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Executable domain-specific languages (DSLs) enable the execution of behavioral models. While an execution is mostly driven by the model content (e.g., control structures), many use cases require interacting with the running model, such as simulating scenarios in an automated or interactive way, or coupling the model with other models of the system or environment. The management of these interactions is usually hardcoded into the semantics of the DSL, which prevents its reuse for other DSLs and the provision of generic interaction-centric tools (e.g., event injector). In this paper, we propose a metalanguage for complementing the definition of executable DSLs with explicit behavioral interfaces to enable external tools to interact with executed models in a unified way. We implemented the proposed metalanguage in the GEMOC Studio and show how behavioral interfaces enable the realization of tools that are generic and thus usable for different executable DSLs.
The aim of this investigation was to understand the bioaccumulation, cell and tissue distribution and biological effects of disodium laureth sulfosuccinate (DSLS)-stabilised TiO2 nanoparticles (NPs) in marine mussels, Mytilus galloprovincialis. Mussels were exposed in vivo to 0.1, 1 and 10 mg Ti/L either as TiO2 NPs (60 and 180 nm) or bulk TiO2, as well as to DSLS alone. A significant Ti accumulation was observed in mussels exposed to TiO2 NPs, which were localised in endosomes, lysosomes and residual bodies of digestive cells, and in the lumen of digestive tubules, as demonstrated by ultrastructural observations and electron probe X-ray microanalysis. TiO2 NPs of 60 nm were internalised within digestive cell lysosomes to a higher extent than TiO2 NPs of 180 nm, as confirmed by the quantification of black silver deposits after autometallography. The latter were localised mainly forming large aggregates in the lumen of the gut. Consequently, lysosomal membrane stability (LMS) was significantly reduced upon exposure to both TiO2 NPs although more markedly after exposure to TiO2-60 NPs. Exposure to bulk TiO2 and to DSLS also affected the stability of the lysosomal membrane. Thus, effects on the lysosomal membrane depended on the nanoparticle size and on the combined biological effects of TiO2 and DSLS.
To performed classification based on global alignment and segmental balance, to better characterize single-segment Meyerding Grade I degenerative spondylolisthesis of lumbar spine (DSLS). A multicenter retrospective cohort study was performed, where 278 and 92 DSLS composed derivation and validation cohorts. Radiographical parameters contained lumbar lordosis (LL), pelvic incidence (PI), pelvic tilt (PT), sacral slope (SS) and sagittal vertical axis (SVA) and inflected and apical vertebrae. The quality-of life scales contained visual analog scales of low back pain (VAS-LBP) and leg pain (VAS-LP) and Oswestry Disability Index (ODI). The classification system was based on global alignment type and PI-LL: Type 1 and 2 with PI < 50°, while inflection < L2 in Type 1, Type 3 and 4 with PI ≥ 50°, while SS < 45° in Type 3; Subtype 2 A and 3 A with ideal PI-LL while 2B and 3B with unideal PI-LL. In derivation cohort, all DSLS acquired reduction and quality-of-life scales improved. At baseline, ODI and VAS-LBP was the highest in type 4, higher than type 3 and 1 (P = 0.030 and P = 0.041) but not for VAS-LP. In PI-LL subtype, ODI was worse in PI-LL mismatch subgroup in type 2 and 3 and VAS-LBP was worse in PI-LL mismatch subgroup in type 3 compared to match subgroup. All quality-of life scales were comparable among types. In validation cohort, there was 2 A-2B and 3 A-3B difference on ODI but comparable after surgery. The DSLS classification based on global shape (type 1-4) and PI-LL (A and B) was developed, where type 4 was linked to poor quality-of-life. This process broaden comprehensive analysis for DSLS.
The objectiveof the study is to investigate the potential association between transient receptor potential (TRP) channels and lung-descending traditional Chinese medicine (LDTCMs). To investigate the potential association between TRP channels and traditional Chinese herbs with lung-descending or lung-diffusing properties, we systematically screened the bioactive components and predicted targets of five lung-descending herbs (Cynanchi Stauntonii Rhizoma Radix, Trichosanthis Fructus, Armeniacae Semen Amarum, Raphani Semen, and Lepidii Semen, also known as Descurainiae Semen) and five lung-diffusing herbs (Ephedrae Herba, Angelicae Dahuricae Radix, Platycodonis Radix, Mori Folium, and Perillae Folium). Target prediction was performed using the TCMSP platform and SwissTargetPrediction databases, followed by Venn analysis to identify herb-specific targets. These targets were subsequently applied to construct a protein-protein interaction (PPI) network with topological visualization. Functional enrichment analyses were then conducted based on Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. To validate the link between lung-descending herbs and specific TRP channel subtypes, calcium flux assays were employed to assess the agonistic effects of ten selected herbs on TRP channels. Finally, molecular docking was performed to identify the key active compounds from lung-descending herbs with the capacity to activate the TRPM8 channel. Network pharmacology analysis revealed that traditional Chinese herbs, particularly those with lung-descending properties, significantly modulate the TRP channel-mediated inflammatory pathways, including TRPM8 and TRPA1. Calcium flux assays demonstrated that extracts from Raphani Semen (RS) and Descurainiae Semen Lepidii Semen (DSLS) can directly activate TRPM8 channels, consistent with previous reports showing that various herbal components and immunosuppressive agents can modulate TRPM8 activity. In contrast, TRPA1 channels were not directly activated by extracts of lung-descending herbs and were therefore excluded from subsequent analyses. Molecular docking simulations further indicated that specific chemical constituents within RS and DSLS form stable binding configurations with key residues lining the TRPM8 pore, suggesting stronger ligand-receptor interactions. Collectively, these results indicate that specific constituents within RS and DSLS contribute to their effects through direct activation of TRPM8 channels. This study employs an integrated approach combining network pharmacology, functional calcium flux assays, and molecular docking to establish TRP channels as effective functional filters for the systematic screening of lung-descending herbs. This strategy not only identifies key herbal candidates with TRP affinity and their bioactive constituents but also provides evidentiary support for developing TRP-targeted pulmonary therapeutics. From the perspective of traditional Chinese medicine, these findings elucidate the mechanistic basis of lung-descending efficacy. From the standpoint of modern pharmacology, they reveal specific TRP channel interactions unique to lung-descending herbs, thereby establishing a molecular foundation for the development of novel respiratory therapeutics.
The article presents a new approach in the development of software for bipedal humanoid robot controllers, based on the construction and application of graphic domain-specific languages (DSLs). The notations used to describe dance movements and gestures are typical examples of DSLs. With certain extensions, related to the description of foot topology, sensors and actuators, such DSLs are applicable for modeling dance movements that would be performed by a robot. The existing software development methodologies in robotics have a purely mechanistic approach to understanding and implementing robotic tasks. Such an approach in humanoid robotics complicates the understanding of the problem, as well as the specification and implementation of solutions. Our approach, which uses DSLs, adopts complex movements and gestures performed by the feet of dancers using professional dancers, people with above-average motor skills, as reference. We believe that the developed software can also be successfully applied to assistive robots that would help people with special needs whose mobility is significantly lower than average.
Background/Objectives: satisfactory sagittal alignment when treating degenerative spondylolisthesis of the lumbar spine (DSLS) may produce better clinical and radiographic outcomes compared to treatment focused solely on isolated segments when indicated. Ghailane et al. proposed a treatment guideline based on their classification system. The aim of this study was to investigate the impact of adherence to Ghailane-Gille (GG) treatment guidelines on surgical outcomes in patients with DSLS. Methods: A monocentric retrospective cohort analysis was performed from 2021 to September 2024. Data were collected from patients treated for DSLS, covering the period from baseline to one-year follow-up. Patients were divided into two groups based on GG treatment guidelines: the "Match group" (patients who underwent surgery following GG guidelines) and the "Mismatch group" (patients who did not adhere to these guidelines). Preoperative and postoperative clinical outcomes, patient satisfaction, and operative parameters were collected and compared between groups. Results: A total of 80 patients were enrolled, with 52 in the Match group and 28 in the Mismatch group. At baseline, the Oswestry Disability Index (ODI) score demonstrated significant variation among classification subtypes and a positive correlation. The Match group exhibited a significant reduction in ODI scores one year postoperatively and maintained high levels of satisfaction; no significant intraoperative differences were noted. Additionally, patients in the Mismatch group were more frequently classified as American Society of Anesthesiologists (ASA) III compared to the Match group (70% vs. 30%), suggesting clinicians' hesitance to fully implement GG guidelines in aggressive treatment strategies for those patients. Conclusions: Adhering to the GG treatment guidelines for restoring sagittal alignment in DSLS patients is associated with decreased ODI scores regardless of age, ensuring patient satisfaction at one-year follow-up. This approach could potentially benefit ASA III patients as well.
Multiple heterogeneous agents are popular for executing pickup and delivery tasks for multiple pairs of customers. The scheduling solutions of agents are expected to complete each task within time windows, even under disturbances. Existing problem models tend to evaluate solutions through multiple simulations based on disturbances. This is time-consuming and implicit. In contrast, this article defines a robustness optimization objective based on the relationship between the agent's arrival time and the time windows for explicit evaluation. Taking robustness together with makespan and cost, the problem is modeled as a triobjective optimization problem. To solve the problem, this article proposes matrix-learning particle swarm optimization (MLPSO) to obtain diversified and high-quality solutions for decision-makers. In MLPSO, solutions are represented as an adjacency matrix of task sequences and an allocation matrix of agents to tasks. Corresponding to the matrix-based representation, solutions are constructed by planning the task order for execution and assigning agents to tasks. A matrix-distance-based learning (MDL) strategy is developed to select neighbors in the decision space for particle update. In this way, good task segments and allocation pairs can be extracted from learning exemplars and current positions to provide stable updating directions for generating high-quality solutions. To further enhance solution convergence and diversity, a dual-space local search (DSLS) is performed on elite and sparse nondominated solutions. Experimental results on 36 instances with various scales show that the proposed MLPSO is significantly better than state-of-the-art algorithms in terms of solution quality and diversity.
Infrared small target detection (IRSTD) plays a crucial role in applications including, but not limited to, aerial surveillance, national defense, and disaster monitoring. However, existing detection models often suffer from limited generalization capability and localization accuracy due to data scarcity and significant variations in targets' scales and positions in real-world scenarios. To address these issues, this paper proposes a self-supervised real-noise fusion network for infrared small target detection. Specifically, we introduce a real-noise sampling and fusion mechanism that extracts authentic background noise from raw infrared imagery and integrates it into training samples, thereby producing more realistic synthetic data. Furthermore, a negative sample augmentation strategy is introduced to enrich negative samples with greater diversity and difficulty, alleviating the issue of limited dataset diversity. To further enhance the model's sensitivity to scale and location variations, a composite dynamic scale and location sensitive (DSLS) loss is designed. Additionally, a self-supervised optimization scheme is employed across multi-scale prediction outputs. Extensive experiments on two public infrared small target datasets validate the effectiveness of the proposed approach. Compared with the current leading method, DNANet, the proposed method achieves IoU improvements of 7.04% and 1.49% and detection rate increases of 0.91% and 0.96%, respectively. These results demonstrate the superior generalization and localization capability of the proposed framework under small-sample conditions, as well as its strong adaptability to variations in targets' scales and positions.
Retrospective radiographic review. Investigate and quantify transverse pedicle angle (TPA), the medial-to-lateral pedicle angulation, and its potential association with pelvic incidence (PI) in patients with isthmic lumbar spondylolisthesis (ISLS) and compare to those with degenerative lumbar spondylolisthesis (DSLS) and controls. A total of 200 patients (64 ISLS, 70 DSLS, 66 control) were included. TPA was calculated at the L3-5 vertebral levels using axial computed tomography slices. PI was measured on lateral radiographs. Two independent observers completed the measurements. As a sensitivity analysis, TPA was also measured at the most cranial and caudal aspects of the L3-5 vertebral levels of a subset of participants (29 ISLS, 31 DSLS, 35 control) and the cranial to caudal change (ΔTPA) was calculated. TPA values (mean ± SD) at L4 and L5 for ISLS (L4: 17.3° ± 3.7°, L5: 26.0° ± 5.2°) were significantly higher than those for the DSLS (L4: 14.3° ± 3.8°, L5: 22.2° ± 5.0°) and control (L4: 14.5° ± 3.9°, L5: 20.7° ± 3.8°) groups. TPA in the DSLS group was significantly higher than controls at L5, but not L4. High PI predicted wider TPA at L5 in both DSLS and ISLS. ΔTPA (mean ± SD) increased sequentially proceeding through the L3-5 spinal levels for the ISLS (L3: 6.8° ± 4.4°, L4: 8.7° ± 5.2°, L5: 15.6° ± 9.0°), DSLS (L3: 8.2° ± 6.0°, L4: 8.3° ± 5.9°, L5: 18.3° ± 7.2°), and control (L3: 6.8° ± 4.4°, L4: 8.2° ± 4.7°, L5: 17.7° ± 7.0°) groups. TPA was significantly increased in ISLS compared with DSLS and controls. High PI significantly predicted high TPA at the L5 vertebral level in ISLS and DSLS. ΔTPA increased sequentially proceeding through the lumbar spine across groups.
Application development for the cyber-physical systems (CPS) domain is considered a quite complex procedure, since it not only requires a high level of expertise but also deep knowledge of heterogeneous domains. On the other hand, modern low-code solutions and DSLs are developed to offload domain complexity by developing models at a higher level of abstraction. In this work we propose an approach based on multiple high-level domain-specific languages (DSLs) as the vehicle to alleviate the developers from the intricacies of the CPS domain, enabling them to easily design and develop different layers (e.g., device, system or application layers) and aspects (e.g., automation processes, observation or monitoring dashboards) of a CPS. The materialized outcome of our approach is the LocSys platform, which allows the integration of DSLs, the development and management of models, and the development of pipelines of transformations between DSL models in a uniform platform, covering different aspects of complex domains. The efficacy of this approach was evaluated during a workshop that included more than 80 participants, with varying levels of expertise and experience in the field. The workshop documented the usability and acceptance of the study using SUS measurements. Preliminary findings suggest that the multi-DSL approach is highly usable (average SUS score 80.65, A- grade) and has been well received by non-domain experts. These results are promising, as they indicate that the LocSys platform can be successfully implemented to build smart environments with embedded automation processes and monitoring dashboards.
Active and passive acoustic observation methods offer an effective approach to studying deep-sea fauna where direct monitoring is particularly challenging. Some of these mesopelagic organisms are part of Deep Scattering Layers (DSLs) which are recognized as being among the largest biomass aggregations of the planet. Current quantitative estimates of this biomass vary by an order of magnitude and it is essential to improve monitoring methods in the face of emerging initiatives to exploit this key ecological resource. In this study, we employ a combination of passive and active acoustic datasets to describe concurrent temporal patterns of DSL migration and changes of the soundscape off two volcanic islands of the subtropical NE Atlantic. We report a chorus centred at 2.5 kHz, matching those previously documented in the Pacific and Indian Oceans, and observed here for the first time in the North Atlantic. This chorus event coincides with the upward migration of organisms from deep scattering layers to surface waters. Furthermore, the maximum received sound levels of this chorus are positively correlated with the measured acoustic backscatter at 38 kHz of the DSL migrating to <150m depth. These results suggest that calibrated Passive Acoustic Monitoring (PAM) measures of chorus intensity could be applied globally as a cost-effective and powerful indicator of migrating organisms from DSLs, potentially reflecting biomass through their associated acoustic backscatter.
The software industry has rapidly evolved with high performance. This is owing to the implementation of good programming practices and architectures that make it scalable and adaptable. Therefore, a strong incentive is required to develop the processes that initiate this project. We aimed to provide a platform that streamlines the development process and connects planning, structuring, and development. Specifically, we developed a system that employs computer vision, deep learning, and MDA to generate source code from the diagrams describing the system and the respective study cases, thereby providing solutions to the proposed problems. The results demonstrate the effectiveness of employing computer vision and deep learning techniques to process images and extract relevant information. The infrastructure is designed based on a modular approach employing Celery and Redis, enabling the system to manage asynchronous tasks efficiently. The implementation of image recognition, text analysis, and neural network construction yields promising outcomes in generating source code from diagrams. Despite some challenges related to hardware limitations during the training of the neural network, the system successfully interprets the diagrams and produces artifacts using the MDA approach. Plugins and DSLs enhance flexibility by supporting various programming languages and automating code deployment on platforms such as GitHub and Heroku.
Protein aggregation is a fundamental phenomenon linked to many amyloid-associated disorders, production of therapeutic proteins and biomaterial. Human serum albumin (HSA), a multidomain protein, exhibits diverse aggregation behaviors under physiological stress. Here, we investigated how domain-specific ligands (DSLs) such as hemin for domain-I, bilirubin for domain-II, and diazepam for domain-III influences HSA aggregation reactions. Using biophysical techniques including circular dichroism, intrinsic fluorescence, thermal unfolding, quenching assays, red edge excitation shift (REES) analysis, transmission electron microscopy, FTIR, and molecular dynamic simulation (MD-simulation), we show that effect of ligand binding induces distinct aggregation morphologies. Native HSA forms β-sheet-rich worm-like fibrils at ~65 °C and pH 7.4. Hemin binding accelerated aggregation by ~2.5-fold and promoted spherical oligomers, whereas bilirubin slowed it by 2-fold leading to amorphous aggregates, and diazepam produced fibrils similar to native HSA. Ligand binding reduced conformational dynamics and altered equilibrium states, with hemin and bilirubin inducing compactness and internalization of tryptophan residues, thereby decreasing fibril elongation tendency. These findings highlight the role of effect of domain-specific ligands in redesigning aggregation precursor states and pathways. Our study provides mechanistic insights into how small molecules modulate the aggregation landscape of multidomain proteins. By showing that ligands can redirect aggregation toward distinct off-pathway species, this work elucidates the mechanistic basis by which ligand binding modulates protein assembly pathways and aggregates morphology.
Genome-wide association studies have identified numerous disease susceptibility loci (DSLs) for Alzheimer's disease (AD). However, only a limited number of studies have investigated the dependence of the genetic effect size of established DSLs on genetic ancestry. We utilized the whole genome sequencing data from the Alzheimer's Disease Sequencing Project (ADSP) including 35,569 participants. A total of 25,459 subjects in four distinct populations (African ancestry, non-Hispanic White, admixed Hispanic, and Asian) were analyzed. We found that nine DSLs showed significant heterogeneity across populations. Single nucleotide polymorphism (SNP) rs2075650 in translocase of outer mitochondrial membrane 40 (TOMM40) showed the largest heterogeneity (Cochran's Q = 0.00, I2 = 90.08), followed by other SNPs in apolipoprotein C1 (APOC1) and apolipoprotein E (APOE). Two additional loci, signal-induced proliferation-associated 1 like 2 (SIPA1L2) and solute carrier 24 member 4 (SLC24A4), showed significant heterogeneity across populations. We observed substantial heterogeneity for the APOE-harboring 19q13.32 region with TOMM40/APOE/APOC1 genes. The largest risk effect was seen among African Americans, while Asians showed a surprisingly small risk effect.
High sulfate contents in skim latex serum (SLS) can be reduced by rubber wood ash (RWA). Subsequently, the desulfated skim latex serum (DSLS) can be further anaerobically treated more effectively with the accompanying generated biomethane. In this study, DSLS was treated using an up-flow anaerobic sludge blanket (UASB) reactor operated at 10-day HRT and under mesophilic (37 °C) conditions. The effect of organic loading rates (OLR) at 0.89, 1.79 and 3.57 g-COD/L-reactor∙d on DSLS biodegradability was investigated in Phase I-IV using NaHCO3 as an external buffering agent. Maximum methane production yield of 226.35 mL-CH4/g-CODadded corresponding to 403.25 mL-CH4/L reactor·d was achieved at the suitable OLR of 1.79 g-COD/L-reactor∙d. UASB effluent recirculation which was then applied to replace the NaHCO3. It was found that with 53% effluent recirculation similar to an OLR of 2.01 g-COD/L-reactor∙d, an average of 185.70 mL-CH4/g-CODadded corresponding to 371.40 mL/L reactor·d of methane production was reached. The dominant bacteria in UASB reactor were members of Proteobacteria, Bacteroidota, Firmicutes, and Desulfobacterota phyla. Meanwhile, the archaeal community was majorly dominated by the genera Methanosaeta sp. and Methanomethylovorans sp. The study clearly indicates the capabilities of UASB reactor with effluent recirculation to treat DSLS anaerobically.
Sphingolipids are thought to promote skeletal muscle insulin resistance. Deoxysphingolipids (dSLs) are atypical sphingolipids that are increased in the plasma of individuals with type 2 diabetes and cause β-cell dysfunction in vitro. However, their role in human skeletal muscle is unknown. We found that dSL species are significantly elevated in muscle of individuals with obesity and type 2 diabetes compared with athletes and lean individuals and are inversely related to insulin sensitivity. Furthermore, we observed a significant reduction in muscle dSL content in individuals with obesity who completed a combined weight loss and exercise intervention. Increased dSL content in primary human myotubes caused a decrease in insulin sensitivity associated with increased inflammation, decreased AMPK phosphorylation, and altered insulin signaling. Our findings reveal a central role for dSL in human muscle insulin resistance and suggest dSLs as therapeutic targets for the treatment and prevention of type 2 diabetes. Deoxysphingolipids (dSLs) are atypical sphingolipids elevated in the plasma of individuals with type 2 diabetes, and their role in muscle insulin resistance has not been investigated. We evaluated dSL in vivo in skeletal muscle from cross-sectional and longitudinal insulin-sensitizing intervention studies and in vitro in myotubes manipulated to synthesize higher dSLs. dSLs were increased in the muscle of people with insulin resistance, inversely correlated to insulin sensitivity, and significantly decreased after an insulin-sensitizing intervention; increased intracellular dSL concentrations cause myotubes to become more insulin resistant. Reduction of muscle dSL levels is a potential novel therapeutic target to prevent/treat skeletal muscle insulin resistance.
Although the dynamics of individual rock-slope failures above recently shrinking glaciers have received increasing study, less is known about the spatial distribution of landslides in paraglacial settings. Here, we present a landslide inventory for large deglaciated area (~100,000 km2) situated within the Last Glacial Maximum (LGM) limits of the Northern Patagonian Icefield (NPI). Using satellite images and the TanDEM-X digital elevation model, we mapped a total of 15,543 landslides, among which 1006 are deep-seated landslides (DSLs) with area ≥0.01 km2. The distribution of DSLs is highly asymmetric in a W-E transect of the NPI region, with pronounced clustering along the semi-arid eastern front of the Patagonian Andes. The most strongly affected domain is volcanic tablelands overlying weak Miocene sedimentary rocks, but DSLs tend to also cluster along recently deglaciated (i.e. since the end of the 19th century) eastern margin of the NPI. Compared with other high mountain regions, alpine valleys of the Patagonian Andes are affected by DSLs only in <1% of their area, an order of magnitude lower than in other reported deglaciated mountains. The modest incidence of DSLs in the Patagonian Andes is due to dominance of hard granitoid rocks and relatively weak historical seismic activity. We conclude that 1) geological conditions control the distribution of DSLs and their types in the NPI region; 2) paraglacial effects play secondary (although locally important) roles in the origin of DSLs; 3) local clusters of large DSLs originate due to specifics of the post-LGM landscape evolution, involving drawdowns of glacial lakes and incision of rivers into the unconsolidated deposits; and 4) increased abundance of landslides above the recently shrinking margin of the NPI results from the repeated Holocene fluctuations of glacier snouts around the Little Ice Age (LIA) glacier limits and the spatial coincidence of glacial debuttressing effects with the presence of active faults.
Cry toxins from Bacillus thuringiensis are effective biopesticides that kill lepidopteran pests, replacing chemical pesticides that indiscriminately attack both target and non-target organisms. However, resistance in susceptible pests is an emerging problem. B. thuringiensis also produces vegetative insecticidal protein (Vip3A), which can kill insect targets in the same group as Cry toxins but using different host receptors, making the combined application of Cry and Vip3A an exciting possibility. Vip3A toxicity requires the formation of a homotetramer. Hence, screening of Vip3A mutants for increased stability requires orthogonal biophysical assays that can test both tetrameric integrity and monomeric robustness. For this purpose, we have used herein for the first time a combination of analytical ultracentrifugation (AUC), mass photometry (MP), differential static light scattering (DSLS) and differential scanning fluorimetry (DSF) to test five mutants at domains I and II. Although all mutants appeared more stable than the wild type (WT) in DSLS, mutants that showed more dissociation into dimers in MP and AUC experiments also showed earlier thermal unfolding by DSF at domains IV-V. All of the mutants were less toxic than the WT, but toxicity was highest for domain II mutations N242C and F229Y. Activation of the protoxin was complete and resulted in a form with a lower sedimentation coefficient. Future high-resolution structural data may lead to a deeper understanding of the increased stability that will help with rational design while retaining native toxicity.
The influence of the underlying surface on the atmospheric environment over rivers and lakes is not fully understood. To improve our understanding, this study targeted the Twain-Hu Basin (THB) in central China, with a unique underlying surface comprising a dense "water network" over rivers and lakes. In this study, the Weather Research and Forecasting Model with Chemistry (WRF-Chem) was used to simulate the impact of this dense "water network" on a wintertime heavy PM2.5 pollution event in the THB. On this basis, the regulating effects of density and area of the lake groups, with centralized big lakes (CBLs) and discrete small lakes (DSLs), on PM2.5 concentrations over the underlying surface of the dense "water network" in the THB were clarified, and the relative contributions of thermal factors and water vapor factors in the atmospheric boundary layer to the variation of PM2.5 concentrations were evaluated. The results show that the underlying surface of dense "water networks" in the THB generally decreases the PM2.5 concentrations, but the influences of different lake-group types are not uniform in spatial distribution. The CBLs can reduce the PM2.5 concentrations over the lake and its surroundings by 4.90-17.68% during the day and night. The ability of DSLs in reducing PM2.5 pollution is relatively weak, with the reversed contribution between -5.63% and 1.56%. Thermal factors and water vapor-related factors are the key meteorological drivers affecting the variation of PM2.5 concentrations over the underlying surface of dense "water networks". The warming and humidification effects of such underlying surfaces contribute positively and negatively to the "purification" of air pollution, respectively. The relative contributions of thermal factors and water vapor-related factors are 52.48% and 43.91% for CBLs and 65.96% and 27.31% for DSLs, respectively. The "purification" effect of the underlying surface with a dense "water network" in the THB on regional air pollution highlights the importance of environmental protection of inland rivers and lakes in regional environmental governance. In further studies on the atmospheric environment, long-term studies are necessary, including fine measurements in terms of meteorology and the environment and more comprehensive simulations under different scenarios.
Soil dry surface layer (DSL) thickness is often considered a key parameter for land surface resistance to gas exchange. Commonly-used, simple models for DSL thickness are typically empirical in nature and based on limited observational evidence. Laboratory experiments were performed to test soil condition and boundary effects on DSL formation. DSL thickness was analyzed in soil columns with varying texture, initial water content, and potential evaporation rate. DSLs formed to greater depth in fine-textured compared to coarse-textured soils, when beginning from similar initial water content. Based on experiments, we compared a simple, but physically-based mass balance DSL model to an empirical DSL model from the literature. The mass balance model performed better than the empirical relative-wetness based model, and is similar in structure to the current DSL parameterization in the Community Land Model. Results suggest soil resistance parameterizations can be improved by employing simple, but texture-dependent, physically-based DSL formulations.