Integrating Human Domain Knowledge into Artificial Intelligence for Hybrid Forest Fire Prediction: Case Studies from South Korea and Italy

Forest fires pose a growing global threat, exacerbated by climate change-induced heat waves. The intricate interplay between changing climate, biophysical, and anthropogenic factors emphasizes the urgent need for sophisticated predictive models. Existing models, whether process-based for interpretability or machine learning-based for automatic feature identification, have distinct strengths and weaknesses. This study addresses these gaps by integrating human domain knowledge, crucial for interpreting forest fire dynamics, into a machine learning framework. We introduce FLAM-Net, a neural network derived from IIASA's wildfire Climate impacts and Adaptation Model (FLAM), melding process-based insights of FLAM with machine learning capabilities. In optimizing FLAM-Net for South Korea, new algorithms interpret national-specific forest fire patterns, and multi-scale applications, facilitated by U-Net-based deep neural networks (DN-FLAM), yield downscaled predictions. Successfully tailored to South Korea's context, FLAM-Net and DN-FLAM reveal spatial concentration near metropolitan areas and the east coastal region, with temporal concentration in spring. Performance evaluation yields Pearson's r values of 0.943, 0.840, and 0.641 for temporal, spatial, and spatio-temporal dimensions. Projections based on Shared Socioeconomic Pathways (SSP) indicate an increasing trend in forest fires until 2050, followed by a decrease due to increased precipitation. During the optimization process of FLAM-Net for Italy, optimal parameters for sub-areas are identified. This involves considering biophysical and anthropogenic factors at each grid, contributing to improved localized projection optimization by utilizing various sets of optimal parameters. There by, this process illuminates the intricate connections between environmental factors and their interpretation in the dynamics of forest fires. This study demonstrates the advantages of hybrid models like FLAM-Net and DN-FLAM, seamlessly combining process-based insights and artificial intelligence for interpretability, accuracy, and efficient optimization. The findings contribute scientific evidence for developing context-specific climate resilience strategies, with global applicability to enhance climate resilience

Protection by the NO-Donor SNAP and BNP against Hypoxia/Reoxygenation in Rat Engineered Heart Tissue

In vitro assays could replace animal experiments in drug screening and disease modeling, but have shortcomings in terms of functional readout. Force-generating engineered heart tissues (EHT) provide simple automated measurements of contractile function. Here we evaluated the response of EHTs to hypoxia/reoxygenation (H/R) and the effect of known cardiocytoprotective molecules. EHTs from neonatal rat heart cells were incubated for 24 h in EHT medium. Then they were subjected to 180 min hypoxia (93% N2, 7% CO2) and 120 min reoxygenation (40% O2, 53% N2, 7% CO2), change of medium and additional follow-up of 48 h. Time-matched controls (40% O2, 53% N2, 7% CO2) were run for comparison. The following conditions were applied during H/R: fresh EHT medium (positive control), the NO-donor S-nitroso-N-acetyl-D,L-penicillamine (SNAP, 10-7, 10-6, 10-5 M) or the guanylate cyclase activator brain type natriuretic peptide (BNP, 10-9, 10-8, 10-7 M). Frequency and force of contraction were repeatedly monitored over the entire experiment, pH, troponin I (cTnI), lactate dehydrogenase (LDH) and glucose concentrations measured in EHT medium. Beating activity of EHTs in 24 h-medium ceased during hypoxia, partially recovered during reoxygenation and reached time-control values during follow-up. H/R was accompanied by a small increase in LDH and non-significant increase in cTnI. In fresh medium, some EHTs continued beating during hypoxia and all EHTs recovered faster during reoxygenation. SNAP and BNP showed small but significant protective effects during reoxygenation. EHTs are applicable to test potential cardioprotective compounds in vitro, monitoring functional and biochemical endpoints, which otherwise could be only measured by using in vivo or ex vivo heart preparations. The sensitivity of the model needs improvement

Development and Evolution of the Muscles of the Pelvic Fin

Locomotor strategies in terrestrial tetrapods have evolved from the utilisation of sinusoidal contractions of axial musculature, evident in ancestral fish species, to the reliance on powerful and complex limb muscles to provide propulsive force. Within tetrapods, a hindlimb-dominant locomotor strategy predominates, and its evolution is considered critical for the evident success of the tetrapod transition onto land. Here, we determine the developmental mechanisms of pelvic fin muscle formation in living fish species at critical points within the vertebrate phylogeny and reveal a stepwise modification from a primitive to a more derived mode of pelvic fin muscle formation. A distinct process generates pelvic fin muscle in bony fishes that incorporates both primitive and derived characteristics of vertebrate appendicular muscle formation. We propose that the adoption of the fully derived mode of hindlimb muscle formation from this bimodal character state is an evolutionary innovation that was critical to the success of the tetrapod transition

A meta-analytic review of stand-alone interventions to improve body image

Objective Numerous stand-alone interventions to improve body image have been developed. The present review used meta-analysis to estimate the effectiveness of such interventions, and to identify the specific change techniques that lead to improvement in body image. Methods The inclusion criteria were that (a) the intervention was stand-alone (i.e., solely focused on improving body image), (b) a control group was used, (c) participants were randomly assigned to conditions, and (d) at least one pretest and one posttest measure of body image was taken. Effect sizes were meta-analysed and moderator analyses were conducted. A taxonomy of 48 change techniques used in interventions targeted at body image was developed; all interventions were coded using this taxonomy. Results The literature search identified 62 tests of interventions (N = 3,846). Interventions produced a small-to-medium improvement in body image (d+ = 0.38), a small-to-medium reduction in beauty ideal internalisation (d+ = -0.37), and a large reduction in social comparison tendencies (d+ = -0.72). However, the effect size for body image was inflated by bias both within and across studies, and was reliable but of small magnitude once corrections for bias were applied. Effect sizes for the other outcomes were no longer reliable once corrections for bias were applied. Several features of the sample, intervention, and methodology moderated intervention effects. Twelve change techniques were associated with improvements in body image, and three techniques were contra-indicated. Conclusions The findings show that interventions engender only small improvements in body image, and underline the need for large-scale, high-quality trials in this area. The review identifies effective techniques that could be deployed in future interventions

Energy Reallocation to Breeding Performance through Improved Nest Building in Laboratory Mice.

Mice are housed at temperatures (20-26°C) that increase their basal metabolic rates and impose high energy demands to maintain core temperatures. Therefore, energy must be reallocated from other biological processes to increase heat production to offset heat loss. Supplying laboratory mice with nesting material may provide sufficient insulation to reduce heat loss and improve both feed conversion and breeding performance. Naïve C57BL/6, BALB/c, and CD-1breeding pairs were provided with bedding alone, or bedding supplemented with either 8g of Enviro-Dri, 8g of Nestlets, for 6 months. Mice provided with either nesting material built more dome-like nests than controls. Nesting material improved feed efficiency per pup weaned as well as pup weaning weight. The breeding index (pups weaned/dam/week) was higher when either nesting material was provided. Thus, the sparing of energy for thermoregulation of mice given additional nesting material may have been responsible for the improved breeding and growth of offspring

A Second-Generation Device for Automated Training and Quantitative Behavior Analyses of Molecularly-Tractable Model Organisms

A deep understanding of cognitive processes requires functional, quantitative analyses of the steps leading from genetics and the development of nervous system structure to behavior. Molecularly-tractable model systems such as Xenopus laevis and planaria offer an unprecedented opportunity to dissect the mechanisms determining the complex structure of the brain and CNS. A standardized platform that facilitated quantitative analysis of behavior would make a significant impact on evolutionary ethology, neuropharmacology, and cognitive science. While some animal tracking systems exist, the available systems do not allow automated training (feedback to individual subjects in real time, which is necessary for operant conditioning assays). The lack of standardization in the field, and the numerous technical challenges that face the development of a versatile system with the necessary capabilities, comprise a significant barrier keeping molecular developmental biology labs from integrating behavior analysis endpoints into their pharmacological and genetic perturbations. Here we report the development of a second-generation system that is a highly flexible, powerful machine vision and environmental control platform. In order to enable multidisciplinary studies aimed at understanding the roles of genes in brain function and behavior, and aid other laboratories that do not have the facilities to undergo complex engineering development, we describe the device and the problems that it overcomes. We also present sample data using frog tadpoles and flatworms to illustrate its use. Having solved significant engineering challenges in its construction, the resulting design is a relatively inexpensive instrument of wide relevance for several fields, and will accelerate interdisciplinary discovery in pharmacology, neurobiology, regenerative medicine, and cognitive science

Improved search for invisible modes of nucleon decay in water with the SNO+ detector

This paper reports results from a search for single and multi-nucleon disappearance from the $^{16}$O nucleus in water within the \snoplus{} detector using all of the available data. These so-called "invisible" decays do not directly deposit energy within the detector but are instead detected through their subsequent nuclear de-excitation and gamma-ray emission. New limits are given for the partial lifetimes: $\tau(n\rightarrow inv) > 9.0\times10^{29}$ years, $\tau(p\rightarrow inv) > 9.6\times10^{29}$ years, $\tau(nn\rightarrow inv) > 1.5\times10^{28}$ years, $\tau(np\rightarrow inv) > 6.0\times10^{28}$ years, and $\tau(pp\rightarrow inv) > 1.1\times10^{29}$ years at 90\% Bayesian credibility level (with a prior uniform in rate). All but the ($nn\rightarrow inv$) results improve on existing limits by a factor of about 3.info:eu-repo/semantics/publishedVersio

Observation of Antineutrinos from Distant Reactors using Pure Water at SNO+

The SNO+ collaboration reports the first observation of reactor antineutrinos in a Cherenkov detector. The nearest nuclear reactors are located 240 km away in Ontario, Canada. This analysis used events with energies lower than in any previous analysis with a large water Cherenkov detector. Two analytical methods were used to distinguish reactor antineutrinos from background events in 190 days of data and yielded consistent observations of antineutrinos with a combined significance of 3.5 $\sigma$.Comment: v2: add missing author, add link to supplemental materia