Relevant Scenarios Research Articles

Investigation of boiling heat transfer process in the barrel of a gravity heat pipe type extruder

Gravity heat pipe barrels produce gas films during the processing of thermoplastic materials, which affect the heat transfer, so there is an urgent need to study the nucleate boiling process and mechanism at different locations in the barrel. The results showed that the local heat flux at the vapor-liquid-solid three-phase contact was the largest, and different process conditions had different effects on the departure diameter and departure time of boiling bubbles. The tail vortex disturbance generated by bubble departure drives the merging and growth of bubbles to departure, which in turn improves the heat transfer. The rounded bottom of the barrel reduced the air film and increased the heat transfer efficiency compared to the horizontal bottom of the barrel. This study can deepen the understanding of the mechanism of bubble boiling heat exchange in gravity heat pipe-type barrels and provide theoretical support for more relevant application scenarios.

Advancing chemical safety assessment through an omics-based characterization of the test system-chemical interaction.

Assessing chemical safety is essential to evaluate the potential risks of chemical exposure to human health and the environment. Traditional methods relying on animal testing are being replaced by 3R (reduction, refinement, and replacement) principle-based alternatives, mainly depending on in vitro test methods and the Adverse Outcome Pathway framework. However, these approaches often focus on the properties of the compound, missing the broader chemical-biological interaction perspective. Currently, the lack of comprehensive molecular characterization of the in vitro test system results in limited real-world representation and contextualization of the toxicological effect under study. Leveraging omics data strengthens the understanding of the responses of different biological systems, emphasizing holistic chemical-biological interactions when developing in vitro methods. Here, we discuss the relevance of meticulous test system characterization on two safety assessment relevant scenarios and how omics-based, data-driven approaches can improve the future generation of alternative methods.

The Role of Epigenetics in Accelerated Aging: A Reconsideration of Later-Life Visual Loss After Early Optic Neuropathy.

In 2005, we reported 3 patients with bilateral optic nerve damage early in life. These patients had stable vision for decades but then experienced significant bilateral vision loss with no obvious cause. Our hypothesis, novel at that time, was that the late decline of vision was due to age-related attrition of retinal ganglion cells superimposed on a reduced neuronal population due to the earlier injury. The field of epigenetics provides a new paradigm with which to consider the normal aging process and the impact of neuronal injury, which has been shown to accelerate aging. Late-in-life decline in function after early neuronal injury occurs in multiple sclerosis due to dysregulated inflammation and postpolio syndrome. Recent studies by our group in mice have also demonstrated the possibility of partial reversal of cellular aging and the potential to mitigate anatomical damage after injury and even improve visual function. The results in mice and nonhuman primates published elsewhere have shown enhanced neuronal survival and visual function after partial epigenetic reprogramming. Injury promotes epigenetic aging , and this finding can be observed in several clinically relevant scenarios. An understanding of the epigenetic mechanisms at play opens the opportunity to restore function in the nervous system and elsewhere with cellular rejuvenation therapies. Our earlier cases exemplify how reconsideration of previously established concepts can motivate inquiry of new paradigms.

Brentuximab Vedotin in Combination with Nivolumab in CD30+ Malignancies Refractory to Brentuximab Vedotin

Introduction Brentuximab vedotin (BV), in combination with multi-agent chemotherapy, is considered a standard of care for newly diagnosed CD30+ lymphomas. Despite high reported efficacy, some patients fail to respond to initial BV exposure and many more eventually progress despite ongoing BV therapy. In addition to direct cytotoxicity, BV may also induce immunogenic cell death (Gardai, et al. Cancer Res 2015) and foster a reduction of regulatory T-cells (Herrera, et al. Blood 2018) that may synergize with immune checkpoint inhibitors. To date, the high response rates reported with BV and anti-PD-1 combinations have been limited to patients naïve to both of these agents (Advani, et al. Blood 2021). To address the more clinically relevant scenario of prior BV +/- anti-PD-1 exposure, we designed a study to evaluate the combination of BV and nivolumab in patients with CD30+ lymphoma refractory to prior BV, including those with prior anti-PD-1 therapy. We report the final safety, efficacy and correlative analysis of BV in combination with nivolumab in R/R CD30+ lymphomas refractory to BV. Methods We conducted an open-label trial (NCT01703949) involving patients 18 years and older with CD30+ lymphomas refractory to BV therapy. Refractoriness was defined as lack of disease response or progression within 6 months following a minimum of 2 cycles of BV. BV was given at 1.8 mg/kg in combination with nivolumab at 3 mg/kg every 3 weeks for 4 cycles. The primary endpoint was overall response rate (ORR). Secondary endpoints included complete response (CR) rate, progression-free survival, overall survival, time to next treatment, safety and tolerability and immune response biomarkers. Results As of July 27, 2023, 19 patients have enrolled and 17 have initiated therapy (Table 1). Fourteen patients had classical Hodgkin lymphoma (cHL), 2 had ALK-negative anaplastic large cell lymphoma (ALK- ALCL) and 3 had CD30+ mycosis fungoides (MF). Median age was 35 (range 27-71) years and the median number of prior regimens was 5 (range 1-9), including a median of 6 prior cycles of BV (range 2-19). All patients had BV-refractory disease including 16 (84%) who were non-responsive to and 3 (16%) who relapsed within 6 months of BV. Five (26%) patients with cHL received prior anti-PD-1 therapy and 4 (21%) had anti-PD-1 refractory disease. Median time from last BV and anti-PD-1 therapy to study treatment was 5.2 and 1.1 months, respectively. Eight (42%) patients had prior autologous stem cell transplant. Of response evaluable patients, the ORR and CR rate was 44% and 6% after 2 cycles and 44% and 19% after 4 cycles of therapy. Of patients who were refractory to prior BV and anti-PD-1 therapy, 1 (25%) and 1 (25%) achieved a PR and CR, respectively. ORR and CR rate was 43% and 14% for patients with cHL, 100% and 50% for patients with ALK- ALCL, and 100% and 100% for patients with MF, respectively. At completion of study, 1 patient with cHL, 1 with MF and 2 with cHL continued BV with nivolumab, BV monotherapy and nivolumab monotherapy, respectively. Median time to progression and next therapy was 4.5 (range 1.8-45.6) and 5.0 (range 1.8-45.6) months, respectively. Of the 3 patients who achieved a CR after 4 cycles of therapy, 2 (67%) continued treatment (1 with BV and nivolumab and 1 with BV monotherapy), and 1 (33%) has been on surveillance for 45.6 months with no evidence of relapse. At a median follow-up of 21.7 (range 0.5-60.4) months, 15 (79%) patients are alive with 3 in CR. Eleven (58%) and 8 (42%) patients reported no and grade 1 peripheral neuropathy (PN) at baseline, respectively. At end of treatment, 12 (63%) and 1 (5%) patients reported grade 1 and 2 PN, respectively. No patients experienced grade ≥3 PN, transaminitis, infections or infusion reactions. One (5%) patient had a 1-week dose delay due to grade 1 ALT/AST elevation. Two (11%) deaths were noted on study; one patient developed respiratory failure secondary to pneumonitis and influenza and another patient experienced cardiac arrest due to benzodiazepine withdrawal. Correlative PD-1 levels drawn at baseline and at the end of treatment did not correlate with response. Conclusions Despite the presence of BV-refractory disease, 4 cycles of BV and nivolumab is tolerable and associated with encouraging efficacy in patients with heavily treated CD30+ lymphoma. This treatment option may have increasing relevance as more patients receive BV or anti-PD-1 therapy as part of initial treatment.

Machine Learning Provides Individualized Prediction of Outcomes after First Complete Remission in Adult AML Patients - Results from the Harmony Platform

Background: Acute myeloid leukemia (AML) is a heterogeneous disease with high disease-related mortality and allogeneic hematopoietic stem cell transplantation (allo-HSCT) remains the only curative option for a large proportion of patients. However, allo-HSCT has a significant transplant-related mortality (TRM), so a careful evaluation between risk of disease relapse and TRM is needed for the challenging decision of whom to transplant in first complete remission (CR1). The European LeukemiaNet (ELN) provides a 3-tier static risk classification which is already a useful guidance, although dynamic risk assessment using measurable residual disease (MRD) information should also be taken into account. However, the intermediate-risk group is characterized by a wide heterogeneity and there are also some favorable-risk patients who require allo-HSCT because of early relapses after CR1. Therefore, more precise prediction tools are warranted to provide additional information valuable for clinical decision-making. Aims: To develop and validate a model that provides individualized outcome estimations in adult AML patients achieving CR1 with intensive treatment approaches. Methods: From the HARMONY Platform including 7467 AML patients at the time of the analysis, we selected patients aged 18-70 years old who received intensive treatment, achieved CR and were not consolidated with allo-HSCT in CR1. Patients who were refractory to first line chemotherapy or who had a relapse-free survival (RFS) of less than two months after achieving CR were excluded. A Bayesian Additive Regression Trees (BART) nonparametric machine learning model was used to predict the individualized likelihood of RFS, cumulative incidence of relapse (CIR) and overall survival (OS) in 1863 AML patients who were also selected based on the availability of comprehensive mutational information by next-generation sequencing analysis. Genomic aberrations that were present in at least 10 patients were included in the model. In order to test the accuracy of the model, a 10-fold cross-validation was applied using the area under receiver operating curve (AUC) at predefined time points (1, 2, 3, 4 and 5 years). Subsequently, the model was validated using an external publicly available database (Tazi et al, Nat. Commun. 2022) which included 722 patients based on identical inclusion criteria. Results: The study population of 1863 adult AML patients in CR1 included 51.2% of males and median age was 50 years. Regarding ELN2022 classification, 52% of patients were classified as favorable, 30% as intermediate and 18% as adverse risk. Most frequently mutated genes were NPM1 (35.9%), DNMT3A (25.6%) and NRAS (21.6%). The HARMONY model was able to estimate individualized likelihood of RFS, CIR and OS for all patients, providing confidence intervals for all estimations. Moreover, we could predict outcomes with increased accuracy over ELN2022 at all predefined time points. At 5 years, the AUC value was significantly better for the HARMONY model than ELN2022 in predicting RFS (0.729 vs 0.679, p=0.003), CIR (0.729 vs 0.680, p=0.002) and OS (0.733 vs 0.675, p<0.001) ( figure 1A). Validation in an external independent AML cohort confirmed superiority of the HARMONY model in predicting RFS (5-year AUC 0.714 vs 0.609, p <0.001), CIR (0.713 vs 0.610, p <0.001) and OS (0.737 vs 0.638, p <0.001) as compared to the ELN2022 risk stratification ( figure 1B), despite the fact that there was a different distribution of risk categories (28% favorable, 45% intermediate and 27% adverse risk). Conclusions: Analysis of large well-defined AML cohorts allows the development of increasingly precise predictive models for clinically relevant scenarios. The HARMONY machine learning model provides individualized outcome prediction for patients aged 18-70 years in CR1 consolidated without allo-HSCT and might be used in the future for clinical decision-making. The model can be accessed online via an interactive web calculator () and, while it has been validated using a large independent AML cohort, future studies are required focusing on prospective validation. Furthermore, the incorporation of additional variables such as MRD and the inclusion of patients treated with targeted therapies and non-intensive approaches will provide more accurate risk predictions.

Seismic performance of a sheet-pile retaining structure in liquefiable soils: Numerical simulations of LEAP-2022 centrifuge tests

This paper focuses on the numerical simulations of a sheet-pile retaining structure under liquefaction-induced lateral spreading, using data from LEAP-2022 dynamic centrifuge tests conducted at various facilities. The simulations employ an updated pressure-dependent multi-yield surface constitutive model (i.e., OpenSees PDMY03), incorporating dilatancy, cyclic mobility, and associated shear deformation features. To more accurately represent the liquefaction resistance characteristics of medium to dense Ottawa sands during LEAP-2022, the contractive and dilative rules of the PDMY03 model are updated based on experimental observations. Subsequently, the model parameters are calibrated through a series of stress-controlled cyclic direct simple shear (CDSS) tests to closely match the liquefaction strength curves of Ottawa sand. With these calibrated model parameters, dynamic response analyses of the sheet-pile retaining structure in liquefiable soils are performed, and the computed results are directly compared to the centrifuge experimental data. It is demonstrated that the updated PDMY03 constitutive model, combined with the employed computational framework, has the potential to realistically predict the experimental results of the sheet-pile retaining structure subjected to liquefaction-induced lateral spreading. Overall, this comprehensive approach enables a realistic evaluation of the performance of equivalent sheet-pile retaining structures under conditions of seismically-induced liquefaction, as well as other relevant scenarios.

An optimization case study for solving a transport robot scheduling problem on quantum-hybrid and quantum-inspired hardware

We present a comprehensive case study comparing the performance of D-Waves’ quantum-classical hybrid framework, Fujitsu’s quantum-inspired digital annealer, and Gurobi’s state-of-the-art classical solver in solving a transport robot scheduling problem. This problem originates from an industrially relevant real-world scenario. We provide three different models for our problem following different design philosophies. In our benchmark, we focus on the solution quality and end-to-end runtime of different model and solver combinations. We find promising results for the digital annealer and some opportunities for the hybrid quantum annealer in direct comparison with Gurobi. Our study provides insights into the workflow for solving an application-oriented optimization problem with different strategies, and can be useful for evaluating the strengths and weaknesses of different approaches.

Flexural strength estimation in edge-damaged silicate glass plates by combined phase-field and visual analysis

The state-of-the-art fractographic guidelines for glasses and fine ceramics, ASTM C1678, are only applicable to limited fracture scenarios. This work outlines a new method to analyze fracture scenarios outside ASTM C1678′s scope. The proposed methodology consists of a two-step process: initially, optical images of the fracture surfaces are obtained, and visual analysis is used to highlight the characteristic fractographic features. Next, the selected features are automatically compared to a baseline set of virtual fracture patterns tailored to any relevant fracture scenarios obtained by numerical phase-field simulations. As validation, scenarios with fractures originating at the glass plates’ edges for both sharp and chamfered corners were analyzed. Strength estimates within 6% of experimental results were achieved with the proposed method. In the future, this technique could be implemented to carry out fractographic analysis on brittle components of arbitrary shapes and loadings, hence substantially extending the application range and accuracy of fractographic methods.

Outdoor Microclimate in Courtyard Buildings: Impact of Building Perimeter Configuration and Tree Density

As the effects of climate change and urbanisation intensify, liveability and comfort in outdoor spaces decrease. Because of large spaces exposed to solar radiation and low crossing of airflows, courtyard buildings are extremely vulnerable in this regard. However, there are significant gaps in the literature on outdoor comfort in courtyards, especially regarding the effect of border configuration (including gap position and features), as well that of tree density. The study proposes a methodology—to be used during preliminary design—to compare the effect of alternative scenarios for courtyard buildings on outdoor microclimate, varying both the building perimeter configuration and courtyard vegetation layout. A matrix is set to combine the two variables and select relevant scenarios, which are then simulated in ENVI-met focusing on air temperature, wind speed and physiological equivalent temperature (PET). A case study in Bologna, Italy (humid subtropical climate) is presented as an example of the implementation. The resulting outdoor microclimate maps and frequency diagrams are compared and discussed. It emerges that both variables have a role in outdoor comfort: while gap configuration affects air temperature more (up to a difference of 1 °C), tree density impacts PET by up to 2 °C difference. The methodology can be replicated in several other contexts to support the optimisation of courtyard building design from the early stages.

Promoting primary healthcare services resilience with chronic disease management digitalization: a foresight study in the Lisbon health region

Abstract Background Due to the pressure on health systems, the COVID-19 Pandemic forced administrators to rapidly harness and integrate existing technology to manage access of patients with chronic diseases to Primary Health Care (PHC) in Portugal. Studies show that one of the most important areas for improvement is the sustainability of artefacts after the implementation phase, which depends on the successful implementation of digital transformation. As such, this study aims to assess the impact and influence of digitalization of PHC to settle a set of actions to be taken so that implementation is carried out more effectively and to support evidence-based policy-making in a PHC Unit located in the peripheral area of Lisbon. Methods This study followed a collaborative foresight approach using a scenario development methodology proposed by Lapão and Thore, divided into three stages: understanding the context, developing scenarios, and their analysis. These steps were achieved by conducting focus groups using the thematic brainstorming approach to analyse strategic and operational scenarios within ten years (between 2022 and 2032). Results Considering the influence of digitalization of PHC in the next ten years, three relevant and plausible scenarios were developed: ‘Digital PHC and active patients’, ‘NHS transition’ and ‘Climate exigency’. Combining innovation skills to establish digital services with improved governance policies has shown significant benefits toward the goals of more patient-centred care. Conclusions The collaborative reflection process throughout the study made the different stakeholders identify and understand the impact of the essential measures to be taken in different scenarios, allowing the digitalization of PHCs to be implemented more effectively, enabling the sustainability of the National Health Service in the Lisbon region, which has only been discussed so far at a limited and theoretical level.

Prescribing statin therapy in physically (in)active individuals vs prescribing physical activity in statin-treated patients: A four-scenario practical approach

Statins are among the most commonly prescribed medications worldwide. Statin-associated muscle symptoms (SAMS) represent a frequent statin-related adverse effect associated with statin discontinuation and increased cardiovascular disease (CVD) events. Emerging evidence indicate that the majority of SAMS might not be actually caused by statins, and the nocebo/drucebo effect (i.e. adverse effects caused by negative expectations) might also explain SAMS. Physical activity (PA) is a cornerstone in the management of CVD risk. However, evidence of increased creatine-kinase levels in statin-treated athletes exposed to a marathon has been generalized, at least to some extent, to the general population and other types of PA. This generalization is likely inappropriate and might induce fear around PA in statin users. In addition, the guidelines for lipid management focus on aerobic PA while the potential of reducing sedentary behavior and undertaking resistance training have been overlooked. The aim of this report is to provide a novel proposal for the concurrent prescription of statin therapy and PA addressing the most common and clinically relevant scenarios by simultaneously considering the different stages of statin therapy and the history of PA. These scenarios include i) statin therapy initiation in physically inactive patients, ii) PA/exercise initiation in statin-treated patients, iii) statin therapy initiation in physically active patients, and iv) statin therapy in athletes and very active individuals performing SAMS-risky activities.

A robotic venous leg ulcer system reveals the benefits of negative pressure wound therapy in effective fluid handling.

We applied a market-leading, single-use negative pressure wound therapy device to a robotic venous leg ulcer system and compared its fluid handling performance with that of standard of care, superabsorbent and foam dressings and compression therapy. For each tested product, we determined a metrics of retained, residual, evaporated and (potential) leaked fluid shares, for three exudate flow regimes representing different possible clinically relevant scenarios. The single-use negative pressure wound therapy system under investigation emerged as the leading treatment option in the aspects of adequate fluid handling and consistent delivery of therapeutic-level wound-bed pressures. The superabsorbent dressing performed reasonably in fluid handling (resulting in some pooling but no leakage), however, it quickly caused excessive wound-bed pressures due to swelling, after less than a day of simulated use. The foam dressing exhibited the poorest fluid handling performance, that is, pooling in the wound-bed as well as occasional leakage, indicating potential inflammation and peri-wound skin maceration risks under real-world clinical use conditions. These laboratory findings highlight the importance of advanced robotic technology as contemporary means to simulate patient and wound behaviours and inform selection of wound care technologies and products, in ways that are impossible to achieve if relying solely on clinical trials and experience.

Efficient Tropical Cyclone Scenario Selection Based on Cumulative Likelihood of Potential Impacts

AbstractThe incidence of climate‐related disasters is on the rise, which makes it imperative to intensify anticipatory action. Tropical cyclones (TC) bring extreme precipitation and storm surge to coastal areas. This poses a compound flood risk to coastal communities due to the coincidence/concurrence of multiple flood drivers. In the absence of sufficient spatiotemporal coverage of historic TC data, appropriate characterization of compound flood risk mainly relies on running a large number of synthetic scenarios with the hope that it covers the wide range of potential threats posed to a coastal community. Such an approach requires huge computational resources that make it infeasible in many cases. Here, we propose a dependence‐informed sampling scheme that helps reduce the dimensionality of the problem and systematically select a handful of scenarios with the largest Cumulative Likelihood of Potential Impact (CLPI). The CLPI is a compound flood index that ranks the candidate storms with the potential to cause compound flooding based on the regional dependencies between forcing (wind and rainfall) and coastal flooding drivers (storm surge and runoff). The analysis of historic TC records near the coast of Texas, USA shows the usefulness of CLPI in improving the efficiency of hazard risk assessment and providing reliable information at a lower cost. The proposed CLPI successfully ranks candidate hurricane scenarios based on their potential impact and filters out the less relevant scenarios without the need for detailed hydrodynamic simulation.

Paving the road towards ITER relevant long deuterium pulses at ELISE by investigating improved operational scenarios

Hydrogen plasma pulses of 1000 s with an extracted current density of over 90 % of the ITER target value (while also fulfilling the requirements for the electron-ion ratio and the global top/bottom beam homogeneity) were demonstrated at the ELISE test facility with its half ITER-size negative hydrogen ion source in pulsed extraction mode, i.e. short beam extraction phases of ≈10 s each ≈150 s, and using the so-called potential rods. In deuterium roughly 67 % of the ITER target for the extracted current density has been achieved for pulses longer than 45 minutes, limited by a pronounced vertical asymmetry and increase with timeinthe co-extracted electron current.In order to stabilize the co-extracted electron current during long pulses, particularly in deuterium, improved operational scenarios have to be developed. At ELISE, it was investigated the possibility to remove the potential rods and instead to set the bias plate to a positive voltage with respect to the source vessel. In this operational scenario short pulses in deuterium can be achieved with an extracted negative ion current density of up to 90 % of the ITER target value.In order to improve the physics insight, a 2D fluid code is applied. The first general result is that the modified potentials of surfaces close to the extraction system strongly affect the fluxes of charged particles towards different surfaces and consequently can result in a reduction of the co-extracted electron current.The temporal behaviour during long pulses with pulsed extraction, in particular of the co-extracted electrons, demonstrates a significant impact of the beam extraction on the caesium dynamics. Thus, CW extraction is mandatory for developing fully ITER relevant operational scenarios. After an extensive upgrade, ELISE is now capable of performing CW pulses, i.e. long-pulse beam extraction.

Intelligent Connectivity Through RIS-Assisted Wireless Communication: Exact Performance Analysis With Phase Errors and Mobility

The current research offers only approximations for evaluating the performance of wireless systems that use reconfigurable intelligent surfaces (RIS) over generalized fading channels with phase error caused by imperfect phase compensation at the RIS. This paper presents an exact analysis of RIS-assisted vehicular communication considering uniformly distributed phase error and generalized fading channels with a coherent combining of received signals reflected by RIS elements and direct transmissions from the source terminal. We use a generalized- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$K$</tex-math></inline-formula> shadowed distribution for the direct link and asymmetrical channels for the RIS-assisted transmission with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\kappa$</tex-math></inline-formula> - <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mu$</tex-math></inline-formula> distribution for the first link and double generalized Gamma (dGG) distribution for the second link, combined with a statistical random waypoint (RWP) model for the moving vehicle. We employ a novel approach to represent the probability density function (PDF) and cumulative distribution function (CDF) of the resultant channel in terms of a single univariate Fox-H function and use the multivariate Fox-H approach to develop an exact statistical analysis of the end-to-end signal-to-noise ratio (SNR) for the RIS-assisted system. We also use the inequality between the arithmetic and geometric means to simplify the statistical results of the considered system in terms of the univariate Fox-H function. Our analysis also provides exact, upper bound, and asymptotic expressions of the outage probability and average bit-error-rate (BER) performance using the derived density and distribution functions. We conduct computer simulations in various practically relevant scenarios to assert that mitigating phase errors is achievable by augmenting the number of elements in the RIS module and employing a higher quantization level.

Characterization of Biology-Guided Radiotherapy Accuracy as a Function of PET Tracer Uptake

To characterize the tracking capability and dosimetric accuracy of biology-guided radiotherapy (BgRT) under clinically relevant PET tracer uptake scenarios relative to the background. A custom-made anthropomorphic phantom filled with a liquid 18F-FDG solution including two embedded fillable 22 mm diameter spherical structures mimicking GTV (= CTV) and OAR was coupled to motion stages to create an independent 3D respiratory motion with 22 mm maximum range for target and a 5 mm 1D sinusoidal motion in the OAR. The biology-tracking zone (BTZ) was generated by adding 5 mm margin to the motion extent. The three BgRT scenarios studied were representative of tumors with good (8:1), borderline (4:1) and undesired (2:1) PET biodistributions compared to background. The clinical safety limit of BgRT uses Activity Concentration within the BTZ (AC ≥ 5 kBq/ml) and Normalized Target Signal as a contrast metric (NTS ≧ 2.7 for planning and ≧ 2 for delivery). The BgRT deliveries were repeated 3 times with radiochromic film and integrated ion chamber capturing the target and OAR doses. Tracked dosimetry was assessed using a margin-loss calculation defined as the maximum linear difference in distance between the planned and delivered 97% prescription iso-dose lines. The imaging-only PET images used to create BgRT plans had an AC of 7.0, 5.3, and 1.6 kBq/ml with an NTS of 6.8, 5.3, and 1.8 for 8:1, 4:1, and 2:1 concentrations, respectively. Qualitatively, the target was not visible on the planning PET images 2:1 loading scenario. At delivery, the mean pre-scan activity concentrations were 6.8, 4.7, and 3.7 kBq/ml with corresponding mean NTS of 3.7, 2.6, 1.5 for 8:1, 4:1 and 2:1 deliveries. The pre-scan values of AC or NTS did not satisfy the clinical system safety limits for 4:1 and 2:1 ratio experiments, but the engineering software allowed for the delivery to capture the resulting doses. The deliveries showed a prescription dose coverage to the CTV of 100% for the 8:1 and 4:1 cases, but 88% for the 2:1 case. When compared to the planned dose values, the delivered minimum doses were -7.6%, -8.6% and -10.9%, whereas the maximum dose differences in CTV were 1.2%, 0% and -4.8% of the planned dose distributions of the 8:1, 4:1 and 2:1 cases, respectively. Calculated margin losses were -2.3, -3.8, and -5.5 mm, for the 8:1, 4:1, and 2:1 cases, respectively. The maximum OAR doses were less than the maximum doses predicted on the bounded DVH curves for all scenarios. With sufficient tracer uptake in the target, BgRT can deliver tracked dosimetry for targets with a large respiratory motion profile. Both the good BgRT candidate and borderline cases produced clinically acceptable delivered doses, even though the borderline case was flagged by the clinical system safety checks. As expected, the delivered BgRT dose distributions were suboptimal with reduced tumor over background PET contrast.

Coupling Mountain Pine Beetle and Forest Population Dynamics Predicts Transient Outbreaks that are Likely to Increase in Number with Climate Change.

Mountain pine beetle (MPB) in Canada have spread well beyond their historical range. Accurate modelling of the long-term dynamics of MPB is critical for assessing the risk of further expansion and informing management strategies, particularly in the context of climate change and variable forest resilience. Most previous models have focused on capturing a single outbreak without tree replacement. While these models are useful for understanding MPB biology and outbreak dynamics, they cannot accurately model long-term forest dynamics. Past models that incorporate forest growth tend to simplify beetle dynamics. We present a new model that couples forest growth to MPB population dynamics and accurately captures key aspects of MPB biology, including a threshold for the number of beetles needed to overcome tree defenses and beetle aggregation that facilitates mass attacks. These mechanisms lead to a demographic Allee effect, which is known to be important in beetle population dynamics. We show that as forest resilience decreases, a fold bifurcation emerges and there is a stable fixed point with a non-zero MPB population. We derive conditions for the existence of this equilibrium. We then simulate biologically relevant scenarios and show that the beetle population approaches this equilibrium with transient boom and bust cycles with period related to the time of forest recovery. As forest resilience decreases, the Allee threshold also decreases. Thus, if host resilience decreases under climate change, for example under increased stress from drought, then the lower Allee threshold makes transient outbreaks more likely to occur in the future.

An Optimization Method of Deep Transfer Learning for Vegetation Segmentation under Rainy and Dry Season Differences in a Dry Thermal Valley.

Deep learning networks might require re-training for different datasets, consuming significant manual labeling and training time. Transfer learning uses little new data and training time to enable pre-trained network segmentation in relevant scenarios (e.g., different vegetation images in rainy and dry seasons); however, existing transfer learning methods lack systematicity and controllability. So, an MTPI method (Maximum Transfer Potential Index method) was proposed to find the optimal conditions in data and feature quantity for transfer learning (MTPI conditions) in this study. The four pre-trained deep networks (Seg-Net (Semantic Segmentation Networks), FCN (Fully Convolutional Networks), Mobile net v2, and Res-Net 50 (Residual Network)) using the rainy season dataset showed that Res-Net 50 had the best accuracy with 93.58% and an WIoU (weight Intersection over Union) of 88.14%, most worthy to transfer training in vegetation segmentation. By obtaining each layer's TPI performance (Transfer Potential Index) of the pre-trained Res-Net 50, the MTPI method results show that the 1000-TDS and 37-TP were estimated as the best training speed with the smallest dataset and a small error risk. The MTPI transfer learning results show 91.56% accuracy and 84.86% WIoU with 90% new dataset reduction and 90% iteration reduction, which is informative for deep networks in segmentation tasks between complex vegetation scenes.

Relationship Between the Living Standards and the Birth Rate of the Population in Russian Regions

The assessment of the competitiveness of the development of countries and regions in the 21st century is measured by how dignified, safe and comfortable the population of the country lives. Russia is no exception, therefore, it faces strategically important tasks of achieving the highest level and quality of life for people in order to save people, increase life expectancy, and ensure natural and migration population growth. The article reveals the theoretical and practical aspects of the modern understanding of the category «standard of living», the relationship of this category with the category «quality of life», on this basis, statistical indicators of the economic well-being of the population of Russian regions, especially the Republic of North Ossetia-Alania, are analyzed. The results of the analysis are supplemented by data from public opinion polls on the standard of living and incomes of the population in the country for the period 2022-2023. residents of the country and the Republic of North Ossetia-Alania. The hypothesis posed about the relationship between the standard of living and the birth rate of the population in the regions of Russia is also confirmed by the methods of mathematical modeling. Based on the results of the study, the following conclusions were drawn: 1) for the purposes of scientific analysis and development of relevant scenario forecasts for the development of economic and demographic and reverse demographic and economic processes, a systematic approach based on a complex combination of objective (quantitative) data and subjective (qualitative) assessments should be applied; 2) large-scale studies of public opinion, comparison of ratings and economic and mathematical modeling show an unambiguous relationship between the income level of the population of Russian regions and the birth rate in these regions. The limitation of these conclusions is the national regions of Russia, in which the birth rate is determined to a large extent by the preserved customs of a large family and traditional family values. This allows us to conclude that the strengthening of the institution of the family, the development of the spiritual values of the population, coupled with an increase in the standard of living, is the only possible scenario for saving Russia’s people.

Developmental and reproductive toxicity hazard characterization of 2-amino-2-methyl-1-propanol (AMP).

2-Amino-2-methyl-1-propanol (AMP™) is a widely used pH stabilizer in personal care products (PCPs); thus, the safety implications of dermal AMP exposure remain of interest. We have previously reported that exposure to AMP in PCPs when used as intended is not anticipated to result in an increased risk of hepatotoxicity (primarily steatosis and altered phospholipid homeostasis). The current study focuses on AMP in PCP's potential for developmental and reproductive toxicity (DART) in humans, based on data from animal studies. Animal studies suggest that exposure to AMP can result in post-implantation loss. However, such effects occur at maternally toxic doses, posing a challenge for determining appropriate hazard classifications in the context of relevant consumer use scenarios. Our assessment concluded that human exposure to AMP in PCPs is not anticipated to result in DART at non-maternally toxic doses. Further, mode of action (MOA) analysis elucidated the potential biological pathways underlying DART effects observed in high-dose animal studies, such that perturbation of uterine choline synthesis was the most well-supported MOA hypothesis. Downstream uterine effects might reflect choline-dependent changes in epigenetic control of pathways important for implantation maintenance and uterine cell energetics. Since AMP-induced post-implantation loss occurs at doses higher than pathology related to liver toxicity, maintaining AMP exposures from exceeding the onset dose for maternal liver effects will also be protective of DART effects. Furthermore, dermal exposure to AMP expected from the use of PCPs is highly unlikely to result in toxicologically significant systemic AMP concentrations; thus, DART is not anticipated.