnerability, with its predominantly intermediate climatic zone susceptible to flooding. While the focus has traditionally been on flood risk reduction, it is imperative to recognize the broader implications of floods on water, food, land, and energy systems. This study aims to strengthen data acquisition and management efforts to better understand rainfall trends and their impact on the water-food-land-energy nexus in the Deduru Oya basin. By compiling 60 years of rainfall data and conducting time series analysis, we observed a decreasing trend in monthly rainfall, particularly during the South-West Monsoon, Second Inter Monsoon, and North-East Monsoon seasons. These findings have significant implica-tions for water availability, agricultural productivity, land use patterns, and energy generation in the basin. Moreover, the malfunction of stakeholders' responsibilities for local-level flood risk management exacerbates the challenges faced by communities living in flood-prone areas. By in-tegrating insights from this study into flood risk management strategies, stakeholders can develop holistic approaches that not only mitigate flood risk but also enhance resilience across the water-food-land-energy nexus. This interdisciplinary approach will inform policymakers, flood manag-ers, practitioners, and the community in formulating effective strategies to address the multifacet-ed challenges posed by floods in the Deduru Oya basin and beyond.

Variability is the predisposition of the elements in systems to assume different values over time and space. In biology, the variability is basic to explain differences and development in organisms but in the fields of scientific and technological information, the effects of variability on evolutionary dynamics of disciplines and technologies are unknown. In a broad analogy with the principles of biology, the variability within research fields can be a central argument to explain trajectories in scientific development and technological evolution. The purpose of the present study is to see whether statistical evidence supports the general hypothesis that the rate of growth in technologies can be explained by the level of variability in scientific fields and with this principal goal to analyze the relation between scientific variability and rate of growth in technologies. Proposed hypothesis of scientific variability here endeavors to explain basic sources of scientific development and technological evolution to lay the foundations for a general theory. The test here is based on emerging research fields of quantum technologies: Quantum Imaging, Quantum Meteorology, Quantum Sensing and Quantum Optics. A preliminary statistical evidence seems in general to support the hypothesis stated that the rate of growth in technological fields can be explained by the level of scientific variability in research fields, measured with relative entropy index. Nonparametric correlation based on Spearman’s rho shows a positive coefficient of 0.80 of these variables; linear model of the rate of technological growth = f(scientific variability) reveals a coefficient of regression equal to 1.63 (R²=0.60). Findings here suggest a general law that scientific variability positively drives scientific development and technological evolution. In particular, a higher variability within research fields can support scientific development and a high rate of growth in technological evolution (measured with scientific and technological information). Proposed hypothesis of scientific variability is especially relevant in environments of rapid change to explain determinants and dynamics of technological change within a general theoretical framework that supports technological management and forecasting of promising innovations.

This study was aim to assess the spatial-temporal trends of urban expansion with land use/land cover change dynamics over a period of 30 years in Addis Ababa. The source of data were Land sat satellite imagery freely available by the United States Geological Survey, Addis Ababa City plan map obtained from Addis Ababa city governance planning and development commission, and Ethiopia Space Science and Geospatial Agency. The data obtained were analysed by using QGIS, and ERDAS software. The finding showed that over the last thirty years Addis Ababa city was highly spreads with (Urban Expansion Intensity Index(UEII)=1.524%); building-up land increased faster (dynamic degree (K) = -6.22 and Annual Urban Expansion Rate(AUER) is 3.56. From the finding, Addis Ababa is spreading speedily.

Accurately glacier mapping is crucial for understanding climate change impacts, but existing efforts may be biased due to overlooking spatial autocorrelation during map validation. To address this, we compared several widely used machine learning algorithms as gradient boosting machines (GBM), k-nearest neighbor (KNN) and random forest (RF) with parametric logistic regression (GLM) and an unsupervised remote sensing-based method (NDSI) for mapping Peru's glacier regions in a thoughtful experimental setup. Spatial and non-spatial cross-validation methods were used to evaluate model’s performance and compared with a fully independent test set. Performance differences of up to 18% were found between bias-reduced (spatial) and overoptimistic (non-spatial) cross-validation results when compared to independent test set, emphasizing the need to consider spatial autocorrelation when using machine learning for glacier mapping. K-nearest neighbors (KNN) was the overall best model across regions consistently demonstrating the highest performance followed by logistic regression (LR) and gradient boosting machines (GBM). Our novel validation approach, accounting for spatial characteristics, provides valuable insights for glacier mapping studies and future efforts on glacier retreat monitoring. Incorporating this approach improves the reliability of glacier mapping, guiding future national-level initiatives.

The climate crisis is developing to a life-changing event on a global level. Health promotion with the aim to increase the health status of individuals, independent from the present health status has been developed on scientific basis at least for the last eight decades and follows. There are some basic principles, which are prerequisites for both, health promotion and climate protection. Those principles include (1) sustainability, (2) orientation on determinants, and (3) requirement of in-dividual as well as community approaches. People are generally aiming to protect their lifestyle habits (e.g. traveling, consumer habits) and personal properties (e.g. car, house) by easy solution with as little effort as possible, and this can affect both, health and climate. To reduce the emission of greenhouse gases and to protect our environment, changes towards a sustainable lifestyle have to be embed into everybody’s mind. Examples for domains, that need to be addressed in health promotion as well as in climate protection include education/ knowledge/ (health) literacy, physical activity, nutrition and dietary habits, mental health, and social capital. If health promo-tion fails to tackle those domains, this will continue to drive climate crisis. And climate change, in turn, will affect health. On the other hand, developing and promoting health resources in the domains mentioned could again help to mitigate the health-damaging effects of climate change.

Objective: The study aimed to provide a picture total of the forest and erosion status of the beach and dykes of Kien Giang and Ca Mau. Theoretical framework: Kien Giang and Ca Mau are located in the West Sea, and in recent years, along the coast of this region, erosion of the coast and sea dykes has been profound. Method: There are 18 sample plots for testing. The map also includes 68 survey plots that are predefined and used as a basis for positioning in the field. The measurement indicators include tree species identification. Results and conclusion: The level of erosion in Ha Tien’s forests varies based on tree density and environmental factors. The forest with no erosion has a thickness of 9,600 trees/ha and a stem diameter of 19 cm, while the extremely erosion forest has 2,000 trees/ha and a stem diameter of 6 cm. Topographically, Ha Tien has little erosion, while U Minh is a low-lying area with high erosion. Erosion levels are 1-2 in January-April, 4-5 in May-October, and 3 in November-December. Currently, the section is divided into 28 sub-sections, with Kien Giang having 23. One sub-section is level 1, 11 sub-sections are level 2, 1 is level 3, 3 are level 4, and 3 are level 5. In Ca Mau, two sub-sections are level 4, and 3 are level 5. Implications of the research: With climate change and rising sea levels, erosion levels tend to increase one level in sub-section areas in the coming years.

For tropical forests to survive anthropogenic climate change, the trees that comprise them will need to tolerate the newly emerging conditions through adaptation or acclimation, or they can avoid climate change through range shifts and “species migrations”. In this review, we show that the rapid pace and extreme severity of modern climate change makes it extremely unlikely that tropical tree species can adapt (with some possible exceptions). We also show that while many tropical tree species are shifting their distributions to higher, cooler elevations, the rate of these migrations are mostly insufficient to offset ongoing changes in temperatures, especially in lowland tropical rainforests where thermal gradients are shallow or nonexistent. We argue that the best hope for tropical tree species to avoid becoming “committed to extinction” is acclimation. While several new methods are being developed to test for acclimation, we unfortunately still do not know if tropical tree species can acclimate or what factors may prevent or facilitate acclimation. Until these questions are answered, our ability to predict the fate of tropical species and tropical forests – and the many services that they provide to humanity – remains critically impaired.

This work proposes a methodological approach applied to ephemeral gravel-bed streams to verify the change in the magnitude and frequency of hydrological events affecting the morphological dynamics and sediment budget in this type of channel. For the case study the Azohía Rambla, located in southeastern Spain, was chosen, emphasizing the research on two reference riverbed sections (RCRs): an upper one, with a predominance of erosion, and a middle one, where processes of incision, transport, and deposition converge. First, this approach focuses on relationships between peak discharges and sediment budgets during the period 2018 to 2022. For this purpose, water level measurements from pressure sensors, a One-Dimensional Hydrodynamic model, and findings from comparative analyses of high-resolution differential digital elevation models (HRDEM of Difference - HRDoD) based on SfM-MVS and LiDAR datasets were used. In a second phase the GeoWEPP model was applied to the period 1996-2022 in order to simulate runoff and sediment yield at the event scale for the watersheds draining into both RCRs. During the calibration phase a sensitivity analysis was carried out to detect the most influential parameters in the model and to confirm its capacity to simulate peak flow and sediment delivery in the area described above. Values of NS (Nash-Sutcliffe efficiency) and PBIAS (percent bias) equal to 0.86 and 7.81%, respectively, were found in the calibration period, while these indices were 0.81 and -4.1% in the validation period. Finally, different event class patterns (ECPs) were established for the monitoring period (2018-2022), according to flow stage and morphological channel adjustments (overtopping, bankfull and sub-bankfull, and half-sub-bankfull), and then retrospectively extrapolated to stages of the prior simulated period (1996-2018) from their typical sequences (PECPs). The results revealed a significant increase in the number of events and PECPs leading to lower bed incision rates and higher vertical accretion, which denotes a progressive increase in bed armoring and bank erosion processes.

Many techniques have been and are being made to find alternatives to water-saving practices. Among them, Partial root drying (PRD), one of the effective approaches, plays a major role in reducing the harmful effects of water deficit stress. An experiment was carried out using irrigation strategies [I1 (100% full irrigation “FI”), I2 (75%FI), I3 (50%FI), and I4 (PRD (50%FI)] and soil organic mulch [L0 (Zero layer organic soil mulch” control”), L1 (Single layer organic soil mulch), L2 (Two layers of organic soil mulch), and L3 (Three layers of organic soil mulch)] to inspect the impact of those treatments for increasing yield, water productivity and saving energy under arid region conditions. To meet the study's objective, two field experiments were carried out at a private farm. Our results demonstrated a general decrease in water stress and salt accumulation inside root-zone area with PRD with L3. The PRD strategy increased fruit yields by 3.7 and 7.3% and water productivity by 51.9 and 53.1% compared with I1 during 2020/2021 and 2021/2022, respectively, while reducing the applied irrigation water by 50 %. The PRD strategy showed superior results in increasing mango yield and water productivity. In general, PRD can be used as good technique to save water and energy up to 50% and enhance productivity along with using organic mulching, ultimately improving mango yield under arid climatic regions. It may prove a good adaptation strategy for current and future water shortage scenarios of climate change.

The Kingdom of Saudi Arabia (KSA) is known for its high car ownership and usage as well its high GDP per capita. This is combined with low/ or no provision of public transportation (PT) systems, has been resulting in perceptual attitudes of full dependency on private car travel. The level of awareness of the benefits of reducing car use and increasing the travel by more sustainable options, has a great impact on social change and behaviour. The Kingdom is currently progressing towards a new phase of “national transfer” through implementation of strategic and sustainable measures and programs. The city of Riyadh is construction a massive metro-system in Riyadh, that is nearing completion and operation. The public is aware of the national agenda, aware of the newly constructed projects and aware of the needed social change to realize the new vision of the country. This paper aims to assess travel behaviour and attitudes towards public transportation of Saudi travellers’ who are witnessing the new transformation in the Kingdom and who are aware of the new sustainable projects. Depicted from the theory of random utility, a discrete choice model of the intent to use public transportation is calibrated as a function of social and attitudinal factors. An online survey was designed and carried out using social media means; a completed 399 questionnaires have been obtained and studied. The methodology includes examining attitudes and preferences of the participants towards using public transportation options against participants’ socio-economic data. The analysis was carried out using ordinal logistic regression analysis (OLR) which is an efficient technique that is derived from the theory of random utility. The results show a good support for PT; a higher support for public transportation modes, form participants who are young females, lower income groups and the university graduates were reported. The level of support seems higher with the higher level of awareness about the new PT system.

The potential impacts of climate change on the distribution of tuna in Pacific Island Countries’ Exclusive Economic Zones have yet to be investigated rigorously, and so their persistence and abundance in these areas remain uncertain. Here, we estimate optimal fisheries areas for four tuna species; Albacore (Thunnus alalunga), Bigeye (Thunnus obesus), Skipjack (Katsuwonus pelamis), and Yellowfin (Thunnus albacares). We consider different climate change scenarios, RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5, within a set of tuna catch records in the Exclusive Economic Zone of Tonga. Using environmental and CPUE datasets, species distribution modelling estimated and predicted these fisheries areas in the current and future climatic scenarios. Our projections indicate an expansion in area and a shift of productive areas to the southern part of this Exclusive Economic Zone of Tonga. This is an indication that future climatic scenarios might be suitable for the species under study however, changes in trophic layers, ocean currents and ocean chemistry might alter this finding. Information provided here will be relevant in planning future national actions towards proper management of these species.

This paper presents designing an attitude motion control strategy for a half-car model using an anti-jerk predictive controller. Anti-jerk predictive controller based on active aerodynamics surfaces is employed to deal with the anticipated future road maneuvers and improve vehicle ride performance by canceling out external jerks acting on the vehicle body. The body jerks are produced during vehicle traversing on a double lane-change maneuver, acceleration, or braking. The control strategy helps the vehicle to achieve a realistic operation of the active aerodynamic surface to improve the vehicle’s ride performance, i.e., ride comfort and road holding during cornering, acceleration, or braking. The anti-jerk predictive controller is developed based on the predictive control strategy, which predicts future road inputs and uses them to compensate for the vehicle’s attitude motion. The simulation results show that the proposed control strategy effectively reduces the effects of vehicle body jerks transmitted to the passengers, improving ride comfort without degrading vehicle handling. The anti-jerk predictive controller successfully tracks the desired attitude position by canceling the external body jerks.

The threat posed by climate change, the progressive erosion of natural resources, the polluting effects related to private motorization, energy waste, excessive consumption of agricultural and natural soils and their progressive waterproofing and reduction in vegetation cover, with the subsequent environmental degradation, have highlighted the need for a sustainable management of natural resources, in terms of an equitable and ethical development, to build inclusive communities able to adapt to the negative effects of emergency phenomena, through new capacities of economic, cultural and social resilience. This contribution presents the results of the activities conducted in the RivEr/Generation_LAB, a project organized by three CIVIS members (Sapienza University of Rome, Universitè libre de Bruxelles, Universidad Autonoma de Madrid) as a part of the CIVIS Project "RivEr/Generation_LAB. Linking resilience with inclusiveness in the urban built environment of Rome, Brussels, and Madrid", financed into the Hub4 Cities, Territories & Mobilities’ Call for proposals 2021. The project proposes a methodology of intervention in the Flaminio district, in particular on the 'Olympic Village' and its relationship with the Tiber River, in line with the Sustainable Development Goals, the Millennium Ecosystem Assessment and the New European Bauhaus, to establish new relationships between cities and the natural environment, favouring sustainable and inclusive public spaces.

Coastal areas are highly vulnerable to climate change hazards (e.g., sea-level rise, flooding, coastal erosion), which can lead to significant impacts at the ecosystem and societal level. Interest in Ecosystem-based Adaptation (EbA) is gaining importance due to its potential multiple benefits, including social and environmental aspects, when compared to more traditional approaches such as hard engineering interventions. When assessing EbA strategies, further understanding of the nature-society functions, processes, values, and benefits is needed to increase its application. This study contributes to a better knowledge of EbA by developing a systematic literature review of studies performing socio-economic assessments of climate change adaptation in coastal areas. The analysis of 54 publications revealed that most of the studies assessed adaptation solutions through cost-benefit analysis, followed by multi-criteria analysis, and other techniques. Hybrid adaptation strategies based on different combinations of hard, soft and EbA interventions were considered as potential optimal solutions in a significant part of the assessments. This study suggests the potential co-benefits of EbA in the form of ecosystem services, livelihood diversification or biodiversity conservation, but also stresses the need for further research on this topic, as well as on evaluating how EbA perform in the long-term under climate changing conditions scenarios.

In the context of global warming and reduction in fresh water availability is presented a study of the evolution of dew, rain and evapotranspiration in the NW of Africa. The time periods are concerned with the years 2005-2020, using existing data, and years 2020-2100, using the low and high emissions representative concentration pathway scenarios RCP 2.6/8.5 from the Cordex database. A continuous decrease in rain precipitation is observed, on order of -14 mm/decade for the more credible scenario RCP 8.5. The amplitude is maximum on the coast and on the foothills of Atlas. A clear decrease in dew yields is also observed along a NW/SE axis, strongly correlated with a corresponding decrease in relative humidity (up to 7%). Chemical dew and rain data in the representative site of Mirleft correspond to the major cations Na+ > Ca2+ > Mg2+ > K+, similar to a local spring water. Concentrations in rain are about two times less than in dew water. Ionic concentrations are compatible with WHO standards. The seasonal variations of the ionic concentrations in dew and rain follow a volume dilution dependence. The expected diminution in dew and rain volumes according to the RCPs 2.6 and 8.5 should increase the dew and rain ionic concentrations in the future.

In this article, we present the use of the coupled land surface model and groundwater flow model SWAT-MODFLOW with the decision support tool WEAP (Water Evaluation and Planning software) to predict future surface water abstraction scenarios in a complex river basin, under conditions of climate change. The modeling framework is applied to the Dee River catchment in Wales, United Kingdom. Regarding hydrology, the coupled model improves overall water balance and low streamflow conditions, compared to a stand-alone SWAT model. The calibrated SWAT-MODFLOW is employed with high resolution climate model data from the UKCP18 project with future scenario of RCP85 from 2020 to 2040. Then, water supply results from SWAT-MODFLOW are fed into WEAP as input for the river reach in the downstream region of the river basin. This system is utilized to create various future scenarios of surface water abstraction of public water supply in the downstream region: maximum licensed withdraw, 50 % authorized abstractions, monthly time series with 1% increase of water use, and maximum water withdraw year based on historical records repeated every year with 1% increase of water use, to estimate the unmet demands and streamflow requirement. This modeling approach can be used in other river basins to manage scenarios of supply and demand.

Forests play an important role in reducing greenhouse gases in the atmosphere, thereby mitigating the impact of climate change. Estimating the accumulated biomass in a forest ecosystem is important for assessing the productivity and sustainability of the forest. Allometric models for above ground biomass (AGB) are linear regression equations based on the relationships between biomass and diameter at breast height (DBH), tree height (H), and/or wood density. This study estimates AGB in the Colo-I-Suva Forest Park by applying the allometry of Chave et al (2005) and the diameter: height ratio derived from Payton & Weaver (2011) for height estimation in a plot of 20

The US pacific northwest recorded its highest temperature in late June 2021. The three-day stretch of scorching heat had a devastating effect on not only the residents of the state, but also on the crops thus impacting the food supply-chain. It is forecasted that streaks of 100-degree temperatures will become common. Farmers will have to adapt to the changing landscape to preserve their crop yield and profitability. A research collaborative consisting of researchers and academicians in Eastern Washington led by a pioneering startup has setup a 16.9-acre Honeycrisp Apple Smart Orchard in Grandview, WA as a laboratory to study the environmental and plant growth factors in real-time using modern computational tools and techniques like IoT (Internet of Things), Edge and Cloud Computing, and Drone and LiDAR (Light Detection and Ranging) imaging. The computational analysis is used to develop guidelines for precision agriculture for orchard blocks to address plant growth issues scientifically and in a timely fashion. The analysis also helps in creating risk-mitigation strategies for severe weather events while helping prepare farmers to maximize crop yield and profitability per acre. I was fortunate to gain access to the terabytes of farm data related to the weather, soil, water, tree, and canopy health, to analyze and formulate recommendations for the farmers that can be adopted nationwide for different crops and weather conditions. This paper discusses the different streams of farm data that were analyzed (ex. soil moisture, soil water potential, and sap flow) and the development of the framework to use data to convert insights into actionable steps. For example, the use of sensors can inform a farmer that their level of soil water potential is below threshold in a specific patch of the orchard, prompting them to turn on irrigation for the patch instead of the whole orchard. I estimate that using an IoT-sensor-based decision framework discussed in this paper, growers can save up to 55% of their water costs for the season. Using these insights, farmers can better manage their irrigation resources and labor, thus maximizing their crop yield and profits.

Creating new business models is crucial for the implementation of clean technologies for industrial decarbonization. With incomplete knowledge of market processes and uncertain conditions, assessing the prospects of a technology-based business model is challenging. This study combines business model innovation, system dynamics and exploratory model analysis to identify new business opportunities in a context of socio-technical transition and assess their prospects through simulation experiments. Furthermore, insights are visualized in a roadmap to coordinate action among the actors involved. This combination of methods is applied to the case of a business model aiming at ensuring stability of the electrical grid by centralizing the management of flexible loads in industrial companies. A system dynamics model was set up to simulate the diffusion of flexible electrification technologies. Through scenario definition and sensitivity analysis, the influence of internal and external factors on diffusion was assessed. Results highlight the central role of energy costs and customer perception. The chosen combination of methods allowed the formulation of concrete recommendation for coordinated action, explicitly accounting for the various sources of uncertainty. We suggest testing this approach in further business model innovation contexts.

Air change rate is an important parameter for quantification of ventilation heat losses and also affects the indoor climate of buildings. Indoor air quality is significantly associated with ventilation. If air change isn't sufficient, trapped allergens, pollutants and irritants can degrade the indoor air quality and affect the well-being of a building's occupants. Many studies on ventilation and health have concluded that lower air change rates can have a negative effect on people’s health and low ventilation may result in an increase in allergic diseases. Quantification of air change rate is complicated, since it is affected by a number of parameters, of which the one of the most variable is the air-wind flow. This study aims to determination and comparison of values of the air change rate in two methods - by quantifying of aerodynamic coefficient Cp = Cpe - Cpi – so called aerodynamic quantification of the building and the methodology based on experimental measurements of carbon dioxide in the selected reference room in apartment building.

Creating new business models is crucial for the implementation of clean technologies for industrial decarbonization. With incomplete knowledge of market processes and uncertain conditions, assessing the prospects of a technology-based business model is challenging. This study combines business model innovation, system dynamics and exploratory model analysis to identify new business opportunities in a context of socio-technical transition and assess their prospects through simulation experiments. Furthermore, insights are visualized in a roadmap to coordinate action among the actors involved. This combination of methods is applied to the case of a business model aiming at ensuring stability of the electrical grid by centralizing the management of flexible loads in industrial companies. A system dynamics model was set up to simulate the diffusion of flexible electrification technologies. Through scenario definition and sensitivity analysis, the influence of internal and external factors on diffusion was assessed. Results highlight the central role of energy costs and customer perception. The chosen combination of methods allowed the formulation of concrete recommendation for coordinated action, explicitly accounting for the various sources of uncertainty. We suggest testing this approach in further business model innovation contexts.

Fundamental principles of modern cities and urban planning are challenged during the COVID-19 pandemic, such as the advantages of large city size, high density, mass transport, free use of public space, unrestricted individual mobility in cities. These principles shaped the development of cities and metropolitan areas for more than a century, but currently, there are signs that they have turned from advantage to liability. Cities Public authorities and private organisations responded to the COVID-19 crisis with a variety of policies and business practices. These countermeasures codify a valuable experience and can offer lessons about how cities can tackle another grand challenge, this of climate change. Do the measures taken during the COVID-19 crisis represent a temporal adjustment to the current health crisis? Or do they open new ways towards a new type of urban development more effective in times of environmental and health crises? We address these questions through literature review and three case studies that review policies and practices for the transformation of city ecosystems mostly affected by the COVID-19 pandemic: (a) the central business district, (b) the transport ecosystem, and (c) the tourism-hospitality ecosystem. We assess whether the measures implemented in these ecosystems shape new policy and planning models for higher readiness of cities towards grand challenges. And how, based on this experience, cities should be organized to tackle the grand challenge of environmental sustainability and climate change.

This study numerically analyzed the effect of composition and temperature and oxygen concentration changes on the selfignition characteristics of n-heptane/methane blended fuels in order to cope with development of alternative fuels and international environmental regulations. CHEMKIN-PRO is used as the analysis program and the LLNL model is used as the reaction model. The numerical results revealed that on autoignition and ignition delay time were sensitive to changes in fuel composition and oxygen concentration. As the methane ratio increases, OH radicals causing ignition are delayed in generation and the concentration is lowered, thus longer the ignition timing. The oxygen concentration in the mixed fuels are changed to simulate the exhaust gas recirculation and a numerical analysis in then performed. As the oxygen concentration decreases, the ignition delay time longer because the nitrogen gas acts as a thermal load in the combustion chamber.

Climate change is likely to have a complex effect on the growth of plants, their phenology, plant-pollinator interactions, and reproductive success. Therefore, we tested the impact of three key factors (temperature, water, and nitrogen supply) on traits, pollination, and seed production in Sinapis alba (Brassicaceae). We grew the plants in different combinations of temperature, water, and nitrogen supplementation, measured multiple vegetative and floral traits, and assessed the response of pollinators in the field. We also evaluated the effect of growing conditions on seed set in plants exposed to pollinators and hand-pollinated plants. Our results show that water stress impaired vegetative growth, decreased flower production, reduced visitation by pollinators and seed set, while nitrogen availability played an important role in nectar production. Temperature modulated the effect of water and nitrogen availability on vegetative and floral traits and strongly affected flowering phenology and flower production. We demonstrated that changes in temperature, water, and nitrogen availability induce changes in plant vegetative and floral traits which impact flower visitation and consequently plant reproduction. Climate change, particularly increasing temperature combined with reduced precipitation, thus may impact plant-pollinator interactions with negative consequences for the reproduction of wild plants and insect-pollinated crops.

Globally, increasing rates of obesity are one of the most important health issues. The association between breakfast skipping and body weight is contradictory between cross-sectional and interventional studies. The systematic review and meta-analyses aim to summarize this association based on observational longitudinal studies. We included prospective studies on breakfast skipping and overweight/obesity or weight change in adults. Literature was searched until September 2020 in PubMed and Web of Science. Summary RRs with a 95% CI were estimated in pairwise meta-analyses by applying a random-effects model. In total, 9 studies were included in the systematic review and 6 of them were included in the meta-analyses. The meta-analysis indicated an 13% increased RR for overweight/obesity when breakfast was skipped on ≥ 3 days per week compared to ≤ 2 days per week (95% CI: 1.06, 1.21, n=3 studies). The meta-analysis on weight change displays a 21% increased RR for weight gain for breakfast skippers compared to breakfast eaters (95% CI: 1.05, 1.40, n=2 studies). The meta-analysis on BMI change displayed no difference between breakfast skipping and eating (RR=1.02, 95% CI: 0.99, 1.05, n=2 studies). This study provides low meta-evidence for an increased risk for overweight/obesity and weight gain for breakfast skipping.

Research focused on understanding wider systemic factors driving behavioral change is limited with a dominant focus on the role of individual farmer and psychosocial factors for farming practice change, including reducing fertilizer application in agriculture. Adopting a wider systems perspective, the current study examines change and the role that supporting services have on fertilizer application rate change. A total of 238 sugarcane growers completed surveys reporting on changes in fertilizer application along with factors that may explain behavior change. Logistic regressions and negative binomial count-data regressions were used to examine whether farmers had changed fertilizer application rates and if they had, how long ago they made the change, and to explore the impact of individual and system factors in influencing change. Approximately one in three sugarcane growers surveyed (37%) had changed the method they used to calculate fertilizer application rates for the cane land they owned/managed at some point. Logistic regression results indicated growers were less likely to change the basis for their fertilizer calculation if they regarded maintaining good relationships with other local growers as being extremely important, they had another source of off-farm income, and if they had not attended a government-funded fertilizer management workshop in the five years preceding the survey. Similar drivers promoted early adoption of fertilizer practice change; namely, regarding family traditions and heritage as being unimportant, having sole decision-making authority on farming activities and having attended up to 5 workshops in the five years prior to completing the survey. Results demonstrated the influence of government-funded services to support practice change.

Since the emergence of the quantified self movement, users aim at health behavior change, but only those who are sufficiently motivated and competent with the tools will succeed. Our literature review shows that theoretical models for quantified self exist but they are too abstract to guide the design of effective user support systems. Here, we propose principles linking theory and implementation to arrive at a hierarchical model for an adaptable and personalized self-quantification system for physical activity support. We show that such a modeling approach should include a multi-factors user model (activity, context, personality, motivation), a hierarchy of multiple time scales (week, day, hour), and a multi-criteria decision analysis (user activity preference, user measured activity, external parameters). This theoretical groundwork, which should facilitate the design of more effective solutions, has now to be validated by further empirical research.

Soil organic carbon (SOC) sequestration in arable soils is a challenging goal for soil management. Multiple factors should be considered for the prediction of the soil capacity to fix atmospheric carbon. In this study, we focused on the effect of crop rotation and previous land use for future carbon sequestration on two experimental fields with identical soils (Retisols) and input of organic fertilizers. We analyzed the SOC dynamics and used the Roth C model to forecast SOC changes under RCP4.5 and RCP8.5 scenarios. Our experimental and modelling results indicated a consistent increase in SOC stocks and the stable fractions of soil organic matter (SOM). The increase in SOC was higher in the experiment with the crop-grassland rotation that in the experiment with a rotation of row crops and barley. With similar total SOC stocks, the efficiency of soil management differed as reflected by the contrasting composition of SOM, as fields with a long cultivation history showed higher SOM stability. The goal of 4‰ annual increase of SOC stocks may be reached under crop- grassland rotation in 2020-40 and 2080-90 when applying mineral or organic fertilizer system for scenario RCP4.5, and mineral fertilizer system in 2080-2090 for scenario RCP8.5.

Together with display and input, storage and processing are requisite to computing. While storage technologies have improved tremendously in capacity and speed over the years, the basic principles enabling information storage into digital 1 and 0 remains the same: induction of phase change in the storage substrate. But recently, there has been much research into structural phase change material (SPCM) and exploration of its possible use in various types of memory storage applications. Despite unconventional use of structural change between amorphous and crystalline state as well as that between crystal structures for encoding information, key barriers for its widespread use remains access speed, capacity to cost ratio, and fidelity of storage. Hence, given the performance requirement of SPCM for memory applications, what are the material and design considerations that feed into translating a promising application into a practical reality? Given the important role of kinetic and thermal energy in structural organization of a phase change material, precise characterization of structural change in the material with external physical factors such as heat, voltage and current, is critical for storage material design. Next comes the precision at which individual memory cells for storing single bits of information could be defined reproducibly and at high fidelity using SPCM. In congruent with memory cell definition lies the equally important aspect of constraining the field characteristics used in modulating the phase state of the memory medium. Specifically, while heat is useful for mediating the “melting” of a crystalline material into its amorphous state, heat conduction is less useful for transferring the “switch command” from the effector to the memory material. More importantly, choice of structural phase change material for memory applications likely revolves around those where individual memory cells could be defined in a cross array format, which is amenable to high density information storage. Durability and fidelity of information storage are additional factors of design that favours selection of SPCM with phase change occurring at narrow operating windows without hysteresis over extended cycling. But, the most important requirement is speed of access. To this end, energetic cost of phase transitions might affect operation of the phase change memory at the system level: for example, usage of large current for high energy transition step may impact on device durability. Ultimately, there is a fundamental limit on the number of reproducible phase transitions in a SPCM before fidelity of information storage is no longer guaranteed. Hence, what are the drivers for uptake of phase change memories in consumer devices? Performance gains must be realized in access speed, storage capacity, form factor, and fidelity of information storage for practical application of structural phase change memories.

The science‐policy interface in climate change adaptation became better managed over the past decades. However, the scientists and other knowledge producers, as well as policy makers still need to take bolder steps to more effectively engage with others to apply science and shape up policies. This paper aims to provide practical recommendations, intended to promote conversations between science and policy sectors to address climate change issues. Here, I used two different approaches to synthesize experiences and identify recommendations: a literature review and a case study. The paper stress main findings: (1) The linear communication model is still commonly involved in the science - policy dialogue and proved to be useful to increase the relevance of science and data products to decision makers. (2) When a gap between knowledge producer and knowledge user or decision maker exists, the need for a third party to specialize in bridging the gap become essential. (3) Indigenous people and knowledge must be involved in adaptation policy making based on legitimation local and traditional knowledge, designing the consultation process to broadly engage local and indigenous people, facilitating meaningful dialogues between traditional knowledge and science, and developing initiatives to strengthen skills and capacity of indigenous communities.

Abstract: A large number of collecting expeditions were launched in regions of ‘centers of diversity’ and hundreds of thousands of sample have been collected and stored in gene banks as ‘genetic resources’. So far, only a small number of the samples have been evaluated for their biotic and abiotic stress tolerance. Now, their time to become useful has come. A new global phenomenon has arisen – climate change. The crop genetic resources and their wild progenitors that have survived countless years of changing environment during the last 11,000 years could harbor genes that may be useful under the new growing conditions and environmental factors thrown up by climate change and global warming. With the deployment of modern bio-engineering techniques selected genes or gene fragments can be transferred from genetic resources to modern varieties of crop plants to make them well-prepared to mitigate the effects of global warming and climate change. The latter is the most serious issue facing plant breeders today. New pests and diseases could affect crop production. These review paper discusses various impacts and issues as a result of this phenomenon and suggest ways to safeguard our most important crops through better management of crop plant genetic resources in the near future.

The outcomes of the 2015 Paris Agreement triggered a number of climate impact assessments, such as for floods and droughts, to focus on future time frames corresponding to the years of reaching specific levels of global warming. Yet, the links between the timing of the warming levels and the corresponding greenhouse gas concentration pathways to reach them, remain poorly understood. To address this gap, we compare projected changes of annual mean, extreme high and extreme low river discharges in Europe at 1.5°C and 2°C under scenarios RCP8.5 and RCP4.5 from an ensemble of Regional Climate Model (RCM) simulations. The statistical significance of the difference between the two scenarios for both warming levels is then evaluated. Results show that in the majority of Europe (>95% of the surface area for the annual mean discharge, >98% for high and low extremes), the changes projected in the two pathways are statistically indistinguishable. These results suggest that in studies of changes at specific warming levels the projections of the two pathways can be merged into a single ensemble without major loss of information. With regard to the uncertainty of the unified ensemble, findings show that the projected changes of annual mean, extreme high and extreme low river discharge are statistically significant in large portions of Europe.

Daily rainfall data was collected for the arid district of Ananthapuramu, Andhra Pradesh state, India from 1981 to 2016 at the sub-district level and aggregated to monthly, annual and seasonal rainfall totals and the number of rainy days. The objective of this study is to evaluate the homogeneity, trend, and trend change points in the rainfall data. After quality checks and homogeneity analysis, a total of 27 rain gauge locations were considered for trend analysis. A serial correlation test was applied to all the time series to identify serially independent series. Non-Parametric Mann-Kendall test and Spearman’s rank correlation tests were applied to serially independent series. The magnitude of the trend was calculated using Sen’s slope method. For the data influenced by serial correlation, various modified versions of Mann-Kendall tests (Pre-Whitening, Trend Free Pre-Whitening, Bias Corrected Pre-Whitening and two variants of Variance Correction Approaches) were applied. A significant increasing summer rainfall trend is observed in 6 out of 27 stations. Significant decreasing trends are observed at two stations in the south-west monsoon season and at two stations in the north-east monsoon season. To identify the trend change-points in the time series, distribution-free Cumulative SUM test and sequential Mann-Kendall tests were applied. Two open-source library packages were developed in R language namely, ‘modifiedmk’ and ‘trendchange’ to implement the statistical tests mentioned in this paper. The study will benefit water resource management, drought mitigation, socio-economic development and sustainable agricultural planning in the region.

Artificial intelligence methods and application have recently shown great contribution in modeling and prediction of the hydrological processes, climate change, and earth systems. Among them, deep learning and machine learning methods mainly have reported being essential for achieving higher accuracy, robustness, efficiency, computation cost, and overall model performance. This paper presents the state of the art of machine learning and deep learning methods and applications in this realm and the current state, and future trends are discussed. The survey of the advances in machine learning and deep learning are presented through a novel classification of methods. The paper concludes that deep learning is still in the first stages of development, and the research is still progressing. On the other hand, machine learning methods are already established in the fields, and novel methods with higher performance are emerging through ensemble techniques and hybridization.

2-Hydroxypropyl-β-cyclodextrin (HPβCD) has unique properties to enhance the stability and the solubility of low water-soluble compounds by inclusion complexation. Understanding of the structural properties of HPβCD and its derivatives based on the number of 2-hydroxypropyl (HP) substituents at the a-D-glucopyranose subunits is rather important. In this work, replica exchange molecular dynamics simulations were performed to investigate the conformational changes of single- and double-sided HP-substitution called as 6-HPβCDs and 2,6-HPβCDs, respectively. The results show that glucose subunits in both 6-HPβCDs and 2,6-HPβCDs have lower chance to flip than in βCD. Also, HP groups are occasionally blocking the hydrophobic cavity of HPβCDs, thus hindering the drug inclusion. We found that HPβCDs with high number of HP-substitutions are more likely to be blocked, while HPβCDs with double-sided HP-substitution are even more probable to be blocked. Overall, 6-HPβCDs with three and four HP-substitutions are highlighted as the most suitable structures for guest encapsulation based on our conformational analyses such as structural distortion, radius of gyration, circularity and cavity self-closure of the HPβCDs.

We examine the mass balance of the glaciers in the Novaya Zemlya Archipelago, located in the Russian High Arctic using time series of time-variable gravity from the NASA/DLR Gravity Recovery and Climate Experiment (GRACE) mission, laser altimetry data from the NASA Ice Cloud and land Elevation Satellite (ICESat) mission, and radar altimetry data from the ESA CryoSat-2 mission. We present a new algorithm for detecting changes in glacier elevation from these satellite altimetry data and evaluate its performance in the case Novaya Zemlya by comparing the results with GRACE. We find that the mass loss of Novaya Zemlya increased from 10±5 Gt/yr over 2003-2009 to 14±4 Gt/yr over 2010-2016, with a brief period of near mass balance between 2009 and 2011. The results are consistent across the gravimetric and altimetric methods. Furthermore, the analysis of elevation change from CryoSat-2 indicates that 60\% of the mass loss occurs at low elevation, where thinning rates are highest. We also find that marine-terminating glaciers in Novaya Zemlya are thinning significantly faster than land-terminating glaciers, which indicates an important role of ice dynamics of marine-terminating glaciers. We posit that the glacier changes have been caused by changes in atmospheric and ocean temperatures. We find that the increase in mass loss after 2010 is associated with a warming in air temperatures, which increased the surface melt rates. There is no enough information on the ocean temperature at the front of the glaciers to conclude on the role of the ocean, but we posit that the temperature of subsurface ocean waters must have increased during the observation period.

In Europe we can see a change in the social structure in the last period. Average life expectancy has increased dramatically over the last 50 years. Because of the improved life situation and advanced level of health care, older people are slower. With advancing age, the likelihood of experiencing a variety of constraints such as visual impairment, reduced hearing or physical ability increases. In such a life stage tenants are often forced to leave their long-term living space because these homes can not serve "new" individual needs and the resulting personal protection goal. This transition from the privacy of their home to the new environment often appears to be a painful change. They will take their familiar and well-known surroundings, because their homes can not be adapted to serve new needs. It must be the policy’s role to create a new inclusive social space and the requirement for architects and designers to create new goals for the design of an adaptable environment. This is a comprehensive approach to the design of the outer and inner space that could serve people even if there is an unexpected situation and changes in movement and physiological limitations of older people. The contribution shows the results of the survey conducted in Germany and Slovakia. In the survey respondents expressed their opinion on what they considered important in creating an adaptive environment. Results are processed graphically with explanation. The results were mainly for designers and developers of the indoor environment. Based on the results of the questionnaire survey, studies of possible modifications in the interior of the flats were then prepared. The contribution yielded these results in three age groups of respondents; i. people aged 35, 50 and over 50.

Arctic feedbacks will accelerate climate change and could jeopardise mitigation efforts. The permafrost carbon feedback releases carbon to the atmosphere from thawing permafrost and the sea ice albedo feedback increases solar absorption in the Arctic Ocean. A constant positive albedo feedback and zero permafrost feedback have been used in nearly all climate policy studies to date, while observations and models show that the permafrost feedback is significant and that both feedbacks are nonlinear. Using novel dynamic emulators in the integrated assessment model PAGE-ICE, we investigate nonlinear interactions of the two feedbacks with the climate and economy under a range of climate scenarios consistent with the Paris Agreement. The permafrost feedback interacts with the land and ocean carbon uptake processes, and the albedo feedback evolves through a sequence of nonlinear transitions associated with the loss of Arctic sea ice in different months of the year. The US’s withdrawal from the current national pledges could increase the total discounted economic impact of the two Arctic feedbacks until 2300 by $25 trillion, reaching nearly $120 trillion, while meeting the 1.5 °C and 2 °C targets will reduce the impact by an order of magnitude.

Both climate change and anthropogenic activities contribute to the deterioration of terrestrial water resources and ecosystems worldwide. Central Asian endorheic basins are among the most affected regions through both climate and human impacts. Here, we used a digital elevation model, digitized bathymetry maps and Landsat images to estimate the areal water cover extent and volumetric storage changes in small terminal lakes in Burabay National Nature Park (BNNP), located in Northern Central Asia (CA), for the period of 1986 to 2016. Based on the analysis of long-term climatic data from meteorological stations, short-term hydrometeorological network observations, gridded climate datasets (CRU) and global atmospheric reanalysis (ERA Interim), we have evaluated the impacts of historical climatic conditions on the water balance of BNNP lake catchments. We also discuss the future based on regional climate model projections. We attribute the overall decline of BNNP lakes to long-term deficit of water balance with lake evaporation loss exceeding precipitation inputs. Direct anthropogenic water abstraction has a minor importance in water balance. However, the changes in watersheds caused by the expansion of human settlements and roads disrupting water drainage may play a more significant role in lake water storage decline. More precise water resources assessment at the local scale will be facilitated by further development of freely available higher spatial resolution remote sensing products. In addition, the results of this work can be used for the development of lake/reservoir evaporation models driven by remote sensing and atmospheric reanalysis data without the direct use of ground observations.

With the rapid development of satellite remote sensing technology, the volume of image datasets in many application areas is growing exponentially and the demand for Land-Cover and Land-Use change remote sensing data is growing rapidly. It is thus becoming hard to efficiently and intelligently retrieve the change information that users need from massive image databases. In this paper, content-based image retrieval is successfully applied to change detection and a content-based remote sensing image change information retrieval model is introduced. First, the construction of a new model framework for change information retrieval in a remote sensing database is described. Then, as the target content cannot be expressed by one kind of feature alone, a multiple-feature integrated retrieval model is proposed. Thirdly, an experimental prototype system that was set up to demonstrate the validity and practicability of the model is described. The proposed model is a new method of acquiring change detection information from remote sensing imagery and so can reduce the need for image pre-processing, deal with problems related toseasonal changes as well as other problems encountered in the field of change detection. Meanwhile, the new model has important implications for improving remote sensing image management and autonomous information retrieval.

This article explores the intersection of innovative leadership and climate change, aiming to provide outstanding contributions to the existing body of knowledge in this field. The article identifies the critical role of innovative leadership in driving sustainable solutions and strategies for addressing climate change. It examines the defining characteristics and behaviors of innovative leaders and explores how their transformative leadership approaches can create a positive impact on climate change mitigation and adaptation efforts. The article also highlights the importance of fostering innovation within organizations and societies to tackle the complex challenges posed by climate change. Through a comprehensive review of relevant literature and case studies, this article presents novel insights, theoretical frameworks, and practical implications for policymakers, organizations, and individuals involved in climate change leadership.

Aquaculture is expected to play a vital role in solving the challenge of sustainably providing the growing world population with healthy and nutritious food. Pathogen outbreaks are a major risk for the sector, so early detection and a timely response are crucial. This can be enabled by monitoring of pathogen levels in aquaculture facilities. This paper describes a photonic biosensing platform based on silicon nitride waveguide technology with integrated active components, which could be used for such applications. Compared to the state of the art, the current system presents improvements in terms of miniaturization of the Photonic Integrated Circuit (PIC), and the development of wafer level processes for hybrid integration of active components and for material-selective chemical and biological surface modification. Furthermore, scalable processes for integrating the PIC in a microfluidic cartridge have been developed, as well as a prototype desktop readout instrument. Three bacterial aquaculture pathogens (Aeromonas salmonicida, Vagococcus salmoninarum, and Yersinia ruckeri) were selected for assay development. DNA biomarkers were identified, corresponding primer-probe sets designed, and qPCR assays developed. The biomarker for Aeromonas was also detected using the hybrid PIC platform. This is the first successful demonstration of biosensing on the hybrid PIC platform.

In this paper, the problem of predicting future failure times based on a jointly type-II censored sample from k exponential populations is considered. The Bayesian prediction intervals and point predictors were then obtained. Generalized Bayes is a Bayesian study based on a learning-rate parameter. This study investigated the effects of the learning rate parameters on the prediction results. The loss functions of squared error, Linex, and general entropy were used as point predictors. Monte Carlo simulations were performed to show the effectiveness of the learning rate parameter in improving the results of prediction intervals and point predictors.

In our previous papers [1,3], using only the concepts of the zero-point energy and quantized space–times, all the fields including gravity were explained. However, the previous papers had the following limitations: First, the concept of the quantized space-time must be experimentally confirmed. Second, we should clarify the meaning of the quantized Einstein’s gravity equation, which is derived in [1]. Moreover, in another paper [2], we succeeded in describing the neutrinos’ self-energy and their oscillations. However, this paper assumes the rest energy of 3-leptons in advance, which is why we needed to uncover the reason why leptons have 3-generations. As mentioned, using the concepts of the zero-point energy and quantized space–times, we derived the quantized Einstein’s gravity equation in our previous paper [1]. The paper provides an analytical solution of this equalized Einstein’s equation, which implies the conservation of angular momentum in terms of quantized space–times. Employing this solution and without the standard big bang model, a unique form of acceleration equation for the acceleration-expansion universe is derived. Moreover, the temperature of the cosmic microwave background (CMB) emission is also obtained. Further, this solution results in an analytical (not numerical) derivation of the gravity wave. Moreover, based on the configuration of quantized space–times in terms of both electric and magnetic fields, we analytically attempted to calculate every equation in terms of electromagnetic and gravity fields, using the solution of the quantized Einstein’s gravity equation. As a result of this theory, first the calculated acceleration and temperature of CMB emission agree with the measurements. Furthermore, the analytical solution of the quantized Einstein’s gravity equation resulted in all the laws of electromagnetic and gravity fields in addition to the analytically derived gravity wave, which agrees well with the recent measurements. Moreover, the calculations of the energies in the basic configuration of the quantized space–times resulted in all 3-leptons’ rest energies. Considering this basic configuration is uniformly distributed everywhere in the universe, we can conclude that τ-particles or static magnetic field energy derived from the basic configuration of the quantized space–times is the identity of dark energy, which also distributes uniformly in the universe.

The climate change constitutes nowadays an enormous global threat for human health and environmental sustainability. The expanding world population and the increased global needs for food production have an important negative impact upon environment. Diet can link human health with environmental sustainability. Food production systems are closely related to anthropogenic greenhouse gas emissions and the aggravation of climate change, and current western type, animal-based, dietary patterns may lead to adverse environmental footprints. In the present narrative review, we address the interconnection of the Mediterranean diet (MD) with climate change and sustainability. MD is a highly recommended dietary intervention for the prevention and management of various endocrine and cardiometabolic diseases. Beyond its evidence-based, health-promoting effects, it also has beneficial environmental impact, reducing greenhouse gas emissions and enhancing biodiversity, food security and sustainability. Based on the evidence reviewed herein, MD should be incorporated within the framework of a “One Health” model, which involves the improvement not only of human health but also of planetary health and food system sustainability. Our review aims to provide a stimulus for health pro-fessionals to strongly recommend the implementation of MD under the current pressure of climate change, despite all barriers, targeting both human health preservation and the planetary well-being.

Background: Land use and land cover change (LULCC) in the Ruhuhu River Sub-Basin (RRSB), a crucial watershed within the Lake Nyasa Basin in Tanzania, poses a significant threat to water resource sustainability and ecological integrity. However, a lack of comprehensive data on long-term LULCC trends has hindered effective conservation efforts. Methods: This study utilized Landsat 5 TM and Landsat 8 OLI data within Google Earth Engine to quantify LULCC dynamics from 1990 to 2023. Six land cover classes were analyzed: water, forest, barren land, grassland, shrubland, and farmland. Results: Results revealed a substantial decline in forest cover (56.92% to 28.60%), primarily converted to farmland (2.99% to 20.22%). Shrubland expanded initially but then declined, while barren land steadily increased. These changes have profound implications for water resources, biodiversity, and ecosystem services within the RRSB and the broader Lake Nyasa Basin. Conclusions: This research highlights the urgency of implementing sustainable land management practices to mitigate the adverse impacts of LULCC in the RRSB. The high classification accuracies achieved (90.9% to 98.7%) validate the robustness of the methodology. This study provides crucial insights for policymakers, land managers, and conservation practitioners, emphasizing the need for targeted interventions to promote sustainable land use and ensure the long-term resilience of the RRSB ecosystem.

Globally, habitat fragmentation has increased the proximity between wildlife, humans, and emerging predators such as free-ranging dogs. In these fragmented landscapes, encounters between primates and dogs are escalating, with primates often falling victim to dog attacks while navigating patchy landscapes and fragmented forests. We aim to investigate how these primates deal with the simultaneous threats posed by humans and predators, specifically focusing on the adaptive strategies of Central Himalayan Langur (CHL) in the landscape of fear. To address this, we conducted a behavioral study on the CHL in an agro-forest landscape, studying them for a total of 3912 hours over two consecutive years. Our results indicate that, compared to their most common resting behavior, CHL allocate more time to feeding and locomotion, and less time to socializing in the presence of humans and predatory dogs. Additionally, they exhibit increased feeding and locomotion and reduced social behavior in agro-forest or open habitats. These behavioral patterns reflect adaptive responses to the landscape of fear, where the presence of predators significantly influences their behavior and resource utilization. This study suggests measures to promote coexistence between humans and wildlife through the integration of effective management strategies that incorporate both ecological and social dimensions of human-wildlife interactions.

Indigenous traditional land uses, including hunting, fishing, sacred activies and land-based education at Red Sucker Lake First Nation (RSLFN) in Manitoba, Canada are impacted by mining. Traditional land use maps and interviews were undertaken with 21 Indigenous people from RSLFN, showing many traditional land uses are concentrated on greenstone belts. The interviews revealed that mining exploration has resulted in large petroleum spills, noise distress, personal property destruction, wildlife die-offs and animal population declines, which negatively impact RSLFN’s traditional land use practices, ecosystem integrity, and community health. Red Sucker Lake First Nation (RSLFN) people want their territories’ land and water protected for traditional uses, culture and ecological integrity. Towards this goal, their Island Lake Tribal Council sought support for an Indigenous-protected and conserved area (IPCA) in their territory outside of existing mining claims, but without success. Governments need to partner with Indigenous nations to reach their biodiversity targets, particularly considering northern Canada’s peatlands, including those in Island Lake, surpassing the Amazon forests for carbon storage. Critical minerals and gold’s role in renewable energy and geopolitics have colonial governments undermining Indigenous rights, climate stabilization and biodiversity. With extractivism prioritized, the environmental impacts of mining extend to not only the mines but also the extensive development required to facilitate extraction including roads, hydro and ports to ship the minerals with proposals for a national Northern Corridor to run nearby.

In the decarbonization of the steel, cement, and chemical industry in Germany, green hydrogen is expected to play a crucial role. The utilization of green hydrogen in the production processes of said industries requires organizations to modify their business model, requiring sustainable business model innovation (SBMI). Numerous tools and frameworks that support organizations in the process of SBMI have been proposed in the literature in recent years. However, the applicability of these tools and frameworks for steel, cement, and chemical companies that intend to utilize green hydrogen to produce their goods remains unexplored. By conducting a systematic literature review on tools and frameworks for SBMI, a literature and practice review to identify and analyze existing green hydrogen projects of steel, cement, and chemical companies, and an evaluation of the identified tools and frameworks in an evaluation matrix, this paper aims to assess the suitability of SBMI tools and frameworks for steel, cement, and chemical companies that plan to use green hydrogen to produce their goods. Based on the evaluation, the Cambridge Business Model Innovation Process (CBMIP) was identified as the most suitable SBMI framework.

Recent satellite measurements of glacier mass balance show mountain glaciers all over the world had generally negative mass balances in the first decades of the 21st century. Mean summer temperatures all over the world rose from 1961-90 to 1991-2020, implying increasingly negative mass balances. We study archived annual balances for 38 Northern Hemisphere glaciers to assess changes within in the 19612020 period. We use a modified doublemass curve to visualize mass balance changes occurring around 1990. Mean balances 196190 were already small negative for many of the studied glaciers and became even more negative in 19912020 for glaciers in the Alps, at high latitudes and in western North America. The largest mass balance changes are for some glaciers in the Alps. We are unable to explain the lack of change in mean balance for one glacier in High Mountain Asia. We find complex changes for eight glaciers in Scandinavia, even including one glacier with positive balance. We explain these changes by visualizing deviations of winter and summer balances from their respective 1961-90 mean values. High winter balances in the 1990s for Scandinavia partly obscured the emerging trend of increasingly negative summer balances, which we expect to continue in the future.

Variability is the predisposition of phenomena to assume different values over time. Variability is higher when the differences of cases from each other are larger or diverge from a specific value, such as arithmetic mean. This study focuses on the variability of research topics within and between research fields to explain, whenever possible, how the variability shapes the structure and dynamics of technological trajectories. Analysis of variability here applies the entropy and variance decomposition on main research fields in quantum technologies. Empirical evidence shows that variability in research topics is inversely proportional to the age of research fields. Inductive implications are that higher variability in research topics of recent scientific fields is due to uncertain dynamics that generates a heterogeneity of different technological trajectories some of them can growth and develop towards fruitful directions others can be dismissed. Hence the variability seems to be one of the drivers that shapes technological evolution and can provide policy and managerial implications to improve the scientific and technological forecasting that may support appropriate decisions of R&D investments towards promising research fields and technologies.

An existing simplified simulation model of global climate, population, economy, and governance is extended, through statistical and other data analysis, to include several measures of human well-being and population displacement. The revised model is used to explore (in testing to the year 2060) vicious cycles and causal cascades that, some have warned, could lead to acceleration of climate change in the coming decades. Model scenario testing addresses two uncertainties, namely the strength of the effect of climate change on governance erosion, and the strength of the “heat trap” effect from physical tipping points such as ice loss and permafrost thaw. This testing indicates that a strong heat trap effect could very well accelerate climate change, but that even a strong governance erosion effect is unlikely to do so. Governance erosion would hurt human well-being but is probably not much of a climate threat per se. These results are tentative but point to the possibility of formally modeling causal cascades beyond what the larger climate models have done to date.

Prospecting for a future breeding site is an essential component of informed dispersal. It allows individuals to reduce the uncertainty of their environment by gathering personal and social information about the local quality of alternative breeding areas, and to make informed emigration and settlement decisions. Although this process has been studied in territorial and social animal species for decades, it is still not well-understood and spatial patterns of prospecting movements are hard to generalize over taxa or even species due to substantial intra and inter-specific variability. Using 124 empirical studies which have explicitly described prospecting in a context of breeding habitat selection in birds, mammals, fish and invertebrates, I review why, how, when and which individuals prospect depending on their life history traits and sociality. From this synthesis, I identify persisting knowledge gaps which explain why prospecting is still understudied and sometimes overlooked. I finally propose key objectives and research directions, to shed light on prospecting movements and their consequences on informed dispersal strategies, individual fitness and population dynamics, both empirically and theoretically. A better understanding of the mechanisms underlying prospecting, their causes and their consequences will fully reveal how prospecting could constitute a powerful adaptive response to environmental changes for many social and territorial species which will help them persist on the long-term. It will also significantly enhance our ability to predict species responses to environmental changes and thus, inform more effective management plans for threatened species

In this study, an analysis was conducted on 16 durum wheat genotypes cultivated under seven different crop management systems. The purpose was to investigate the influence of Genotype (G), Environment (E), and Genotype by Environment interactions (GxE) on the content of total free phenolic compounds (TPC) and the antioxidant capacity (AC) of durum wheat in Mediterranean environments and identify their adaptability in climatic change. Additionally, possible correlations between TPC and AC with protein content (PC), and vitreous-kernel percentage (VKP) of the samples were examined. The results indicated significant impacts from E, G, and GxE on both TPC and AC. Among the E, the mean values for TPC, ABTS, DPPH, and FRAP values were recorded at 48.8 mg TE/100 g dw, 121.3 mg TE/100 g dw, 23.0 mg TE/100 g dw, and 88.4 mg TE/100 g dw, respectively. Environments subjected to splitting topdressing N fertilization consistently showed low values, while the late sowing ones possessed high values. The Organic environment maintained a stable position in the middle across all measurements. The predominant influence was attributed to GxE, as indicated by the order GxE >E>G for ABTS, DPPH, and FRAP while for TPC was E>GxE>G. A comprehensive exploration of GxE interaction holds the potential to improve the total free phenolics content and antioxidant capacity of durum wheat within wheat farming systems. Achieving this enhancement involves the meticulous selection of cultivars that not only display high values but also exhibit stability across diverse conditions. Noteworthy genotypes for TPC include G5, G7 and G10, for ABTS include G3, G5 and G7, and for protein include G1, G9, and G16. G7 and G5 had high presence of frequency with G7 being the closest genotype to the ideal for both TPC and ABTS. These results suggest that the cultivation period as well as the nitrogen fertilization and its application method have a significant impact on the various antioxidant properties of durum wheat. This study holds significant importance as it represents the first comprehensive exploration of the impact of various E on the TPC and AC in durum wheat, with a special emphasis on the crop management. Notably, the significance of several statistical tools is also highlighted, such as the GGE biplot, Pi, and KR, in identifying superior genotypes, with the GGE biplot being highly valuable since it offers a visual representation of the study's outcomes.

Identification of Dengue drivers is crucial for pro-active prevention strategies. In semi-arid regions, the relationship between meteorological variables, particularly rainfall, and the dengue vector is complex. This study analyzes associations between the number of dengue cases and rainfall categories in six semi-arid locations in India. Focusing on official website data, we find significant correlations only with heavy rainfall (R>10 mm/day). The findings underscore the importance of heavy rainfall in Dengue incidence and offer insights for pro-active prevention. The study methodology involves rainfall and dengue occurrence over Indian region. This research contributes to the growing body of knowledge on Dengue prevention, emphasizing the need for targeted interventions during periods of heavy rainfall.

In recent years, the Canadian dairy sector has faced escalating challenges due to its significant contribution to greenhouse gas emissions, particularly methane. This paper critically examines a spectrum of innovative techniques aimed at mitigating methane emissions within this sector, scrutinizing their cost-effectiveness, efficiency, compatibility with animal welfare standards, and adherence to both existing and prospective Canadian environmental legislations. The discourse commences with an exhaustive overview of contemporary methane reduction methodologies pertinent to dairy farming, followed by a rigorous analysis of their economic feasibility. This includes a detailed cost-benefit analysis, juxtaposed with the efficiency and technological advancements these techniques embody. A pivotal aspect of this examination is the alignment of animal welfare with emission reduction objectives, ensuring that strategies employed do not compromise the health and well-being of dairy cattle. Furthermore, the paper delves into the legislative landscape of Canada, evaluating the congruence of these techniques with current environmental laws and anticipating future regulatory shifts. Performance indicators for emission reduction are critically assessed, establishing benchmarks tailored to the Canadian context. This is complemented by an exploration of the market potential of these innovations, including factors influencing their adoption and scalability in the market. The analysis culminates with a synthesis of case studies and best practices within Canada, offering insights into successful implementations and drawing lessons for future endeavors. This comprehensive approach serves not only to address the immediate environmental and health impacts associated with dairy farming emissions but also contributes significantly to the overarching goal of sustainable development in the agricultural sector.

Small-scale fisheries are significant sources of nutrition and livelihood globally. However, increasing anthropogenic activities in coastal areas of developing countries have threatened the sustainability of artisanal fisheries and species. Fisheries of Sardinella maderensis (Lowe, 1838), to which Nigeria contributes 9% of the global stock and is a significant livelihood source in the coastal communities of Ibeju-Lekki, Lagos, face sustainability threats. This research investigated the effects of anthropogenic activities on S. maderensis fishery in the coastal areas of Ibeju-Lekki, Lagos, Nigeria. The study adopted a mixed-method approach involving qualitative and quantitative research methods. These include species identification, water quality analysis, land use change analysis, field surveys, focus group discussions and interviews. Results show genetic analysis of the fish samples from six stations revealed that the species had a mean of 98% similarity to Sardinella maderensis in NCBI. Multiple linear regression indicates that anthropogenic variables explained approximately 4.62% of the variance in the fish catch (p < .001, R2 = .05). Water samples showed heavy metal levels were above international limits, high total petroleum hydrocarbon (TPH) pollution in all stations (27.56 mg/L- 3985.40 mg/L). Physiochemical analysis of water samples indicated TDS higher than acceptable limits (Mean = 24971.1 mg/L) and inadequate chlorophyll-a level (Mean = 0.01 µg/L). Hence, urgent strategies are required to mitigate anthropogenic threats through inclusive coastal management policies supporting resilient artisanal fisheries and marine spatial planning.

This article aims at investigating the complex relationship between the local population and its natural and urban environment. The study of area which, is previously dominated by cereal cultivation, facing profitability challenges due to climate change, water scarcity Rapid urban expansion and overexploitation of aquifers, influenced by changes in agricultural practices, are disrupting the local ecosystem. The study relies on three interconnected indicators: population growth, climate change effects on agriculture, and the NDVI (Normalized Difference Vegetation Index) reveal the impact of these factors on agricultural practices. Google Earth Engine was employed to determine urbanization and greenness indices using scripts. Key findings include a shift towards intensive and protected agriculture, driven by individual and collective choices of official and unofficial actors, deviating from government directives. Additionally, the study highlights the unsustainability of this new agricultural direction, as the available water re-sources cannot meet the demands, potentially leading to recurrent agricultural shortages. The study underscores the importance of incorporating agricultural production into future urban planning and development programs to maintain a renewed balance between built environ-ments and agriculture on the outskirts of cities.

We propose a silviculture with a purely biological logic that takes soil into account. The article is divided into three parts: 1) presentation of the issue in the context of biodiversity and forest pro-tection; 2) impact of the soil functioning on forestry; 3) possible implementation of soil functioning in forestry practice, to support and protect a non-or minimally anthropized evolution of the forest. The first chapter illustrates the importance of the forest for the future of the planet and our human species, referring to recently published works on the topic of climate warming and biodiversity. The second illustrates the aspects that link soil dynamics to the silvogenetic cycle, focusing on the humipedon (organic and organo-mineral surface horizons, approximately the first 30 cm of forest soil), and more significant carbon storage in old forests since up to 2/3 is found in the soil. In the third chapter we consider the possibility of lengthening the forestry cycle, to allow the return of nutrients to the soil. Theoretical graphs and distribution models of the number of trees as a func-tion of diameter and age are reported, with examples of logging in uneven Alpine forests, with reference to Swiss fir-beech forests published on the Pro-Silva website.

Study design: Retrospective observational study. Objectives: To evaluate the change in adjacent segment disease (ASD) after hybrid dynamic stabilization with Dynesys-Transition-Optima (DTO). Methods: In 2012–2020, 115 lumbar spinal stenosis patients with spondylolisthesis re-fractory to nonsurgical management received hybrid dynamic stabilization with DTO system in a single medical center from a single neurosurgeon. After excluding those who did not receive L3–L4 dynamic stabilization and L4–L5 transforaminal lumbar interbody fusion fixation and those with incomplete postoperative data (n = 84), the 31 patients studied received follow-up vis-its at 6, 12 and 24 months postoperatively. Radiological assessment applied at the L2–L3, L3–L4 and L5–S1 segments separately included disc height, listhesis distance and angular change while in motion. Implant failure and screw loosening sign were both documented. Results: In the L3–L4 segment, the listhesis distance appeared 1 year after the operation; however, alterations in other segments showed at 6 months. At 2 years, the L3–L4 segment showed significantly less increase in listhesis distance and relatively less disc height reduction than other segments. In motion an-gular change, only the L3–L4 segment had a significant decrease at 2 years. Only the L3–L4 seg-ment maintained negative growth over 2 years in time-dependent assessment of motion angular change. Conclusions: In our study, disc height decreased, listhesis distance increased less and ASD changed later at the index level than the L2–L3 and L5–S1 levels. Angular change was re-duced at the index level while in motion. Although ASD was not significantly prevented, index level degeneration was both minor

This academic paper explores the synergistic potential of Agroforestry systems and Climate-Smart Agriculture (CSA) in enhancing climate change adaptation strategies. Focusing on Australia and Pacific Island Countries, the study delves into the pivotal role of these approaches in mitigating the impacts of changing climate variables on agricultural production. By analysing important climate variables, their potential alterations, and their subsequent effects on crop production, the paper advocates for a holistic and forward-thinking approach to sustainable agriculture in the face of climate change.

This paper an approach for analyzing the impact of sea level changes on prehistoric human settlement patterns in the Southwestern Iberian Peninsula. The approach is based on highly qualified and fully georeferenced information sources managed within a spatial database. This allows for a more precise analysis of the distance to the coast and its relation to marine resources from a specific location, areas that may have lost their archaeological potential due to being currently submerged, and the actual distribution of sites as a starting point for territorial analysis. Coastal changes, such as sea level fluctuations over the past 120,000 years, have affected the position of the coastline and influenced human settlement patterns. Through an analysis of the archaeological site locations relative to their paleo-coastlines based on available dating data, this study emphasizes the necessity of adopting a comprehensive approach to comprehend human settlement patterns and their correlation with the dynamic coastal changes. This approach provides valuable insights for formulating strategies for exploiting coastal resources and structuring socio-economic systems in the region.

The assessment and prediction of drought risk under future climate change and land use land cover (LULC) scenarios is critically important for drought prevention and mitigation, as it enables a clearer understanding of potential shifts in drought patterns. The primary aim of this study is to evaluate sub-seasonal and seasonal meteorological and hydrological drought hazards across the Yellow River Basin (YRB) under projected future climate conditions and LULC patterns. The BCC-CSM1-1 climate model projections from the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset are utilized to represent future climate for 2025-2060 under RCP 4.5 and 8.5 scenarios. The CA-Markov model is employed to predict future LULC distributions. Meteorological and hydrological drought risks across different YRB zones are evaluated through a copula-based risk assessment approach, based on the joint probability distribution of drought duration and severity. The results indicate that sub-seasonal meteorological and hydrological droughts will likely be the primary concern moving forward. Specifically, the upper YRB (zones A, B, C) exhibits greater vulnerability to sub-seasonal meteorological drought, while the Loess Plateau (zones C, E) shows higher susceptibility to sub-seasonal hydrological drought. Moreover, zone F in the downstream region may experience increased seasonal hydrological drought risk due to projected urban expansion in the middle and lower portions of the YRB.

Plant-based extracts have been recently employed as sustainable tools to improve biotic and abiotic stress tolerance and increase grape quality. However, knowledge about the effect of these extracts on secondary metabolism compounds, that are fundamental for grape and wine quality, is still scarce. In this study, a trial was installed in an experimental vineyard with the variety Touriga Franca located at University of Trás-os-Montes e Alto Douro, Baixo Corgo sub-region of the Douro Demarcated Region, in two growing seasons: 2019 and 2020. Foliar sprayings with the natural products, nettle extract (NE) and Japanese knotweed extract (JKE), were tested to evaluate their effect on downy mildew incidence and severity, on grapevines bioactive compounds contents and antioxidant activity, at veraison and harvest. NE and JKE have stimulated an improvement in the concentration of total carotenoids in leaves and the concentration of total phenolics in berries along with an improved concentration of total phenolics and flavonoids in leaves and berries. Thus, it was verified that these extracts enhance grapevines bioactive compounds and antioxidant capacity and, consequently, the physiological performance of the plant and the quality of the berries. Considering the challenges posed by climate change in the Mediterranean basin viticulture sector, the use of plant extracts might represent a sustainable tool to mitigate the increasing severity of drought, often associated to heatwaves and high irradiation. Moreover, downy mildew incidence results suggest that an integrated disease management approach combining conventional control with alternative fungicides can be used in the future for a more sustainable viticulture.

Detecting the trends of species and populations is fundamental to identify taxa with high conservation priority. Unfortunately, long-term monitoring programs are challenging and often lacking. The Italian agile frog Rana latastei is endemic to Northern Italy and adjacent countries, is considered vulnerable by the IUCN, and is protected at the European level. However, quantitative estimates of its decline are extremely scarce. In this study, we document the trends in abundance and distribution of Rana latastei within the Monza Park, which currently represents the area closer to the type locality of the species. Wetlands within the park were monitored from 2000 to 2023; counts of egg clutches were taken as a measure of reproductive output and of the abundance of breeding females. In 2000, the species occurred over a significant proportion of the park. Total abundance showed strong yearly variation but remained rather constant from 2000 to 2019. However, Rana latastei disappeared from the park around 2021 and was never detected in 2022-23. The decline is probably related to the joint effect of multiple factors, including the conversion of breeding sites for farming, inappropriate water management, invasive alien species, and severe drought. The local extinction of Rana latastei occurred despite legal protection, highlighting the need for more effective and stringent tools for the conservation of European biodiversity.

When attempting to quantify future harms caused by carbon emissions and to set appropriate energy policies, it has been argued that the most important metric is the number of human deaths caused by climate change. Several studies have attempted to overcome the uncertainties associated with such forecasting. In this article, approaches to estimating future human deaths tolls from climate change are compared and synthesized, and implications for energy policy are considered. Several studies are consistent with the “1000-ton rule,” according to which a future person is killed every time 1000 tons of fossil carbon are burned (order-of-magnitude estimate). If warming reaches or exceeds 2°C this century, mainly richer humans will be responsible for killing roughly 1 billion mainly poorer humans through anthropogenic global warming. Such mass manslaughter is clearly unacceptable. On this basis, relatively aggressive energy policies are summarized that would enable immediate and substantive decreases to carbon emissions. The limitations to such calculations are outlined and future work is recommended to accelerate the decarbonization of the global economy while minimizing the number of sacrificed human lives.

In the future, the pursuit of high-quality economic development and a focus on ecological environmental protection in China will inevitably result in significant conflicts between land use and ecological land use. The challenge lies in achieving sustainable high-quality development while simultaneously protecting the ecological environment, optimizing the land use structure, and promoting a harmonious relationship between humans and the land. These challenges are faced by all regions. Land use conflicts primarily occur in peri-urban areas characterized by prominent economic development and urban agglomeration. Previous studies have mainly focused on analyzing the effects of land use on habitat quality during intense urbanization. However, it is important to recognize that land pressure encompasses economic, ecological, and social aspects. To gain a comprehensive understanding of the spatial conflict of land use and the impact on habitat quality in Ankang, a city that has been advocating ecological protection for the past two decades, this study aims to objectively analyze the spatial trends in land use changes in such cities. Additionally, it aims to provide insights for the harmonious development of land use in eco-region-oriented cities. Using the SSP-RCP scenarios provided by CMIP6, this paper employs a system analysis method, PLUS model, InVEST model, and land use conflict measurement model to dynamically simulate the future habitat quality and spatial conflict patterns of land use in Ankang City. The study explores the spatial coupling effect of both factors under different scenarios. The results indicate the following:(1) Under different future shared socio-economic path scenarios, land use intensity and land conflict levels follow the order of SSP585 (high forcing scenario), SSP370 (medium to high forcing scenario), SSP245 (medium forcing scenario), and SSP126 (low forcing scenario), with intensity and conflict decreasing accordingly. (2) The overall development trend in Ankang City reveals an intensification of land use conflicts and a decrease in habitat quality. The expansion rate of construction land is increasing and exhibiting aggregation, while agricultural land area is expanding and forest land area is continuously decreasing. (3) Land use intensity exhibits a significant positive correlation with land conflict levels, while land conflict levels demonstrate a significant negative correlation with habitat quality. These findings suggest that land use has had some impact on the ecological environment, with indications of habitat degradation. Even in Ankang, where ecological development is highly valued, the city will gradually face conflicts between ecological protection and economic development in future scenarios. The study highlights that Ankang's future development space will be constrained within the context of environmental protection, leading to greater land use conflicts in urban and surrounding areas. Consequently, the quality of habitats will inevitably decline. Therefore, it is crucial to allocate sufficient space for economic development while simultaneously prioritizing ecological protection. This approach will ensure a healthy economic development trajectory and foster a harmonious relationship between humans and the land.

40 years of cloud observations are available globally from satellites allowing derivation of climate data records (CDRs) for climate change studies. The aim of this study is to investigate how stable these cloud CDRs are and whether they qualify stability requirements recommended by the WMO’s Global Climate Observing System (GCOS). We also investigate robust trends in global total cloud amount (CA) and cloud top temperature (CTT) that are significant and common across all CDRs. The latest versions of four global cloud CDRs, namely CLARA-A3, ESA Cloud CCI, PATMOS-x and ISCCP-HGM, are analysed. This assessment finds that all three AVHRR based cloud CDRs satisfy even the strictest GCOS stability requirements for CA and CTT when averaged globally. While CLARA-A3 is most stable in global averages, PATMOS-x offers the most stable CDR spatially. While we find these results highly encouraging, there however remain large spatial differences in the stability of and across the CDRs. All four CDRs continue to agree on the statistically significant decrease in global cloud amount over the last four decades, although this decrease is now weaker compared to the previous assessments. This decreasing trend is stabilizing or even reversing in the last two decades; the latter is seen also in MODIS-Aqua and CALIPSO GEWEX datasets. Statistically significant trends in CTT are observed in global averages in the AVHRR-based CDRs, but the spatial agreement in the sign and the magnitude of the trends is weaker compared to those in CA. We also present maps of Common Stability Coverage and Common Trend Coverage that could provide a valuable metric to carry out an ensemble-based analysis of the CDRs.

In recent years, the need to make the built environment more resilient and adaptable to climate change has become increasingly evident. In Europe, this aspect concerns the vast majority of existing buildings, which present several deficiencies from the energy-efficiency point of view, considering they were designed before the introduction of modern energy codes. Nowadays, it is possible to retrofit existing buildings using advanced and high-efficient technologies such as Double Skin Façades (DSFs). The research aims to evaluate the use of properly designed DSFs for the energy restoration of existing buildings. In detail, various DSF configurations are applied to a residential building located in central Italy and investigated under present and future climate conditions, estimated through regional climate models. The results underline that all the analysed Double Skin Façades confirm to be a useful option, and, in particular, the Multi-Storey typology allows drastic energy needs decrement. Moreover, the general increase in temperatures and solar radiations could affect the building energy performance, and the insertion of DSF can mitigate the climate change effects, reducing the predicted energy consumption and ensuring better behaviours than the building in its original state.

Promoting diet and physical activity is important for women with recent gestational diabetes mellitus (GDM) and their partners to reduce the risk of future type 2 diabetes (T2D). The study aimed to understand how motivation for changing diet and physical activity behaviors among women with recent GDM and their partners was experienced after participation in the Danish Face-it intervention. Fourteen couple interviews were conducted. Data analysis followed reflexive thematic analysis. Guided by self-determination theory and interdependence theory, we identified four themes affecting couples’ motivation for health behavior change: 1) The need for relatedness after delivery, 2) Promoting competence and autonomy for health behavior change, 3) Individual and mutual preferences for health behaviors, and 4) The health threat of future T2D as a cue to action. We found that the couples in general perceived the Face-it intervention as useful and motivating. Using couple interviews increased our understanding of how the women and partners influenced each other’s perspectives after a GDM-affected pregnancy and thus how targeting couples as opposed to women alone may motivate health behavior change.

Abstract: This paper summarises an early and successful piece of citizen science, performed within The University of Queensland Seismograph Stations (UQSS) observatory, in cooperation with colleagues at CSIRO. It was designed to en-courage young STEM students from Brisbane high schools to engage in “real” re-search, back in 1995. Having completed the project report, their (analog) results sat in a cupboard until the report was dusted off and the project was re-analysed in 2022 by an honors student, considering timely climate change applications for the study. This is a time when science is changing considerably from analog to digital medium and operational methods. The original project was called Earthquake generated T phases on BRS Seismograph (Brisbane, Q’ld)- a predictor for Tasman Sea Tsunamis? [1] Fortunately, seismology is a very collaborative field. The research question has since changed. There is a lot of data analysis involved in the science of recording earthquake signals, with auxiliary definitive catalogues, observers logbooks, housing of the recordings themselves (analog and digital) and the software mediums that change over time. In other words, a lot of headaches can be encountered in longitudinal data collection study such as this. The citizen science students used a pre-prepared decadal collection (1980-90) derived from the BRS observatory data catalogue. BRS is part of the global World-Wide Seismograph Station Network (WWSSN). Currently in Australia, university earth science observatories have diminished, and in their place, public seismic networks (PSN) have evolved, either in back-yard sheds or school science labs. The level of expertise required fits the role of advancing citizen science for a real science advantage. This is a topical citizen disaster preparedness action area for today’s climate emergency, which is threatening the globe and all lifeforms. Citizen engagement or mobilisation is an essential preparedness strategy. Keywords: citizen science 1; seismology 2; earth observation 3; climate change 4; education for sustainable development 5; disaster preparedness 6; disaster alerts 7

The 2030 global agenda of the United Nations emphasizes peace, human rights, gender equality, partnership, and women's empowerment. It balances the social, economic, and environmental dimensions of sustainable development. The SDG framework was designed to be integrated and indivisible, making the interconnections of 17 Goals and 169 Sustainable Development Goals Targets (SDTs) more complex that need extensive and intensive investigative research. Recent studies have increased on the interrelationships of SDGs, but none of these have focused on integrating Climate Change (CC), Sustainable Forest Management (SFM), and Information and Communication Technology (ICT), also known as CSI Nexus. This study aims to investigate and identify the 169 SDTs linked to CC, SFM, and ICT and assesses the significance of the relationships between these variables. The alignment of SDTs to CSI Nexus was identified through clustering and mapping techniques. The result argued that 56 SDTs are directly connected within CC+SFM+ICT, 16 within CC+SFM, one within SFM+ICT, and 51 within ICT+CC. Our result suggests that CC is significantly associated with SFM; however, ICT has no significant association with CC and SFM. It further asserts that the ICT and SFM have minimal influence on the SDG 2030 framework. The proposed CSI Nexus and SDTs Integration Framework was a science-informed guide for priority-setting, policy coherence, and decision-making supporting the 2030 Sustainable Development Goals. This study does not include interactions, network analysis and visualization, simulations, and modeling between SDG targets.

To remain relevant in the green transition, companies are beginning to voluntarily account for the exchange of emissions in their supply chain transactions and using the resulting greenhouse gas inventories for climate resilient decision support. Market advantages of sustainability and transparency see a shift from internal decision support tools to external communication tools which potentially expose companies to the risk of uncovering greenwashing if claims are not supported by transparent data, sound modelling, and a climate just emissions inventory, which considers external impacts connected to the production system. The different methods and standards in place for such greenhouse gas inventories, despite all referring to the ISO life cycle analysis standards and guidelines, present mixed signals and leave room for different interpretations, that may ultimately lead to cascading greenwashing, misleading results, and false successes. The new GHG Protocol Land Sector and Removals Guidance draft addresses this in part. With the GHG Protocol moving into revision periods, we identify gaps that present barriers to companies, or allow for interpretations that goes against the intentions of reporting GHG emissions related to an activity or organisation. The literature agrees that not rectifying these subtle-ties present counterproductive decision support for the green transition’s overall goal: to reduce global emissions.

The emerging concept of planetary health needs to be discussed in a more organized and sustainable way within the global public health and healthcare disciplines. Therefore, planetary health should be considered a cardinal component of the global academic framework for healthcare professionals. The availability of related curricula and courses is crucial to equip health professionals in this relatively new discipline of planetary health. In this review article, we aimed to explore published articles and online databases of courses to summarize the available planetary health education opportunities and discussions for health professionals, to identify the gaps in resource allocation and to suggest future recommendations. We observed a visible re-source inequity in global south with the lack of a universal planetary health module for healthcare professionals. Additionally, there is minimal inclusion of allied health disciplines in this learning process. We, therefore, recommend a dedicated network of motivated healthcare professionals and regional hubs with an agenda to ensure a comprehensive, uniform, and inclusive planetary health education curriculum and practice.

Lettuce is a salt-sensitive crop and has a threshold electrical conductivity of 1.3–2.0 mS cm-1 and above that is considered detrimental. As there has been very little information on the physio-logical response of different critical stages of lettuce under different salt stress (SS), the current study is focused on investigating the effects of SS on the critical physiological traits influencing the carbon assimilation in different growth stages of lettuce. The experiment was conducted in deep-water culture hydroponic system in a greenhouse condition. Four levels of sodium chloride salt treatments (EC: 20, 16, 8, and 1.8 mS cm-1) were applied. During both growth stages (day 11 (GS1) and day 19 (GS2) after salt treatment), the leaf transpiration rate, stomatal conductance, and intercellular CO2 were severely decreased. However, the carbon assimilation rate remained unchanged under SS. Similarly, the water use efficiency increased under the SS. It is concluded that the increasing SS increased stomatal and non-stomatal limiting factors during GS1 suggesting the enhanced limitation in photosynthetic activity while no such trend was observed during GS2. The decreased gm with increased SS at GS1 and GS2 suggested that SS induced the irreversible decrease of gm, which in turn can be responsible for the transient reduction in the Vcmax and Jmax during GS2. Taken together, the evidence from this research recommends that varying the SS levels can significantly affect the physiological performance of lettuce at both growth stages.

Whereas many carbon cycle models track CO₂ perturbations relative to a pre-industrial equilibrium, this paper uses absolute quantities to describe atmospheric CO₂ sinks, source and flow rates. This method, when combined with the notion of source and sink resistance, and a finite biospheric reservoir, accurately describes ¹⁴C levels between 1820 and 2020 using only five external parameters. The inputs are:- global records of fossil-fuel emissions, records of CO₂ mixing-ratio and listings of atmospheric atomic weapons tests. Over the same period ¹³C flows are also accurately described given a ð¹³C value for fossil fuel and a ð¹³C value for the initial background. This top-down approach differs from complex climate models since it circumvents the necessity to catalogue individual processes. The paper proceeds to use the method to examine the anthropogenic fossil-fuel emissions contributions during the period 1750 to 2020, deducing that around 24% remains in the atmosphere, while 76% has been absorbed in the land, terrestrial biosphere and surface ocean. During the same period 13% of the total CO₂ atmospheric concentration is due to fossil fuels. However, regarding the increase, fossil fuels contributed to 38% of the rise during this period.

The changing of land use and land cover (LULC) are both affected by climate and human activity and affect climate, biological diversity, and human well-being. Accurate and timely information about the LULC pattern and change is crucial for land management decision-making, ecosystem monitoring, and urban planning, especially in developing economies undergoing industrialization, urbanization, and globalization. Biodiversity degradation and urban expansion in eastern China are research hot-spots. However, the influence of LULC changes on the region remains largely unexplored. Here, an object-based and multi-temporal image analysis approach was developed to detect how LULC changes during 1985-2015 in the Tiaoxi watershed (Zhejiang province, eastern China) using Landsat TM and OLI data. The main objective of this study is to improve the accuracy of unsupervised change detection from object-based and multi-temporal images. To this end, a total of seven LULC maps are generated with multi-temporal images. A random stratified sample design was used for assessing change detection accuracy. The proposed method achieved an overall accuracy of 91.86%, 92.14%, 92.00%, and 93.86% for 2000, 2005, 2010, and 2015, respectively. Nevertheless, the proposed method, in conjunction with object-oriented and multi-temporal satellite images, offers a robust and flexible approach to LULC changes mapping that helps with emergency response and government management. Urbanization and agriculture efficiency are the main reasons for LULC changes in the region. We anticipate that this freely available data will improve the modeling for surface forcing, provide evidence of changes in LULC, and inform water-management decision-making.

This article argues that we need to look at living examples provided by non-state communities in various regions of the world that are, perhaps unwittingly, contributing to the maintenance of the Earth's optimal thermal balance. These fully sustainable communities have been living outside the mainstream for centuries, even millennia, providing examples in the global struggle against the degradation of social–ecological systems. They have all, to varying degrees, embraced simple forms of living that make them ‘exemplary ethical communities’ (EECs) – human communities with a track record of sustainability related to forms of traditional knowledge and the capacity to survive outside the capitalist market and nation-state system. The article proceeds in three steps: First, it condenses a large body of research on the limits of the existing nation-state system and its accompanying ideology, nationalism, identifying this institutional–ideological complex as the major obstacle to tackling climate change. Second, alternative social formations that could offer viable micro-level and micro-scale alternatives are suggested. These are unlikely to identify with existing nation-states as they often form distinct types of social communities. Taking examples from hunter-gatherer societies and simple-living religious groups, it is shown how the protection and maintenance of these EECs could become the keystone in the struggle for survival of humankind and other forms of life. Finally, further investigation is called for, into how researchers can come forward with more examples of actually existing communities that might provide pathways to sustainability and resistance to the looming global environmental catastrophe.