Single Driver Research Articles

The role of compound climate and weather extreme events in creating socio-economic impacts in South Florida

Natural hazards such as hurricanes, floods, and wildfires cause devastating socio-economic impacts on communities. In South Florida, most of these hazards are becoming increasingly frequent and severe because of the warming climate, and changes in vulnerability and exposure, resulting in significant damage to infrastructure, homes, and businesses. To better understand the drivers of these impacts, we developed a bottom-up impact-based methodology that takes into account all relevant drivers for different types of hazards. We identify the specific drivers that co-occurred with socio-economic impacts and determine whether these extreme events were caused by single or multiple hydrometeorological drivers (i.e., compound events). We consider six types of natural hazards: hurricanes, severe storm/thunderstorms, floods, heatwaves, wildfire, and winter weather. Using historical, socio-economic loss data along with observations and reanalysis data for hydrometeorological drivers, we analyze how often these drivers contributed to the impacts of natural hazards in South Florida. We find that for each type of hazard, the relative importance of the drivers varies depending on the severity of the event. For example, wind speed is a key driver of the socio-economic impacts of hurricanes, while precipitation is a key driver of the impacts of flooding. We find that most of the high-impact events in South Florida were compound events, where multiple drivers contributed to the occurrences and impacts of the events. For example, more than 50% of the recorded flooding events were compound events and these contributed to 99% of total property damages and 98% of total crop damages associated with flooding in Miami-Dade County. Our results provide valuable insights into the drivers of natural hazard impacts in South Florida and can inform the development of more effective risk reduction strategies for improving the preparedness and resilience of the region against extreme events. Our bottom-up impact-based methodology can be applied to other regions and hazard types, allowing for more comprehensive and accurate assessments of the impacts of compound hazards.

A Phase 2 Study of Canakinumab in Patients with Lower-Risk Myelodysplastic Syndromes or Chronic Myelomonocytic Leukemia

Background Myelodysplastic syndromes (MDS) lie on a continuum of myeloid neoplastic progression between clonal hematopoiesis (CH) and acute myeloid leukemia (AML). Interleukin 1 beta (IL-1β)-induced inflammasome activation is a mechanism of cancer initiation and progression. Given that IL-1β upregulation induces aberrant myeloid differentiation of hematopoietic stem and progenitor cells (HSPCs), we hypothesize that IL-1β plays a critical role in MDS pathogenesis, and targeting IL-1β signaling will overcome aberrant MDS HSPCs' myeloid skewing. Here, we report final results of a phase 2 study evaluating the safety and efficacy of canakinumab, an IL-1β inhibitor, in patients with lower-risk MDS or chronic myelomonocytic leukemia (CMML). Methods We conducted a single center, open-label phase 2 trial at The University of Texas MD Anderson Cancer Center (Houston, TX, USA). Patients aged ≥ 18 with IPSS-R ≤ 3.5 MDS/CMML who have previously been treated were included in the study. Patients received 300 mg of canakinumab on day 1 of a 4-week cycle. The primary objective was to determine the clinical activity of canakinumab in MDS/CMML patients. Response was assessed using the modified International Working Group 2006 criteria for MDS (Cheson et al. 2006). Secondary objectives were to evaluate the safety profile including rate of transfusion independence (TI), duration of response (DoR), progression-free survival (PFS), and overall survival (OS). All patients who received 1 dose of study drug were included in the analyses. This study is registered with ClinicalTrials.gov (NCT04239157). Findings Between August 2020 and May 2023, 27 patients were enrolled in the phase 2 portion of this study, and 2 patients failed screening. The median age was 74 years with 15 (60%) male patients; 20 patients (80%) were post-hypomethylating agent failure with a median number of prior lines of therapy of 2 (1-5). Transfusion dependency was observed in 24 patients (96%) prior to canakinumab initiation. Fourteen (56%) patients showed normal karyotype. IPSS-R stratification revealed an intermediate-2 risk in 12 (48%) patients and a high risk in one (4%). The most common mutations were SF3B1 (40%), TET2 (32%), DNMT3A (28%), and RUNX1 (24%). IPSS -M risk score was calculated for 24 cases showing one (4%) very low (VL), four (16%) low (L), 14 (16%) moderate low (ML), eight (32%) moderate high (MH), five (20%) high (H), and two (8%) very high (VH) risk categories. Canakinumab was well tolerated and no drug-related toxicities were observed. One death due to sepsis, which was deemed not treatment-related, occurred on the study drug. Out of 23 evaluable patients, the overall response rate was 17·4%, with erythroid and platelet hematological improvement (HI-E and HI-P, respectively) confirmed in 3 (13.0%) patients and 1 (4.3%) patient, respectively. Thirteen patients had stable disease (56·5%) and 6 (26·1%) progressed during therapy, 1 of which transformed to AML (Fig. 1). TI was achieved in 3 patients (median DoR 8·53 months (95% CI 0·41-16·1) and 2 of them maintained TI for over 12 months. With a median follow-up time of 22·6 months (95% CI 15·0-29·4), median OS was 17·3 months (95% CI 14·3-not estimable). We performed separate univariate analyses to evaluate any associations between the IPSS-M and OS/PFS. The median OS in patients with higher-risk MDS by IPSS-M (MH, H, VH) was 15·0 months vs 29·4 months in the lower-risk disease by IPSS-M (VL, L, ML) group (p=0·12). Interestingly, statistically significant findings were observed with 1-year PFS when stratifying patients into higher vs lower risk MDS by IPSS-M (64·3% vs 100·0%, respectively; p=0·022, Fig. 2). Conclusion In this cohort of MDS patients who had experienced multiple lines of prior therapy and exhibited high-molecular-complexity, canakinumab showed limited efficacy (HI 17.3%). Nevertheless, canakinumab showed a good safety profile and yielded sustained long-term responses in patients with single somatic driver mutation in TET2 or DNMT3A. This suggests that clonal complexity, and therefore disease burden, may be a determining factor in response to canakinumab. Therefore, we have amended the protocol of a phase 1/2 clinical trial evaluating the safety and activity of canakinumab in clonal cytopenia of unknown significance (CCUS) and low-molecular complexity MDS patients. Our results will clarify the role of IL-1β signaling in MDS initiation and progression.

Microbiome and photoperiod interactively determine thermal sensitivity of polar and temperate diatoms.

The effect of temperature on ectothermic organisms in the context of climate change has long been considered in isolation (i.e. as a single driver). This is challenged by observations demonstrating that temperature-dependent growth is correlated to further factors. However, little is known how the chronobiological history of an organism reflected in its adaptation to re-occurring cyclic patterns in its environment (e.g. annual range of photoperiods in its habitat) and biotic interactions with its microbiome, contribute to shaping its realized niche. To address this, we conducted a full-factorial microcosm multi-stressor experiment with the marine diatoms Thalassiosira gravida (polar) and Thalassiosira rotula (temperate) across multiple levels of temperature (4°C; 9°C; 13.5°C) and photoperiod (4 h; 16 h; 24 h), both in the presence or absence of their microbiomes. While temperature-dependent growth of the temperate diatom was constrained by short and long photoperiods, the polar diatom coped with a 24 h photoperiod up to its thermal optimum (9°C). The algal microbiomes particularly supported host growth at the margins of their respective fundamental niches except for the combination of the warmest temperature tested at 24 h photoperiod. Overall, this study demonstrates that temperature tolerances may have evolved interactively and that the mutualistic effect of the microbiome can only be determined once the multifactorial abiotic niche is defined.

What drives health care spending in Switzerland? Findings from a decomposition by disease, health service, sex, and age

BackgroundHigh and increasing spending dominates the public discussion on healthcare in Switzerland. However, the drivers of the spending increase are poorly understood. This study decomposes health care spending by diseases and other perspectives and estimates the contribution of single cost drivers to overall healthcare spending growth in Switzerland between 2012 and 2017.MethodsWe decompose total healthcare spending according to National Health Accounts by 48 major diseases, injuries, and other conditions, 20 health services, 21 age groups, and sex of patients. This decomposition is based on micro-data from a multitude of data sources such as the hospital inpatient registry, health and accident insurance claims data, and population surveys. We identify the contribution of four main drivers of spending: population growth, change in population structure (age/sex distribution), changes in disease prevalence, and changes in spending per prevalent patient.ResultsMental disorders were the most expensive major disease group in both 2012 and 2017, followed by musculoskeletal disorders and neurological disorders. Total health care spending increased by 19.7% between 2012 and 2017. An increase in spending per prevalent patient was the most important spending driver (43.5% of total increase), followed by changes in population size (29.8%), in population structure (14.5%), and in disease prevalence (12.2%).ConclusionsA large part of the recent health care spending growth in Switzerland was associated with increases in spending per patient. This may indicate an increase in the treatment intensity. Future research should show if the spending increases were cost-effective.

Comparative changes in seasonal marine heatwaves and cold spells over the Tropical Indian Ocean during recent decades and disentangling the drivers of highly intense events

AbstractThe unprecedented increase in the Sea Surface Temperature (SST) in the warming climate yield stress to the system and pose severe threats to the marine ecosystem. Marine Heatwaves (MHWs) and Marine Cold Spells (MCSs) are two extreme events related to SST variability. For better management of ocean productivity, marine ecosystem, marine services, and fisheries, the understanding of seasonal discrepancies rather than annual documentation of MHWs and MCSs metrics is more utilitarian. This study documents the decadal changes in the MHWs and MCSs over the Tropical Indian Ocean (TIO) for all seasons. Additionally, highly intense events (based on intensity and duration) are identified and demonstrate the associated drivers. During the past two decades (1982–1990, 1991–2000), the MCSs were more frequent than MHWs in every season. However, in the recent two decades (2001–2010, 2011–2020), TIO become more prone to MHWs with considerably more frequent and prolonged events in JJAS months. Moreover, MCSs are disappearing from the TIO. It was noted that the choice of baseline period has an impact on the magnitude of MHWs and MCSs changes, but the spatial pattern (regions with high/low magnitude MHWs and MCSs) stays fairly constant in all baseline period sensitivity checks. The investigation of highly intense events reveals that MHWs and MCSs are produced and sustained by the same drivers when they are at their opposing edges. In general, the coherence effort from winds, net heat fluxes (shortwave radiation, longwave radiation, latent heat flux, and sensible heat flux), mixed level depth, and mean sea level pressure contribute to the genesis of seasonal MHWs or MCSs events. Additionally, in some cases, a single driver (e.g., wind) may also play a crucial role in these extreme events. The remote climate modes of variability, such as El Niño–Southern Oscillation, also contribute significantly to the MHWs and MCSs. El Niño (La Niña) events not only increase the spatial coverage of MHWs (MCSs) but also increases the intensity.

Extreme and compound ocean events are key drivers of projected low pelagic fish biomass.

Ocean extreme events, such as marine heatwaves, can have harmful impacts on marine ecosystems. Understanding the risks posed by such extreme events is key to develop strategies to predict and mitigate their effects. However, the underlying ocean conditions driving severe impacts on marine ecosystems are complex and often unknown as risks to marine ecosystems arise not only from hazards but also from the interactions between hazards, exposure and vulnerability. Marine ecosystems may not be impacted by extreme events in single drivers but rather by the compounding effects of moderate ocean anomalies. Here, we employ an ensemble climate-impact modeling approach that combines a global marine fish model with output from a large ensemble simulation of an Earth system model, to identify the key ocean ecosystem drivers associated with the most severe impacts on the total biomass of 326 pelagic fish species. We show that low net primary productivity is the most influential driver of extremely low fish biomass over 68% of the ocean area considered by the model, especially in the subtropics and the mid-latitudes, followed by high temperature and low oxygen in the eastern equatorial Pacific and the high latitudes. Severe biomass loss is generally driven by extreme anomalies in at least one ocean ecosystem driver, except in the tropics, where a combination of moderate ocean anomalies is sufficient to drive extreme impacts. Single moderate anomalies never drive extremely low fish biomass. Compound events with either moderate or extreme ocean conditions are a necessary condition for extremely low fish biomass over 78% of the global ocean, and compound events with at least one extreme variable are a necessary condition over 61% of the global ocean. Overall, our model results highlight the crucial role of extreme and compound events in driving severe impacts on pelagic marine ecosystems.

Mutations in genes related to myocyte contraction and ventricular septum development in non-syndromic tetralogy of Fallot.

Eighty percent of patients with a diagnosis of tetralogy of Fallot (TOF) do not have a known genetic etiology or syndrome. We sought to identify key molecular pathways and biological processes that are enriched in non-syndromic TOF, the most common form of cyanotic congenital heart disease, rather than single driver genes to elucidate the pathogenesis of this disease. We undertook exome sequencing of 362 probands with non-syndromic TOF and their parents within the Pediatric Cardiac Genomics Consortium (PCGC). We identified rare (minor allele frequency <1 × 10-4), de novo variants to ascertain pathways and processes affected in this population to better understand TOF pathogenesis. Pathways and biological processes enriched in the PCGC TOF cohort were compared to 317 controls without heart defects (and their parents) from the Simons Foundation Autism Research Initiative (SFARI). A total of 120 variants in 117 genes were identified as most likely to be deleterious, with CHD7, CLUH, UNC13C, and WASHC5 identified in two probands each. Gene ontology analyses of these variants using multiple bioinformatic tools demonstrated significant enrichment in processes including cell cycle progression, chromatin remodeling, myocyte contraction and calcium transport, and development of the ventricular septum and ventricle. There was also a significant enrichment of target genes of SOX9, which is critical in second heart field development and whose loss results in membranous ventricular septal defects related to disruption of the proximal outlet septum. None of these processes was significantly enriched in the SFARI control cohort. Innate molecular defects in cardiac progenitor cells and genes related to their viability and contractile function appear central to non-syndromic TOF pathogenesis. Future research utilizing our results is likely to have significant implications in stratification of TOF patients and delivery of personalized clinical care.

SynLight: a bicistronic strategy for simultaneous active zone and cell labeling in the Drosophila nervous system.

At synapses, chemical neurotransmission mediates the exchange of information between neurons, leading to complex movement, behaviors, and stimulus processing. The immense number and variety of neurons within the nervous system make discerning individual neuron populations difficult, necessitating the development of advanced neuronal labeling techniques. In Drosophila, Bruchpilot-Short and mCD8-GFP, which label presynaptic active zones and neuronal membranes, respectively, have been widely used to study synapse development and organization. This labeling is often achieved via the expression of 2 independent constructs by a single binary expression system, but expression can weaken when multiple transgenes are expressed by a single driver. Recent work has sought to circumvent these drawbacks by developing methods that encode multiple proteins from a single transcript. Self-cleaving peptides, specifically 2A peptides, have emerged as effective sequences for accomplishing this task. We leveraged 2A ribosomal skipping peptides to engineer a construct that produces both Bruchpilot-Short-mStraw and mCD8-GFP from the same mRNA, which we named SynLight. Using SynLight, we visualized the putative synaptic active zones and membranes of multiple classes of olfactory, visual, and motor neurons and observed the correct separation of signal, confirming that both proteins are being generated separately. Furthermore, we demonstrate proof of principle by quantifying synaptic puncta number and neurite volume in olfactory neurons and finding no difference between the synapse densities of neurons expressing SynLight or neurons expressing both transgenes separately. At the neuromuscular junction, we determined that the synaptic puncta number labeled by SynLight was comparable to the endogenous puncta labeled by antibody staining. Overall, SynLight is a versatile tool for examining synapse density in any nervous system region of interest and allows new questions to be answered about synaptic development and organization.

Case Series of Soft Tissue Sarcoma Patients with Brain Metastasis with Implications from Genomic and Transcriptomic Analysis.

Brain metastasis rarely occurs in soft tissue sarcoma (STS). Here, we present five cases of STS with brain metastases with genetic profiles. We included five patients from Seoul National University Hospital who were diagnosed with STS with metastasis to the brain. Tissue from the brain metastasis along with that from the primary site or other metastases were used for DNA and RNA sequencing to identify genetic profiles. Gene expression profiles were compared with sarcoma samples from The Cancer Genome Atlas. The overall survival after diagnosis of brain metastasis ranged from 2.2 to 34.3 months. Comparison of mutational profiles between brain metastases and matched primary or other metastatic samples showed similar profiles. In two patients, copy number variation profiles between brain metastasis and other tumors showed several differences including MYCL, JUN, MYC, and DDR2 amplification. Gene ontology analysis showed that the group of genes significantly highly expressed in the brain metastasis samples was enriched in the G-protein coupled receptor activity, structural constituent of chromatin, protein heterodimerization activity, and binding of DNA, RNA, and protein. Gene set enrichment analysis showed enrichment in the pathway of neuroactive ligand-receptor interaction and systemic lupus erythematosus. The five patients had variable ranges of clinical courses and outcomes. Genomic and transcriptomic analysis of STS with brain metastasis implicates possible involvement of complex expression modification and epigenetic changes rather than the addition of single driver gene alteration.

Nonlinear Flood Responses to Tide Level and Land Cover Changes in Small Watersheds

Regarding global warming, the threat of flooding is projected to increase due to the change in intensity and frequency of single drivers and amplification caused by multi-driver interactions. This interaction becomes more complicated in developing regions with rapidly changing land cover. As a result, demands on flood risk management are rising especially in small watersheds, which are more vulnerable to driver disturbances compared with large watersheds. Existing studies focused on large watersheds rather than small watersheds. However, the findings derived from large-scale analysis cannot be transferred to small watersheds directly. This research investigated the flood responses in the Yonghe River Watershed (YRW) (63.8 km2) in Guangzhou, China, considering the impact of land cover change. The YRW experienced a disastrous compound flood on 22 May 2020. A hydrodynamic model integrating the Hydrologic Engineering Center’s Hydrologic Modeling System and River Analysis System (HEC-HMS and HEC-RAS, respectively) was established and calibrated using the inundation depths observed during the flood. Model analysis using multiple scenarios showed that the watershed is river-dominated, and flood responses to the three factors are nonlinear but with different increasing rates. The response curves for tide levels and land cover changes increase faster at high values, whereas the rainfall intensity curves vary slightly. These findings highlight the importance of integrating tidal impacts into flood risk management, even in river-dominated coastal watersheds. The study further recommends that in small watersheds, 50% imperviousness is an indicator of the urgent demand for flood risk management measures.

CloneRate: fast estimation of single-cell clonal dynamics using coalescent theory.

While evolutionary approaches to medicine show promise, measuring evolution itself is difficult due to experimental constraints and the dynamic nature of body systems. In cancer evolution, continuous observation of clonal architecture is impossible, and longitudinal samples from multiple timepoints are rare. Increasingly available DNA sequencing datasets at single-cell resolution enable the reconstruction of past evolution using mutational history, allowing for a better understanding of dynamics prior to detectable disease. There is an unmet need for an accurate, fast, and easy-to-use method to quantify clone growth dynamics from these datasets. We derived methods based on coalescent theory for estimating the net growth rate of clones using either reconstructed phylogenies or the number of shared mutations. We applied and validated our analytical methods for estimating the net growth rate of clones, eliminating the need for complex simulations used in previous methods. When applied to hematopoietic data, we show that our estimates may have broad applications to improve mechanistic understanding and prognostic ability. Compared to clones with a single or unknown driver mutation, clones with multiple drivers have significantly increased growth rates (median 0.94 versus 0.25 per year; P = 1.6×10-6). Further, stratifying patients with a myeloproliferative neoplasm (MPN) by the growth rate of their fittest clone shows that higher growth rates are associated with shorter time to MPN diagnosis (median 13.9 versus 26.4 months; P = 0.0026). We developed a publicly available R package, cloneRate, to implement our methods (Package website: https://bdj34.github.io/cloneRate/). Source code: https://github.com/bdj34/cloneRate/.

Research on risk assessment method of subway driver driving fatigue based on AHP-FCE

Subway driver is one of the important factors in the "man-machine-environment" system of subway driving safety, which is of great significance to the safe operation of rail traffic. Based on the fatigue generation mechanism and previous experimental data, this paper establishes a risk assessment index system for subway driver driving fatigue including four elements: physiological, psychological, management and environmental factors based on systematic analysis of possible risks and influencing factors of driving fatigue. The Analytic Hierarchy Process (AHP) and Fuzzy Comprehensive Evaluation (FCE) were organically combined to establish a driving fatigue risk assessment model for subway drivers and obtain the driving fatigue risk level of subway drivers. Finally, through the case evaluation of a single driver on the main line of an existing operation line, it is found that the risk level of driving fatigue of the subway driver is general risk, and the AHP-FCE model has good adaptability and rationality, which has good application value for the study of driving fatigue of subway drivers.

Use of electrical measurements for non-invasive estimation of plasma electron density in the inductively coupled SPIDER ion source

SPIDER (source for the production of ions of deuterium extracted from RF plasma) is the full-scale prototype of the ITER neutral beam injector ion source. The plasma heating takes place inside eight drivers via inductive coupling, through the radiofrequency (RF) coil. To achieve optimum conditions during source operation it is necessary to know the plasma behavior under various operational conditions. One of the essential parameters is the plasma electron density. It is possible to experimentally measure this parameter and, currently, different methods are being explored, such as the estimations coming from a Langmuir probe and optical emission spectroscopy. However, these methods are either available for temporary measurements or require dedicated analyses with large uncertainties. In this regard, alternative, reliable, and fast diagnostic tools will be beneficial for the estimation of the order of magnitude of electron density inside the driver. Two models for the estimation of electron density are recalled, discussed, and further modified in this work: one is based on the classical power balance equation, and the other is recently described in the literature and relies on classical plasma conductivity. Both models use equivalent electrical parameters of the driver derived from available electrical measurements at the output of the RF generator and through the knowledge of the matching network and the transmission line length. This work explicitly focuses on the application of these models to estimate the plasma electron density in a single driver of SPIDER. Furthermore, the estimations are compared with the first experimental results obtained from temporary electrostatic probe measurements and are found to be in good agreement in terms of magnitude and trends.

Understanding the intricate tradeoffs among ecosystem services in the Beijing-Tianjin-Hebei urban agglomeration across spatiotemporal features

Revealing the intricate interactions between ecosystem services and their values is essential for the comprehensive management of diverse ecosystems. However, understanding tradeoffs among various ecosystem services and their influencing factors, especially at different spatial scales, remains challenging, primarily due to the difficulty in quantifying cultural services. In this study, we conducted a comprehensive analysis of the ecosystem service value (ESV) at both grid and county scales in the Beijing-Tianjin-Hebei urban agglomeration from 2000 to 2020, considering the representation of different ecosystem services. Our investigation aimed to elucidate tradeoffs among ecosystem services and identify key natural-social-economic-climate drivers. The key findings are as follows: (1) Over the study period, the overall ESV in the Beijing-Tianjin-Hebei urban agglomeration exhibited an upward trend, with regulation of waterflows, water body, and forest land making the largest contributions. (2) At the grid scale, there were 3 tradeoffs and 52 synergies among multiple ecosystem services in 2000, which increased to 18 tradeoffs in 2020, indicating a considerable degradation of numerous ecosystem services. Conversely, at the county scale, all ecosystem services exhibited a synergistic relationship. (3) The most significant synergistic effect was observed between regulation of waterflows and maintenance of soil fertility, while the most prominent tradeoff effect was identified between food production and waste treatment. (4) Social-economic factors exerted a more substantial influence on ESV, followed by climate factors, whereas the impact of natural factors was limited. GDP emerged as the primary single driver of total ESV, while farmland production potential played a crucial role in shaping the 11 ecosystem services. Notably, GDP-temperature and GDP-farmland production potential output were identified as the most influential dual factors. These findings underscore the importance of simultaneously enhancing economic development, controlling temperature rise, and improving food production as essential measures to enhance ESV.

A multiscale analysis of the spatially heterogeneous relationships between non-point source pollution-related processes and their main drivers in Chaohu Lake watershed, China.

A better understanding of the relationships between non-point source (NPS) pollution-related processes and their drivers will help to develop scientific watershed management measures. Although various studies have explored the drivers' impact on NPS pollution-related processes, quantitative knowledge of the properties within these relationships is still needed. This study uses the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model to produce three related processes of NPS pollution, quick flow (QF), nitrogen export (NE), and sediment export (SE), in the upstream watershed of Chaohu Lake, China. The spatial distributions of QF, NE, and SE and their responses to multiple natural-socioeconomic drivers at nine spatial scales (1 km2, 10 km2, 20 km2, 30 km2, 50 km2, 75 km2, 100 km2, 200 km2, and town) were compared. The results showed that the spatial scale has little impact on the spatial distributions of NPS pollution-related processes. Across the nine scales, the socioeconomic drivers related to agricultural activities, area proportions of cultivated land (cultivated) and paddy field (paddy), have dominant impacts on NE, while the topographical drivers, the connectivity index (IC) and slope, have dominant impacts on both SE and QF. The magnitudes of single and paired natural-socioeconomic drivers' impacts on NPS pollution-related processes increase logarithmically or linearly with increasing spatial scale, but they tend to reach a stable threshold at a certain coarse scale. Our results emphasized the necessity and importance of embracing spatial scale effects in watershed water environmental management.

The negative beam source with single driver for CRAFT NNBI: design and conditioning results

The Comprehensive Research Facility for Fusion Technology (CRAFT) is a large scientific facility that is preferentially deployed for the construction of major national science and technology infrastructures. A negative beam source based neutral beam injector (NNBI) with beam energy of 200–400 keV, beam power of 2 MW and beam duration of 100 s is one of the devices. A giant radio frequency (RF) based negative beam source was designed for the CRAFT NNBI system. In order to understand the physics and pre-study the engineering problems for RF negative beams source, several beam sources with different scales will be designed and tested. According to the R&D schedule, a negative beam source with a single driver was designed, developed and tested first. The single driver beam source is a quarter of the size of the full size negative beam source. It contains an RF driver, an expansion chamber and a negative ion accelerator with three electrodes, which are a plasma grid (PG), extraction grid (EG) and ground grid (GG). To enhance the negative ion production, Cesium is injected into the plasma chamber and a magnetic filter filed is produced by current flow through the PG to decrease the electron temperature. The negative beam source was tested on the test facility after assembly, including RF plasma generation, negative ion production, extraction and acceleration. The characteristic of plasma discharge, beam extraction and acceleration was studied without and with Cs injection. The long pulse of 105 seconds negative ion beam was achieved successfully. The extracted negative ion current is 4 A and the ratio of electron and negative ion is around 0.8. It lays a good foundation for the R&D of negative ion source with a multi-driver for the CRAFT NNBI system. The details of the design and experimental results of beam source was shown in this paper.

Warming and parasitism impair the performance of Baltic native and invasive macroalgae and their associated fauna

AbstractGlobal warming, bioinvasions, and parasitism affect single‐species performances and species interactions, substantially impacting the structure and stability of marine ecosystems. In light of accelerated global change, the information derived from studies focusing on single species and single drivers is insufficient, calling for a multi‐stressor approach under near‐natural conditions. We investigated the effects of warming (+3°C) on the performance of a benthic community composed of native and invasive macroalgae, consumers and a trematode parasite in a mesocosm setting. We also assessed the effects of warming and parasitism on the survival and growth of gastropods and mussels and the thermal dependency of trematode performance. Our findings show that warming and grazing by infected gastropods had a large detrimental effect on the invasive macroalga growth. Furthermore, the single and interactive effects of parasitism and warming were detrimental to intermediate host survival and growth, especially to large mussels. Finally, cercarial emergence positively correlated to the natural peaks of summer temperatures, while infection intensity in mussels was higher in larger individuals. Our findings suggest that grazing and warming will be detrimental to the invasive macroalga, favoring the native alga. Moreover, parasitism will enhance grazing, especially in summer, when higher temperatures trigger parasite development. However, parasite‐enhanced grazing may be buffered by higher mortality or a shift in the size of infected intermediate hosts under warming. Our findings demonstrate how complex effects of ocean warming can be on food webs and how they can be mediated by parasitism and, as a result, influence native and invasive macroalgae differently.

Design and Comparative Analysis of an Ultra-Highly Efficient, Compact Half-Bridge LLC Resonant GaN Converter for Low-Power Applications

For low-power applications, this paper presents the development and design of a compact and ultra-highly efficient half-bridge LLC resonant converter. By using Galium Nitride (GaN) devices and high-efficient magnetics, the efficiency and power density of resonant converters can be improved. Compared to Silicon MOSFETs, GaN high-electron-mobility transistors (GaN HEMT) have a lower output capacitance and gate charge, resulting in lower driving loss and shorter dead times. Consequently, the proposed LLC converter based on GaN devices has excellent performance characteristics such as ultra-high efficiency, low switching losses, compact size, high voltage endurance, high operating temperature and high operating frequency. Furthermore, the proposed resonant converter features soft switching properties that ensure that the switches and diodes on the primary side are always switched at zero voltage and current. By doing so, LLC resonant converter switching losses are significantly reduced by up to 3.1%, and an overall efficiency of 98.5% is achieved. The LLC resonant converter design with GaN HEMT has great advantages over Si MOSFET solution regarding efficiency, overall losses, switching loose and power factor correction. A 240 W, 240 V to 60 V half-bridge GaN HEMT LLC resonant converter is simulated with a switching frequency of 75 KHz, along with the comparative analysis of the Si metal oxide semiconductor field effect transistor (MOSFET) solution. Moreover, the design and analysis of highly efficient magnetics with a power factor of 0.99 at full load is presented. A 240-Watt single stage LED driver with power factor correction is also designed to verify and compare the performance of proposed LLC resonant converter.

Bus Travel Time Prediction Based on the Similarity in Drivers’ Driving Styles

Providing accurate and real-time bus travel time information is crucial for both passengers and public transportation managers. However, in the traditional bus travel time prediction model, due to the lack of consideration of the influence of different bus drivers’ driving styles on the bus travel time, the prediction result is not ideal. In the traditional bus travel time prediction model, the historical travel data of all drivers in the entire bus line are usually used for training and prediction. Due to great differences in individual driving styles, the eigenvalues of drivers’ driving parameters are widely distributed. Therefore, the prediction accuracy of the model trained by this dataset is low. At the same time, the training time of the model is too long due to the large sample size, making it difficult to provide a timely prediction in practical applications. However, if only the historical dataset of a single driver is used for training and prediction, the amount of training data is too small, and it is also difficult to accurately predict travel time. To solve these problems, this paper proposes a method to predict bus travel times based on the similarity of drivers’ driving styles. Firstly, the historical travel time data of different drivers are clustered, and then the corresponding types of drivers’ historical data are used to predict the travel time, so as to improve the accuracy and speed of the travel time prediction. We evaluated our approach using a real-world bus trajectory dataset collected in Shenyang, China. The experimental results show that the accuracy of the proposed method is 13.4% higher than that of the traditional method.

NOTCH Signaling in Mantle Cell Lymphoma: Biological and Clinical Implications.

Despite major progress in mantle cell lymphoma (MCL) therapeutics, MCL remains a deadly disease with a median survival not exceeding four years. No single driver genetic lesion has been described to solely give rise to MCL. The hallmark translocation t(11;14)(q13;q32) requires additional genetic alterations for the malignant transformation. A short list of recurrently mutated genes including ATM, CCND1, UBR5, TP53, BIRC3, NOTCH1, NOTCH2, and TRAF2 recently emerged as contributors to the pathogenesis of MCL. Notably, NOTCH1 and NOTCH2 were found to be mutated in multiple B cell lymphomas, including 5-10% of MCL, with most of these mutations occurring within the PEST domain of the protein. The NOTCH genes play a critical role in the early and late phases of normal B cell differentiation. In MCL, mutations in the PEST domain stabilize NOTCH proteins, rendering them resistant to degradation, which subsequently results in the upregulation of genes involved in angiogenesis, cell cycle progression, and cell migration and adhesion. At the clinical level, mutated NOTCH genes are associated with aggressive features in MCL, such as the blastoid and pleomorphic variants, a shorter response to treatment, and inferior survival. In this article, we explore in detail the role of NOTCH signaling in MCL biology and the ongoing efforts toward targeted therapeutic interventions.