Critical Disturbance Research Articles

8158 Transient Blindness In Metformin-Associated Lactic Acidosis

Abstract Disclosure: Y. Abouelkheer: None. A. Nasir: None. M. Ibrahem: None. Transient Blindness in Metformin-associated Lactic Acidosis Background: Metformin-associated lactic acidosis (MALA) is a rare side effect of metformin use. MALA can result in acute transient blindness in patients with severe metabolic derangements. Clinical Case: A 62-year-old woman presented with severe diarrhea, poor oral intake, malaise, and vomiting on a background of metformin-treated type 2 diabetes mellitus. Laboratory investigations showed bicarbonate <2 mmol/L, anion gap 48 mmol/L, lactic acid 20.5 mmol/L, serum osmolality 352 mOsm/kg, negative urine toxicology screen, and positive SARS-CoV-2. In the emergency department, the patient developed sudden onset bilateral vision loss. The examination was remarkable for complete vision loss bilaterally in all fields, associated with minimally reactive pupils and spontaneous ocular movements with an otherwise unrevealing neurological examination. Computed Tomography (CT) of the brain with stroke protocol showed no evidence of acute intracranial process. CT angiogram of the brain and neck showed patent intracranial and cervical vasculature without high-grade stenosis, large vessel occlusion, or aneurysm. While receiving medical management with intravenous fluid resuscitation and sodium bicarbonate supplementation, the patient had a spontaneous return of vision with no additional neurological complications or deficits. The severe metabolic derangements were associated with distributive shock, requiring admission to the intensive care unit for urgent hemodialysis, pressor support, empiric antibiotics, and stress-dose steroids. Shortly after the patient’s only hemodialysis session, we noted the resolution of her critical metabolic disturbances, renal failure, and shock state. Laboratory investigations post-dialysis showed bicarbonate 12 mmol/L, anion gap 36 mmol/L, and lactic acid 10.5 mmol/L. Follow-up MRI showed chronic lacunar infarct of the left basal ganglia, and she was discharged home six days later. Conclusion: Transient blindness in MALA can mimic acute neurovascular events. Prompt correction of metabolic derangements can aid in reversing systemic symptoms and blindness. Reference: DeFronzo R, Fleming GA, Chen K, Bicsak TA. Metformin-associated lactic acidosis: Current perspectives on causes and risk. Metabolism. 2016;65(2):20-29. doi:10.1016/j.metabol.2015.10.014 Presentation: 6/2/2024

Improving fire severity prediction in south-eastern Australia using vegetation-specific information

Abstract. Wildfire is a critical ecological disturbance in terrestrial ecosystems. Australia, in particular, has experienced increasingly large and severe wildfires over the past 2 decades, while globally fire risk is expected to increase significantly due to projected increases in extreme weather and drought conditions. Therefore, understanding and predicting fire severity is critical for evaluating current and future impacts of wildfires on ecosystems. Here, we first introduce a vegetation-type-specific fire severity classification applied to satellite imagery, which is further used to predict fire severity during the fire season (November to March) using antecedent drought conditions, fire weather (i.e. wind speed, air temperature, and atmospheric humidity), and topography. Compared to fire severity maps from the fire extent and severity mapping (FESM) dataset, we find that fire severity prediction results using the vegetation-type-specific thresholds show good performance in extreme- and high-severity classification, with accuracies of 0.64 and 0.76, respectively. Based on a “leave-one-out” cross-validation experiment, we demonstrate high accuracy for both the fire severity classification and the regression using a suite of performance metrics: the determination coefficient (R2), mean absolute error (MAE), and root-mean-square error (RMSE), which are 0.89, 0.05, and 0.07, respectively. Our results also show that the fire severity prediction results using the vegetation-type-specific thresholds could better capture the spatial patterns of fire severity and have the potential to be applicable for seasonal fire severity forecasts due to the availability of seasonal forecasts of the predictor variables.

Ізольована гіпоплазія правого шлуночка: діагностика, лікування та досвід спостереження пацієнтів дитячого віку

Isolated hypoplasia of the right ventricle (IHRV) is a rare congenital heart defect characterized by a reduction of the right ventricular cavity due to hypoplasia of its trabecular part. Aim - to analyze the anatomical variants of IHRV and their influence on the choice of treatment tactics based on the experience of observing pediatric patients. Materials and methods. This retrospective study included 11 consecutive patients diagnosed with IHRV from 2012 to 2024. Patients were divided into 3 groups based on the ratio of RV to left ventricle (LV) length. The Group I (n=4): mild IHRV (RV/LV length ratio >0.8). The Group II (n=4): moderate IHRV (RV/LV length ratio = 0.7-0.8). The Group III (n=3): severe IHRV (RV/LV ventricle length ratio <0.67). Results. From the Group I (n=4), one patient required medication therapy with beta-blockers and others did not require any treatment. From the Group II (n=4), one patient underwent Glenn shunt and patent foramen ovale (PFO) closure, another - Glenn shunt and PFO closure with fenestration. Two patients have stable clinical conditions. Patients from the Group III (n=3) had duct-dependent pulmonary blood flow in the neonatal period. One patient received treatment with beta-blockers; the second patient underwent patent ductus arteriosus stenting; and the third - systemic-to-pulmonary shunt. Conclusions. Patients with severe IHRV may have critical hemodynamic disturbances requiring urgent cardiac surgical interventions, whereas patients with mild and moderate hypoplasia may require medical treatment with possible surgical intervention at a later age. Long-term follow-up in this defect reveals a slow progressive growth of the right heart chambers. The research was carried out in accordance with the principles of the Declaration of Helsinki. Informed consent of the child and child's parents was obtained for the research. The authors declare no conflict of interest.

Acid rain prediction in the Guangdong-Hong Kong-Macao Greater Bay Area using an explainable machine learning framework

Acid rain, characterized by pH values lower than 5.6, is a critical natural disturbance of ecosystems, which threatens the sustainability of ecosystems, agriculture, and human society worldwide. However, accurately quantifying the driving factors of acid rain remains challenging due to a changing environment of significant spatial heterogeneity. Here, we established an explainable machine-learning framework (MLF) using 19 meteorological, air pollutant, and land surface variables as model input to construct the pH values of acid rain across the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) during 2006–2021. The MLF includes Extreme Gradient Boosting (XGBoost) for acid deposition prediction and a SHapley Additive exPlanations method (SHAP) for interpreting factor importance. The results indicated that the observed increases in pH values of acid rain are predominantly controlled by the significant decreases in maximum daily sulfur dioxide (SO2) concentration of air across GBA, with its relative contribution ranging from 16.2% to 31.9% for each city. Changes in the urbanization rate and the proximity to the coast also play significant roles in predicting the pH values of acid rain. Meteorological variables typically have minimal impact on acid rain predictions, with their contribution generally being less than 5%, indicating the complex physical process of acid rain generation. This study enhanced our comprehension of the spatial variability of acid rain drivers across a highly developed region, providing valuable insights and case studies for regions worldwide that frequently experience acid rain.

Formation of convective roll patterns over a longitudinal throughflow in an active inhomogeneous porous medium with weak clogging

The convective stability of a plane-parallel longitudinal throughflow in a system consisting of two porous sublayers with distinct permeability is studied taking into account the weak pore clogging effect and given a finite difference in concentration between the upper and lower boundaries of the system. A system of differential equations for convection is derived within the framework of the continuum approach and the nonlinear MIM model. A linear stability analysis of the basic longitudinal flow is carried out. The boundary value problem is solved using the numerical technique for constructing a fundamental system of solutions. The neutral stability curves of the basic flow with respect to the disturbances in the form of rolls with different wavelength are obtained. For the absence of pore clogging, the convective stability maps of the critical solutal Rayleigh-Darcy number versus the permeability ratio for the initial uncontaminated sublayers, as well as the plots of the critical disturbance frequency and wave number versus the permeability ratio for some values of the Peclet number, are constructed. It is shown that these results have symmetry with respect to the solution for equal initial permeability of sublayers. The clogging effect associated with the solute adsorption and desorption in a porous medium is studied in the two-layered systems with the values 0.1 and 10 of the ratio of initial permeabilities of the sublayers; convection localization occurs in distinct sublayers. It was found that clogging increases the stability of the longitudinal basic flow relative to solutal inhomogeneity and breaks the symmetry of solutions with respect to the case when the two-layered system is reduced to a single layer with the same filtration properties of the porous medium throughout its volume. The influence of sorption effects on the critical parameters of oscillatory convection is investigated by plotting the critical solutal Rayleigh-Darcy number, disturbance frequency and wave number against the adsorption coefficient at fixed values of the desorption coefficient. The isolines of the stream function are constructed to analyze convective flow patterns. It was established that there is a weak relationship between the typical size of local convective roll patterns and the clogging parameters. It is shown that the sorption processes, which can lead to clogging, have a significant impact on the velocity of convective rolls moving along the two-layered system at a slight variation in their sizes.

Forest Disturbance Thresholds and Cumulative Hydrological Impacts

AbstractForest disturbance threshold is defined as a critical disturbance level (e.g., % of forest cover change) in forested landscapes above which significant hydrological impacts are detected. Determining disturbance thresholds is critically important for supporting forest management to ensure the sustaining of ecological and hydrological functions. However, there are very few quantitative evaluations of forest disturbance thresholds globally. In this study, we applied a well‐tested methodology (the modified double mass curve) to derive the long‐term, continuous hydrological response curves and then to quantify forest disturbance thresholds on annual streamflow in 42 forested watersheds in British Columbia, Canada. The results show that forest disturbance thresholds for significant and cumulative hydrological impacts vary from 7% to 52% of cumulative equivalent clear‐cut area with an average of 17% or from 8% to 52% of disturbed area with an average of 19%. Climate (inter‐annual and intra‐annual) and watershed properties exert critical controls on forest disturbance thresholds. Watersheds with greater snowfall proportions (more annual precipitation falling as snow), more desynchronizations (temporal mismatching) of energy demand and water supply at the intra‐annual scale, less diverse ecosystems, and larger watershed sizes have lower forest disturbance thresholds. Given the present forest disturbance levels in the central interior of British Columbia, about half (53%) of the forested watersheds have already crossed the average disturbance threshold. These results highlight that watershed planning and management using forest disturbance thresholds must carefully consider local climate and watershed properties. The methodology can be effectively and robustly extended elsewhere around the globe.

Tracheal Intubation and Mechanical Ventilation in Adults with Severe Salicylate Poisoning

BackgroundSalicylate poisoning may lead to critical acid–base disturbances. Tracheal intubation and mechanical ventilation for patients with severe salicylism has been strongly discouraged. Study ObjectiveThis study aims to describe pH trends, complications, and outcomes in a cohort of salicylate-poisoned patients who were intubated. MethodsThis retrospective observational study included adults presenting to the emergency department (ED) with severe salicylate poisoning (serum salicylate concentration >40 mg/dL and admission to an intensive care unit) over a 14-year period (2007–2021). The primary and secondary outcomes were the change in serum pH and the occurrence of severe complications (systolic blood pressure <80 mm Hg, oxygen saturation <80%, or cardiac arrest), respectively, in the 6 h after presentation. ResultsAmong 32 adults with severe salicylate poisoning (median serum salicylate level 64.2, interquartile range 52.5–70.7), 11 (34%) underwent tracheal intubation. The initial mean pH (±SD) in the no intubation group was 7.48 ± 0.07 and was 7.36 ± 0.04 in the intubation group. The mean absolute difference in pH measured before and after intubation was -0.02 (95% confidence interval −0.11 to 0.07). No severe complications were observed during or up to 6 h after tracheal intubation and mechanical ventilation. ConclusionIn our single-center experience managing adults with severe salicylate poisoning, tracheal intubation and mechanical ventilation were not associated with substantial perturbation of serum pH or severe complications. These findings challenge the current paradigm that these interventions should be avoided in salicylate-poisoned patients.

Stochastic dynamics of coral reef system with stage-structure for crown-of-thorns starfish

The outbreak of crown-of-thorns starfish (CoTS) is one of the most critical biological disturbances in coral reef systems and contributes greatly to the degradation of coral. Although many studies have focused on coral-CoTS interactions, there is no effective method for suppressing CoTS outbreaks in the long term, in part because of incomplete knowledge of their life cycle. In this paper, a stochastic system is formulated to characterize the interactions among coral, immature CoTS, and mature CoTS, where environmental noise is introduced into the growth of coral. The existence and uniqueness of a global positive solution with any given initial value are investigated, sufficient conditions are established for the extinction of CoTS, and the existence and uniqueness of a stable stationary distribution are explored by applying the Markov semigroup theory. In particular, by solving the Fokker–Planck equation, the approximate expression of the probability density function of the distribution around its quasi positive equilibrium is expounded under certain parametric restrictions. By employing Milstein’s higher-order method, numerical simulations are presented to validate the theoretical results. This study reveals that coral are more vulnerable and are more likely to go extinct in the presence of strong noise, while weak noise is more conducive to the existence of a stable stationary distribution, which implies the long-term persistence of coral and CoTS.

Enhancing Control Room Operator Decision Making

In the dynamic and complex environment of industrial control rooms, operators are often inundated with numerous tasks and alerts, leading to a state known as task overload. This condition can result in decision fatigue and increased reliance on cognitive biases, which may compromise the decision-making process. To mitigate these risks, the implementation of decision support systems (DSSs) is essential. These systems are designed to aid operators in making swift, well-informed decisions, especially when their judgment may be faltering. Our research presents an artificial intelligence (AI)-based framework utilizing dynamic influence diagrams and reinforcement learning to develop a powerful decision support system. The foundation of this AI framework is the creation of a robust, interpretable, and effective DSS that aids control room operators during critical process disturbances. By incorporating expert knowledge, the dynamic influence diagram provides a comprehensive model that captures the uncertainties inherent in complex industrial processes. It excels in anomaly detection and recommending optimal actions. Furthermore, this model is improved through a strategic collaboration with reinforcement learning, which refines the recommendations to be more context-specific and accurate. The primary goal of this AI framework is to equip operators with a live, reliable DSS that significantly enhances their response during process upsets. This paper describes the development of the AI framework and its implementation in a simulated control room environment. Our results show that the DSS can improve operator performance and reduce cognitive workload. However, it also uncovers a trade-off with situation awareness, which may decrease as operators become overly dependent on the system’s guidance. Our study highlights the necessity of balancing the advantages of decision support with the need to maintain operator engagement and understanding during process operations.

Abstract WP311: Novel Computational Framework for Modelling the Effects of Temperature on Survival Time in Ischemic Stroke

Introduction: The detrimental influence of cerebral hyperthermia is well known, with notably deleterious effects in the ischemic brain, where even mild increases (&lt;1°C) may rapidly potentiate ischemic injury. Experimental models of ischemic hyperthermia are undermined by the lack of pragmatic means for temporally- and spatially-resolved, direct cerebral thermometry. Computational models of cerebrovascular ischemia are well-suited to such exploration, and the use of digital phantoms for sophisticated biophysical modeling has been facilitated by emergent hardware, software, and computational solutions. We present a realistic computational environment for the simulation of thermal disturbance in cerebrovascular ischemia, permitting multiscale demonstration of hemodynamic, metabolic, and thermal aberrations in ischemic brain Methods: A multi-tissue biophysical numerical model of the human head and brain was extended to incorporate the dynamics of nutritive flow, metabolic need, tissue heating, and cytotoxicity. By restricting perfusion in a region of brain using a rudimentary representation of vascularization, we could quantify tissue heating arising from impaired radiative cooling, and time-dependent cell death. The procedure was iterated with an expected proportionality between temperature and metabolic rate Results: Fig 1 demonstrates simulated hypoperfusion affecting one hemisphere with resultant cerebral hyperthermia arising from impaired countercurrent heat exchange. Incorporating the effects of hyperthermia upon metabolic demand, the downward influence of heating on survivability is apparent, with ~30-minute acceleration to cytotoxicity. Conclusion: We present a combined model for tissue physiology and survival time following ischemic stroke using a multi-tissue model of whole-head bio-thermodynamics to examine effects of critical temperature disturbance on predicted tissue survival time.

Production chain and covid-19 disruption: Sustainability via flexibility framework a case of the beverage industry

The pandemic has uncovered the weakness and volatility of production chains. The study examined the implication of corona-virus on the production chain functionality in a beverage production firm in terms of sustainability and flexibility. The study also evaluated a contextual analysis of an organization, the impact of the corona-virus outbreak, and the challenges the organization encountered. A purposive method was utilized as an information-gathering source from 200 participants. The outcome shows that the pandemic prompted critical disturbances such as the deficiency of resources/extra parts, accessibility of transportation, accessibility of work, and safety guidelines. The study also postulates that there is a need to re-design the production chain to be more flexible and resilient by providing recuperation plans (anticipation, choice of supply, modeling, observing) that consider measures in various echelons. Given this, a prescribed optimal procedure was suggested for the contextual analysis by considering inward, outward, and technological bottlenecks during the pandemic. A portion of the designated procedure and the optimization of the production chain can be considered and utilized in the other sectors.

Study of dynamic stability of MV (middle voltage) Network of Douala within the meaning of Lyapunov

The studies undertaken have used the method of Lyapunov of the system theory to evaluate the stability of the electric network starting from the power function depending on the dephasing between voltage and current in time. To carry out these studies, a look into the dynamic stability of the electrical network, and the stability within the meaning of Lyapunov was effected. Then a modelling of our network with application under MATLAB/Simulink was carried out as well as the tests of simulations without disturbances, and another test with disturbances was made. This reveals that the Douala network suffered falls in voltage, increasing instability depending on the critical disturbances, with the network eliminating the faults slowly.

Flow dynamics in sinusoidal channels at moderate Reynolds numbers

Pressure-gradient-driven flows through sinusoidal channels have been studied. The analysis was carried out up to the formation of secondary nonlinear states and spanned a range of low and moderate Reynolds numbers. Direct numerical simulations were used to identify and determine the properties of steady as well as non-stationary, two-dimensional (2-D) and three-dimensional secondary flows. Our results indicate the existence of several distinct solution types. Two-dimensional, stationary flows with periodicity determined by the corrugation represent the first type. The second type is associated with the appearance of 2-D oscillatory flows arising from the onset of unstable travelling waves. Such oscillatory solutions are generally out of phase with the wall corrugation but could be in phase in special cases determined by the ratio of the critical disturbance wavelength and the channel corrugation wavelength. Consequently, several distinct types of time-dependent solutions are possible. The third type of solution results from the centrifugal effect caused by wall curvature and leads to three-dimensionalization of the flow through the onset of stationary streamwise vortices. Finally, various states resulting from the interaction of different solution types are possible. We examine those states and present a bifurcation diagram illustrating the formation of some of them. The results presented in this paper might help with the development of small-scale flow measurement and detection devices operating at low and moderate Reynolds numbers, as well as in the use of wall topographies for the intensification of mixing in flows with moderate, subturbulent Reynolds numbers.

A FOLLOW-UP ON THE METHODICAL FRAMEWORK FOR THE IDENTIFICATION, ANALYSIS AND CONSIDERATION OF UNCERTAINTY IN THE CONTEXT OF THE INTEGRATION OF SENSORY FUNCTIONS BY MEANS OF SENSING MACHINE ELEMENTS

AbstractWhen integrating sensing machine elements for in-situ measurements in technical systems, special attention must be paid to uncertainty to ensure the reliability of the provided information. Therefore, a methodical framework for the identification, analysis and consideration of uncertainty was already developed in prior research, which still offers room for improvement regarding the included methods and tools. Therefore, in this contribution, the initially proposed methods and tools are adapted and extended to enhance their efficiency and applicability and to reduce their error proneness in order to increase the acceptance of the framework in practice. First, the identification of uncertainty is improved by means of an extended effect graph for an automated identification of disturbance factor induced data and model uncertainty. Second, the significance of the subsequent evaluation of uncertainty is enhanced by replacing the initially proposed local sensitivity analysis with a global sensitivity analysis. Finally, a flowchart is proposed that supports the identification of applicable and promising strategies for the development of measures to consider critical disturbance factor induced uncertainty.

Differences across herds with different dairy breeds in daily milk yield based proxies for resilience.

Global sustainability issues such as climate change, biodiversity loss and food security require food systems to become more resource efficient and better embedded in the local environment. This needs a transition towards more diverse, circular and low-input dairy farming systems with animals best suited to the specific environmental conditions. When varying environmental challenges are posed to animals, cows need to become resilient to disturbances they face. This resilience of dairy cows for disturbances can be quantified using sensor features and resilience indicators derived from daily milk yield records. The aim of this study was to explore milk yield based sensor features and resilience indicators for different cattle groups according to their breeds and herds. To this end, we calculated 40 different features to describe the dynamics and variability in milk production of first parity dairy cows. After correction for milk production level, we found that various aspects of the milk yield dynamics, milk yield variability and perturbation characteristics indeed differed across herds and breeds. On farms with a lower breed proportion of Holstein Friesian across cows, there was more variability in the milk yield, but perturbations were less severe upon critical disturbances. Non-Holstein Friesian breeds had a more stable milk production with less (severe) perturbations. These differences can be attributed to differences in genetics, environments, or both. This study demonstrates the potential to use milk yield sensor features and resilience indicators as a tool to quantify how cows cope with more dynamic production conditions and select animals for features that best suit a farms' breeding goal and specific environment.

Long-Term Dynamics of Forest Fires in Southern Siberia

The research focus. Wildfire is a critical environmental disturbance affecting forest dynamics, succession, and the carbon cycle in Siberian forests. Forests of southern Siberia experienced an increase of fire rate. We analyzed spatial and temporal dynamics of burned area in the southern Central Siberian Mountains. We considered burning rate within different forest types: dark needle conifers (DNC) composed by Siberian pine, spruce and fir, light-needle composed by Scotch pine and larch, and mix wood (composed by birch, aspen and conifers). Methods. We used long-term (1982–2021) climatic variables from the ERA5-Land database. Satellite observations included MODIS wildfire data (2002–2021) and gravimetric (GRACE) data (2002–2021) for estimation soil moisture content. We analyzed the spatial distribution of burned areas considering dominant forest stands and terrain (elevation, slope aspect and steepness). Results. We found a significant decreasing trend in burned area. On average, about 978.7 ± 447.5 thousand ha including 257.1 ± 154.3 thousand ha of forests are disturbed by fire annually. Light coniferous forests are characterized by the highest degree of the fire disturbance (relative burned area, RBA, was ca. 0.83% per year); whereas DNC stands have the lowest RBA (ca. 0.15% per year). The spatial distribution of fires in light coniferous forests showed predominance of fires on the southern slopes comparing to northern slopes (by 15–20%). We found a decreasing logarithmic trend in burned area between plains and low mountains and high mountains due to lower forest fuel loads and increased amount of precipitation on higher elevations. We also observed lower RBA values (by 300–400%) on steep slopes for light coniferous forests and mixed forests comparing to gentle slopes due to lower available forest fuels. The long-term dynamics of burned area in the region was related to the variation of climatic variables, such as soil moisture (r2 = 0.70, p < 0.01), moisture content (r2 = 0.63, p < 0.01) and drought index (r2 = 0.3, p < 0.05).

The impact of adolescent achievement goal orientation on learning anxiety: The mediation effect of peer interaction.

Learning anxiety is one of the most critical emotional disturbances, which also has a high incidence rate in adolescents. Peer interaction is critical and unique for adolescents. Although previous studies have found that achievement goal orientation has an important role in the development of learning anxiety, its mechanism has not been clarified. This study surveyed 470 adolescents (191 middle school students and 279 high school students; 211 boys) and established a structural equation model to explore the mediating role of peer interaction in the influence of achievement goal orientation on learning anxiety. Results showed that (1) there were significant gender differences in mastery-avoidance goal orientation, peer interaction, and learning anxiety, and there were grade differences in performance-approach goal and performance-avoidance goal orientations; (2) mastery-approach, mastery-avoidance, and performance-avoidance goal orientations directly predicted learning anxiety; and (3) social anxiety in peer interactions had a mediating effect on the influence of mastery-approach, mastery-avoidance, and performance-avoidance goal orientations on learning anxiety. The findings extend theoretical considerations by teasing out the process of peer interaction affecting the relationship between achievement goal orientation and learning anxiety. Additionally, the results have practical implications for the effective use of peer interaction to reduce learning anxiety.

Battery-Less Industrial Wireless Monitoring and Control System for Improved Operational Efficiency

An industrial wireless monitoring and control system, capable of supporting energy-harvesting devices through smart sensing and network management, designed for improving electro-refinery performance by applying predictive maintenance, is presented. The system is self-powered from bus bars, and features wireless communication and easy-to-access information and alarms. With cell voltage and electrolyte temperature measurements, the system enables real-time cell performance discovery and early reaction to critical production or quality disturbances such as short-circuiting, flow blockages, or electrolyte temperature excursions. Field validation shows an increase in operational performance of 30% (reaching 97%) in the detection of short circuits, which, thanks to a neural network deployed, are detected, on average, 10.5 h earlier compared to the traditional methodology. The developed system is a sustainable IoT solution, being easy to maintain after its deployment, and providing benefits of improved control and operation, increased current efficiency, and decreased maintenance costs.

Risk Factors and Prediction of the Probability of Wildfire Occurrence in the China–Mongolia–Russia Cross-Border Area

Wildfire is essential in altering land ecosystems’ structures, processes, and functions. As a critical disturbance in the China–Mongolia–Russia cross-border area, it is vital to understand the potential drivers of wildfires and predict where wildfires are more likely to occur. This study assessed factors affecting wildfire using the Random Forest (RF) model. No single factor played a decisive role in the incidence of wildfires. However, the climatic variables were most critical, dominating the occurrence of wildfires. The probability of wildfire occurrence was simulated and predicted using the Adaptive Network-based Fuzzy Inference System (ANFIS). The particle swarm optimization (PSO) model and genetic algorithm (GA) were used to optimize the ANFIS model. The hybrid ANFIS models performed better than single ANFIS for the training and validation datasets. The hybrid ANFIS models, such as PSO-ANFIS and GA-ANFIS, overcome the over-fitting problem of the single ANFIS model at the learning stage of the wildfire pattern. The high classification accuracy and good model performance suggest that PSO-ANFIS can be used to predict the probability of wildfire occurrence. The probability map illustrates that high-risk areas are mainly distributed in the northeast part of the study area, especially the grassland and forest area of Dornod Province of Mongolia, Buryatia, and Chita state of Russia, and the northeast part of Inner Mongolia, China. The findings can be used as reliable estimates of the relative likelihood of wildfire hazards for wildfire management in the region covered or vicinity.

Mitochondrial redox impairment and enhanced autophagy in peripheral blood mononuclear cells from type 1 diabetic patients

Type 1 diabetes (T1D) involves critical metabolic disturbances that contribute to an increased cardiovascular risk. Leukocytes are key players in the onset of atherosclerosis due to their interaction with the endothelium. However, whether mitochondrial redox impairment, altered bioenergetics and abnormal autophagy in leukocytes contribute to T1D physiopathology is unclear.In this study we aimed to evaluate the bioenergetic and redox state of peripheral blood mononuclear cells (PBMCs) from T1D patients in comparison to those from healthy subjects, and to assess autophagy induction and leukocyte-endothelial interactions.T1D patients presented lower levels of fast-acting and total antioxidants in their blood, and their leukocytes produced higher amounts of total reactive oxygen species (ROS) and superoxide radical with respect to controls. Basal and ATP-linked respiration were similar in PBMCs from T1D and controls, but T1D PBMCs exhibited reduced spare respiratory capacity and a tendency toward decreased maximal respiration and reduced non-mitochondrial respiration, compared to controls. The autophagy markers P-AMPK, Beclin-1 and LC3-II/LC3-I were increased, while P62 and NBR1 were decreased in T1D PBMCs versus those from controls. Leukocytes from T1D patients displayed lower rolling velocity, higher rolling flux and more adhesion to the endothelium versus controls.Our findings show that T1D impairs mitochondrial function and promotes oxidative stress and autophagy in leukocytes, and suggest that these mechanisms contribute to an increased risk of atherosclerosis by augmenting leukocyte-endothelial interactions.